• KIPS Transactions on Computer and Communication Systems
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• v.11 no.3
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• pp.83-90
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• 2022

Diabetes is a common disease today, and there are also many cases of developing into serious complications called Diabetic Foot Ulcers(DFU). Diagnosis and prevention of DFU in advance is an important task, and this paper proposes the method. Based on existing studies introduced in the paper, it can be seen that foot pressure and temperature information are deeply correlated with DFU. Introduce the process and architecture of SmarTinsole, an IoT device that measures these indicators. Also, the paper describes the preprocessing process for AI-based diagnosis of DFU. Through the comparison of the measured pressure graph and the actual human step distribution, it presents the results that multiple information collected in real-time from SmarTinsole are more efficient and reliable than the previous study.

• Journal of Korea Society of Industrial Information Systems
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• v.27 no.5
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• pp.1-11
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• 2022

With the development of deep learning technology, various research and development are underway to estimate preference rankings through learning, and it is used in various fields such as web search, gene classification, recommendation system, and image search. Approximation algorithms are used to estimate deep learning-based preference ranking, which builds more than k comparison sets on all comparison targets to ensure proper accuracy, and how to build comparison sets affects learning. In this paper, we propose a k-disjoint comparison set generation algorithm and a k-chain comparison set generation algorithm, a novel algorithm for generating paired comparison sets for crowd-sourcing-based deep learning affinity measurements. In particular, the experiment confirmed that the k-chaining algorithm, like the conventional circular generation algorithm, also has a random nature that can support stable preference evaluation while ensuring connectivity between data.

• Communications of Mathematical Education
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• v.38 no.2
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• pp.231-246
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• 2024

In this paper, we present the development and a case study on 'Mathematics & Coding Mobile Contents' tailored for secondary education. These innovative resources aim to alleviate the burden of laborious calculations, enabling students to allocate more time to engage in discussions and visualize complex mathematical concepts. By integrating these contents into the curriculum, students can effectively meet the national standards for achievement in mathematics. They are empowered to develop their mathematical thinking skills through active engagement with the material. When properly integrated into secondary mathematics education, these resources not only facilitate attainment of national curriculum standards but also foster students' confidence in their mathematical abilities. Furthermore, they serve as valuable tools for nurturing both computational and mathematical thinking among students.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.4
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• pp.89-97
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• 2024

The problem of the spokes puzzle(SP), which connects the spokes(edges) required by the wheel axis (hub, vertex) without intersection to form a network in which all the hubs are connected, can be said to be a wasteland of research. For this problem, there is no algorithm that presents a brute-force search or branch-and-bound method that takes exponential time. This paper proposes an algorithm to plot a lattice graph with cross-diagonal lines of m×n for a given SP and to pruning(delete) the surplus edges(spokes). The proposed algorithm is a simple way to select an edge of a hub whose number of edges matches the hub requirement and delete the edge crossing it. If there is no hub with an edge that meets the hub requirement, a strategy was adopted to preferentially delete(pruning) the edge of the hub with the maximum amount of spare. As a result of applying the proposed algorithm to 20 benchmarking experimental data, it was shown that a solution that minimizes the number of trials and errors can be obtained for all problems.

• Journal of the Korean Society of Food Science and Nutrition
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• v.41 no.6
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• pp.816-822
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• 2012

Volatile components of acorn crude starches and gel powder created from them were analyzed by Gas Chromatograph-Ion Mobility Mass Spectrometry (GC-IMS). Crude starches were obtained from acorns harvested in South Korea (KAS), China (CAS), and North Korea (NAS). The principal component analysis (PCA) of each volatile component exhibited a significant contribution of PC 1 showing up to 60.5%. The acorn crude starch from KAS could be distinguished from crude starch from China by PC 1 (p<0.05). However, NAS and CAS could not be segregated statistically by the PC 1 component. PC 2, which exhibited 22.8% contribution, of KAS, also showed a meaningful difference (p<0.05) from those of CAS and NAS, making it possible to distinguish domestic acorn starch from imports.

• The Journal of Korean Association of Computer Education
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• v.20 no.6
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• pp.1-15
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• 2017

The purpose of this study is to design a LMS(Learning Management System) dashboard for instructor feedback support based on learning analytics and to apply a LMS dashboard incorporating such taxonomy which allows an instructor to give a student personalized feedback according to the class content and a student's traits. In the dashboard design phase, usable instructional data were selected from LMS based on feedback taxonomy in terms of learning analytics. Two validity tests were conducted with 8 instructional technologists over 8 years of experience, and were revised accordingly. The final dashboard screen has three parts: A comprehensive analysis screen to provide appropriate feedback based on instructor feedback taxonomy analysis, a summary screen for learner analysis, and a recommended feedback guide screen. Detailed analysis information are provided through other dashboards that are displayed in eight screens: login analysis, learning information confirmation analysis, teaching materials learning analysis, assignment/tests, and posts analysis. All of these dashboards were represented by analysis information and data based on learner analytics through visualization methods including graphs and tables. The implications of educational utilization of the dashboard for instructor feedback support based on learning analytics and the future researches were suggested based on these results.

