Home / Journals / CSSE / Vol.36, No.1, 2021
  • Open Access

    ARTICLE

    Hybrid Cloud Architecture for Higher Education System

    Omar Nooh Almotiry1, Mohemmed Sha2,*, Mohamudha Parveen Rahamathulla3, Omer Salih Dawood Omer2
    Computer Systems Science and Engineering, Vol.36, No.1, pp. 1-12, 2021, DOI:10.32604/csse.2021.014267
    Abstract As technology improves, several modernization efforts are taken in the process of teaching and learning. An effective education system should maintain global connectivity, federate security and deliver self-access to its services. The cloud computing services transform the current education system to an advanced one. There exist several tools and services to make teaching and learning more interesting. In the higher education system, the data flow and basic operations are almost the same. These systems need to access cloud-based applications and services for their operational advancement and flexibility. Architecting a suitable cloud-based education system will leverage all the benefits of the… More >

  • Open Access

    ARTICLE

    A Model Transformation Approach for Detecting Distancing Violations in Weighted Graphs

    Ahmad F. Subahi*
    Computer Systems Science and Engineering, Vol.36, No.1, pp. 13-39, 2021, DOI:10.32604/csse.2021.014376
    Abstract This work presents the design of an Internet of Things (IoT) edge-based system based on model transformation and complete weighted graph to detect violations of social distancing measures in indoor public places. A wireless sensor network based on Bluetooth Low Energy is introduced as the infrastructure of the proposed design. A hybrid model transformation strategy for generating a graph database to represent groups of people is presented as a core middleware layer of the detecting system’s proposed architectural design. A Neo4j graph database is used as a target implementation generated from the proposed transformational system to store all captured real-time… More >

  • Open Access

    ARTICLE

    Monitoring of Unaccounted for Gas in Energy Domain Using Semantic Web Technologies

    Kausar Parveen1,*, Ghalib A. Shah2, Muhammad Aslam3, Amjad Farooq3
    Computer Systems Science and Engineering, Vol.36, No.1, pp. 41-56, 2021, DOI:10.32604/csse.2021.013787
    Abstract Smart Urbanization has increased tremendously over the last few years, and this has exacerbated problems in all areas of life, especially in the energy sector. The Internet of Things (IoT) is providing effective solutions in gas distribution, transmission and billing through very sophisticated sensory devices and software. Billions of heterogeneous devices link to each other in smart urbanization, and this has led to the Semantic interoperability (SI) problem between the connected devices. In the energy field, such as electricity and gas, several devices are interlinked. These devices are competent for their specific operational role but unable to communicate across the… More >

  • Open Access

    ARTICLE

    Automatic Channel Detection Using DNN on 2D Seismic Data

    Fahd A. Alhaidari1, Saleh A. Al-Dossary2, Ilyas A. Salih1,*, Abdlrhman M. Salem1, Ahmed S. Bokir1, Mahmoud O. Fares1, Mohammed I. Ahmed1, Mohammed S. Ahmed1
    Computer Systems Science and Engineering, Vol.36, No.1, pp. 57-67, 2021, DOI:10.32604/csse.2021.013843
    Abstract Geologists interpret seismic data to understand subsurface properties and subsequently to locate underground hydrocarbon resources. Channels are among the most important geological features interpreters analyze to locate petroleum reservoirs. However, manual channel picking is both time consuming and tedious. Moreover, similar to any other process dependent on human intervention, manual channel picking is error prone and inconsistent. To address these issues, automatic channel detection is both necessary and important for efficient and accurate seismic interpretation. Modern systems make use of real-time image processing techniques for different tasks. Automatic channel detection is a combination of different mathematical methods in digital image… More >

  • Open Access

    ARTICLE

    Impact of Distance Measures on the Performance of AIS Data Clustering

    Marta Mieczyńska1,*, Ireneusz Czarnowski2
    Computer Systems Science and Engineering, Vol.36, No.1, pp. 69-82, 2021, DOI:10.32604/csse.2021.014327
    Abstract Automatic Identification System (AIS) data stream analysis is based on the AIS data of different vessel’s behaviours, including the vessels’ routes. When the AIS data consists of outliers, noises, or are incomplete, then the analysis of the vessel’s behaviours is not possible or is limited. When the data consists of outliers, it is not possible to automatically assign the AIS data to a particular vessel. In this paper, a clustering method is proposed to support the AIS data analysis, to qualify noises and outliers with respect to their suitability, and finally to aid the reconstruction of the vessel’s trajectory. In… More >

