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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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High Throughput and Energy Efficient SHA-2 ASIC Design for Continuous Integrity Checking Applications

High Throughput and Energy Efficient SHA-2 ASIC Design for C...

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IEEE European Test Symposium (ETS)

作者： Asimina Koutra Vasileios Tenentes Dept. of Computer Science and Engineering University of Ioannina Greece

High throughput and energy efficient integrated cryptographic hash primitives are important for the continuous integrity checking and tampering detection in secure access management mechanisms of on-chip instrumentation, such as the IJTAG. However, previous SHA-256 cores focus only on throughput. In this paper, we synthesize with a 32 nm CMOS Technology SHA-256 cores that can be integrated in ASICs, and we present insights on their achieved throughput and energy efficiency. Moreover, we present a novel clock-gated design for reducing dynamic power dissipation of SHA-256 cores; and a novel Multi-Vt design for reducing static power dissipation of SHA-256 cores. The proposed designs can achieve upto 25.9% improvement of the energy efficiency of existing SHA-256 designs, without impacting their performed throughput. To the best of our knowledge, this is the first work that applies low power design techniques on SHA-256 cores.

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Predicting Grid-Level Urban Population Dynamics Based on POI and Road Networks: A Random Forest Approach and SHAP Evaluation 24

Predicting Grid-Level Urban Population Dynamics Based on POI...

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24th COTA International Conference of Transportation Professionals: Resilient, Intelligent, Connected, and Lowcarbon Multimodal Transportation, CICTP 2024

作者： Yao, Yao Jiang, Yinghong Li, Jiaxing Xu, Jian Yu, Qing Zhang, Haoran Co. Ltd. Shanghai China School of Urban Planning and Design Peking Univ. Shenzhen Graduate School Shenzhen China Dept. of Computer Science and Engineering Southern Univ. of Science and Technology Shenzhen China

ISBN: (数字)9780784485484

ISBN: (纸本)9780784485484

Predicting urban population dynamics encounters challenges like intricate spatiotemporal variations, privacy concerns tied to user data, and a lack of model interpretability, all impeding sustainable urban development. To address these issues, this paper introduces a method for hourly urban population prediction based on Points of Interest (POI) and road network data. By modeling POIs and road networks, the approach reconstructs grid-level counts of accessible POIs across different time intervals. These features are key inputs for a Random Forest algorithm, demonstrating high precision and consistent stability in forecasting population dynamics at an hourly level. Additionally, SHAP analysis assesses the spatiotemporal significance of different POI types and their accessibility concerning the prediction model. Results highlight the substantial influence of office spaces, residential areas, and shopping facilities on the population prediction model, with local POIs and those accessible within a 60-min radius making noteworthy contributions. This research establishes a foundation for urban population forecasting, providing valuable insights for traffic planning, management, and future urban development strategies. © ASCE.

关键词： Prediction models

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REAL-WORLD ATMOSPHERIC TURBULENCE CORRECTION VIA DOMAIN ADAPTATION

arXiv

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arXiv 2024年

作者： Wang, Xijun López-Tapia, Santiago Katsaggelos, Aggelos K. Dept. of Computer Science Northwestern University EvanstonIL United States Dept. of Electrical and Computer Engineering Northwestern University EvanstonIL United States

Atmospheric turbulence, a common phenomenon in daily life, is primarily caused by the uneven heating of the Earth’s surface. This phenomenon results in distorted and blurred acquired images or videos and can significantly impact downstream vision tasks, particularly those that rely on capturing clear, stable images or videos from outdoor environments, such as accurately detecting or recognizing objects. Therefore, people have proposed ways to simulate atmospheric turbulence and designed effective deep learning-based methods to remove the atmospheric turbulence effect. However, these synthesized turbulent images can not cover all the range of real-world turbulence effects. Though the models have achieved great performance for synthetic scenarios, there always exists a performance drop when applied to real-world cases. Moreover, reducing real-world turbulence is a more challenging task as there are no clean ground truth counterparts provided to the models during training. In this paper, we propose a real-world atmospheric turbulence mitigation model under a domain adaptation framework, which links the supervised simulated atmospheric turbulence correction with the unsupervised real-world atmospheric turbulence correction. We will show our proposed method enhances performance in real-world atmospheric turbulence scenarios, improving both image quality and downstream vision tasks. Copyright © 2024, The Authors. All rights reserved.

关键词： Atmospheric turbulence

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Energy Consumption for Cognitive Radio Network Enabled Multi-Access Edge Computing 3

Energy Consumption for Cognitive Radio Network Enabled Multi...

