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A Hybrid Optoelectronic Sensor Platform with an Integrated Solution‐Processed Organic Photodiode
(2021)
Hybrid systems, unifying printed electronics with silicon‐based technology, can be seen as a driving force for future sensor development. Especially interesting are sensing elements based on printed devices in combination with silicon‐based high‐performance electronics for data acquisition and communication. In this work, a hybrid system integrating a solution‐processed organic photodiode in a silicon‐based system environment, which enables flexible device measurement and application‐driven development, is presented. For performance evaluation of the integrated organic photodiode, the measurements are compared to a silicon‐based counterpart. Therefore, the steady state response of the hybrid system is presented. Promising application scenarios are described, where a solution‐processed organic photodiode is fully integrated in a silicon system.
In recent years, predictive maintenance tasks, especially for bearings, have become increasingly important. Solutions for these use cases concentrate on the classification of faults and the estimation of the Remaining Useful Life (RUL). As of today, these solutions suffer from a lack of training samples. In addition, these solutions often require high-frequency accelerometers, incurring significant costs. To overcome these challenges, this research proposes a combined classification and RUL estimation solution based on a Convolutional Neural Network (CNN) and a Long Short-Term Memory (LSTM) network. This solution relies on a hybrid feature extraction approach, making it especially appropriate for low-cost accelerometers with low sampling frequencies. In addition, it uses transfer learning to be suitable for applications with only a few training samples.
Uncontrollable manufacturing variations in electrical hardware circuits can be exploited as Physical Unclonable Functions (PUFs). Herein, we present a Printed Electronics (PE)-based PUF system architecture. Our proposed Differential Circuit PUF (DiffC-PUF) is a hybrid system, combining silicon-based and PE-based electronic circuits. The novel approach of the DiffC-PUF architecture is to provide a specially designed real hardware system architecture, that enables the automatic readout of interchangeable printed DiffC-PUF core circuits. The silicon-based addressing and evaluation circuit supplies and controls the printed PUF core and ensures seamless integration into silicon-based smart systems. Major objectives of our work are interconnected applications for the Internet of Things (IoT).
We propose secure multi-party computation techniques for the distributed computation of the average using a privacy-preserving extension of gossip algorithms. While recently there has been mainly research on the side of gossip algorithms (GA) for data aggregation itself, to the best of our knowledge, the aforementioned research line does not take into consideration the privacy of the entities involved. More concretely, it is our objective to not reveal a node's private input value to any other node in the network, while still computing the average in a fully-decentralized fashion. Not revealing in our setting means that an attacker gains only minor advantage when guessing a node's private input value. We precisely quantify an attacker's advantage when guessing - as a mean for the level of data privacy leakage of a node's contribution. Our results show that by perturbing the input values of each participating node with pseudo-random noise with appropriate statistical properties (i) only a minor and configurable leakage of private information is revealed, by at the same time (ii) providing a good average approximation at each node. Our approach can be applied to a decentralized prosumer market, in which participants act as energy consumers or producers or both, referred to as prosumers.
The desire to connect more and more devices and to make them more intelligent and more reliable, is driving the needs for the Internet of Things more than ever. Such IoT edge systems require sound security measures against cyber-attacks, since they are interconnected, spatially distributed, and operational for an extended period of time. One of the most important requirements for the security in many industrial IoT applications is the authentication of the devices. In this paper, we present a mutual authentication protocol based on Physical Unclonable Functions, where challenge-response pairs are used for both device and server authentication. Moreover, a session key can be derived by the protocol in order to secure the communication channel. We show that our protocol is secure against machine learning, replay, man-in-the-middle, cloning, and physical attacks. Moreover, it is shown that the protocol benefits from a smaller computational, communication, storage, and hardware overhead, compared to similar works.
A Localization System Using Inertial Measurement Units from Wireless Commercial Handheld Devices
(2013)
This paper describes a newly developed technology for the calculation of trajectories of mobile objects, which is based on commercially available sensors being integrated into modern mobile phones and other gadgets. First, a step counting technique was implemented. Second, a novel step length estimator is proposed. These two algorithms utilize the data from accelerometer sensor only. Third, the heading information was obtained using a gyroscope with complementary filter in quaternion form. The combined algorithm was implemented on a low-power ARM processor to provide the trajectory points relative to an initial point. The proposed technique was tested by 10 subjects, in different shoes with different paces. The dependence of the performance of the technology on the attaching point of the mobile device is weak. The proposed algorithms have better balance and estimation accuracy and depend in less degree on the variety in physical parameters of people in comparison with the existing techniques. In experiments inertial measurement units were mounted in different places, i.e. in the hand, in trousers or in T-shirt pockets. The return position error did not exceed 5% of the total travelled distance for all performed tests.
A novel Bluetooth Low Energy advertising scan algorithm is presented for hybrid radios that are additionally capable to measure energy on Bluetooth channels, e.g. as they would need to be compliant with IEEE 802.15.4. Scanners applying this algorithm can achieve a low latency whilst consuming only a fraction of the power that existing mechanisms can achieve at a similar latency. Furthermore, the power consumption can scale with the incoming network traffic and in contrast to the existing mechanisms, scanners can operate without any frame loss given ideal network conditions. The algorithm does not require any changes to advertisers, hence, stays compatible with existing devices. Performance evaluated via simulation and experiments on real hardware shows a 37 percent lower power consumption compared to the best existing scan setting while even achieving a slightly lower latency which proves that this algorithm can be used to improve the quality of service of connection-less Bluetooth communication or reduce the connection establishment time of connection-oriented communication.
Cryptographic protection of messages requires frequent updates of the symmetric cipher key used for encryption and decryption, respectively. Protocols of legacy IT security, like TLS, SSH, or MACsec implement rekeying under the assumption that, first, application data exchange is allowed to stall occasionally and, second, dedicated control messages to orchestrate the process can be exchanged. In real-time automation applications, the first is generally prohibitive, while the second may induce problematic traffic patterns on the network. We present a novel seamless rekeying approach, which can be embedded into cyclic application data exchanges. Although, being agnostic to the underlying real-time communication system, we developed a demonstrator emulating the widespread industrial Ethernet system PROFINET IO and successfully use this rekeying mechanism.
In this paper, the multiaxial formulation of a mechanism-based model for fatigue life prediction is presented whichcan be applied to low-cycle fatigue (LCF) and thermomechanical fatigue (TMF) problems in which high-cycle fa-tigue loadings are superimposed. The model assumes that crack growth is the lifetime limiting mechanism and thatthe crack advance in a loading cycleda/dNcorrelates with the cyclic crack-tip opening displacement ΔCTOD.The multiaxial formulation makes use of fracture mechanics solutions and thus, does not need additional modelparameters quantifying the effect of the multiaxiality. Furthermore, the model includes contributions of HCF on ΔCTODand assesses the effect of the direction of the HCF loadings with respect to LCF or TMF loadings inthe life prediction. The model is implemented into the finite-element program ABAQUS. It is applied to predictthe fatigue life of a thermomechanically loaded notched specimen that should represent the situation between theinlet and outlet bore holes of cylinder heads. A good correlation of the predicted and the measured fatigue lives isobtained.
High temperature components in internal combustion engines and exhaust systems must withstand severe mechanical and thermal cyclic loads throughout their lifetime. The combination of thermal transients and mechanical load cycling results in a complex evolution of damage, leading to thermomechanical fatigue (TMF) of the material. Analytical tools are increasingly employed by designers and engineers for component durability assessment well before any hardware testing. The DTMF model for TMF life prediction, which assumes that micro-crack growth is the dominant damage mechanism, is capable of providing reliable predictions for a wide range of high-temperature components and materials in internal combustion engines. Thus far, the DTMF model has employed a local approach where surface stresses, strains, and temperatures are used to compute damage for estimating the number of cycles for a small initial defect or micro-crack to reach a critical length. In the presence of significant gradients of stresses, strains, and temperatures, the use of surface field values could lead to very conservative estimates of TMF life when compared with reported lives from hardware testing. As an approximation of gradient effects, a non-local approach of the DTMF model is applied. This approach considers through-thickness fields where the micro-crack growth law is integrated through the thickness considering these variable fields. With the help of software tools, this method is automated and applied to components with complex geometries and fields. It is shown, for the TMF life prediction of a turbocharger housing, that the gradient correction using the non-local approach leads to more realistic life predictions and can distinguish between surface cracks that may arrest or propagate through the thickness and lead to component failure.
This paper presents a streaming-based E-Learning environment where closer integration between learning and work is achieved by integrating multimedia services into manufacturing processes. It contains a comprehensive and detailed explanation of the proposed E-Learning streaming framework, especially the adaption of streaming services to mobile environments. We first analyze several scenarios where E-Learning streaming services can be integrated into manufacturing processes. To allow systematic and tailor-made integration, we develop a model and a specification language for E-Learning streaming services and apply the model using practical scenarios from real manufacturing processes. Adaption of multimedia streaming services to mobile devices is discussed based on Synchronized Multimedia Integration Language (SMIL). Last, we comment on the benefits of using E-Learning streaming services as part of manufacturing processes and analyze the acceptance of the developed system. The key components of our E-Learning environment are 1) an xml based streaming service specification language, 2) adaption of multimedia E-Learning services to mobile environments, and 3) Web Services for searching, registration, and creation of E-Learning streaming services.
