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2024 International Conference on Integrated Circuits, Communication, and Computing systems, ICIC3S 2024

作者： Bhickta, Shalini Jaglan, Naveen Kumar, Amit Jaypee University of Information Technology Department of Electronics and Communication Engineering Solan Waknaghat India Jaypee University of Information Technology Department of Computer Science and Engineering Solan Waknaghat India

ISBN: (纸本)9798350364088

In modern wireless tele- communication, the key element for better and higher performance of the communication system is an Antenna. An antenna which removes all complex issues of weather, scattering and effects of multiple paths is in demand for current wireless system issues. The Antenna with Reconfiguration capabilities in current scenario solves these issues. The popularity of Reconfiguration in antennas has seen a significant growth due to its versatile capabilities. Therefore, reconfiguration in the structure of an Antenna without changing the physical dimensions and saving space realize the goal of high speed, gain, channel capacity and signal-to-Noise Ratios (SNR). In this paper a brief knowledge of various methods of designing a reconfiguration antenna is reviewed. The different switching techniques used for the activating the reconfiguration mechanism is discussed. The advancement of reconfiguration in multi-input multi-output (MIMO) systems is also studied. © 2024 IEEE.

关键词： Signal to noise ratio

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Improved Density Peaking Algorithm for Community Detection Based on Graph Representation Learning

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computer systems science & Engineering 2022年第12期43卷 997-1008页

作者： Jiaming Wang Xiaolan Xie Xiaochun Cheng Yuhan Wang Guangxi Key Laboratory of Embedded Technology and Intelligent System Guilin541006GuangxiChina School of Information Science and Engineering Guilin University of TechnologyGuilin541006GuangxiChina Department of Computer Science Middlesex UniversityLondon

There is a large amount of information in the network data that we canexploit. It is difficult for classical community detection algorithms to handle network data with sparse topology. Representation learning of network data is usually paired with clustering algorithms to solve the community detection ***, there is always an unpredictable distribution of class clusters outputby graph representation learning. Therefore, we propose an improved densitypeak clustering algorithm (ILDPC) for the community detection problem, whichimproves the local density mechanism in the original algorithm and can betteraccommodate class clusters of different shapes. And we study the communitydetection in network data. The algorithm is paired with the benchmark modelGraph sample and aggregate (GraphSAGE) to show the adaptability of ILDPCfor community detection. The plotted decision diagram shows that the ILDPCalgorithm is more discriminative in selecting density peak points compared tothe original algorithm. Finally, the performance of K-means and other clusteringalgorithms on this benchmark model is compared, and the algorithm is proved tobe more suitable for community detection in sparse networks with the benchmarkmodel on the evaluation criterion F1-score. The sensitivity of the parameters ofthe ILDPC algorithm to the low-dimensional vector set output by the benchmarkmodel GraphSAGE is also analyzed.

关键词： Representation learning data mining low-dimensional embedding community detection density peaking algorithm

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A new method for human activity identification using convolutional neural networks

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International Journal of Cloud Computing 2023年第2-4期12卷 191-200页

作者： Prakash, P.S. Balakrishnan, S. Venkatachalam, K. Balasubramanian, Saravana Balaji Department of Computer Science and Engineering Vivekanandha College of Engineering for Women Namakkal Tiruchengode637205 India Department of Computer Science and Business Systems Sri Krishna College of Engineering and Technology Tamilnadu Coimbatore India Department of Applied Cybernetics Faculty of Science University of Hradec Králové Hradec Králové50003 Czech Republic Department of Information Technology Lebanese French University Erbil Iraq

Body fitness monitoring applications are using mobile sensors to identify human activities. Human activity identification is a challenging task because of the wide availability of human activities. This paper proposes a novel technique that extracts the discriminative dimensions for human activity identification. Particularly, a novel technique with convolutional neural networks (CNN) is used for catching dependency. A deep convolutional neural network (DCNN) consists of two different types of layers, convolutional and pooling are used. The depth of each filter increases from left to right in the network. Three activities like walking, running, remaining still are collected from smart mobile sensors. The axis like x, y, and z information was transferred with column vector magnitude information and utilised for studying or training CNN. Experimental results show that CNN-based method achieves 93.67% accuracy than the baseline random forest approach's 89.20%. Copyright © 2023 Inderscience Enterprises Ltd.

