Lieping Zhang^1,2, Xiaoxu Shi^1,2, Liu Tang^1,2, Yilin Wang³, Jiansheng Peng⁴, Jianchu Zou^4,*

CMC-Computers, Materials & Continua, Vol.78, No.2, pp. 2111-2136, 2024, DOI:10.32604/cmc.2024.047235

Abstract A Rapid-exploration Random Tree (RRT) autonomous detection algorithm based on the multi-guide-node deflection strategy and Karto Simultaneous Localization and Mapping (SLAM) algorithm was proposed to solve the problems of low efficiency of detecting frontier boundary points and drift distortion in the process of map building in the traditional RRT algorithm in the autonomous detection strategy of mobile robot. Firstly, an RRT global frontier boundary point detection algorithm based on the multi-guide-node deflection strategy was put forward, which introduces the reference value of guide nodes’ deflection probability into the random sampling function so that the global search tree can detect frontier… More >

Lalit Mohan Patnaik^1,5, Wenfeng Wang^2,3,4,5,6,*

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.2, pp. 1203-1215, 2024, DOI:10.32604/cmes.2023.029451

Abstract This article reviews the theory of fairness in AI–from machine learning to federated learning, where the constraints on precision AI fairness and perspective solutions are also discussed. For a reliable and quantitative evaluation of AI fairness, many associated concepts have been proposed, formulated and classified. However, the inexplicability of machine learning systems makes it almost impossible to include all necessary details in the modelling stage to ensure fairness. The privacy worries induce the data unfairness and hence, the biases in the datasets for evaluating AI fairness are unavoidable. The imbalance between algorithms’ utility and humanization has further reinforced such worries.… More >

Yeferson Torres-Berru^1,2,*, Vivian F. Lopez-Batista¹, Lorena Conde Zhingre³

Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 3501-3516, 2023, DOI:10.32604/iasc.2023.035367

Abstract In a public procurement process, corruption can occur at each stage, favoring a participant with a previous agreement, which can result in over-pricing and purchases of substandard products, as well as gender discrimination. This paper’s aim is to detect biased purchases using a Spanish Language corpus, analyzing text from the questions and answers registry platform by applicants in a public procurement process in Ecuador. Additionally, gender bias is detected, promoting both men and women to participate under the same conditions. In order to detect gender bias and favoritism towards certain providers by contracting entities, the study proposes a unique hybrid… More >

M. M. Alqarni¹, Muhammad Rafiq², Fazal Dayan^3,*, Jan Awrejcewicz⁴, Nauman Ahmed⁵, Ali Raza⁶, Muhammad Ozair Ahmad⁵, Witold Pawłowski⁷, Emad E. Mahmoud⁸

CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 6371-6388, 2023, DOI:10.32604/cmc.2023.033553

Abstract Amoebiasis is a parasitic intestinal infection caused by the highly pathogenic amoeba Entamoeba histolytica. It is spread through person-to-person contact or by eating or drinking food or water contaminated with feces. Its transmission rate depends on the number of cysts present in the environment. The traditional models assumed a homogeneous and contradictory transmission with reality. The heterogeneity of its transmission rate is a significant factor when modeling disease dynamics. The heterogeneity of disease transmission can be described mathematically by introducing fuzzy theory. In this context, a fuzzy SEIR Amoebiasis disease model is considered in this study. The equilibrium analysis and… More >

Zhihui Xiong, Xiaohui Zhou^*, Jinjie Zhao, Hao Cui, Bo Wang

CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.3, pp. 2449-2478, 2023, DOI:10.32604/cmes.2023.023353

Abstract The numerical simulation results utilizing the Peridynamics (PD) method reveal that the initial crack and crack propagation of the tunnel concrete lining structure agree with the experimental data compared to the Japanese prototype lining test. The load structure model takes into account the cracking process and distribution of the lining segment under the influence of local bias pressure and lining thickness. In addition, the influence of preset cracks and lining section form on the crack propagation of the concrete lining model is studied. This study evaluates the stability and sustainability of tunnel structure by the Peridynamics method, which provides a… More >

