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Real-Time and Intelligent Flood Forecasting Using UAV-Assisted Wireless Sensor Network

Computers, Materials & Continua 2022年第1期70卷 715-738页

作者： Shidrokh Goudarzi Seyed Ahmad Soleymani Mohammad Hossein Anisi Domenico Ciuonzo Nazri Kama Salwani Abdullah Mohammad Abdollahi Azgomi Zenon Chaczko Azri Azmi Centre for Artificial Intelligent(CAIT) Universiti Kebangsaan MalaysiaBangi43600Malaysia School of Computer Engineering Iran University of Science and TechnologyResalat Sq.16846-13114TehranIran School of Computing Faculty of Engineering Universiti Teknologi MalaysiaJohorMalaysia School of Computer Science and Electronic Engineering University of EssexColchester CO43SQUnited Kingdom Department of Electrical Engineering and Information Technologies University of Naples“Federico II”Naples80125Italy Razak Faculty of Technology and Informatics Universiti Teknologi MalaysiaKuala Lumpur54100Malaysia School of Electrical and Data Engineering University of Technology SydneyUltimoNSWAustralia

The Wireless Sensor Network(WSN)is a promising technology that could be used to monitor rivers’water levels for early warning flood detection in the 5G ***,during a flood,sensor nodes may be washed up or become faulty,which seriously affects network *** address this issue,Unmanned Aerial Vehicles(UAVs)could be integrated with WSN as routers or data mules to provide reliable data collection and flood *** light of this,we propose a fault-tolerant multi-level framework comprised of a WSN and a UAV to monitor river *** framework is capable to provide seamless data collection by handling the disconnections caused by the failed nodes during a ***,an algorithm hybridized with Group Method Data Handling(GMDH)and Particle Swarm Optimization(PSO)is proposed to predict forthcoming floods in an intelligent collaborative *** proposed water-level prediction model is trained based on the real dataset obtained fromthe Selangor River *** performance of the work in comparison with other models has been also evaluated and numerical results based on different metrics such as coefficient of determination(R2),correlation coefficient(R),RootMean Square Error(RMSE),Mean Absolute Percentage Error(MAPE),and BIAS are provided.

关键词： Unmanned aerial vehicles wireless sensor networks group method data handling particle swarm optimization river flow prediction

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LSTM Based Neural Network Model for Anomaly Event Detection in Care-Independent Smart Homes

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Computer Modeling in Engineering & sciences 2024年第9期140卷 2689-2706页

作者： Brij B.Gupta Akshat Gaurav Razaz Waheeb Attar Varsha Arya Ahmed Alhomoud Kwok Tai Chui Department of Computer Science and Information Engineering Asia UniversityTaichung413TaiwanChina Symbiosis Centre for Information Technology(SCIT) Symbiosis International UniversityPune411057India Center for Interdisciplinary Research University of Petroleum and Energy Studies(UPES)Dehradun248007India Computer Engineering Ronin InstituteMontclairNJ 07043USA Management Department College of Business AdministrationPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Business Administration Asia UniversityTaichung413TaiwanChina Department of Electrical and Computer Engineering Lebanese American UniversityBeirut1102Lebanon Department of Computer Sciences Faculty of Computing and Information TechnologyNorthern Border UniversityRafha91911Saudi Arabia School of Science and Technology Hong Kong Metropolitan University(HKMU)Hong KongChina

This study introduces a long-short-term memory(LSTM)-based neural network model developed for detecting anomaly events in care-independent smart homes,focusing on the critical application of elderly fall *** balances the dataset using the Synthetic Minority Over-sampling Technique(SMOTE),effectively neutralizing bias to address the challenge of unbalanced datasets prevalent in time-series classification *** proposed LSTM model is trained on the enriched dataset,capturing the temporal dependencies essential for anomaly *** model demonstrated a significant improvement in anomaly detection,with an accuracy of 84%.The results,detailed in the comprehensive classification and confusion matrices,showed the model’s proficiency in distinguishing between normal activities and *** study contributes to the advancement of smart home safety,presenting a robust framework for real-time anomaly monitoring.

