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2024 International Conference on Intelligent and Innovative Practices in engineering and Management, IIPEM 2024

作者： Manju, K. Dinesh, P.M. Deepa, K. Kathan, Karthik Lakshmi, G. Prasanna Alagarsamy, Manjunathan Sona College of Technology Department of Electronics and Communication Engineering Tamil Nadu Salem India SRM Institute of Science and Technology Faculty of Engineering and Technology Department of Computer Science and Engineering Tamil Nadu Tiruchirapalli India Kongunadu College of Engineering and Technology Department of Electrical and Electronics Engineering Tamil Nadu Trichy621215 India Sandip University School of Computer Science and Engineering Maharashtra Nashik India K.Ramakrishnan College of Technology Department of Electronics and Communication Engineering Tamil Nadu Trichy621112 India

ISBN: (纸本)9798350390049

Automation is more important now. This article focuses on automating chicken farms using mobile communication devices and wireless sensor networks. Chicken is the world's most popular food because it contains more protein, less fat, and less cholesterol than other poultry. Chicken's nutrition is another benefit. This project utilizes the Internet of Things to monitor and adjust chicken farm environmental conditions. Temperature, moisture, water level, ammonia gas, and waste level were considered. This research aimed to improve chicken farm chick growth. The individual also monitors chicken behavior and feeding. Another usage for the sensor module is water level management and monitoring. If all sensors are connected to the microcontroller, all sensor data may be gathered. After that, a Wi-Fi module uploads the data to a website. A computer or mobile device connected to the internet allows the poultry farm owner to examine its interior surroundings. This informs the owner on agricultural conditions. This system will maintain temperature, humidity, and water level without human intervention using a DC motor, ventilation window, and co-exhaust fan. This will be done without human intervention. Devices will activate as needed when threshold values are attained. Our method allows semi-automated chicken product production and bird behavior monitoring. This allows us to deliver nutritious chicken meat while reducing bird killing. © 2024 IEEE.

关键词： Humidity sensors

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The Integration of Kansei engineering and Artificial Intelligence Based on Methodology and Application Perspective: A Review 10th

The Integration of Kansei Engineering and Artificial Intelli...

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10th International Conference on Kansei engineering and Emotion Research, KEER 2024

作者： Sung, Wen-Tsai Isa, Indra Griha Tofik Department of Electrical Engineering National Chin-Yi University of Technology Taichung411030 Taiwan Graduate Institute Prospective Technology of Electrical Engineering and Computer Science National Chin-Yi University of Technology Taichung411030 Taiwan

ISBN: (纸本)9789819798896

In product development design, not only functional aspects but also human factors such as emotional, psychological, and affective elements need to be considered. Kansei engineering (KE) is a methodology that integrates human factors into product design. In line with this, artificial intelligence (AI) technology continues to develop that enables integration between KE and AI. In this study, a review of the integration of KE and AI will be carried out based on methodological and application perspectives. The stages were carried out using a systematic literature review approach consisting of (1) collecting article data;(2) article selection;(3) analysis and review of articles;(4) data documentation;and (5) conclusion. The year of publication for the articles reviewed is between 2018 and 2024. In the initial data search, 38 articles were obtained, which were then selected only for articles in journal format. Research findings show that AI can be part of KE in improving emotional relationships by extracting the hidden preferences of users deeper, carrying out automatic design creation, and personalizing application products like robots to better appeal to users’ emotions. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Product design

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Interrupted sampling forwarding jamming parameter estimation based on YOLOv7-tiny 7

Interrupted sampling forwarding jamming parameter estimation...

