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Article | 03-July-2017

ESTIMATION OF THE CENTRAL MOMENTS OF A RANDOM VECTOR BASED ON THE DEFINITION OF THE POWER OF A VECTOR

The moments of a random vector based on the definition of the power of a vector, proposed by J. Tatar, are scalar and vector characteristics of a multivariate distribution. Analogously to the univariate case, we distinguish the uncorrected and the central moments of a random vector. Other characteristics of a multivariate distribution, i.e. an index of skewness and kurtosis, have been introduced by using the central moments of a random vector. For the application of the mentioned quantities for

Katarzyna Budny

Statistics in Transition New Series, Volume 18 , ISSUE 1, 1–20

Article | 08-April-2018

The Research of Direct Torque Control Based on Space Vector Modulation

In order to solve the conventional direct torque control contradiction between the dynamic and static performance ,a permanent magnet synchronous motor system direct torque control architecture is proposed based on space vector modulation strategy . In this method flux and torque are controlled through stator voltage components in stator fluxlinkage coordinate axes and space vector modulation is used to control inverters.The simulation verifies that SVM-DTCis capable of effectively improving

Su Xiaohui, Chen Guodong, Xu Shuping

International Journal of Advanced Network, Monitoring and Controls, Volume 2 , ISSUE 1, 100–107

Article | 12-April-2018

Speaker-dependent Isolated-Word Speech Recognition System Based on Vector Quantization

Speaker-dependent speech recognition system requires the system should not only recognize speech, but also recognize the speaker of the segment. In this paper, two indicators are selected—short-time average zero-crossing rate and dual-threshold endpoint to test the signal endpoint through the study of speaker-dependent isolated-word speech characteristics, and MFCC parameters are taken as the characteristic parameters; based on vector quantization, template matching algorithms are

Yinyin Zhao, Lei Zhu

International Journal of Advanced Network, Monitoring and Controls, Volume 2 , ISSUE 3, 93–97

Article | 01-December-2014

FACE RECOGNITION BASED ON IMPROVED SUPPORT VECTOR CLUSTERING

Traditional methods for face recognition do not scale well with the number of training sample, which limits the wide applications of related techniques. We propose an improved Support Vector Clustering algorithm to handle the large-scale biometric feature data effectively. We prove theoretically that the proposed algorithm converges to the optimum within any given precision quickly. Compared to related state-of-the-art Support Vector Clustering algorithms, it has the competitive performances on

Yongqing Wang, Xiling Liu

International Journal on Smart Sensing and Intelligent Systems, Volume 7 , ISSUE 4, 1807–1829

Research Article | 27-December-2017

INDEX FINGER MOTION RECOGNITION USING SELF-ADVISE SUPPORT VECTOR MACHINE

and well-known classifier, Support Vector Machine (SVM). An improvement of SVM, Self-advise SVM (SA-SVM), is tested to evaluate and compare its performance with the original one. The experimental result shows that SA-SVM improves the classification performance by on average 0.63 %.

Khairul Anam, Adel Al Jumaily, Yashar Maali

International Journal on Smart Sensing and Intelligent Systems, Volume 7 , ISSUE 2, 644–657

Article | 01-March-2016

VIBRATION BASED HEALTH MONITORING OF HONEYCOMB CORE SANDWICH PANELS USING SUPPORT VECTOR MACHINE

monitoring of these structures using support vector machine (SVM). The proposed technique is first used on simulated mode shape data of the structure and then the technique is validated using experimental mode shape data. The experimental set up has been developed in laboratory and Laser Doppler Vibrometer (LDV) is used to extract the experimental mode shapes. The results have been obtained using both support vector classification and regression analysis and it is found that that the former is better at

Saurabh Gupta, Satish B Satpal, Sauvik Banerjee, Anirban Guha

International Journal on Smart Sensing and Intelligent Systems, Volume 9 , ISSUE 1, 215–232

Article | 01-March-2015

ROBUST VISUAL TRACKING BASED ON SUPPORT VECTOR MACHINE AND WEIGHTED SAMPLING METHOD

Visual tracking algorithm based on binary classification has become the research hot issue. The tracking algorithm firstly constructs a binary classifier between object and background, then to determine the object’s location by the probability of the classifier. However, such binary classification may not fully handle the outliers, which may cause drifting. To improve the robustness of these tracking methods, a novel object tracking algorithm is proposed based on support vector machine (SVM

Gao Xiaoxing, Liu Feng

International Journal on Smart Sensing and Intelligent Systems, Volume 8 , ISSUE 1, 255–271

Article | 16-December-2013

Electrocardiogram for Biometrics by using Adaptive Multilayer Generalized Learning Vector Quantization (AMGLVQ): Integrating Feature Extraction and Classification

Electrocardiogram (ECG) signal for human identity recognition is a new area on biometrics research. The ECG is a vital signal of human body, unique, robustness to attack, universality and permanence, difference to others traditional biometrics technic. This study also proposes Adaptive Multilayer Generalized Learning Vector Quantization (AMGLVQ), that integrating feature extraction and classification method. The experiments shown that AMGLVQ can improve the accuracy of classification better

Elly Matul Imah, Wisnu Jatmiko, T. Basaruddin

International Journal on Smart Sensing and Intelligent Systems, Volume 6 , ISSUE 5, 1891–1917

Article | 01-September-2012

AN APPROPRIATE PROCEDURE FOR DETECTION OF JOURNAL-BEARING FAULT USING POWER SPECTRAL DENSITY, K-NEAREST NEIGHBOR AND SUPPORT VECTOR MACHINE

Journal-bearings play a significant role in industrial applications and the necessity of condition monitoring with nondestructive tests is increasing. This paper deals a proper fault detection technique based on power spectral density (PSD) of vibration signals in combination with K-Nearest Neighbor and Support Vector Machine (SVM). The frequency domain vibration signals of an internal combustion engine with three journal-bearing conditions were gained, corresponding to, (i) normal, (ii

A. Moosavian, H. Ahmadi, A. Tabatabaeefar, B. Sakhaei

International Journal on Smart Sensing and Intelligent Systems, Volume 5 , ISSUE 3, 685–700

