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Facemask detection ontology with GBML as meta classifier

AIP Conference Proceedings 2023年第1期2754卷

作者： B. J. D. Kalyani S. Neelima Kopparthi Praneeth Sai Kopparthi Bhanu Prashanth Associate Professor Department of Computer Science and Engineering Institute of Aeronautical Engineering Dundigal Hyderabad India 500043 Associate Professor Department of Computer Science and Engineering Priyadarshini Institute of Science and Technology for Women Khammam India 507002 Process Executive Wipro Limited Hyderabad India 500032 Vardhaman College of Engineering Hyderabad India 501218

World Health Organization (WHO) recommend usage of mask as an operative prevention to avoid spread of Covid 19. Various reports present that wearing face masks top virus transmission and reduces the risk of transmission. This paper focus on cloud-based AI methodology for the detection of face mask. A mask detection data base with two categories of information includes with mask and without mask images that are stored in cloud data Centre via webcam. The proposed work uses Full Convolution Neural Network (FCNN) and Gradient Boost Machine Learning (GBML) model for classification and detection mask. This paper focus on the objective of to recognize whether the person on image or video stream is wearing a mask or not and not wear properly.

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Effects of business intelligence tools on financial performance of it industry

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AIP Conference Proceedings 2024年第1期2971卷

作者： Yeluri S. D. S. Sri Vardhan U. M. Gopal Krishna I. Tejaswini K. Samuel Johnson Israel P. Prathyusha Assistant Professor Department of Computer Science and Engineering Sumathi Reddy Institute of Technology for women Ananthasagar Telangana VIT – AP School of Computer Science & Engineering VIT – AP University Andhra Pradesh India VIT – AP School of Business VIT – AP University Andhra Pradesh India Sumathi Reddy Institute of Technology for Women Warangal Telangana India

The goal of Business Intelligence is to look into, combine, and logically collect and analyse data from different customer information sources, the environment, competitors, and markets, etc., in order to judge how well businesses in the IT industry are doing. The goal of this study is to find out how Business Intelligence tools affect how well IT companies do financially. The method is a descriptive survey that can’t be used in real life. As part of the study, 420 IT experts from IT companies in Hyderabad were looked into as part of the statistical population. Also, confirmatory factor analysis was used to check the validity of the 25-item questionnaire, and validity analysis was used to gather data. The results showed that Business Intelligence had a big effect on the financial performance system of the organisation. Still, Business Intelligence made IT companies more innovative. Financial Forecasting and Financial Control System affect the financial performance system by 0.11 and 0.05 points, respectively. The Fund Management System affects the financial performance system by -0.07 points. The Financial Performance System is affected by the Internal Audit System by 0.05. The effects of Financial Forecasting, Financial Control System, and Internal Audit System on the organization’s financial performance system. Thus, it can be concluded that Structured Equation Modelling in IBM SPSS AMOS has been used to indirectly examine the impact of Business Intelligence tools on financial performance. Surprisingly, these three elements are required to improve financial performance.

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Minimal Cases for Computing the Generalized Relative Pose using Affine Correspondences

arXiv

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arXiv 2020年

作者： Guan, Banglei Zhao, Ji Barath, Daniel Fraundorfer, Friedrich College of Aerospace Science and Engineering National University of Defense Technology China Computer Vision and Geometry Group Department of Computer Science ETH Zürich Institute for Computer Graphics and Vision Graz University of Technology Austria Remote Sensing Technology Institute German Aerospace Center Germany

We propose three novel solvers for estimating the relative pose of a multi-camera system from affine correspondences (ACs). A new constraint is derived interpreting the relationship of ACs and the generalized camera model. Using the constraint, we demonstrate efficient solvers for two types of motions assumed. Considering that the cameras undergo planar motion, we propose a minimal solution using a single AC and a solver with two ACs to overcome the degenerate case. Also, we propose a minimal solution using two ACs with known vertical direction, e.g., from an IMU. Since the proposed methods require significantly fewer correspondences than state-of-the-art algorithms, they can be efficiently used within RANSAC for outlier removal and initial motion estimation. The solvers are tested both on synthetic data and on real-world scenes from the KITTI odometry benchmark. It is shown that the accuracy of the estimated poses is superior to the state-of-the-art techniques. Copyright © 2020, The Authors. All rights reserved.

