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3rd International Conference on Advances in information and Communication technology, ICTA 2024

作者： Tan, Nguyen Hong Khanh, Phan Hung Long, Cu Kim Van Hai, Pham Tuan, Tran Manh Chuan, Pham Minh Tam, Ngo Duc Son, Le Hoang Graduate University of Science and Technology Vietnam Academy of Science and Technology Hanoi Viet Nam Faculty of Information Technology Information Communication and Technology University Thai Nguyen Viet Nam Hanoi Viet Nam Hanoi Viet Nam Faculty of Computer Science and Engineering Thuyloi University 175 Tay Son Dong Da Hanoi Viet Nam Faculty of Information Technology UTEHY Hung Yen Viet Nam Artificial Intelligence Research Center VNU Information Technology Institute Vietnam National University Hanoi Viet Nam

ISBN: (纸本)9783031809422

Decision support systems have been widely applied in various sectors in which a vast of models and algorithms have been researched and developed based on knowledge graphs. Recently, Fuzzy Knowledge Graph (FKG) has overcome the challenge of handling uncertain, incomplete input data in decision support systems;yet still its performance could be improved through the integration of multiple data sources. This paper proposes a novel conceptual framework of FKG called FKGF based on multiple data sources. The experimental results based on multiple data sources in the healthcare sector (including ***, kaggle, hospital, etc.) show that the proposed framework gives positive results when combining data from many different sources. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Knowledge graph

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Harmonic Analysis of Cûk DC-DC Converter 23

Harmonic Analysis of Cûk DC-DC Converter

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23rd International Symposium on Electrical Apparatus and Technologies, SIELA 2024

作者： Vacheva, Gergana Stanchev, Plamen Hinov, Nikolay Technical University of Sofia Faculty of Electronic Engineering and Technologies Departement of Power Electronics Sofia Bulgaria Technical University of Sofia Faculty of Computer Systems and Technologies Departement of Information Technology in Industry Sofia Bulgaria

ISBN: (纸本)9798350382365

In the present paper, a harmonic analysis of a Cuk DC-DC converter is realized. A simulation model was implemented in MATLAB/Simulink. The converter is described using differential equations that are represented in state space. Two scenario of on and off transistor are considered. Simulation results are shown, where it can be observed in which case resonance occurs, which significantly influences the design of the circuit. Main advantages and disadvantages of the selected topology are described. © 2024 IEEE.

关键词： Cuk converter

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A secure quantum homomorphic encryption ciphertext retrieval scheme

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Soft Computing 2025年第3期29卷 1497-1509页

作者： Cheng, Zhen-Wen Chen, Xiu-Bo Xu, Gang Chang, Yan Miao, Li-Hua Yang, Yi-Xian Wang, Ya-Lan School of Data and Computer Science Shandong Women’s University Jinan250300 China Information Security Center State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing100876 China School of Information Science and Technology North China University of Technology Beijing100144 China School of Cybersecurity Chengdu University of Information Technology Chengdu610225 China Huawei Technologies Co. Ltd Shenzhen518129 China Department of Computer Science Faculty of Engineering and Physical Sciences University of Surrey Surrey GuildfordGU2 7XH United Kingdom

