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检索条件"主题词=software algorithms"

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Experiences and Proposals of Use of Generative AI in Advanced software Courses

Experiences and Proposals of Use of Generative AI in Advance...

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IEEE Education Engineering (EDUCON)

作者： Daniel Palacios-Alonso Jaime Urquiza-Fuentes J. Ángel Velázquez-Iturbide Julio Guillén-García Department of Computing and Statistics Universidad Rey Juan Carlos Madrid Spain

ISBN: (数字)9798350394023

ISBN: (纸本)9798350394030

The last year, we have witnessed the popularization of generative artificial intelligence. Its output includes text, code, image, audio, speech, voice, music, and video. Therefore, it impacts education courses where students are required to elaborate on any of these artifacts. In particular, the generation of code affects informatics courses, where assignments usually ask students to develop and deliver programming code. The impact of generative artificial intelligence on informatics courses has been mainly studied for introductory programming courses. These studies have shown that generative artificial intelligence is able to produce highly sophisticated programs, but also that its results and rationale can be inaccurate. Moreover, the impact of generative artificial intelligence has not been studied for other informatics subjects. In this paper, we present our preliminary experience and proposals on three advanced software courses, namely video games, advanced algorithms and language processors. For the video games course, we present the opportunities of use of generative artificial intelligence and the results of a survey conducted with students on their use to obtain different media products. For the algorithms course, we present the result of a session driven by the instructor on different design techniques, showing the merits and demerits of the answers generated. For the language processors course, a proposal of use of generative artificial intelligence is presented, broken down into the parts of a typical language processor. The paper concludes with some suggestions for instructors.

关键词： Surveys Video games Program processors Codes Generative AI software algorithms software

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Hardware-software Co-Design for Path Planning by Drones

Hardware-Software Co-Design for Path Planning by Drones

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IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Ayushi Dube Omkar Patil Gian Singh Nakul Gopalan Sarma Vrudhula School of Computing and Augmented Intelligence Arizona State University Tempe United States

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

This work consists of two main components: designing a hardware-software co-design, MT + , for adapting the Mikami-Tabuchi algorithm for on-board path planning by drones in a 3D environment; and development of a specialized custom hardware accelerator CDU, as a part of MT + , for parallel collision detection. Collision detection is a performance bottleneck in path planning. MT + reduces the delay in path planning without using any heuristic. A comparative analysis between the state-of-the-art path planning algorithm A* and Mikami-Tabuchi is performed to show that Mikami-Tabuchi is faster than A* in typical real-world environments. In custom-generated environments, path planning using Mikami-Tabuchi shows a latency improvement of 1.7× across varying average sizes of obstacles and 2.7× across varying obstacle density over state-of-the-art path planning algorithm, A*. Further, the experiments show that the co-design achieves speedups over a full software implementation on CPU, averaging between 10% to 60% across different densities and sizes of obstacles. CDU area and power overheads are negligible against a conventional single-core processor.

关键词： Three-dimensional displays software algorithms Parallel processing Path planning software Delays Collision avoidance Hardware acceleration Intelligent robots Drones

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Enhanced DDoS Detection in software Defined Networking Using Ensemble-Based Machine Learning

Enhanced DDoS Detection in Software Defined Networking Using...

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International Conference on Electrical Engineering and Information & Communication Technology (ICEEICT)

作者： Ms. Bithi Md. Alamgir Hossain Md. Kawsar Ahmed Rabeya Sultana Ishtiaq Ahammad Md Shihabul Islam Department of Computer Science and Engineering Prime University Dhaka Bangladesh Department of Computer Science and Engineering Northern University Bangladesh Dhaka Bangladesh

