Vol.65, No.2, 2020-Table of Contents
  • Complementary Kalman Filter as a Baseline Vector Estimator for GPS-Based Attitude Determination
  • Abstract The Global Positioning System (GPS) offers the interferometer for attitude determination by processing the carrier phase observables. By using carrier phase observables, the relative positioning is obtained in centimeter level. GPS interferometry has been firstly used in precise static relative positioning, and thereafter in kinematic positioning. The carrier phase differential GPS based on interferometer principles can solve for the antenna baseline vector, defined as the vector between the antenna designated master and one of the slave antennas, connected to a rigid body. Determining the unknown baseline vectors between the antennas sits at the heart of GPS-based attitude determination. The conventional… More
  •   Views:2088       Downloads:1340        Download PDF
  • Second Law Analysis and Optimization of Elliptical Pin Fin Heat Sinks Using Firefly Algorithm
  • Abstract One of the most significant considerations in the design of a heat sink is thermal management due to increasing thermal flux and miniature in size. These heat sinks utilize plate or pin fins depending upon the required heat dissipation rate. They are designed to optimize overall performance. Elliptical pin fin heat sinks enhance heat transfer rates and reduce the pumping power. In this study, the Firefly Algorithm is implemented to optimize heat sinks with elliptical pin-fins. The pin-fins are arranged in an inline fashion. The natureinspired metaheuristic algorithm performs powerfully and efficiently in solving numerical global optimization problems. Based on… More
  •   Views:1741       Downloads:1209        Download PDF
  • DL-HAR: Deep Learning-Based Human Activity Recognition Framework for Edge Computing
  • Abstract Human activity recognition is commonly used in several Internet of Things applications to recognize different contexts and respond to them. Deep learning has gained momentum for identifying activities through sensors, smartphones or even surveillance cameras. However, it is often difficult to train deep learning models on constrained IoT devices. The focus of this paper is to propose an alternative model by constructing a Deep Learning-based Human Activity Recognition framework for edge computing, which we call DL-HAR. The goal of this framework is to exploit the capabilities of cloud computing to train a deep learning model and deploy it on lesspowerful… More
  •   Views:2234       Downloads:1409       Cited by:10        Download PDF
  • Mitigating and Monitoring Smart City Using Internet of Things
  • Abstract The present trends in smart world reflects the extensive use of limited resources through information and communication technology. The limited resources like space, mobility, energy, etc., have been consumed rigorously towards creating optimized but smart instances. Thus, a new concept of IoT integrated smart city vision is yet to be proposed which includes a combination of systems like noise and air loss monitoring, web monitoring and fire detection systems, smart waste bin systems, etc., that have not been clearly addressed in the previous researches. This paper focuses on developing an effective system for possible monitoring of losses, traffic management, thus… More
  •   Views:1675       Downloads:1125       Cited by:8        Download PDF
  • Discrete Wavelet Transmission and Modified PSO with ACO Based Feed Forward Neural Network Model for Brain Tumour Detection
  • Abstract In recent years, the development in the field of computer-aided diagnosis (CAD) has increased rapidly. Many traditional machine learning algorithms have been proposed for identifying the pathological brain using magnetic resonance images. The existing algorithms have drawbacks with respect to their accuracy, efficiency, and limited learning processes. To address these issues, we propose a pathological brain tumour detection method that utilizes the Weiner filter to improve the image contrast, 2D- discrete wavelet transformation (2D-DWT) to extract the features, probabilistic principal component analysis (PPCA) and linear discriminant analysis (LDA) to normalize and reduce the features, and a feed-forward neural network (FNN)… More
  •   Views:1579       Downloads:1139       Cited by:1        Download PDF
  • Context Based Adoption of Ranking and Indexing Measures for Cricket Team Ranks
  • Abstract There is an international cricket governing body that ranks the expertise of all the cricket playing nations, known as the International Cricket Council (ICC). The ranking system followed by the ICC relies on the winnings and defeats of the teams. The model used by the ICC to implement rankings is deficient in certain key respects. It ignores key factors like winning margin and strength of the opposition. Various measures of the ranking concept are presented in this research. The proposed methods adopt the concepts of h-Index and PageRank for presenting more comprehensive ranking metrics. The proposed approaches not only rank… More
  •   Views:1810       Downloads:1198        Download PDF
  • A Smart English Text Zero-Watermarking Approach Based on Third-Level Order and Word Mechanism of Markov Model
