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7th International Conference on Inventive Computation Technologies, ICICT 2024

作者： Sindhuja, M. Srm Institute of Science And Technology School of Computing College of Engineering And Technology Department of Computing Technologies Tamil Nadu Kattankulathur603203 India

ISBN: (纸本)9798350359299

Cluster Head Selection (CHS) is one of the critical tasks in Wireless Sensor Networks (WSNs) as it directly impacts the network's performance and lifetime. In this manuscript, a Quantum-Inspired Recommendation Algorithm (QIRA) for optimal cluster head selection in WSNs has been proposed. QIRA utilizes the superposition and entanglement properties of quantum mechanics to explore the search space of potential cluster head candidates. The algorithm is designed to consider multiple features such as residual energy, distance to the base station, and node centrality during the process of Cluster Head Selection. The evaluation of the proposed QIRA algorithm, is has been done using wide-ranging simulations and compared with existing cluster head selection processes. The results demonstrate that QIRA is able to achieve significant improvements in terms of network lifetime, energy consumption, and data throughput. © 2024 IEEE.

关键词： Energy efficiency

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An EETR Approach for Therapeutic Response Prediction Using Gene Expression and Drug Properties 3rd

An EETR Approach for Therapeutic Response Prediction Using G...

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3rd International Conference on computing and Communication Networks, ICCCN 2023

作者： Selvi Rajendran, P. Jawahar, Janiel Computer Science and Engineering School of Computing Hindustan Institute of Technology and Science Chennai India

ISBN: (纸本)9789819726707

In recent years, the role of computational methods such as machine learning and deep learning has evolved to help better understand an individual’s response to drugs. Through advancements in the discipline of precision medicine, cancer therapies are made based on an individual's pharmacogenomics data. In this way, doctors can make informed decisions about patient outcomes and reduce treatment costs. Beyond these advancements, there is enough void to precisely predict drug response. A drug’s response to therapy is dependent on a number of factors such as the drug’s physicochemical properties, pharmacokinetics, metabolism, protein, mutation, somatic variation, environment, and much more. Studying the correlation of more of these factors and their association with the drug is one of the promising ways to bridge the gap in improving results. Extra tree regression is an ensemble-based algorithm and is less prone to overfitting than other ensemble learning algorithms particularly when low bias and reduced overfitting are desired, and computational efficiency is important. In this paper, we have applied the drug’s physicochemical properties to predict the Inhibition values using an enhanced extra tree regression (EETR) algorithm. The EETR algorithm prediction outperformed both the random forest and original ETR algorithm in terms of both MSE and R2 score. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Adversarial machine learning

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Inductive Wireless Charging for Onboard Interleaved Buck Boost Integrated Hybrid Storage System of Electric Vehicle 4

Inductive Wireless Charging for Onboard Interleaved Buck Boo...

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4th IEEE International Conference on Sustainable Energy and Future Electric Transportation, SEFET 2024

作者： Singhal, Abhishek Tummuru, Narsa Reddy Vakacharla, Venkata Ratnam School of Computing and Electrical Engineering Indian Institute of Technology Himachal Mandi India

ISBN: (纸本)9798350383997

This work proposes a system configuration for onboard interleaved buck boost (IBB) converter which integrate wireless inductive power transfer (IPT) system as well as hybrid energy storage system (HESS). This IBB converter works as boost converter to drive the load at its output as well as it works as a controlled rectifier for IPT link on secondary side to charge the battery. HESS system has battery, super capacitor (SC) combination which improves the battery lifetime and reduce the current stress on the battery during the transients. IBB converter works as a boost converter when it supplies power to load from HESS and it works a buck converter when it charges HESS from IPT link. Dual loop voltage control scheme is used to manage the power available at output dc link. Based on the power availability IBB converter fulfils the load power demand by charging or discharging of HESS while maintaining constant output voltage. To validate the proposed system configuration a scaled down hardware prototype of 500W is prepared in the laboratory. © 2024 IEEE.

