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Optimizing Resource Allocation in 5G Networks Through Downlink and Uplink Decoupling

Optimizing Resource Allocation in 5G Networks Through Downli...

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International Conference on Ultra Modern Telecommunications and Workshops (ICUMT)

作者： Christos Bouras Charalampos Chatzigeorgiou Vasileios Kokkinos Apostolos Gkamas Philippos Pouyioutas Computer Engineering & Informatics Dept University of Patras Greece Computer Science Dept University Ecclisiastical Academy of Vella Greece Computer Science Dept University of Nicosia

This research paper sets out to explore the multi-faceted and complex topic of decoupling downlink and uplink in 5G networks, with a view to optimizing resource allocation. Drawing on an extensive range of current literature and industry trends, the authors conduct a comprehensive and in-depth analysis of the potential benefits and drawbacks of decoupling, taking into account the impact on network capacity, flexibility, and user experience. Additionally, the article offers valuable insights into the practical implementation of decoupling in real-world 5G networks, including an exploration of the challenges and considerations that may arise, and potential future developments in this field. Through a rigorous and meticulous examination of the topic, the authors aim to provide an understanding of the subject, offering valuable guidance and insights to future researchers and developers working in this area. With a focus on depth and detail, this paper represents a vital contribution to the ongoing dialogue surrounding decoupling in 5G networks and has the potential to drive significant advancements in the field in the years to come.

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Vitality Efficiency Info Gathering using Shortest Route in WSN's 13

Vitality Efficiency Info Gathering using Shortest Route in W...

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13th International Conference on Advances in Computing, Control, and Telecommunication Technologies, ACT 2022

作者： Krishna, Konda Hari Tapsi Babu, Y. Suresh Dept. of Computer Science & Engineering Lingaya's Vidyapeeth University Haryana Faridabad India A.P Tadepalligudem India P.G Dept of Computer Science JKC College Guntur India

ISBN: (纸本)9781713857938

A remote sensor system (WSN) is a remote system comprising of spatially dispersed self-sufficient gadgets utilizing sensors to screen physical or natural conditions. A WSN framework consolidates a portal that gives remote network back to the wired world and dispersed hubs. Vitality utilization and constrained battery life is the primary issue in remote correspondence particularly in remote sensor system. In this manner as of late vitality productivity is getting more consideration in remote sensor system. To enhance the battery life of sensor hubs we permit the sink to move in sensor system. For better sink versatility, the development example of the sink ought to be chosen, with the goal that sink can take after the way and accumulate the information all the more effectively additionally in less time. Sink Trail and Sink Trails, two vitality proficient proactive information reporting conventions are utilized to choose the most brief way for sink portability. © Grenze Scientific Society, 2022.

关键词： Electric batteries

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Motion Sickness Alleviation Based on a Mindfulness Brain-computer Interface 16

Motion Sickness Alleviation Based on a Mindfulness Brain-Com...

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16th International Conference on Advanced Computational Intelligence, ICACI 2024

作者： Zhu, Jiawei Bao, Xiaoyu Huang, Qiyun Wang, Tao Huang, Li Han, Yupeng Li, Kendi Chen, Di Xu, Kailin Wang, Zijian Jiang, Ya Li, Yuanqing Pazhou Laboratory Dept. Research Center for Brain-Computer Interface Guangzhou China Huizhou Desay SV Automotive Co. Ltd. Huizhou China South China University of Technology Dept. School of Automation Science and Engineering China Pazhou Laboratory Dept. Research Center for Brain-Computer Interface China South China Brain-Computer Interface Technology Co. Ltd. Guangzhou China

ISBN: (纸本)9798350308501

Motion sickness is a common affliction that affects nearly half of the global population and poses challenges to comfortable travel experiences, necessitating diverse intervention strategies. Pharmacological interventions have shown promise but present limitations due to side effects. To date, there is no non- pharmacological alleviation method for motion sickness that has been proven effective in a large population. In this study, we developed a novel mindfulness brain-computer interface (mindfulness BCI) for alleviation of motion sickness. Thirty-one subjects who were susceptible to motion sickness participated in our experiments in a real-world car motion environment. The experimental results demonstrated that the proposed mindfulness BCI can effectively alleviate motion sickness symptoms, where more than 90% of subjects reported the effectiveness of the mindfulness BCI system and a significant reduction of Motion Sickness Susceptibility Questionnaire (MISC) scores was obtained when comparing the BCI-based meditation state with the resting state for the subjects (t30=4.968, P © 2024 IEEE.

