Home / Journals / CSSE / Vol.35, No.6, 2020
  • Open Access

    ARTICLE

    A Discovery Method for New Words From Mobile Product Comments

    Hai Yang Zhu1,∗,†, Xiaobo Yin1,∗,‡, Shunxiang Zhang1,∗,§, Zhongliang Wei1,¶, Guangli Zhu1,II, Meng-Yen Hsieh2,*,**
    Computer Systems Science and Engineering, Vol.35, No.6, pp. 399-410, 2020, DOI:10.32604/csse.2020.35.399
    Abstract A large number of new words in product reviews generated by mobile terminals are valuable indicators of the privacy preferences of customers. By clustering these privacy preferences, sufficient information can be collected to characterize users and provide a data basis for the research issues of privacy protection. The widespread use of mobile clients shortens the string length of the comment corpus generated by product reviews, resulting in a high repetition rate. Therefore, the effective and accurate recognition of new words is a problem that requires an urgent solution. Hence, in this paper, we propose a method for discovering new words… More >

  • Open Access

    ARTICLE

    Internet of Things in Healthcare: Architecture, Applications, Challenges, and Solutions

    Vankamamidi S. Naresh1,∗,†, Suryateja S. Pericherla2,‡, Pilla Sita Rama Murty3,§, Sivaranjani Reddi4,¶
    Computer Systems Science and Engineering, Vol.35, No.6, pp. 411-421, 2020, DOI:10.32604/csse.2020.35.411
    Abstract Healthcare, the largest global industry, is undergoing significant transformations with the genesis of a new technology known as the Internet of Things (IoT). Many healthcare leaders are investing more money for transforming their services to harness the benefits provided by IoT, thereby paving the way for the Internet of Medical Things (IoMT), an extensive collection of medical sensors and associated infrastructure. IoMT has many benefits like providing remote healthcare by monitoring health vitals of patients at a distant place, providing healthcare services to elderly people, and monitoring a large group of people in a region or country for detection and… More >

  • Open Access

    ARTICLE

    An Accurate Persian Part-of-Speech Tagger

    Morteza Okhovvat1,∗, Mohsen Sharifi2,†, Behrouz Minaei Bidgoli2,‡
    Computer Systems Science and Engineering, Vol.35, No.6, pp. 423-430, 2020, DOI:10.32604/csse.2020.35.423
    Abstract The processing of any natural language requires that the grammatical properties of every word in that language are tagged by a part of speech (POS) tagger. To present a more accurate POS tagger for the Persian language, we propose an improved and accurate tagger called IAoM that supports properties of text to speech systems such as Lexical Stress Search, Homograph words Disambiguation, Break Phrase Detection, and main aspects of Persian morphology. IAoM uses Maximum Likelihood Estimation (MLE) to determine the tags of unknown words. In addition, it uses a few defined rules for the sake of achieving high accuracy. For… More >

  • Open Access

    ARTICLE

    B-Spline Curve Approximation by Utilizing Big Bang-Big Crunch Method

    Özkan inik1,∗, Erkan Ülker2, ismail Koç2
    Computer Systems Science and Engineering, Vol.35, No.6, pp. 431-440, 2020, DOI:10.32604/csse.2020.35.431
    Abstract The location of knot points and estimation of the number of knots are undoubtedly known as one of the most difficult problems in B-Spline curve approximation. In the literature, different researchers have been seen to use more than one optimization algorithm in order to solve this problem. In this paper, Big Bang-Big Crunch method (BB-BC) which is one of the evolutionary based optimization algorithms was introduced and then the approximation of B-Spline curve knots was conducted by this method. The technique of reverse engineering was implemented for the curve knot approximation. The detection of knot locations and the number of… More >

  • Open Access

    ARTICLE

    Human Activity Recognition Based on Parallel Approximation Kernel K-Means Algorithm

    Ahmed A. M. Jamel1,∗, Bahriye Akay2,†
    Computer Systems Science and Engineering, Vol.35, No.6, pp. 441-456, 2020, DOI:10.32604/csse.2020.35.441
    Abstract Recently, owing to the capability of mobile and wearable devices to sense daily human activity, human activity recognition (HAR) datasets have become a large-scale data resource. Due to the heterogeneity and nonlinearly separable nature of the data recorded by these sensors, the datasets generated require special techniques to accurately predict human activity and mitigate the considerable heterogeneity. Consequently, classic clustering algorithms do not work well with these data. Hence, kernelization, which converts the data into a new feature vector representation, is performed on nonlinearly separable data. This study aims to present a robust method to perform HAR data clustering to… More >

  • Open Access

    ARTICLE

    Multiparty Quantum Key Agreement With Strong Fairness Property

    Vankamamidi S. Naresh1,∗, Sivaranjani Reddi2
    Computer Systems Science and Engineering, Vol.35, No.6, pp. 457-465, 2020, DOI:10.32604/csse.2020.35.457
    Abstract Multiparty Key Agreement (MKA) is the backbone for secure multiparty communication. Although numerous efficient MKA-cryptosystems are available in the classical field, their security relies on the assumption that some computational issues are infeasible. To overcome this dependency, a new area, quantum cryptography, evolves to support key agreement among two or more participants securely. In this paper, first, we present a two-part quantum key agreement with Strong Fairness Property (SFP) and extends it to a Multiparty Quantum Key Agreement (MQKA) protocol. In the first round of proposed MQKA, a participant will act as a group controller (GC) and establishes two-party groups… More >

