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21st OITS International Conference on Information technology, OCIT 2023

作者： Shabnam Pandey, Manju National Institute of Technology Department of Computer Application Raipur India

ISBN: (纸本)9798350358230

With the continual expansion of the scale of these massive volumes of data, one of the most difficult tasks is storing them. Large data sets are challenging to handle as they grow quickly over time. Companies that manufacture assets or offer any physical services, including industrial automation, are experiencing a change in their operations. It has drastically changed in the modern day, especially compared to many industries that offer efficient assets to differentiate by offering digital services changes in industrial behavior, and an emphasis on automation using IoT devices along with server agents. The purpose of this paper is to run server-based data, which enables the easier scaling of device metrics performances and manages the IoT resources. In this study, the toolchain components influx DB, telegraf, and grafana are used along with the digital twin in a realistic edge server setup. © 2023 IEEE.

关键词： Digital devices

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Air Quality Prediction Using Supervised Machine Learning Techniques 6th

Air Quality Prediction Using Supervised Machine Learning Tec...

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6th International Conference on Information and Communication technology for Intelligent Systems, ICTIS 2021

作者： Shrivastava, Atul Lal Dwivedi, Rajendra Kumar Department of Information Technology and Computer Application MMMUT Gorakhpur India

ISBN: (纸本)9789811935701

To maintain good air quality, the observation of pollution levels framework estimates a variety of air contaminants in various locations. In the current circumstances, it is the most desirable concern. The release of hazardous gases into the environment by businesses, vehicles, and other sources pollutes the air. These days, the level of pollution in the air has surpassed fundamental levels, and the amount of contamination in several major urban areas has exceeded the public authority’s air quality list criteria. It has a tremendous impact on a person’s health. With advances in machine learning technology, it is now possible to forecast the future of toxins based on historical data. In this paper, we described a device that can collect the current toxic gases. With the help of the previous records of toxic gases, we executed a computation using machine learning techniques to detect the contamination in the air. It would be a good idea to use machine learning to forecast the future contamination information. The information gathered is saved in an Excel document for further analysis. To collect contamination data, the respective sensors are used on Arduino. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Contamination

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Detecting Deceptive News in Social Media Using Supervised Machine Learning Techniques 6th

Detecting Deceptive News in Social Media Using Supervised Ma...

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6th International Conference on Information and Communication technology for Intelligent Systems, ICTIS 2021

作者： Malviya, Anshita Dwivedi, Rajendra Kumar Department of Information Technology & Computer Application MMMUT Gorakhpur India

ISBN: (纸本)9789811935749

Our society has witnessed numerous incidents concerning fake *** media has always played a significant role in its *** with notorious mindsets often are the generators and spreaders of such *** mischievous people spread the fake news without even realizing the effect it has on naive *** believe on the fake news and start behaving *** news appeals to our *** plays with our feelings, and it can make us angry, happy, or ***, fake news can lead to hatred or anger toward a specific ***, people easily befool each other using social media as a tool to spread the fake *** this paper, we proposed a machine learning-based model for detection of such deceptive news which creates disturbances in our *** model is implemented in *** used machine learning algorithms, *** regression, multinomial Naive Bayes, passive-aggressive classifier, and multinomial classifier with *** vectorization techniques have been used for evaluation of *** show that the passive-aggressive classifier using Tf-idf vectorization outperforms others in terms of accuracy to detect the fake news. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Social networking (online)

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Simulation and Evaluation of Mental Sand Table based on Virtual Reality 3

Simulation and Evaluation of Mental Sand Table based on Virt...

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3rd International Conference on Consumer Electronics and computer Engineering, ICCECE 2023

作者： Xie, Sijia Liu, Zhiqiang Tang, Chuanqian Chen, Yanruyu Qinghai University Computer Technology and Application Department Xining China

ISBN: (纸本)9798350331578

In view of the low popularity rate of traditional mental sand table, insufficient site resources can not meet the problems of multiple people at the same time, based on virtual reality technology to achieve the real simulation of functional characteristics of mental sand table, promote the development and use of mental sand table. According to the functional characteristics of the traditional psychological sand table, the three-dimensional simulation construction of scene style, atmosphere characteristics, sand types and quantities is realized. The ray range is obtained based on the window matrix and the 3D perspective, and the 3D model boundary is detected and recolor is carried out to enhance the user's interactive visual feedback. The sand model and user interaction data were serialized and deserialized, and the horizontal and vertical offsets of model grid vertices were recorded to realize the storage and recovery of sand table data. Combined with the self-rating anxiety scale, the user experiment results show that VR mental sand table has positive significance in relieving anxiety and popularizing mental sand table. © 2023 IEEE.

