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检索条件"任意字段=8th IEEE International Conference on Software Engineering and Computer Systems, ICSECS 2023"

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Github Users Recommendations Based on Repositories and User Profile 1

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8th international conference on Emerging Research in Computing, Information, Communication and Applications, ERCICA 2023

作者： Nagaraj, R. Ramya, G.R. Yougesh Raj, S. Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Coimbatore India

ISBN: (数字)9789819976331

ISBN: (纸本)9789819976324

A recommendation system is important in today’s world because it suggests many options to the user that may be useful or appealing. these kinds of recommending systems are used in many applications and devices to focus on delivering the advertisements to a specific set of people. Even the commercial and social network websites depend on the recommendation system as it helps to recommend on basis of user profiles. In this paper, we analyzed the open-source software Github, which is a mandatory tool for the developers as it helps them to connect and exchange their works with fellow developers. We have predicted and analyzed the spread of followers to a particular user based on their repository details and nature of relation. this system would be beneficial for the developer to approach or work with other users in the same domain. Nowadays, Github is one of the fast-growing platforms with millions of users sharing their projects and by implementing the recommender system helps the user to reduce their time in searching for the similar users. this recommendation system is tested on the real-time data of an existing Github user by implementing different concepts of social network analysis such as centrality measure, similarity measure, link prediction, triads, and natural language processing concept stemming. © 2024, the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Recommender systems

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Pneumonia Detection Using Improved Convolutional Neural Network 8

Pneumonia Detection Using Improved Convolutional Neural Netw...

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8th international conference on Advanced Computing and Communication systems, ICACCS 2022

作者： Sindhu, Vibhanshu Singh Dixit, Rohan Sreedevi, Indu Delhi Technological University Department of Software Engineering Delhi India Delhi Technological University Department of Computer Science and Engineering Delhi India Delhi Technological University Department of Electronics and Communication Engineering Delhi India

ISBN: (纸本)9781665408165

Pneumonia, ordinarily caused by the bacteria called streptococcus pneumoniae is a life endangering contagious illness affecting one or both lungs in humans. In this study, we extract features from a given chest Xray image by developing a convolutional neural network model from scratch and thereafter, use classification to determine if a person has pneumonia or not. Often, dealing with medical images, we are faced with consistency and interpretability problems, this model aims to alleviate the same issues. the dataset used comprises of 29864 chest Xray pictures. We have done data preprocessing, data visualization to plot the positive and negative pneumonia graphs and data normalization to ensure our gradients do not diverge. We have refined our model and achieved an excellent training set accuracy of 94.20 percent, test set accuracy of 87.11 percent, positive pneumonia prediction accuracy of 82.69 percent, and negative pneumonia prediction accuracy of 90.21 percent. © 2022 ieee.

关键词： Convolutional neural networks

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Industry 4.0: Developing Center of Excellence for PLC Lab in the field of Automation 8

Industry 4.0: Developing Center of Excellence for PLC Lab in...

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Joint 8th international conference on Digital Arts, Media and Technology and 6th ECTI Northern Section conference on Electrical, Electronics, computer and Telecommunications engineering, ECTI DAMT and NCON 2023

作者： Kuong, Samnang thap, tharoeun Math, Sa Yahoui, Hamed Tran, thanh Kha Heng, Sokha Royal University of Phnom Penh Phnom Dept. of Telecommunication and Electronic Engineering Penh Cambodia Automation & Processing Center Claude Bernard University Lyon 1 Dept. of Mechanical Engineering Lyon France Royal University of Phnom Penh Phnom Faculty of Engineering Penh Cambodia

ISBN: (纸本)9798350396546

Nowadays, industry 4.0 presents a modern and innovative paradigm with integrated up-to-date technology. the Asean Factori 4.0 projects under the funding of the Erasmus+ programme targeted to provide the training of the joined staff, students, and lecturers from the involved universities. this project contributes to the trainees for the state-of-the-art knowledge related to industry 4.0, automation, technologies, applications, and skills in utilizing the programable logic control (PLC) and its use cases for automation projects. this paper presents the key enabler technologies for industry 4.0 applications and developing Center of Excellence (CE) for PLC Lab in the fields of automation. Furthermore, we describe the learning courses and training contents under the training periods. the significant tools, frameworks, software, theoretical and practical methods are delivered to the involvements. Finally, a practical elevator project utilized the CE PLC Lab conducted by students have presented. © 2023 ieee.

