Saad M. Darwish^1,*, Abdul Rahman M. Sabri², Dhafar Hamed Abd², Adel A. Elzoghabi¹

Computer Systems Science and Engineering, Vol.48, No.6, pp. 1595-1624, 2024, DOI:10.32604/csse.2024.054615 - 22 November 2024

Abstract The number of blogs and other forms of opinionated online content has increased dramatically in recent years. Many fields, including academia and national security, place an emphasis on automated political article orientation detection. Political articles (especially in the Arab world) are different from other articles due to their subjectivity, in which the author’s beliefs and political affiliation might have a significant influence on a political article. With categories representing the main political ideologies, this problem may be thought of as a subset of the text categorization (classification). In general, the performance of machine learning models… More >

ROSSANA RONCATO^1,2, JERRY POLESEL³, FEDERICA TOSI^4,5,*, ELENA PERUZZI^1,*, ERIKA BRUGUGNOLI⁶, CLAUDIA LAURIA PANTANO⁷, MARIA FURFARO⁸, FILIPPO DI GIROLAMO^9,10, ALESSANDRO NANI¹¹, ARIANNA PANI⁴, NOEMI MILAN¹, ELENA DE MATTIA¹, ANDREA SARTORE-BIANCHI^4,5, ERIKA CECCHIN¹

Oncology Research, Vol.32, No.9, pp. 1407-1422, 2024, DOI:10.32604/or.2024.049181 - 23 August 2024

Abstract Objectives: Treatment of metastatic colorectal cancer (mCRC) includes resection of liver metastases (LM), however, no validated biomarker identifies patients most likely to benefit from this procedure. This meta-analysis aimed to assess the impact of the most relevant molecular alterations in cancer-related genes of CRC (i.e., RAS, BRAF, SMAD4, PIK3CA) as prognostic markers of survival and disease recurrence in patients with mCRC surgically treated by LM resection. Methods: A systematic literature review was performed to identify studies reporting data regarding survival and/or recurrence in patients that underwent complete liver resection for CRC LM, stratified according to… More > Graphic Abstract

Meijing Li^*, Runqing Huang, Xianxian Qi

CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 2283-2299, 2024, DOI:10.32604/cmc.2024.053630 - 15 August 2024

Abstract Chinese Clinical Named Entity Recognition (CNER) is a crucial step in extracting medical information and is of great significance in promoting medical informatization. However, CNER poses challenges due to the specificity of clinical terminology, the complexity of Chinese text semantics, and the uncertainty of Chinese entity boundaries. To address these issues, we propose an improved CNER model, which is based on multi-feature fusion and multi-scale local context enhancement. The model simultaneously fuses multi-feature representations of pinyin, radical, Part of Speech (POS), word boundary with BERT deep contextual representations to enhance the semantic representation of text… More >

Islam Zada^1,*, Mohammed Naif Alatawi², Syed Muhammad Saqlain¹, Abdullah Alshahrani³, Adel Alshamran⁴, Kanwal Imran⁵, Hessa Alfraihi⁶

CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 2917-2939, 2024, DOI:10.32604/cmc.2024.052835 - 15 August 2024

Abstract Malware attacks on Windows machines pose significant cybersecurity threats, necessitating effective detection and prevention mechanisms. Supervised machine learning classifiers have emerged as promising tools for malware detection. However, there remains a need for comprehensive studies that compare the performance of different classifiers specifically for Windows malware detection. Addressing this gap can provide valuable insights for enhancing cybersecurity strategies. While numerous studies have explored malware detection using machine learning techniques, there is a lack of systematic comparison of supervised classifiers for Windows malware detection. Understanding the relative effectiveness of these classifiers can inform the selection of… More >

Fanny Delehaye^1,2,*, Olivier Dejardin^1,3, Isabelle Pellier⁴, Ludivine Launay^1,5, Maxime Esvan⁶, Damien Bodet², Liana Carausu⁷, Julien Lejeune⁸, Frédéric Millot⁹, Caroline Thomas¹⁰, Virginie Gandemer¹¹, Arnaud Alves^1,12, Julien Rod^1,13

Psycho-Oncologie, Vol.18, No.2, pp. 117-126, 2024, DOI:10.32604/po.2024.043073 - 06 August 2024

