Cyril Enault^*

Revue Internationale de Géomatique, Vol.33, pp. 77-92, 2024, DOI:10.32604/rig.2024.046591

Abstract La théorie égocentrée est aujourd’hui bien connue des éthologues et des psychologues mais moins diffusée chez les géographes car elle reste encore à l’état de théorie abstraite. Ce papier se propose dans un premier temps de rendre opérationnel cette approche dans le cadre de travaux géographiques à l’échelle de l’individu. Puis, elle envisage d’établir le lien entre l’échelle individu et l’échelle de la ville avec comme objectif de produire des cartes déformées de la ville. More > Graphic Abstract

Yuming Tang^1,#, Yitian Zhang^2,#, Tao Niu¹, Zhen Li^2,3,*, Zijian Zhang^1,3, Huaping Chen⁴, Long Zhang⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 2451-2477, 2024, DOI:10.32604/cmes.2024.030084

Abstract Federated Learning (FL), as an emergent paradigm in privacy-preserving machine learning, has garnered significant interest from scholars and engineers across both academic and industrial spheres. Despite its innovative approach to model training across distributed networks, FL has its vulnerabilities; the centralized server-client architecture introduces risks of single-point failures. Moreover, the integrity of the global model—a cornerstone of FL—is susceptible to compromise through poisoning attacks by malicious actors. Such attacks and the potential for privacy leakage via inference starkly undermine FL’s foundational privacy and security goals. For these reasons, some participants unwilling use their private data to train a model, which… More >

Dayu Xu^1,#, Jiaming Lü^1,#, Xuyao Zhang², Hongtao Zhang^1,*

CMC-Computers, Materials & Continua, Vol.78, No.2, pp. 2557-2573, 2024, DOI:10.32604/cmc.2024.045932

Abstract Data stream clustering is integral to contemporary big data applications. However, addressing the ongoing influx of data streams efficiently and accurately remains a primary challenge in current research. This paper aims to elevate the efficiency and precision of data stream clustering, leveraging the TEDA (Typicality and Eccentricity Data Analysis) algorithm as a foundation, we introduce improvements by integrating a nearest neighbor search algorithm to enhance both the efficiency and accuracy of the algorithm. The original TEDA algorithm, grounded in the concept of “Typicality and Eccentricity Data Analytics”, represents an evolving and recursive method that requires no prior knowledge. While the… More >

Bishrul Haq¹, Sher Muhammad Daudpota¹, Ali Shariq Imran², Zenun Kastrati^3,*, Waheed Noor⁴

CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 115-137, 2023, DOI:10.32604/cmc.2023.040638

Abstract The Internet has become one of the significant sources for sharing information and expressing users’ opinions about products and their interests with the associated aspects. It is essential to learn about product reviews; however, to react to such reviews, extracting aspects of the entity to which these reviews belong is equally important. Aspect-based Sentiment Analysis (ABSA) refers to aspects extracted from an opinionated text. The literature proposes different approaches for ABSA; however, most research is focused on supervised approaches, which require labeled datasets with manual sentiment polarity labeling and aspect tagging. This study proposes a semi-supervised approach with minimal human… More >

Yuki Kawasaki^1,*, Takeshi Sasaki¹, Daisuke Kobayashi²

Congenital Heart Disease, Vol.18, No.4, pp. 431-445, 2023, DOI:10.32604/chd.2023.030910

Abstract Background: Elevated Fontan pressure (FP) alone cannot fully predict clinical outcomes. We hypothesized that hemodynamic profiling using a cardiac index (CI)-systemic vascular resistance (SVR) plot could characterize clinical features and predict the prognosis of post-Fontan patients. Methods: We included post-Fontan patients who underwent cardiac catheterization at age < 10 years. Patients were classified into four categories: A, CI  ≥ 3, SVR index (SVRI) ≥ 20; B, CI < 3, SVRI ≥ 20; C, CI ≥ 3, SVRI < 20; and D, CI < 3, SVRI < 20. The primary outcome was freedom from the combined endpoint: new onset of protein-losing enteropathy or plastic bronchitis, heart transplant, and death. Clinical and hemodynamic variables and freedom from… More > Graphic Abstract

