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Proceedings of the 5th International Conference on information Management & Machine Intelligence

作者： Sameer Sinha Sudhansu Shekhar Patra Bibhuti Bhusan Dash Manoj Ranjan Mishra Suchismita Rout Lalbihari Barik IT HCL Technologies India School of Computer Applications KIIT Deemed to be University India School of Computer Enginereing KIIT Deemed to be University India Department of Information Systems Faculty of Computing and Information Technology in Rabigh King Abdul Aziz University Kingdom of Saudi Arabia

ISBN: (纸本)9798400709418

Sensors and Internet of Things (IoT) devices are being used for more and more purposes every day. To handle the processing and storage requirements of time-sensitive applications, a new computing paradigm known as "Fog Computing" has arisen. It makes use of low-powered end devices that are connected to the IoT and include sensors. The fog nodes' virtual computers (VMs) handle the IoT workloads' instant processing and analysis. Efficiently scaling fog centres to fulfil the maximum amount of client requests that the fog system can fulfil is one of the open research challenges. The service providers want to maintain consumer demands in the fog system by providing efficient services. A multi-server queueing model with a retention plan is modeled in order to assess the fog system's various performance metrics.

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Improved harris hawks optimization algorithm based on collaborative quantization 6

Improved harris hawks optimization algorithm based on collab...

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6th International Conference on Mechatronics and Intelligent Robotics, ICMIR 2022

作者： Li, Yan Zhang, Xiang Qian, Qian Pan, Jiawen Feng, Yong Fu, Yunfa Faculty of Information Engineering and Automation Kunming University of Science and Technology Kunming Yunnan650500 China Yunnan Key Laboratory of Computer Technology Applications Kunming University of Science and Technology Kunming Yunnan650500 China Logistic Service Group Yunnan University Kunming Yunnan650500 China

ISBN: (纸本)9781510656635

Harris hawk optimization algorithm (HHO) is one of the population-based algorithms proposed by in *** has received great attention from researchers. However, HHO algorithm still has some problems, such as the exploitation ability is too large compared with the exploration ability, which leads to low optimization accuracy, slow convergence speed and so on. Therefore, the collaborative strategy and quantization strategy are introduced. With the support of the two strategies, the algorithm can avoid falling into local extremum in the early phase of iteration and improve its optimization accuracy at the late phase of iteration. Through the test of four representative functions, compared with the other three basic algorithms, the proposed algorithm greatly improves the optimization accuracy and convergence speed of the optimal solution, and the ability to find global extremum is greatly improved. © 2022 SPIE.

关键词： Optimization

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A CNN Based Approach to Classify the Folk Dances of Odisha

A CNN Based Approach to Classify the Folk Dances of Odisha

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2022 IEEE International Conference on Electronics, Computing and Communication Technologies, CONECCT 2022

作者： Samantaray, Swati Patra, Sudhansu Shekhar Mohanty, Amlan Barik, Lalbihari Barik, Akash Brahma, Aditya Narayan Kiit Deemed to Be University School of Humanities Bhubaneswar India Kiit Deemed to Be University School of Computer Applications Bhubaneswar India Iiit Department of Computer Science Bhubaneswar India King Abdulaziz University Faculty of Computing & Information Technology in Rabigh Department of Information Systems Saudi Arabia New Horizon College of Engineering Dept. of Computer Science Bengaluru India

ISBN: (数字)9781665497817

ISBN: (纸本)9781665497817

Folk dances are a primordial expression of ecstasy and bliss and serve as a mode of communication. They also facilitate in keeping the people connected to their traditions as well as ancestry. Furthermore, these dances help in preserving cultural unity and their tales can often reveal a lot about the periods these dances have developed through. Mahari, Gotipua and Odissi are such folk dance forms of the eastern state of Odisha. These folk dances are on the verge of extinction owing to the reducing number of practitioners, audience, absence of documentation, and digitalization. The absence of documentation has presented a barrier to the legitimacy of folk dance as an academic field of study. This research paper intends to focus on the classification of the folk dances of Odisha such as Mahari, Gotipua and Odissi which will help them to digitize and preserve. We propose deep learning-based methods for the classification and then it can be preserved. To validate the poses and hand motions, we offer a convolutional neural network model (CNN). © 2022 IEEE.

