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2024 International Conference on Optimization Computing and Wireless Communication, ICOCWC 2024

作者： Jebaraj, N.R. Solomon Shekhawat, Jyoti Gupta, Rupal Department of Computer Science and Information Technology Bangalore India Computer Science & Application Vivekananda Global University Jaipur India Teetthanker Mahaveer University Department of Computing Sciences and Information Technology Uttar Pradesh Moradabad India

ISBN: (纸本)9798350383348

This paper offers a top-stage view of clustering algorithms that can be used for Clustering algorithms, which are robust and bendy techniques for uncovering patterns and anomalies in large datasets. Those algorithms can be used for grouping transactions with capabilities together with place, hour, gadgets bought, card holder, or each different characteristic related to the marketing. For credit card fraud detection, clustering algorithms are famous answers due to their capability to discover anomalous clusters that could represent fraudulent transactions. High-quality, well-known clustering algorithms and ok-way, hierarchical, and fuzzy clustering are mentioned as their particular packages. The paper also offers a few case studies concerning the usage of clustering algorithms for credit card fraud detection. This case research suggests real-global examples of how clustering algorithms may be implemented for credit rating card information. In the end, the paper outlines the demanding situations and possibilities of clustering algorithms. It is essential for banking structures, as unauthorized use of credit scorecards results in widespread economic losses. Detection of fraud is often predicated on gadgets mastering algorithms in conjunction with clustering algorithms. Clustering algorithms are the unsupervised getting-to-know method used to group patterns of facts based on similarity to find ability fraud. Famous clustering algorithms embody okay-manner, Gaussian aggregate models, and Self-Organizing Maps. Those algorithms are trying to differentiate legitimate clients from those committing fraud by figuring out clusters of ordinary behavior. Ok-manner uses an iterative manner to group data in keeping with Euclidean distance measures. Gaussian aggregate models use a probabilistic method to classify kinds of records and may incorporate preceding information approximately the statistics location if you want to generate extra accurate clusters. Self-organizing maps use a

关键词： aggregate detection Exceptional fraudulent functions

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Investigating the Use of Spatial Transformer Networks and Recurrent Neural Networks for Medical Image Segmentation

Investigating the Use of Spatial Transformer Networks and Re...

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2024 International Conference on Optimization Computing and Wireless Communication, ICOCWC 2024

作者： Saxena, Vineet Nachappa, M.N. Shree, Ritu Teetthanker Mahaveer University Department of Computing Sciences and Information Technology Uttar Pradesh Moradabad India Department of Computer Science and Information Technology Bangalore India Computer Science & Application Vivekananda Global University Jaipur India

ISBN: (纸本)9798350383348

This paper investigates using popular deep learning models, Spatial Transformer Networks (STNs), and Recurrent Neural Networks (RNNs) for clinical picture segmentation. STNs are used to study a learnable pose-invariant body that permits image segmentation throughout exceptional segmentation tasks and affected person populace. RNNs seize temporal context within the facts and enhance segmentation accuracy. The paper evaluates the overall performance of the two models on the publicly available MIMIC-III dataset. It compares the outcomes with a segmentation model primarily based on the usual convolutional neural network (CNN) structure. The results reveal that the STN and RNN fashions gain superior overall performance compared to the usual CNN version in medical photograph segmentation. The look additionally highlights the capacity of deep studying fashions for addressing various demanding situations associated with clinical photograph segmentation. © 2024 IEEE.

关键词： architecture convolutional population Recurrent segmentation

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Enhancing Network Security with Blockchain technology

Enhancing Network Security with Blockchain Technology

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2024 International Conference on Optimization Computing and Wireless Communication, ICOCWC 2024

作者： Inzimam Bishnoi, Amit Kumar Menaka, C. Vivekananda Global University Department of Computer Science & Application Jaipur India Teerthanker Mahaveer University Computing Sciences and Information Technology Uttar Pradesh Moradabad India Department of Computer Science and Information Technology Bangalore India

