With the promotion of technology, 3D displays not only offer high-end video and sound qualities, but also provide larger-than-life viewing experiences. Twenty-five participants were recruited to investigate the effect of video type (horror, action, and comedy), display technique (2D, 3D), and ambient illumination (a dark room, 1500 lux) on saccade length, number of fixations, Simulator Sickness Questionnaire

Effective hospital outpatient forecasting is an important prerequisite for modern hospitals to implement intelligent management of medical resources. As outpatient visits flow may be complex and diverse volatility, we propose a hybrid Autoregressive Integrated Moving Average (ARIMA)-Long Short Term Memory (LSTM) model, which hybridizes the ARIMA model and LSTM model to obtain the linear tendency and

In order to prevent the illegal videos from being posted on the Internet and causing adverse effects, video sites need to manually review each newly released video. The manual review is time-consuming and labor-intensive, and is prone to omissions. Against this background, this article intends to propose a method for automatically detecting illegal content in videos. Automatic video detection can greatly

This article is an advanced approach to linguistic intuitionistic fuzzy variable through application of cubic set theory. For instance, we establish the idea of the linguistic intuitionistic cubic fuzzy variable (LICFV) theory and define several operations for LICFV; also establish a series of weighted aggregation operators under linguistic intuitionistic cubic fuzzy information, so called linguistic

In graph-based extractive text summarization techniques, the weight assigned to the edges of the graph is the crucial parameter for the sentence ranking. The weights associated with the edges are based on the similarity between sentences (nodes). Most of the graph-based techniques use the common words based similarity measure to assign the weight. In this paper, we propose a new graph-based summarization

China has developed into an aging population since 2000, following the global pattern of population aging. China has been ideally placed because of its excellent aging characteristics, which involve an ample proportion of the older population, speedy growth, and rapid expansion of the most past and unequal aging distribution. The aging demographic rises against the increasing burden of disease, high

The Internet-of-Things (IoT) are used everywhere in our daily lives. IoT applications provide us with many useful functionalities such as preventing fires, detecting and tracking objects, controlling and reporting the changes in/outside the environments, and capturing images/videos in our homes, roads, and offices. For example, the images data gathered through the smart sensors of autonomous vehicles

Unmanned surface vehicle is increasingly becoming a research hotspot, which can be used in a variety of civil and military missions. However, compared with the relative maturity of other technologies, the sensing technology of unmanned surface vehicles is relatively weak. Taking "WAM-V-USV" as the research platform, this paper is mainly focus on the detection and tracking methods of moving objects

Speech-in-noise perception is an important research problem in many real-world multimedia applications. The noise-reduction methods contributed significantly; however rely on a priori information about the noise signals. Deep learning approaches are developed for enhancing the speech signals in nonstationary noisy backgrounds and their benefits are evaluated for the perceived speech quality and intelligibility

Combined heat and power economic dispatch (CHPED) is an energy management problem that minimizes the operation cost of power and heat generation while a vast variety of operational constraints of the system should be met. The CHPED is a complicated, non-convex and non-linear problem. In this study, a new real-coded genetic algorithm with random walk-based mutation (RCGA-CRWM) is under study, which

This study examined the test scheduling optimization problem of industrial robot servo system (IRSS) samples with unequal numbers of different types of test items on the multiple IRSS comprehensive test platforms with the same function. In order to improve IRSS performance test efficiency, a multi-station test scheduling optimization method, which combines IRSS sample-level scheduling and test item-level

In the big data background, data privacy becomes more and more important when data leakage and other security events occur more frequently. As one of the key means of privacy protection, anonymous communication attracts large attention. Aiming at the problems such as low efficiency of message forwarding, high communication delay and abusing of anonymity, this paper presents an identity-based traceable

In view of the increase of network information transmission times, the transmission delay of multi hop nodes in the Internet of Things increases, resulting in the decline of network information transmission performance. In order to improve the quality and performance of information transmission, a minimum transmission delay algorithm of multi-hop nodes in the Internet of Things is designed based on

Human activity recognition (HAR) is an active field in ubiquitous computing and body area network (BAN), which has been widely applied in medical care, sport and smart home. In recent years, a lot of methods based on deep learning show great performance on HAR. In consideration of the temporal and spatial dependencies of time series, the extracted features of traditional methods are not comprehensive

Background A wearable sensor (WS) is a prominent technology application that senses and gathers information from a user for analyzing changes in physiological signs. Analyzing the physiological sign differences enables the better healthcare solutions. Purpose This paper introduces an unsynchronized sensor data analytics (USDA) model for the effective handling of wearable device data regardless of the