关键词： Neural network models

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Task Offloading Scheme for Latency Sensitive Tasks In 5G IOHT on Fog Assisted Cloud Computing Environment 3

Task Offloading Scheme for Latency Sensitive Tasks In 5G IOH...

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3rd International Conference for Emerging technology, INCET 2022

作者： Khan, Md. Tabrej Barik, Lalbihari Adholiya, Ashish Patra, Sudhansu Shekhar Brahma, Aditya Narayan Barik, Rabindra Kumar Pacific Academy of Higher Education and Research University Dept of Computer Science Udaipur India King Abdulaziz University Faculty of Computing & Information Technology in Rabigh Department of Information Systems Saudi Arabia Pacific Academy of Higher Education and Research University Udaipur India Kiit Deemed to Be University School of Computer Applications Bhubaneswar India

ISBN: (纸本)9781665494991

Fog computing is acquiring its popularity and adoption over the cloud computing because of its closeness to the 5G Internet of Health Things (IoHT) devices in the medical applications and also which provides services as cloud-like near to the edge-devices. The architecture and the latency of fog computing helps the mobile nodes and the 5G IoHT devices by delivering cloud-like computational and storage capabilities with a low latency and less bandwidth. Due to such additional behaviour fog computing is a technique for offloading applications' tasks running on the edge devices. Since the fog environment is dynamic in nature offloading the selection of the right fog nodes for offloading compute workloads are a challenging tasks and needs to be addressed. This paper proposes a task-offloading technique that considers QoS using modified sine-cosine optimization technique. The implemented algorithm is compared with PSO, BAT and GWA algorithm and finds that our modified sine-cosine algorithm works better as compared to the mentioned algorithms. © 2022 IEEE.

关键词： Fog computing

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System for Predicting Heart Disease using Sophisticated Machine Learning Techniques

System for Predicting Heart Disease using Sophisticated Mach...

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information Technologies and Communications (GCITC), Global Conference on

作者： Trilok Nath Pandey Bibhuti Bhusan Dash Lalbihari Barik Utpal Chandra De Abinash Tripathy Sudhansu Shekhar Patra School of Computer Science and Engineering Vellore Institute of Technology Chennai Tamil Nadu India School of Computer Applications KIIT Deemed to be University Bhubaneswar India Department of Information Systems Faculty of Computing and Information Technology in Rabigh King Abdul Aziz University Kingdom of Saudi Arabia School of Computer Applications KIIT Deemed to be University Bhubaneswar Odisha India

Cardiovascular illness stands as a significant global health issue, and timely identification of this condition holds paramount importance to ensure effective intervention. In this paper, we introduce a fused model for anticipating heart ailments. This amalgamation incorporates four distinct algorithms: LightGBM, XGBoost, Multilayer Perceptron, and AdaBoost. Through an assessment on the Cleveland dataset, AdaBoost emerged as the most accurate with a precision of 0.985. Subsequently, XGBoost followed closely with an accuracy of 0.980, succeeded by LightGBM at 0.956, and Multilayer Perceptron at 0.936. To harness the collective power of these models, we employed a weighted bagging technique that accords weights to predictions based on their individual accuracy rates. The resultant composite model attained an accuracy of 0.96. This outcome is slightly lower than the model with the highest accuracy, as it involves a weighted mean calculation across model predictions. This study indicates the potential utility of the proposed methodology in cardiac disease prediction, leveraging the ensemble approach to potentially outperform standalone models.

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Surface Electric Field Measurement of Composite Insulator Using an Optical Waveguide Sensor

SSRN

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SSRN 2023年

作者： Zhang, Jiahong Li, Weichang Shi, Jiali Faculty of Information Engineering and Automation Kunming University of Science and Technology Kunming650000 China Yunnan Key Laboratory of Computer Technology Applications Kunming University of Science and Technology Kunming650000 China

