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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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Design and implementation for semantic information retrieval through convergence of ontology and user context based on mobile device Pers. Ubiquitous Comput. (IF 2.0) Pub Date : 2021-01-02 Mi Sug Gu, Jaehong Hwang, Hyung-Jin Mun
On account of prevalence of mobile devices, a variety of mobile-based services have been conducted recently. In this situation, it is possible to serve the information that fits to users’ requests according to the users’ context using mobile devices. Therefore, it is necessary to research data mining techniques with mobile devices. Therefore, we researched information retrieval system in mobile environment
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First broad and systematic horizon scanning campaign and study to detect societal and ethical dilemmas and emerging issues spanning over cybersecurity solutions Pers. Ubiquitous Comput. (IF 2.0) Pub Date : 2021-01-02 Aleksandra Pawlicka, Michał Choraś, Rafał Kozik, Marek Pawlicki
Cybersecurity and cybercrime cannot exist without each other. They are not contraries, but rather two opposite poles of the same idea. Although it may seem that it is a rather black and white kind of relationship, the measures aimed at protecting innocent people raise a myriad of ethical dilemmas. This paper presents the results of a horizon scanning study aimed at identifying the ethical and human
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Enhancement learning on financial text data Pers. Ubiquitous Comput. (IF 2.0) Pub Date : 2021-01-02 Xiliu Man, Jianwu Lin
With the fast development of natural language processing (NLP), financial text data processing has gained much attention due to its huge potential business value. Deep learning model based on manual perception-based labeling is commonly used to illustrate implicit meanings behind financial text. However, such manual labeling is costly and subjective, and may not perform well due to its weak link with
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Applying the concept of implicit HCI to a groupware environment for teaching ethics Pers. Ubiquitous Comput. (IF 2.0) Pub Date : 2021-01-02 Claudio Alvarez, Gustavo Zurita, Nelson Baloian
Implicit HCI is about computers understanding the intentions and needs of the user and proactively triggering functions or adapting the interface to help users achieve their goals. In ubiquitous learning environments, this could mean that the software and hardware settings make relevant learning material available to students; activate proper learning environments, like collaborative authoring tools
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User interface design patterns and ontology models for adaptive mobile applications Pers. Ubiquitous Comput. (IF 2.0) Pub Date : 2021-01-02 Amani Braham, Félix Buendía, Maha Khemaja, Faiez Gargouri
Mobile applications are an essential element in pervasive and ubiquitous computing, and they face many challenges during their generation process from the analysis of user needs to the design of specific mobile interfaces and their development in several technological platforms. Moreover, the rise of Ambient Intelligent and context-aware environments also introduces multiple interaction aspects to
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Correction to: SwarmCity project: monitoring traffic, pedestrians, climate, and pollution with an aerial robotic swarm Pers. Ubiquitous Comput. (IF 2.0) Pub Date : 2020-12-21 Juan Jesús Roldán-Gómez, Pablo Garcia-Aunon, Pablo Mazariegos, Antonio Barrientos
A Correction to this paper has been published: https://doi.org/10.1007/s00779-020-01504-1
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Validation of UWB positioning systems for player tracking in tennis Pers. Ubiquitous Comput. (IF 2.0) Pub Date : 2020-11-28 Anton Umek, Anton Kos
Precise and reliably tracking of players’ position during the action or during the game is important in many sports. Our motivation was to investigate and validate the use of ultra-wideband (UWB) systems for various player and coach applications that depend on tracking the position of the player and possible related events. We developed and implemented a real-time positioning system that allows (a)
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Interactive sonification to assist children with autism during motor therapeutic interventions Pers. Ubiquitous Comput. (IF 2.0) Pub Date : 2020-11-27 Franceli L. Cibrian, Judith Ley-Flores, Joseph W. Newbold, Aneesha Singh, Nadia Bianchi-Berthouze, Monica Tentori
