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Heating Energy Performance Assessment using KNN Classification method: Investigating Test Size, Neighbor Parameter, and Class Count Effects 8

Heating Energy Performance Assessment using KNN Classificati...

引用

8th IEEE international conference on image and signal Processing and their Applications, ISPA 2024

作者： Boudjella, Aissa Boudjella, Manal Yasmine Liu, Chuang Samarkand International University of Ttechnology Dept. of Applied Mathematics Samarkand Uzbekistan Bircham International University Dept. Electrical Engineering Miami United States University of Sciences and Technology USTO Dept. of Physics Oran Algeria Samarkand International University of Technology Dept. of Thermal Engineering Samarkand Uzbekistan

ISBN: (纸本)9798350309249

We analyze the energy requirements for assessing the heating load of building systems using the k-Nearest Neighbor (KNN) method for classification. Unsupervised transformations of the dataset are employed in learning algorithms. Two distinct data representation classes are generated separately from the original dataset based on captured heating load magnitudes. The unsupervised transformations of the dataset yield 4 and 8 classes, *** evaluate performance, various test and training sizes are employed, comparing measurement outcomes and predicting class label descriptions for two dataset representations as the parameter for the nearest neighbor (k) ranges from 1 to 20. Results obtained from the simulation indicate that accuracy is influenced by factors such as test size, the k parameter, and dataset class count. The training and test accuracy rates reach maximum values of 95% and 85%, respectively. Keeping k constant, the test size has a negligible impact on accuracy. The classes exhibit three critical regions: 1) Region I, where accuracy fluctuates with increasing k in the interval [1]-[5], and 2) Region II, where accuracy declines with increasing k in the interval [5]-[10]. In Region III k [10]-[20], accuracy remains relatively constant. While reducing the number of classes may result in a slight improvement in accuracy by simplifying the classification task, the trade-offs and complexities of increasing the number of classes for data representation should be carefully considered. Although this approach can lead to a more flexible design, it may slightly reduce accuracy. © 2024 IEEE.

关键词： Learning algorithms

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Research on License Plate image Super-Resolution Reconstruction Method based on SRGAN 5

Research on License Plate Image Super-Resolution Reconstruct...

引用

2023 5th international conference on Artificial Intelligence and Computer Applications, ICAICA 2023

作者： Zhang, Yu Liu, Yabian Liu, Xiangju Liang, Tong He, Xin Yang, Jing School of Computer and Information Engineering Qilu Institute of Technology Jinan China

ISBN: (纸本)9798350323313

In the context of intelligent transportation systems, license plate image reconstruction plays a pivotal role. This paper introduces a license plate image super-resolution reconstruction method, referred to as P-SRGAN, based on the foundation of SRGAN. Expanding on the foundation laid by SRGAN and incorporating insights from PatchGAN, the discriminator network is configured as a 5-layer fully convolutional neural network within our framework. This architectural decision enhances the precision of assessments, providing effective guidance to the generator in the reconstruction of images with heightened quality and finer details. Through experimentation using the Chinese City Parking Dataset (CCPD), our P-SRGAN surpasses existing high-performing super-resolution reconstruction algorithms, as evidenced by superior Peak signal-to-Noise Ratio (PSNR) and Structural Similarity Index (SSIM) results. These findings underscore the superior quality of reconstruction achieved by P-SRGAN and its more favorable outcomes. © 2023 IEEE.

关键词： image enhancement

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An 1.38nJ/Inference Clock-Free Mixed-signal Neuromorphic Architecture Using ReL-PSP Function and Computing-in-Memory

An 1.38nJ/Inference Clock-Free Mixed-Signal Neuromorphic Arc...

引用

2023 IEEE Biomedical Circuits and systems conference, BioCAS 2023

作者： Fang, Wenbing Xuan, Zihao Chen, Song Kang, Yi University of Science and Technology of China School of Microelectronics Hefei China

ISBN: (纸本)9798350300260

Spiking neural networks (SNNs) associated with neuromorphic hardware architectures inspired by the human brain are considered to have promising prospects in ultra-low power applications such as internet of Things (IoTs) and edge computing devices due to their spike-based information processing and transmission. In this paper, we propose a fully event-driven, clock-free and mixed-signal CMOS design of a highly energy-efficient spiking neural network hardware architecture for visual recognition tasks. The SNN algorithm we employ is based on the Rectified Linear Postsynaptic Potential function (ReL-PSP), which operates in the continuous time domain and dovetails perfectly with our completely clock-free hardware design. In combination with current domain SRAM CIM (Computing-in-Memory), energy expenditure of the I&F (Integrate-and-Fire) neuron and synaptic array has been notably reduced. Simulation results under 28nm CMOS technology indicate that our design achieves 96.92% classification accuracy on MNIST handwritten digit recognition, with only 1.38nJ energy consumption per image and 10us latency. © 2023 IEEE.