  • Abstract Text information is principally dependent on the natural languages. Therefore, improving security and reliability of text information exchanged via internet network has become the most difficult challenge that researchers encounter. Content authentication and tampering detection of digital contents have become a major concern in the area of communication and information exchange via the Internet. In this paper, an intelligent text Zero-Watermarking approach SETZWMWMM (Smart English Text Zero-Watermarking Approach Based on Mid-Level Order and Word Mechanism of Markov Model) has been proposed for the content authentication and tampering detection of English text contents. The SETZWMWMM approach embeds and detects the watermark… More
  •   Views:1480       Downloads:1022        Download PDF
  • Three-Dimensional Isogeometric Analysis of Flexoelectricity with MATLAB Implementation
  • Abstract Flexoelectricity is a general electromechanical phenomenon where the electric polarization exhibits a linear dependency to the gradient of mechanical strain and vice versa. The truncated pyramid compression test is among the most common setups to estimate the flexoelectric effect. We present a three-dimensional isogeometric formulation of flexoelectricity with its MATLAB implementation for a truncated pyramid setup. Besides educational purposes, this paper presents a precise computational model to illustrate how the localization of strain gradients around pyramidal boundary shapes contributes in generation of electrical energy. The MATLAB code is supposed to help learners in the Isogeometric Analysis and Finite Elements Methods… More
  •   Views:2141       Downloads:1394       Cited by:8        Download PDF
  • Success Rate Queue-Based Relocation Algorithm of Sensory Network to Overcome Non-Uniformly Distributed Obstacles
  • Abstract With the recent development of big data technology that collects and analyzes various data, the technology that continuously collects and analyzes the observed data is also drawing attention. Moreover, its importance is growing in data collection in areas where people cannot access. In general, it is not easy to properly deploy IoT wireless devices for data collection in these areas, and it is also inappropriate to use general wheelbased mobile devices for relocation. Recently, researches have been actively carried out on hopping moving models in place of wheel-based movement for the inaccessible regions. The majority of studies, however, so far… More
  •   Views:1639       Downloads:947       Cited by:1        Download PDF
  • A Direct Data-Cluster Analysis Method Based on Neutrosophic Set Implication
  • Abstract Raw data are classified using clustering techniques in a reasonable manner to create disjoint clusters. A lot of clustering algorithms based on specific parameters have been proposed to access a high volume of datasets. This paper focuses on cluster analysis based on neutrosophic set implication, i.e., a k-means algorithm with a threshold-based clustering technique. This algorithm addresses the shortcomings of the k-means clustering algorithm by overcoming the limitations of the threshold-based clustering algorithm. To evaluate the validity of the proposed method, several validity measures and validity indices are applied to the Iris dataset (from the University of California, Irvine, Machine… More
  •   Views:1590       Downloads:1008        Download PDF
  • Roman Urdu News Headline Classification Empowered with Machine Learning
  • Abstract Roman Urdu has been used for text messaging over the Internet for years especially in Indo-Pak Subcontinent. Persons from the subcontinent may speak the same Urdu language but they might be using different scripts for writing. The communication using the Roman characters, which are used in the script of Urdu language on social media, is now considered the most typical standard of communication in an Indian landmass that makes it an expensive information supply. English Text classification is a solved problem but there have been only a few efforts to examine the rich information supply of Roman Urdu in the… More
  •   Views:2411       Downloads:1168       Cited by:2        Download PDF
  • Statistical Inference of User Experience of Multichannel Audio on Mobile Phones
  • Abstract Mobile phones and other handheld electronic devices are now ubiquitous and play an important role in our everyday lives. Over the last decade, we have seen a sharp rise in the sophistication of both hardware and software for these devices, thus significantly increasing their utility and use. Electronic devices are now commonly used for the streaming of audio and video and for the regular playback of music. Multichannel audio has now become a popular format and with recent updates in software, the latest audio codecs that support this format can effectively be played back on most electronic devices. As a… More
  •   Views:1529       Downloads:1080       Cited by:1        Download PDF
  • Polynomials of Degree-Based Indices for Three-Dimensional Mesh Network