  • Open Access

    ARTICLE

    Bivariate Beta–Inverse Weibull Distribution: Theory and Applications

    Ali Algarni, Muhammad Qaiser Shahbaz*
    Computer Systems Science and Engineering, Vol.36, No.1, pp. 83-100, 2021, DOI:10.32604/csse.2021.014342
    Abstract Probability distributions have been in use for modeling of random phenomenon in various areas of life. Generalization of probability distributions has been the area of interest of several authors in the recent years. Several situations arise where joint modeling of two random phenomenon is required. In such cases the bivariate distributions are needed. Development of the bivariate distributions necessitates certain conditions, in a field where few work has been performed. This paper deals with a bivariate beta-inverse Weibull distribution. The marginal and conditional distributions from the proposed distribution have been obtained. Expansions for the joint and conditional density functions for… More >

  • Open Access

    ARTICLE

    Multi Criteria Decision Making System for Parking System

    Manjur Kolhar*, Abdalla Alameen
    Computer Systems Science and Engineering, Vol.36, No.1, pp. 101-116, 2021, DOI:10.32604/csse.2021.014915
    Abstract System supported smart parking can reduce traffic by making it stress free to locate empty parking spaces, hence lowering the risk of unfocussed driving. In this study, we propose a smart parking system using deep learning and an application-based approach. This system has two modules, one module detects and recognizes a license plate (LP), and the other selects a parking space; both modules use deep learning techniques. We used two modules that work independently to detect and recognize an LP by using an image of the vehicle. To detect parking space, only deep learning techniques were used. The two modules… More >

  • Open Access

    ARTICLE

    Fuzzy Adaptive Filtering-Based Energy Management for Hybrid Energy Storage System

    Xizheng Zhang1,2,*, Zhangyu Lu1, Chongzhuo Tan1, Zeyu Wang1
    Computer Systems Science and Engineering, Vol.36, No.1, pp. 117-130, 2021, DOI:10.32604/csse.2021.014081
    Abstract Regarding the problem of the short driving distance of pure electric vehicles, a battery, super-capacitor, and DC/DC converter are combined to form a hybrid energy storage system (HESS). A fuzzy adaptive filtering-based energy management strategy (FAFBEMS) is proposed to allocate the required power of the vehicle. Firstly, the state of charge (SOC) of the super-capacitor is limited according to the driving/braking mode of the vehicle to ensure that it is in a suitable working state, and fuzzy rules are designed to adaptively adjust the filtering time constant, to realize reasonable power allocation. Then, the positive and negative power are determined,… More >

  • Open Access

    ARTICLE

    The Bivariate Transmuted Family of Distributions: Theory and Applications

    Jumanah Ahmed Darwish, Lutfiah Ismail Al turk, Muhammad Qaiser Shahbaz*
    Computer Systems Science and Engineering, Vol.36, No.1, pp. 131-144, 2021, DOI:10.32604/csse.2021.014764
    Abstract The bivariate distributions are useful in simultaneous modeling of two random variables. These distributions provide a way to model models. The bivariate families of distributions are not much widely explored and in this article a new family of bivariate distributions is proposed. The new family will extend the univariate transmuted family of distributions and will be helpful in modeling complex joint phenomenon. Statistical properties of the new family of distributions are explored which include marginal and conditional distributions, conditional moments, product and ratio moments, bivariate reliability and bivariate hazard rate functions. The maximum likelihood estimation (MLE) for parameters of the… More >

