L. Gornet¹, S. Marguet², G. Marckmann³

CMC-Computers, Materials & Continua, Vol.4, No.2, pp. 63-74, 2006, DOI:10.3970/cmc.2006.004.063

Abstract The purpose of the present study is to determine the components of the effective elasticity tensor and the failure properties of Nomex^® honeycomb cores. In order to carry out this study, the NidaCore software, a program dedicated to Nomex®Cores predictions, has been developed using the Finite Element tool Cast3M-CEA. This software is based on periodic homogenization techniques and on the modelling of structural instability phenomena. The homogenization of the periodic microstructure is realized thanks to a strain energy approach. It assumes the mechanical equivalence between the microstructures of a RVE and a similar homogeneous macroscopic volume.… More >

Dongsheng Li^1,2, Ghazal Saheli¹, Moe Khaleel², Hamid Garmestani¹

CMC-Computers, Materials & Continua, Vol.4, No.1, pp. 31-42, 2006, DOI:10.3970/cmc.2006.004.031

Abstract A multiscale model based on statistical continuum mechanics is proposed to predict the mechanical and electrical properties of heterogeneous porous media. This model is applied within the framework of microstructure sensitive design (MSD) to guide the design of the microstructure in porous lanthanum strontium manganite (LSM) fuel cell electrode. To satisfy the property requirement and compatibility, porosity and its distribution can be adjusted under the guidance of MSD to achieve optimized microstructure. More >

Zhong Huang¹, Jian Su², Guangjun Wen¹, Wenxian Zheng³, Chu Chu¹, Yijun Zhang^4,*, Yibo Zhang⁵

CMC-Computers, Materials & Continua, Vol.61, No.1, pp. 399-408, 2019, DOI:10.32604/cmc.2019.05876

Abstract A priori knowledge of the number of tags is crucial for anti-collision protocols in slotted UHF RFID systems. The number of tags is used to decide optimal frame length in dynamic frame slotted ALOHA (DFSA) and to adjust access probability in random access protocols. Conventional researches estimate the number of tags in MAC layer based on statistics of empty slots, collided slots and successful slots. Usually, a collision detection algorithm is employed to determine types of time slots. Only three types are distinguished because of lack of ability to detect the number of tags in More >

Jialing Liu¹, Jingbing Li^1,2,*, Yenwei Chen³, Xiangxi Zou¹, Jieren Cheng^1,2, Yanlin Liu¹, Uzair Aslam Bhatti^1,2

CMC-Computers, Materials & Continua, Vol.61, No.1, pp. 363-378, 2019, DOI:10.32604/cmc.2019.06037

Abstract Remote medical diagnosis can be realized by using the Internet, but when transmitting medical images of patients through the Internet, personal information of patients may be leaked. Aim at the security of medical information system and the protection of medical images, a novel robust zero-watermarking based on SIFT-DCT (Scale Invariant Feature Transform-Discrete Cosine Transform) for medical images in the encrypted domain is proposed. Firstly, the original medical image is encrypted in transform domain based on Logistic chaotic sequence to enhance the concealment of original medical images. Then, the SIFT-DCT is used to extract the feature More >

Ling Tan^1,*, Chong Li², Jingming Xia², Jun Cao³

CMC-Computers, Materials & Continua, Vol.61, No.1, pp. 275-288, 2019, DOI:10.32604/cmc.2019.03735

Abstract Due to the widespread use of the Internet, customer information is vulnerable to computer systems attack, which brings urgent need for the intrusion detection technology. Recently, network intrusion detection has been one of the most important technologies in network security detection. The accuracy of network intrusion detection has reached higher accuracy so far. However, these methods have very low efficiency in network intrusion detection, even the most popular SOM neural network method. In this paper, an efficient and fast network intrusion detection method was proposed. Firstly, the fundamental of the two different methods are introduced More >

Yueping Wang^1,*, Xuan Zhang², Yixuan Zhang³

CMC-Computers, Materials & Continua, Vol.61, No.1, pp. 171-184, 2019, DOI:10.32604/cmc.2019.06204

