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A Hybrid Programming Course recommendation system using Fuzzy Logic and xDeepFM

A Hybrid Programming Course recommendation system using Fuzz...

引用

2023 international conference on intelligent systems, advanced computing and Communication, ISACC 2023

作者： Ghosh, Subhasish Bgc Trust University Bangladesh Department of Computer Science and Engineering Chittagong Bangladesh

ISBN: (纸本)9798350399387

The choice of courses is crucial to a student's career achievement. Different courses offered by various academic institutions need the students to browse the course outline in the current educational environment manually. Most of them need more understanding, struggle with decisions, and make rash decisions regarding the best course of action. A course recommendation system helps students choose a course that suits their interests and abilities. The skill level classification using Mamdani FIS allows a new student to select an equivalent course that can solve the cold start issue of the recommendation system. After the student chooses the initial course, the xDeepFM model can continue recommending relevant courses to help the student. This research contributes to integrating the FIS with xDeepFM to enhance the accuracy of course recommendations. Additionally, the hybrid method solves the cold start and the data sparsity problem and simultaneously lessens variability in relevant course search results and information overload. The experimentation result indicates that xDeepFM is a suitable method to be combined with FIS to build an efficient hybrid course recommendation system. © 2023 ieee.

关键词： Recommender systems

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IoT Architecture for Electricity Distribution Considering data Fusion and intelligent Decision Making 5

IoT Architecture for Electricity Distribution Considering Da...

引用

5th ieee international conference on Power, intelligent computing and systems, ICPICS 2023

作者： Bao, Shandong Xu, Kun Zheng, Lihua Shan, Yongze Liu, Yihao Li, Lingcong State Grid Heilongjiang Electric Power Co. Ltd. Mudanjiang Power Supply Company Mudanjiang China Northeastern Electric Power University Jilin China

ISBN: (纸本)9798350333442

Distribution Internet of Things is the embodiment of the application of power Internet of things in the field of distribution. This paper proposes a distribution Internet of Things architecture that combines data fusion and intelligent decision making. The architecture adopts T-NN algorithm to realize data fusion, and integrates multi-source data to improve the accuracy and reliability of data. DS model is used to specify the optimal strategy, and DQN algorithm is used to train the agent. By designing the reward function, the accuracy and efficiency of intelligent decision is improved, and the intelligent management and control of the distribution system is realized. The experimental results show that the architecture can effectively improve the efficiency and reliability of the distribution system, and provide strong support for the realization of intelligent energy management and the construction of intelligent distribution network. © 2023 ieee.

关键词： Reinforcement learning

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AI2DS: advanced Deep Autoencoder-Driven Method for intelligent Network Intrusion Detection systems 4

AI2DS: Advanced Deep Autoencoder-Driven Method for Intellige...

引用

4th ieee international conference on Artificial Intelligence in Cybersecurity, ICAIC 2025

作者： Rahman, Md Habibur Martinez, Leo Mishra, Avdesh Nijim, Mais Goyal, Ayush Hicks, David Texas A&M University-Kingsville Department of Electrical Engineering and Computer Science KingsvilleTX78363 United States

ISBN: (纸本)9798331518882

Network security is a growing concern as digital infrastructure expands, and traditional measures struggle against modern cyber threats. With the increasing complexity of attacks, there is a need for more adaptive and intelligent solutions. This research introduces AI2DS (advanced Deep Autoencoder-Driven Method for intelligent Network Intrusion Detection systems), an autoencoder-based architecture that enhances security by identifying deviations from normal network behavior. The model is trained on normal data, using reconstruction errors to detect anomalies through adaptive thresholding. By simplifying attack classification into a single 'intrusion' class, AI2DS demonstrates high accuracy and broad applicability. The model shows average improvements of 6.61%, 31.11, 11.46%, and 16.91 in Precision, Recall, F1 Score, and Accuracy, respectively, over state-of-the-art methods, with potential for real-time application and future advancements. © 2025 ieee.

关键词： Network intrusion

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advanced Distribution System State Estimation Techniques: A Review 1

Advanced Distribution System State Estimation Techniques: A ...