This paper presents a method for supporting the application of Additive Tooling (AT)-based validation environments in integrated product development. Based on a case study, relevant process steps, activities and possible barriers in the realisation of an injection-moulded product are identified and analysed. The aim of the method is to support the target-oriented application of Additive Tooling to obtain physical prototypes at an early stage and to shorten validation cycles.
When designing and installing Indoor Positioning Systems, several interrelated tasks have to be solved to find an optimum placement of the Access Points. For this purpose, a mathematical model for a predefined number of access points indoors is presented. Two iterative algorithms for the minimization of localization error of a mobile object are described. Both algorithms use local search technique and signal level probabilities. Previously registered signal strengths maps were used in computer simulation.
Quantifying the midsole material characteristics of athletic footwear is a standard task in footwear research and development. Current material testing protocols primarily focus on the determination of cushioning properties of the heel region or the quantification of the midsole properties as one assembly. However, midsoles possess different spatial material properties that have not been quantified from previous methodologies. Therefore, new material testing methods are required to quantify the local material response of athletic footwear. We developed a cyclical force-controlled material testing protocol for the determination of non-homogeneously distributed material stiffness with a high spatial resolution. In five prototype shoes varying in their stiffness distribution, we found that the material properties can be reliably measured across the midsole. Furthermore, we observed a characteristic non-linear material response regardless of the midsole location. We found that the material stiffness increased with an increase of the applied force and that this effect is further intensified by higher testing cycles. Additionally, the obtained midsole stiffness depends on the geometry of the midsole. We explored different approaches to reduce the measurement time of the testing protocol and found that the number of measurements can be reduced by 70% using 2 D-interpolation procedures. Determining the spatial material properties of midsoles needs to be considered to understand foot-shoe interactions. Furthermore, this measurement protocol can be used for quality control within the footwear and can be adapted for considering the effects of different running styles or speeds on ground force application characteristics.
In 4D printing an additively manufactured component is given the ability to change its shape or function under the influence of an external stimulus. To achieve this, special smart materials are used that are able to react to external stimuli in a specific way. So far, a number of different stimuli have already been investigated and initial applications have been impressively demonstrated, such as self-folding bodies and simple grippers. However, a methodical specification for the selection of the stimuli and their implementation was not yet in the foreground of the development.
The focus of this work is therefore to develop a methodical approach with which the technology of 4DP can be used in a solution- and application-oriented manner. The developed approach is based on the conventional design methodology for product development to solve given problems in a structured way. This method is extended by specific approaches under consideration of the 4D printing and smart materials.
To illustrate the developed method, it is implemented in practice using a problem definition in the form of an application example. In this example, which represents the recovery of an object from a difficult-to-access environment, the individual functions of positioning, gripping and extraction are implemented using 4D printing. The material extrusion process is used for additive manufacturing of all components of the example. Finally, the functions are successfully tested. The developed approach offers an innovative and methodical approach to systematically solve technical complex problems using 4DP and smart materials.
Uptakes of 9.2 mmol g−1 (40.5 wt %) for CO2 at 273 K/0.1 MPa and 15.23 mmol g−1 (3.07 wt %) for H2 at 77 K/0.1 MPa are among the highest reported for metal–organic frameworks (MOFs) and are found for a novel, highly microporous copper‐based MOF (see picture; Cu turquoise, O red, N blue). Thermal analyses show a stability of the flexible framework up to 250 °C.
Metal–organic frameworks (MOFs) as highly porous materials have gained increasing interest because of their distinct adsorption properties.1–3 They exhibit a high potential for applications in gas separation and storage,4 as sensors5 as well as in heterogeneous catalysis.6 In the last few years, the H2 storage capacity of MOFs has been considerably increased. Mesoporous MOFs show high adsorption capacities for CH4, CO2, and H2 at high pressures.2, 3, 7–10 To increase the uptake of H2 and CO2 by physisorption at ambient pressure, adsorbents with small micropores as well as high specific surface areas and micropore volumes are required.11, 12 Such microporous materials seem to be more appropriate for gas‐mixture separation by physisorption than mesoporous materials. For gas separation in MOFs the interactions between the fluid adsorptive and “open metal sites” (coordinatively unsaturated binding sites) or the ligands are regarded as important.13 Industrial processes, such as natural‐gas purification or biogas upgrading, can be improved with those materials during a vapor‐pressure swing adsorption cycle (VPSA cycle) or a temperature swing adsorption cycle (TSA cycle).14 The microporous MOF series CPO‐27‐M (M=Mg, Co, Ni, Zn), for example, shows very high CO2 uptakes at low pressures (<0.1 MPa).15, 16 Concerning H2 adsorption, the microporous MOF PCN‐12 offers with 3.05 wt % the highest uptake at ambient pressure and 77 K reported to date.17
Herein, we present a novel microporous copper‐based MOF equation image[Cu(Me‐4py‐trz‐ia)] (1; Me‐4py‐trz‐ia2−=5‐(3‐methyl‐5‐(pyridin‐4‐yl)‐4H‐1,2,4‐triazol‐4‐yl)isophthalate) with extraordinarily high CO2 and H2 uptakes at ambient pressure, the H2 uptake being similar to that in PCN‐12. The ligand Me‐4py‐trz‐ia2−, which can be obtained from cheap starting materials by a three‐step synthesis in good yield, combines carboxylate, triazole, and pyridine functions and is adopted from a recently presented series of linkers,18 for which up to now only a few coordination polymers are known.
The transition from college to university can have a variety of psychological effects on students who need to cope with daily obligations by themselves in a new setting, which can result in loneliness and social isolation. Mobile technology, specifically mental health apps (MHapps), have been seen as promising solutions to assist university students who are facing these problems, however, there is little evidence around this topic. My research investigates how a mobile app can be designed to reduce social isolation and loneliness among university students. The Noneliness app is being developed to this end; it aims to create social opportunities through a quest-based gamified system in a secure and collaborative network of local users. Initial evaluations with the target audience provided evidence on how an app should be designed for this purpose. These results are presented and how they helped me to plan the further steps to reach my research goals. The paper is presented at MobileHCI 2020 Doctoral Consortium.
The increase in households with grid connected Photovoltaic (PV) battery system poses challenge for the grid due to high PV feed-in as a result of mismatch in energy production and load demand. The purpose of this paper is to show how a Model Predictive Control (MPC) strategy could be applied to an existing grid connected household with PV battery system such that the use of battery is maximized and at the same time peaks in PV energy and load demand are reduced. The benefits of this strategy are to allow increase in PV hosting capacity and load hosting capacity of the grid without the need for external signals from the grid operator. The paper includes the optimal control problem formulation to achieve the peak shaving goals along with the experiment set up and preliminary experiment results. The goals of the experiment were to verify the hardware and software interface to implement the MPC and as well to verify the ability of the MPC to deal with the weather forecast deviation. A prediction correction has also been introduced for a short time horizon of one hour within this MPC strategy to estimate the PV output power behavior.
In rural low voltage grid networks, the use of battery in the households with a grid connected Photovoltaic (PV) system is a popular solution to shave the peak PV feed-in to the grid. For a single electricity price scenario, the existing forecast based control approaches together with a decision based control layer uses weather and load forecast data for the on–off schedule of the battery operation. These approaches do bring cost benefit from the battery usage. In this paper, the focus is to develop a Model Predictive Control (MPC) to maximize the use of the battery and shave the peaks in the PV feed-in and the load demand. The solution of the MPC allows to keep the PV feed-in and the grid consumption profile as low and as smooth as possible. The paper presents the mathematical formulation of the optimal control problem along with the cost benefit analysis . The MPC implementation scheme in the laboratory and experiment results have also been presented. The results show that the MPC is able to track the deviation in the weather forecast and operate the battery by solving the optimal control problem to handle this deviation.
In this work a method for the estimation of current slopes induced by inverters operating interior permanent magnet synchronous machines is presented. After the derivation of the estimation algorithm, the requirements for a suitable sensor setup in terms of accuracy, dynamic and electromagnetic interference are discussed. The boundary conditions for the estimation algorithm are presented with respect to application within high power traction systems. The estimation algorithm is implemented on a field programmable gateway array. This moving least-square algorithm offers the advantage that it is not dependent on vectors and therefore not every measured value has to be stored. The summation of all measured values leads to a significant reduction of the required storage units and thus decreases the hardware requirements. The algorithm is designed to be calculated within the dead time of the inverter. Appropriate countermeasures for disturbances and hardware restrictions are implemented. The results are discussed afterwards.
This paper presents the use of model predictive control (MPC) based approach for peak shaving application of a battery in a Photovoltaic (PV) battery system connected to a rural low voltage gird. The goals of the MPC are to shave the peaks in the PV feed-in and the grid power consumption and at the same time maximize the use of the battery. The benefit to the prosumer is from the maximum use of the self-produced electricity. The benefit to the grid is from the reduced peaks in the PV feed-in and the grid power consumption. This would allow an increase in the PV hosting and the load hosting capacity of the grid.