Research Article | 26-September-2018

Chemical Signals of Vector Beetle Facilitate the Prevalence of a Native Fungus and the Invasive Pinewood Nematode

In China, the invasive Bursaphelenchus xylophilus, the vector Monochamus alternatus beetle, and associated fungi exhibit a symbiotic relationship causing serious losses to pine forests. Although this complex system has been intensively investigated, the role of vector beetles on the development of associated fungi and their indirect contribution to the prevalence of pinewood nematode (PWN) is yet unknown. Here, three of the highly prevalent fungal species, viz., Sporothrix sp. 1, Ophiostoma ips

BIN ZHANG, WEI ZHANG, MIN LU, FAHEEM AHMAD, HAOKAI TIAN, JING NING, XIAOLONG LIU, LILIN ZHAO, JIANGHUA SUN

Journal of Nematology, Volume 49 , ISSUE 4, 341–347

Article | 30-November-2018

A New Method of Improving the Traditional Traffic Identification and Accuracy

traffic traces, used machine learning techniques(SVM model[17]) to improve system performance and enable real-time traffic identification for high-speed networks. Zhao X proposed a P2P network traffic classification method based on support vector machine [19], using a statistical principle to divide the network traffic of four different types of P2P traffic applications (file sharing BitTorrent, media streaming PPLive, Internet phone Skype, instant messaging MSN), and studied network traffic

Wang Zhongsheng, Gao Jiaqiong

International Journal of Advanced Network, Monitoring and Controls, Volume 3 , ISSUE 3, 53–60

Article | 01-December-2015

VEHICLE MODEL RECOGNITION BASED ON USING IMAGE PROCESSING AND WAVELET ANALYSIS

Today, using intelligent transport systems such as identifying vehicle type for monitoring traffic in urban areas can advantage a lot. In this paper, a new method has been presented to detect vehicle type with only one reference image per class. Our algorithm is based on searching mean gradients and analysing these changes by Daubechies wavelet transformation. Firstly, a feature vector is obtained based on the car boundary changes of the side view image in proposed system. This vector is then

Elyas Abbasi Jennat Abadi, Soheyl Akhlaghi Amiri, Masoud Goharimanesh, Aliakbar Akbari

International Journal on Smart Sensing and Intelligent Systems, Volume 8 , ISSUE 4, 2212–2230

Research Article | 27-December-2017

Hybrid Intelligent Method of Identifying Stator Resistance of Motorized Spindle

Aiming at the problem that changes of nonlinear dynamic resistance of stator affect the performance of speed sensorless vector control system, a hybrid computing intelligence approach is used in the identification of stator resistance of motorized spindle. The partial least squares (PLS) regression is combined with neural network to solve the problem of few samples and multi-correlation of variables in complicated data modeling. The PLS method is used to extract variable components from sample

Lixiu Zhang, Yuhou Wu, Ke Zhang

International Journal on Smart Sensing and Intelligent Systems, Volume 7 , ISSUE 2, 781–797

Article | 01-December-2015

ROBOTIC ADAPTIVE IMPEDANCE CONTROL BASED ON VISUAL GUIDANCE

Uncalibrated visual servoing based on SVR-Jacobian estimator is proposed in unknown environment. Multiple support vector regression (SVR) machines are used to estimate the Jacobian matrix of images,and the nonlinear mapping between the image features of the curved line and the robot joint angle is constructed, uncalibrated robot impedance control can be carried out.Image Jacobian matrix expression with Gaussian kernel is put forward, the effectiveness of the presented approach is verified by

Li Erchao, Li Zhanming, He Junxue

International Journal on Smart Sensing and Intelligent Systems, Volume 8 , ISSUE 4, 2159–2174

Research paper | 10-April-2013

STUDY ON FEATURE SELECTION AND IDENTIFICATION METHOD OF TOOL WEAR STATES BASED ON SVM

extracted features, i.e. high computational cost and inefficient complexity of the model, which leads to overfitting. It is crucial to extract a smaller feature set by an effective feature selection algorithm. In this paper, an approach based on one-versus-one multi-class Support Vector Machine Recursive Feature Elimination (SVM-RFE) is proposed to solve the feature selection problem in tool wear condition monitoring. Moreover, in order to analyze a performance degradation process on the machine tool

Weilin Li, Pan Fu, Weiqing Cao

International Journal on Smart Sensing and Intelligent Systems, Volume 6 , ISSUE 2, 448–465

Article | 01-September-2012

TRANSIENT DYNAMIC BEHAVIOR OF TWO PHASE MAGNETO-ELECTRO-ELASTIC SENSORS BONDED TO ELASTIC RECTANGULAR PLATES

Transient dynamic behavior of Magneto-electro-elastic (MEE) sensors bonded to a mild steel plate using 3D magnetic vector potential approach is presented. The electric field induced by time varying magnetic field is non-conservative and can be described by electric scalar potential and magnetic vector potentials. The aim of the study is to find how different volume fractions of the MEE composite behave in sensor applications at various locations on the plate subjected to different boundary

B. Biju, N. Ganesan, K. Shankar

International Journal on Smart Sensing and Intelligent Systems, Volume 5 , ISSUE 3, 645–672

Article | 02-April-2020

Research on Control Strategy of Matrix Converter Motor System

/ three phase matrix converter consists of 9 two-way switches. Two basic principles of Matrix Converter Control Strategies as follows: Two input phase can not be connected meanwhile to an output phases to prevent short circuits; any output phase must ensure that an input is linked in order to prevent inductive load open circuit. Constraints in the above principles, matrix converter has a total of 27 switch states. Matrix converter control strategy has switch function method, dual-voltage vector method

Shuping Xu, Yichen Chang, Xiaohui Su, Yu Guo

International Journal of Advanced Network, Monitoring and Controls, Volume 5 , ISSUE 1, 54–60

Article | 27-December-2017

FACE DETECTION IN PROFILE VIEWS USING FAST DISCRETE CURVELET TRANSFORM (FDCT) AND SUPPORT VECTOR MACHINE (SVM)

