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Exploring Educational Applicability of Virtual Touch System on Maker Space 5

Exploring Educational Applicability of Virtual Touch System ...

引用

5th IEEE International Conference on Knowledge Innovation and Invention, ICKII 2022

作者： Yu, Pao-Ta Lo, Hung-Ting Fang, Yu-Cheng Li, An-Fang Liao, Ying-Han Tsai, Cheng-Yu National Chung Cheng University Dept. of Computer Science & Information Engineering Chiayi Taiwan

ISBN: (数字)9781665479295

ISBN: (纸本)9781665479295

Interaction with gestures is more intuitive than traditional input with a keyboard and a mouse. It has gradually become the major technology for extended reality. However, for most users, gesture control is not familiar as other interactive devices, and most user interfaces of daily-use applications are currently not designed for gesture control. Thus, we propose a mid-air hand gesture control system, named vTouch to realize a touch device trained by deep learning with a convolutional neural network for image feature extraction, attention mechanisms for extracting time-series data features, and fully connected layer for classification. Besides, there is a customized driver in kernel mode which treats the vTouch system as a virtual multi-touch device. An experimental design is also proposed to evaluate the effectiveness of the training and the usability of the system. © 2022 IEEE.

关键词： User interfaces

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Information Technology (IT) Governance Framework with Artificial Neural Network and Balance Scorecard to Improve the Success Rate of Software Projects 6

Information Technology (IT) Governance Framework with Artifi...

引用

6th International Conference on Electronics, Communication and Aerospace Technology, ICECA 2022

作者： Ranesh, M. Maria Antony Samuel, S. Justin Natchadalingam, R. Jeyanthi, P. School of Computing Sathyabama Institute of Science and Technology Dept of Information Technology India Psn Engineering College Dept of Computer Science and Engineering Tirunelveli India

ISBN: (纸本)9781665482714

IT governance enables companies to plan and manage their IT investments in order to achieve their strategic objectives. Overall goal of this paper is to discuss about an approach to increase the success of the software projects through Artificial Intelligence. Standard governance standards are analyzed to understand the impact on software project success rates. Enterprise governance is a subset of IT governance that aids in the management of information technology resources. COBIT is a widely used methodology for developing effective enterprise IT governance. ISACA (Information Systems Audit and Control Association) stated implementation solution currently uses a sequentially ordered approach, which has raised issues. Several challenges have arisen as a result of top management's lack of commitment and misplaced solutions. Limitation on this investigation is the customized and confidential governance pattern used across various organization, hence there are very limited real time data for end-to-end analysis. Nonetheless, in combination with the agile project management paradigm, new project life-cycle solutions have evolved. Artificial Intelligence (AI) is an important element to address the increasing demand for machine learning systems. Artificial neural network (ANN) method is highly useful to arrive at best possible solution to improve the project success. This study found that ANN with Balance Score Card was exceptionally effective in providing the optimal solution to increase the project success rates. © 2022 IEEE.

关键词： Neural networks

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The Road-ahead for E-healthcare 4.0: A Review of Security Challenges 1

The Road-ahead for E-healthcare 4.0: A Review of Security Ch...

引用

1st International Conference on Informatics, ICI 2022

作者： Talati, Rutu Chaudhari, Payal Pandit Deendayal Energy University Dept. of Computer Science and Engineering Gujarat Gandhinagar India

ISBN: (纸本)9781665437219

The security, privacy, and confidentiality problems posed by E- Healthcare data demand a re-examination of traditional information security principles and procedures. With the penetration of IT services in Healthcare domain the Healthcare in genre 1.0 has evolved as E- Healthcare genre 4.0. While in genre 1.0 the healthcare domain was greatly dependent on practitioner's handwritten notes to preserve their patients' medical history, in genre 2.0 the paper records have been started to be replaced with computerized records (EHRs). E-Healthcare 3.0 was centered on the patient allowing him to store and preserve his medical records. Since last one decade the E-Healthcare 4.0 has come with the inclusion of Fog Computing (FC), Cloud Computing (CC), Internet of Things (IoT), and Tele-Healthcare advances to disperse information among a few partners. With the rapid evolution of IT sector inside healthcare domain, the security challenges for E-Healthcare domain have also started to arise. This paper discusses such challenges and their proposed solution. © 2022 IEEE.

关键词： Internet of things

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Analytical Approach Towards Radiological Image-based Fracture Assessment Using Artificial Intelligence

Analytical Approach Towards Radiological Image-based Fractur...