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7th IEEE International Conference on Electronic Information and Communication Technology, ICEICT 2024

作者： Shi, Zhaopeng Wu, Hao Zhu, Xuan Wang, Wantian Ni, Xun Zhang, Jiahao Huazhong University of Science and Technology School of Electronic Information and Communications China Naval University of Engineering National Key Laboratory of Electromagnetic Energy Wuhan China Wuhan University School of Electrical Engineering and Automation China Huazhong University of Science and Technology School of Computer Science and Technology Wuhan China

ISBN: (纸本)9798350384437

Interrupted sampling repeater jamming (ISRJ) is a new type of active coherent jamming technology based on the principle of under-sampling. It mainly uses the Doppler tolerance characteristics of wideband signals to achieve multi-false target jamming. The feasibility of the existing anti-ISRJ methods largely depends on the estimation accuracy of the key parameters of the interference. In order to ensure the accuracy and real-time performance of ISRJ parameter estimation under low jamming-to-noise ratio, this paper proposes a ISRJ feature parameter estimation algorithm based on YOLOv7-tiny object detection model with high precision and lightweight. Through simulation and comparative analysis of different methods, the method proposed in this paper can achieve parameter estimation for ISRJ under low jamming-to-noise ratio, and has high precision and real-time performance. © 2024 IEEE.

关键词： Object detection

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Sources of nonlinearity and mitigation of phase noise in MUTC photodetectors at comb-line frequencies

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Optics Express 2025年第11期33卷 24130-24140页

作者： Ishraq Md Anjum Ergun Simsek Seyed Ehsan Jamali Mahabadi Thomas F Carruthers Curtis R Menyuk Joe C Campbell David A Tulchinsky Keith J Williams Department of Computer Science and Electrical Engineering University of Maryland Baltimore County Baltimore MD 21250 USA Department of Electrical and Computer Engineering University of Virginia Charlottesville VA 22904 USA Naval Research Laboratory Washington DC 20375 USA

We calculate the phase noise for the first 100 comb line frequencies of two modified uni-traveling-carrier (MUTC) photodetectors. The frequency comb is generated by one-picosecond pulses with a 2-GHz repetition frequency. We observe a non-monotonic increase in the phase noise and investigate its origins. Our model identifies the interplay among the space charge effect, the heterostructure design, and the nonlinear relationship between the electric field and the electron drift current that leads to a complex variation of the phase noise as a function of the comb line frequency. Based on the findings, we present ways to reduce the phase noise of the photodetectors. While the optimal design depends on the desired frequency range of operation, we find a design that can reduce the phase noise over a wide range of comb-line frequencies.

关键词： computer simulation Frequency combs Phase noise Photodetectors Quantum efficiency Shot noise

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High-Precision Vehicle Positioning Technology by Combining Vehicle Images and Satellite Maps

High-Precision Vehicle Positioning Technology by Combining V...

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2024 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2024

作者： Chen, Yu-Xuan Lin, Huei-Yung National Chung Cheng University Department of Electrical Engineering 168 University Road Chiayi621 Taiwan National Taipei University of Technology Department of Computer Science and Information Engineering Taipei106 Taiwan

ISBN: (纸本)9781665410205

With the continuous advances of technologies, the demand for precise vehicle positioning has grown significantly. Although it is now possible to capture driving scenes and record driving paths using a dashcam, standard civilian GPS typically has the accuracy errors ranging from 3 to 5 meters. This level of precision is in general not sufficient for the rapidly evolving ADAS (Advanced Driver Assistance Systems). In this paper, we present a high-precision vehicle positioning technique based on satellite map and image data. Instead of using expensive LiDAR sensors, the proposed approach utilizes lane detection, semantic segmentation and geolocation to extract environmental features from images. A∗ algorithm is then adopted to refine the driving trajectory for the improvement of vehicle positioning accuracy. Furthermore, we establish an image dataset containing satellite maps and latitude/longitude coordinate information of various road scenes. The code and datasets are made available publicly at https://***/M6104150181M610415018-Paper. © 2024 IEEE.

关键词： Semantic Segmentation

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Deep Reinforcement Learning for Power Control in Secure Broadcast Channels 21

Deep Reinforcement Learning for Power Control in Secure Broa...

