Cloud/edge computing and deep learning greatly improve performance of semantic understanding systems, where cloud/edge computing provides flexible, pervasive computation and storage capabilities to support variant applications, and deep learning models could comprehend text inputs by consuming computing and storage resource. Therefore, we propose to implement an intelligent online custom service system

To solve the problem of limited computing ability in mobile devices, edge computing is adopted as a feasible solution which provides services for IoT devices in different geographical locations. However, due to the service uncertainties, including the network congestion and the performance degradation of edge nodes, novel offloading strategies must be developed to accommodate the uncertain situations

Flocking is a social animals’ common behaviour observed in nature. It has a great potential for real-world applications such as exploration in agri-robotics using low-cost robotic solutions. In this paper, an extended model of a self-organised flocking mechanism using heterogeneous swarm system is proposed. The proposed model for swarm robotic systems is a combination of a collective motion mechanism

With the development of 5G technology, the short delay requirements of commercialization and large amounts of data change our lifestyle day-to-day. In this background, this paper proposes a fast blind deblurring algorithm for QR code images, which mainly achieves the effect of adaptive scale control by introducing an evaluation mechanism. Its main purpose is to solve the out-of-focus caused by lens

The article deals with the issue of identifying the impact of parking policy on the economy of road transport focusing on the conditions of the European Union. The aim of the article is to identify the impact of insufficient parking and the impact of EU social policy governing the work of drivers on the economy of the road transport sector. In terms of structure, the paper contains the identification

Nowadays, in the modern, fast-paced world, customers encounter a considerable range of products and services. They have a wide range of products to choose from, and it is up to them to decide. They often make decisions based on personal values, because they are the ones who know best what is best for them. Customer satisfaction depends on satisfying his needs and desires. If a product fails to meet

With the popularization of smart devices and the rapid development of Internet of Things (IoT), location-based social networks (LBSNs) are growing rapidly. As a crucial personalized location service of LBSNs, point-of-interest (POI) recommendation has become a research hotspot. However, due to the use of personal information, POI recommendation system brings serious risks of privacy disclosure. Existing

Combining spatial and temporal primitives together is quite useful to specify dynamic behaviors of cyber-physical systems. The ability to represent spatio-temporal properties by means of formulas in spatio-temporal logics has recently found important applications in various fields, such as runtime verification, parameter synthesis, and falsification. In this paper, we present a spatio-temporal specification

The rapid development of mobile communication technology has promoted the emergence of mobile edge computing (MEC), which allows mobile users to transfer their computing tasks to nearby edge servers to reduce access latency. In the actual MEC environment, the signal coverage areas of edge servers usually overlap partially, and users in the overlapped areas can choose to connect to one of the edge servers

The development of the Industry 4.0 concept offers completely new technologies’ enablers using high level of automation and digitalization. There is a huge challenge for enterprises not only due to the application of modern technologies (such as Internet of Things, Big Data Analytics, Cloud Computing, etc.) related to the creation of Cyber-Physical Systems but also for a human resources development

Recent years have witnessed the rapid prevalence of big data and it is necessary for mobile application to filter out information for users. As a significant means of information retrieval, recommendation system that recommends a ranked list of items to users according to their preferences has become a key functionality in Location-Based Social Networks (LBSNs). Point of interest (POI) recommendation

In the scenarios of specific conditions and crises such as the coronavirus pandemic, the availability of e-learning ecosystem elements is further highlighted. The growing importance for securing such an ecosystem can be seen from DDoS (Distributed Denial of Service) attacks on e-learning components of the Croatian e-learning system. The negative impact of the conducted attack is visible in numerous

Dynamic system is important for cognitive science in which cognitive map, fuzzy cognitive map are special cases. Both cognitive and fuzzy cognitive maps have complex state spaces, that is: chaos, limit cycles, fixed points and so on. In this paper, we study a class of fuzzy dynamic system, which called linguistic dynamic system. As a result, class of linguistic dynamic system is always convergent.