关键词： Convolutional neural networks

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Establishing a Novel CAD-Based Paradigm for Design of VLSI Integrated Circuits

Establishing a Novel CAD-Based Paradigm for Design of VLSI I...

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2024 International Conference on Optimization Computing and Wireless Communication, ICOCWC 2024

作者： Agarwal, Ankita Gour, Murli Manohar Manivasagam Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India Vivekananda Global University Department of Mathematics Jaipur India Department of Computer Science and Information Technology Bangalore India

ISBN: (纸本)9798350383348

This paper describes growing and enforcing a novel laptop-aided design (CAD) paradigm for the format of Very-huge-Scale included (VLSI) circuits. This technique integrates the setup standards of sound judgment synthesis, circuit optimization, and elapsed time estimation techniques to provide clients with a unified framework for designing modern VLSI structures. The proposed paradigm consists of machine studying techniques, such as Gaussian techniques and convex programming, to optimize the selection of components and evaluate layout placements. The designed circuit is then expected via simulation, measurement, and evaluation. The proposed CAD paradigm is validated in an 8-bit ripple-convey adder system layout. The results of the take a look at provide robust proof that this novel CAD-primarily based paradigm is a powerful technique for designing modern VLSI systems. © 2024 IEEE.

关键词： Designing Incorporated Integrates Measurement Paradigm Strategies

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Modeling Permanent Magnet Electric Drives with Fuzzy Logic Control

Modeling Permanent Magnet Electric Drives with Fuzzy Logic C...

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2024 International Conference on Optimization Computing and Wireless Communication, ICOCWC 2024

作者： Bishnoi, Sunita Krishnamoorthy, Ramkumar Singh, Akhilendra Pratap Vivekananda Global University Department of Chemistry Jaipur India Department of Computer Science and Information Technology Bangalore India Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India

ISBN: (纸本)9798350383348

Fuzzy good judgment management (FLC) has been used to model everlasting magnet electric-powered drives and has proved to be an effective tool for designing complicated dynamic systems. This form of management is primarily based on a fuzzy set principle, which enables the use of imprecise or indistinct phrases to explain the conduct of a gadget. The bushy logic method for modeling electric drives is predicated on fuzzy rules that remember unique variables and conditions that allow you to determine the most suitable output. In this manner, the behavior of complicated dynamic structures consisting of PM electric drives may be accurately modeled and managed. The fuzzy common sense version for PM electric drives incorporates numerous additives, inclusive of a fuzzy inference engine, fuzzy guidelines, and defuzzification. The FLC model starts by building and defining the bushy system regulations. Every rule is represented mathematically as a feature of the inputs and outputs. The inputs are commonly defined in terms of perspective measurements, voltage, frequency, and contemporary variables. Then, the bushy inference engine takes the entered variables and makes use of the bushy system rules to decide the right output for every input cost. In the end, the defuzzification process is used to decide the precise output price by taking the fuzzy output and deriving an actual fee from it. © 2024 IEEE.

关键词： Actual Defuzzification Frequency Judgment Management Modeling

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Enhancing Plant Recognition in Intelligent Agricultural Irrigation systems Using Stable Diffusion and Lora Models with CFloss 17

Enhancing Plant Recognition in Intelligent Agricultural Irri...

