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Correction to: Deep learning-based elderly gender classification using Doppler radar Pers. Ubiquitous Comput. (IF 2.0) Pub Date : 2021-04-08 ZhiChen Wang, Zelin Meng, Kenshi Saho, Kazuki Uemura, Naoto Nojiri, Lin Meng
A Correction to this paper has been published: https://doi.org/10.1007/s00779-021-01555-y
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BHE-AC: a blockchain-based high-efficiency access control framework for Internet of Things Pers. Ubiquitous Comput. (IF 2.0) Pub Date : 2021-04-08 Baobao Chai, Biwei Yan, Jiguo Yu, Guijuan Wang
In this information age, with the emergence of organizations, the number of various resources on the Internet of Things is also increasing. Generally, different users have different access permissions to different resources and most of the existing schemes have realized access control. But most of them are rough and not feasible in many organizations. Moreover, traditional access control schemes adopted
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Captioning model based on meta-learning using prior-convergence knowledge for explainable images Pers. Ubiquitous Comput. (IF 2.0) Pub Date : 2021-04-06 Ji-Won Baek, Kyungyong Chung
Big data has a variety of data types, including image and text. In particular, image data-based research on face recognition and objection detection has been conducted in diverse areas. Deep learning needs a massive amount of data for learning a model accurately. The amount of data collected is different in each area, and thus it is likely to lack data for analysis through deep learning. Accordingly
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The role of self-efficacy on the adoption of information systems security innovations: a meta-analysis assessment Pers. Ubiquitous Comput. (IF 2.0) Pub Date : 2021-03-31 Mumtaz Abdul Hameed, Nalin Asanka Gamagedara Arachchilage
Self-efficacy is the most frequently examined attribute in the adoption of Information Systems (IS) security innovations. Yet, the role of self-efficacy in the adoption of IS security innovations is ambiguous. The empirical studies that examined the factor have produced mixed and inconsistent results. Through a meta-analysis of 59 extant research, the study aggregated findings of the past research
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Forecasting major impacts of COVID-19 pandemic on country-driven sectors: challenges, lessons, and future roadmap Pers. Ubiquitous Comput. (IF 2.0) Pub Date : 2021-03-26 Saket Kumar, Rajkumar Viral, Vikas Deep, Purushottam Sharma, Manoj Kumar, Mufti Mahmud, Thompson Stephan
The pandemic caused by the coronavirus disease 2019 (COVID-19) has produced a global health calamity that has a profound impact on the way of perceiving the world and everyday lives. This has appeared as the greatest threat of the time for the entire world in terms of its impact on human mortality rate and many other societal fronts or driving forces whose estimations are yet to be known. Therefore
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Bringing proxemics to walker-assisted gait: using admittance control with spatial modulation to navigate in confined spaces Pers. Ubiquitous Comput. (IF 2.0) Pub Date : 2021-03-25 Mario F. Jiménez, Wandercleyson Scheidegger, Ricardo C. Mello, Teodiano Bastos, Anselmo Frizera
Smart walkers may be used to assist human navigation. However, social conventions and human behavior should be taken into consideration to allow their interaction with other people. This paper presents a navigation strategy for a smart walker with social conventions defined by proxemics, which uses an admittance controller to generate haptic and visual signals for a safe navigation within a corridor
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Correction to: Diagnosis and combating COVID-19 using wearable Oura smart ring with deep learning methods Pers. Ubiquitous Comput. (IF 2.0) Pub Date : 2021-03-23 M. Poongodi, Mounir Hamdi, Mohit Malviya, Ashutosh Sharma, Gaurav Dhiman, S. Vimal
A Correction to this paper has been published: https://doi.org/10.1007/s00779-021-01553-0
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MSDP: multi-scheme privacy-preserving deep learning via differential privacy Pers. Ubiquitous Comput. (IF 2.0) Pub Date : 2021-03-21 Kwabena Owusu-Agyemeng, Zhen Qin, Hu Xiong, Yao Liu, Tianming Zhuang, Zhiguang Qin
Human activity recognition (HAR) generates a massive amount of the dataset from the Internet of Things (IoT) devices, to enable multiple data providers to jointly produce predictive models for medical diagnosis. That the accuracy of the models is greatly improved when trained on a large number of datasets from these data providers on the untrusted cloud server is very significant and raises privacy