关键词： Industry 4.0

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Two-Stage Decoding Network for End-to-End Task-Oriented Dialog systems 8

Two-Stage Decoding Network for End-to-End Task-Oriented Dial...

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8th international conference on Intelligent Computing and Signal Processing, ICSP 2023

作者： Zhang, Xinping Wang, Junhua Changchun University of Technology School of Computer Science and Engineering Jilin Province Changchun China

ISBN: (纸本)9798350302455

Task-oriented dialog model guides dialogue generation by identifying user intentions and incorporating external knowledge. the existing models based on end-to-end memory networks have two problems. First, most models use Bi-GRU or Bi-LSTM to encode the dialogue context. Such a sequential structure encoder makes it easy to cause the loss of long dialogue information, so the model cannot accurately identify the user's intention. Second, the previous model uses the output of the encoder as the query vector to search for external knowledge, which results in the query vector fusing too much information unrelated to the search for external knowledge, so it is difficult for the model to incorporate external knowledge effectively. We propose a Two-Stage Decoding Network (TSDN) based on end-to-end memory networks to mitigate these problems. Concretely, our model consists of a Bert encoder, external knowledge, and a two-stage decoder, where one stage is for extracting entity information and another is for generating the response. the Bert encoder has excellent capture of important information about the dialog context. the two-stage decoding strategy can better search for external knowledge and generate high-quality responses. Experimental results on two benchmark datasets show that our approach achieves higher BLEU scores and Entity F1 scores compared to the baseline model. © 2023 ieee.

关键词： Long short-term memory

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Multiplier Design for Digital Modulator for Wireless Communication Applications 8

Multiplier Design for Digital Modulator for Wireless Communi...

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8th ieee international conference for Convergence in Technology, I2CT 2023

作者： Hosamani, Ravi Yerriswamy, T. Praveen Kumar, Y.G. K.L.E. Institute of Technology Dept. of Electronics and Communication Engg Karnataka Hubballi580027 India K.L.E. Institute of Technology Dept. of Computer Science and Engg. Karnataka Hubballi580027 India SSIT Dept. of Electronics and Communication Engg Tumakuru India

ISBN: (纸本)9798350334012

State-of-the-art technologies cannot be implemented without being expedited by very large-scale integration (VLSI) circuits because computational complexity is continuously increasing. For example, application-specific integrated circuits (ASICs) are required for 5G communications to attain data rates above tens of gigabits per second. systems for the Internet of things (IoT) must have extremely efficient hardware to support data transfer within a few milliseconds while operating within a constrained power budget. the digital design gives greater flexibility than the analog design since the digital communication modules are robust and also provide significant immunity to noise and interference. We have a multichannel technology known as orthogonal frequency division multiplexing (OFDM) that combines QAM and FDM (OFDM). To offer several bit streams with a high data rate, 64-QAM or 256-QAM are employed in separate frequency channels with OFDM in 5G. the proposed design, QAM is built utilizing several multiplier architectures, including Vedic multipliers and booth multipliers, and performance evaluation is done concerning area and power using ASIC and CMOS Technology. Aim of the proposed multipliers is that they require significantly fewer components as compared to the naive method. Further complexity reductions are achieved. the obtained result shows that the use of the multiplier module will outperform state-of-the-art modulator efficiency. Using cadence tool 32bit and 64bit QAM design and physical parameters area and power efficiency are estimated and tabulated respectively. © 2023 ieee.

关键词： Orthogonal frequency division multiplexing

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VulSAT: Source Code Vulnerability Detection Scheme Based on SAT Structure 8

VulSAT: Source Code Vulnerability Detection Scheme Based on ...

