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arXiv 2023年

作者： Sajavičius, Svajunas Takacs, Thomas Department of Software Engineering Faculty of Informatics Kaunas University of Technology Lithuania Institute of Applied Geometry Johannes Kepler University Linz Austria

The imposition of inhomogeneous Dirichlet (essential) boundary conditions is a fundamental challenge in the application of Galerkin-type methods based on non-interpolatory functions, i.e., functions which do not possess the Kronecker delta property. Such functions typically are used in various meshfree methods, as well as methods based on the isogeometric paradigm. The present paper analyses a model problem consisting of the Poisson equation subject to non-standard boundary conditions. Namely, instead of classical boundary conditions, the model problem involves Dirichlet- and Neumann-type nonlocal boundary conditions. Variational formulations with strongly and weakly imposed inhomogeneous Dirichlet-type nonlocal conditions are derived and compared within an extensive numerical study in the isogeometric framework based on non-uniform rational B-splines (NURBS). The attention in the numerical study is paid mainly to the influence of the nonlocal boundary conditions on the properties of the considered discretisation methods. Copyright © 2023, The Authors. All rights reserved.

关键词： Galerkin methods

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State-based Sandbox Tool for Distributed Malware Detection with Avoid Techniques 13

State-based Sandbox Tool for Distributed Malware Detection w...

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13th International Conference on Dependable Systems, Services and Technologies, DESSERT 2023

作者： Rehida, Pavlo Markowsky, George Sachenko, Anatoliy Savenko, Oleg Khmelnytskyi National University Department of Computer Engineering and Information Systems Khmelnytskyi Ukraine Kennesaw State University Department of Software Engineering and Game Development Marietta United States Kazimierz Pulaski University of Technology and Humanities Department of Informatics Radom Poland Research Institute for Intelligent Computer Systems West Ukrainian National Unversity Ternopil Ukraine

ISBN: (纸本)9798350396119

This paper deals with the problem of detecting the malware by using emulation approach. Modern malware include various avoid techniques, to hide its anomaly actions. Advantages of using sandbox and emulation technologies are described. Various anti-emulation techniques that are used in modern malware considered. Obfuscation as one primary approach to hide malware malicious actions described and discussed. State of emulator is presented, and the advantages of its usage are covered. Distributed model for malware detection is considered. Basic emulator and its current capabilities presented. Prepared files that represent malware are described. Experimental results for developed files that differs with included avoid techniques are presented. Disadvantages of proposed approach is described. Future research and sandbox improvement are described. © 2023 IEEE.

关键词： anti-emulation techniques malware detection obfuscation techniques sandbox

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Investigating Efficacy of Perplexity in Detecting LLM-Generated Code

arXiv

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arXiv 2024年

作者： Xu, Jinwei Zhang, He Yang, Yanjin Cheng, Zeru Lyu, Jun Liu, Bohan Zhou, Xin Yang, Lanxin Bacchelli, Alberto Chiam, Yin Kia Chiew, Thiam Kian State Key Laboratory of Novel Software Technology Software Institute Nanjing University Nanjing210008 China Department of Informatics University of Zürich Zürich8006 Switzerland Department of Software Engineering Faculty of Computer Science and Information Technology University of Malaya Kuala Lumpur50603 Malaysia

Large language model-generated code (LLMgCode) has become increasingly prevalent in software development. Many studies report that LLMgCode has more quality and security issues than human-authored code (HaCode). It is common for LLMgCode to mix with HaCode in a code change, while the change is signed by only human developers, without being carefully checked. Many automated methods have been proposed to detect LLMgCode from HaCode, in which the perplexity-based method (PERPLEXITY for short) is the state-of-the-art method. However, the efficacy evaluation of PERPLEXITY has focused on the detection accuracy. In this article, we are interested in whether PERPLEXITY is good enough in a wider range of realistic evaluation settings. To this end, we devise a large-scale dataset that includes 11,664 HaCode snippets and 13,164 LLMgCode snippets, and based on that, we carry out a family of experiments to compare PERPLEXITY against feature-based and pre-training-based methods from three perspectives: (1) detection accuracy in terms of programming language, degree of difficulty, and scale of solution, (2) generalization capability, and (3) inference efficiency. The experimental results show that PERPLEXITY has the best generalization capability while it has low accuracy and efficiency in most cases. Based on the experimental results and detection mechanism of PERPLEXITY, we discuss implications into both the strengths and limitations of PERPLEXITY, e.g., PERPLEXITY is unsuitable for high-level programming languages while it has good interpretability. As the first large-scale investigation on detecting LLMgCode from HaCode, this article provides a wide range of evidence for future improvement. Copyright © 2024, The Authors. All rights reserved.

关键词： High level languages

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Scheduling Periodic Real-Time Tasks with Inter-Task Synchronisation

Scheduling Periodic Real-Time Tasks with Inter-Task Synchron...