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Aerial image super-resolution based on deep recursive dense network for disaster area surveillance Pers. Ubiquitous Comput. (IF 2.0) Pub Date : 2021-03-19 Feiqiang Liu, Qiang Yu, Lihui Chen, Gwanggil Jeon, Marcelo Keese Albertini, Xiaomin Yang
Aerial images are often applied into disaster area surveillance. High-resolution (HR) aerial images are preferred to monitor the disaster area since they can provide abundant information. However, limited by hardware device and imaging environment, the resolution of captured aerial images may not meet the needs of practical application. Image super-resolution (SR) is an effective way to improve the
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Enhanced BB84 quantum cryptography protocol for secure communication in wireless body sensor networks for medical applications Pers. Ubiquitous Comput. (IF 2.0) Pub Date : 2021-03-18 Anusuya Devi V, Kalaivani V
Wireless body sensor network (WBSN) is an interdisciplinary field that could permit continuous health monitoring with constant clinical records updates through the Internet. WBAN is a special category of wireless networks. Coronavirus disease 2019 (COVID-19) pandemic creates the situation to monitor the patient remotely following the social distance. WBSN provides the way to effectively monitor the
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A framework and tool for the assessment of information security risk, the reduction of information security cost and the sustainability of information security culture Pers. Ubiquitous Comput. (IF 2.0) Pub Date : 2021-03-18 S.G. Govender, E. Kritzinger, M. Loock
Information security data breaches are becoming larger and more frequent. Incorporating information security into the culture of the information technology (IT) staff members that support these technologies is a key function that must be considered in parallel to improved security technology. The framework proposed in this paper considers focusing on cost-reducing products, services and structures
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Correction to: The early warning research on nursing care of stroke patients with intelligent wearable devices under COVID-19 Pers. Ubiquitous Comput. (IF 2.0) Pub Date : 2021-03-16 Fengxia Li, Zhimin Tao, Ruiling Li, Zhi Qu
A Correction to this paper has been published: https://doi.org/10.1007/s00779-021-01537-0
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From awareness to influence: toward a model for improving employees’ security behaviour Pers. Ubiquitous Comput. (IF 2.0) Pub Date : 2021-03-15 Moneer Alshaikh, Blair Adamson
This paper argues that a conventional approach to cybersecurity awareness is not effective in influencing employees and creating sustainable behaviour change. The increase in security incidents caused by employees is evidence that providing information to raise employees’ awareness does not necessarily result in improving their security behaviour, and organisations must transform their security awareness
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Serious games for basic learning mechanisms: reinforcing Mexican children’s gross motor skills and attention Pers. Ubiquitous Comput. (IF 2.0) Pub Date : 2021-03-12 Raymundo Cornejo, Fernando Martínez, Vania C. Álvarez, Claudia Barraza, Franceli L. Cibrian, Ana I. Martínez-García, Mónica Tentori
Early childhood is the most important and rapid period of development in a human life as it is a period where the maturation of the brain and the central nervous system take place. In fact, researchers have established some theories and several studies indicating the relationship between brain maturity and learning disabilities. Nonetheless, when academic problems are present, therapy intervention
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Hybrid FOW—a novel whale optimized firefly feature selector for gait analysis Pers. Ubiquitous Comput. (IF 2.0) Pub Date : 2021-03-10 K. M. Monica, R. Parvathi
Human gait analysis is a well-defined technique for human identification and tracking at distance based on their walking style. It plays an important role in the video surveillance, medical, and defense applications. A number of sensors such as MEMS accelerators, gyroscopes, pressure, and position were deployed for measuring the different gait signals from the body and utilized for the different analysis
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ADASYN and ABC-optimized RBF convergence network for classification of electroencephalograph signal Pers. Ubiquitous Comput. (IF 2.0) Pub Date : 2021-03-08 Sandeep Kumar Satapathy, Shruti Mishra, Pradeep Kumar Mallick, Gyoo-Soo Chae
Electroencephalograph (EEG) is supposed to be a major challenge in the area of biomedical signal processing. Being one of the widely used invasive techniques, it is capable to find many cases of brain disorder problems like epileptic seizures and sleep disorder. This work follows the procedure of convergence computing where there are different computing techniques have been combined together to achieve
