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36th international conference on software engineering and Knowledge engineering, SEKE 2024

作者： Hu, Xuyan Gu, Yicheng Qi, Zhengwei Shanghai Jiao Tong University Shanghai China

ISBN: (纸本)1891706594

GPUs, as crucial tools for intensive computing tasks, are primarily used for rendering and computation. However, due to the high cost of GPUs and their frequent updates, owning powerful local GPUs is considered a luxury. Offloading tasks to the cloud is an effective solution. This method allows users to leverage the powerful capabilities of cloud-based high-performance computing resources to perform complex rendering tasks more quickly and cost-effectively. However, there has not yet been a solution that simultaneously considers both rendering and computation without requiring any modifications to local applications. This paper introduces gHermes, an application-unaware acceleration solution that automatically generates code to intercept rendering and computing tasks, overcoming the limitations of existing technologies. Additionally, for computational tasks, gHermes also enables fine-grained control of GPU utilization. Experimental results show that gHermes can handle both computing and rendering tasks efficiently. While ensuring the Quality of Service (QoS) requirements for rendering tasks (30-60 FPS), it effectively utilizes GPU resources for computation services. © 2024 Knowledge Systems Institute Graduate School. All rights reserved.

关键词： Rendering (computer graphics)

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Bringing Industry-Grade Code Quality and Practices into software engineering Education (Doctoral Consortium) 24

Bringing Industry-Grade Code Quality and Practices into Soft...

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24th Koli Calling

作者： Birillo, Anastasiia JetBrains Res Belgrade Serbia Univ Utrecht Utrecht Netherlands

ISBN: (纸本)9798400710384

Using professional development tools and practices is an essential part of being a programmer. However, beginners often struggle with professional tools. In this work, we ask the question: "How can we adapt professional programming tools to improve software engineering education?" and aim to find efficient ways to solve this problem.

关键词： Code Quality Assessment Code Formatting LLMs Generative AI Next-Step Hints

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Design and Implementation of System Communication computing Acceleration Algorithm under Cloud Edge Collaboration

Design and Implementation of System Communication Computing ...

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international conference on Electronic engineering and Information Systems (EEISS)

作者： Ye, Qinghe Wang, Yue Wu, Chunpeng Zheng, Min Lin, Long Zhou, Fei State Grid Smart Grid Res Inst Co Ltd State Grid Lab Grid Adv Comp & Applicat Beijing Peoples R China

ISBN: (纸本)9798350351040;9798350351033

The security software platform based on the support body has increasingly complex application functions and also faces massive data transmission, which puts higher requirements on the performance of the system. At present, most secure computing platforms are based on distributed and redundant communication architectures, and lack appropriate failure management mechanisms to effectively utilize the fault tolerance of redundant communication architectures. In response to the problems faced by existing support managed secure computing platforms, this article conducted a study on the fast management mechanism of redundant communication architecture in support managed secure computing platforms. It discussed the implementation of different acceleration algorithms for system communication computing based on cloud edge collaboration, and experiments showed that the accuracy of system communication LSII (Locality Sensitive Hashing) technology acceleration was higher than other algorithms. The accuracy of cloud computing platforms based on LS1I technology was 0.92. At the same time, cloud edge collaboration can improve the resource utilization of system communication.

关键词： System Communication Calculation Cloud Edge Collaboration Accelerate Algorithm Design Cloud computing

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Application of Computer software in Chemical Data Processing using Spider Monkey Optimization Algorithm 2

Application of Computer Software in Chemical Data Processing...

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2nd IEEE international conference on Networks, multimedia and Information Technology, NMITCON 2024

作者： Rana Veer Samara Sihman Bharattej, R. Rupavath, Rana Veer Samara Sihman Brahmatej Hussein, Abbas Hameed Abdul Anjaneyulu, Madugula Upendra Roy, B.P. Saint Leo University Department of Computer Science St Leo United States Indiana Wesleyan University Marion United States Ahl Al Bayt University College of Pharmacy Karbala Iraq Gokaraju Rangaraju Institute of Engineering and Technology Bachupally Department of Ai&ml Hyderabad India Channabasaveshwara Institute of Technology Gubbi Department of Electronics and Communication Engineering Tumkur India

