• Title/Summary/Keyword: data processing technique

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Finite Element Method Modeling for Individual Malocclusions: Development and Application of the Basic Algorithm (유한요소법을 이용한 환자별 교정시스템 구축의 기초 알고리즘 개발과 적용)

  • Shin, Jung-Woog;Nahm, Dong-Seok;Kim, Tae-Woo;Lee, Sung Jae
    • The korean journal of orthodontics
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    • v.27 no.5 s.64
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    • pp.815-824
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    • 1997
  • The purpose of this study is to develop the basic algorithm for the finite element method modeling of individual malocclusions. Usually, a great deal of time is spent in preprocessing. To reduce the time required, we developed a standardized procedure for measuring the position of each tooth and a program to automatically preprocess. The following procedures were carried to complete this study. 1. Twenty-eight teeth morphologies were constructed three-dimensionally for the finite element analysis and saved as separate files. 2. Standard brackets were attached so that the FA points coincide with the center of the brackets. 3. The study model of a patient was made. 4. Using the study model, the crown inclination, angulation, and the vertical distance from the tip of a tooth was measured by using specially designed tools. 5. The arch form was determined from a picture of the model with an image processing technique. 6. The measured data were input as a rotational matrix. 7. The program provides an output file containing the necessary information about the three-dimensional position of teeth, which is applicable to several finite element programs commonly used. The program for a basic algorithm was made with Turbo-C and the subsequent outfile was applied to ANSYS. This standardized model measuring procedure and the program reduce the time required, especially for preprocessing and can be applied to other malocclusions easily.

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An Analytical Approach Using Topic Mining for Improving the Service Quality of Hotels (호텔 산업의 서비스 품질 향상을 위한 토픽 마이닝 기반 분석 방법)

  • Moon, Hyun Sil;Sung, David;Kim, Jae Kyeong
    • Journal of Intelligence and Information Systems
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    • v.25 no.1
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    • pp.21-41
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    • 2019
  • Thanks to the rapid development of information technologies, the data available on Internet have grown rapidly. In this era of big data, many studies have attempted to offer insights and express the effects of data analysis. In the tourism and hospitality industry, many firms and studies in the era of big data have paid attention to online reviews on social media because of their large influence over customers. As tourism is an information-intensive industry, the effect of these information networks on social media platforms is more remarkable compared to any other types of media. However, there are some limitations to the improvements in service quality that can be made based on opinions on social media platforms. Users on social media platforms represent their opinions as text, images, and so on. Raw data sets from these reviews are unstructured. Moreover, these data sets are too big to extract new information and hidden knowledge by human competences. To use them for business intelligence and analytics applications, proper big data techniques like Natural Language Processing and data mining techniques are needed. This study suggests an analytical approach to directly yield insights from these reviews to improve the service quality of hotels. Our proposed approach consists of topic mining to extract topics contained in the reviews and the decision tree modeling to explain the relationship between topics and ratings. Topic mining refers to a method for finding a group of words from a collection of documents that represents a document. Among several topic mining methods, we adopted the Latent Dirichlet Allocation algorithm, which is considered as the most universal algorithm. However, LDA is not enough to find insights that can improve service quality because it cannot find the relationship between topics and ratings. To overcome this limitation, we also use the Classification and Regression Tree method, which is a kind of decision tree technique. Through the CART method, we can find what topics are related to positive or negative ratings of a hotel and visualize the results. Therefore, this study aims to investigate the representation of an analytical approach for the improvement of hotel service quality from unstructured review data sets. Through experiments for four hotels in Hong Kong, we can find the strengths and weaknesses of services for each hotel and suggest improvements to aid in customer satisfaction. Especially from positive reviews, we find what these hotels should maintain for service quality. For example, compared with the other hotels, a hotel has a good location and room condition which are extracted from positive reviews for it. In contrast, we also find what they should modify in their services from negative reviews. For example, a hotel should improve room condition related to soundproof. These results mean that our approach is useful in finding some insights for the service quality of hotels. That is, from the enormous size of review data, our approach can provide practical suggestions for hotel managers to improve their service quality. In the past, studies for improving service quality relied on surveys or interviews of customers. However, these methods are often costly and time consuming and the results may be biased by biased sampling or untrustworthy answers. The proposed approach directly obtains honest feedback from customers' online reviews and draws some insights through a type of big data analysis. So it will be a more useful tool to overcome the limitations of surveys or interviews. Moreover, our approach easily obtains the service quality information of other hotels or services in the tourism industry because it needs only open online reviews and ratings as input data. Furthermore, the performance of our approach will be better if other structured and unstructured data sources are added.