关键词： Hybrid power

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Comparative Design Analysis of a 1 MW Islanded and Non-Islanded Floating Solar Power System at Mangla Hydro Reservoir 11

Comparative Design Analysis of a 1 MW Islanded and Non-Islan...

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11th International Conference on Electrical and Electronics engineering, ICEEE 2024

作者： Paramel, Arshida Aggarwal, Geetika Sabeel, Khursheed Dawood, Huda School of Computing Engineering and Digital Technology Teesside University Middlesbrough United Kingdom

ISBN: (纸本)9798350362541

Solar energy is increasingly recognised as an essential part of the global mission for the net zero goal, owing to its renewable nature and cost-effectiveness. In response to escalating power demands, private power operators and industrial investors seek ways to mitigate electricity costs. This study addresses a specific project: an industrial tender for a 1-megawatt hybrid floating solar power plant intended for a water purification industry in Pakistan. The sector has varying monthly load requirements based on product utilisation and aims to sell surplus energy back to the grid after meeting its operational demands. The choice of a floating solar power plant is driven by the prohibitively high land costs in the vicinity of the dam in Islamnagar, Azad Kashmir, coupled with the unfeasibility of meeting industrial water requirements at locations distant from the dam. This paper will conduct a comparative analysis of grid-connected and standalone options for this industry, focusing on performance metrics. The optimal system, characterised by high efficiency and minimal loss, will be selected for the solar plant design. This design will address aspects including load management, battery storage, and energy provision to the grid. © 2024 IEEE.

关键词： Costs

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Assessing Faculty Perceptions of a Pass/Fail Grading Model in CS1 54

Assessing Faculty Perceptions of a Pass/Fail Grading Model i...

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54th IEEE Frontiers in Education Conference, FIE 2024

作者： Zarb, Mark Brown, John N. A. McDermott, Roger McGowan, Jess Young, Tiffany School of Computing Engineering and Technology Robert Gordon University Aberdeen United Kingdom

ISBN: (纸本)9798350351507

This Innovative Practice Full Paper outlines the findings of a survey conducted at the Robert Gordon University (Scotland, UK), focusing on feedback from faculty members and reflections subsequent to the introduction of a Pass/Fail grading system in the CS1 curriculum within the school of computing, complementing previous work done focussing on the same implementation from the student perspective. This study aims to understand the impact of this grading model on teaching and assessment practices, student engagement, and motivation from the perspective of the module coordinators involved in the foundation year modules where this grading model was implemented. Analysis of the data indicates a generally positive reception of the Pass/Fail grading model among staff members. They reported streamlined marking processes and simplified grading grids as notable advantages. However, concerns were voiced regarding potential student demotivation and the ambiguity in determining the Pass/Fail threshold, which matched results from the student survey. Staff also encountered challenges in adapting assessment designs, particularly in shifting away from traditional grading paradigms. By shedding light on these observations, this paper contributes insights into the intricacies and consequences of integrating a Pass/Fail grading system into the early stages of an undergraduate computing curriculum. It not only underscores the need for careful consideration of pedagogical shifts but also provides valuable guidance for future implementation strategies. In summary, this research delves into the experiences and perspectives of staff members directly involved in implementing the Pass/Fail grading model. By addressing both the benefits and challenges encountered, it offers a comprehensive understanding of the implications of such a grading system within the context of undergraduate computing education. This, in turn, can inform decision-making processes and refine pedagogical approaches for

关键词： Decision making

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Enhancing ResNet Architectures with Bayesian Optimized Stochastic Configuration Networks for Lung X-Ray Image Classification

Enhancing ResNet Architectures with Bayesian Optimized Stoch...