关键词： Motion estimation

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Efficient MedSAMs: Segment Anything in Medical Images on Laptop

arXiv

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arXiv 2024年

作者： Ma, Jun Li, Feifei Kim, Sumin Asakereh, Reza Le, Bao-Hiep Nguyen-Vu, Dang-Khoa Pfefferle, Alexander Wei, Muxin Gao, Ruochen Lyu, Donghang Yang, Songxiao Purucker, Lennart Marinov, Zdravko Staring, Marius Lu, Haisheng Dao, Thuy Thanh Ye, Xincheng Li, Zhi Brugnara, Gianluca Vollmuth, Philipp Foltyn-Dumitru, Martha Cho, Jaeyoung Mahmutoglu, Mustafa Ahmed Bendszus, Martin Pflüger, Irada Rastogi, Aditya Ni, Dong Yang, Xin Zhou, Guang-Quan Wang, Kaini Heller, Nicholas Papanikolopoulos, Nikolaos Weight, Christopher Tong, Yubing Udupa, Jayaram K. Patrick, Cahill J. Wang, Yaqi Zhang, Yifan Contijoch, Francisco McVeigh, Elliot Ye, Xin He, Shucheng Haase, Robert Pinetz, Thomas Radbruch, Alexander Krause, Inga Kobler, Erich He, Jian Tang, Yucheng Yang, Haichun Huo, Yuankai Luo, Gongning Kushibar, Kaisar Amankulov, Jandos Toleshbayev, Dias Mukhamejan, Amangeldi Egger, Jan Pepe, Antonio Gsaxner, Christina Luijten, Gijs Fujita, Shohei Kikuchi, Tomohiro Wiestler, Benedikt Kirschke, Jan S. de la Rosa, Ezequiel Bolelli, Federico Lumetti, Luca Grana, Costantino Xie, Kunpeng Wu, Guomin Puladi, Behrus Martín-Isla, Carlos Lekadir, Karim Campello, Victor M. Shao, Wei Brisbane, Wayne Jiang, Hongxu Wei, Hao Yuan, Wu Li, Shuangle Zhou, Yuyin Wang, Bo AI Collaborative Centre University Health Network Department of Laboratory Medicine and Pathobiology University of Toronto Vector Institute Toronto Canada Peter Munk Cardiac Centre University Health Network Toronto Canada Toronto General Hospital Research Institute University Health Network Department of Computer Science University of Toronto University Health Network Vector Institute Toronto Canada University of Science Vietnam National University Ho Chi Minh City Viet Nam Institute of Computer Science University of Freiburg Freiburg Germany School of Medicine and Health Harbin Institute of Technology Harbin China Division of Image Processing Department of Radiology Leiden University Medical Center Leiden Netherlands Department of System and Control Engineering School of Engineering Institute of Science Tokyo Formerly Tokyo Institute of Technology Tokyo Japan Institute for Anthropomatics and Robotics Karlsruhe Institute of Technology Karlsruhe Germany School of Information and Communication Engineering University of Electronic Science and Technology of China Chengdu China School of Electrical Engineering and Computer Science University of Queensland Brisbane Australia School of Cyberspace Hangzhou Dianzi University Hangzhou China Division for Computational Radiology and Clinical AI The Department of Neuroradiology University Hospital Bonn Germany Division for Computational Radiology and Clinical AI The Department of Neuroradiology University Hospital Bonn Germany Department of Neuroradiology Heidelberg University Hospital Heidelberg Germany Division for Computational Radiology and Clinical AI Department of Neuroradiology University Hospital Bonn Germany School of Biomedical Engineering Shenzhen University Shenzhen China School of Biological Science and Medical Engineering Southeast University Nanjing China Department of Urology Cleveland Clinic Cleveland United States Department of Computer Science University of Minnesota Minneapolis United St