Generalized multi-scale decision table is an important model in granular computing, which can be applied to feature selection and rule extraction. The generalization effect of the model is different at different scales, so scale selection is a key to generalized multi-scale decision table. However, in existing studies, scale selection is usually based on a large number of set operations, and for different

The smart world is connecting all universe more than ever thought possible, benefiting from the significant advances of the Internet of Things (IoT) applications using wireless sensor networks (WSN) as the core technology. A challenging issue in the IoT paradigm is the heterogeneity in different parts of the network. The network developers need to use resources belonging to different platforms for

In wireless sensor networks (WSNs), a mobile sink accumulate the data instead of routing directly to the sink to avoid the hotspot problem. In this process, it traverses a predetermined path by visiting a set of nodes called the rendezvous point (RP), and all the non-rendezvous points can transmit their data to the closest RP. Identifying the best collection of RPs and determining the mobile sink traveling

Solar Photovoltaic (PV) system is an excellent renewable energy solution in today’s scenario. Harvesting maximum power from the solar PV system under dynamic meteorological conditions is a challenging task. Numerous bio-inspired Maximum Power Point Tracking (MPPT) strategies have been proposed in the literature. The conventional methods of MPPT control are easy and simple to implement, but has drawbacks

Anxiety affects human capabilities and behavior as much as it affects productivity and quality of life. It is considered to be the main cause of depression and suicide. Anxious states are detectable by specialists by virtue of their acquired cognition and skills. There is a need for non-invasive reliable techniques that performs the complex task of anxiety detection. In our study, we investigate the

Surveillance drones are remarkable devices for monitoring, as they have strong spatial and remote sensing capabilities. The prompt detection of peripheral damage to the blades of wind turbines is necessary to reduce downtime and prevent the potential failure of wind farms. Computer vision breakthroughs with deep learning have developed and been refined over time, mainly using convolution neural networks

In Vehicular ad hoc networks (VANETs), vehicle-to-vehicle (V2V) is a significant mode of communication in which vehicles communicate with other moving vehicles with the aid of wireless transceivers. Due to the rapid mobility of vehicles, network connectivity over VANETs is frequently unstable, especially in sparse highways. This paper analyzes V2V connectivity dynamics by designing the microscopic

Over downtown and highway road scenarios several applications have been proposed to enhance the quality of driving trips there. Safety, efficiency and entertainment services are provided to vehicles through several advanced technologies. Many of these applications require accurate investigation of the traffic characteristics and distributions over the area of interest in order to successfully provide

Maintaining customer–company relationship is very important from the perspective of business. It helps to gain new customers as well as retain existing customers, even the dissatisfied ones, through SIoT based informal and humble counseling. Full form of SIoT is social internet of things where smart objects communicate via social networks to extract required information and propagate suitable ones

Nowadays, wireless energy charging (WEC) is emerging as a promising technology for improving the lifetime of sensors in wireless rechargeable sensor networks (WRSNs). Using WEC, a mobile charger (MC) reliably supplies electric energy to the sensors. However, finding an efficient charging schedule for MC to charge the sensors is one of the most challenging issues. The charging schedule depends on remaining

With the recent technological innovations for measuring the physiological characteristics in the human body, Wireless Body Area Networks (WBANs) have received much attention from the industry and academics. One of the feasible solutions provided by today’s WBAN is the continuous health monitoring in which sensors planted in various parts of the body, which measure and send information about physiological

This paper presents a novel bio-inspired optimization algorithm called Rat Swarm Optimizer (RSO) for solving the challenging optimization problems. The main inspiration of this optimizer is the chasing and attacking behaviors of rats in nature. This paper mathematically models these behaviors and benchmarks on a set of 38 test problems to ensure its applicability on different regions of search space

Advancement of sensor technologies has conducted to the rapid evolution of platforms, tools and approaches such as Internet of Things (IoT) for developing behavioral and physiological monitoring systems. Nowadays, According to growing number of elderlies living alone without their relatives scattered over the wide geographical areas, it is significantly essential to track their health function status

Accuracy in IoT data acquisition has been an indispensable need to meet the increasing demand for time-sensitive data analysis, and real-time decision-making. Conspicuously, this study proposes a Quantum Computing inspired technique of temporal space optimization for real-time big IoT applications. For this purpose, quantification of IoT sensors is performed in terms of Sensors of Interest (SoI) and

In the reliability and security challenges for the Internet of Things (IoT) systems, managing unpredictable events and controlling the abnormal situation automatically are provisioned by the integration of self-healing properties. Despite this, in our knowledge, this integration is not used to repair from malicious behaviors and potential distributed denial of service (DDoS) device attacks, especially

