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The objective of this project is to enhance the operations of a micro-enterprise that deals with food ingredients. The emphasis is on streamlining procedures and executing effective tactics. By utilizing tools like SWOT analysis, evaluations, and strategy development, the company's strengths, weaknesses, opportunities, and threats were assessed. The company developed business-level and functional-level strategies to expedite growth and attain objectives based on the findings. Moreover, precise suggestions were given to minimize the quantity of SKUs and optimize operations. The work highlighted the significance of developing a process map for streamlining operations, boosting efficiency, and elevating customer contentment. Through the implementation of said recommendations and strategies, the company can strategically position itself for success within the highly competitive food ingredients industry.
Online grocery shopping (OGS) has significantly risen due to accelerated retail digitization and reshaped consumer shopping behaviors over the last years. Despite this trend, the German online grocery market lags behind its international counterparts. Notably, with almost half of the German population aged over 50 and the 55–64 age group emerging as the largest user segment in e-commerce, the over-50 demographic presents an attractive yet relatively overlooked audience for the expansion of the online grocery market. However, research on OGS behavior among German over-50s is scarce. This study addresses this gap, empirically investigating OGS adoption factors within this demographic through an online survey with 179 respondents. Our findings reveal that over a third of the over-50 demographic has embraced OGS, indicating a growing receptivity for OGS among the over-50s. Notably, home delivery, product variety, convenience, and curiosity emerged as primary drivers for OGS adoption among this demographic. Surprisingly, most adopters did not increase online grocery orders since 2020 and a not inconsiderable proportion have even stopped buying groceries online again. For potential OGS adopters, regional product availability turned out as a motivator, signaling substantial growth potential and providing online grocers with strategic opportunities to target this demographic. In light of our research, we offer practical suggestions to online grocery retailers, aiming to overcome barriers and capitalize on key drivers identified in our study for sustained growth in the over-50 market segment.
In a dynamic global landscape, the role of UK Export Finance (UKEF) and other export credit agencies (ECAs) has never been more important. Access to finance is critical for exporters as it enables them to invest in production, expand operations, manage cash flow and mitigate trade risks. However, businesses face challenges in securing export finance and trade credit insurance as geopolitical and trade megatrends lead to increased political, market and credit risks. Drawing on qualitative data from 35 semi-structured interviews and expert discussions and based on the Futures Triangle analytical framework, this white paper analyses the geopolitical and trade megatrends that UKEF and other ECAs will face in the coming years. It presents novel findings about the implications for ECA mandates, strategies, products and operations: The evolution of mandates towards a “growth promoter”, the need to further scale up operations, the use of big data and artificial intelligence for risk analysis and forecasting, and the need to balance multiple and conflicting priorities, including export growth, support for small and medium-sized exporters, inclusive trade, climate action, and positive impact in developing markets.
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.
This report examines exporters’ challenges and possible solutions for public intervention to promote foreign trade. Based on fieldwork conducted in Georgia, we explore which policy approaches can help to stimulate Georgian exports further. Our outcomes show that exporters face substantial barriers such as navigating complex trade regulations, lack of knowledge about target markets, trade finance gaps, as well as new export promotion programs (EPPs) in competitor countries. Other upper-middle-income countries can learn from our results that exporters can significantly benefit from a comprehensive export promotion strategy combined with an ecosystem-based “team” approach. EPPs related to awareness and capacity building in Georgia should be part of this strategy, focusing on challenges such as a lack of knowledge about trade practices and international business skills. Other EPPs must help to mitigate related market failures, as information gathering is costly, and firms have no incentive to share this information with competitors. Furthermore, targeted marketing support and customer matchmaking can answer Georgian exporters’ challenges, such as lack of market access and low sector visibility. Our results also show that public intervention through financial support and risk mitigation is essential for firms with an international orientation. The high-quality, rich outcomes provide significant value for other upper-middle-income countries by exploring the example of Georgia’s contemporary circumstances in an in-depth manner based on extensive interviews and document analysis. Limitations include that our work primarily relies on qualitative data and further research could involve a quantitative study with a diverse range of sectors.