Promptable segmentation foundation models have emerged as a transformative approach to addressing the diverse needs in medical images, but most existing models require expensive computing, posing a big barrier to their adoption in clinical practice. In this work, we organized the first international competition dedicated to promptable medical image segmentation, featuring a large-scale dataset spanning nine common imaging modalities from over 20 different institutions. The top teams developed lightweight segmentation foundation models and implemented an efficient inference pipeline that substantially reduced computational requirements while maintaining state-of-the-art segmentation accuracy. Moreover, the post-challenge phase advanced the algorithms through the design of performance booster and reproducibility tasks, resulting in improved algorithms and validated reproducibility of the winning solution. Furthermore, the best-performing algorithms have been incorporated into the open-source software with a user-friendly interface to facilitate clinical adoption. The data and code are publicly available to foster the further development of medical image segmentation foundation models and pave the way for impactful real-world applications. © 2024, CC BY-NC-SA.

关键词： Open source software

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Optimizing Hindi Paragraph Summarization through PageRank Method

Optimizing Hindi Paragraph Summarization through PageRank Me...

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International Conference on Edge Computing and Applications (ICECAA)

作者： Sheshang Degadwala Dhairya Vyas Khush Nilaykumar Patel Mukesh Soni Pavitar Parkash Singh Ramya Maranan Associate Professor & Head of Computer Engineering Department Sigma University Vadodara Gujarat India The Maharaja Sayajirao University of Baroda Vadodara Gujarat India Charotar University of Science and Technology Anand Gujarat Department of CSE University Centre for Research & Development Chandigarh University Mohali Punjab India Lovely Professional University Department of Research and Innovation Saveetha School of Engineering SIMATS Chennai Tamil Nadu India

This research paper presents a novel approach to optimize Hindi paragraph summarization using the PageRank method. With the increasing volume of Hindi language content on the internet, there is a growing need for effective summarization techniques tailored specifically for Hindi text. The proposed method leverages the inherent structure and connectivity of Hindi paragraphs to extract the most important sentences for summarization. The PageRank algorithm is applied to construct a rank representation of the text, with sentences as nodes and their co-occurrence patterns as edges. By calculating PageRank scores iteratively, the algorithm identifies the most central and significant sentences in the paragraph. Linguistic features such as sentence length, position, and content relevance are incorporated to enhance the quality of the summaries. Additionally, the algorithm dynamically adjusts sentence importance based on their relations with other sentences rank. Experimental results on a comprehensive dataset demonstrate that the PageRank-based approach outperforms existing summarization techniques in terms of informativeness and coherence, as evidenced by higher similarity score. The proposed method offers an effective solution for optimizing Hindi paragraph summarization, facilitating the management and comprehension of Hindi text in various applications.

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The Terms Estimation of S Robotics using MTRS as well as FEM

The Terms Estimation of S Robotics using MTRS as well as FEM

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Advance Computing and Innovative Technologies in Engineering (ICACITE), International Conference on

作者： R. Gopal Mustafa Mudhafar Amjad Hashem Venkadeshan Ramalingam Dibyahash Bordoloi Muhammad Numan Ali Khan Myasar Mundher Adnan Zahraa N. Abdulhussain Assistant Professor Information and communication Engineering College of Engineering University of Buraimi Sultanate of Oman Department of Medical Physics Faculty of Medical Applied Sciences University of Kerbala Karbala Iraq Computer Engineer Department Al-kunooze University College Basra Iraq Network Computing College of Computing and Information Sciences University of Technology and Applied Sciences– Shinas Sultanate of Oman Dept of CSE Graphic Era Hill University Adjunct professor Graphic Era Deemed to be University Dehradun Uttarakhand Faculty – Network Computing College of Computing and Information Sciences University of Technology and Applied Sciences – Shinas Sultanate of Oman Department of computers Techniques engineering College of technical engineering The Islamic university Najaf Iraq College of Technical Engineering National University of Science and TechnologyDhi Qar Iraq

