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Dual-Band Printed Antenna Design for Bluetooth and WLAN Applications 7

Dual-Band Printed Antenna Design for Bluetooth and WLAN Appl...

引用

7th ieee international conference on Electronic Information and Communication Technology, ICEICT 2024

作者： Khan, Naveed Hamid Nawaz Feng, Botao Ding, Xiao Gu, Wenzhe Deng, Li Chung, Kwok L. Shenzhen University College of Electronics and Information Engineering Shenzhen518060 China Macau University of Science and Technology Faculty of Humanities and Arts Macau999078 China Huizhou University School of Computer Science and Engineering Huizhou China Beijing University of Posts and Telecommunications College of Information and Communication Engineering Beijing China Huizhou University School of Computer Science and Engineering Huizhou516007 China

ISBN: (纸本)9798350384437

This study presents the fabrication process of a printed antenna on a FR-4 substrate with accurate measurements of 25×37×1 mm3. The antenna design, known for its simplicity, has four semicircles with four small square patches at each end. In addition, it includes two rectangular patches that are fitted with pin diode switches in order to enable the ability to operate in two different frequency bands. The antenna's ground has a carefully placed opening. The antenna being examined demonstrates resonance at both the frequencies of 2.4 GHz and 5 GHz, with reflection coefficients of -19.6 dB and -16.5 dB correspondingly. The VSWR for both working frequencies is below 2, satisfying the requirements of Bluetooth and WLAN applications. The tiny size and creative design elements of this antenna allow for versatility and adaptation in many wireless communication systems. © 2024 ieee.

关键词： Microwave antennas

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A Novel Approach for Specification and Verification of Symmetric Distributed Algorithms Using SPIN 3

A Novel Approach for Specification and Verification of Symme...

引用

3rd international conference on Distributed Computing and High Performance Computing, DCHPC 2024

作者： Namvaritazehkand, Leila Ebnenasir, Ali University of Tabriz Faculty of Electrical and Computer Engineering Department of Computer Engineering East Azerbaijan Tabriz Iran Michigan Technological University Department of Computer Science HoughtonMI49931 United States

ISBN: (纸本)9798350381580

This paper focuses on the challenges of modeling and verifying symmetric distributed algorithms with point-to-point and bidirectional communications using the SPIN model checker. In this paper, we first state the problems of implementing the model of such algorithms in the Promela language. Then, we present a solution for each of these problems, where these solutions present a hybrid data structure that facilitates the definition of any set of variables or channels as a matrix. Also, we model and verify one of the valuable and practical algorithms called the causal broadcast (CB) algorithm as a case study using the proposed method. In addition, we specify the main properties of the CB algorithm, namely validity, integrity, causal delivery, and termination, in Linear Temporal Logic (LTL) and then verify them using the SPIN model checker. © 2024 ieee.

关键词： Model checking

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Adaptive Dynamic Programming-Based Distributed Coordinated Control for Dual-Arm Reconfigurable Manipulators 6

Adaptive Dynamic Programming-Based Distributed Coordinated C...

引用

6th international conference on Robotics, Control and automation engineering, RCAE 2023

作者： Liu, Guanting Li, Yuanchun Qu, Meng An, Tianjiao Zhu, Mingchao Ma, Bing Changchun University of Technology Department of Control Science and Engineering Changchun China Changchun Institute of Optics Fine Mechanics and Physics Chinese Academy of Sciences Department of Control Science and Engineering Changchun China

ISBN: (纸本)9798350315301

In this paper, a distributed coordinated control method of dual-arm reconfigurable manipulators based on adaptive dynamic programming is proposed. Through kinematic analysis, the dynamic models of the reconfigurable manipulators and the grasped object are established, respectively. According to the load distribution method, the motion induction force is effectively distributed on each arm. Then, the dynamic model of a single reconfigurable manipulator is obtained. The performance index function is defined to reflect the joint position tracking error and internal force tracking error. The neural network is utilized to approximate the performance index function to obtain the optimal control strategy through the Policy Iteration (PI) algorithm. Thus, a distributed optimal coordinated controller is acquired. The tracking error of the manipulator system is proved be ultimately uniformly bounded (UUB) through Lyapunov's stability. Finally, the effectiveness of the developed control method is verified by simulations. © 2023 ieee.

关键词： Dynamic models

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Optimizing Wind Turbine Placement for Enhanced Energy Production Using Modified Genetic Algorithm 7

Optimizing Wind Turbine Placement for Enhanced Energy Produc...

