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ResNet-50: The Deep Networks for Automated Breast Cancer Classification using MR Images 2

ResNet-50: The Deep Networks for Automated Breast Cancer Cla...

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2nd International Conference on Advancements in Smart, Secure and Intelligent Computing, ASSIC 2024

作者： Das, Tejaswini Nayak, Debasish Swapnesh Kumar Kar, Anindita Jena, Lambodar Swarnkar, Tripti University Dept. of Computer Application FET-ITER Bhubaneswar India University FET-ITER Dept. of Computer Science and Engineering Bhubaneswar India Bhubaneswar India

ISBN: (纸本)9798350370188

One in every four cancer cases in women is breast cancer, which is the most prevalent malignancy in this group globally. In 2020, breast cancer will account for one in every eight new instances of cancer, according to projections of 2.3 million new cases. Breast cancer identification, both early and accurate, is critical to improve patient outcomes and survival rates. Magnetic resonance imaging (MRI) has developed as a valuable method for diagnosing breast cancer. Deep learning algorithms, notably convolutional neural networks (CNNs), have demonstrated exceptional effectiveness in a variety of medical image processing applications, including breast cancer classification. The ResNet-50 architecture has received a lot of interest in this context because of its excellent performance in image recognition tasks. ResNet-50 is a deep residual network that introduces skip connections and residual learning to solve the difficulty of training very deep neural networks. A total number of 1480 cancer MRI samples are collected from the Kaggle database, having two classes, which include healthy and malignant scans. It is observed that our proposed model with the data pre-processing techniques has achieved a classification accuracy of 92.01%. © 2024 IEEE.

关键词： Magnetic resonance imaging

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A New Proposed Hybrid Page Replacement Algorithm (HPRA) in Real Time Systems. 5

A New Proposed Hybrid Page Replacement Algorithm (HPRA) in R...

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5th International Conference on Smart Systems and Inventive Technology, ICSSIT 2023

作者： Banerjee, Pallab Raj, Vivek Thakur, Kanika Kumar, Biresh Dehury, Mohan Kumar Amity University Jharkhand Dept. of Computer Science Engineering Ranchi India Amity University Jharkhand Dept. of Computer Science and It Ranchi India

ISBN: (纸本)9781665474672

Programming code is variable length. As code size grows larger than primary memory, virtual memory is a relevant concept. As the concept suggests, virtual memory allows to extend primary storage usage with storage devices such as hard *** a requested page is not located in memory (page fault) or a free accessible page is insufficient to meet the request, page replacement occurs. This is because there are none, or the number of free pages is less than the requested number. The operating system handles allocating memory frames to each program when the program is loaded into memory. In this work, the three existing page replacement algorithms (FIFO, LRU, and Optimal), along with a counter variable that keeps track of the frequency of pages are combined to create a Hybrid Page Replacement Algorithm in real time (HPRA). The HPRA was assessed by contrasting its performance in terms of the number of page faults produced with the industry-standard above-mentioned page replacement algorithm. © 2023 IEEE.

关键词： Real time systems

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Literature Review on Packet Sniffing: Essential for Cybersecurity & Network Security 5

Literature Review on Packet Sniffing: Essential for Cybersec...

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5th International Conference on Intelligent Communication Technologies and Virtual Mobile Networks, ICICV 2024

作者： Shaw, Ranju Parveen, Suraiya Jamia Hamdard University Dept. of Computer Science Engineering with Specialization in Cyber Forensic Information Security Delhi India Faculty at Jamia Hamdard University Sest Department of Computer Science Engineering Delhi India

ISBN: (纸本)9798350385649

In the realm of cybersecurity and network security, the significance of monitoring and analyzing network traffic cannot be overstated Network packet sniffing, a technique employed to capture and inspect data packets traversing a network, has emerged as an imperative tool for understanding network behavior, identifying vulnerabilities, and enhancing overall security. This study analyzes packet sniffing by exploring its role in modern cybersecurity practices. By analyzing packet sniffing mechanisms, including its methodologies and potential applications, this res earch sheds light on its effectiveness as a proactive security solution. Furthermore, the study examines the ethical considerations surrounding packet sniffing, addressing concerns related to user privacy and data protection. It also investigates the legal aspects that govern the use of packet sniffing techniques, ensuring compliance with regulations while maximizing its benefits. Through case studies and real-world examples, this research illustrates how packet sniffing can be leveraged to detect network anomalies, thwart malicious activities, and fortify network infrastructures. By presenting a comprehensive overview of packet sniffing's capabilities and limitations, this study equips cybersecurity practitioners with the knowledge needed to make informed decisions about its integration into their defensive strategies. © 2024 IEEE.

关键词： Cybersecurity

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A Close Look at Shared Resource Consumption in NoSQL Databases for Accurate Accounting 36

A Close Look at Shared Resource Consumption in NoSQL Databas...