Interactive sonification is an effective tool used to guide individuals when practicing movements. Little research has shown the use of interactive sonification in supporting motor therapeutic interventions for children with autism who exhibit motor impairments. The goal of this research is to study if children with autism understand the use of interactive sonification during motor therapeutic interventions
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Knowledge-based edge computing framework based on CoAP and HTTP for enabling heterogeneous connectivity Pers. Ubiquitous Comput. (IF 2.0) Pub Date : 2020-11-25 Rongxu Xu, Wenquan Jin, Do Hyeun Kim
Over the last decades, Internet of Things-based applications have become increasingly popular among many researchers and companies in developing a comfortable and safe lifestyle for people. Currently, many Internet of Things-based systems are providing extensive benefits to our daily lifestyle, although low power, failure in connectivity, and lack of computing knowledge are major challenges within
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Sensing-gain constrained participant selection mechanism for mobile crowdsensing Pers. Ubiquitous Comput. (IF 2.0) Pub Date : 2020-11-24 Dan Tao, Ruipeng Gao, Hongbin Sun
Participant selection is a fundamental challenge to perform sensing tasks with adequate data quality in various mobile crowdsensing (MCS) applications. In this paper, we explore participant selection mechanisms with sensing-gain constraints in MCS. First, we propose a novel quality-aware participant reputation model with active factors. Second, since user density differs in various applications, we
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Synergic deep learning model–based automated detection and classification of brain intracranial hemorrhage images in wearable networks Pers. Ubiquitous Comput. (IF 2.0) Pub Date : 2020-11-23 C. S. S. Anupama, M. Sivaram, E. Laxmi Lydia, Deepak Gupta, K. Shankar
With an intention of improving healthcare performance, wearable technology products utilize several digital health sensors which are classically linked into sensor networks, including body-worn and ambient sensors. On the other hand, intracerebral hemorrhage (ICH) defines the injury of blood vessels in the brain regions, which is accountable for 10–15% of strokes. X-ray computed tomography (CT) scans
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Enabling distributed intelligence in Internet of Things: an air quality monitoring use case Pers. Ubiquitous Comput. (IF 2.0) Pub Date : 2020-11-23 Noussair Lazrak, Jamal Ouarzazi, Jihad Zahir, Hajar Mousannif
Air pollution is worsening almost everywhere in the world. According to the Health Effects Institute (HEI), more than 95% of the world population breathe polluted air, toxic to their cardiovascular and respiratory health, which caused the death of 4.2 million people worldwide in 2016. As a result, the air pollution has become one of the leading causes of death worldwide. Therefore, an early cost-efficient
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Research on the influence mechanism of users’ quantified-self immersive experience: on the convergence of mobile intelligence and wearable computing Pers. Ubiquitous Comput. (IF 2.0) Pub Date : 2020-11-22 Hong Jin, Jiayue Yan, Yudong Zhang, Huilong Zhang
The rapid development of mobile intelligence and wearable computing promotes the rise of quantified-self. Users quantify themselves and realize self-tracking and self-cognition through the connection between mobile phone terminals and wearable computing devices. The characteristics of immersive quantified information design in the convergence mode of mobile intelligence and wearable computing attract
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Designing for cultural learning and reflection using IoT serious game approach Pers. Ubiquitous Comput. (IF 2.0) Pub Date : 2020-11-18 Hai Huang, Kher Hui Ng
Previous studies have highlighted the difficulty that designers face in designing interactive systems that will help visitors learn and reflect upon cultural issues in support of museums’ new roles of shaping cultural identify and community building. In this paper, we report a study to explore the potential of Internet of things (IoT) serious games to support cultural learning and reflection by incorporating
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Study on the evolution of information sharing strategy for users of online patient community Pers. Ubiquitous Comput. (IF 2.0) Pub Date : 2020-11-17 Panpan Zhu, Jiang Shen, Man Xu
Technological advances are driving the growth of online health communities. However, there are some problems such as low user participation and insignificant social benefits in online health communities. This paper discusses the evolution law of information sharing behavior of members of online health community to study the influence of different behaviors on health information sharing results and
