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In the given paper the aggregated randomized indices method is modified for credit scoring. Coefficients of the modified method can be calibrated on a massive training set in comparison with a standard version. Different credit scoring models are analyzed, i.e. with a binary scale and a continuous one. The Monte Carlo method is applied to measure the efficiency of models.
The freshness of vegetables attracts significant interest, because consumers will determine the way of cooking based on the maturity of the vegetable or select better vegetables in supermarkets based on the freshness information. This paper focuses on tomatoes, and reports our preliminary studies on acoustic probing techniques to estimate their storage term. We hit an acoustic probe that sweeps audible...
This paper investigates the identification of Continuous-Time models based on binary observations. Currently, no identification algorithm has been proposed in this field. The reason is twofold: first the time-domain differentiation operator of a such model structure prevents the use of existing identification methods based on binary observations, second the simple knowledge of binary observations...
The following paper discusses the development of a risk-based cost estimation model for completing non-standard manufacturing orders. The model in question is a hybrid of Monte Carlo Simulation (MCS), which constitutes the main module of the applied model. Vector of order risk probability, which is the input data for the MCS module, is highly difficult to assess and is burdened to a considerable degree...
Real-time human detection is a challenging task due to appearance variance, occlusion and rapidly changing content; therefore it requires efficient hardware and optimized software. This paper presents a real-time human detection scheme on a Raspberry Pi. An efficient algorithm for human detection is proposed by processing regions of interest (ROI) based upon foreground estimation. Different number...
Texture feature is an important feature descriptor for many image analysis applications. The objectives of this research are to determine distinctive texture features for crowd density estimation and counting. In this paper, we have comprehensively reviewed different texture features and their different possible combinations to evaluate their performance on pedestrian crowds. A two-stage classification...
Software effort estimation influences almost all the process of software development such as: bidding, planning, and budgeting. Hence, delivering an accurate estimation in early stages of the software life cycle may be the key of success of any project. To this aim, many solo techniques have been proposed to predict the effort required to develop a software system. Nevertheless, none of them proved...
Blind steganalysis is a method used to detect whether there is a hidden message in a media without having to know the steganography algorithm behind it. Digital image is converted into features using feature extraction algorithm subtractive pixel adjacency matrix. A model is built based on the resulting features using machine learning method support vector machine. The support vector machine method...
This paper examines the benefits of forced expiratory spirometry (FES) test with powerful machine learning algorithms for the purpose age estimation. The proposed method consists of three phases: feature extraction, training of regression models and estimation. Some useful features are determined and extracted from the results of FES test in the first phase. In the second phase, the regression models...
Eddy Current Testing (ECT) is a fast and effective method for detecting and sizing most of the default in conducting materials. The size estimation of an unknown defect from the measurement of the impedance variations is an important technique in industrial area. This paper considers to solve this problem by the novel combination of the Least Square Support Vector Machines (LS-SVM) and Finite Element...
Weather forecast is a valuable practical problem and has important implications for agriculture, industry and other services. There have been different proposed methods to forecast the weather parameters [3, 6, 8, 9], but the parameters of the prediction model depends on the geographical conditions and the economic development of the given area. Therefore, for every new location, we need to redefine...
Sleep deprivation distracted most people. The common ways to monitor people sleeping are electroencephalogram and polysomnography. Recently, wearable devices provide function to estimate sleep status. However, in some situations people feel uncomfortable to wear devices, such as elder with dementia. This paper presents a scheme to estimate sleep status based on wearable free device. We utilized SVM...
A decision-level fusion (DLF)-based team tactics estimation method in soccer videos is newly presented. In our method, tactics estimation based on audio-visual and formation features is newly adopted since the tactics of the soccer game are closely related to the audio-visual sequences and player positions. Therefore, by using these features, we classify the tactics via Support Vector Machine (SVM)...
It has been shown that unsupervised outlier detection methods can be adapted to the one-class classification problem. In this paper, we focus on the comparison of oneclass classification algorithms with such adapted unsupervised outlier detection methods, improving on previous comparison studies in several important aspects. We study a number of one-class classification and unsupervised outlier detection...
The accurate estimation of Mean Time Between Failures (MTBF) may be necessary under small sample size conditions and can be difficult. This article proposes combinations of two methods to calculate the cumulative probability using hierarchical Bayesian estimation and the mean rank order method, and two approaches to estimate parameters of the Weibull distribution using the ε-support vector regression...
The Geologic resource estimation requires the accurate prediction of the regionalized variables such as ore grade at an un-sampled location with the knowledge of sparse borehole information. It plays prominent role in the decision-making process for investment and development of various mining projects and hence judicious selection of the assessment method is essential for making profitable investment...
Most studies estimate the grasping force from electromyography (EMG) signals without the feature extraction. However, feature extraction can find the information which reflect the muscle contraction in greatest degree and eliminate the noise and redundancy. In order to find the feature with the highest accuracy, this paper selected 6 features which could represent the contraction of muscle. What's...
Detecting and localizing insulator plays a vital role in any power line monitoring system. In this work, we present a novel method for rotation invariant insulator detection. Rotation invariance is achieved by an efficient approach for estimating rotation angle of all insulator of an image. Sliding window based local directional pattern (LDP) feature is extracted from the image and support vector...
This paper presents a method that estimates human emotion evoked by visual stimuli using functional magnetic resonance imaging (fMRI) data. First, in our method, preprocessing and masking procedures are applied to the fMRI data. These procedures provide the multiple brain data corresponding to Brodmann areas (BA). In most cases, the dimensionality of fMRI data and the BA data is larger than the number...
In this paper, we propose a tourism category classification method based on estimation of reliable decision. The proposed method performs tourism category classification using location, visual, and textual tag features obtained from tourism images in image sharing services. As the biggest contribution of this paper, the proposed method performs successful classification based on two classification...
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