In this paper, an integrated optical waveguide sensor is designed and developed to comprehensively analyze the surface electric field distribution characteristics of composite insulators. Based on the optical waveguide electric field sensor, a measuring system for the surface axial and radial electric fields of composite insulators is built, and the axial and radial electric fields along the surface of composite insulator is measured under normal, damaged and internally defects. Based on the optical waveguide electric field sensor, an experimental system is setup for measuring the axial and radial electric fields along surface of composite insulators under normal, damaged and internally defective conditions. The experimental results showed that when a 10 kV power frequency voltage is connected, the radial and axial electric fields at the low and high voltage ends of the normal insulator are 21.53 kV/m, 53.07 kV/m and 47.55 kV/m, 105.12 kV/m respectively. When the insulator surface is damaged, the radial and axial electric field intensities at the damaged locations increased by 37.59%-204.85% and 12.89%-32.69%, respectively. When an internal defect occurred, the radial and axial electric field along the defect area increased by 18% and decreased by 127.72%, respectively. The radial electric field is more affected by the defect. The comparison with the calculated results shows that the integrated optical waveguide electric field sensor has great potential capability to be used for measuring the surface electric field of insulators. © 2023, The Authors. All rights reserved.

关键词： Electric fields

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Impact of Massive Tourist and Vehicles Flow on Air and Water Quality of Uttarakhand

Impact of Massive Tourist and Vehicles Flow on Air and Water...

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International Conference on Cyber and IT Service Management (CITSM)

作者： Bhupesh Rawat Ankur Singh Bist Hardjanto Nusantoro Muhammad Dede Soleman Po Abas Sunarya Iqbal Desam Girinzio Faculty of Computer Applications Graphic Era Hill University Uttarakhand India Faculty of Computer Science and Engineering Graphic Era Hill University Uttarakhand India Master of Information Technology University of Raharja Tangerang Indonesia Faculty of Science and Technology University of Raharja Tangerang Indonesia

The degradation of air quality in hilly regions due to the influx of tourists and vehicular traffic is a significant global concern. This research focuses on assessing the impact of these factors specifically in the Uttarakhand region. While various other factors contribute to the problem, our study aims to quantify the proportion of these two inputs. To achieve this, we employ data collection methods and develop innovative deep learning techniques tailored to the issue. The novelty of our work lies in the application of these novel methods to address the problem at hand. By conducting this study, researchers have gained insights into the extent of the impact and its implications for the region. The findings of our research contribute to the existing body of knowledge and provide valuable information for policymakers, environmentalists, and stakeholders involved in addressing air quality concerns in hilly regions.

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Uncertainty Estimation for Trust Attribution to Speed-of-Sound Reconstruction with Variational Networks

arXiv

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arXiv 2025年

作者： Laguna, Sonia Zhang, Lin Bezek, Can Deniz Farkas, Monika Schweizer, Dieter Kubik-Huch, Rahel A. Goksel, Orcun Computer-assisted Applications in Medicine ETH Zurich Switzerland Department of Information Technology Uppsala University Sweden Department of Radiology Kantonsspital Baden Affiliated Hospital for Research and Teaching of the Faculty of Medicine University of Zurich Switzerland

Speed-of-sound (SoS) is a biomechanical characteristic of tissue, and its imaging can provide a promising biomarker for diagnosis. Reconstructing SoS images from ultrasound acquisitions can be cast as a limited-angle computed-tomography problem, with Variational Networks being a promising model-based deep learning solution. Some acquired data frames may, however, get corrupted by noise due to, e.g., motion, lack of contact, and acoustic shadows, which in turn negatively affects the resulting SoS reconstructions. We propose to use the uncertainty in SoS reconstructions to attribute trust to each individual acquired frame. Given multiple acquisitions, we then use an uncertainty based automatic selection among these retrospectively, to improve diagnostic decisions. We investigate uncertainty estimation based on Monte Carlo Dropout and Bayesian Variational Inference. We assess our automatic frame selection method for differential diagnosis of breast cancer, distinguishing between benign fibroadenoma and malignant carcinoma. We evaluate 21 lesions classified as BI-RADS 4, which represents suspicious cases for probable malignancy. The most trustworthy frame among four acquisitions of each lesion was identified using uncertainty based criteria. Selecting a frame informed by uncertainty achieved an area under curve of 76% and 80% for Monte Carlo Dropout and Bayesian Variational Inference, respectively, superior to any uncertainty-uninformed baselines with the best one achieving 64%. A novel use of uncertainty estimation is proposed for selecting one of multiple data acquisitions for further processing and decision making. Copyright © 2025, The Authors. All rights reserved.