  • Abstract In order to study the behavior and interconnection of network devices, graphs structures are used to formulate the properties in terms of mathematical models. Mesh network (meshnet) is a LAN topology in which devices are connected either directly or through some intermediate devices. These terminating and intermediate devices are considered as vertices of graph whereas wired or wireless connections among these devices are shown as edges of graph. Topological indices are used to reflect structural property of graphs in form of one real number. This structural invariant has revolutionized the field of chemistry to identify molecular descriptors of chemical compounds.… More
  •   Views:1480       Downloads:981       Cited by:7        Download PDF
  • Secret Image Communication Scheme Based on Visual Cryptography and Tetrolet Tiling Patterns
  • Abstract Visual cryptographic scheme is specially designed for secret image sharing in the form of shadow images. The basic idea of visual cryptography is to construct two or more secret shares from the original image in the form of chaotic image. In this paper, a novel secret image communication scheme based on visual cryptography and Tetrolet tiling patterns is proposed. The proposed image communication scheme will break the secret image into more shadow images based on the Tetrolet tiling patterns. The secret image is divided into 4×4 blocks of tetrominoes and employs the concept of visual cryptography to hide the secret… More
  •   Views:1680       Downloads:1009       Cited by:3        Download PDF
  • Case Study: Spark GPU-Enabled Framework to Control COVID-19 Spread Using Cell-Phone Spatio-Temporal Data
  • Abstract Nowadays, the world is fighting a dangerous form of Coronavirus that represents an emerging pandemic. Since its early appearance in China Wuhan city, many countries undertook several strict regulations including lockdowns and social distancing measures. Unfortunately, these procedures have badly impacted the world economy. Detecting and isolating positive/probable virus infected cases using a tree tracking mechanism constitutes a backbone for containing and resisting such fast spreading disease. For helping this hard effort, this research presents an innovative case study based on big data processing techniques to build a complete tracking system able to identify the central areas of infected/suspected people,… More
  •   Views:2168       Downloads:1427       Cited by:5        Download PDF
  • Ensemble Strategy for Insider Threat Detection from User Activity Logs
  • Abstract In the information era, the core business and confidential information of enterprises/organizations is stored in information systems. However, certain malicious inside network users exist hidden inside the organization; these users intentionally or unintentionally misuse the privileges of the organization to obtain sensitive information from the company. The existing approaches on insider threat detection mostly focus on monitoring, detecting, and preventing any malicious behavior generated by users within an organization’s system while ignoring the imbalanced ground-truth insider threat data impact on security. To this end, to be able to detect insider threats more effectively, a data processing tool was developed to… More
  •   Views:1714       Downloads:1279       Cited by:1        Download PDF
  • End-to-End Latency Evaluation of the Sat5G Network Based on Stochastic Network Calculus
  • Abstract Simultaneous use of heterogeneous radio access technologies to increase the performance of real-time, reliability and capacity is an inherent feature of satellite-5G integrated network (Sat5G). However, there is still a lack of theoretical characterization of whether the network can satisfy the end-to-end transmission performance for latencysensitive service. To this end, we build a tandem model considering the connection relationship between the various components in Sat5G network architecture, and give an end-to-end latency calculation function based on this model. By introducing stochastic network calculus, we derive the relationship between the end-to-end latency bound and the violation probability considering the traffic characteristics… More
  •   Views:1419       Downloads:1054       Cited by:2        Download PDF
  • Fast Compass Alignment for Strapdown Inertial Navigation System
  • Abstract Initial alignment is the precondition for strapdown inertial navigation system (SINS) to navigate. Its two important indexes are accuracy and rapidity, the accuracy of the initial alignment is directly related to the working accuracy of SINS, but in selfalignment, the two indexes are often contradictory. In view of the limitations of conventional data processing algorithms, a novel method of compass alignment based on stored data and repeated navigation calculation for SINS is proposed. By means of data storage, the same data is used in different stages of the initial alignment, which is beneficial to shorten the initial alignment time and… More
  •   Views:1343       Downloads:820        Download PDF
  • Ensemble Learning Based on GBDT and CNN for Adoptability Prediction
  • Abstract By efficiently and accurately predicting the adoptability of pets, shelters and rescuers can be positively guided on improving attraction of pet profiles, reducing animal suffering and euthanization. Previous prediction methods usually only used a single type of content for training. However, many pets contain not only textual content, but also images. To make full use of textual and visual information, this paper proposed a novel method to process pets that contain multimodal information. We employed several CNN (Convolutional Neural Network) based models and other methods to extract features from images and texts to obtain the initial multimodal representation, then reduce… More
