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32nd IEEE International Symposium on Industrial Electronics, ISIE 2023

作者： Wasinski, Frank Bonath, Werner Ricklefs, Ubbo Borcsok, Josef Schwarz, Michael Hahn, Eike University of Applied Sciences THM Dept. of Electrical Engineering and Information Technology Giessen Germany Institute for Computer Architecture and System Programming University of Kassel ICAS Kassel Germany

ISBN: (纸本)9798350399714

Optical speed sensors based on the spatial frequency filter method are a proven technology that offer high measurement accuracy over a wide speed range. Newly developed variants also enable measurements at very low speeds and increase the robustness of the method [1]. This makes the sensor very suitable for use in the area of functional safety. A measurement chain up to safety integrity level 3 (SIL3) should be feasible via a combination with a safety system on a chip (SoC) for evaluating the measurement data and an extension of the sensor module to include safety-related elements [2], [3]. By integrating the sensor at IC level, a compact overall solution is to be made possible. After the first successful tests with the safety SoC, further examinations of the measuring method with regard to functional safety are now necessary. © 2023 IEEE.

关键词： System-on-chip

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Integration of weighted majority voting in machine learning algorithms to enhance pine tree crown mapping on UAV imagery

Integration of weighted majority voting in machine learning ...

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2024 Symposium on Beyond the Canopy: Technologies and Applications of Remote Sensing

作者： Hosingholizade, Ali Erfanifard, Yousef Alavipanah, Seyed Kazem Pirasteh, Saied Garcia Millan, Virginia Dept. of Remote Sensing and GIS Faculty of Geography University of Tehran Tehran Iran Institute of Artificial Intelligence School of Mechanical and Electrical Engineering Shaoxing University China Department of Geotechnics and Geomatics Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai602105 India Dept. of Computer Science and Programming Languages School of Computer Science and Enginering University of Málaga Málaga Spain

The shape and area of the crown of each tree are among the most influential parameters for identifying and controlling the processes of photosynthesis, respiration, transpiration and its management. In such a way that various physiographic functions, such as carbon dioxide absorption, light energy absorption, oxygen release and transpiration, which are vital for the growth and development of the tree, are done in the crown. In this research, the RGB image of the UAV with a spatial resolution of 2 cm was resampled to three pixel sizes of 10, 30 and 50 cm. Then, each image was classified separately by SVM, ANN and MLC algorithms, which are all part of Ensemble. In the next step, each of the obtained crowns was compared with the digitization of the same crown, and based on the area of the crown obtained from each classification and normalization method, the weight was obtained specifically for the same crown. Finally, by using the weighted majority voting method, classifications were fusioned at the decision level. The results showed that the ANN method gives better results in all pixel sizes compared to MLC and SVM. Also, the combination of different classification methods with the weighted majority voting method based on the weight assigned to the same crown based on each classification method has significantly increased the classification accuracy of the tree crown in all the sizes of the analyzed pixels. © Author(s) 2024.

关键词： Pixels

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Effectiveness of Performance Visualizations for Declarative Model Transformations

Effectiveness of Performance Visualizations for Declarative ...

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IEEE International Workshop on Visualizing Software for Understanding and Analysis (VISSOFT)

作者： Raffaela Groner Matthias Tichy Dept. of Computer Science and Engineering Chalmers | University of Gothenburg Gothenburg Sweden Institute of Software Engineering and Programming Languages Ulm University Ulm Germany

ISBN: (数字)9798331528485

ISBN: (纸本)9798331528492

Several profilers for general-purpose languages like Java offer visualizations to support users in understanding the execution of a program and identifying the causes of a performance issue. Unfortunately, these performance visualizations are difficult to reuse in profilers for declarative model transformations since they cannot display transformation-specific information. For example, a profiler for a declarative model transformation language must provide information on the traversal of the input model since it impacts the performance but is hidden from the developer. Moreover, the respective visualization must scale for input models that consist of several thousand model elements. Hence, we developed performance visualizations for the declarative model transformation language Henshin that provide insights into the transformation execution. Subsequently, we performed a mixed methods study with 18 Henshin novices to evaluate the effectiveness of our visualizations. In our study, the participants tried to improve the execution performance of four transformations by performing a root cause analysis using our visualizations. The results of our study show that depending on the task, between 16 and 18 participants understood the execution of a transformation correctly based on our visualizations. Moreover, between 12 and 18 participants proposed effective optimizations using our visualizations.

