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2022 Applied Informatics International Conference, AiIC 2022

作者： Saadoon, Muntadher Admodisastro, Novia University of Malaya Faculty of Computer Science and Information Technology Department of Software Engineering Kuala Lumpur50603 Malaysia Universiti Putra Malaysia Faculty of Computer Science and Information Technology Selangor Serdang43400 Malaysia

ISBN: (数字)9781728184289

ISBN: (纸本)9781728184289

Hadoop MapReduce becomes the essential framework to store, process and analyse big data in large-scale computing environments. The framework provides numerous opportunities to handle data-intensive applications like web crawling and indexing, data mining, anomaly prediction and machine learning. However, manual configurations of the framework parameters expose to human errors and lead to performance overhead and resource consumption penalties. Existing deployment automation solutions intended to mitigate the limitations by only facilitating the application execution workflow without considering crucial conditions that violates the overall performance after setting up the infrastructure parameters. This paper proposes a self-configured workflow platform with a user-friendly collaborating environment that provides automated setups of the framework paraments to obtain ideal performance compared to the native deployment of Hadoop MapReduce. The self-configured workflow platform has been evaluated in experiments on a real Hadoop cloud-based cluster and the results shows that the execution times are comparable to the native application. © 2022 IEEE.

关键词： MapReduce

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The Development of a Glove-like Controller Interface for VR applications 14

The Development of a Glove-like Controller Interface for VR ...

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14th ACM SIGMM Workshop on Immersive Mixed and Virtual Environment Systems, MMVE 2022

作者： Salgado, Eduardo Pereira Salgado, Eurico Marques Salgado, Débora Pereira Rodrigues, Thiago Braga Faculty of Computer Science Federal University of Uberlândia Uberlândia Brazil Faculty of Mechanical Engineering Federal University of Uberlândia Uberlândia Brazil Faculty of Engineering & Informatics Technological University of the Shannon Athlone Ireland Department Computer and Software Engineering Technological University of the Shannon Athlone Ireland

ISBN: (纸本)9781450393829

Smart gloves are wearable interfaces which provide detection of movements and gestures, kinesthetic, and even tactile feedback. These capabilities are important for immersive applications as it can bring more realistic features. The presented paper shows a concept of a working in progress application of a smart glove. The proposed hardware uses resistive flexible and electromagnets sensors to provide tactile and haptic feedback to be used in immersive applications such as the ones that use Virtual Reality (VR). The project will be done in a way that can provide user-centric requirement such as: the glove must be lightweight, comfortable, adjustable to different hands and finger shapes, and low cost to be manufactured. The intend is to use this glove as part of a biggest framework and immersive application. © 2022 ACM.

关键词： Wearable sensors

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Pūioio: On-device Real-Time Smartphone-Based Automated Exercise Repetition Counting System

arXiv

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arXiv 2023年

作者： Sinclair, Adam Kautai, Kayla Shahamiri, Seyed Reza Department of Electrical Computer and Software Engineering Faculty of Engineering The University of Auckland Auckland New Zealand

Automated exercise repetition counting has applications across the physical fitness realm, from personal health to rehabilitation. Motivated by the ubiquity of mobile phones and the benefits of tracking physical activity, this study explored the feasibility of counting exercise repetitions in real-time, using only on-device inference, on smartphones. In this work, after providing an extensive overview of the state-of-the-art automatic exercise repetition counting methods, we introduce a deep learning based exercise repetition counting system for smartphones consisting of five components: (1) Pose estimation, (2) Thresholding, (3) Optical flow, (4) State machine, and (5) Counter. The system is then implemented via a cross-platform mobile application named Pūioio that uses only the smartphone camera to track repetitions in real time for three standard exercises: Squats, Push-ups, and Pull-ups. The proposed system was evaluated via a dataset of pre-recorded videos of individuals exercising as well as testing by subjects exercising in real time. Evaluation results indicated the system was 98.89% accurate in real-world tests and up to 98.85% when evaluated via the pre-recorded dataset. This makes it an effective, low-cost, and convenient alternative to existing solutions since the proposed system has minimal hardware requirements without requiring any wearable or specific sensors or network connectivity. © 2023, CC BY.