The paper presents the mathematical formulation of the optimal control problem
along with the cost benefit analysis. The MPC implementation scheme in the
laboratory and experiment results have also been presented. The results show
that the MPC is able to track the deviation in the weather forecast and operate
the battery by solving the optimal control problem to handle this deviation.
Pure orbital blowout fractures occur within the confines of the internal orbital wall. Restoration of orbital form and volume is paramount to prevent functional and esthetic impairment. The anatomical peculiarity of the orbit has encouraged surgeons to develop implants with customized features to restore its architecture. This has resulted in worldwide clinical demand for patient-specific implants (PSIs) designed to fit precisely in the patient’s unique anatomy. Material extrusion or Fused filament fabrication (FFF) three-dimensional (3D) printing technology has enabled the fabrication of implant-grade polymers such as Polyetheretherketone (PEEK), paving the way for a more sophisticated generation of biomaterials. This study evaluates the FFF 3D printed PEEK orbital mesh customized implants with a metric considering the relevant design, biomechanical, and morphological parameters. The performance of the implants is studied as a function of varying thicknesses and porous design constructs through a finite element (FE) based computational model and a decision matrix based statistical approach. The maximum stress values achieved in our results predict the high durability of the implants, and the maximum deformation values were under one-tenth of a millimeter (mm) domain in all the implant profile configurations. The circular patterned implant (0.9 mm) had the best performance score. The study demonstrates that compounding multi-design computational analysis with 3D printing can be beneficial for the optimal restoration of the orbital floor.
This paper presents a system that uses a multi-stage AI analysis method for determining the condition and status of bicycle paths using machine learning methods. The approach for analyzing bicycle paths includes three stages of analysis: detection of the road surface, investigation of the condition of the bicycle paths, and identification of substrate characteristics. In this study, we focus on the first stage of the analysis. This approach employs a low-threshold data collection method using smartphone-generated video data for image recognition, in order to automatically capture and classify surface condition and status.
For the analysis convolutional neural networks (CNN) are employed. CNNs have proven to be effective in image recognition tasks and are particularly well-suited for analyzing the surface condition of bicycle paths, as they can identify patterns and features in images. By training the CNN on a large dataset of images with known surface conditions, the network can learn to identify common features and patterns and reliably classify them.
The results of the analysis are then displayed on digital maps and can be utilized in areas such as bicycle logistics, route planning, and maintenance. This can improve safety and comfort for cyclists while promoting cycling as a mode of transportation. It can also assist authorities in maintaining and optimizing bicycle paths, leading to more sustainable and efficient transportation system.
The durability of polymer electrolyte membrane fuel cells (PEMFC) is governed by a nonlinear coupling between system demand, component behavior, and physicochemical degradation mechanisms, occurring on timescales from the sub-second to the thousand-hour. We present a simulation methodology for assessing performance and durability of a PEMFC under automotive driving cycles. The simulation framework consists of (a) a fuel cell car model converting velocity to cell power demand, (b) a 2D multiphysics cell model, (c) a flexible degradation library template that can accommodate physically-based component-wise degradation mechanisms, and (d) a time-upscaling methodology for extrapolating degradation during a representative load cycle to multiple cycles. The computational framework describes three different time scales, (1) sub-second timescale of electrochemistry, (2) minute-timescale of driving cycles, and (3) thousand-hour-timescale of cell ageing. We demonstrate an exemplary PEMFC durability analysis due to membrane degradation under a highly transient loading of the New European Driving Cycle (NEDC).
Background:
Ankle braces aim to reduce lateral ankle sprains. Next to protection, factors influencing user compliance, such as sports performance, motion restriction, and users’ perceptions, are relevant for user compliance and thus injury prevention. Novel adaptive protection systems claim to change their mechanical behavior based on the intensity of motion (eg, the inversion velocity), unlike traditional passive concepts of ankle bracing.
Purpose:
To compare the performance of a novel adaptive brace with 2 passive ankle braces while considering protection, sports performance, freedom of motion, and subjective perception.
Study Design:
Controlled laboratory study.
Methods:
The authors analyzed 1 adaptive and 2 passive (one lace-up and one rigid brace) ankle braces, worn in a low-cut, indoor sports shoe, which was also the no-brace reference condition. We performed material testing using an artificial ankle joint system at high and low inversion velocities. Further, 20 male, young, healthy team sports athletes were analyzed using 3-dimensional motion analysis in sports-related movements to address protection, sports performance, and active range of motion dimensions. Participants rated subjective comfort, stability, and restriction experienced when using the products.
Results:
Subjective stability rating was not different between the adaptive and passive systems. The rigid brace was superior in restricting peak inversion during the biomechanical testing compared with the passive braces. However, in the material test, the adaptive brace increased its stiffness by approximately 400% during the fast compared with the slow inversion velocities, demonstrating its adaptive behavior and similar stiffness values to passive braces. We identified minor differences in sports performance tasks. The adaptive brace improved active ankle range of motion and subjective comfort and restriction ratings.
Conclusion:
The adaptive brace offered similar protective effects in high-velocity inversion situations to those of the passive braces while improving range of motion, comfort, and restriction rating during noninjurious motions.
Clinical Relevance:
Protection systems are only effective when used. Compared with traditional passive ankle brace technologies, the novel adaptive brace might increase user compliance by improving comfort and freedom of movement while offering similar protection in injurious situations.
As cyber-attacks and functional safety requirements increase in Operational Technology (OT), implementing security measures becomes crucial. The IEC/IEEE 60802 draft standard addresses the security convergence in Time-Sensitive Networks (TSN) for industrial automation.We present the standard’s security architecture and its goals to establish end-to-end security with resource access authorization in OT systems. We compare the standard to our abstract technology-independent model for the management of cryptographic credentials during the lifecycles of OT systems. Additionally, we implemented the processes, mechanisms, and protocols needed for IEC/IEEE 60802 and extended the architecture with public key infrastructure (PKI) functionalities to support complete security management processes.
The M-Bus protocol (EN13757) is in widespread use for metering applications within home area and neighborhood area networks, but lacks a strict specification. This may lead to incompatibilities in real-life installations and to problems in the deployment of new M-Bus networks. This paper presents the development of a novel testbed to emulate physical Metering Bus (M-Bus) networks with different topologies and to allow the flexible verification of real M-Bus devices in real-world scenarios. The testbed is designed to support device manufacturers and service technicians in test and analysis of their devices within a specific network before their installation. The testbed is fully programmable, allowing flexible changes of network topologies, cable lengths and types. Itis easy to use, as only the master and the slaves devices have to be physically connected. This allows to autonomously perform multiple tests, including automated regression tests. The testbed is available to other researchers and developers. We invite companies and research institutions to use this M-Bus testbed to increase the common knowledge and real-world experience.
The NaSiO Institute (Institute for Sustainable Silicate Research in Offenburg, https://inasio.hs-offenburg.de/) has been working for years on climate-friendly alternatives to insulation materials and inorganic binders, as well as the reasonable use of construction waste in the building industry. The aim of research is to realize the enormous CO 2 saving potential of the construction sector worldwide. A stopping of climate heating will only succeed if these climate-friendly alternatives are used in the construction industry. This is the only way to realize the enormous CO2 savings that will be needed in future to comply with the Paris Agreement.
Treadmills are essential to the study of human and animal locomotion as well as for applied diagnostics in both sports and medicine. The quantification of relevant biomechanical and physiological variables requires a precise regulation of treadmill belt velocity (TBV). Here, we present a novel method for time-efficient tracking of TBV using standard 3D motion capture technology. Further, we analyzed TBV fluctuations of four different treadmills as seven participants walked and ran at target speeds ranging from 1.0 to 4.5 m/s. Using the novel method, we show that TBV regulation differs between treadmill types, and that certain features of TBV regulation are affected by the subjects’ body mass and their locomotion speed. With higher body mass, the TBV reductions in the braking phase of stance became higher, even though this relationship differed between locomotion speeds and treadmill type (significant body mass × speed × treadmill type interaction). Average belt speeds varied between about 98 and 103% of the target speed. For three of the four treadmills, TBV reduction during the stance phase of running was more intense (> 5% target speed) and occurred earlier (before 50% of stance phase) unlike the typical overground center of mass velocity patterns reported in the literature. Overall, the results of this study emphasize the importance of monitoring TBV during locomotor research and applied diagnostics. We provide a novel method that is freely accessible on Matlab’s file exchange server (“getBeltVelocity.m”) allowing TBV tracking to become standard practice in locomotion research.
Melamine (1,3,5-triazine-2,4,6-triamine or cyanuramide, C3H6N6) is a trimer of cyanamide, with a 1,3,5-triazine skeleton (Figure 3.5-1). The molecule contains 66% nitrogen by mass and, if mixed with resins, has fire retardant properties due to its release of nitrogen gas when burned or charred. The word melamine (from German) is a combination of the word melam (which is a distillation derivative of ammonium thiocyanate) and amine [1]. Melamine is also a metabolite of cyromazine, an insecticide in which the proton of an NH2-group is substituted by a cyclopropyl group.