引用

Computing, sciences and Communications (ICCSC), International Conference on

作者： Takhellambam Sylvia Sanjay Kumar Dubey Khelchandra Thongam Computer Science & Engineering Dept. Amity University Noida Uttar Pradesh India Computer Science & Engineering Dept. National Institute of Technology Manipur Imphal India

ISBN: (数字)9798350353648

ISBN: (纸本)9798350353655

The utilization of Artificial Intelligence (AI) techniques has been prevalent in various applications and the gradual increase in implementation towards healthcare sectors has scaled up. computer aided diagnosis has emerged as a major research area directed toward efficient use of resources. Fracture of bone has been a popular health problem associated with risk for mortality. Fractures are frequent in the long bones or the weight-bearing bones. AI techniques to accurately detect and classify fractures are still a challenging task beyond the conventional methods. Our objective is to assess the effectiveness of multiple algorithms in identifying and categorizing ankle fractures using radiological images. This review paper focuses on several available approaches of Deep-Learning (DL) and Machine-Learning (ML) regarding Ankle Fracture Classification and Identification based on Radiological Images for Medical Applications. The goal is to assist physicians and orthopaedics with simple and realistic decision support systems. In addition to a comprehensive analysis of the research, this study looked at several real-world examples of AI applications in the healthcare industry. Consequently, it is critical to have a fundamental grasp of these ML and DL algorithms to be ready for upcoming advancements in AI. We have reviewed and classified scientific conference and journal articles used for various AI techniques and offer future utility as a comparative analysis for further research in healthcare sectors.

关键词： Ankle Wrist Reviews Mortality Medical services Machine learning Bones Classification algorithms Object recognition Artificial intelligence

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A Survey of VANET Security Models and its Issues on Node Level Data Transmission 2

A Survey of VANET Security Models and its Issues on Node Lev...

引用

2nd International Conference on Artificial Intelligence and Smart Energy, ICAIS 2022

作者： Sireesha, K. Malladi, Srinivas Koneru Lakshmaiah Education Foundation Dept. of Computer Science and Engineering AP Vaddeswaram India

ISBN: (纸本)9781665400527

Vehicular Ad hoc Network (VANET) plays a vital role in communication between moving vehicles on a network enabled and regulated by wireless network protocols. However, as the size of the network increases, the vulnerability of the node attacks and data attacks also increases exponentially. Most of the conventional models are depend on the network size, its topology structure and data size. In this paper, a study of different VANET security models and its issues are studied based on the network parameters and security metrics. Different types of VANET security models, network attacks and encryption models are discussed in this paper. Finally, the limitations of the conventional VANET security models are discussed on large VANETs. © 2022 IEEE.

关键词： Cryptography

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Container-Based VoIP Failover Design on Kubernetes Overlay Networks

Container-Based VoIP Failover Design on Kubernetes Overlay N...

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2022 International Conference on Computational science and Computational Intelligence, CSCI 2022

作者： Jhuang, Cai-Sian Wu, Quincy National Chi Nan University Dept. Computer Science and Informance Engineering Nantou Taiwan

ISBN: (纸本)9798350320282

This paper studied how to utilize a popular container scheduling orchestrator - Kubernetes (K8s) - in today's cloud computing scenario to support the Voice over IP (VoIP) applications. In VoIP, two major protocols - Session Initiation Protocol (SIP) and Real-time Transport Protocol (RTP) - usually require network traffic to obey the following pattern: the packets from both end devices must be directed to the same server during a call. However, in a K8s network environment, the automatic LoadBalancer mechanism only ensures that traffic is directed to a healthy Pod but does not consider the need for both sides of the session to be handled by the same server. Therefore, after VoIP is introduced into the container, some subtle design must be proposed to integrate SIP and RTP into the existing K8s network architecture to handle two-way communication and failover so that the above problem can be properly addressed. In this paper, we use the K8s Label selector, K8s leader-election, and a few open-source software to solve the problem of failover, and measure the pressure of failover on K8s and the underlying operating system. © 2022 IEEE.

关键词： Cloud computing

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Integrated Multiclass Sentiment Analysis of Movie Reviews: Combining Fine-Tuned DistilBERT, LightGBM and XAI for Interpretation

Integrated Multiclass Sentiment Analysis of Movie Reviews: C...

引用

Computing, Applications and Systems (COMPAS), IEEE International Conference on

作者： Maharin Afroj Md. Polash Islam Shirin Sultana Md. Saifur Rahman Department of Computer Science and Engineering Bangladesh University of Business and Technology Dhaka Bangladesh Dept of Computer Science and Engineering Bangladesh University of Business and Technology Dhaka Bangladesh

ISBN: (数字)9798331529765

ISBN: (纸本)9798331529772

Sentiment analysis of movie reviews plays a critical role in understanding audience perspectives and predicting trends in the entertainment industry. This work presents an integrated approach that encourages a fine-tuned DistilBERT model for feature extraction, followed by LightGBM for classification, and SHAP (Shapley Additive Explanations) for model interpretability. By combining these advanced techniques, our approach achieves a high accuracy of 97%, significantly outperforming traditional methods. The use of DistilBERT enables precise contextual understanding of textual data while offering a more efficient and lightweight alternative to the full BERT model. LightGBM provides efficient and scalable classification, and SHAP ensures transparent and interpretable model decisions, allowing us to understand key factors driving sentiment predictions. This integrated framework enhances accuracy and also provides valuable insights into the model’s behavior, making it a robust tool for sentiment analysis in movie reviews.

