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SSRN 2023年

作者： Zhang, Fenghua Feng, Bingwen Xia, Zhihua Weng, Jian Lu, Wei Chen, Bin College of Information Science and Technology Jinan University Guangzhou510632 China School of Computer Science and Engineering Guangdong Province Key Laboratory of Information Security Technology Ministry of Education Key Laboratory of Machine Intelligence and Advanced Computing Sun Yat-sen University Guangzhou510006 China School of Cyber Security Guangdong Polytechnic Normal University Guangzhou510665 China

Various data hiding methods have been suggested to hide secret images within stego images. However, many of them could be easily detected by steganalytic tools due to their large hiding information. In this paper, we enhance the undetectability of image hiding network by mapping latent representation conditional on secret information. We extend the idea of image generation-based steganography and propose a Transformer-based image hiding network that can hide a secret image with the same size as the target image. The proposed scheme uses style transferring to help map latent representation. The hiding network of the proposed scheme consists of three modules: encoding, transfer, and synthesis modules. The encoding module extracts the latent representations from content and secret images, the transfer module stylizes the latent representation, and the synthesis module fuses the the latent representations to synthesize a target image with the secret image hidden in it. A new synthesis module as well as the corresponding extraction network is designed to improve recovery accuracy. The proposed scheme shows high image quality on both target images and recovered secret images. Furthermore, it can resist steganalytic tools and thus provides good security. © 2023, The Authors. All rights reserved.

关键词： Steganography

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A highly flexible and low-profile metasurface antenna for wearable WBAN systems

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Optik 2024年 313卷

作者： Muhammad, Hevin A. Abdulkarim, Yadgar I. Abdoul, Peshwaz Abdulkareem Awl, Halgurd N. Teksen, Fikret Alpay Alkurt, Fatih O.zkan Karaaslan, Muharrem Bakır, Mehmet Appasani, Bhargav Department of Physics College of Science Charmo University 46023 Chamchamal Kurdistan Region Sulaimani Iraq Electrical and Computer Engineering Department University of Alberta EdmontonABT6G 2R3 Canada Department of Communication Engineering Sulaimani Polytechnic University Sulaimani46001 Iraq Faculty of Engineering and Computer Science Qaiwan International University Kurdistan Region Sulaimani Iraq Department of Electrical-Electronics Engineering Iskenderun Technical University Hatay 31200 Turkey Department of Computer Engineering Yozgat Bozok University Yozgat66200 Turkey School of Electronics Engineering Kalinga Institute of Industrial Technology Bhubaneswar751024 India

Recent years have witnessed the popularity of wearable devices. These devices use Wireless Body Area Networks (WBANs) for healthcare monitoring, personalized tracking, and various other applications. An important component of these devices is the wearable antenna that provides reliable and efficient wireless communication between body-worn sensors and external devices. This paper presents a novel metasurface-based wearable antenna for WBAN applications. By incorporating metasurfaces into the antenna design, achieving enhanced performance is possible. The design was tested using four flexible substrates: wool, paper, fleece, and felt. The paper substrate was chosen because of its superior performance. The dimensions of the antenna are 30 mm x 20 mm, and a 5 ×3 metasurface is used, whose unit cell comprises a square patch. Simulation and experimental results have been performed to measure the radiation pattern, return loss, and gain. A good corroboration is observed between the measured and simulated results. The antenna resonates at three frequencies and offers wide-band resonance characteristics when backed by the metasurface. The peak gain of the antenna without the metasurface was less than 4 dB, but when backed by the metasurface, the peak gain was enhanced to approximately 6 dB. Also, it has been observed that the designed antenna's performance is not significantly affected by the radius of curvature, making it ideal for on-body measurements. This design can inspire further research on low-cost paper substrate-based antennas for WBAN applications. © 2024 Elsevier GmbH

关键词： Wearable antennas

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Neural Network based Solar Panel Tracking for Maximum Power Yield 5

Neural Network based Solar Panel Tracking for Maximum Power ...