ISBN: (数字)9798350385779

ISBN: (纸本)9798350385786

The burgeoning adoption of software Defined Networking (SDN) has revolutionized network management, yet it introduces unprecedented challenges, notably the susceptibility to Distributed Denial-of-Service (DDoS) attacks. Recognizing this imperative, our research delves into fortifying SDN security, proposing a novel approach that marries machine learning prowess with the intricacies of SDN architecture. This study endeavors to bolster DDoS detection within SDN environments, strategically leveraging an ensemble-based Random Forest (RF) algorithm and Recursive Feature Elimination. The overarching goal is to enhance the efficacy of SDN security measures, providing a dynamic defense against evolving DDoS threats. An implementation process unfolds through comprehensive data preprocessing, featuring the strategic selection of key features via Recursive Feature Elimination. Central to our approach is the application of an ensemble-based Random Forest algorithm, which has been rigorously trained using a dedicated dataset tailored for software Defined Networking. A comprehensive assessment follows, where critical performance indicators such as Recall, Accuracy, Precision, F-1 Score, and Area Under the Curve (AUC) substantiate the reliability of our method. The outcome is a paradigm shift in DDoS detection within SDN. Our ensemble-based RF algorithm not only exhibits commendable accuracy but also outperforms traditional methods across key metrics. The strategic feature selection contributes not only to heightened efficiency but also bolsters the overall resilience of SDN networks against DDoS incursions. Beyond the confines of conventional methodologies, this model, attaining almost 100% accuracy, heralds a milestone in SDN security.

关键词： Radio frequency Heuristic algorithms software algorithms Feature extraction Denial-of-service attack Security software defined networking

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Research on Fault Mode Analysis Method of Nuclear I&C software Based on Time Automata

Research on Fault Mode Analysis Method of Nuclear I&C Softwa...

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Prognostics and System Health Management Conference (PHM-Qingdao)

作者： Genhua Liang Yong Li Yanqun Wu Fei Yang Zhichuan Zeng Xuanlin Zhu HongXin Deng National key Laboratory of Nuclear Reactor Technology Nuclear Power Institute of China Chengdu China School of Electronic and Electrical Engineering Shanghai University of Engineering Science Shanghai China

ISBN: (数字)9798350354010

ISBN: (纸本)9798350354027

This paper presents a novel fault mode analysis method for nuclear instrumentation and control (I&C) software based on timed automata. The proposed approach addresses the limitations of traditional fault analysis techniques in handling complex, real-time systems by accurately capturing the dynamic characteristics and intricate interaction patterns of nuclear I&C software. Key contributions include: (1) development of a timed automata-based modeling framework tailored for nuclear I&C software; (2) design of a comprehensive fault mode library compatible with timed automata models; and (3) implementation of an automated fault mode analysis algorithm leveraging model checking techniques. The method's efficacy is demonstrated through a case study on a digital reactor protection system, specifically the Reactor Coolant Pump speed protection subsystem. Results show significant improvements in fault mode identification rates, particularly for time-related faults, and enhanced capabilities in quantitative analysis and dynamic behavior capture compared to traditional methods. This approach provides a more rigorous and systematic tool for improving the reliability and safety of digital I&C systems in nuclear power plants, with potential applications in other safety-critical domains.

关键词： Analytical models Systematics Statistical analysis Instruments software algorithms Automata software software reliability Protection Inductors

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Detection of Link Fabrication Attacks in software-Defined Networks using DBSCAN

Detection of Link Fabrication Attacks in Software-Defined Ne...

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International Conference on Computing and Networking Technology (ICCNT)

作者： Abirami Ganesh Lakshana Ravishankar Nithiyashri Sankar Meignanamoorthi D V. Vetriselvi Department of Computer Science and Engineering College of Engineering Guindy Anna University Chennai India

ISBN: (数字)9798350370249

ISBN: (纸本)9798350370270

Topology poisoning attacks pose a significant security threat to software-Defined Networking (SDN) environments. Centralized control in SDN brings about vulnerabilities, such as the susceptibility to topology poisoning attacks. The relay attack disrupts network traffic routing, leading to potential data breaches and degraded network performance. To maintain the integrity and security of SDN operations, it is crucial to ensure accurate network topology information. Topology poisoning attacks often mimic legitimate network behavior which makes it complex to detect them. The increasing deployment of SDNs in 5G networks, IoT, and cloud services increases the necessity of addressing these attacks. We propose the detection of fake links using link latency-based anomaly detection system using Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm. The true positive percentage for detecting fake links obtained was 95.0% and true negative percentage was 99.60%.

关键词： Fabrication Network topology Noise software algorithms Telecommunication traffic Routing Topology Security software defined networking Relays

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Examining the Accuracy of AI Detection software Tools in Education

Examining the Accuracy of AI Detection Software Tools in Edu...