  • Open Access

    ARTICLE

    Multi-Object Detection of Chinese License Plate in Complex Scenes

    Dan Liu1,3, Yajuan Wu1, Yuxin He2, Lu Qin2, Bochuan Zheng2,3,*
    Computer Systems Science and Engineering, Vol.36, No.1, pp. 145-156, 2021, DOI:10.32604/csse.2021.014646
    Abstract Multi-license plate detection in complex scenes is still a challenging task because of multiple vehicle license plates with different sizes and classes in the images having complex background. The edge features of high-density distribution and the high curvature features of stroke turning of Chinese character are important signs to distinguish Chinese license plate from other objects. To accurately detect multiple vehicle license plates with different sizes and classes in complex scenes, a multi-object detection of Chinese license plate method based on improved YOLOv3 network was proposed in this research. The improvements include replacing the residual block of the YOLOv3 backbone… More >

  • Open Access

    ARTICLE

    Design and Implementation of Museum Educational Content Based on Mobile Augmented Reality

    Jin Qian1,2, Juan Cheng1,2,*, Yixing Zeng1, Tjondronegoro Dian W.3
    Computer Systems Science and Engineering, Vol.36, No.1, pp. 157-173, 2021, DOI:10.32604/csse.2021.014258
    Abstract In the digital age, museums are becoming increasingly integrated with media technology. The interactive mode of museum education brought about by new digital communication technology can increase the audience’s participation and interest in museum education content. This paper attempts to use Mobile Augment Reality (MAR) technology to design museum education content under the guidance of the principle of abstraction hierarchy from the theory of education optimization. With the help of MAR technology, museum education content can move up and down at different levels of information abstraction. The purpose is to help the audience move between perceptual knowledge and rational knowledge… More >

  • Open Access

    ARTICLE

    Fast Sentiment Analysis Algorithm Based on Double Model Fusion

    Zhixing Lin1,2, Like Wang3,4, Xiaoli Cui5, Yongxiang Gu3,4,*
    Computer Systems Science and Engineering, Vol.36, No.1, pp. 175-188, 2021, DOI:10.32604/csse.2021.014260
    Abstract Nowadays, as the number of textual data is exponentially increasing, sentiment analysis has become one of the most significant tasks in natural language processing (NLP) with increasing attention. Traditional Chinese sentiment analysis algorithms cannot make full use of the order information in context and are inefficient in sentiment inference. In this paper, we systematically reviewed the classic and representative works in sentiment analysis and proposed a simple but efficient optimization. First of all, FastText was trained to get the basic classification model, which can generate pre-trained word vectors as a by-product. Secondly, Bidirectional Long Short-Term Memory Network (Bi-LSTM) utilizes the… More >

  • Open Access

    ARTICLE

    PRNU Extraction from Stabilized Video: A Patch Maybe Better than a Bunch

    Bin Ma1, Yuanyuan Hu1, Jian Li1,*, Chunpeng Wang1, Meihong Yang2, Yang Zheng3
    Computer Systems Science and Engineering, Vol.36, No.1, pp. 189-200, 2021, DOI:10.32604/csse.2021.014138
    Abstract This paper presents an algorithm to solve the problem of Photo-Response Non-Uniformity (PRNU) noise facing stabilized video. The stabilized video undergoes in-camera processing like rolling shutter correction. Thus, misalignment exists between the PRNU noises in the adjacent frames owing to the global and local frame registration performed by the in-camera processing. The misalignment makes the reference PRNU noise and the test PRNU noise unable to extract and match accurately. We design a computing method of maximum likelihood estimation algorithm for extracting the PRNU noise from stabilized video frames. Besides, unlike most prior arts tending to match the PRNU noise in… More >

  • Open Access

    ARTICLE

    Functionality Aware Dynamic Composition of Web Services

    Mohemmed Sha*, Abdalla Alameen
    Computer Systems Science and Engineering, Vol.36, No.1, pp. 201-211, 2021, DOI:10.32604/csse.2021.014513
    Abstract The composition of the web service is a common technique to attain the best results of complex web tasks. The selection of appropriate web services, linking those services in the action flow and attaining the actual functionality of the task are the important factors to be considered. Even though different frameworks and methods have been proposed to dynamically compose web services, each method has its advantage and disadvantage over the other. Most of the methods give much importance to the Quality of Service (QoS) but fail to achieve the actual functionality after composition. This paper proposes a functionality-oriented composition technique… More >

