Vol.60, No.2, 2019-Table of Contents
  • Design and Performance Comparison of Rotated Y-Shaped Antenna Using Different Metamaterial Surfaces for 5G Mobile Devices
  • Abstract In this paper, a rotated Y-shaped antenna is designed and compared in terms of performance using a conventional and EBG ground planes for future Fifth Generation (5G) cellular communication system. The rotated Y-shaped antenna is designed to transmit at 38 GHz which is one of the most prominent candidate bands for future 5G communication systems. In the design of conventional antenna and metamaterial surfaces (mushroom, slotted), Rogers-5880 substrate having relative permittivity, thickness and loss tangent of 2.2, 0.254 mm, and 0.0009 respectively have been used. The conventional rotated Y-shaped antenna offers a satisfactory wider bandwidth (0.87 GHz) at 38.06 GHz… More
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  • A Comparative Study of Machine Learning Methods for Genre Identification of Classical Arabic Text
  • Abstract The purpose of this study is to evaluate the performance of five supervised machine learning methods for the task of automated genre identification of classical Arabic texts using text most frequent words as features. We design an experiment for comparing five machine-learning methods for the genre identification task for classical Arabic text. We set the data and the stylometric features and vary the classification method to evaluate the performance of each method. Of the five machine learning methods tested, we can conclude that Support Vector Machine (SVM) are generally the most effective. The contribution of this work lies in the… More
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  • Improved Enhanced Dbtma with Contention-Aware Admission Control to Improve the Network Performance in Manets
  • Abstract DBTMA relies entirely on RTS/CTS dialogue for un-collided transmission of data. The purpose is to improve the QoS at MAC layer by developing it over 802.11e standard. However, DBTMA does not guarantee real-time constraints without efficient method for controlling the network loads. The main challenges in MANETs include prediction of the available bandwidth, establishing communication with neighboring nodes and predicting the consumption of bandwidth flow. These challenges are provided with solutions using Contention-Aware Admission Control (CACP) protocol. In this paper, the EDBTMA protocol is combined with CACP protocol that introduces bandwidth calculation using admission control strategy. The calculation includes certain… More
  •   Views:1235       Downloads:808        Download PDF
  • Analysis of Bus Ride Comfort Using Smartphone Sensor Data
  • Abstract Passenger comfort is an important indicator that is often used to measure the quality of public transport services. It may also be a crucial factor in the passenger’s choice of transport mode. The typical method of assessing passenger comfort is through a passenger interview survey which can be tedious. This study aims to investigate the relationship between bus ride comfort based on ride smoothness and the vehicle’s motion detected by the smartphone sensors. An experiment was carried out on a bus fixed route within the University campus where comfort levels were rated on a 3-point scale and recorded at 5-second… More
  •   Views:1072       Downloads:661        Download PDF
  • Heterogeneous Memristive Models Design and Its Application in Information Security
  • Abstract Based on the three-dimensional classic Chua circuit, a nonlinear circuit containing two flux-control memristors is designed. Due to the difference in the design of the characteristic equation of the two magnetron memristors, their position form a symmetrical structure with respect to the capacitor. The existence of chaotic properties is proved by analyzing the stability of the system, including Lyapunov exponent, equilibrium point, eigenvalue, Poincare map, power spectrum, bifurcation diagram et al. Theoretical analysis and numerical calculation show that this heterogeneous memristive model is a hyperchaotic five-dimensional nonlinear dynamical system and has a strong chaotic behavior. Then, the memristive system is… More
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  • Drug Side-Effect Prediction Using Heterogeneous Features and Bipartite Local Models
  • Abstract Drug side-effects impose massive costs on society, leading to almost one-third drug failure in the drug discovery process. Therefore, early identification of potential side-effects becomes vital to avoid risks and reduce costs. Existing computational methods employ few drug features and predict drug side-effects from either drug side or side-effect side separately. In this work, we explore to predict drug side-effects by combining heterogeneous drug features and employing the bipartite local models (BLMs) which fuse predictions from both the drug side and side-effect side. Specifically, we integrate drug chemical structures, drug interacted proteins and drug associated genes into a unified framework… More
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  • RETRACTED: Automatic Arrhythmia Detection Based on Convolutional Neural Networks
  • Abstract ECG signal is of great importance in the clinical diagnosis of various heart diseases. The abnormal origin or conduction of excitation is the electrophysiological mechanism leading to arrhythmia, but the type and frequency of arrhythmia is an important indicator reflecting the stability of cardiac electrical activity. In clinical practice, arrhythmic signals can be classified according to the origin of excitation, the frequency of excitation, or the transmission of excitation. Traditional heart disease diagnosis depends on doctors, and it is influenced by doctors' professional skills and the department's specialty. ECG signal has the characteristics of weak signal, low frequency, large variation,… More