关键词： clock-free mixed-signal circuit Neuromorphic processor ReL-PSP function Spiking Neural Network (SNN) SRAM Computing-in-Memory

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image encryption using XOR-based continuous tone MSS and Cellular Automata 6

Image encryption using XOR-based continuous tone MSS and Cel...

引用

6th international conference on Information systems and Computer Networks, ISCON 2023

作者： Akanksha Garg, Hitendra Shivani, Shivendra GLA University Dept. of Computer Engineering and Applications Mathura India Thapar Institute of Engineering and Technology Dept. of Computer Science Patiala India

ISBN: (纸本)9798350346961

Online communication has become quicker and simpler as a result of the growth of the internet and the advancement in technology. People are using multimedia data in almost all spheres of life. The amount of multimedia data transmitted has been increasing at a massive rate. Multimedia data delivered over open and unreliable networks are susceptible to unauthorized access. As a result, a cryptographic standard is needed to securely and efficiently transmit multimedia data such as images over the networks. This study uses cellular automata and an XOR-based continuous tone MSS approach to create an image encryption method. The suggested approach has eliminated VC's drawbacks, including secret/share quantity constraints, unpredictable share patterns, codebook requirements, and pixel extension in shares and recovered secret pictures. The recommended approach uses an (n,n) multi-secret sharing system that can send n secret photos simultaneously. At the time of encoding, the master share overcomes been made using the secret key, and it may be successfully retrieved when decoding using a comparable secret key. The exploratory results and security examination shows the proficiency of the given approach. The complexity of the proposed approach can be adjusted by using the different combinations of cellular automata rules.. © 2023 IEEE.

关键词： Cellular automata

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Joint Direction and Time Measurement Information based Positioning Method for TDMA signal 23

Joint Direction and Time Measurement Information Based Posit...

引用

23rd IEEE international conference on Communication technology, ICCT 2023

作者： Jiang, Bin Lu, An'nan You, Mingyi Lou, Caiyi Ye, Yunxia Huang, Kai Shi, Binhua No. 36 Research Institute of Cetc National Key Laboratory of Electromagnetic Space Security Jiaxing China

ISBN: (纸本)9798350325959

Time Division Multiple Access (TDMA) is a practical multiple access technology in modern communication systems. In TDMA communication system, terminals share wireless channel resources in the form of frame-time slots. A frame is divided into multiple time slots, and the duration of each time slot is fixed. In order to locate TDMA communication terminal by a single station, this paper presents a method of joint direction and time finding information based on the assistance of TDMA terminal with known location. In this method, the problem is constructed as a least squares model, and then the target location is obtained by using grid search strategy. Then, the positioning error is analyzed theoretically, and the influence of direction finding error, time measuring error, observation station position error and reference terminal position error on positioning error is studied. Finally, the positioning performance of the proposed method is verified by several simulation experiments. © 2023 IEEE.

关键词： Combine directional and time measurement information Generalized least squares criterion Reference station Single observation station TDMA terminal signal

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A ConvNeXt-backbone cGAN for Underwater Power Engineering image Enhancement 13

A ConvNeXt-backbone cGAN for Underwater Power Engineering Im...

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13th international conference on Power and Energy systems, ICPES 2023

作者： Chen, Tiebin Zhu, Suxun Ren, Bowen Chen, Laijun Industry Research Center Xining China Sichuan Energy Internet Research Institute Chengdu China

ISBN: (纸本)9798350345063

Underwater images is often greatly affected by color distortion, decreased contrast, and blurred details during the construction and maintenance of underwater power engineering. we proposed an underwater power engineering image enhancement model based on conditional generative adversarial networks (cGAN). Firstly, the generator incorporates the ConvNeXt module to enhance the global feature extraction capability by utilizing large convolutional kernels specifically designed for underwater image enhancement tasks. Subsequently, a boundary loss function is formulated to better capture high frequency information related to local textures and styles by comparing the boundary differences in the images. Lastly, a style transfer method is employed to transform land power engineering images and combine them with underwater environmental images to create a novel dataset for underwater power engineering. Case study results demonstrate the effectiveness of the proposed model in improving the quality of underwater power engineering images through adversarial learning, surpassing the enhancement performance of conventional models. © 2023 IEEE.

关键词： image enhancement

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Design of LEO-MIMO Precoding Update Algorithm based on Time Sliding Window 5

Design of LEO-MIMO Precoding Update Algorithm Based on Time ...