关键词： Brain computer interface

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Exploration of Ripe Raw and Defective Tomatoes with Deep Learning Techniques 2

Exploration of Ripe Raw and Defective Tomatoes with Deep Lea...

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2nd International Conference on Augmented Intelligence and Sustainable Systems, ICAISS 2023

作者： Vanitha, C.N. Sathyamoorthy, Malathy Dhanaraj, Rajesh Kumar Rai, Priti Geetha, V. Manikantan, M. Kongu Engineering College Science and Engineering Department of Computer Erode India Kpr Institute of Engineering and Technology Department of Information Technology Coimbatore India Pune India Gl Bajaj Institute of Management Greater Noida India Reva University School of Applied Sciences Department of Computer Science Bangalore India Kongu Engineering College Dept. of CT-UG Perundurai India

ISBN: (纸本)9798350325799

Due to great need of agricultural operations, there was a shortage of workers during the harvest period. This results in a bottleneck in the operations of agricultural organizations. One of the most common problems in these sectors is the hazardous practice of farming. This type of farming operation makes vegetables very costly and unattractive. The reduction of costs is controlled by the need for labour. This issue is solved by adapting to new technology and compensating the labour deficiency. The algorithms that are processed in this method are Convolutional Neural Network (CNN), Object Detection and Generative Adversarial Network (GAN). These algorithms will enable the model to recognise faulty tomatoes. This model accurately identifies raw, ripe and defective tomatoes using deep learning methods and it is highly helpful for the betterment of agriculture. © 2023 IEEE.

关键词： Object detection

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Image Degradation due to Interacting Hot Pixels and SEUs 37

Image Degradation due to Interacting Hot Pixels and SEUs

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37th IEEE International Symposium on Defect and Fault Tolerance in VLSI and Nanotechnology Systems, DFT 2024

作者： Chapman, Glenn H. Farahmandpour, Alireza Chakma, Amit Koren, Israel Koren, Zahava School of Engineering Science Simon Fraser University BurnabyBCV5A 1S6 Canada University of Massachusetts Dept. of Electrical and Computer Engineering AmherstMA01003 United States

ISBN: (纸本)9798350366884

Hot pixels (induced by cosmic rays) in digital imaging sensors accumulate with camera age, impacting the quality of all images produced by the camera. During its lifetime, the imager also experiences Single Event Upsets (SEU s) that create transient defects affecting a single image. The SEUs occur at a much higher rate (events/second) compared to 10-100s additional permanent hot pixels that occur per year. We explore in this paper how an SEU that occurs within a close proximity (within a 5×5 pixel area) of an existing Hot Pixel may distort the image. We also consider situations where an SEU impacts two or more adjacent pixels. When such events happen, the currently employed color demosaicing and JPEG image compression algorithms spread the damage into a 16×16 pixel area, creating significant color changes and resulting in noticeable image degradation. We use formulas developed for a two Hot Pixel interaction to estimate the probability of a Hot Pixel-SEU interaction, and predict its increase with camera age. © 2024 IEEE.

关键词： Cosmic rays

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Swarm Intelligence for Multi-Robot Coordination in Agricultural Automation 10

Swarm Intelligence for Multi-Robot Coordination in Agricultu...

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10th International Conference on Advanced Computing and Communication Systems, ICACCS 2024

作者： Abhang, L.B. Gummadi, Annapurna Changala, Ravindra Vuyyuru, Veera Ankalu Sabareesh, R. Raj, I. Infant Pravara Rural Engineering CollegeLoni under. Sppu University Automation and Robotics Dept Pune India Hyderabad India Guru Nanak Institutions Technical Campus Department of Information Technology Hyderabad India Koneru Lakshmaiah Education Foundation Department of Computer Science and Engineering Andhra Pradesh Vaddeswaram India Ecsotics Farm Foods Private Limited Bangalore India K.Ramakrishnan College of Engineering Department of Computer Science and Engineering Tamil Nadu Trichy India

