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University Students’ Attitudes toward Adoption of Mobile Health Application for Serving Older People

Sensors and Materials 2023年第7期35卷 2581-2601页

作者： Chao, Pei-Ju Cheng, Yu-Huei Liu, Yi-Hui Hsu, Tsu-Hsuan Travel & Tourism Program International College Ming Chuan University 5 De Ming Rd. Gui Shan District Taoyuan333 Taiwan Department of Information and Communication Engineering Chaoyang University of Technology 168 Jifeng E. Rd. Wufeng District Taichung413 Taiwan Department of Senior Citizen Service Management National Taichung University of Science and Technology No. 129 Sec. 3 Sanmin Rd. North District Taichung404 Taiwan Graduate Institute of Rehabilitation Counseling National Changhua University of Education 1 Jin-De Rd. Changhua City500 Taiwan

In this quantitative study, we examined the awareness of mobile health (mHealth) applications among Taiwan’s university students, particularly the government-operated My Health Bank application. The My Health Bank application allows users to access their personal health information simply through their smartphone’s sensor-assisted facial recognition camera and fingerprint sensor. Whether these university students might help older adults to use this application if they perceive it to be helpful was also explored. Two instruments were used in this study, namely, the Perceptions toward My Health Bank (PMHB) and Geriatric Attitudes Scale (GAS). Two hundred twenty-five (225) university students from the Departments of Senior Citizen Service management (n = 136) and Nursing (n = 89) at two universities participated in this study. The findings indicated low adoption of My Health Bank and related mHealth applications among students even though they had high adoption rates of smartphones. However, they perceived that the functions of this application are useful and should be promoted to older adults. Thus, building a basic foundation of mHealth and related technology courses is recommended to assist healthcare students in being well-prepared for working with older adults in the digital society. © MYU K.K.

关键词： mHealth

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Role of Wireless Communications in Digital Economy in the Present Context 6

Role of Wireless Communications in Digital Economy in the Pr...

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6th International Conference on Trends in Electronics and Informatics, ICOEI 2022

作者： Revathi, S. Shrivastava, Arpan Yussupova, Ardak Hidayatulloh, A. Nururrochman Saltanat, Daurbekova Mishra, Arpana Sri Ramakrishna Institute of Technology Department of Computer Science and Engineering Coimbatore India Management Devi Ahilya Vishva Vidyalaya Madhya Pradesh India Kazakh National University of Arts Department of Art Studies Nur-Sultan Kazakhstan Universitas Gadjah Mada Leadership and Policy Innovation Program Indonesia International Education Corporation Department of Construction Almaty050042 Kazakhstan Sharda University Electrical Electronics and Communication Engineering Greater Noida India

ISBN: (纸本)9781665483285

Wireless communication has connected millions of people across the world to internet to enable them to reap benefits of digital economy in present scenario. Almost all the sectors of economy including healthcare, agriculture and transportation nowadays rely largely upon wireless communications. In the present context, the sudden outbreak of Covid-19 has caused governments to impose restrictions on various activities and employees have been directed to work from their homes to ensure safety. In such a situation, wireless communication has made it possible to connect with each other via the internet. Apart from this, Smart healthcare-system has been developed through utilisation of wireless communication systems. During this pandemic situation, delivery of healthcare services in remote areas has gained huge momentum and wireless communication plays a vital role in this regard. Aim of current critical assessment is to provide an in-depth analysis of the role played by wireless communication in establishment of a well-structured digital economy in present scenario. In literature-review, different applications of wireless technology via ICT in various sectors and aspects of life have been discussed through a conceptual and a theoretical framework. The Method section of current study has provided an in-depth insight into the ways required information have been collected in this study. As found in the results and discussion section, a positive relation exists between wireless-communication and establishment of digital economy in current situation. This study has concluded that there are certain challenges associated with wireless communication;however, it has significant influence in making processes smarter and faster as compared to earlier. © 2022 IEEE.

关键词： Internet of things

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Enhanced Performance and Data Privacy in Lung Nodule Classification via Federated Deep Learning Approach 24

Enhanced Performance and Data Privacy in Lung Nodule Classif...

