Wei Wu^*, Yuan Zhang, Yunpeng Li, Chuanyang Li, Yan Hao

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 537-555, 2024, DOI:10.32604/cmes.2024.049174

Abstract Fusing hand-based features in multi-modal biometric recognition enhances anti-spoofing capabilities. Additionally, it leverages inter-modal correlation to enhance recognition performance. Concurrently, the robustness and recognition performance of the system can be enhanced through judiciously leveraging the correlation among multimodal features. Nevertheless, two issues persist in multi-modal feature fusion recognition: Firstly, the enhancement of recognition performance in fusion recognition has not comprehensively considered the inter-modality correlations among distinct modalities. Secondly, during modal fusion, improper weight selection diminishes the salience of crucial modal features, thereby diminishing the overall recognition performance. To address these two issues, we introduce an enhanced DenseNet multimodal recognition network… More > Graphic Abstract

Hasan J. Alyamani^*

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 1129-1142, 2024, DOI:10.32604/cmes.2024.047756

Abstract The evaluation of disease severity through endoscopy is pivotal in managing patients with ulcerative colitis, a condition with significant clinical implications. However, endoscopic assessment is susceptible to inherent variations, both within and between observers, compromising the reliability of individual evaluations. This study addresses this challenge by harnessing deep learning to develop a robust model capable of discerning discrete levels of endoscopic disease severity. To initiate this endeavor, a multi-faceted approach is embarked upon. The dataset is meticulously preprocessed, enhancing the quality and discriminative features of the images through contrast limited adaptive histogram equalization (CLAHE). A diverse array of data augmentation… More > Graphic Abstract

Wenjun Zhou^1,2, Mingzhi Yang¹, Qian Peng², Yong Peng^1,*, Kui Wang¹, Qiang Xiao¹

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 735-755, 2024, DOI:10.32604/cmes.2024.047258

Abstract The widespread adoption of aluminum alloy electric buses, known for their energy efficiency and eco-friendliness, faces a challenge due to the aluminum frame’s susceptibility to deformation compared to steel. This issue is further exacerbated by the stringent requirements imposed by the flammability and explosiveness of batteries, necessitating robust frame protection. Our study aims to optimize the connectors of aluminum alloy bus frames, emphasizing durability, energy efficiency, and safety. This research delves into Multi-Objective Coordinated Optimization (MCO) techniques for lightweight design in aluminum alloy bus body connectors. Our goal is to enhance lightweighting, reinforce energy absorption, and improve deformation resistance in… More >

Jiaqi Wu¹, Li Zhuo^1,*, Jianliang Pei¹, Yao Li², Hongqiang Xie¹, Jiaming Wu¹, Huaizhong Liu¹

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 621-645, 2024, DOI:10.32604/cmes.2024.046398

Abstract The surrounding geological conditions and supporting structures of underground engineering are often updated during construction, and these updates require repeated numerical modeling. To improve the numerical modeling efficiency of underground engineering, a modularized and parametric modeling cloud server is developed by using Python codes. The basic framework of the cloud server is as follows: input the modeling parameters into the web platform, implement Rhino software and FLAC^3D software to model and run simulations in the cloud server, and return the simulation results to the web platform. The modeling program can automatically generate instructions that can run the modeling process in… More >

ÇAĞLA GÜL GÜLDİKEN, LEVENT AKYALÇIN, HASAN FERDİ GERÇEL^*

Journal of Polymer Materials, Vol.36, No.4, pp. 337-349, 2019, DOI:10.32381/JPM.2019.36.04.4

Abstract In the present study, polybenzimidazole (PBI) polymer which has a great importance in polymer electrolyte membrane (PEM) research was synthesized via the solution polycondensation method, under various synthesis conditions to put forward the effect of the synthesis parameters on the properties of the synthesized polymer and consequently to the quality of the prepared polymer electrolyte membrane. The synthesized polymers were characterized in terms of their chemical structure, thermal degradation behaviour, and molecular weight by Fourier transform infrared spectroscopy (FTIR), nuclear magnetic resonance spectroscopy (¹ H NMR), thermogravimetric analysis (TGA). The Mechanical properties, acid-doping level capacity, proton conductivity, and fuel cell… More >