In a recent paper (Gong et al. Quantum Inf Process 19:3, 2020), a novel ciphertext retrieval scheme based on the Grover algorithm and quantum homomorphic encryption was presented. In this scheme, when the server performs the operation of marking the solution on the user’s encrypted state in the Grover iteration, it needs to remove many gate-errors generated in the homomorphic evaluation of the T gate. And the server could judge this specific solution from the quantum circuit of marking the solution. It makes this scheme unable to achieve the low-cost and secure ciphertext retrieval. Therefore, we improve the Gong et al.’s scheme and propose a secure quantum homomorphic encryption ciphertext retrieval scheme. In our scheme, the trusted third party is introduced to cooperate with the server to execute the Grover algorithm. In each Grover iteration, the trusted third party can quickly mark the solution on the plaintext state, encrypt the marked state, and transmit it to the server. Then the server performs the remaining operations of this Grover iteration on the encrypted state. The trusted third party finally decrypts the iterated state. This cooperative approach ensures that the number of auxiliary qubits required and extra quantum gates executed in our scheme are lower than the Gong et al.’s scheme. By analyzing the security of our scheme, we confirm that the server and the trusted third party will not be informed of this solution. Thus, our scheme realizes the secure ciphertext retrieval with low computational overhead. We utilize IBM’s Qiskit framework to simulate our scheme, and the experimental result shows that our scheme is correct. It is worth noting that the low-cost and secure ciphertext retrieval will play a crucial role in modern information security and privacy protection. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2025.

关键词： Ciphertext

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Early Prediction and Diagnosis Cardiovascular Disease Using Deep Learning Models

Early Prediction and Diagnosis Cardiovascular Disease Using ...

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2024 IEEE International Conference on Emerging Technologies in computer Science for Interdisciplinary Applications, ICETCS 2024

作者： Rani, Rudra Yamini Prasad, Mudarakola Lakshmi Reddy, Induru Sunnihith Tayubi, Iftikhar Aslam Sultan, Ghazala Reddy, Pundru Chandra Shaker VNR Vignana Jyothi Institute of Engineering and Technology Department of Information Technology Telangana Hyderabad India Computer Science and Engineering Institute of Aeronautical Engineering Telangana Dundigal India Computer Science and Business Systems RMK Engineering College Tamilnadu Tiruvallur India King Abdulaziz University Faculty of Computing and Information Technology Rabigh Jeddah Saudi Arabia Aligarh Muslim University Department of Computer Science Uttar Pradesh Aligarh India SR University School of Computer Science and Artificial Intelligence Telangana Warangal506371 India

ISBN: (纸本)9798350372502

Cardiovascular disease (CVD) risk assessment and prognosis in otherwise healthy people is an important part of disease management. Early detection and diagnosis of CVD, supported by the extensive health data on the condition already stored in hospital systems, has the ability to greatly improve disease outcomes. Clinical practice for the management of Cardiovascular Diseases (CVDs) stands to benefit greatly from the use of machine learning approaches. Patients and the healthcare system can save money thanks to these methods, which can be used to create evidence-based clinical guidelines and management algorithms. This will cut down on expensive and time-consuming clinical and laboratory examinations. This study suggests creating new deep learning algorithms that can automatically identify important variables and detect early-stage heart disease;these algorithms should be resilient, effective, efficient, and unique in order to improve early anticipation and interference for CVDs. An F1-score of around 89% is produced by the suggested Catboost model. Hence, it outperformed numerous other state-of-the-art methods by maximizing classification efficiency with better correctness and precision. © 2024 IEEE.

关键词： Hospitals

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Bridging the Physical and Virtual Worlds: A Hand Tracking Gesture Recognition System for XR Applications 1

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32nd International Conference on Organization and technology of Maintenance, OTO 2023

作者： Fumić, Matija Livada, Časlav Faculty of Electrical Engineering Computer Science and Information Technology Osijek Josip Juraj Strossmayer University in Osijek Kneza Trpimira 2B Osijek31000 Croatia