Wenxin Chen^1,#, Jie Wu^1,2,#, Long Li^3,*, Shiyong Wu^4,*

International Journal of Mental Health Promotion, Vol.25, No.8, pp. 949-959, 2023, DOI:10.32604/ijmhp.2023.030072

Abstract Background: University students’ ego-identity, an essential component of their psychological development and mental health, has widely attracted the attention of policymakers, schools, and parents. Method: A total of 298 Chinese vocational pathway undergraduates were recruited, and a conditional process analysis model was adopted to explore the interaction mechanism of ego-identity. Results: The results suggest that the ego-identity of Chinese vocational pathway undergraduates is significantly affected by interaction anxiousness, academic resilience, and cultural intelligence. (1) Interaction anxiousness significantly and positively predicts ego-identity. (2) Academic resilience positively and partially mediates the effect of interaction anxiousness on ego-identity. (3) Cultural intelligence significantly and… More >

Bilal Bataineh^*

Intelligent Automation & Soft Computing, Vol.37, No.2, pp. 1941-1961, 2023, DOI:10.32604/iasc.2023.039868

Abstract Autonomous vehicles are currently regarded as an interesting topic in the AI field. For such vehicles, the lane where they are traveling should be detected. Most lane detection methods identify the whole road area with all the lanes built on it. In addition to having a low accuracy rate and slow processing time, these methods require costly hardware and training datasets, and they fail under critical conditions. In this study, a novel detection algorithm for a lane where a car is currently traveling is proposed by combining simple traditional image processing with lightweight machine learning (ML) methods. First, a preparation… More >

K. Ravishankar^*, C. Jothikumar

Computer Systems Science and Engineering, Vol.47, No.1, pp. 613-635, 2023, DOI:10.32604/csse.2023.038343

Abstract Since COVID-19 infections are increasing all over the world, there is a need for developing solutions for its early and accurate diagnosis is a must. Detection methods for COVID-19 include screening methods like Chest X-rays and Computed Tomography (CT) scans. More work must be done on preprocessing the datasets, such as eliminating the diaphragm portions, enhancing the image intensity, and minimizing noise. In addition to the detection of COVID-19, the severity of the infection needs to be estimated. The HSDC model is proposed to solve these problems, which will detect and classify the severity of COVID-19 from X-ray and CT-scan… More >

Christine Plumejeaud-Perreau¹ , Lucie Nahassia² , Julie Gravier²

Revue Internationale de Géomatique, Vol.31, No.1, pp. 47-80, 2022, DOI:10.3166/RIG31.47-80

Abstract À travers trois exemples issus d’études des dynamiques de peuplement en France sur le temps long, intra et interurbaines, cet article montre que l’introduction d’ontologies « ahistoriques » a facilité la mise en place d’analyses numériques quantifiant les dynamiques spatiales. Cependant il démontre que ces ontologies ne sont pas neutres, qu’elles ne dissolvent pas la spécificité des sources mobilisées, et constituent au contraire des savoirs situés. Mais au-delà de ces critiques, les auteures tendent à argumenter que le processus de construction et de dialogue établi autour d’ontologie a-historique est très bénéfique à la recherche, qu’il est un socle pour une… More >

Shuang Liu^1,2,3, Xiao Liu¹, Shilong Chang¹, Yufeng Sun⁴, Kaiyuan Li¹, Ya Hou¹, Shiwei Wang¹, Jie Meng⁵, Qingliang Zhao⁶, Sibei Wu¹, Kun Yang^1,2,3,*, Linyan Xue^1,2,3,*

CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 5837-5852, 2023, DOI:10.32604/cmc.2023.034720

Abstract Achieving accurate classification of colorectal polyps during colonoscopy can avoid unnecessary endoscopic biopsy or resection. This study aimed to develop a deep learning model that can automatically classify colorectal polyps histologically on white-light and narrow-band imaging (NBI) colonoscopy images based on World Health Organization (WHO) and Workgroup serrAted polypS and Polyposis (WASP) classification criteria for colorectal polyps. White-light and NBI colonoscopy images of colorectal polyps exhibiting pathological results were firstly collected and classified into four categories: conventional adenoma, hyperplastic polyp, sessile serrated adenoma/polyp (SSAP) and normal, among which conventional adenoma could be further divided into three sub-categories of tubular adenoma,… More >