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Analyzing gene polymorphism and metal folic acid interactions in neural tube defects using optimized deep recurrent neural networks Pers. Ubiquitous Comput. (IF 2.0) Pub Date : 2021-03-06 Ibrahim Mustafa, Aldosary Saad, Mohamed H. Mahmoud, Salman Alamery, Nourelhoda M. Mahmoud
Recently, increasing importance has been given to neural tube defects (NTDs), considered a congenital disability that affects the brain and the spinal cord. NTD occurs because of genetic information passed from parents to children via genes that affect the brain region’s shape or function. Presently, minimum folate carrier (MFC A80G) gene polymorphism and maternal folic acid interactions are associated
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Solving high-dimensional forward-backward doubly SDEs and their related SPDEs through deep learning Pers. Ubiquitous Comput. (IF 2.0) Pub Date : 2021-03-05 Bin Teng, Yufeng Shi, Qingfeng Zhu
Forward-backward doubly stochastic differential equations (FBDSDEs) are related to a type of quasi-linear parabolic stochastic partial differential equations (SPDEs). We propose a deep learning-based numerical algorithm for solving such equations. Using deep neural networks as approximations of the controls, we can deal with high-dimensional cases. Numerical experiments are carried out to demonstrate
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Prediction of muscular paralysis disease based on hybrid feature extraction with machine learning technique for COVID-19 and post-COVID-19 patients Pers. Ubiquitous Comput. (IF 2.0) Pub Date : 2021-03-03 Prabu Subramani, Srinivas K, Kavitha Rani B, Sujatha R, Parameshachari B.D
Many Coronavirus disease 2019 (COVID-19) and post-COVID-19 patients experience muscle fatigues. Early detection of muscle fatigue and muscular paralysis helps in the diagnosis, prediction, and prevention of COVID-19 and post-COVID-19 patients. Nowadays, the biomedical and clinical domains widely used the electromyography (EMG) signal due to its ability to differentiate various neuromuscular diseases
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Improving network efficiency in wireless body area networks using dual forwarder selection technique Pers. Ubiquitous Comput. (IF 2.0) Pub Date : 2021-03-01 Haseeb Ur Rahman, Anwar Ghani, Imran Khan, Naved Ahmad, S Vimal, Muhammad Bilal
Wearable computing has a great prospect in smart healthcare applications. The emergence of the Internet of Things, Wireless Body Area Networks (WBANs), and big data processing open numerous challenges and opportunities. In healthcare, the monitoring is done by placing/implanting sensor nodes (resource-constrained devices) on a patient’s body to communicate data to a resource-rich node called a sink
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Research of automatic recognition of car license plates based on deep learning for convergence traffic control system Pers. Ubiquitous Comput. (IF 2.0) Pub Date : 2021-02-27 Hyochang Ahn, Han-Jin Cho
The technology that can recognize the license plates of vehicles in real time and manage them automatically is a key element of building an intelligent transportation system. License plate recognition is the most important technique in vehicle image processing used to identify a vehicle. Object recognition using a camera is greatly influenced by environmental factors in which the camera is installed
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What investors say is what the market says: measuring China’s real investor sentiment Pers. Ubiquitous Comput. (IF 2.0) Pub Date : 2021-02-26 Yunchuan Sun, Xiaoping Zeng, Siyu Zhou, Han Zhao, Peter Thomas, Haifeng Hu
This paper describes a novel approach to measure individual investor sentiment using text-based analysis of millions of posts extracted from Chinese financial online forums. We describe how we built a database of more than 200 million stock posts from online financial forums, created GubaLex, a sentiment dictionary consisting of 48,878 words to allow sentiment analysis, and how we developed GubaSenti
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Blockchain-assisted secure image transmission and diagnosis model on Internet of Medical Things Environment Pers. Ubiquitous Comput. (IF 2.0) Pub Date : 2021-02-26 Bassam A. Y. Alqaralleh, Thavavel Vaiyapuri, Velmurugan Subbiah Parvathy, Deepak Gupta, Ashish Khanna, K. Shankar
In recent days, the Internet of Medical Things (IoMT) is commonly employed in different aspects of healthcare applications. Owing to the increasing necessitates of IoT, a huge amount of sensing data is collected from distinct IoT gadgets. To investigate the generated data, artificial intelligence (AI) models plays an important role to achieve scalability and accurate examination in real-time environment