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3rd International Conference on Emerging Smart Technologies and Applications, eSmarTA 2023

作者： Elnaim, Areeg Ali Babeker, Amin Barakat, Mohammed Gaid, Abdulguddoos S.A. Saeed, Mamoon M. Ahmed, Zainab. E. Saeed, Rashid A. College of Engineering and Communication Alneelain University Khartoum Sudan School of Electronics Engineering Sudan University of Science and Technology Khartoum Sudan Taiz University Dept. of Communication & Computer Engineering Taiz Yemen Faculty of Engineering Department of Communications and Electronics Engineering Yemen Gezira University Department of Electrical and Computer Engineering Khartoum Sudan College of Computers and Information Technology Taif University Department of Computer Engineering Taif21944 Saudi Arabia

ISBN: (纸本)9798350305333

This article discusses optimizing energy Consumption in CRN-enabled Multi-access Edge Computing (MEC) systems, presenting a novel approach to optimize the energy Consumption of a cognitive radio network-enabled MEC system using iterative optimization techniques. The proposed model aims to minimize the system's energy consumption while maintaining its performance and quality of service requirements. The iterative optimization algorithm is used to find the optimal allocation of resources, such as computing, communication, and power, among different nodes in the MEC system. As a result, the cognitive radio network enables efficient spectrum utilization by dynamically allocating available spectrum to different users based on their requirements. The performance evaluation approach is evaluated through simulations, and the results show that it can significantly improve the energy consumption of the MEC system while maintaining its performance and QoS requirements. This article contributes to developing sustainable and energy-efficient communication systems for future wireless networks. © 2023 IEEE.

关键词： Cognitive radio

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Smart Mushroom Cultivation: Enhancing Growth Conditions through Sensor-Based Monitoring

Smart Mushroom Cultivation: Enhancing Growth Conditions thro...

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Advances in Computation, Communication and Information Technology (ICAICCIT), International Conference on

作者： Ishaan Rana Ankit Gupta Rakshit Mittal Harshita Chaudhary Shobha Tyagi Pronika Chawla Dept. of Computer Science and Engineering MRIIRS Faridabad India

Smart mushroom cultivation using remote sensing involves the integration of advanced technology to optimize the growth and productivity of mushrooms. Remote sensing techniques using arduino, sensors and cloud services are employed to monitor and manage various farming and growth related parameters in mushroom farms. Using the remote sensing of mushroom fields provides a macroscopic view of environmental conditions, helping farmers identify suitable locations for mushroom cultivation based on factors like temperature, humidity, and vegetation cover. Ground-based sensors are strategically placed within the cultivation area to measure crucial variables like temperature and humidity levels. These sensors transmit data to a central control system, allowing farmers to maintain optimal conditions for mushroom growth. Automated climate control systems can adjust parameters in response to real-time data, ensuring consistent and ideal growing conditions. This enables timely intervention, reducing crop loss and the need for chemical treatments. Furthermore, remote sensing can improve resource management. Precise water and nutrient monitoring based on sensor data can lead to more efficient resource utilization, reducing waste and operating costs. In summary, smart mushroom cultivation using remote sensing technology optimizes environmental monitoring, and resource usage. By harnessing the power of remote sensing, mushroom farmers can increase yields, reduce environmental impact, and enhance the overall sustainability and profitability of their operations.

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Vertical Validation: Evaluating Implicit Generative Models for Graphs on Thin Support Regions

arXiv

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arXiv 2024年

作者： Elkady, Mai Bui, Thu Ribeiro, Bruno Inouye, David I. Computer Science Dept. Purdue University West LafayetteIN United States Electrical and Computer Engineering Dept. Purdue University West LafayetteIN United States

There has been a growing excitement that implicit graph generative models could be used to design or discover new molecules for medicine or material design. Because these molecules have not been discovered, they naturally lie in unexplored or scarcely supported regions of the distribution of known molecules. However, prior evaluation methods for implicit graph generative models have focused on validating statistics computed from the thick support (e.g., mean and variance of a graph property). Therefore, there is a mismatch between the goal of generating novel graphs and the evaluation methods. To address this evaluation gap, we design a novel evaluation method called Vertical Validation (VV) that systematically creates thin support regions during the train-test splitting procedure and then reweights generated samples so that they can be compared to the held-out test data. This procedure can be seen as a generalization of the standard train-test procedure except that the splits are dependent on sample features. We demonstrate that our method can be used to perform model selection if performance on thin support regions is the desired goal. As a side benefit, we also show that our approach can better detect overfitting as exemplified by memorization. Copyright © 2024, The Authors. All rights reserved.