ISBN: (数字)9783031514944

ISBN: (纸本)9783031514937

Extended reality (XR) is a term that encompasses augmented reality (AR), virtual reality (VR), and mixed reality (MR). These technologies allow users to interact with digital content in immersive and realistic ways. One of the challenges of XR is to provide natural and intuitive ways to control and manipulate the virtual environment. This paper presents the development of a gesture recognition system for hand tracking in extended reality technologies (XR) and its practical applications. The system uses a gesture definition language that allows the user to create custom gestures based on the hand skeleton model. The system was implemented using the Oculus Quest 2 device and the Oculus SDK in the Unity game engine and is compatible with all devices that support hand tracking. The gesture recognition system was implemented using a three-bone thumb and little finger model that is compatible with all hand models that contain four bones. The implementation of this gesture recognition system in XR has several benefits, including increased immersion, improved interaction with virtual objects, and reduced physical fatigue compared to traditional input methods such as controllers or keyboards. This system provides users with a more intuitive and natural way to interact with their virtual environment. Overall, this work demonstrates the feasibility and potential of integrating gesture recognition into XR technologies and its ability to enhance user experience and interaction. The system presented in this work can serve as a foundation for future developments in this area, with potential applications in gaming, education, healthcare, and other fields. © 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Augmented reality

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Impact of Imperfect SIC in NOMA Enabled Heterogeneous Cellular Network 27

Impact of Imperfect SIC in NOMA Enabled Heterogeneous Cellul...

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27th IEEE International Conference on Intelligent engineering Systems, INES 2023

作者： Baghel, Amit Parihar, Abhinav Singh Bhatia, Vimal Bridal, Peter Augustynek, Martin Indian Institute of Technology Department of Electrical Engineering Indore India University of Zilina Faculty of Electrical Engineering and Information Technology Zilina Slovakia VŠB - Technical University of Ostrava Faculty of Electrical and Computer Science Engineering Czech Republic

ISBN: (纸本)9798350328516

To accommodate a large number of users requiring higher data rates and improved outage performance, a heterogeneous cellular network (HCN) uses a multi-tier architecture made up of a macro-base station (MBS) and pico-base station (PBS). Due to its superior spectrum efficiency, non-orthogonal multiple access (NOMA) has been identified as a suitable multiple-access strategy for the upcoming sixth-generation wireless networks. Successive interference cancellation (SIC) is an essential technique in NOMA that enables multiple users to share the same resource while maintaining high performance and fairness. Thus, it is essential to understand the performance guarantees of actual NOMA-enabled HCN systems (HCN-NOMA) using a multi-tier design under both ideal and imperfect SIC using a stochastic geometry. In multi-tier HCN, the outage probability and system throughput of orthogonal multiple access (OMA) and NOMA under perfect and imperfect SIC are evaluated and compared in this paper. It has been found that using NOMA rather than OMA results in performance gains of up to 40% at 25 dB SNR in HCN. Performance increases of up to 30% against OMA at 25 dB SNR can be observed, despite imperfections in the SIC at NOMA. © 2023 IEEE.

关键词： Spectrum efficiency

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A Hybrid Algorithm ACS-GA for Solving the Traveling Salesman Problem 1

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15th International Conference on Genetic and Evolutionary Computing, ICGEC 2023

作者： Bai, Zhonghai Snášel, Václav Vo, Bay Kong, Lingping Wang, Xiaopeng Faculty of Electrical Engineering and Computer Science VŠB-Technical University of Ostrava Ostrava70800 Czech Republic Faculty of Information Technology HUTECH University Ho Chi Minh City Viet Nam

ISBN: (数字)9789819700684

ISBN: (纸本)9789819700677

Traveling Salesman Problem (TSP), a well-known combinatorial optimization problem, aims to find the shortest path for a salesman to visit all the given cities and return to the departure city, with each city visited once and only once. To solve the problem, we propose a hybrid metaheuristic algorithm that combines the ant colony system(ACS) and genetic algorithm(GA). Distinguishing from previous hybrid algorithms, the two algorithms in our proposed hybrid algorithm run independently in parallel, exchange each other’s optimal solutions in a fixed iteration cycle and incorporate the exchanged optimal solutions into the independently running algorithm through update pheromone or add to the candidate parent. The experimental part uses data instances with a city size distribution between 51 and 226. The results of running the ACS, GA, Tabu Search (TS), and hybrid algorithms ACS-GA were compared. The results show that our hybrid algorithm ACS-GA outperforms the results of the single algorithm in terms of solution quality and stability overall. This research provides a better solution to optimizing TSP by proposing a novel hybrid metaheuristic algorithm. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Genetic algorithms

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LTSpice Based Stability Analysis of DC-DC Converter for LED Drivers 9

LTSpice Based Stability Analysis of DC-DC Converter for LED ...

