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46th International Conference on Software engineering: Software engineering Education and Training, ICSE-SEET 2024

作者： Boman, Lina Andersson, Jonatan de Oliveira Neto, Francisco Gomes University of Gothenburg Dept. of Computer Science and Engineering Gothenburg Sweden Chalmers and the University of Gothenburg Dept. of Computer Science and Engineering Gothenburg Sweden

ISBN: (纸本)9798400704987

Women in computing were among the first programmers in the early 20th century and were substantial contributors to the industry. Today, men dominate the software engineering industry. Research and data show that women are far less likely to pursue a career in this industry, and those that do are less likely than men to stay in it. Reasons for women and other underrepresented minorities to leave the industry are a lack of opportunities for growth and advancement, unfair treatment and workplace culture. This research explores how the potential to cultivate or uphold an industry unfavourable to women and non-binary individuals manifests in software engineering education at the university level. For this purpose, the study includes surveys and interviews. We use gender name perception as a survey instrument, and the results show small differences in perceptions of software engineering students based on their gender. Particularly, the survey respondents anchor the values of the male software engineer (Hans) to a variety of technical and non-technical skills, while the same description for a female software engineer (Hanna) is anchored mainly by her managerial skills. With interviews with women and non-binary students, we gain insight on the main barriers to their sense of ambient belonging. The collected data shows that some known barriers from the literature such as tokenism, and stereotype threat, do still exist. However, we find positive factors such as role models and encouragement that strengthen the sense of belonging among these students. © 2024 Copyright held by the owner/author(s).

关键词： Students

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Implementation of Blockchain and IPFS to safeguard evidentiary data

Implementation of Blockchain and IPFS to safeguard evidentia...

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2024 International Conference on Knowledge engineering and Communication Systems, ICKECS 2024

作者： Srivastava, Supriya Kaur, GeetKiran Himank Singla, Sanjay Chandigarh University Dept. of Computer Science & Engineering Mohali140413 India Chandigarh University Dept. of Computer Science & Engineering Gharuan India

ISBN: (纸本)9798350359688

Nowadays due to increasing cases of evidence alteration the need of a robust evidence protection system is increasing rapidly. This paper presents an innovative solution that combines the InterPlanetary File System (IPFS) with blockchain technology to enhance the security, immutability, and transparency of evidential data obtained from crime *** proposed system initiates by utilizing IPFS, a decentralized and distributed file storage protocol, to securely store multimedia evidence, such as photographs. The content-addressed nature of IPFS guarantees tamper-resistant storage, making it an ideal choice for preserving the integrity of sensitive evidentiary materials. The IPFS addresses obtained from IPFS are then embedded within the blockchain, establishing a decentralized and verifiable link between the evidence and its storage location. We use multi-signature wallet to upload the data on blockchain so that we can make it more secure and monitored about who is uploading evidence state data. To verify links and integrity of evidence usage we set up a system of periodical updates of state of evidence whenever accessed. These updates serve as a mechanism to record the state of the evidence at different points in time, adding an additional layer of reliability and accountability. © 2024 IEEE.

关键词： Blockchain

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Optimization of Cost-based Dynamic Economic Dispatch Problem using Mathematical Programming

Optimization of Cost-based Dynamic Economic Dispatch Problem...

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2024 International Conference on Innovations in science, engineering and Technology, ICISET 2024

作者： Mahmood, Mou Chowdhury, Nahid-Ur-Rahman Southeast University Dept. of Computer Science and Engineering Dhaka Bangladesh Ahsanullah University of Science and Technology Dept. of Electrical and Electronic Engineering Dhaka Bangladesh

ISBN: (纸本)9798350355499

This paper introduces a robust and effective methodology for addressing the dynamic economic dispatch (DED) optimization problem, which is pivotal in power system operations and planning. DED is basically an enhanced version of static economic dispatch (SED) problem that involves scheduling a set of generation units over a typical operational period, often spanning 24 hours, to cover the predicted load demand with the on/off status of each generation unit predetermined. The literature distinguishes between two main types of DED: cost-based and price-based. This paper focuses on the cost-based approach, utilizing quadratic constrained programming (QCP) to model the problem effectively. QCP is particularly suited for this task as it optimally manages the ramp rate constraints and capacities of the available generation units maintaining the minimum operating cost. To demonstrate the effectiveness of the proposed methodology, simulations were conducted using two distinct scenarios involving 5-unit and 10-unit power dispatch strategies. The results, obtained through the general algebraic modeling system (GAMS), clearly presents the superiority of GAMS in achieving optimal solutions when compared to other existing metaheuristic techniques. © 2024 IEEE.