关键词： LSTM neural networks anomaly detection smart home health-care elderly fall prevention

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Learning internet of things by using augmented reality 2021

Learning internet of things by using augmented reality

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5th International Conference on Virtual and Augmented Reality Simulations, ICVARS 2021

作者： Panessai, Ismail Yusuf Iksan, Nur Zahari, Siti Aishah Abdulbaqi, Azmi Shawkat Modi Lakulu, Muhammad Modi Bin Husin, Mohd Razimi Ahmad, Hishamuddin Arif, Harleny Abd Wahyudiono, Pratiwi Hendro Department of Computing Faculty of Art Computing and Creative Industry Universiti Pendidikan Sultan Idris Malaysia Centre Indonesia University of Anbar College of Computer Science and Information Technology Iraq Department of Educational Studies Faculty of Human Development Universiti Pendidikan Sultan Idris Malaysia Centre Indonesia

ISBN: (纸本)9781450389327

This research is to find an Augmented Reality (AR) apps that suitable use for education purpose. Today, in school, students and teachers have been introduce to Internet of Thing (IoT) in technology design subject. It has considered using technology application can motivate and increase performance and student achievement in their learning units. The expected of this research is to find a good tools that can be use both of teachers or students in learning and teaching process especially for subject of technology and Design. The early component in this apps should be a pop out image with details of electronics components until practical exercise. At the end of the used of this application, users are expected to have clear steps in mind about basic Arduino component and installations. For evaluation phases, the apps tested and used by vocational school student in subject of technology and Design. © 2021 ACM.

关键词： Internet of things

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Enhancing UX Design Through Eye-Tracking and Image Processing: Practical Insights and Applications 10

Enhancing UX Design Through Eye-Tracking and Image Processin...

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10th International Conference on Platform technology and Service, PlatCon 2024

作者： Baharum, Aslina Ismail, Rozita Halamy, Suhaida Rahim, Emelia Abdul Noor, Noorsidi Aizuddin Mat Deris, Farhana Diana School of Engineering and Technology Sunway University Bandar Sunway Selangor Malaysia College of Computing and Informatics Universiti Tenaga Nasional Putrajaya Campus Selangor Kajang Malaysia School of Information Science College of Computing Informatics and Mathematics Universiti Teknologi MARA Cawangan Sarawak Sarawak Kota Samarahan Malaysia Faculty of Business Management Universiti Teknologi MARA Cawangan Sarawak Sarawak Kota Samarahan Malaysia Mass Appraisal Housing and Planning Research Group Centre for Real Estate Studies Real Estate Department Faculty of Built Environment and Surveying Universiti Teknologi Malaysia Johor Johor Bahru Malaysia Faculty of Social Sciences and Humanities Universiti Teknologi Malaysia Johor Johor Bahru Malaysia

ISBN: (纸本)9798350367874

In the digital age, optimizing user experience (UX) is paramount for the success of various applications and interfaces. Eye-tracking, a method used to monitor and analyze eye movements, has emerged as a powerful tool in UX research. This study investigates the intersection of eye-tracking and image processing, focusing on how insights derived from eye-tracking data can enhance UX design. Through a series of case studies, this research explores the practical applications of eye-tracking in improving user interaction with image-based interfaces. By analyzing user attention patterns, gaze fixation durations, and visual engagement metrics, the study uncovers valuable insights into user behaviour and preferences. These insights inform design decisions related to interface layout, content placement, and visual hierarchy, ultimately leading to more intuitive and engaging user experiences. The findings from this study provide practical guidelines and best practices for integrating eye tracking into the UX design process, offering valuable insights for designers, developers, and researchers seeking to optimize user interaction with image-based applications and interfaces. © 2024 IEEE.

关键词： Eye movements

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Reconstruction and fitting of second-harmonic signals by wavelength modulation spectroscopy method based on fast Fourier transform

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Chinese Optics Letters 2022年第9期20卷 68-72页

作者： Linquan Lai Yue Chen Kongtao Chen Jiale Tang Kaiwen Yin Fuqiang Jia Dun Qiao Yuanlong Fan Kang Li Nigel Copner Fujian Key Laboratory of Ultrafast Laser Technology and Applications School of Electronic Science and TechnologyXiamen UniversityXiamen 361005China Wireless&Optoelectronics Research&Innovation Centre Faculty of ComputingEngineering&ScienceUniversity of South WalesWales CF371DLUK

Conventional wavelength modulation spectroscopy(WMS)is vulnerable to the influence of low-frequency *** of the method highly depends on the performance of the costly lock-in *** this article,we report a new and effective method for reconstructing second-harmonic signals through WMS based on fast Fourier transform(FFT).This method is less disturbed by low-frequency noise because it does not use a low-frequency ramp *** and detection procedures were *** discrete second-harmonic waveform can be obtained by continuously changing the DC signal and FFT analysis in this ***-harmonic waveforms acquired by the two means are generally *** experimental study validates the obtained gas concentration from 5% to 30%,showing a good linear relationship by the proposed *** maximum relative error on concentration extraction is 2.87%;as for conventional WMS,this value is 4.50%.The developed measurement method may have potential in computed tomography.