引用

7th international conference on Contemporary Computing and Informatics, IC3I 2024

作者： Sudarshan, T.A. Srinivasulu, Ch. Thethi, H. Pal Bhutani, Vijay Subhashini, P. Ramesh, G. New Horizon College of Engineering Department of Mechanical Engineering Bangalore India Institute of Aeronautical Engineering Department of Computer Science and Engineering Telangana Hyderabad50043 India Lovely Professional University Phagwara India Amity University Amity School of Engineering and Technology Uttar Pradesh Greater Noida India Mlr Institute of Technology Department of Computer Science and Engineering Telangana Hyderabad India Griet Department of Computer Science and Engineering Bachupally Hyderabad India

ISBN: (纸本)9798350350067

The optimal site of wind farms is determined using an updated genetic algorithm approach, which maximizes output capacity while reducing the amount of turbines built and the area used by each farm. In particular, two examples are examined: One kind of wind is a homogeneous wind that blows in just one direction, while the other two are also possible. In the first scenario (a), 599 individuals were first split into 25 subpopulations and then evolved three thousand times. The evolution of case (b) takes place over three thousand generations, beginning with 600 individuals distributed over 19 subpopulations. Every design's fitness, overall power generation, power output efficiency, and ideal configurations are all part of the findings. The results show that the modified genetic algorithm provides much better results compared to the conventional Genetic Algorithm method. © 2024 ieee.

关键词： Windmill

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Exploring the Challenge of Controller Placement in Software-Defined Networking: A Comprehensive Review 2

Exploring the Challenge of Controller Placement in Software-...

引用

2nd international conference on automation, Computing and Renewable Systems, ICACRS 2023

作者： Gunavathie, M.A. Jacophine Susmi, S. Sivasankari, S.S. Venkatesh, M. Information Technology Panimalar Engineering College Chennai India Information Technology University College of Engineering Tindivanam India Electronics and Communication Engineering Dayananda Sagar University Bangalore India Computer Science and Business Systems Thiagarajar College of Engineering Madurai India

ISBN: (纸本)9798350340235

The placement of controllers is a critical issue that can significantly impact network performance and efficiency in Software DefinedNetworking (SDN). The optimal placement of controllers should take into account various factors such as network topology, resource requirements, and potential failures. For the purpose of determining the optimal placement of controllers, various approaches have been proposed in the literature, including mathematical optimization models, game theory, and simulation-based methods. These approaches aim to minimize latency, maximize network capacity, and improve network reliability in the face of failures. Overall, the optimal placement of controllers in SDNs remains an active area of research, and there is a need for continued exploration of new and innovative approaches to this problem. By taking into account the various factors that influence network performance and efficiency, researchers can continue to develop solutions that improve the design and operation of SDN networks. © 2023 ieee.

关键词： Controller placement Software Defined Networking

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Predictive Value Chain Analysis to Improve Generalization Accuracy In Quality Assurance

Predictive Value Chain Analysis to Improve Generalization Ac...

引用

2024 international conference on Control and automation, Electronics, Robotics, Internet of Things, and Artificial Intelligence, CERIA 2024

作者： Harmayani Sihombing, Poltak Mahyudin Elveny, Marischa Universitas Sumatera Utara Postgraduate Program in Computer Science Faculty of Computer Science and Information Technology Medan Indonesia Universitas Sumatera Utara Faculty of Computer Science and Information Technology Medan Indonesia Universitas Sumatera Utara Faculty of Computer Science and Information Technology Postgraduate Doctorate in Computer Science Medan Indonesia

ISBN: (纸本)9798331511166

Adaptive predictive analysis model utilizing Spiking Neural Networks (SNNs) to enhance quality assurance processes in Smart Campus environments. Traditional predictive models often struggle with the dynamic and complex nature of educational data, leading to inaccurate predictions and inefficient decision-making. SNNs, inspired by biological neurons, are particularly suited for processing temporal data and adapting to evolving patterns. The proposed model integrates spike-timing-dependent plasticity (STDP) and dynamic weight adjustment to continuously learn and refine predictions in response to real-time data, ensuring improved accuracy and robustness. The study uses historical data from the Internal Quality Assurance System (SPMI) over a three-year period, focusing on key performance indicators such as student enrollment trends, faculty productivity, and resource utilization. Experimental results demonstrate that the SNN-based model outperforms traditional neural networks, achieving a 20% reduction in Mean Squared Error (MSE) and a higher R-squared value. These findings indicate that the model not only enhances predictive accuracy but also offers significant improvements in operational efficiency and resource management. By providing timely and precise insights, this model supports proactive decision-making in educational institutions, enabling administrators to optimize resource allocation, monitor academic quality, and anticipate future challenges. This research contributes to the growing field of artificial intelligence in education, offering a scalable, adaptive approach to managing complex data and improving institutional performance in real-time. © 2024 ieee.

关键词： Data accuracy

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Enhancing Network Security: Leveraging Isolation Forest for Malware Detection 2

Enhancing Network Security: Leveraging Isolation Forest for ...