Analysis Trap and Device Characteristic of Silicon-Al2O3-Nitride-Oxide-Silicon Memory Cell Transistors using Charge Pumping Method (Charge Pumping Method를 이용한 Silicon-Al2O3-Nitride-Oxide-Silicon Flash Memory Cell Transistor의 트랩과 소자)

  • Park, Sung-Soo;Choi, Won-Ho;Han, In-Shik;Na, Min-Gi;Lee, Ga-Won
    • Journal of the Institute of Electronics Engineers of Korea SD
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    • v.45 no.7
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    • pp.37-43
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    • 2008
  • In this paper, the dependence of electrical characteristics of Silicon-$Al_2O_3$-Nitride-Oxide-Silicon (SANOS) memory cell transistors and program/erase (P/E) speed, reliability of memory device on interface trap between Si substrate and tunneling oxide and bulk trap in nitride layer were investigated using charge pumping method which has advantage of simple and versatile technique. We analyzed different SANOS memory devices that were fabricated by the identical processing in a single lot except the deposition method of the charge trapping layer, nitride. In the case of P/E speed, it was shown that P/E speed is slower in the SANOS cell transistors with larger capture cross section and interface trap density by charge blocking effect, which is confirmed by simulation results. However, the data retention characteristics show much less dependence on interface trap. The data retention was deteriorated as increasing P/E cycling number but not coincides with interface trap increasing tendency. This result once again confirmed that interface trap independence on data retention. And the result on different program method shows that HCI program method more degraded by locally trapping. So, we know as a result of experiment that analysis the SANOS Flash memory characteristic using charge pumping method reflect the device performance related to interface and bulk trap.

Breeding of new variety Pleurotus pulmonarius using protoplast fusion technique (원형질체융합 기법을 이용한 산느타리 계통육성)

  • Gwon, Hee-Min;Lee, Yun-Hae;Kim, Jeong-Han;Baek, Il-Sun;Kang, Hee-Wan;Choi, Jong-In
    • Journal of Mushroom
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    • v.19 no.3
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    • pp.166-175
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    • 2021
  • In this study, monokaryons of "Heukari" (Pleurotus ostreatus) and "Hosan" (Pleurotus pulmonarius) were separated to remove the cell wall, and a cross-species protoplast fusion was developed through chemical treatment with polyethylene glycol. The protoplast-fused PF160306 and PF160313 strains have a culture period of 10 and 2 days shorter than that of the "Heuktari" and "Hosan" cultivars, respectively. Furthermore, the growth of the strains was faster than that of the existing cultivars. The yield was 135.9 g per bottle, which was approximately 8% higher than that of the commercially available "Hosan" cultivar; however, it was not statistically significant. A growth survey was conducted after treatment at five temperatures (15, 18, 21, 23, and 25℃). The growth of the strains accelerated with the increase in temperature. However, at 21℃, the yellow color of pileus was the brightest. Band pattern, assessed using URP Primer 7, was similar to that of the "Hosan" cultivar. The DPPH radical scavenging capacity and polyphenol content were 62.5% and 43.5 mg/mL, respectively, for "Sunjung" and 65.7% and 49.9 mg/mL, respectively, for PF160313. Furthermore, the antihypertensive activities of the "Sunjung" cultivar and PF160313 were similarly high at 74% and 75%, respectively. In conclusion, cross-species hybridization via the protoplast fusion technique can be used for obtaining primary data for mushroom breeding to develop new varieties. In addition, the protoplast fusion technique might aid in expanding the market for yellow mushrooms.