关键词： Automation

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StakePage: Analysis of Stakeholders of an Information System Using Page Rank Algorithm 1

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11th International Conference on Recent Trends in Computing, ICRTC 2022

作者： Hassan, Tanveer Mohammad, Chaudhary Wali Sadiq, Mohd. Department of Applied Sciences and Humanities Faculty of Engineering and Technology Jamia Millia Islamia A Central University New Delhi110025 India Software Engineering Laboratory Computer Engineering Section UPFET Jamia Millia Islamia A Central University New Delhi110025 India

ISBN: (数字)9789811988257

ISBN: (纸本)9789811988240

The requirements elicitation process is the sub-process of requirements engineering in which stakeholders are involved to identify the requirements of an information system. Various methods have been developed to identify and analyze the stakeholders like goal-oriented requirements elicitation process, traditional methods, etc. Based on our review, we found that little attention is given to the analysis of the stakeholders using different measures of social networks before the starting of the requirements elicitation process. Therefore, to address this issue, this paper presents a StackPage method for the analysis of the stakeholders using page rank algorithm of social network measures. The applicability of the StackPage method is discussed with the help of the stakeholders of an institute examination system. Finally, the results are compared with two state-of-the-art methods, i.e., StakeRare and StakeSoNet methods. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Requirements engineering

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Autism Artificial Intelligence Performance Analysis: Five Years of Operation

Autism Artificial Intelligence Performance Analysis: Five Ye...

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International Conference on Advanced Learning Technologies (ICALT)

作者： Seyed Reza Shahamiri Department of Electrical Computer and Software Engineering Faculty of Engineering The University of Auckland Auckland New Zealand

Affecting approximately 1 in 60 individuals, Autism spectrum disorder (ASD) is a lifelong developmental condition associated with substantial healthcare costs and time-consuming diagnosis, whereas early detection of ASD traits may help limit further development of the condition. To help speed up ASD diagnosis, screening approaches have been introduced, but they are not widely used due to their reliability issues since these approaches use basic scoring functions to identify traits of autism rather than intelligently learning autistic indicators from historical cases and controls. Autism Artificial Intelligence is one such system that visualizes autistic behavioral indicators and leverages a Convolutional Neural Network to learn the behavioral patterns associated with autism using historical data collected from more than 6000 ASD cases and control. Autism AI has been operational since August 2018, and more than 10,000 individuals have benefited from this platform. In this paper, after briefly explaining the system, we will analyze how well it has performed compared to AQ-10 and Q-CHAT-10 screening methods and benchmark it against the diagnosis data we have collected.

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Ranking Center-based NSGA-II

Ranking Center-based NSGA-II

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2023 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2023

作者： Khosrowshahli, Rasa Rahnamayan, Shahryar Ibrahim, Amin Makrehchi, Masoud Lab Canada Ontario Tech University Department of Electrical Computer and Software Engineering OshawaON Canada Brock University Engineering Department St. CatharinesON Canada Ontario Tech University Faculty of Business and Information Technology OshawaON Canada

ISBN: (纸本)9798350337020

Multi-objective optimization is a branch of computation to solve mathematical optimization problems when conflicting multiple objective functions must be simultaneously optimized. Many population-based algorithms, such as NSGA-II are used to find an optimal Pareto set of solutions in a short time. However, previous research works showed the performance of classic NSGA-II is degraded when solving problems with many objectives (M ≥ 5). In this work, we aim to take advantage of center-based sampling scheme to increase the exploration and exploitation capability of NSGA-II algorithm. This sampling strategy has demonstrated promising results on several single-objective evolutionary algorithms such as GA, DE, and PSO. Recently, a novel clustering center-based strategy has been proposed, which motivated us to utilize center-based sampling scheme in NSGA-II to solve multi-objective optimization problems. The outcomes confirm that the proposed clustering center-based NSGA-II is able to effectively solve CEC-2017 multi-objective benchmark problems with 2, 3, 5, 10, and 15 objectives. © 2023 IEEE.

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Load Balancing Framework for Cross-Region Tasks in Cloud Computing

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computers, Materials & Continua 2022年第1期70卷 1479-1490页

作者： Jaleel Nazir Muhammad Waseem Iqbal Tahir Alyas Muhammad Hamid Muhammad Saleem Saadia Malik Nadia Tabassum Department of Software Engineering The Superior CollegeLahorePakistan Department of Computer Science Lahore Garrison UniversityLahore54000Pakistan Department of Statistics and Computer Science University of Veterinary and Animal SciencesLahore54000Pakistan Department of Industrial Engineering Faculty of EngineeringRabighKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Information Systems Faculty of Computing and Information Technology-RabighKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Computer Science Virtual University of PakistanLahore54000Pakistan