Abstract La période post-traitement une part fondamental de la prise en charge du cancer pédiatrique. Durant cette période, les difficultés scolaires et psychologiques chez les survivants d’un cancer pédiatriques (SCP) sont connues et peuvent être pronostic sur la bonne réintégration sociale. Cette étude estime l’influence de la déprivation sociale du foyer de l’enfant sur ces difficultés. Notre étude se base sur une base de données multicentrique, et se concentre sur les SCP avant reçu une évaluation psychosociale au cours de leur suivi, de 2013 à 2020. Nous rapportons les données des difficultés scolaires et psychologiques. Le… More >

Taghreed Alsufyani^1,*, Noura J. Alotaibi², Nour Houda M’sakni¹, Mona A. Almalki¹, Eman M. Alghamdi³

Phyton-International Journal of Experimental Botany, Vol.93, No.7, pp. 1523-1542, 2024, DOI:10.32604/phyton.2024.050351 - 30 July 2024

Abstract This study simplifies the complex relationship among grapevine plants, aphids, ladybirds, and ants, which is essential for effective pest management and ecological balance. This study investigated the impact of aphid attacks and the presence of ants and ladybirds on the volatile compounds profile released into the chemosphere of the community consisting of the common vine Vitis vinifera, the aphid Aphis illinoisensis, the ladybird Coccinella undecimpunctata-and the ant Tapinoma magnum. This study aims to analyze the volatile compounds emitted by the grapevine and surrounding insects in response to these intricate interactions. The extraction of volatile organic compounds (VOCs) was carried… More >

Ahmad Ababneh¹, Yousef Sanjalawe², Salam Fraihat^3,*, Salam Al-E’mari⁴, Hamzah Alqudah⁵

CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 1347-1379, 2024, DOI:10.32604/cmc.2024.050600 - 18 July 2024

Abstract This study introduces the Orbit Weighting Scheme (OWS), a novel approach aimed at enhancing the precision and efficiency of Vector Space information retrieval (IR) models, which have traditionally relied on weighting schemes like tf-idf and BM25. These conventional methods often struggle with accurately capturing document relevance, leading to inefficiencies in both retrieval performance and index size management. OWS proposes a dynamic weighting mechanism that evaluates the significance of terms based on their orbital position within the vector space, emphasizing term relationships and distribution patterns overlooked by existing models. Our research focuses on evaluating OWS’s impact… More >

Suyi Liu^1,*, Jianning Chi¹, Chengdong Wu¹, Fang Xu^2,3,4, Xiaosheng Yu¹

CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 4471-4489, 2024, DOI:10.32604/cmc.2024.049450 - 20 June 2024

Abstract In recent years, semantic segmentation on 3D point cloud data has attracted much attention. Unlike 2D images where pixels distribute regularly in the image domain, 3D point clouds in non-Euclidean space are irregular and inherently sparse. Therefore, it is very difficult to extract long-range contexts and effectively aggregate local features for semantic segmentation in 3D point cloud space. Most current methods either focus on local feature aggregation or long-range context dependency, but fail to directly establish a global-local feature extractor to complete the point cloud semantic segmentation tasks. In this paper, we propose a Transformer-based… More >

Dengyong Zhang^1,2, Yuting Zhao^1,2, Feng Li^1,2, Arun Kumar Sangaiah^3,4,*

Intelligent Automation & Soft Computing, Vol.39, No.2, pp. 115-133, 2024, DOI:10.32604/iasc.2024.040847 - 21 May 2024

Abstract Image inpainting is a kind of use known area of information technology to repair the loss or damage to the area. Image feature extraction is the core of image restoration. Getting enough space for information and a larger receptive field is very important to realize high-precision image inpainting. However, in the process of feature extraction, it is difficult to meet the two requirements of obtaining sufficient spatial information and large receptive fields at the same time. In order to obtain more spatial information and a larger receptive field at the same time, we put forward… More >

Yuancong Chai, Yuefei Zhu^*, Wei Lin, Ding Li

CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 1223-1243, 2024, DOI:10.32604/cmc.2024.049904 - 25 April 2024

Abstract With the increasing proportion of encrypted traffic in cyberspace, the classification of encrypted traffic has become a core key technology in network supervision. In recent years, many different solutions have emerged in this field. Most methods identify and classify traffic by extracting spatiotemporal characteristics of data flows or byte-level features of packets. However, due to changes in data transmission mediums, such as fiber optics and satellites, temporal features can exhibit significant variations due to changes in communication links and transmission quality. Additionally, partial spatial features can change due to reasons like data reordering and retransmission.… More >