Construction of Event Networks from Large News Data Using Text Mining Techniques (텍스트 마이닝 기법을 적용한 뉴스 데이터에서의 사건 네트워크 구축)

  • Lee, Minchul;Kim, Hea-Jin
    • Journal of Intelligence and Information Systems
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    • v.24 no.1
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    • pp.183-203
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    • 2018
  • News articles are the most suitable medium for examining the events occurring at home and abroad. Especially, as the development of information and communication technology has brought various kinds of online news media, the news about the events occurring in society has increased greatly. So automatically summarizing key events from massive amounts of news data will help users to look at many of the events at a glance. In addition, if we build and provide an event network based on the relevance of events, it will be able to greatly help the reader in understanding the current events. In this study, we propose a method for extracting event networks from large news text data. To this end, we first collected Korean political and social articles from March 2016 to March 2017, and integrated the synonyms by leaving only meaningful words through preprocessing using NPMI and Word2Vec. Latent Dirichlet allocation (LDA) topic modeling was used to calculate the subject distribution by date and to find the peak of the subject distribution and to detect the event. A total of 32 topics were extracted from the topic modeling, and the point of occurrence of the event was deduced by looking at the point at which each subject distribution surged. As a result, a total of 85 events were detected, but the final 16 events were filtered and presented using the Gaussian smoothing technique. We also calculated the relevance score between events detected to construct the event network. Using the cosine coefficient between the co-occurred events, we calculated the relevance between the events and connected the events to construct the event network. Finally, we set up the event network by setting each event to each vertex and the relevance score between events to the vertices connecting the vertices. The event network constructed in our methods helped us to sort out major events in the political and social fields in Korea that occurred in the last one year in chronological order and at the same time identify which events are related to certain events. Our approach differs from existing event detection methods in that LDA topic modeling makes it possible to easily analyze large amounts of data and to identify the relevance of events that were difficult to detect in existing event detection. We applied various text mining techniques and Word2vec technique in the text preprocessing to improve the accuracy of the extraction of proper nouns and synthetic nouns, which have been difficult in analyzing existing Korean texts, can be found. In this study, the detection and network configuration techniques of the event have the following advantages in practical application. First, LDA topic modeling, which is unsupervised learning, can easily analyze subject and topic words and distribution from huge amount of data. Also, by using the date information of the collected news articles, it is possible to express the distribution by topic in a time series. Second, we can find out the connection of events in the form of present and summarized form by calculating relevance score and constructing event network by using simultaneous occurrence of topics that are difficult to grasp in existing event detection. It can be seen from the fact that the inter-event relevance-based event network proposed in this study was actually constructed in order of occurrence time. It is also possible to identify what happened as a starting point for a series of events through the event network. The limitation of this study is that the characteristics of LDA topic modeling have different results according to the initial parameters and the number of subjects, and the subject and event name of the analysis result should be given by the subjective judgment of the researcher. Also, since each topic is assumed to be exclusive and independent, it does not take into account the relevance between themes. Subsequent studies need to calculate the relevance between events that are not covered in this study or those that belong to the same subject.