ISBN: (纸本)9798350384369

The research investigates the optimization of multi-robot coordination in agricultural automation through Particle Swarm Optimization. The methodology unfolds in four key aspects: firstly, by harnessing swarm intelligence principles, the approach enhances coordination among multiple robots in agricultural settings, fostering collaboration and dynamic task allocation in response to real-time changes. Secondly, the integration of Particle Swarm Optimization (PSO) introduces a powerful optimization technique, enabling the algorithm to dynamically adapt the swarm's configuration. This adaptability optimizes task allocation and individual robot positions, enhancing overall efficiency. Thirdly, the methodology systematically tackles scalability, adaptability, and robustness challenges in agricultural automation. By synergizing swarm intelligence and PSO, it ensures efficient scalability with an increasing number of robots and responsiveness to evolving agricultural demands. The holistic design makes it well-suited for practical implementation in real-world agricultural scenarios. A series of experiments varying PSO parameters were conducted, revealing nuanced relationships between iterations, swarm size, and coefficients and their impact on convergence time and fitness metrics. The outcomes demonstrate the trade-offs involved in selecting these parameters for efficient coordination in agricultural tasks. A comparative analysis with ABO and ACO highlights PSO's superior performance, achieving remarkable fitness value of 98% in the context of robotic swarm applications. © 2024 IEEE.

关键词： Scalability

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Improving Existing VANETs by Incorporating UAVS Using Ant Colony and PSO Algorithms 4

Improving Existing VANETs by Incorporating UAVS Using Ant Co...

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4th IEEE International Conference on Data engineering and Communication Systems, ICDECS 2024

作者： Thangam, S. Dixit, Aniket Karn, Alok Kumar Thakur, Arnav Arunbalaji, Cg Jesy Janet Kumari, J. Saleem Raja, A. Amrita School of Computing Amrita Vishwa Vidyapeetham Dept. of Computer Science and Engineering Bengaluru India University of Technology and Applied Sciences-Shinas College of Computing and Information Sciences It Department Oman

ISBN: (纸本)9798350393354

Vehicular Ad Hoc Networks (VANETs) are a type of wireless communication network that enable vehicles to communicate with each other and with roadside infrastructure in a peer-to-peer fashion;despite their vast applications, they come with several shortcomings. The key challenges in their real-world implementation include scalability, connectivity, and coverage issues. Unmanned Aerial Vehicles (UAVs), also known as drones, can complement existing VANETs in several ways to enhance their functionality and address some of their limitations. This paper studies the incorporation of UAVs in VANETs to overcome the challenges faced by the present networks. The approach is based on the dynamic deployment of UAVs in the most optimal positions, found by utilizing Particle Swarm Optimization (PSO) and Ant Colony algorithms which analyze the vehicle density, and previous coverage information in the network. The deployment of UAVs is intended to provide a seamless network coverage for ground vehicles. The impact of dynamic UAV mobility in communicating VANETs is comparatively studied. The simulation is done using Network Simulator-3 (NS3) simulator to evaluate the performance of 4 VANET protocols, AODV, DSR, OLSR, and DSDV, in terms of packet delivery ratio (PDR), Average End-to-End Delay, Throughput, Average Throughput per Packet, Packet Drop Rate, and Normalized Routing Load after incorporating the proposed modification designs. The paper concludes that the incorporation of Ant Colony is better suited to enhance VANETs than PSO. © 2024 IEEE.

关键词： Vehicular ad hoc networks

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AdvAD: exploring non-parametric diffusion for imperceptible adversarial attacks 24

AdvAD: exploring non-parametric diffusion for imperceptible ...

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Proceedings of the 38th International Conference on Neural Information Processing Systems

作者： Jin Li Ziqiang He Anwei Luo Jian-Fang Hu Z. Jane Wang Xiangui Kang Guangdong Key Lab of Information Security School of Computer Science and Engineering Sun Yat-Sen University Electrical and Computer Engineering Dept University of British Columbia

