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E-Health and Bioengineering Conference (EHB)

作者： Aurelia Nica Ira-Adeline Simionov Alina Antache Dragos-Sebastian Cristea Stefan-Mihai Petrea Victor Cristea Food Science Food Engineering Biotechnology and Aquaculture Department Food Science and Engineering Faculty “Dunǎrea de Jos” University of Galati Galaţi Romania Faculty of Automation Computer Sciences Electronics and Electrical Engineering “Dunarea de Jos” University of Galati Galaţi Romania Faculty of Economics and Business Administration “Dunarea de Jos” University of Galati Galaţi Romania Applied Science Department Transboarding Faculty “Dunărea de Jos” University of Galaţi Galaţi Romania

ISBN: (数字)9781665485579

ISBN: (纸本)9781665485586

The process of fish breeding is extensively applied in fish farms and it is influenced by either environmental factors (in case of natural reproduction) and by the use of exogenous hormones (in case of artificial reproduction). Reproducing some species under controlled conditions without hormonal preparations is not possible. Many hormonal agents have been previously described in the scientific literature as beneficial in the fish breeding process. The effectiveness of these agents varies. This paper reviews some of the basic hormonal substances and describes the results of artificial reproduction. The most frequently encountered substances that give the best results are: Carp pituitary homogenate (CPH), Ovopel and Ovaprim. It can be concluded that in order to ensure the success of reproduction, the doses applied are particularly important, as well as the way of administration of the agent.

关键词： Economics Fish Environmental factors Biochemistry Biomedical engineering

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Development of a UAV-based System for Technical Diagnostics of Overhead Power Lines

Development of a UAV-based System for Technical Diagnostics ...

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International Conference on Computational Problems of Electrical engineering (CPEE)

作者： Oleksandr Kozlovskyi Dmitro Trushakov Serhiy Rendzinyak Vasyl Korud Department of Electrical Systems and Energy Management Central Ukrainian National Technical University Kropyvnytskyi Ukraine Department of Automation and Control in Technical Systems Central Ukrainian National Technical University Kropyvnytskyi Ukraine Faculty of Electronics and Computer Technologies Ivan Franko National University of Lviv Lviv Ukraine Institute of Power Engineering and Control System Lviv Polytechnic National University Lviv Ukraine

The problems associated with the operation of overhead power lines and ways of improving control over their condition with the help of UAVs are considered. A structural diagram of the system of technical diagnostics of overhead lines based on UAVs was developed, for which the necessary diagnostic parameters were selected according to informative criteria. An analysis of types of UAVs was carried out in order to determine their suitability and efficiency of use for diagnosing the condition of overhead lines.

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Model-free power optimization of wind farm based on nelder-mead method 2

Model-free power optimization of wind farm based on nelder-m...

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2nd International Conference on Smart Power and Internet Energy Systems, SPIES 2020

作者： Xu, Zhiwei Geng, Hua Chu, Bing Tsinghua University Beijing National Research Center for Information Science and Technology Department of Automation Beijing China University of Southampton School of Electronics and Computer Science Faculty of Physical Sciences and Engineering Southampton United Kingdom

ISBN: (纸本)9781728166117

Wake effects generated by wind turbines causes the strong wake interactions among turbines and thus significantly lowers the power output of wind farm. However, it is generally difficult to model the interactions between turbines due to its complexity. To mitigate the wake interactions and thus improve the power output of wind farm, this paper proposes a model-free optimization scheme. The power optimization problem of wind farm is divided into several optimization sub-problems according to the power efficiencies of wind farm under different wind directions. Each optimization sub-problem is solved approximately by developed power optimization algorithm based on Nelder-Mead method. Simulation results show that the proposed scheme can quickly and effectively improve the power output of wind farm in complex wind condition without modeling the wake interactions among the turbines. © 2020 IEEE.

关键词： Optimization

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An invisible DWT watermarking algorithm using noise removal with application to dermoscopic images 9

An invisible DWT watermarking algorithm using noise removal ...

