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  • Semantic Link Network Based Knowledge Graph Representation and Construction
  • Abstract A knowledge graph consists of a set of interconnected typed entities and their attributes, which shows a better performance to organize, manage and understand knowledge. However, because knowledge graphs contain a lot of knowledge triples, it is difficult to directly display to researchers. Semantic Link Network is an attempt, and it can deal with the construction, representation and reasoning of semantics naturally. Based on the Semantic Link Network, this paper explores the representation and construction of knowledge graph, and develops an academic knowledge graph prototype system to realize the representation, construction and visualization of knowledge graph.
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  • Hybrid Efficient Convolution Operators for Visual Tracking
  • Abstract Visual tracking is a classical computer vision problem with many applications. Efficient convolution operators (ECO) is one of the most outstanding visual tracking algorithms in recent years, it has shown great performance using discriminative correlation filter (DCF) together with HOG, color maps and VGGNet features. Inspired by new deep learning models, this paper propose a hybrid efficient convolution operators integrating fully convolution network (FCN) and residual network (ResNet) for visual tracking, where FCN and ResNet are introduced in our proposed method to segment the objects from backgrounds and extract hierarchical feature maps of objects, respectively. Compared with the traditional VGGNet,…
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  • Evaluation Model of Farmer Training Effect Based on AHP–A Case Study of Hainan Province
  • Abstract On the basis of studying the influencing factors of training effect evaluation, this paper constructs an AHP-fuzzy comprehensive evaluation model for farmers’ vocational training activities in Hainan Province to evaluate farmers’ training effect, which overcomes the limitations of traditional methods. Firstly, the content and index system of farmer training effect evaluation are established by analytic hierarchy process, and the weight value of each index is determined. Then, the fuzzy comprehensive evaluation (FCE) of farmer training effect is carried out by using multi-level FCE. The joint use of AHP and FCE improves the reliability and effectiveness of the evaluation process and…
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  • A Generation Method of Letter-Level Adversarial Samples
  • Abstract In recent years, with the rapid development of natural language processing, the security issues related to it have attracted more and more attention. Character perturbation is a common security problem. It can try to completely modify the input classification judgment of the target program without people’s attention by adding, deleting, or replacing several characters, which can reduce the effectiveness of the classifier. Although the current research has provided various methods of perturbation attacks on characters, the success rate of some methods is still not ideal. This paper mainly studies the sample generation of optimal perturbation characters and proposes a characterlevel…
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  • Investigating and Modelling of Task Offloading Latency in Edge-Cloud Environment
  • Abstract Recently, the number of Internet of Things (IoT) devices connected to the Internet has increased dramatically as well as the data produced by these devices. This would require offloading IoT tasks to release heavy computation and storage to the resource-rich nodes such as Edge Computing and Cloud Computing. However, different service architecture and offloading strategies have a different impact on the service time performance of IoT applications. Therefore, this paper presents an Edge-Cloud system architecture that supports scheduling offloading tasks of IoT applications in order to minimize the enormous amount of transmitting data in the network. Also, it introduces the…
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  •   Views:158       Downloads:129        Download PDF
  • Virtual Reality-Based Random Dot Kinematogram
  • Abstract This research implements a random dot kinematogram (RDK) using virtual reality (VR) and analyzes the results based on normal subjects. Visual motion perception is one of visual functions localized to a specific cortical area, the human motion perception area (human analogue for the middle temporal/middle superior temporal area) located in the parieto–occipito–temporal junction of the human brain. The RDK measures visual motion perception capabilities. The stimuli in conventional RDK methods are presented using a monitor screen, so these devices require a spacious dark room for installation and use. Recently, VR technology has been implemented in different medical domains. The test…
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  •   Views:158       Downloads:124        Download PDF
  • Bit Rate Reduction in Cloud Gaming Using Object Detection Technique
  • Abstract The past two decades witnessed a broad-increase in web technology and on-line gaming. Enhancing the broadband confinements is viewed as one of the most significant variables that prompted new gaming technology. The immense utilization of web applications and games additionally prompted growth in the handled devices and moving the limited gaming experience from user devices to online cloud servers. As internet capabilities are enhanced new ways of gaming are being used to improve the gaming experience. In cloud-based video gaming, game engines are hosted in cloud gaming data centers, and compressed gaming scenes are rendered to the players over the…
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  •   Views:182       Downloads:413        Download PDF
  • A Secure Intrusion Detection System in Cyberphysical Systems Using a Parameter-Tuned Deep-Stacked Autoencoder
  • Abstract Cyber physical systems (CPSs) are a networked system of cyber (computation, communication) and physical (sensors, actuators) elements that interact in a feedback loop with the assistance of human interference. Generally, CPSs authorize critical infrastructures and are considered to be important in the daily lives of humans because they form the basis of future smart devices. Increased utilization of CPSs, however, poses many threats, which may be of major significance for users. Such security issues in CPSs represent a global issue; therefore, developing a robust, secure, and effective CPS is currently a hot research topic. To resolve this issue, an intrusion…
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  • Mobile Memory Management System Based on User’s Application Usage Patterns
  • Abstract Currently, the number of functions to improve user convenience in smartphone applications is increasing. In addition, more mobile applications are being loaded into mobile operating system memory for faster launches, thus increasing the memory requirements for smartphones. The memory used by applications in mobile operating systems is managed using software; allocated memory is freed up by either considering the usage state of the application or terminating the least recently used (LRU) application. As LRU-based memory management schemes do not consider the application launch frequency in a low memory situation, currently used mobile operating systems can lead to the termination of…
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  •   Views:114       Downloads:104        Download PDF
  • DTLM-DBP: Deep Transfer Learning Models for DNA Binding Proteins Identification
  • Abstract The identification of DNA binding proteins (DNABPs) is considered a major challenge in genome annotation because they are linked to several important applied and research applications of cellular functions e.g., in the study of the biological, biophysical, and biochemical effects of antibiotics, drugs, and steroids on DNA. This paper presents an efficient approach for DNABPs identification based on deep transfer learning, named “DTLM-DBP.” Two transfer learning methods are used in the identification process. The first is based on the pre-trained deep learning model as a feature’s extractor and classifier. Two different pre-trained Convolutional Neural Networks (CNN), AlexNet 8 and VGG…
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  •   Views:110       Downloads:96        Download PDF
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