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29th Working Group Reports on Innovation and technology in computer Science Education, ITiCSE WGR 2024

作者： Hooshangi, Sara Shakil, Asma Dasgupta, Subhasish Davis, Karen C.C. Farghally, Mohammed Fitzpatrick, KellyAnn Gutica, Mirela Hardt, Ryan Riddle, Steve Seyam, Mohammed Department of Computer Science Virginia Tech BlacksburgVA United States School of Computer Science University of Auckland Auckland New Zealand Info Systems and Tech Mgmt Dept George Washington University WashingtonDC United States Computer Science and Software Engineering Dept. Miami University OxfordOH United States School of Computing Instruction Georgia Institute of Technology AtlantaGA United States School of Computing & Academic Studies British Columbia Institute of Technology BurnabyBC Canada Computer & Information Science University of St. Thomas Saint PaulVA United States School of Computing Newcastle University Newcastle upon Tyne United Kingdom

ISBN: (纸本)9798400712081

Team-based capstone courses are integral to many undergraduate and postgraduate degree programs in the computing field. They are designed to help students gain hands-on experience and practice professional skills such as communication, teamwork, and self-reflection as they transition into the real world. Prior research on capstone courses has focused primarily on the experiences of students. The perspectives of instructors who teach capstone courses have not been explored comprehensively. However, an instructor's experience, motivation, and expectancy can have a significant impact on the quality of a capstone course. In this working group, we used a mixed methods approach to understand the experiences of capstone instructors. Issues such as class size, industry partnerships, managing student conflicts, and factors influencing instructor motivation were examined using a quantitative survey and semi-structured interviews with capstone teaching staff from multiple institutions across different continents. Our findings show that there are more similarities than differences across various capstone course structures. Similarities include team size, team formation methodologies, duration of the capstone course, and project sourcing. Differences in capstone courses include class sizes and institutional support. Some instructors felt that capstone courses require more time and effort than regular lecture-based courses. These instructors cited that the additional time and effort is related to class size and liaising with external stakeholders, including industry partners. Some instructors felt that their contributions were not recognized enough by the leadership at their institutions. Others acknowledged institutional support and the value that the capstone brought to their department. Overall, we found that capstone instructors were highly intrinsically motivated and enjoyed teaching the capstone course. Most of them agree that the course contributes to their professional de

关键词： Students

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Improved RC6 Block Cipher Based on Data Dependent Rotations

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computers, Materials & Continua 2022年第1期70卷 1921-1934页

作者： Osama S.Faragallah Ibrahim F.Elashry Ahmed AlGhamdi Walid El-Shafai S.El-Rabaie Fathi E.Abd El-Samie Hala S.El-sayed Mohamed A.Elaskily Department of Information Technology College of Computers and Information TechnologyTaif UniversityP.O.Box 11099Taif21944Saudi Arabia Department of Electrical Communications Faculty of EngineeringKafrelsheikh UniversityKafrelsheikhEgypt Department of Computer Engineering College of Computers and Information TechnologyTaif UniversityP.O.Box 11099Taif21944Saudi Arabia Department of Electronics and Electrical Communications Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Department of Electrical Engineering Faculty of EngineeringMenoufia UniversityShebin El-Kom32511Egypt Department of Informatics Electronic Research Institute(ERI)CairoEgypt

This paper introduces an Improved RC6(IRC6)cipher for data encryption based on data-dependent *** proposed scheme is designed with the potential of meeting the needs of the Advanced Encryption Standard(AES).Four parameters are used to characterize the proposed *** parameters are the size of the word(w)in bits,the number of rounds(r),the length of the secret key(b)in bytes,and the size of the block(L)in *** main feature of IRC6 is the variable number of working registers instead of just four registers as in RC6,resulting in a variable block size for plaintext and *** IRC6 cipher is designed to improve the robustness against attacks by increasing the diffusion for each round and providing greater security with fewer *** effectiveness of the proposed IRC6 scheme is verified against theoretical *** proposed IRC6 scheme depends on full diffusion and confusion mechanisms regardless of the utilized block *** proposed IRC6 scheme saves 70%of the encryption time and 64%of the decryption time of *** simulation results prove that the IRC6 achieves a better encryption/decryption time compared to the ***,the proposed IRC6 is anticipated to fulfill the market needs and system security requirements.

