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检索条件"机构=Dept. of Computer Engineering and Systems Science"

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Detecting Helmets Of The Bike Riders Using Deep Learning Algorithms

Detecting Helmets Of The Bike Riders Using Deep Learning Alg...

引用

International Conference on Computing and Networking Technology (ICCNT)

作者： Yousuf Mia Md. Solaimanur Rahman Animesh Basak Sheikh Mufrad Hossain Md. Sabab Zulfiker Merina Akter Sumaia Dept. of Computer Science & Engineering Daffodil International University Dhaka Bangladesh Dept. of Computer Science & Engineering Model Institute of Science & Technology Gazipur Bangladesh

We propose real-time bike helmet detection in our study. A lot of people ride bikes in our nation. Motorbikes are more popular than vehicles because they are cheaper to maintain, take up less parking space, and provide more mobility and adaptability in urban situations. Bike riding is entertaining yet risky. Bicyclist safety is the planned system's main purpose. Many drivers don't wear helmets even though they're mandated by law. In emerging countries, mortality has been growing steadily. A helmet detection technology that identifies drivers without helmets is needed to safeguard the public. We employ a real-time 3202 dataset for this approach. We gather wearing helmet 1911 and no helmet 1291 data and utilize algorithms like VGG16, Resnet50, MobileNet v.02, Inception V3, EfficientNet, and CNN. The EfficientNet achieved 98% accuracy. Each person's comparison statement techniques are in the implementation section. To construct the optimum model for the conditions, this inquiry uses model validation approaches.

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

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

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Intelligent Technologies (CONIT), International Conference on

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

ISBN: (数字)9798350349900

ISBN: (纸本)9798350349917

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.

关键词： Measurement NOMA 5G mobile communication Wireless networks Massive MIMO Signal processing Throughput

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Adaptive Strategies for Maximizing Spectral Efficiency in dual branch MRC systems Facing non-Uniform Fading Patterns

Adaptive Strategies for Maximizing Spectral Efficiency in du...

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Annual Information Technology, Electromechanical engineering and Microelectronics Conference (IEMECON)

作者： Deepak Upadhyay Kunj Bihari Sharma Mridul Gupta Rashmi Sharma Abhay Upadhyay Dept. of Computer Science and Engineering Graphic Era Hill University Dehradun India Dept. of Computer Science and Engineering Graphic Era Deemed to be University Dehradun India Dept. of Electronics and Communication Engineering Graphic Era Deemed to be University Dehradun India Dept. of Computer Science and Engineering Symbiosis Institute of Technology Nagpur Campus Symbiosis International Deemed University Pune India

ISBN: (数字)9798350387315

ISBN: (纸本)9798350387322

The presented research paper investigates the development and performance of adaptive strategies for non-uniform fading patterns in dual-branch Maximal Ratio Combining systems. The study employs key enabling strategies, including power control, adaptive modulation, and antenna selection, with the purpose of improving the spectral efficiency and reliability of wireless communication systems. Conducting simulations in MATLAB and Python, this paper presents a comprehensive analysis using heatmaps, 3D surface plots, and dynamic simulation outputs to show the effect of the strategies under different Signal-to-Noise Ratios and fading conditions. The outcomes, illustrated in a clear-cut manner in the visuals, reveal that the adaptive strategies lead to a drastic reduction in the Bit Error Rates and a more optimal distribution of power across the branches, ensuring highly effective performance even in the case of the most challenging non-uniform fading patterns. Ultimately, the research findings show sight into the necessity of adaptive strategies to ensure proper coverage and quality of communication in non-uniform fading conditions, which novel research could benefit from.

关键词： Fading channels Solid modeling Analytical models Adaptive systems Three-dimensional displays Spectral efficiency Power control Bit error rate Modulation Signal to noise ratio

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Developing xApps for Rogue Base Station Detection in SDR-Enabled O-RAN

Developing xApps for Rogue Base Station Detection in SDR-Ena...