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A secure remote health monitoring model for early disease diagnosis in cloud-based IoT environment Pers. Ubiquitous Comput. (IF 2.0) Pub Date : 2020-11-16 Samira Akhbarifar, Hamid Haj Seyyed Javadi, Amir Masoud Rahmani, Mehdi Hosseinzadeh
Internet of Things (IoT) and smart medical devices have improved the healthcare systems by enabling remote monitoring and screening of the patients’ health conditions anywhere and anytime. Due to an unexpected and huge increasing in number of patients during coronavirus (novel COVID-19) pandemic, it is considerably indispensable to monitor patients’ health condition continuously before any serious
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Continuous touch gesture recognition based on RNNs for capacitive proximity sensors Pers. Ubiquitous Comput. (IF 2.0) Pub Date : 2020-11-09 David Castells-Rufas, Juan Borrego-Carazo, Jordi Carrabina, Jordi Naqui, Ernesto Biempica
The use of capacitive sensors in the automotive context opens new possibilities in the development of new interfaces for machine interaction with the vehicle occupants. Large smart surfaces with gesture recognition will possibly be part of such new interfaces. However, the data processing cost of such new sensors should be maintained at a minimum while increasing the complexity of their gesture recognition
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The importance of social identity on password formulations Pers. Ubiquitous Comput. (IF 2.0) Pub Date : 2020-11-07 Marthie Grobler, M. A. P. Chamikara, Jacob Abbott, Jongkil Jay Jeong, Surya Nepal, Cecile Paris
Passwords are regarded as the most common authentication mechanism used by Web-based services, despite large-scale attacks and data breaches regularly exploiting password-associated vulnerabilities. We investigate the trends behind password formulation in an exploratory study to postulate that social identity and language play a major role in users’ general attitude toward formulating passwords. For
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A systematic approach for COVID-19 predictions and parameter estimation Pers. Ubiquitous Comput. (IF 2.0) Pub Date : 2020-11-06 Vishal Srivastava, Smriti Srivastava, Gopal Chaudhary, Fadi Al-Turjman
The world is currently facing a pandemic called COVID-19 which has drastically changed our human lifestyle, affecting it badly. The lifestyle and the thought processes of every individual have changed with the current situation. This situation was unpredictable, and it contains a lot of uncertainties. In this paper, the authors have attempted to predict and analyze the disease along with its related
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Child–display interaction: Lessons learned on touchless avatar-based large display interfaces Pers. Ubiquitous Comput. (IF 2.0) Pub Date : 2020-10-30 Elisa Rubegni, Vito Gentile, Alessio Malizia, Salvatore Sorce, Niko Kargas
During the last decade, touchless gestural interfaces have been widely studied as one of the most promising interaction paradigms in the context of pervasive displays. In particular, avatars and silhouettes have proved to be effective in making the touchless capacity of displays self-evident. In this paper, we focus on a child–display interaction approach to avatar-based touchless gestural interfaces
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A study on topic models using LDA and Word2Vec in travel route recommendation: focus on convergence travel and tours reviews Pers. Ubiquitous Comput. (IF 2.0) Pub Date : 2020-10-29 Seong-Taek Park, Chang Liu
At present, we live in prosperity contrary to the past times. As income increases, people enjoy wealth, but more people tend to pursue their own inner happiness: travel. People go to other places or visit foreign countries for business or journey. This study aims to identify the best tour route for foreign tourists in South Korea. Based on the review analysis results, this paper also aims to put forward
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Suppose your bus broke down and nobody came Pers. Ubiquitous Comput. (IF 2.0) Pub Date : 2020-10-26 Alexander G. Mirnig, Magdalena Gärtner, Elisabeth Füssl, Karin Ausserer, Alexander Meschtscherjakov, Vivien Wallner, Moritz Kubesch, Manfred Tscheligi
The absence of a human driver creates novel challenges for fully automated public transport. Passengers are likely to have different expectations, needs, or even fears when traveling without a driver in potentially dangerous situations. We present the results from two field studies in which we explored incident management in a driverless shuttle bus. We explored participant’s behavior and willingness
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Interaction of children with and without communication disorders using Montessori activities for the tablet Pers. Ubiquitous Comput. (IF 2.0) Pub Date : 2020-10-26 Juan-Ramón Pérez-Pérez, David Cabielles-Hernández, Miguel Sánchez-Santillán, MPuerto Paule-Ruiz
