Jing Geng^1,*, Huali Yang², Shengze Hu³

Intelligent Automation & Soft Computing, Vol.37, No.2, pp. 1311-1324, 2023, DOI:10.32604/iasc.2023.038481

Abstract Educational data mining based on student cognitive diagnosis analysis can provide an important decision basis for personalized learning tutoring of students, which has attracted extensive attention from scholars at home and abroad and has made a series of important research progress. To this end, we propose a noise-filtering enhanced deep cognitive diagnosis method to improve the fitting ability of traditional models and obtain students’ skill mastery status by mining the interaction between students and problems nonlinearly through neural networks. First, modeling complex interactions between students and problems with multidimensional features based on cognitive processing theory can enhance the interpretability of… More >

Hong Zhang^1,2,*, Gang Yang¹, Hailiang Yu¹, Zan Zheng¹

CMC-Computers, Materials & Continua, Vol.76, No.1, pp. 1047-1063, 2023, DOI:10.32604/cmc.2023.039274

Abstract To accurately predict traffic flow on the highways, this paper proposes a Convolutional Neural Network-Bi-directional Long Short-Term Memory-Attention Mechanism (CNN-BiLSTM-Attention) traffic flow prediction model based on Kalman-filtered data processing. Firstly, the original fluctuating data is processed by Kalman filtering, which can reduce the instability of short-term traffic flow prediction due to unexpected accidents. Then the local spatial features of the traffic data during different periods are extracted, dimensionality is reduced through a one-dimensional CNN, and the BiLSTM network is used to analyze the time series information. Finally, the Attention Mechanism assigns feature weights and performs Softmax regression. The experimental results… More >

Deepthi K. Oommen^*, J. Arunnehru

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

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 younger onset. The research used… More >

Shuja Ali¹, Ahmad Jalal¹, Mohammed Hamad Alatiyyah², Khaled Alnowaiser³, Jeongmin Park^4,*

CMC-Computers, Materials & Continua, Vol.76, No.1, pp. 1249-1265, 2023, DOI:10.32604/cmc.2023.038114

Abstract Unmanned aerial vehicles (UAVs) can be used to monitor traffic in a variety of settings, including security, traffic surveillance, and traffic control. Numerous academics have been drawn to this topic because of the challenges and the large variety of applications. This paper proposes a new and efficient vehicle detection and tracking system that is based on road extraction and identifying objects on it. It is inspired by existing detection systems that comprise stationary data collectors such as induction loops and stationary cameras that have a limited field of view and are not mobile. The goal of this study is to… More >

Ali Jaber Abdulhamed^1,*, Aws Al-Akam¹, Ahmed A. Abduljabbar², Mohammed H. Alkhafaji³

Energy Engineering, Vol.120, No.8, pp. 1729-1746, 2023, DOI:10.32604/ee.2023.029069

Abstract Thermoelectric generators (TEGs) are considered promising devices for waste heat recovery from various systems. The Seebeck effect can be utilized to generate power using the residual heat emitted by the filter dryer receiver (FDR) of an air conditioning (A/C) system, which would otherwise go to waste. The study aims to build a set of thermoelectric generators (TEG) to collect the waste heat of the FDR and generate low-power electricity. A novel electrical circuit with two transformers is designed and fabricated to produce a more stable voltage for operation and charging. The thermoelectric generator (TEGs) was installed on the FDR of… More >

Nisha Vasudevan^1,*, Vasudevan Venkatraman², A. Ramkumar¹, T. Muthukumar³, A. Sheela⁴, M. Vetrivel⁵, R. J. Vijaya Saraswathi⁶, F. T. Josh⁷

Energy Engineering, Vol.120, No.8, pp. 1747-1761, 2023, DOI:10.32604/ee.2023.027821

Abstract MigroGrid (MG) has emerged to resolve the growing demand for energy. But because of its inconsistent output, it can result in various power quality (PQ) issues. PQ is a problem that is becoming more and more important for the reliability of power systems that use renewable energy sources. Similarly, the employment of nonlinear loads will introduce harmonics into the system and, as a result, cause distortions in the current and voltage waveforms as well as low power quality issues in the supply system. Thus, this research focuses on power quality enhancement in the MG using hybrid shunt filters. However, the… More >

Shaochun Liu, Jiamin Hu, Haohua He, Junru Fu, Xu Jie, Dahu Zhou^*, Haihui Fu^*

Phyton-International Journal of Experimental Botany, Vol.92, No.7, pp. 2035-2049, 2023, DOI:10.32604/phyton.2023.028296

Abstract OsPLS4 encodes a β-ketoacyl carrier protein reductase (KAR). The role of OsPLS4 in rice sheath blight (Rhizoctonia solani) remains unclear. Our preliminary studies showed that premature leaf senescence mutants (pls4) were highly susceptive to sheath blight in the early stage of rice development. To explore the role of this gene in the development of rice sheath blight, the transcriptome profiles of the rice pls4 mutant and wild type were compared by RNA-seq. The results revealed 2,569 differentially expressed genes (DEGs). The down-regulated genes were significantly enriched in the defense response-related biological processes. These down-regulated genes included the chitinase genes and… More >

M.-F. Bacqué, I. Dumont, J. Maclure, P. Guex, L. Fasse, M. Derzelle

Psycho-Oncologie, Vol.16, No.2, pp. 219-222, 2022, DOI:10.3166/pson-2022-0200

Abstract This article has no abstract. More >

J. Phan, V. Laurence, P. Marec-Berard, C. Cordero, C. Riberon, C. Flahault

Psycho-Oncologie, Vol.16, No.2, pp. 243-252, 2022, DOI:10.3166/pson-2022-0197

Abstract Objectif : Les adolescents et jeunes adultes (AJA) atteints de cancer faisant face à la perte d’un autre AJA malade peuvent être confrontés à une « triple tâche » : le processus d’adolescence, l’ajustement psychologique au cancer et la mort d’un pair malade. L’objectif de l’étude a été d’explorer les processus sous-jacents à la perte d’un pair malade chez les AJA atteints de cancer.
Matériel et méthodes : Un entretien unique a été soumis à une Analyse phénoménologique interprétative (IPA), conçu pour comprendre le système de significations attaché à un phénomène subjectif et intime tel que le deuil.
Résultats :… More >

M. Laget, L. Fasse, B. Fresneau, E. Ricadat, S. Rivollet

Psycho-Oncologie, Vol.16, No.2, pp. 267-272, 2022, DOI:10.3166/pson-2022-0190

Abstract Dans le cadre du dispositif de suivi médical destiné aux adultes guéris d’un cancer pédiatrique à l’Institut Gustave-Roussy (Villejuif, France), un entretien psychologique est proposé. Cet article s’appuie sur 198 entretiens auprès de patients ayant entre 18 et 67 ans, diagnostiqués entre 0 et 24 ans. Ces rencontres donnent à entendre la subjectivité du vécu du cancer et de la guérison, révélant les traces de cette expérience dans l’après-coup. Les enjeux de l’activité narrative amorcée dans le cadre de cette consultation, et pouvant se poursuivre au-delà, sont abordés dans une perspective métapsychologique. More >