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An Architecture Supporting Intelligent Mobile Healthcare Using Human-Computer Interaction HCI Principles

Computer systems Science & engineering 2022年第2期40卷 557-569页

作者： Mesfer Alrizq Shauban Ali Solangi Abdullah Alghamdi Muhammad Ali Nizamani Muhammad Ali Memon Mohammed Hamdi College of Computer Science and Information Systems Najran UniversityNajranSaudi Arabia Faculty of Engineering&Technology University of SindhJamshoro78060Pakistan

Recent advancements in the Internet of Things IoT and cloud computing have paved the way for mobile Healthcare(mHealthcare)services.A patient within the hospital is monitored by several ***,upon leaving the hospital,the patient can be remotely monitored whether directly using body wearable sensors or using a smartphone equipped with sensors to monitor different user-health *** raises potential challenges for intelligent monitoring of patient's *** this paper,an improved architecture for smart mHealthcare is proposed that is supported by HCI design *** HCI also provides the support for the User-Centric Design(UCD)for smart mHealthcare ***,the HCI along with IoT's(Internet of Things)5-layered architecture has the potential of improving User Experience(UX)in mHealthcare design and help saving *** intelligent mHealthcare system is supported by the IoT sensing and communication layers and health care providers are supported by the application layer for the medical,behavioral,and health-related *** care providers and users are further supported by an intelligent layer performing critical situation assessment and performing a multi-modal communication using an intelligent *** HCI design focuses on the ease-of-use,including user experience and safety,alarms,and error-resistant displays of the end-user,and improves user's experience and user satisfaction.

关键词： Human computer interaction mhealthcare user-centric design sensor network nternet-of-things

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Identification of spalling in concrete structures by a hammering test using autoencoder 8th

Identification of spalling in concrete structures by a hamme...

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8th International Symposium on Life-Cycle Civil engineering, IALCCE 2023

作者： Emoto, Hisao Fukui, Nobuki Iitaka, Yuto Kanazawa, Shin-Ichi Social Systems and Civil Engineering Tottori University Tottori-City Japan Industrial Technology and Systems Engineering Fukushima College Iwaki-City Japan Civil Engineering Program Faculty of Engineering Niigata University Niigata-City Japan

ISBN: (纸本)9781003323020

Visual inspection of bridges is important to maintain the sustainability of civil infrastructure. A hammering test is one of the non-destructive and verified methods used for this purpose, by which an expert inspector identifies spalling inside a concrete structure. The reliability of this method depends on the technique of the inspector. However, Japan society faces the problem of a scarcity of labor across all fields. Because of this, there are few training opportunities for new inspectors to learn the technique. This study aims to identify spalling concrete by using an autoencoder, instead of professional inspectors. First, a spalled concrete specimen was used to record the hammering sounds. The experimental method and a comparison of frequency spectra at each level of damage were described. Next, the autoencoder was applied to identify spalling concrete, and a comparison of the identification precision at each damage level was conducted. The results of the analysis show that spalling concrete can be identified by autoencoder to a concrete thickness of less than 30 mm. © 2023 The Author(s).

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Solvent effects on the measured bubble-point pressures and pseudo bubble-point pressures of different heavy crude oil-solvent systems

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Petroleum 2022年第4期8卷 577-586页

作者： Jiangyuan Yao Wei Zou Yongan Gu Petroleum Technology Research Centre(PTRC) Petroleum Systems EngineeringFaculty of Engineering and Applied ScienceUniversity of ReginaReginaS4S 0A2Canada