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Mediterranean Conference on Embedded Computing (MECO)

作者： Luká š Kohú tka Institute of Informatics Information Systems and Software Engineering Slovak University of Technology in Bratislava Bratislava Slovakia

This paper presents a new FPGA-based task scheduler that has a dedicated support of periodic hard real-time tasks in addition to aperiodic tasks. Whenever a period of a periodic task is elapsed, the task is scheduled automatically. The proposed scheduler is using Earliest Deadline First (EDF) algorithm. For task synchronisation, the scheduler supports temporary suspension of tasks with automatic resumption of tasks. Thanks to FPGA implementation of the scheduler and its priority queues, the scheduler operations take two clock cycles regardless of the number of tasks. The paper contains synthesis results for Intel FPGA Cyclone V.

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Data Trading and Monetization: Challenges and Open Research Directions 23

Data Trading and Monetization: Challenges and Open Research ...

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Proceedings of the 7th International Conference on Future Networks and Distributed Systems

作者： Qusai Ramadan Zeyd Boukhers Muath Alshaikh Christoph Lange Jan Jurjens Institute of Software Engineering University of Koblenz Germany Fraunhofer Institute for Applied Information Technology FIT Germany and University Hospital of Cologne Germany College of Computing and Informatics Saudi Electronic University Kingdom of Saudi Arabia Fraunhofer Institute for Applied Information Technology FIT Germany and RWTH Aachen University Germany University of Koblenz Germany and Fraunhofer-Institute for Software and Systems Engineering ISST Germany

ISBN: (纸本)9798400709036

Traditional data monetization approaches face challenges related to data protection and logistics. In response, digital data marketplaces have emerged as intermediaries simplifying data transactions. Despite the growing establishment and acceptance of digital data marketplaces, significant challenges hinder efficient data trading. As a result, few companies can derive tangible value from their data, leading to missed opportunities in understanding customers, pricing decisions, and fraud prevention. In this paper, we explore both technical and organizational challenges affecting data monetization. Moreover, we identify areas in need of further research, aiming to expand the boundaries of current knowledge by emphasizing where research is currently limited or lacking.

关键词： Data Exchange

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Leveraging Big Data for Effective Healthcare Management with Artificial Intelligence 1

Leveraging Big Data for Effective Healthcare Management with...

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1st International Conference on Artificial Intelligence for Innovations in Healthcare Industries, ICAIIHI 2023

作者： Dubey, Krati Kasar, Chaitali B. Thulluri, Guravaiah Yesugad, Anuradha Karishma, Mehaboob Padhi, Dipanjali Manipal University Jaipur Department of Information Technology Jaipur India Dr. D. Y. Patil Institute of Technology Department of Electronics and Telecommunication Engineering Pune411018 India Embedded Senior Software Developer Sak Informatics Hyderabad India Pune India Sir C R R College Department of Computer Application Eluru India Dhole Patil College of Engineering Department of Electronics & Telecommunication Engineering Pune India

ISBN: (纸本)9798350330915

To improve clinical judgment, resource allocation, and patient outcomes, this study investigates the integration of big data with artificial intelligence (AI) for medical management. Utilizing a descriptive design with an emphasis on secondary data collecting, the study adopts an interpretive perspective and a deductive approach. Data collection, AI algorithm implementation, integration into the system, and infrastructure issues are all included in the technical setup. Accuracy, sensitivity, quickness of processing, and scalability are examples of performance measures, and the influence on patients and healthcare providers is highlighted by user viewpoints and experiences. Informed permission, data security, and legal compliance are all included in the ethical considerations. The results highlight the potential advantages of data-driven medical services, but they also highlight how crucial ethical precautions and user acceptance are. Upcoming studies ought to concentrate on improving algorithms, protecting privacy, and evaluating long-term effects © 2023 IEEE.

关键词： artificial intelligence big data clinical decision support ethical considerations healthcare management

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Lessons Learned from the Smart City Concept Implementation in West Lombok Regency, West Nusa Tenggara Province

Lessons Learned from the Smart City Concept Implementation i...

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International Conference on ICT For Smart Society (ICISS)

作者： Wikan Danar Sunindyo Alfrojems Knowledge and Software Engineering Research Group School of Electrical Engineering and Informatics Bandung Institute of Technology Bandung Indonesia Indonesia Business Coalition for Women Empowerment South Jakarta Indonesia

Accelerating regional economic growth is needed to be able to catch up with a region, especially if the region has economic potential, especially in terms of natural capital, such as a beautiful environment. However, in practice, a development process will experience obstacles as an inseparable part. This condition certainly requires appropriate treatment efforts based on empirical evidence data. This also happened to West Lombok. Where in fact the regions that get the opportunity to become Smart City pilots certainly have a positive impact, but the challenges that must be carried out also go hand in hand with the process of implementing these efforts. Referring to this background, the purpose of this research is to be able to explore and analyze the challenges experienced by West Lombok in implementing the Smart City program in its region. The method used is qualitative with data collection techniques in the form of documentation studies, observations, interviews, and focus group discussions. This study involved 50 informants with various backgrounds but still in accordance with the characteristics of the informants determined by the researcher through the use of purposive sampling technique. The results of this study are that there are four challenges that need to get more attention from the local government of West Lombok and its stakeholders as an effort to realize West Lombok as a smart city. The four challenges include policy, infrastructure, human capital, and environment. The need for strategic efforts carried out by West Lombok to be able to encourage the achievement of the target of becoming a smart city in Indonesia, especially in West Nusa Tenggara Province.

