Donglei Lu¹, Dongjie Zhu^2,*, Yundong Sun³, Haiwen Du³, Xiaofang Li⁴, Rongning Qu⁴, Yansong Wang³, Ning Cao¹, Helen Min Zhou⁵

Computer Systems Science and Engineering, Vol.38, No.3, pp. 339-350, 2021, DOI:10.32604/csse.2021.016683

Abstract In recent years, the Internet of Things technology has developed rapidly, and smart Internet of Things devices have also been widely popularized. A large amount of data is generated every moment. Now we are in the era of big data in the Internet of Things. The rapid growth of massive data has brought great challenges to storage technology, which cannot be well coped with by traditional storage technology. The demand for massive data storage has given birth to cloud storage technology. Load balancing technology plays an important role in improving the performance and resource utilization of cloud storage systems. Therefore,… More >

Lin Zhou^1,*, Qiuyue Zhong¹, Tianyi Wang¹, Siyuan Lu¹, Hongmei Hu²

Computer Systems Science and Engineering, Vol.38, No.3, pp. 279-289, 2021, DOI:10.32604/csse.2021.016524

Abstract Generative adversarial networks (GANs) are paid more attention to dealing with the end-to-end speech enhancement in recent years. Various GAN-based enhancement methods are presented to improve the quality of reconstructed speech. However, the performance of these GAN-based methods is worse than those of masking-based methods. To tackle this problem, we propose speech enhancement method with a residual dense generative adversarial network (RDGAN) contributing to map the log-power spectrum (LPS) of degraded speech to the clean one. In detail, a residual dense block (RDB) architecture is designed to better estimate the LPS of clean speech, which can extract rich local features… More >

Changchun Gao¹, Shiyu Liu^1,*, Chenhui Yu¹, Peng Guo²

Computer Systems Science and Engineering, Vol.38, No.3, pp. 365-379, 2021, DOI:10.32604/csse.2021.016506

Abstract The creative industry is a knowledge-based industry, but it is difficult and complex to create knowledge for enterprises. The principle of cooperation-sharing posits that companies’ limited resources prohibit them from gaining a competitive advantage in all business areas. Therefore, cooperation-sharing can help businesses overcome this hurdle. Cooperation-sharing expedites economic development, breaks the barrier of independent knowledge creation, and enhances resource utilization. However, the effectiveness and stability of knowledge cooperation-sharing are key problems facing governments and other regulators. This study can help regulators promote honesty in enterprise cooperation-sharing. Based on the hypothesis of bounded rationality, the evolutionary game theory was used… More >

Li Li¹, Chen Cui^1,2, Jianfeng Lu¹, Shanqing Zhang^1,*, 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 >

Harsh Tripathi¹, Amer Ibrahim Al-Omari², Mahendra Saha¹, Ayed R. A. Alanzi^3,*

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 >

Md Sadikur Rahman¹, Emad E. Mahmoud², Ali Akbar Shaikh^1,*, Abdel-Haleem Abdel-Aty^3,4, 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 >

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

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 >

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

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 >

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

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 >

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

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 >