关键词： Sentiment analysis Adaptation models Accuracy Reviews Computational modeling Scalability Motion pictures Feature extraction Data models Context modeling

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Survival Prediction for Patients with Cirrhosis

Survival Prediction for Patients with Cirrhosis

引用

IEEE International Conference on System, Computation, Automation and Networking (ICSCAN)

作者： Sowmiya X L Sanjana R Nishintha A Pavithra S Shree Charan Kannan R. Ponnusamy Dept. of Computer Science and Engineering Chennai Institute of Technology Chennai Tamilnadu India Dept. of Computer Science and Engineering Chennai Institute of Technology Tamil Nadu India

ISBN: (数字)9798331510022

ISBN: (纸本)9798331510039

Cirrhosis is one of the major causes of death around the world. Hence, the possibility of survival prediction among patients affected by this disease constitutes the principal factor in properly planning treatment and management procedures. This work aims to design a predictive model of the probability of survival of patients who have cirrhosis based on patient data, including clinical parameters, medical history, and laboratory findings of these patients. The data-driven machine learning algorithm improves the predictive accuracy and significantly enhances the clinical decision-making process. This considers multiple predictors: the patient's liver function tests, the demographic factors, and the indicators of disease progression in the body. It will be validated for reliability and accuracy using real-world patient case data. Therefore, this tool could aid clinicians in devising treatment plans that improve patient outcomes and efficiently utilise healthcare resources. This study also contributes to the emerging genre of AI-assisted care because chronic liver disease management, specifically cirrhosis, in this case, requires constituting predictive analytics.

关键词： Measurement Accuracy Liver diseases Medical services Predictive models Planning Resource management Reliability Predictive analytics Diseases

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Designing Reliable Navigation Behaviors for Autonomous Agents in Partially Observable Grid-world Environments

Designing Reliable Navigation Behaviors for Autonomous Agent...

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International Joint Conference on Neural Networks (IJCNN)

作者： Andrew R. Buck Derek T. Anderson James M. Keller Cindy Bethel Audrey Aldridge Dept. of Electrical Engineering and Computer Science University of Missouri Columbia MO USA Dept. of Computer Science and Engineering Mississippi State University Starkville MS USA

ISBN: (数字)9798350359312

ISBN: (纸本)9798350359329

Deciding where to go is one of the primary challenges in designing an agent that can explore an unknown environment. Grid-worlds provide a flexible framework for representing different variations of this problem, allowing for various types of goals and constraints. Typically, agents move one cell at a time, gathering new information at each time step. However, recomputing a new action after each step can lead to unintended behaviors, such as indecision and forgetting about previous goals. To mitigate this, we define a set of persistent feature layers that can be used by either a linear weighted policy or a neural network approach to identify potential destination locations. The outputs of these policies are processed using knowledge of the environment to ensure that objectives are met in a timely and effective manner. We demonstrate how to train and evaluate a U-Net model in a custom grid-world environment and provide guidance and suggestions for how to use this approach to build complex agent behaviors.

关键词： Navigation Neural networks Reliability engineering Autonomous agents

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Role Of Cloud Security in Big Data Processing for Healthcare System 8

Role Of Cloud Security in Big Data Processing for Healthcare...

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8th International Conference on Advanced Computing and Communication Systems, ICACCS 2022

作者： Shukla, Amogh Lodha, Nitin Vellore Institute of Technology Dept. of Computer Science and Engineering Tamil Nadu Vellore India

ISBN: (纸本)9781665408165

Demand of Big data processing over cloud is in-creasing day by day. Present research work has focused on the role of cloud security in big data processing. The area of re-search is healthcare system where patients are prescribed for the different diseases. Cloud is providing zero downtime, high reliability where information is collected for further processing and provided to user on request. It has been observed that there is several research works that has been made in such fields but there are several issues related to big data security as well as performance issues. There is need to propose a secure and high performance system that should provide security to managed as well as unmanaged big data without influencing its performance. Present research has provided security to health care system big data. However there are many encryption mechanism that could be used to secure the data but these re-search are suffering due to performance issues. After compression operation data is encrypted in blocks of 64 bits each using the block cypher DES, which creates 64 bits of cipher text from 64 bits of plain text. A small number of tiny discrepancies exist between encoding and decrypting with the same method and key. The key is 56 bits long. © 2022 IEEE.

关键词： Health care

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