Mobile technologies used for education may offer advantages for children with Communication Disorders, among which we can find language disorders and speech disorders, which are identified in DSM-V. In this research, we have introduced two educational activities, “Matching Cards” and “Cards & Sounds”, based on the Montessori Method and which deal with the first stages of reading and writing. We have
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Factors enhancing independent tourists’ experience through convergence of smartphone-based services and information searching Pers. Ubiquitous Comput. (IF 2.0) Pub Date : 2020-10-23 Guozhong Li, Joung-Hae Seo, Eun-Mi Park
The aim of the present study is to identify influential factors of travel intention under the context of highly developed IT society today. Due to the development of IT and diversified ways of technology convergence, individual travelers become highly efficient in travel-related information processing. As predicted, the results of both Korean and Chinese samples show that acquaintance recommendation
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A blockchain-based IoT data management scheme using Bernoulli distribution convergence in the mobile edge computing Pers. Ubiquitous Comput. (IF 2.0) Pub Date : 2020-10-22 Yoon-Su Jeong, Yong-Ho Yon
With the creation of a mobile edge computing environment in which IoT technologies are converged on cloud services, the importance of high-capacity data processing technologies is increasing. In this paper, we propose a block chain–based convergence data management technique to efficiently handle different kinds of data processed in mobile edge computing environment. The proposed technique minimized
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Radio-frequency-based indoor-localization techniques for enhancing Internet-of-Things applications Pers. Ubiquitous Comput. (IF 2.0) Pub Date : 2020-10-19 Andreas Girgensohn, Mitesh Patel, Jacob T. Biehl
An important capability of most smart, Internet-of-Things-enabled spaces (e.g., office, home, hospital, factory) is the ability to leverage context of use. Location is a key context element, particularly indoor location. Recent advances in radio ranging technologies, such as Wi-Fi RTT, promise the availability of low-cost, near-ubiquitous time-of-flight-based ranging estimates. In this paper, we build
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Perceiving spatiotemporal traffic anomalies from sparse representation-modeled city dynamics Pers. Ubiquitous Comput. (IF 2.0) Pub Date : 2020-10-19 Jun Gao, Daqing Zheng, Su Yang
Early perception of anomaly traffic patterns, both spatially and temporally, is of importance for emergency response in the smart cities. To capture the spatiotemporal correlations among traffic flows for city dynamics modeling in correspondence with normal states, we conduct sparse representation on taxi activity over spatially partitioned cells in a city. We can perceive the deviation from the normal
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Convergent learning–based model for leukemia classification from gene expression Pers. Ubiquitous Comput. (IF 2.0) Pub Date : 2020-10-16 Pradeep Kumar Mallick, Saumendra Kumar Mohapatra, Gyoo-Soo Chae, Mihir Narayan Mohanty
Microarray data analysis is a major challenging field of research in recent days. Machine learning–based automated gene data classification is an essential aspect for diagnosis of gene related any malfunctions and diseases. As the size of the data is very large, it is essential to design a suitable classifier that can process huge amount of data. Deep learning is one of the advanced machine learning
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A location-based ubiquitous crowdsourcing approach for the emergency supply of oxygen cylinders Pers. Ubiquitous Comput. (IF 2.0) Pub Date : 2020-10-08 May El Barachi, Faouzi Kamoun, Abderrazek Hachani, Fatna Belqasmi, Amir Ben Said, Imed Amri
Many people with chronic obstructive pulmonary diseases (COPD) are subjected to emergencies triggered by breathing difficulties. Oxygen therapy, administered from medical oxygen cylinders, can be used to relieve respiratory airways, and restore the supply of oxygen to the body’s vital organs. In this paper, we present a location-based ubiquitous crowdsourcing solution to enable COPD patients to request
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Correction to: Activity recognition through interactive machine learning in a dynamic sensor setting Pers. Ubiquitous Comput. (IF 2.0) Pub Date : 2020-10-06 Agnes Tegen, Paul Davidsson, Jan A. Persson
Fig. 7 and Fig. 8 have incorrect legends in the images and have been updated.