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9th International Conference on Mathematical Modeling in Physical Sciences, IC-MSQUARE 2020

作者： Moldovanu, S. Michis, F.A. Moraru, L. Dunarea de Jos University of Galati Department of Computer Science and Information Technology Faculty of Automation Computers Sciences Electronics and Electrical Engineering 2 Stiintei Street GalatiRO-800210 Romania Department of Chemistry Physics and Environment Faculty of Sciences and Environment Dunarea de Jos University of Galati 47 Domneasca Street Galati800008 Romania Dunarea de Jos University of Galati Modelling and Simulation Laboratory Galati Romania

A new approach for the digital watermarking process is proposed to be part of the pre-processing stage of a computer-aided diagnosis system. We propose to embed a denoised image acting as the watermark image in the original host image with the final goal of improving the quality of demoscopic images for further image processing operation related to CAD. The proposed algorithm uses Discrete Wavelet Transform (DWT) corroborated with some basic properties of Human Visual System such as Contrast Sensitive Function (CSF) and Noise Visibility Function (NVF) with the goal of correlating the texture properties and noise. This approach hides the watermark (i.e. denoised version of the host image) in high-pass subbands that are focused on image features. The main concern is to evaluate the distortion produced to the host image by watermarking and an objective quality measure function, i.e. Weighted Peak Signal-to-Noise Ratio (WPSNR), is used to evaluate the existing differences between the original and watermarked images. The proposed approach is tested using the available skin lesion images from the digital image archive of the Department of Dermatology of the University Medical Center Groningen. The experiment results show the improved performance of the proposed scheme against a 3 × 3 median filtering attack in comparison with the a 5 × 5 median filtering attack. © Published under licence by IOP Publishing Ltd.

关键词： Discrete wavelet transforms

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Image encryption application and security analysis based on current modulated edge-emitting semiconductor lasers with pulse packages embedded in the microcontroller

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Optik 2023年 287卷

作者： Subramani, Rajeshkanna Emin, Berkay Kingni, Sifeu Takougang Akgül, Akif Center for Artificial Intelligence Chennai Institute of Technology Tamilnadu Chennai600069 India Department of Electronics and Automation Osmancık Omer Derindere Vocational School Hitit University Corum19500 Turkey Department of Mechanical Petroleum and Gas Engineering National Advanced School of Mines and Petroleum Industries University of Maroua P.O. Box 46 Maroua Cameroon Department of Computer Engineering Faculty of Engineering Hitit University Corum19030 Turkey Laboratory of Products Development and Entrepreneurship Institute of Innovation and Technology P.O. Box 8210 Yaounde Cameroon

This paper investigates the dynamical characteristics of current-modulated edge-emitting semiconductor lasers (CMEESLs) and their image encryption application. The associated dynamical characteristic of the CMEESL is divulged in the two-dimensional coordinate space of the system parameters by altering the modulation's frequency and amplitude. The CMEESL divulges cyclical pulse packages preceded by cyclic-doubling cascade follow by complex pulse packages when the modulation current density frequency is limited below 1 GHz. The microcontroller implementation of the CMEESL is realized and its results find agreement compared with the numerical dynamics of the CMEESL. The chaotic equations describing CMEESL are first modeled in the LabVIEW program and random number generation (RNG) is performed. The obtained random numbers are subjected to the NIST 800–22 statistical standard package, proving its worth to be employed for encryption applications. Employing the random numbers gotten, the LabVIEW environment is used in encrypting the image. The encrypted image is subjected to histogram, correlation, number of pixel change rates (NPCR) - unified average changing intensity (UACI), and entropy analyses. The reliability of the method is proven by the success achieved in the encryption process. © 2023 Elsevier GmbH

关键词： Microcontrollers

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Improved Classification of Benign and Malignant Breast Lesions Based on Contrast Manipulation and Gradient Map

Improved Classification of Benign and Malignant Breast Lesio...

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E-Health and Bioengineering Conference (EHB)

作者： Iulia–Nela Anghelache Nastase Simona Moldovanu Luminita Moraru The Modelling & Simulation Laboratory University Dunarea de Jos of Galati UGAL Galati Romania Department of Computer Science and Information Technology Faculty of Automation Computers Electrical Engineering and Electronics University Dunarea de Jos of Galati UGAL Galati Romania Department of Chemistry Physics and Environment Faculty of Sciences and Environment University Dunarea de Jos of Galati UGAL Galati Romania

ISBN: (数字)9781665485579

ISBN: (纸本)9781665485586

This study proposes an approach to enhance the contrast breast ultrasound (BUS) images with the preservation of the finer details. The main idea is to use the relevant and most important features in the classification of BUS images as benign or malignant. Among the contrast manipulation techniques, both linear under- and overexposure methods, contrast limiting adaptive histogram equalization (CLAHE) method and homomorphic filtering are used. The gradient maps of original images are generated for further analysis. Also, the gradient maps of original images are improved by the local mean subtraction and divisive normalization. Eight structural features are extracted from each gradient map image type. The extracted features feed a Random Forest (RF) classifier to determine their relevance for BUS images classification. An accuracy of 97.12% has been obtained for improved gradient map images and 93.03% for gradient map images.