Study of Feature Based Algorithm Performance Comparison for Image Matching between Virtual Texture Image and Real Image (가상 텍스쳐 영상과 실촬영 영상간 매칭을 위한 특징점 기반 알고리즘 성능 비교 연구)

  • Lee, Yoo Jin;Rhee, Sooahm
    • Korean Journal of Remote Sensing
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    • v.38 no.6_1
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    • pp.1057-1068
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    • 2022
  • This paper compares the combination performance of feature point-based matching algorithms as a study to confirm the matching possibility between image taken by a user and a virtual texture image with the goal of developing mobile-based real-time image positioning technology. The feature based matching algorithm includes process of extracting features, calculating descriptors, matching features from both images, and finally eliminating mismatched features. At this time, for matching algorithm combination, we combined the process of extracting features and the process of calculating descriptors in the same or different matching algorithm respectively. V-World 3D desktop was used for the virtual indoor texture image. Currently, V-World 3D desktop is reinforced with details such as vertical and horizontal protrusions and dents. In addition, levels with real image textures. Using this, we constructed dataset with virtual indoor texture data as a reference image, and real image shooting at the same location as a target image. After constructing dataset, matching success rate and matching processing time were measured, and based on this, matching algorithm combination was determined for matching real image with virtual image. In this study, based on the characteristics of each matching technique, the matching algorithm was combined and applied to the constructed dataset to confirm the applicability, and performance comparison was also performed when the rotation was additionally considered. As a result of study, it was confirmed that the combination of Scale Invariant Feature Transform (SIFT)'s feature and descriptor detection had the highest matching success rate, but matching processing time was longest. And in the case of Features from Accelerated Segment Test (FAST)'s feature detector and Oriented FAST and Rotated BRIEF (ORB)'s descriptor calculation, the matching success rate was similar to that of SIFT-SIFT combination, while matching processing time was short. Furthermore, in case of FAST-ORB, it was confirmed that the matching performance was superior even when 10° rotation was applied to the dataset. Therefore, it was confirmed that the matching algorithm of FAST-ORB combination could be suitable for matching between virtual texture image and real image.

Speed-up Techniques for High-Resolution Grid Data Processing in the Early Warning System for Agrometeorological Disaster (농업기상재해 조기경보시스템에서의 고해상도 격자형 자료의 처리 속도 향상 기법)

  • Park, J.H.;Shin, Y.S.;Kim, S.K.;Kang, W.S.;Han, Y.K.;Kim, J.H.;Kim, D.J.;Kim, S.O.;Shim, K.M.;Park, E.W.
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.19 no.3
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    • pp.153-163
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    • 2017
  • The objective of this study is to enhance the model's speed of estimating weather variables (e.g., minimum/maximum temperature, sunshine hour, PRISM (Parameter-elevation Regression on Independent Slopes Model) based precipitation), which are applied to the Agrometeorological Early Warning System (http://www.agmet.kr). The current process of weather estimation is operated on high-performance multi-core CPUs that have 8 physical cores and 16 logical threads. Nonetheless, the server is not even dedicated to the handling of a single county, indicating that very high overhead is involved in calculating the 10 counties of the Seomjin River Basin. In order to reduce such overhead, several cache and parallelization techniques were used to measure the performance and to check the applicability. Results are as follows: (1) for simple calculations such as Growing Degree Days accumulation, the time required for Input and Output (I/O) is significantly greater than that for calculation, suggesting the need of a technique which reduces disk I/O bottlenecks; (2) when there are many I/O, it is advantageous to distribute them on several servers. However, each server must have a cache for input data so that it does not compete for the same resource; and (3) GPU-based parallel processing method is most suitable for models such as PRISM with large computation loads.

An Efficient Core-Based Multicast Tree using Weighted Clustering in Ad-hoc Networks (애드혹 네트워크에서 가중치 클러스터링을 이용한 효율적인 코어-기반 멀티캐스트 트리)

  • Park, Yang-Jae;Han, Seung-Jin;Lee, Jung-Hyun
    • The KIPS Transactions:PartC
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    • v.10C no.3
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    • pp.377-386
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    • 2003
  • This study suggested a technique to maintain an efficient core-based multicast tree using weighted clustering factors in mobile Ad-hoc networks. The biggest problem with the core-based multicast tree routing is to decide the position of core node. The distance of data transmission varies depending on the position of core node. The overhead's effect on the entire network is great according to the recomposition of the multicast tree due to the movement of core node, clustering is used. A core node from cluster head nodes on the multicast tree within core area whose weighted factor is the least is chosen as the head core node. Way that compose multicast tree by weighted clustering factors thus and propose keeping could know that transmission distance and control overhead according to position andmobility of core node improve than existent multicast way, and when select core node, mobility is less, and is near in center of network multicast tree could verification by simulation stabilizing that transmission distance is short.