Load balancing is a technique for identifying overloaded and underloaded nodes and balancing the load between *** maximize various performance parameters in cloud computing,researchers suggested various load balancing *** store and access data and services provided by the different service providers through the network over different regions,cloud computing is one of the latest technology systems for both end-users and service *** volume of data is increasing due to the pandemic and a significant increase in usage of the internet has also been *** of the cloud are looking for services that are intelligent,and,can balance the traffic load by service providers,resulting in seamless and uninterrupted *** types of algorithms and techniques are available that can manage the load balancing in the cloud *** this paper,a newly proposed method for load balancing in cloud computing at the database level is *** database cloud services are frequently employed by companies of all sizes,for application development and business *** balancing for distributed applications can be used to maintain an efficient task scheduling process that also meets the user requirements and improves resource *** balancing is the process of distributing the load on various nodes to ensure that no single node is *** avoid the nodes from being overloaded,the load balancer divides an equal amount of computing time to all *** results of two different scenarios showed the cross-region traffic management and significant growth in revenue of restaurants by using load balancer decisions on application traffic gateways.

关键词： Load balancing performance database region virtualization

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SmartCoach: Comprehensive Tutor Recommender and Student Attentiveness Measuring Platform 3

SmartCoach: Comprehensive Tutor Recommender and Student Atte...

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3rd International Conference on Advancements in Computing, ICAC 2021

作者： Samarasekara, H.D.K. Hansaka, H.M.P. Rajapaksha, S.D.D. Tharaka, W.A.D.G. Manathunga, Kalpani Sriyarathna, Disni Charuka Faculty of Computing Department of Computer Science and Software Engineering Sri Lanka

ISBN: (纸本)9781665408622

With the pandemic, coaching or tutoring classes became to halt as the underlying system wasn't facilitating to adapt to emergency teaching mechanisms due to sparse of relevant technologies and tutor unawareness. SmartCoach is an integrated platform that allows students to find suitable tutors based on recommendations and other parameters like proximity, previous track record etc. using sentiment analysis and natural language processing. For tutors, SmartCoach allows publishing learning materials, automatic quiz creation, tracking attendance and, attentiveness during classes using OpenCV library. Moreover tutors get a dashboard featuring critical aspects about their classes and, personal income. This research is aimed to introduce a comprehensive distance learning platform with novel technological approaches that connect both potential students and tutors to a common platform. © 2021 IEEE.

关键词： Sentiment analysis

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Exploiting the sequential nature of genomic data for improved analysis and identification

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computers in Biology and Medicine 2024年 183卷 109307-109307页

作者： Nawaz, M. Saqib Nawaz, M. Zohaib Junyi, Zhang Fournier-Viger, Philippe Qu, Jun-Feng College of Computer Science and Software Engineering Shenzhen University China Faculty of Computing and Information Technology Department of Computer Science University of Sargodha Pakistan School of Computer Engineering Hubei University of Arts and Science Hubei Xiangyang China

Genomic data is growing exponentially, posing new challenges for sequence analysis and classification, particularly for managing and understanding harmful new viruses that may later cause pandemics. Recent genome sequence classification models yield promising performance. However, the majority of them do not consider the sequential arrangement of nucleotides and amino acids, a critical aspect for uncovering their inherent structure and function. To overcome this, we introduce GenoAnaCla, a novel approach for analyzing and classifying genome sequences, based on sequential pattern mining (SPM). The proposed approach first constructs and preprocesses datasets comprising RNA virus genome sequences in three formats: nucleotide, coding region, and protein. Then, to capture sequential features for the analysis and classification of viruses, GenoAnaCla extracts frequent sequential patterns and rules in three forms and in codons. Eight classifiers are utilized, and their effectiveness is assessed by employing a variety of evaluation metrics. A performance comparison demonstrates that the suggested approach surpasses the current state-of-the-art genome sequence classification and detection techniques with a 3.18% performance increase in accuracy on average. © 2024 Elsevier Ltd

关键词： Genome

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Campus safety monitoring system based on deep learning 20

Campus safety monitoring system based on deep learning

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20th International Symposium on Distributed Computing and Applications for Business engineering and Science, DCABES 2021

作者： Zhang, Qianying Hang, Jin Zhang, Boxuan Wei, Mengzhong Zhu, Quanyin Li, Xiang Huaiyin Institute of Technology Faculty of Computer Software Engineering Huai'an China

ISBN: (纸本)9781665428897

In view of the safety hazards existing on campus, a campus safety detection system based on deep learning behavior recognition, license plate recognition and speed detection is proposed and designed. The design divides the campus safety monitoring system into three functional modules: hazard behavior identification, license plate tracking and vehicle speed measurement, and on this basis, designs the database of storage information and the warning system of speed too fast to realize the monitoring function of campus safety. © 2021 IEEE.

关键词： License plates (automobile)

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