YCgCr (luminance - green chrominance - red chrominance) color models is used to extract skin blocks. The segmentation scheme utilizes only the S and CgCr components, and is therefore luminance independent. Features extracted from three frequency bands from curvelet decomposition are used to detect face in each block. A support vector machine (SVM) classifier is trained for the classification task. In the performance test, the results showed that the proposed algorithm can detect profile faces in

Bashir Muhammad, Syed Abd Rahman Abu-Bakar

International Journal on Smart Sensing and Intelligent Systems, Volume 9 , ISSUE 1, 108–123

Sampling Methods | 12-July-2018

INTERACTION BETWEEN DATA COLLECTION AND ESTIMATION PHASES IN SURVEYS WITH NONRESPONSE

where data collection and estimation are considered together. For a chosen auxiliary vector, we define the concepts incidence and inverse incidence and show their properties and relationship. As we show, incidences are used in balancing the response in data collection; the inverse incidences are important for weighting adjustment in the estimation.

Carl-Erik Särndal, Imbi Traat, Kaur Lumiste

Statistics in Transition New Series, Volume 19 , ISSUE 2, 183–200

Article | 22-July-2019

TESTING HYPOTHESES ABOUT STRUCTURE OF PARAMETERS IN MODELS WITH BLOCK COMPOUND SYMMETRIC COVARIANCE STRUCTURE

In this article we deal with testing the hypotheses of the so-called structured mean vector and the structure of a covariance matrix. For testing the above mentioned hypotheses Jordan algebra properties are used and tests based on best quadratic unbiased estimators (BQUE) are constructed. For convenience coordinate-free approach (see Kruskal (1968) and Drygas (1970)) is used as a tool for characterization of best unbiased estimators and testing hypotheses. To obtain the test for mean vector

Roman Zmyslony, Arkadiusz Kozioł

Statistics in Transition New Series, Volume 20 , ISSUE 2, 139–153

Article | 01-March-2015

OBJECT TRACKING BASED ON MACHINE VISION AND IMPROVED SVDD ALGORITHM

be high, which makes it do not scale well with the number of training sample, and limits its wide applications. Based on the idea proposed by Support Vector Data Description, we present an improved SVDD algorithm to handle object tracking efficiently. The experimental results on synthetic data, tracking results on car and plane demonstrate the validity of the proposed algorithm.

Yongqing Wang, Yanzhou Zhang

International Journal on Smart Sensing and Intelligent Systems, Volume 8 , ISSUE 1, 677–696

Article | 10-April-2018

Association Rule Mining Based on Estimation of Distribution Algorithm for Blood Indices

To come over the limitations of Apriori algorithm and association rule mining algorithm based on Genetic Algorithm (GA), this paper proposed a new association rule mining algorithm based on the population-based incremental algorithm (PBIL), which is a kind of distribution estimation algorithms. The proposed association rule-mining algorithm keeps the advantages of GA mining association rules in coding and the fitness function. Through using probability vector possessing learning properties to

Xinyu Zhang, Botu Xue, Guanghu Sui, Jianjiang Cui

International Journal of Advanced Network, Monitoring and Controls, Volume 2 , ISSUE 3, 20–26

Research paper | 01-September-2014

KNOWLEDGE-BASED MODELING FOR PREDICTING CANE SUGAR CRYSTALLIZATION STATE

, based on support vector machine with particle swarm optimization, to improve the predictive accuracy and generalization capacity. Furthermore, the intelligent system is tested using a self-regulating intelligent comprehensive monitoring and controlling platform that represents the cane sugar process. Results demonstrate the feasibility of the system for predicting the crystallization state in a real cane sugar process.

Yanmei Meng, Xian Yu, Haiping He, Zhihong Tang, Xiaochun Wang, Jian Chen

International Journal on Smart Sensing and Intelligent Systems, Volume 7 , ISSUE 3, 942–965

Research Article | 01-September-2011

BIOLOGICALLY-INSPIRED VISUAL ATTENTION FEATURES FOR A VEHICLE CLASSIFICATION TASK

viewpoints. Salient visual features classified with a series of binary support vector machines and complemented by a dissimilarity score achieve average classification rates between 94% and 97.3% for five-category vehicle classification depending on the combination of viewpoints used. The viewpoints that make the most important contribution to the classification are identified in order to decrease the implementation cost. The evaluation of performance against other feature descriptors and various

A.-M. Cretu, P. Payeur

International Journal on Smart Sensing and Intelligent Systems, Volume 4 , ISSUE 3, 402–423

Article | 07-May-2018

Multiple Vehicle License Plate Location in Complex Background

the color, dimension, texture and match the similarity to choose, search and merger area in the image, suspicious area of the license plate is obtained. Using visual word package to express rectangular profile after coarse positioning. Using support vector machine (SVM) to classify and identify rectangular area of license plate. Accurate positioning license plate location is positioned accurately. The method of accuracy is 96.4% for 135 pieces of test sample positioning, strong anti-jamming.

Yaxin Zhao, Li Zhao, Ya Li

International Journal of Advanced Network, Monitoring and Controls, Volume 3 , ISSUE 1, 62–68

Article | 01-June-2016

NOVEL SVDD-BASED ALGORITHM FOR MOVING OBJECT DETECTING AND TRACKING UNDER DYNAMIC SCENES

features, where the detecting and tracking drift caused by noisy background can be effectively handled by robust maximum margin classifier, such as one-class SVM. But the time and space complexities of traditional one-class SVM methods tend to be high, which limits its wide applications to various fields. Inspired by the idea proposed by Support Vector Data Description (SVDD), in this paper we present a novel SVDD-based algorithm to efficiently deal with detecting and tracking moving object under

Chunxiang Wang, Dongfang Xu, Yongqing Wang

International Journal on Smart Sensing and Intelligent Systems, Volume 9 , ISSUE 2, 1130–1155