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Intelligent Data Science Technologies and Applications (IDSTA), International Conference on

作者： Mohanad Halaweh Ghaleb El Refae College of Business Al Ain University Al Ain UAE

ISBN: (数字)9798350354751

ISBN: (纸本)9798350354768

Educators have raised concerns about the utilization of ChatGPT in generating unoriginal text and the possibility of plagiarism. To address these concerns, various AI text detection software tools have been developed to evaluate whether a text is AI generated or human generated. The aim of this research is to empirically examine the accuracy of AI detection tools in identifying AI-generated texts. An experiment was conducted using textual data generated by ChatGPT, which was assessed using Turnitin and four other AI detection tools. Through multiple iterations and interventions, the text was paraphrased by ChatGPT until it appeared original and could not be detected as AI-generated by Turnitin’s AI detection tool. The findings revealed that all the AI detection software tools that were examined failed to detect the AI-generated text by ChatGPT in the final iteration. The findings provide valuable insights that have implications for various stakeholders, including educators, researchers, and AI text detection software developers. Based on the tools examined, educators and researchers do not need to set a specific threshold or percentage, including 0%, to determine what qualifies as acceptable AI-generated text. This is because establishing such a threshold can be misleading, considering the current limitations in the algorithms of these tools. Furthermore, the data generated in this paper can provide a solid basis for replicated research or software testing and assessment. It can be utilized to evaluate the accuracy of alternative AI detection tools and any future advancements in the tools mentioned in this investigation.

关键词： software testing Accuracy Plagiarism software algorithms Text detection Chatbots Solids Stakeholders Artificial intelligence software tools

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USASAT-NGSO-3X Filing Analysis Using ITU-BR GIBC software For Various Orbital Shells

USASAT-NGSO-3X Filing Analysis Using ITU-BR GIBC Software Fo...

引用

IEEE Asia-Pacific Conference on Geoscience, Electronics and Remote Sensing Technology (AGERS)

作者： Fika Triana Meiditomo Sutyarjoko Heroe Wijanto Graduate Program of Regulation and Management of Telecommunication School of Eletrical Engineering Telkom University Bandung Indonesia Regulation and Management of Telecommunication School of Electrical Engineering Telkom University Bandung Indonesia The University Center of Excellence for Intelligent Sensing-IoT School of Electrical Engineering Telkom University Bandung Indonesia

ISBN: (数字)9798331543105

ISBN: (纸本)9798331543112

Interference is a significant problem in satellite communication operations, one of which is between Non-Geostationary Orbit (non-GSO) satellites and Geostationary Orbit (GSO) ground stations. To calculate the impact of this interference, an evaluation of the EPFD (Equivalent Power Flux Density) is carried out, which describes the average power density of the signal received at the receiving station location. This study conducted an in-depth study of the level of interference by signals from the USASAT NGSO-3X satellite in various orbital shells that affect the GSO system. By using the worst-case geometry method, the EPFD calculation can provide valuable insight into the level of interference that occurs. Based on the results of the study, it was concluded that a more in-depth study of the ITU-BR GIBC software algorithm was needed regarding the analysis of EPFD values using the worst-case geometry method. GIBC simulations show inconsistencies in the EPFD values correlated with the values set in Article 22 ITU-R and S.1503-2 ITU-R, both through aggregate and separate orbit examinations, so that a review of the ITU-R S.1503-2 algorithm is needed to ensure that interference between non-GSO satellites and GSO earth stations remains under control within the specified limits.

关键词： Space vehicles Geometry Earth Satellites Aggregates Space technology software algorithms Interference Orbits software

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Cost-sensitive Approach for improving AUC-ROC Curve of software Defect Prediction

Cost-sensitive Approach for improving AUC-ROC Curve of Softw...

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International Seminar on Intelligent Technology and Its Applications (ISITIA)

作者： Rizal Broer Bahaweres Islah Khofifah Nuraini Department of Informatics UIN Jakarta Indonesia

ISBN: (数字)9798350378573

ISBN: (纸本)9798350378580

Defects in software can cause various problems that are detrimental to many parties, from owners and developers to users. Predicting defects in software is one of the crucial factors that must be done before an application is launched. However, often when the prediction process is carried out, misclassification occurs, which causes losses at a later date. Misclassification usually occurs in datasets that are not balanced between majority and minority data. We suggest a combination of neural network (NN) and cost-sensitive method to minimize losses affected by misclassification. The author then compares the results of the evaluation of the proposed model with models without cost sensitivity to find out whether the model's performance has increased. Other classification algorithms such as decision tree (DT), logistic regression (LR), random forest (RF), and SVM will also be evaluated as part of a performance comparison of the proposed model based on AUC and ROC values in five different NASA datasets. The findings show that the cost-sensitive method can increase the AUC value in all datasets with an average increase of 13.6%. Cost-sensitive can overcome classification errors by increasing the AUC value in all models, and the optimal algorithm based on the average score in the proposed of neural network model.