• Journal of the Korean Geotechnical Society
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• v.31 no.11
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• pp.5-13
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• 2015

For the bearing capacity evaluation, dynamic pile tests instead of static pile tests have been commonly used in embedded piles, which are known to have low noise and low vibration construction method. The objective of this study is to analyze the bearing capacity and penetration behaviors of embedded piles, which are constructed in different ground conditions, by using force and velocity signals obtained in the final blows during construction of embedded piles. For the dynamic pile analyses, the CAse Pile Wave Analysis Program (CAPWAP) and Wave Equation Analysis of Piles (WEAP) have been commonly used. In this study, the CAPWAP and WEAP are used for the analyses of the dynamic pile tests, which are conducted on embedded piles. The input values, output values, and force-velocity graphs of CAPWAP determined by analyzing the measured force-velocity signals are investigated. In addition, similar force-velocity singals are obtained from the WEAP by analyzing the input values of the WEAP. Considering the subsurface investigation results around the pile tips, if the N-value increases exponentially along the depth, toe quake value should be small, and therefore large bearing capacity is identified. On the contrary, if the N-value increases linearly, the bearing capacity is small because of large toe quake value. Furthermore, the stiffness of hammer cushion and pile cushion, which is difficult to find correct values, is recommended lower than 500 kN/mm. This study demonstrates that the results of WEAP may be similar to those of CAPWAP and the WEAP can be used to estimate the bearing capacity of embedded piles.

• Resources Recycling
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• v.27 no.1
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• pp.84-91
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• 2018

In this study, a novel soft information based most probable classification scheme is proposed for sorting recyclable metal alloys with laser induced breakdown spectroscopy (LIBS). Regression analysis with LIBS captured spectrums for estimating concentrations of common elements can be efficient for classifying unknown arbitrary metal alloys, even when that particular alloy is not included for training. Therefore, partial least square regression (PLSR) is employed in the proposed scheme, where spectrums of the certified reference materials (CRMs) are used for training. With the PLSR model, the concentrations of the test spectrum are estimated independently and are compared to those of CRMs for finding out the most probable class. Then, joint soft information can be obtained by assuming multi-variate normal (MVN) distribution, which enables to account the probability measure or a prior information and improves classification performance. For evaluating the proposed schemes, MVN soft information is evaluated based on PLSR of LIBS captured spectrums of 9 metal CRMs, and tested for classifying unknown metal alloys. Furthermore, the likelihood is evaluated with the radar chart to effectively visualize and search the most probable class among the candidates. By the leave-one-out cross validation tests, the proposed scheme is not only showing improved classification accuracies but also helpful for adaptive post-processing to correct the mis-classifications.

• Journal of Digital Convergence
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• v.15 no.10
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• pp.525-535
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• 2017

The purpose of this study aims to examine consumer perception and current status of water park. The Naver and Daum were used for data collection channels and the keyword 'water park' was used for data retrieval. The data analysis period was limited to the study period from January 1, 2015 to December 31, 2016 for a total of two years. First, as a result of the frequency analysis, hidden cameras, Lotte water park, arrests, suspects, gimhae were in top 5 in 2015, Lotte water park, swimming, summer, opening, admission ticket were in top 5 in 2016. Second, as a result of the connection degree central analysis, hidden camera, arrest, suspect, female, shower room were in top 5 in 2015, swimming, Lotte water park, summer and One Mount, admission ticket were in top 5 in 2016. Third, as a result of the N-GRAM network graph, the water park/hidden camera, the hidden camera/hidden camera, the suspect/arrest, the Gimhae/Lotte water park, water park/suspect were in top 5 in 2015, and One Mount/water park, Gimhae/Lotte water park, water park/admission ticket, water park/water park, water park/opening were in top 5 in 2016. Fourth, as a result of the CONCOR analysis, three groups in 2015 and two groups in 2016 were formed.

• The KIPS Transactions:PartB
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• v.11B no.3
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• pp.281-288
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• 2004

In order to extract and analyze complex features of the behavior of animals in response to external stimuli such as toxic chemicals, we implemented an adaptive computational method to characterize changes in the behavior of chironomids in response to treatment with the insecticide, diazinon. In this paper, we propose an energy minimization model to extract the features of response behavior of chironomids under toxic treatment, which is applied on the image of velocity vectors. It is based on the improved active contour model and the variations of the energy functional, which are produced by the evolving active contour. The movement tracks of individual chironomid larvae were continuously measured in 0.25 second intervals during the survey period of 4 days before and after the treatment. Velocity on each sample track at 0.25 second intervals was collected in 15-20 minute periods and was subsequently checked to effectively reveal behavioral states of the specimens tested. Active contour was formed around each collection of velocities to gradually evolve to find the optimal boundaries of velocity collections through processes of energy minimization. The active contour which is improved by T. Chan and L. Vese is used in this paper. The energy minimization model effectively revealed characteristic patterns of behavior for the treatment versus no treatment, and identified changes in behavioral states .is the time progressed.