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Diagnosis and combating COVID-19 using wearable Oura smart ring with deep learning methods Pers. Ubiquitous Comput. (IF 2.0) Pub Date : 2021-02-26 M. Poongodi, Mounir Hamdi, Mohit Malviya, Ashutosh Sharma, Gaurav Dhiman, S. Vimal
Since the coronavirus (COVID-19) outbreak keeps on spreading all through the world, scientists have been crafting varied technologies mainly focusing on AI for an approach to acknowledge the difficulties of the epidemic. In this current worldwide emergency, the clinical business is searching for new advancements to screen and combat COVID-19 contamination. Strategies used by artificial intelligence
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The prediction of mortality influential variables in an intensive care unit: a case study Pers. Ubiquitous Comput. (IF 2.0) Pub Date : 2021-02-26 Naghmeh Khajehali, Zohreh Khajehali, Mohammad Jafar Tarokh
The intensive care units (ICUs) are among the most expensive and essential parts of all hospitals for extremely ill patients. This study aims to predict mortality and explore the crucial factors affecting it. Generally, in the health care systems, having a fast and precise ICU mortality prediction for patients plays a key role in care quality, resulting in reduced costs and improved survival chances
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Imaging features and clinical manifestations of neuromyelitis optica Pers. Ubiquitous Comput. (IF 2.0) Pub Date : 2021-02-23 Jundong Li, Jing Guo, Xiaoxia Zhao
With the rapid development of modern medical technology and imaging technology, neuromyelitis optica has attracted more and more attention of medical workers. However, this central nervous disease, which affects the optic nerve and spinal cord, still afflicts many people. And the recurrence rate of this disease is very high, so that many patients become disabled, it is difficult to fundamentally cure
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An improved fast shapelet selection algorithm and its application to pervasive EEG Pers. Ubiquitous Comput. (IF 2.0) Pub Date : 2021-02-17 Xiunan Zou, Xiangwei Zheng, Cun Ji, Yuang Zhang
With the rapid development of pervasive devices, a great deal of time series are generated by various sensors, and many time series classification (TSC) algorithms have been proposed to deal with these data. Among them, shapelet-based algorithms have attracted great attention due to its high accuracy and strong interpretability. However, time complexity of shapelet-based algorithms is high. In this
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Predicting interaction design patterns for designing explicit interactions in ambient intelligence systems: a case study Pers. Ubiquitous Comput. (IF 2.0) Pub Date : 2021-02-13 Viridiana Silva-Rodríguez, Sandra E. Nava-Muñoz, Luis A. Castro, Francisco E. Martínez-Pérez, Héctor G. Pérez-González, Francisco Torres-Reyes
Ambient intelligence (AmI) focuses on supporting people by designing sensitive and responsive environments to context through implicit and explicit interactions. Explicit interactions in AmI systems have requirements specific to making interactions robust, smooth, intuitive, and reliable. Based on requirements, the designers can detect and eliminate faults from the beginning of the design process and
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Analyzing online impression management ability of Chinese teenagers Pers. Ubiquitous Comput. (IF 2.0) Pub Date : 2021-02-11 Zengquan Fang, Xiaoxu Ji, Xuejing Qi, Junsheng Zhang
Internet and new media have been highly integrated into the growth process of teenagers, along with their learning, life and social interactions. It becomes an important part of Internet literacy to mold and manage one’s impression to others. In this paper, we study the influential factors of online impression management ability from personal factors, domestic factors and scholastic factors. We design
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On-demand UAV base station deployment for wireless service of crowded tourism areas Pers. Ubiquitous Comput. (IF 2.0) Pub Date : 2021-02-10 Lijie Yin, Ning Zhang, Chen Tang
With the support of wireless network, tourists in tourism areas could enjoy various tourism information search and smart tourism–related services. However, due to the limited capacity of wireless networks, in peaking seasons, tourism area crowding in local areas could result in emergency and temporary wireless network congestion. While increasing infrastructure investment (e.g., densifying base stations)
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Multi-modal secure healthcare data dissemination framework using blockchain in IoMT Pers. Ubiquitous Comput. (IF 2.0) Pub Date : 2021-02-08 Rajakumar Arul, Yasser D. Al-Otaibi, Waleed S. Alnumay, Usman Tariq, Umar Shoaib, M. D. Jalil Piran
