Shu Fang¹, Lei Huang¹, Yi Wan², Weize Sun^{1, *}, Jingxin Xu³

CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 541-555, 2020, DOI:10.32604/cmc.2020.010066

Abstract With the development of science and technology, the status of the water environment has received more and more attention. In this paper, we propose a deep learning model, named a Joint Auto-Encoder network, to solve the problem of outlier detection in water supply data. The Joint Auto-Encoder network first expands the size of training data and extracts the useful features from the input data, and then reconstructs the input data effectively into an output. The outliers are detected based on the network’s reconstruction errors, with a larger reconstruction error indicating a higher rate to be an outlier. For water supply… More >

Chao Guo¹, Cheng Gong², Juan Guo³, Zhanzhen Wei^{1, *}, Yanyan Han¹, Sher Zaman Khan⁴

CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 527-540, 2020, DOI:10.32604/cmc.2020.09788

Abstract Under the background of the rapid development of ground mobile communication, the advantages of high coverage, survivability, and flexibility of satellite communication provide air support to the construction of space information network. According to the requirements of the future space information communication, a software-defined Space-Air-Ground Integrated network architecture was proposed. It consisted of layered structure satellite backbone network, deep space communication network, the stratosphere communication network and the ground network. The SpaceAir-Ground Integrated network was supported by the satellite backbone network. It provided data relay for the missions such as deep space exploration and controlled the deep-space spacecraft when needed.… More >

Weibo Yang¹, Weidong Liu^{2, *}, Jinming Liu³, Mingyang Zhang⁴

CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 515-525, 2020, DOI:10.32604/cmc.2020.09801

Abstract The Convolutional Neural Network (CNN) is a widely used deep neural network. Compared with the shallow neural network, the CNN network has better performance and faster computing in some image recognition tasks. It can effectively avoid the problem that network training falls into local extremes. At present, CNN has been applied in many different fields, including fault diagnosis, and it has improved the level and efficiency of fault diagnosis. In this paper, a two-streams convolutional neural network (TCNN) model is proposed. Based on the short-time Fourier transform (STFT) spectral and Mel Frequency Cepstrum Coefficient (MFCC) input characteristics of two-streams acoustic… More >

Junxiang Wang^{1, *}, Lin Huang¹, Ying Zhang¹, Yonghong Zhu¹, Jiangqun Ni², Yunqing Shi³

CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 325-344, 2020, DOI:10.32604/cmc.2020.09784

Abstract To measure the security for hot searched reversible data hiding (RDH) technique, especially for the common-used histogram-shifting based RDH (denoted as HS-RDH), several steganalysis schemes are designed to detect whether some secret data has been hidden in a normal-looking image. However, conventional steganalysis schemes focused on the previous RDH algorithms, i.e., some early spatial/pixel domain-based histogram-shifting (HS) schemes, which might cause great changes in statistical characteristics and thus be easy to be detected. For recent improved methods, such as some adaptive prediction error (PE) based embedding schemes, those conventional schemes might be invalid, since those adaptive embedding mechanism would effectively… More >

Yan Liu¹, Wenyuan Fang¹, Qiang Wei^{1, *}, Yuan Zhao¹, Liang Wang²

CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 273-295, 2020, DOI:10.32604/cmc.2020.09659

Abstract Code defects can lead to software vulnerability and even produce vulnerability risks. Existing research shows that the code detection technology with text analysis can judge whether object-oriented code files are defective to some extent. However, these detection techniques are mainly based on text features and have weak detection capabilities across programs. Compared with the uncertainty of the code and text caused by the developer’s personalization, the programming language has a stricter logical specification, which reflects the rules and requirements of the language itself and the developer’s potential way of thinking. This article replaces text analysis with programming logic modeling, breaks… More >

Jae-Hyun Ro¹, Won-Seok Lee¹, Min-Goo Kang², Dae-Ki Hong³, Hyoung-Kyu Song^{1, *}

CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 181-191, 2020, DOI:10.32604/cmc.2020.09998