  •   Views:1652       Downloads:953       Cited by:1        Download PDF
  • Rate-Energy Tradeoff for Wireless Simultaneous Information and Power Transfer in Full-Duplex and Half-Duplex Systems
  • Abstract In this paper, we study the rate-energy tradeoff for wireless simultaneous information and power transfer in full-duplex and half-duplex scenarios. To this end, the weighting function of energy efficiency and transmission rate, as rate-energy tradeoff metric is first introduced and the metric optimization problem is formulated. Applying Karush-Kuhn-Tucker (KKT) conditions for Lagrangian optimality and a series of mathematical approximations, the metric optimization problem can be simplified. The closed-form solution of the power ratio is obtained, building direct relationship between power ratio and the rate-energy tradeoff metric. By choosing power ratio, one can make the tradeoff between information rate and harvested… More
  •   Views:1187       Downloads:777       Cited by:2        Download PDF
  • Remote Sensing Image Classification Algorithm Based on Texture Feature and Extreme Learning Machine
  • Abstract With the development of satellite technology, the satellite imagery of the earth’s surface and the whole surface makes it possible to survey surface resources and master the dynamic changes of the earth with high efficiency and low consumption. As an important tool for satellite remote sensing image processing, remote sensing image classification has become a hot topic. According to the natural texture characteristics of remote sensing images, this paper combines different texture features with the Extreme Learning Machine, and proposes a new remote sensing image classification algorithm. The experimental tests are carried out through the standard test dataset SAT-4 and… More
  •   Views:1484       Downloads:922       Cited by:6        Download PDF
  • Quantum Hierarchical Agglomerative Clustering Based on One Dimension Discrete Quantum Walk with Single-Point Phase Defects
  • Abstract As an important branch of machine learning, clustering analysis is widely used in some fields, e.g., image pattern recognition, social network analysis, information security, and so on. In this paper, we consider the designing of clustering algorithm in quantum scenario, and propose a quantum hierarchical agglomerative clustering algorithm, which is based on one dimension discrete quantum walk with single-point phase defects. In the proposed algorithm, two nonclassical characters of this kind of quantum walk, localization and ballistic effects, are exploited. At first, each data point is viewed as a particle and performed this kind of quantum walk with a parameter,… More
  •   Views:1372       Downloads:801        Download PDF
  • Empirical Analysis of Agricultural Cultural Resources Value Evaluation under DEA Model
  • Abstract Agricultural culture is a productive activity about education and management. It aims at high efficiency and high quality, uses technology as its means, and takes nature as its carrier. Agricultural cultural resources are the product of the rapid development of modern economy. It promotes the development of the national economy and profoundly affects people's production and life. DEA model, also known as data envelope analysis method, is an algorithm that uses multiple data decision units for input and output training to obtain the final model. This article explains the concept and basic characteristics of agricultural culture. Through questionnaire surveys and… More
  •   Views:1433       Downloads:849        Download PDF
  • An Improved Differential Fault Analysis on Block Cipher KLEIN-64
  • Abstract KLEIN-64 is a lightweight block cipher designed for resource-constrained environment, and it has advantages in software performance and hardware implementation. Recent investigation shows that KLEIN-64 is vulnerable to differential fault attack (DFA). In this paper, an improved DFA is performed to KLEIN-64. It is found that the differential propagation path and the distribution of the S-box can be fully utilized to distinguish the correct and wrong keys when a half-byte fault is injected in the 10th round. By analyzing the difference matrix before the last round of S-box, the location of fault injection can be limited to a small range.… More
  •   Views:1244       Downloads:832       Cited by:2        Download PDF
  • Adversarial Attacks on License Plate Recognition Systems
  • Abstract The license plate recognition system (LPRS) has been widely adopted in daily life due to its efficiency and high accuracy. Deep neural networks are commonly used in the LPRS to improve the recognition accuracy. However, researchers have found that deep neural networks have their own security problems that may lead to unexpected results. Specifically, they can be easily attacked by the adversarial examples that are generated by adding small perturbations to the original images, resulting in incorrect license plate recognition. There are some classic methods to generate adversarial examples, but they cannot be adopted on LPRS directly. In this paper,… More