ISBN: (纸本)9798350383348

The block chain era is hastily traction as a sturdy approach to community security. In its conventional shape, block chain integrated is a distributed, immutable, and cryptographically-secured ledger, composed of virtual built in integrated shared amongst a disbursed community of nodes. This distributed ledger presents a platform for relaxed storage and verification of digital assets, built-inclusive of integrated crypto currencies, at the same time as built-integrated users with transactional privateness. As block chain-integrated technology advances, new applications, and protocols are built-integrated to resolve a variety of building situations related to network security. One such application is the utility of smart contracts to verify that community transactions are built-integrated, secure, and legitimate. By means of leverage building block chain integrated distributed ledger generation, clever contracts are capable of automating the execution of transactions at the same time as concurrently verifying their authenticity. This technique is built-in vital integrated fields of built finance and healthcare, as those built industries should manipulate and display access to treasured statistics and builtings. Moreover, smart contracts can be used to the right of entry to manage and authentication protocols, present built integrated customers with greater comfy get entry to data or sources. Any other use case there is for the deployment of distributed denial-of-carrier (DDoS) assault prevention protocols. DDoS attacks are one of the most luxurious and unfavorable online safety threats, and they use big amounts of bandwidth to crush a built in integrated or network-integrated infrastructure. © 2024 IEEE.

关键词： Bandwidth Contracts Conventional Generation Healthcare Infrastructure

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Research on the Network Transmission technology of Integrating the Resource Demand of computer Cloud Computing 2

Research on the Network Transmission Technology of Integrati...

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2nd IEEE International Conference on Distributed Computing and Electrical Circuits and Electronics, ICDCECE 2023

作者： Ou, Wenjisi Zheng, Wei Zhou, Qiang Jiangxi Vocational and Technical College of Information Application Department of Computer Technology Nanchang330043 China

ISBN: (纸本)9798350347456

The establishment of a network environment under the network environment under the network environment of the network environment. First of all, in view of the periodic characteristics of business requirements in the PaaS software system, the business cycle characteristics of the business system and the business cycle characteristics of the business system are integrated based on the business cycle characteristics of the business, and the business model of the business system is formed. The multi-objective optimization method based on multi-objective optimization is used to solve the multi-objective optimization problem. This paper proposes a Paas-oriented master-slave service model, and develops and applies it. Experiments show that if a finite resource is used in the whole system, then the whole system is limited, this method can maximize the utilization of resources in the system. This paper presents a new security threat assessment method based on cloud computing environment, and it has strong recognition. © 2023 IEEE.

关键词： Multiobjective optimization

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Internet of Everything: A Review on Smart Healthcare Taxonomy, Research Challenges and Methodologies 14

Internet of Everything: A Review on Smart Healthcare Taxonom...

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14th International Conference on Computing Communication and Networking Technologies, ICCCNT 2023

作者： Raj, Anu Prakash, Shiva Srivastava, Jyoti Madan Mohan Malaviya University of Technolgy Information Technology & Computer Application Department Gorakhpur India

ISBN: (纸本)9798350335095

The Internet of Everything (IoE) has the potential to revolutionize many aspects of our daily lives, including healthcare, business and industrial world etc. Smart healthcare systems that utilize IoE technologies could greatly improve patient outcomes, increase efficiency, and reduce costs. However, there are several challenges that must be overcome in order to develop effective and reliable power supply systems for IoE-enabled healthcare devices. IoE healthcare devices may be deployed in a variety of settings, and the power supply system must be able to monitor and manage these devices remotely. The development of high-performance smart healthcare systems for the IoE requires the development of reliable and scalable power supply systems that can overcome the challenges of distribution, connection, charging technologies, and management. This paper mainly emphasizes on the IoE and their components that are used in the smart healthcare system and rising of the research challenges. In this paper, by addressing the taxonomy of healthcare and research challenges, researchers and businesses can develop innovative solutions that will transform healthcare delivery and improve patient outcomes. © 2023 IEEE.

关键词： Internet of Everything

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Research on Cloud Computing Security technology under computer Big Data Network 3

Research on Cloud Computing Security Technology under Comput...

