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People Interconnect - A Platform for Unified Communication

People Interconnect - A Platform for Unified Communication

引用

International conference on ent Computing and Control systems (ICICCS)

作者： Baby Shamini P Kalaivani S N.Sivasankari Chandran G Jency A Sruthi S Computer Science and Engineering R.M.K. Engineering College Electronics and Communication Engineering Rajalakshmi Institute of Technology Electronics and Communication Engineering St.Joseph College of Engineering Electrical and Electronics Engineering DMI College of Engineering Artificial Intelligence and Data Science R.M.K College of Engineering and Technology

ISBN: (数字)9798331512088

ISBN: (纸本)9798331512095

People interconnect was created with the mind set to not just be another communication platform but also to empower a wide range of users, fostering productivity, knowledge sharing and social interaction. People interconnect is an effort for a more modern approach to connect seamlessly through group video calls, screen-sharing, and chatting that leverages advanced technologies such as *** and WebRTC to provide seamless and robust communication solutions. By integrating *** and WebRTC into its architecture, the system offers a wide range of features to facilitate communication and collaboration. *** is employed to enable real-time chat functionality. WebRTC is harnessed for group video calls, offering high quality video conferencing experiences. The inclusion of video calling capability enhances the user experience by enabling face-to-face communication, fostering a more immersive and engaging interaction. Users can initiate video calls with individuals or groups, further enhancing collaboration and ***, the integration of an inbuilt compiler adds a unique dimension to the application, catering to the needs of developers and programmers.

关键词： Productivity Program processors Collaboration Streaming media Control systems User experience software software reliability WebRTC Videoconferences

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A653MSim: An ARINC 653 Multicore Simulator 16th

A653MSim: An ARINC 653 Multicore Simulator

引用

16th EAI International conference on Simulation Tools and Techniques, SIMUTools 2024

作者： Lefoul, Jean-Baptiste de Magalhães, Felipe Gohring Bhatnagar, Brandon Nicolescu, Gabriela Polytechnique Montréal MontrealQC Canada Mannarino Systems & Software Inc. Montreal Canada

ISBN: (纸本)9783031873447

The ARINC 653 standard imposes stringent timing and behavioral requirements on avionic software applications. As multicore systems gain interest in aerospace applications, there is a growing need for tools to aid in their design and implementation. To address this challenge, we propose A653MSim, a simulation solution that enables the validation of multicore ARINC 653-compliant system functionality. Our validation demonstrates that A653MSim not only ensures functional compliance with the ARINC 653 standard but also exhibits linear scalability as the number of simulated cores increases. © ICST Institute for computer Sciences, Social Informatics and Telecommunications engineering 2025.

关键词： Application programs

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Using Social Media as LMS in Terms of Teaching, Evaluating and Course Management in the Perspective of Bangladesh and the Feasibility of it’s Integration

Using Social Media as LMS in Terms of Teaching, Evaluating a...

引用

International conference on Electrical, computer and Communication engineering (ECCE)

作者： Anika Tasnim Islam Tahmid Tahmid Md. Rifat Hasan S.M. Nahid Hasan Computer Science and Engineering Fareast International University Dhaka Bangladesh Computer Science and Engineering Universität Innsbruck Innsbruck Austria

ISBN: (数字)9798350357509

ISBN: (纸本)9798350357516

Learning online has become the most evolving content and approach frontier in a new method of education. In recent times, a well-featured learning management system software is a necessary contrivance for every person associated with an online education system. Some of them use social media as a method of education which doesn’t help them a lot and sometimes fails in serving its purpose of providing quality functioning. From the perspective of Bangladesh, there are many kinds of people here. So, their point of view and essential requirements also differ from one another. So, there should exist a convenient and effective online educational platform or software. Its primary concern could be serving people from all walks of life in a simple, not very difficult, and uncomplicated way. This study has come up with the concept of integrating Learning Management System(LMS) features into social media platforms which means social media like Facebook, YouTube, etc. There will be an option for studying purposes. It will be very beneficial not only to the students but also to the teachers who are in search of a superior online education platform. The study concludes with the statement that considering some conditions and constraints, it is possible to build this proposed integrated system with the assistance of social media platforms

关键词： Surveys Learning management systems Electric potential Video on demand Social networking (online) Statistical analysis Education Buildings software Web sites

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Multi-Intent Enhanced Hypergraph Model for Session-Based Recommendation

Multi-Intent Enhanced Hypergraph Model for Session-Based Rec...

