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2024 International Symposium on computing and Intelligent Systems, SCI 2024

作者： Pecheti, Shiva Teja Kodurupaka, Nithin Basavadeepthi, H.M. Tanvi, Talari Beena, B.M. Department of Computer Science & Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Karnataka Bangalore560035 India

This research focuses on creating a Drug Information and Recommendation System using Amazon Web Services (AWS) for sentiment analysis of pharmaceutical reviews. The methodology encompasses data collection, preprocessing, sentiment analysis, and drug prediction. AWS services such as EC2, S3, and IAM are utilized to ensure compatibility, scalability, and security. The resultant platform, Sentiment AI, is deployed seamlessly on AWS, demonstrating efficient resource utilization and real-time monitoring through CloudWatch. This work signifies a significant step forward in pharmaceutical sentiment analysis, harnessing the power of cloud computing to provide reliable and effective insights into user perceptions of medications. © 2024 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).

关键词： Sentiment analysis

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A Comparative Study on using Genetic Algorithm with DEAP framework on Different Optimization Problems 7

A Comparative Study on using Genetic Algorithm with DEAP fra...

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7th International Conference on Contemporary computing and Informatics, IC3I 2024

作者： Aravind Krishna, S.V. Prashanna, R. Midhru Jayan, J. Jeyakumar, G. Amrita School of Computing Amrita Vishwa Vidyapeetham Department of Computer Science and Engineering Tamil Nadu Coimbatore India

ISBN: (纸本)9798350350067

Evolutionary Algorithms (EAs) are the solution approaches for solving optimization problems using the classical generate-and-test method. These algorithms are widely used by the practitioners for solving the optimization problems and are studied by the researchers for their advancements. Few highlighted advancements in the domain of EAs are distributed EAs, ensemble EAs, modular EAs, and tuning free EAs. Nevertheless, for the practitioners to get the clarity on the working principle of EAs, the literature is lacking with a comprehensive article reporting their performance on different problems. The research study presented in this paper is an attempt to alleviate this shortcoming. This paper aimed at presenting in detail the working principle of Genetic Algorithm (GA) on different problems which are generally used as reference problems for design and analysis of algorithms. The problems considered in the study are one-max problem, 0/1 Knapsack problem and N Queen problem. The experimental setups are carefully designed, for these three problems, and are solved by implementing GAs on the DEAP (Distributed Evolutionary Algorithms in Python) framework. The performance of the GAs is studied based on the quality and speed performance metrics and the inferences are presented in this paper. © 2024 IEEE.

关键词： Genetic algorithms

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Towards an Internet-like Power Grid

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Journal of Modern Power Systems and Clean Energy 2022年第1期10卷 1-11页

作者： Iasonas Kouveliotis-Lysikatos Nikos Hatziargyriou Yanli Liu Felix Wu Department of Electrical Engineering and Computer Science KTH-Royal Institute of TechnologyTeknikringen 3310040StockholmSweden School of Electrical and Computer Engineering National Technical University of Athens15773 AthensGreece School of Electrical and Information Engineering Tianjin UniversityTianjin300072China Department of Electrical and Electronic Engineering The University of Hong KongHong KongChina Department of Electrical Engineering and Computer Sciences University of CaliforniaBerkeleyCA 94720USA

The great challenges faced by modern power systems require a fresh look at the conventional operation paradigm. The significant challenges faced by modern power systems require an innovative method for the conventional operation paradigm. We claim that the decarbonization of the power grid and extensive electrification of numerous sectors of human activity can only be fostered by a self-adaptable and smart power grid that manifests similar qualities to those of the Internet. The Internet is constructed on a layered architecture that facilitates technology innovations and its intelligence is distributed throughout a hierarchy of networks. In this paper, the fundamental differences between the network data flows and power flows are examined, and the basic requirements for an innovative operation paradigm are highlighted. The current power grid is operated in a highly inflexible, centralized manner to meet increased security goals. A new highly flexible, distributed architecture can be realized by distributing the operation responsibility in smaller areas or even in grid components that can make autonomous decisions. The characteristics of such a power grid are presented, and the key features and advances for the on-going transition to a sustainable power system are identified. Finally, a case study on distributed voltage control is presented and discussed.

关键词： Smart grid Internet distributed intelligence decentralized architecture

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International Journal of computers and Applications 2023年第5期45卷 379-390页

作者： Liu, J. Shao, H.J. Deng, X. Jiang, Y.T. School of Computer Jiangsu University of Science and Technology Zhenjiang China Department of Electrical and Computer Engineering University of Nevada Las VegasNV United States

The paper discusses the high computational costs associated with convolutional neural networks (CNNs) in real-world applications due to their complex structure, primarily in hidden layers. To overcome this issue, the paper proposes a novel channel pruning technique that leverages the correlation topology of feature maps generated by each CNNs layer to construct a network with fewer nodes, reducing computational costs significantly. Redundant channels exhibit a high degree of topological similarity and tend to increase as the number of network layers rises. Removing the channel corresponding to highly correlated feature maps allows retrieval of the ‘base’ set of characteristics needed by subsequent layers. The proposed channel pruning technique provides a promising approach to reducing the computational costs of deep convolutional neural networks while maintaining high performance levels. By designing a network structure optimized for specific input data types, the method results in more efficient and effective machine learning models. The pruning operation requires fine-tuning to optimize network performance, and experiments using X-ray, chest CT, and MNIST images show that the pruned network can eliminate approximately 80% of redundant channels with minimal performance deterioration (maintaining original CNNs performance at 99.2%). © 2023 Informa UK Limited, trading as Taylor & Francis Group.