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3rd IEEE International Conference on Electronic technology, Communication and information, ICETCI 2023

作者： Zhou, Qiang Ou, Wenjisi Zheng, Wei Jiangxi Vocational and Technical College of Information Application Department of Computer Technology Nanchang330043 China

ISBN: (纸本)9798350398410

In this paper, a parameter estimation-based security access integration method for computer network smart data is designed. The scale of data clustering is determined according to the distribution and evolution characteristics in the clustering process. Finally, this paper proposes a new security access control scheme. The system uses local abnormal factors to judge non-safe data and eliminates abnormal data according to the judgment results. The system sorts and outputs the factors that may have abnormal data points in the current time window. The Java object-oriented programming language is used. The network attack will be divided into fuzzy measures of DoS attack and non-DoS attack, and finally, the results of various attacks will be displayed. Simulation results show that this paper's entire access control scheme is highly feasible. The proposed algorithm has a high recognition rate. © 2023 IEEE.

关键词： Access control

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Investigating the use of Neural Networks in Enhancing Music Composition and Sound Quality

Investigating the use of Neural Networks in Enhancing Music ...

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2024 International Conference on Advances in Computing Research on Science Engineering and technology, ACROSET 2024

作者： Gupta, Sachin Inzimam Manivasagam Sanskriti University Department of Management Mathura India Vivekananda Global University Department of Computer Science & Application Jaipur India Department of Computer Science and Information Technology Bangalore India

ISBN: (纸本)9798350388800

An exciting new area of study in the world of music technology is the use of neural networks to the improvement of sound quality and the automation of musical creation. The goal of this research is to evaluate the potential of neural networks in boosting musical creation and reception. To determine whether algorithms based on neural networks can help us create groundbreaking music, we do extensive research into the field. First, the study presents a recurrent neural network (RNN)-based approach to composing melodic sequences of notes. This method draws on the remarkable pattern-recognition skills of neural networks to motivate richer musical production. Listening to a big library of pieces, the RNN model is able to learn how to construct new pieces that are enjoyable to human hearing. Synthesizing high-quality audio waveforms is crucial in modern music composition, and this study investigates the use of Generative Adversarial Networks (GANs) to this problem. The AudioWaveGAN approach utilizes GANs to produce high-quality sound, filtering out unwanted noise while also composing immersive pieces. Our study compares the proposed method to various established rivals. The criteria for evaluation are based on genuine conventional methods. The findings illustrate the superiority of the suggested technique in terms of originality, sound quality, and a combined score, emphasizing its potential to change music creation and production. This study represents a major advance toward using neural networks in music creation and audio processing. The research shows that these fresh methods open up exciting opportunities for artists, composers, and music producers who want to release hitherto unattainable wellsprings of inspiration and provide their listeners with fully enveloping aural journeys. © 2024 IEEE.

关键词： Generative adversarial networks

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An empirical analysis of evolutionary computing approaches for IoT security assessment

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Journal of Intelligent and Fuzzy Systems 2025年第6期48卷 779-791页

作者： Kumar Sahu, Vinay Pandey, Dhirendra Singh, Priyanka Haque Ansari, Md Shamsul Khan, Asif Varish, Naushad Khan, Mohd Waris Department of Information Technology Babasaheb Bhim Rao Ambedkar University Uttar Pradesh Lucknow India CSE Department SRM University AP India Department of Computer Application Integral University Uttar Pradesh Lucknow India Telangana Hyderabad India Department of Computer Science Jamia Millia Islamia New Delhi India

The Internet of Things (IoT) strategy enables physical objects to easily produce, receive, and exchange data. IoT devices are getting more common in our daily lives, with diverse applications ranging from consumer sector to industrial and commercial systems. The rapid expansion and widespread use of IoT devices highlight the critical significance of solid and effective cybersecurity standards across the device development life cycle. Therefore, if vulnerability is exploited directly affects the IoT device and the applications. In this paper we investigated and assessed the various real-world critical IoT attacks/vulnerabilities that have affected IoT deployed in the commercial, industrial and consumer sectors since 2010. Subsequently, we evoke the vulnerabilities or type of attack, exploitation techniques, compromised security factors, intensity of vulnerability and impacts of the expounded real-world attacks/vulnerabilities. We first categorise how each attack affects information security parameters, and then we provide a taxonomy based on the security factors that are affected. Next, we perform a risk assessment of the security parameters that are encountered, using two well-known multi-criteria decision-making (MCDM) techniques namely Fuzzy-Analytic Hierarchy Process (F-AHP) and Fuzzy-Analytic Network Process (F-ANP) to determine the severity of severely impacted information security measures. © 2025 – The authors. Published by IOS Press.