In this paper,the bubble-point pressures and pseudo bubble-point pressures of various heavy crude oil-solvent systems were measured and studied by conducting the constant-composition-expansion(CCE)tests,during which the test pressure was depleted in a stepwise manner.A total of fourteen CCE tests were performed for five heavy crude oil-CO_(2)systems,four heavy crude oil-CH_(4)systems,and five heavy crude oil-C_(3)H_(8)systems,*** the CCE tests were conducted by using a pressure-volume-temperature(PVT)*** was found that for most heavy crude oil-solvent systems with relatively low solvent concentrations,the measured PVT cell pressure *** volume(Pcell-nmix)data in the CCE tests had three distinct regions,which were one-liquid phase region(Regions I),foamy-oil region(Region II)and two-phase region(Region III).Accordingly,the PVT cell pressure at the intersection point of Regions I and II was referred to as the measured bubble-point pressure,whereas the PVT cell pressure at the intersection point of Regions II and III was termed as the measured pseudo bubble-point *** some heavy crude oil-solvent systems with high solvent concentrations,however,the measured Pcell-nmix data may have two regions *** this special case,the PVT cell pressure at the intersection point of the two regions was considered as the measured bubble-point pressure and no pseudo bubble-point pressure could be *** was also found that the heavy crude oil-CH_(4)system had not only the highest bubble-point pressure and pseudo bubble-point pressure but also the largest difference between the bubble-point pressure and pseudo bubble-point pressure,in comparison with the heavy crude oil-CO_(2)system and the heavy crude oil-C_(3)H_(8)system at the same solvent *** facts indicate that CH_(4)not only is the most volatile solvent but also can remain as dispersed gas bubbles to induce the most stable foamy oil in the largest pressure range after it is nucl

关键词： Heavy crude oil-solvent systems Phase behaviours PVT studies Constant-composition-expansion(CCE)tests Bubble-point pressure Pseudo bubble-point pressure

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Universality class of machine learning for critical phenomena

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Science China(Physics,Mechanics & Astronomy) 2023年第12期66卷 63-70页

作者： Gaoke Hu Yu Sun Teng Liu Yongwen Zhang Maoxin Liu Jingfang Fan Wei Chen Xiaosong Chen School of Systems Science and Institute of Nonequilibrium Systems Beijing Normal UniversityBeijing 100875China Data Science Research Center Faculty of ScienceKunming University of Science and TechnologyKunming 650500China State Key Laboratory of Multiphase Complex Systems Institute of Process EngineeringChinese Academy of SciencesBeijing 100190China University of Chinese Academy of Sciences Beijing 100049China

Herein,percolation phase transitions on a two-dimensional lattice were studied using machine learning *** reveal that different phase transitions belonging to the same universality class can be identified using the same neural networks(NNs),whereas phase transitions of different universality classes require different *** on this finding,we proposed the universality class of machine learning for critical ***,we investigated and discussed the NNs of different universality *** research contributes to machine learning by relating the NNs with the universality class.

关键词： universality class machine learning percolation

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Surface adhesion enhancement of A5052 aluminum alloy by surface texturing with a UV pulsed laser

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Keikinzoku/Journal of Japan Institute of Light Metals 2024年第1期74卷 18-21页

作者： Kuwano, Ryoichi Hino, Makoto Tokunaga, Tsuyoshi Nagata, Norihito Koga, Toshihiko Hagen, Nathan Otani, Yukitoshi Department of Mechanical Systems Engineering Faculty of Engineering Hiroshima Institute of Technology 2-1-1 Miyake Saeki-ku Hiroshima-shi Hiroshima731-5193 Japan Department of Innovative Mechanical and Electronic Engineering Faculty of Engineering Chiba Institute of Technology Narashino-shi Chiba Japan SURTECH NAGATA Co. Ltd. Akashi-shi Hyogo Japan Department of Mechanical Engineering Undergraduate course in Bachelor of Science in Manufacturing Technology Polytechnic University Kodaira-shi Tokyo Japan Center for Optical Research and Education（CORE） Utsunomiya University Utsunomiya-shi Tochigi Japan