In anisotropic media, the existence of leaky surface acoustic waves is a well-known phenomenon. Very recently, their analogs at the apex of an elastic silicon wedge have been found in experiments using laser-ultrasonics. In addition to a wedge-wave (WW) pulse with low speed, a pseudo-wedge wave (p-WW) pulse was found with a velocity higher than the velocity of shear bulk waves, propagating in the same direction. With a probe-beam-deflection technique, the propagation of the WW pulses was monitored on one of the faces of the wedge at variable distance from the apex. In this way, their depth structure and the leakage of the p-WW could be visualized directly. Calculations were carried out using a method based on a representation of the displacement field in Laguerre functions. This method has been validated by calculating the surface density of states in anisotropic media and comparing the results with those obtained from the surface Green's tensor. The approach has then been extended to the continuum of acoustic modes in infinite wedges with fixed wave-vector along the apex. These calculations confirmed the measured speeds of the WW and p-WW pulses.
Anisotropy has been found to play an important role for the existence of edge-localized acoustic modes as well as for nonlinear effects in rectangular edges. For a certain propagation geometry in silicon, the effective second-order nonlinearity for wedge waves was determined numerically from second-order and third-order elastic moduli and compared with the nonlinearity for Rayleigh waves propagating in the direction of the apex on one of the two surfaces forming the edge. In the presence of weak dispersion resulting from modifications of the wedge tip or coating of the adjacent surfaces, solitary pulses are predicted to exist and their shape was calculated.
This study investigates the impact of global payroll outsourcing on organizational efficiency and cost reduction based on the analysis of diverse implications stemming from thirty one (31) survey results. The findings reveal multifaceted challenges and benefitsassociated with outsourcing global payroll processing.
The research also unveils the most benefits of global payroll outsourcing. Notably, there's a consensus on the reduction in time-to-process payroll, cost per payroll processed, and improved payroll accuracy rate. Outsourcing streamlines processes, enhances operational efficiency, and contributes to faster, more accurate financial reporting.
Despite these benefits and challenges, statistical analysis reveals weak correlations between outsourcing global payroll and cost reduction or improved efficiency in various parameters, indicating a lack of a significant relationship. Consequently, the results, suggest no substantial correlation between global payroll outsourcing and enhanced efficiency or cost reduction based on this study's data.
Most E-Learning projects tend to separate learning activities from everyday work. This paper presents an approach where closer integration between learning and work is achieved by integrating multimedia services into manufacturing processes. The goal of E-Learning services integration in manufacturing is, through the development of new multimedia solutions, to accelerate and enhance the ability of manufacturing industry to capitalise on the emergence of a powerful global information infrastructure. In this paper we suggest to combine the areas of media streaming services and manufacturing processes, by providing electronic learning offerings as collections of media streaming services. The key components of our approach are 1) an xml based streaming service specification language, 2) automated configuration of distributed E-Learning streaming applications, 3) web services for searching, registration, and creation of E-Learning streaming services.
Integrating voice / video communication into business processes can accelerate resolution time, reduce mistakes, and establish a full audit-trail of the interactions. Some VoIP service providers offer website based or plugin based solutions, which are, however, difficult to integrate with other applications. A promising approach to overcome these disadvantages is the development of appropriate Web Services to allow applications interacting with a VoIP system. We propose a generic framework for VoIP applications consisting of an XML-based service specification language and a set of reusable Web Service components. Service providers using the proposed service-oriented architecture can offer to their customers a protocol-neutral Web Service interface, thus enabling the deployment of a general and integrated VoIP solution.
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.
In this paper we suggest to combine the areas of media streaming services, mobile devices, and manufacturing processes to support monitoring, controlling and supervising production processes in order to achieve high levels of efficiency and environmentally friendly production. It contains a comprehensive and detailed explanation of the proposed E-Learning streaming framework, especially the adaption of streaming services to mobile environments. The key components of our approach are 1) an XML-based streaming service specification language, 2) adaption of multimedia E-Learning services to mobile environments, and 3) a media delivery platform for searching, registration, and creation of streaming services for mobile devices.
The need of suitable system of records in gaining ground as companies seek to maximize performance by harnessing the knowledge of their businesses, is discussed. Focused systems of record deliver a clear and consistent view even as they address a range of functions. Enterprise resource planning (ERP), as the financial system of record, embodies that view of manufacturing, inventory management, accounting and order processing. Customer relationship management (CRM), as a system of record, taps not only into the marketing and sales and service, but also into product development.
The central purpose of this paper is to present a novel framework supporting the specification and the implementation of media streaming services using XML and Java Media Framework (JMF). It provides an integrated service development environment comprising of a streaming service model, a service specification language and several implementation and retrieval tools. Our approach is based on a clear separation of a streaming service specification, and its implementation by a distributed JMF application and can be used for different streaming paradigms, e.g. push and pull services.