  •   Views:1764       Downloads:914       Cited by:5        Download PDF
  • Picture-Induced EEG Signal Classification Based on CVC Emotion Recognition System
  • Abstract Emotion recognition systems are helpful in human–machine interactions and Intelligence Medical applications. Electroencephalogram (EEG) is closely related to the central nervous system activity of the brain. Compared with other signals, EEG is more closely associated with the emotional activity. It is essential to study emotion recognition based on EEG information. In the research of emotion recognition based on EEG, it is a common problem that the results of individual emotion classification vary greatly under the same scheme of emotion recognition, which affects the engineering application of emotion recognition. In order to improve the overall emotion recognition rate of the emotion… More
  •   Views:1475       Downloads:902       Cited by:1        Download PDF
  • Software Defect Prediction Based on Non-Linear Manifold Learning and Hybrid Deep Learning Techniques
  • Abstract Software defect prediction plays a very important role in software quality assurance, which aims to inspect as many potentially defect-prone software modules as possible. However, the performance of the prediction model is susceptible to high dimensionality of the dataset that contains irrelevant and redundant features. In addition, software metrics for software defect prediction are almost entirely traditional features compared to the deep semantic feature representation from deep learning techniques. To address these two issues, we propose the following two solutions in this paper: (1) We leverage a novel non-linear manifold learning method - SOINN Landmark Isomap (SLIsomap) to extract the… More
  •   Views:2172       Downloads:910       Cited by:3        Download PDF
  • A Robust Resource Allocation Scheme for Device-to-Device Communications Based on Q-Learning
  • Abstract One of the most effective technology for the 5G mobile communications is Device-to-device (D2D) communication which is also called terminal pass-through technology. It can directly communicate between devices under the control of a base station and does not require a base station to forward it. The advantages of applying D2D communication technology to cellular networks are: It can increase the communication system capacity, improve the system spectrum efficiency, increase the data transmission rate, and reduce the base station load. Aiming at the problem of co-channel interference between the D2D and cellular users, this paper proposes an efficient algorithm for resource… More
  •   Views:1579       Downloads:861       Cited by:4        Download PDF
  • Quantum Electronic Contract Scheme Based on Single Photon
  • Abstract An electronic contract is a contract signed by electronic means, which is widely used in electronic commerce activities. In recent years, with the rapid development of quantum cryptography technology, the quantum electronic contract has been widely studied by researchers. Supported by the basic principles of quantum mechanics, a quantum electronic contract scheme based on the single photon is proposed in this paper. In this scheme, two copies of the same contract are signed by both parties involved, and then a copy of each contract is sent to a trusted third party. The trusted third party verifies the signatures of both… More
  •   Views:1092       Downloads:806        Download PDF
  • A Two-Dimension Time-Domain Comparator for Low Power SAR ADCs
  • Abstract This paper presents a two-dimension time-domain comparator suitable for low power successive-approximation register (SAR) analog-to-digital converters (ADCs). The proposed two-dimension time-domain comparator consists of a ring oscillator collapsebased comparator and a counter. The propagation delay of a voltage controlled ring oscillator depends on the input. Thus, the comparator can automatically change the comparison time according to its input difference, which can adjust the power consumption of the comparator dynamically without any control logic. And a counter is utilized to count the cycle needed to finish a comparison when the input difference is small. Thus, the proposed comparator can not only… More
  •   Views:1246       Downloads:734        Download PDF
  • Blockzone: A Decentralized and Trustworthy Data Plane for DNS
  • Abstract The domain name system (DNS) provides a mapping service between memorable names and numerical internet protocol addresses, and it is a critical infrastructure of the Internet. The authenticity of DNS resolution results is crucial for ensuring the accessibility of Internet services. Hundreds of supplementary specifications of protocols have been proposed to compensate for the security flaws of DNS. However, DNS security incidents still occur frequently. Although DNS is a distributed system, for a specified domain name, only authorized authoritative servers can resolve it. Other servers must obtain the resolution result through a recursive or iterative resolving procedure, which renders DNS… More
  •   Views:1540       Downloads:1026        Download PDF
  • A Trust Value Sharing Scheme in Heterogeneous Identity Federation Topologies