引用

2nd international conference on Advancement in Computation and computer Technologies, InCACCT 2024

作者： Pawar, Janardan Adinath Avhankar, Madhavi Satish Gupta, Ashulekha Barve, Amit Patil, Harshal Maranan, Ramya Indira College of Commerce and Science Department of Computer Science Maharashtra Pune India Graphic Era Deemed to be University Department of Management Uttarakhand Dehradun India Parul University Parul Institute of Technology Faculty of Engineering and Technology Department of Computer Science and Engineering P.O. Limda Gujarat India Department of Computer Science and Engineering Maharashtra Pune India SIMATS Saveetha School of Engineering Department of Research and Innovation Tamil Nadu Chennai India

ISBN: (纸本)9798350371314

In this work it has been shown that the growth of computer attacks continues to advance constantly, as well as the large number of vulnerability detection and protection tools that exist, therefore, not protecting a computer system allows easy access by intruders to the system, putting the confidentiality, integrity and availability of information at risk, in addition to increasing costs for performing corrective maintenance on damaged devices. Furthermore, studying the traffic flow of a network using the WireShark tool revealed instances of malware attacks, prompting the development of a proposed malware detection system for the network. To obtain the Dataset, all network statistics had to be forwarded to a host, where this host was connected to a Port Mirror. Once these statistics were obtained, they were captured thanks to the Netflow protocol, in order to have better management of the entire captured traffic flow. Isolation Forest shows an excellent probability of 92% and the model can distinguish between non-anomalous data and data that is malware which is superior than support vector machine (SVM). © 2024 ieee.

关键词： Support vector machines

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Advanced Malware Detection Methods for Polymorphic Virus Identification 5

Advanced Malware Detection Methods for Polymorphic Virus Ide...

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5th ieee international conference on Communication, Computing and Industry 6.0, C2I6 2024

作者： Anil, D. Shreeshayana, R. Kiran, B. Preethi Uvce Bangalore University Department of Computer Science and Engineering Bengaluru India Atme College of Engineering Department of Electrical and Electronics Engineering Mysuru India Pes University Department of Computer Science and Engineering Bengaluru India Reva University School of Computing and Information Technology Bengaluru India

ISBN: (数字)9798350379884

ISBN: (纸本)9798350379884

Polymorphic viruses pose a significant challenge to traditional malware detection methods due to their ability to modify their code structure with each infection, effectively evading signature-based detection. This paper explores advanced malware detection methods tailored for identifying polymorphic viruses, focusing on the integration of machine learning, deep learning and hybrid approaches. Through a comprehensive analysis of static and dynamic features extracted from executables and URLs, this study employs classifiers such as Random Forests and Support Vector Machines (SVMs) to enhance detection accuracy. The SVM classifier demonstrated superior performance, achieving a detection accuracy of 96.23% compared to the 93.67% accuracy of the Random Forest classifier. This research highlights the potential of combining static and dynamic analysis with machine learning techniques to address the limitations of traditional methods, offering a robust framework for detecting and mitigating polymorphic and zero-day threats. © 2024 ieee.

关键词： Adversarial machine learning

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Joint Planning of Flexible Distribution Network Considering N-1 Criterion and Disaster Scenarios 5

Joint Planning of Flexible Distribution Network Considering ...

引用

5th international conference on Power engineering, ICPE 2024

作者： Shen, Hao Lu, Ning Wuhan University of Technology College of Automation Wuhan China

ISBN: (纸本)9798331531140

To explore the difference between branch N-1 criterion and resilience improvement in distributed resource planning of distribution network, a joint planning scheme for distributed resources considering both N-1 criterion constraints and disaster scenarios is proposed. Firstly, considering normal operation scenarios, N-1 branch faults scenarios and disaster scenarios, a mixed integer linear programming model for distribution network operation was established using stochastic programming based on the optimal power flow model. Then, in order to solve the huge computational burden brought by N-1 scenarios, the column generation algorithm was used to split the original problem into main problem and subproblem and reduce the computational burden by iteration. The accuracy of the algorithm was guaranteed through a secondary verification. Finally, simulation experiments were conducted using ieee33 bus system and load curtailment analysis was carried out. The experimental results show that while the substation operates normally, the distribution network planning considering branch N-1 criterion still has good resilience in disaster scenarios with multiple branch failures. © 2024 ieee.

关键词： Power distribution planning

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Exploring BioClinical BERT's NLP Capabilities with Explainability Techniques

Exploring BioClinical BERT's NLP Capabilities with Explainab...

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2024 ieee international conference on Emerging Technologies in computer science for Interdisciplinary Applications, ICETCS 2024

作者： Sankaranarayanan, Aditi Shetty, Diya Chetwani, Kirti Shambhavi, B.R. BMS College of Engineering Dept. of Information Science and Engineering Bengaluru India Bengaluru India

ISBN: (纸本)9798350372502

Natural Language Processing has gained significant attention in the world of Information Technology and is experiencing rapid growth. Its applications span across various domains, with a notable surge in its utilization within the healthcare industry. This has fueled the development of language models that are trained on a large amount of clinical data, like Bio+Clinical BERT. However, there remains a crucial concern regarding the trustworthiness of NLP models. Traditional accuracy measures alone may not be sufficient to instill confidence in their reliability. In this study, we address this concern by exploring the application of Explainability to NLP tasks in the healthcare sector. We employ Explainability techniques to gain deeper insights into the underlying mechanisms and evaluate the trustworthiness of fine-Tuned models based on Bio+Clinical BERT. Specifically, LIME and SHAP techniques have been utilized to produce explanations, which prove instrumental in enhancing our understanding of the models, as well as identifying their strengths and weaknesses. © 2024 ieee.

关键词： Natural language processing systems

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