A new electronic capsule with bidirectional communication system is being developed for multi-task application. The capsule is designed to be a platform for medical assistant application inside the body. The designed telemetry unit is a synchronous bidirectional communication block using continuous phase DQPSK of 115 kHz low carrier frequency for inductive data transmission suited for human body energy transfer. The communication system can assist the electronic pill to trigger an actuator for drug delivery, to record temperature, or to measure pH of the body. It consists additionally to a 32bit processor, memory, external peripheries, and detection facility. The complete system is designed to fit small-size mass medical application with low power consumption, size of 7x25mm. The system is designed, simulated and emulated on FPGA. A final layout of the complete chip design is still under progress.
To provide proper solutions to the problem of device dependant content delivery, a fine categorization of the application target devices is needed. Earlier attempts provided two different presentations for desktop and mobile platforms. The mobile platform presentation was divided into three categories, based on a general classification (PDA, Smartphone or mobile phone). In order to improve the on mobile device presentation a finer categorization is introduced. In this paper, our focus is to clarify the concept of this more flexible presentation module, in which the delivered content depends on the efficiency of the device based on a selected set of capabilities.
One of the challenges in humanoid robotics is motion control. Interacting with humans requires impedance control algorithms, as well as tackling the problem of the closed kinematic chains which occur when both feet touch the ground. However, pure impedance control for totally autonomous robots is difficult to realize, as this algorithm needs very precise sensors for force and speed of the actuated parts, as well as very high sampling rates for the controller input signals. Both requirements lead to a complex and heavy weight design, which makes up for heavy machines unusable in RoboCup Soccer competitions.
A lightweight motor controller was developed that can be used for admittance and impedance control as well as for model predictive control algorithms to further improve the gait of the robot.
Electronic pills, smart capsules or miniaturized microsystems swallowed by human beings or animals for various biomedical and diagnostic applications are growing rapidly in the last years. This paper searched out the important existing electronic pills in the market and prototypes in research centers. Further objective of this research is to develop a technology platform with enhanced feature to cover the drawback of most
capsules. The designed telemetry unit is a synchronous bidirectional communication block using continuous phase DQPSK of 115 kHz low carrier frequency for inductive data transmission suited for human body energy transfer. The communication system can assist the electronic pill to trigger an actuator for drug delivery, to record temperature, or to measure pH of the body. It consists additionally to a 32bit processor, memory, external peripheries, and detection facility. The complete system is designed to fit small-size mass medical application with low power consumption, size of 7x25mm. The system is designed, simulated and emulated on FPGA.
An algorithm is presented that has successfully been utilized in practice for several years. It improves data analysis in chromatography. The program runs in an extremely reliable way and evaluates chromatographic raw data with an acceptable error. The algorithm requires a minimum of preliminaries and integrates even unsmoothed noisy data correctly.
We report improved separation of the highly toxic contact herbicides paraquat, diquat, difenzoquat, mepiquat, and chloromequat by HPTLC. Quantification was based on a new derivatization reaction using sodium tetraphenylborate. Measurements were in the wavelength range from 440 to 480 nm or from 440 to 590 nm. An LED emitting very intense light at 365 nm was used for excitation. The quantification limits of paraquat and diquat in water, using improved solid-phase extraction, was in the low ng L −1 range. The linear range covered more than two orders of magnitude. Recovery was investigated for all the compounds, and was insufficient, ranging from 11 to 92%, but the method is inexpensive, rapid, and works reliably.
A Nonlinear FEM Model to Calculate Third-Order Harmonic and Intermodulation in TC-SAW Devices
(2018)
Nonlinearities in Temperature Compensated SAW (TC-SAW) devices in the 2 GHz range are investigated using a nonlinear finite element model by simultaneously considering both third-order intermodulation distortion (IMD3)and third harmonic (H3). In the employed perturbation approach, different contributions to the total H3, the direct and indirect contribution, are discussed. H3 and IMD3 measurements were fitted simultaneously using scaling factors for SiO 2 film and Cu electrode nonlinear material tensors in TC-SAW devices. We employ a P-Matrix simulation as intermediate step: Firstly, measurement and nonlinear P-Matrix calculations for finite devices are compared and coefficients of the P-Matrix simulation are determined. The nonlinear tensor data of the different materials involved in periodic nonlinear finite element method (FEM) computations are optimized to fit periodic P-Matrix calculations by introducing scaling factors. Thus, the contribution of different materials to the nonlinear behavior of TC-SAW devices is obtained and the role of materials is discussed.
Signal detection and bandwidth estimation, also known as channel segmentation or information channel estimation, is a perpetual topic in communication systems. In the field of radio monitoring this issue is extremely challenging, since unforeseeable effects like fading occur accidentally. In addition, most radio monitoring devices normally scan a wide frequency range of several hundred MHz and have to detect a multitude of different signals, varying in signal power, bandwidth and spectral shape. Since narrowband sensing techniques cannot be directly applied, most radio monitoring devices use Nyquist wideband sensing to discover the huge frequency range. In practice, sensing is normally conducted by an FFT sweep spectrum analyzer that delivers the power spectral density (PSD) values to the radio monitoring system. The channel segmentation is the initial step of a comprehensive signal analysis in a radio monitoring system based on the PSD values. In this paper, a novel approach for channel segmentation is presented that is based on a quantization and a histogram evaluation of the measured PSD. It will be shown that only the combination of both evaluations will lead to an successful automatic channel segmentation. The performance of the proposed algorithm is shown in a real radio monitoring szenario.
A Novel Approach of High Dynamic Current Control of Interior Permanent Magnet Synchronous Machines
(2019)
Harmonic-afflicted effects of permanent magnet synchronous machines with high power density are hardly faced by traditional current PI controllers, due to limited controller bandwidth. As a consequence, currents and lastly torque ripples appear. In this paper, a new deadbeat current controller architecture has been presented, which is capable to encounter the effects of these harmonics. This new control algorithm, here named “Hybrid-Deadbeat-Controller”, combines the stability and the low steady-state errors offered by common PI regulators with the high dynamic offered by the deadbeat control. Therefore, a novel control algorithm is proposed, capable of either compensating the current harmonics in order to get smoother currents or to control a varying reference value to achieve a smoother torque. The information needed to calculate the optimal reference currents is based on an online parameter estimation feeding an optimization algorithm to achieve an optimal torque output and will be investigated in future research. In order to ensure the stability of the controller over the whole area of operation even under the influence of effects changing the system’s parameter, this work as well focusses on the robustness of the “hybrid” dead beat controller.
In large aircrafts the cabling is very complex and often causes reliability problems. This is specially true for modern In-flight Entertainment (IFE) systems, where every passenger can select a preferred movie, play computer games or be able to communicate with other travellers. Due to EMC problems, wireless communication systems (WiFi etc.) didn't succeed in solving these problems. In this paper an innovative communication system is proposed which perfectly supplements an aircraft IFE system. The key innovation of this system is to use structures that are essential parts of the airframe for data transfer, such as seat rails. Those rails consist of rectangular shapes and could easily be modified to fulfill the function of waveguides for microwaves. A waveguide as part of the seat rail would provide enormous benefits for aircrafts, such as a large bandwidth and consequently high data rates, no problems with EMC, unlimited flexibility of seat configuration, mechanical robustness with associated increase of reliability and a few additional advantages related to aircrafts such as reduction of weight and costs.
Synthesis and crystal structure of a novel copper-based MOF material are presented. The tetragonal crystal structure of [ ∞ 3 ( Cu 4 ( μ 4 -O ) ( μ 2 -OH ) 2 ( Me 2 trz p ba ) 4 ] possesses a calculated solvent-accessible pore volume of 57%. Besides the preparation of single crystals, synthesis routes to microcrystalline materials are reported. While PXRD measurements ensure the phase purity of the as-synthesized material, TD-PXRD measurements and coupled DTA–TG–MS analysis confirm the stability of the network up to 230 °C. The pore volume of the microcrystalline material determined by nitrogen adsorption at 77 K depends on the synthetic conditions applied. After synthesis in DMF/H2O/MeOH the pores are blocked for nitrogen, whereas they are accessible for nitrogen after synthesis in H2O/EtOH and subsequent MeOH Soxhleth extraction. The corresponding experimental pore volume was determined by nitrogen adsorption to be V Pore = 0.58 cm 3 g - 1 . In order to characterize the new material and to show its adsorption potential, comprehensive adsorption studies with different adsorptives such as nitrogen, argon, carbon dioxide, methanol and methane at different temperatures were carried out. Unusual adsorption–desorption isotherms with one or two hysteresis loops are found – a remarkable feature of the new flexible MOF material.
Linear acceleration is a key performance determinant and major training component of many sports. Although extensive research about lower limb kinetics and kinematics is available, consistent definitions of distinctive key body positions, the underlying mechanisms and their related movement strategies are lacking. The aim of this ‘Method and Theoretical Perspective’ article is to introduce a conceptual framework which classifies the sagittal plane ‘shin roll’ motion during accelerated sprinting. By emphasising the importance of the shin segment’s orientation in space, four distinctive key positions are presented (‘shin block’, ‘touchdown’, ‘heel lock’ and ‘propulsion pose’), which are linked by a progressive ‘shin roll’ motion during swing-stance transition. The shin’s downward tilt is driven by three different movement strategies (‘shin alignment’, ‘horizontal ankle rocker’ and ‘shin drop’). The tilt’s optimal amount and timing will contribute to a mechanically efficient acceleration via timely staggered proximal-to-distal power output. Empirical data obtained from athletes of different performance levels and sporting backgrounds are required to verify the feasibility of this concept. The framework presented here should facilitate future biomechanical analyses and may enable coaches and practitioners to develop specific training programs and feedback strategies to provide athletes with a more efficient acceleration technique.
