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Transforming Sustainable Aquaculture: Synergizing Fuzzy Systems and Deep Learning Innovations

International Journal of Fuzzy Systems 2024年第8期26卷 2536-2552页

作者： Haobijam, Basanta Huang, Yo-Ping Chang, Yue-Shan Chang, Tsun-Wei Department of Electrical Engineering National Taipei University New Taipei City23741 Taiwan Department of Electrical Engineering National Penghu University of Science and Technology Penghu88046 Taiwan Department of Electrical Engineering National Taipei University of Technology Taipei10608 Taiwan Department of Computer Science and Information Engineering National Taipei University New Taipei City23741 Taiwan Department of Information and Communication Engineering Chaoyang University of Technology Taichung41349 Taiwan Department of Computer Science and Information Engineering HungKuo Delin University of Technology New Taipei City236302 Taiwan

Pisciculture encounters an array of intricate challenges that span disease management, preservation of water quality, prevention of genetic hybridization, ensuring the integrity of net systems, sourcing sustainable aquatic feed, and comprehending fish growth and reproductive dynamics. Addressing these multifaceted challenges necessitates a comprehensive research approach. This study employs an innovative synergy of fuzzy logic and deep learning techniques, resulting in a robust strategy to tackle these obstacles effectively. Fuzzy logic excels in assessing stressed fish conditions by handling inherent uncertainties. Simultaneously, YOLOv7 with fuzzy color enhancement (YOLOv7FCE) is used to detect damaged fish nets, thereby mitigating losses and upholding the integrity of the net infrastructure. This approach also leverages YOLOv7FCE for identifying Cobia fish within shoals, streamlining the identification process. Subsequently, DeepLabv3 is implemented to meticulously segment the recognized Cobia fish, facilitating precise measurements of their physical attributes. This comprehensive methodology yields profound insights into growth patterns and feeding tendencies within the confined aquatic environment. By embracing this approach, the research presents a versatile and adaptive framework that not only enhances our comprehension of piscine dynamics but also holds the potential to revolutionize the aquaculture industry. © The Author(s) under exclusive licence to Taiwan Fuzzy Systems Association 2024.

关键词： Fish

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To Kill a Mockingbird: Cryptanalysis of an Authenticated Key Exchange Scheme for Drones 15

To Kill a Mockingbird: Cryptanalysis of an Authenticated Key...

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15th International Conference on information and Knowledge technology, IKT 2024

作者： Toghraee, Neda Mala, Hamid Dept. of Information Technology Engineering Faculty of Computer Engineering University of Isfahan Isfahan Iran

ISBN: (纸本)9798331522254

Drones have evolved into sophisticated autonomous systems with a multitude of applications, including military operations, environmental monitoring, traffic oversight, data transmission, package delivery, fire targeting, and film production. As the Internet of Drones (IoD) ecosystem expands, ensuring secure and real-time access for authorized users becomes increasingly vital. User and drone authentication is crucial for this reason. In response to these challenges, Srinivas et al. proposed a lightweight three-factor authentication protocol designed for the IoD. While the authors assert that their protocol is resilient against known cyber threats, our research identifies critical vulnerabilities that challenge this claim. Although this scheme has already been cryptanalyzed in previous studies, in this paper we propose two new attacks on this scheme. Firstly, we present a concrete attack against the perfect forward secrecy of this scheme, and then we show that it is vulnerable to unauthorized access attack by a valid user to an unauthorized area's information. These weaknesses highlight the pressing need for the development of more secure authentication mechanisms in the IoD environment. Moving forward, addressing these vulnerabilities will be essential for fostering trust and ensuring the safe integration of drones into various applications, ultimately contributing to the advancement of IoD technology. © 2024 IEEE.

关键词： Authentication Protocol

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RSSI-Based 3D Wireless Sensor Node Localization Using Hybrid T Cell Immune and Lotus Optimization

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computers, Materials & Continua 2024年第12期81卷 4833-4851页

作者： Weiwei Hu Kiran Sree Pokkuluri Rajesh Arunachalam Bander A.Jabr Yasser A.Ali Preethi Palanisamy School of Information Engineering Technology&MediaUniversity of HenanKaifeng475004China Department of Computer Science and Engineering Shri Vishnu Engineering College forWomenBhimavaram534202Andhra PradheshIndia Department of Electronics and Communication Engineering Saveetha School of EngineeringSaveetha Institute of Medical and Technical SciencesThandalam602105ChennaiIndia Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityRiyadh11543Saudi Arabia Department of Computer Science and Engineering Saveetha School of EngineeringSaveetha Institute of Medical and Technical SciencesThandalam602105ChennaiIndia

