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IEEE International Conference on Cloud Computing, CLOUD

作者： Namit Juneja Varun Chandola Jaroslaw Zola Olga Wodo Parth Desai Dept. of Computer Science and Engineering University at Buffalo USA Dept. of Materials Design and Innovation University at Buffalo USA

ISBN: (数字)9798350368536

ISBN: (纸本)9798350368543

We propose a resource-efficient Bayesian Optimization (BO) formulation that can provide the same convergence guarantees as traditional BO, while ensuring that the opti-mization makes efficient use of the available cloud or high-performance computing (HPC) resources. The paper is motivated by the fact that for many optimization problems that lend themselves well to BO, like hyper-parameter optimization for training large machine learning models, the single function evaluation cost depends on the model parameters as well as system parameters. The proposed Resource Efficient Bayesian Optimization (REBO) algorithm is a novel formulation that exploits this dependence and provides significant cost benefits for users who want to deploy BO on cloud and HPC resources that are characterized by availability of compute resources with varying costs and expected performance benefits. We demonstrate the effectiveness of REBO, in terms of convergence and resource-efficiency, on a variety of machine learning hyper-parameter optimization applications.

关键词： Training Cloud computing Costs Computational modeling Optimization methods Machine learning Bayes methods

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Technological Innovations in IoT-Based Smart Agriculture Systems for Sustainable Crop Management 4

Technological Innovations in IoT-Based Smart Agriculture Sys...

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4th International Conference on Technological Advancements in Computational Sciences, ICTACS 2024

作者： Padmapriya, S. Todmal, Ashok Veeraiah, Vivek Rajput, Bhawna Janghel Muthugurunathan, G. Rakshitha Dhanalakshmi Srinivasan University Dept. of Cse Tamil Nadu India Mit College of Management Mit Art Design and Technology University Maharashtra Pune India Sri Siddhartha Academy of Higher Education Dept. of Computer Science Karnataka India Rungta College of Engineering and Technology Dept. of Cse Chhattisgarh Bhilai India Madanapalle Institute of Technology & Science Dept. of Cse AP Madanapalle India Nmamit Dept. of Aiml Nitte India

ISBN: (纸本)9798350387490

Modern farming is now achievable because to the IoT, which has revolutionised agricultural management. investigates the most current IoT based smart agriculture system technologies in view of sustainable crop management. Combining IoT sensors with data analytics found in studies that precision farming, automated irrigation systems, real-time soil monitoring, coupled with resource optimisation may be accomplished. IoT technology might help farmers to better regulate their water, pest management, along with soil health, thus improving their yield with less impact on the environment. Exposing upcoming trends along with research opportunities investigates cost difficulties, system integration, data security. This paper provides understanding of how IoT technology is changing sustainable agriculture by way of a thorough review of present developments and case studies. © 2024 IEEE.

关键词： Smart agriculture

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Strategies for Data Security and Privacy Protection in Cloud Infrastructure

Strategies for Data Security and Privacy Protection in Cloud...

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Blockchain and Distributed Systems Security (ICBDS), IEEE International Conference on

作者： Namrata Naikwade Shafi Pathan Dept. of Computer Science & Engineering MIT Art Design and Technology University Pune India

ISBN: (数字)9798350354348

ISBN: (纸本)9798350354355

In today's rapidly growing digital era, cloud computing has emerged as an important technology, providing the ability to scale resources efficiently, accessibility, and cost-effectiveness for storing and processing huge amounts of data. However, alongside its numerous benefits, the adoption of cloud computing has also introduced deep concerns regarding data protection and privacy. The current scenario of cloud computing is characterized by increase in usage of cloud services and an exponential growth of data. While organizations leverage the cloud to enhance agility and innovation, the data sharing ability of cloud and the outsourcing of data management raise significant challenges for ensuring the privacy, integrity, and availability of sensitive data. Moreover, the rising cyber threats, regulatory compliance requirements, and the possibility for unauthorized access bring out the critical importance of robust data protection mechanisms in the cloud *** paper presents a comprehensive survey of strategies for data protection and identity protection in the context of cloud based systems. It examines encryption techniques, access control mechanisms, identity management solutions, among other approaches, highlighting their strengths, limitations, and applicability in different cloud deployment models and use cases. Furthermore, the paper discusses emerging trends such as homomorphic encryption, Attributes Based Encryption (ABE) Schemes and Identity Based Encryption (IBE), which hold promise for enhancing data protection in the developing landscape of cloud technology.