In recent years, physically unclonable functions (PUFs) have gained significant attraction in IoT security applications, such as cryptographic key generation and entity authentication. PUFs extract the uncontrollable production characteristics of different devices to generate unique fingerprints for security applications. When generating PUF-based secret keys, the reliability and entropy of the keys are vital factors. This study proposes a novel method for generating PUF-based keys from a set of measurements. Firstly, it formulates the group-based key generation problem as an optimization problem and solves it using integer linear programming (ILP), which guarantees finding the optimum solution. Then, a novel scheme for the extraction of keys from groups is proposed, which we call positioning syndrome coding (PSC). The use of ILP as well as the introduction of PSC facilitates the generation of high-entropy keys with low error correction costs. These new methods have been tested by applying them on the output of a capacitor network PUF. The results confirm the application of ILP and PSC in generating high-quality keys.
This paper presents a novel low-jitter interface between a low-cost integrated IEEE802.11 chip and a FPGA. It is designed to be part of system hardware for ultra-precise synchronization between wireless stations. On physical level, it uses Wi-Fi chip coexistence signal lines and UART frame encoding. On its basis, we propose an efficient communication protocol providing precise timestamping of incoming frames and internal diagnostic mechanisms for detecting communication faults. Meanwhile it is simple enough to be implemented both in low-cost FPGA and commodity IEEE802.11 chip firmware. The results of computer simulation shows that developed FPGA implementation of the proposed protocol can precisely timestamp incoming frames as well as detect most of communication errors even in conditions of high interference. The probability of undetected errors was investigated. The results of this analysis are significant for the development of novel wireless synchronization hardware.
Advances in printed electronics (PE) enables new applications, particularly in ultra-low-cost domains. However, achieving high-throughput printing processes and manufacturing yield is one of the major challenges in the large-scale integration of PE technology. In this article, we present a programmable printed circuit based on an efficient printed lookup table (pLUT) to address these challenges by combining the advantages of the high-throughput advanced printing and maskless point-of-use final configuration printing. We propose a novel pLUT design which is more efficient in PE realization compared to existing LUT designs. The proposed pLUT design is simulated, fabricated, and programmed as different logic functions with inkjet printed conductive ink to prove that it can realize digital circuit functionality with the use of programmability features. The measurements show that the fabricated LUT design is operable at 1 V.
A novel approach of a testbed for embedded networking nodes has been conceptualized and implemented. It is based on the use of virtual nodes in a PC environment, where each node executes the original embedded code. Different nodes are running in parallel and are connected via so-called virtual interfaces. The presented approach is very efficient and allows a simple description of test cases without the need of a network simulator. Furthermore, it speeds up the process of developing new features.
The newly synthesized Zn4O-based MOF 3∞[Zn4(μ4-O){(Metrz-pba)2mPh}3]·8 DMF (1·8 DMF) of rare tungsten carbide (acs) topology exhibits a porosity of 43% and remarkably high thermal stability up to 430 °C. Single crystal X-ray structure analyses could be performed using as-synthesized as well as desolvated crystals. Besides the solvothermal synthesis of single crystals a scalable synthesis of microcrystalline material of the MOF is reported. Combined TG-MS and solid state NMR measurements reveal the presence of mobile DMF molecules in the pore system of the framework. Adsorption measurements confirm that the pore structure is fully accessible for nitrogen molecules at 77 K. The adsorptive pore volume of 0.41 cm3 g−1 correlates well with the pore volume of 0.43 cm3 g−1 estimated from the single crystal structure.
A novel peptidyl-lys metalloendopeptidase (Tc-LysN) from Tramates coccinea was recombinantly expressed in Komagataella phaffii using the native pro-protein sequence. The peptidase was secreted into the culture broth as zymogen (~38 kDa) and mature enzyme (~19.8 kDa) simultaneously. The mature Tc-LysN was purified to homogeneity with a single step anion-exchange chromatography at pH 7.2. N-terminal sequencing using TMTpro Zero and mass spectrometry of the mature Tc-LysN indicated that the pro-peptide was cleaved between the amino acid positions 184 and 185 at the Kex2 cleavage site present in the native pro-protein sequence. The pH optimum of Tc-LysN was determined to be 5.0 while it maintained ≥60% activity between pH values 4.5—7.5 and ≥30% activity between pH values 8.5—10.0, indicating its broad applicability. The temperature maximum of Tc-LysN was determined to be 60 °C. After 18 h of incubation at 80 °C, Tc-LysN still retained ~20% activity. Organic solvents such as methanol and acetonitrile, at concentrations as high as 40% (v/v), were found to enhance Tc-LysN’s activity up to ~100% and ~50%, respectively. Tc-LysN’s thermostability, ability to withstand up to 8 M urea, tolerance to high concentrations of organic solvents, and an acidic pH optimum make it a viable candidate to be employed in proteomics workflows in which alkaline conditions might pose a challenge. The nano-LC-MS/MS analysis revealed bovine serum albumin (BSA)’s sequence coverage of 84% using Tc-LysN which was comparable to the sequence coverage of 90% by trypsin peptides.
Governments have restricted public life during the COVID-19 pandemic, inter alia closing sports facilities and gyms. As regular exercise is essential for health, this study examined the effect of pandemic-related confinements on physical activity (PA) levels. A multinational survey was performed in 14 countries. Times spent in moderate-to-vigorous physical activity (MVPA) as well as in vigorous physical activity only (VPA) were assessed using the Nordic Physical Activity Questionnaire (short form). Data were obtained for leisure and occupational PA pre- and during restrictions. Compliance with PA guidelines was calculated based on the recommendations of the World Health Organization (WHO). In total, n = 13,503 respondents (39 ± 15 years, 59% females) were surveyed. Compared to pre-restrictions, overall self-reported PA declined by 41% (MVPA) and 42.2% (VPA). Reductions were higher for occupational vs. leisure time, young and old vs. middle-aged persons, previously more active vs. less active individuals, but similar between men and women. Compared to pre-pandemic, compliance with WHO guidelines decreased from 80.9% (95% CI: 80.3–81.7) to 62.5% (95% CI: 61.6–63.3). Results suggest PA levels have substantially decreased globally during the COVID-19 pandemic. Key stakeholders should consider strategies to mitigate loss in PA in order to preserve health during the pandemic.
In this paper, a complete passive transponder device has been discussed which is meant to monitor leakage in silicone breast implants. The passive tag operates in the HF frequency range of 13.56MHz using RFID ISO 15693 standard. The complete system consists of the transponder, reader and a PC. This paper focusses on the development of such a state of the art passive RFID transponder to monitor the wellness of the silicone breast implants periodically in order to detect leakage in the same. Keyword: RFID (Radio frequency identification device), EM (Electromagnetic) field, Passive Transponder, Silicone breast implants.
The following describes a new method for estimating the parameters of an interior permanent magnet synchronous machine (IPMSM). For the estimation of the parameters the current slopes caused by the switching of the inverter are used to determine the unknowns of the system equations of the electrical machine. The angle and current dependence of the machine parameters are linearized within a PWM cycle. By considering the different switching states of the inverter, several system equations can be derived and a solution can be found within one PWM cycle. The use of test signals and filter-based approaches is avoided. The derived algorithm is explained and validated with measurements on a test bench.
There are additional long-term effects which also change the micro-structure of the polymer network and consequently the effective number of polymer chains in the material. These effects are summarized by ageing processes and will be used in the following to explain the basic assumptions of the model which can be generalized to simulate the viscous behaviour of the material. An implementation of these concepts into FEM codes is straightforward and has been carried out to the solver ABAQUS, Baaser & Ziegler (2006), Baaser et al. (2009).
In recent years, the topic of embedded machine learning has become very popular in AI research. With the help of various compression techniques such as pruning, quantization and others compression techniques, it became possible to run neural networks on embedded devices. These techniques have opened up a whole new application area for machine learning. They range from smart products such as voice assistants to smart sensors that are needed in robotics. Despite the achievements in embedded machine learning, efficient algorithms for training neural networks in constrained domains are still lacking. Training on embedded devices will open up further fields of applications. Efficient training algorithms would enable federated learning on embedded devices, in which the data remains where it was collected, or retraining of neural networks in different domains. In this paper, we summarize techniques that make training on embedded devices possible. We first describe the need and requirements for such algorithms. Then we examine existing techniques that address training in resource-constrained environments as well as techniques that are also suitable for training on embedded devices, such as incremental learning. At the end, we also discuss which problems and open questions still need to be solved in these areas.
Time-Sensitive Networking (TSN) is the most promising time-deterministic wired communication approach for industrial applications. To extend TSN to "IEEE 802.11" wireless networks two challenging problems must be solved: synchronization and scheduling. This paper is focused on the first one. Even though a few solutions already meet the required synchronization accuracies, they are built on expensive hardware that is not suited for mass market products. While next Wi-Fi generation might support the required functionalities, this paper proposes a novel method that makes possible high-precision wireless synchronization using commercial low-cost components. With the proposed solution, a standard deviation of synchronization error of less than 500 ns can be achieved for many use cases and system loads on both CPU and network. This performance is comparable to modern wired real-time field busses, which makes the developed method a significant contribution for the extension of the TSN protocol to the wireless domain.