Flying ad hoc network (FANET) provides portable and flexible communication for many applications and possesses several unique design challenges; a key one is the successful delivery of messages to the destination, reliably. For reliable communication, routing plays an important role, which establishes a path between source and destination on the basis of certain criteria. Conventional routing protocols

In recent years, mobile social networks have largely been developed and gained considerable popularity. An approach to protecting privacy on mobile social networks is the use of encryption and access control. Good alternatives for use on mobile social networks are the Public Broadcast Encryption approach for appropriate concordance and consistency with the structure of social networks as well as the

Wrist-worn smart devices are being used to share various sensitive personal information in various fields such as social, medical treatment, sports, etc. Secure pairing establishing a trusted channel between involved devices is a prerequisite to ensure data transmission security. Handshake has been employed to realize secure pairing between devices worn by different users without pre-shared knowledge

The number of mobile applications downloaded recently from Google stores increase steadily. It is believed that mobile applications market revenues will grow fast and receive more attention from software developers. Even though, hardware technologies and operating systems have made a big contribution to improve the battery capacity, power consumption is one of the most important and crucial non-functional

In order to enhance the hybrid teaching of physical education online and offline, a quality evaluation method for online and offline hybrid teaching based on mobile edge computing is proposed. Through the evaluation target, index, weight of index and evaluation standard, this paper first constructs the quality evaluation index system of hybrid physical education online and offline. Then, factor and

The main goal of this study is to examine future changes in meteorological, hydrological drought under the impact of climate change in Dong Nai River Basin, using Standardized Precipitation Index (SPI) and Stream flow Drought Index (SDI). The Soil and Water Assessment Tool (SWAT) is used as a simulated tool to estimate the streamflow in baseline (1980–2005) and climate change (RCP 4.5, 2016–2035) scenarios

Scholarly articles are a great source of knowledge. Learning from them like E-learning requires automatic approaches to build concept-maps, learning paths, etc., as these sources are monotonically increasing and are big too. These sources have multi-domain, variety, huge volumes, which are, in fact, Big Data’s characteristics. Thus data from different domains have to be handled together, especially

With rich resources, movies have been applied as instructional media in the domain of education, such as fields of Second/Foreign Language Leaning, Communication, and Media Art. Factorization machine (FM) can effectively simulate common matrix factorization models by changing the form of real-value vector, which can be utilized in movies recommendation under the context of education. However, it is

Brown Planthopper (BPH) is one of the most dangerous insects that cause damage to rice. Aphids infected rice fields with low productivity can be lost even. Dealing with this situation, the Plant Protection industry has invented the light trap - a device based on the specific activity of insects phototaxis. These measures are considered effective and less costly today. However, the current light traps

The multi-dimensional characteristics of public opinion in online education lead to the difficulty of data cross-dimensional mining. To solve this problem, this paper designs a cross-dimensional data mining model of public opinion in online education based on fuzzy association rules. Based on the public opinion subject, object, and ontology to analyze the characteristics of public opinion in online

When using the current method to update the index of educational resources, there is no analysis of the hierarchical association structure between educational resources. There are some problems such as too long index construction time, high query time and low query accuracy. Therefore, this paper introduces mobile computing to study the adaptive updating method of education resource index. This paper

The part of this special issue with the title of “Context-aware Computing and Nature-inspired Computing: ICCASA and ICTCC 2020” edited by Prof. Phan Cong Vinh is presented to scientists, researchers, experts and students in the fields of context-aware computing and nature-inspired computing. Hopefully, they will find this part stimulating their research related to the hot topics of contextual cognitive

In response to the demand for high-quality electronic information talents in the mobile network industry, in the situation of artificial intelligence (AI) to promote technological innovation, this paper conducts an overall design in the target system, curriculum system, teaching platform, teaching mode and teaching case. The practice education mode of teaching practice, engineering practice, innovation

In this paper, we analyze the performance of vehicle-to-vehicle (V2V) communication system, which employs full-duplex (FD) and energy harvesting (EH) techniques at source and relay nodes from power beacon (PB) through radio frequency. Unlike previous systemswhere all nodes located at fixed locations, we investigate the case that three nodes (source, relay,and destination) are moving vehicles. Therefore

In view of the problem that the traditional learning service recommendation does not fully consider the distinct differences between individuals, it is easy to lead to the contradiction between unchanging learning resources and learners’ personalized learning needs that are constantly improving, so an adaptive learning service recommendation improvement algorithm based on big data is proposed. Idea

OCR (Optical Character Recognition) for scanned paper invoices is very challenging due to the variability of 19 invoice layouts, different information fields, large data tables, and low scanning quality. In this case, table structure recognition is a critical task in which all rows, columns, and cells must be accurately positioned and extracted. Existing methods such as DeepDeSRT only dealt with high-quality

Today, the agriculture industry has been developing intellectualization and automation proactively for reducing labor force and increase yields. In the past, farmers usually followed the rule of thumb to grow crops; however, due to the dramatic climate change, it becomes harder for farmers to cope with it by merely following the rule of thumb, which leads to crop damage. Therefore, it is vital to input

The rapid development of information technology accelerates the modernization of distance education. To realize the unified organization and management of learning resources as well as improve the utilization rate of resources, this paper proposes the design of a mobile online education resource sharing system from the perspective of man-machine cooperation. This paper analyzes the main body and scope

The rapid rate of dependence over internet usage using digital devices also results in enormous data traffic. The conventional way to handle these services is to increase the infrastructure. However, it results in high cost of implementation. Therefore, to overcome the data burden, researchers have come up with data offloading schemes using solutions for NP-hard Target Set Selection (TSS) problem.

