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An Optimized Framework Development of ABC Algorithm Along with SVMP Algorithm for Lung Cancer Detection 4

An Optimized Framework Development of ABC Algorithm Along wi...

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4th IEEE international conference on Advance computing and Innovative Technologies in Engineering, ICACITE 2024

作者： Rajasekar, M. Arunachalam, P. Priyadharsini, P. Lavanya Devi, N. Abbas, Huda Hayder Al-Qaisy, Shams A. Saveetha Institute of Medical and Technical Science Simats University Saveetha School Oof Engineering Institute of Department of Computer Science and Engineering India Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology Chennai India Nehru Institute of Engineering and Technology Department of Computer Science and Business Systems Tamilnadu Coimbatore India Psna College of Engineering and Technology Department of Ece Dindigul India National University of Science and Technology Collage of Pharmacy Dhi Qar64001 Iraq Al-Farahidi University Baghdad Iraq

ISBN: (纸本)9798350360165

In medicine, early detection of lung cancer is essential for successful treatment regimens. Despite the small sample size, cancer databases often include gene expression levels as attributes. Therefore, in order to increase the convergence speed of the classification algorithm, redundant features should be eliminated. In this work, we present a unique hybrid method for cancer classification called artificial bee colony with support vector machine selection. This approach for early search of a subset of genes for cancer prognosis optimizes feature selection by combining cuckoo search algorithm (CSA) and Spider-Monkey optimization (SMO) algorithm In order with increased accuracy of artificial bee colony method, we perform Minimum Redundancy Maximum Relevance (mRMR).) method, we reduce the redundancy in gene expression data from the cancer dataset and then these selected gene subsets are efficiently classified into different cancer clusters or groups using deep learning (DL) techniques. We evaluate the effectiveness of our proposed method against eight reference microarray gene expression data sets of various cancers. Classification performance is evaluated using measures such as confusion matrix, F1-score, recall, and accuracy. Our findings show that, when applied to large gene expression datasets linked to cancer, the suggested gene selection strategy in conjunction with DL provides improved classification accuracy compared to other existing DL and machine learning methods. © 2024 IEEE.

关键词： Lung cancer

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Multi-UAV Employed Secure Parcel Delivery System using Blockchain 14

Multi-UAV Employed Secure Parcel Delivery System using Block...

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14th international conference on Information and Communication technology convergence, ICTC 2023

作者： Nugraha, Ramdhan Masuduzzaman, Md Choi, Munkyu Shin, Soo Young Kumoh National Institute of Technology Department of It Convergence Engineering Gumi Korea Republic of

ISBN: (纸本)9798350313277

The optimization of parcel delivery services to consumers has become a priority due to the rapid development of the logistics industry, particularly in relation to the primary application of Industry 4.0. It is difficult to maintain trust between a travel company and its consumers. Although many of the current solutions identified in the research address trust issues, most of them are based on centralized architectures, such as cloud computing, where data is vulnerable to a variety of security threats. In this article, a multi-UAV-based secure parcel delivery system using blockchain has been proposed to increase trust among entities. Moreover, genetic algorithms (GA) are exploited to generate routing paths for multiple heterogeneous UAVs. Initially, optimizing fitness function, selection, crossover, and mutation operators are generated by utilizing the GA. The novelty of this research is to propose a secure delivery system using GA for heterogeneous multiple UAVs. Finally, the GA method is constructed to optimize the time constraint issue, and different consensus mechanisms are scrutinized to verify the performance (e.g., latency and average transaction) while storing the parcel delivery information in the blockchain network. © 2023 IEEE.

关键词： Blockchain Delivery System Genetic Algorithm Unmanned Aerial Vehicle Vehicle Routing

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Counterfactual Long-Distance Quantum Communication 1

Counterfactual Long-Distance Quantum Communication

引用

1st international conference on Quantum Communications, Networking, and computing, QCNC 2024

作者： Nang Paing, Saw Duong, Trung Q. Shin, Hyundong Convergence Engineering Kyung Hee University Department of Electronics and Information Yongin-si Korea Republic of Memorial University of Newfoundland Department of Electrical and Computer Engineering St. John'sNLAlB 3X5 Canada

