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Shakeel Ahmed¹, Munazza Ambreen¹, Muneer Ahmad², Abdulellah A. Alaboudi³, Roobaea Alroobaea⁴, NZ Jhanjhi^5,*
Computer Systems Science and Engineering, Vol.38, No.2, pp. 131-140, 2021, DOI:10.32604/csse.2021.016504 - 23 April 2021
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 More >

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Hashem Alyami¹, Mohd Faizan², Wael Alosaimi³, Abdullah Alharbi³, Abhishek Kumar Pandey², Md Tarique Jamal Ansari⁴, Alka Agrawal², Raees Ahmad Khan^2,*
Computer Systems Science and Engineering, Vol.38, No.2, pp. 141-149, 2021, DOI:10.32604/csse.2021.017039 - 23 April 2021
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 More >

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Rabbani Rasha¹, Mohammad Monirujjaman Khan^1,*, Mehedi Masud², Mohammed A. AlZain³
Computer Systems Science and Engineering, Vol.38, No.2, pp. 151-164, 2021, DOI:10.32604/csse.2021.015314 - 23 April 2021
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 More >

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Jun Wang¹, Tingjuan Zhang^2,*, Yong Cheng³, Najla Al-Nabhan⁴
Computer Systems Science and Engineering, Vol.38, No.2, pp. 165-182, 2021, DOI:10.32604/csse.2021.017016 - 23 April 2021
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 More >

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Ayodele Lasisi^1,*, Ali M. Aseere²
Computer Systems Science and Engineering, Vol.38, No.2, pp. 183-195, 2021, DOI:10.32604/csse.2021.015275 - 23 April 2021
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… More >

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Shun-Yuan Wang¹, Yun-Jung Hsu¹, Sung-Jung Hsiao², Wen-Tsai Sung^3,*
Computer Systems Science and Engineering, Vol.38, No.2, pp. 197-214, 2021, DOI:10.32604/csse.2021.015713 - 23 April 2021
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… More >

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Nandhini Jembu Mohanram^1,2,*, 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 - 23 April 2021
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… More >

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Kazeem Oyebode¹, Shengzhi Du^2,*, Barend Jacobus van Wyk³
Computer Systems Science and Engineering, Vol.38, No.2, pp. 229-238, 2021, DOI:10.32604/csse.2021.015372 - 23 April 2021
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… More >

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1186

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Chia-Nan Wang¹, Zhao-Hong Cheng^2,*, 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 - 23 April 2021
（This article belongs to the 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… More >

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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 - 23 April 2021
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… More >

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