Biomimetic Gyroscope Integrated with Actuation Parts of a Robot Inspired by Insect Halteres (평형곤을 모사한 생체모방형 구동부 일체형 각속도 센서)

  • Jeong, Mingi;Kim, Jisu;Jang, Seohyeong;Lee, Tae-Jae;Shim, Hyungbo;Ko, Hyoungho;Cho, Kyu-Jin;Cho, Dong-Il Dan
    • Journal of Institute of Control, Robotics and Systems
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    • v.22 no.9
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    • pp.705-709
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    • 2016
  • Micro-electro-mechanical systems (MEMS) gyroscopes are widely used in various robot applications. However, these conventional gyroscopes need to vibrate the proof mass using a built-in actuator at a fixed resonance frequency to sense the Coriolis force. When a robot is not moving, the meaningless vibration of the gyroscope wastes power. In addition, this continuous vibration makes the sensor vulnerable to external sound waves with a frequency close to the proof-mass resonance frequency. In this paper, a feasibility study of a new type of gyroscope inspired by insect halteres is presented. In dipterous insects, halteres are a biological gyroscope that measures the Coriolis force. Wing muscles and halteres are mechanically linked, and the halteres oscillate simultaneously with wing beats. The vibrating haltere experiences the Coriolis force if the insect is going through a rotational motion. Inspired by this haltere structure, a gyroscope using a thin mast integrated with a robot actuation mechanism is proposed. The mast vibrates only when the robot is moving without requiring a separate actuator. The Coriolis force of the mast can be measured with an accelerometer installed at the tip of the mast. However, the signal from the accelerometer has multiple frequency components and also can be highly corrupted with noise, such that raw data are not meaningful. This paper also presents a suitable signal processing technique using the amplitude modulation method. The feasibility of the proposed haltere-inspired gyroscope is also experimentally evaluated.

Evaluation of Marginal and Internal Gap of Cobalt-Chromium Sintering Metal Coping Fabricated by Dental CAD/CAM System (치과 CAD/CAM 시스템으로 제작한 코발트-크롬 소결 금속 코핑의 변연 및 내면 적합도 평가)

  • Kim, Dong-Yeon;Sin, Chun-Ho;Jung, Il-Do;Kim, Ji-Hwan;Kim, Woong-Chul
    • Journal of dental hygiene science
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    • v.15 no.5
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    • pp.536-541
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    • 2015
  • The purpose of this study was to evaluate the marginal and internal gap of Cobalt (Co)-Chromium (Cr) sintering metal coping fabricated by dental computer-aided design/computer-aided manufacturing systems. Abutment tooth 46 of universal numbering system was selected for the study. Twenty Co-Cr metal copings of two groups were manufactured and scanned. Co-Cr cast metal copings (CCM) group of ten were fabricated using investment, burnout and casing after subtractive manufacturing of wax block. Also, Co-Cr sintering metal copings (CSM) group of ten were fabricated using sintering processing after subtractive manufacturing of Co-Cr soft metal bock. Marginal and internal gap of Co-Cr metal copings of twenty were measured by digital microscope (${\times}160$) with silicone replica technique. The data was analyzed from IBM SPSS Statistics ver. 22.0 Statistical software for Mann-Whitney U test (${\alpha}=0.05$). $Mean{\pm}standard$ deviation of marginal gap of CCM group was $90.12{\pm}61.73{\mu}m$ of CSM group was $60.17{\pm}24.83{\mu}m$. However, two groups was statistically not different (p>0.05). This study showed that CSM group was clinically acceptable adaptation.