引用

software engineering and computer Science (CSECS), International conference on

作者： Jiawei Ding Jinsheng Wei Guanming Lu School of Communications and Information Engineering Nanjing University of Posts and Telecommunications Nanjing China

ISBN: (数字)9798331522216

ISBN: (纸本)9798331522223

Session-based recommendation leverages interaction data from anonymous users to suggest items of potential interest. Although existing research typically examines user intent from global and local perspectives, the omission of initial user intent has led to an incomplete understanding of user preferences. Furthermore, during the intent fusion stage, many methods simply sum or concatenate different intents, making it difficult to discriminate the contribution of each intent to the final recommendation. To overcome these limitations, we propose the multi-intent enhanced hypergraph model for session-based recommendation (MEHM). Specifically, we introduce two novel modules: an Initial Intent Learning Module (IILM) and a Multi-Intent Fusion Module (MIFM). In the Initial Intent Learning Module, we propose a first-item-guided strategy that infers the user's initial intent based on the first few items in the session. In the Multi-Intent Fusion Module, we integrate multiple forms of user intent-namely, the initial, global, and current intents-by using global intent as a reference and assigning appropriate weights to both initial and current intents. This design allows for a more precise and holistic representation of user preferences. Extensive experiments on three real-world datasets demonstrate that our method achieves superior performance compared to existing state-of-the-art approaches.

关键词： computer science System performance Noise Electronic commerce Public healthcare Recommender systems software engineering

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Analysis of Key Parameters in software Defined Network for Optimizing the Performance

Analysis of Key Parameters in Software Defined Network for O...

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Emerging systems and Intelligent Computing (ESIC), International conference on

作者： Pushpendra Kumar Chandra Suraj Sharma Niranjan Kumar Ray Satish Kumar Negi Dept. of CSE Guru Ghasidas Vishwavidyalaya Bilaspur India School of Computer Engineering KIIT Deemed to be University Bhubaneswar Odisha India

ISBN: (数字)9798331522100

ISBN: (纸本)9798331522117

SDN is a novel approach to networking by decoupling the control and data planes and allowing for centralized management and dynamic configuration. The paper looks into the core performance parameters critical to SDN functionality, focusing on their role in ensuring efficient, scalable, and reliable network operations. Additionally, it highlights optimization strategies and tools that address the challenges posed by these parameters. This research study aims to provide the desired broad perspective in development of innovative solutions to improve SDN performance in meeting the requirements of modern and emerging networking environments.

关键词： Fault tolerance Scalability Fault tolerant systems Focusing Throughput Energy efficiency software defined networking Optimization Centralized control

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Instructors' Perspectives on Capstone Courses in Computing Fields: A Mixed-Methods Study 2024

Instructors' Perspectives on Capstone Courses in Computing F...

引用

29th Working Group Reports on Innovation and Technology in computer Science Education, ITiCSE WGR 2024

作者： Hooshangi, Sara Shakil, Asma Dasgupta, Subhasish Davis, Karen C.C. Farghally, Mohammed Fitzpatrick, KellyAnn Gutica, Mirela Hardt, Ryan Riddle, Steve Seyam, Mohammed Department of Computer Science Virginia Tech BlacksburgVA United States School of Computer Science University of Auckland Auckland New Zealand Info Systems and Tech Mgmt Dept George Washington University WashingtonDC United States Computer Science and Software Engineering Dept. Miami University OxfordOH United States School of Computing Instruction Georgia Institute of Technology AtlantaGA United States School of Computing & Academic Studies British Columbia Institute of Technology BurnabyBC Canada Computer & Information Science University of St. Thomas Saint PaulVA United States School of Computing Newcastle University Newcastle upon Tyne United Kingdom