  •   Views:1187       Downloads:906        Download PDF
  • Rigid Medical Image Registration Using Learning-Based Interest Points and Features
  • Abstract For image-guided radiation therapy, radiosurgery, minimally invasive surgery, endoscopy and interventional radiology, one of the important techniques is medical image registration. In our study, we propose a learning-based approach named “FIP-CNNF” for rigid registration of medical image. Firstly, the pixel-level interest points are computed by the full convolution network (FCN) with self-supervise. Secondly, feature detection, descriptor and matching are trained by convolution neural network (CNN). Thirdly, random sample consensus (Ransac) is used to filter outliers, and the transformation parameters are found with the most inliers by iteratively fitting transforms. In addition, we propose “TrFIP-CNNF” which uses transfer learning and fine-tuning… More
  •   Views:1124       Downloads:1026        Download PDF
  • Directional Antenna Intelligent Coverage Method Based on Traversal Optimization Algorithm
  • Abstract Wireless broadband communication is widely used in maneuver command communications systems in many fields, such as military operations, counter-terrorism and disaster relief. How to reasonably formulate the directional antenna coverage strategy according to the mobile terminal dynamic distribution and guide the directional antenna dynamic coverage becomes a practical research topic. In many applications, a temporary wireless boardband base station is required to support wireless signal communications between many terminals from nearby vehicles and staffs. It is therefore important to efficiently set directional antenna while ensuring large enough coverage over dynamically distributed terminals. The wireless broadband base station mostly uses two… More
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  • Binaural Sound Source Localization Based on Convolutional Neural Network
  • Abstract Binaural sound source localization (BSSL) in low signal-to-noise ratio (SNR) and high reverberation environment is still a challenging task. In this paper, a novel BSSL algorithm is proposed by introducing convolutional neural network (CNN). The proposed algorithm first extracts the spatial feature of each sub-band from binaural sound signal, and then combines the features of all sub-bands within one frame to assemble a two-dimensional feature matrix as a grey image. To fully exploit the advantage of the CNN in extracting high-level features from the grey image, the spatial feature matrix of each frame is used as input to train the… More
  •   Views:1044       Downloads:864        Download PDF
  • An Application-Oriented Buffer Management Strategy in Opportunistic Networks
  • Abstract In Opportunistic networks (ONs), buffer management is critical to improve the message exchanging efficiency due to the limited storage space and transmission bandwidth at the wireless edge. Current solutions make message scheduling and drop policy based on assumptions that messages can always been forwarded in a single contact, and all node pairs have the same contact rates. However, such ideal assumptions are invalid for realistic mobility traces of hand-held. Recent studies show that the single contact duration is limited and the mobility of nodes is heterogeneous in reality. In this paper, a buffer management strategy based on contact duration and… More
  •   Views:927       Downloads:649        Download PDF
  • A Review on Deep Learning Approaches to Image Classification and Object Segmentation
  • Abstract Deep learning technology has brought great impetus to artificial intelligence, especially in the fields of image processing, pattern and object recognition in recent years. Present proposed artificial neural networks and optimization skills have effectively achieved large-scale deep learnt neural networks showing better performance with deeper depth and wider width of networks. With the efforts in the present deep learning approaches, factors, e.g., network structures, training methods and training data sets are playing critical roles in improving the performance of networks. In this paper, deep learning models in recent years are summarized and compared with detailed discussion of several typical networks… More
  •   Views:1867       Downloads:971        Download PDF
  • Satellite Cloud-Derived Wind Inversion Algorithm Using GPU
  • Abstract Cloud-derived wind refers to the wind field data product reversely derived through satellite remote sensing cloud images. Satellite cloud-derived wind inversion has the characteristics of large scale, computationally intensive and long time. The most widely used cloud-derived serial--tracer cloud tracking method is the maximum cross-correlation coefficient (MCC) method. In order to overcome the efficiency bottleneck of the cloud-derived serial MCC algorithm, we proposed a parallel cloud-derived wind inversion algorithm based on GPU framework in this paper, according to the characteristics of independence between each wind vector calculation. In this algorithm, each iteration is considered as a thread of GPU cores,… More
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  • An Improved Integration for Trimmed Geometries in Isogeometric Analysis
  • Abstract Trimming techniques are efficient ways to generate complex geometries in Computer-Aided Design (CAD). In this paper, an improved integration for trimmed geometries in isogeometric analysis (IGA) is proposed. The proposed method can improve the accuracy of the approximation and the condition number of the stiffness matrix. In addition, comparing to the traditional approaches, the trimming techniques can reduce the number of the integration elements with much fewer integration points, which improves the computational efficiency significantly. Several examples are illustrated to show the effectiveness of the proposed approach. More