Research Article | 05-September-2018

Multi-algorithmic Palmprint Authentication System Based on Score Level Fusion

transform. The match scores obtained from matching modules were normalized using z-score and fused with different score level fusion schemes namely sum-rule,weighted sum-rule, and Support Vector Machine (SVM) fusion, respectively. The experimental results show that SVM score level fusion lead to an increased performance for the proposed multi-algorithmic palmprint authentication system with genuine acceptance rate of 98% for 0.1% false acceptance rate, and equal error rate of 1.5% compared to weighted

C. Murukesh, G. Arul Elango

International Journal on Smart Sensing and Intelligent Systems, Volume 11 , ISSUE 1, 1–11

Article | 01-June-2015

A NOVEL KNOWLEDGE-COMPATIBILITY BENCHMARKER FOR SEMANTIC SEGMENTATION

vision-based knowledge, then outputs an estimate of the corresponding averaged class-accuracy value. The knowledge encodes three kinds of information, namely: cooccurrence statistics, scene properties and relative positions. We introduce three types of feature vectors for regression. Each specifies the characteristics of a probability vector that captures the compatibility between an annotation and each kind of the knowledge. Experiment results show that the Gradient Boosting regression outperforms

Vektor Dewanto, Aprinaldi, Zulfikar Ian, Wisnu Jatmiko

International Journal on Smart Sensing and Intelligent Systems, Volume 8 , ISSUE 2, 1284–1312

Research Article | 01-December-2017

PERFORMANCE EVALUATION OF SVM KERNELS ON MULTISPECTRAL LISS III DATA FOR OBJECT CLASSIFICATION

Object based classification plays an important role in every field. Support vector machine is the popular algorithm for object based classification. Support vector machine classifies the data points using straight line. Some datasets are impossible to separate by straight line. To cope with this problem kernel function is used. The central idea of kernel function is to project points up in a higher dimensional space hoping that separability of data would improve. There are various kernels in

S.V.S. Prasad, T. Satya Savithri, Iyyanki V. Murali Krishna

International Journal on Smart Sensing and Intelligent Systems, Volume 10 , ISSUE 4, 829–844

Research Article | 01-December-2017

PERFORMANCE EVALUATION OF SVM KERNELS ON MULTISPECTRAL LISS III DATA FOR OBJECT CLASSIFICATION

Object based classification plays an important role in every field. Support vector machine is the popular algorithm for object based classification. Support vector machine classifies the data points using straight line. Some datasets are impossible to separate by straight line. To cope with this problem kernel function is used. The central idea of kernel function is to project points up in a higher dimensional space hoping that separability of data would improve. There are various kernels in

S.V.S. Prasad, T. Satya Savithri, Iyyanki V. Murali Krishna

International Journal on Smart Sensing and Intelligent Systems, Volume 10 , ISSUE 4, 863–878

Article | 08-April-2018

Study on the Control Strategy of Matrix Converter Motor System

To overcome the defects of pure integrator initial value of the integral, the cumulative error and DC offset, permanent magnet synchronous motor stator flux observer method is proposed based on full-order state observer. The stator flux as state vector to construct the system state equation, the current as output vector to construct the system output equation, configuration observer poles proportional to the motor model pole, and use of the robust pole assignment algorithm in Matlab for

Xu Shuping, Li Erdong, Su Xiaohui

International Journal of Advanced Network, Monitoring and Controls, Volume 1 , ISSUE 2, 76–81

Article | 22-July-2019

VARIABLE SELECTION IN MULTIVARIATE FUNCTIONAL DATA CLASSIFICATION

A new variable selection method is considered in the setting of classification with multivariate functional data (Ramsay and Silverman (2005)). The variable selection is a dimensionality reduction method which leads to replace the whole vector process, with a low-dimensional vector still giving a comparable classification error. Various classifiers appropriate for functional data are used. The proposed variable selection method is based on functional distance covariance (dCov) given by Sz

Tomasz Górecki, Mirosław Krzyśko, Waldemar Wołyński

Statistics in Transition New Series, Volume 20 , ISSUE 2, 123–138

Article | 04-June-2018

Creating a Conference Poster with High-Resolution Network Figures

Creating a poster with high-resolution network images can be a challenging task. In this article, the process of exporting a network figure from a network analysis tool, importing it in a vector graphics tool, and preparing the poster for print is discussed. The steps include critical strategies for producing print-quality figures that also apply to the preparation of network figures for journal publication. We discuss different file formats and argue that the favorite tool for creating

Jürgen Pfeffer

Connections, Volume 37 , ISSUE 1-2, 95–100

Article | 11-April-2018

Research on Combination Forecasting Model of Mine Gas Emission

This paper focuses on the effective analysis of the mine gas emission monitoring data, so as to realize the accurate and reliable mine gas emission prediction. Firstly, a weighted multiple computing models based on parametric t– norm is constructed. And a new mine gas emission combination forecasting method is proposed. The BP neural network model and the support vector machine were used as the single prediction models. Finally, genetic algorithm and least square method were used to

Liang Rong, Chang Xintan, Jia Pengtao, Dong Dingwen

International Journal of Advanced Network, Monitoring and Controls, Volume 2 , ISSUE 3, 194–198

Research paper | 31-October-2017

CLASSIFICATION PROBLEMS BASED ON REGRESSION MODELS FOR MULTI-DIMENSIONAL FUNCTIONAL DATA

Data in the form of a continuous vector function on a given interval are referred to as multivariate functional data. These data are treated as realizations of multivariate random processes. We use multivariate functional regression techniques for the classification of multivariate functional data. The approaches discussed are illustrated with an application to two real data sets.