ISBN: (纸本)9798350366778

Long-distance quantum communication holds significant promises for information transmission over extremely large distances. However, ensuring communication security over extensive distances poses considerable challenges. In this article, we propose a new approach to long-distance quantum communication that is carried out in an information-carrying particle-free manner, known as counterfactual quantum communication. Our approach extends the counterfactual transmission signal by leveraging quantum repeaters situated between distant nodes, facilitating counterfactual entanglement swapping. Due to the absence of information-carrying particles in the channel, it enhances the security of information transmission. We demonstrate that our proposed protocol not only establishes the direct communication link between distant nodes, but also generates redundant communication links between neighboring nodes, enhancing resilience against primary link failures. Furthermore, we provide numerical simulations of C-Swap gate and counterfactual long-distance quantum communication scenarios to quantify success probabilities where the photon is not lost during the counterfactual communication. © 2024 IEEE.

关键词： Quantum communication

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Orthotropic Square Plates with Circular Variations in Tapering and Nonhomogeneity 8

Orthotropic Square Plates with Circular Variations in Taperi...

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8th IEEE international conference on Engineering Technologies and Applied Sciences, ICETAS 2023

作者： Lather, Neeraj Gupta, Diksha Kumar, Ankit Gupta, Madhu Sharma, Amit Amity University Haryana Department of Mathematics Gurugram India University of Technology Bahrain Department of Mathematics and Science Salmabad Bahrain School of Engineering and Technology Chitkara University Himachal Pradesh India

ISBN: (纸本)9798350327090

This research paper focuses on analyzing the vibrational frequency characteristics of a square plate that is orthotropic and non-homogeneous. The plate has a circular variation in thickness in two dimensions and circular variation in density in one dimension at the clamped boundary. The temperature distribution across the plate is assumed to follow a two-dimensional parabolic pattern. The Rayleigh-Ritz technique is used to solve the governing equation and determine the vibrational modes. convergence analysis is performed to ensure the accuracy and reliability of the obtained frequency modes for orthotropic square plates. The objective of this study is to provide numerical data that illustrate how the manipulation of plate parameters and design can control the vibrational frequencies, thereby enhancing the performance of orthotropic square plates for specific applications. © 2023 IEEE.

关键词： Vibration analysis

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An Efficient SFLA and CUCKOO Search Hybridization for Source Distribution in Cloud computing

An Efficient SFLA and CUCKOO Search Hybridization for Source...

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2023 IEEE international conference on Integrated Circuits and Communication Systems, ICICACS 2023

作者： Malsoru, Vankudothu Patil, Amareshwari Kusuma, S.M. Shivakanth, Gandla Samanvita, N. Cmr Technical Campus Department of It Hyderabad India Pda College of Engineering Department of Computer Science & Engineering Kalaburagi India Ramaiah Institute of Technology Department of Electronics and Telecommunication Engineering Bengaluru India K L University Vadeeshwaram Department of Computer Science & Engineering Vijayawada India Nitte Meenakshi Institute of Technology Department of Electrical & Electronics Engineering Bengaluru India

ISBN: (纸本)9798350398465

Cloud calculating is a computing prototype that offers inexpensive, scalable computing resources like CPU, storage, and network bandwidth. It provides a pay-as-you-go model for gaining instantaneous online access to a shared pool of resources. This strategy is proposed to cut down on the required amount of computing time. In the most recent paper, authors employ a hybrid approach to resource allocation by combining two powerful optimization algorithms: the Shuffled Frog Leaping Algorithm (SFLA) and the Cuckoo Search (CS) Algorithm. With this algorithm, we can get around the computational time constraints of the HABCCS algorithm and the krill herd algorithm. It's easily scalable, so even niche uses can benefit. The SFLA has the potential to generate a global optimization solution and comes with the added benefits of faster convergence and simpler implementation. Algorithms from the field of computer science are used in difficult situations because of their advantageous simplicity in evaluation. The knapsack problems that normally crop up during the phase of allocating resources are also addressed. The efficacy of the third strategy is evaluated. The investigational consequences demonstrate the greater presentation of the projected method equated to the state-of-the-art methods. © 2023 IEEE.

关键词： Cloud computing

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Research on Tea Disease Model Based on Improved ResNet34 and Transfer Learning

Research on Tea Disease Model Based on Improved ResNet34 and...