  • Open Access

    ARTICLE

    Text Classification for Azerbaijani Language Using Machine Learning

    Umid Suleymanov1, Behnam Kiani Kalejahi1,2,*, Elkhan Amrahov1, Rashid Badirkhanli1
    Computer Systems Science and Engineering, Vol.35, No.6, pp. 467-475, 2020, DOI:10.32604/csse.2020.35.467
    Abstract Text classification systems will help to solve the text clustering problem in the Azerbaijani language. There are some text-classification applications for foreign languages, but we tried to build a newly developed system to solve this problem for the Azerbaijani language. Firstly, we tried to find out potential practice areas. The system will be useful in a lot of areas. It will be mostly used in news feed categorization. News websites can automatically categorize news into classes such as sports, business, education, science, etc. The system is also used in sentiment analysis for product reviews. For example, the company shares a… More >

  • Open Access

    ARTICLE

    A Novel Fault Tolerance Energy-Aware Clustering Method via Social Spider Optimization (SSO) and Fuzzy Logic and Mobile Sink in Wireless Sensor Networks (WSNs)

    Shayesteh Tabatabaei1,∗
    Computer Systems Science and Engineering, Vol.35, No.6, pp. 477-494, 2020, DOI:10.32604/csse.2020.35.477
    Abstract In recent years, the application of WSNs has been remarkably increased and notable developments and advances have been achieved in this regard. In particular, thanks to smart, cheaper and smaller nodes, different types of information can be detected and gathered in different environments and under different conditions. As the popularity of WSNs has increased, the problems and issues related to networks are examined and investigated. As a case in point, routing issue is one of the main challenges in this regard which has a direct impact on the performance of sensor networks. In WSN routing, sensor nodes send and receive… More >

  • Open Access

    ARTICLE

    Semantic Analysis Techniques using Twitter Datasets on Big Data: Comparative Analysis Study

    Belal Abdullah Hezam Murshed1,∗, Hasib Daowd Esmail Al-ariki2,†, Suresha Mallappa3,‡
    Computer Systems Science and Engineering, Vol.35, No.6, pp. 495-512, 2020, DOI:10.32604/csse.2020.35.495
    Abstract This paper conducts a comprehensive review of various word and sentence semantic similarity techniques proposed in the literature. Corpus-based, Knowledge-based, and Feature-based are categorized under word semantic similarity techniques. String and set-based, Word Order-based Similarity, POSbased, Syntactic dependency-based are categorized as sentence semantic similarity techniques. Using these techniques, we propose a model for computing the overall accuracy of the twitter dataset. The proposed model has been tested on the following four measures: Atish’s measure, Li’s measure, Mihalcea’s measure with path similarity, and Mihalcea’s measure with Wu and Palmer’s (WuP) similarity. Finally, we evaluate the proposed method on three real-world twitter… More >

  • Open Access

    ARTICLE

    Video Source Identification Algorithm Based on 3D Geometric Transformation

    Jian Li1, Yang Lv1, Bin Ma1,*, Meihong Yang2, Chunpeng Wang1, Yang Zheng3
    Computer Systems Science and Engineering, Vol.35, No.6, pp. 513-521, 2020, DOI:10.32604/csse.2020.35.513
    Abstract Digital video has become one of the most preferred ways for people to share information. Considering people tend to release illegal information in anonymous way, the problem of video source identification attracts more and more attention as an important part of multimedia forensics. The Photo-Response Non-Uniformity (PRNU) based algorithm shows to be a promising solution for the problem of video source identification. However, it is necessary to make a geometric transformation for testing PRNU noise to align it with the reference noise, due to the effect of video stabilization. This paper analyzes the three-dimensional (3D) characteristics of camera jitters and… More >

  • Open Access

    ARTICLE

    A Data-Aware Remote Procedure Call Method for Big Data Systems

    Jin Wang1,2, Yaqiong Yang1, Jingyu Zhang1,3,*, Xiaofeng Yu4, Osama Alfarraj5, Amr Tolba5,6
    Computer Systems Science and Engineering, Vol.35, No.6, pp. 523-532, 2020, DOI:10.32604/csse.2020.35.523
    Abstract In recent years, big data has been one of the hottest development directions in the information field. With the development of artificial intelligence technology, mobile smart terminals and high-bandwidth wireless Internet, various types of data are increasing exponentially. Huge amounts of data contain a lot of potential value, therefore how to effectively store and process data efficiently becomes very important. Hadoop Distributed File System (HDFS) has emerged as a typical representative of dataintensive distributed big data file systems, and it has features such as high fault tolerance, high throughput, and can be deployed on low-cost hardwares. HDFS nodes communicate with… More >

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