  • Abstract Recent developments in heterogeneous identity federation systems have heightened the need for the related trust management system. The trust management system evaluates, manages, and shares users’ trust values. The service provider (SP) members of the federation system rely on users’ trust values to determine which type and quality of service will be provided to the users. While identity federation systems have the potential to help federated users save time and energy and improve service experience, the benefits also come with significant privacy risks. So far, there has been little discussion about the privacy protection of users in heterogeneous identity federation… More
  •   Views:1138       Downloads:765        Download PDF
  • Proportional Fairness-Based Power Allocation Algorithm for Downlink NOMA 5G Wireless Networks
  • Abstract Non-orthogonal multiple access (NOMA) is one of the key 5G technology which can improve spectrum efficiency and increase the number of user connections by utilizing the resources in a non-orthogonal manner. NOMA allows multiple terminals to share the same resource unit at the same time. The receiver usually needs to configure successive interference cancellation (SIC). The receiver eliminates co-channel interference (CCI) between users and it can significantly improve the system throughput. In order to meet the demands of users and improve fairness among them, this paper proposes a new power allocation scheme. The objective is to maximize user fairness by… More
  •   Views:1587       Downloads:851       Cited by:2        Download PDF
  • Recommendation Algorithm Based on Probabilistic Matrix Factorization with Adaboost
  • Abstract A current problem in diet recommendation systems is the matching of food preferences with nutritional requirements, taking into account individual characteristics, such as body weight with individual health conditions, such as diabetes. Current dietary recommendations employ association rules, content-based collaborative filtering, and constraint-based methods, which have several limitations. These limitations are due to the existence of a special user group and an imbalance of non-simple attributes. Making use of traditional dietary recommendation algorithm researches, we combine the Adaboost classifier with probabilistic matrix factorization. We present a personalized diet recommendation algorithm by taking advantage of probabilistic matrix factorization via Adaboost. A… More
  •   Views:1450       Downloads:824        Download PDF
  • An Adjust Duty Cycle Method for Optimized Congestion Avoidance and Reducing Delay for WSNs
  • Abstract With the expansion of the application range and network scale of wireless sensor networks in recent years, WSNs often generate data surges and delay queues during the transmission process, causing network paralysis, even resulting in local or global congestion. In this paper, a dynamically Adjusted Duty Cycle for Optimized Congestion based on a real-time Queue Length (ADCOC) scheme is proposed. In order to improve the resource utilization rate of network nodes, we carried out optimization analysis based on the theory and applied it to the adjustment of the node’s duty cycle strategy. Using this strategy to ensure that the network… More
  •   Views:1541       Downloads:757       Cited by:2        Download PDF
  • A Middleware for Polyglot Persistence and Data Portability of Big Data PaaS Cloud Applications
  • Abstract Vendor lock-in can occur at any layer of the cloud stack-Infrastructure, Platform, and Software-as-a-service. This paper covers the vendor lock-in issue at Platform as a Service (PaaS) level where applications can be created, deployed, and managed without worrying about the underlying infrastructure. These applications and their persisted data on one PaaS provider are not easy to port to another provider. To overcome this issue, we propose a middleware to abstract and make the database services as cloud-agnostic. The middleware supports several SQL and NoSQL data stores that can be hosted and ported among disparate PaaS providers. It facilitates the developers… More
  •   Views:1323       Downloads:837       Cited by:2        Download PDF
  • A Novel Method for Node Connectivity with Adaptive Dragonfly Algorithm and Graph-Based m-Connection Establishment in MANET
  • Abstract Maximizing network lifetime is measured as the primary issue in Mobile Adhoc Networks (MANETs). In geographically routing based models, packet transmission seems to be more appropriate in dense circumstances. The involvement of the Heuristic model directly is not appropriate to offer an effectual solution as it becomes NP-hard issues; therefore investigators concentrate on using Meta-heuristic approaches. Dragonfly Optimization (DFO) is an effective meta-heuristic approach to resolve these problems by providing optimal solutions. Moreover, Meta-heuristic approaches (DFO) turn to be slower in convergence problems and need proper computational time while expanding network size. Thus, DFO is adaptively improved as Adaptive Dragonfly… More
  •   Views:1360       Downloads:792        Download PDF
  • Quantum Algorithms and Experiment Implementations Based on IBM Q
