Khaldon Azzam Kordi¹, Mardeni Roslee^1,*, Mohamad Yusoff Alias¹, Abdulraqeb Alhammadi², Athar Waseem³, Anwar Faizd Osman⁴

CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 3261-3298, 2024, DOI:10.32604/cmc.2024.044890

Abstract This study comprehensively examines the current state of deep learning (DL) usage in indoor positioning. It emphasizes the significance and efficiency of convolutional neural networks (CNNs) and recurrent neural networks (RNNs). Unlike prior studies focused on single sensor modalities like Wi-Fi or Bluetooth, this research explores the integration of multiple sensor modalities (e.g., Wi-Fi, Bluetooth, Ultra-Wideband, ZigBee) to expand indoor localization methods, particularly in obstructed environments. It addresses the challenge of precise object localization, introducing a novel hybrid DL approach using received signal information (RSI), Received Signal Strength (RSS), and Channel State Information (CSI) data to enhance accuracy and stability.… More >

Wajdi Alhakami^*

CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 3211-3237, 2024, DOI:10.32604/cmc.2023.043935

Abstract The Kingdom of Saudi Arabia (KSA) has achieved significant milestones in cybersecurity. KSA has maintained solid regulatory mechanisms to prevent, trace, and punish offenders to protect the interests of both individual users and organizations from the online threats of data poaching and pilferage. The widespread usage of Information Technology (IT) and IT Enable Services (ITES) reinforces security measures. The constantly evolving cyber threats are a topic that is generating a lot of discussion. In this league, the present article enlists a broad perspective on how cybercrime is developing in KSA at present and also takes a look at some of… More >

Israa Ismail^1,*, Ghada Eltaweel¹, Mohamed Meselhy Eltoukhy^1,2

CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 3193-3209, 2024, DOI:10.32604/cmc.2023.043873

Abstract Super-resolution techniques are employed to enhance image resolution by reconstructing high-resolution images from one or more low-resolution inputs. Super-resolution is of paramount importance in the context of remote sensing, satellite, aerial, security and surveillance imaging. Super-resolution remote sensing imagery is essential for surveillance and security purposes, enabling authorities to monitor remote or sensitive areas with greater clarity. This study introduces a single-image super-resolution approach for remote sensing images, utilizing deep shearlet residual learning in the shearlet transform domain, and incorporating the Enhanced Deep Super-Resolution network (EDSR). Unlike conventional approaches that estimate residuals between high and low-resolution images, the proposed approach… More >

Farah Mohammad^1,*, Saad Al-Ahmadi², Jalal Al-Muhtadi^1,2

CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 3175-3192, 2024, DOI:10.32604/cmc.2023.042873

Abstract Electricity theft is a widespread non-technical issue that has a negative impact on both power grids and electricity users. It hinders the economic growth of utility companies, poses electrical risks, and impacts the high energy costs borne by consumers. The development of smart grids is crucial for the identification of power theft since these systems create enormous amounts of data, including information on client consumption, which may be used to identify electricity theft using machine learning and deep learning techniques. Moreover, there also exist different solutions such as hardware-based solutions to detect electricity theft that may require human resources and… More >

Shalu¹, Twinkle Acharya¹, Dhwanilnath Gharekhan^1,*, Dipak Samal²

Revue Internationale de Géomatique, Vol.33, pp. 111-134, 2024, DOI:10.32604/rig.2024.051788

Abstract Seismic vulnerability modeling plays a crucial role in seismic risk assessment, aiding decision-makers in pinpointing areas and structures most prone to earthquake damage. While machine learning (ML) algorithms and Geographic Information Systems (GIS) have emerged as promising tools for seismic vulnerability modeling, there remains a notable gap in comprehensive geospatial studies focused on India. Previous studies in seismic vulnerability modeling have primarily focused on specific regions or countries, often overlooking the unique challenges and characteristics of India. In this study, we introduce a novel approach to seismic vulnerability modeling, leveraging ML and GIS to address these gaps. Employing Artificial Neural… More >

Hina Batool¹, Jiuyun Xu^1,*, Ateeq Ur Rehman², Habib Hamam^3,4,5,6

Journal on Artificial Intelligence, Vol.6, pp. 105-128, 2024, DOI:10.32604/jai.2024.049912

