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  • Open Access

    ARTICLE

    An Intelligent Incremental Filtering Feature Selection and Clustering Algorithm for Effective Classification

    U. Kanimozhi, D. Manjula

    Intelligent Automation & Soft Computing, Vol.24, No.4, pp. 701-709, 2018, DOI:10.1080/10798587.2017.1307626

    Abstract We are witnessing the era of big data computing where computing the resources is becoming the main bottleneck to deal with those large datasets. In the case of high-dimensional data where each view of data is of high dimensionality, feature selection is necessary for further improving the clustering and classification results. In this paper, we propose a new feature selection method, Incremental Filtering Feature Selection (IF2S) algorithm, and a new clustering algorithm, Temporal Interval based Fuzzy Minimal Clustering (TIFMC) algorithm that employs the Fuzzy Rough Set for selecting optimal subset of features and for effective More >

  • Open Access

    ARTICLE

    Hyperspectral Reflectance Imaging for Detecting Typical Defects of Durum Kernel Surface

    Feng-Nong Chena,b#, Pu-Lan Chenc#, Kai Fana, Fang Chengd

    Intelligent Automation & Soft Computing, Vol.24, No.2, pp. 351-358, 2018, DOI:10.1080/10798587.2017.1293927

    Abstract In recent years, foodstuff quality has triggered tremendous interest and attention in our society as a series of food safety problems. The hyperspectral imaging techniques have been widely applied for foodstuff quality. In this study, we were undertaken to explore the possibility of unsound kernel detecting (Triticum durum Desf), which were defined as black germ kernels, moldy kernels and broken kernels, by selecting the best band in hyperspectral imaging system. The system possessed a wavelength in the range of 400 to 1,000  nm with neighboring bands 2.73  nm apart, acquiring images of bulk wheat samples… More >

  • Open Access

    ARTICLE

    An Improved Lung Sound De-noising Method by Wavelet Packet Transform with Pso-Based Threshold Selection

    Qing-Hua Hea, Bin Yub, Xin Honga, Bo Lva, Tao Liub, Jian Ranb, Yu-Tian Bia

    Intelligent Automation & Soft Computing, Vol.24, No.2, pp. 223-230, 2018, DOI:10.1080/10798587.2016.1261957

    Abstract Lung abnormalities and respiratory diseases increase with the development of urban life. Lung sound analysis provides vital information of the present condition of the pulmonary. But lung sounds are easily interfered by noises in the transmission and record process, then it cannot be used for diagnosis of diseases. So the noised sound should be processed to reduce noises and to enhance the quality of signals received. On the basis of analyzing wavelet packet transform theory and the characteristics of traditional wavelet threshold de-noising method, we proposed a modified threshold selection method based on Particle Swarm More >

  • Open Access

    ARTICLE

    A Z-Number Valued Regression Model and Its Application

    Lala M. Zeinalovaa, O. H. Huseynovb, P. Sharghic

    Intelligent Automation & Soft Computing, Vol.24, No.1, pp. 187-192, 2018, DOI:10.1080/10798587.2017.1327551

    Abstract Regression analysis is widely used for modeling of real-world processes in various fields. It should be noted that information relevant to real-world processes is characterized by imprecision and partial reliability. This involves combination of fuzzy and probabilistic uncertainties. Prof.. L. Zadeh introduced the concept of a Z-number as a formal construct for dealing with such information. The present stateof-the-art of regression analysis under Z-number valued information is very scarce. In this paper we consider a Z-number valued multiple regression analysis and its application to a real-world decisionmaking problem. The obtained results show applicability of the More >

  • Open Access

    ARTICLE

    Seed Selection for Data Offloading Based on Social and Interest Graphs

    Ying Li1, Jianbo Li1,*, Jianwei Chen1, Minchao Lu1, Caoyuan Li2,3

    CMC-Computers, Materials & Continua, Vol.57, No.3, pp. 571-587, 2018, DOI:10.32604/cmc.2018.02851

    Abstract The explosive growth of mobile data demand is becoming an increasing burden on current cellular network. To address this issue, we propose a solution of opportunistic data offloading for alleviating overloaded cellular traffic. The principle behind it is to select a few important users as seeds for data sharing. The three critical steps are detailed as follows. We first explore individual interests of users by the construction of user profiles, on which an interest graph is built by Gaussian graphical modeling. We then apply the extreme value theory to threshold the encounter duration of user More >