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5th International Conference on Contemporary Computing and Informatics, IC3I 2022

作者： Neeraja, B. Salman, Hayder M. Reddy, Ch. Venkata Krishna Ghai, Sachin Deepak, A. Kumar, Pramod Government Polytechnic Department of Electrical and Electronics Engineering Telangana Hyderabad India Al-Turath Universiy College Department of Computer Science Baghdad10013 Iraq Chaitanya Bharathi Institute of Technology Department of EEE Hyderabad India Graphic Era Deemed to Be University Department of Management Studies Uttarakhand Dehradun India Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences SIMATS Tamilnadu Chennai India Lloyd Institute of Engineering and Technology Uttar Pradesh Greater Noida India

ISBN: (纸本)9798350398267

The progressive global rise in the usage of renewable energy sources for power generation to lessen the impact of carbon emissions is encouraging. When compared to other renewable energy options, solar has the greatest potential to meet the world's electrical needs. Solar cell performance is highly sensitive to both the intensity of available sunlight and the surrounding temperature. Maximum Power Point Tracking (MPPT) allows for maximum power to be extracted from solar cells despite their poor efficiency. The current decade has seen a surge in research into photovoltaic (PV) systems. Traditional MPPT methods have a less complicated procedure and are easier to implement, but they can't compete with AI-based methods when it comes to efficiency, especially in cases of shading and constantly moving climatic conditions. Although several methods exist for MPPT, more recent methods, such as artificial intelligence, can be employed for excellent efficiency in the case of extracting the maximum power available from solar cells. This research proposes a maximum MPPT method for solar PV systems based on artificial neural networks (ANNs). Five-layer, feed-forward topology-based ANNs are designed in MATLAB Simulink. The commonplace PID controller was used as a benchmark. Compared to a PID-based MPPT controller, the ANN-based controller performs better in simulations. The suggested system's strengths lie in its quick tracking speed, low rising time, and good static and dynamic tracking efficiency. © 2022 IEEE.

关键词： Solar panels

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Superabsorbent Hydrogel Evaporator with Sandwich Sa/Cnts/Sa Cellular Wall for Solar-Driven Water Purification

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SSRN 2024年

作者： Yu, Xi Fang, Jianhui Kong, Xuan Yu, Zikang Zheng, Senyi Pan, Chaomei Liang, Huafeng Wang, Lihuan Yu, Hui Liu, Zijin Fan, Longfei Zuo, Qi Wu, Xiaohui Gan, Feng Li, Zhengrong Kan, Chi-Wai Yan, Jianhua Wang, Xianfeng Guangdong-Hong Kong Joint Laboratory for New Textile Materials School of Textile Materials and Engineering Wuyi University Jiangmen529020 China Guangdong Laboratory of Chemistry Fine Chemical Industry Jieyang Center Jieyang515200 China School of Textile and Garment Anhui Polytechnic University Anhui Wuhu241000 China School of Computer Science Guangdong Vocational and Technical University of Business and Technology Zhaoqing526000 China Institute of Textiles & Clothing The Hong Kong Polytechnic University Hong Kong100872 Hong Kong Innovation Center for Textile Science and Technology Donghua University Shanghai200051 China

The global shortage of fresh water resources is imminent, and solar desalination has been recognized as a low-cost, simplest and feasible strategy for freshwater resource acquisition. However, the evaporation rate of the current solar evaporator will be affected by the absorption capacity of sunlight, and the evaporator is vulnerable to collapse under external pressure, which seriously limits the water evaporation performance in the long-term use. Therefore, we developed a simple and effective idea to prepare the hydrogel evaporators. With the combination of homogeneous dispersion and freeze drying, carbon nanotubes (CNTs) were embedded in the hydrophilic polymer sodium alginate (SA) to prepare highly water-absorbing aerogel. The aerogel possessed interconnected arrayed cavity with sandwich SA/CNTs/SA cellular wall, which could quickly and efficiently absorb water (absorption ratio of 29 times) and transport seawater in the direction of the cellular. The evaporator has continuous and stable water transport function and high photothermal conversion efficiency, light absorption efficiency reaches more than 96%, and has an evaporation rate of 2.25 kg·m-2·h-1 under one sun. In addition, the solar energy absorber has extremely stable compressibility and good reusability, thereby improving the working life and continuous working ability of the evaporator. © 2024, The Authors. All rights reserved.

关键词： Sodium alginate

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BroadSurv: A Novel Broad Learning System-based Approach for Survival Analysis

BroadSurv: A Novel Broad Learning System-based Approach for ...