关键词： Virtual reality

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Reliable Communication in Opportunistic Network based on Trust: A Review 3

Reliable Communication in Opportunistic Network based on Tru...

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3rd International Conference on Intelligent Systems, Advanced Computing, and Communication, ISACC 2025

作者： Ahmed, Mala Paul, Amrita Bose Prokash Goswami, Jyoti AEC Assam Science and Technology University Department of Computer Application Assam India

ISBN: (纸本)9798331523893

Communication plays a significant role in a network where the nodes get connected opportunistically. To establish reliable communication in such a network is very much challenging due to the intermittent node connectivity. Recent research work focuses on establishing trust relationship between the nodes for reliable communication in wireless networks. Generally trust of a node is calculated based on historical information or feedback given by other nodes that has previous communication with that particular node. This paper provides an overview of the trust models that are available in the literature and connote their issues and challenges for opportunistic network. The authors propose a trust based framework for reliable communication in opportunistic network. The framework signifies the importance of belief-trust for establishing reliable communication over the network. © 2025 IEEE.

关键词： Belief trust Direct trust Indirect trust Opportunistic network Recommender system Reliable communication Trust model

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Detecting and recognizing faces from video images using multi-deep CNN based rank-level fusion 2

Detecting and recognizing faces from video images using mult...

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2nd International Conference on Advancement in Computation and computer Technologies, InCACCT 2024

作者： Ghosh, Manas Sing, Jamuna Kanta RCC Institute of Information Technology Department of Computer Application Kolkata India Jadavpur University Department of Computer Science & Engineering Kolkata India

ISBN: (纸本)9798350371314

The advent of deep neural networks has provided a competitive edge in facial analysis efforts, especially the detection and recognition of faces from video images. This paper outlines a methodology wherein a face database is created from an outdoor video clip, and a rank-level fusion mechanism has been proposed for face recognition using a database that makes use of the probabilities produced by the softmax functions of multiple deep convolutional neural network (CNN) models. These probabilities are referred to as certainty indices for the potential classes to which a test sample may belong. For each of the CNN models, fuzzy ranks are obtained for a subset of classes with the top certainty indices by applying a Gaussian distribution function followed by a complementation operation. For each class, appearing in one or more subsets corresponding to deep network models, average of the certainty indices is complemented and fused with the sum of complemented fuzzy ranks. While calculating the cumulative sum of the fuzzy ranks, a penalty, is foisted to the class for not being present in any subset. This can avoid the chance of becoming an unexpected winner. The class with the lowest final ranking was identified as the class pertaining to the test sample. In addition to testing with the custom-made outdoor video-based face dataset, the projected method was evaluated with a standard surveillance indoor dataset, ChokePoint. Considering all test sets on ChokePoint dataset, the average recognition accuracy of the proposed method is 99.54%. The same for custom-made dataset is 93.96%. For both datasets, precision and macro-average scores of the proposed method in all cases are higher than the individual deep CNN models. © 2024 IEEE.

关键词： Face recognition

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"Nyctophy": Assessing the effectiveness of serious game for nyctophobia based on virtual reality by usability and heart rate monitoring 9th

"Nyctophy": Assessing the effectiveness of serious game for ...

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9th International Conference on computer Science and Computational Intelligence, ICCSCI 2024

作者： Ardiyanto, Elshad Ryan Alexander, Patrick Putra, Edyth Novian Ramdhan, Dimas Game Application & Technology Program Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia

