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Modified Metaheuristics with Transfer Learning Based Insect Pest Classification for Agricultural Crops

computer systems science & engineering 2023年第9期46卷 3847-3864页

作者： Saud Yonbawi Sultan Alahmari T.Satyanarayana murthy Ravuri Daniel E.Laxmi Lydia Mohamad Khairi Ishak Hend Khalid Alkahtani Ayman Aljarbouh Samih M.Mostafa Department of Software Engineering College of Computer Science and EngineeringUniversity of JeddahJeddahSaudi Arabia King Abdul Aziz City for Science and Technology RiyadhKingdom of Saudi Arabia Chaitanya Bharathi Institute of Technology HyderabadTelanganaIndia Department of Computer Science and Engineering Prasad V.Potluri Siddhartha Institute of TechnologyVijayawadaIndia Department of Computer Science and Engineering GMR Institute of TechnologyAndhra PradeshRajamIndia School of Electrical and Electronic Engineering Engineering CampusUniversiti Sains Malaysia(USM)Nibong TebalPenangMalaysia Department of Information Systems College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversitySaudi Arabia Department of Computer Science University of Central AsiaNarynKyrgyzstan Faculty of Computers and Information South Valley UniversityQenaEgypt

Crop insect detection becomes a tedious process for agronomists because a substantial part of the crops is damaged,and due to the pest attacks,the quality is *** are the major reason behind crop quality degradation and diminished crop ***,accurate pest detection is essential to guarantee safety and crop *** identification of insects necessitates highly trained taxonomists to detect insects precisely based on morphological ***,some progress has been made in agriculture by employing machine learning(ML)to classify and detect *** study introduces a Modified Metaheuristics with Transfer Learning based Insect Pest Classification for Agricultural Crops(MMTL-IPCAC)*** presented MMTL-IPCAC technique applies contrast limited adaptive histogram equalization(CLAHE)approach for image *** neural architectural search network(NASNet)model is applied for feature extraction,and a modified grey wolf optimization(MGWO)algorithm is employed for the hyperparameter tuning process,showing the novelty of the *** last,the extreme gradient boosting(XGBoost)model is utilized to carry out the insect classification *** simulation analysis stated the enhanced performance of the MMTL-IPCAC technique in the insect classification process with maximum accuracy of 98.73%.

关键词： Sustainable agriculture crop monitoring pest management insect classification computer vision

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Overview of Parallel Computing for Meta-Heuristic Algorithms

Journal of Network Intelligence

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Journal of Network Intelligence 2022年第3期7卷 656-681页

作者： Sun, Ying Chu, Shu-Chuan Hu, Pei Watada, Junzo Si, Mingchao Pan, Jeng-Shyang College of Computer Science and Engineering Shandong University of Science and Technology No.579 Qianwan’gang Road Shandong Qingdao266590 China Graduate School of Information Production and Systems Waseda University Kitakyushu808-0135 Japan College of Computer Science and Engineering Shandong University of Science and Technology China Chaoyang University of Technology Taiwan Taiwan Fujian University of Technology China

The meta-heuristic algorithm is used in the research of various complex problems. Due to the limitations of the original meta-heuristic algorithm, many improved meta-heuristic algorithms have been proposed, such as compact, adaptive, multi-objective and parallel schemes. Among them, the parallel strategy may get a significant improvement for related applications. This paper mainly studies the application of parallel computing in meta-heuristic algorithms. There are two main types of parallelism: one is absolute parallelism, using multiple processors which can solve optimization problems with high computational costs and improve execution efficiency. The other is virtual parallelism (multi-grouping), which decomposes the population into multiple sub-populations, and each sub-population communicates between species to generate better solutions. In addition, the combination of parallel computing and meta-heuristic algorithms can solve a wide variety of application problems: path planning, engineering design, large-scale optimization, image segmentation, neural networks and prediction problems, etc. This paper presents a comprehensive study and systematic survey of parallel meta-heuristics. © 2022, Journal of Network Intelligence. All rights reserved.

关键词： Motion planning

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Covert Communication in Satellite-Terrestrial systems with a Full-Duplex Receiver

Covert Communication in Satellite-Terrestrial Systems with a...

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2024 International Conference on Satellite Internet, SAT-NET 2024

作者： Guo, Zewei Sun, Ranran He, Ji Shen, Yulong Jiang, Xiaohong Future University Hakodate School of Systems Information Science Hakodate041-8655 Japan Hangzhou Institute of Technology Xidian University Hangzhou311200 China Xidian University School of Computer Science and Technology Xi'an710071 China Institute of Systems General Academy of Systems Engineering Academy of Military Sciences Beijing100101 China Xidian University Shaanxi Key Laboratory of Network and System Security Xi'an710071 China

ISBN: (纸本)9798350375176

This paper investigates the covert communication in a satellite-terrestrial system, including a satellite transmitter Alice, a terrestrial full-duplex receiver Bob and a terrestrial warden Willie. To help the covert transmission from Alice, the full-duplex Bob transmits the jamming signal to confuse Willie and also receives the signal from Alice simultaneously. To explore the fundamental covertness in such a system, we first provide theoretical modelings for satellite-terrestrial downlink, and the detection error probability of Willie. Based on these models, we then study the transmit power optimization for covert rate maximization. Finally, we present extensive numerical results to validate our theoretical analysis and to illustrate the impact of various system parameters on the maximum covert rate. © 2024 IEEE.