Tomasz Górecki, Mirosław Krzyśko, Waldemar Wołyński

Statistics in Transition New Series, Volume 16 , ISSUE 1, 97–110

Research Article | 15-February-2020

A Proposal for Classification of Multisensor Time Series Data based on Time Delay Embedding

in a suitable manner for analysis by popular machine learning algorithms. Though a plethora of different approaches have been developed so far, 1NN classifier based on dynamic time warping (DTW) has been found to be the most popular due to its simplicity. In this work, an approach for time series classification is proposed based on multidimensional delay vector representation of time series. Multivariate time series is considered here as a group of single time series and each time series is

Basabi Chakraborty

International Journal on Smart Sensing and Intelligent Systems, Volume 7 , ISSUE 5, 1–5

Article | 05-June-2013

A NOVEL TRI-FACTOR MUTUAL AUTHENTICATION WITH BIOMETRICS FOR WIRELESS BODY SENSOR NETWORKS IN HEALTHCARE APPLICATIONS

Chen-Guang He, Shu-Di Bao, Ye Li

International Journal on Smart Sensing and Intelligent Systems, Volume 6 , ISSUE 3, 910–931

Research Article | 27-May-2018

CANONICAL CORRELATION ANALYSIS IN THE CASE OF MULTIVARIATE REPEATED MEASURES DATA

In this paper, we present, in the real example, canonical variables applicable in the case of multivariate repeated measures data under the following assumptions: (1) multivariate normality for the vector of observations and (2) Kronecker product structure of the positive definite covariance matrix. These variables are especially useful when the number of observations is not large enough to estimate the covariance matrix, and thus the traditional canonical variables fail. Computational schemes

Mirosław Krzyśko, Wojciech Łukaszonek, Waldemar Wołyński

Statistics in Transition New Series, Volume 19 , ISSUE 1, 75–85

research-article | 30-November-2018

First record of Aphelenchoides stammeri (Nematoda: Aphelenchoididae) from Turkey

Pine wilt disease, caused by the pinewood nematode, Bursaphelenchus xylophilus (Steiner and Buhrer, 1934; Nickle, 1970) (Nematoda: Parasitaphelenchidae), has been leading to extensive damage in pine forests of eastern Asia (Webster, 1999). After detection of the nematode in Portugal (Mota et al., 1999), the scientific interest in this wood-inhabiting group of nematodes and other components of the pine wilt disease (host tree and vector insects) has increased in European countries. Although the

Mehmet Dayi, Ece B. Kasapoğlu Uludamar, Süleyman Akbulut, İ. Halil Elekcioğlu

journal of nematology, Volume 51 , 1–6

Article | 03-March-2021

Bankruptcy prediction of small- and medium-sized enterprises in Poland based on the LDA and SVM methods

Aneta Ptak-Chmielewska

Statistics in Transition New Series, Volume 22 , ISSUE 1, 179–195

Article | 01-September-2015

FABRICATION OF HIGH FREQUENCY SURFACE ACOUSTIC WAVE (SAW) DEVICES FOR REAL TIME DETECTION OF HIGHLY TOXIC CHEMICAL VAPORS

In this paper, a low cost fabrication of sub micron features size SAW device with conventional lithography and their application for toxic chemical vapor detection has been presented. The SAW devices with different interdigital transducer (IDT) electrodes line widths were designed and fabricated. The fabricated SAW devices features had an accuracy of ± 0.1 μm. Frequency response of the SAW devices was measured with vector network analyzer for design parameter confirmation. The fabricated

Upendra Mittal, Tarikul Islam, A T Nimal, M U Sharma

International Journal on Smart Sensing and Intelligent Systems, Volume 8 , ISSUE 3, 1601–1623

Article | 05-September-2013

PREDICTION OF PCCP FAILURE BASED ON HYDROPHNE DETECTING

Prestressed Concrete Cylinder Pipe (PCCP) is a widely used water pipe all over the world. A major cause of PCCP failure is the internal wire break, which will emit acoustic signal. In this paper, a hydrophone-based PCCP real-time monitoring and failure-prediction system was proposed. By applying wavelet energy normalization analysis to signal feature extraction and Support Vector Machine (SVM) to signal recognition, a high prediction accuracy of 98.33% was achieved. The result showed that the

Yuan Zhang, Yibo Li

International Journal on Smart Sensing and Intelligent Systems, Volume 6 , ISSUE 4, 1582–1598

Research Article | 01-September-2014

 VIDEO-BASED VEHICLE DETECTION AND CLASSIFICATION IN CHALLENGING SCENARIOS   

dimension reduction. In vehicle classification part, we adopt fuzzy support vector machine, and design a novel vehicle classifier based on nested one-vs-one algorithm. Finally, experimental tests show excellent results of our methods in both vehicle detection and classification.   

Yiling Chen, GuoFeng Qin

International Journal on Smart Sensing and Intelligent Systems, Volume 7 , ISSUE 3, 1077–1094

Research Article | 01-September-2017

MACHINE VISION BASED MISSING FASTENER DETECTION IN RAIL TRACK IMAGES USING SVM CLASSIFIER

Missing fastener detection is a critical task due to its similar characteristics with surrounding environments. In this paper, a machine vision based fully automatic detection and classification of missing fastener detection system is proposed using Support Vector Machine (SVM) classifier. This proposed system consists of preprocessing, transformation, feature extraction and classifications. Image resizing is performed as preprocessing step and Gabor transform is used as transformation

R. Manikandan, M. Balasubramanian, S. Palanivel

International Journal on Smart Sensing and Intelligent Systems, Volume 10 , ISSUE 5, 574–589

Article | 01-December-2016

AN INTELLIGENT FEATURE SELECTION AND CLASSIFICATION METHOD BASED ON HYBRID ABC–SVM

This paper presents a new approach to feature selection and classifcation based on support vector machine and hybrid artificial bee colony. The approach consists of two stages. At the first stage, this paper presented a hybrid artificial bee colony-based classifier model that combines artificial bee colony to improve classification accuracy with the most superior model parameter and features were selected from the original feature set. The classification accuracy and the feature subset provided

Jie Li, Qiuwen Zhang, Zhang Yongzhi, Li Chang, Xiao Jian

International Journal on Smart Sensing and Intelligent Systems, Volume 9 , ISSUE 4, 1876–

Research Article | 08-February-2019

A GIS BASED GRAPH ORIENTED ALGORITHMIC MODEL FOR POLY-OPTIMIZATION OF WASTE MANAGEMENT SYSTEM

) analyses in the system through the application of GIS technology (ability to use digital (vector or halftonebased) terrain maps), execution of spatial analyses, data visualization on maps, etc., using also commonly available spatial data available as part of the Infrastructure for Spatial Information (established under the Act on Infrastructure for Spatial Information).