关键词： Visualization Root cause analysis Java Color Software Encoding Data mining Optimization

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Ottoman OCR: Printed naskh font

Ottoman OCR: Printed naskh font

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2021 International Conference on INnovations in Intelligent SysTems and Applications, INISTA 2021

作者： Dolek, Ishak Kurt, Atakan Sakarya Applied Sciences University Computer Programming Dept. Sakarya Turkey Istanbul University-Cerrahpasa Computer Engineering Dept. Istanbul Turkey

ISBN: (纸本)9781665436038

We present an OCR tool developed for printed Ottoman documents in naksh font as part of a project named End-to-End Conversion of Ottoman Documents to Modern Turkish This tool uses a deep learning model trained with a data set containing original and synthetic documents. We conducted an experimental comparison of this tool named *** with Tesseract Arabic, Tesseract Persian, Abby Finereader, Miletos and Google Docs OCR tools (or models) using a test data set comprised of 21 pages of original documents. With 88, 64% raw, 95, 92% normalized and 97, 18% joined character recognition accuracy rates, *** outperformed the other tools with a marked difference. *** also achieved 58% word recognition accuracy which is the only rate over 50% among the OCR tools compared. We shared the test data set, ground truth, OCR outputs and the test program written in Python using difflib at ***/test for independent verification. © 2021 IEEE.

关键词： Software testing

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Study of an OPTO-ASIC for a Functionally Safe Speed Sensor Using the Spatial Frequency Filter Method

Study of an OPTO-ASIC for a Functionally Safe Speed Sensor U...

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IEEE Design and Diagnostics of Electronic Circuits and Systems (DDECS)

作者： Frank Wasinski Werner Bonath Ubbo Ricklefs Michael Schwarz Josef Börcsök Dept. of Electrical Engineering and Information Technology THM University of Applied Sciences Giessen Germany ICAS Institute for Computer Architecture and System Programming University of Kassel Kassel Germany

ISBN: (数字)9798331528010

ISBN: (纸本)9798331528027

For decades, speed sensors based on the spatial frequency filter method have successfully proven themselves in a wide range of applications. This makes the sensor concept particularly suitable for the area of functional safety. New filter variants extend the previous measuring range to very low speeds up to standstill detection. By combining the sensor with a safety system on chip for recording and analysing measured values, a functionally safe measuring chain can be established. In order to demonstrate the variability and performance of the new filters, an optical application-specific integrated circuit was designed, which forms the basis for further extensive tests. The core components are a large number of freely configurable photodiode channels, which were realised via a redundant structure, as well as two different transimpedance amplifier concepts. In the further course of the project, the ASIC will be analysed with regard to its desired performance parameters and its robustness.

关键词： Optical filters Semiconductor device measurement Optical design Stimulated emission Safety Topology System-on-chip Optical sensors Optical amplifiers Velocity measurement

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Workload Balancing Model for Heterogeneous IoT Nodes Architectures

Workload Balancing Model for Heterogeneous IoT Nodes Archite...

