Liang Zeng^1,2, Junyang Shi¹, Yanyan Li¹, Shanshan Wang^1,2,*, Weigang Li³

CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 375-392, 2024, DOI:10.32604/cmc.2023.045803

Abstract The job shop scheduling problem is a classical combinatorial optimization challenge frequently encountered in manufacturing systems. It involves determining the optimal execution sequences for a set of jobs on various machines to maximize production efficiency and meet multiple objectives. The Non-dominated Sorting Genetic Algorithm III (NSGA-III) is an effective approach for solving the multi-objective job shop scheduling problem. Nevertheless, it has some limitations in solving scheduling problems, including inadequate global search capability, susceptibility to premature convergence, and challenges in balancing convergence and diversity. To enhance its performance, this paper introduces a strengthened dominance relation NSGA-III algorithm based on differential evolution… More >

Laila Almutairi¹, Shabnam Mohamed Aslam^2,*

CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 2791-2811, 2023, DOI:10.32604/cmc.2023.040268

Abstract The rapid growth of service-oriented and cloud computing has created large-scale data centres worldwide. Modern data centres’ operating costs mostly come from back-end cloud infrastructure and energy consumption. In cloud computing, extensive communication resources are required. Moreover, cloud applications require more bandwidth to transfer large amounts of data to satisfy end-user requirements. It is also essential that no communication source can cause congestion or bag loss owing to unnecessary switching buffers. This paper proposes a novel Energy and Communication (EC) aware scheduling (EC-scheduler) algorithm for green cloud computing, which optimizes data centre energy consumption and traffic load. The primary goal… More >

JIAHAO ZHANG^1,2,3, JIE REN⁴, ZIRUI LI^1,2,3,*, YIXING GOU^1,2,3,*

BIOCELL, Vol.47, No.7, pp. 1439-1447, 2023, DOI:10.32604/biocell.2023.028628

Abstract Circulating tumor cells (CTCs) are essential biomarkers for liquid biopsies, which are important in the early screening, prognosis, and real-time monitoring of cancer. However, CTCs are less abundant in the peripheral blood of patients, therefore, their isolation is necessary. Recently, the use of microfluidics for CTC sorting has become a research hotspot owing to its low cost, ease of integration, low sample consumption, and unique advantages in the manipulation of micron-sized particles. Herein, we review the latest research on microfluidics-based CTC sorting. Specifically, we consider active sorting using external fields (electric, magnetic, acoustic, and optical tweezers) and passive sorting using… More >

Caiyun Liu, Peng Liu^*

Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 3221-3242, 2023, DOI:10.32604/iasc.2023.035114

Abstract Shared manufacturing is recognized as a new point-to-point manufacturing mode in the digital era. Shared manufacturing is referred to as a new manufacturing mode to realize the dynamic allocation of manufacturing tasks and resources. Compared with the traditional mode, shared manufacturing offers more abundant manufacturing resources and flexible configuration options. This paper proposes a model based on the description of the dynamic allocation of tasks and resources in the shared manufacturing environment, and the characteristics of shared manufacturing resource allocation. The execution of manufacturing tasks, in which candidate manufacturing resources enter or exit at various time nodes, enables the dynamic… More >

Lei Xing¹, Yakui Liu^2,3,*

Energy Engineering, Vol.120, No.4, pp. 1023-1043, 2023, DOI:10.32604/ee.2023.025335

Abstract The optimal allocation of integrated energy system capacity based on the heuristic algorithms can reduce economic costs and achieve maximum consumption of renewable energy, which has attracted many attentions. However, the optimization results of heuristic algorithms are usually influenced by the choice of hyperparameters. To solve the above problem, the particle swarm algorithm is introduced to find the optimal hyperparameters of the heuristic algorithms. Firstly, an integrated energy system consisting of the photovoltaic, wind turbine, electrolysis cell, hydrogen storage tank, and energy storage is established. Meanwhile, the minimum economic cost, the maximum wind and PV power consumption rate, and the… More >

AnJian-CaiRang^1,2, Dawei Song^3,4,*

Journal on Artificial Intelligence, Vol.4, No.2, pp. 85-98, 2022, DOI:10.32604/jai.2022.029141

Abstract Sorting the Tibetan language quickly and accurately requires first identifying the component elements that make up Tibetan syllables and then sorting by the priority of the component. Based on the study of Tibetan text structure, grammatical rules and syllable structure, we present a structure-based Tibetan syllable recognition method that uses syllable structure instead of grammar. This method avoids complicated Tibetan grammar and recognizes the components of Tibetan syllables simply and quickly. On the basis of identifying the components of Tibetan syllables, a Tibetan syllable sorting algorithm that conforms to the language sorting rules is proposed. The core of the Tibetan… More >

Jyoti Khandelwal¹, Vijay Kumar Sharma¹, Dilbag Singh^2,*, Atef Zaguia³

CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3299-3312, 2022, DOI:10.32604/cmc.2022.023116

Abstract Digital image steganography technique based on hiding the secret data behind of cover image in such a way that it is not detected by the human visual system. This paper presents an image scrambling method that is very useful for grayscale secret images. In this method, the secret image decomposes in three parts based on the pixel's threshold value. The division of the color image into three parts is very easy based on the color channel but in the grayscale image, it is difficult to implement. The proposed image scrambling method is implemented in image steganography using discrete wavelet transform… More >

Mohammad Khalid Imam Rahmani^*

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4895-4913, 2022, DOI:10.32604/cmc.2022.023837

Abstract In the present era, a very huge volume of data is being stored in online and offline databases. Enterprise houses, research, medical as well as healthcare organizations, and academic institutions store data in databases and their subsequent retrievals are performed for further processing. Finding the required data from a given database within the minimum possible time is one of the key factors in achieving the best possible performance of any computer-based application. If the data is already sorted, finding or searching is comparatively faster. In real-life scenarios, the data collected from different sources may not be in sorted order. Sorting… More >

Kalaipriyan Thirugnansambandam¹, Debnath Bhattacharyya², Jaroslav Frnda³, Dinesh Kumar Anguraj², Jan Nedoma^4,*

CMC-Computers, Materials & Continua, Vol.69, No.3, pp. 3629-3644, 2021, DOI:10.32604/cmc.2021.018939

Abstract In Wireless Sensor Network (WSN), coverage and connectivity are the vital challenges in the target-based region. The linear objective is to find the positions to cover the complete target nodes and connectivity between each sensor for data forwarding towards the base station given a grid with target points and a potential sensor placement position. In this paper, a multiobjective problem on target-based WSN (t-WSN) is derived, which minimizes the number of deployed nodes, and maximizes the cost of coverage and sensing range. An Evolutionary-based Non-Dominated Sorting Genetic Algorithm-II (NSGA-II) is incorporated to tackle this multiobjective problem efficiently. Multiobjective problems are… More >

Hui Wang, Liang Li, Long-yun Gao, Wu Chen

Intelligent Automation & Soft Computing, Vol.24, No.1, pp. 35-40, 2018, DOI:10.1080/10798587.2016.1267238

Abstract With the development of big data science, handling intensive knowledge in the complex network becomes more and more important. Knowledge representation of multi-agent negotiation in the complex network plays an important role in big data science. As a modern approach to declarative programming, answer set programming is widely applied in representing the multi-agent negotiation knowledge in recent years. But almost all the relevant negotiation models are based on complete rational agents, which make the negotiation process complex and low efficient. Sorting negotiation demands is the most key step in creating an efficient negotiation model to improve the negotiation ability of… More >