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2024 7th International Conference on Healthcare Service management, ICHSM 2024

作者： Nguyen, Duc-Khanh Li, Ai-Hsien Adam Lai, Yen-Jun Chiu, Yen-Ling Phan, Dinh-Van Chien, Ting-Ying Chan, Chien-Lung Department of Information Management Yuan Ze University Taoyuan Taiwan Department of Statistics and Informatics University of Economics The University of Danang Danang Viet Nam Division of Cardiology Far Eastern Memorial Hospital New Taipei Taiwan Graduate Program in Biomedical Informatics Yuan Ze University Taoyuan Taiwan Department of Radiology Far Eastern Memorial Hospital New Taipei Taiwan Graduate Institute of Medicine and Graduate Program in Biomedical Informatics Yuan Ze University Taoyuan Taiwan Department of Medical Research Far Eastern Memorial Hospital New Taipei Taiwan Department of Computer Science and Engineering Yuan Ze University Taoyuan Taiwan ZDT Group- YZU Joint Research and Development Center for Big Data Taoyuan Taiwan Yuan Ze University Taoyuan Taiwan

ISBN: (纸本)9798400710162

This study explores the feasibility of deep learning for classifying nodule neoplasms, analyzing their performance on two openly available datasets, LUNGx SPIE, and LIDC-IDRI. These datasets offer valuable diversity in image quantity, quality, and malignancy annotation methodologies, posing a real-world challenge for effective model development. To handle the disparities in these diverse datasets, we aim to develop a robust classification model trained using federated learning. This decentralized approach allows model training across datasets without sharing patient data, preserving privacy and overcoming data fragmentation. Our experiments demonstrate that federated learning enables the development of a robust and superior deep learning model compared to individual models trained on limited data. This combination of deep learning, and federated learning holds immense promise for nodule neoplasm classification and can significantly improve patient care and outcomes. © 2024 Copyright held by the owner/author(s).

关键词： Federated learning

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A Study on the Application Design of Soil Moisture Diffusion and Crop Roots According to Subsurface Irrigation Method

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Journal of Biosystems engineering 2021年第3期46卷 197-205页

作者： Kim, Jin Hyun Kim, Tae Wook Kim, Seol Ha Lee, Hwang Gyu Eum, Duk Ho Lee, Sang Hun Department of Precision Mechanical Engineering Kyungpook National University Sangju37224 Korea Republic of Young Engineering Education Program for Multidisciplinary Smart Disaster Management Kyungpook National University Sangju37224 Korea Republic of Nam Kyung Co. Ltd. 497-48 Chorok-Ro Yanggam-Myeon Gyeonggido 445-932 Hwaseong18626 Korea Republic of Department of Southern Area Crop Science National Institute of Crop Science Rural Development Administration Miryang50424 Korea Republic of

Purpose: Global climate change has increased drought frequency and caused significant damage to agricultural industries worldwide;for example, soybean yield has decreased by 30% on small-scale farms. Therefore, the development of subsurface irrigation methods, which conserve both water and labor, is urgently needed for open-field cropping systems. Although water and nutrient supply through subsurface irrigation shows clear advantages, the specific design of these irrigation systems relies on empirical data rather than systematic research and practical optimization. Because of irregularities and uncertainties in field soil conditions, the theoretical approach for water diffusion in soil frequently could give a wrong range of data to an irrigation system. In this study, the water diffusion by means of a commercial subsurface irrigation system has been experimentally tested in several soil types to get practical application and understand the water diffusion performance. Methods: In the present study, to better understand the shape of the subsurface diffusion plume in an open-field soybean crop during irrigation, we supplied 4 L of water through 3 mm vertical tubes using three types of dripper, at transfer rates of 2, 4, and 8 L/h. A map of the wetted soil near the dripper showed that the optimal water supply depends on the growth stage of the soybeans. Results: Subsurface irrigation testing was conducted on well-graded sand containing clay (SWC: sand well + sand clay) and poorly graded sand (SP: sand plastic). As both SWC and SP showed that the wetted area rises well upward to the ground surface from the dripping point with 2 L/h supply, it is considered that 2 L/h case is effective for water absorption by the roots of the crops. Besides, the size of the grown root of 30 days showed 450 mm of width and 300 mm of depth, so it was estimated that 150 mm wide and 100 mm deep after 10 days, and 300 mm wide and 200 mm deep after 20 days. Judging from the results of the root

关键词： Soil moisture

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Development and Validation of Customer Intention Factors for Live-Stream Shopping

Development and Validation of Customer Intention Factors for...