  •   Views:1050       Downloads:916        Download PDF
  • Locating Steganalysis of LSB Matching Based on Spatial and Wavelet Filter Fusion
  • Abstract For the case of that only a single stego image of LSB (Least Significant Bit) matching steganography is available, the existing steganalysis algorithms cannot effectively locate the modified pixels. Therefore, an algorithm is proposed to locate the modified pixels of LSB matching based on spatial and wavelet filter fusion. Firstly, the validity of using the residuals obtained by spatial and wavelet filtering to locate the modified pixels of LSB matching is analyzed. It is pointed out that both of these two kinds of residuals can be used to identify the modified pixels of LSB matching with success rate higher than… More
  •   Views:984       Downloads:648        Download PDF
  • Key Process Protection of High Dimensional Process Data in Complex Production
  • Abstract In order to solve the problem of locating and protecting key processes and detecting outliers efficiently in complex industrial processes. An anomaly detection system which is based on the two-layer model fusion frame is designed in this paper. The key process is located by using the random forest model firstly, then the process data feature selection, dimension reduction and noise reduction are processed. Finally, the validity of the model is verified by simulation experiments. It is shown that this method can effectively reduce the prediction accuracy variance and improve the generalization ability of the traditional anomaly detection model from the… More
  •   Views:915       Downloads:676        Download PDF
  • Collaborative Filtering Recommendation Algorithm Based on Multi-Relationship Social Network
  • Abstract Recommendation system is one of the most common applications in the field of big data. The traditional collaborative filtering recommendation algorithm is directly based on user-item rating matrix. However, when there are huge amounts of user and commodities data, the efficiency of the algorithm will be significantly reduced. Aiming at the problem, a collaborative filtering recommendation algorithm based on multi-relational social networks is proposed. The algorithm divides the multi-relational social networks based on the multi-subnet complex network model into communities by using information dissemination method, which divides the users with similar degree into a community. Then the user-item rating matrix… More
  •   Views:1103       Downloads:897        Download PDF
  • Enabling Comparable Search Over Encrypted Data for IoT with Privacy-Preserving
  • Abstract With the rapid development of cloud computing and Internet of Things (IoT) technology, massive data raises and shuttles on the network every day. To ensure the confidentiality and utilization of these data, industries and companies users encrypt their data and store them in an outsourced party. However, simple adoption of encryption scheme makes the original lose its flexibility and utilization. To address these problems, the searchable encryption scheme is proposed. Different from traditional encrypted data search scheme, this paper focuses on providing a solution to search the data from one or more IoT device by comparing their underlying numerical values.… More
  •   Views:1070       Downloads:784        Download PDF
  • MSICST: Multiple-Scenario Industrial Control System Testbed for Security Research
  • Abstract A security testbed is an important aspect of Industrial Control System (ICS) security research. However, existing testbeds still have many problems in that they cannot fully simulate enterprise networks and ICS attacks. This paper presents a Multiple-Scenario Industrial Control System Testbed (MSICST), a hardware-in-the-loop ICS testbed for security research. The testbed contains four typical process scenarios: thermal power plant, rail transit, smart grid, and intelligent manufacturing. We use a combination of actual physical equipment and software simulations to build the process scenario sand table and use real hardware and software to build the control systems, demilitarized zone, and enterprise zone… More
  •   Views:1114       Downloads:1320        Download PDF
  • Tibetan Sentiment Classification Method Based on Semi-Supervised Recursive Autoencoders
  • Abstract We apply the semi-supervised recursive autoencoders (RAE) model for the sentiment classification task of Tibetan short text, and we obtain a better classification effect. The input of the semi-supervised RAE model is the word vector. We crawled a large amount of Tibetan text from the Internet, got Tibetan word vectors by using Word2vec, and verified its validity through simple experiments. The values of parameter α and word vector dimension are important to the model effect. The experiment results indicate that when α is 0.3 and the word vector dimension is 60, the model works best. Our experiment also shows the… More
  •   Views:1003       Downloads:739        Download PDF
  • MalDetect: A Structure of Encrypted Malware Traffic Detection
  • Abstract Recently, TLS protocol has been widely used to secure the application data carried in network traffic. It becomes more difficult for attackers to decipher messages through capturing the traffic generated from communications of hosts. On the other hand, malwares adopt TLS protocol when accessing to internet, which makes most malware traffic detection methods, such as DPI (Deep Packet Inspection), ineffective. Some literatures use statistical method with extracting the observable data fields exposed in TLS connections to train machine learning classifiers so as to infer whether a traffic flow is malware or not. However, most of them adopt the features based… More