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2021 International Conference on Information, Cybernetics, and Computational Social Systems, ICCSS 2021

作者： Wu, Guangheng Duan, Junwei Wang, Jing Wang, Lu Dong, Cheng Lv, Changwei Jinan University College of Information Science and Technology Guangzhou China Guangdong Polytechnic Normal University School of Computer Science Guangzhou China Jinan University Academic Affairs Office Guangzhou China Jinan University School of Intelligent System Science and Engineering Zhuhai China Shenzhen Institute of Information Technology Shenzhen China

ISBN: (纸本)9781665402453

Survival analysis (time-to-event analysis) is a set of statistic methods to analyze time-to-event data and is widely used in many fields such as economics, finance and medicine. One of the fundamental problems in survival analysis is to explore the relationship between the covariates and the survival time. Recently, with the development of deep learning-based techniques, various approaches have been proposed for survival analysis. To better handle the censoring, special cost functions or sophisticated network structures are usually designed for these methods. In this paper, a novel two-stage method is proposed to model the survival data. In the first stage, pseudo conditional probabilities are computed, which can act as the quantitative response variables in regression problems. In the second stage, with these pseudo values, a complicated survival analysis problem is transformed into a regression problem that can be effectively solved by broad learning system. The experimental results show that, with a flexible structure and a simple cost function, our proposed method has a better performance in handling the censored problems. © 2021 IEEE.

关键词： Bioinformatics

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An Empirical Analysis of Artificial Intelligence (AI) as a Growth Engine for the Healthcare Sector 2

An Empirical Analysis of Artificial Intelligence (AI) as a G...

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2nd International Conference on Advance Computing and Innovative Technologies in engineering, ICACITE 2022

作者： Whig, Vandana Othman, Bestoon Gehlot, Anita Haque, Md Alimul Qamar, Saqib Singh, Jagdeep Mahaveer University Tmimt Teerthanker UP Moradabad India Uttaranchal Institute of Technology Uttaranchal University India Koya Technical Institute Erbil Polytechnic University Erbil Iraq Nawroz University College of Administration and Economics Department of Business Administration Duhok Iraq Department of Computer Application Andhra Pradesh 517325 India Veer Kunwar Singh University Department of Computer Science Ara802301 India Chitkara University Institute of Engineering and Technology Chitkara University Punjab India

ISBN: (纸本)9781665437899

The present research shed light on AI technology and its impact on the healthcare industry. Based on the surveys made by the researcher it is understood that without AI technology rapid development in the healthcare industry could not become possible for them. As for this, the adoption of AI technology is important for all health care firms to save their time and efforts for specific work. The research has been done with the aim of measuring whether there is a huge role of AI technology in the UK healthcare sector or not. © 2022 IEEE.

关键词： Health care

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Analysis on Methane Production from Various Coal Slime Fermentations Based on Metagenomics

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SSRN 2023年

作者： Guo, Hongyu Jia, Wenqing Chen, Zhenhong Cai, Yidong Wang, Yongjun Zhao, Shufeng Zhao, Weizhong School of Energy Science and Engineering Henan Polytechnic University Jiaozuo454000 China Research Institute of Petroleum Exploration & Development Beijing100083 China School of Energy Resources China University of Geosciences Beijing100083 China College of Computer Science and Technology Henan Polytechnic University Jiaozuo454000 China Department of Environmental Engineering Technical University of Denmark LyngbyDK-2800 Denmark

Metagenomic sequencing technology was applied to evaluate differences in the anaerobic fermentation process of coal slimes by analyzing microbial diversity, functional activity structure, and cooperative relationship during the anaerobic fermentation of coal slimes with different coal ranks. The obtained results showed that the production of biomethane from coal slime was decreased by increasing metamorphism degree. Internal reason was higher abundance of microbial community in low rank coal slimes compared to that in high rank coal which had higher activity in the gene expression of key steps such as hydrolysis and acidification, methanation and the production of hydrogen and acetic acid. Acetic acid decarboxylation and CO2 reduction are two key pathways of methanation process. At the same time, K11261 (formylmethanofuran dehydrogenase subunit) and K01499 (methenyltetrahydromethanopterin cyclohydrolase) genes were further enriched in low rank slime systems, which enhanced the proportion of CO2 reduction in methanation pathway and was beneficial to biomethane production. Research revealed the roles of different coal slime ranks in biomethane production process and is considered as an important reference significance for further exploration of coal slime resource utilization. © 2023, The Authors. All rights reserved.

关键词： Gene expression

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Artificial Intelligence assisted Electric Vehicles Fast Charging Station Design using Grid Distribution Network Model

Artificial Intelligence assisted Electric Vehicles Fast Char...