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21st International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks, WiOpt 2023

作者： Arvanitaki, Antonia Stamatakis, George Carlsson, Niklas Mohapatra, Parthajit Pappas, Nikolaos Department of Computer and Information Science Linköping University Linköping Sweden Department of Electrical Engineering Indian Institute of Technology Tirupati India

ISBN: (纸本)9783903176553

In this work, we investigate the dynamic power management problem in a two-user secure broadcast channel scenario where the information at the source is kept in two separate queues, one for confidential and one for non-confidential information. The intended receiver of the confidential information transmits a jamming signal to prevent the other receiver from successfully decoding the confidential information. The decoding strategies used at the receivers include successive decoding (SD) and treating interference as noise (TIN). An autonomous agent, located at the source, decides on the power that will be used for the transmission of confidential information. We formulate the transmission power decision problem as a Markov Decision Process (MDP) and utilize the Deep Deterministic Policy Gradient (DDPG) algorithm for the agent to learn approximately optimal policies. We demonstrate that SD yields better rewards than TIN at the legitimate receiver. Additionally, we contrast the DDPG algorithm with three baseline power control policies and show that the former performs better than the latter. © 2023 IFIP.

关键词： Autonomous agents

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Design and Evaluation of Generative Adversarial Network for Automated Image Colorization System 5

Design and Evaluation of Generative Adversarial Network for ...

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5th International Conference on Smart Electronics and Communication, ICOSEC 2024

作者： Vidyalakshmi, R. Gayathri, N. Aarthi, M.S. Kathirvel, N. Bhuvaneshvari, K. Sivaramkrishnan, M. Karpagam College of Engineering Department of Electrical and Electronics Engineering Coimbatore India Sri Eshwar College of Engineering Department of Computer Science Engineering Coimbatore India P.A. College of Engineering and Technology Department of Electrical and Electronics Engineering Coimbatore India Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Department of Information Technology Chennai India

ISBN: (纸本)9798331504403

For the preservation of historical materials and the enhancement of visual representation, image colorization is crucial. Image colorization adds color to black-and-white or grayscale images, revitalizing old photographs and papers. It affords us a more immersive and relatable experience of history. Additionally, colorization imparts realism and liveliness to visual content. It facilitates audience engagement, emotional expression, and the development of visually captivating content that elicits a response and imparts a memory. The process of image colorization utilizing Deep Learning (DL) models is investigated in this study. The pre-processing techniques utilized to ensure data integrity and consistency are sourced from Kaggle. The image colorization challenge is built using DL models, notably Generative Adversarial Networks (GANs) and Convolutional Autoencoders (CAEs). These algorithms learn to colorize grayscale images through the use of training data. Peak Signal-to-Noise Ratio (PSNR), Learned Perceptual Image Patch Similarity (LPIPS), Structural Similarity Index (SSIM), and Fréchet Inception Distance (FID) are some of the metrics utilized to assess the models. The evaluation results indicate that the GAN model exhibits superior performance in image colorization compared to the CAE model. This is supported by higher PSNR and SSIM values, as well as lower values for LPIPS and FID. © 2024 IEEE.

关键词： Generative adversarial networks

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A Comparative Evaluation of 3D Geometries of Scenes Estimated using Factor Graph Based Disparity Estimation Algorithms

A Comparative Evaluation of 3D Geometries of Scenes Estimate...

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IS and T International Symposium on Electronic Imaging: 3D Imaging and Applications, 3DIA 2023

作者： Shabanian, Hanieh Balasubramanian, Madhusudhanan Computer Science Department School of Computing and Analytics Northern Kentucky University Highland HeightsKY United States Electrical and Computer Engineering Department University of Memphis MemphisTN United States