引用

1st ieee international conference on Smart and Sustainable Developments in Electrical Engineering, SSDEE 2025

作者： Ankam, Sruthi Basetti, Vedik Sen, Sachidananda SR University Dept. of E.E.E. Warangal India

ISBN: (纸本)9798331542108

This study provides an outline of Distribution System State Estimation (DSSE), a technique introduced by Fred Schweppes in 1970. Since then, SE has been crucial in managing and controlling electric transmission operations. It has also played a role in enhancing Supervisory Control and data acquisition systems (SCADA) as well as Energy Management systems (EMS). DSSE has certain difficulties like high R/X ratios, unbalanced phases, inadequate current and voltage measurements, scalability problems, etc. To improve the DSSE accuracy phasor measurement units are used. study on state estimation techniques based on Branch-Current and Node-Voltages are being conducted. The methods applied for dynamic state estimation play a significant role in power systems for monitoring, control, and stability assessment. These methods are used in state estimation in power systems to enhance the system's reliability, stability, monitoring, and control in modern distribution systems. © 2025 ieee.

关键词： SCADA systems

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Visualization of data Cubes for Anomaly Detection in Network Traffic data Streams 11

Visualization of Data Cubes for Anomaly Detection in Network...

引用

11th ieee international conference on intelligent data acquisition and advanced computing systems - Technology and Applications (IDAACS)

作者： Ahlers, Volker Laue, Tim Wellermann, Nils Heine, Felix Univ Appl Sci & Arts Hannover Hannover Germany

ISBN: (纸本)9781665426053

For anomaly-based intrusion detection in computer networks, data cubes can be used for building a model of the normal behavior of each cell. During inference an anomaly score is calculated based on the deviation of cell metrics from the corresponding normality model. A visualization approach is shown that combines different types of diagrams and charts with linked user interaction for filtering of data.

关键词： network security data cubes multidimensional analysis user interfaces information visualization

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A Smart Home Design with intelligent Patient Monitoring Features by Using Internet of Things (IoT) Enabled Communication Technology

A Smart Home Design with Intelligent Patient Monitoring Feat...

引用

2024 international conference on Innovative computing, intelligent Communication and Smart Electrical systems, ICSES 2024

作者： Prince, P. Rajabhushanam, C. Department of Computer Science and Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798331543617

The integration of Internet of Things (IoT) technology into smart home systems has revolutionized patient monitoring by providing real-time health insights and automated environmental adjustments. This study focuses on designing and evaluating a smart home system with intelligent patient monitoring features, aimed at enhancing patient safety, comfort, and healthcare delivery. The system employs a network of IoT-enabled devices, including wearable health sensors, environmental monitors, and smart cameras, to track vital signs such as ECG, SPO2, and body temperature, along with environmental parameters like air quality, humidity, and temperature. The system achieved a high accuracy rate, with vital sign sensors demonstrating over 98% reliability across various metrics. A communication framework using Wi-Fi and MQTT protocols ensures seamless data transfer and real-time responsiveness. Edge computing enables low-latency data processing, while cloud analytics provide predictive insights for early health issue detection. Key findings demonstrate the system's efficiency in emergency response, with an average detection-to-alert time of 1.4 seconds, and its ability to adapt the environment based on health conditions with over 95% precision. Automated features such as temperature control, fall detection, and personalized lighting enhance patient care and well-being. This work underscores the transformative potential of smart home technologies in healthcare, paving the way for future advancements in personalized health monitoring systems. © 2024 ieee.

关键词： Electronic health record

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The Application of Internet of Things Technology in intelligent Wind Power Grid 4

The Application of Internet of Things Technology in Intellig...

引用

4th international conference on Energy Engineering and Power systems, EEPS 2024

作者： Xu, Jianuo Lappeenranta University of Technology Lappeenranta53850 Finland

ISBN: (纸本)9798350366914

With the rapid development of Internet of Things technology, people can integrate the Internet of Things in more and more work scenarios, making work simpler and more intelligent. For wind power generation technology, the same applies. Traditional wind power often relies on a large amount of manpower to monitor data and adjust generator parameters, enabling wind turbines to operate at higher efficiency. If IoT technology is combined with modern wind power generation systems, it can not only reduce a large amount of manpower consumption, but also enable wind turbines to perform more precise automatic control, improve power generation efficiency, and reduce operating costs. This article provides important information on the Internet of Things technologies used in intelligent wind power generation, including wind speed and direction sensors, turbine health monitoring systems, and advanced control systems. These technologies can optimize the performance of wind power generation, improve efficiency, and reduce unexpected failures and unplanned downtime. © 2024 ieee.

