Håvard Bjerkeseth Solvin^1,2,5,*, Simone Goa Diab^1,4, Ole Jakob Elle^2,3, Henrik Holmstrøm^1,4, Henrik Brun^2,4,*

Congenital Heart Disease, Vol.18, No.5, pp. 551-559, 2023, DOI:10.32604/chd.2023.031537

Abstract Background: The management of suspected critical congenital heart defects (CCHD) relies on timely echocardiographic diagnosis. The availability of experienced echocardiographers is limited or even non-existent in many hospitals with obstetric units. This study evaluates remote-mentored echocardiography performed by physicians without experience in imaging of congenital heart defects (CHD). Methods: The setup included a pediatric cardiologist in a separate room, guiding a physician without experience in echocardiographic imaging of CHD in the examination of a symptomatic newborn. This remote-mentoring pair was blinded to the diagnosis of the newborn and presented with a simplified patient history. The echocardiographic images were streamed to… More > Graphic Abstract

Sikandar Khan¹, Khalid Saeed¹, Muhammad Faran Majeed^2,*, Salman A. AlQahtani³, Khursheed Aurangzeb³, Muhammad Shahid Anwar^4,*

CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 1303-1323, 2023, DOI:10.32604/cmc.2023.039697

Abstract Delay Tolerant Networks (DTNs) have the major problem of message delay in the network due to a lack of end-to-end connectivity between the nodes, especially when the nodes are mobile. The nodes in DTNs have limited buffer storage for storing delayed messages. This instantaneous sharing of data creates a low buffer/shortage problem. Consequently, buffer congestion would occur and there would be no more space available in the buffer for the upcoming messages. To address this problem a buffer management policy is proposed named “A Novel and Proficient Buffer Management Technique (NPBMT) for the Internet of Vehicle-Based DTNs”. NPBMT combines appropriate-size… More >

Jayaraj Thankappan¹, Delphin Raj Kesari Mary², Dong Jin Yoon³, Soo-Hyun Park^4,*

CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 1053-1079, 2023, DOI:10.32604/cmc.2023.038437

Abstract Flooding is a hazardous natural calamity that causes significant damage to lives and infrastructure in the real world. Therefore, timely and accurate decision-making is essential for mitigating flood-related damages. The traditional flood prediction techniques often encounter challenges in accuracy, timeliness, complexity in handling dynamic flood patterns and leading to substandard flood management strategies. To address these challenges, there is a need for advanced machine learning models that can effectively analyze Internet of Things (IoT)-generated flood data and provide timely and accurate flood predictions. This paper proposes a novel approach-the Adaptive Momentum and Backpropagation (AM-BP) algorithm-for flood prediction and management in… More >

Muhammad Fezan Afzal¹, Imran Khan¹, Javed Rashid^1,2,3, Mubbashar Saddique^4,*, Heba G. Mohamed⁵

CMC-Computers, Materials & Continua, Vol.76, No.3, pp. 3653-3670, 2023, DOI:10.32604/cmc.2023.041627

Abstract Software Product Line (SPL) is a group of software-intensive systems that share common and variable resources for developing a particular system. The feature model is a tree-type structure used to manage SPL’s common and variable features with their different relations and problem of Crosstree Constraints (CTC). CTC problems exist in groups of common and variable features among the sub-tree of feature models more diverse in Internet of Things (IoT) devices because different Internet devices and protocols are communicated. Therefore, managing the CTC problem to achieve valid product configuration in IoT-based SPL is more complex, time-consuming, and hard. However, the CTC… More >

Fang Yu¹, Wenbin Bi², Ning Cao^3,*, Jun Luo⁴, Diantang An⁵, Liqiang Ding⁴, Russell Higgs⁶

CMC-Computers, Materials & Continua, Vol.76, No.3, pp. 3921-3931, 2023, DOI:10.32604/cmc.2023.028330

Abstract The purpose of introducing blockchain into electronic archives sharing and utilization is to break the information barrier between electronic archives sharing departments by relying on technologies such as smart contract and asymmetric encryption. Aiming at the problem of dynamic permission management in common access control methods, a new access control method based on smart contract under blockchain is proposed, which improves the intelligence level under blockchain technology. Firstly, the Internet attribute access control model based on smart contract is established. For the dynamic access of heterogeneous devices, the management contract, permission judgment contract and access control contract are designed; Secondly,… More >