关键词： Satellite communication systems

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Evolutionary computation for stochastic problems

Evolutionary computation for stochastic problems

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2024 Genetic and Evolutionary Computation Conference Companion, GECCO 2024 Companion

作者： Neumann, Frank Neumann, Aneta Singh, Hemant Kumar The University of Adelaide Optimisation and Logistics School of Computer and Mathematical Science AdelaideSA5005 Australia University of New South Wales School of Engineering and information Technology CanberraACT2600 Australia

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Relevance Search over Knowledge Graph with User-entity Interaction Data 12

Relevance Search over Knowledge Graph with User-entity Inter...

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12th IEEE Global Conference on Consumer Electronics, GCCE 2023

作者： Li, Jianyu Yue, Kun Yunnan University School of Information Science and Engineering China Yunnan University Yunnan Key Laboratory of Intelligent Systems and Computing Kunming China

ISBN: (纸本)9798350340181

Relevance search is to find a list of entities in a knowledge graph (KG), which are associative to a query entity. However, many entities are not linked in KG but are actually associated by user interactions. To this end, we propose a joint weighting function to evaluate the entity associations from both KG and user-entity interaction data simultaneously. Upon the subgraph extracted from KG w.r.t the query entity, we obtain the associative entities by calculating their association degrees. Experimental results show that the effectiveness of our method outperforms other competitors. © 2023 IEEE.

关键词： Association reactions

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Utilization of DenseNet201, EfficientNetB3, Resnet50, and VGG19 as Pre-Trained Convolutional Neural Network Models for Brain Tumour Classification

Utilization of DenseNet201, EfficientNetB3, Resnet50, and VG...

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International Conference on Artificial Intelligence in information and Communication (ICAIIC)

作者： Kanwarpartap Singh Gill Rupesh Gupta Gunjan Shandilya Srinivas Aluvala Adel Sulaiman Hani Alshahrani Mana Saleh Al Reshan Asadullah Shaikh Chitkara University Institute of Engineering and Technology Chitkara University Punjab India School of Computer Science & Artificial Intelligence SR University Warangal India Department of Computer Science College of Computer Science and Information Systems Najran University Najran Saudi Arabia Emerging Technologies Research Lab (ETRL) College of Computer Science and Information Systems Najran University Najran Saudi Arabia Department of Information Systems College of Computer Science and Information Systems Najran University Najran Saudi Arabia

ISBN: (数字)9798331507022

ISBN: (纸本)9798331507039

A major development in medical imaging diagnosis is the use of pretrained Convolutional Neural Network (CNN) models for brain tumour classification. This study uses pretrained CNN EfficientNetB3, ResNet50, and VGG19, to explore the crucial field of early brain tumour identification. The dataset used in the research consists of 7023 brain MRI images, which are divided into 2000 validation images, 1311 testing images, and 3712 training images. After preparing the data, we want to see which CNN designs work best for sorting images of gliomas, meningiomas, no tumors, and pituitaries into different groups. The study shows how important it is to find brain tumors early and how we can make brain imaging tests more accurate and helpful for diagnosing them. The EfficientNetB3 model is the best and wins with remarkable 99% accuracy. The results show the good and bad points of different models and give important information to help improve skills in diagnosing using neuroimaging.

关键词： Neuroimaging Training Accuracy Magnetic resonance imaging Brain tumors Brain modeling Convolutional neural networks Medical diagnostic imaging Residual neural networks Testing

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An online greedy algorithm for path stretch of LEO satellite networks 3

An online greedy algorithm for path stretch of LEO satellite...

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3rd International Conference on Consumer Electronics and computer engineering, ICCECE 2023

作者： Lu, Yong Liang, Ruishi School of Electronic Information Engineering Fosan University Foshan China School of Computer University of Electronic Science and Technology of China Zhongshan Institute Zhongshan China

ISBN: (纸本)9798350331578

In this paper, aiming at the NP-hard property of routing problems in LEO satellite networks, which include the Minimum Path Stretch Schedule (MIN-PSS), Maximum Path Contraction Schedule (MAX-PCS) and Maximum Constant Path Schedule (MAX-CPS) problems, we put forward an online greedy algorithm with the time complexity O(nlogn) to cope with the core MIN-PSS problem. The MAX-PCS and MAX-CPS problems can be solved by the similar method. The simulation results show that the proposed algorithm can effectively reduce the rate of path stretch with low computational complexity. © 2023 IEEE.

关键词： Approximation algorithms

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Exploring the Potential of Quantum Computing for Revolutionary Problem-Solving and Computational Advancements

Exploring the Potential of Quantum Computing for Revolutiona...

