Anam Mughees^1,2,*, Muhammad Kamran^1,3

CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 507-526, 2024, DOI:10.32604/cmc.2024.051820

Abstract Non-intrusive load monitoring is a method that disaggregates the overall energy consumption of a building to estimate the electric power usage and operating status of each appliance individually. Prior studies have mostly concentrated on the identification of high-power appliances like HVAC systems while overlooking the existence of low-power appliances. Low-power consumer appliances have comparable power consumption patterns, which can complicate the detection task and can be mistaken as noise. This research tackles the problem of classification of low-power appliances and uses turn-on current transients to extract novel features and develop unique appliance signatures. A hybrid… More >

Siti Aekbal Salleh^1,2,*, Nafisah Khalid¹, Natasha Danny⁶, Nurul Ain Mohd. Zaki^2,3, Mustafa Ustuner⁴, Zulkiflee Abd Latif^1,2, Vladimir Foronda⁵

Revue Internationale de Géomatique, Vol.33, pp. 183-199, 2024, DOI:10.32604/rig.2024.050723

Abstract Due to the spectral and spatial properties of pervious and impervious surfaces, image classification and information extraction in detailed, small-scale mapping of urban surface materials is quite difficult and complex. Emerging methods and innovations in image classification have centred on object-based classification techniques and various segmentation techniques, which are fundamental to this approach. Consequently, the purpose of this study is to determine which classification method is most suitable for extracting linear features in terms of techniques and performance by comparing two classification methods, pixel-based approach and object-based approach, using WorldView-2 satellite imagery to specifically highlight… More > Graphic Abstract

Amerah Alabrah^*

CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 3897-3912, 2024, DOI:10.32604/cmc.2024.048528

Abstract The emergence of digital networks and the wide adoption of information on internet platforms have given rise to threats against users’ private information. Many intruders actively seek such private data either for sale or other inappropriate purposes. Similarly, national and international organizations have country-level and company-level private information that could be accessed by different network attacks. Therefore, the need for a Network Intruder Detection System (NIDS) becomes essential for protecting these networks and organizations. In the evolution of NIDS, Artificial Intelligence (AI) assisted tools and methods have been widely adopted to provide effective solutions. However,… More >

Igor B. Palymskiy^1,2,*

FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.5, pp. 957-974, 2024, DOI:10.32604/fdmp.2024.048829

Abstract The fully nonlinear equations of gas dynamics are solved in the framework of a numerical approach in order to study the stability of the steady mode of Rayleigh-Bénard convection in compressible, viscous and heat-conducting gases encapsulated in containers with no-slip boundaries and isothermal top and bottom walls. An initial linear temperature profile is assumed. A map of the possible convective modes is presented assuming the height of the region and the value of the temperature gradient as influential parameters. For a relatively small height, isobaric convection is found to take place, which is taken over… More >

Yanjie Zhang^1,2, Jin Kuang³, Xun Luo^1,2, Mengxian Zhao⁴, Xiaolei Liu^5,*

International Journal of Mental Health Promotion, Vol.26, No.5, pp. 399-406, 2024, DOI:10.32604/ijmhp.2024.048925

Abstract Background: Emerging adulthood is a pivotal life stage, presenting significant psychological and social changes, such as decreased sociability, depression, and other mental health problems. Previous studies have associated these changes with an unhealthy lifestyle. The 24-h movement guidelines for healthy lifestyles have been developed to promote appropriate health behaviors and improve individual wellness. However, the relationship between adherence to the 24-h movement guidelines and different characteristics of Chinese emerging adults is yet to be explored. This cross-sectional study aimed to investigate the association between adherence to the 24-h movement guidelines and four characteristics (self-exploration, instability, possibilities,… More >

Haijian Shao^1,2,*, Suqin Lei¹, Chenxu Yan³, Xing Deng¹, Yunsong Qi¹

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.2, pp. 1507-1537, 2024, DOI:10.32604/cmes.2024.050140

Abstract This paper expounds upon a novel target detection methodology distinguished by its elevated discriminatory efficacy, specifically tailored for environments characterized by markedly low luminance levels. Conventional methodologies struggle with the challenges posed by luminosity fluctuations, especially in settings characterized by diminished radiance, further exacerbated by the utilization of suboptimal imaging instrumentation. The envisioned approach mandates a departure from the conventional YOLOX model, which exhibits inadequacies in mitigating these challenges. To enhance the efficacy of this approach in low-light conditions, the dehazing algorithm undergoes refinement, effecting a discerning regulation of the transmission rate at the pixel… More > Graphic Abstract

Fadl Dahan^*

Intelligent Automation & Soft Computing, Vol.39, No.2, pp. 381-395, 2024, DOI:10.32604/iasc.2024.047921

Abstract In the domain of medical imaging, the accurate detection and classification of brain tumors is very important. This study introduces an advanced method for identifying camouflaged brain tumors within images. Our proposed model consists of three steps: Feature extraction, feature fusion, and then classification. The core of this model revolves around a feature extraction framework that combines color-transformed images with deep learning techniques, using the ResNet50 Convolutional Neural Network (CNN) architecture. So the focus is to extract robust feature from MRI images, particularly emphasizing weighted average features extracted from the first convolutional layer renowned for… More >

Aiman¹, Muhammad Arshad¹, Bilal Khan¹, Khalil Khan², Ali Mustafa Qamar^3,*, Rehan Ullah Khan⁴

Intelligent Automation & Soft Computing, Vol.39, No.2, pp. 301-317, 2024, DOI:10.32604/iasc.2024.045402

Abstract This study explores the area of Author Profiling (AP) and its importance in several industries, including forensics, security, marketing, and education. A key component of AP is the extraction of useful information from text, with an emphasis on the writers’ ages and genders. To improve the accuracy of AP tasks, the study develops an ensemble model dubbed ABMRF that combines AdaBoostM1 (ABM1) and Random Forest (RF). The work uses an extensive technique that involves text message dataset pretreatment, model training, and assessment. To evaluate the effectiveness of several machine learning (ML) algorithms in classifying age… More >

Mahmood Ul Haq¹, Muhammad Athar Javed Sethi¹, Najib Ben Aoun^2,3, Ala Saleh Alluhaidan^4,*, Sadique Ahmad^5,6, Zahid farid⁷

CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 2169-2186, 2024, DOI:10.32604/cmc.2024.049645

Abstract Face recognition (FR) technology has numerous applications in artificial intelligence including biometrics, security, authentication, law enforcement, and surveillance. Deep learning (DL) models, notably convolutional neural networks (CNNs), have shown promising results in the field of FR. However CNNs are easily fooled since they do not encode position and orientation correlations between features. Hinton et al. envisioned Capsule Networks as a more robust design capable of retaining pose information and spatial correlations to recognize objects more like the brain does. Lower-level capsules hold 8-dimensional vectors of attributes like position, hue, texture, and so on, which are… More >

Hina Naz¹, Zuping Zhang^1,*, Mohammed Al-Habib¹, Fuad A. Awwad², Emad A. A. Ismail², Zaid Ali Khan³

CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 2673-2696, 2024, DOI:10.32604/cmc.2024.049186

Abstract Cardiovascular disease is the leading cause of death globally. This disease causes loss of heart muscles and is also responsible for the death of heart cells, sometimes damaging their functionality. A person’s life may depend on receiving timely assistance as soon as possible. Thus, minimizing the death ratio can be achieved by early detection of heart attack (HA) symptoms. In the United States alone, an estimated 610,000 people die from heart attacks each year, accounting for one in every four fatalities. However, by identifying and reporting heart attack symptoms early on, it is possible to… More >