Cheng-Jen Ma^*†‡, Ching-Wen Huang^*‡§, Yung-Sung Yeh^*†¶, Hsiang-Lin Tsai^*§#**, Huang-Ming Hu^††‡‡, I-Chen Wu^††‡‡, Tian-Lu Cheng^§§¶¶, Jaw-Yuan Wang^{*†‡§**¶¶}

Oncology Research, Vol.25, No.5, pp. 673-679, 2017, DOI:10.3727/97818823455816X14786040691928

Abstract We analyzed the results of previously treated patients with metastatic colorectal cancer (mCRC) who received regorafenib plus FOLFIRI with the irinotecan dose escalation on the basis of uridine diphosphate glucuronosyltransferase 1A1 (UGT1A1) genotyping. Thirteen patients with previously treated mCRC were subjected to UGT1A1 genotyping between October 2013 and June 2015 and were administered regorafenib plus FOLFIRI with irinotecan dose escalation. Patients with UGT1A1*1/*1 and *1/*28 genotypes were administered 180 mg/m² of irinotecan, whereas those with the UGT1A1*28/*28 genotype were administered 120 mg/m2 of irinotecan. For all patients, the irinotecan dose was increased by 30 mg/m2 every… More >

Aigerim Baimakhanova^1,*, Ainur Zhumadillayeva², Bigul Mukhametzhanova³, Natalya Glazyrina², Rozamgul Niyazova², Nurseit Zhunissov¹, Aizhan Sambetbayeva⁴

Computer Systems Science and Engineering, Vol.48, No.3, pp. 793-811, 2024, DOI:10.32604/csse.2024.043273

Abstract As digital technologies have advanced more rapidly, the number of paper documents recently converted into a digital format has exponentially increased. To respond to the urgent need to categorize the growing number of digitized documents, the classification of digitized documents in real time has been identified as the primary goal of our study. A paper classification is the first stage in automating document control and efficient knowledge discovery with no or little human involvement. Artificial intelligence methods such as Deep Learning are now combined with segmentation to study and interpret those traits, which were not… More >

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… 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… 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… 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… 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… 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… 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… More >