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arXiv 2024年

作者： Ogunleye, Bayode Zakariyyah, Kudirat Ibilola Ajao, Oluwaseun Olayinka, Olakunle Sharma, Hemlata School of Architecture Technology & Engineering University of Brighton BrightonBN2 4GJ United Kingdom Department of Computing & Mathematics Manchester Metropolitan University ManchesterM1 5GD United Kingdom School of Computer Science The University of Sheffield SheffieldS1 4DP United Kingdom Department of Computing Sheffield Hallam University SheffieldS1 2NU United Kingdom

The use of generative artificial intelligence (GenAI) in academia is a subjective and hotly debated topic. Currently, there are no agreed guidelines towards the usage of GenAI systems in higher education (HE) and, thus, it is still unclear how to make effective use of the technology for teaching and learning practice. This paper provides an overview of the current state of research on GenAI for teaching and learning in HE. To this end, this study conducted a systematic review of relevant studies indexed by Scopus, using the preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines. The search criteria revealed a total of 625 research papers, of which 355 met the final inclusion criteria. The findings from the review showed the current state and the future trends in documents, citations, document sources/authors, keywords, and co-authorship. The research gaps identified suggest that while some authors have looked at understanding the detection of AI-generated text, it may be beneficial to understand how GenAI can be incorporated into supporting the educational curriculum for assessments, teaching, and learning delivery. Furthermore, there is a need for additional interdisciplinary, multidimensional studies in HE through collaboration. This will strengthen the awareness and understanding of students, tutors, and other stakeholders, which will be instrumental in formulating guidelines, frameworks, and policies for GenAI usage. © 2024, CC BY.

关键词： Artificial intelligence

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Frequency Measurement Research with Weight Averaging of Pulse Output Signal of Voltage-to-Frequency Converter

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SSRN 2022年

作者： Dorozhovets, Mykhaylo Pawlowski, Eligiusz Świsulski, Dariusz Department of Metrology and Diagnostic Systems Faculty of Electrical and Computer Engineering Rzeszow University of Technology ul. Wincentego Pola 2A Rzeszów35-959 Poland Department of Information and Measuring Technology National University Lviv Polytechnic Lviv Ukraine Faculty of Electrical Engineering and Computer Science Lublin University of Technology Lublin Poland Faculty of Electrical and Control Engineering Gdańsk University of Technology Gdańsk Poland

The paper presents investigation of the efficiency of weight averaging of a pulse frequency modulated signal. The sampling effects and the interference influence in the input signal of the voltage-to frequency converter on the result of output frequency weight averaging are analyzed. A general form of the averaging result dependence on the used weighting function, signal value, interference level and modulation parameters is derived. In the case of high interferences whose frequencies are unstable or may change over a wide range, the specified level of their suppression, together with the reduction of the sampling effect, can be achieved using weighting functions, such as trigonometric, with an appropriate level of side lobes. The interference suppression dependently on frequency ranges using selected weighing functions are tested using both the simulation and experimental methods. The obtained results show very good convergence with the values calculated from theoretical formulas. © 2022, The Authors. All rights reserved.

关键词： Weighing

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Optimized Deformed Residual Neural Network Accompanied by a Featured Discriminator for Wet and Fine-Grained Fingerprint Sensor Image

SSRN

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SSRN 2024年

作者： Chen, Pin-Hsuan Chiu, Ching-Te Chen, Sung-Che Hsu, Mao-Hsiu Institute of Communications Engineering National Tsing Hua University 101 Section 2 Guangfu Road East Distric Hsinchu300 Taiwan Information Systems and Applications National Tsing Hua University 101 Section 2 Guangfu Road East Distric Hsinchu300 Taiwan Department of Computer Science National Tsing Hua University 101 Section 2 Guangfu Road East Distric Hsinchu300 Taiwan Nation Formosa University Electro-Optical Engineering No. 64 Wenhua Road Yunlin County Huwei Township632 Taiwan

Fingerprint recognition is crucial for device and data security, especially with the widespread use of capacitive sensors in mobile devices. However, denoising wet fingerprints from these sensors poses challenges due to small fingerprint areas, limited features, and significant moisture-induced dark regions. Our "DRB-FD" method combines a Featured Discriminator (FD) and a Deformed Residual Block (DRB) with attention mechanisms, drop-out layers, and pre-activation. In experiments using the Nasic9395 0606 aug dataset, DRB-FD achieved a remarkable 73.1% improvement, with the False Rejection Rate (FRR) decreasing by 25% compared to the baseline PGT-Net. Both FD and DRB significantly contributed, showing improvements of 47.4% (FRR decreased by 16.2%) and 48.9% (FRR decreased by 8.8%), respectively. Besides achieving better FRR results, there is a significant increase in the number of fingerprint points successfully matched after repair by the DRB-FD model. In conclusion, our innovative approach effectively denoises wet fingerprints from capacitive sensors in mobile systems, substantially enhancing the accuracy and reliability of fingerprint recognition systems. This advancement represents a significant step forward in biometric technology, offering promising applications in mobile security and user authentication. © 2024, The Authors. All rights reserved.

