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检索条件"主题词=software algorithms"

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AI-driven Student Task Management Platform With Plagiarism Checker For Submissions

AI-driven Student Task Management Platform With Plagiarism C...

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Emerging Systems and Intelligent Computing (ESIC), International Conference on

作者： Tejaswini Durge Aniket Bansod Soham Deshmukh Sanika Boke Chaitali Shewale Pawan Wawage Department of Information Technology Vishwakarma Institute of Information Technology Pune

ISBN: (数字)9798331522100

ISBN: (纸本)9798331522117

In current society, plagiarism of material from external sources is common and claiming it as one’s own is considered a serious offense, particularly in academic settings. Plagiarism has become a significant issue among students at all levels-undergraduate, postgraduate and even doctoral. This paper addresses the specific challenge of plagiarism in computer programming assignments, where students frequently blend and modify original solutions to produce fraudulent work. To address this issue, a system has been proposed that enables teachers to efficiently check for plagiarism with a single click by uploading a folder of submissions. Although various software tools have been developed to detect plagiarism, there has been limited evaluation of their effectiveness in accurately identifying the true authorship of submitted work. Our approach leverages artificial intelligence algorithms to break down submitted articles into smaller sections and compare them against existing databases. This research aims to effectively identify and recognize instances of plagiarism while preventing potential copyright issues. Index Terms—Plagiarism detection, Text similarity, Machine learning, Cosine similarity, Semantic analysis

关键词： Plagiarism Semantics software algorithms Machine learning Multimedia computing Programming Metadata Transformers Real-time systems software tools

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Key Technologies and Implementation of a Digital Twin-Driven Shuttle Car Operation System for Coal Mines

Key Technologies and Implementation of a Digital Twin-Driven...

引用

Advanced algorithms and Control Engineering (ICAACE), International Conference on

作者： Liang Han Yong Wang Xiaobo Che Qilu University of Technology (Shandong Academy of Sciences) Institute of Automation Jinan China

ISBN: (数字)9798331535087

ISBN: (纸本)9798331535094

To address the efficiency bottlenecks and safety hazards inherent in traditional operational modes of coal mine shuttle cars, while improving the excessive reliance on manual labor and insufficient intelligent capabilities, this paper proposes a digital twin-based operational system for coal mine shuttle vehicles. The system constructs a digital model of shuttle vehicles and enables bidirectional synchronicity through MQTT -based transmission of virtual-real twin data, achieving accurate virtual mapping of shuttle equipment. This implementation provides personnel with explicit real-time monitoring of transportation processes, thereby facilitating enhanced operational decision- making for shuttle control. Enterprise-conducted simulated field tests demonstrate the system's practical applicability in effectively improving safety and operational efficiency in coal mine transportation. This study not only validates the practical implementation value of digital twin technology in mining transportation equipment but also contributes to the future development of intelligent and unmanned operations in coal mine transportation systems.

关键词： Temperature sensors Adaptation models Heuristic algorithms software algorithms Transportation Data models Hardware Coal mining Digital twins Automobiles

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Using Reinforcement Learning for Security Testing: A Systematic Mapping Study

Using Reinforcement Learning for Security Testing: A Systema...

引用

IEEE International Conference on software Testing Verification and Validation Workshop, ICSTW

作者： Tanwir Ahmad Matko Butkovic Dragos Truscan Dept. of Information Technology Åbo Akademi University Turku Finland

ISBN: (数字)9798331534677

ISBN: (纸本)9798331534684

Security of software systems has become increasingly important due to the advancement in technology that occurs on a daily basis and due to the interconnectivity that the Internet network system provides. The manual testing process is time-consuming process and inefficient, especially for very large and complex systems. Reinforcement learning has shown promising results in different test generation approaches due to its ability to optimize the test generation process towards relevant parts of the system. A considerable body of work has been developed in recent years to exploit reinforcement learning for security test generation. This study provides a list of approaches and tools for security test generation using Reinforcement Learning (RL). By searching popular research publication databases, a list of 47 relevant studies has been identified and classified according to the type of approach, RL algorithm, application domain and publication metadata.

关键词： software testing Systematics software algorithms Reinforcement learning software systems Robustness Classification algorithms Security Test pattern generators Testing

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Exploring Fairness Debt Through Evidence from Studies on Algorithmic Discrimination

Exploring Fairness Debt Through Evidence from Studies on Alg...