Blockchain technology can solve current interoperability challenges in health information systems and provide the technical standard which ensures a secure sharing of electronic health data between individuals, healthcare providers, medical care institutions, and medical experts. In healthcare management, IoMT devices can deliver real-time sensory data from patients to be analyzed and processed. In
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Artificial intelligence technology based on deep learning in digestive endoscopy imaging diagnosis Pers. Ubiquitous Comput. (IF 2.0) Pub Date : 2021-02-05 Jinling Cheng, Tao Song, Zhi Liu, Lelai Zhou, Dianmin Sun
With the continuous progress in the era of big data, artificial intelligence technology has begun to get more and more applications in medicine, and it is becoming more and more possible to use artificial intelligence in the diagnostic technology of digestive endoscopy images. This article mainly studies the progress of artificial intelligence technology in the diagnosis of gastrointestinal endoscopy
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An IoT-based infrastructure to enhance self-evacuations in natural hazardous events Pers. Ubiquitous Comput. (IF 2.0) Pub Date : 2021-02-05 José Mariano Finochietto, Matias Micheletto, Gabriel M. Eggly, Roger Pueyo Centelles, Rodrigo Santos, Sergio F. Ochoa, Roc Meseguer, Javier Orozco
Regardless of the extensive research conducted on large-scale evacuations, the instrumentation of these processes still represents an open issue for first response organizations. Self-evacuation of civilians that follows evacuation plans has shown to be feasible as early response to several natural disasters; however, the typical lack of interaction capability of the evacuees with first response organizations
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The value of artificial intelligence and imaging diagnosis in the fight against COVID-19 Pers. Ubiquitous Comput. (IF 2.0) Pub Date : 2021-02-04 Dandan Zhang, Xiaoya Liu, Mingyue Shao, Yaping Sun, Qingyuan Lian, Hongmei Zhang
The outbreak of the new type of coronavirus pneumonia (COVID-19) has caused a huge impact on the world. In this case, only by adhering to the prevention and control methods of early diagnosis, early isolation, and early treatment, can the spread of the virus be prevented to the greatest extent. This article uses artificial intelligence–assisted medical imaging diagnosis as the research object, combines
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Wireless sensor network–based delay minimization framework for IoT applications Pers. Ubiquitous Comput. (IF 2.0) Pub Date : 2021-02-01 Muthuramalingam Sankayya, Rakesh kumar Sakthivel, N. Gayathri, Fadi Al-Turjman
In IoT, the major challenge is processing huge amount of data from different types of sensors and to achieve a reliable data transmission in the sensor network. This makes it a necessity in enhancing Quality of Service, to acquire real-time service with assured quality. The major problem faced in the sensor network is delay, as more time is required to set up a connection with limited spectrum for
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Correction to: Applying the concept of implicit HCI to a groupware environment for teaching ethics Pers. Ubiquitous Comput. (IF 2.0) Pub Date : 2021-01-31 Claudio Alvarez, Gustavo Zurita, Nelson Baloian
A Correction to this paper has been published: https://doi.org/10.1007/s00779-021-01528-1
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Are off-balance-sheet indicators useful to evaluate accounting information quality? Pers. Ubiquitous Comput. (IF 2.0) Pub Date : 2021-01-30 Yunchuan Sun, Xiaoping Zeng, Luyu Wang, Siyu Zhou, Xiaowu Liu, Sanjaya Kuruppu
In this paper, we argue that off-balance-sheet information is potentially useful to evaluate accounting information quality in addition to financial indicators. We propose a novel method to evaluate the accounting information quality of listed companies in China by merging four financial attributes and six indicators derived from off-balance-sheet information, where the principal component analysis
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Drones-as-a-service: a simulation-based analysis for on-drone decision-making Pers. Ubiquitous Comput. (IF 2.0) Pub Date : 2021-01-29 Majed Alwateer, Seng W Loke, Niroshinie Fernando
Drone services are expected to emerge in many areas around the world in the near future and this is generating increasing interest. While there is a proliferation of ideas for various applications that can be delivered via drone services, the subject of drone service provisioning has received relatively less attention and, hence, is not well understood. We envision that a variety of drone applications