We subjected an A5052 aluminum alloy sample to a dry and rapid surface treatment using 355-nm pulsed laser irradiation, and measured the effects of surface modification. We varied the laser irradiation pitch and found the processed surfaces to have an irregular and complicated topography up to a depth of about 5 μm. X-ray photoelectron spectroscopy (XPS) analysis of the material surfaces revealed that Al2O3 with a binding energy of 74 eV was formed regardless of laser irradiation, and that increased irradiation density accelerates surface oxidation. While the non-laser-irradiated areas exhibited hydrophobicity, laser-irradiated regions became superhydrophilic with a contact angle of less than 5°. We performed tensile shear tests on lap joint specimens produced at a beam scanning speed of 500 mm/s and a laser irradiation pitch of 5 μm, and obtained a joint strength of 10 MPa. These results indicate that UV pulsed laser irradiation is effective for fast surface modification. © 2024 The Japan Institute of Light Metals.

关键词： Aluminum oxide

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Amina: an Arabic multi-purpose integral news articles dataset

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Neural Computing and Applications 2024年第35期36卷 22149-22169页

作者： Zaytoon, Mohamed Bashar, Muhannad Khamis, Mohamed A. Gomaa, Walid Faculty of Engineering Alexandria University Alexandria21544 Egypt Egypt-Japan University of Science and Technology Alexandria New Borg El-Arab City21934 Egypt AI Unit Ejada Systems Ltd Alexandria Egypt Faculty of Computers and Data Science Alexandria National University Alexandria Egypt

Electronic newspapers are one of the most common sources of Modern Standard Arabic. Existing datasets of Arabic news articles typically provide a title, body, and single label. Ignoring important features, like the article author, image, tags, and publication date, can degrade the efficacy of classification models. In this paper, we propose the Arabic multi-purpose integral news articles (AMINA) dataset. AMINA is a large-scale Arabic news corpus with over 1,850,000 articles collected from 9 Arabic newspapers from different countries. It includes all the article features: title, tags, publication date and time, location, author, article image and its caption, and the number of visits. To test the efficacy of the proposed dataset, three tasks were developed and validated: article textual content (classification and generation) and article image classification. For content classification, we experimented the performance of several state-of-the-art Arabic NLP models including AraBERT and CAMeL-BERT, etc. For content generation, the reformer architecture is adopted as a character text generation model. For image classification applied on Al-Sharq and Youm7 news portals, we have compared the performance of 10 pre-trained models including ConvNeXt, MaxViT, ResNet18, etc. The overall study verifies the significance and contribution of our newly introduced Arabic articles dataset. The AMINA dataset has been released at https://***/datasets/MohamedZayton/AMINA. © The Author(s) 2024.

关键词： Newsprint

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A Monitoring Strategy of Multi-Robot systems in Dynamic Environments: Coverage Control and Density Estimation 11

A Monitoring Strategy of Multi-Robot Systems in Dynamic Envi...

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11th RSI International Conference on Robotics and Mechatronics, ICRoM 2023

作者： Kaviri, Samane Tahsiri, Ahmadreza Taghirad, Hamid D. K.N. Toosi University of Technology Faculty of Electrical Engineering Department Od Systems and Control Tehran Iran

ISBN: (纸本)9798350308105

A critical task in environmental monitoring is the reconstruction of the density function of an event over the mission region. In such tasks, Unmanned Aerial Vehicles (UAVs) are employed as spatially distributed mobile sensing agents. In this paper, we consider the cooperative coverage problem for a group of UAVs in the mission region with a time-varying density function. The density function is modeled by a Gaussian Mixture Model (GMM) with unknown parameters. By resorting to a consensus-based Expectation-Maximization (EM) approach, the GMM parameters are estimated based on the local observations of UAVs. Finally, the proposed strategy is applied to an offshore oil spill monitoring mission. The simulation results verify the theoretical results and demonstrate the competence of the proposed strategy for such applications. © 2023 IEEE.