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36th IEEE/IFIP Network Operations and Management Symposium, NOMS 2023

作者： Lee, Jaeryun Tak, Byungchul Seo, Euiseong Kyungpook National University School of Computer Science and Engineering Daegu Korea Republic of Sungkyunkwan University Dept. of Computer Science and Engineering Suwon Korea Republic of

ISBN: (纸本)9781665477161

A NoSQL database plays an essential role in all parts of today's multi-tenant large-scale IT services. Accurate information about per-tenant resource accounting is invaluable for optimal service management. However, there is a lack of study on the characteristics of resource consumption by multi-tenants in NoSQL database services, particularly for those resources consumed as part of activities asynchronously triggered by requests accumulated over time from multiple tenants. According to our investigation, this shared resource usage takes up a significant portion of total resource consumption in NoSQL *** assert that an accurate understanding of the shared resource consumption pattern is required to design correct and effective techniques for resource management. To this end, we conduct a detailed investigation of the shared resource consumption in popular NoSQL databases. Our focuses are to find out what portion of the overall resource consumption occurs in a shared manner, what type of operations cause them, and what effect the workload intensity has on the amount of shared resource consumption. We have developed a set of techniques for monitoring, recording, and analyzing the resource consumption data toward answering these questions. Our investigation revealed that the shared resource consumption can be as large as 30% of the total resource consumption, implying that resource accounting based only on directly causal events, may lead to underestimation of the true amount. We believe our study highlights the importance of shared resource accounting and provides crucial insights for building accurate resource accounting techniques. © 2023 IEEE.

关键词： Database systems

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A simplified hybrid model for state of charge estimation using 1-D Kalman filter and Coulomb counting 50

A simplified hybrid model for state of charge estimation usi...

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50th Annual Conference of the IEEE Industrial Electronics Society, IECON 2024

作者： Garg, Kritika Sarker, Rahul Ahmad, Aaqib Kaur, Mehakpreet Teja, A.V. Ravi Dept. of Electrical Engineering IIT Ropar Rupnagar India Dept. of Computer Science Engineering PU Patiala India

ISBN: (纸本)9781665464543

This document is a model with an accurate estimation of the battery’s State Of Charge (SOC), which is pivotal for prime performance and optimal lifespan of the rechargeable batteries. Though traditional methods, like Open Circuit Voltage (OCV) and Coulomb Counting (CC), are advantageous, they suffer from several limitations, such as sensitivity to temperature changes, frequent calibration, ageing effects, and measurement inaccuracies. This paper proposes 1-D Kalman Filter (1-D HKF) with an approach that incorporates the OCV and CC results into the state space model for better and more accurate SOC estimation. So, the model is called 1-D HKF or Hybrid Kalman filter that, influenced the long-term stability and estimation accuracy of CC and the accuracy of OCV at specific points to get over the individual limitations. The model trained by 1-D HKF adapts itself and adjusts the gain based on the uncertainties of each measured value to ensure optimal value information. So, We evaluate the performance of the 1-D HKF versus the traditional methods Kalman Filter using examples and exploratory data. The proposed approach illustrates significantly improved accuracy and robustness across various operating conditions, including varying temperatures and discharge rates. © 2024 IEEE.

关键词： State of charge

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End-to-End SNR Capacity and throughput enhancement Using Non-Orthogonal Multiple access and Massive MIMO in 5G 4

End-to-End SNR Capacity and throughput enhancement Using Non...

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4th International Conference on Intelligent Technologies, CONIT 2024

作者： Upadhyay, Deepak Upadhyay, Abhay Gupta, Mridul Sharma, Kunj Bihari Graphic Era Hill University Dept. of Computer Science and Engineering Dehradun India Graphic Era Deemed to Be University Dept. of Computer Science and Engineering Dehradun India Graphic Era Deemed to Be University Dept. of Electronics and Communication Engineering Dehradun India

ISBN: (纸本)9798350349900

This study provides a detailed analysis of the potential improvements in 5G network performance due to the adoption of NOMA and Massive MIMO technologies. Obtaining higher data rates, reduced latency, and increased overall network capacities remain a primary objective, and the research provides a comparison based on simulated data. Simulation models are designed to compare the proposed model against the conventional implementation of 5G networks based on a set of primary indicators, namely, throughput and latency. An abstract Wave Efficiency indicator is also presented to showcase a new metric for determining the qualitative improvements in signal processing and spectrum utilization. As the results of the research have demonstrated, the incorporation of NOMA and Massive MIMO increases overall network throughput while reducing latency. This demonstrates the potential contributions of these technologies to making wireless communications systems more efficient and reliable. The introduction of the Wave Efficiency is offered as a measurable variable for displaying the qualitative improvement in the wireless communications technologies, facilitating further implementation of NOMA and Massive MIMO in 5G networks. © 2024 IEEE.

关键词： 5G mobile communication systems

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Implementation of Pruned and Quantized Semantic Segmentation Neural Network Using Cambridge-Driving Labeled Video Database (CamVid) Dataset 2

Implementation of Pruned and Quantized Semantic Segmentation...