ISBN: (纸本)9798350372892

The development of chemical-based products and functional materials is crucial for modern technologies, yet it often entails significant costs and time delays. Artificial intelligence and machine learning present novel approaches to leverage data for addressing these challenges;however, they encounter specific hurdles in the chemical domain. To address these issues, a software platform has been introduced to facilitate training and development of Recurrent Neural Networks (RNN). This platform incorporates the Spider Monkey Optimization (SMO) algorithm to optimize model's hyperparameters, including neurons number, rate of learning, and activation function. This software package goes beyond neural network training and development by encompassing design and operating-parameter optimization, essential aspects of chemical engineering processes. Within this framework, the weights that were optimized and bias obtained from neural network were stored and utilized in other SMO process for optimizing important process variables, like swiftness and temperature, according to user specifications. © 2024 IEEE.

关键词： software packages

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AI-Driven Learning Management Systems:Modern Developments, Challenges and Future Trends during theAge of ChatGPT

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Computers, Materials & Continua 2024年第8期80卷 3289-3314页

作者： Sameer Qazi Muhammad Bilal Kadri Muhammad Naveed Bilal AKhawaja Sohaib Zia Khan Muhammad Mansoor Alam Mazliham Mohd Su’ud Department of Computer Science Faculty of EngineeringScience and TechnologyIQRA UniversityKarachi75500Pakistan College of Computer and Information Sciences Prince Sultan UniversityRiyadh11586Saudi Arabia Faculty of Engineering Department of Electrical EngineeringIslamic University of MadinahP.O.BOX 170Madinah41411Saudi Arabia Faculty of Engineering Department of Mechanical EngineeringIslamic University of MadinahP.O.BOX 170Madinah41411Saudi Arabia Faculty of Computing Riphah International UniversityIslamabad46000Pakistan Faculty of Computing and Informatics(FCI)Multimedia University Cyberjaya63100Malaysia Faculty of Engineering and Information Technology School of Computer ScienceUniversity of Technology SydneySydneyNSW 2007Australia

COVID-19 pandemic restrictions limited all social activities to curtail the spread of the *** foremost and most prime sector among those affected were schools,colleges,and *** education system of entire nations had shifted to online education during this *** shortcomings of Learning Management Systems(LMSs)were detected to support education in an online mode that spawned the research in Artificial Intelligence(AI)based tools that are being developed by the research community to improve the effectiveness of *** paper presents a detailed survey of the different enhancements to LMSs,which are led by key advances in the area of AI to enhance the real-time and non-real-time user *** AI-based enhancements proposed to the LMSs start from the Application layer and Presentation layer in the form of flipped classroom models for the efficient learning environment and appropriately designed UI/UX for efficient utilization of LMS utilities and resources,including AI-based *** layer enhancements are also required,such as AI-based online proctoring and user authentication using *** extend to the Transport layer to support real-time and rate adaptive encrypted video transmission for user security/privacy and satisfactory working of *** also needs the support of the Networking layer for IP-based geolocation features,the Virtual Private Network(VPN)feature,and the support of software-Defined Networks(SDN)for optimum Quality of Service(QoS).Finally,in addition to these,non-real-time user experience is enhanced by other AI-based enhancements such as Plagiarism detection algorithms and Data Analytics.

关键词： Learning management systems chatbots ChatGPT online education Internet of Things(IoT) artificial intelligence(AI) convolutional neural networks natural language processing

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20th international conference on Foundations of Computer Science, FCS 2024, and 20th international conference on Frontiers in Education, FECS 2024, held as part of the World Congress in Computer Science, Computer engineering and Applied computing, CSCE 2024

20th International Conference on Foundations of Computer Sci...