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IEEE/ACM International Conference on Technical Debt (TechDebt)

作者： Fardin Aryan Lucas Valença Ronnie de Souza Santos University of Calgary Calgary AB Canada

ISBN: (数字)9798331502218

ISBN: (纸本)9798331502225

Context. The increasing deployment of artificial intelligence in decision-making processes has highlighted biases embedded in algorithms, leading to discriminatory outcomes that impact society. This phenomenon has led to the proposal of fairness debt, a type of software debt that emerges when biases are not addressed early in development and accumulate over time, creating costly, complex issues that can perpetuate societal inequities. Goal. This study aimed to explore the concept of fairness debt within algorithm-driven decision-making systems, identifying how deferred fairness considerations lead to accumulated biases and affect society. Method. We conducted a mapping study, analyzing 86 papers on algorithmic discrimination to classify root causes, effects, and instances of discrimination associated with fairness debt. Findings. Our findings indicate that several root causes, such as training bias, historical bias, and design bias, contribute to the accumulation of fairness debt, with manifestations in issues like sexism, racism, ableism, and ageism within systems. These accumulated biases can exacerbate social inequalities, limit algorithmic reliability, and perpetuate stereotypes, demonstrating fairness debt’s extensive societal impact. Discussions. Our study demonstrates that fairness debt extends beyond technical issues, encompassing broader societal consequences that demand proactive mitigation strategies, emphasizing the risks associated with deferring fairness considerations and highlighting the importance of fairness as a foundational principle in modern software systems, in particular AI systems. Conclusion. We explore algorithm discrimination through the lens of fairness debt, showcasing e that social concerns of algorithms can be interpreted as main component of software engineering practice, considering the socio-technical factors embedded in it and helping researchers and developers exploring discrimination in their systems and practices.

关键词： Training Prevention and mitigation software algorithms Decision making software systems Classification algorithms software reliability Proposals Artificial intelligence software engineering

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Recommendation Algorithm of Transformer Multi-Scene Based on Lightweight Adaptation Layer

Recommendation Algorithm of Transformer Multi-Scene Based on...

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2025 2nd International Conference on algorithms, software Engineering and Network Security (ASENS)

作者： Jiyuan Sun School of Software Beihang University Beijing China

ISBN: (数字)9798331520298

ISBN: (纸本)9798331520304

With the wide application of personalized recommendation systems in e-commerce, social media and online news platforms, how to accurately capture the changes of users' interests in different scenes has become a key issue. This paper proposes a Transformer multi-scene recommendation algorithm based on lightweight adaptation layer, which aims to improve the efficiency and adaptability of recommendation system. By introducing time coding and parallel block design, the proposed algorithm optimizes the structure of Transformer model, so that it can deal with the time dependence in sequence data more effectively, and adjust the parameters flexibly to meet the needs of different scenes. The experimental results show that the proposed method outperforms the existing recommendation algorithms, including the traditional Transformer model and other multi-task learning models, on several public data sets. This study provides an efficient and flexible solution for multi-scene recommendation tasks.

关键词： Adaptation models Social networking (online) Computational modeling software algorithms Transformers Multitasking Encoding Data models Recommender systems software engineering

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Build and Runtime Integrity for Java

Build and Runtime Integrity for Java

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International Conference on software Engineering - Companion, ICSE, Companion

作者： Aman Sharma KTH Royal Institute of Technology Stockholm Sweden

ISBN: (数字)9798331536831

ISBN: (纸本)9798331536848

software Supply Chain attacks are increasingly threatening the security of software systems, with the potential to compromise both build and runtime integrity. Build-time integrity ensures that the software artifact creation process, from source code to compiled binaries, remains untampered. Runtime integrity, on the other hand, guarantees that the executing application loads and runs only trusted code, preventing dynamic injection of malicious components. This paper explores solutions to safeguard Java application's software supply chain at both stages. We propose techniques to detect malicious code injection through two main contributions: (1) novel algorithm for Java artifact equivalence, and (2) detection and prevention of runtime code injection.

关键词： Java Runtime Codes Source coding Supply chains software algorithms software systems software Malware Security

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Vedic Mathematics Techniques - Real World Applications in Various Fields

Vedic Mathematics Techniques - Real World Applications in Va...

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Advancements in Electrical, Electronics, Communication, Computing and Automation (ICAECA), International Conference on

作者： Malini S Nivedha G Vijeta Iyer K. Meena Department of ECE Kumaraguru College of Technology Coimbatore India Department of Mathematics Kumaraguru College of Technology Coimbatore India

ISBN: (数字)9798331525439

ISBN: (纸本)9798331525446

Vedic mathematics is an ancient system of mathematical principles, rooted in Vedas which offers unique and efficient methods for solving complex problems. This paper aims to review and compare various research studies focusing on applications of Vedic mathematics techniques in contemporary fields. Through a detailed examination of literature, we explore its integration into education, computer science and various fields and how it improves computational speed and enhances mental calculation abilities. Moreover, in this paper we are going to investigate the importance of Vedic mathematics to optimize algorithm designs in software *** in modern-day problem-solving plays an vital role in reducing time factor. Ultimately, we discuss the broader implications of incorporating ancient mathematical methods into contemporary educational frameworks and technological innovations. The study delves into how Vedic techniques enhance computational efficiency, offering faster solutions to problems in arithmetic, algebra, and geometry. We explore the role of these methods in improving mental arithmetic skills, reducing time complexity in algorithmic problem-solving, and optimizing software development. The paper also discusses how Vedic Mathematics has found relevance in real-world applications, such as cryptography, signal processing, and machine learning, where speed and accuracy are paramount.