Yuting Xu^1,*, Deqing Zhang¹, Huaibei Guo², Mengyue Wang¹

Journal on Artificial Intelligence, Vol.6, pp. 53-69, 2024, DOI:10.32604/jai.2024.049083

Abstract In multi-label learning, the label-specific features learning framework can effectively solve the dimensional catastrophe problem brought by high-dimensional data. The classification performance and robustness of the model are effectively improved. Most existing label-specific features learning utilizes the cosine similarity method to measure label correlation. It is well known that the correlation between labels is asymmetric. However, existing label-specific features learning only considers the private features of labels in classification and does not take into account the common features of labels. Based on this, this paper proposes a Causality-driven Common and Label-specific Features Learning, named CCSF algorithm. Firstly, the causal learning… More >

Sureka Sivavelu, Venkatesh Palanisamy^*

CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 3469-3487, 2024, DOI:10.32604/cmc.2024.047407

Abstract The development of defect prediction plays a significant role in improving software quality. Such predictions are used to identify defective modules before the testing and to minimize the time and cost. The software with defects negatively impacts operational costs and finally affects customer satisfaction. Numerous approaches exist to predict software defects. However, the timely and accurate software bugs are the major challenging issues. To improve the timely and accurate software defect prediction, a novel technique called Nonparametric Statistical feature scaled QuAdratic regressive convolution Deep nEural Network (SQADEN) is introduced. The proposed SQADEN technique mainly includes two major processes namely metric… More >

K. B. Ajeyprasaath, P. Vetrivelan^*

CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 3195-3213, 2024, DOI:10.32604/cmc.2023.046911

Abstract Video streaming applications have grown considerably in recent years. As a result, this becomes one of the most significant contributors to global internet traffic. According to recent studies, the telecommunications industry loses millions of dollars due to poor video Quality of Experience (QoE) for users. Among the standard proposals for standardizing the quality of video streaming over internet service providers (ISPs) is the Mean Opinion Score (MOS). However, the accurate finding of QoE by MOS is subjective and laborious, and it varies depending on the user. A fully automated data analytics framework is required to reduce the inter-operator variability characteristic… More >

Bin Xiao^*

Frontiers in Heat and Mass Transfer, Vol.22, No.1, pp. 35-48, 2024, DOI:10.32604/fhmt.2024.048039

Abstract Experiments were conducted in this study to examine the thermal performance of a thermosyphon, made from Inconel alloy 625, could recover waste heat from automobile exhaust using a limited amount of fluid. The thermosyphon has an outer diameter of 27 mm, a thickness of 2.6 mm, and an overall length of 483 mm. The study involved directing exhaust gas onto the evaporator. This length includes a 180-mm evaporator, a 70-mm adiabatic section, a 223-mm condenser, and a 97-mm finned exchanger. The study examined the thermal performance of the thermosyphon under exhaust flow rates ranging from 0–10 g/sec and temperatures varying… More >

Alessandro Araldi¹, David Emsellem², Giovanni Fusco¹, Andrea Tettamanzi³, Denis Overal²

Revue Internationale de Géomatique, Vol.31, No.2, pp. 265-302, 2022, DOI:10.3166/RIG.31.265-302© 2022

Abstract The identification and description of building typologies play a fundamental role in the understanding of the overall built-up form. A growing body of research is developing and implementing sophisticated, computer-aided protocols for the identification of building typologies. This paper shares the same goal. An innovative data-driven procedure for the unsupervised identification and description of building types and organization is here presented. After a specific pre-processing procedure, we develop an unsupervised clustering combining a new algorithm of Naive Bayes inference and hierarchical ascendant approaches relying on six morphometric features of buildings. This protocol allows us to identify groups of buildings sharing… More >