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Improving medical communication process using recurrent networks and wearable antenna s11 variation with harmonic suppressions Pers. Ubiquitous Comput. (IF 2.0) Pub Date : 2021-01-27 Prabu Subramani, Fadi Al-Turjman, Rajagopal Kumar, Anusha Kannan, Anand Loganthan
In medical applications, most of the patients are remotely monitored to eliminate the risk of being infected from the healthcare facilities. The process of remotely monitoring patients involves placing several body sensor networks on the patient’s body to collect their health details. The collected information is transmitted via the wireless communication process that must be of a high quality. Hence
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The early warning research on nursing care of stroke patients with intelligent wearable devices under COVID-19 Pers. Ubiquitous Comput. (IF 2.0) Pub Date : 2021-01-26 Fengxia Li, Zhimin Tao, Ruiling Li, Zhi Qu
Stroke patients under the background of the new crown epidemic need to be home-based care. However, traditional nursing methods cannot take care of the patients’ lives in all aspects. Based on this, based on machine learning algorithms, our work combines regression models and SVM to build a smart wearable device system and builds a system prediction module to predict patient care needs. The node is
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Spatio-temporal analysis of urban crime leveraging multisource crowdsensed data Pers. Ubiquitous Comput. (IF 2.0) Pub Date : 2021-01-22 Binbin Zhou, Longbiao Chen, Sha Zhao, Fangxun Zhou, Shijian Li, Gang Pan
Crime analysis is important for social security management. With the advance of crowd sensing techniques, abundant multisource crowd sensed data could be used for crime analysis. The occurrence of crimes usually has some patterns in terms of temporal and spatial aspects. Investigating the spatio-temporal correlation of crimes could provide more useful cues for crime analysis and help discover underlying
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An adaptive model to support biofeedback in AmI environments: a case study in breathing training for autism Pers. Ubiquitous Comput. (IF 2.0) Pub Date : 2021-01-21 Arturo Morales, Franceli L. Cibrian, Luis A. Castro, Monica Tentori
Biofeedback systems have shown promising clinical results in regulating the autonomic nervous system (ANS) of individuals. However, they typically offer a “one-size-fits-all” solution in which the personalization of the stimuli to the needs and capabilities of its users has been largely neglected. Personalization is paramount in vulnerable populations like children with autism given their sensory diversity
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The cost structure of influencers’ posts: the risk of losing followers Pers. Ubiquitous Comput. (IF 2.0) Pub Date : 2021-01-20 Carlos Oliveira, Ana Cristina B Garcia, Adriana S Vivacqua
This paper presents an exploratory study of the posting behavior of digital influencers in social participation platforms. As there are different platforms of social participation, we present a taxonomy to unify the different classifications and delimit the scope of our work. Influencers could produce a positive externality of increasing participation by suggesting social causes and government actions
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Understanding usage style transformation during long-term smartwatch use Pers. Ubiquitous Comput. (IF 2.0) Pub Date : 2021-01-19 Aku Visuri, Niels van Berkel, Jorge Goncalves, Reza Rawassizadeh, Denzil Ferreira, Vassilis Kostakos
Despite large investments in smartwatch development, the market growth remains smaller than forecasted. The purpose of smartwatch use remains unclear, indicated by the lack of large-scale adoption. Thus, we aim to better understand the early adoption and everyday smartwatch use. We investigate a diverse usage data of smartwatches logged over a period of up to 14 months from 79 individuals between December
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Game-based assessment tool using convergence of gamification and motivation theory in intelligent tutoring system Pers. Ubiquitous Comput. (IF 2.0) Pub Date : 2021-01-19 Jaechoon Jo, Eunsun Yi, Yeongwook Yang, Shin-hyeong Choi
As the online education market grows steadily, video lecture–based online educational environments such as the massive open online course (MOOC), open courseware (OCW), and flipped classroom are being used diversely in informal as well as formal education. However, since the learning in the online educational environment is predominantly conducted by the learners themselves, problems such as low motivation
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Feature-level interpolation-based GAN for image super-resolution Pers. Ubiquitous Comput. (IF 2.0) Pub Date : 2021-01-15 Lizong Zhang, Wei Zhang, Guoming Lu, Pengcheng Yang, Zhihong Rao