  • Open Access

    ARTICLE

    Data Security Storage Model of the Internet of Things Based on Blockchain

    Pingshui Wang1,2,*, Willy Susilo2
    Computer Systems Science and Engineering, Vol.36, No.1, pp. 213-224, 2021, DOI:10.32604/csse.2021.014541
    Abstract With the development of information technology, the Internet of Things (IoT) has gradually become the third wave of the worldwide information industry revolution after the computer and the Internet. The application of the IoT has brought great convenience to people’s production and life. However, the potential information security problems in various IoT applications are gradually exposed and people pay more attention to them. The traditional centralized data storage and management model of the IoT is easy to cause transmission delay, single point of failure, privacy disclosure and other problems, and eventually leads to unpredictable behavior of the system. Blockchain technology… More >

  • Open Access

    ARTICLE

    Effective Latent Representation for Prediction of Remaining Useful Life

    Qihang Wang, Gang Wu*
    Computer Systems Science and Engineering, Vol.36, No.1, pp. 225-237, 2021, DOI:10.32604/csse.2021.014100
    Abstract AI approaches have been introduced to predict the remaining useful life (RUL) of a machine in modern industrial areas. To apply them well, challenges regarding the high dimension of the data space and noisy data should be met to improve model efficiency and accuracy. In this study, we propose an end-to-end model, termed ACB, for RUL predictions; it combines an autoencoder, convolutional neural network (CNN), and bidirectional long short-term memory. A new penalized root mean square error loss function is included to avoid an overestimation of the RUL. With the CNN-based autoencoder, a high-dimensional data space can be mapped into… More >

  • Open Access

    ARTICLE

    The Measurement of the Software Ecosystem’s Productivity with GitHub

    Zhifang Liao1, Yiqi Zhao1, Shengzong Liu2, Yan Zhang3, Limin Liu1,*, Jun Long1
    Computer Systems Science and Engineering, Vol.36, No.1, pp. 239-258, 2021, DOI:10.32604/csse.2021.014144
    Abstract Software productivity has always been one of the most critical metrics for measuring software development. However, with the open-source community (e.g., GitHub), new software development models are emerging. The traditional productivity metrics do not provide a comprehensive measure of the new software development models. Therefore, it is necessary to build a productivity measurement model of open source software ecosystem suitable for the open-source community’s production activities. Based on the natural ecosystem, this paper proposes concepts related to the productivity of open source software ecosystems, analyses influencing factors of open source software ecosystem productivity, and constructs a measurement model using these… More >

  • Open Access

    ARTICLE

    Highway Cost Prediction Based on LSSVM Optimized by Intial Parameters

    Xueqing Wang1, Shuang Liu1,*, Lejun Zhang2
    Computer Systems Science and Engineering, Vol.36, No.1, pp. 259-269, 2021, DOI:10.32604/csse.2021.014343
    Abstract The cost of highway is affected by many factors. Its composition and calculation are complicated and have great ambiguity. Calculating the cost of highway according to the traditional highway engineering estimation method is a completely tedious task. Constructing a highway cost prediction model can forecast the value promptly and improve the accuracy of highway engineering cost. This work sorts out and collects 60 sets of measured data of highway engineering; establishes an expressway cost index system based on 10 factors, including main route mileage, roadbed width, roadbed earthwork, and number of bridges; and processes the data through principal component analysis… More >

  • Open Access

    ARTICLE

    Three-Dimensional Measurement Using Structured Light Based on Deep Learning

    Tao Zhang1,*, Jinxing Niu1, Shuo Liu1, Taotao Pan1, Brij B. Gupta2,3
    Computer Systems Science and Engineering, Vol.36, No.1, pp. 271-280, 2021, DOI:10.32604/csse.2021.014181
    Abstract Three-dimensional (3D) reconstruction using structured light projection has the characteristics of non-contact, high precision, easy operation, and strong real-time performance. However, for actual measurement, projection modulated images are disturbed by electronic noise or other interference, which reduces the precision of the measurement system. To solve this problem, a 3D measurement algorithm of structured light based on deep learning is proposed. The end-to-end multi-convolution neural network model is designed to separately extract the coarse- and fine-layer features of a 3D image. The point-cloud model is obtained by nonlinear regression. The weighting coefficient loss function is introduced to the multi-convolution neural network,… More >

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