  • Abstract With the rapid development of quantum theory and technology in recent years, especially the emergence of some quantum cloud computing platforms, more and more researchers are not satisfied with the theoretical derivation and simulation verification of quantum computation (especially quantum algorithms), experimental verification on real quantum devices has become a new trend. In this paper, three representative quantum algorithms, namely Deutsch-Jozsa, Grover, and Shor algorithms, are briefly depicted, and then their implementation circuits are presented, respectively. We program these circuits on python with QISKit to connect the remote real quantum devices (i.e., ibmqx4, ibmqx5) on IBM Q to verify these… More
  •   Views:1438       Downloads:933        Download PDF
  • An Improved Deep Fusion CNN for Image Recognition
  • Abstract With the development of Deep Convolutional Neural Networks (DCNNs), the extracted features for image recognition tasks have shifted from low-level features to the high-level semantic features of DCNNs. Previous studies have shown that the deeper the network is, the more abstract the features are. However, the recognition ability of deep features would be limited by insufficient training samples. To address this problem, this paper derives an improved Deep Fusion Convolutional Neural Network (DF-Net) which can make full use of the differences and complementarities during network learning and enhance feature expression under the condition of limited datasets. Specifically, DF-Net organizes two… More
  •   Views:1405       Downloads:940       Cited by:4        Download PDF
  • Paillier-Based Fuzzy Multi-Keyword Searchable Encryption Scheme with Order-Preserving
  • Abstract Efficient multi-keyword fuzzy search over encrypted data is a desirable technology for data outsourcing in cloud storage. However, the current searchable encryption solutions still have deficiencies in search efficiency, accuracy and multiple data owner support. In this paper, we propose an encrypted data searching scheme that can support multiple keywords fuzzy search with order preserving (PMS). First, a new spelling correction algorithm-(Possibility-Levenshtein based Spelling Correction) is proposed to correct user input errors, so that fuzzy keywords input can be supported. Second, Paillier encryption is introduced to calculate encrypted relevance score of multiple keywords for order preserving. Then, a queue-based query… More
  •   Views:1231       Downloads:766       Cited by:2        Download PDF
  • Identifying Honeypots from ICS Devices Using Lightweight Fuzzy Testing
  • Abstract The security issues of industrial control systems (ICSs) have become increasingly prevalent. As an important part of ICS security, honeypots and antihoneypots have become the focus of offensive and defensive confrontation. However, research on ICS honeypots still lacks breakthroughs, and it is difficult to simulate real ICS devices perfectly. In this paper, we studied ICS honeypots to identify and address their weaknesses. First, an intelligent honeypot identification framework is proposed, based on which feature data type requirements and feature data acquisition for honeypot identification is studied. Inspired by vulnerability mining, we propose a feature acquisition approach based on lightweight fuzz… More
  •   Views:1395       Downloads:885       Cited by:1        Download PDF
  • Research on Real-Time High Reliable Network File Distribution Technology
  • Abstract The rapid development of Internet of Things (IoT) technology has made previously unavailable data available, and applications can take advantage of device data for people to visualize, explore, and build complex analyses. As the size of the network and the number of network users continue to increase, network requests tend to aggregate on a small number of network resources, which results in uneven load on network requests. Real-time, highly reliable network file distribution technology is of great importance in the Internet of Things. This paper studies real-time and highly reliable file distribution technology for large-scale networks. In response to this… More
  •   Views:1246       Downloads:796        Download PDF
  • Secure Provenance of Electronic Records Based on Blockchain
  • Abstract At present, the provenance of electronic records is stored centrally. The centralized way of information storage has huge risks. Whether the database itself is destroyed or the communication between the central database and the external interruption occurs, the provenance information of the stored electronic records will not play its role. At the same time, uncertainties such as fires and earthquakes will also pose a potential threat to centralized databases. Moreover, the existing security provenance model is not specifically designed for electronic records. In this paper, a security provenance model of electronic records is constructed based on PREMIS and METS. Firstly,… More
  •   Views:1213       Downloads:816       Cited by:4        Download PDF
  • Tissue Segmentation in Nasopharyngeal CT Images Using TwoStage Learning
  • Abstract Tissue segmentation is a fundamental and important task in nasopharyngeal images analysis. However, it is a challenging task to accurately and quickly segment various tissues in the nasopharynx region due to the small difference in gray value between tissues in the nasopharyngeal image and the complexity of the tissue structure. In this paper, we propose a novel tissue segmentation approach based on a two-stage learning framework and U-Net. In the proposed methodology, the network consists of two segmentation modules. The first module performs rough segmentation and the second module performs accurate segmentation. Considering the training time and the limitation of… More