关键词： Generative adversarial networks

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Multi-Day Intermodal Travel Planning for Urban Cities Using Ising Machines

Multi-Day Intermodal Travel Planning for Urban Cities Using ...

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International Conference on Intelligent Transportation

作者： Siya Bao Nozomu Togawa Dept. of Computer Science and Communications Engineering Waseda University

The multi-day intermodal travel planning problem (MITPP) is an optimization problem (OP) and it generates the optimal sequences of point-of-interests (POIs) and hotels while searching for the most suitable transport modes between POIs and hotels. Conventional methods and solvers using von Neumann computers provide good approximate solutions to the OPs, but the computation time grows exponentially dealing with large-scale or complex OPs. Meanwhile, Ising machines or quantum annealing machines are non-von Neumann computers that are designed to solve complex OPs. In this paper, we focus on solving the MITPP by a two-phase Ising-based method. The first POI clustering phase aims at generating POIs clusters for sightseeing days and the second POI routing phase generates travel routes for each day with the optimal transport modes. Practical factors such as POI satisfaction, POI duration, hotel fee, and transportation fee are included in the MITPP. We map these elements onto quadratic unconstrained binary optimization (QUBO) models. For evaluation, we use a real-world dataset in Sapporo, Japan. Empirical results confirm that the proposed method can effectively solve the MITPP both in terms of solution quality and execution time and outperforms a conventional solver, a conventional method, and the latest Ising-based method.

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Perceptual Crack Detection for Rendered 3D Textured Meshes

arXiv

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arXiv 2024年

作者： Sarvestani, Armin Shafiee Zhou, Wei Wang, Zhou Dept. of Electrical & Computer Engineering University of Waterloo Canada School of Computer Science and Informatics Cardiff University United Kingdom

Recent years have witnessed many advancements in the applications of 3D textured meshes. As the demand continues to rise, evaluating the perceptual quality of this new type of media content becomes crucial for quality assurance and optimization purposes. Different from traditional image quality assessment, crack is an annoying artifact specific to rendered 3D meshes that severely affects their perceptual quality. In this work, we make one of the first attempts to propose a novel Perceptual Crack Detection (PCD) method for detecting and localizing crack artifacts in rendered meshes. Specifically, motivated by the characteristics of the human visual system (HVS), we adopt contrast and Laplacian measurement modules to characterize crack artifacts and differentiate them from other undesired artifacts. Extensive experiments on large-scale public datasets of 3D textured meshes demonstrate effectiveness and efficiency of the proposed PCD method in correct localization and detection of crack artifacts. Moreover, to quantify the performance of the proposed detection method and validate its effectiveness, we propose a simple yet effective weighting mechanism to incorporate the resulting crack map into classical quality assessment (QA) models, which creates significant performance improvement in predicting the perceptual image quality when tested on public datasets of static 3D textured meshes. A software release of the proposed method is publicly available at: https://***/arshafiee/crack-detection-VVM. © 2024, CC BY.

关键词： Quality assurance

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Demystifying the Applications of Internet of Medical Things (IoMT) for smart health care system

Demystifying the Applications of Internet of Medical Things ...

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Data, Information and Computing science (CDICS), International Conference on

作者： Ruqqaiya Begum Polisetty Swetha Koti Tejasvi M. A. Jabbar Dept. of Computer Science and Engineering Vardhaman College of Engineering Hyderabad India Dept. of Computer Science and Engineering(AI&ML) Vardhaman College of Engineering Hyderabad India

ISBN: (数字)9798350382778

ISBN: (纸本)9798350382785

As Internet of Things (IoT) devices become more commonplace and are used in more aspects of daily life, a bright future for people, data, and processes is emerging. Because of its potential to enhance patient care as well as its capacity to deliver more trustworthy clinical data, boost productivity, and save costs, In recent years, the Internet of Medical Things (IoMT) has a strategic goal for future e-healthcare. It is understandable why so many healthcare organization’s nowadays want to take advantage of what the IoMT has to offer. Its infrastructure includes interconnected medical equipment, software, and care systems and services. For everyone to understand how IoMT is enhancing the health care system with the aid of other technologies, we have described the implementation of IoMT in detail in this paper. Along with this, we have also discussed the different security concerns and difficulties the healthcare system is experiencing due to the IoMT’s information-gathering shortcomings.

关键词： Productivity Biomedical equipment Costs Smart healthcare Internet of Medical Things Software Security

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