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arXiv 2024年

作者： de Oliveira Neto, Francisco Gomes Dobslaw, Felix Chalmers The University of Gothenburg Dept. of Computer Science and Engineering Gothenburg Sweden Mid Sweden University Dept. of Quality Mngmt Communication and Inf. Systems Östersund Sweden

The increasing demand for software engineering education presents learning challenges in courses due to the diverse range of topics that require practical applications, such as programming or software design, all of which are supported by group work and interaction. Social Annotation (SA) is an approach to teaching that can enhance collaborative learning among students. In SA, both students and teachers utilize platforms like Feedback Fruits, Perusall, and Diigo to collaboratively annotate and discuss course materials. This approach encourages students to share their thoughts and answers with their peers, fostering a more interactive learning environment. We share our experience of implementing social annotation via Perusall as a preparatory tool for lectures in an introductory programming course aimed at undergraduate students in Software engineering. We report the impact of Perusall on the examination results of 112 students. Our results show that 81% of students engaged in meaningful social annotation successfully passed the course. Notably, the proportion of students passing the exam tends to rise as they complete more Perusall assignments. In contrast, only 56% of students who did not participate in Perusall discussions managed to pass the exam. We did not enforce mandatory Perusall participation in the course. Yet, the feedback from our course evaluation questionnaire reveals that most students ranked Perusall among their favorite components of the course and that their interest in the subject has increased. © 2024, CC BY.

关键词： Students

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Ensuring Electronic Health Record (EHR) Privacy using Zero Knowledge Proofs (ZKP) and Secure Encryption Schemes on Blockchain

Ensuring Electronic Health Record (EHR) Privacy using Zero K...

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Advancements in Computing (ICAC), International Conference on

作者： Ranaweera T.A.V.Y Hewage H.N.H Hapuhinna H.K.D.W.M.C.B. Preethilal K.L.K.T Amila Senarathne Laneesha Ruggahakotuwa Dept. Computer Systems Engineering Sri Lanka Institute of Information Technology Malabe Sri Lanka

In the haste of EHR digitization, the protection of patient data becomes paramount, casting a spotlight on small healthcare clinics grappling with the threats of an ever more interconnected healthcare sector. That is due to the existing centralized system and traditional password-based authentications which cause a single point of failure. Besides this patient consent for EHR sharing is narrowed to a one-time consent. To overcome these problems, this study suggests a robust solution that makes data sharing utilizing blockchain while achieving privacy using web-based Zero Knowledge Proofs (ZKP) authentication and Homomorphic Encryption (HE). The research also considers securely outsourcing EHRs to research organizations to improve data exchange for research purposes. Along with patient-controlled encryption, consent control, and time-limited data access, it also explores dynamic consent management while complying with healthcare standards. Lastly, this study stream-lines secure data sharing with insurance providers while ensuring patient privacy and defending against insurance fraud.

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Feedforward control in the Presence of Input Nonlinearities: With Application to a Wirebonder

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IFAC-PapersOnLine 2023年第2期56卷 1895-1900页

作者： Maurice Poot Jilles van Hulst Kai Wa Yan Dragan Kostić Jim Portegies Tom Oomen CST Dept. of Mechanical Engineering Eindhoven University of Technology Eindhoven The Netherlands Center of Competency ASMPT Beuningen The Netherlands CASA Dept. of Mathematics and Computer Science Eindhoven University of Technology Eindhoven The Netherlands Delft Center for Systems and Control Delft University of Technology Delft The Netherlands

The increasing demands on throughput and accuracy of semiconductor manufacturing equipment necessitates accurate feedforward motion control that includes compensation of input nonlinearities. The aim of this paper is to develop a data-driven feedforward approach consisting of a Wiener feedforward, i.e., linear parameterization with an output nonlinearity, to achieve high tracking accuracy and task flexibility for a class of Hammerstein systems. The developed approach exploits iterative learning control to learn a feedforward signal from data that minimizes the error and utilizes a control-relevant cost function to learn the parameters of a Wiener feedforward parameterization. Experimental validation on a wirebonder shows that the developed approach enables high tracking accuracy and task flexibility.

关键词： Iterative and repetitive learning control Identification and control methods Nonlinear system identification Data-driven control Learning for control

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Respect the Difference: Reinforcement Learning for Heterogeneous FPGA Placement

Respect the Difference: Reinforcement Learning for Heterogen...