Printed electronics (PE) enables disruptive applications in wearables, smart sensors, and healthcare since it provides mechanical flexibility, low cost, and on-demand fabrication. The progress in PE raises trust issues in the supply chain and vulnerability to reverse engineering (RE) attacks. Recently, RE attacks on PE circuits have been successfully performed, pointing out the need for countermeasures against RE, such as camouflaging. In this article, we propose a printed camouflaged logic cell that can be inserted into PE circuits to thwart RE. The proposed cell is based on three components achieved by changing the fabrication process that exploits the additive manufacturing feature of PE. These components are optically look-alike, while their electrical behaviors are different, functioning as a transistor, short, and open. The properties of the proposed cell and standard PE cells are compared in terms of voltage swing, delay, power consumption, and area. Moreover, the proposed camouflaged cell is fabricated and characterized to prove its functionality. Furthermore, numerous camouflaged components are fabricated, and their (in)distinguishability is assessed to validate their optical similarities based on the recent RE attacks on PE. The results show that the proposed cell is a promising candidate to be utilized in camouflaging PE circuits with negligible overhead.
We provide a privacy-friendly cloud-based smart metering storage architecture which provides few-instance storage on encrypted measurements by at the same time allowing SQL queries on them. Our approach is most flexible with respect to two axes: on the one hand it allows to apply filtering rules on encrypted data with respect to various upcoming business cases; on the other hand it provides means for a storage-efficient handling of encrypted measurements by applying server-side deduplication techniques over all incoming smart meter measurements. Although the work at hand is purely dedicated to a smart metering architecture we believe our approach to have value for a broader class of IoT cloud storage solutions. Moreover, it is an example for Privacy-by-design supporting the positive-sum paradigm.
Most eCommerce applications, like web-shops have millions of products. In this context, the identification of similar products is a common sub-task, which can be utilized in the implementation of recommendation systems, product search engines and internal supply logistics. Providing this data set, our goal is to boost the evaluation of machine learning methods for the prediction of the category of the retail products from tuples of images and descriptions.
Nowadays decarbonisation of the energy system is one of the main concerns for most governments. Renewable energy technologies, such as rooftop photovoltaic systems and home battery storage systems, are changing the energy system to be more decentralised. As a consequence, new ways of energy business models are emerging, e.g., peer-to-peer energy trading. This new concept provides an online marketplace where direct energy exchange can occur between its participants. The purpose of this study is to conduct a content analysis of the existing literature, ongoing research projects, and companies related to peer-to-peer energy trading. From this review, a summary of the most important aspects and journal papers is assessed, discussed, and classified. It was found that the different energy market types were named in various ways and a proposal for standard language for the several peer-to-peer market types and the different actors involved is suggested. Additionally, by grouping the most important attributes from peer-to-peer energy trading projects, an assessment of the entry barrier and scalability potential is performed by using a characterisation matrix.
Many sectors, like finance, medicine, manufacturing, and education, use blockchain applications to profit from the unique bundle of characteristics of this technology. Blockchain technology (BT) promises benefits in trustability, collaboration, organization, identification, credibility, and transparency. In this paper, we conduct an analysis in which we show how open science can benefit from this technology and its properties. For this, we determined the requirements of an open science ecosystem and compared them with the characteristics of BT to prove that the technology suits as an infrastructure. We also review literature and promising blockchain-based projects for open science to describe the current research situation. To this end, we examine the projects in particular for their relevance and contribution to open science and categorize them afterwards according to their primary purpose. Several of them already provide functionalities that can have a positive impact on current research workflows. So, BT offers promising possibilities for its use in science, but why is it then not used on a large-scale in that area? To answer this question, we point out various shortcomings, challenges, unanswered questions, and research potentials that we found in the literature and identified during our analysis. These topics shall serve as starting points for future research to foster the BT for open science and beyond, especially in the long-term.
A Review on Kinetic Energy Harvesting with Focus on 3D Printed Electromagnetic Vibration Harvesters
(2021)
The increasing amount of Internet of Things (IoT) devices and wearables require a reliable energy source. Energy harvesting can power these devices without changing batteries. Three-dimensional printing allows us to manufacture tailored harvesting devices in an easy and fast way. This paper presents the development of hybrid and non-hybrid 3D printed electromagnetic vibration energy harvesters. Various harvesting approaches, their utilised geometry, functional principle, power output and the applied printing processes are shown. The gathered harvesters are analysed, challenges examined and research gaps in the field identified. The advantages and challenges of 3D printing harvesters are discussed. Reported applications and strategies to improve the performance of printed harvesting devices are presented.
A new RFID/NFC (ISO 15693 standard) based inductively powered passive SoC (System on chip) for biomedical applications is presented here. The proposed SOC consists of an integrated 32 bit microcontroller, RFID/NFC frontend, sensor interface circuit, analog to digital converter and some peripherals such as timer, SPI interface and memory devices. An energy harvesting unit supplies the power required for the entire system for complete passive operation. The complete chip is realized on CMOS 0.18 μm technology with a chip area of 1.5 mm × 3.0 mm.
It is generally agreed that the development and deployment of an important amount of IoT devices throughout the world has revolutionized our lives in a way that we can rely on these devices to complete certain tasks that may have not been possible just years ago which also brought a new level of convenience and value to our lives.
This technology is allowing us in a smart home environment to remotely control doors, windows, and fridges, purchase online, stream music easily with the use of voice assistants such as Amazon Echo Alexa, also close a garage door from anywhere in the world to cite some examples as this technology has added value to several domains ranging from household environments, cites, industries by exchanging and transferring data between these devices and customers. Many of these devices’ sensors, collect and share information in real-time which enables us to make important business decisions.
However, these devices pose some risks and also some security and privacy challenges that need to be addressed to reach their full potential or be considered to be secure. That is why, comprehensive risk analysis techniques are essential to enhance the security posture of IoT devices as they can help evaluate the robustness and reliability towards potential susceptibility to risks, and vulnerabilities that IoT devices in a smart home setting might possess.
This approach relies on the basis of ISO/IEC 27005 methodology and risk matrix method to highlight the level of risks, impact, and likelihood that an IoT device in smart home settings can have, map the related vulnerability, threats and risks and propose the necessary mitigation strategies or countermeasures that can be taken to secure a device and therefore satisfying some security principles. Around 30 risks were identified on Amazon Echo and the related IoT system using the methodology. A detailed list of countermeasures is proposed as a result of the risk analysis. These results, in turn, can be used to elevate the security posture of the device.
Background: Assistive Robotic Arms are designed to assist physically disabled people with daily activities. Existing joysticks and head controls are not applicable for severely disabled people such as people with Locked-in Syndrome. Therefore, eye tracking control is part of ongoing research. The related literature spans many disciplines, creating a heterogeneous field that makes it difficult to gain an overview.
Objectives: This work focuses on ARAs that are controlled by gaze and eye movements. By answering the research questions, this paper provides details on the design of the systems, a comparison of input modalities, methods for measuring the performance of these controls, and an outlook on research areas that gained interest in recent years.
Methods: This review was conducted as outlined in the PRISMA 2020 Statement. After identifying a wide range of approaches in use the authors decided to use the PRISMA-ScR extension for a scoping review to present the results. The identification process was carried out by screening three databases. After the screening process, a snowball search was conducted.
Results: 39 articles and 6 reviews were included in this article. Characteristics related to the system and study design were extracted and presented divided into three groups based on the use of eye tracking.
Conclusion: This paper aims to provide an overview for researchers new to the field by offering insight into eye tracking based robot controllers. We have identified open questions that need to be answered in order to provide people with severe motor function loss with systems that are highly useable and accessible.
The formation and analysis of ten microporous triazolyl isophthalate based MOFs, including nine isomorphous and one isostructural compound is presented. The compounds 1 M – 3 M with the general formula [ M ( R 1 - R 2 - trz - ia ) ] ∞ 3 ·x H 2 O (M 2+ = Co 2+ , Cu 2+ , Zn 2+ , Cd 2+ ; R 1 = H, Me; R 2 = 2py, 2pym, prz (2py = 2-pyridinyle; 2pym = 2-pyrimidinyle; prz = pyrazinyle)) crystallize with rtl topology. They are available as single crystals and also easily accessible in a multi-gram scale via refluxing the metal salts and the protonated ligands in a solvent. Their isomorphous structures facilitate the synthesis of heteronuclear MOFs; in case of 2 M , Co 2+ ions could be gradually substituted by Cu 2+ ions. The Co 2+ :Cu 2+ ratios were determined by ICP-OES spectroscopy, the distribution of Co 2+ and Cu 2+ in the crystalline samples are investigated by SEM-EDX analysis leading to the conclusions that Cu 2+ is more favorably incorporated into the framework compared to Co 2+ and, moreover, that the distribution of the two metal ions between the crystals and within the crystals is inhomogeneous if the crystals were grown slowly. The various compositions of the heteronuclear materials lead to different colors and the sorption properties for CO 2 and N 2 are dependent on the integrated metal ions.