Passive stereo vision systems are useful for estimating 3D geometries from digital images similar to the human biological system. In general, two cameras are situated at a known distance from each other and simultaneously capture images of the same scene from different views. This paper presents a comparative evaluation of 3D geometries of scenes estimated by three disparity estimation algorithms, namely the hybrid stereo matching algorithm (HCS), factor graph-based stereo matching algorithm (FGS), and a multi-resolution FGS algorithm (MR-FGS). Comparative studies were conducted using our stereo imaging system as well as hand-held, consumer-market digital cameras and camera phones of a variety of makes/models. Based on our experimental results, the factor graph algorithm (FGS) and multi-resolution factor graph algorithm (MR-FGS) result in a higher level of 3D reconstruction accuracy than the HCS algorithm. When compared with the FGS algorithm, MR-FGS provides a significant improvement in the disparity contrast along the depth boundaries and minimal depth discontinuities. © 2023, Society for Imaging science and Technology.

关键词： Stereo image processing

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A Data-Driven Approach based on Dynamic Mode Decomposition for Efficient Encoding of Dynamic Light Fields

A Data-Driven Approach based on Dynamic Mode Decomposition f...

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2023 IEEE/CVF Conference on computer Vision and Pattern Recognition Workshops, CVPRW 2023

作者： Ravishankar, Joshitha Khaidem, Sally Sharma, Mansi Indian Institute of Technology Madras Department of Electrical Engineering India Amrita Vishwa Vidyapeetham Amrita School of Computing Department of Computer Science and Engineering Coimbatore India

ISBN: (纸本)9798350302493

Dynamic light fields provide a richer, more realistic 3D representation of a moving scene. However, this leads to higher data rates since excess storage and transmission requirements are needed. We propose a novel approach to efficiently represent and encode dynamic light field data for display applications based on dynamic mode decomposition (DMD). Acquired images are firstly obtained through optimized coded aperture patterns for each temporal frame/camera viewpoint of a dynamic light field. The underlying spatial, angular, and temporal correlations are effectively exploited by a data-driven DMD on these acquired images arranged as time snapshots. Next, High Efficiency Video Coding (HEVC) removes redundancies in light field data, including intra-frame and inter-frame redundancies, while maintaining high reconstruction quality. The proposed scheme is the first of its kind to treat light field videos as mathematical dynamical systems, leverage on dynamic modes of acquired images, and gain flexible coding at various bitrates. Experimental results demonstrate our scheme's superior compression efficiency and bitrate savings compared to the direct encoding of acquired images using HEVC codec. © 2023 IEEE.

关键词： Dynamic mode decomposition

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Multi-scale Attention Network for Diabetic Foot Ulcer Segmentation Using Self-supervised Learning 4th

Multi-scale Attention Network for Diabetic Foot Ulcer Segme...

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4th Diabetic Foot Ulcers Grand Challenge, DFUC 2024 held in Conjunction 27th International Conference on Medical Image Computing and computer Assisted Intervention, MICCAI 2024

作者： Murali, Aravind Shrenivas Chuquilín, Marino Lee, Eung-Joo College of Information Science University of Arizona Tucson United States Department of Physics University of Arizona Tucson United States Department of Electrical and Computer Engineering University of Arizona Tucson United States

ISBN: (纸本)9783031808708

As part of the Diabetic Foot Ulcer Challenge (DFUC) 2024, we propose a novel self-supervised learning (SSL) approach for the segmentation of Diabetic Foot Ulcers (DFUs), leveraging a multi-scale feature extraction architecture combined with the DINOv2 model. This innovative approach is designed to address the variability and complexity in DFU images, which are often characterized by diverse shapes, sizes, and textures that pose significant challenges to traditional segmentation methods. Our method integrates an Attention U-NET as the segmentation head, enabling precise capture of critical ulcer features within DFU images, such as the boundaries and internal structures of ulcers. Using test datasets evaluated by the DFUC 2024 organizers, the model achieved a Dice coefficient of 0.5709 and a Jaccard index of 0.4793, demonstrating its instance segmentation capabilities on unseen data. The relevant code is released at: https://***/vsilab/dfu_ssl. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Self-supervised learning

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