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IEEE International Conference on Field-Programmable Technology (FPT)

作者： Fatemehsadat Mahmoudi Mohamed A. Elgammal Soheil Gholami Shahrouz Kevin E. Murray Vaughn Betz Dept. of Electrical & Computer Engineering University of Toronto Toronto Canada Cerebras Systems Toronto Canada

Simulated Annealing (SA) is widely used for FPGA placement due to its ability to adapt to different architectures and optimization goals. However, as FPGA capacity has grown and the devices have become more heterogeneous, the solution space has become very large, making efficient approaches to explore the space critical. We present RLPlace 2.0, an FPGA placer based on simulated annealing that utilizes Reinforcement Learning (RL) and better-than-random initial placement for efficient solution space exploration. The RL agent decides not only on the move types to use at each point in the anneal but also the type of block to move. The RL agent that controls the process is trained entirely online, enabling automatic adaptation to the architecture and design. For traditional FPGA benchmarks, RLPlace 2.0 outperforms both VPR 8 and RLPlace 1.0 in wirelength (WL) and critical path delay (CPD) at all runtime points. For example, on average over the Koios benchmark suite, RLPlace 2.0 reduces CPD by 3% and WL by 1.8% while cutting placement time by 54% at the default run time point vs. VPR 8. On more complex and heterogeneous FPGAs that incorporate a hard Network on Chip (NoC), RLPlace 2.0 enables more efficient co-optimization of NoC and programmable routing metrics by learning when and how to move the NoC routers throughout the anneal. On average for benchmarks containing NoC routers, RLPlace 2.0 achieves the same WL and CPD, 41% reduced NoC latency, and 6% improved NoC bandwidth usage in 50% less time compared to RLPlace 1.0.

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Building Collaborative Learning: Exploring Social Annotation in Introductory Programming

Building Collaborative Learning: Exploring Social Annotation...

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Software engineering: Software engineering Education and Training (ICSE-SEET), IEEE/ACM International Conference on

作者： Francisco Gomes De Oliveira Neto Felix Dobslaw Dept. of Computer Science and Engineering Chalmers and the University of Gothenburg Gothenburg Sweden Dept. of Quality Mngmt Communication and Inf. Systems Mid Sweden University Östersund Sweden

ISBN: (数字)9798400704987

ISBN: (纸本)9798350352115

关键词： Training Software design Annotations Federated learning Buildings Programming profession Software engineering

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Enhancing Cybersecurity Through Advanced Fraud and Anomaly Detection Techniques: A Systematic Review

Enhancing Cybersecurity Through Advanced Fraud and Anomaly D...

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Science, engineering and Business for Sustainable Development Goals (SEB-SDG), International Conference on

作者： Oluwambo Tolulope Olowe Ayodele A. Adebiyi Adebiyi O. Marion Olowe Mofiyinfoluwa Tobi Deborah Olaniyan Julius Olaniyan Aderemi Emmanuel Kayode Akindeji Dept of Computer Science Landmark University Omuaran Nigeria Dept. of Industrial & Systems Engineering University of Pretoria Pretoria South Africa Dept. of Power Electric Engineering Durban University of Technology Durban South Africa

ISBN: (数字)9798350358155

ISBN: (纸本)9798350358162

Fraud and anomaly detection in cybersecurity have become critical areas of research, prompting a comprehensive review of recent developments and model effectiveness. This study investigates prevalent trends and challenges in fraud and anomaly detection, focusing on data science approaches within e-commerce and smart cities. Through the analysis, key factors influencing detection efficacy, such as deep learning models and hybrid approaches, are examined. Findings highlight the multidimensional nature of cyber threats across various domains and underscore the importance of proactive security measures, including robust authentication, network fortification, and employee training. This paper contributes to enhancing awareness and understanding of evolving cyber threats while offering actionable insights for bolstering detection capabilities and mitigating risks.

关键词： Deep learning Training Systematics Authentication Data science Market research Software

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Automated Boundary Identification for Machine Learning Classifiers

Automated Boundary Identification for Machine Learning Class...

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Search-Based and Fuzz Testing (SBFT), IEEE/ACM International Workshop on

作者： Felix Dobslaw Robert Feldt Dept. of Quality Mngmt Communication and Inf. Systems Mid Sweden University Östersund Sweden Dept. of Computer Science and Engineering Chalmers University of Technology Gothenburg Sweden

ISBN: (数字)9798400705625

ISBN: (纸本)9798350376012

AI and Machine Learning (ML) models are increasingly used as (critical) components in software systems, even safety-critical ones. This puts new demands on the degree to which we need to test them and requires new and expanded testing methods. Recent boundary-value identification methods have been developed and shown to automatically find boundary candidates for traditional, non-ML software: pairs of nearby inputs that result in (highly) differing outputs. These can be shown to developers and testers, who can judge if the boundary is where it is supposed to ***, we explore how this method can identify decision boundaries of ML classification models. The resulting ML Boundary Spanning Algorithm (ML-BSA) is a search-based method extending previous work in two main ways. We empirically evaluate ML-BSA on seven ML datasets and show that it better spans and thus better identifies the entire classification boundary(ies). The diversity objective helps spread out the boundary pairs more broadly and evenly. This, we argue, can help testers and developers better judge where a classification boundary actually is, compare to expectations, and then focus further testing, validation, and even further training and model refinement on parts of the boundary where behaviour is not ideal.