Nyctophobia is a phobia of the dark and is common among children but also found in adults. While the phobia itself is commonly known, the diversity of its treatment is still minimal. As technology has reached its highest point, numerous inventions and innovations have emerged in the medical sector. This study aimed to examine the usability of Virtual Reality and Keyboard and Mouse as an interface using the Extended Reality Game Usability Questionnaire (XR-GUQ) in Nyctophobia therapy and to analyze the heart rate response, impact, and implications using t-test Paired/Wilcoxon Signed Rank. Thirty-four Bina Nusantara University students from various backgrounds completed the test using interfaces and a smartwatch. They were divided into two groups, high- and low fear, using the modified Acrophobia Questionnaire (AQ), which resulted in a significant difference. The XR-GUQ result was insignificant in all variables, which indicates similar usability scores on both interfaces. The t-test Paired/Wilcoxon Signed Rank test revealed a significant difference between the high- and low-fear groups when using the Virtual Reality interface compared to the Keyboard and Mouse interface. This significant difference was found within each group regardless of the interface used. This research shows similar scores in terms of usability but a significant difference in heart rate response with the help of a serious game to give a new sensation of phobia therapy. © 2024 The Authors.

关键词： Serious games

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Greedy-based task scheduling algorithm for minimising energy and power consumption for virtual machines in cloud environment

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International Journal of Cloud Computing 2023年第2-4期12卷 424-434页

作者： Razaak, M.P. Abdul Ansari, Gufran Ahmad Department of Computer Application B.S. Abdur Rahman Crescent Institute of Science and Technology Tamil Nadu Chennai India

The research in cloud computing has the following significant elements, VMP referring to virtual machine placement and its energy efficiency. This paper proposes applying evolutionary computing in VMP which will result in active physical servers’ reduction in numbers. This proposed method will also help in saving energy by scheduling under utilising servers. Task scheduling process is recommended in this article which minimises the energy consumed by active servers. Task scheduler is interlinked with cloud server with the help of VMP. Minimisation algorithm for active physical servers (MAPS) is an algorithm which has been used in this proposal in order to improve the efficiency. The active information that flows between the cloud server and VMP is controlled by MAPS algorithm. Java software is adopted to implement in this recommendation. The demonstrated experimental result shows that the proposed greedy algorithm performs better than existing state-of-arts in terms of energy efficiency. Copyright © 2023 Inderscience Enterprises Ltd.

关键词： Energy efficiency

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Differential flatness-based distributed control of underactuated robot swarms

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Applied Mathematics and Mechanics(English Edition) 2023年第10期44卷 1777-1790页

作者： Ningbo AN Qishao WANG Xiaochuan ZHAO Qingyun WANG Department of Dynamics and Control Beihang UniversityBeijing 100191China Institute of Computer Application Technology China North Industries Group Corporation LimitedBeijing 100095China

This paper proposes a distributed control method based on the differential flatness(DF) property of robot swarms. The swarm DF mapping is established for underactuated differentially flat dynamics, according to the control objective. The DF mapping refers to the fact that the system state and input of each robot can be derived algebraically from the flat outputs of the leaders and the cooperative errors and their finite order derivatives. Based on the proposed swarm DF mapping, a distributed controller is designed. The distributed implementation of swarm DF mapping is achieved through observer design. The effectiveness of the proposed method is validated through a numerical simulation of quadrotor swarm synchronization.

关键词： differential flatness(DF) underactuated robot distributed control synchronization

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Applying Bayesian belief in LoRa: smart parking case study

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Journal of Ambient Intelligence and Humanized Computing 2023年第6期14卷 7857-7870页

作者： Gupta, Sakshi Snigdh, Itu School of Computer Application Lovely Professional University Punjab Phagwara India Department of Computer Science and Engineering Birla Institute of Technology Mesra Jharkhand Ranchi India

With the popularity of LoRa, many IoT applications are now being realized with this Low Power Wide Area Network (LPWAN) technology. Apart from ensuring low power and long-range communications, LoRa is also interference-free and hence an obvious choice for applications in urban scenarios. We dedicate our study to analyze and infer the impact of LoRa parameters like SF (Spreading Factor), BW (Bandwidth), CR (Coding Rate) on network performance metrics like delay, throughput for a smart parking scenario. Suited to the smart parking case study, we also present network performance observations for varied LOS settings (Line-of-Sight), NON-LOS, and obstruction. We try to identify the most significant parameters under different network conditions and determine the relationship among them through canonical correlation through our article. We also propose a Bayesian belief network to infer the best possible combination of LoRa parameters for achieving high-quality network efficiency under the environment scenarios. © 2023, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Bayesian networks

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