The recent growth in the field of data mining and machine learning has remitted into more recognition of outcome prediction and classification. However, the application of these techniques in the field of sports is still unexplored. This paper presents the implementation of data mining and machine learning in sports particularly. Here, machine learning based algorithm to predict the outcome of the

Evolutionary algorithms have shown their powerful capabilities in different machine learning problems including clustering which is a growing area of research nowadays. In this paper, we propose an efficient clustering technique based on the evolution behavior of genetic algorithm and an advanced variant of nearest neighbor search technique based on assignment and election mechanisms. The goal of the

The critical issue identified in recent times is the high utility itemset mining (HUIM). It may be used for showing products that are profitably utilizing considering the factors of profit and quality as opposed to the frequent itemset (FIM) or the association rule (ARM) mining. There are numerous high utility itemset mining (HUIs) algorithms, mostly designed for handling the exponential search space

In order to improve the real-time efficiency of expressway operation monitoring and management, the anomaly detection in intelligent monitoring network of expressway based on edge computing and deep learning is studied. The video data collected by the camera equipment in the intelligent monitoring network structure of the expressway is transmitted to the edge processing server for screening and then

Image dehazing has become a critical problem to cater to as it has several parameters that need to be addressed. Real color, contrast, and illumination are the major parameters that are to be restored in the dehazed image. Different scenarios distort these parameters in different ways so it is difficult to restore the original image. Many approaches are used in the literature to cater to these problems

Automated tumor characterization has a prominent role in the computer-aided diagnosis (CAD) system for the human brain. Despite being a well-studied topic, CAD of brain tumors poses severe challenges in some specific aspects. One such challenging problem is the category-based classification of brain tumors among glioma, meningioma, and pituitary tumors using magnetic resonance imaging (MRI) images

This paper presents the implementation of smart cuckoo search (SCS) algorithm for intelligent path planning of mobile robots. A new fitness function is modeled and optimized by SCS algorithm to generate collision free optimal route for the mobile robots. The simulation results are illustrated to verify the ability of robot to deal with different environment conditions and reach to the target in all

In 2019, Banerjee et al. (IEEE Int Things J 6(5):8739–8752, 2019; https://doi.org/10.1109/JIOT.2019.2931372) proposed an authenticated key agreement scheme to facilitate the session establishment resulting into a session key between a user and a smart device for IoT based networks. As per their claim, the scheme of Banerjee et al. provides known security features and resist all known attacks using

A good dimensional reduction technique is needed to apply and improve the effectiveness of dimensionality reduction for medical data. High-dimensional data brings great challenges in terms of computational complexity and classification efficiency. It is necessary to compress effectively from high dimensional space to low dimensional space to design a learning curve with good performance. Therefore

The current e-commerce payment systems for credit or check cards require a payment gateway (PG). This incurs PG fees, which in turn increases the cost of engaging in e-commerce. This paper proposes a simple payment model that uses basic cryptocurrency features, such as public key, private key, and digital signature, to eliminate the need for transaction intermediaries such as public key certificate

This study aims to provide a new approach for describing and measuring the vulnerability of in-vehicle networks regarding cyberattacks. Cyberattacks targeting in-vehicle networks can result in a reasonable threat considering passenger safety. Unlike previous literature, the methodology focuses on a comparatively large sample of vehicle networks (114 objects) by proposing a new framework of statistical

Internet of Medical Things (IoMT) includes interconnected sensors, wearable devices, medical devices, and clinical systems. At the same time, skin cancer is a commonly available type of cancer that exists all over the globe. This study projects a new segmentation based classification model for skin lesion diagnosis by combining a GrabCut algorithm and Adaptive Neuro-Fuzzy classifier (ANFC) model. The

As path planning is an NP-hard problem it can be solved by multi-objective algorithms. In this article, we propose a multi-objective path planning algorithm which consists of three steps: (1) the first step consists of optimizing a path by the hybridization of the Grey Wolf optimizer-particle swarm optimization algorithm, it minimizes the path distance and smooths the path. (2) the second step, all

With the emergence of large-volume and high-speed streaming data, traditional techniques for mining closed frequent itemsets has become inefficient. Online mining of closed frequent itemsets over streaming data is one of the most important issues in data streams minging. In view of the low efficiency of traditional closed frequent item data mining, a combined data structure based on the principle of

The Maclaurin symmetric mean (MSM) and dual Maclaurin symmetric mean (DMSM) operators are two aggregation operators to aggregate the cubic Pythagorean linguistic fuzzy number. The cubic Pythagorean linguistic fuzzy structure is more real to designate fuzzy data in real decision-making problems. The cubic Pythagorean linguistic fuzzy number is more superior and difficult information in the environment