关键词： Training Conferences Machine learning Fuzzing Software systems Classification algorithms Testing

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Towards Eco-Sustainability and Green Analytics Model to Measure the Performance of Big Data systems 9

Towards Eco-Sustainability and Green Analytics Model to Meas...

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9th International Conference on Information Management, ICIM 2023

作者： Jusoh, Yusmadi Yah Abdullah, Rusli Nor, Rozi Nor Haizan Yahaya, Jamaiah Hj. Muhammad, Shireen Arunachalam, Aishwharya Raani Universiti Putra Malaysia Faculty of Computer Science and Information Technology Dept. of Software Engineering and Information Systems Serdang Malaysia Universiti Kebangsaan Malaysia Faculty of Information Science and Technology Bangi Malaysia Faculty of Communication Selangor Malaysia

ISBN: (纸本)9798350336382

Many BDS is doomed to failure because of the missing knowledge on measuring the performance of BDS. The failure to identify the performance measurement and correct will make the problems worsen. This will complicate the efforts of fixing such problems and more importantly, will affect the quality of knowledge, insights, and results expected by the users in the future. In achieving durable performance, the organization needsto understand the factors that contribute to the performance of the eco-sustainability and green analytics metrics for BDS. Although the existence of its importance and awareness was largely neglected. Therefore, the eco-sustainability and green analytic measurement of the BDS is examined in this research. Measuring the BDS performance has the benefit of identifying problems and launching corrective actions before these problems happen and become worsen. The research will investigate the eco-sustainability and green analytic measures which will be proposed and used to capture performance for each process of BDS. Then, based on such measures and metrics, as well as existing performance concepts, frameworks, and models, a measurement model for BDS will be created. The model will be validated through expert evaluations and confirmatory studies with users and practitioners of BDS users. The research has a greater significance in leveraging existing performance concepts in BDS settings and the research proposes users' participation in the sustainability and continuous performance evaluation of theirBDS. © 2023 IEEE.

关键词： Big data

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Unveiling Disparities: NLP Analysis of Software Industry and Vocational Education Gaps

Unveiling Disparities: NLP Analysis of Software Industry and...

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Natural Language-Based Software engineering (NLBSE), IEEE/ACM International Workshop on

作者： Emil Bäckstrand Rasmus Djupedal Lena-Maria Öberg Francisco Gomes De Oliveira Neto Dept. of Quality Management Communication and Inf. Systems Mid Sweden University Östersund Sweden Dept. of Computer Science and Engineering Chalmers|University of Gothenburg Gothenburg Sweden

ISBN: (数字)9798400705762

ISBN: (纸本)9798350352559

The rapid growth of software industry highlights the importance of the education system in producing competent professionals to meet industry demands. Previous research has identified a gap between industry needs and the content of educational programs. This study presents Vocational Education and Labour Market Analyser (VELMA), a tool designed to extract information from job ads and educational curricula (both from Sweden), utilising topic modelling to identify the diverse technologies and skills in demand within the industry and those covered by professional education. Particularly, we use Latent Dirichlet Allocation (LDA) to categorise keywords into cohesive themes for document frequency analysis. Our findings highlight industry demand for skills in cloud and embedded technologies, security engineering, and software architecture. In contrast, the Higher Vocational Education (HVE) curricula emphasise the education of web developers and general object-oriented programming languages. CCS CONCEPTS • Applied computing $\rightarrow$ Document management and text processing; Education; $\cdot$ Software and its engineering $\rightarrow$ Designing software.

关键词： Industries Analytical models Text analysis Object oriented modeling Education Software Natural language processing

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The Efficiency of Conductor Placement in Circuits with Single Modal Redundancy in Differential and Common Modes

The Efficiency of Conductor Placement in Circuits with Singl...

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Annual Siberian Russian Workshop on Electron Devices and Materials (EDM)

作者： Alexandr M. Lakoza Valery P. Kosteletsky Dept. of Microwave and Quantum Radio Engineering Tomsk State University of Control Systems and Radioelectronics Tomsk Russia

This article presents the results of selecting, justifying, and optimizing the cross section parameters for a modal filter (MF) with single modal redundancy (MR). This filter is employed for protecting circuits from interfering ultrashort pulses (UPS) in differential and common mode. The results demonstrate that the attenuation coefficient in the differential and common modes depends on the width of the active conductor and the distance between the structures. As a result, we present their optimal values. It is shown that the location of primary (reserved) and secondary (reserving) conductors in a four-wire MF has a significant impact. The smallest voltage value at the MF output is observed when EMF sources are connected to the most remote conductors both in differential and in common mode for four types of pulses. Insertion loss values in differential mode were minus 5.19, 11.57, 5.26, and 5.22 dB, while in common mode - minus 5.45, 11.7, 5.65, and 5.65 dB for trapezoidal, digitized, unipolar and bipolar action, respectively. Switching to closer pairs of conductors degrades insertion loss levels by 0.57-0.76 dB for common mode, and 0.61-0.82 dB for differential modes, depending on the selected lines.

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