Robots and automata are key elements of every vision and forecast of life in the near and distant future. However, robots and automata also have a long history, which reaches back into antiquity. Today most historians think that one of the key roles of robots and automata was to amaze or even terrify the audience: They were designed to express something mythical, magical, and not explainable. Moreover, the visions of robots and their envisioned fields of application reflect the different societies. Therefore, this short history of robotics and (especially) anthropomorphic automata aims to give an overview of several historical periods and their perspective on the topic. In a second step, this work aims to encourage readers to reflect on the recent discussion about fields of application as well as the role of robotics today and in the future.
A Simple and Reliable HPTLC Method for the Quantification of the Intense Sweetener Sucralose®
(2003)
This paper describes a simple and fast thin layer chromatography (TLC) method for the monitoring of the relatively new intense sweetener Sucralose® in various food matrices. The method requires little or no sample preparation to isolate or concentrate the analyte. The Sucralose® extract is separated on amino‐TLC‐plates, and the analyte is derivatized “reagent‐free” by heating the developed plate for 20 min at 190°C. Spots can be measured either in the absorption or fluorescence mode. The method allows the determination of Sucralose® at the levels of interest regarding foreseen European legislation (>50 mg/kg) with excellent repeatability (RSD = 3.4%) and recovery data (95%).
HPTLC on amino plates, with simple heating of the plates for derivatization, has been used for quantification of glucosamine in nutritional supplements. On heating the plate glucosamine reacts to form a compound which strongly absorbs light between 305 and 330 nm, with weak fluorescence. The reaction product can be detected sensitively either by absorption of light or by fluorescence detection. The detection limit in absorption mode is approximately 25 ng per spot. In fluorescence mode a detection limit of 15 ng is achievable. A calibration plot for absorption detection is linear in the range 25 to 4000 ng glucosamine. The derivative formed from glucosamine by heating is stable for months, and the relative standard deviation is 1.64% for 600 ng glucosamine. The amounts of glucosamine found in nutritional supplements were in agreement with the label declarations.
In medical applications wireless technologies are not widely spread. Today they are mainly used in non latency-critical applications where reliability can be guaranteed through retransmission protocols and error correction mechanisms. By using retransmission protocols within the disturbed shared wireless channel latency will increase. Therefore retransmission protocols are not sufficient for removing latency-critical wired connections within operating rooms such as foot switches. Todays research aims to improve reliability through the physical characteristics of the wireless channel by using diversity methods and more robust modulation. In this paper an Architecture for building up a reliable network is presented. The Architecture offers the possibility for devices with different reliability, latency and energy consumption requirements to participate. Furthermore reliability, latency and energy consumption are scalable for every single participant.
A simple Method for quantifying Triazine Herbicides using Thin-Layer Chromatography and a CCD-Camera
(2010)
We present a video-densitometric quantification method for the triazine herbicides atraton, terbumeton, simazine, atrazine, and terbutylazine. Triazine herbicides were separated on silica gel using methyl-t-butyl ether, cyclohexane (1 + 1, v/v) as mobile phase. The quantification is based on a derivation reaction using chlorine and starch-iodine which forms red-brown triazine zones. Measurements were carried out using a 16 bit ST-1603ME CCD camera with 1.56 megapixel from Santa Barbara Instrument Group, Inc., Santa Barbara, USA. A white LED was used for illumination purposes. The range of linearity covers two magnitudes using the (1/R-1) expression data transformation. The signal-to-noise ratio increases directly linearly with the measurement time. The separation method is cheap, fast and reliable.
We present an improved quantification method for urethane found in spirits. The quantification is based on a derivatization reaction using cinnamaldehyde in combination with phosphoric acid. Measurements were carried out in the wavelength range from 445 to 460 nm using a diode-TLC device. An LED was used for illumination purposes. It emits very dense light at 365 nm. The quantification range of urethane is in the lower ng range. By applying 20 µL of sprits, the urethane quantification range is from 320 µg/L to 8.1 mg urethane per litre of spirit. The range of linearity covers nearly two magnitudes. The method is cheap, fast and reliable, and is able to monitor all European legislation limits without time-consuming sample pre-treatments.
A new, small, and optimized for low power processor core named SIRIUS has been developed, simulated, synthesized to a netlist and verified. From this netlist, containing only primitives like gates and flip-flops, a mapping to an ASIC - or FPGA technology can easily be done with existing synthesizer tools, allowing very complex SOC designs with several blocks. Emulation via FPGA can be done on already simple setups and cheap hardware because of the small core size. The performance is estimated 50 MIPS on Cyclone II FPGA and about 100 MIPS on a 0.35 CMOS 5M2P technology with 4197 primitives used for the core, including a 16 x 16 multiplier. An example design of the ASIC for an electronic ePille device currently in development is shown.
A printed electronics technology has the advantage of additive and extremely low-cost fabrication compared with the conventional silicon technology. Specifically, printed electrolyte-gated field-effect transistors (EGFETs) are attractive for low-cost applications in the Internet-of-Things domain as they can operate at low supply voltages. In this paper, we propose an empirical dc model for EGFETs, which can describe the behavior of the EGFETs smoothly and accurately over all regimes. The proposed model, built by extending the Enz-Krummenacher-Vittoz model, can also be used to model process variations, which was not possible previously due to fixed parameters for near threshold regime. It offers a single model for all the operating regions of the transistors with only one equation for the drain current. Additionally, it models the transistors with a less number of parameters but higher accuracy compared with existing techniques. Measurement results from several fabricated EGFETs confirm that the proposed model can predict the I-V more accurately compared with the state-of-the-art models in all operating regions. Additionally, the measurements on the frequency of a fabricated ring oscillator are only 4.7% different from the simulation results based on the proposed model using values for the switching capacitances extracted from measurement data, which shows more than 2× improvement compared with the state-of-the-art model.
A new miniaturized capsule with 32bit processor and bidirectional communication system is being developed for multitask application. The capsule is designed to be a platform for medical assistant application inside the body. The processor core SIRIUS has been developed, simulated, synthesized to a netlist and verified. The designed telemetry unit is a synchronous bidirectional communication block using continuous phase DQPSK of 115 kHz low carrier frequency for inductive data transmission suited for human body energy transfer. The communication system can assist the electronic pill to trigger an actuator for drug delivery, to record temperature, or to measure pH of the body. The complete system is designed to fit small-size mass medical application with low power consumption, size of 7x25 mm. The system is designed, simulated, emulated on FPGA, and routed in AMIS Technology.
Ensuring that software applications present their users the most recent version of data is not trivial. Self-adjusting computations are a technique for automatically and efficiently recomputing output data whenever some input changes.
This article describes the software architecture of a large, commercial software system built around a framework for coarse-grained self-adjusting computations in Haskell. It discusses advantages and disadvantages based on longtime experience. The article also presents a demo of the system and explains the API of the framework.
In short-reach connections, large-diameter multimode fibres allow for robust and easy connections. Unfortunately, their propagation properties depend on the excitation conditions. We propose a launching technique using a fibre stub that can tolerate fabrication tolerances in terms of tilts and off-sets to a large extent. A study of the influence of displaced connectors along the transmission link shows that the power distributions approach a steady-state power distribution very similar to the initial distribution established by the proposed launching scheme.
Decentralized applications (dApp) have proliferated in recent years, but their long-term viability is a topic of debate. However, for dApps to be sustainable, and suitable for integration into a larger service networks, they need to attract users and promise reliable availability. Therefore, assessing their longevity is crucial. Analyzing the utilization trajectory of a service is, however, challenging due to several factors, such as demand spikes, noise, autocorrelation, and non-stationarity. In this study, we employ robust statistical techniques to identify trends in currently popular dApps. Our findings demonstrate that a significant proportion of dApps, across a range of categories, exhibit statistically significant positive overall trends, indicating that success in decentralized computing can be sustainable and transcends specific fields. However, there is also a substantial number of dApps showing negative trends, with a disproportionately high number from the decentralized finance (DeFi) category. Furthermore, a more detailed inspection of time series segments shows a clearly diminishing proportion of positive trends from mid-2021 to the present. In summary, we conclude that the dApp economy might have lost some momentum, and that there is a strong element of uncertainty regarding its future significance.
With increasing flexible AC transmission system (FACTS) devices in operation, like the most versatile unified power flow controller (UPFC), the AC/DC transmission flexibility and power system stability have been suffering unprecedented challenge. This paper introduces the user-defined modeling (UDM) method into the UPFC dynamic modeling process, to deal with the challenging requirements of power system operation. This has also been verified using a leading-edge stability analysis software named DSATools TM in the IEEE-39 bus benchmark system. The characteristics of steady-state and dynamic responses are compared and analyzed under different conditions. Furthermore, simulation results prove the feasibility and effectiveness of the proposed UPFC in terms of both the independent regulation of power flow and the improvement of transient stability.
A Survey of Channel Measurements and Models for Current and Future Railway Communication Systems
(2016)
It is important to minimize the unscheduled downtime of machines caused by outages of machine components in highly automated production lines. Considering machine tools such as, grinding machines, the bearing inside of spindles is one of the most critical components. In the last decade, research has increasingly focused on fault detection of bearings. In addition, the rise of machine learning concepts has also intensified interest in this area. However, up to date, there is no single one-fits-all solution for predictive maintenance of bearings. Most research so far has only looked at individual bearing types at a time.