关键词： Cryptography block cipher RC6,IRC6,AES

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Encrypted Finite-Horizon Energy-to-Peak State Estimation for Time-Varying Systems Under Eavesdropping Attacks: Tackling Secrecy Capacity

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IEEE/CAA Journal of Automatica Sinica 2023年第4期10卷 985-996页

作者： Lei Zou Zidong Wang Bo Shen Hongli Dong Guoping Lu College of Information Science and Technology Donghua UniversityShanghai 201620 Engineering Research Center of Digitalized Textile and Fashion Technology Ministry of EducationShanghai 201620China College of Electrical Engineering and Automation Shandong University of Science and TechnologyQingdao 266590China Department of Computer Science Brunel University LondonUxbridgeMiddlesex UB83PHUK Intelligence Energy Research Institute Northeast Petroleum UniversityDaqing 163318 Heilongjiang Provincial Key Laboratory of Networking and Intelligent Control Northeast Petroleum UniversityDaqing 163318 Sanya Offshore Oil&Gas Research Institute Northeast Petroleum UniversitySanya 572024China School of Electrical Engineering Nantong UniversityNantong 226019China

This paper is concerned with the problem of finitehorizon energy-to-peak state estimation for a class of networked linear time-varying *** to the inherent vulnerability of network-based communication,the measurement signals transmitted over a communication network might be intercepted by potential *** avoid information leakage,by resorting to an artificial-noise-assisted method,we develop a novel encryption-decryption scheme to ensure that the transmitted signal is composed of the raw measurement and an artificial-noise term.A special evaluation index named secrecy capacity is employed to assess the information security of signal transmissions under the developed encryption-decryption *** purpose of the addressed problem is to design an encryptiondecryption scheme and a state estimator such that:1)the desired secrecy capacity is ensured;and 2)the required finite-horizon–l_(2)-l_(∞)performance is *** conditions are established on the existence of the encryption-decryption mechanism and the finite-horizon state ***,simulation results are proposed to show the effectiveness of our proposed encryption-decryption-based state estimation scheme.

关键词： Artificial-noise-assisted technique eavesdropping encryption-decryption scheme energy-to-peak state estimation finitehorizon state estimation

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Image Captioning with Reinforcement Learning 2

Image Captioning with Reinforcement Learning

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2nd IEEE International Conference on computer Vision and Machine Intelligence, CVMI 2023

作者： Verma, Anand Agarwal, Saurabh Arya, K.V. Petrlik, Ivan Esparza, Roberto Rodriguez, Ciro ABV-IIITM Gwalior Department of Information Technology Madhya Pradesh 474015 India ABV-Indian Institute of Information Technology and Management Multimedia and Information Security Research Group Department of Computer Science and Engineering Gwalior474015 India National University Federico Villarreal Faculty of Industrial and Systems Engineering Lima Peru National University Mayor de San Marcos Faculty of Systems Engineering and Informatics Peru

ISBN: (纸本)9798350305142

Image captioning involves generating a natural language description that accurately represents the content and context of an image. To achieve this, image captioning utilises various machine learning techniques and fields, such as computer vision and natural language processing. In the field of image captioning, a lot of advances have been made with encoder-decoder models and reinforcement learning algorithms. However, there are still problems of imbalance between testing and training, as reinforcement learning only handles single comparator metrics such as CIDEr, SPICE, and BLEU and could not perform better in multiple metrics at once. Which is why a lack of diversity can be seen in generated captions. This idea proposes a general technique for collaborative updating that can bridge the gap between evaluation measures and test metrics to produce captions that are more human-like. To increase the precision of image captions, the approach involves using a compiled reward system that considers multiple evaluation metrics to compare the generated sentence with the provided sentences. We will evaluate the model's performance and the reward updating process on standard datasets like MS COCO. © 2023 IEEE.

关键词： Reinforcement learning

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Design of 12-Lead Electrocardiogram Smart Clothing Based on Capacitive Sensing Technique

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IEEE Sensors Journal 2024年第10期24卷 16826-16835页

作者： Chang, Wei-Ting Lin, Bor-Shing Tsai, Wei-Lun Chen, Heng-Yin Liu, Chengyu Lin, Bor-Shyh Chi Mei Medical Center The Department of Cardiology Tainan71004 Taiwan National Taipei University Department of Computer Science and Information Engineering New Taipei City237303 Taiwan Institute of Imaging and Biomedical Photonics National Yang Ming Chiao Tung University Tainan71150 Taiwan Industrial Technology Research Institute System Design and Integration Department Hsinchu31057 Taiwan Southeast University School of Instrument Science and Engineering Nanjing210096 China