关键词： Windmill

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Multi-Objective Optimization on Stealthy False data Injection Attack in Smart Power Transmission Grid

Multi-Objective Optimization on Stealthy False Data Injectio...

引用

2023 international conference on Networks, Communications and intelligent computing, NCIC 2023

作者： Ye, Tong Zhou, Boyang Nie, Yinghui Zhu, Zhen Zhejiang Lab China Zhejiang Lab UCAS HIAS China

ISBN: (纸本)9798350371949

In smart power transmission grids, the existing energy management systems (EMSes) unprecedentedly faces the stealthy false data injection attack (SFDI), where an adversary aims to compromise the optimal power flow analysis (OPF) to generate incorrect power dispatches and affect the power grid security and economy, via injecting subtle differences to the power consumption data measured by the wide-area remote terminal units (RTUs) in the supervisory control and data acquisition system (SCADA). To study the above OPF-targeted SFDI (OT-SFDI), we investigate a novel mechanism OT-SAG based on a bilevel genetic algorithm to efficiently optimize the attack vectors with multiple objectives, and accurately simulate the impact on the power grid. We evaluate OT-SAG under the OT-SFDI scenario in real power transmission grid constructed based on the ieee 30-bus datasets. The numerical results show that OT-SAG can efficiently optimize a diversity of OT-SFDI attack vectors, and accurately evaluate their effectiveness, concerning the adversaries' different objectives in the attack cost, stealthiness and attack impact. © 2023 ieee.

关键词： Multiobjective optimization

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Novel Dual-Encryption and Compression Strategy: AES and Fernet for Secure Multimedia Transmission 5

Novel Dual-Encryption and Compression Strategy: AES and Fern...

引用

5th international conference on IoT Based Control Networks and intelligent systems, ICICNIS 2024

作者： Zala, Dhruvi Karansinh Akram Khan, Mohammad Madhav University Faculty of Engineering and Technology Rajasthan 307026 India

ISBN: (纸本)9798331518097

The increasing variety of multimedia data types, such as text, images, and audio, has necessitated advanced data encryption techniques to ensure secure transmission and storage. Traditional encryption methods, including AES and Fernet, have shown limitations in meeting the demands of modern multimedia security. This research focused on developing an enhanced encryption system by integrating AES and Fernet encryption algorithms with the zlib compression technique. The proposed system provided an efficient solution for encrypting and decrypting diverse data formats, offering both improved security and enhanced processing speed. Key outcomes included stronger safety and security measures alongside better compression ratios. This approach aimed to establish a robust and adaptive security framework capable of addressing the evolving requirements for protecting multimedia data and ensuring the integrity of digital information. © 2024 ieee.

关键词： advanced Encryption Standard (AES) Compression Encryption Fernet Hybrid Approach Multimedia data Security

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Research on Network Security Protection System Based on Fusion of Computer Big data Technology 5

Research on Network Security Protection System Based on Fusi...

引用

5th ieee international conference on Power, intelligent computing and systems, ICPICS 2023

作者： Xuxi, Yin Information Engineering College Guangzhou Huashang Vocational College Guangzhou China

ISBN: (纸本)9798350333442

In this paper, a set of intelligent detection system for complex network intrusion data is designed. The system stores complex network traffic that is difficult to determine to the Hadoop data warehouse of the distributed file system (HDFS), and uses Hive to query the offline analysis data to detect abnormal network activities and effectively discover network attacks that are difficult to detect in the online analysis system. The system is based on a new model of big data to detect unknown attacks. Using compressed sensing network data transmission center high density information security storage method, network data high density transmission and information security storage are realized. RSA algorithm and CBC algorithm are used to encrypt data information. The test results show that the average time of network information security encryption protection and encryption is about 1500ms. The system has high safety performance and fast running speed. © 2023 ieee.

关键词： Network security

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