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

With the rapid development of machine-to-machine (M2M) mobile smart terminals, M2M services can be used in a wide range of industries, including such as tele-medicine, remote meter reading and public security. Since different industries and enterprise users have different requirements for M2M specific applications, the security identity authentication of M2M mobile terminals is particularly worthy

Energy saving is one of the most important issues for Internet of Things (IoT). An intuitive way to save energy of IoT devices is to reduce the reporting frequency to the IoT server. However, to do so, the time-variant values are distorted, which may be influential to the measured results. In this paper, we take PM2.5 application as an example to discuss the relation between energy efficiency and data

Ultra-dense networks (UDNs) are considered as key 5G technologies. They provide mobile users a high transmission rate and efficient radio resource management. However, UDNs lead to the dense deployment of small base stations (BSs) that can cause stronger interference and subsequently increase the handover management complexity. At present, the conventional handover triggering mechanism of user equipment

Deep neural networks have achieved state-of-the-art performances in wide range scenarios, such as natural language processing, object detection, image classification, speech recognition, etc. While showing impressive results across these machine learning tasks, neural network models still suffer from computational consuming and memory intensive for parameters training/storage on mobile service scenario

Big data-based credit reference system gradually attracts wide attention due to its ad-vantages in remedying the shortages of traditional credit reference and dealing with new challenges arising from financial credit management. Nevertheless, this new method is also adapted through different studies and experiments to be problematic with island of credit information and information security. Some researchers

In this paper, we present the concept and the prototype implementation of our novel “Smart Observatory of Involuntary Medical Seizures (SOIMS)”. SOIMS merges Wireless Body Area Networks (WBAN), Internet of Things (IoT) and Machine Learning (ML) as an intelligent platform for the prediction and modelling of involuntary seizures. The prediction process is elaborated with our proposed algorithms, namely

High mobility is the essential feature of vehicular ad-hoc networks (VANETs), which however challenges the low cost and real-time security of the network. The concept of Trust Communication (TC) is proposed to address the issue. Following this concept, each vehicle gains a trust value depending on its performance of communication. Then, other vehicles choose to communicate with the vehicle owning a

With the combined advantages of satellite communications, aerial networks and terrestrial systems, a space-air-ground integrated network has gradually become a promising architecture for the next generation wireless communication. Due to heterogeneous characteristics of different layers, it is necessary to perform efficient resource allocation. Motivated by this fact, we propose a novel architecture

The energy consumption of an enterprise energy management system (EMS) is a complex process with nonlinearity, time-variance, larger delay, greater inertia and other dynamic characteristics, resulting in the failure of a single-item prediction model to achieve satisfactory prediction results. In this paper, a combination prediction method, based on BP neural network, was proposed to predict the energy

The exchanged folded hyerpcube is a brand-new interconnection network proposed by Qi et al. This paper considers the case such that n = 1 + s + t, and the exchanged folded hypercube is denoted by EFH(s, t). The bus topology is one of the most well-known topologies in WDM optical networks. A bus-topology WDM optical network with N terminals can be described by a linear array graph Ln, where N = 2n.

Machine learning has been increasingly used for making informed public policy decisions, however, its application in the area of social protection in developing societies has been largely overlooked. We have employed unsupervised machine learning K-means clustering technique for exploring a big data that comprised of 88 attributes and 570 instances for better targeting of households that are in urgent

This paper takes education data mining as the research theme, mine the existing massive education big data, compares the analysis methods of existing data models, and proposes an improved random forest reference model. The information gain of various features is calculated by introducing the feature weighting system, and the evaluation index is used to improve the existing data analysis. The simulation

This paper proposes a delay-balanced adaptive channel allocation (DB-ACA) mechanism for improving the channel access performance of an LTE-U and WiFi coexistence system. To support the DB-ACA mechanism, an integrated network architecture is introduced for coordinating the channel access in the coexistence system. Based on the integrated network architecture, the coexistence system is able to adaptively

Currently most of the existing indoor fingerprint positioning algorithms are based on fingerprint database. The accuracy of the fingerprint database will directly affect the final positioning accuracy. Therefore, through the research of fingerprint data, a method based on skewness-kurtosis normality test and Kalman filter fusion is proposed. In the training phase, the RSSI (Received Signal Strength

In recent years, aged care living has drawn attention because of population aging and extension of average lifespan. Moreover, the rapid development of information communication technology and the internet of things lay the foundation for the application of sensor networks and cloud computing on medical care. Most elderly often suffer from chronic diseases due to weaker immunity causing a higher infection

Capturing all-in-focus images with 3D scenes is typically a challenging task due to depth of field limitations, and various multi-focus image fusion methods have been employed to generate all-in-focus images. However, existing methods have difficulty simultaneously achieving real-time and superior fusion performance. In this paper, we propose a region- and pixel-based method that can recognize the

The outbreak of chronic diseases such as COVID-19 has made a renewed call for providing urgent healthcare facilities to the citizens across the globe. The recent pandemic exposes the shortcomings of traditional healthcare system, i.e., hospitals and clinics alone are not capable to cope with this situation. One of the major technology that aids contemporary healthcare solutions is the smart and connected

Nowadays various distributed stream processing systems (DSPSs) are employed to process the ever-expanding real-time data. The DSPSs are highly susceptible to system failure, and the fault-tolerance issue is a major problem, which is getting lot of attention nowadays. Flink is a popular streaming computing framework that implements a lightweight, asynchronous checkpoint technique based on the barrier

The teaching effectiveness of China’s university design theory course has not undergone any major reforms in recent years to keep pace with new technology, modern teaching methodologies or student expectations. This is mainly due to the traditional approach of emphasizing practice rather than design theory and is inherent in design education in China, a view supported by design major students. The

This paper considers the power allocation problem in device-to-device (D2D) communication underlaying a cellular network and investigates the impact of different transmitting and interference power constraints on the energy efficiency and spectral efficiency of the network. We formulate the power allocation problem in D2D communication as a nonlinear fractional programming problem with an objective

This paper investigates the multi-objective problem of deploying wireless sensor networks with cooperative distance-based sensing coverage. This problem considers deploying a number of sensor nodes to cove multiple target points on a deployment area. Based on the locations of target points and the sensor nodes with their own inner and outer coverage radii, the distance-based sensing coverages of target