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ReminiScentia: shaping olfactory interaction in a personal space for multisensory stimulation therapy Pers. Ubiquitous Comput. (IF 2.0) Pub Date : 2020-10-06 Raúl Casillas-Figueroa, Alberto L. Morán, Victoria Meza-Kubo, Cristina Ramírez-Fernández, Christian Acosta-Quiroz, Felipe Orihuela-Espina, Samuel Montero-Hernandez
Recently, multimodal interfaces are incorporating smell as an additional means of interaction. Devices called olfactory displays have been designed to improve applications with various objectives, such as notifying or alerting through scents, increasing immersion in virtual or augmented reality applications, or learning and enhancement of mental functions. Based on the potential of olfactory memory
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Self-moving robots and pulverised urban displays: status quo, taxonomy, and challenges in emerging pervasive display research Pers. Ubiquitous Comput. (IF 2.0) Pub Date : 2020-09-30 Marius Hoggenmueller, Luke Hespanhol, Alexander Wiethoff, Martin Tomitsch
After almost a decade of relentless development, pervasive urban displays have fragmented into a diversity of approaches with radically distinct characteristics in terms of how mobile they are, as well as the materials they are made of. In this article, we investigate such a diversity in terms of the relationships between key conceptual entities of pervasive urban displays, namely the displayed content
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Visual saliency model based on crowdsourcing eye tracking data and its application in visual design Pers. Ubiquitous Comput. (IF 2.0) Pub Date : 2020-09-29 Shiwei Cheng, Jing Fan, Yilin Hu
The visual saliency models based on low-level features of an image have the problem of low accuracy and scalability, while the visual saliency models based on deep neural networks can effectively improve the prediction performance, but require a large amount of training data, e.g., eye tracking data, to achieve good results. However, the traditional eye tracking method is limited by high equipment
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A framework to estimate cognitive load using physiological data Pers. Ubiquitous Comput. (IF 2.0) Pub Date : 2020-09-27 Muneeb Imtiaz Ahmad, Ingo Keller, David A. Robb, Katrin S. Lohan
Cognitive load has been widely studied to help understand human performance. It is desirable to monitor user cognitive load in applications such as automation, robotics, and aerospace to achieve operational safety and to improve user experience. This can allow efficient workload management and can help to avoid or to reduce human error. However, tracking cognitive load in real time with high accuracy
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User-defined semantics for the design of IoT systems enabling smart interactive experiences Pers. Ubiquitous Comput. (IF 2.0) Pub Date : 2020-09-26 Carmelo Ardito, Giuseppe Desolda, Rosa Lanzilotti, Alessio Malizia, Maristella Matera, Paolo Buono, Antonio Piccinno
Automation in computing systems has always been considered a valuable solution to unburden the user. Internet of Things (IoT) technology best suits automation in different domains, such as home automation, retail, industry, and transportation, to name but a few. While these domains are strongly characterized by implicit user interaction, more recently, automation has been adopted also for the provision
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Designing everyday automation with well-being in mind Pers. Ubiquitous Comput. (IF 2.0) Pub Date : 2020-09-18 Holger Klapperich, Alarith Uhde, Marc Hassenzahl
Nowadays, automation not only permeates industry but also becomes a substantial part of our private, everyday lives. Driven by the idea of increased convenience and more time for the “important things in life,” automation relieves us from many daily chores—robots vacuum floors and automated coffee makers produce supposedly barista-quality coffee on the press of a button. In many cases, these offers
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Passive Wi-Fi monitoring in the wild: a long-term study across multiple location typologies. Pers. Ubiquitous Comput. (IF 2.0) Pub Date : 2020-09-17 Miguel Ribeiro,Nuno Nunes,Valentina Nisi,Johannes Schöning
In this paper, we present a systematic analysis of large-scale human mobility patterns obtained from a passive Wi-Fi tracking system, deployed across different location typologies. We have deployed a system to cover urban areas served by public transportation systems as well as very isolated and rural areas. Over 4 years, we collected 572 million data points from a total of 82 routers covering an area
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Measuring commitment to self-tracking: development of the C2ST scale Pers. Ubiquitous Comput. (IF 2.0) Pub Date : 2020-09-17 Elçin Hancı, Joyca Lacroix, Peter A. M. Ruijten, Antal Haans, Wijnand IJsselsteijn
Self-tracking technologies bring a new set of experiences into our lives. Through sensors and ubiquitous measurements of bodily performance, a new form of automation experience shapes our understanding of our body and our behavior. While for many individuals self-tracking has an important role in their daily lives, a theoretical understanding of the level and behavioral manifestations of commitment