This paper presents an approach where closer integration between learning and work is achieved by integrating multimedia services into manufacturing processes. The goal of E-Learning services integration in manufacturing processes is, through the development of new multimedia services, to accelerate and enhance the ability of manufacturing industry to capitalise on the emergence of a powerful global information infrastructure. In this paper we suggest to combine the areas of media streaming services and manufacturing processes, by providing electronic learning offerings as collections of media streaming services. The key components of our approach are 1) an xml based streaming service specification language, 2) automated configuration of distributed E-Learning streaming applications, 3) Web Services for searching, registration, and creation of E-Learning streaming services.
We propose a new streaming media service development environment comprising of a streaming media service model, a XML based service specification language and several implementation and configuration management tools. In our project, the described approach is used for integration of streaming based eLearning services in manufacturing processes of a subcontractor to the automotive industry. The key components of our approach are 1) an xml based streaming service specification language, 2) a set of web services for searching, registration, and creation of streaming services, 3) caching and replication policies based on timing information derived from the service specifications.
The goal of eLearning services integration in manufacturing is, through the development of new multimedia solutions, to accelerate and enhance the ability of the manufacturing industry to capitalise on the emergence of a powerful global information infrastructure. The key components of our approach are: (1) an XML based streaming service specification language; (2) automatic configuration of distributed eLearning streaming service implementations; (3) a set of Web services for searching, registration, and creation of streaming services; (4) caching and replication policies based on timing information derived from the service specifications. We also introduce a new concept for cache management during runtime, e.g., content is distributed to cache servers located at the edge of a network close to the client.
The central purpose of this paper is to present a novel framework supporting the specification, the implementation and retrieval of media streaming services. It provides an integrated service development environment comprising of a streaming service model, a service specification language and several implementation and retrieval tools. Our approach is based on a clear separation of a streaming service specification, and its implementation by a distributed application and can be used for different streaming paradigms, e.g. push and pull services.
CNN-based deep learning models for disease detection have become popular recently. We compared the binary classification performance of eight prominent deep learning models: DenseNet 121, DenseNet 169, DenseNet 201, EffecientNet b0, EffecientNet lite4, GoogleNet, MobileNet, and ResNet18 for their binary classification performance on combined Pulmonary Chest Xrays dataset. Despite the widespread application in different fields in medical images, there remains a knowledge gap in determining their relative performance when applied to the same dataset, a gap this study aimed to address. The dataset combined Shenzhen, China (CH) and Montgomery, USA (MC) data. We trained our model for binary classification, calculated different parameters of the mentioned models, and compared them. The models were trained to keep in mind all following the same training parameters to maintain a controlled comparison environment. End of the study, we found a distinct difference in performance among the other models when applied to the pulmonary chest Xray image dataset, where DenseNet169 performed with 89.38 percent and MobileNet with 92.2 percent precision.
The COVID19 pandemic, a unique and devastating respiratory disease outbreak, has affected global populations as the disease spreads rapidly. Recent Deep Learning breakthroughs may improve COVID19 prediction and forecasting as a tool of precise and fast detection, however, current methods are still being examined to achieve higher accuracy and precision. This study analyzed the collection contained 8055 CT image samples, 5427 of which were COVID cases and 2628 non COVID. The 9544 Xray samples included 4044 COVID patients and 5500 non COVID cases. The most accurate models are MobileNet V3 (97.872 percent), DenseNet201 (97.567 percent), and GoogleNet Inception V1 (97.643 percent). High accuracy indicates that these models can make many accurate predictions, as well as others, are also high for MobileNetV3 and DenseNet201. An extensive evaluation using accuracy, precision, and recall allows a comprehensive comparison to improve predictive models by combining loss optimization with scalable batch normalization in this study. Our analysis shows that these tactics improve model performance and resilience for advancing COVID19 prediction and detection and shows how Deep Learning can improve disease handling. The methods we suggest would strengthen healthcare systems, policymakers, and researchers to make educated decisions to reduce COVID19 and other contagious diseases.
Learning programming fundamentals is considered as one of the most challenging and complex learning activities. Some authors have proposed visual programming language (VPL) approaches to address part of the inherent complexity [1]. A visual programming language lets users develop programs by combining program elements, like loops graphically rather than by specifying them textually. Visual expressions, spatial arrangements of text and graphic symbols are used either as syntax elements or secondary notation. VPLs are normally used for educational multimedia, video games, system development, and data warehousing/business analytics purposes. For example, Scratch, a platform of Massachusetts Institute of Technology, is designed for kids and after school programs.