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Conference on New Media Studies (CoNMedia)

作者： Erick Fernando Desman Hidayat Christian Haposan Pengaribuan Yulius Denny Prabowo Department of Information System Faculty of Engineering and Informatics Universitas Multimedia Nusantara Tangerang Indonesia Management Department BINUS Entrepreneurship Center Bina Nusantara University Jakarta Indonesia Management Study Program Faculty of Business Sampoerna University Jakarta Indonesia Computer Science Department Binus Online Learning Bina Nusantara University Jakarta Indonesia

Along with technological improvements, online shopping is currently developing quickly. Online shops started by selling electronics, clothing, food, and home appliances and continue to evolve, selling various things. Currently, digital marketing has a novel technique, namely live shopping, where sellers can present, promote and offer their products directly through live streaming on social media and e-commerce platforms. This research will focus on gaining insight into the factors influencing customers to watch and purchase through live streaming. This research is an early-stage study of exploring and searching for research models. The study used a literature review approach by reviewing similar previous research articles. Several variable components were used in this study. The findings of the factors include visibility capacity, meta-vocation capacity, purchase orientation capacity, social presence, price, perceived product quality, perceived enjoyment, purchase orientation, perceived usefulness, and intention to buy. These factors were tested and proved to be valid with Cronbach's Alpha value being more than 0.5 and reliable with the value of the loading factor a greater than 0.6. Criteria The factors of the findings for further analysis of the relationship between factors and other variables.

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The inquiries for efficient decarbonization in the Indonesian upstream oil and gas field

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Case Studies in Chemical and Environmental engineering 2024年 9卷

作者： Iswara, Aditya Prana Chiang Hsieh, Lin-Han Abbas, Shahbaz Dermawan, Denny Kristianto, Sonny Department of Disaster Management Postgraduate School Universitas Airlangga Surabaya Indonesia Institute of Environmental Engineering & Management National Taipei University of Technology Taipei Taiwan Department of Engineering Management College of Electrical and Mechanical Engineering National University of Sciences and Technology Islamabad Pakistan Waste Treatment Engineering Study Program Shipbuilding Institute of Polytechnic Surabaya Jalan Teknik Kimia Kampus ITS Sukolilo Surabaya Indonesia Waste Treatment Engineering Laboratory Shipbuilding Institute of Polytechnic Surabaya Jalan Teknik Kimia Kampus ITS Sukolilo Surabaya Indonesia Department of Forensic Science Postgraduate School Universitas Airlangga Surabaya 60115 Indonesia

The mandatory carbon reduction guidelines and regulations in Indonesia encourage all industrial sectors particularly the petroleum industry to implement decarbonization programs by systematically reducing carbon emissions as part of climate action. Unlike existing carbon emission studies in the petroleum industry, the literature lacks studies on the decarbonization patterns. In addition, the effectiveness of carbon mitigation in the upstream oil and gas field has not been studied so far. This study developed short panel data models to understand the current decarbonization efforts and patterns during 2015–2018. The results indicate that the considered variables are significantly impactful in carbon reduction with different coefficient patterns. It is suggested to associate decarbonization with oil and gas production and highlight energy efficiency optimization to stabilize production. The impact of financial, human, and administrative resources on the supporting facility is critical for executing sustainable carbon mitigation projects. © 2024 The Authors

关键词： Carbon reduction Climate action Decarbonization patterns Mitigation strategies Petroleum industry

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A Novel Hybrid Framework for Energy-Efficient Clustering and Routing in Heterogeneous IoT-Driven Wireless Sensor Networks

A Novel Hybrid Framework for Energy-Efficient Clustering and...