Wireless Sensor Network(WSNs)consists of a group of nodes that analyze the information from surrounding *** sensor nodes are responsible for accumulating and exchanging ***,node local-ization is the process of identifying the target node’s *** this research work,a Received Signal Strength Indicator(RSSI)-based optimal node localization approach is proposed to solve the complexities in the conventional node localization ***,the RSSI value is identified using the Deep Neural Network(DNN).The RSSI is conceded as the range-based method and it does not require special hardware for the node localization process,also it consumes a very minimal amount of cost for localizing the nodes in 3D *** position of the anchor nodes is fixed for detecting the location of the ***,the optimal position of the target node is identified using Hybrid T cell Immune with Lotus Effect Optimization algorithm(HTCI-LEO).During the node localization process,the average localization error is minimized,which is the objective of the optimal node *** the regular and irregular surfaces,this hybrid algorithm effectively performs the localization *** suggested hybrid algorithm converges very fast in the three-dimensional(3D)*** accuracy of the proposed node localization process is 94.25%.

关键词： Sensor node localization received signal strength indicator 3D wireless sensor network deep neural network average localization error and hybrid T cell immune with lotus effect optimization algorithm

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Modeling the Percentage of NEET in Indonesia with Spatial Cauchy Regression through the Bayesian Analysis Approach

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IAENG International Journal of Applied Mathematics 2024年第7期54卷 1288-1295页

作者： Rantini, Dwi Fakhruzzaman, Muhammad Noor Ningrum, Ratih Ardiati Othman, Fazidah Choir, Achmad Syahrul Ramadan, Arip Alya, Najma Attaqiya Putri, Elfira Rahma Pratama, Muhammad Alfian Engineering Department Data Science Technology Study Program Faculty of Advanced Technology and Multidiscipline Universitas Airlangga Indonesia Engineering Department Data Science Technology Study Program Faculty of Advanced Technology andMultidiscipline Universitas Airlangga Indonesia Department of Computer System and Technology Faculty of Computer Science and Information Technology University of Malaya Malaysia Statistical Computing StudyProgram Politeknik Statistika STIS Indonesia Information System Study Program School of Industrial and System Engineering Telkom University Indonesia

Indonesia has entered a period of demographic bonus. Human resources must be optimized. The number of children who do not in employment, education or training (NEET) in each province needs attention. Several factors that could contribute to the decline in the NEET percentage are literacy rates and the number of adolescents with computer skills. Increasing these two factors is believed to be able to reduce the percentage of NEET in every province in Indonesia. To find out the relationship between these two factors and how much influence they have on the percentage of NEET, this research is modeled by Cauchy regression and includes spatial effects. The results of the analysis show that the best model is when the spatial effect is modeled by Fernandez Steel Skew Normal conditionally autoregressive (FSSN CAR). This result is seen from the smallest value of the Watanabe Akaike information Criterion (WAIC) in this model, which is 190.5. The parameter estimated shows that the higher the literacy rate and the number of adolescents with computer skills, the lower the percentage of NEET in each province in Indonesia. The results of this research can be useful for the Indonesian government to increase the number of educational facilities related to these two factors. © (2024), (International Association of Engineers). All rights reserved.

关键词： Bayesian CAR Cauchy Education NEET

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Internet of things technology, research, and challenges: a survey

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Multimedia Tools and Applications 2025年第11期84卷 8455-8490页

作者： Vishwakarma, Amit Kumar Chaurasia, Soni Kumar, Kamal Singh, Yatindra Nath Chaurasia, Renu Management science and technology Khalifa University Abu Dhabi United Arab Emirates Computer science & Engineering SGT University Gurugram India Department of Information Technology IGDTUW New Delhi India Electrical Engineering IIT Kanpur Kanpur India Computer science & Engineering AIT Rooma Kanpur India

The world of digitization is growing exponentially;data optimization, security of a network, and energy efficiency are becoming more prominent. The Internet of Things (IoT) is the core technology of modern society. This paper is based on a survey of recent and past technologies used for IoT optimization models, such as IoT with Blockchain, IoT with WSN, IoT with ML, and IoT with big data analysis. Suppose anyone wants to start core research on IoT technologies, research opportunities, challenges, and solutions. In that case, this paper will help me understand all the basics, such as security, interoperability, standards, scalability, complexity, data management, and quality of service (QoS). This paper also discusses some recent technologies and the challenges in implementation. Finally, this paper discusses research possibilities in basic and applied IoT Domains. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Internet of things