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20th international conference on Foundations of Computer Science, FCS 2024, and 20th international conference on Frontiers in Education, FECS 2024, held as part of the World Congress in Computer Science, Computer engineering and Applied computing, CSCE 2024

ISBN: (纸本)9783031859298

The proceedings contain 38 papers. The special focus in this conference is on Foundations of Computer Science. The topics include: Exploring Efficient but Intricate Delivery Truck Routing Heuristics in Supply Chain Management;a Novel Simple Data Structure for Selecting, Inserting, and Deleting in Square Root Time;Autosymmetry Using GF(2) Matrices;TOIChain™: A Proposal for High Performance Tamper Resistant Transactions Without Scaling Limits;searching Real Numbers in Constant Time;MultiMap Implementation in OpenJDK;optimization of the Floyd-Warshall Shortest Path Algorithm;triangle Packing in Graphs with Bounded Degree;navigating the Ethical Landscape of Big Data Collection and Analysis;Assessing ABET’s Outcomes Through a software engineering Capstone Course;ECAF: Educational Cybersecurity Assessment Framework for Small Businesses;Leveraging Chat-GPT to Generate Educational Assessment Materials for software engineering;a Longitudinal Study to Investigate the Impact of a Service-Learning Course on Its Participants;tertiary Mathematics Students in Different Learning Environments: Perceptions and Achievement;using Logical Fallacies to Educate Computer Science Students;Assessing ChatGPT for Algorithm Time Complexity Education;capstone Projects as Ventures to New Knowledge;exploratory Physics Laboratory Experiments;A Personal Tutoring Bot with VR/AR Tools;ES4AL: A Website for Effectiveness Study for Algorithm Learning in Computer Science;INDRA: A Drone Penetration Testing Platform for Cybersecurity Education;Exploring the Potential of Generative AI in Education: Opportunities, Challenges, and Best Practices for Classroom Integration;digital Badging as a Motivator in an Undergraduate Course;Coding Process Visualizations for Improved Learning and Academic Integrity in CS1;OBDev: Wireless On Board Development Environment for Raspberry Pi Pico W;unravelling Dropout Intentions: Multifaceted Factors Influencing Student Retention in Computer Science Education;to Hack or Not to H

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Proceedings - 2024 ACM/IEEE 46th international conference on software engineering: software engineering Education and Training, ICSE-SEET 2024

Proceedings - 2024 ACM/IEEE 46th International Conference on...

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46th international conference on software engineering: software engineering Education and Training, ICSE-SEET 2024

ISBN: (纸本)9798400704987

The proceedings contain 38 papers. The topics discussed include: assessing the impact of hints in learning formal specification;assessing AI detectors in identifying AI-generated code: implications for education;building collaborative learning: exploring social annotation in introductory programming;teaching software development for real-world problems using a microservice-based collaborative problem-solving approach;gamifying a software testing course with continuous integration;adopting an agile approach for reflective learning and teaching;experiences with summer camp communication via discord;using accessibility awareness interventions to improve computing education;training app developers in a software studio: the business nano challenge experience;breaking barriers: investigating the sense of belonging among women and non-binary students in software engineering;and an empirical study of the content and quality of sprint retrospectives in undergraduate team software projects.

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Space environment simulation for LEO spacecrafts devoted to a multimedia constellation 3

Space environment simulation for LEO spacecrafts devoted to ...

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2024 3rd international conference on Aerospace and Control engineering, ICoACE 2024

作者： Jiang, Hu Cai, Zhiming Cao, Caixia Innovation Academy for Microsatellites Chinese Academy of Sciences Shanghai201304 China Shanghai Engineering Center for Microsatellites Shanghai201304 China

A constellation consisting of more than one thousand LEO satellites has been proposed in China in recent years. The purpose of this constellation is to provide an effective solution for space-based multimedia networks all over the world. The operational orbit is roughly defined as follows. Altitude is about one thousand kilometers, the inclination is about 90 degrees, and tens of orbit planes are designed for satellites to deploy in space. The space environment for satellites in such orbit altitude is particularly focused on to carry out such a huge space engineering successfully. Herein, such radiation causes as the Earth radiation belt, solar proton, and cosmic ray are considered. Based on internationally advanced space environment assessment software, SPENVIS, with the novelty of a multimedia network deployed at 1000 km altitude, the practical constraints to be suitable for tough space environment situations are simulated. Based on radiation simulations, it has shown that if the 7-year lifespan for LEO satellites is concerned, there is about 50.4 krad radiation dosage after 3mm Aluminium shielding;there is about 20.9 krad dosage with 6mm Aluminium shielding;and there is about 16.5 krad dosage with 9mm Aluminium shielding. Considering the design margin for radiation dosage, for 7-year lifespan satellites, the anti-total dose capacity is about 50.4×2 krad total dose with 3 mm Aluminium shielding;there is about 20.9×2 krad dosage with 6 mm Aluminium shielding;and there is about 16.5×2 krad total dose with 9 mm Aluminium shielding. If only the above space environment requirements are met, the proposed multimedia constellation would be in operation safe and sound in space during the lifespan of the satellites in question. © 2025 Institute of Physics Publishing. All rights reserved.