Abstract Federated Learning (FL) appeared as an encouraging approach for handling decentralized data. Creating a FL system needs both machine learning (ML) knowledge and thinking about how to design system software. Researchers have focused a lot on the ML side of FL, but have not paid enough attention to designing the software architecture. So, in this survey, a set of design patterns is described to tackle the design issues. Design patterns are like reusable solutions for common problems that come up when designing software architecture. This paper focuses on (1) design patterns such as architectures, frameworks, client selection protocols, personalization techniques,… More >

Wai Tuck Chow^*, Jia Tai Lau

Digital Engineering and Digital Twin, Vol.2, pp. 103-130, 2024, DOI:10.32604/dedt.2024.044545

Abstract This paper presents a novel approach to using supervised learning with a shallow neural network to increase the efficiency of the finite element analysis of holes under biaxial load. With this approach, the number of elements in the finite element analysis can be reduced while maintaining good accuracy. The neural network will be used to predict the maximum stress for holes of different configurations such as holes in a finite-width plate (2D), multiple holes (2D), staggered holes (2D), and holes in an infinite plate (3D). The predictions are based on their respective coarse mesh with only 2 elements along the… More >

YI HU^1,#, ZHONGYANG REN^2,#, ZHENGZHONG ZHAO¹, YONGJIA HUANG³, WANTING HUANG³, JIE LIU^3,*, LING DING^3,*

BIOCELL, Vol.48, No.5, pp. 745-758, 2024, DOI:10.32604/biocell.2024.049140

Abstract Background: Acute pancreatitis (AP), known for its rapid onset and significant incidence and mortality rates, presents a clinical challenge due to the limited availability of effective treatments and preventive measures. Anemarsaponin B (ASB) has emerged as a potential therapeutic agent, demonstrating capabilities in reducing immune inflammation, positioning it as a promising candidate for AP treatment. Methods: We investigated the effects of ASB on AP in mice, induced by caerulein and lipopolysaccharide (LPS). Peripheral blood samples were collected 24 h post-induction with caerulein to assess of key biomarkers including lipase, amylase, TNF-α, IL-1β, IL-6, SOD, and GSH-Px. A range of techniques… More >

TINGTING LIU^1,#, YIWEI HAO^2,#, LIFENG ZHAO^2,*

BIOCELL, Vol.48, No.5, pp. 707-729, 2024, DOI:10.32604/biocell.2024.049130

Abstract Parkinson’s disease (PD) is a common neurodegenerative disease in the elderly, accounting for more than 1% of the population aged 65 years. Monogenic inheritance is relatively rare in PD, accounting for approximately 5% to 10% of PD patients, and there is a growing body of evidence suggesting that multiple genetic risk factors play a significant role in the pathogenesis of PD. Several groups have identified and reported a number of genes carrying mutations associated with affected family members. Mutated genes associated with PD are also candidates for idiopathic PD, and these genes may also carry other mutation sites that increase… More >

CHENG-GONG LUO^1,2,#, JIAO ZHANG^1,#, YUN-ZHAO AN¹, XUAN LIU¹, SHUAI-JIE LI¹, WEI ZHANG¹, KAI LI¹, XU ZHAO¹, DONG-BO YUAN¹, LING-YUE AN¹, WEI CHEN², YE TIAN^1,*, BIN XU^1,*

BIOCELL, Vol.48, No.5, pp. 771-792, 2024, DOI:10.32604/biocell.2024.048878

Abstract Background: Ferroptosis, a lipid peroxidation-mediated programmed cell death, is closely linked to tumor development, including prostate cancer (PCa). Despite established connections between ferroptosis and PCa, a comprehensive investigation is essential for understanding its impact on patient prognosis. Methods: A risk model incorporating four ferroptosis-related genes was developed and validated. Elevated risk scores correlated with an increased likelihood of biochemical recurrence (BCR), diminished immune infiltration, and adverse clinicopathological characteristics. To corroborate these results, we performed validation analyses utilizing datasets from both the Cancer Genome Atlas Cohort (TCGA) and the Gene Expression Synthesis Cohort (GEO). Moreover, we conducted further investigations into the… More >