• Journal of Korea Multimedia Society
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• v.25 no.4
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• pp.559-567
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• 2022

The optimal shipping location is determined by measuring the volume and weights of cargo shipped to non-standard cargo carriers. Currently, workers manually measure cargo volume, but automate it to improve work inefficiency. In this paper, we proposed the method of a real-time volume calculation using LiDar sensor for automating cargo measurement of non-standard cargo. For this purpose, we utilized the statistical techniques for data preprocessing and volume calculation, also used Voxel Grid filter to light weighted of data which are appropriate in real-time calculation. We implemented the function of Normal vectors and Triangle Mesh to generate surfaces and Alpha Shapes algorithms to process 3D modeling.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.380-386
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• 1998

In this paper we introduce the concept of fuzzy integrals for set-valued mappings, which is an extension of fuzzy integrals for single-valued functions defined by Sugeno. And we give some properties including convergence theorems on fuzzy integrals for set-valued mappings.

• Journal of the Korean Society of Industry Convergence
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• v.23 no.2_2
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• pp.289-299
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• 2020

The composition of convergence cross-section of the material is a technique that provides reasonable design and construction of structures. It is frequently used in medium-sized bridges and architectural structures. However, the structural behavioral spare capacity enhancement of the structure by the application of the convergence cross-section is still limited by the expandability due to the limiting state of each material. In order to overcome these limitations, this study reasonably analyzed the construction stages before and after the convergence cross-section constructed and developed a technique for forming multi-point boundary conditions using struts, which are compression members. Based on the existing cases, a reasonable construction step for forming the material composite section of the entire structural system of the structure was derived, and a numerical analysis model for a specific part was constructed to analyze the behavior of the strut application. As a result of this study, the effect of reducing the sectional force of 7.40% in beam-column joint and 6.31% in the center of girder was derived, and the deflection, which is a measure of the serviceability of the structure, improved by 54.41% from the installation and dismantling of strut members at each construction stage.

• Bulletin of the Korean Mathematical Society
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• v.48 no.4
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• pp.779-789
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• 2011

In this paper we study the Banach space $L^1$(G) of real valued measurable functions which are integrable with respect to a vector measure G in the sense of D. R. Lewis. First, we investigate conditions for a scalarly integrable function f which guarantee $f{\in}L^1$(G). Next, we give a sufficient condition for a sequence to converge in $L^1$(G). Moreover, for two vector measures F and G with values in the same Banach space, when F can be written as the integral of a function $f{\in}L^1$(G), we show that certain properties of G are inherited to F; for instance, relative compactness or convexity of the range of vector measure. Finally, we give some examples of $L^1$(G) related to the approximation property.

• International journal of advanced smart convergence
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• v.8 no.2
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• pp.94-101
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• 2019

Building a stable knowledge base is an important issue in the application of knowledge engineering. In this paper, we present an algorithm for detecting and locating discrepancies in the line of the reasoning process especially when discrepancies occur on belief values. This includes backtracking the rule firing from a goal node of the rule network. Retracting a belief function allows the current belief state to move back to another belief state without the rule firing. It also gives an estimate, called contribution measure, of how much the rule has an impact on the current belief state. Examining the measure leads the expert to locate the possible cause of problem in the rule. For non-monotonic reasoning, the belief retraction method moves the belief state back to the previous state. A tracing algorithm is presented to identify and locate the cause of problem. This also gives repair suggestions for rule refinement.

• Journal of the Korea Convergence Society
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• v.6 no.5
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• pp.257-274
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• 2015

The purpose of the current study was to validate Fetzer Institute & National Institute on Aging Working Group[NIA](1999)'s Brief-Multidimensional Measure of Religiousness/Spirituality Scale (BMMRS) in Korean adults. The Korean version of BMMRS, Spiritual Well-Being Scale(SWS), Korean Sprituality Scale(KSS), Penn State Worry Questionnaire(PSWQ), and Intolerance of uncertainty Scale(IUS) were administered to the 286 students and community samples. A principle axis factoring analysis with direct oblimin rotation and Kaiser normalization identified a six-factor solution accounting for 66.24% of the variance in scores, labeled as: positive spiritual experience, negative spiritual experience, forgiveness, religious practices, negative congregational support, and positive congregational support. Confirmatory factor analysis results showed that 6 factor model of BMMRS have a good fitness. Also, the internal consistency(.64~.97) and the test-retest reliablity was adequate.(.72~.88) Korean version of BMMRS has adequate psychometric characteristics so it can be used to verify the effects of various compassion-related psychotherapeutic approaches.