Design of mobile software applications is considered as one of the most challenging application domains due to the build in sensors as part of a mobile device, like GPS, camera or Near Field Communication (NFC). Sensors enable creation of context-aware mobile applications in which applications can discover and take advantage of contextual information, such as user location, nearby people and objects, and the current user activity. As a consequence, context-aware mobile applications can sense clues about the situational environment making mobile devices more intelligent, adaptive, and personalized. Such context aware mobile applications seem to be motivating and attractive case studies, especially for programming beginners (“my own first app”).
In this work, we introduce a use-case centered approach as well as clear separation of user interface design and sensor-based program development. We provide an in-depth discussion of a new VPL based teaching method, a step by step development process to enable programming beginners the creation of context aware mobile applications. Finally, we argue that addressing challenges for programming beginners by our teaching approach could make programming teaching more motivating, with an additional impact on the final software quality and scalability.
The key contributions of our study are the following:
- An overview of existing attempts to use VPL approaches for mobile applications
- A use case centered teaching approach based on a clear separation of user interface design and sensor-based program development
- A teaching case study enabling beginners a step by step creation of context-aware mobile applications based on the MIT App Inventor (a platform of Massachusetts Institute of Technology)
- Open research challenges and perspectives for further development of our teaching approach
References:
[1] Idrees, M., Aslam, F. (2022). A Comprehensive Survey and Analysis of Diverse Visual Programming Languages, VFAST Transactions on Software Engineering, 2022, Volume 10, Number 2, pp 47-60.
3D Bin Picking with an innovative powder filled gripper and a torque controlled collaborative robot
(2023)
A new and innovative powder filled gripper concept will be introduced to a process to pick parts out of a box without the use of a camera system which guides the robot to the part. The gripper is a combination of an inflatable skin, and a powder inside. In the unjammed condition, the powder is soft and can adjust to the geometry of the part which will be handled. By applying a vacuum to the inflatable skin, the powder gets jammed and transforms to a solid shaped form in which the gripper was brought before applying the vacuum. This physical principle is used to pick parts. The flexible skin of the gripper adjusts to all kinds of shapes, and therefore, can be used to realize 3D bin picking. With the help of a force controlled robot, the gripper can be pushed with a consistent force on flexible positions depending of the filling level of the box. A Kuka LBR iiwa with joint torque sensors in all of its seven axis’ was used to achieve a constant contact pressure. This is the basic criteria to achieve a robust picking process.
We revisit the quantitative analysis of the ultrafast magnetoacoustic experiment in a freestanding nickel thin film by Kim and Bigot [J.-W. Kim and J.-Y. Bigot, Phys. Rev. B 95, 144422 (2017)] by applying our recently proposed approach of magnetic and acoustic eigenmode decomposition. We show that the application of our modeling to the analysis of time-resolved reflectivity measurements allows for the determination of amplitudes and lifetimes of standing perpendicular acoustic phonon resonances with unprecedented accuracy. The acoustic damping is found to scale as ∝ω2 for frequencies up to 80 GHz, and the peak amplitudes reach 10−3. The experimentally measured magnetization dynamics for different orientations of an external magnetic field agrees well with numerical solutions of magnetoelastically driven magnon harmonic oscillators. Symmetry-based selection rules for magnon-phonon interactions predicted by our modeling approach allow for the unambiguous discrimination between spatially uniform and nonuniform modes, as confirmed by comparing the resonantly enhanced magnetoelastic dynamics simultaneously measured on opposite sides of the film. Moreover, the separation of timescales for (early) rising and (late) decreasing precession amplitudes provide access to magnetic (Gilbert) and acoustic damping parameters in a single measurement.
While most ultrafast time-resolved optical pump-probe experiments in magnetic materials reveal the spatially homogeneous magnetization dynamics of ferromagnetic resonance (FMR), here we explore the magneto-elastic generation of GHz-to-THz frequency spin waves (exchange magnons). Using analytical magnon oscillator equations, we apply time-domain and frequency-domain approaches to quantify the results of ultrafast time-resolved optical pump-probe experiments in free-standing ferromagnetic thin films. Simulations show excellent agreement with the experiment, provide acoustic and magnetic (Gilbert) damping constants and highlight the role of symmetry-based selection rules in phonon-magnon interactions. The analysis is extended to hybrid multilayer structures to explore the limits of resonant phonon-magnon interactions up to THz frequencies.