Abstract In this paper, the supervised Deep Neural Network (DNN) based signal detection is analyzed for combating with nonlinear distortions efficiently and improving error performances in clipping based Orthogonal Frequency Division Multiplexing (OFDM) ssystem. One of the main disadvantages for the OFDM is the high Peak to Average Power Ratio (PAPR). The clipping is a simple method for the PAPR reduction. However, an effect of the clipping is nonlinear distortion, and estimations for transmitting symbols are difficult despite a Maximum Likelihood (ML) detection at the receiver. The DNN based online signal detection uses the offline learning model where all weights and… More >

Kue-Hong Chen^{1, *}, Cheng-Tsung Chen^{2, 3}

CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 145-160, 2020, DOI:10.32604/cmc.2020.08864

Abstract In this study, we applied a defined auxiliary problem in a novel error estimation technique to estimate the numerical error in the method of fundamental solutions (MFS) for solving the Helmholtz equation. The defined auxiliary problem is substituted for the real problem, and its analytical solution is generated using the complementary solution set of the governing equation. By solving the auxiliary problem and comparing the solution with the quasianalytical solution, an error curve of the MFS versus the source location parameters can be obtained. Thus, the optimal location parameter can be identified. The convergent numerical solution can be obtained and… More >

Shahid Rahman¹, Fahad Masood², Wajid Ullah Khan², Niamat Ullah¹, Fazal Qudus Khan³, Georgios Tsaramirsis³, Sadeeq Jan^{4, *}, Majid Ashraf⁵

CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 31-61, 2020, DOI:10.32604/cmc.2020.09186

Abstract Steganography aims to hide the messages from unauthorized persons for various purposes, e.g., military correspondence, financial transaction data. Securing the data during transmission is of utmost importance these days. The confidentiality, integrity, and availability of the data are at risk because of the emerging technologies and complexity in software applications, and therefore, there is a need to secure such systems and data. There are various methodologies to deal with security issues when utilizing an open system like the Internet. This research proposes a new technique in steganography within RGB shading space to achieve enhanced security compared with existing systems. We… More >

Marco Astengo^1,2*, Caroline Berntsson^3*, Åse A. Johnsson^3,4, Peter Eriksson^1,2, Mikael Dellborg^1,2

Congenital Heart Disease, Vol.12, No.2, pp. 174-180, 2017, DOI:10.1111/chd.12424

Abstract Objective: Coarctation of the aorta (CoA) is a common condition. Adult patients with newly diagnosed CoA and patients with recurring or residual CoA require evaluation of the severity of aortic obstruction. Cardiac catheterization is considered the gold standard for the evaluation of hemodynamically significant CoA. The European Society of Cardiology (ESC) Guidelines for the management of grown-up congenital heart disease (GUCH) include noninvasive criteria for identifying significant CoA. Our aim was to investigate the ability of the Class I and Class IIa ESC recommendations to identify significant CoA at cardiac catheterization.
Design: Sixty-six adult patients with native or recurrent CoA… More >

Shyam Sathanandam¹, Pooja Kashyap¹, David Zurakowski², Lindsey Bird¹, Vera McGhee³, Jeffrey Towbin¹, Benjamin Rush Waller III¹

Congenital Heart Disease, Vol.12, No.2, pp. 181-187, 2017, DOI:10.1111/chd.12423

Abstract Objectives: The primary aim of this study was to compare thermodilution (TD) cardiac index (TDCi) measured by injecting cold saline (C-TDCi) to saline at room temperature (R-TDCi). The secondary aim was to assess the change in body temperature with cold saline injections in children.
Design: This is a prospective, case control study.
Setting: Cardiac catheterization lab at Le Bonheur Children’s Hospital, Memphis, Tennessee.
Patients: Eighty-six children ≤18 years of age that underwent cardiac catheterization between April 2013 and April 2015, excluding patients with admixing lesions, on inotropic support and with ejection fraction < 30%.
Interventions: A TD catheter in the… More >