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9th Junior Conference on Lighting, Lighting 2024

ISBN: (纸本)9798350352757

This article presents a stability analysis of a boost DC-DC converter for powering an LED strip. A model of a DC converter is presented and the principle of operation is described. LTSpice software was used to implement the mathematical model. LED strip data provided by the manufacturer is used. Simulation results of the realized studies by Fourier transformation are presented. Investigating the influence of transient in LED drivers is useful in order to ensure the stability of the manufactured device under various external influences. © 2024 IEEE.

关键词： Light emitting diodes

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Autonomous Vehicle Control in CARLA Simulator Using Reinforcement Learning 66

Autonomous Vehicle Control in CARLA Simulator Using Reinforc...

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66th International Symposium ELMAR, ELMAR 2024

作者： Cincurak, Dorian Grbic, Ratko Vranjcs, Mario Vranjes, Denis TTTech Auto Central and Eastern Europe OsijekHR-31000 Croatia Computer Science and Information Technology Osijek Faculty of Electrical Engineering OsijekHR-31000 Croatia

ISBN: (纸本)9798350375411

Autonomous vehicles (AVs) have emerged as a transformative technology that promises safer and more efficient transportation systems. Central to the development of autonomous driving is the ability to make real-time decisions in complex and dynamic environments. Reinforcement learning (RL) has gained considerable attention as a promising approach that enables AVs to learn control policies directly from interaction with their environment. In this paper, two RL algorithms for autonomous driving were developed in the CARLA autonomous driving simulator: one based on the Deep Q-Learning (DQN) algorithm and the other based on the Deep Deterministic Policy Gradient (DDPG) algorithm. The evaluation of the developed algorithms was carried out using the user-defined metrics and shows promising results in learning from interaction. © 2024 IEEE.

关键词： Deep reinforcement learning

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Smart Waste Segregation for Home Environment 3

Smart Waste Segregation for Home Environment

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3rd International Conference on Advanced Research in Computing, ICARC 2023

作者： Rijah, Uthuma Lebbe Muhammed Abeygunawardhana, Pradeep K. W. Sri Lanka Institute of Information Technology Faculty of Graduate Studies and Research Malabe Sri Lanka Sri Lanka Institute of Information Technology Department of Computer Systems Engineering Malabe Sri Lanka

ISBN: (纸本)9798350347371

The segregation of waste and recycling is essential for effective waste management. Due to the busy schedule most of the people do not have a time to separate their waste. However, there is a significant issue with the segregation of the collected garbage. The implementation of an intelligent trash-management architecture is essential for the removal or reduction of waste and the maintenance of a clean, corporate environment. An IoT-stationed smart waste management device is proposed in this study that uses sensor devices to identify rubbish in the dustbins. With the aid of sensors, the waste substances in it will be separated through IoT as soon as it is discovered. Sensors and the IoT module are connected through a microcontroller. To detect the presence of garbage, an ultrasonic sensor is used. All garbage entered will be caught by the web camera and processed by the machine learning module once it has been processed. Using the model, we can identify the many forms of waste, such as paper, plastic, and glass, which account for most of the garbage materials found in a home area. This aids in removing the trash from the trash can in the most efficient and effective manner possible. This research presents an IoT, and Machine Learning based completely intelligent trash segregation and management System that recognizes the dustbins' wastes using sensor systems. This project aims to develop an automated waste segregation system using a CNN algorithm that will capture waste images from a camera with object detection and classify waste materials such as paper, plastic, and glass so that the waste can be recycled appropriately. The proposed architecture with CNN gives an accuracy of 84.67%. This system will help in garbage disposal by categorizing it, contributing to a cleaner environment. © 2023 IEEE.

关键词： Cameras

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