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Digital media news categorization using Bernoulli document model for web content convergence Pers. Ubiquitous Comput. (IF 2.0) Pub Date : 2020-09-17 Pradeep Kumar Mallick, Sushruta Mishra, Gyoo- Soo Chae
There are multiple distinct sources through which numerous news contents that occur in digital medium tend to converge. Web contents constitute massive number of features. Complete coverage of all kinds of news is absolutely vital to retain customer confidence and to have a competitive edge over other news agencies. Aggregating such massive news content from different heterogeneous sources requires
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Research on mobile impulse purchase intention in the perspective of system users during COVID-19. Pers. Ubiquitous Comput. (IF 2.0) Pub Date : 2020-09-12 Wei Zhang,Xuemei Leng,Siyu Liu
COVID-19 has caused a serious impact on the global economy. Effectively stimulating consumption has become a momentous mission in responding to the impact of the epidemic. The popularity of mobile shopping makes shopping behavior no longer limited by time and space, so impulse purchase is more commonly seen nowadays; it can effectively promote residents’ consumption. However, consensus has not been
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End-to-end multivariate time series classification via hybrid deep learning architectures Pers. Ubiquitous Comput. (IF 2.0) Pub Date : 2020-09-11 Mehak Khan, Hongzhi Wang, Alladoumbaye Ngueilbaye, Aya Elfatyany
Deep learning has revolutionized many areas, including time series data mining. Multivariate time series classification (MTSC) remained to be a well-known problem in the time series data mining community, due to its availability in various practical applications such as healthcare, finance, geoscience, and bioinformatics. Recently, multivariate long short-term memory with fully convolutional network
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Enhanced multi-source data analysis for personalized sleep-wake pattern recognition and sleep parameter extraction Pers. Ubiquitous Comput. (IF 2.0) Pub Date : 2020-09-06 Sarah Fallmann, Liming Chen, Feng Chen
Sleep behavior is traditionally monitored with polysomnography, and sleep stage patterns are a key marker for sleep quality used to detect anomalies and diagnose diseases. With the growing demand for personalized healthcare and the prevalence of the Internet of Things, there is a trend to use everyday technologies for sleep behavior analysis at home, having the potential to eliminate expensive in-hospital
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Reinforcement learning–enabled efficient data gathering in underground wireless sensor networks Pers. Ubiquitous Comput. (IF 2.0) Pub Date : 2020-09-03 Deng Zhao, Zhangbing Zhou, Shangguang Wang, Bo Liu, Walid Gaaloul
Wireless underground sensor networks (WUSNs) consist of sensors that are buried in and communicate through soil medium, while the channel quality of WUSNs is greatly impacted by the underground environment, such as soil moisture and composition. Due to the precipitation and harsh weather, the underground environments change frequently, which make wireless communication in WUSNs much complicated than
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A NB-IoT data transmission scheme based on dynamic resource sharing of MEC for effective convergence computing Pers. Ubiquitous Comput. (IF 2.0) Pub Date : 2020-09-02 Sa Math, Prohim Tam, Ahyoung Lee, Seokhoon Kim
The convergence of mobile edge computing (MEC) to the current Internet of Things (IoT) environment enables a great opportunity to enhance massive IoT data transmission. In the narrowband Internet of Things (NB-IoT), the huge number of IoT devices sends the information to the remote network. Simultaneously, the massive IoT devices from the heterogeneous locations access to the radio remote head (RRH)
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Addressing Brazilian diversity in personal computing systems with a tailoring-based approach Pers. Ubiquitous Comput. (IF 2.0) Pub Date : 2020-08-29 Vânia Paula de Almeida Neris, Frederico Fortuna, Rodrigo Bonacin, Tatiana Silva de Alencar, Luciano de Oliveira Neris, M. Cecília C. Baranauskas
Access to knowledge, information, and technology is a key element for the development of individuals and society as a whole. While computing systems play a fundamental role in this process, efforts aimed at diminishing the worldwide digital divide are still scarce. In this study, we propose a tailoring-based approach for personal systems design as a way to promote digital and social inclusion in contexts
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Convergence of multiple deep neural networks for classification with fewer labeled data Pers. Ubiquitous Comput. (IF 2.0) Pub Date : 2020-08-28 Chuho Yi, Jungwon Cho
With the advent of deep neural networks (DNNs) in the last two decades, tremendous developments have been made in many fields, such as image classification/recognition, voice recognition, and action recognition. These advanced DNNs require large amounts of labeled data, whose collection is costly and requires great effort. In this paper, we provide a convergence method for DNNs to solve some of these
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