The technique of laser ultrasonics perfectly meets the need for noncontact, noninvasive, nondestructive mechanical probing of nanometer- to millimeter-size samples. However, this technique is limited to the excitation of low-amplitude strains, below the threshold for optical damage of the sample. In the context of strain engineering of materials, alternative optical techniques enabling the excitation of high-amplitude strains in a nondestructive optical regime are needed. We introduce here a nondestructive method for laser-shock wave generation based on additive superposition of multiple laser-excited strain waves. This technique enables strain generation up to mechanical failure of a sample at pump laser fluences below optical ablation or melting thresholds. We demonstrate the ability to generate nonlinear surface acoustic waves (SAWs) in Nb-SrTiO3 substrates, with associated strains in the percent range and pressures up to 3 GPa at 1 kHz repetition rate and close to 10 GPa for several hundred shocks. This study paves the way for the investigation of a host of high-strain SAW-induced phenomena, including phase transitions in conventional and quantum materials, plasticity and a myriad of material failure modes, chemistry and other effects in bulk samples, thin layers, and two-dimensional materials.
Differentiation between human and non-human objects can increase efficiency of human-robot collaborative applications. This paper proposes to use convolutional neural networks for classifying objects in robotic applications. The body temperature of human beings is used to classify humans and to estimate the distance to the sensor. Using image classification with convolutional neural networks it is possible to detect humans in the surroundings of a robot up to five meters distance with low-cost and low-weight thermal cameras. Using transfer learning technique we trained the GoogLeNet and MobilenetV2. Results show accuracies of 99.48 % and 99.06 % respectively.
Public educational institutions are increasingly confronted with a decline in the number of applicants, which is why competition between colleges and universities is also intensifying. For this reason, it is important to position oneself as an institution in order to be perceived by the various target groups and to differentiate oneself from the competition. In this context, the brand and thus its perception and impact play a decisive role, especially in view of the desired communication of the institution's own values and its self-image, the brand identity. To this end, emotions serve as an approach to creating positive stimulation and brand loyalty.
In this study, circular economy (CE) relevance in Germany will be discussed based on LinkedIn readily available data. LinkedIn company profiles located in Germany with ‘circular economy’ in their description or any other field were selected and used as a data source to analyze their CE relation. Overall, 514 German companies were analyzed in reference to the 15 German regions they belong. Most companies are located in the federal state of Berlin (126), followed by North Rhine-Westphalia (96) and Bavaria (77). In terms of the industry sector, they are self-classified to environmental services (64), management consulting (50), renewables & environment (33), research (31), and computer software (18) etc. Regarding their employees with LinkedIn profiles, 22,621 people are affiliated with these companies, ranging from one to 7,877. All examined companies have a total of 819,632 followers on LinkedIn, ranging from none to 88,167. An increase in CE-related companies was recorded in 13 of the 16 federal states of Germany over a one-year period. This work provides essential insights into the increasing relevance and trends of the circular economy in German enterprises and will help conduct further national studies with readily available data from LinkedIn.
Femtosecond (fs) time-resolved magneto-optics is applied to investigate laser-excited ultrafast dynamics of one-dimensional nickel gratings on fused silica and silicon substrates for a wide range of periodicities Λ = 400–1500 nm. Multiple surface acoustic modes with frequencies up to a few tens of GHz are generated. Nanoscale acoustic wavelengths Λ/n have been identified as nth-spatial harmonics of Rayleigh surface acoustic wave (SAW) and surface skimming longitudinal wave (SSLW), with acoustic frequencies and lifetimes being in agreement with theoretical calculations. Resonant magnetoelastic excitation of the ferromagnetic resonance (FMR) by SAW’s third spatial harmonic, and, most interestingly fingerprints of the parametric resonance at 1/2 SAW frequency have been observed. Numerical solutions of Landau–Lifshitz–Gilbert (LLG) equation magnetoelastically driven by complex polychromatic acoustic fields quantitatively reproduce all resonances at once. Thus, our results provide a solid experimental and theoretical base for a quantitative understanding of ultrafast fs-laser-driven magnetoacoustics and tailoring the magnetic-grating-based metasurfaces at the nanoscale.