关键词： Surveys Access control Cloud computing Technological innovation Data security Data protection Encryption Protection Usability Secure storage

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Optimization of Imprecise Multiplier Circuits by using Binary Decision Diagram 9

Optimization of Imprecise Multiplier Circuits by using Binar...

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9th IEEE International Symposium on Smart Electronic Systems, iSES 2023

作者： Choudhary, Pooja Bhargava, Lava Vinod, G.U. Suhag, Ashok Kumar Fujita, Mashahiro Singh, Virendra Swami Keshvanand Institute of Technology Management and Gramothan Dept. of Electronics and Communication Engineering Jaipur India Malaviya National Institute of Technology Jaipur India Malaviya National Institute of Technology Dept. of Electronics and Communication Engineering Jaipur India Qualcomm Bangalore India Bml Munjal University Dept. of Electronics and Communication Engineering Haryana India Vlsi Design and Education Center University of Tokyo Japan Indian Institute of Technology Dept. of Electrical Engineering Dept. of Computer Science Engineering Bombay India

ISBN: (纸本)9798350383249

Imprecise multipliers are employed to enhance the efficiency and reduce the power consumption of arithmetic circuits while tolerating acceptable levels of inaccuracy in the outcomes. The multiplier circuit has a broader range of applications within embedded systems, particularly in the fields of digital signal processing, IoT and multimedia, etc. We proposed a systematic formal approach utilizing the Look-Up Table (LUT) employing the Burch method to evaluate the imprecise multiplier based on the Binary Decision Diagram (BDD) considering Worst Case Error constraint. Implemented 13 bit multiplier using normal and proposed imprecise multiplier shows 98% reduction in number of nodes. The proposed 25 bit imprecise multiplier based on Burch HL shows an 89% decrement in a number of nodes w.r.t. Burch LH method. BDD generation for imprecise multiplier is 75% faster than normal. © 2023 IEEE.

关键词： Timing circuits

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I See What You're Hearing: Facilitating The Effect of Environment on Perceived Emotion While Teleconferencing

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Proceedings of the ACM on Human-computer Interaction 2023年第1 CSCW期7卷 1-15页

作者： Marino, David Henry, Max Fortin, Pascal E. Bhayana, Rachit Cooperstock, Jeremy McGill University Center for Intelligent Machines MontrealQCH3A 0G4 Canada McGill University Dept. of Electrical and Computer Engineering MontrealQCH3A 0G4 Canada Indraprastha Institute of Information Technology Dept. of Human Centered Design New Delhi Delhi110020 India

Our perception of emotion is highly contextual. Changes in the environment can affect our narrative framing, and thus augment our emotional perception of interlocutors. User environments are typically heavily suppressed due to the technical limitations of commercial videoconferencing platforms. As a result, there is often a lack of contextual awareness while participating in a video call, and this affects how we perceive the emotions of conversants. We present a videoconferencing module that visualizes the user's aural environment to enhance awareness between interlocutors. The system visualizes environmental sound based on its semantic and acoustic properties. We found that our visualization system was about 50% effective at eliciting emotional perceptions in users that was similar to the response elicited by environmental sound it *** contributed system provides a unique approach to facilitate ambient awareness on an implicit emotional level in situations where multimodal environmental context is suppressed. © 2023 ACM.

关键词： Visualization

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Bridging the Modality Gap: Generative Adversarial Networks for T1-T2 MRI Image Translation

Bridging the Modality Gap: Generative Adversarial Networks f...

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International Conference on Computing and Networking Technology (ICCNT)

作者： Mayank Pandey Naga Sai Shreya Kunda Pranave Kc Tripty Singh Rekha R Nair Dept. of Computer Science and Engineering Amrita School of Computing Bengaluru Amrita Vishwa Vidyapeetham India Dept. of Computer Science and Engineering Alliance College of Engineering and Design Alliance University Bengaluru India

ISBN: (数字)9798350370249

ISBN: (纸本)9798350370270

CycleGAN, a significant deep learning model, has transformed medical imaging by providing a remedy for translating MRI images between different modalities. Its ability to transform T1-weighted to T2-weighted images is crucial in healthcare environments where obtaining multiple scans can be time-consuming and burdensome for patients. This can be achieved by utilizing CycleGAN, which generates images that contains vital information that will help the healthcare professionals to diagnose the patient without exposing them to further radiations. This unleashes an effective and safer way of diagnosing patients. The adaptability of CycleGAN also allows scalability and the ability to customize it for different types of medical images, where scanning can be achieved with less exposure to radiation, without loosing or compromising any important information.