关键词： Cosmic rays

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DomainVoyager: Embracing The Unknown Domain by Prompting for Automatic Augmentation

DomainVoyager: Embracing The Unknown Domain by Prompting for...

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IEEE international conference on multimedia and Expo (ICME)

作者： Liu, Chuang Zhu, Haogang Su, Xiu Beihang Univ State Key Lab Software Dev Environm Lab Beijing Peoples R China Beihang Univ Zhongfa Aviat Inst Key Lab Data Sci & Intelligent Comp 166 Shuanghongqiao St Hangzhou 311115 Peoples R China Zhongguancun Lab Beijing Peoples R China Cent South Univ Big Data Inst Changsha Peoples R China

ISBN: (纸本)9798350390155;9798350390162

For medical image analysis, domain generalization (DG) faces significant challenges due to variances in data across medical imaging devices. Addressing this, we introduce Prompt Guided Domain Aligning Augmentation (PGDAA), a novel approach that harnesses Large Language Models (LLMs) to iteratively refine data augmentation sequences in DG for medical segmentations. Specifically, by harnessing the LLM's advanced capabilities in interpreting and responding to specific prompts, PGDAA iteratively voyages the parameter searching space for data augmentation, identifying optimal augmentation sequences. In each searching round, the LLM leverages provided prior data augmentation methods, their parameters, and corresponding evaluation results to acquire a sufficient performance memory bank, thereby proposing more effective augmentation sequences to significantly narrowing inter-domain gaps. Notably, this integration of LLMs in DG represents a pioneering application in the field, which adds minor training parameters and can be easily combined with other DG benchmarks for further improvements. Comprehensive experiments reveal our method outperforms the baseline by 4.47% and 5.08% on Fundus and Prostate datasets, achieving 90.10% and 89.28% accuracy, respectively.

关键词： medical image domain generalization prompt engineering data augmentation

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software Defect Prediction using Machine Learning 18

Software Defect Prediction using Machine Learning

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18th INDIAcom;11th international conference on computing for Sustainable Global Development, INDIACom 2024

作者： Setia, Sonia Ravulakollu, Kiran Kumar Verma, Kimmi Garg, Setu Mishra, Sunil Kumar Sharan, Bhagwati Sharda University School of Engineering and Technology Department of Computer Science and Engineering Greater Noida India Woxsen University School of Technology Hyderabad India Delhi Technical Campus Greater Noida India Its Engineering College Ece Department Greater Noida India Accurate Institute of Management and Technology Greater Noida India Srm University School of Engineering and Sciences Department of Computer Science and Engineering AP Guntur India

ISBN: (纸本)9789380544519

A software's most crucial component is its quality. software Defect Prediction has gained a lot of traction in recent years and has the potential to directly impact quality. software quality is greatly impacted by defective software modules, which may result in budget overruns, missed deadlines, and significantly increased maintenance costs. There are diverse phases executed to predict the defect in software such as to employ the data for input, pre-process it, extract the attributes and classify the defect. This research work presents numerous algorithms, namely Gaussian naive bayes (GNB), Bernoulli NB, random forest (RF) and multi-layer perceptron (MLP), for predicting the software defect. This work also focuses on developing an ensemble algorithm to enhance the efficacy of predicting the defects. This ensemble consisted of a Principal Component Analysis (PCA) algorithm with class balancing. Diverse parameters such as accuracy, precision and recall are employed for analyzing the results. © 2024 Bharati Vidyapeeth, New Delhi.

关键词： Bernoulli Naive Bayes Class Balancing Gaussian Naive Bayes PCA Random Forest software Defect

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