• Journal of the Institute of Convergence Signal Processing
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• v.20 no.3
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• pp.138-144
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• 2019

In a modern society, people are concerned seriously about their travel destinations depending on time, economic problem. In this paper, we propose an non-hierarchical clustering based hybrid recommendation using context knowledge. The proposed method is personalized way of recommended knowledge about preferred travel places according to the user's location, place, and weather. Based on 14 attributes from the data collected through the survey, users with similar characteristics are grouped using a non-hierarchical clustering based hybrid recommendation. This makes more accurate recommendation by weighting implicit and explicit data. The users can be recommended a preferred travel destination without spending unnecessary time. The performance evaluation uses accuracy, recall, F-measure. The evaluation result was shown 0.636 accuracy, 0.723 recall, and 0.676 F-measure.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.4
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• pp.1824-1845
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• 2016

The GMM is a conventional approach which has been recently applied in many face recognition studies. However, the question about how to deal with illumination changes while ensuring high performance is still a challenge, especially with real-world databases. In this paper, we propose a Visual Observation Confidence (VOC) measure for robust face recognition for illumination changes. Our VOC value is a combined confidence value of three measurements: Flatness Measure (FM), Centrality Measure (CM), and Illumination Normality Measure (IM). While FM measures the discrimination ability of one face, IM represents the degree of illumination impact on that face. In addition, we introduce CM as a centrality measure to help FM to reduce some of the errors from unnecessary areas such as the hair, neck or background. The VOC then accompanies the feature vectors in the EM process to estimate the optimal models by modified-GMM training. In the experiments, we introduce a real-world database, called KoFace, besides applying some public databases such as the Yale and the ORL database. The KoFace database is composed of 106 face subjects under diverse illumination effects including shadows and highlights. The results show that our proposed approach gives a higher Face Recognition Rate (FRR) than the GMM baseline for indoor and outdoor datasets in the real-world KoFace database (94% and 85%, respectively) and in ORL, Yale databases (97% and 100% respectively).

• Journal of the Institute of Convergence Signal Processing
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• v.20 no.4
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• pp.193-198
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• 2019

The wide spread of genuine and fake information on internet has lead to various studies on text analysis. Copying and pasting others' work without acknowledgement, research results manipulation without proof has been trending for a while in the era of data science. Various tools have been developed to reduce, combat and possibly eradicate plagiarism in various research fields. Text similarity measurements can be manually done by using both parametric and non parametric methods of which this study implements cosine similarity and Pearson correlation as parametric while Spearman correlation as non parametric. Cosine similarity and Pearson correlation metrics have achieved highest coefficients of similarity while Spearman shown low similarity coefficients. We recommend the use of non parametric methods in measuring text similarity due to their non normality assumption as opposed to the parametric methods which relies on normality assumptions and biasness.

• Proceedings of the Korean Geotechical Society Conference
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• 2005.03a
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• pp.1361-1368
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• 2005

In this paper, the theoretical method of measuring the tunnel convergence and underground displacement, the objective indices of assessing safety for tunnel construction, using the fiber optic sensor is studied by developing the program to automatically measure them. The model test of Con'c beam is conducted to evaluate reliability of the fiber optic sensor. Furthermore, using the RS232 communication protocol as well as Visual C# and Visual C++, the programming tools, the program was developed to detect automatically the measured value of the fiber optic sensor, calculate the tunnel convergence and underground displacement, predict the deformed shape of the tunnel, and evaluate loosening zone due to the tunnel excavation.