Image super-resolution is widely applied in face recognition, video perception, medical imaging, and many other fields. Although significant progress has been made, existing methods remain limited in reconstructing fine-grained texture details, making the pixels of the resulting images coarse. To address this problem, we propose a novel interpolation-based generative adversarial network (GAN) for high-resolution
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Proprioceptively displayed interfaces: aiding non-visual on-body input through active and passive touch Pers. Ubiquitous Comput. (IF 2.0) Pub Date : 2021-01-14 Clint Zeagler, Peter Presti, Elizabeth Mynatt, Thad Starner, Melody Moore Jackson
On-body input interfaces that can be used accurately without visual attention could have a wide range of applications where vision is needed for a primary task: emergency responders, pilots, astronauts, and people with vision impairments could benefit by making interfaces accessible. This paper describes a between-participant study (104 participants) to determine how well users can locate e-textile
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Error-less data fusion for posture detection using smart healthcare systems and wearable sensors for patient monitoring Pers. Ubiquitous Comput. (IF 2.0) Pub Date : 2021-01-12 Mohammed A. Alqarni
Smart healthcare applications rely on frequent monitoring information from the patient’s body using wearable sensors (WSs). Healthcare systems rely on multi-level information for identifying the diseases and hence providing a proper diagnosis. The challenging task is the acquisition of WS information and assimilation of the same for diagnosis purposes. This proposal introduces an error-less data fusion
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Time series forecasting of COVID-19 transmission in Asia Pacific countries using deep neural networks Pers. Ubiquitous Comput. (IF 2.0) Pub Date : 2021-01-10 Hafiz Tayyab Rauf, M. Ikram Ullah Lali, Muhammad Attique Khan, Seifedine Kadry, Hanan Alolaiyan, Abdul Razaq, Rizwana Irfan
The novel human coronavirus disease COVID-19 has become the fifth documented pandemic since the 1918 flu pandemic. COVID-19 was first reported in Wuhan, China, and subsequently spread worldwide. Almost all of the countries of the world are facing this natural challenge. We present forecasting models to estimate and predict COVID-19 outbreak in Asia Pacific countries, particularly Pakistan, Afghanistan
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KM-LA: knowledge-based mining for linear analysis of inconsistent medical data for healthcare applications Pers. Ubiquitous Comput. (IF 2.0) Pub Date : 2021-01-10 Abhay Kumar Singh, Muhammad Rukunuddin Ghalib
Healthcare data analysis is a prominent field of research supporting information technologies in the medical industry. Handling large volumes of data and mining them for application-related services requires time-efficient and less complex processing. With the implication of machine learning in computing processes, the analysis systems and mining performance are improved. In this manuscript, knowledge-based
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Thermodynamic imaging calculation model on COVID-19 transmission and epidemic cities risk level assessment—data from Hubei in China Pers. Ubiquitous Comput. (IF 2.0) Pub Date : 2021-01-09 Sulin Pang, Jiaqi Wu, Yinhua Lu
Novel coronavirus pneumonia in 17 city (Hubei) provinces was analyzed by using the principle of thermodynamics. A thermodynamic imaging model of infectious diseases was established to calculate the cumulative superimposed density of epidemic in 17 cities (prefectures). An evaluation rule of urban risk grade is established and evaluates the COVID-19 risk of 17 cities. The results show that (1) the higher
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Reconsidering the user in IoT: the subjectivity of things Pers. Ubiquitous Comput. (IF 2.0) Pub Date : 2021-01-09 John S. Seberger
This essay develops an interdisciplinary framework for understanding the relationship between “the person” and “the user” in the Internet of Things (IoT) by exploring a similarly troubled dyadic discourse: the thing. The goal is twofold: first, to provide a critical framework for scholars studying the humanistic and social implications of IoT; second, to broaden the scholarly discussion of IoT beyond
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Modeling and “smart” prototyping human-in-the-loop interactions for AmI environments Pers. Ubiquitous Comput. (IF 2.0) Pub Date : 2021-01-08 Miriam Gil, Manoli Albert, Joan Fons, Vicente Pelechano