This paper gives an overview of the most important approaches for bearing-fault analysis in grinding machines. There are two main parts of the analysis presented in this paper. The first part presents the classification of bearing faults, which includes the detection of unhealthy conditions, the position of the error (e.g. at the inner or at the outer ring of the bearing) and the severity, which detects the size of the fault. The second part presents the prediction of remaining useful life, which is important for estimating the productive use of a component before a potential failure, optimizing the replacement costs and minimizing downtime.
The increase of the Internet of Things (IoT) calls for secure solutions for industrial applications. The security of IoT can be potentially improved by blockchain. However, blockchain technology suffers scalability issues which hinders integration with IoT. Solutions to blockchain’s scalability issues, such as minimizing the computational complexity of consensus algorithms or blockchain storage requirements, have received attention. However, to realize the full potential of blockchain in IoT, the inefficiencies of its inter-peer communication must also be addressed. For example, blockchain uses a flooding technique to share blocks, resulting in duplicates and inefficient bandwidth usage. Moreover, blockchain peers use a random neighbor selection (RNS) technique to decide on other peers with whom to exchange blockchain data. As a result, the peer-to-peer (P2P) topology formation limits the effective achievable throughput. This paper provides a survey on the state-of-the-art network structures and communication mechanisms used in blockchain and establishes the need for network-based optimization. Additionally, it discusses the blockchain architecture and its layers categorizes existing literature into the layers and provides a survey on the state-of-the-art optimization frameworks, analyzing their effectiveness and ability to scale. Finally, this paper presents recommendations for future work.
Voice user interfaces (VUIs) offer an intuitive, fast and convenient way for humans to interact with machines and computers. Yet, whether they’ll be truly successful and find widespread uptake in the near future depends on the user experience (UX) they offer. With this survey-based study (n = 108), we aim to identify the major annoyances German voice assistant users are facing in voice-driven human-computer interactions. The results of our questionnaire show that irritations appear in six categories: privacy issues, unwanted activation, comprehensibility, response quality, conversational design and voice characteristics. Our findings can help identify key areas of work to optimize voice user experience in order to achieve greater adaptation of the technology. In addition, they can provide valuable information for the further development and standardization of voice user experience (VUX) research.
In this article, we present a taxonomy in Robot-Assisted Training; a growing body of research in Human–Robot Interaction which focuses on how robotic agents and devices can be used to enhance user’s performance during a cognitive or physical training task. Robot-Assisted Training systems have been successfully deployed to enhance the effects of a training session in various contexts, i.e., rehabilitation systems, educational environments, vocational settings, etc. The proposed taxonomy suggests a set of categories and parameters that can be used to characterize such systems, considering the current research trends and needs for the design, development and evaluation of Robot-Assisted Training systems. To this end, we review recent works and applications in Robot-Assisted Training systems, as well as related taxonomies in Human–Robot Interaction. The goal is to identify and discuss open challenges, highlighting the different aspects of a Robot-Assisted Training system, considering both robot perception and behavior control.
Hot work tools are subjected to complex thermal and mechanical loads during hot forming processes. Locally, the stresses can exceed the material’s yield strength in highly loaded areas as e.g. in small radii in die cavities. To sustain the high loads, the hot forming tools are typically made of martensitic hot work steels. While temperatures for annealing of the tool steels usually lie in the range between 400 and 600 °C, the steels may experience even higher temperatures during hot forming, resulting in softening of the material due to coarsening of strengthening particles. In this paper, a temperature dependent cyclic plasticity model for the martensitic hot work tool steel 1.2367 (X38CrMoV5-3) is presented that includes softening due to particle coarsening and that can be applied in finite-element calculations to assess the effect of softening on the thermomechanical fatigue life of hot work tools. To this end, a kinetic model for the evolution of the mean size of secondary carbides based on Ostwald ripening is coupled with a cyclic plasticity model with kinematic hardening. Mechanism-based relations are developed to describe the dependency of the mechanical properties on carbide size and temperature. The material properties of the mechanical and kinetic model are determined on the basis of tempering hardness curves as well as monotonic and cyclic tests.
In this paper, a temperature-dependent viscoplasticity model is presented that describes thermal and cyclic softening of the hot work steel X38CrMoV5-3 under thermomechanical fatigue loading. The model describes the softening state of the material by evolution equations, the material properties of which can be determined on the basis of a defined experimental program. A kinetic model is employed to capture the effect of coarsening carbides and a new isotropic cyclic softening model is developed that takes history effects during thermomechanical loadings into account. The temperature-dependent material properties of the viscoplasticity model are determined on the basis of experimental data measured in isothermal and thermomechanical fatigue tests for the material X38CrMoV5-3 in the temperature range between 20 and 650 ∘C. The comparison of the model and an existing model for isotropic softening shows an improved description of the softening behavior under thermomechanical fatigue loading. A good overall description of the experimental data is possible with the presented viscoplasticity model, so that it is suited for the assessment of operating loads of hot forging tools.
Air traffic control today still works primarily with classical sensors like primary and Secondary Surveillance Radars (PSR, MSSR, Mode-S) [1]. Upcoming is a new technology, ADS (Automatic Dependent Surveillance), which derives positional information from a Global Navigation Satellite System (GNSS) and distributes this data together with additional information from the on-board Flight Management System (FMS) to other aircraft (air-to-air) and to ADS groundstations (air-to-ground). [2] Because the transmission of the data takes place on a shared broadcasting media, like the 1090 MHz Extended Squitter (ES) channel, the technology is also referred to as ADS-Broadcast (ADS-B).
The DMFC is a promising option for backup power systems and for the power supply of portable devices. However, from the modeling point of view liquid-feed DMFC are challenging systems due to the complex electrochemistry, the inherent two-phase transport and the effect of methanol crossover. In this paper we present a physical 1D cell model to describe the relevant processes for DMFC performance ranging from electrochemistry on the surface of the catalyst up to transport on the cell level. A two-phase flow model is implemented describing the transport in gas diffusion layer and catalyst layer at the anode side. Electrochemistry is described by elementary steps for the reactions occurring at anode and cathode, including adsorbed intermediate species on the platinum and ruthenium surfaces. Furthermore, a detailed membrane model including methanol crossover is employed. The model is validated using polarization curves, methanol crossover measurements and impedance spectra. It permits to analyze both steady-state and transient behavior with a high level of predictive capabilities. Steady-state simulations are used to investigate the open circuit voltage as well as the overpotentials of anode, cathode and electrolyte. Finally, the transient behavior after current interruption is studied in detail.
Multiple Object Tracking (MOT) is a long-standing task in computer vision. Current approaches based on the tracking by detection paradigm either require some sort of domain knowledge or supervision to associate data correctly into tracks. In this work, we present a self-supervised multiple object tracking approach based on visual features and minimum cost lifted multicuts. Our method is based on straight-forward spatio-temporal cues that can be extracted from neighboring frames in an image sequences without supervision. Clustering based on these cues enables us to learn the required appearance invariances for the tracking task at hand and train an AutoEncoder to generate suitable latent representations. Thus, the resulting latent representations can serve as robust appearance cues for tracking even over large temporal distances where no reliable spatio-temporal features can be extracted. We show that, despite being trained without using the provided annotations, our model provides competitive results on the challenging MOT Benchmark for pedestrian tracking.
Featherweight Generic Go (FGG) is a minimal core calculus modeling the essential features of the programming language Go. It includes support for overloaded methods, interface types, structural subtyping and generics. The most straightforward semantic description of the dynamic behavior of FGG programs is to resolve method calls based on runtime type information of the receiver.
This article shows a different approach by defining a type-directed translation from FGG to an untyped lambda-calculus. The translation of an FGG program provides evidence for the availability of methods as additional dictionary parameters, similar to the dictionary-passing approach known from Haskell type classes. Then, method calls can be resolved by a simple lookup of the method definition in the dictionary.
Every program in the image of the translation has the same dynamic semantics as its source FGG program. The proof of this result is based on a syntactic, step-indexed logical relation. The step-index ensures a well-founded definition of the relation in the presence of recursive interface types and recursive methods.
Featherweight Generic Go (FGG) is a minimal core calculus modeling the essential features of the programming language Go. It includes support for overloaded methods, interface types, structural subtyping, and generics. The most straightforward semantic description of the dynamic behavior of FGG programs is to resolve method calls based on runtime type information of the receiver. This article shows a different approach by defining a type-directed translation from FGG− to an untyped lambda-calculus. FGG− includes all features of FGG but type assertions. The translation of an FGG− program provides evidence for the availability of methods as additional dictionary parameters, similar to the dictionary-passing approach known from Haskell type classes. Then, method calls can be resolved by a simple lookup of the method definition in the dictionary. Every program in the image of the translation has the same dynamic semantics as its source FGG− program. The proof of this result is based on a syntactic, step-indexed logical relation. The step index ensures a well-founded definition of the relation in the presence of recursive interface types and recursive methods. Although being non-deterministic, the translation is coherent.