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8th international conference on Signal and Image Processing, ICSIP 2023

作者： Xue, Jintao Yu, Zihan Song, Yubo Qin, Zhongyuan Sun, Xin Wang, Wen Southeast University School of Cyber Science and Engineering Nanjing211189 China State Grid Zhejiang Electric Power Co. Ltd. Research Institute Internet Technology Center Hangzhou310063 China State Grid Zhejiang Electric Power Co. Ltd Internet Department Hangzhou310063 China

ISBN: (纸本)9798350397932

the number of software vulnerabilities have increased rapidly, and their forms have shown the characteristics of complexity and diversity, which has brought severe challenges to software systems. Deep learning can automatically learn the features of code and is widely used in source code vulnerability detection. Some studies treat codes as text sequences, ignoring the structural relationship between lines of code. Other studies extract the code as a graph structure, but ignore the order relationship of code lines and do not make full use of the dependencies between code lines. this paper proposes a C/C++ source code vulnerability detection scheme based on SAT (Structure-Aware Transformer) structure. It first standardizes the source code, then extracts the PDG (program dependency graph) representation of source code, next convert each node into a vector representation using sentence embedding, which retains the dependencies between nodes. Finally input it into the SAT architecture model for training, and judge whether the input program contains vulnerabilities according to the output results. We compared VulSAT with a variety of vulnerability detection methods (i.e., Devign, SySeVR, VulCNN, Checkmarx, VulDeePecker), and selected C/C++ functions in the SARD vulnerability dataset as experimental objects. the performance of accuracy rate and false positive rate has been improved to a certain extent. © 2023 ieee.

关键词： Deep learning

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Analyze and Evaluate the Factors Affecting the thermal Comfort Index in the Air-Conditioned Room by Numerical Simulation software 8

Analyze and Evaluate the Factors Affecting the Thermal Comfo...

引用

8th international Scientific conference on Applying New Technology in Green Buildings, ATiGB 2023

作者： Dang, Hung-Son Doan, Minh-Hung Ho Chi Minh University of Technology and Education Faculty of Vehicle and Energy Engineering 01 Vo Van Ngan St. Thu Duc City Ho Chi Minh City Viet Nam

ISBN: (纸本)9798350343977

Air conditioning systems are becoming more popular than ever in the modern day. they appear all over office buildings, commercial centers, hospitals, etc. With its benefits, people can feel comfortable and comfortable in the space where they work and live. Since then, the research on thermal comfort for people in the air-conditioned room has been focused. CFD simulation is considered one of the scientific research methods related to the flow characteristics of fluids with high applicability. It is an effective tool to understand and evaluate the factors affecting the flow rate. the air-conditioned space's temperature field and velocity will provide the optimal solution for human purposes. the thermal comfort (TC) index was investigated by changing the openings of the cassette air conditioner airflow wide angle (AFWA) to 30°, 40°, 50°, and 60°, respectively, and keeping the ventilation airflow at 400 m3jh fixed. the TC index is surveyed through the Vertical Air Temperature Difference (VATD) index. In addition, the airflow rate of the cassette changed from 810 m3jh to 1230 m3jh during the simulation, thereby giving detailed evaluation results on the indicators affecting thermal comfort inside the room. Using CFD numerical simulation software (Ansys Fluent) to analyze and evaluate the research results shows that changing the AFWA of the air supply significantly when the AFWA increases will affect the uniformity of the comfort index. the AFWA of the louvers gave the highest uniformity and comfort index in this study at 30 degrees and 40° with the ventilation flow value of 810 m3jh at the vertical temperature gradient, VATD has the smallest difference values of 0.95K and 1K, respectively. © 2023 ieee.

关键词： thermal comfort

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Enhanced DDOS Attack Detection Algorithm to Increase Network Lifetime in Cloud Environment 8

Enhanced DDOS Attack Detection Algorithm to Increase Network...

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8th international conference on Advanced Computing and Communication systems, ICACCS 2022

作者： Pavan Kumar, R Sai Chand, K Gopi Krishna, M Vamsi Nithin, B Gowtham Roshini, A. Swetha, K. Koneru Lakshmaiah Education Foundation Department of Computer Science and Engineering AP Vaddeswaram India

ISBN: (纸本)9781665408165

DDoS attacks, one of the oldest forms of cyberthreats, continue to be a favorite tool of mass interruption, presenting cybersecurity hazards to practically every type of company, large and small. As a matter of fact, according to IDC, DDoS attacks are predicted to expand at an 18 percent compound annual growth rate (CAGR) through 2023, indicating that it is past time to enhance investment in strong mitigation systems. And while some firms may assume they are limited targets for a DDoS assault, the amount of structured internet access to power corporation services and apps exposes everyone to downtime and poor performance if the infrastructure is not protected against such attacks. We propose using correlations between missing packets to increase detection accuracy. Furthermore, to ensure that these correlations are calculated correctly. © 2022 ieee.