Abstract Full-duplex (FD) has been recognized as a promising technology for future 5G networks to improve the spectrum efficiency. However, the biggest practical impediments of realizing full-duplex communications are the presence of self-interference, especially in complex cellular networks. With the current development of self-interference cancellation techniques, full-duplex has been considered to be more suitable for device-to-device (D2D) and small cell communications which have small transmission range and low transmit power. In this paper, we consider the full-duplex D2D communications in multi-tier wireless networks and present an analytical model which jointly considers mode selection, resource allocation, and More >

Xinfang Wang¹, Lianqing Hong², Xi Wu³, Jia He³, Ting Wang^3,4,*, Hongbo Li⁵, Shaoling Liu⁶

CMC-Computers, Materials & Continua, Vol.61, No.1, pp. 141-154, 2019, DOI:10.32604/cmc.2019.06030

Abstract An ultrasonic nomogram was developed for preoperative prediction of Castleman disease (CD) pathological type (hyaline vascular (HV) or plasma cell (PC) variant) to improve the understanding and diagnostic accuracy of ultrasound for this disease. Fifty cases of CD confirmed by pathology were gathered from January 2012 to October 2018 from three hospitals. A grayscale ultrasound image of each patient was collected and processed. First, the region of interest of each gray ultrasound image was manually segmented using a process that was guided and calibrated by radiologists who have been engaged in imaging diagnosis for more… More >

Yang Yu¹, Zeyu Xiong^1,*, Yueshan Xiong¹, Weizi Li²

CMC-Computers, Materials & Continua, Vol.61, No.1, pp. 103-118, 2019, DOI:10.32604/cmc.2019.05154

Abstract Logistic regression is often used to solve linear binary classification problems such as machine vision, speech recognition, and handwriting recognition. However, it usually fails to solve certain nonlinear multi-classification problem, such as problem with non-equilibrium samples. Many scholars have proposed some methods, such as neural network, least square support vector machine, AdaBoost meta-algorithm, etc. These methods essentially belong to machine learning categories. In this work, based on the probability theory and statistical principle, we propose an improved logistic regression algorithm based on kernel density estimation for solving nonlinear multi-classification. We have compared our approach with More >

Somayeh Hessam¹, Shaghayegh Vahdat¹, Irvan Masoudi Asl^2,*, Mahnaz Kazemipoor³, Atefeh Aghaei⁴, Shahaboddin Shamshirband,^5,6,*, Timon Rabczuk⁷

CMC-Computers, Materials & Continua, Vol.61, No.1, pp. 11-26, 2019, DOI:10.32604/cmc.2019.06472

Abstract In recent years, Parkinson's Disease (PD) as a progressive syndrome of the nervous system has become highly prevalent worldwide. In this study, a novel hybrid technique established by integrating a Multi-layer Perceptron Neural Network (MLP) with the Biogeography-based Optimization (BBO) to classify PD based on a series of biomedical voice measurements. BBO is employed to determine the optimal MLP parameters and boost prediction accuracy. The inputs comprised of 22 biomedical voice measurements. The proposed approach detects two PD statuses: 0-disease status and 1- good control status. The performance of proposed methods compared with PSO, GA, More >

Yue Zhao¹, Jianjian Yue¹, Wei Song^1,*, Xiaona Xu¹, Xiali Li¹, Licheng Wu¹, Qiang Ji²

CMC-Computers, Materials & Continua, Vol.60, No.3, pp. 1223-1235, 2019, DOI:10.32604/cmc.2019.05636

Abstract Tibetan language has very limited resource for conventional automatic speech recognition so far. It lacks of enough data, sub-word unit, lexicons and word inventories for some dialects. And speech content recognition and dialect classification have been treated as two independent tasks and modeled respectively in most prior works. But the two tasks are highly correlated. In this paper, we present a multi-task WaveNet model to perform simultaneous Tibetan multi-dialect speech recognition and dialect identification. It avoids processing the pronunciation dictionary and word segmentation for new dialects, while, in the meantime, allows training speech recognition and More >