Autonomous capabilities are required in AmI environments in order to adapt systems to new environmental conditions and situations. However, keeping the human in the loop and in control of such systems is still necessary because of the diversity of systems, domains, environments, context situations, and social and legal constraints, which makes full autonomy a utopia within the short or medium term
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TableRobot: an automatic annotation method for heterogeneous tables Pers. Ubiquitous Comput. (IF 2.0) Pub Date : 2021-01-08 Guibin Wu, Junjie Zhou, Yongping Xiong, Chaoyi Zhou, Chong Li
Using deep learning networks to recognize the table attracts lots of attention. However, due to the lack of high-quality table datasets, the performance of using deep learning networks is limited. Therefore, TableRobot has been proposed, an automatic annotation method for heterogeneous tables. To be more specific, the annotations of table consist of the coordinates of the item block and the mapping
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An automatic detection system of diabetic retinopathy using a hybrid inductive machine learning algorithm Pers. Ubiquitous Comput. (IF 2.0) Pub Date : 2021-01-07 Mohamed H. Mahmoud, Salman Alamery, H. Fouad, Amir Altinawi, Ahmed E. Youssef
Recently, the leading cause of preventable blindness is diabetic retinopathy (DR). Although there are several undiagnosed and non-treated cases of DR, accurate and adequate retinal screening could facilitate the early detection and treatment of DR. The goal of this research is to develop a reliable DR screening and detection model to reduce the risk of DR-related blindness. DR-infected eyes describe
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Ontology Guided Sparse Tensor Factorization for joint recommendation with hierarchical relationships Pers. Ubiquitous Comput. (IF 2.0) Pub Date : 2021-01-07 Hao Liu, Xiutao Shi, Guangxi Li, Shijun Liu, Li Pan
Although recommender systems enjoy widespread adoption in numerous different production settings, standard methods draw only on previous purchases or ratings, and optionally simple customer or product features. In many domains, however, the purchase or rating history is very sparse. Standard approaches suffer from such data sparsity and neglect to account for important additional dependencies that
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Can core competence help enterprises to deleverage?—empirical evidence based on text analysis Pers. Ubiquitous Comput. (IF 2.0) Pub Date : 2021-01-07 Changling Sun, Huacheng Wang, Yudong Qi, Yunchuan Sun
This paper constructs the measurement index of core competence by text analysis method and empirically tests the influence of core competence on enterprise capital structure. We find that the stronger the core competence is, the lower the asset-liability ratio will be, which means core competence can help enterprises to deleverage. The mechanism test finds that the influence of core competence on enterprise
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Deep learning-based elderly gender classification using Doppler radar Pers. Ubiquitous Comput. (IF 2.0) Pub Date : 2021-01-07 ZhiChen Wang, Zelin Meng, Keshi Saho, Kazuki Uemura, Naoto Nojiri, Lin Meng
Society today is facing a rapidly aging population. While various monitoring systems have been proposed for protecting elderly persons in their daily lives, concerns relating to privacy limit the effectiveness of these systems. In response to this issue, we investigate the use of Doppler radar images for monitoring the elderly, as these images are known to protect privacy very well. As the first step
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Centered convolutional deep Boltzmann machine for 2D shape modeling Pers. Ubiquitous Comput. (IF 2.0) Pub Date : 2021-01-06 Jiangong Yang, Shigang Liu, Xili Wang
An object shape information plays a vital role in many computer applications. Among these applications, some tasks can allow object shape analysis directly solve the problem. Thus, how to extract shape features and model the shape is a crucial issue. This paper proposes a new shape modeling method utilizing the centered convolutional deep Boltzmann machine to model two-dimensional (2D) shape. The proposed
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TransferSense: towards environment independent and one-shot wifi sensing Pers. Ubiquitous Comput. (IF 2.0) Pub Date : 2021-01-05 Qirong Bu, Xingxia Ming, Jingzhao Hu, Tuo Zhang, Jun Feng, Jing Zhang
WiFi has recently established itself as a powerful medium for radio frequency (RF) sensing due to its low cost and convenience. Many tasks, such as gesture recognition, activity recognition, and fall detection, can be implemented by measuring and calculating how the propagation of WiFi signals is affected by human activities. However, current WiFi-based sensing solutions have limited scales as they
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