关键词： Quadratic programming

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Futuristics Technologies for Reduction of Plastic Waste 13

Futuristics Technologies for Reduction of Plastic Waste

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13th International Conference on System Modeling and Advancement in Research Trends, SMART 2024

作者： Dhiman, Riya Sharma, Ashish Chandigarh University Dept. of Computer Science Mohali India Chandigarh University Dept. of Electrical Engineering Mohali India

ISBN: (纸本)9798350380583

Plastic plays a vital role in daily life most of the food items, Baggies, vegetables are packed in plastic material. As plastic is non-biodegradable there are harming effect on human beings and animals. Due to these global warming also increases. Although 80% Fishes, 88% Vertebrates, 56% Mammals and 52% Reptiles are affected due to plastic waste. In this work with the various techniques proposed like Eco-bricks, Furniture, Replace Plastic By Bamboo and also Doormats are made through the Plastic Waste. It is seen that by using above techniques significantly reduce the harmful effect of plastic and there is improvement in life of human beings and animals also the alternative techniques to reuse the plastic and to replace plastic are proposed with which there is a increase in the earning of poor peoples. Above techniques are helpful to decrease the employment and also by using these techniques more than 60% of plastic reuse, with this the temperature is also decreased. © 2024 IEEE.

关键词： Invertebrates

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Towards Robust mmWave-based Human Activity Recognition using Large Simulated Dataset for Model Pretraining

Towards Robust mmWave-based Human Activity Recognition using...

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2024 IEEE International Conference on Big Data, BigData 2024

作者： Joshi, Vinay Xu, Shengkai Cao, Qiming Zhu, Yi Wang, Pu Xue, Hongfei Unc Charlotte Dept. of Computer Science Charlotte United States Purdue University Electrical and Computer Engineering West Lafayette United States Wayne State University Dept. of Computer Science Detroit United States

ISBN: (纸本)9798350362480

Human activity recognition (HAR) is crucial for real-world applications such as healthcare, surveillance, and smart homes. Among sensing technologies, millimeter wave (mmWave) sensors stand out due to their contactless nature, high sensitivity, and ability to operate in low-light environments while preserving privacy. However, the scarcity of mmWave sensing data limits the generalizability of mmWave-based HAR systems. To address this, we propose mmAP, a data augmentation and pretraining framework that synthesizes a large mmWave dataset using human mesh data, followed by pretraining a robust and general mmWave heatmap encoder using a multi-modal masked autoencoder framework using the synthesized data. We enhance the model's robustness with heatmap-specific data perturbations and perform task-specific fine-tuning on a small real-world dataset. The experiment results over the baseline demonstrate the effectiveness of the proposed mmAP framework. © 2024 IEEE.

关键词： Large datasets

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Design of dv/dt Filter for Insulation Protection in SiC Inverter-Fed Motor Drive Systems

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Transactions of the Korean Institute of electrical Engineers 2024年第1期73卷 56-62页

作者： Choi, Hye-Won Bae, Yun-Jae Kang, Yong-Jin Park, Cheol-Hyun Lee, Kyo-Beum Dept. of Electrical and Computer Engineering Ajou University Korea Republic of Product Development Group LS ELECTRIC Korea Republic of

This paper proposes design of dv/dt filter for insulation protection in SiC inverter-fed motor drive systems. The SiC inverter is subjected to voltage and current surges. It may cause additional losses in the motor, insulation failure, high bearing current, and electromagnetic interference. To mitigate these problems, a high value of gate resistance is placed at the gate driver;however, it introduces additional switching losses on the devices. In this paper, the filter is injected between the inverter and the motor system. The characteristics of each filter such as rising time, peak voltage, and dv/dt are analyzed to ensure the national electric manufacturers association (NEMA) standard. The proposed design scheme of the dv/dt filter is demonstrated by various experimental results. © 2024 Korean Institute of electrical Engineers. All rights reserved.

关键词： Silicon carbide

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Towards Fast Rates for Federated and Multi-Task Reinforcement Learning 63

Towards Fast Rates for Federated and Multi-Task Reinforcemen...

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63rd IEEE Conference on Decision and Control, CDC 2024

作者： Zhu, Feng Heath, Robert W. Mitra, Aritra North Carolina State University Dept. of Electrical and Computer Engineering United States University of California Dept. of Electrical and Computer Engineering San Diego United States

ISBN: (纸本)9798350316339

We consider a setting involving N agents, where each agent interacts with an environment modeled as a Markov Decision Process (MDP). The agents' MDPs differ in their reward functions, capturing heterogeneous objectives/tasks. The collective goal of the agents is to communicate intermittently via a central server to find a policy that maximizes the average of long-term cumulative rewards across environments. The limited existing work on this topic either only provide asymptotic rates, or generate biased policies, or fail to establish any benefits of collaboration. In response, we propose Fast-FedPG - a novel federated policy gradient algorithm with a carefully designed bias-correction mechanism. Under a gradient-domination condition, we prove that our algorithm guarantees (i) fast linear convergence with exact gradients, and (ii) sublinear rates that enjoy a linear speedup w.r.t. the number of agents with noisy, truncated policy gradients. Notably, in each case, the convergence is to a globally optimal policy with no heterogeneity-induced bias. In the absence of gradient-domination, we establish convergence to a first-order stationary point at a rate that continues to benefit from collaboration. © 2024 IEEE.