关键词： Support vector machines Seminars Radio frequency Sensitivity software algorithms NASA Prediction algorithms

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Design and Implementation of a Cross-Platform Real-Time Power System Simulation software for the New power system

Design and Implementation of a Cross-Platform Real-Time Powe...

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Intelligent Power and Systems (ICIPS), International Conference on

作者： Ying Huang Yuanhong Lu Jingyue Zhang Jie Zhan Yanjun Zhao Yufeng Hu State Key Laboratory of HVDC Electric Power Research Institute China Southern Power Grid Guangzhou 510663 China Southern Power Grid Guangzhou China CSG Key Laboratory for Power System Simulation Electric Power Research Institute China Southern Power Grid Guangzhou 510663 China Southern Power Grid Guangzhou China Guangdong Provincial Key Laboratory of Intelligent Operation and Control for New Energy Power System Guangzhou 510663 China Southern Power Grid Guangzhou China National Energy Power Grid Technology R&D Centre Guangzhou 510663 China Southern Power Grid Guangzhou China CSG Key Laboratory for Power System Simulation Electric Power Research Institute China Southern Power Grid Guangzhou Guangzhou China

ISBN: (数字)9798331532765

ISBN: (纸本)9798331532772

With the rapid increase in renewable energy installation nodes and the substantial enhancement of switching frequencies in the new power system, this paper proposes a design scheme for a cloud simulation software that employs the Latency Insertion Method (LIM) to decompose large-scale new power system models into several subsystems, enabling multi-platform integrated parallel computing. The self-developed platform meets the demands of ultra-large simulation scales, ultra-small simulation time steps, and massive simulation computations in power systems. Experimental results demonstrate that the accelerated simulation technology, which integrates model segmentation using LIM with multi-core parallel execution, can enhance the simulation speed by up to 858 times while maintaining simulation accuracy. This significantly improves simulation efficiency and is suitable for large-scale simulations of new power systems.

关键词： Renewable energy sources Accuracy Computational modeling Switching frequency software algorithms Random access memory Parallel processing software Real-time systems Power systems

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An Empirical Study on Self-Admitted Technical Debt in Quantum software

An Empirical Study on Self-Admitted Technical Debt in Quantu...

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Asia-Pacific Conference on software Engineering

作者： Yuta Ishimoto Yuto Nakamura Ryota Katsube Naoto Sato Hideto Ogawa Masanari Kondo Yasutaka Kamei Naoyasu Ubayashi Kyushu University Fukuoka Japan Research & Development Group Hitachi Ltd. Kanagawa Japan Waseda University Tokyo Japan

ISBN: (数字)9798331534011

ISBN: (纸本)9798331534028

Quantum computers, which utilize the principles of quantum mechanics, are expected to be applied to a wide range of fields. With the advancement of quantum computer development, a lot of quantum software, which enables the operation of quantum computers, has been developed. It has a distinct nature (e.g., superposition and entanglement of qubits) compared to traditional software, leading to the unique challenges of its development. While prior studies have clarified and defined some unique challenges of quantum software, many remain unclear due to limited research. In this study, we conducted an empirical study of Self-Admitted Technical Debt (SATD) for quantum software. SATD is a type of technical debt, a problem in the code that the developer is aware of. Hence, we conjecture that analyzing SATDs can reveal the unique challenges developers face when developing quantum software. We manually coded 202 comments from the Python® files of the 61 open-source quantum software on GitHub®. The 202 comments correspond to a 95% confidence level with a 5% confidence interval, as in previous studies. The results showed that 88 comments (45.6% of all SATD comments) were quantum-specific SATDs (QSATDs), which require knowledge of quantum computation to repay. Furthermore, we propose a taxonomy for QSATDs. This taxonomy, which consists of four main categories and eight subcategories, classifies QSATDs in terms of quantum-specific aspects such as circuit implementation, backend, and algorithms. Our empirical results are beneficial for quantum software developers, helping them understand implementation areas that require attention. For researchers, our results promote further research, including the exploration of challenges in QSATD repayment.

关键词： Computers Quantum computing Codes Taxonomy software algorithms Qubit Quantum mechanics software Quantum circuit software engineering

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