The new 5G networks must face the challenge to fulfill multiple requirements in different use cases, applications and verticals. These networks are designed to provide strict Quality of Service (QoS) compliance independently of the network conditions in each use case. Some use cases are deployed in Public Land Mobile Network (PLMN), infrastructures that are managed by mobile network operators. However

This paper investigates the energy efficiency of a full duplex (FD) cognitive radio (CR) system in the low-power regime under a practical self-interference cancellation performance and imperfect spectrum sensing. We consider an opportunistic spectrum access network in which the secondary user (SU) is capable of self-interference suppression (SIS). The SIS ability enables the SU to work in simultaneous

In practical applications of the motor imagery-based brain–computer interface (BCI) system, the differences in electroencephalogram (EEG) signal manifestation and corresponding rhythm ranges in different individuals pose a significant challenge. The corresponding EEG features in different frequency bands differ; therefore, personalized screening must be conducted to obtain information that is conducive

Mobile Ad-Hoc Networks are currently experiencing a second youth in terms of research interest as well as providing benefits to our society. Clearly, this has been fostered by the wide range of applications that have become actually feasible thanks to the pervasive and increasing presence of smartphones, drones, sensors and other small devices with communication and sensing capability. Aiming to deploy

The LoRa technology enables long distance links with reduced power consumption at low cost, the main limitation being the low bandwidth that it offers. With LoRa, remote locations, like rural areas, can benefit from connectivity based services that would otherwise be impossible. In this work, we describe a LoRa architecture that can include generic external data sources using an MQTT-based interface

Wireless body area network (WBAN) is encountering a tough challenge in terms of energy efficiency due to multiple realistic factors like increasing scale of network environment, emerging demand of healthcare applications and limited manufacturing technique of sensors. In this work, we address the energy saving issue of WBAN. We consider a layered network framework and hybrid channels with multiple

Recently, real-time obstacle detection by monocular vision exhibits a promising prospect in enhancing the safety of unmanned surface vehicles (USVs). Since the obstacles that may threaten USVs generally appear below the water edge, most existing methods first detect the horizon line and then search for obstacles below the estimated horizon line. However, these methods detect horizon line only using

In traditional text based medical image retrieval system, it is hard to find visually similar images in large medical image database. Content-based image retrieval is developed to retrieve similar images and it is based on visual attributes describing the content of an image. Developing a method for content based medical image retrieval is a challenging task. This paper proposed a new method for content-based

Online Social Networking platforms (OSNs) have become part of people’s everyday life and their usage covers the deep-rooted need for communication among humans. During recent years, as people are questioning more and more OSN service providers, a new generation of proposals, based on blockchain became very popular thanks to the ethics adopted by these platforms. Steemit is the most important blockchain-based

Encryption technology has a great influence on data security. There are many encryptions have been proposed. In general, the encryptions with higher complexity will provide higher security, but it will also consume a lot of computing resources. In some cases, these high complexity method may not suitable such as Internet of Thing devices. This is because Internet of Thing device has lower computing

Accurate demand prediction of bike-sharing is an important prerequisite to reducing the cost of scheduling and improving the user satisfaction. However, it is a challenging issue due to stochasticity and non-linearity in bike-sharing systems. In this paper, a model called pseudo-double hidden layer feedforward neural networks is proposed to approximately predict actual demands of bike-sharing. Specifically

In this paper, we propose new deep learning architectures to fuse data provided by multiple sensors. More specifically, we combine classical features extracted from a sensor and raw data of other sensors. In order to make this data fusion possible, we exploited convolution, dense, and concatenation layers. The Mobile HEALTH dataset has been used to support our study. The results show that the proposed

In a world that is getting increasingly digital and interconnected, and where more and more physical objects are integrated into the information network (Internet of Things, IoT), Data Visualization can facilitate the understanding of huge volumes of data. In this paper, we present the design and implementation of a testbed where IoT and Data Visualization have been exploited to increase the sustainability

