Home / Journals / CSSE / Vol.38, No.2, 2021
  • Open Access

    ARTICLE

    An Effective Online Collaborative Training in Developing Listening Comprehension Skills

    Shakeel Ahmed1, Munazza Ambreen1, Muneer Ahmad2, Abdulellah A. Alaboudi3, Roobaea Alroobaea4, NZ Jhanjhi5,*
    Computer Systems Science and Engineering, Vol.38, No.2, pp. 131-140, 2021, DOI:10.32604/csse.2021.016504
    Abstract The COVID-19 outbreak severely affected formal face-to-face classroom teaching and learning. ICT-based online education and training can be a useful measure during the pandemic. In the Pakistani educational context, the use of ICT-based online training is generally sporadic and often unavailable, especially for developing English-language instructors’ listening comprehension skills. The major factors affecting availability include insufficient IT resources and infrastructure, a lack of proper online training for speech and listening, instructors with inadequate academic backgrounds, and an unfavorable environment for ICT-based training for listening comprehension. This study evaluated the effectiveness of ICT-based training for developing secondary-level English-language instructors’ listening comprehension… More >

  • Open Access

    ARTICLE

    An Ensemble Approach to Identify Firearm Listing on Tor Hidden-Services

    Hashem Alyami1, Mohd Faizan2, Wael Alosaimi3, Abdullah Alharbi3, Abhishek Kumar Pandey2, Md Tarique Jamal Ansari4, Alka Agrawal2, Raees Ahmad Khan2,*
    Computer Systems Science and Engineering, Vol.38, No.2, pp. 141-149, 2021, DOI:10.32604/csse.2021.017039
    Abstract The ubiquitous nature of the internet has made it easier for criminals to carry out illegal activities online. The sale of illegal firearms and weaponry on dark web cryptomarkets is one such example of it. To aid the law enforcement agencies in curbing the illicit trade of firearms on cryptomarkets, this paper has proposed an automated technique employing ensemble machine learning models to detect the firearms listings on cryptomarkets. In this work, we have used part-of-speech (PoS) tagged features in conjunction with n-gram models to construct the feature set for the ensemble model. We studied the effectiveness of the proposed… More >

  • Open Access

    ARTICLE

    Investigain: A Productive Asset Management Web Application

    Rabbani Rasha1, Mohammad Monirujjaman Khan1,*, Mehedi Masud2, Mohammed A. AlZain3
    Computer Systems Science and Engineering, Vol.38, No.2, pp. 151-164, 2021, DOI:10.32604/csse.2021.015314
    Abstract The Investigain is a progressive web application to make mutual funds investments through a Systematic Investment Plan. The application utilizes the web’s modern capabilities, such as Asynchronous JavaScript and XML (AJAX), JavaScript, and Hypertext Marker Language (HTML5). The application also uses a powerful relational database management system, such as MySQL, to display asset management information. The application has two portals, one for investors and one for a particular asset manager or asset management company. Each investor has an account in the investor portal. The investor can view his/her profile, current balance, balance history, dividends, the units of mutual funds bought,… More >

  • Open Access

    ARTICLE

    Deep Learning for Object Detection: A Survey

    Jun Wang1, Tingjuan Zhang2,*, Yong Cheng3, Najla Al-Nabhan4
    Computer Systems Science and Engineering, Vol.38, No.2, pp. 165-182, 2021, DOI:10.32604/csse.2021.017016
    Abstract Object detection is one of the most important and challenging branches of computer vision, which has been widely applied in people s life, such as monitoring security, autonomous driving and so on, with the purpose of locating instances of semantic objects of a certain class. With the rapid development of deep learning algorithms for detection tasks, the performance of object detectors has been greatly improved. In order to understand the main development status of target detection, a comprehensive literature review of target detection and an overall discussion of the works closely related to it are presented in this paper. This… More >

  • Open Access

    ARTICLE

    A Cuckoo Search Detector Generation-based Negative Selection Algorithm

    Ayodele Lasisi1,*, Ali M. Aseere2
    Computer Systems Science and Engineering, Vol.38, No.2, pp. 183-195, 2021, DOI:10.32604/csse.2021.015275
    Abstract The negative selection algorithm (NSA) is an adaptive technique inspired by how the biological immune system discriminates the self from non-self. It asserts itself as one of the most important algorithms of the artificial immune system. A key element of the NSA is its great dependency on the random detectors in monitoring for any abnormalities. However, these detectors have limited performance. Redundant detectors are generated, leading to difficulties for detectors to effectively occupy the non-self space. To alleviate this problem, we propose the nature-inspired metaheuristic cuckoo search (CS), a stochastic global search algorithm, which improves the random generation of detectors… More >

