A Correction to this paper has been published: https://doi.org/10.1007/s00779-021-01555-y

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

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

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

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

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

A Correction to this paper has been published: https://doi.org/10.1007/s00779-021-01553-0

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

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

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

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

A Correction to this paper has been published: https://doi.org/10.1007/s00779-021-01537-0

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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)

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

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

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

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

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

A Correction to this paper has been published: https://doi.org/10.1007/s00779-021-01528-1

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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