• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.6
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• pp.673-679
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• 2014

The important requirements of designing a pattern classifier are high throughput and low memory requirements, and low cost hardware implementation. A pattern classifier by using Multiple Attractor Cellular Automata(MACA) proposed by Maji et al. reduced the complexity of the classification algorithm from $O(n^3)$ to O(n) by using Dependency Vector(DV) and Dependency String(DS). In this paper, we generate a pattern classifier using LFSR to improve efficiently the space and time complexity and we propose a method for finding DV by using the 0-basic path. Also we investigate DV and the attractor of the generated pattern classifier. We can divide an n-bit DS by m number of $DV_i$ s and generate various pattern classifiers.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.2
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• pp.253-266
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• 2023

The Null Pointer Dereference vulnerability is a significant vulnerability that can cause severe attacks such as denial-of-service. Previous research has proposed methods for detecting vulnerabilities, but large and complex programs pose a challenge to their efficiency. In this paper, we present a lightweight tool for detecting specific functions in large binaryprograms through symbolizing variables and emulating program execution. The tool detects vulnerabilities through data dependency analysis and heuristics in each execution path. While our tool had an 8% higher false positive rate than the bap_toolkit, it detected all existing vulnerabilities in our dataset.

• Journal of The Korean Association For Science Education
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• v.26 no.3
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• pp.406-414
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• 2006

This study investigated 7th grade students' context dependency on explanations about propagating path of light in three different contextual problems: observation of an object, observation of an object's image in a mirror, and observation of one's own face reflection in a mirror. Researchers examined student response in each context through interviews. The students were classified into four groups according to their explanations for the three different contexts. Each group was redivided into two or three subgroups in accordance with their conceptual features. After that, researchers investigated the characteristics of each subgroup. Main findings of the study indicated that (1) group 1 students' conceptions differed in each context; (2) group 2 students showed scientific conceptions in C1 context but in C2 context they showed visual ray conceptions or image misconceptions; (3) group 3 students did not show scientific conceptions in C3 context by strong misconceptions about one's own face reflection in the mirror. Also, this paper discussed the educational implications of the results.

• Journal of Convergence for Information Technology
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• v.7 no.4
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• pp.139-149
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• 2017

This study tries to examine the effect of positive and negative parents' attitudes on adolescents' smartphone dependency, and prove the meditating effect of poor attachment between the two variables in the times of convergence. For the study, the data from the Korean Children and Youth Panel Survey were analyzed by utilizing the path analysis, the data from 1,971. The results are as follows: First, positive and negative parents' attitudes influenced adolescents' poor attachment. Second, positive and negative parents' attitudes had a effect on adolescents' smartphone dependency. Third, parents' attttudes directly influenced adolescents' smart phone dependency and its' effect was indirectly mediated by the subjects's poor attachment.

• Proceedings of the KOR-KST Conference
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• 2000.02a
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• pp.25-47
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• 2000

In route guidance systems fastest-path routing has typically been adopted because of its simplicity. However, empirical studies on route choice behavior have shown that drivers use numerous criteria in choosing a route. The objective of this study is to develop computationally efficient algorithms for identifying a manageable subset of the nondominated (i.e. Pareto optimal) paths for real-time vehicle routing which reflect the drivers' preferences and route choice behaviors. We propose two pruning algorithms that reduce the search area based on a context-dependent linear utility function and thus reduce the computation time. The basic notion of the proposed approach is that ⅰ) enumerating all nondominated paths is computationally too expensive, ⅱ) obtaining a stable mathematical representation of the drivers' utility function is theoretically difficult and impractical, and ⅲ) obtaining optimal path given a nonlinear utility function is a NP-hard problem. Consequently, a heuristic two-stage strategy which identifies multiple routes and then select the near-optimal path may be effective and practical. As the first stage, we utilize the relaxation based pruning technique based on an entropy model to recognize and discard most of the nondominated paths that do not reflect the drivers' preference and/or the context-dependency of the preference. In addition, to make sure that paths identified are dissimilar in terms of links used, the number of shared links between routes is limited. We test the proposed algorithms in a large real-life traffic network and show that the algorithms reduce CPU time significantly compared with conventional multi-criteria shortest path algorithms while the attributes of the routes identified reflect drivers' preferences and generic route choice behaviors well.

