Article | 03-July-2017
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
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 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
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
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
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
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 (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
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
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
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
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
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
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
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 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
/ 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
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
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
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
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
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
, 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
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
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
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
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
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
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
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
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
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 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
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
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
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
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
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
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
Aneta Ptak-Chmielewska
Statistics in Transition New Series, Volume 22 , ISSUE 1, 179–195
Article | 01-September-2015
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
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
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
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
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
) 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
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
. 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
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
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
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
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
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
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
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
Yongqing Wang,
Chunxiang Wang
International Journal on Smart Sensing and Intelligent Systems, Volume 8 , ISSUE 3, 1706–1729
Research Article | 01-December-2017
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
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
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
. 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
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
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 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
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
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
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
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
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
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
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
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
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
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