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2024 International Conference on Advanced Mechatronic Systems, ICAMechS 2024

作者： Xu, Hengren Zheng, Jinchuan Cao, Zhenwei Man, Zhihong Swinburne University of Technology School of Science Computing and Engineering Technologies Melbourne Australia

ISBN: (纸本)9798350366204

This paper introduces the ResNet-BOSCN architecture, which integrates Bayesian Optimized Stochastic Configuration Networks (SCNs) with traditional Residual Networks (ResNet) to tackle the challenges of lung X-ray image classification. Unlike conventional methods, ResNet-BOSCN employs Bayesian Optimization to dynamically optimize the network's hidden node count, effectively addressing the complexities inherent in medical imaging datasets. This optimization enables the architecture to adapt more precisely to varying data characteristics, significantly enhancing classification accuracy. ResNet-BOSCN achieves an accuracy of 98.81% in three-class lung X-ray image classification, marking a substantial improvement over the standard ResNet101's accuracy of 97.62%. © 2024 IEEE.

关键词： Lung cancer

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Multiobjective Differential Evolution for Higher-Dimensional Multimodal Multiobjective Optimization

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IEEE/CAA Journal of Automatica Sinica 2024年第6期11卷 1458-1475页

作者： Jing Liang Hongyu Lin Caitong Yue Ponnuthurai Nagaratnam Suganthan Yaonan Wang School of Electrical and Information Engineering Zhengzhou UniversityZhengzhou 450001 School of Electrical Engineering and Automation Henan Institute of TechnologyXinxiang 453003China School of Electrical and Information Engineering Zhengzhou UniversityZhengzhou 450001China KINDI Center for Computing Research Qatar UniversityDohaQatarand also with the Nanyang Technology UniversitySingapore College of Electrical and Information Engineering and also with the National Engineering Research Center for Robot Visual Perception and Control TechnologyHunan UniversityChangsha 410082China IEEE

In multimodal multiobjective optimization problems(MMOPs),there are several Pareto optimal solutions corre-sponding to the identical objective *** paper proposes a new differential evolution algorithm to solve MMOPs with higher-dimensional decision *** to the increase in the dimensions of decision variables in real-world MMOPs,it is diffi-cult for current multimodal multiobjective optimization evolu-tionary algorithms(MMOEAs)to find multiple Pareto optimal *** proposed algorithm adopts a dual-population framework and an improved environmental selection *** utilizes a convergence archive to help the first population improve the quality of *** improved environmental selection method enables the other population to search the remaining decision space and reserve more Pareto optimal solutions through the information of the first *** combination of these two strategies helps to effectively balance and enhance conver-gence and diversity *** addition,to study the per-formance of the proposed algorithm,a novel set of multimodal multiobjective optimization test functions with extensible decision variables is *** proposed MMOEA is certified to be effective through comparison with six state-of-the-art MMOEAs on the test functions.

关键词： Benchmark functions diversity measure evolution-ary algorithms multimodal multiobjective optimization.

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Efficient protection of golden nutri cereal implementing enhanced disease identification injecting hybrid split-attention mechanism through Novel SANDNES Mechanism

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Multimedia Tools and Applications 2024年第38期83卷 85499-85521页

作者： Divya, A. Sungeetha, D. Ramesh, Sundar Department of Electronics and Communication Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Chennai602105 India Department of Networking and Communications School of Computing Faculty of Engineering and Technology SRM Institute of Science and Technology Tamilnadu Kattankulathur Chennai India

Millets, often referred to as "Nutri Cereals," hold significant potential for enhancing future food availability. Over the past 50 years, advancements such as the use of fertilizers, insecticides, and controlled irrigation have markedly increased the productivity of pearl millet crops worldwide. According to the 2020 review report by the Directorate of Millets Development, 693 million hectares of agricultural land are dedicated to pearl millet cultivation. However, managing crop diseases remains a substantial challenge for farmers. Effective crop disease management is crucial for sustainable agriculture, yet traditional algorithms often struggle with accurate detection and computational inefficiency especially in the case of golden cereal termed as "Pearl Millet". Our study introduces a novel approach for disease detection in pearl millet crops using aerial imagery, named Split-Attention Networks with Disentangled Nonlocal and Edge Supervision (SANDNES). This method leverages advanced neural network architectures to enhance disease detection accuracy and efficiency. Our comprehensive numerical evaluations demonstrate that SANDNES outperforms traditional U-Net and U-Net + Nonlocal baseline models Comprehensive evaluations demonstrate SANDNES' exceptional performance, achieving an impressive average F1 score of 89.04%, significantly surpassing other methods in accuracy and efficiency. Specifically, SANDNES achieved notable performance improvements, with F1 scores of 94.88% for healthy crops, 85.96% for honeydew, 82.97% for smut, and 92.69% for ergot. This method leverages split-attention mechanisms for precise feature localization, with Disentangled Nonlocal and Edge Supervision enhancing contextual reasoning and boundary delineation. SANDNES superior computational efficiency and high accuracy make it suitable for real-time precision agriculture applications. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024