A 12-lead electrocardiogram (ECG) is one of the most commonly used tools for evaluating cardiovascular diseases (CVDs). In clinical, the conventional Ag/AgCl electrodes with conductive gel are usually used to monitor ECG, but they may encounter gel drying and skin allergic reaction problems for long-term ECG monitoring. In order to improve the above issue, several dry electrodes, made by conductive materials, was proposed in the design of wearable devices, but they still encounter the problems of electrode shifting and stretching, and the risk of skin irritation. Capacitive electrode can access biopotential without contacting skin directly and can completely avoid skin irritation. However, for capacitive electrode, how to maintain a good electrode-skin contacting condition is still a challenge due to electrode fixation problem, in particular in multichannel ECG measurement. In this study, a 12-lead ECG smart clothing based on capacitive sensing technology was proposed to monitor ECG in daily life. To improve the electrode-skin contacting condition, elastic conductive foams were used as the electrode plate to effectively fit the rough body contours. Moreover, a specific wearable belt mechanism was also designed to improve the convenience of use, and it could also provide good friction and proper pressure to reduce the electrode slippage and maintain a good electrode-skin contact condition. The experimental results showed that the proposed smart clothing could stably access the good ECG signal quality under different motion levels, and the specific ECG features corresponding to different CVDs could also be reflected on the measured ECG signal in clinical experiment. © 2001-2012 IEEE.

关键词： Electrocardiograms

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Gender and Age Estimation using Transfer Learning with Multi-tasking Approach 2

Gender and Age Estimation using Transfer Learning with Multi...

引用

2nd Asian Conference on Innovation in technology, ASIANCON 2022

作者： Vidyarthi, Pankaj Dhavale, Sunita Kumar, Suresh Defence Institute of Advanced Technology Department of Computer Science & Engineering Pune411025 India Defence Institute of Psychological Research Drdo Delhi110054 India

ISBN: (数字)9781665468510

ISBN: (纸本)9781665468510

The estimation of Age and Gender of a Human being using facial characteristic is getting lot of attractions these days due to wide variety of its applications in the real-world scenarios. Significant work has been carried out in this regard and various methods and approaches has been published which have offered very good results as far as accuracy are concerned. This paper brings out a comparison of most famous pretrained models for estimating both gender and age of a person in videos using multi-tasking approach enabling a single model to estimate both age as well as gender. The estimation accuracy of EfficientNetV2B1 model using multi-tasking approach provides good accuracy (of 90.31) and MAE (of 0.063) compared to other models. The publicly available dataset UTKFACE has been used for training the multi-tasking CNN. © 2022 IEEE.

关键词： computer vision

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Internet of Things Assisted Remote Health and Safety Monitoring Scheme Using Intelligent Sensors 2

Internet of Things Assisted Remote Health and Safety Monitor...

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2nd IEEE International Conference on Advances in Computing, Communication and Applied informatics, ACCAI 2023

作者： Ramkumar, V. Shanthi, S. Kumar, K. Suresh Kanageswari, S. Mahalakshmi, S. Anusuya, R. R.M.K. Engineering College Department of ECE Chennai India Care College of Engineering Department of ECE Tiruchirappalli India Panimalar Engineering College Department of Mba Chennai India Loyola College Department of Computer Science Chennai India R.M.K Engineering College Department of Computer Science and Design Chennai India Modern Institute of Technology and Research Centre Department of Cse Rajasthan Alwar India

ISBN: (纸本)9798350315905

The Internet of Things (IoT) in telemedicine creates an enormous data volume that must be processed, analyzed, and stored. Risk to one's health is no longer mitigated by one's chronological age, thanks to today's hectic schedules and unexpected ways of living. The Internet of Things has made it easier to provide continuous remote health checks on patients outside of the hospital or clinic, or even in their own homes. Detectors record data on a variety of patient health factors, and the Internet of Things saves and displays this data on a website that also allows for remote monitoring. When the potential of IoT technology is taken into consideration, the challenges that patients with physical instability have while trying to regularly contact a doctor in person can be circumvented. The microcontroller's role in this project is that of a data relay. This system presents a new method for health service activities by using sensors to monitor a person's vitals and the network to alert concerned family members or physicians in the case of an *** attached buzzer in the controller will sound when there is a change in detector output, alerting the career. A microcontroller is used to monitor the patient's condition;this controller communicates with an LCD display and a wireless LAN to send out alert messages. The patient's heart rate, blood pressure, and temperature will all be displayed in the cloud in instantaneously, and a warning will be sent to the physician via the Internet of Things if the sensor recognizes an abnormality. In order to comprehend how the sensors worked, a comprehensive analysis of the data was collected with regard to fluctuations in physical and environmental activity. © 2023 IEEE.