关键词： Investments

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Machine Learning and Internet of things-based Driver Safety and Support System 8

Machine Learning and Internet of Things-based Driver Safety ...

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8th international conference on Communication and Electronics systems, ICCES 2023

作者： Rakesh, S. Jeyageetha, K. Nishant, S. Nageswari, D. Prakash, R.B.R. Mary, S. Suma Christal Nitte Institute of Professional Education Nitte University Nitte Institute of Professional Education Mangalore campus pumpwell circle Mangalore India Ramco Institute of Technology Department of Computer Science and Engineering Virudhunagar district Rajapalayam India St. Joseph's College of Engineering Electrical & Electronics Engineering Omr Chennai119 India Rmk College of Engineering & Technology Gummidipoondi Taluk Thiruvallur Puduvoyal601206 India Koneru Lakshmaiah Education Foundation Electrical and Electronics Engineering Vaddeswaram522302 India Panimalar Engineering College Department of Information Technology Poonamalle Chennai India

ISBN: (纸本)9798350396638

Accident patterns can be determined through driving analysis. In environmental, safety, and fleet management applications, accident detection can decrease potential risks to vehicles and drivers, enhance service quality, and save money. Earlier automatic accident detection methods relied on traffic data or external sensors. However, traffic data is difficult to obtain, and external sensors might be untrustworthy and inconvenient. Since traditional techniques have been constrained by a shortage of accident data, cutting-edge technologies such as machine learning (ML) have been underutilized. the most challenging aspect of the task is detecting roadside barriers. the proposed idea is to create something that can identify barriers while driving a car. A Raspberry Pi Camera module aids in the object detection and identification process. the most effective technique for detecting image boundaries is determined by testing on an example image. this study recommends an Advanced Classifier to determine different categories. the proposed technology can identify cars, animals, people, etc. If an object is in the user's route, the system will warn them to slow down. In particular, the proposed Auto-Alert uses both CNN and LSTM models. Importantly, this requires the design and proof of concept of a credible traffic monitoring and density estimation system. the proposed work shows how important CNN and LSTM networks are to help drivers in traffic. Results show that the suggested method is more accurate and faster than the present methodology. © 2023 ieee.

关键词： Object detection

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A Survey of Industry in Cambodia and Future Prospects Industry 4.0 8

A Survey of Industry in Cambodia and Future Prospects Indust...

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作者： Chheang, Vuthy Heng, Sokha thourn, Kosorl Yahoui, Hamed Royal University of Phnom Penh Dept. of Telecommunication and Electronic Engineering Phnom Penh Cambodia Royal University of Phnom Penh Faculty of Engineering Phnom Penh Cambodia Institute of Technology of Cambodia Department of Telecommunication and Network Engineering Phnom Penh Cambodia Automation & Processing Center Dept. of Mechanical Engineering Claude Bernard University Lyon 1 Lyon France

ISBN: (纸本)9798350396546

In developed countries, industry 4.0 revolution is growing towards automation and data cloud analysis in manufacturing technologies to create a smart and high-class factory which be able to make higher production and logistics systems with few employees. this paper is based on a project funded by the ERASMUS+ Program of the European Union: ASEAN Factori 4.0, Across South East Asian Nations: From Automation and Control Training to the Overall Roll-out of Industry 4.0, 609854-EPP-1-2019-1-FREPPKA2-CBHE-JP which provided for a great survey of Cambodia industries in order to develop universities programs of automated production system. With these results of surveyed industries contributes to the Telecommunication and Electronic engineering Department of Royal University of Phnom Penh recognizing where to begin for requirement of future industry 4.0 in Cambodia, such as automated production, applied technologies, and programing skills. In short of future, Cambodia will be extended for Industry 4.0 technologies with 5G, data centers, artificial intelligent (AI), industrial Automation (IA), additive manufacturing, industrial internet of things (IIoT) and smart factories, intelligent management, cyber-security, and machine learning as similar as other developed Asian countries. © 2023 ieee.

关键词： Industry 4.0

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