ISBN: (数字)9798350360165

ISBN: (纸本)9798350360172

This look at addresses the critical project of reaching dependable and precise proprioception in soft robots, it really is essential for his or her effective deployment in complicated environments. By integrating multi-tap resistive sensors in the robot’s form, our technique lets in for the distinct sensing of nearby deformations at various factors throughout the robotics’ frame, moving beyond traditional techniques that anticipate steady curvature. We beautify the decision of these deformations and couple the sensory facts with a strong finite detail technique (FEM) model. This included framework allows the correct estimation of the smooth robot’s form and the significance of outside forces applied to it, attaining a mean relative inaccuracy of about 4%. Additionally, our technique proves its software program in tender manipulation structures, in which it achieves thirteen% relative mistakes in external force estimation inside diverse zero to five N. The approach gives a promising direction for enhancing robotic interactions in sensitive and dynamic responsibilities, providing massive enhancements in robotic proprioception without reliance on outdoor monitoring generation.

关键词： Deformable models Deformation Force Estimation Soft robotics Robot sensing systems Software

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Effect of geometric heterogeneity using an auxiliary device on the accuracy of complete arch implant scanning: An in vitro study of different clinical simulations

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Journal of Prosthetic Dentistry 2023年

作者： Abdelrehim, Aly Sulaiman, Eshamsul Sofian, Hazrina Salleh, Nosizana Mohd Graduate student Department of Restorative Dentistry Faculty of Dentistry Universiti Malaya (UM) Kuala Lumpur Malaysia Associate Professor Department of Restorative Dentistry Faculty of Dentistry Universiti Malaya (UM) Kuala Lumpur Malaysia Senior Lecturer Department of Software Engineering Faculty of Computer Science & Information Technology Universiti Malaya (UM) Kuala Lumpur Malaysia

Statement of problem: Intraoral scanning of implants supporting complete arch prostheses is limited because of the lack of geometric heterogeneity and unique reference points, creating inherent errors in the image stitching process by the scanner software program. Purpose: The purpose of this in vitro study was to evaluate the significance of geometric heterogeneity on complete arch implant scanning by using a novel auxiliary geometric device. Three different clinical simulations were tested to assess its significance. The study also assessed whether scans produced using the auxiliary device would meet a clinically acceptable threshold. Material and methods: A total of 60 scans (n=20) were performed using an intraoral scanner in 3 different clinical simulations: 2 parallel implants, 4 parallel implants, and 4 implants with a 30-degree posterior angulation of the distal implants. Scanning alternated between using the auxiliary geometric scanning device (test groups;4IP+, 4IA+, 2IP+) and not using the device (control groups;4IP-, 4IA-, 2IP-). A reference scan for each model was prepared from a high precision laboratory scanner. The scans were analyzed for accuracy in 3-dimensional deviation, interimplant distance deviation, and angular deviation by using an inspection software program. The effect of the auxiliary device was statistically analyzed by comparing scans of the same group using the paired t test for normally distributed data and the Wilcoxon Signed Rank test when data were not normally distributed (α=.05). Results: Significant effects of the auxiliary geometric device were found in 3-dimensional, distance and angular deviations (P<.05). Scans performed using the device were significantly more accurate in most implant positions (P<.05). Linear and angular deviations were clinically acceptable for all test groups. However, the deviations were above the clinically acceptable threshold for the control groups. Conclusions: Using an auxiliary geometric device sig