  • Open Access

    ARTICLE

    A Sensor Network Web Platform Based on WoT Technology

    Shun-Yuan Wang1, Yun-Jung Hsu1, Sung-Jung Hsiao2, Wen-Tsai Sung3,*
    Computer Systems Science and Engineering, Vol.38, No.2, pp. 197-214, 2021, DOI:10.32604/csse.2021.015713
    Abstract This study proposes a Web platform, the Web of Things (WoT), whose Internet of Things (IoT) architecture is used to develop the technology behind a new standard Web platform. When a remote sensor passes data to a microcontroller for processing, the protocol is often not known. This study proposes a WoT platform that enables the use of a browser in a mobile device to control a remote hardware device. An optimized code is written using an artificial intelligence-based algorithm in a microcontroller. Digital data convergence technology is adopted to process the packets of different protocols and place them on the… More >

  • Open Access

    ARTICLE

    Fault Aware Dynamic Resource Manager for Fault Recognition and Avoidance in Cloud

    Nandhini Jembu Mohanram1,2,*, Gnanasekaran Thangavel3, N. M. Jothi Swaroopan4
    Computer Systems Science and Engineering, Vol.38, No.2, pp. 215-228, 2021, DOI:10.32604/csse.2021.015027
    Abstract Fault tolerance (FT) schemes are intended to work on a minimized and static amount of physical resources. When a host failure occurs, the conventional FT frequently proceeds with the execution on the accessible working hosts. This methodology saves the execution state and applications to complete without disruption. However, the dynamicity of open cloud assets is not seen when taking scheduling choices. Existing optimization techniques are intended in dealing with resource scheduling. This method will be utilized for distributing the approaching tasks to the VMs. However, the dynamic scheduling for this procedure doesn’t accomplish the objective of adaptation of internal failure.… More >

  • Open Access

    ARTICLE

    Leveraging Graph Cut’s Energy Function for Context Aware Facial Recognition in Indoor Environments

    Kazeem Oyebode1, Shengzhi Du2,*, Barend Jacobus van Wyk3
    Computer Systems Science and Engineering, Vol.38, No.2, pp. 229-238, 2021, DOI:10.32604/csse.2021.015372
    Abstract Context-aware facial recognition regards the recognition of faces in association with their respective environments. This concept is useful for the domestic robot which interacts with humans when performing specific functions in indoor environments. Deep learning models have been relevant in solving facial and place recognition challenges; however, they require the procurement of training images for optimal performance. Pre-trained models have also been offered to reduce training time significantly. Regardless, for classification tasks, custom data must be acquired to ensure that learning models are developed from other pre-trained models. This paper proposes a place recognition model that is inspired by the… More >

  • Open Access

    ARTICLE

    Scheduling Optimization Modelling: A Case Study of a Woven Label Manufacturing Company

    Chia-Nan Wang1, Zhao-Hong Cheng2,*, Nguyen Ky Phuc Phan3, Van Thanh Nguyen4
    Computer Systems Science and Engineering, Vol.38, No.2, pp. 239-249, 2021, DOI:10.32604/csse.2021.016578
    (This article belongs to this Special Issue: Impact of Industry 4.0 on Supply Chain Management and Optimization)
    Abstract Production scheduling involves all activities of building production schedules, including coordinating and assigning activities to each person, group of people, or machine and arranging work orders in each workplace. Production scheduling must solve all problems such as minimizing customer wait time, storage costs, and production time; and effectively using the enterprise’s human resources. This paper studies the application of flexible job shop modelling on scheduling a woven labelling process. The labelling process includes several steps which are handled in different work-stations. Each workstation is also comprised of several identical parallel machines. In this study, job splitting is allowed so that… More >

  • Open Access

    ARTICLE

    Multi-indicator Active Queue Management Method

    Mosleh M. Abualhaj*, Abdelrahman H. Hussein, Qasem M. Kharma, Qusai Y. Shambour
    Computer Systems Science and Engineering, Vol.38, No.2, pp. 251-263, 2021, DOI:10.32604/csse.2021.015787
    Abstract A considerable number of applications are running over IP networks. This increased the contention on the network resource, which ultimately results in congestion. Active queue management (AQM) aims to reduce the serious consequences of network congestion in the router buffer and its negative effects on network performance. AQM methods implement different techniques in accordance with congestion indicators, such as queue length and average queue length. The performance of the network is evaluated using delay, loss, and throughput. The gap between congestion indicators and network performance measurements leads to the decline in network performance. In this study, delay and loss predictions… More >

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