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2023 IEEE INFOCOM Conference on computer Communications Workshops, INFOCOM WKSHPS 2023

作者： Huang, Jun-Hong Cheng, Shin-Ming Kaliski, Rafael Hung, Cheng-Feng National Taiwan University of Science and Technology Dept. of Computer Science and Information Engineering Taipei Taiwan Research Center for Information Technology Innovation Academia Sinica Taipei Taiwan National Sun Yat-sen University Dept. of Electrical Engineering Kaohsiung Taiwan

ISBN: (纸本)9781665494274

In order to support the diverse requirements of 5G communications, a multitude of RAN components are required. To enable multiple vendor support for 5G, each of whom can independently choose components, Open-RAN (O-RAN) defined a set of standards to which the components must adhere. In addition, O-RAN defines the management elements used to manage each component to secure the 5G networks. While the proposed architecture can manage both 4G and 5G environments, including 5G NSA (Non-Standalone), it inherently suffers from the same vulnerabilities found in 4G LTE. Consequently, an attacker can use unprotected signaling and a low-cost Software Defined Radio (SDR) to launch rogue base station (RBS) attacks on the user equipment (UE), even in O-RAN architectures. In this paper, we consider the stability of signals collected from high-quality operational BSs versus cheap RBSs. Using signal stability features, we develop a machine learning (ML) based RBS detector located on the UE. With the aid of an O-RAN xAPP, ML models can be retrained using the data collected from multiple UEs, and the updated model can be delivered to UEs to enable higher detection accuracy. We conduct extensive experiments by implementing an RBS using a USRP B210, enabling O-RAN using E- Release, and data collected from operational BSs. Moreover, the detector is implemented as an Android APP, which realizes the connection to the O-RAN xAPP. The experimental results show that our detector can achieve more than 99% accuracy, precision 'recall' and F1 score. © 2023 IEEE.

关键词： Base stations

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

Enhancing Network Function Virtualization and Service Functi...

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Pioneering Developments in computer science & Digital Technologies (IC2SDT), International Conference on

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

ISBN: (数字)9798350365016

ISBN: (纸本)9798350365023

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.

关键词： Measurement Technological innovation Costs Machine learning algorithms Heuristic algorithms Machine learning Throughput Network function virtualization Resource management Optimization

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An Optimized Grid Computing based Feature Selection approaches from Brain Image dataset using Pretrained models

An Optimized Grid Computing based Feature Selection approach...

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Advances in Signal Processing, Power, Communication, and Computing (ASPCC), IEEE International Conference on

作者： Sradhanjali Nayak Pradyut Kumar Biswal Pravakar Mishra Sateesh Kumar Pradhan Dept. of Computer Science NIIS Institute of Business Administration Bhubaneswar India Dept. of ETC IIIT Bhubaneswar Bhubaneswar India Dept. of Computer Science and Engineering NIIS Institute Of Business Administration Bhubaneswar India Dept. of Computer Science and Application Utkal University Bhubaneswar India

ISBN: (数字)9798350355093

ISBN: (纸本)9798350355109

The outcome of simulated experiments expressed the efficiency of grid-based algorithm in the domain of image processing in the context of Brain MRI Images for Tumor Detection. It provides a faster approach in detecting object and achieving higher rate of detection in comparison with existing algorithms for the similar purpose. The foremost goal of this work is improving the rate of detection by using grid based feature fusion approach with Genetic Algorithm(GA), Particle Swarm Optimization(PSO) and Scalp Swarm Optimization Algorithm. This technique produces efficient result due to hybrid fusion of gridded Images and optimization for exhaustive and precise image analysis. In the initial phase Each image is segmented into 4 grids. Pretrained models like Inception-V2, Resnet 50, Mobnetv2, VGG-16 are used to extract features before and after the images are gridded. The extracted features are analysed with classifiers such as Decision tree, Support vector Machine, Multiplayer and Self Attention Transformer that not only chooses the best set of features as well as best feature extractor. Among all these models the VGG-16 gives best result in terms of Accuracy, sensitivity, specificity and F-score. Hence VGG-16 is utilized as evaluation functions in the optimization Algorithms. The performance of the approach is measured by the values produced against the terms as precision, Recall, F-score, and accuracy rate. In the first phase of iteration, features extracted from each grid are assigned with initial weight. Optimization algorithms are used for optimizing the weight values in the combined features to bring best accuracy ratio. Grid based segmentation of Image stabilize the computation time thereby reduces the time complexity. Weighted sum Scalp Swarm Optimisation assigns best weighted values to segmentation parameters to get maximum performance. The experimental outcomes proves the efficiency of the proposed strategy.