关键词： Topology

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HFPSA: A Hybrid Fuzzy Logic, Particle Swarm Optimization and Simulated Annealing Mechanism for Sensor Node Localization 5

HFPSA: A Hybrid Fuzzy Logic, Particle Swarm Optimization and...

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5th International Conference on Data Intelligence and Cognitive Informatics, ICDICI 2024

作者： Vishwas, H.N. Ramesh, T.K. Amrita Vishwa Vidyapeetham Amrita School of Computing Department of Computer Science and Engineering Bengaluru India Amrita Vishwa Vidyapeetham Amrita School of Engineering Department of Electronics and Communication Engineering Bengaluru India

ISBN: (纸本)9798350389609

Wireless sensor networks have been adopted widely in various application and these networks play crucial role in numerous real-time monitoring systems. However, the event occurrence, detection of event and localizing the event are the crucial aspect of these networks. Accurate node localization in WSNs is essential for various applications, including environmental monitoring and military surveillance. However, conventional methods like trilateration frequently face challenges due to issues like signal attenuation and environmental obstacles, resulting in substantial localization errors in real-world settings. The main aim of this article is to overcome these challenges by developing and a hybrid localization approach that improves both accuracy and reliability in WSN node localization. The proposed approach uses a combination of particle swarm optimization with simulated annealing with RSSI based distance estimation mechanism. Moreover, this approach also uses Fuzzy logic model to handle the uncertainty in distance error measurement. The combination of these model is validated by measuring the performance by simulating the WSN localization environment where proposed HFPSA has reported improve localization performance by reducing the overall localization error. © 2024 IEEE.

关键词： Particle swarm optimization (PSO)

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VisioRenalNet: Spatial Vision Transformer UNet for enhanced T2-Weighted Kidney MRI Segmentation 2

VisioRenalNet: Spatial Vision Transformer UNet for enhanced ...

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2nd International Conference on Machine Learning and Data engineering, ICMLDE 2023

作者： Afnaan, K. Palaniswamy, Suja Singh, Tripty Prakash, Bhanu Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Bangalore India Singapore Singapore

Chronic Kidney Disease (CKD) afflicts approximately 20% of the global population, underscoring the pressing need for precise detection and diagnosis. Accurate kidney segmentation in medical imaging is pivotal for capturing intricate details, facilitating effective evaluation and treatment planning. This work consists implementation of U-Net Variants along with enhanced variant for kidney segmentation in Magnetic Resonance Images (MRI). We systematically assess the performance of various U-Net variants, including U-Net, VGGUNet, DenseUNet, ResUNet, U-Net++, and AttentionUNet, utilizing a publicly available dataset of T2-weighted abdomen MRI scans from 100 subjects. Subsequently, we propose an enhanced U-Net framework that seamlessly integrates transformer blocks, spatial Attention Mechanism, and swish activation to enhance performance and robustness. Enhanced UNet provides improved feature learning, enhanced contextual information, selective focus and improved performance metrices for Kidney Segmentation. This significant advancement in medical image segmentation can contribute to enhanced diagnosis, more effective treatment planning, and improved disease management for individuals suffering from kidney diseases. Notably, our enhanced U-Net variant, after 50 epochs, achieved an average Dice coefficient of 89.1%, a Jaccard score of 80.4%, and an impressive accuracy of 96.2%, surpassing all baseline U-Net variants in all evaluation metrics, thereby affirming its superiority in kidney segmentation. © 2024 Elsevier B.V.. All rights reserved.

关键词： Chemical activation

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Feedback-Regulated Information Fusion Approach for Optimizing Multiple Spread Control in complex Network 5

Feedback-Regulated Information Fusion Approach for Optimizin...

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5th International Conference on Innovative Data Communication Technologies and Application, ICIDCA 2024

作者： Cheriyan, Jo Nair, Jyothisha J. Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Kerala Amritapuri690546 India

The information spread uses a social media platform, where one user intends to share information with others intentionally or non-intentionally. The rapid spread of information on social media platforms is a complex phenomenon influenced by many factors. However, the factors influencing this rapid spread in the online space still need to be discovered. Individuals utilize social media platforms to share their experiences regarding various events related to products or services. Given the intricate and multilayered nature of social media networks, the feedback received from each layer essentially mirrors the collective perceptions of the world. This process involves fusing information from each node within the network to arrive at a decision specific to the corresponding layer. And regulate the multiple spreads through the social networks. The system is verified by using a diffusion model to ensure correctness. The verification and validation show the suitability of the proposed system in controlling multiple spreading. © 2024 The Authors. Published by Elsevier B.V.