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2024 international conference on Intelligent computing and Robotics, ICICR 2024

作者： Ye, Rong Gao, Yanjun He, Yun Shao, Guoqi Gao, Quan Li, Tong College of Food Science and Technology Yunnan Agricultural University Kunming650201 China College of Big Data Yunnan Agricultural University Kunming650201 China The Key Laboratory for Crop Production and Smart Agriculture of Yunnan Province Kunming650201 China

ISBN: (纸本)9798350372274

Aiming at the problems of tea leaf disease recognition with complex background and low accuracy in real environment, this study improved ResNet34 first-layer convolution layer model and combined with different migration methods to build tea disease recognition model. To enhance the model's generalization ability, transfer learning is integrated into the ResNet34 model, and the pre-trained parameter weights are transferred to the original model for training, so as to improve the training speed. Then, by comparing the performance of all four models, namely migration, feature extraction, fine-tuning, and new training, The experimental results show that the test accuracy of the fine-tuned ResNet34 model reaches 94.67%, which is 0.41% higher than that of the whole migration model and 6.56% higher than that of the original ResNet34 model. In addition, the modified fine-tuning model reduces the iteration time of each round by 37.21% compared with the original ResNet34 model. The research shows that the improved model has strong robustness to self-built data sets such as sample imbalance and background heterogeneity. The fine-tuning model can reduce the number of parameters and the reduction of calculation, accelerate the convergence rate of the model, and facilitate the deployment of the model to the mobile terminal equipment of intelligent agriculture in the future, providing useful guidance for the intelligent prevention and control of tea diseases and ensuring the food safety of tea. ©2024 IEEE.

关键词： Federated learning

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Advancements in Human Activity Recognition: A comprehensive Review of Smartphone and Wearable Sensor Integration 7

Advancements in Human Activity Recognition: A comprehensive ...

引用

7th international conference on Inventive Computation Technologies, ICICT 2024

作者： Dhohada, Cheruku Sumalatha, Konatham Vellore Institute of Technology Computer Science And Engineering Vellore India Vellore Institute of Technology Department of Database Systems Vellore India

ISBN: (纸本)9798350359299

In recent years, deep learning and machine learning methods have been extensively employed in almost every field due to their capability of data processing and analysis. These are the subdomains of Artificial intelligence that gather information in different formats and from different sources. Human Activity Recognition using smartphones and wearable sensors has evolved into a dynamic field with numerous applications and challenges. Ongoing research efforts continue to refine methodologies, address challenges, and expand the scope of Human activity recognition, making it an exciting area with significant potential. Nowadays everyone is using smartphones, so it is easy to find their applications in health monitoring, fitness tracking, context-aware computing, and security. The ability to automatically detect activities such as walking, running, and sleeping opens avenues for personalized services and interventions that help in people's daily lives. While traditional machine learning and deep learning models offer valuable insights individually, ensemble learning presents an opportunity to further enhance accuracy and robustness. This research work aims to give a concise overview of the various deep learning and machine learning approaches, their convergence, and an analysis of the applications of these algorithms in the field of smartphone sensor-based human activity recognition. © 2024 IEEE.

关键词： Learning systems

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GUIDANCE LAW BASED ON FAST convergence OF IMPACT TIME

GUIDANCE LAW BASED ON FAST CONVERGENCE OF IMPACT TIME

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2024 CSAA/IET international conference on Aircraft Utility Systems, AUS 2024

作者： Zhu, Tian Huang, Keying Zhang, Qianqian Zhao, Jun Aeronautics Computing Technique Research Institute Shanxi Xi’an China

For the problem of of missile salvo, the impact-time-control-guidance (ITCG) method controls the remaining flight time by designing the guidance law, so as to achieve the target at the specified collision time. In this paper, on the basis of the ITCG method, the feedback control method is used to offset the control command of the original guidance law to realize the control of the collision time. Firstly, the heading angle of the missile is adjusted by Bang-bang control to achieve the purpose of quickly adjusting the residual flying time. Secondly, when the residual flying time error is small, the remaining flight time error is further eliminated by PID control. In this paper, the results indicates that the ITCG method can effectively contain the actual flight time of the missile and converge to the expected missile flight time more quickly than the PNG method, so as to achieve the purpose of accurately striking the target. © The Institution of Engineering & technology 2024.