关键词： Risk assessment

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Performance Juxtapose of Plant Leaf Disease Detection using Adaptive Deep Convolutional Recurrent Neural Network (ADCRNN) in MATLAB Versus Python

Performance Juxtapose of Plant Leaf Disease Detection using ...

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2024 International Conference on Intelligent Algorithms for Computational Intelligence Systems, IACIS 2024

作者： Jayashree, S. Sumalatha, V. Vels Institute of Science Technology & Advanced Studies Department of Information Technology Chennai India Vels Institute of Science Technology & Advanced Studies Department of Computer Application Chennai India

ISBN: (纸本)9798350360660

Leaf diseases can cause several detriments in crops' overall yield and fertility. While analyzing the various diseases that affect plants is imperative, identifying the diseases using algorithmic techniques that render optimal performance is crucial. In agriculture, detecting multiple diseases in plants is difficult. However, the provision to automate disease identification through machine learning approaches through the various phases of preprocessing and segmentation is implemented in this study. This indagation delineates the leaf disease identification using the proposed hybrid algorithmic Adaptive Deep Convolutional Recurrent Neural Network (ADCRNN) in bifurcated platforms such as MATLAB and Python. The Radial basis function is incorporated to optimize the throughput in MATLAB before observing the juxtaposed results in both platforms. The purpose of utilizing ADCRNN is to effectively combine the advantages and parallelly overcome the challenges of Deep Convolutional Neural Network (DCNN), RNN, and adaptive techniques that unsheathe the pivotal features from the provided input. The ADCRNN simulation is carried out in MATLAB and Python, and the results are successfully obtained. In addition, after optimization, the proposed ADCRNN technique's accuracy increased to 94.5% in performance evaluation in MATLAB. © 2024 IEEE.

关键词： MATLAB

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Multi-agent QoS-aware autonomic resource provisioning framework for elastic BPM in containerized multi-cloud environment

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Journal of Ambient Intelligence and Humanized Computing 2023年第9期14卷 12895-12920页

作者： Saif, Mufeed Ahmed Naji Niranjan, S.K. Murshed, Belal Abdullah Hezam Al-ariki, Hasib Daowd Esmail Abdulwahab, Hudhaifa Mohammed Department of Computer Applications Sri Jayachamarajendra College of Engineering VTU Mysore India Department of Studies in Computer Science University of Mysore Karnataka Mysore India Department of Computer Science College of Eng. &IT University of Amran Amran Yemen Department of Information Technology Faculty of Engineering and Information Technology Al-ata’a University for Science and Technology Taiz Yemen Department of Computer Networks Engineering and Technologies Sana’a Community College Sana’a Yemen Department of Computer Application Ramaiah Institute of Technology VTU Bangalore India

Cloud computing enables businesses to improve their market competitiveness, enabling instant and easy access to a pool of virtualized and distributed resources such as virtual machines (VM) and containers for executing their business operations efficiently. Though the cloud enables the deployment and management of business processes (BPs), it is challenging to deal with the enormous fluctuating resource demands and ensure smooth execution of business operations in containerized multi-cloud. Therefore, there is a need to ensure elastic provisioning of resources to tackle the over and under-provisioning problems and satisfy the objectives of cloud providers and end-users considering the quality of service (QoS) and service level agreement (SLA) constraints. In this article, an efficient multi-agent autonomic resource provisioning framework is proposed to ensure the effective execution of BPs in a containerized multi-cloud environment with guaranteed QoS. To improve the performance and ensure elastic resource provisioning, autonomic computing is utilized to monitor the resource usage and predict the future resource demands, then resources are scaled based on demand. Initially, the required resources for executing the incoming workloads are identified by clustering the workloads into CPU and I/O intensive, and the local agent achieves this with the help of an initialization algorithm and K-means clustering. Then, the analysis phase predicts the workload demand using the proposed enhanced deep stacked auto-encoder (EDSAE), further, the containers are scaled based on the prediction outcomes, finally, the multi-objective termite colony optimization (MOTCO) algorithm is used by the global agent to find suitable containers for executing the clustered workloads. The proposed framework has been implemented in the Container Cloudsim platform and evaluated using the business workload traces. The overall simulation results proved the effectiveness of the proposed approach compare

关键词： Quality of service

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