关键词： Blood pressure

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TransAxx: Efficient Transformers with Approximate Computing

arXiv

引用

arXiv 2024年

作者： Danopoulos, Dimitrios Zervakis, Georgios Soudris, Dimitrios Henkel, Jörg The School of Electrical and Computer Engineering National Technical University of Athens Athens15780 Greece The Department of Computer Engineering & Informatics University of Patras Patras Greece Karlsruhe Institute of Technology Karlsruhe76131 Germany

Vision Transformer (ViT) models which were recently introduced by the transformer architecture have shown to be very competitive and often become a popular alternative to Convolutional Neural Networks (CNNs). However, the high computational requirements of these models limit their practical applicability especially on low-power devices. Current state-of-the-art employs approximate multipliers to address the highly increased compute demands of DNN accelerators but no prior research has explored their use on ViT models. In this work we propose TransAxx, a framework based on the popular PyTorch library that enables fast inherent support for approximate arithmetic to seamlessly evaluate the impact of approximate computing on DNNs such as ViT models. Using TransAxx we analyze the sensitivity of transformer models on the ImageNet dataset to approximate multiplications and perform approximate-aware finetuning to regain accuracy. Furthermore, we propose a methodology to generate approximate accelerators for ViT models. Our approach uses a Monte Carlo Tree Search (MCTS) algorithm to efficiently search the space of possible configurations using a hardware-driven hand-crafted policy. Our evaluation demonstrates the efficacy of our methodology in achieving significant trade-offs between accuracy and power, resulting in substantial gains without compromising on performance. Copyright © 2024, The Authors. All rights reserved.

关键词： Economic and social effects

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To Explore the Potential Inhibitors against Multi-target Proteins of COVID-19 using In-Silico Study

arXiv

引用

arXiv 2024年

作者： Aqeel, Imra Biomedical Informatics Research Lab Department of Computer & Information Sciences Pakistan Institute of Engineering & Applied Sciences Nilore Islamabad45650 Pakistan

The global pandemic due to emergence of COVID-19 has created the unrivaled public-c health crisis. It has huge morbidity rate never comprehended in the recent decades. researchers have made many efforts to find the optimal solution of this pandemic. Progressively, drug repurposing is an emergent and powerful strategy with saving cost, time, and labor. Lacking of identified repurposed drug candidates against COVID-19 demands more efforts to explore the potential inhibitors for effective cure. In this study, we used the combination of molecular docking and machine learning regression approaches to explore the potential inhibitors for the treatment of COVID-19. The 5903 approved drugs from ZINC database, have screened against the multi-target proteins of COVID-19 including Spike (S), main protease 3CL (3CLpro), and Nucleocapsid (N) proteins. These proteins are responsible for binding of virons with host cell receptors, replicating the virus, and wrapping the virus RNA into a helical symmetrical structure. We calculated the binding affinities of these drugs to multi-target proteins using molecular docking process. We perform the QSAR modeling by employing various machine learning regression approaches to identify the potential inhibitors against COVID-19. Our findings with best scores of R2 and RMSE demonstrated that our proposed Decision Tree Regression (DTR) model is the most appropriate model to explore the potential inhibitors. We proposed five novel promising inhibitors with their respective Zinc IDs ZINC (3873365, 85432544, 8214470, 85536956, and 261494640) within the range of -19.7 kcal/mol to -12.6 kcal/mol. We further analyzed the physiochemical and pharmacokinetic properties of these most potent inhibitors to examine their behavior. The analysis of these properties is the key factor to promote an effective cure for public health. Our work constructs an efficient structure with which to probe the potential inhibitors against COVID-19, creating the combination o

关键词： COVID-19

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Advancing Color Perception: An IoT-driven Pedagogical System for Visually Impaired Children

Advancing Color Perception: An IoT-driven Pedagogical System...

引用

Advances in Signal Processing, Power, Communication, and Computing (ASPCC), IEEE International Conference on

作者： Prasandika Balage Nuwan Jayawardene School of Computer Science and Engineering University of Westminster London United Kingdom Department of Computing Informatics Institute of Technology Colombo Sri Lanka

ISBN: (数字)9798350355093

ISBN: (纸本)9798350355109

Visual impairment is characterized by the loss of vision, encompassing both complete blindness and partial vision loss. Studies reveal a notable prevalence of visual impairment among school-aged children. The significance of colors in acquiring and discerning visual information is crucial, aiding children in effectively perceiving and comprehending their surroundings. This study presents an Internet of Things (IoT) system designed for teaching colors to visually impaired children. The system achieved an accuracy rate surpassing 77.8%, and it is operated effectively regardless of surrounding lighting conditions. Given that the target users of the system are visually impaired children, this research was conducted in close alignment with Human-computer Interaction (HCI) principles.

关键词： Human computer interaction Visualization Accuracy Visual impairment Education Lighting Color Blindness Signal processing Internet of Things

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