• International Journal of Computer Science & Network Security
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• v.23 no.1
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• pp.33-40
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• 2023

Machine-learning techniques are discovering effective performance on data analytics. Classification and regression are supported for prediction on different kinds of data. There are various breeds of classification techniques are using based on nature of data. Threshold determination is essential to making better model for unlabelled data. In this paper, threshold value applied as range, based on min-max normalization technique for creating labels and multiclass classification performed on rainfall data. Binary classification is applied on autism data and classification techniques applied on child abuse data. Performance of each technique analysed with the evaluation metrics.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.21 no.45
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• pp.57-65
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• 1998

This paper addresses the data classification using the induction of decision trees. A weakness of other techniques of induction of decision trees is that decision trees are too large because they construct decision trees until leaf nodes have a single class. Our study include both overcoming this weakness and constructing decision trees which is small and accurate. First, we construct the decision trees using classification threshold and exception threshold in construction stage. Next, we present two stage pruning method using classification threshold and reduced error pruning in pruning stage. Empirical results show that our method obtain the decision trees which is accurate and small.

• Journal of Korean Institute of Industrial Engineers
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• v.23 no.4
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• pp.755-767
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• 1997

Analyzing autocorrelated data set is still an open problem. Developing on easy and efficient method for severe positive correlated data set, which is common in simulation output, is vital for the simulation society. Bootstrap is on easy and powerful tool for constructing non-parametric inferential procedures in modern statistical data analysis. Conventional bootstrap algorithm requires iid assumption in the original data set. Proper choice of resampling units for generating replicates has much to do with the structure of the original data set, iid data or autocorrelated. In this paper, a new bootstrap resampling scheme is proposed to analyze the autocorrelated data set : the Threshold Bootstrap. A thorough literature search of bootstrap method focusing on the case of autocorrelated data set is also provided. Theoretical foundations of Threshold Bootstrap is studied and compared with other leading bootstrap sampling techniques for autocorrelated data sets. The performance of TB is reported using M/M/1 queueing model, else the comparison of other resampling techniques of ARMA data set is also reported.

• Journal of the Korea Society of Computer and Information
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• v.20 no.11
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• pp.1-8
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• 2015

Flash memory has advantages in that it is fast access speed, low-power, and low-price. Therefore, they are widely used in electronics industry sectors. However, the flash memory has weak points, which are the limited number of erase operations and non-in-place update problem. To overcome the limited number of erase operations, many wear leveling techniques are studied. They use many tables storing information such as erase count of blocks, hot and cold block indicators, reference count of pages, and so on. These tables occupy some space of main memory for the wear leveling techniques. Accordingly, they are not appropriate for low-power devices limited main memory. In order to resolve it, a wear leveling technique using bit array and Bit Set Threshold (BST) for flash memory. The proposing technique reduces the used space of main memory using a bit array table, which saves the history of block erase operations. To enhance accuracy of cold block information, we use BST, which is calculated by using the number of invalid pages of the blocks in a one-to-many mode, where one bit is related to many blocks. The performance results illustrate that the proposed wear leveling technique improve life time of flash memory to about 6%, compared with previous wear leveling techniques using a bit array table in our experiment.

• The Journal of the Acoustical Society of Korea
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• v.39 no.6
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• pp.585-591
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• 2020

The adaptive transmission techniques are efficient method for underwater acoustic communication to improve the system efficiency by varying transmission parameters according to channel conditions. In this paper, we construct four transmission modes with different data rates using the convolutional codes, which is freely set to size of information bits. On the receiver side, one critical component of adaptive system is to find which mode has best performance. In this paper, we proposed threshold detection algorithm to decide appropriate mode and applied turbo equalization method based on BCJR decoder in order to improve performance. We analyzed the performance of four modes based on threshold detection algorithm through the lake experiment.