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2024 International Conference on Cybernation and Computation, CYBERCOM 2024

作者： Guru Vimal Kumar, M. Paramesh, J. Sriram, K.P. Anbalagan, E. Sasikumar, S. Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Department of Computer Science and Engineering Avadi Chennai India Saveetha Engineering College Department of Computer Science and Engineering Chennai India Information Technology St. Joseph's Institute of Technology OMR Chennai India Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798331542344

Quantum computing is a model of computing a new approach to perform and solve computational problems and comes up with amazing advantages such as exponential speed-up of specific tasks that lead to a revolution of industries. In this study, Quantum Computing potential is discussed in multiple fields - drug discovery and optimization, and quantum machine learning contrasted with traditional methods based on the running time, accuracy, and scalability of quantum and classical algorithms. Applying several quantum algorithms to molecular simulation, optimization problem, and image classification data sets, quantum algorithms solved problems with at least 70% less number of iterations and at worse the same accuracy as classical methods. For instance, researchers noted that quantum neural networks performed better than classical networks in image recognition. The quantum algorithms in this study were implemented and simulated using IBM Qiskit, D-Wave's Ocean SDK and TensorFlow Quantum. Based on the literature reviewed;it was established that quantum computing has potential to revolutionalise endeavours in drug design, cryptography and artificial intelligent applications. While there are issues in qubit stability quantum decoherence, errors and other related complications, it is predicted that all these problems will be solved by qubit stability and quantum error correction shortly and therefore, realistic, scalable quantum systems are in the next few years. Further research is required on the quantum technology one which may bring a revolution in the way different industries solve their problems. © 2024 IEEE.

关键词： Qubits

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SQLStateGuard: Statement-Level SQL Injection Defense Based on Learning-Driven Middleware 15

SQLStateGuard: Statement-Level SQL Injection Defense Based o...

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15th Annual ACM Symposium on Cloud Computing, SoCC 2024

作者： Liu, Xin Huang, Yuanyuan Wang, Tianyi Li, Song Niu, Weina Shen, Jun Zhou, Qingguo Zhou, Xiaokang School of Information Science and Engineering Lanzhou University Gansu Lanzhou China The State Key Laboratory of Blockchain and Data Security Zhejiang University Zhejiang Hangzhou China School of Computer Science and Engineering University of Electronic Science and Technology of China Sichuan Chengdu China School of Computing and Information Technology University of Wollongong WollongongNSW Australia Kansai University Osaka Suita Japan

ISBN: (纸本)9798400712869

SQL injection is a significant and persistent threat to web services. Most existing protections against SQL injections rely on traffic-level anomaly detection, which often results in high false-positive rates and can be easily bypassed by attackers. This paper introduces SQLStateGuard, the world's first middleware-driven statement-level SQL injection defense approach, to address these issues. The SQLStateGuard uses a custom SQL middleware based on the idea of Runtime Application Self-Protection to capture raw SQL statements. These statements are then analyzed by SQLSG-Net, a database-oriented detection network based on gated linear units. If SQLSG-Net detects malicious SQL statements, the SQL middleware will block them. Experiments show that the detection accuracy of SQLStateGuard exceeds 99%, outperforming existing approaches, and it can identify the type of a specific SQL injection. Additionally, SQLStateGuard has no fingerprint and does not respond to SQL syntax errors, making it more challenging for attackers to gather information. This paper also presents a novel dataset generation process for SQLStateGuard and shares two statement-level SQL injection datasets with the research community, including over 145,000 malicious SQL statements categorized by the type of SQL injection. © 2024 ACM.

关键词： Middleware

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A Review of Smart Materials for the Boost of Soft Actuators,Soft Sensors,and Robotics Applications

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Chinese Journal of Mechanical engineering 2022年第2期35卷 12-27页

作者： Yufei Hao Shixin Zhang Bin Fang Fuchun Sun Huaping Liu Haiyuan Li School of mechanical engineering University of Science and Technology BeijingBeijing 100083China School of Engineering and Technology China University of Geosciences(Beijing)Beijing 100083China Department of Computer Science and Technology Tsinghua National Laboratory for Information Science and TechnologyTsinghua UniversityBeijing 100084China School of Automation Beijing University of Posts and TelecommunicationsBeijing 100876China

With the advance of smart material science,robotics is evolving from rigid robots to soft *** to rigid robots,soft robots can safely interact with the environment,easily navigate in unstructured fields,and be minimized to operate in narrow spaces,owning to the new actuation and sensing technologies developed by the smart *** the review,different actuation and sensing technologies based on different smart materials are analyzed and *** to the driving or feedback signals,actuators are categorized into electrically responsive actuators,thermally responsive actuators,magnetically responsive actuators,and photoresponsive actuators;sensors are categorized into resistive sensors,capacitive sensors,magnetic sensors,and optical waveguide *** introducing the principle and several robotic prototypes of some typical materials in each category of the actuators and *** advantages and disadvantages of the actuators and sensors are compared based on the categories,and their potential applications in robotics are also presented.

关键词： Smart material Soft robot Actuator Sensor

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