关键词： fast Fourier transform wavelength modulation spectroscopy second-harmonic waveform

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IoT Security Frameworks: A Comparative Review with a Focus on Privacy 2

IoT Security Frameworks: A Comparative Review with a Focus o...

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2nd International Conference on Cyber Resilience, ICCR 2024

作者： Al-Hasnawi, Abduljaleel Niu, Yitong Tawfeq, Jamal F. Ranjan Pradhan, Manas Salahat, Mohammed Ghazal, Taher M. Ministry Of Higher Education And Scientific Research Baghdad Iraq College Of Information Technology Imam Ja'afar Al-Sadiq University Department Of Communication Technology Engineering Baghdad Iraq School Of Aeronautical Engineering AnYang University Anyang China Medical Technical College Al-Farahidi University Department Of Medical Instrumentation Technical Engineering Baghdad10070 Iraq School Of Computing Skyline University College University City Sharjah Sharjah United Arab Emirates College Of Engineering And Technology University Of Science And Technology Of Fujairah Fujairah United Arab Emirates Khalifa University Centre For Cyber Physical Systems Computer Science Department United Arab Emirates Center For Cyber Security Faculty Of Information Science And Technology Selangor Bangi43600 Malaysia

ISBN: (纸本)9798350394962

The privacy of sensitive data within the Internet of Things (IoT) is at risk due to potential privacy violations. These violations can occur through illegal access by external entities, as well as inadvertent disclosures or intentional attacks by those within the system who exceed their authorized access privileges. Furthermore, there needs to be more control experienced by data owners regarding their sensitive data as it transitions from their domain to other entities within the Internet of Things (IoT) ecosystem. Numerous methods have been presented in the academic literature over the past few years to effectively tackle the privacy concerns associated with the Internet of Things (IoT). This paper aims to classify existing literature by organizing it according to the specific technology or technique employed to safeguard privacy. The classification encompasses four primary areas of privacy solutions, specifically, solutions based on encryption, solutions based on identity management, solutions based on policy enforcement, and solutions focused on self-protection. The paper examines various state-of-the-art solutions within each category. It begins by providing a broad comparison between these solutions and our work. Subsequently, it focuses on a specific comparison of the privacy objectives of the offered PEFM solutions. © 2024 IEEE.

关键词： Internet of things

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Struct2Hair: A hair shape descriptor for hairstyle modeling

Struct2Hair: A hair shape descriptor for hairstyle modeling

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作者： Zhang, Wenshu Nie, Yinyu Guo, Shihui Chang, Jian Zhang, Jianjun Tong, Ruofeng Faculty of Arts and Media Norwich University of the Arts Norfolk United Kingdom The Visual Computing & Artificial Intelligence Lab Technical University of Munich München Germany School of Informatics Xiamen University Fujian China National Centre for Computer Animation Bournemouth University Dorset United Kingdom College of Computer Science and Technology Zhejiang University Zhejiang China

In recent years, it becomes possible to extract hair information for hair reconstruction from multiple cameras or monocular camera. Using a single image as the input avoids the high cost setups and complex calibration compared to multiviewed reconstruction. Taking advantage of an extendible hairstyle database, this paper introduced Struct2Hair, a novel single-viewed hair modelling approach by extracting hair shape descriptor (HSD). The HSD is defined as the fundamental structure-aware feature, which is a combination of critical shapes in a hairstyle. A complete dataset of critical hair shapes is constructed from a known database of three-dimensional (3D) hair models. We first analyze the input two-dimensional (2D) image to extract the orientation information and 2D hair sketch automatically. The extracted information is then used to retrieve the corresponding critical shapes with optimization to build the robust HSD. Finally, the HSD constructs a weighted 3D hair orientation field to guide full-head hair model generation. Our method can preserve local geometric features of hair and retain the whole shape of the hairstyle globally owing to the HSD, which will benefit further hair editing and stylization. © 2022 John Wiley & Sons Ltd.

关键词： Cameras

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Using Business Intelligence Dashboard for Sustainable Urban Water Security Monitoring

Using Business Intelligence Dashboard for Sustainable Urban ...

