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  • Open Access


    A Holographic Diffraction Label Recognition Algorithm Based on Fusion Double Tensor Features

    Li Li1, Chen Cui1,2, Jianfeng Lu1, Shanqing Zhang1,*, Ching-Chun Chang3

    Computer Systems Science and Engineering, Vol.38, No.3, pp. 291-303, 2021, DOI:10.32604/csse.2021.016340

    Abstract As an efficient technique for anti-counterfeiting, holographic diffraction labels has been widely applied to various fields. Due to their unique feature, traditional image recognition algorithms are not ideal for the holographic diffraction label recognition. Since a tensor preserves the spatiotemporal features of an original sample in the process of feature extraction, in this paper we propose a new holographic diffraction label recognition algorithm that combines two tensor features. The HSV (Hue Saturation Value) tensor and the HOG (Histogram of Oriented Gradient) tensor are used to represent the color information and gradient information of holographic diffraction label, respectively. Meanwhile, the tensor… More >

  • Open Access


    Improved Attribute Chain Sampling Plan for Darna Distribution

    Harsh Tripathi1, Amer Ibrahim Al-Omari2, Mahendra Saha1, Ayed R. A. Alanzi3,*

    Computer Systems Science and Engineering, Vol.38, No.3, pp. 381-392, 2021, DOI:10.32604/csse.2021.015624

    Abstract Recently, the Darna distribution has been introduced as a new lifetime distribution. The two-parameter Darna distribution represents is a mixture of two well-known gamma and exponential distributions. A manufacturer or an engineer of products conducts life testing to examine whether the quality level of products meets the customer’s requirements, such as reliability or the minimum lifetime. In this article, an attribute modified chain sampling inspection plan based on the time truncated life test is proposed for items whose lifetime follows the Darna distribution. The plan parameters, including the sample size, the acceptance number, and the past lot result of the… More >

  • Open Access


    Saddle Point Optimality Criteria of Interval Valued Non-Linear Programming Problem

    Md Sadikur Rahman1, Emad E. Mahmoud2, Ali Akbar Shaikh1,*, Abdel-Haleem Abdel-Aty3,4, Asoke Kumar Bhunia1

    Computer Systems Science and Engineering, Vol.38, No.3, pp. 351-364, 2021, DOI:10.32604/csse.2021.015451

    Abstract The present paper aims to develop the Kuhn-Tucker and Fritz John criteria for saddle point optimality of interval-valued nonlinear programming problem. To achieve the study objective, we have proposed the definition of minimizer and maximizer of an interval-valued non-linear programming problem. Also, we have introduced the interval-valued Fritz-John and Kuhn Tucker saddle point problems. After that, we have established both the necessary and sufficient optimality conditions of an interval-valued non-linear minimization problem. Next, we have shown that both the saddle point conditions (Fritz-John and Kuhn-Tucker) are sufficient without any convexity requirements. Then with the convexity requirements, we have established that… More >

  • Open Access


    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


    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


    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

    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


    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


    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 >

  • Open Access


    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


    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 >

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