关键词： Image segmentation Accuracy Scalp Signal processing algorithms Feature extraction Grid computing Transformers Particle swarm optimization Optimization Tumors

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Channel Capacity Enhancement in Dual Branch MRC under Extreme Fading Using Quantum Computing

Channel Capacity Enhancement in Dual Branch MRC under Extrem...

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IEEE Region 10 Symposium

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

ISBN: (数字)9798350364866

ISBN: (纸本)9798350364873

We have investigated the potential of channel capacity and signal integrity enhancement in dual branch MRC systems even under extreme fading through classical and quantum computing. We have used the classical algorithm to gauge the performance of the quantum algorithm, including QAOA and QEC. Our simulation results show that quantum-assisted MRC work optimally by providing superior SNR and BER. Quantum algorithms not only maximizes the effective channel capacity but also minimizes end-to-end system latency and number of error rate more efficiently. The addition of Quantum Machine Learning for the dynamic parameter setting in real-time has demonstrated that it may be possible to combat severe fading effects. To the best of our knowledge, this paper laid the cornerstone to explore more opportunities in implementing quantum-enabled techniques for advanced telecommunication system development to realize more robust and efficient technologies.

关键词： Fading channels Technological innovation Quantum algorithm Channel capacity Simulation Machine learning Real-time systems Telecommunications Signal integrity Signal to noise ratio

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

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

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Pioneering Developments in computer science & Digital Technologies (IC2SDT), International Conference on

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

ISBN: (数字)9798350365016

ISBN: (纸本)9798350365023

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.

关键词： System performance Focusing Minimization Load management Reliability Resource management Dynamical systems Distributed computing Optimization Edge computing

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Online Transit Entanglement Routing in Quantum Networks: Architecture Design and Optimization

Online Transit Entanglement Routing in Quantum Networks: Arc...

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IEEE Conference on Global Communications (GLOBECOM)

作者： Wan-Ting Ho Shing-Yan Fang Wei-Chia Hsieh Li-Feng Cheni Jian-Jhih Kuo Ming-Jer Tsai Dept. of Computer Science National Tsing Hua University Hsinchu Taiwan Dept. of Computer Science and Information Engineering National Chung Cheng University Chiayi Taiwan

ISBN: (数字)9798350351255

ISBN: (纸本)9798350351262

Quantum networks (QNs) gradually gain significant attention due to their higher security compared with classical networks. Conventional approaches in QN routing often aggregate multiple requests into a batch before determining their routing paths. However, this approach may overlook the limited lifetime of qubits, resulting in critical decoherence. In this paper, we present a new online entanglement routing architecture with an online optimization problem and propose a novel [1, O(log |V|)]-competitive algorithm supporting online requests with admission control, aiming to maximize the number of admitted requests. Finally, extensive simulation results show that our algorithm can outperform the existing approaches by up to 98%.

关键词： Simulation Data security Aggregates Qubit Decision making Focusing Routing Quantum networks Global communication Optimization

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Cyber Complaint Automation System

Cyber Complaint Automation System

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Advanced Computing and Communication Technologies for High Performance Applications

作者： Anand V Prabhu MJ Jefiya Joel Denny Joseph Tisa Sunny Cerene Mariam Abraham Computer Science and Engineering dept. of Artificial Intelligence and Data Science

Due to the Internet's quick spread and the digitali-sation of commercial activity, cybercrime has risen dramatically. computers or data are the intended victim of cybercrime. This paper is about “Cyber Complaint Automation System”. The current cyber cell of Kerala police has a time comsuming approach. Complaint can be given in two ways. A written complaint can be given to cyber police station. Second option is to use cyber crime reporting portal. In this portal user has to undergo four different steps to sucessfully register the complaint. These complaints are stored in a database and manually classified into respective departments. This methodology of a cyber complaint takes a great deal of effort and time. The time wasted on current system helps the criminal in covering his track. As a result, the victim's time and money are squandered, and police receive criticism. We are working to create a software that will drastically shorten the time it takes to handle a complaint in an effort to remedy this scenario. Our system automates the classification process and prioritize emergency complaints. Thus helps the police to apprehend the criminal faster.

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