Sustainable Production
(2023)
Visual programming languages (VPL) let users develop software programs by combining visual program elements, like lists of objects, loops or conditional statements rather than by specifying them textually.
Humanoid robots programming is a very attractive and motivating application domain for students, especially for programming beginners. Humanoid robots are constructed in such a way that they mimic the human body by using actuators that perform like muscles. Typically, a humanoid robot consists of sensors and actuators, i.e. torso, a head, two arms, and two legs, though some humanoid robots may replicate only part of the body, for example, from the waist up. In some cases, humanoid robots are equipped with heads designed to replicate additional human facial features such as eyes. Additional sensors are needed by a robot to gather information about the conditions of the environment to allow the robot to make necessary decisions about its position or certain actions that the situation requires, e.g. an arm movement or an open/close hand action. Other examples for sensor are reflective infrared sensors used to detect objects in proximity.
In this work, we introduce a use-case centered approach based on sensors and actors of a robot and a workflow model to visually describe the sequence of actions including conditional actions or concurrent actions. We provide an in-depth discussion of a new VPL based teaching method for programming humanoid robots based on VPLs. Open research challenges, limits and perspectives for further development of our teaching approach are discussed as well.
Sensors and actuators enable creation of context-aware applications in which applications can discover and take advantage of contextual information, such as user location, nearby people and objects. In this work, we use a general context definition, which can be applied to various devices, e.g., robots and mobile devices. Developing context-based software applications is considered as one of the most challenging application domains due to the sensors and actuators as part of a device. We introduce a new development approach for context-based applications by using use-case descriptions and Visual Programming Languages (VPL). The introduction of web-based VPLs, such as Scratch and Snap, has reinvigorated the usefulness of VPLs. We provide an in-depth discussion of our new VPL based method, a step by step development process to enable development of context-based applications. Two case studies illustrate how to apply our approach to different problem domains: Context-based mobile apps and context-based humanoid robot applications.
The main advantage of mobile context-aware applications is to provide effective and tailored services by considering the environmental context, such as location, time, nearby objects and other data, and adapting their functionality according to the changing situations in the context information without explicit user interaction. The idea behind Location-Based Services (LBS) and Object-Based Services (OBS) is to offer fully-customizable services for user needs according to the location or the objects in a mobile user's vicinity. However, developing mobile context-aware software applications is considered as one of the most challenging application domains due to the built-in sensors as part of a mobile device. Visual Programming Languages (VPL) and hybrid visual programming languages are considered to be innovative approaches to address the inherent complexity of developing programs. The key contribution of our new development approach for location and object-based mobile applications is a use case driven development approach based on use case templates and visual code templates to enable even programming beginners to create context-aware mobile applications. An example of the use of the development approach is presented and open research challenges and perspectives for further development of our approach are formulated.
Due to globalization and the resulting increase in competition on the market, products must be produced more and more cheaply, especially in series production, because buyers expect new variants or even completely new products in ever shorter cycles. Injection molding is the most important production process for manufacturing plastic components in large quantities. However, the conventional production of a mold is extremely time-consuming and costly, which creates a contradiction to the fast pace of the market. Additive tooling is an area of application of additive manufacturing, which in the field of injection molding is preferably used for the prototype production of mold inserts. This allows injection molding tools to be produced faster and more cheaply than through the subtractive manufacturing of metal tools. Material Jetting processes using polymers (MJT-UV/P), also called Polyjet Modeling (PJM), have a great potential for use in additive tooling. Due to the poorer mechanical and thermal properties compared to conventional mold insert materials, e.g. steel or aluminum, the previously used design principles cannot be applied. Accordingly, new design guidelines are necessary, which are developed in this paper. The necessary information is obtained with the help of a systematic literature research. The design guidelines are mapped in a uniform design guide, which is structured according to the design process of injection molds. The guidelines do not only refer to the constructive design of the injection mold or the polymer mold insert, but to the entire design process and describe the four phases of planning, conception, development and realization. Particular attention is paid to the special geometric designs of a polymer mold insert and the thermomechanical properties of the mold insert materials. As a result, design guidelines are available that are adapted to the special requirements of additive tooling of molds inserts made of plastics for injection molding.