  •   Views:1457       Downloads:783       Cited by:1        Download PDF
  • A Hybrid Path Planning Method Based on Articulated Vehicle Model
  • Abstract Due to the unique steering mechanism and driving characteristics of the articulated vehicle, a hybrid path planning method based on the articulated vehicle model is proposed to meet the demand of obstacle avoidance and searching the path back and forth of the articulated vehicle. First, Support Vector Machine (SVM) theory is used to obtain the two-dimensional optimal zero potential curve and the maximum margin, and then, several key points are selected from the optimal zero potential curves by using Longest Accessible Path (LAP) method. Next, the Cubic Bezier (CB) curve is adopted to connect the curve that satisfies the curvature… More
  •   Views:1385       Downloads:831       Cited by:2        Download PDF
  • APU-D* Lite: Attack Planning under Uncertainty Based on D* Lite
  • Abstract With serious cybersecurity situations and frequent network attacks, the demands for automated pentests continue to increase, and the key issue lies in attack planning. Considering the limited viewpoint of the attacker, attack planning under uncertainty is more suitable and practical for pentesting than is the traditional planning approach, but it also poses some challenges. To address the efficiency problem in uncertainty planning, we propose the APU-D* Lite algorithm in this paper. First, the pentest framework is mapped to the planning problem with the Planning Domain Definition Language (PDDL). Next, we develop the pentest information graph to organize network information and… More
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  • Computational Analysis of the Effect of Nano Particle Material Motion on Mixed Convection Flow in the Presence of Heat Generation and Absorption
  • Abstract The present study is concerned with the physical behavior of the combined effect of nano particle material motion and heat generation/absorption due to the effect of different parameters involved in prescribed flow model. The formulation of the flow model is based on basic universal equations of conservation of momentum, energy and mass. The prescribed flow model is converted to non-dimensional form by using suitable scaling. The obtained transformed equations are solved numerically by using finite difference scheme. For the analysis of above said behavior the computed numerical data for fluid velocity, temperature profile, and mass concentration for several constraints that… More
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  • Who Will Come: Predicting Freshman Registration Based on Decision Tree
  • Abstract The registration rate of freshmen has been a great concern at many colleges and universities, particularly private institutions. Traditionally, there are two inquiry methods: telephone and tuition-payment-status. Unfortunately, the former is not only time-consuming but also suffers from the fact that many students tend to keep their choices secret. On the other hand, the latter is not always feasible because only few students are willing to pay their university tuition fees in advance. It is often believed that it is impossible to predict incoming freshmen’s choice of university due to the large amount of subjectivity. However, if we look at… More
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  • Research on Data Extraction and Analysis of Software Defect in IoT Communication Software
  • Abstract Software defect feature selection has problems of feature space dimensionality reduction and large search space. This research proposes a defect prediction feature selection framework based on improved shuffled frog leaping algorithm (ISFLA).Using the two-level structure of the framework and the improved hybrid leapfrog algorithm's own advantages, the feature values are sorted, and some features with high correlation are selected to avoid other heuristic algorithms in the defect prediction that are easy to produce local The case where the convergence rate of the optimal or parameter optimization process is relatively slow. The framework improves generalization of predictions of unknown data samples… More
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  • An Improved Binary Search Anti-Collision Protocol for RFID Tag Identification
  • Abstract Radio frequency identification (RFID) has been widespread used in massive items tagged domains. However, tag collision increases both time and energy consumption of RFID network. Tag collision can seriously affect the success of tag identification. An efficient anti-collision protocol is very crucially in RFID system. In this paper, an improved binary search anti-collision protocol namely BRTP is proposed to cope with the tag collision concern, which introduces a Bi-response mechanism. In Biresponse mechanism, two groups of tags allowed to reply to the reader in the same slot. According to Bi-response mechanism, the BRTP strengthens the tag identification of RFID network… More
  •   Views:1564       Downloads:860       Cited by:2        Download PDF