  • Open Access

    ARTICLE

    Band Selection Method of Absorption Peak Perturbance for the FTIR/ATR Spectrum Analysis

    Jun Xie1, Chong Wang1, Jiaxiang Cai2, Fuhong Cai1,*

    CMC-Computers, Materials & Continua, Vol.57, No.2, pp. 261-268, 2018, DOI:10.32604/cmc.2018.03669

    Abstract The rapid quantification method of human serum glucose was established by using the Fourier transform infrared spectroscopy (FTIR) and attenuated total reflection (ATR). By the subtracted spectra between glucose aqueous solution and de-ionized water, absorption peaks are calculated in fingerprint area. Based on these absorption peaks and multiple linear regression (MLR) model, discrete band selection method of absorption peaks disturbance model (APDM) was developed. 5 absorption peaks 1150 cm-1, 1103 cm-1, 1078 cm-1, 1034 cm-1, 991 cm-1 were found in fingerprint area. Used these absorption peaks to establish absorption peaks disturbance model, the optimal wavelength combinations are 1140 More >

  • Open Access

    ARTICLE

    Feature Selection Method Based on Class Discriminative Degree for Intelligent Medical Diagnosis

    Shengqun Fang1, Zhiping Cai1,*, Wencheng Sun1, Anfeng Liu2, Fang Liu3, Zhiyao Liang4, Guoyan Wang5

    CMC-Computers, Materials & Continua, Vol.55, No.3, pp. 419-433, 2018, DOI:10.3970/cmc.2018.02289

    Abstract By using efficient and timely medical diagnostic decision making, clinicians can positively impact the quality and cost of medical care. However, the high similarity of clinical manifestations between diseases and the limitation of clinicians’ knowledge both bring much difficulty to decision making in diagnosis. Therefore, building a decision support system that can assist medical staff in diagnosing and treating diseases has lately received growing attentions in the medical domain. In this paper, we employ a multi-label classification framework to classify the Chinese electronic medical records to establish corresponding relation between the medical records and disease… More >

  • Open Access

    ARTICLE

    Ability of noninvasive criteria to predict hemodynamically significant aortic obstruction in adults with coarctation of the aorta

    Marco Astengo1,2*, Caroline Berntsson3*, Åse A. Johnsson3,4, Peter Eriksson1,2, Mikael Dellborg1,2

    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… More >

  • Open Access

    ARTICLE

    Condition Monitoring of Roller Bearing by K-Star Classifier and K-Nearest Neighborhood Classifier Using Sound Signal.

    Rahul Kumar Sharma*1, V. Sugumaran1, Hemantha Kumar2, Amarnath M3

    Structural Durability & Health Monitoring, Vol.11, No.1, pp. 1-16, 2017, DOI:10.3970/sdhm.2017.012.001

    Abstract Most of the machineries in small or large scale industry have rotating element supported by bearings for rigid support and accurate movement. For proper functioning of machinery, condition monitoring of the bearing is very important. In present study sound signal is used to continuously monitor bearing health as sound signals of rotating machineries carry dynamic information of components. There are numerous studies in literature that are reporting superiority of vibration signal of bearing fault diagnosis. However, there are very few studies done using sound signal. The cost associated with condition monitoring using sound signal (Microphone)… More >

  • Open Access

    ARTICLE

    Brake Fault Diagnosis Through Machine Learning Approaches – A Review

    Alamelu Manghai T.M.1, Jegadeeshwaran R2, Sugumaran V.3

    Structural Durability & Health Monitoring, Vol.11, No.1, pp. 43-67, 2017, DOI:10.3970/sdhm.2017.012.043

    Abstract Diagnosis is the recognition of the nature and cause of a certain phenomenon. It is generally used to determine cause and effect of a problem. Machine fault diagnosis is a field of finding faults arising in machines. To identify the most probable faults leading to failure, many methods are used for data collection, including vibration monitoring, thermal imaging, oil particle analysis, etc. Then these data are processed using methods like spectral analysis, wavelet analysis, wavelet transform, short-term Fourier transform, high-resolution spectral analysis, waveform analysis, etc., The results of this analysis are used in a root More >

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