Le Zou¹, Linsong Hu¹, Yifan Wang¹, Zhize Wu², Xiaofeng Wang^1,*

CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 927-941, 2024, DOI:10.32604/cmc.2024.048889

Abstract Depth estimation is an important task in computer vision. Collecting data at scale for monocular depth estimation is challenging, as this task requires simultaneously capturing RGB images and depth information. Therefore, data augmentation is crucial for this task. Existing data augmentation methods often employ pixel-wise transformations, which may inadvertently disrupt edge features. In this paper, we propose a data augmentation method for monocular depth estimation, which we refer to as the Perpendicular-Cutdepth method. This method involves cutting real-world depth maps along perpendicular directions and pasting them onto input images, thereby diversifying the data without compromising edge features. To validate the… More >

Yushan Yin¹, Witold Pedrycz^1,2, Zhiwu Li^1,*

CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 623-650, 2024, DOI:10.32604/cmc.2024.048787

Abstract Utilizing granular computing to enhance artificial neural network architecture, a new type of network emerges—the granular neural network (GNN). GNNs offer distinct advantages over their traditional counterparts: The ability to process both numerical and granular data, leading to improved interpretability. This paper proposes a novel design method for constructing GNNs, drawing inspiration from existing interval-valued neural networks built upon NNNs. However, unlike the proposed algorithm in this work, which employs interval values or triangular fuzzy numbers for connections, existing methods rely on a pre-defined numerical network. This new method utilizes a uniform distribution of information granularity to granulate connections with… More >

Sapiah Sakri¹, Shakila Basheer¹, Zuhaira Muhammad Zain¹, Nurul Halimatul Asmak Ismail^2,*, Dua’ Abdellatef Nassar¹, Manal Abdullah Alohali¹, Mais Ayman Alharaki¹

CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 1157-1185, 2024, DOI:10.32604/cmc.2024.048051

Abstract Background: Sepsis, a potentially fatal inflammatory disease triggered by infection, carries significant health implications worldwide. Timely detection is crucial as sepsis can rapidly escalate if left undetected. Recent advancements in deep learning (DL) offer powerful tools to address this challenge. Aim: Thus, this study proposed a hybrid CNNBDLSTM, a combination of a convolutional neural network (CNN) with a bi-directional long short-term memory (BDLSTM) model to predict sepsis onset. Implementing the proposed model provides a robust framework that capitalizes on the complementary strengths of both architectures, resulting in more accurate and timelier predictions. Method: The sepsis prediction method proposed here utilizes… More >

Amardeep Singh¹, Hamad Ali Abosaq², Saad Arif³, Zohaib Mushtaq^4,*, Muhammad Irfan⁵, Ghulam Abbas⁶, Arshad Ali⁷, Alanoud Al Mazroa⁸

CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 857-873, 2024, DOI:10.32604/cmc.2024.048036

Abstract Data security assurance is crucial due to the increasing prevalence of cloud computing and its widespread use across different industries, especially in light of the growing number of cybersecurity threats. A major and ever-present threat is Ransomware-as-a-Service (RaaS) assaults, which enable even individuals with minimal technical knowledge to conduct ransomware operations. This study provides a new approach for RaaS attack detection which uses an ensemble of deep learning models. For this purpose, the network intrusion detection dataset “UNSW-NB15” from the Intelligent Security Group of the University of New South Wales, Australia is analyzed. In the initial phase, the rectified linear… More >

Mohammed Alatiyyah^*

CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 875-907, 2024, DOI:10.32604/cmc.2024.047790

Abstract In the contemporary era of technological advancement, smartphones have become an indispensable part of individuals’ daily lives, exerting a pervasive influence. This paper presents an innovative approach to passenger counting on buses through the analysis of Wi-Fi signals emanating from passengers’ mobile devices. The study seeks to scrutinize the reliability of digital Wi-Fi environments in predicting bus occupancy levels, thereby addressing a crucial aspect of public transportation. The proposed system comprises three crucial elements: Signal capture, data filtration, and the calculation and estimation of passenger numbers. The pivotal findings reveal that the system demonstrates commendable accuracy in estimating passenger counts… More >

Ahsan Wajahat¹, Jingsha He¹, Nafei Zhu¹, Tariq Mahmood^2,3, Tanzila Saba², Amjad Rehman Khan², Faten S. Alamri^4,*

CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 651-673, 2024, DOI:10.32604/cmc.2024.047530

Abstract The growing usage of Android smartphones has led to a significant rise in incidents of Android malware and privacy breaches. This escalating security concern necessitates the development of advanced technologies capable of automatically detecting and mitigating malicious activities in Android applications (apps). Such technologies are crucial for safeguarding user data and maintaining the integrity of mobile devices in an increasingly digital world. Current methods employed to detect sensitive data leaks in Android apps are hampered by two major limitations they require substantial computational resources and are prone to a high frequency of false positives. This means that while attempting to… More >

Yashan Feng¹, Yafang Tian¹, Yongxin Yang¹, Yufang Zhang¹, Haiwei Guo¹, Jing’an Li^2,*

CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 263-278, 2024, DOI:10.32604/cmc.2024.047004

Abstract Electroactive anticorrosion coatings are specialized surface treatments that prevent or minimize corrosion. The study employs strategic thermodynamic equilibrium calculations to pioneer a novel factor in corrosion protection. A first-time proposal, the total acidity (TA) potential of the hydrogen (pH) concept significantly shapes medical magnesium alloys. These coatings are meticulously designed for robust corrosion resistance, blending theoretical insights and practical applications to enhance our grasp of corrosion prevention mechanisms and establish a systematic approach to coating design. The groundbreaking significance of this study lies in its innovative integration of the TA/pH concept, which encompasses the TA/pH ratio of the chemical environment.… More >

Fayez Alfayez^*

CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 1539-1560, 2024, DOI:10.32604/cmc.2024.046443

Abstract This paper emphasizes a faster digital processing time while presenting an accurate method for identifying spine fractures in X-ray pictures. The study focuses on efficiency by utilizing many methods that include picture segmentation, feature reduction, and image classification. Two important elements are investigated to reduce the classification time: Using feature reduction software and leveraging the capabilities of sophisticated digital processing hardware. The researchers use different algorithms for picture enhancement, including the Wiener and Kalman filters, and they look into two background correction techniques. The article presents a technique for extracting textural features and evaluates three picture segmentation algorithms and three… More >

BIOCELL, Vol.48, Suppl.1, pp. 1-289, 2024

Abstract This article has no abstract. More >

MARKO SKELIN^1,2,3,*, BRUNA PERKOV-STIPIČIN¹, SANJA VUŠKOVIĆ⁴, MARINA ŠANDRK PLEHAČEK⁵, ANE BAŠIĆ⁶, DAVID ŠARČEVIĆ⁷, MAJA ILIĆ⁸, IVAN KREČAK^2,3,9

Oncology Research, Vol.32, No.5, pp. 807-815, 2024, DOI:10.32604/or.2024.048948

Abstract Background: The European Society for Medical Oncology (ESMO) guidelines are among the most comprehensive and widely used clinical practice guidelines (CPGs) globally. However, the level of scientific evidence supporting ESMO CPG recommendations has not been systematically investigated. This study assessed ESMO CPG levels of evidence (LOE) and grades of recommendations (GOR), as well as their trends over time across various cancer settings. Methods: We manually extracted every recommendation with the Infectious Diseases Society of America (IDSA) classification from each CPG. We examined the distribution of LOE and GOR in all available ESMO CPG guidelines across different topics and cancer types.… More >