  •   Views:1340       Downloads:1477        Download PDF
  • Robust Re-Weighted Multi-View Feature Selection
  • Abstract In practical application, many objects are described by multi-view features because multiple views can provide a more informative representation than the single view. When dealing with the multi-view data, the high dimensionality is often an obstacle as it can bring the expensive time consumption and an increased chance of over-fitting. So how to identify the relevant views and features is an important issue. The matrix-based multi-view feature selection that can integrate multiple views to select relevant feature subset has aroused widely concern in recent years. The existing supervised multi-view feature selection methods usually concatenate all views into the long vectors… More
  •   Views:1033       Downloads:694        Download PDF
  • Ab Initio Molecular-Dynamics Simulation Liquid and Amorphous Al94-xNi6Lax (x=3-9) Alloys
  • Abstract Ab initio molecular-dynamics simulations have been used to investigate the liquid and amorphous Al94-xNi6Lax (x=3-9) alloys. Through calculating the pair distribution functions and partial coordination numbers, the structure and properties of these alloys are researched, which will help the design bulk metallic glass. The concentration of La atoms can affect the short-range order of Al94-xNi6Lax alloys, which is also studied in this calculation result. More
  •   Views:1059       Downloads:678        Download PDF
  • Fuzzy C-Means Algorithm Automatically Determining Optimal Number of Clusters
  • Abstract In clustering analysis, the key to deciding clustering quality is to determine the optimal number of clusters. At present, most clustering algorithms need to give the number of clusters in advance for clustering analysis of the samples. How to gain the correct optimal number of clusters has been an important topic of clustering validation study. By studying and analyzing the FCM algorithm in this study, an accurate and efficient algorithm used to confirm the optimal number of clusters is proposed for the defects of traditional FCM algorithm. For time and clustering accuracy problems of FCM algorithm and relevant algorithms automatically… More
  •   Views:1024       Downloads:2282        Download PDF
  • A Novel Scene Text Recognition Method Based on Deep Learning
  • Abstract Scene text recognition is one of the most important techniques in pattern recognition and machine intelligence due to its numerous practical applications. Scene text recognition is also a sequence model task. Recurrent neural network (RNN) is commonly regarded as the default starting point for sequential models. Due to the non-parallel prediction and the gradient disappearance problem, the performance of the RNN is difficult to improve substantially. In this paper, a new TRDD network architecture which base on dilated convolution and residual block is proposed, using Convolutional Neural Networks (CNN) instead of RNN realizes the recognition task of sequence texts. Our… More
  •   Views:1080       Downloads:900        Download PDF
  • Multi-Rate Polling: Improve the Performance of Energy Harvesting Backscatter Wireless Networks
  • Abstract In recent years, Researchers have proposed the concept of Energy Harvesting Backscatter Wireless Networks (EHBWN). EHBWN usually consists of one sink and several backscatter nodes. Backscatter nodes harvest energy from their environment and communicate with sink through backscattering the carrier wave transmitted by sink. Although a certain amount of access protocols for Energy Harvesting Wireless Networks have been present, they usually do not take the sink’s receiver sensitivity into account, which makes those protocols unsuitable in practice. In this paper, we first give an analysis of the backscatter channel link budget and the relationship between the effective communication range and… More
  •   Views:1024       Downloads:748        Download PDF
  • A Multi-Objective Decision-Making Approach for the Optimal Location of Electric Vehicle Charging Facilities
  • Abstract Electric vehicles (EVs) are recognized as one of the most promising technologies worldwide to address the fossil fuel energy resource crisis and environmental pollution. As the initial work of EV charging station (EVCS) construction, site selection plays a vital role in its whole life cycle. In this paper, a multi-objective optimization model for the location layout of EVCSs is established when considering various factors such as user demand, investment cost, soil locations, the emergency charging mileage limit, the actual road condition and service network reliability. The model takes the minimum investment cost and the minimum user charging cost as the… More
  •   Views:1863       Downloads:1057        Download PDF
  • A Capacity Improving Scheme in Multi-RSUs Deployed V2I
  • Abstract The communication reliability and system capacity are two of the key performance indicators for Internet of Vehicles (IoV). Existing studies have proposed a variety of technologies to improve reliability and other performance, such as channel selection and power allocation in Vehicle-to-Infrastructure (V2I). However, these researches are mostly applied in a single roadside unit (RSU) scenario without considering inter-cell interference (ICI) of multi-RSUs. In this paper, considering the distribution characteristics of multi-RSUs deployment and corresponding ICI, we propose a reliable uplink transmission scheme to maximize the total capacity and decrease the interference of multi-RSUs (mRSU-DI) in condition of the uplink interruption… More
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