关键词： Crops

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Evaluation of Dynamic Power Flow Control and P2P Energy Sharing of Community Microgrids Using PSS Sincal

Evaluation of Dynamic Power Flow Control and P2P Energy Shar...

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2024 International Conference on Smart Systems for Electrical, Electronics, Communication and Computer engineering, ICSSEEC 2024

作者： Thirunavukkarasu, Gokul Sidarth Ismath, Mohamed Ishraf Mohamed Seyedmahmoudian, Mehdi Mekhilef, Saad Stojcevski, Alex School of Science Computing and Engineering Technologies Swinburne University of Technology VIC Australia

ISBN: (纸本)9798350378177

This paper presents an in-depth evaluation of peer-to-peer (P2P) energy sharing in community microgrids using PSS Sincal for power flow simulations. The study focuses on an IEEE bus system configured as community microgrids, where each bus functions as an independent microgrid equipped with loads, Solar PV systems, batteries, and converters. These microgrids are connected to the main grid and leverage a dynamic power flow control mechanism through strategically placed switches managed by a custom algorithm by ensuring the power flow converges. Four distinct scenarios were rigorously tested: 'Isolated Operation,' where each community grid meets its power requirements solely through PV generation;'Total Dependence on the Main Grid,' where PV systems generate no power, and communities rely entirely on the main grid;'Partial PV Generation,' where PV systems partially meet power needs, supplemented by the main grid;and 'Surplus PV Generation,' where PV systems generate excess power for sharing. The PSS Sincal simulations demonstrated the algorithm's effectiveness in enhancing energy distribution efficiency, stability, and the utilization of renewable resources. This study underscores the practical viability of P2P energy sharing in community mi- crogrids, contributing valuable insights to the development of resilient and intelligent power networks. © 2024 IEEE.

关键词： Microgrids

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Label-specific multi-label text classification based on dynamic graph convolutional networks

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Soft computing 2025年第3期29卷 1897-1909页

作者： Yan, Yaoyao Liu, Fang‘ai Liu, Kenan Xu, Weizhi Zhuang, Xuqiang Information Science and Engineering School Shandong Normal University Jinan250358 China Institute of Computing Technology Chinese Academy of Sciences Beijing100190 China

Multi-label text classification is a key task in natural language processing, aiming to assign each text to multiple predefined categories simultaneously. Existing neural network models usually learn the same text representation for different labels, which limits the effectiveness of the models in capturing deep semantics and distinguishing between similar labels;moreover, these models tend to ignore inter-label correlation, leading to loss of information. To overcome these limitations, we propose a novel label-specific dynamic graph convolutional network (LDGCN). This network combines convolutional operations and BiLSTM to model text sequences and obtains label-specific text representations through a label attention mechanism. In addition, LDGCN improves the dynamic graph convolutional network by utilizing statistical label co-occurrence and label reconstruction maps to effectively capture inter-label dependencies and adaptive interactions between label-specific semantic components. Extensive experiments on the RCV1, AAPD, and EUR-Lex datasets show that our model achieves 96.92%, 86.30%, and 81.42% on the P@1 metrics, respectively, and demonstrates a significant advantage in dealing with tail labels. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2025.

关键词： Semantics

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