Muhammad Hasnain¹, Imran Ghani², Seung Ryul Jeong^3,*, Muhammad Fermi Pasha⁴, Sardar Usman⁵, Anjum Abbas⁶

CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 783-799, 2023, DOI:10.32604/cmc.2023.030162

Abstract Forecasting on success or failure of software has become an interesting and, in fact, an essential task in the software development industry. In order to explore the latest data on successes and failures, this research focused on certain questions such as is early phase of the software development life cycle better than later phases in predicting software success and avoiding high rework? What human factors contribute to success or failure of a software? What software practices are used by the industry practitioners to achieve high quality of software in their day-to-day work? In order to conduct this empirical analysis a… More >

Zejie Wang¹, Qianxin Wang^1,*, Sanxi Li²

CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.3, pp. 823-843, 2022, DOI:10.32604/cmes.2022.020106

Abstract The combination of Precision Point Positioning (PPP) with Multi-Global Navigation Satellite System (MultiGNSS), called MGPPP, can improve the positioning precision and shorten the convergence time more effectively than the combination of PPP with only the BeiDou Navigation Satellite System (BDS). However, the Inter-System Bias (ISB) measurement of Multi-GNSS, including the time system offset, the coordinate system difference, and the inter-system hardware delay bias, must be considered for Multi-GNSS data fusion processing. The detected ISB can be well modeled and predicted by using a quadratic model (QM), an autoregressive integrated moving average model (ARIMA), as well as the sliding window strategy… More >

Beifen Dai^1,#, Zhihao Xu^2,#, Hongjue Li³, Bo Wang³, Jinsong Cai¹, Xiaomo Liu^4,*

Oncologie, Vol.24, No.1, pp. 113-130, 2022, DOI:10.32604/oncologie.2022.020259

Abstract Large-scale genomic studies are important ways to comprehensively decode the human genomics, and provide valuable insights to human disease causalities and phenotype developments. Genomic studies are in need of high throughput bioinformatics analyses to harness and integrate such big data. It is in this overarching context that artificial intelligence (AI) offers enormous potentials to advance genomic studies. However, racial bias is always an important issue in the data. It is usually due to the accumulation process of the dataset that inevitability involved diverse subjects with different races. How can race bias affect the outcomes of AI methods? In this work,… More >

Khudran M. Alzhrani^*

Intelligent Automation & Soft Computing, Vol.33, No.1, pp. 483-500, 2022, DOI:10.32604/iasc.2022.023914

Abstract Individuals inadvertently allow emotions to drive their rational thoughts to predetermined conclusions regarding political partiality issues. Being well-informed about the subject in question mitigates emotions’ influence on humans’ cognitive reasoning, but it does not eliminate bias. By nature, humans tend to pick a side based on their beliefs, personal interests, and principles. Hence, journalists’ political leaning is defining factor in the rise of the polarity of political news coverage. Political bias studies usually align subjects or controversial topics of the news coverage to a particular ideology. However, politicians as private citizens or public officials are also consistently in the media… More >

Pradeep Kumar Singh¹, Pijush Kanti Dutta Pramanik¹, Madhumita Sardar¹, Anand Nayyar^2,3,*, Mehedi Masud⁴, Prasenjit Choudhury¹

CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2827-2846, 2022, DOI:10.32604/cmc.2022.020437

Abstract A collaborative filtering-based recommendation system has been an integral part of e-commerce and e-servicing. To keep the recommendation systems reliable, authentic, and superior, the security of these systems is very crucial. Though the existing shilling attack detection methods in collaborative filtering are able to detect the standard attacks, in this paper, we prove that they fail to detect a new or unknown attack. We develop a new attack model, named Obscure attack, with unknown features and observed that it has been successful in biasing the overall top-N list of the target users as intended. The Obscure attack is able to… More >