关键词： Feedback control

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A Novel Quantum Algorithm for Solving Optimization Problems in Electrical Engineering 4

A Novel Quantum Algorithm for Solving Optimization Problems ...

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4th international conference on Innovative Practices in technology and Management, ICIPTM 2024

作者： Sharma, Ajay Sharma, Kuldeep Yadav, Kanchan Rao, A.L.N. Srivastava, Amit Pant, Shivani Chitkara University Chitkara Centre for Research and Development Himachal Pradesh 174103 India Chitkara University Chitkara University Institute of Engineering and Technology Centre of Research Impact and Outreach Punjab Rajpura140401 India GLA University Department of Electrical Engineering Mathura India Lloyd Institute of Engineering & Technology Greater Noida India Lloyd Law College Greater Noida India Uttaranchal University Uttaranchal Institute of Technology Uttarakhand India

ISBN: (纸本)9798350307757

The ability of theoretical and monadic quantum models against number comparison to conventional Quantum Genetic Algorithm (QGA), quantitative particle swarm optimization, ant colony groups with simulated annealing types is analyzed in the context of electrical engineering. Several experiments were done, involving a collection of multiple data sets standard for the proposed circuit layout within power distribution and signal processing applications. In regard to comparative analysis, each algorithm presents its particular strengths for QGA-competitive convergence speed;QPSO - quick conversion of individuals into a global optimum during evolution's course and robust solutions quality in an unstable environment without tuning. The related works of the proposed algorithms include evaluating it against metaheuristics for power systems, nature-inspired hybrid heuristic approaches as well as physics motivated optimization schemes. The paper emphasizes the superiority of quantum algorithms over their classical counterparts, which is a major innovation in optimization space. This detailed analysis contributes to further comprehending the potentials of quantum computing in overcoming tough optimization challenges faced by electrical engineers. © 2024 IEEE.

关键词： Ant colony optimization

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Advanced Simulation and Optimization Strategies in Thermo-Fluid Dynamics: A Deep Learning Approach to Enhancing Heat Transfer in Evaporative Cooling Systems

Advanced Simulation and Optimization Strategies in Thermo-Fl...

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2024 OPJU international technology conference on Smart computing for Innovation and Advancement in Industry 4.0, OTCON 2024

作者： Rajalakshmi, B. Alekhya, V. Lakhanpal, Sorabh Khan, Irfan Munshid, Maha Chasib Maranan, Ramya New Horizon College of Engineering Department of Computer Science Bangalore India Institute of Aeronautical Engineering Hyderabad Dundigal India Lovely Professional University Phagwara India Lloyd Institute of Engineering & Technology Knowledge Park II Uttar Pradesh Greater Noida201306 India National University of Science and Technology Collage of Nursing Dhi Qar64001 Iraq Simats Saveetha School of Engineering Department of Research and Innovation Tamil Nadu Chennai602105 India

ISBN: (纸本)9798350373783

This article describes a novel technique to study and improve evaporative cooling systems to move heat better. The system uses the GA, CNN, LSTM, and FVM algorithms. Each thermofluid dynamics study approach provides something unique. The CNN approach independently acquires spatial information from raw modeling data to study fluid movement. Temporal linkages in sequential data reveal heat's movement over space and time via LSTM. GAN adds continuing antagonistic processes to the dataset, strengthening the model. GA adjusts GAN settings to improve data, whereas FVM simulates realistic fluid dynamics to improve heat transport. Ablation studies demonstrate each algorithm's distinct contributions and importance. Performance comparisons reveal that the recommended framework outperforms others in accuracy, processing time, memory utilization, convergence rate, resilience, and adaptability. Bar charts, line charts, pie charts, and histograms show how the recommended method compares to others. The framework is precise, efficient, and versatile, making it ideal for improving thermo-fluid dynamics models in evaporative cooling systems. Researchers and engineers seeking to improve heat transfer in evaporative cooling systems can utilize it. The proposed architecture is full and adaptable to thermal-fluid utilization issues. © 2024 IEEE.

关键词： Evaporative cooling systems

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