关键词： Feedback

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Fall Detection for Elderly People using LiDAR Sensor 3

Fall Detection for Elderly People using LiDAR Sensor

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3rd International Conference on Artificial Intelligence For Internet of Things, AIIoT 2024

作者： Viswa, A.V. Dharma Pravardhana, V. Thangavel, Senthil Kumar Jeyakumar, G. Amrita Vishwa Vidyapeetham Amrita School of Computing Coimbatore Department of Computer Science and Engineering Tamil Nadu India

ISBN: (纸本)9798350372120

Understanding the prevalence and severity of accidental falls among the elderly is crucial. Even for those living independently, falls are frequent and can lead to severe injuries, often being a primary cause of elderly mortality. To address this need, the development of a comprehensive platform becomes essential, capable of continuously monitoring individuals' activity status for timely detection of falls and other unexpected behaviors. Real-time monitoring is vital for providing swift and efficient early warnings during a fall. Conventional methods of monitoring, such as manual surveillance, are resource-intensive and may lack the immediacy required to respond effectively to fall incidents. Therefore, to overcome these limitations, innovative solutions have been introduced. Implementing an automated system can significantly reduce the time and energy expended on monitoring while ensuring a prompt and proactive response to potential fall events. Despite advancements in fall detection research, many existing studies rely on wearable devices primarily within home settings. Extending the scope of these technologies to diverse environments could result in more inclusive and versatile fall detection systems, enhancing elderly safety across various settings. Conventional fall detection systems frequently encounter privacy concerns when employing RGB camera-based monitoring due to their intrusive nature. To tackle this issue, alternative non-intrusive methods such as LiDAR technology have been introduced. LiDAR proves to be effective in detecting falls while also upholding privacy, rendering it a promising option for enhancing geriatric safety. © 2024 IEEE.

关键词： Anomaly detection

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Prescribed-Time Nash Equilibrium Seeking for Pursuit-Evasion Game

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IEEE/CAA Journal of Automatica Sinica 2024年第6期11卷 1518-1520页

作者： Lei Xue Jianfeng Ye Yongbao Wu Jian Liu D.C.Wunsch Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of EducationNanjing 210096 School of Automation Southeast UniversityNanjing 210096China Department of Electrical and Computer Engineering Missouri University of Science and TechnologyRollaMO 65409 USA IEEE

Dear Editor,This letter is concerned with prescribed-time Nash equilibrium(PTNE)seeking problem in a pursuit-evasion game(PEG)involving agents with second-order *** order to achieve the prior-given and user-defined convergence time for the PEG,a PTNE seeking algorithm has been developed to facilitate collaboration among multiple pursuers for capturing the evader without the need for any global ***,it is theoretically proved that the prescribedtime convergence of the designed algorithm for achieving Nash equilibrium of ***,the effectiveness of the PTNE method was validated by numerical simulation results.A PEG consists of two groups of agents:evaders and *** pursuers aim to capture the evaders through cooperative efforts,while the evaders strive to evade *** is a classic noncooperative *** has attracted plenty of attention due to its wide application scenarios,such as smart grids[1],formation control[2],[3],and spacecraft rendezvous[4].It is noteworthy that most previous research on seeking the Nash equilibrium of the game,where no agent has an incentive to change its actions,has focused on asymptotic and exponential convergence[5]-[7].

关键词： seeking prescribed convergence

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Investigation of Android Malware Using Deep Learning Approach

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Intelligent Automation & Soft computing 2023年第2期35卷 2413-2429页

作者： V.Joseph Raymond R.Jeberson Retna Raj Department of Computer Science and Engineering Sathyabama Institute of Science and TechnologyChennai600119TamilnaduIndia School of Computing SRM Institute of Science and TechnologyChennai603203TamilnaduIndia

In recent days the usage of android smartphones has increased exten-sively by *** are several applications in different categories bank-ing/ﬁnance,social engineering,education,sports andﬁtness,and many more *** android stack is more vulnerable compared to other mobile plat-forms like IOS,Windows,or Blackberry because of the open-source *** the Existing system,malware is written using vulnerable system calls to bypass signature detection important drawback is might not work with zero-day exploits and stealth *** attackers target the victim with various attacks like adware,backdoor,spyware,ransomware,and zero-day exploits and create threat hunts on the day-to-day *** the existing approach,there are various tradi-tional machine learning classiﬁers for building a decision support system with limitations such as low detection rate and less feature *** important contents taken for building model from android applications like Intent Filter,Per-mission Signature,API Calls,and System commands are taken from the manifestﬁ*** function parameters of various machine and deep learning classiﬁers like Nave Bayes,k-Nearest Neighbors(k-NN),Support Vector Machine(SVM),Ada Boost,and Multi-Layer Perceptron(MLP)are done for effective *** our pro-posed work,we have used an unsupervised learning multilayer perceptron with multiple target labels and built a model with a better accuracy rate compared to logistic regression,and rank the best features for detection of applications and clas-sify as malicious or benign can be used as threat model by online antivirus scanners.

关键词： Android application permissions multilayer perception relief scoring

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