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Intelligent Technologies (CONIT), International Conference on

作者： C. Anitha K. Chitra G. Vijayalakshmi G Kumaran T. Vijetha K. Ormila Department of Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Chennai Tamil Nadu India Department of Electrical and Electronics Engineering CMR Institute of Technology Bengaluru Karnataka India Department of Electronics and Communication Engineering Prince Shri Venkateshwara Padmavathy Engineering College Chennai Tamil Nadu India Department of CSE Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Chennai Tamilnadu India Department of ECE MLR Institute of Technology Dundigal Hyderabad India Department of Electrical and Electronics Engineering A.M.K. Technological Polytechnic College Chennai Tamil Nadu India

ISBN: (数字)9798350349900

ISBN: (纸本)9798350349917

The electric vehicle charging station is a game-changer that supplants the older kind of charging stations. Our futuristic electric vehicle charging station may be installed virtually anywhere, takes minimal space, and operates independently of the government’s power source, in contrast to the current practice of reserving these stations for major urban areas. Among the many global industries that rely on fossil fuels, transportation ranks high. The development of electric vehicles (EVs) and other forms of transportation electrification are thus essential in the fight against carbon-dioxide emissions and the over-reliance on traditional energy sources that are harmful to the environment. At the same time, electricity distribution, use, and supply have been accompanied by massive amounts of data due to the fast digitization of electrical networks and EVs. These datasets may be used to inform choices and insights by using artificial intelligence (AI) algorithms. Despite a number of recent studies in this area, no one has explicitly examined the usefulness of AI for charge-demand profiling, data augmentation, demand forecasting, explainability of demand, and charge optimization of the EVI. For the purpose of efficiently delivering the fast charging function, this study suggested a novel logic called Grid Distributed Fast EV Charging (GDFEVC). To evaluate the proposed model’s efficiency, it was cross-validated with the standard Fast EV Charging Model (FEVCM). This AI framework has been empirically tested on a real-world EVI case study, and the results show that it helps with the new problems with dispersed energy supplies that are coming up with EV adoption.

关键词： Job shop scheduling Electricity Transportation Pricing Predictive models Dynamic scheduling Electric vehicle charging

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Research on Adaptive Grouping Method of TSP Path Planning Based on Genetic Algorithm

Research on Adaptive Grouping Method of TSP Path Planning Ba...

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Industrial Application of Artificial Intelligence (IAAI), IEEE International Conference on

作者： Xi Zhao Ying Li Computer Engineering Technical College Guangdong Polytechnic of Science and Technology Zhuhai China

ISBN: (数字)9781665404716

ISBN: (纸本)9781665404723

The traditional adaptive grouping of robot TSP path planning, the calculation of the adaptive function of the algorithm is insufficient, which makes the workload of the adaptive grouping larger, resulting in the data processing time of the grouping too long. Therefore, an adaptive grouping method for TSP path planning based on genetic algorithm is proposed. Firstly establish the TSP grid structure, confirm the path planning environment and working space, and use genetic algorithm to solve the grid structure path. After obtaining the data results, use the fitness function to determine the weight data in the genetic algorithm, and finally establish a mathematical model for self-adaptation Grouping. The feasibility of the above method is verified. The experimental results show that the adaptive grouping method of TSP path planning based on genetic algorithm has shorter processing time for data adaptive grouping, which proves that the method is more effective.

关键词： Conferences Data processing Path planning Mathematical model Artificial intelligence Robots Genetic algorithms

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Correction to: Machine Learning-Based Analysis of Surface Hardening in Shot-Peened Superalloys (Journal of Materials engineering and Performance, (2024), 10.1007/s11665-024-09918-1)

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Journal of Materials engineering and Performance 2024年 1-1页

作者： Rodrigues, Paul Kerwad, Mokhtar Massoud Askar, Shavan Pallathadka, Harikumar Abduvalieva, Dilsora Zearah, Sajad Ali Department of Computer Engineering College of Computer Science King Khalid University Al-Faraa Asir-Abha Saudi Arabia Faculty of Information Technology Misurata University Misurata Libya Erbil Technical Engineering College Erbil Polytechnic University Erbil Iraq Manipur International University Manipur Imphal India Department of Mathematics and Information Technologies Tashkent State Pedagogical University Tashkent Uzbekistan Scientific Research Center Al-Ayen University Thi-Qar Iraq

There was an error in the grant number given the Acknowledgment section of this article as originally published. The correct Acknowledgment reads as follows: The authors extend their appreciation to the Deanship of Scientific Research at King Khalid University for funding this work through large group Research Project under grant number RPG2/403/45. The original article has been corrected. © ASM International 2024.

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