关键词： Multipurpose robots

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Predicting Energy Consumption Using Stacked LSTM Snapshot Ensemble

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Big Data Mining and Analytics 2024年第2期7卷 247-270页

作者： Mona Ahamd Alghamdi Abdullah S.A.L-Malaise AL-Ghamdi Mahmoud Ragab Information Systems Department Faculty of Computing and Information Technology(FCIT)King Abdulaziz University(KAU)Jeddah 21589Kingdom of Saudi Arabia Information Systems Department FCITKAUJeddah 21589Kingdom of Saudi Arabiaand also with School of EngineeringComputing and DesignDar Al-Hekma UniversityJeddah 22246Kingdom of Saudi Arabia Information Technology Department FCITKAUJeddah 21589Kingdom of Saudi Arabiaand also with Mathematics DepartmentFaculty of ScienceAl-Azhar UniversityNaser City 11884Egypt

The ability to make accurate energy predictions while considering all related energy factors allows production plants,regulatory bodies,and governments to meet energy demand and assess the effects of energy-saving *** energy consumption falls within normal parameters,it will be possible to use the developed model to predict energy consumption and develop improvements and mitigating measures for energy *** objective of this model is to accurately predict energy consumption without data limitations and provide results that are easily *** proposed model is an implementation of the stacked Long Short-Term Memory(LSTM)snapshot ensemble combined with the Fast Fourier Transform(FFT)and *** and Berard’s Individual Household Electric-Power Consumption(IHEPC)dataset incorporated with weather data are used to analyse the model’s accuracy with predicting energy *** model is trained,and the results measured using Root Mean Square Error(RMSE),Mean Absolute Error(MAE),Mean Absolute Percentage Error(MAPE),and coefficient of determination(R^(2))metrics are 0.020,0.013,0.017,and 0.999,*** stacked LSTM snapshot ensemble performs better than the compared models based on prediction accuracy and minimized *** results of this study show that prediction accuracy is high,and the model’s stability is high as *** model shows that high levels of accuracy prove accurate predictive ability,and together with high levels of stability,the model has good interpretability,which is not typically accounted for in ***,this study shows that it can be inferred.

关键词： energy consumption prediction Artificial Intelligence(AI) Deep Learning(DL) snapshot ensemble

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Patterns for Improving User Contribution 28

Patterns for Improving User Contribution

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28th European Conference on Pattern Languages of Programs, EuroPLoP 2023

作者： Haiderzai, Mohammad Daud Vranic, Valentino Institute of Informatics Information Systems and Software Engineering Faculty of Informatics and Information Technologies Slovak University of Technology Bratislava Slovakia

ISBN: (纸本)9798400700408

User contributions is an important part in software development, the pursuit of identifying effective means of user contributions in software development is a crucial area of interest for software companies and their development teams. Determining the most opportune moments, locations, and methods for such contributions presents a significant challenge for organizations, which necessitates the exploration of generic and proven solutions. Applying patterns, established and observed solutions may provide the answers to such challenges and similar ones. This paper offers insights into the practical implementation of seven newly discovered organizational patterns in a real-life environment. The patterns are comprehensively described, accompanied by illustrative examples, and subsequently applied in actual practices. © 2023 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： Software design

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A morphological word embedding for Arabic language 6

A morphological word embedding for Arabic language

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6th International Conference on AI in Computational Linguistics, ACLing 2024

作者： Masbah, Abdelouahab Ababou, Nabil Mazroui, Azzedine Computer Science Research Laboratory Faculty of Sciences Mohammed First University Oujda Morocco Systems Engineering Laboratory Faculty of Science and Technology Sultan Moulay Slimane University Beni Mellal Morocco

Word embedding is a technique for representing words as dense real vectors and is crucial for most natural language processing tasks. Common approaches include non-contextual embeddings such as Word2vec and contextual embeddings like BERT, both of which operate on the principle that words appearing in similar contexts have close vector representations. Despite their effectiveness, these methods often fail to capture some morphological information useful in many natural language processing applications. In this study, we propose an original word embedding of Arabic words based on the morphological characteristics of the words. Tests show that integrating this morphology-based word embedding into a topic detection model outperforms models using Word2vec or AraBERT embeddings. © 2024 Elsevier B.V.. All rights reserved.

关键词： Embeddings

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