Jason Elroy Martis¹, Sannidhan Manjaya Shetty^2,*, Manas Ranjan Pradhan³, Usha Desai⁴, Biswaranjan Acharya^5,*

CMC-Computers, Materials & Continua, Vol.76, No.1, pp. 915-938, 2023, DOI:10.32604/cmc.2023.038847 - 08 June 2023

Abstract In the past, sketches were a standard technique used for recognizing offenders and have remained a valuable tool for law enforcement and social security purposes. However, relying on eyewitness observations can lead to discrepancies in the depictions of the sketch, depending on the experience and skills of the sketch artist. With the emergence of modern technologies such as Generative Adversarial Networks (GANs), generating images using verbal and textual cues is now possible, resulting in more accurate sketch depictions. In this study, we propose an adversarial network that generates human facial sketches using such cues provided More >

Faguo Wu^1,2,3,4,*, Bo Zhou², Jie Jiang⁵, Tianyu Lei¹, Jiale Song¹

CMC-Computers, Materials & Continua, Vol.76, No.1, pp. 957-973, 2023, DOI:10.32604/cmc.2023.038771 - 08 June 2023

Abstract With the rapid increase in demand for data trustworthiness and data security, distributed data storage technology represented by blockchain has received unprecedented attention. These technologies have been suggested for various uses because of their remarkable ability to offer decentralization, high autonomy, full process traceability, and tamper resistance. Blockchain enables the exchange of information and value in an untrusted environment. There has been a significant increase in attention to the confidentiality and privacy preservation of blockchain technology. Ensuring data privacy is a critical concern in cryptography, and one of the most important protocols used to achieve… More >

Jian Feng^*, Yuwen Wang, Shaojian Chen

CMC-Computers, Materials & Continua, Vol.76, No.1, pp. 397-413, 2023, DOI:10.32604/cmc.2023.038741 - 08 June 2023

Abstract Session-based Recommendation (SBR) aims to accurately recommend a list of items to users based on anonymous historical session sequences. Existing methods for SBR suffer from several limitations: SBR based on Graph Neural Network often has information loss when constructing session graphs; Inadequate consideration is given to influencing factors, such as item price, and users’ dynamic interest evolution is not taken into account. A new session recommendation model called Price-aware Session-based Recommendation (PASBR) is proposed to address these limitations. PASBR constructs session graphs by information lossless approaches to fully encode the original session information, then introduces More >

Oussama Accouche^1,*, Rajan Kumar Gangadhari²

CMC-Computers, Materials & Continua, Vol.76, No.1, pp. 151-173, 2023, DOI:10.32604/cmc.2023.038648 - 08 June 2023

Abstract Distributed renewable energy sources offer significant alternatives for Qatar and the Arab Gulf region’s future fuel supply and demand. Microgrids are essential for providing dependable power in difficult-to-reach areas while incorporating significant amounts of renewable energy sources. In energy-efficient data centers, distributed generation can be used to meet the facility’s overall power needs. This study primarily focuses on the best energy management practices for a smart microgrid in Qatar while taking demand-side load management into account. This article looked into a university microgrid in Qatar that primarily aimed to get all of its energy from… More >

Deepthi K. Oommen^*, J. Arunnehru

CMC-Computers, Materials & Continua, Vol.76, No.1, pp. 793-811, 2023, DOI:10.32604/cmc.2023.038640 - 08 June 2023

Abstract Alzheimer’s Disease (AD) is a progressive neurological disease. Early diagnosis of this illness using conventional methods is very challenging. Deep Learning (DL) is one of the finest solutions for improving diagnostic procedures’ performance and forecast accuracy. The disease’s widespread distribution and elevated mortality rate demonstrate its significance in the older-onset and younger-onset age groups. In light of research investigations, it is vital to consider age as one of the key criteria when choosing the subjects. The younger subjects are more susceptible to the perishable side than the older onset. The proposed investigation concentrated on the… More >

Tianzi Zhao^1,2,3,4, Liang Jin^1,2,3,*, Xiaofeng Zhou^1,2,3, Shuai Li^1,2,3, Shurui Liu^1,2,3,4, Jiang Zhu^1,2,3