ISBN: (纸本)9798400712081

Team-based capstone courses are integral to many undergraduate and postgraduate degree programs in the computing field. They are designed to help students gain hands-on experience and practice professional skills such as communication, teamwork, and self-reflection as they transition into the real world. Prior research on capstone courses has focused primarily on the experiences of students. The perspectives of instructors who teach capstone courses have not been explored comprehensively. However, an instructor's experience, motivation, and expectancy can have a significant impact on the quality of a capstone course. In this working group, we used a mixed methods approach to understand the experiences of capstone instructors. Issues such as class size, industry partnerships, managing student conflicts, and factors influencing instructor motivation were examined using a quantitative survey and semi-structured interviews with capstone teaching staff from multiple institutions across different continents. Our findings show that there are more similarities than differences across various capstone course structures. Similarities include team size, team formation methodologies, duration of the capstone course, and project sourcing. Differences in capstone courses include class sizes and institutional support. Some instructors felt that capstone courses require more time and effort than regular lecture-based courses. These instructors cited that the additional time and effort is related to class size and liaising with external stakeholders, including industry partners. Some instructors felt that their contributions were not recognized enough by the leadership at their institutions. Others acknowledged institutional support and the value that the capstone brought to their department. Overall, we found that capstone instructors were highly intrinsically motivated and enjoyed teaching the capstone course. Most of them agree that the course contributes to their professional de

关键词： Students

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IoT Based Monitoring System for Health During Menstruation

IoT Based Monitoring System for Health During Menstruation

引用

Sentiment Analysis and Deep Learning (ICSADL), International conference on

作者： Chinmaya Khadse Shital Hajare Nishad Sheikh Roshni Dahule Priya Kate Department of Computer Science and Engineering Faculty of Engineering and Technology Datta Meghe Institute of Higher Education and Research Sawangi Wardha Maharashtra India Department of Artificial Intelligence and Machine Learning Faculty of Engineering and Technology Datta Meghe Institute of Higher Education and Research Sawangi Wardha Maharashtra India Department of Computer Science and Engineering Faculty of Engineering and Technology Datta Meghe Institute of Higher Education and Research Sawani Wardha Maharashtra India

ISBN: (数字)9798331523923

ISBN: (纸本)9798331523930

The integration of IoT and ML brought forth new prospective solutions in menstrual health management, pertaining to continuous monitoring of physiological signals and personalization of insights for women. This article discusses the usage of IoT, smartphones, and cloud-based systems for tracking vital signs, temperature, pulse rate, and flow of menstruation that will enable pro-active management of the cycle. The use of ML algorithms, including supervised models-like Random Forest and Logistic Regression-and complex techniques like RNNs and LSTM networks-offers added advantages for predicting menstrual cycles and ovulation. These technologies offer personalized health recommendations, early diagnosis of menstrual disorders, and help in communicating with healthcare providers in a very short span of time. While offering huge potential to improve women's health, concerns around data privacy, ethical considerations, and equitable access to these digital health solutions are highlighted. The existing systems showed improvements yet they encountered problems because of insufficient data diversity and health system integration as well as insufficient personalization and imprecise cycle predictions. Data privacy issues and security threats that stem from ML models along with constant bias concerns prevent broad acceptance of ML systems in general use. This research study analyzes IoT and ML applications in menstrual health today and introduces their advantages as well as the barriers that require resolution before mass acceptance can occur. The proposal introduces an approach to create menstrual tracking software through a combination of rule-based systems with ML algorithms that generates precise forecasts alongside tailored information for women who have PCOS or PCOD.

关键词： Data privacy Ethics software algorithms Prediction algorithms software Internet of Things Biomedical monitoring Wearable devices Smart phones Monitoring

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Diabetic Foot Ulcer Classification Using Deep Learning Approach 8th

Diabetic Foot Ulcer Classification Using Deep Learning Appro...

引用

8th IFIP TC 12 International conference on computer, Communication and Signal Processing, ICCCSP 2024

作者： Sivakamasundari, P. Niranjana, G. Department of Computer Science and Engineering SRM Institute of Science and Technology Tamil Nadu Kattankulathur India Department of Computing Technologies SRM Institute of Science and Technology Tamil Nadu Kattankulathur India

ISBN: (纸本)9783031736162

Podiatrist diagnosis and lesion localization are used as current testing approaches for Diabetic Foot ulcers (DFU). Current systems for automation concentrate on either categorization or division. One of the most common metabolic conditions, Diabetes (also called diabetes mellitus), is brought on by the pancreas incapacity to generate sufficient anti hyper-glycemic hormone to control glycemia levels. It may cause "Diabetic Peripheral Neuropathy," a collection of nerve diseases that can develop if the blood glucose level is left uncontrolled and unmanaged. Blood glucose levels may be efficiently maintained by recognising diabetes initially through constant surveillance and screenings. Using image processing methods such as data stretching with Deep Learning, image reduction and improvement, image division, and feature extraction, this paper offers a thorough approach for analysing thermal scans of the diabetic foot. By using these techniques, doctors may assess and track a patient's condition with fewer examinations. In this work, EfficientNetB3 architecture is compared with other Deep Learning models for accuracy in DFU identification. To create a powerful deep learning model, we gathered an extensive collection of 1,775 DFU photos. The basis of belief for this data gathering was created by two medical experts using annotator software to define the DFU region of interest. It took 48 ms to figure out a single image and 57.2 MB to validate the model. EfficientnetB3 got an average mean accuracy of 93%. This work demonstrates the effectiveness of Deep Learning for DFU localization in real-time, which could have improved with the use of a larger data set. © IFIP International Federation for Information Processing 2025.