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2023 IEEE IAS Global Conference on Emerging Technologies, GlobConET 2023

作者： Zainuddin, Zada Yahya, Farashazillah Lin, Wee Bui Fazli, Bashirah Mohd Zulkifli, Harlisa Abdullah, Mohammad Fikry Universiti Malaysia Sabah Faculty of Computing and Informatics Sabah Kota Kinabalu Malaysia Universiti Malaysia Sarawak Faculty of Computer Science and Information Technology Sarawak Malaysia National Water Research Institute of Malaysia Water Quality and Environment Research Centre Selangor Malaysia National Water Research Institute of Malaysia Information Management Division Selangor Malaysia Leeds University Business School University of Leeds Leeds United Kingdom

ISBN: (纸本)9798350331790

This paper presents the findings from the experts on the effective factor of monitoring dashboards for urban water security. The urban water security dashboard monitors the water quality, availability, and other relevant indicators. Although monitoring dashboards exist, there are potential improvements in the context of urban water security. The study integrates the technological factors in the domain area. An expert review is conducted to get confirmation from professionals in the chosen sector about the effective factors for the dashboards from the IT perspective. This methodology uses qualitative via face-to-face and online sessions. Thematic analysis and content validity index (CVI) have been used to evaluate the experts' review. The findings show security and knowledge discovery is the main factor emphasised. The experts deemed visual design the least priority when creating a business intelligence dashboard. Experts also recommend embedding Artificial Intelligence (AI) with the data analysis for dashboards. The discussion identified challenges and future work for this research. The discussion identified three potential areas of future research in water security and informatics: i) investigating other dimensions of effective dashboards, ii) conducting additional research on the environmental dashboard, and iii) investigating dashboards' real-world application in urban water security. © 2023 IEEE.

关键词： Water quality

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Internet of Things: Perspective Path Based Tests in the Heterogeneity Environment

Internet of Things: Perspective Path Based Tests in the Hete...

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IEEE International Conference on Consumer Electronics-Taiwan (ICCE-TW)

作者： Teik-Boon Tan Yiqi Tew Tong-Ming Lim Wai-Khuen Cheng Yen-Lin Chen Faculty of Computing and Information Technlogy Tunku Abdul Rahman University of Management and Technology Kuala Lumpur Malaysia Faculty of Computing and Information Technology Tunku Abdul Rahman University of Management and Technology Kuala Lumpur Malaysia Centre for Business Incubation and Entrepreneurial Ventures Tunku Abdul Rahman University of Management and Technology Kuala Lumpur Malaysia Department of Computer Science Universiti Tunku Abdul Rahman Kampar Malaysia Department of Computer Science and Information Engineering National Taipei University of Technology Taipei Taiwan

ISBN: (数字)9798350386844

ISBN: (纸本)9798350386851

This paper provides an overview of the Internet of Things (IoT) environment and the challenges of conducting tests in such an environment. We provide explanations on challenges specifically on heterogeneous nature and the changes due to scaling that leads to the issue of complexity of tests with needs of combining different components and protocols of the IoT solution. We present the need for improvements as existing methods are only reducing minor irrelevant tests. Lastly, we propose using the perspective path-based tests on IoT architecture in the paper.

关键词： Protocols Logic gates Complexity theory Sensors Internet of Things Consumer electronics

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Ocular Disease Recognition System Using Convolutional Neural Network

Ocular Disease Recognition System Using Convolutional Neural...

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International Conference on Computer Applications and Industrial Electronics (ICCAIE)

作者： Nurul Izzah Fauzi Habibah Ismail Ismail Ahmedy College of Computing Informatics and Mathematics Universiti Teknologi MARA Terengganu Malaysia Centre of Foundation Studies Universiti Teknologi MARA Selangor Malaysia Faculty of Computer Science and Information Technology Universiti Malaya Kuala Lumpur Malaysia

ISBN: (数字)9798350348798

ISBN: (纸本)9798350348804

Glaucoma and diabetic retinopathy are all ocular diseases that can cause significant vision loss and blindness. Early detection and treatment of these diseases is critical for vision preservation and preventing permanent vision damage. In recent years, deep learning techniques have been applied to ocular disease recognition with promising results, however the current system that available predict lower precision and it can lead to the poor decision making by ophthalmologist. Convolutional Neural Networks (CNNs) particularly have been shown to be effective in recognising various ocular diseases from eye images. In this study, CNN was trained with 600 eye images to identify glaucoma and diabetic retinopathy. A supervised learning approach was used to train the model from beginning to end. To increase the model's precision, various image augmentation methods were applied. The outcome demonstrates that, after classification's evaluation, the model managed to obtain 97% accuracy value. In the future, this system can train and validate CNNs using larger datasets, as well as collect and use more diverse datasets of eye fundus images to improve the accuracy of the system.

关键词： Glaucoma Diabetic retinopathy Accuracy Image recognition Transfer learning Medical services Convolutional neural networks

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