Krzysztof GASKA, Agnieszka GENEROWICZ, Izabela ZIMOCH, Józef CIUŁA, Dariusz SIEDLARZ

Architecture, Civil Engineering, Environment, Volume 11 , ISSUE 4, 151–159

Article | 05-September-2013

Smartphone Application for Fault Recognition

1Nishchal K. Verma, Rahul K. Sevakula, Jayesh K. Gupta, Sumanik Singh, Sonal Dixit, Al Salour

International Journal on Smart Sensing and Intelligent Systems, Volume 6 , ISSUE 4, 1763–1782

Article | 14-October-2020

A Comparative Study of Face Recognition Classification Algorithms

. The methods used involve linear logistic regression, linear discriminant analysis (LDA), K-Nearest Neighbor (KNN), support vector machine (SVM), Naïve Bayes (NB) and other methods. The definition and advantages and disadvantages of the act are briefly explained. Finally, the five methods are compared and analyzed according to the evaluation indicators such as the accuracy rate, recall rate, F1-score, and AUC area commonly used in machine learning. II. RELATED WORK A. Principal component

Changyuan Wang, Guang Li, Pengxiang Xue, Qiyou Wu

International Journal of Advanced Network, Monitoring and Controls, Volume 5 , ISSUE 3, 23–29

research-article | 31-August-2021

Using Text and Visual Cues for Fine-Grained Classification

mechanism on texts to get our most relevant words from text features and we put attention on the visual features to get our most relevant features like edges, color, size of object, etc. The attention mechanism [27] scores each input word (via dot product with attention weights), then to create a distribution scores are passed through softmax function. An attention vector is produce by multiplying distribution with the context vector and then passed to the decoder. The advantage of attention are its

Zaryab Shaker, Xiao Feng, Muhammad Adeel Ahmed Tahir

International Journal of Advanced Network, Monitoring and Controls, Volume 6 , ISSUE 3, 42–49

Article | 16-December-2013

Target Classification Using Pyroelectric Infrared Sensors in Unattended Wild Ground Environment

Dongfeng Xie, Huawei Liu, Baoqing Li, Qianwei Zhou, Xiaobing Yuan

International Journal on Smart Sensing and Intelligent Systems, Volume 6 , ISSUE 5, 2119–2135

Article | 01-June-2015

NOVEL MULTI-CLASS SVM ALGORITHM FOR MULTIPLE OBJECT RECOGNITION

tend to be poor, and limits the wide applications. Inspired by the idea presented by Multi-class Core Vector Machine, we propose a novel Multi-class SVM algorithm, which achieves excellent performance on dealing with multiple object recognition. The simulation results on synthetic numerical data and recognition results on real-world pictures demonstrate the validity of the proposed algorithm.

Yongqing Wang, Yanzhou Zhang

International Journal on Smart Sensing and Intelligent Systems, Volume 8 , ISSUE 2, 1203–1224

Article | 13-December-2019

MULTI-DOMAIN NEYMAN-TCHUPROV OPTIMAL ALLOCATION

optimal allocation vector and relative variance than in such purely numerical tools (although the eigenproblem solution provides also numerical solutions, see, e.g. Wesołowski and Wieczorkowski (2017)). The domain-wise optimal allocation and the respective optimal variance of the estimator are determined by the unique direction (defined in terms of the positive eigenvector of matrix D) in the space RI, where I is the number of domains in the population.

Jacek Wesołowski

Statistics in Transition New Series, Volume 20 , ISSUE 4, 1–12

Article | 05-September-2013

AN INVESTIGATION OF DECISION ANALYTIC METHODOLOGIES FOR STRESS IDENTIFICATION

data set created by the MIT Media lab is used to evaluate the relative performance of these methods. Our study show that the PCA can not only reduce the needed number of features from 22 to five, but also the number of sensors used from five to two and it only uses one type of sensor, thus increasing the application usability. The selected features can be used to quickly detect stress level with good accuracy (78.94%), if support vector machine fusion method is used.

Yong Deng, Chao-Hsien Chu, Huayou Si, Qixun Zhang, Zhonghai Wu

International Journal on Smart Sensing and Intelligent Systems, Volume 6 , ISSUE 4, 1675–1699

Article | 01-June-2016

PREDICTION OF SEWAGE QUALITY BASED ON FUSION OF BPNETWORKS

Sewage treatment system is a complicated nonlinear system with multi-variables, chemical reaction, biological process and altered loads, hard to describe mathematically. Thus prediction of the effluent quality parameters of sewage treatment plant has being a challenge. In this paper we adopt fusion of two BP networks to predict sewage quality parameters with a popular process Cyclic Activated Sludge System (CASS). We take use of SVM (support vector machine) to classify the input data into two

Lijuan Wang

International Journal on Smart Sensing and Intelligent Systems, Volume 9 , ISSUE 2, 909–926

Article | 10-April-2018

Research on Intelligent Monitoring Technology of Micro Hole Drilling

Aiming at the problem that the micro drills is easy to be broken in the process of drilling; it is difficult to detect the drill bit. The drilling torque signal is taken as the monitoring object. A new method for the on-line monitoring the micro-drill breakage based on BP neural network is proposed. After the three layer wavelet decomposition of the drilling torque signal, the energy feature vector is used as the input layer of the BP network, and the mapping model of the working state and the

Yanhong Sun, Mei Tian

International Journal of Advanced Network, Monitoring and Controls, Volume 2 , ISSUE 4, 142–146

Article | 01-September-2015

COMPUTER VISION-BASED COLOR IMAGE SEGMENTATION WITH IMPROVED KERNEL CLUSTERING

Yongqing Wang, Chunxiang Wang

International Journal on Smart Sensing and Intelligent Systems, Volume 8 , ISSUE 3, 1706–1729

Research Article | 01-December-2017

Dwipa Ontology III: Implementation of Ontology Method Enrichment on Tourism Domain