Social anxiety disorder is characterized by sentiments of fear and anxiety in social interactions. This study’s aim was to design and evaluate a serious game to raise awareness of cognitive behavioral therapy (CBT) skills associated with social anxiety disorder. The target group was university students, as 10–25% within this group have impaired functioning due to social anxiety. This study was based

Video derain is an important issue in the field of digital image processing and computer vision. This paper divides rain streaks into two types: one is rain in natural scenes, and the other is rain in stochastic scenes. In this paper, we propose a novel rotational video derain algorithm via nonconvex and nonsmooth algorithm (RoDerain). Not only can the rain streaks in natural scene be removed, but

Given a population S of N tags in an RFID system, the tag-information sampling problem is to randomly choose K distinct tags from S to form a subset T, and then inform each tag in T of a unique integer from {1,2,⋯ ,K}. This is a fundamental problem in many real-time analysis applications of RFID systems, as it enables rapidly selecting a small random tag subset T from a large tag population S and collecting

As an important means of medical imaging, elastic imaging is an indispensable part of mobile telemedicine. Ultrasound elastography has become a research hotspot because it can accurately measure soft tissue lesions. Displacement estimation is the most important step in ultrasound elastography. At present, the phase zero search method is an accurate and fast displacement estimation method. However,

In this paper, a Device-to-Device communication on unlicensed bands (D2D-U) enabled network is studied. To improve the spectrum efficiency (SE) on the unlicensed bands and fit its distributed structure while ensuring the fairness among D2D-U links and the harmonious coexistence with WiFi networks, a distributed joint power and spectrum scheme is proposed. In particular, a parameter, named as price

Smart grid is an energy network that integrates advanced power equipment, communication technology and control technology. It can transmit two-way power and data among all components of the grid at the same time. The existing smart grid communication technologies include power line carrier (PLC) communication, industrial Ethernet, passive optical networks and wireless communication,each of which have

Traditional Wi-Fi based action recognition models often utilize only amplitude information from CSI, with phase information simply discarded due to phase error problems. Such a design decision inevitably limits the information utilization, thus the overall performance. These models also strive at high recognition accuracy, invoking complicated model designs with high computational complexity, rendering

Deep convolutional neural networks have significantly improved the peak signal-to-noise ratio of Super-Resolution (SR). However, image viewer applications commonly allow users to zoom the images to arbitrary magnification scales, thus far imposing a large number of required training scales at a tremendous computational cost. To obtain a more computationally efficient model for arbitrary-scale SR, this

As the key information of vehicles, vehicle logo can assist in completing the identification of vehicle information. Therefore, the task of vehicle logo detection is of great practical significance. The existing object detection systems for vehicle logo detection cannot account for the detection accuracy of large and small-scale objects. Moreover, the accuracy of these methods can be further improved

Nowadays, with rapid development of technology and hardware, mobile devices have become an important part of people’s daily life. Although LTE (Long Term Evolution) had been developed stably and can support large scale communication services to mobile devices, the traffic offloading in core network and mobile devices is still an issue. Besides, the intensive collision between mobile devices is also

In recent years, the success of deep learning in natural scene image processing boosted its application in the analysis of remote sensing images. In this paper, we applied Convolutional Neural Networks (CNN) on the semantic segmentation of remote sensing images. We improve the Encoder- Decoder CNN structure SegNet with index pooling and U-net to make them suitable for multi-targets semantic segmentation

The coordinated development of big data, Internet of Things, cloud computing and other technologies has led to an exponential growth in Internet business. However, the traditional Internet architecture gradually shows a rigid phenomenon due to the binding of the network structure and the hardware. In a high-traffic environment, it has been insufficient to meet people’s increasing service quality requirements

Important progresses have been made in the field of artificial intelligence in recent years, and facial expression recognition (FER), which could greatly facilitate the development of human-computer interaction, has been becoming a significant research hotspot. In this paper, a novel nonnegative tensor factorization method is proposed based on low-rank subspace (NTF−LRS) for FER. Firstly, in order

With the development of deep learning technology, many deep learning methods have been applied to font recognition and generation. However, few studies focus on font inpainting problems. This paper is dedicated to repairing damaged fonts based on style to repair damaged fonts in a better way. In this paper, we propose a CGAN (Conditional Generative Adversarial Nets)-based font repair method. This paper

Video question answering (VideoQA) automatically answers natural language question according to the content of videos. It promotes the development of online education, scenario analysis, video content retrieving, etc. VideoQA is a challenging task because it requires a model to understand semantic information of the video and the question to generate the answer. Firstly, we propose a general framework