Ayesha Maqbool^1,*, Farkhanda Afzal², Tauseef Rana³, Alina Mirza⁴

Intelligent Automation & Soft Computing, Vol.28, No.3, pp. 653-667, 2021, DOI:10.32604/iasc.2021.017506

Abstract This paper presents a co-operative, self-organisation method for Multiple Autonomous Vehicles aiming to share surveillance responsibilities. Spatial organization or formation configuration of multiple vehicles/agents’ systems is crucial for a team of agents to achieve their mission objectives. In this paper we present simple yet efficient thermodynamic inspired formation control framework. The proposed method autonomously allocates region of surveillance to each vehicle and also re-adjusts the area of their responsibilities during the mission. It provides framework for heterogeneous UAVs to scatter themselves optimally in order to provide maximum coverage of a given area. The method is inspired from a natural phenomenon… More >

Neelam Gohar^1,*, Sidra Niaz¹, Mamoona Naveed Asghar², Salma Noor¹

Intelligent Automation & Soft Computing, Vol.28, No.1, pp. 241-259, 2021, DOI:10.32604/iasc.2021.015461

Abstract Game theory is a popular area of artificial intelligence in which the voter acknowledges his own desires and favors the person he wants to be his representative. In multi-agent systems, social choice functions help aggregate agents’ different preferences over alternatives into a single choice. Since all voting rules are susceptible to manipulation, the analysis of elections is complicated by the possibility of voter manipulation attempts. One approach to understanding elections is to treat them as an iterative process and see if we can reach an equilibrium point. Meir et al. proposed an iterative process to reach a stable outcome, i.e.,… More >

Ali Mustafa^1,2, M Najam ul Islam¹, Salman Ahmed^1,3,*

Computer Systems Science and Engineering, Vol.37, No.3, pp. 399-413, 2021, DOI:10.32604/csse.2021.015575

Abstract Consensus control of multi-agent systems is an innovative paradigm for the development of intelligent distributed systems. This has fascinated numerous scientific groups for their promising applications as they have the freedom to achieve their local and global goals and make their own decisions. Network communication topologies based on graph and matrix theory are widely used in a various real-time applications ranging from software agents to robotics. Therefore, while sustaining the significance of both directed and undirected graphs, this research emphases on the demonstration of a distributed average consensus algorithm. It uses the harmonic mean in the domain of multi-agent systems… More >

MAYSON H. ALKHATIB^1,2,*, SALWA M. AL-HASHEMI¹, HANA M. GASHLAN¹

BIOCELL, Vol.45, No.3, pp. 695-703, 2021, DOI:10.32604/biocell.2021.014349

Abstract Incorporation of etoposide (ETP) into nanoemulsion (NE) containing polyunsaturated fatty acids (PUFAs) may potentially augment its antiproliferation effect on the cancer cells. The current study aimed to examine the in vitro antitumor activity of a novel formulation (ETP-BC/EP-NE) produced by combining the anticancer drug (ETP) with NE (BC/EP-NE) consisting of the black currant seed and organic evening primrose oils. The produced formulas were physically characterized using zetasizer measurements. Their cytotoxic effect was testified at concentrations ranges from 0.0001 to 5 μM using CCK-8. Apoptotic and anti-invasion effects were evaluated using the assays of mitochondrial membrane potential, annexin V-FITC double staining,… More >

Ali M. Aseere^1,*, Ayodele Lasisi²

Intelligent Automation & Soft Computing, Vol.27, No.3, pp. 683-699, 2021, DOI:10.32604/iasc.2021.014811

Abstract In the absence of fast and adequate measures to combat them, life-threatening diseases are catastrophic to human health. Computational intelligent algorithms characterized by their adaptability, robustness, diversity, and recognition abilities allow for the diagnosis of medical diseases. This enhances the decision-making process of physicians. The objective is to predict and classify diseases accurately. In this paper, we proposed a multi-agent stacked ensemble classifier based on a vaguely quantified rough set, simple logistic algorithm, sequential minimal optimization (SMO), and JRip. The vaguely quantified rough set (VQRS) is used for feature selection and eradicating noise in the data. There are two classifier… More >

Mohamed Elhoseny¹, Mazin Abed Mohammed^2,*, Salama A. Mostafa³, Karrar Hameed Abdulkareem⁴, Mashael S. Maashi⁵, Begonya Garcia-Zapirain⁶, Ammar Awad Mutlag⁷, Marwah Suliman Maashi⁸

CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 51-71, 2021, DOI:10.32604/cmc.2021.012632

Abstract Heart disease (HD) is a serious widespread life-threatening disease. The heart of patients with HD fails to pump sufficient amounts of blood to the entire body. Diagnosing the occurrence of HD early and efficiently may prevent the manifestation of the debilitating effects of this disease and aid in its effective treatment. Classical methods for diagnosing HD are sometimes unreliable and insufficient in analyzing the related symptoms. As an alternative, noninvasive medical procedures based on machine learning (ML) methods provide reliable HD diagnosis and efficient prediction of HD conditions. However, the existing models of automated ML-based HD diagnostic methods cannot satisfy… More >

Janyl Jumadinova¹, Oliver Bonham-Carter¹, Hanzhong Zheng^1,2,*, Michael Camara¹, Dejie Shi³

Journal on Big Data, Vol.2, No.4, pp. 145-155, 2020, DOI:10.32604/jbd.2020.010090

Abstract Text mining has emerged as an effective method of handling and extracting useful information from the exponentially growing biomedical literature and biomedical databases. We developed a novel biomedical text mining model implemented by a multi-agent system and distributed computing mechanism. Our distributed system, TextMed, comprises of several software agents, where each agent uses a reinforcement learning method to update the sentiment of relevant text from a particular set of research articles related to specific keywords. TextMed can also operate on different physical machines to expedite its knowledge extraction by utilizing a clustering technique. We collected the biomedical textual data from… More >

Chenxi Liu¹, Suchun Yang^2,*

Intelligent Automation & Soft Computing, Vol.26, No.5, pp. 1035-1046, 2020, DOI:10.32604/iasc.2020.010135

Abstract Based on an analysis of the development of economic decision support systems, agents are applied to construct intelligent economic decision support systems. This paper proposes a task-oriented agent design concept and designs multiple types of agents to complete the decision-making tasks with the task as the core. The structure of multi-agent based systems is provided, and the concrete realization structure of different types of agents in the system is also provided. Additionally, this study discusses the operational mechanism of the whole system and the cooperation between multiple agents in the system. Finally, these functions are implemented through a combination of… More >

Mo Hou^1,*, Weiyu Kevin Chiang^2,*, Weiqiang Hong¹, Maoyun Yang¹, Wenhua Yu^3,4

Molecular & Cellular Biomechanics, Vol.17, No.4, pp. 165-178, 2020, DOI:10.32604/mcb.2020.010805

Abstract To achieve the image registration/fusion and perfect the quality of the integration, with dual modality contrast agent (DMCA), a novel multi-scale representation registration method between ultrasound imaging (US) and magnetic resonance imaging (MRI) is presented in the paper, and how DMCA influence on registration accuracy is chiefly discussed. Owing to US’s intense speckle noise, it is a tremendous challenge to register US with any other modality images. How to improve the algorithms for US processing has become the bottleneck, and in the short term it is difficult to have a breakthrough. In that case, DMCA is employed in both US… More >

OLIVIA A. ROBLES-RODRÍGUEZ¹, MARÍA J. LOERA-ARIAS^1,*, JOSÉ J. PÉREZ-TRUJILLO¹, ARNULFO VILLANUEVA-OLIVO¹, ERNESTO PICÓN-GALINDO¹, LAURA VILLARREAL-MARTÍNEZ², ADOLFO SOTO-DOMÍNGUEZ¹, HUMBERTO RODRÍGUEZ-ROCHA¹, ARACELY GARCÍA-GARCÍA¹, ODILA SAUCEDO-CÁRDENAS^1,3, ROBERTO MONTES DE OCA-LUNA^1,*

BIOCELL, Vol.44, No.3, pp. 401-409, 2020, DOI:10.32604/biocell.2020.010064

Abstract Human-induced pluripotent stem cells (iPSCs) are an accessible source of adult-derived, patient-specific pluripotent stem cells for use in basic research, drug discovery, disease modeling, and stem cell therapy. Improving the accessibility of methods to obtain iPSCs regardless of the cell source can enhance their clinical application. Therefore, our purpose is to report a simple protocol to obtain iPS-like cells from urine-derived renal epithelial cells (RECs) using different extracellular matrices and transfection reagents. In this study, we began by culturing urine-derived cells from healthy donors to establish a primary culture of renal epithelial cells, followed by their characterization. Subsequently, we generated… More >