This article summarizes some research results related to ontology enrichment specific to tourism domains from 2014 to 2017. Currently, some ontology enrichment approaches can use learning machinery such as support vector machine (SVM), Conditional Random Field (CRF) and kNN. Several studies have also been successful in evaluating ontology enrichment results with several parameters such as precision, recall and F-Measure. In addition, our research can enrich Dwipa Ontology II which has been

Guson Prasamuarso Kuntarto, Irwan Prasetya Gunawan, Fahmi L. Moechtar, Yudhiansyah Ahmadin, Berkah I. Santoso

International Journal on Smart Sensing and Intelligent Systems, Volume 10 , ISSUE 4, 903–919

Article | 30-November-2018

A Survey of Calibration Methods for Traditional Cameras Based on Line Structure Light

between the 3D point M and its projection point m is as follows[7]: (1) sm˜=A[R,t]M˜ Where R is the rotation matrix, t = [tx ty tz]T for the translation vector, and describes the external parameters of the camera that the camera is calibrated. fu = ax/dx, fv = ay/dy, dx, dy indicates the physical size of each pixel in the Y-axis Y-axis direction. fu, fv, u0, v0 is only related to the internal parameters of the camera, which is the internal parameters that the camera needs to calibrate. B. Camera

Ruixia Wu, Baolong Liu, Huimin Yao

International Journal of Advanced Network, Monitoring and Controls, Volume 4 , ISSUE 1, 66–71

Article | 24-June-2021

COMPUTING MODEL FOR SIMULATION OF THE POLLUTION DISPERSION NEAR THE ROAD WITH SOLID BARRIERS

In this study, a numerical model is proposed for calculating pollution zones near the road, taking into account the geometry of the automobile transport, meteorological conditions, the location of the barriers and their height, and the chemical transformation of nitrogen oxides in the atmospheric air. The numerical solution is based on the integration of the mass transfer equations using the finite-difference method. To determine the components of the air flow velocity vector, a two-dimensional

Mykola BILIAIEV, Oleksandr PSHINKO, Tetiana RUSAKOVA, Viktoriia BILIAIEVA, Aleksander SŁADKOWSKI

Transport Problems, Volume 16 , ISSUE 2, 73–86

Research Article | 13-December-2017

A BROADBAND SPECTROSCOPIC SENSOR PROBE

. Although the probe is capable of a very wide frequency range, separate instruments are generally required, and here we focus on measurements above 1MHz. We demonstrate measurements in the frequency domain using a vector network analyser, and in the time domain using a broadband oscilloscope. For switching, we employed a coaxial switch and demonstrate how that is included within the instrument calibration. Calibration of the probe used three references: an open circuit, short circuit (indium foil) and a

I M Woodhead, I Platt, J H Christie, S Krenek

International Journal on Smart Sensing and Intelligent Systems, Volume 1 , ISSUE 2, 459–469

Article | 01-December-2012

STUDY ON THE CONGESTION CONTROLLER FOR TIMEDELAY NETWORKED CONTROL SYSTEMS WITH EXTERNAL DISTURBANCES

iterative formula of adjoint vector equations. A reduced-order disturbance observer is constructed to make the FFCC law physically realizable. Numerical examples are presented to illustrate the effectiveness and robustness of the proposed design approach.

Hua Tong, Peng Liu

International Journal on Smart Sensing and Intelligent Systems, Volume 5 , ISSUE 4, 859–878

Research Article | 03-December-2018

Characterization of Juvenile Stages of Bursaphelenchus crenati Rühm, 1956 (Nematoda: Aphelenchoidoidea)

combined with the most active cellular differentiation and elongation of the genital primordium. The dauer juveniles collected from elytra of vector beetles were similar to the third juvenile stage of the propagative generation by genital primordium structure and body size.

Alexander Y. Ryss, Kristina S. Polyanina

Journal of Nematology, Volume 50 , ISSUE 4, 459–472

Research Article | 01-September-2017

A MULTI-KEYWORD RANKED SEARCH SCHEME OVER ENCRYPTED BASED ON HIERARCHICAL CLUSTERING INDEX

A Secure and Dynamic Multi-keyword Ranked Search Scheme over Encrypted Cloud Data Due to the increasing popularity of cloud computing, more and more data owners are motivated to outsource their data to cloud servers for great convenience and reduced cost in data management. In this project, present a secure multi-keyword ranked search scheme over encrypted cloud data, which simultaneously supports dynamic update operations like deletion and insertion of documents. Specifically, the vector space

A. Indhuja, T.P.Udaya shankar, R.M Balajee Mastan Vali Shaik, P Sujatha

International Journal on Smart Sensing and Intelligent Systems, Volume 10 , ISSUE 5, 539–559

Article | 01-April-2020

A single base insertion of the 4-α-galactosyltransferase gene led to the deficiency of Gb3 biosynthesis

cDNAs for α 1,4 galactosyltransferase (A4GALT) have been isolated. To explore the molecular basis of the p phenotype in Japanese donors, we analyzed the A4GALT gene sequences of normal and p phenotype samples. The coding region in the A4GALT gene for DNA sequencing was amplified by PCR amplification. A4GALT expression vectors for individual mutants were constructed by PCR amplification of the coding region using primers and subsequent subcloning into an expression vector. The expression

Mitsunobu Tanaka, Naoko Yamashita, Junko Takahashi, Fumiya Hirayama, Yoshihiko Tani, Hirotoshi Shibata

Immunohematology, Volume 22 , ISSUE 1, 23–29

Article | 01-June-2015

PERFORMANCE BOUND ANALYSIS ON TRANSMIT ANTENNAS SELECTION SYSTEMS CONSIDERING ERRONEOUS CHANNEL INFORMATION

encoding scheme and derive the probability density function (PDF) of Frobenius norm of column vector of the channel matrix. Using the known PDF we can derive the joint PDF of order statistics channel for the subset {i, j}. Assuming that the transmitted signals employ Mary phase-shift keying (MPSK) constellation, we consider the impact of imperfect antenna selection subsets on system performance, and explicitly derive a closed-form BER expression of Chernoff upper bounds (CUB). For two special cases