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17th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2024

作者： Lu, Yingzhu Tang, Chengyu Fan, Yawen Zhou, Qin Nanjing University of Posts and Telecommunications Department of Computer Science and Technology Nanjing China Nanjing Forestry University Department of Computer Science and Technology Nanjing China School of Communications and Information Engineering Nanjing University of Posts and Telecommunications Nanjing China School of Information Science and Engineering East China University of Science and Technology Shanghai China

ISBN: (纸本)9798331507398

This paper proposes a novel approach to optimize the plant recognition function of intelligent agricultural irrigation system, utilizing Stable Diffusion model and Lora (Low-Rank Adaptation) model. Stable Diffusion model is a latent diffusion model that converts text into images, while Lora is a method of fine-tuning large models by reducing trainable parameters while maintaining model performance as much as possible. By combining the Stable Diffusion model and Lora model, this paper trains custom models for each plant species using a small amount of data and generates corresponding images of each variety to assist training, thus optimizing classification results. In addition, to address the issue of imbalanced data, this study also introduces Focal Loss to mitigate the impact of both class imbalance and difficulty in classification. Building upon Focal Loss, CFloss is created as the model's loss function. This method was tested on the OxfordFlower102 dataset used by the original model, and the results demonstrate that it effectively improves classification accuracy and significantly enhances the plant recognition function of the irrigation system. © 2024 IEEE.

关键词： Image classification

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Enhancing visual clarity in hazy media: a comprehensive approach through preprocessing and feature fusion attention-based dehazing

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Multimedia Tools and Applications 2025年第17期84卷 18071-18093页

作者： Ayoub, Abeer El-Shafai, Walid El-Samie, Fathi E. Abd Hamad, Ehab K. I. Rabaie, El-Sayed M. Department of Electronics and Electrical Communication Engineering Faculty of Electronic Engineering Menoufia University Menouf32952 Egypt Security Engineering Lab Computer Science Department Prince Sultan University Riyadh11586 Saudi Arabia Department of Information Technology College of Computer and Information Sciences Princess Nourah Bint Abdulrahman University P.O. Box 84428 Riyadh11671 Saudi Arabia Electrical Engineering Department Faculty of Engineering Aswan University Aswan81542 Egypt

Particles in the atmosphere, such as dust and smoke, can cause visual clarity problems in both images and videos. Haze is the result of the interaction between airborne particles and light, which is scattered and attenuated. Hazy media present difficulties in a variety of applications due to the reduced contrast and loss of essential information. In response, dehazing techniques have been introduced to bring hazy videos and images back to clarity. Here, we provide a novel technique for eliminating haze. It comprises preprocessing steps before dehazing. Preprocessing is applied to hazy images through homomorphic processing and Contrast Limited Adaptive Histogram Equalization (CLAHE). We present a dehazing technique referred to as the pre-trained Feature Fusion Attention Network (FFA-Net) that directly lets dehazed images be restored from hazy or preprocessed hazy inputs without requiring the determination of atmospheric factors, such as air light and transmission maps. The FFA-Net architecture incorporates a Feature Attention (FA) method to do this task. We assess the proposed technique in a variety of circumstances, including visible frames, Near-Infrared (NIR) frames, and real-world hazy images. Evaluation criteria like entropy, correlation, and Peak Signal-to-Noise Ratio (PSNR) are used to compare the quality of dehazed frames or images to their hazy counterparts. Furthermore, histogram analysis and spectral entropy are adopted to determine the effectiveness of the proposed technique in comparison to existing dehazing techniques. Comparative results are presented for both real-world and simulated environments. The benefits of the proposed technique are demonstrated by a comparison of the results obtained from the standalone pre-trained FFA-Net and the proposed comprehensive methodology. Moreover, a thorough assessment is carried out for comparing the effectiveness of the proposed FFA-Net technique to those of some current dehazing techniques on real hazy images. T

关键词： Image enhancement

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RESTful Web Service Architecture for Secure and Efficient Agricultural Data Integration in Jombang Regency 6

RESTful Web Service Architecture for Secure and Efficient Ag...