关键词： Histograms Ultrasonic imaging Limiting Breast Feature extraction Lesions Standards

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Melanoma Detection using a Random Forest Algorithm

Melanoma Detection using a Random Forest Algorithm

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E-Health and Bioengineering Conference (EHB)

作者： Felicia-Anisoara Damian Simona Moldovanu Luminita Moraru The Modelling & Simulation Laboratory University Dunarea de Jos of Galati UGAL Galati Romania Department of Computer Science and Information Technology Faculty of Automation Computers Electrical Engineering and Electronics University Dunarea de Jos of Galati UGAL Galati Romania Department of Chemistry Physics and Environment Faculty of Sciences and Environment University Dunarea de Jos of Galati UGAL Galati Romania

ISBN: (数字)9781665485579

ISBN: (纸本)9781665485586

In recent years, statistical evidence has identified melanoma as a major cause of skin cancer deaths. In this study, we propose a skin analysis lesions based on colour features (C) and Hu (H) moments to differentiate benign (nevi) and malignant (melanoma) lesions and, a classification based on Random Forest algorithm. Colour features are found as follows. Pre-processing for hair removing using the Dull-razor method; image segmentation based on the optimal colour threshold set on each RGB colour channel (red, green, blue); 23 colour features extraction using the minimum and maximum RGB intensity and Hu moments; Random Forest (RF) algorithm to accurately differentiate benign and malignant skin lesions. This study used three datasets: 7-Point, Med-Node, PH2. RF classifier performance in terms of accuracy was: 94% for the 7-point dataset with H5, H7, H6, H2, C08 selected as relevant features; 98.1% for the Med-Node dataset and H7, H5, H6, H2, H1 ACC the relevant features; and, 96.5% for the PH2 dataset and H5, H6, H7, C03, H1 selected as relevant features, respectively. Shape features based on Hu moments are found to improve the classification performance of the skin lesions compared to the colour features.

关键词： Visualization Image segmentation Image color analysis Shape Melanoma Skin Classification algorithms

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NTIRE 2023 Challenge on Image Super-Resolution (×4): Methods and Results

NTIRE 2023 Challenge on Image Super-Resolution (×4): Method...

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

作者： Zhang, Yulun Zhang, Kai Chen, Zheng Li, Yawei Timofte, Radu Zhang, Junpei Zhang, Kexin Peng, Rui Ma, Yanbiao Jiao, Licheng Huang, Huaibo Zhou, Xiaoqiang Ai, Yuang He, Ran Qiu, Yajun Zhu, Qiang Li, Pengfei Li, Qianhui Zhu, Shuyuan Zhang, Dafeng Li, Jia Wang, Fan Li, Chunmiao Kim, TaeHyung Kil, Jungkeong Kim, Eon Yu, Yeonseung Lee, Beomyeol Lee, Subin Lim, Seokjae Chae, Somi Choi, Heungjun Huang, ZhiKai Chen, YiChung Chiang, YuanChun Yang, HaoHsiang Chen, WeiTing Chang, HuaEn Chen, I-Hsiang Hsieh, ChiaHsuan Kuo, SyYen Choi, Ui-Jin Conde, Marcos V. Khowaja, Sunder Ali Yoon, Jiseok Lee, Ik Hyun Gendy, Garas Sabor, Nabil Hou, Jingchao He, Guanghui Zhang, Zhao Li, Baiang Zheng, Huan Zhao, Suiyi Gao, Yangcheng Wei, Yanyan Ren, Jiahuan Wei, Jiayu Li, Yanfeng Sun, Jia Cheng, Zhanyi Li, Zhiyuan Yao, Xu Wang, Xinyi Li, Danxu Cui, Xuan Cao, Jun Li, Cheng Zheng, Jianbin Sarvaiya, Anjali Prajapati, Kalpesh Patra, Ratnadeep Barik, Pragnesh Rathod, Chaitanya Upla, Kishor Raja, Kiran Ramachandra, Raghavendra Busch, Christoph Computer Vision Lab Eth Zurich Switzerland Shanghai Jiao Tong University China University of Würzburg Germany Xidian University China Mais&cripac Institute of Automation Chinese Academy of Sciences China School of Artificial Intelligence University of Chinese Academy of Sciences China University of Science and Technology of China China Beijing Institute of Technology China School of Information Science and Technology ShanghaiTech University China School of Information and Communication Engineering University of Electronic Science and Technology of China China China Lotte Data Communication Company Seoul Korea Republic of Graduate Institute of Electronics Engineering National Taiwan University Taiwan Department of Electrical Engineering National Taiwan University Taiwan Graduate Institute of Communication Engineering National Taiwan University Taiwan ServiceNow United States MegaStudyEdu Korea Republic of Computer Vision Lab Caidas University of Würzburg Germany University of Sindh Pakistan Iklab Inc. Tech University of Korea Siheung-Si Korea Republic of Micro-Nano Electronics Department Shanghai Jiao Tong University China Electrical Engineering Department Faculty of Engineering Assiut University Egypt Hefei University of Technology China Beijing Jiaotong University China South China University of Technology Guangdong Guangzhou China Sardar Vallabhbhai National Institute of Technology India Norwegian University of Science and Technology Norway