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A Smart CIoT with Secure Healthcare Framework Using Optimized Deep Recuperator Neural Network Long Short-Term Memory

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IEEE Internet of Things Journal 2024年第6期11卷 10551-10562页

作者： Narmatha, C. Manimurugan, S. Karthikeyan, P. University of Tabuk Faculty of Computers and Information Technology Tabuk71491 Saudi Arabia Oakland University Department of Electrical and Computer Engineering RochesterMI112345 United States National Chung Cheng University Department of Computer Science and Information Engineering Chiayi62102 Taiwan RV University School of Computer Science and Engineering Bengaluru560059 India

The healthcare system currently relies on the facility to store and process large amounts of health data, supported by efficient management. The Internet of Things (IoT) has driven the growth of Adroit Healthcare, which has vast data processing capabilities and extensive data collection. The consumer IoT (CIoT), also known as the IoT in the context of individual use cases, is dominated by personal healthcare applications. The remarkable expansion of the CIoT can be attributed to the extensive embrace of wearable technology, facilitating everyday monitoring of vital health indicators like blood pressure, heart rate, and respiration rate. However, the CIoT raises concerns about data security, confidentiality, and customer trust. This study proposes an integrating blockchain and deep learning (DL) approach to promote responsible use of CIoT. The study develops an Intelligent IoT (IIoT) and healthcare diagnostic model, named BT-PWO-DRNN-LSTM, using blockchain technology and Prairie Wolf optimization-based deep recuperator neural network (DRNN) and long short-term memory (LSTM). The BT-PWO-DRNN-LSTM approach includes three key processes: 1) encrypted transactions;2) cryptographic hash feature;and 3) medical diagnosis. The PWO technique is used for secure communication of medical images, the neighborhood catalogue disposition (NCD) technique is used in the cryptographic hash feature operation (CHFO), and the DL approach is employed as a classification algorithm for diagnosing disorders. The use of PWO methodology for secure healthcare communication and optimal parameter fine-tuning highlights the originality of the study. The BT-PWO-DRNN-LSTM prototype showed positive results with high sensitivity, specificity, and accuracy during the diagnostic process. © 2014 IEEE.

关键词： Blockchain

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A Deep Learning Approach for Digitization of Invoices 2

A Deep Learning Approach for Digitization of Invoices

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2nd IEEE International Conference on Intelligent and Innovative Technologies in Computing, Electrical and Electronics, ICIITCEE 2024

作者： Siras, Sarvesh Kshirsagar, Saurabh Inamdar, Vandana Pune Technological University College of Engineering Department of Computer Engineering and Information Technology Pune India

ISBN: (纸本)9798350306415

Digitizing documents using Optical Character Recognition (OCR) has significantly improved in recent years. It is driven by the increasing demand for digitizing printed documents, especially invoices. The task of extracting data from invoices is now easier using an OCR engine like Tesseract. Giving the invoice as input directly to an OCR doesn't help maintain its structures, especially if the invoice has tables. Maintaining the invoice structure is also necessary if the data in the table needs to be processed in a structured form like an Excel *** paper proposes a solution to this problem of invoice processing using the invoice segmentation method involving Convolutional Neural Networks (CNNs) and processing the segmented invoice separately with image pre-processing techniques and OCR. It also discusses the importance of deep learning in invoice processing, Tesseract, the need for image pre-processing, and some techniques that can help enhance the accuracy of invoice processing. © 2024 IEEE.

关键词： CascadeTabNet CNN (Convolutional Neural Network) Deep learning Image processing Invoice OCR (Optical Character Recognition) pre-processing segmentation tabular invoice processing Tesseract

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Analysis of channel capacity for UWB antenna for improvements in the data rates and low Power transmission over wireless application

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International Journal of information technology (Singapore) 2024年第7期16卷 4343-4349页

作者： Bhopale, Nitin I. Pawar, Sunil N. Department of Electronics and Computer Engineering Sanjivani College of Engineering National Institute of Electronics and Information Technology (NIELIT) Chhattrapati Sambhaji Nagar Department of Electronics and Computer Engineering JNEC