Artificial Intelligence (AI) can potentially transform many aspects of modern society in various ways, including automation of tasks, personalization of products and services, diagnosis of diseases and their treatment, transportation, safety, and security in public spaces, etc. Recently, AI technology has been transforming the financial industry, offering new ways to analyse data and automate processes, reduce costs, increase efficiency, and provide more personalized services to customers. However, it also raised important ethical and regulatory questions that need to be addressed by the industry and society as a whole. The aim of the Erasmus+ project Transversal Skills in Applied Artificial Intelligence - TSAAI (KA220-HED - Cooperation Partnerships in higher education) has been to establish a training platform that will incorporate teaching guidelines based on a curriculum covering different areas of application of AI technology. In this work, we will focus on applying AI models in the financial and insurance sectors.
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.
In this paper we present the concept of the "KI-Labor Südbaden" to support regional companies in the use of AI technologies. The approach is based on the "Periodic Table of AI" and is extended with both new dimensions for sustainability, and the impact of AI on the working environment. It is illustrated on the basis of three real-world use cases: 1. The detection of humans with lowresolution infrared (IR) images for collaborative robotics; 2. The use of machine data from specifically designed vehicles; 3. State-of-the-art Large Language Models (LLMs) applied to internal company documents. We explain the use cases, thereby demonstrating how to apply the Periodic Table of AI to structure AI applications.
In this work the nonlinear behavior of layered surface acoustic wave (SAW) resonators is studied with the help of finite element (FE) computations. The full calculations depend strongly on the availability of accurate tensor data. While there are accurate material data for linear computations, the complete sets of higher-order material constants, needed for nonlinear simulations, are still not available for relevant materials. To overcome this problem, scaling factors were used for each available nonlinear tensor. The approach here considers piezoelectricity, dielectricity, electrostriction, and elasticity constants up to the fourth order. These factors act as a phenomenological estimate for incomplete tensor data. Since no set of fourth-order material constants for LiTaO3 is available, an isotropic approximation for the fourth-order elastic constants was applied. As a result, it was found that the fourth-order elastic tensor is dominated by one-fourth order Lamé constant. With the help of the FE model, derived in two different, but equivalent ways, we investigate the nonlinear behavior of a SAW resonator with a layered material stack. The focus was set to third-order nonlinearity. Accordingly, the modeling approach is validated using measurements of third-order effects in test resonators. In addition, the acoustic field distribution is analyzed.
Established robot manufacturers have developed methods to determine and optimize the accuracy of their robots. These methods vary from robot manufacturers to their competitors. Due to the lack of published data, a comparison of robot performance is difficult. The aim of this article is to find methods to evaluate important characteristics of a robot with an accurate and cost-effective setup. A laser triangulation sensor and geometric referenced spheres were used as a base to compare the robot performance.
In this contribution, we present a novel 3D printed multi-material, electromagnetic vibration harvester. The harvester is based on a cantilever design and utilizes an embedded constantan wire within a matrix of polyethylene terephthalate glycol (PETG). A prototype has been manufactured with a combination of a fused filament fabrication (FFF) printer and a robot with a custom-made tool.
In the framework of electro-elasticity theory and the finite element method (FEM), a model is set up for the computation of quantities in surface acoustic wave (SAW) devices accounting for nonlinear effects. These include second-order and third-order intermodulations, second and third harmonic generation and the influence of electro-acoustic nonlinearity on the frequency characteristics of SAW resonators. The model is based on perturbation theory, and requires input material constants, e.g., the elastic moduli up to fourth order for all materials involved. The model is two-dimensional, corresponding to an infinite aperture, but all three Cartesian components of the displacement and electrical fields are accounted for. The first version of the model pertains to an infinite periodic arrangement of electrodes. It is subsequently generalized to systems with a finite number of electrodes. For the latter version, a recursive algorithm is presented which is related to the cascading scheme of Plessky and Koskela and strongly reduces computation time and memory requirements. The model is applied to TC-SAW systems with copper electrodes buried in an oxide film on a LiNbO3 substrate. Results of computations are presented for the electrical current due to third-order intermodulations and the displacement field associated with the second harmonic and second-order intermodulations, generated by monochromatic input tones. The scope of this review is limited to methodological aspects with the goal to enable calculations of nonlinear quantities in SAW devices on inexpensive and easily accessible computing platforms.
This thesis deals with the redesign of manufacturing systems by simulation and optimization. Material flow simulation is a common tool for solving problems in system design. Limitations are the high requirements in time and knowledge to execute simulation studies, evaluate results and solve design problems. New chances arrives with the technologies of industry 4.0 and the digital shadow, providing data for simulation. However, the methods to use production data for the redesign of production systems are not available yet. Purpose of this work is providing the methods to automate simulation from digital shadow, use simulation to optimize and solve problems in system design. Two case studies are used to support the action research approach of this work. The result of this work is a framework for the application of the digital shadow in optimization and problem-solving.