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2nd IEEE International Conference on Device Intelligence, Computing and Communication Technologies, DICCT 2024

作者： Upadhyay, Deepak Malhotra, Sonal Gupta, Mridul Mishra, Somesh Graphic Era Hill University Dept. of Computer Science and Engineering Dehradun India Graphic Era Deemed to Be University Dept. of Electronics and Communication Engineering Dehradun India Graphic Era Deemed to Be University Dept. of Computer Science and Engineering Dehradun India

ISBN: (纸本)9798350372847

In This research investigates the streamlined implementation of Semantic Segmentation Neural Networks through advanced techniques: pruning and quantization. Leveraging the CamVid dataset, our study achieved remarkable reductions in computational complexity and memory usage. Pruning removed redundant connections, effectively reducing learnable parameters, while quantization significantly minimized memory footprint. Despite these optimizations, the networks maintained high semantic segmentation accuracy. The implications of our findings are pivotal, particularly in resource-constrained applications like autonomous driving and image analysis. By enhancing efficiency without compromising accuracy, this research facilitates the seamless integration of deep learning models into real-time systems. Our study not only advances the field of computer vision but also underscores the practical feasibility of deploying sophisticated neural networks in practical, resource-efficient contexts. © 2024 IEEE.

关键词： Semantic Segmentation

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Performance Evaluation of Triple-Branch Diversity Receivers in Composite Gamma-Shadowed Rician Fading Channels with AMC and Asymmetric SNR Conditions 1

Performance Evaluation of Triple-Branch Diversity Receivers ...

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1st International Conference on Pioneering Developments in computer science and Digital Technologies, IC2SDT 2024

作者： Upadhyay, Deepak Upadhyay, Abhay Gupta, Mridul Sharma, Kunj Bihari Yadav, Devansh Graphic Era Hill University Dept. of Computer Science and Engineering Dehradun India Graphic Era deemed to be University Dept. of Computer Science and Engineering Dehradun India Graphic Era deemed to be University Dept. of Electronics and Communication Engineering Dehradun India

ISBN: (纸本)9798350365016

This paper provides an in-depth analysis of the performance enhancement resulting from AMC in triple-branch diversity receivers under composite Gamma shadowed Rician fading channels with uneven SNR conditions. This paper was able to show the level of enhancement in average SNR resulting through simulations of AMC on signal quality in several receiver branches, which clearly shows AMC's ability in alleviating fading and shadowing based degradations. The analysis revealed that AMC adequately alleviates degradations by changing modulation schemes and coding rates based on the current quality of the channel. This reinforces AMC's ability to improve the link's reliability and likelihood to optimize the efficiency of the communication channel. This makes AMC a desirable design and optimization feature for wireless communication in highly fading and shadowed environments, which makes this innovation a potential fundamental technology in the realization of robust, resilient, and adaptive communication systems. © 2024 IEEE.

关键词： Signal to noise ratio

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An Approach of Fog Computing and Edge Computing for Computing Resources Optimization Strategies 1

An Approach of Fog Computing and Edge Computing for Computin...

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1st International Conference on Pioneering Developments in computer science and Digital Technologies, IC2SDT 2024

ISBN: (纸本)9798350365016

This paper investigates optimization strategies for fog and edge computing systems, focusing on the key challenges of resource allocation, load balancing, latency minimization, and power efficiency. We analyze the results of the simulation study to determine the impact and potential of our strategies and find that the improvements achieved are small to moderate, varying between 1.75% and 2.95%. This knowledge demonstrates that system optimization requires small, gradual increments and that fog and edge computing are dynamic systems. Our results suggest that optimization based on integration and adaptability can produce a significant difference in the performance and reliability of distributed systems. © 2024 IEEE.

关键词： Fog computing

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Enhancing Network Function Virtualization and Service Function Chaining: Innovative Optimization Strategies and Their Impact 1

Enhancing Network Function Virtualization and Service Functi...

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1st International Conference on Pioneering Developments in computer science and Digital Technologies, IC2SDT 2024

作者： Upadhyay, Deepak Gupta, Mridul Sharma, Kunj Bihari Upadhyay, Abhay Graphic Era Hill University Dept. of Computer Science and Engineering Dehradun India Graphic Era deemed to be University Dept. of Electronics and Communication Engineering Dehradun India Graphic Era Deemed to be University Dept. of Computer Science and Engineering Dehradun India

ISBN: (纸本)9798350365016

Throughout this paper, the reader was able to better understand how innovative optimization techniques through NFV and SFC frameworks could and should be applied to address the developing and shifting focus of contemporary network infrastructures. Focusing on performance metrics performance via latency, throughput, resource utilization, and operational cost, the presented algorithms and machine learning models developed and executed due to this research showed innovative and dynamic optimization of network functions. Through further extensive simulations equalling 125 seconds, our findings reported creative results of improving performance in several significant areas: latency was reduced, throughput was enhanced, resource utilization was more efficient, and operational cost was reduced. These results indicated that our optimization strategies can pay off and bring a number of benefits to NFV and SFC that address a clear need for change in the current type of network management models. Therefore, this paper is valuable and serves as a testament of our strategies' power along with opening various doors for following network optimization research. Therefore, one can see how important it is to implement innovation in the face of change. © 2024 IEEE.

关键词： Network function virtualization

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