关键词： Diagnosis

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A Graph-Based Unsupervised Log Anomaly Detection Based on the Magnetic Laplacian

A Graph-Based Unsupervised Log Anomaly Detection Based on th...

引用

software engineering and computer Science (CSECS), International conference on

作者： Kangfan Yan Yuhong Jiang China University of Geosciences Wuhan China

ISBN: (数字)9798331522216

ISBN: (纸本)9798331522223

Logs record the runtime status of software systems and detailed information of user operations. However, due to the complexity and heterogeneity of log formats and semantics, log anomaly detection work faces challenges. Most existing log anomaly detection methods only consider the quantitative and/or sequential relationships, while ignoring the directional information within logs, which may result in low detection accuracy. In addition, the high cost of manual annotation for logs is another challenge to effective log analysis. To address the aforementioned challenges, this paper introduces L2G-Log, a graph-based unsupervised method for log anomaly detection. The method begins by constructing logs into directed, attributed, and weighted graphs, followed by employing graph neural networks for graph-level anomaly detection. Specially, we introduce a One-Class graph convolutional neural network based on the magnetic Laplacian called OCMagNet. Firstly, it extracts the directional information in log graphs through the magnetic Laplacian and generates a vector representation for each node in graphs. Then, it utilizes Readout(·) to aggregate vector representations into a graph representation for each log graph. Finally, DeepSVDD is employed to identify anomalies without manual labeling of log data. Experiments conducted on two benchmark datasets demonstrate that L2G-Log achieves performance that is on par with or surpasses existing anomaly detection methods.

关键词： Laplace equations Runtime Aggregates Semantics Manuals software systems Vectors Graph neural networks Anomaly detection Unsupervised learning

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Cloud Based Automated Control System Workshops and Rooms for Controlling Parameters

Cloud Based Automated Control System Workshops and Rooms for...

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Advances in computer Science, Electrical, Electronics, and Communication Technologies (CE2CT), International conference on

作者： Dinesh Kumar Ravinder Singh Kuntal Pragya Deep Anup Shekhar Chamoli Pinki Singh Rishabh Mandal Department of Computer Science and Engineering SRM Institute of Science & Technology Ghaziabad UP Department of Mathematics Nitte Meenakshi Institute of Technology Bangalore Karnataka India Department of AI & DS IIMT College of Engineering Greater Noida India Uttaranchal School of Computing Sciences Uttaranchal University Dehradun India Department of Computer Science and Engineering Accurate College of Engineering & Management Greator Noida India Department of Computer Science and Engineering Tula's Institute Dehradun UK India

ISBN: (数字)9798331518578

ISBN: (纸本)9798331518585

Across all industries, cloud-based automated control systems have completely changed how operational and environmental parameters are tracked and controlled. With cloud-integrated systems for real-time data collection, processing, and control, this concept presents intelligent, remote-controlled workshops and control rooms. To guarantee accurate control of crucial variables like temperature, humidity, pressure, and equipment efficiency, these systems make use of IoT devices, AI techniques, and big data analytics. Through sophisticated data perspectives, the cloud-based strategy enables predictive maintenance, improves flexibility, and lowers operating expenses. Stakeholders may make prompt, data-driven choices from anywhere with remote access to control rooms. These seminars provide practical experience with cloud-controlled settings and function as training and development centres. The system's flexibility to meet a range of industrial demands is further enhanced by its compatibility with external tools and equipment. The design, deployment, and possible uses of cloud-based control systems are covered in this paper, with an emphasis on how they might promote operational excellence, energy efficiency, and smart manufacturing.

关键词： Knowledge engineering Machine control Clouds Control systems software Machine tools Security Time factors Personnel Standards

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