• Structural Engineering and Mechanics
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• v.39 no.6
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• pp.877-893
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• 2011

Response spectra of earthquake ground motions are important in the earthquake-resistant design and reliability analysis of structures. The formulation of the response spectrum in the frequency domain efficiently computes and evaluates the stochastic response spectrum. The frequency information of the excitation can be described using different functional forms. The shapes of the calculated response spectra of the excitation show strong magnitude and site dependency, but weak distance dependency. In this paper, to compare the effect of the earthquake ground motion variables, the contribution of these sources of variability to the response spectrum's uncertainty is calculated by using a stochastic analysis. The analytical results show that earthquake source factors and soil condition variables are the main sources of uncertainty in the response spectra, while path variables, such as distance, anelastic attenuation and upper crust attenuation, have relatively little effect. The presented formulation of dynamic structural response in frequency domain based only on the frequency information of the excitation can provide an important basis for the structural analysis in some location that lacks strong motion records.

• Proceedings of the KSR Conference
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• 2008.11b
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• pp.331-336
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• 2008

Magnetic path direction in the back-iron of a linear induction motor(LIM) is perpendicular to that of the lift-magnet of the MAGLEV which is recently developing in KOREA. In general the back-iron is isolated magnetically in conventional rail in order to eliminate the thrust dependency of the LIM on the lift force. However the magnetic isolation causes some increase in construction and management cost. So a unit-type rail system is considered, which the magnetic circuit of the back-iron is sharing that of the lift-magnet. In this paper 3-dimensional analysis for the lift-magnet is carried out using finite element method. As a result, a new shape of the unit-type rail is presented to reduce the magnetic dependency between thrust force and lift force. Also the distribution of magnetic flux density vectors and current-lift force characteristics are presented.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.9
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• pp.4665-4683
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• 2019

Previous methods build image annotation model by leveraging three basic dependencies: relations between image and label (image/label), between images (image/image) and between labels (label/label). Even though plenty of researches show that multiple dependencies can work jointly to improve annotation performance, different dependencies actually do not "work jointly" in their diagram, whose performance is largely depending on the result predicted by image/label section. To address this problem, we propose the adaptive attention annotation model (AAAM) to associate these dependencies with the prediction path, which is composed of a series of labels (tags) in the order they are detected. In particular, we optimize the prediction path by detecting the relevant labels from the easy-to-detect to the hard-to-detect, which are found using Binary Cross-Entropy (BCE) and Triplet Margin (TM) losses, respectively. Besides, in order to capture the inforamtion of each label, instead of explicitly extracting regional featutres, we propose the self-attention machanism to implicitly enhance the relevant region and restrain those irrelevant. To validate the effective of the model, we conduct experiments on three well-known public datasets, COCO 2014, IAPR TC-12 and NUSWIDE, and achieve better performance than the state-of-the-art methods.

• Journal of Digital Convergence
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• v.16 no.9
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• pp.477-487
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• 2018

The purpose of this study is to examine the effect of peer attachment on life satisfaction of adolescents and to verify the mediating effects of career identity and smart-phone dependency in the process. For this purpose, the data from the sixth year Korean Child and Youth Panel Survey(2015) on 1,823 middle school students were analyzed by hierarchical regression analysis and path analysis among variables. The results of the analysis are as follows. First, peer attachment of adolescents had a significantly positive effect on their life satisfaction. Second, adolescents' career identity had a partial mediating effect on the relationship between peer attachment and life satisfaction. Third, the effect of peer attachment on life satisfaction of adolescents was partly mediated by their smart-phone dependency. On the basis of above findings, the practical programs to enhance career-identity and life satisfaction and reduce smart-phone dependency were presented.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.3
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• pp.2109-2116
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• 2015

This study aimed to identify the influencing factors on nicotine dependency of middle school smokers and to provide the basic data for the effective smoking cessation program. Data were collected from May 3 to July 26 in 2013 by self-reported questionnaires. The subjects of this study were 202 middle school smokers in D city. For data analysis, SPSS 18.0 and AMOS 18.0 was used to calculate Percentage, mean, Standard deviation, ANOVA, Scheffe test, Pearson's correlation coefficient and Path analysis. The results showed that smoking reinforced factors, social environment factors, self-efficacy and impulsivity were significantly influenced on the nicotine dependency directly and indirectly. Therefore, it is necessary to include intervention of smoking reinforced factors, social environment factors, self-efficacy and impulsivity to develop smoking cessation program for smoking in middle school students.