Haifeng Lin^1,2, Xiangfeng Liu², Chen Chen², Zhibo Liu², Dexin Zhao³, Yiwen Zhang⁴, Weizhuang Li⁴, Mingsheng Cao^5,6,*

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.1, pp. 939-956, 2024, DOI:10.32604/cmes.2023.028656

Abstract Identifying a device and detecting a change in its position is critical for secure devices management in the Internet of Things (IoT). In this paper, a device management system is proposed to track the devices by using audio-based location distinction techniques. In the proposed scheme, traditional cryptographic techniques, such as symmetric encryption algorithm, RSA-based signcryption scheme, and audio-based secure transmission, are utilized to provide authentication, non-repudiation, and confidentiality in the information interaction of the management system. Moreover, an audio-based location distinction method is designed to detect the position change of the devices. Specifically, the audio frequency response (AFR) of several… More >

Ana María Peco Chacón, Isaac Segovia Ramírez, Fausto Pedro García Márquez^*

Intelligent Automation & Soft Computing, Vol.37, No.3, pp. 2595-2608, 2023, DOI:10.32604/iasc.2023.037277

Abstract Maintenance operations have a critical influence on power generation by wind turbines (WT). Advanced algorithms must analyze large volume of data from condition monitoring systems (CMS) to determine the actual working conditions and avoid false alarms. This paper proposes different support vector machine (SVM) algorithms for the prediction and detection of false alarms. K-Fold cross-validation (CV) is applied to evaluate the classification reliability of these algorithms. Supervisory Control and Data Acquisition (SCADA) data from an operating WT are applied to test the proposed approach. The results from the quadratic SVM showed an accuracy rate of 98.6%. Misclassifications from the confusion… More >

Lucio Nobile^*

Structural Durability & Health Monitoring, Vol.17, No.5, pp. 353-368, 2023, DOI:10.32604/sdhm.2023.028247

Abstract The frequent occurrence of seismic events in Italy poses a strategic problem that involves either the culture of preservation of historical heritage or the civil protection action aimed to reduce the risk to people and goods (buildings, bridges, dams, slopes, etc.). Most of the Italian architectural heritage is vulnerable to earthquakes, identifying the vulnerability as the inherent predisposition of the masonry building to suffer damage and collapse during an earthquake. In fact, the structural concept prevailing in these ancient masonry buildings is aimed at ensuring prevalent resistance to vertical gravity loads. Rarely do these ancient masonry structures offer relevant resistance… More >

Yongsoo Lee, Yeeun Lee, Eungyu Lee, Taejin Lee^*

CMC-Computers, Materials & Continua, Vol.76, No.2, pp. 1701-1719, 2023, DOI:10.32604/cmc.2023.040235

Abstract Cybersecurity increasingly relies on machine learning (ML) models to respond to and detect attacks. However, the rapidly changing data environment makes model life-cycle management after deployment essential. Real-time detection of drift signals from various threats is fundamental for effectively managing deployed models. However, detecting drift in unsupervised environments can be challenging. This study introduces a novel approach leveraging Shapley additive explanations (SHAP), a widely recognized explainability technique in ML, to address drift detection in unsupervised settings. The proposed method incorporates a range of plots and statistical techniques to enhance drift detection reliability and introduces a drift suspicion metric that considers… More >

Ilyоs Abdullaev¹, Natalia Prodanova², K. Aruna Bhaskar³, E. Laxmi Lydia⁴, Seifedine Kadry^5,6,7, Jungeun Kim^8,*

CMC-Computers, Materials & Continua, Vol.76, No.2, pp. 1463-1477, 2023, DOI:10.32604/cmc.2023.038417

Abstract Recently, computation offloading has become an effective method for overcoming the constraint of a mobile device (MD) using computation-intensive mobile and offloading delay-sensitive application tasks to the remote cloud-based data center. Smart city benefitted from offloading to edge point. Consider a mobile edge computing (MEC) network in multiple regions. They comprise N MDs and many access points, in which every MD has M independent real-time tasks. This study designs a new Task Offloading and Resource Allocation in IoT-based MEC using Deep Learning with Seagull Optimization (TORA-DLSGO) algorithm. The proposed TORA-DLSGO technique addresses the resource management issue in the MEC server,… More >