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Cosine series quantum sampling method with applications in signal and image processing

arXiv

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arXiv 2020年

作者： Wereszczyński, Kamil Michalczuk, Agnieszka Pęszor, Damian Paszkuta, Marcin Cyran, Krzysztof Polański, Andrzej Department of Graphics Computer Vision and Digital Systems Faculty of Automatic Control Electronics Poland Computer Science Silesian University of Technology Akademicka 16 Gliwice44-100 Poland

A novel family of Cosine series Quantum Sampling (QCoSamp) operators appropriate for quantum computing is described. The development of quantum algorithms, analogous to classical algorithms, we apply to the harmonic analysis of signals. We show quantum sampling through measurements of a quantum system, and after operators of the family are applied, allow for input signal mapping with a Fourier series representation. Technical methodologies employed, facilitating the implementation of each QCoSamp algorithm to a quantum computer and application to the field of signal and image processing we also *** Codes 94-02 © 2020, CC-BY-NC-ND.

关键词： Quantum optics

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Performance evaluations of a cloud computing physical machine with task reneging and task resubmission (feedback) 27th

Performance evaluations of a cloud computing physical machin...

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27th International Conference on computer Networks, CN 2020

作者： Kuaban, Godlove Suila Soodan, Bhavneet Singh Kumar, Rakesh Czekalski, Piotr Institute of Theoretical and Applied Informatics Polish Academy of Sciences Baltycka 5 Gliwice44-100 Poland School of Mathematics Shri Mata Vaishno Devi University KatraJammu and Kashmir182320 India Department of Computer Graphics Vision and Digital Systems Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Akademicka 16 Gliwice44-100 Poland

ISBN: (纸本)9783030507183

Cloud service providers (CSP) provide on-demand cloud computing services, reduces the cost of setting-up and scaling-up IT infrastructure and services, and stimulates shorter establishment times for start-ups that offer or use cloud-based services. Task reneging or dropping sometimes occur when a task waits in the queue longer than its timeout or execution deadline, or it is compromised and must be dropped from the queue or as an active queue management strategy to avoid tail dropping of tasks when the queues are full. Reneged or dropped tasks could be resubmitted provided they were not dropped due to security reasons. In this paper, we present a simple M/M/c/N queueing model of a cloud computing physical machine, where the interarrival times and the services times are exponentially distributed, with N buffer size and c virtual machines running in parallel. We present numerical examples to illustrate the effect of task reneging and task resubmission on the queueing delay, probability of task rejection, and the probability of immediate service. © Springer Nature Switzerland AG 2020.

关键词： Cloud computing

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Construction of practical teaching system for integration of specialism and innovation based on virtual simulation technology 29th

Construction of practical teaching system for integration of...

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29th National Conference on computer science technology and Education, NCCSTE 2019

作者： Wang, Yangping Dang, Jianwu Yong, Jiu Wang, Wenrun Yue, Biao School of Electronic and Information Engineering Lanzhou Jiaotong University Lanzhou China National Computer Science and Technology Experimental Teaching Demonstration Center Lanzhou Jiaotong University Lanzhou China Gansu Provincial Engineering Research Center for Artificial Intelligence and Graphics and Image Processing Lanzhou China

ISBN: (纸本)9789811553899

The practical teaching for the majors of rail transit in colleges and universities involves a large number of high-cost, high-consumption, large-scale or comprehensive training. It will often encounter high-risk or extreme environment, inaccessible or irreversible operation, which seriously affects the cultivation of students professional engineering ability. In this paper, a practical teaching system based on virtual simulation technology is constructed for rail transit specialty. The system integrates the professional advantages and practical platform in the university, develops virtual simulation experimental teaching resources and practical teaching cases, and enables students to carry out "independent, cooperative and inquiry" learning in an open, safe, realistic and interactive virtual environment. This system will enhance students professional engineering practice ability and innovation ability, promote the training level of rail transit professionals and the overall quality of students. And for students, it can achieve the goal of strengthening the basic principles of curriculum, training design and research thinking, and enhancing innovation and entrepreneurship ability. © Springer Nature Singapore Pte Ltd. 2020.

关键词： Students

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