关键词： Variational techniques

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Assessing Cybersecurity Awareness among The Hashemite University Students In Terms Of computer Usage

Assessing Cybersecurity Awareness among The Hashemite Univer...

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International Conference on Electronics, computers and Artificial Intelligence (ECAI)

作者： Ashraf H. Aljammal Ahmad Qawasmeh Salah Taamneh Fadi Wedyan Mamoon Obiedat Hani Bani Salameh Department of Computer Science and Applications Prince Al Hussein bin Abdullah II Faculty of Information Technology The Hashemite University Zarqa Jordan Department of Engineering Computing and Mathematical Sciences Lewis University Romeoville Illinois USA Department of Information Technology Prince Al Hussein bin Abdullah II Faculty of Information Technology The Hashemite University Zarqa Jordan Department of Software Engineering Prince Al Hussein bin Abdullah II Faculty of Information Technology The Hashemite University Zarqa Jordan

ISBN: (数字)9798350371154

ISBN: (纸本)9798350371161

Internet usage among information technology users has expanded substantially, as have cybercrimes with potentially disastrous repercussions. Therefore, internet users have to employ the available security measures and policies during internet usage. Nowadays, University students make up a sizable portion of internet users. This study assesses the cybersecurity awareness among The Hashemite University students In terms of computer Usage. A questionnaire survey is used to assess students’ cybersecurity knowledge while using their PCs and connecting to the internet, concentrating on their behaviors and use of security measures.

关键词： Surveys Malware Internet computer security information technology computer crime Artificial intelligence

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IoT Based Human Biometric System Using Alcohol Level Detection for Driver Security 1

IoT Based Human Biometric System Using Alcohol Level Detecti...

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1st International Conference on Artificial Intelligence for Innovations in Healthcare Industries, ICAIIHI 2023

作者： Sinha, Anurag Kumar, Nitish Ticku, Amrita Modi, Vyom Shah, Meghal Shrivastava, Kapil School of Computing and Information Sciences Ignou New Delhi India Lovely Professional University Department of Computer Science Punjab Phagwara144001 India Bharti Vidyapeeth's College of Engineering India India Faculty of Engineering Marwadi Education Foundation Gujarat Rajkot360006 India Charotar University of Science & Technology Department of Computer Science & Engineering Gujarat 388421 India Department of Computer Engineering and Applications GLA University Mathura India

ISBN: (纸本)9798350330915

In today's society, driving after intoxication has become a major factor in traffic accidents. It is common knowledge that operating a vehicle while intoxicated is a major contributing factor in a significant number of accidents. The effects of drunk driving go beyond the drunk driver;they also affect other drivers and passengers in the same vehicle. As a result, this growing threat needs to be addressed immediately. Our project's goal is to create a system that uses the Internet of Things (IoT) to find traces of alcohol in someone's breath and apply preventive measures in order to effectively address this issue. Although there are laws against drunk driving, it is difficult to enforce them widely because law enforcement cannot constantly be present on the roads to spot drunk drivers. This restriction increases the chance of accidents significantly. In order to reduce future risks, a trustworthy system that can recognize and discourage drunk drivers is urgently needed. Drunk driving deaths are increasing, so we need to figure out how to reduce these kinds of deaths. The breath analyzing sensor used in the suggested system is the MQ-3, which calculates the breath alcohol content of an individual. The amount of alcohol that is allowed in the blood in India is 0.03. The engine won't start if the person's blood alcohol content is higher than this limit, making it impossible for them to drive. Additionally, the system will send an alert, possibly through a Raspberry Pi, to a friend or relative, providing the exact location using GPS coordinates. This notification serves as a precautionary measure to keep others informed about the situation. Implementing such a system can contribute significantly to reducing accidents related to alcohol consumption. In conclusion, detectors like the one proposed in this project hold immense significance in preventing the loss of life and property caused by reckless driving under the influence of alcohol. © 2023 IEEE.

关键词： Internet of things

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