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5th international conference on Electronic Communication and Artificial Intelligence, ICECAI 2024

作者： Hu, Zewei Zheng, Lin Yang, Chao School of Information and Communication Guilin University of Electronic Technology Guilin541004 China Guangxi Key Laboratory of Wireless Wideband Communication and Signal Processing Guilin541004 China

ISBN: (纸本)9798350386943

In the Low Earth Orbit (LEO) satellite internet of Things (IoT), there is a significant imbalance in the distribution of ground terminal locations. Under a fixed beam regime, this leads to scenarios where satellite network capacity is simultaneously overloaded and underutilized, resulting in low capacity utilization rates for LEO satellite-to-earth communications. Distributed LEO-MIMO (Low Earth Orbit-Multiple Input Multiple Output) can alleviate overloads and distribute capacity by extending the satellite beam coverage area. However, unlike terrestrial distributed MIMO, which faces co-channel interference issues, distributed satellite networking in LEO systems also deals with the heterogeneity of Doppler shifts across different satellite links. To address these issues, a distributed LEO-MIMO linear precoding update algorithm is proposed. This paper, utilizing spectral graph theory, reduces the problem of constructing a single-frame precoding matrix to a graph signal correlation calculation problem. We introduce a precoding solving algorithm based on a time sliding window, which enhance data processing efficiency and reduce communication latency. © 2024 IEEE.

关键词： Satellite links

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HySeg-Net: A Robust Interactive Hybrid Technique for image Segmentation and Classification in Hand Gesture Recognition 5th

HySeg-Net: A Robust Interactive Hybrid Technique for Image S...

引用

5th international conference on Advances in Information Communication technology and Computing, AICTC 2024

作者： Narayan, Satya Gajrani, Jyoti Jain, Vinesh Kumar Jat, Dharm Singh Engineering College Ajmer Ajmer India NUST Namibia South Africa

ISBN: (纸本)9789819761050

image segmentation is helpful for a variety of tasks in many fields, including image analysis, object recognition and characterization, content-based image recovery, and foreground detection. Several models have been developed by considering spatial analysis and adjustment of skin models to continuously enhance the segmentation process. However, the field of hand image segmentation using skin identification is still controversial due to high pixel variation and particularly low human skin shading and thus, limits the performance of models. This research designs a HySeg-Net framework, by proposing marker-based Automated Maximal Similarity-based Region Merging (AMSRM) that enhances the segmentation for recognition of foreground objects. The approach also leverages stoppage limit, region merging, and convolutional neural networks (CNN) techniques to make the framework robust for skin data belonging to different geographical regions. The proposed technique is validated on two standard datasets, namely American Sign Language and Polish Sign Language with varying backgrounds. The framework achieves significant improvements in various parameters including Probability Random Index (PRI), Global Consistent Error (GCE), Variation of Information (VOI), Mean Square Error (MSE), and subsequently peak signal-to-noise ratio (PSNR). Ablation study demonstrates that the results of HySeg-Net are better as compared to the state-of-the-art techniques. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Convolutional neural networks

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E-commerce Website based on Graphics and image Processing technology (IPT) 22

E-commerce Website based on Graphics and Image Processing Te...

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6th international conference on Graphics and signal Processing, ICGSP 2022

作者： Dang, Mihua Liu, Hongli Xi'an Traffic Engineering Institute Shaanxi Xi'an China

ISBN: (纸本)9781450396370

With the rapid development of information technology, e-commerce has gradually entered thousands of households from high technology. E-commerce website (ECW) have become an important bridge for daily communication between enterprises and between enterprises and consumers. image is one of the most important and commonly used information of human beings;Digital IPT is the process of converting image signal into digital format and processing it by computer. This paper studies and analyzes the application of graphics and IPT in the construction of ECW, discusses the graphics and IPT and the result design process of ECW, and tests the network name's views on the website construction proposed in this paper through online questionnaire experiment. The results show that 84% of internet users using graphics and IPT in the construction of ECWs will make people more willing to browse websites, and 76% said that the visual effect of web pages is good, while websites without graphics and IPT have little effect on improving shopping desire, and only 61% of internet users said they are willing to browse websites. It is verified that the application of graphics and IPT in the construction of ECW in this paper is conducive to improve the browsing volume of the website, and can also improve the visual aesthetic sense for internet users, which is welcomed by the audience. © 2022 ACM.

关键词： Websites

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internet of Things-Enabled Diabetic Retinopathy Classification from Fundus images 6th

Internet of Things-Enabled Diabetic Retinopathy Classificati...

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6th international conference on Information and Communication technology for Intelligent systems, ICTIS 2021

作者： Bhutnal, Vinodkumar Moparthi, Nageswara Rao Department of Computer Science and Engineering Koneru Lakshmaiah Education Foundation AP Vaddeswaram India

ISBN: (纸本)9789811935749

The main aim of this research is to review design of consolidated framework that represents the IoMT-based DR detection and severity analysis with performance *** automatic DR classification and severity analysis under IoMT is the main research problem statement of this *** the recent studies on the DR classification and severity analysis, it is observed that the early prediction of the DR diseases along with its severity analysis is challenging research problem several concerns like the fundus image modalities, image quality, computational efficiencies, accurate region of interest localization, and overall *** the trade-off among these challenges is a tedious task for the *** of the works have been built using the automatic mechanism of deep learning for DR *** few attempts were reported for the automatic DR classification and disease severity analysis but not sufficient for the IoMT-enabled smart healthcare *** motivates us to attempt the novel IoMT-enabled automatic DR classification and severity analysis from the input retinal fundus images of different modalities. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： internet of things

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