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(Image Analysis of Electrophoresis Gels by using Region Growing with Multiple Peaks) (다중 피크의 영역 성장 기법에 의한 전기영동 젤의 영상 분석)

  • 김영원;전병환
    • Journal of KIISE:Software and Applications
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    • v.30 no.5_6
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    • pp.444-453
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    • 2003
  • Recently, a great interest of bio-technology(BT) is concentrated and the image analysis technique for electrophoresis gels is highly requested to analyze genetic information or to look for some new bio-activation materials. For this purpose, the location and quantity of each band in a lane should be measured. In most of existing techniques, the approach of peak searching in a profile of a lane is used. But this peak is improper as the representative of a band, because its location does not correspond to that of the brightest pixel or the center of gravity. Also, it is improper to measure band quantity in most of these approaches because various enhancement processes are commonly applied to original images to extract peaks easily. In this paper, we adopt an approach to measure accumulated brightness as a band quantity in each band region, which Is extracted by not using any process of changing relative brightness, and the gravity center of the region is calculated as a band location. Actually, we first extract lanes with an entropy-based threshold calculated on a gel-image histogram. And then, three other methods are proposed and applied to extract bands. In the MER method, peaks and valleys are searched on a vertical search line by which each lane is bisected. And the minimum enclosing rectangle of each band is set between successive two valleys. On the other hand, in the RG-1 method, each band is extracted by using region growing with a peak as a seed, separating overlapped neighbor bands. In the RG-2 method, peaks and valleys are searched on two vertical lines by which each lane is trisected, and the left and right peaks nay be paired up if they seem to belong to the same band, and then each band region is grown up with a peak or both peaks if exist. To compare above three methods, we have measured the location and amount of bands. As a result, the average errors in band location of MER, RG-1, and RG-2 were 6%, 3%, and 1%, respectively, when the lane length is normalized to a unit value. And the average errors in band amount were 8%, 5%, and 2%, respectively, when the sum of band amount is normalized to a unit value. In conclusion, RG-2 was shown to be more reliable in the accuracy of measuring the location and amount of bands.

An Embedding /Extracting Method of Audio Watermark Information for High Quality Stereo Music (고품질 스테레오 음악을 위한 오디오 워터마크 정보 삽입/추출 기술)

  • Bae, Kyungyul
    • Journal of Intelligence and Information Systems
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    • v.24 no.2
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    • pp.21-35
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    • 2018
  • Since the introduction of MP3 players, CD recordings have gradually been vanishing, and the music consuming environment of music users is shifting to mobile devices. The introduction of smart devices has increased the utilization of music through music playback, mass storage, and search functions that are integrated into smartphones and tablets. At the time of initial MP3 player supply, the bitrate of the compressed music contents generally was 128 Kbps. However, as increasing of the demand for high quality music, sound quality of 384 Kbps appeared. Recently, music content of FLAC (Free License Audio Codec) format using lossless compression method is becoming popular. The download service of many music sites in Korea has classified by unlimited download with technical protection and limited download without technical protection. Digital Rights Management (DRM) technology is used as a technical protection measure for unlimited download, but it can only be used with authenticated devices that have DRM installed. Even if music purchased by the user, it cannot be used by other devices. On the contrary, in the case of music that is limited in quantity but not technically protected, there is no way to enforce anyone who distributes it, and in the case of high quality music such as FLAC, the loss is greater. In this paper, the author proposes an audio watermarking technology for copyright protection of high quality stereo music. Two kinds of information, "Copyright" and "Copy_free", are generated by using the turbo code. The two watermarks are composed of 9 bytes (72 bits). If turbo code is applied for error correction, the amount of information to be inserted as 222 bits increases. The 222-bit watermark was expanded to 1024 bits to be robust against additional errors and finally used as a watermark to insert into stereo music. Turbo code is a way to recover raw data if the damaged amount is less than 15% even if part of the code is damaged due to attack of watermarked content. It can be extended to 1024 bits or it can find 222 bits from some damaged contents by increasing the probability, the watermark itself has made it more resistant to attack. The proposed algorithm uses quantization in DCT so that watermark can be detected efficiently and SNR can be improved when stereo music is converted into mono. As a result, on average SNR exceeded 40dB, resulting in sound quality improvements of over 10dB over traditional quantization methods. This is a very significant result because it means relatively 10 times improvement in sound quality. In addition, the sample length required for extracting the watermark can be extracted sufficiently if the length is shorter than 1 second, and the watermark can be completely extracted from music samples of less than one second in all of the MP3 compression having a bit rate of 128 Kbps. The conventional quantization method can extract the watermark with a length of only 1/10 compared to the case where the sampling of the 10-second length largely fails to extract the watermark. In this study, since the length of the watermark embedded into music is 72 bits, it provides sufficient capacity to embed necessary information for music. It is enough bits to identify the music distributed all over the world. 272 can identify $4*10^{21}$, so it can be used as an identifier and it can be used for copyright protection of high quality music service. The proposed algorithm can be used not only for high quality audio but also for development of watermarking algorithm in multimedia such as UHD (Ultra High Definition) TV and high-resolution image. In addition, with the development of digital devices, users are demanding high quality music in the music industry, and artificial intelligence assistant is coming along with high quality music and streaming service. The results of this study can be used to protect the rights of copyright holders in these industries.