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Patterns of Remote Work Environments 22

Patterns of Remote Work Environments

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Proceedings of the 27th European Conference on Pattern Languages of Programs

作者： Kristian Toldy Waheedullah Sulaiman Khail Valentino Vranić Institute of Informatics / Faculty of Informatics and Information Technologies / Information Systems and Software Engineering Slovak University of Technology in Bratislava Slovakia Helmholtz-Zentrum Berlin für Materialien und Energie Gmbh Germany

ISBN: (纸本)9781450395946

People are more and more in a position to work remotely. They face the same problems of establishing and running remote work environments over and over again. In order to help them a bit, six organizational patterns of remote work environments are presented in this paper: Unofficial Meetings, Remote Mentor, Unified Communication Channels, Standard Operating Procedures, Information Hub, and Cut Meetings. The patterns come from a firsthand remote work experience obtained in a company focusing on quality assurance through a crowd testing methodology where software companies get real users to test their newest products.

关键词： organizational patterns agile distributed teams communication meeting remote work

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Design Amharic Text Sentiment Analysis Model Using Machine Learning Techniques. In Case of Restaurant Reviews

Design Amharic Text Sentiment Analysis Model Using Machine L...

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Information and Communication technology for Development for Africa (ICT4DA), International Conference on

作者： Birku Gedif Abebe Alemu Yibeltal Assefa Shegaw Nibret Information Science College Of Informatics University of Gondar Computer Science College Of Informatics University of Gondar Software Engineering Kombolcha Institute of Technology Wollo University ICT4D Research Center Bahir Dar Institute of Technology Bahir Dar University

Sentiment analysis is a type of natural language processing for tracking the attitude of the public about a particular product, service or topic. It is also highly challenging as natural language processing research topic, and covers many novel sub-problems. Now business organizations and academics are putting forward their efforts to find the best system for sentiment analysis. The focus of this study was an Amharic unstructured restaurant review on the web. The objective of the paper was to design Amharic text sentiment analysis model using supervised machine learning techniques and evaluate the performance of classifiers. This paper explored the supervised machine learning classification approaches (naive Bayes, support vector machine and k-nearest neighbor) with different feature selection schemes to obtain a sentiment analysis model for domain specific restaurant review dataset at sentence level. The proposed model has the following components: Data preparation, preprocessing such as tokenization, normalization, filter stop words, feature extraction and selection to prepare feature vector, polarity classification. Performance analysis carried out on classifiers, based on n-grams proposed. From the results of the experimental studies, all algorithms are known to be highly effective classifiers, and are able to achieve good accuracy in this experiment. The experiments show that Term frequency (TF) and the TF -IDF scheme gives maximum accuracy 80.43 % and 79.49 % respectively for SVM in bigram features. Term frequency and term occurrence also give maximum accuracy 78.37 % and 78.00 % respectively for Naive Bayes classifier at bigram features. TF-IDF also give maximum accuracy 78.00% for KNN at 4-gram. The challenge was opinion holders sometimes give objective text to express their opinion, but the classifier did not identify those facts from opinions. These kinds of complexities of natural languages make sentiment mining systems more challenging and to resolving t

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A Teaching Materials Recommendation System Considering Individual Characteristics

A Teaching Materials Recommendation System Considering Indiv...

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IIAI International Conference on Advanced Applied informatics (IIAIAAI)

作者： Chengjiu Yin Ryoya Shiroki Lin Lin Huiyong Li Research Institute for Information Technology Kyushu University Fukuoka Japan Graduate School of System Informatics Kobe University Kobe Japan School of Software Technology and DUT-RU International School of Information Science and Engineering Dalian University of Technology Dalian China

ISBN: (数字)9798350377903

ISBN: (纸本)9798350377910

In this study, we proposed and implemented a combined recommendation system by utilizing both learning log data, which contributes to improving learning performance, and learning style questionnaire, which contributes to increasing learning motivation. We also conducted an empirical experiment to evaluate the effect of the proposed recommendation system on learning performance, read efficiency, and perception of the proposed system. Students learned the same teaching material from the Commercial Law course. They were divided into three groups and received a page recommendation of the teaching material: recommended by only VARK data, recommended by only learning log, and recommended by both of V ARK data and learning log data. The findings show that the students who received the combined recommendation increased their mean values of learning performance and reading efficiency in the experiment and reported the highest improvement in usefulness and satisfaction on the system. On the other hand, the students who received the log data-only recommendation didn't increase their mean values of learning performance and reading efficiency and reported the lowest improvement of usefulness and satisfaction on the system. The students' post-questionnaires on their learning motivation and suggestions for learning recommendation system are also discussed.

关键词： Surveys Commercial law Education informatics Recommender systems Testing

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