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Electrical engineering and Automatic Control (ICEEAC), International Conference on

作者： Mustafa Kh Aswad Fozia Al-Badree Beetro Ayad Ali Keshlaf Sintific commtiee Research Dept. Libyan Center for Electronic Systems Programming and Aviation Research Tripoli Libya Faculty Of Engineering University of Zawia Zawia Libya Computer Engineering and IT Dept. Faculty of Engneering Sabrahta Univeristy Sabrahta Libya

ISBN: (数字)9798350349740

ISBN: (纸本)9798350349757

Heterogeneous IoT architectures are evolving rapidly and different challenged are faced with the traditional IoT architectures including the performance time of real-time IoT application. Parallel computing programming technique could enhance the performance and efficiency for distributed systems and multicore processors as well as the IoT systems. However, parallel computing, presents certain difficulties and constraints, including synchronization, communication, security concerns, and load balancing. In this regard, a novel IoT workload balancing model for heterogeneous IoT architectures is presented in this paper. This model is intended to reduce the execution time of large systems by redistributing part of their functions to other involved IoT nodes. An experiment has been conducted to evaluate the actual real load for each IoT node and tried to rebalance the load using the proposed model. The results were encouraging as the performance time was reduced by about one third on two cores.

关键词： Program processors Computational modeling computer architecture Parallel processing programming Real-time systems Internet of Things

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Speaker's Emotions Recognition Module Based on the GoogleLeNet Neural Network

Speaker's Emotions Recognition Module Based on the GoogleLeN...

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2022 International Conference on Smart Information Systems and Technologies, SIST 2022

作者： Tereikovskyi, Ihor Tereikovska, Liudmyla Kryvoruchko, Olena Tereikovskyi, Oleh Tyshchenko, Dmytro Franchuk, Tamara National Technical University Of Ukraine Igor Sikorsky Kyiv Polytechnic Institute Dept. Of System Programming And Specialized Computer Systems Kyiv Ukraine Kyiv National University Of Construction And Architecture Dept. Of Information Technology For Design And Applied Mathematics Kyiv Ukraine Kyiv National University Of Trade And Economics Dept. Of Software Engineering And Cyber Security Kyiv Ukraine National Technical University Of Ukraine Igor Sikorsky Kyiv Polytechnic Institute Dept. Of Department Of Computer Engineering Kyiv Ukraine

ISBN: (数字)9781665467902

ISBN: (纸本)9781665467902

The article is devoted to the development of means for recognition of the emotions of the speaker, based on the neural network analysis of fixed fragments of the voice signal. The possibility of improving recognition tools through the use of a convolutional neural network of the GoogLeNet type is shown. The expediency of training the network on the examples of the TESS database is determined. A procedure for representing a voice signal in the form of a square grayscale image has been developed. Based on the use of the specified database, the modification of the GoogLeNet network was carried out. The architecture and software implementation of the recognition module have been developed. With the help of computer experiments, it has been established that after 150 epochs of training on a fairly limited training sample, the modified GoogLeNet makes it possible to achieve an accuracy of recognition of the speaker's emotions of approximately 0.97 on test examples. The obtained accuracy is comparable to the accuracy of the best modern systems of this purpose and confirms the promise of using neural network models like GoogLeNet for emotion recognition based on voice signal analysis. The need for further research aimed at reducing the resource intensity of the neural network model is shown. © 2022 IEEE.

关键词： Emotion Recognition

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Emergent Atomic Environments in Twisted Bilayer Graphene and Their Use in the Prediction of the Vibrational Properties

arXiv

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arXiv 2023年

作者： Ickecan, Dilara Okyayli, Yunus Emre Bleda, Erdi Ata Erbahar, Dogan Marmara University Dept. of Physics Ziverbey Istanbul34722 Turkey Istanbul Ticaret University Dept. of Computer Programming Istanbul34840 Turkey Dogus University Dept. of Mechanical Engineering Erbahar Researcher Lab Umraniye Istanbul34775 Turkey Dogus University Faculty of Engineering Dept. of Mechanical Engineering Umraniye Istanbul34775 Turkey