关键词： Capacitive sensors

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Splitting algorithms and circuits analysis

arXiv

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arXiv 2022年

作者： Chaffey, Thomas Das, Amritam Sepulchre, Rodolphe University of Cambridge Department of Engineering Trumpington Street CambridgeCB2 1PZ United Kingdom Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm100 44 Sweden

The splitting algorithms of monotone operator theory find zeros of sums of relations. This corresponds to solving series or parallel one-port electrical circuits, or the negative feedback interconnection of two subsystems. One-port circuits with series and parallel interconnections, or block diagrams with multiple forward and return paths, give rise to current-voltage relations consisting of nested sums and inverses. In this extended abstract, we present new splitting algorithms specially suited to these structures, for interconnections of monotone and anti-monotone *** Codes 93C10, 47H05, 47N70 © 2022, CC BY-SA.

关键词： Timing circuits

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从四方到立方:高性能太阳能电池的钙钛矿相结构演变

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science Bulletin 2023年第2期68卷 141-145,M0003页

作者：魏旗梁昊 Yuki Haruta Makhsud Saidaminov 米启兮 Michael Saliba 崔光磊宁志军 School of Physical Science and Technology ShanghaiTech UniversityShanghai 201210China High Performance Computing Department National Supercomputing Center in ShenzhenShenzhen 200441China Department of Chemistry and Department of Electrical&Computer Engineering and Centre for Advanced Materials and Related Technologies(CAMTEC) University of VictoriaVictoria V8P 5C2Canada Institute for Photovoltaics University of StuttgartStuttgart 70569Germany Qingdao Industrial Energy Storage Research Institute Qingdao Institute of Bioenergy and Bioprocess TechnologyChinese Academy of SciencesQingdao 266101China

Crystal structure, which is generally determined by the composition, ionic radius and valence state of constituent elements, plays a significant role in the material’s fundamental properties such as optical, electronic, and mechanical characters. The manipulation of the crystal structure through compositional engineering, and understanding the relationship between crystal structure and properties are essential for the development of materials.

关键词：太阳能电池结构演变钙钛矿相

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Communication and computation O-RAN resource slicing for URLLC services using deep reinforcement learning

arXiv

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arXiv 2022年

作者： Filali, Abderrahime Nour, Boubakr Cherkaoui, Soumaya Kobbane, Abdellatif INTERLAB Research Laboratory Faculty of Engineering Department of Electrical and Computer Science Engineering Université of Sherbrooke SherbrookeQCJ1K 2R1 Canada UM5R ENSIAS BP 713 Rabat Morocco

The evolution of the future beyond-5G/6G networks towards a service-aware network is based on network slicing technology. With network slicing, communication service providers seek to meet all the requirements imposed by the verticals, including ultra-reliable low-latency communication (URLLC) services. In addition, the open radio access network (O-RAN) architecture paves the way for flexible sharing of network resources by introducing more programmability into the RAN. RAN slicing is an essential part of end-to-end network slicing since it ensures efficient sharing of communication and computation resources. However, due to the stringent requirements of URLLC services and the dynamics of the RAN environment, RAN slicing is challenging. In this article, we propose a two-level RAN slicing approach based on the O-RAN architecture to allocate the communication and computation RAN resources among URLLC end-devices. For each RAN slicing level, we model the resource slicing problem as a single-agent Markov decision process and design a deep reinforcement learning algorithm to solve it. Simulation results demonstrate the efficiency of the proposed approach in meeting the desired quality of service requirements. © 2022, CC BY.

关键词： Deep learning

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Predicting Cognitive Function Status in Esrd Patients at the Functional Subnetwork Scale

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SSRN 2023年

作者： Lu, Yu Liu, Tongqiang Shi, Haifeng Jiao, Zhuqing School of Microelectronics and Control Engineering Changzhou University Changzhou213164 China Department of Nephrology The Affiliated Changzhou No.2 People’s Hospital of Nanjing Medical University Changzhou213003 China Department of Radiology The Affiliated Changzhou No.2 People’s Hospital of Nanjing Medical University Changzhou213003 China School of Computer Science and Artificial Intelligence Changzhou University Changzhou213164 China

Background: The topological attribute parameters of the global network are taken as the characteristics from the perspective of the whole. It is constrained to comprehend the subtleties and variances of brain functional networks, which fell short of thoroughly examining the complex relationships and information transfer mechanisms among various regions. Methods: To address this issue, we proposed a novel method for predicting cognitive function status in the patients with end-stage renal disease (ESRD) at the functional subnetwork scale (CFSFSS). The nodes from different network indicators in the brain functional network were combined to form the functional subnetworks. The area under the curve (AUC) of the topological attribute parameters of the functional subnetworks were extracted as features, which were selected by the minimal Redundancy Maximum Relevance (mRMR). The parameter combinations with improved fitness were searched by the enhanced whale optimization algorithm (E-WOA), so as to optimize the support vector regression (SVR) and solve the global optimization problem of the predictive model. Results: CFSFSS achieved superior predictive performance compared with other existing methods. With mRMR and E-WOA, it exhibited enhanced overall efficiency and technical advancements compared to other methods. Conclusion: The proposed method not only effectively helps to more accurately predict the cognitive function status, but also provides more references for clinical decision-making and intervention of cognitive impairment in ESRD patients. © 2023, The Authors. All rights reserved.