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International Conference on Contemporary Computing and Informatics (IC3I)

作者： Gopal Kumar Gupta Arpit Jain Khemraj Sharma P. M. Ashok Kumar Shubhi Gupta Sheenu Agarwal Symbiosis Institute Of Technology Nagpur Campus Symbiosis International (Deemed University) Pune India Department of Computer Science Engineering Koneru Lakshmaiah Education Foundation Vaddeswaram AP India Department of Business Administration Doctoral Program in Management Sciences NANHUA UNIVERSITY Dalin Chiayi R.O.C Department of Computer Science and Engineering Amity University Greater Noida Uttar Pradesh India Department of Electronics and Communication Engineering Uttarakhand Technical University Dehradun U.K. India

ISBN: (数字)9798350350067

ISBN: (纸本)9798350350074

Smart computing has been particularly notable in the development of wireless sensor networks (WSNs), which have many applications. Battery-powered, self-configuring sensor nodes are the basis of these networks. Energy and resources are limited when it comes to sensors. Unbalanced nodes in the network consume more power, which adversely affects the network’s lifespan. An improved energy-efficient cluster-based routing protocol for heterogeneous wireless sensor networks (WSNs) based on the Internet of Things is proposed in this study. Several performance metrics were used to evaluate the proposed model’s effectiveness, including energy efficiency, alive nodes, dead nodes, network lifetime, and residual energy. The results of the comparison were compared with existing methodologies, such as LEACH, PSO, and hybrid PSO. The proposed approach outperforms the existing model by a substantial margin in networks with 50 and 100 nodes, according to the simulation results.

关键词： Wireless communication Measurement Wireless sensor networks Simulation Heuristic algorithms Routing Energy efficiency Routing protocols Internet of Things Informatics

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ECG signals-based security and steganography approaches in WBANs: A comprehensive survey and taxonomy

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Sustainable Computing: Informatics and Systems 2024年 41卷

作者： Masdari, Mohammad Band, Shahab S. Qasem, Sultan Noman Sayed, Biju Theruvil Pai, Hao-Ting Department of Computer Engineering Urmia Branch Islamic Azad University Urmia Iran Future Technology Research Center National Yunlin University of Science and Technology Douliu Taiwan Department of Information Management International Graduate School of Artificial Intelligence National Yunlin University of Science and Technology Taiwan Riyadh11432 Saudi Arabia Computer Science Department Faculty of Applied Science Taiz University Taiz6803 Yemen Department of Computer Science Dhofar University PO Box 2509 SalalahPCode 211 Oman Bachelor Program of Big Data Applications in Business National Pingtung University Pingtung Taiwan

Wireless Body Area Networks (WBANs) are integral components of e-healthcare systems, responsible for monitoring patients' physiological states through intelligent implantable or wearable sensor nodes. These nodes collect medical data, which is then transmitted to remote healthcare facilities for thorough evaluation. Securing medical data within WBANs is paramount due to its central role in preserving patient privacy and confidentiality. Notably, Electrocardiogram (ECG) signals have recently gained prominence as pivotal elements within diverse security frameworks. Incorporating ECG signals strategically enhances the security and reliability of WBANs and broader e-healthcare systems, instilling greater trustworthiness. This survey article provides an in-depth exploration of contemporary ECG-based security schemes, adding to the scholarly discourse. The imperative to categorize these security paradigms revolves around their use of ECG signals. This categorization identifies three key domains: the first involves schemes that utilize ECG signals for cryptographic operations, encompassing key generation, agreement, management, and authentication. The second category employs steganography-based techniques, using ECG signals to conceal patients' sensitive medical data. The third category focuses on enhancing ECG signal security during data transmission. Each category is meticulously elaborated, detailing architectural foundations, notable contributions, and intrinsic security services. Furthermore, each section presents a comprehensive overview of the attributes characterizing ECG-based security frameworks. This includes insights into employed datasets, simulation environments, evaluation metrics, and inherent advantages and limitations. Expanding on this, a thorough analysis of distinctive attributes underpinning these security frameworks concludes by shedding light on potential directions for future research. © 2023 Elsevier Inc.