One of the challenges of using fog computing in IoT systems is the efficient placement of resources in IoT applications. This paper presents a resource placement method for fog-based IoT systems to reduce their latency and energy consumption. Given the limited processing power of fog nodes, only a limited number of modules can be run on these nodes. In fog-cloud systems, placing the modules on fog

Some electronic devices have a short lifetime, and variety-seeking and consumerism are increasingly growing in today’s societies. Moreover, electronic wastes contain precious substances such as gold, silver, copper, and aluminum. The proper disposal and processing of them by recycling offer considerable advantages to the environment, given the hazardous natures of such devices’ substances. The proposed

An interval-valued refined neutrosophic set is simply an extension of interval neutrosophic set and refined neutrosophic set which can be used in statistics, game theory, engineering, and experimental science. In this study, we define the cut set and extension principle based on interval-valued refined neutrosophic sets which is a bridge between interval-valued refined neutrosophic sets and crisp sets

Diabetic retinopathy (DR) is one of the complications of diabetes and a leading cause of blindness in the world. The tiny blood vessels inside the retina are damaged due to diabetes and result in various vision-related problems and it may lead to complete vision loss without early detection and treatment. Diabetic retinopathy may not cause any symptoms during its earlier stage of the disease and many

The vital task of improving the Responsiveness of the automotive supply chains is to forecast the demand and analyze the vehicle's most influential attributes. The purpose of this paper is to develop a model to forecast the demand and analyzing the vehicle attributes using a combined approach of big data analytics and fuzzy decision-making trial and evaluation laboratory (DEMATEL) technique. The forecasting

This study aims to explore the influence of different light color temperatures and lighting illuminances on two kinds of crafts regarding touch motivation, preference, and product evaluation. A total of 40 subjects are recruited in this study. The independent variables include lighting color temperature (3500 K, 4500 K, and 5500 K) and illuminance (500 lx, 1000 lx, 1500 lx, and 2000 lx), and three

When the power company is cutting and sending electricity, low frequency oscillation will occur in the power equipment at the harbor, which causes equipments to fail to function properly. This paper proposes an improved NSGA-II to coordinately control the power system, with the power system stabilizer and static reactive power compensator. The classical single machine system is simulated and analyzed

Under the pressure of fast-paced life, people’s demand for pharmaceuticals increases, and 24-h pharmacies begin to increase. But these pharmacies cannot really provide pharmaceuticals anytime and anywhere, and at the same time, the existing pharmaceuticals-vending machine (PM) has only single function and imperfect management. The mature automated medicine distribution equipment is only used in hospitals

The Pythagorean fuzzy set (PFS) is one of the most important concepts to accommodate more uncertainties than the intuitionistic fuzzy sets, fuzzy sets and hence its applications are more extensive. The well-known sine trigonometric function ensures the periodicity and symmetry of the origin in nature and thus satisfies the expectations of decision-makers over the parameters of the multi-time process

With the development of information technology, ambient intelligence has been combined with various application areas so as to create new convergence service industries. Through IT convergence, human-oriented technologies for improving people’s quality of life has continued to be developed. Healthcare service that has been provided along with the development of various smart IT devices makes it possible

The penetration of distributed generation (DG) units has been steadily increasing in distribution networks (DNs). However, oversizing and improper locating or operating of them can increase the losses or deteriorate the voltage profile. In this regard, distribution network reconfiguration (DNR) can be envisioned as a solution to maximize the DG penetration while improving the voltage profile and minimizing

There are many uncertain issues. To address these problems, many theories and models has been proposed. The conjunction of possibility measures can conjunct different possibility measures and deal with issues of decision making, which is an interesting model and has promising prospect. Meanwhile, the intuitionistic evidence sets is based on the intuitionistic basic probability assignment, which means

In the original publication of the article, the author names Fahad Shabbir Ahmad and Raza-Ul-Mustafa was incorrectly published.

Gait recognition in elderly patient monitoring is a standard process that employs medical healthcare systems, wearable sensors, motion capturing devices, and Information and Communication Technologies (ICT). The patterns of the patient movement are observed at different time instances for identifying the abnormality in gaits to provide better assistance. In this article, a novel Overlapping Gait Pattern

With the rapid increase in the number of vehicles in our country, parking and parking management are becoming more and more difficult. Use information technology to improve the use of parking spaces and improve the efficiency of parking management, it is an effective way to alleviate the parking problem. In 2015, the research on "Internet + parking" accelerated rapidly in China. And various intelligent