关键词： Deep learning Magnetic resonance imaging Scalability Magnetic resonance Medical services Transforms Generative adversarial networks Medical diagnostic imaging

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A Social Referencing Disambiguation Framework for Domestic Service Robots

A Social Referencing Disambiguation Framework for Domestic S...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Kevin Fan Melanie Jouaiti Ali Noormohammadi-As Chrystopher L. Nehaniv Kerstin Dautenhahn Dept. of Electrical & Computer Engineering University of Waterloo ON Canada Dept. of Systems Design Engineering University of Waterloo ON Canada

The successful integration of domestic service robots into home environments can bring significant services and convenience to the general population and possibly mitigate important societal issues, such as care provision for older adults. However, home environments are complex, dynamic and object-rich. It is, thus, very probable that service robots will encounter ambiguity while interacting with household items. To enable service robots to be more adaptive, we proposed a learning so-cial referencing computational framework and experimentally evaluated the framework on a mobile manipulator robot, Fetch, in object selection scenarios. The framework allows the robot to (1) detect and analyze the ambiguity level based on the robot's view and user's command, (2) assess the human's attention level and attract their attention, (3) disambiguate references to objects using human feedback and (4) learn novel objects after clarification from the user. System evaluation results are presented. The framework is modular and can be applied to different robotic platforms.

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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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Futuristic Authentication: Development of an Artificial Intelligence based Enhanced Face Detection and Recognition System 7

Futuristic Authentication: Development of an Artificial Inte...

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7th International Conference on Inventive Computation Technologies, ICICT 2024

作者： Rama Satish, K.V. Jadhav, Dattatraya Arun Siva Prasad, M.V. Gopal Thatipudi, Jayendra Tejasri, V. Divya, J. Rnsit Dept of Ai Ml Bengaluru India Keystone School of Engineering Electronic And Telecommunication Department Pune India Anurag Engineering College Department of Cse Kodad India University of North Texas Dept. of Computer Science India S.R.K.R.Engineering College Department of It Chinaamiram Andhra Pradesh Bhimavaram India R.M.K.Enginnering College Dept of Computer Science And Design India

ISBN: (纸本)9798350359299

This research presents the design and implementation of an advanced Face Detection and Recognition System employing an Artificial Intelligence Assisted Face Recognition Model (AIFRM). The proposed system leverages the powerful Cascaded VGG16 architecture to enhance the accuracy of face detection and recognition tasks. The methodology involves a two-step approach, beginning with robust face detection using the cascaded VGG16 model. This is followed by feature extraction and recognition using the same architecture, resulting in a highly efficient and accurate facial recognition system. The cascaded VGG16 model is trained on diverse datasets to ensure adaptability to various scenarios and lighting conditions, enhancing the system's real-world applicability. The experimental results demonstrate the effectiveness of the proposed system in achieving state-of-the-art accuracy in face detection and recognition. The cascaded VGG16 model proves to be a formidable backbone for the AIFRM, contributing to the system's success in handling complex scenarios. The system's high accuracy, reaching 97%, positions it as a reliable solution for security, surveillance, and authentication applications in diverse environments. © 2024 IEEE.

关键词： Face recognition

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Development of a teaching model based on lifelong learning through active methodological strategies 12

Development of a teaching model based on lifelong learning t...

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12th International Conference on Virtual Campus, JICV 2022

作者： Trujillo-Aguilera, F D. Blazquez-Parra, E.B. Almendros, J. Calderon Marti-Campoy, A. Plaza-Garcia, I. University of Malaga Dept. Electronic Technology Malaga Spain University of Malaga Dept. Graphic Engineering Design and Projects Malaga Spain Polytechnic University of Valencia Dept. of Computer and Systems Informatics Valencia Spain University of Zaragoza Dept. of Electronic Engineering and Communications Zaragoza Spain

ISBN: (数字)9781665451062

ISBN: (纸本)9781665451062

Based on one of the fundamental principles of the educational model of the European Higher Education Area concerning the development of the capacity to achieve lifelong learning, this project has been developed in which a set of active teaching activities have been implemented for the acquisition of key competences in the challenge of achieving one of the most important goals that any educational system must provide: lifelong learning, thereby facilitating the incorporation of new university graduates into the world of work. This project has been implemented on the subject of Power Electronics. However, to facilitate the transfer to other subjects, the catalogue of active teaching activities is sufficiently varied to make it easy to extrapolate and use in other subjects, thanks to the fact that teachers have a wide variety of activities to choose from the set. Finally, a survey has been drawn to evaluate this new active methodology's satisfaction, impact and improvement to know the students' perspectives once they have worked with this catalogue of activities. © 2022 IEEE.

关键词： E-learning

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