Mingjie Zhuang

International Journal on Smart Sensing and Intelligent Systems, Volume 8 , ISSUE 2, 1333–1353

Research Article | 21-May-2019

FACTORS RESPONSIBLE FOR THE DEVELOPMENT OF LYME CARDITIS

Borrelia burgdorferi sensu lato spirochetes are unique in many aspects. They are the etiological agents of Lyme borreliosis, meta-zoonotic, tick-borne disease of mammals, including humans. Ixodes spp. ticks are the vector. With the exception of erythema chronicum migrant (EM), manifestations of the disease may vary depending on the genospecies of Borrelia burgdorferi sensu lato. One of the symptoms is Lyme carditis. To date, the causative factors and the mechanisms of pathogenesis have not been

Tomasz Chmielewski, Stanisława Tylewska-Wierzbanowska

Postępy Mikrobiologii - Advancements of Microbiology, Volume 56 , ISSUE 1, 100–105

research-article | 30-November-2020

Prevalence of Dirofilaria immitis in mosquitoes (Diptera) – systematic review and meta-analysis

Dirofilariasis is a zoonotic vector-borne disease transmitted by at least 27 species of the genus Dirofilaria (Spirurida, Onchocercidae), especially D. repens and D. immitis (canine or dog heartworm). The disease is widely distributed and the reservoirs are mainly mammals from approximately 111 species including canids. Presently, dirofilariasis in humans is considered to be an emerging disease in some regions (Azari-Hamidian et al., 2007, 2009; Simón et al., 2012). At present, at least 77

Seyed Mohammad Riahi, Mustapha Ahmed Yusuf, Shahyad Azari-Hamidian, Rahmat Solgi

Journal of Nematology, Volume 53 , 1–13

Article | 24-June-2021

ASSESSING THE IMPACT OF TRANSPORT AND LOGISTICS ON ECONOMIC GROWTH IN EMERGING ECONOMIES: A CASE STUDY FOR THE CONDITIONS OF THE REPUBLIC OF KAZAKHSTAN

This article examines the link between logistics indicators and economic growth in Kazakhstan in the period 1995-2019. Factors and the causal relationship between the indicators of transport development and economic growth, using the models of total production, demand and vector error correction, are studied. The analysis established specifics of the relationship between indicators of various types of transport and economic growth and their mutual influence, both in terms of directions and the

Zhanarys RAIMBEKOV, Bakyt SYZDYKBAYEVA

Transport Problems, Volume 16 , ISSUE 2, 199–211

original-report | 30-November-2020

New ABO intron 1 variant alleles

K. Fennell, M.A. Keller, M.A. Villa, C. Paccapelo, M. Kucerakova, J. Rosochova, C. Clemente DosSantos, L. Brackney, C.J. Lee, R. Metcalf, G. Crovetti, M. Barbieri, S. Travali, G. Barrotta, G. Giuca, L.E. Guerra, G. Ochoa-Garay

Immunohematology, Volume 37 , ISSUE 4, 178–184

research-article | 30-November-2019

A proposal of Bursaphelenchus uncispicularis Zhuo, Li, Li, Yu & Liao, 2007 as a junior synonyms of B. yongensis Gu, Braasch, Burgermeister, Brandstetter & Zhang, 2006

present in China, Japan and Korea with a common host species (P. thunbergii) and a common widespread vector (C. fulvus). Based on the geographic, ecological, molecular, and morphological data, we propose Bursaphelenchus uncispicularis Zhuo, Li, Li, Yu & Liao, 2007 as a junior synonyms of B. yongensis Gu, Braasch, Burgermeister, Brandstetter & Zhang, 2006.

Jianfeng Gu, Kan Zhuo, Jinling Liao

Journal of Nematology, Volume 52 , 1–3

research-article | 11-March-2021

Morphology, development stages, and phylogeny of the Rhabditolaimus ulmi (Nematoda: Diplogastridae), a phoront of the bark beetle Scolytus multistriatus from the elm Ulmus glabra Huds. in Northwest Russia

ecological role in relation to its vector life cycle, and (iii) provide molecular characterization of R. ulmi and reconstruct phylogeny of the genus. Materials and methods Nematode samples During 2014 to 2020 declining Ulmus glabra Huds. trees were surveyed for wood-inhabiting nematodes in parklands of eight St. Petersburg city districts: Admiralteisky, Vyborgsky, Vasileostrovsky, Krasnoselsky, Kirovsky, Moscowsky, Petrogradsky, and Primorsky. In total, 25 locations were selected for consistent

Alexander Y. Ryss, Kristina S. Polyanina, Sergio Álvarez-Ortega, Sergei A. Subbotin

Journal of Nematology, Volume 53 , 1–25

Article | 03-September-2013

Detection and classification of the behavior of people in an intelligent building by camera

the heating . My goal is to develop a robust and reliable system which is composed of two fixed cameras in every room of intelligent building which are connected to a computer for acquisition of video sequences, with a program using these video sequences as inputs, we use RGB color histograms and textures for LBP represented different images of video sequences, and SVM (support vector machine) Lights as a programming tool for the detection and classification of the behavior of people in this

Henni Sid Ahmed, Belbachir Mohamed Faouzi, Jean Caelen

International Journal on Smart Sensing and Intelligent Systems, Volume 6 , ISSUE 4, 1317–1342

Article | 15-September-2020

An evaluation of design-based properties of different composite estimators

For the last several decades, the US Census Bureau has been applying AK composite estimation method for estimating monthly levels and month-to-month changes in unemployment using data from the Current Population Survey (CPS), which uses a rotating panel design. For each rotation group, survey-weighted totals, known as monthin-sample estimates, are derived each month to estimate population totals. Denoting the vector of month-in-sample estimates by Y and the design-based variance-covariance

Daniel Bonnéry, Yang Cheng, Partha Lahiri

Statistics in Transition New Series, Volume 21 , ISSUE 4, 166–190

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