CMC-Computers, Materials & Continua, Vol.76, No.1, pp. 329-346, 2023, DOI:10.32604/cmc.2023.038595 - 08 June 2023

Abstract The widespread usage of Cyber Physical Systems (CPSs) generates a vast volume of time series data, and precisely determining anomalies in the data is critical for practical production. Autoencoder is the mainstream method for time series anomaly detection, and the anomaly is judged by reconstruction error. However, due to the strong generalization ability of neural networks, some abnormal samples close to normal samples may be judged as normal, which fails to detect the abnormality. In addition, the dataset rarely provides sufficient anomaly labels. This research proposes an unsupervised anomaly detection approach based on adversarial memory… More >

Bhawna Goyal^1,*, Ayush Dogra², Rahul Khoond¹, Dawa Chyophel Lepcha¹, Vishal Goyal³, Steven L. Fernandes⁴

CMC-Computers, Materials & Continua, Vol.76, No.1, pp. 311-327, 2023, DOI:10.32604/cmc.2023.038398 - 08 June 2023

Abstract The synthesis of visual information from multiple medical imaging inputs to a single fused image without any loss of detail and distortion is known as multimodal medical image fusion. It improves the quality of biomedical images by preserving detailed features to advance the clinical utility of medical imaging meant for the analysis and treatment of medical disorders. This study develops a novel approach to fuse multimodal medical images utilizing anisotropic diffusion (AD) and non-subsampled contourlet transform (NSCT). First, the method employs anisotropic diffusion for decomposing input images to their base and detail layers to coarsely… More >

Sarab AlMuhaideb^*, Yasmeen AlNegheimish, Taif AlOmar, Reem AlSabti, Maha AlKathery, Ghala AlOlyyan

CMC-Computers, Materials & Continua, Vol.76, No.1, pp. 195-220, 2023, DOI:10.32604/cmc.2023.038368 - 08 June 2023

Abstract Healthcare organizations rely on patients’ feedback and experiences to evaluate their performance and services, thereby allowing such organizations to improve inadequate services and address any shortcomings. According to the literature, social networks and particularly Twitter are effective platforms for gathering public opinions. Moreover, recent studies have used natural language processing to measure sentiments in text segments collected from Twitter to capture public opinions about various sectors, including healthcare. The present study aimed to analyze Arabic Twitter-based patient experience sentiments and to introduce an Arabic patient experience corpus. The authors collected 12,400 tweets from Arabic patients… More >

Muhammad Saad¹, Maaz Bin Ahmad^1,*, Muhammad Asif², Muhammad Khalid Khan¹, Toqeer Mahmood³, Elsayed Tag Eldin^4,*, Hala Abdel Hameed^5,6

CMC-Computers, Materials & Continua, Vol.76, No.1, pp. 687-709, 2023, DOI:10.32604/cmc.2023.038335 - 08 June 2023

Abstract Pandemics have always been a nightmare for humanity, especially in developing countries. Forced lockdowns are considered one of the effective ways to deal with spreading such pandemics. Still, developing countries cannot afford such solutions because these may severely damage the country’s economy. Therefore, this study presents the proactive technological mechanisms for business organizations to run their standard business processes during pandemic-like situations smoothly. The novelty of this study is to provide a state-of-the-art solution to prevent pandemics using industrial internet of things (IIoT) and blockchain-enabled technologies. Compared to existing studies, the immutable and tamper-proof contact… More >

Amjed Al Fahoum^*, Ala’a Zyout, Hiam Alquran, Isam Abu-Qasmieh

CMC-Computers, Materials & Continua, Vol.76, No.1, pp. 1173-1193, 2023, DOI:10.32604/cmc.2023.038304 - 08 June 2023

Abstract Complex proteins are needed for many biological activities. Folding amino acid chains reveals their properties and functions. They support healthy tissue structure, physiology, and homeostasis. Precision medicine and treatments require quantitative protein identification and function. Despite technical advances and protein sequence data exploration, bioinformatics’ “basic structure” problem—the automatic deduction of a protein’s properties from its amino acid sequence—remains unsolved. Protein function inference from amino acid sequences is the main biological data challenge. This study analyzes whether raw sequencing can characterize biological facts. A massive corpus of protein sequences and the Globin-like superfamily’s related protein families… More >