关键词： Federated learning

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A Comprehensive Analysis on Skin Cancer Classification Using Transfer Learning 3

A Comprehensive Analysis on Skin Cancer Classification Using...

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3rd International Conference on Advancement in electrical and Electronic engineering, ICAEEE 2024

作者： Renu, Israt Zerin Haque, Md. Momenul Paul, Subrata Kumer Mou, Mahmuda Shirin Rahman, Md Nahid Gupta, Sudipta Sen Paul, Rakhi Rani Rabindra Maitree University Dept. of Computer Science and Engineering Kushtia7000 Bangladesh Qadirabad Dept. of Computer Science and Engineering Dayarampur Natore6431 Bangladesh University of Rajshahi Dept. of Computer Science and Engineering Rajshahi6205 Bangladesh

ISBN: (纸本)9798350388282

Skin cancer, a prevalent and potentially life-threatening disease, necessitates accurate and timely diagnosis for effective treatment. In addressing this critical healthcare challenge, this research proposes a novel approach to skin cancer classification. The study identifies the need for enhanced diagnostic accuracy and introduces a solution by integrating the efficiency of transfer learning, specifically utilizing the EfficientNet V2 architecture. The proposed methodology leverages pre-trained convolutional neural networks (CNNs) to extract high-level features from dermatological images, which are subsequently input into a sophisticated classifier, forming a robust framework for precise skin cancer classification. The research employs a diverse dataset comprising 3297 images sourced from the publicly available Skin Cancer ISIC archive dataset, ensuring comprehensive coverage of benign and malignant skin lesions. During the training phase, the proposed EfficientNet V2 transfer learning approach outperforms conventional methods, achieving an impressive accuracy of 84%, surpassing both Inception V3 (82%) and a generic CNN model (81%). Interpretability analysis is conducted to elucidate the decision-making process of the EfficientNet V2 model, providing insights into the key features influencing its predictions. This transparency is crucial for building trust in the model's recommendations and facilitating its seamless integration into clinical workflows. The EfficientNet V2 transfer learning approach emerges as a promising and effective solution for advancing skin cancer classification systems, contributing significantly to the ongoing efforts to improve diagnostic accuracy in dermatology. © 2024 IEEE.

关键词： Decision making

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Field Demonstration of Blockchain-based Security for a Solar Farm

Field Demonstration of Blockchain-based Security for a Solar...

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2024 IEEE Energy Conversion Congress and Exposition, ECCE 2024

作者： Ahn, BoHyun Nakka, Kalyan Handke, Nathanial R. Reyna, Trevor J. Kim, Taesic Texas A&m University-Kingsville Dept. of Electrical Engineering and Computer Science KingsvilleTX78363 United States Texas A&m University Dept. of Computer Science and Engineering College StationTX77843 United States University of Missouri-Columbia Dept. of Electrical Engineering and Computer Science ColumbiaMO65211 United States

ISBN: (纸本)9798350376067

This paper introduces a Blockchain (BC)-based security model for a solar farm, providing security functions such as firmware patching management, role-based access control, public key infrastructure, and man-in-the-middle attacks detection (MITM), malware file detection. In particular, this paper provides detailed field-testing methods at a solar fam to demonstrate the feasibility and effectiveness of cyber-attack detection methods. Practical cyberattacks targeting solar farms are designed and conducted. It is demonstrated that the proposed BC-based system proactively detects MITM attacks, firmware modification attack, and malware attack, while ensuring the continuous operation of the solar farm during attack events. © 2024 IEEE.

关键词： Cyber attacks

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Towards the Compilation of Digital Twin Models for Service-Oriented Systems 34

Towards the Compilation of Digital Twin Models for Service-O...

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34th Annual International Conference on Collaborative Advances in Software and Computing, CASCON 2024

作者： Jiang, Hao Kontogiannis, Kostas Western University Computer Science Dept. LondonON Canada York University Dept. of Electrical Eng. & Computer Science TorontoON Canada

ISBN: (纸本)9798331504830

Service-oriented architecture (SOA) serves as a foundational technology for complex IT systems, such as e-commerce platforms, banking solutions, public-sector applications, and gaming systems. As these systems become increasingly intricate, the need for models that enable software engineers to simulate component interactions early in the software lifecycle becomes crucial. This approach helps identify potential issues during the design phase. The goal of this research is to apply digital twin model principles to simulate component transactions, message exchanges, and ultimately evaluate whether a given design meets the goals and requirements of stakeholders. In this paper, we outline ongoing work towards a prototype framework that uses sequence diagrams and activity diagrams to build digital twin models of service-oriented systems. The framework aims to ensure that any design changes are reflected in the digital twin model early in the software lifecycle, potentially uncovering non-compliant or unintended interactions. © 2024 IEEE.

关键词： Service oriented architecture (SOA)

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