Purpose
This study aims to investigate a systematic approach to the production and use of additively manufactured injection mould inserts in product development (PD) processes. For this purpose, an evaluation of the additive tooling design method (ATDM) is performed.
Design/methodology/approach
The evaluation of the ATDM is conducted within student workshops, where students develop products and validate them using AT-prototypes. The evaluation process includes the analysis of work results as well as the use of questionnaires and participant observation.
Findings
This study shows that the ATDM can be successfully used to assist in producing and using AT mould inserts to produce valid AT prototypes. As a reference for the implementation of AT in industrial PD, extracts from the work of the student project groups and suitable process parameters for prototype production are presented.
Originality/value
This paper presents the application and evaluation of a method to support AT in PD that has not yet been scientifically evaluated.
Study of impact of change in market economics of Biosimilars due to SPC waiver on EU 469/2009
(2023)
This research was conducted to understand and investigate the impact of SPC waiver EU 933/2019 made as an amendment to EU 469/2019. The research was conducted for analysis and extraction of the data to compile the exact number of biological products impacted with the SPC waiver. The highest sale top-5 products were identified according to the expert’s opinion. The sales revenue opportunity valuable to the top-5 products in the top-5 non-EU markets for early exports is investigated. Additionally, a survey was conducted to assess the readiness of the industry for these changes. The information from this study will be very useful to students of the biopharmaceutical market research and to the stakeholders from the biopharmaceutical industry.
Printed circuit boards (PCB) are a foundation of electronical devices in modern society. The fabrication of these boards requires various processes and machines. The utilisation of a robot with multiple tools can shorten the process chain compared to screen printing. In this paper a system is presented, which utilises an industrial six axis robot to manufacture
PCBs. The process flow and conversion process of the Gerber format into robot specific commands is presented. The advantages and challenges applying a robot to print circuits are discussed.
Novel approaches for the design of assistive technology controls propose the usage of eye tracking devices such as for smart wheelchairs and robotic arms. The advantages of artificial feedback, especially vibrotactile feedback, as opposed to their use in prostheses, have not been sufficiently explored. Vibrotactile feedback reduces the cognitive load on the visual and auditory channel. It provides tactile sensation, resulting in better use of assistive technologies. In this study the impact of vibration on the precision and accuracy of a head-worn eye tracking device is investigated. The presented system is suitable for further research in the field of artificial feedback. Vibration was perceivable for all participants, yet it does not produce any significant deviations in precision and accuracy.
In an extensive research project, we have assessed the application of different service models by export credit agencies (ECAs) and export-import banks (EXIMs). We conducted interviews with 35 representatives of ECAs and EXIMs from 27 countries. The question guiding this study is: How do ECAs and EXIMs adopt public service models for supporting exporters? We conducted a holistic multiple case study, investigating if and how these organisations apply public service models developed by Schedler and Guenduez, and which roles of the state are relevant. We find that there is a variety of different service models used by ECAs and EXIMs, and that the service model approaches have great potential to learn from each other and innovate existing services.
The present paper addresses the research question: What recommendations for action and potential adjustments should an online magazine for beauty and fashion implement in order to make affiliate articles in these sections even more appealing to the target group and provide added value for them?
To be able to answer this research question, three hypotheses were defined and tested with using qualitative and quantitative research. The qualitative research consisted of user experience testings, where four affiliate articles in the fields of beauty and fashion were tested with 13 participants. The quantitative research involved collecting, analyzing and evaluating data from the four affiliate articles conducted with the company's real-life target group. Based on these results, recommendations for action were derived, which should not only improve the quality of the content in the future, but also increase the efficiency of the implementation of those articles.
In order to attract new students, German universities must provide quick and easy access to relevant information. A chatbot can help increase the efficiency in academic advising for prospective students. In this study we evaluate the acceptance and effects of chatbots in German student-university communication. We conducted a qualitative UX-Study with the chatbot prototype of Offenburg University of Applied Sciences (HSO), in order to determine which features are particularly relevant and which requirements are made by the users. The results show that acceptance increases if the chatbot offers quick and adequate assistance, furthermore, our participants preferred an informal communication style and valued friendly and helpful personality traits for chatbots.