A Survey on the Knowledge and Attitude of Workers Concerning Occupational Health (근로자의 산업보건 지식과 태도에 관한 조사연구)

  • 박영식;조수열;남철현
    • Journal of Environmental Health Sciences
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    • v.18 no.2
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    • pp.3-18
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    • 1992
  • This research was carried out on 1,017 production workers for four months from May to August, 1991, to search more effective management method of their health by grasping their knowledge and attitude on industrial health. The results of this study can be summarized as follows: 1. As for general characteristics, 74.2% were male and 25.8% were female among the 1,017 workers. The two largest age groups were 30~39, 38.7%. As for education level, graduation from high school was 58.6%, 61.2% were married, 35.9% owned their house, and workers who worked more than 1 year less than 5 years was 52.9%, workers who worked 8 hours a day was 46.7%, the largest group income level was 60~69 thousand won 21.2%, and the degree of satisfaction with work was ordinary, 45.6%. 2. The degree of recognition concerning occupational diseases was 92.5% at a very high rate. Causes of occupational diseases under the present work field were in order of noise, dust, heavy metal. The largest group of the counterplan for prevention was an improvement of working environment, 62.0%. 3. The major cause that threatens worker's health was poor working environment, 31.4%. As the best method for workers' health management, working environment management was pointed. 4. As for health examination result, the response that it is of use to health management was 53.8%. As for examination method and result, 42.7% responded that they are formal. The practice period was more than once every six months as the largest group, and the highest desire for improvement was that they wants an exact information of the result. 5. 49.3% of the respondents know about the measurement of working environment an the response that the measurement is necessary to improve working environment was 57.9%, and that the results from the measurement were reflected on improvement an management 57.5%. Appropriate period to take a measurement was more than once per six months, 40.2% and per three months, 29.1%. 6. As for safety and halth instruction, 34.5% were educated for both, 38.2% for only safety education and just 4.6% for only health education. 51.9% responded that they had never been educated out of work place. The period of its practice was more than once a month, 39.5% and every three months, 21.3%. 7. The importance of safety and health showed that the one is equal to the other, 59.8%, that the one is more important, 29.6%, and that other is more important, 7.6%. 67.7% said the necessity of a safety and health manager. 8. In spite of more or less health obstacle of work environment, 14.9% of the respondents wanted to overwork to gain an allowance for over-time work, 39.9% didn't, and 40.2% according to condition and state. 9. As the most important cause of industrial accident, 40.2% indicated unsafe behavior. As for the individual protective instrument, 66.1% of all the respondents said they have worn it to protect industrial diseases. 10. As for the degree of understanding of the contents in Industrial Safety and Health Law and Industrial Law of Accident Insurance, an affirmative response was respectively 49.3% and 50.8% and the sources of safety-health information were televisions and radios, 28.0%. Therefore, it is necessary that we do positive working environmental improvement, continuous management and health education's inforcement to increase their health and prevent occupational diseases.

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Trend and Further Research of Rice Quality Evaluation (쌀의 품질평가 현황과 금후 연구방향)