ISBN: (纸本)9798350302493

This paper reviews the NTIRE 2023 challenge on image super-resolution (×4), focusing on the proposed solutions and results. The task of image super-resolution (SR) is to generate a high-resolution (HR) output from a corresponding low-resolution (LR) input by leveraging prior information from paired LR-HR images. The aim of the challenge is to obtain a network design/solution capable to produce high-quality results with the best performance (e.g., PSNR). We want to explore how high performance we can achieve regardless of computational cost (e.g., model size and FLOPs) and data. The track of the challenge was to measure the restored HR images with the ground truth HR images on DIV2K testing dataset. The ranking of the teams is determined directly by the PSNR value. The challenge has attracted 192 registered participants, where 15 teams made valid submissions. They achieve state-of-the-art performance in single image super-resolution. © 2023 IEEE.

关键词： Statistical tests

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NTIRE 2023 Challenge on Efficient Super-Resolution: Methods and Results

NTIRE 2023 Challenge on Efficient Super-Resolution: Methods ...

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

作者： Li, Yawei Zhang, Yulun Timofte, Radu Van Gool, Luc Yu, Lei Li, Youwei Li, Xinpeng Jiang, Ting Wu, Qi Han, Mingyan Lin, Wenjie Jiang, Chengzhi Luo, Jinting Fan, Haoqiang Liu, Shuaicheng Wang, Yucong Cai, Minjie Li, Mingxi Zhang, Yuhang Fan, Xian-Jun Sheng, Yankai Mao, Yanyu Zhang, Nihao Wang, Qian Zheng, Mingjun Sun, Long Pan, Jinshan Dong, Jiangxin Tang, Jinhui Yang, Zhongbao Wang, Yan Pan, Erlin Cai, Qixuan Dai, Xinan Zhussip, Magauiya Kalyazin, Nikolay Vyal, Dmitry Zou, Xueyi Yan, Youliang Chung, Heaseo Zhang, Jin Yu, Gaocheng Zhang, Feng Wang, Hongbin Liao, Bohao Du, Zhibo Wu, Yu-Liang Shi, Gege Peng, Long Wang, Yang Cao, Yang Zha, Zhengjun Huang, Zhi-Kai Chen, Yi-Chung Chiang, Yuan-Chun Yang, Hao-Hsiang Chen, Wei-Ting Chang, Hua-En Chen, I-Hsiang Hsieh, Chia-Hsuan Kuo, Sy-Yen Liu, Xin Pan, Jiahao Yu, Hongyuan Yu, Weichen Ge, Lin Dong, Jiahua Zou, Yajun Wu, Zhuoyuan Han, Binnan Zhang, Xiaolin Zhang, Heng Yin, Xuanwu Zuo, Kunlong Deng, Weijian Yuan, Hongjie Lu, Zengtong Ouyang, Mingyu Ma, Wenzhuo Liu, Nian Zheng, Hanyou Zhang, Yuantong Zhang, Junxi Chen, Zhenzhong Gendy, Garas Sabor, Nabil Hou, Jingchao He, Guanghui Zhu, Yurui Wang, Xi Fu, Xueyang Zha, Zheng-Jun Yin, Daheng Liu, Mengyang Chen, Baijun Li, Ao Luo, Lei Jin, Kangjun Zhu, Ce Zhang, Xiaoming Xie, Chengxing Li, Linze Meng, Haiteng Zhang, Tianlin Li, Tianrui Zhao, Xiaole Zhang, Zhao Li, Baiang Zheng, Huan Zhao, Suiyi Gao, Yangcheng Ren, Jiahuan Hu, Kang Shi, Jingpeng Wu, Zhijian Huang, Dingjiang Zhu, Jinchen Li, Hui Xv, Qianru Liu, Tianle Weng, Shizhuang Wu, Gang Jiang, Junpeng Liu, Xianming Jiang, Junjun Zhang, Mingjian Hu, Jing Wu, Chengxu Fan, Qinrui Feng, Chengming Luo, Ziwei Hu, Shu Lyu, Siwei Wu, Xi Wang, Xin Computer Vision Lab ETH Zurich Switzerland Computer Vision Lab University of Würzburg Germany Megvii Technology China MicroBT China College of Computer Science and Electronic Engineering Hunan University China Attrsense Xian University of Posts and Telecommunications Xi'an China National Engineering Laboratory for Cyber Event Warning and Control Technologies China Nanjing University of Science and Technology China Nankai University China