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Seismic data has often missing traces due to technical acquisition or economical constraints. A compete dataset is crucial in several processing and inversion techniques. Deep learning algorithms, based on convolutional neural networks (CNNs), have shown alternative solutions that overcome limitation of traditional interpolation methods e.g. data regularity, linearity assumption, etc. There are two different paradigms of CNN methods for seismic interpolation. The first one, so-called deep prior interpolation (DPI), trains a CNN to map random noise to a complete seismic image using only the decimated image itself. The second one, referred as standard deep learning method, trains a CNN to map a decimated seismic image into a complete one using a dataset of complete and artificially decimated images. Within this research, we systematically compare the performance of both methods for different quantities of regular and irregular missing traces using 4 datasets. We evaluate the results of both methods using 5 well-known metrics. We found that DPI method performs better than the standard method if the percentage of missing traces is low (10%) and otherwise if the level of decimation is high (50%).
Radio frequency identification (RFID) antennas are popular for high frequency (HF) RFID, energy transfer and near field communication (NFC) applications. Particularly for wireless measurement systems the RFID/NFC technology is a good option to implement a wireless communication interface. In this context, the design of corresponding reader and transmitter antennas plays a major role for achieving suitable transmission quality. This work proves the feasibility of the rapid prototyping of a RFID/NFC antenna, which is used for the wireless communication and energy harvesting at the required frequency of 13.56 MHz. A novel and low-cost direct ink writing (DIW) technology utilizing highly viscous silver nanoparticle ink is used for this process. This paper describes the development and analysis of low-cost printed flexible RFID/NFC antennas on cost-effective substrates for a microelectronic vital parameter measurement system. Furthermore, we compare the measured technical parameters with existing copper-based counterparts on a FR4 substrate.
The Raman spectra from the chemical compounds toluene and cyclohexane obtained using a Fourier Transform (FT)-Raman spectrometer prototype have been contrasted with the Raman spectra of these same materials collected with two different commercial FT-Raman devices. The FT-Raman spectrometer consist of a Michelson interferometer, a self-designed photon counter and a reference photo-detector. The evaluation methodology of the spectral information, contrary to the commercial devices that commonly use the zero-crossing method, is carried out by re-sampling the Raman scattering and by accurately extracting the optical path information of the Michelson interferometer. The FTRaman arrangement has been built using conventional parts without disregarding the spectral frequency precision that usually such a FTRaman instruments deliver. No additional complex hardware components or costly software modules have been included in this FT-Raman device. The main Raman lines from the spectra obtained with the three FT-Raman devices have been compared with the Raman lines from the standard Raman spectra of these two materials. The values obtained using the FT-Raman spectrometer prototype have shown a frequency accuracy comparable to that obtained with the commercial devices without facing the need for a large investment. Although the proposed FT-Raman prototype cannot be directly compared to the last generation of FT-Raman spectrometers from the commercial manufacturers, such a device could give an opportunity to users that require high frequency precision in their spectral analysis and are provided with rather scarce resources.
The need for the logistics sector to timely respond to the increasing requirements of a globalised and digitalised world relies greatly on the com- petences and skills of its labour force. It becomes therefore essential to reinforce the cooperation between universities and business partners in the logistics and supply chain management fields across the European region and to build a logistics knowledge cluster supported by a communication and collaboration platform to foster continuous learning, skill acquisition and experience sharing anytime anywhere. In this paper we focus on designing the conceptual and technical framework for a communication and collaboration platform with the aim to establish the communication pipelines between the partner institutions, facilitating user interactions and exchange, leading to the creation of new knowledge and innovation in the logistics field. This framework is based on the requirements of the three main stakeholders: students, lecturers and companies, and consists of four functional areas defined according to the platform opera- tional requirements. A working prototype of the platform was developed using the Moodle learning management system and its core tools to determine its applicability and possible enhancement requirements. In the next stages of the project some additional tools like a knowledge base and the integration of the partners’ learning management systems to form the logistics knowledge cluster will be implemented.
With the increasing share of renewable energies and the nuclear phase-out, the energy transition is accelerating. From the perspective of building technology, there is great potential to support this transition given its large share in total energy consumption and the increasing number of flexible and controllable components and storages. However, a question often asked at the plant level is: "How do we use this flexibility to support the regional grid?". In this work, a grid-supportive controller of a real-world building energy plant was developed using mathematical optimisation methods and its technical feasibility was demonstrated. The results could convince actors from the energy industry and academia about the practicality of these methods and offer tools for their implementation.
The monitoring of industrial environments ensures that highly automated processes run without interruption. However, even if the industrial machines themselves are monitored, the communication lines are currently not continuously monitored in todays installations. They are checked usually only during maintenance intervals or in case of error. In addition, the cables or connected machines usually have to be removed from the system for the duration of the test. To overcome these drawbacks, we have developed and implemented a cost-efficient and continuous signal monitoring of Ethernet-based industrial bus systems. Several methods have been developed to assess the quality of the cable. These methods can be classified to either passive or active. Active methods are not suitable if interruption of the communication is undesired. Passive methods, on the other hand, require oversampling, which calls for expensive hardware. In this paper, a novel passive method combined with undersampling targeting cost-efficient hardware is proposed.
A crack opening stress equation for in-phase and out-of-phase thermomechanical fatigue loading
(2016)
In this paper, a crack opening stress equation for in-phase and out-of-phase thermomechanical fatigue (TMF) loading is proposed. The equation is derived from systematic calculations of the crack opening stress with a temperature dependent strip yield model for both plane stress and plane strain, different load ratios and different ratios of the temperature dependent yield stress in compression and tension. Using a load ratio scaled by the ratio of the yield stress in compression and tension, the equation accounts for the effect of the temperature dependent yield stress and the constraint on the crack opening stress. Based on the scaling relation established in this paper, Newman's crack opening stress equation for isothermal loading is enabled to predict the crack opening stress under TMF loading.
This paper describes the use of the single-linkage hierarchical clustering method in outlier detection for manufactured metal work pieces. The main goal of the study is to group defects that occur 5 mm into a work piece from the edge, i.e., the border of the metal work piece. The goal is to remove defects outside the area of interest as outliers. According to the assumptions made for the performance criteria, the single-linkage method has achieved better results compared to other agglomeration methods.
Air traffic is by nature crossing borders and organizations. The supporting infrastructure represents a federative distributed system of independent Air Traffic Service Units, typically each with its own proprietary system architecture. Interaction between the centers is taking place over dedicated protocols, often organized as a mesh of 1:1 bilateral data exchanges.
This contribution gives an overview of the ongoing efforts to standardize this data exchange. At the core is a data-centric view, using a shared virtual Flight Object as the IT counterpart of a real flight. It permits a uniform way to access and update a flight’s static and dynamic attributes. A middleware is presented that implements this abstraction and maps it onto a physical level, employing DDS (Data Distribution Service) technology for the 1:N dissemination of flight data.