Multiple input- Multiple output- Ultra-wideband (MIMO-UWB) is a wireless communication approach that combines multiple antennas at the transmitter and receiver with ultra-wideband frequency spectra to increase data speeds, dependability and spatial diversity in communication systems. The purpose of this research is to study the hybridization of MIMO-UWB over the Rayleigh fading channel using various antenna designs. Convolution encoders are used to encode binary data. The bit interleaver records the encrypted data that is sent to the mapper. The Inverse Fast Fourier Transform is used to handle information from Parallel subcarriers two,four, and eight. To prevent Inter symbol interference, a cyclic prefix is subsequently added. A Fast Fourier transform is used to synchronize signals after they are distorted and two, four, and eight antennas. The cyclic prefix is then deleted. Once the interleaving is done, the data received through various antennas are transformed into serial, demodulated, and decoded. Bit Error Rate (BER) and data rates are used to assess the hybridization system for MIMO-UWB sectorial antenna designs of 2x2,4x4, and *** results obtained indicate that both traditional MIMO and combined MIMO-UWB have higher data rates as SNR increases, with hybridized MIMO-UWB having higher data rates than conventional MIMO and achieving low transmission power. In the same way, hybridized MIMO-UWB yields lower BER values than standard MIMO. This suggests that hybrid MIMO-UWB outperforms traditional MIMO in terms of Rayleigh fading. © Bharati Vidyapeeth's Institute of computer Applications and Management 2024.

关键词： Bit error rate (BER) Multiple input- multiple output (MIMO) Quadrature amplitude modulation (QAM) Rayleigh fading Ultra-wideband antenna (UWB)

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Generating Time-Series Data Using Generative Adversarial Networks for Mobility Demand Prediction

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computers, Materials & Continua 2023年第3期74卷 5507-5525页

作者： Subhajit Chatterjee Yung-Cheol Byun Department of Computer Engineering Jeju National UniversityJeju-si63243Korea Department of Computer Engineering Major of Electronic EngineeringJeju National UniversityInstitute of Information Science&TechnologyJeju63243Korea

The increasing penetration rate of electric kickboard vehicles has been popularized and promoted primarily because of its clean and efficient *** kickboards are gradually growing in popularity in tourist and education-centric *** the upcoming arrival of electric kickboard vehicles,deploying a customer rental service is *** to its freefloating nature,the shared electric kickboard is a common and practical means of *** plans for shared electric kickboards are required to increase the quality of service,and forecasting demand for their use in a specific region is *** demand accurately with small data is *** data is necessary for training machine learning algorithms for effective *** generation is a method for expanding the amount of data that will be further accessible for *** this work,we proposed a model that takes time-series customers’electric kickboard demand data as input,pre-processes it,and generates synthetic data according to the original data distribution using generative adversarial networks(GAN).The electric kickboard mobility demand prediction error was reduced when we combined synthetic data with the original *** proposed Tabular-GAN-Modified-WGAN-GP for generating synthetic data for better prediction *** modified The Wasserstein GAN-gradient penalty(GP)with the RMSprop optimizer and then employed Spectral Normalization(SN)to improve training stability and faster ***,we applied a regression-based blending ensemble technique that can help us to improve performance of demand *** used various evaluation criteria and visual representations to compare our proposed model’s *** data generated by our suggested GAN model is also *** TGAN-Modified-WGAN-GP model mitigates the overfitting and mode collapse problem,and it also converges faster than previous GAN models for synthetic data creation.

关键词： Machine learning generative adversarial networks electric vehicle time-series TGAN WGAN-GP blend model demand prediction regression

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Dynamic Spectrum Management and Spectrum Sharing Techniques in 5G Networks: A Survey

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Journal of Mobile Multimedia 2024年第5期20卷 997-1038页

作者： Mondal, Sonali Dutta, Manash Pratim Chakraborty, Swarnendu Kumar Department of Computer Science & Engineering National Institute of Technology Arunachal Pradesh India Department of Computer Science & Information Technology Cotton University Assam India

The enormous developments of gaming devices as well as mobile apps have increased the demand of bandwidth. Development of wireless applications has been affected because of the insufficient spectrum resources in the 3G and 4G network. This spectrum scarcity is the main limitation of 3G and 4G networks, which leads to the revolution of the 5G technology. Spectrum scarcity is a great challenge in wireless communication. There are two significant research areas that need to be explored such as, searching spectrum resource and maximum spectrum utilization. To address spectrum insufficiency, consistent research is needed to find out spectrum band and share the spectrum resource. In this work, complete Spectrum management framework is discussed as well as spectrum sharing techniques are classified. We have conducted a thorough survey on various spectrum sharing schemes. The literature survey has been classified based on some significant sharing techniques depending on spectrum access method, network architecture, spectrum allocation behavior etc. We have also summarized contribution as well as limitation of recent spectrum sharing approaches. To enhance 5G technology, related spectrum sharing surveys are studied and future research directions are also discussed here. © 2024 River Publishers.

关键词： 5G cognitive radio spectrum management framework spectrum sensing spectrum sharing

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