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6th International Conference on Informatics, Multimedia, Cyber and information system, ICIMCIS 2024

作者： Sifaunajah, Agus Amalia, Rifka Dwi Lestari, Devina Ayu Arifin, Muhyiddin Zainul Munawarah Khafidhoh, Nur Yaqin, Nurul University of KH. A. Wahab Hasbullah Faculty of Information Technology Department of Information Systems Jombang Indonesia Universitas Pembangunan Nasional Veteran Jakarta Faculty of Computer Science Department of Information Systems Jakarta Indonesia University of KH. A. Wahab Hasbullah Faculty of Information Technology Department of Informatics Jombang Indonesia

ISBN: (纸本)9798331533243

Efficient and secure agricultural data integration is becoming increasingly important to improve the quality of agricultural land management in Jombang Regency, given the significant role of this sector in the local economy. This study proposes a RESTful Web service architecture to address the challenges of data integration across various systems within the Jombang Regency Regional Government. By leveraging the principles of Representational State Transfer (REST) architecture, the system aims to facilitate efficient, structured, and secure data exchange between various agricultural applications used by the local government. RESTful Web services were selected for their ability to handle multiple data formats such as XML and JSON, as well as for their ease of integration with other systems. Additionally, the system is designed to ensure that only authorized users can access sensitive data, thereby maintaining the integrity and confidentiality of information. The research findings demonstrate that the implementation of this RESTful Web service architecture enables stakeholders to access accurate and up-to-date agricultural information more extensively. © 2024 IEEE.

关键词： Sensitive data

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Broadband Microstrip Antenna Design for Wireless Communications

Broadband Microstrip Antenna Design for Wireless Communicati...

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2024 International Conference on Optimization Computing and Wireless Communication, ICOCWC 2024

作者： Sharma, Anu Mahajan, Prerna Yadav, Dhyan Chandra Teerthanker Mahaveer University Department of Computing Sciences and Information Technology Uttar Pradesh Moradabad India Department of Computer Science and Information Technology Bangalore India Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India

ISBN: (纸本)9798350383348

The Broadband Microstrip Antenna Design for Wireless Communications is an essential component of the modern telecommunications system. It is important to design an antenna that is efficient, cost-effective, and easy to install in order to successfully implement large-scale wireless networks that operate on a wide range of frequencies. These antennas must also have good radiation patterns to ensure that they can provide the required coverage for the users in the network. The Broadband Microstrip Antenna Design follows the principles of electromagnetic wave propagation and the design requirements of modern wireless communications systems. Design efforts for these antennas hinge on the principles of miniaturization, resistance to environmental factors (such as wind and rain), and wideband operation. Furthermore, modern antenna design includes testing radiation patterns and uploading the data to software-based simulation tools to ensure the design meets their requirements. The challenge of developing an efficient antenna design for wireless communication networks is faced by engineers and researchers alike. Microstrip antennas, also called patch antennas, are a popular choice for wireless communication applications, as they offer high efficiency, controllable power gain, and good cross-polarization. © 2024 IEEE.

关键词： Antenna Design Environmental Microstrip Networks Resistance

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Multimodal Technique for Human Authentication Using Fusion of Palm and Dorsal Hand Veins 2nd

Multimodal Technique for Human Authentication Using Fusion o...

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2nd InternationalWorkshop on New Approaches for Multidimensional Signal Processing, NAMSP 2021

作者： Ahmed, Mona A. Roushdy, Mohamed Salem, Abdel-Badeeh M. Faculty of Computer and Information Sciences Computer Science Department Ain Shams University Cairo Egypt Faculty of Computer and Information Technology Computer Science Department Future University New Cairo Egypt

ISBN: (纸本)9789811685576

Multimodal biometric systems have been widely used to achieve high recognition accuracy. This paper presents a new multimodal biometric system using an intelligent technique to authenticate human by fusion of palm and dorsal hand veins pattern. We developed an image analysis technique to extract region of interest (ROI) from palm and dorsal hand veins image. After extracting ROI we design a sequence of preprocessing steps to improve palm and dorsal hand veins images using Homomorphic, Median filter, Wiener filter and Contrast Limited Adaptive Histogram Equalization (CLAHE) to enhance vein image. Our smart technique is based on the following intelligent algorithms, namely;principal component analysis (PCA) algorithm for feature extraction and k-Nearest Neighbors (K-NN) classifier for matching operation. The database chosen was the CASIA Multi-Spectral Palmprint Image Database V1.0 and Bosphorus Hand Vein Database. The achieved result for the fusion of both biometric traits was Correct Recognition Rate (CRR) is 97.6% with FAlse Reject Rate (FRR) 2.4%. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Median filters

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