关键词： Authentication

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Effective Tumor Annotation for Automated Diagnosis of Liver Cancer

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IEEE Journal of Translational engineering in Health and Medicine 2025年 13卷 251-260页

作者： Chuang, Yi-Hsuan Su, Ja-Hwung Lin, Tzu-Chieh Cheng, Hue-Xin Shen, Pin-Hao Ou, Jin-Ping Han, Ding-Hong Liao, Yi-Wen Lee, Yeong-Chyi Cheng, Yu-Fan Hong, Tzung-Pei Li, Katherine Shu-Min Lu, Yi Wang, Chih-Chi Kaohsiung Chang Gung Memorial Hospital Chang Gung University College of Medicine Liver Transplantation Program Departments of Diagnostic Radiology Niao-Sung District Kaohsiung 833401 Taiwan National University of Kaohsiung Department of Computer Science and Information Engineering Kaohsiung 811 Taiwan National Sun Yat-sen University Department of Computer Science and Engineering Kaohsiung 804 Taiwan National Kaohsiung University of Science and Technology Department of Intelligent Commerce Kaohsiung 824004 Taiwan Cheng Shiu University Department of Information Management Kaohsiung 833301 Taiwan Liver Transplantation Center Department of Surgery Kaohsiung Chang Gung Memorial Hospital Niao-Sung District Kaohsiung 833401 Taiwan

In recent years, visual cancer information retrieval using Artificial Intelligence has been shown to be effective in diagnosis and treatment. Especially for a modern liver-cancer diagnosis system, the automated tumor annotation plays a crucial role. So-called tumor annotation refers to tagging the tumor in Biomedical images by computer vision technologies such as Deep Learning. After annotation, the tumor information such as tumor location, tumor size and tumor characteristics can be output into a clinical report. To this end, this paper proposes an effective approach that includes tumor segmentation, tumor location, tumor measuring, and tumor recognition to achieve high-quality tumor annotation, thereby assisting radiologists in efficiently making accurate diagnosis reports. For tumor segmentation, a Multi-Residual Attention Unet is proposed to alleviate problems of vanishing gradient and information diversity. For tumor location, an effective Multi-SeResUnet is proposed to partition the liver into 8 couinaud segments. Based on the partitioned segments, the tumor is located accurately. For tumor recognition, an effective multi-labeling classifier is used to recognize the tumor characteristics by the visual tumor features. For tumor measuring, a regression model is proposed to measure the tumor size. To reveal the effectiveness of individual methods, each method was evaluated on real datasets. The experimental results reveal that the proposed methods are more promising than the state-of-the-art methods in tumor segmentation, tumor measuring, tumor localization and tumor recognition. Specifically, the average tumor size error and the annotation accuracy are 0.432 cm and 91.6%, respectively, which suggest potential for reducing radiologists’ workload. In summary, this paper proposes an effective tumor annotation for an automated diagnosis support system. © 2013 IEEE.

关键词： Liver cancer diagnosis liver tumor location liver tumor measuring liver tumor recognition liver tumor segmentation

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Deep Learning in Smart Healthcare: A GAN-based Approach for Imbalanced Alzheimer's Disease Classification

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Procedia Computer science 2024年 241卷 146-153页

作者： Hina Tufail Abdul Ahad Ira Puspitasari Ibraheem Shayea Paulo Jorge Coelho Ivan Miguel Pires Department of Computer Science University of Management and Technology Sialkot Pakistan Information System Study Program Faculty of Science and Technology Universitas Airlangga School of Software Northwestern Polytechnical University Xian Shaanxi P.R. China Department of Electronics and Communication Engineering Istanbul Technical University(ITU) Turkey Polytechnic University of Leiria Leiria Portugal Institute for Systems Engineering and Computers at Coimbra (INESC Coimbra) Coimbra Portugal Instituto de Telecomunicações Escola Superior de Tecnologia e Gestão de Águeda Universidade de Aveiro Águeda Portugal

Alzheimer's disease (AD) is a type of dementia that leads to memory loss and impairment, which afects patients’ lives badly. It is not curable yet, but its progression can be slowed down if detected at earlier stages. In this research study, we propose a transfer learning-based convolutional neural network (CNN) model to classify magnetic resonance imaging (MRI) into one of four stages of Alzheimer's disease. One of the major limitations of the deep learning-based classification model is the non-availability of healthcare datasets related to AD. The widely used Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset has a major class imbalance issue. We propose a generative adversarial network (GAN) based data augmentation technique to overcome the data imbalance. This promotes the investigation of applying GANs to generate synthetic samples for minority classes in Alzheimer's disease datasets to enhance classification performance. The results show the progression in the overall classification process of AD.

关键词： Alzheimer disease (AD) Deep learning Convolutional Neural Network (CNN) Computer-aided diagnosis (CAD)

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