• Journal of information and communication convergence engineering
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• v.10 no.4
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• pp.378-383
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• 2012

This paper presents the implementation of an automatic road sign recognizer for an intelligent transport system. In this system, lists of road signs are processed with actions such as line segmentation, single sign segmentation, and storing an artificial sign in the database. The process of taking the video stream and extracting the road sign and storing in the database is called the road sign recognition. This paper presents a study on recognizing traffic sign patterns using a segmentation technique for the efficiency and the speed of the system. The image is converted from one scale to another scale such as RGB to grayscale or grayscale to binary. The images are pre-processed with several image processing techniques, such as threshold techniques, Gaussian filters, Canny edge detection, and the contour technique.

• Korean Journal of Remote Sensing
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• v.25 no.3
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• pp.271-285
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• 2009

Multi-temporal satellite imagery can be changed into a transform image that emphasizes the changed area only through the application of various change detection techniques. From the transform image, an automated change detection model calculates the optimal threshold value for classifying the changed and unchanged areas. However, the model can cause undesirable results when the histogram of the transform image is unbalanced. This is because the model uses a single threshold value in which the sign is either positive or negative and its value is constant (e.g. -1, 1), regardless of the imbalance between changed pixels. This paper proposes an advanced method that can improve accuracy by applying separate threshold values according to the increased or decreased range of the changed pixels. It applies multiple threshold values based on the cumulative producer's and user's accuracies in the automated binary change detection model, and the analyst can automatically extract more accurate optimal threshold values. Multi-temporal IKONOS satellite imagery for the Daejeon area was used to test the proposed method. A total of 16 transformation results were applied to the two study sites, and optimal threshold values were determined using accuracy assessment curves. The experiment showed that the accuracy of most transform images is improved by applying multiple threshold values. The proposed method is expected to be used in various study fields, such as detection of illegal urban building, detection of the damaged area in a disaster, etc.

• Journal of Wetlands Research
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• v.14 no.4
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• pp.571-580
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• 2012

This study is on the purpose of leading Geomorphoclimatic Instantaneous Unit Hydrograph(GcIUH) by using GIS Techniques, and estimating trigger rainfall for predicting flash flood in Seolmacheon catchment, mountain river watershed. This study leads GcIUH by using GIS techniques, calculates NRCS-CN values for effective rainfall rate, and analyzes 2011 main rainfall events using estimated GcIUH. According to the results, the case of Memorial bridge does not exceed the amount of threshold runoff, however, the case of Sabang bridge shows that simulated peak flow, approximately $149.4m^3/s$, exceeds the threshold runoff. To estimate trigger rainfall, this study determines the depth of 50 year-frequency designed flood amount as a threshold water depth, and estimates trigger rainfall of flash flood in consideration of duration. Hereafter, this study will analyze various flood events, estimate the appropriateness of trigger rainfall as well as threshold runoff through this analysis, and develop prototype of Flash Flood Prediction System which is considered the characteristics of mountain river watershed on the basis of this estimation.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2368-2372
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• 2005

We proposed a novel method for object recognition using the Smart tag system in the previous research. We identified the object easily, but could not assure the object pose, because the threshold problem was not solved. So we propose a new method to solve this threshold problem. This method uses a smart tag to decide the threshold by recording color information of the image when the object feature is extracted. This method records the original of the object color information at the smart tag first. And then it records the object image information, the circumstance image information and the sensors information continuously when the object feature is extracted through the experiments. Finally, it estimates the current threshold by recorded information. This method can be applied the threshold to each objects. And it can solve the difficult threshold decision problem easily. To approve the possibility of our method, we implemented our approach by using easy and simple techniques as possible.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.18 no.2
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• pp.279-287
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• 1993

In this paper, double laxity threshold MLT(Minimum Laxity Threshold) algorithm and double queue threshold QLT(Queue Length Threshold) algorithm are proposed as DPS(Dynamic Priority Scheduling) techniques for advanced processing of multiple class traffics. Also, the performance of the proposed algorithms is analyzed by a computer simulation. According to the simulation results, it can be shown that the proposed double laxity threshold ML T algorithm advances the processing performance versus ML T algorithm for 2 or more classes delay sensitive traffics, and that double queue length threshold QL T algorithm provides more efficient performance than QL T for 2 or more classes of non real time traffics.