关键词： Technological innovation software algorithms Signal processing algorithms Machine learning Mathematics Hardware Problem-solving Cryptography Time complexity Arithmetic

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Research on Robot Cross-Platform Collaboration Technology for Future Factories

Research on Robot Cross-Platform Collaboration Technology fo...

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Service Robotics (ICoSR), International Conference on

作者： Weiwei Wang Jialiang Jin Chunxiang Zhu Jianwen Ye Xiaoyu Li Binfeng Huang College of Engineering Training Centre China Jiliang University Hangzhou China College of Information Engineering China Jiliang University Hangzhou China

ISBN: (数字)9798350367119

ISBN: (纸本)9798350367126

In the progression of the future factory, software systems and robotic systems have been widely implemented across different domains. Amidst this plethora of systems, a cloud-edge-end integrated architecture has been designed. Business data resides in the cloud for storage, analysis, and presentation. A business collaboration platform acts as the edge, providing standard API interfaces and command and control for the systems. Application software and robotic systems serve as the ends, executing specific tasks. End systems can only communicate and integrate with the edge through standard API interfaces. The collaboration and interaction between end systems are managed by the business collaboration platform, which schedules, executes, transitions, and pushes tasks based on priority algorithms. This decouples the integration between end systems, significantly reducing the complexity and difficulty of system integration. The architecture has been implemented and its effectiveness has been validated through practical use. The time required for system integration and deployment has been substantially reduced, and the associated costs have notably decreased.

关键词： Schedules Service robots software algorithms Collaboration System integration Computer architecture software systems Production facilities Standards Business

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Optimization of a new modified PRICO process for an efficient hydrogen liquefaction using differential evolution algorithm

Optimization of a new modified PRICO process for an efficien...

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Innovative Engineering Sciences and Technological Research (ICIESTR), International Conference on

作者： Walaa Sidahmed Rahma Ashish M. Gujarathi Rashid Al-Hajri Petroleum and Chemical Engineering Department Sultan Qaboos University Muscat Oman

ISBN: (数字)9798350348637

ISBN: (纸本)9798350348644

Liquid hydrogen has been considered as one of the most essential clean energy carriers and it is believed to have a crucial role as a sustainable alternative fuel in the near future. However, liquefaction of hydrogen is not a simple process and it requires a considerable amount of energy. The novelty of this research work is based on the use of a new highly efficient modified PRICO+ process utilizing a precooling system with the addition of R290 (propane) chillers and further cooling using Nelium (helium/neon) refrigerant cycle. The optimization was carried out with the support of Aspen HYSYS (version 12.1) process simulator and MATLAB R2018b. The differential evolution algorithm DE was applied in the study as it is one of the most popular and robust evolutionary algorithms. The main objectives of this work are to minimize the consumption of energy, maximize the exergy efficiency and effectiveness of cooling and conduct a comparison analysis between the base case using PRICO process and the proposed modified PRICO+. The results obtained from the modified process showed a great noticeable enhancement. The specific energy consumption SEC was 5.91 kWh/kgLH2. The figure of merit FOM and the coefficient of performance COP were 0.530 and 0.259, respectively, which shows a good cooling performance of the process. The exergy efficiency was also optimized and found to be 61.07% which is 24% higher than the base case used in this study and significantly higher than that of the other PRICO processes.

关键词： Energy consumption Neon Cooling Hydrogen software algorithms software Mathematical models Safety MATLAB Optimization

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Methodology and Toolkit for Spectral Analysis of Neural Signals

Methodology and Toolkit for Spectral Analysis of Neural Sign...

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Midwest Symposium on Circuits and Systems (MWSCAS)

作者： Ziao Chen K. C. Ho Satish S. Nair Electrical Engineering & Computer Science University of Missouri Columbia MO USA

ISBN: (数字)9798350387179

ISBN: (纸本)9798350387186

We developed a toolkit that implements the algorithms to estimate the oscillatory bursts embedded in in vivo neural signals. The in vivo signals are decomposed into two components, the $1/\mathrm{f}^{\beta}$ background activity and the embedded oscillatory bursts. The bursts themselves can vary in amplitude, frequency, and number of cycles, making it challenging to characterize them. The first algorithm determines the statistical characteristics of the two components. The second one synthesizes each component individually using the estimated characteristics. The third algorithm captures the best integration of the two components using the Kullback-Leibler divergence criterion to generate an ‘in silico’ version of the in vivo local field potential (LFP) by matching its probability density function with that of the in vivo signal. The methodology and algorithms are illustrated using an in vivo dataset in the public domain. The software tool with the algorithms is available for public download.

关键词： In vivo Circuits and systems software algorithms Local field potentials Probability density function software tools Spectral analysis

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