ISBN: (纸本)9798331314385

Imperceptible adversarial attacks aim to fool DNNs by adding imperceptible perturbation to the input data. Previous methods typically improve the imperceptibility of attacks by integrating common attack paradigms with specifically designed perception-based losses or the capabilities of generative models. In this paper, we propose Adversarial Attacks in Diffusion (AdvAD), a novel modeling framework distinct from existing attack paradigms. AdvAD innovatively conceptualizes attacking as a non-parametric diffusion process by theoretically exploring basic modeling approach rather than using the denoising or generation abilities of regular diffusion models requiring neural networks. At each step, much subtler yet effective adversarial guidance is crafted using only the attacked model without any additional network, which gradually leads the end of diffusion process from the original image to a desired imperceptible adversarial example. Grounded in a solid theoretical foundation of the proposed non-parametric diffusion process, AdvAD achieves high attack efficacy and imperceptibility with intrinsically lower overall perturbation strength. Additionally, an enhanced version AdvAD-X is proposed to evaluate the extreme of our novel framework under an ideal scenario. Extensive experiments demonstrate the effectiveness of the proposed AdvAD and AdvAD-X. Compared with state-of-the-art imperceptible attacks, AdvAD achieves an average of 99.9% (+17.3%) ASR with 1.34 (-0.97) l2 distance, 49.74 (+4.76) PSNR and 0.9971 (+0.0043) SSIM against four prevalent DNNs with three different architectures on the ImageNet-compatible dataset. Code is available at https://***/XianguiKang/AdvAD.

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Adaptive Strategies for Scalable and Heterogeneous VANET Network 5

Adaptive Strategies for Scalable and Heterogeneous VANET Net...

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

作者： Thangam, S. Jha, Priyanshu Hawari, Jawed Sah, Nabin Kumar Jain, Nikunj Jesy Janet Kumari, J.J. Saleem Raja, A. Amrita School of Computing Amrita Vishwa Vidyapeetham Dept. of Computer Science and Engineering Bengaluru India College of Computing and Information Sciences University of Technology and Applied Sciences It Department Shinas Oman

ISBN: (纸本)9798350385649

Despite technological advancements, Vehicular Ad-hoc Networks (VANETs) continue to face challenges related to reliability and high-speed mobility. This study focuses on enhancing scalability, improving mobility, and addressing network heterogeneity in the context of data dissemination. Data dissemination involves the distribution or transmission of statistical data to users. Tools like NS3, SUMO utilizing OSM for realistic traffic simulations, MATLAB for Data Analysis and evaluation of various protocols like ADHOC, Dynamic Source Routing (DSR), Optimized Link State Routing Protocol (OLSR), Destination Sequenced Distance Vector Routing (DSDV). The research aimed to refine VANET simulations for effective decision making, as its primary objective data dissemination i.e. distribution or transmission of statistical data to users, forming the central focus of this investigation. © 2024 IEEE.

关键词： Vehicular ad hoc networks

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Optimizing Multi-Class Classification in Educational Data with Ensemble Learning and Data Balancing Techniques

Optimizing Multi-Class Classification in Educational Data wi...

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Intelligent Data science Technologies and Applications (IDSTA), International Conference on

作者： Mohammad F. Al-Hammouri Ziad Akram Ali Hammouri Islam T. Almalkawi Ansam Lafee Dept. of Computer Engineering The Hashemite University Zarqa Jordan Dept. of Computer Science Middle East University Amman Jordan

ISBN: (数字)9798350354751

ISBN: (纸本)9798350354768

The field of education is increasingly embracing AI tools to improve student outcomes. This work aims to reduce academic failure in higher education by employing machine learning techniques to identify at-risk students early in their educational journey, enabling the implementation of supportive strategies to assist them. This study examines a dataset from a higher education institution and utilizes it to develop a classification model for predicting students’ academic performance. The problem is formulated as a multi-class classification task with three categories: Graduate, Enrolled, and Dropout, with a significant imbalance skewed toward the Graduate. To improve prediction accuracy toward the minority class, the data balancing technique SMOTE with Edited Nearest Neighbor (SMOTE-ENN) is applied. Three popular classification models—Random Forest, XGBOOST and CatBoost—are employed. The findings show that SMOTE-ENN significantly improves classification results. Moreover, XGBOOST demonstrated the highest accuracy (94.6%) in correctly identifying all classes, as evidenced by the confusion matrix evaluation, achieving the highest results compared to previous work in the literature. Implementing these models allows for accurate predictions of students’ performance and helps reduce dropout rates.

关键词： Performance evaluation Accuracy Machine learning algorithms Education Forestry Predictive models Data science Prediction algorithms Data models Ensemble learning

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