关键词： Forecasting

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Streaming quantum state purification

arXiv

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arXiv 2023年

作者： Childs, Andrew M. Fu, Honghao Leung, Debbie Li, Zhi Ozols, Maris Vyas, Vedang Institute for Quantum Computing University of Waterloo WaterlooONN2L 3G1 Canada Department of Computer Science Institute for Advanced Computer Studies Joint Center for Quantum Information and Computer Science University of Maryland College ParkMD20742 United States Massachusetts Institute of Technology 77 Massachusetts Ave. CambridgeMA02139 United States Perimeter Institute for Theoretical Physics 31 Caroline St. N. WaterlooONN2L 2Y5 Canada QuSoft University of Amsterdam Science Park 123 Amsterdam1098 XG Netherlands Concordia Institute of Information Systems Engineering Concordia University 1455 Blvd. De Maisonneuve Ouest MontrealQCH3G 1M8 Canada

Quantum state purification is the task of recovering a nearly pure copy of an unknown pure quantum state using multiple noisy copies of the state. This basic task has applications to quantum communication over noisy channels and quantum computation with imperfect devices, but has primarily been studied previously for the case of qubits. We derive an efficient purification procedure based on the swap test for qudits of any dimension, starting with any initial error parameter. Treating the initial error parameter and the dimension as constants, we show that our procedure has sample complexity asymptotically optimal in the final error parameter. Our protocol has a simple recursive structure that can be applied when the states are provided one at a time in a streaming fashion, requiring only a small quantum memory to implement. © 2023, CC BY.

关键词： Quantum communication

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Proximity Based Automatic Data Annotation for Autonomous Driving

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IEEE/CAA Journal of Automatica Sinica 2020年第2期7卷 395-404页

作者： Chen Sun Jean M.Uwabeza Vianney Ying Li Long Chen Li Li Fei-Yue Wang Amir Khajepour Dongpu Cao Department of Mechanical and Mechatronics Engineering University of WaterlooWaterloo ON N2L3G1Canada Department of Geography and Environmental Management University of WaterlooWaterloo ON N2L3G1Canada School of Data and Computer Science Sun Yat-sen UniversityZhuhai 519082Chinaand also with Waytous Inc.Qingdao 266109China

The recent development in autonomous driving involves high-level computer vision and detailed road scene ***,most autonomous vehicles employ expensive high quality sensor-set such as light detection and ranging(LIDAR)and HD maps with high level *** this paper,we propose a scalable and affordable data collection and annotation framework image-to-map annotation proximity(I2MAP),for affordance learning in autonomous driving *** provide a new driving dataset using our proposed framework for driving scene affordance learning by calibrating the data samples with available tags from online database such as open street map(OSM).Our benchmark consists of 40000 images with more than40 affordance labels under various day time and weather even with very challenging heavy *** implemented sample advanced driver-assistance systems(ADAS)functions by training our data with neural networks(NN)and cross-validate the results on benchmarks like KITTI and BDD100K,which indicate the effectiveness of our framework and training models.

关键词： Affordance learning autonomous vehicles data synchronization scene understanding

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WikiLink: an encyclopedia-based semantic network for design innovation

arXiv

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arXiv 2022年

作者： Zuo, Haoyu Jing, Qianzhi Song, Tianqi Liu, Huiting Sun, Lingyun Childs, Peter Chen, Liuqing Department of Computer Science and Technology Zhejiang University Hangzhou310030 China Dyson School of Design Engineering Imperial College London Exhibition Rd South KensingtonSW7 2AZ United Kingdom

Data-driven design and innovation is a process to reuse and provide valuable and useful information. However, existing semantic networks for design innovation is built on data source restricted to technological and scientific information. Besides, existing studies build the edges of a semantic network only on either statistical or semantic relationships, which is less likely to make full use of the benefits from both types of relationships and discover implicit knowledge for design innovation. Therefore, we constructed WikiLink, a semantic network based on Wikipedia. Combined weight which fuses both the statistic and semantic weights between concepts is introduced in WikiLink, and four algorithms are developed for inspiring new ideas. Evaluation experiments are undertaken and results show that the network is characterised by high coverage of terms, relationships and disciplines, which proves the network’s effectiveness and usefulness. Then a demonstration and case study results indicate that WikiLink can serve as an idea generation tool for innovation in conceptual design. The source code of WikiLink and the backend data are provided open-source for more users to explore and build on. © 2022, CC BY.

关键词： Conceptual design

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