University of Electronic Science and Technology of China China Tianjin University China Noah's Ark Lab Huawei Technologies McMaster University Canada Espresomedia Korea Republic of AntGroup China University of Science and Technology of China China Department of Electrical Engineering National Taiwan University Taiwan Graduate Institute of Communication Engineering National Taiwan University Taiwan Graduate Institute of Electronics Engineering National Taiwan University Taiwan ServiceNow United States China Mobile Research Institute China Chongqing University of Technology China Multimedia Department Xiaomi Inc. China Institute of Automation Chinese Academy of Sciences China Shenyang Institute of Automation Chinese Academy of Sciences China School of Information and Communication Engineering Communication University of China China Smart Classroom Division Ruijie Networks Co. Ltd. China School of Remote Sensing and Information Engineering Wuhan University China Micro-Nano Electronics Department Shanghai Jiao Tong University Shanghai200240 China Electrical Engineering Department Faculty of Engineering Assiut University Assiut71516 Egypt Southeast University China University of Electronic Science and Technology of China Chengdu China Chongqing University of Posts and Telecommunications Chongqing China Information Technology Co. Ltd Hangzhou China Southwest Jiaotong University China National Space Science Center Chinese Academy of Science China Hefei University of Technology Hefei China Anhui University China Fried Ric

ISBN: (纸本)9798350302493

This paper reviews the NTIRE 2023 challenge on efficient single-image super-resolution with a focus on the proposed solutions and results. The aim of this challenge is to devise a network that reduces one or several aspects such as runtime, parameters, FLOPs, activations, memory footprint, and depth of RFDN while at least maintaining the PSNR of 29.00dB on DIV2K validation datasets. The challenge had 272 registered participants, and 35 teams made valid submissions. They gauge the state-of-the-art for efficient single-image super-resolution. © 2023 IEEE.

关键词： Optical resolving power

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Gesture interpretation control system using convolutional neural networks

Gesture interpretation control system using convolutional ne...

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2019 International Conference on Biomedical Innovations and Applications, BIA 2019

作者： Baldursson, Benedikt Rasti, Behnood Gudmundsson, Karl Cojocaru, Dorian Andersen, Kristinn Thorsteinsson, Saemundur E. University of Iceland Faculty of Electrical and Computer Engineering Hafnarfjordur Iceland University of Craiova Faculty of Automation Computers and Electronics Craiova Romania

ISBN: (纸本)9781728147543

This paper proposes a non-invasive control system for electrical wheelchairs utilizing facial gestures of individuals captured by real-Time monocular camera. The images are interpreted with a convolutional neural network that achieves up to ~99.5% overall accuracy. The control system uses an embedded system with a graphics processing unit for predicting real-Time throughput with fast inference time. This solution offers great versatility, where the user can make a gesture to depict a command of his choice. © 2019 IEEE.

关键词： Control systems

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