While Bernal stacked bilayer graphene bears two distinct atom types in its lattice, there exists no analytical framework addressing the number of atomic environments that emerge in twisted bilayer graphene superlattices. Here, we computationally analyze 140 different twisted bilayer superlattices using descriptor functions to study the emergent local environments. Our study reveals that the number of atoms with unique local environments depend on the superlattice size linearly manifesting itself on two distinct lines in accordance with the respective space groups. We then introduce the use of local environments in the investigation of vibrational properties. Local phonon density of states of the atoms with unique local environments are calculated by molecular dynamics simulations and are used to train a machine learning model. This model is used to predict the phonon density of states of twisted bilayer structures. Performance of the trained model is cross validated and discussed thoroughly via different selection of training and test sets. It is shown that the model proves effective in predicting the vibrational properties of any given twisted bilayer structure. Since the generic method presented reaches far beyond twisted bilayer graphene the possible applications ranging from non-periodic structures to strain induced moiré superlattices are also discussed. Copyright © 2023, The Authors. All rights reserved.

关键词： Superlattices

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Concept of an Optical Distance and Speed Sensor Using Novel Offsetless Spatial Frequency Filters in the Area of Functional Safety

Concept of an Optical Distance and Speed Sensor Using Novel ...

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IEEE International Symposium on Industrial Electronics (ISIE)

作者： Frank Wasinski Werner Bonath Ubbo Ricklefs Josef Börcsök Michael Schwarz Eike Hahn Dept. of Electrical Engineering and Information Technology THM University of Applied Sciences Giessen Germany ICAS Institute for Computer Architecture and System Programming University of Kassel Kassel Germany

关键词：

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Analyzing the impact of machine learning and artificial intelligence and its effect on management of lung cancer detection in covid-19 pandemic

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Materials Today: Proceedings 2022年 56卷 2213-2216页

作者： Boddu, Raja Sarath Kumar Karmakar, Partha Bhaumik, Ankan Nassa, Vinay Kumar Vandana Bhattacharya, Sumanta Department of CSE Lenora College of Engineering Andhra Pradesh Rampachodavaram India Government of West Bengal Bikash Bhawan Salt Lake W.B. Kolkata India Dept. of Applied Mathematics With Oceanology and Computer Programming Vidyasagar University Midnapore India Department of Computer Science Engineering South Point Group of Institutions Sonepat Haryana India Department of Mathematics Dasmesh Khalsa College Zirakpur India Department of Science and Technology and Biotechnology MAKAUT India

Cancer victims, particularly those with lung cancer, are more susceptible and at higher danger of COVID-19 and associated consequences as a result of their compromised immune systems, which makes them particularly sensitive. Because of a variety of circumstances, cancer patients' diagnosis, treatment, and aftercare are very complicated and time-consuming during an epidemic. In such circumstances, advances in artificial intelligence (AI) and machine learning algorithms (ML) offer the capacity to boost cancer sufferer diagnosis, therapy, and care via the use of cutting technologies. For example, using clinical and imaging data combined with machine learning methods, the researchers may be able to distinguish among lung alterations induced by corona virus and those produced by immunotherapy and radiation. During this epidemic, artificial intelligence (AI) may be utilized to guarantee that the appropriate individuals are recruited in cancer clinical trials more quickly and effectively than in the past, which was done in a conventional and complicated manner. In order to better care for cancer patients and find novel and more effective therapies, It is critical that we move beyond traditional research methods and use artificial intelligence (AI) and machine learning to update our research (ML). Artificial intelligence (AI) and machine learning (ML) are being utilised to help with several aspects of the COVID-19 epidemic, such as epidemiology, molecular research and medication development, medical diagnosis and treatment, and socioeconomics. The use of artificial intelligence (AI) and machine learning (ML) in the diagnosis and treatment of COVID-19 patients is also being investigated. The combination of artificial intelligence and machine learning in COVID-19 may help to identify positive patients more quickly. In order to understand the dynamics of an epidemic that is relevant to artificial intelligence, when used in different patient groups, AI-based algorithms can quic

关键词： COVID-19

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