  • Son, Jong-Rok;Kim, Jae-Hyun;Lee, Jung-Il;Youn, Young-Hwan;Kim, Jae-Kyu;Hwang, Hung-Goo;Moon, Hun-Pal
    • KOREAN JOURNAL OF CROP SCIENCE
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    • v.47
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    • pp.33-54
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    • 2002
  • Rice quality is much dependent on the pre-and post harvest management. There are many parameters which influence rice or cooked rice qualitys such as cultivars, climate, soil, harvest time, drying, milling, storage, safety, nutritive value, taste, marketing, eating, cooking conditions, and each nations' food culture. Thus, vice evaluation might not be carried out by only some parameters. Physicochemical evaluation of rice deals with amy-lose content, gelatinizing property, and its relation with taste. The amylose content of good vice in Korea is defined at 17 to 20%. Other parameters considered are as follows; ratio of protein body-1 per total protein amount in relation to taste, and oleic/linoleic acid ratio in relation to storage safety. The rice higher Mg/K ratio is considered as high quality. The optimum value is over 1.5 to 1.6. It was reported that the contents of oligosaccharide, glutamic acid or its derivatives and its proportionalities have high corelation with the taste of rice. Major aromatic compounds in rice have been known as hexanal, acetone, pentanal, butanal, octanal, and heptanal. Recently, it was found that muco-polysaccharides are solubilized during cooking. Cooked rice surface is coated by the muco-polysaccharide. The muco-polysaccharide aye contributing to the consistency and collecting free amino acids and vitamins. Thus, these parameters might be regarded as important items for quality and taste evaluation of rice. Ingredients of rice related with the taste are not confined to the total rice grain. In the internal kernel, starch is main component but nitrogen and mineral compounds are localized at the external kernel. The ingredients related with taste are contained in 91 to 86% part of the outside kernel. For safety that is considered an important evaluation item of rice quality, each residual tolerance limit for agricultural chemicals must be adopted in our country. During drying, rice quality can decline by the reasons of high drying temperature, overdrying, and rapid drying. These result in cracked grain or decolored kernel. Intrinsic enzymes react partially during the rice storage. Because of these enzymes, starch, lipid, or protein can be slowly degraded, resulting in the decline of appearance quality, occurrence of aging aroma, and increased hardness of cooked rice. Milling conditions concerned with quality are paddy quality, milling method, and milling machines. To produce high quality rice, head rice must contain over three fourths of the normal rice kernels, and broken, damaged, colored, and immature kernels must be eliminated. In addition to milling equipment, color sorter and length grader must be installed for the production of such rice. Head rice was examined using the 45 brand rices circulating in Korea, Japan, America, Australia, and China. It was found that the head rice rate of brand rice in our country was approximately 57.4% and 80-86% in foreign countries. In order to develop a rice quality evaluation system, evaluation of technics must be further developed : more detailed measure of qualities, search for taste-related components, creation and grade classification of quality evaluation factors at each management stage of treatment after harvest, evaluation of rice as food material as well as for rice cooking, and method development for simple evaluation and establishment of equation for palatability. On policy concerns, the following must be conducted : development of price discrimination in conformity to rice cultivar and grade under the basis of quality evaluation method, fixation of head rice branding, and introduction of low temperature circulation.

A study of Artificial Intelligence (AI) Speaker's Development Process in Terms of Social Constructivism: Focused on the Products and Periodic Co-revolution Process (인공지능(AI) 스피커에 대한 사회구성 차원의 발달과정 연구: 제품과 시기별 공진화 과정을 중심으로)

  • Cha, Hyeon-ju;Kweon, Sang-hee
    • Journal of Internet Computing and Services
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    • v.22 no.1
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    • pp.109-135
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    • 2021
  • his study classified the development process of artificial intelligence (AI) speakers through analysis of the news text of artificial intelligence (AI) speakers shown in traditional news reports, and identified the characteristics of each product by period. The theoretical background used in the analysis are news frames and topic frames. As analysis methods, topic modeling and semantic network analysis using the LDA method were used. The research method was a content analysis method. From 2014 to 2019, 2710 news related to AI speakers were first collected, and secondly, topic frames were analyzed using Nodexl algorithm. The result of this study is that, first, the trend of topic frames by AI speaker provider type was different according to the characteristics of the four operators (communication service provider, online platform, OS provider, and IT device manufacturer). Specifically, online platform operators (Google, Naver, Amazon, Kakao) appeared as a frame that uses AI speakers as'search or input devices'. On the other hand, telecommunications operators (SKT, KT) showed prominent frames for IPTV, which is the parent company's flagship business, and 'auxiliary device' of the telecommunication business. Furthermore, the frame of "personalization of products and voice service" was remarkable for OS operators (MS, Apple), and the frame for IT device manufacturers (Samsung) was "Internet of Things (IoT) Integrated Intelligence System". The econd, result id that the trend of the topic frame by AI speaker development period (by year) showed a tendency to develop around AI technology in the first phase (2014-2016), and in the second phase (2017-2018), the social relationship between AI technology and users It was related to interaction, and in the third phase (2019), there was a trend of shifting from AI technology-centered to user-centered. As a result of QAP analysis, it was found that news frames by business operator and development period in AI speaker development are socially constituted by determinants of media discourse. The implication of this study was that the evolution of AI speakers was found by the characteristics of the parent company and the process of co-evolution due to interactions between users by business operator and development period. The implications of this study are that the results of this study are important indicators for predicting the future prospects of AI speakers and presenting directions accordingly.

Prediction of a hit drama with a pattern analysis on early viewing ratings (초기 시청시간 패턴 분석을 통한 대흥행 드라마 예측)

  • Nam, Kihwan;Seong, Nohyoon
    • Journal of Intelligence and Information Systems
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    • v.24 no.4
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    • pp.33-49
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    • 2018
  • The impact of TV Drama success on TV Rating and the channel promotion effectiveness is very high. The cultural and business impact has been also demonstrated through the Korean Wave. Therefore, the early prediction of the blockbuster success of TV Drama is very important from the strategic perspective of the media industry. Previous studies have tried to predict the audience ratings and success of drama based on various methods. However, most of the studies have made simple predictions using intuitive methods such as the main actor and time zone. These studies have limitations in predicting. In this study, we propose a model for predicting the popularity of drama by analyzing the customer's viewing pattern based on various theories. This is not only a theoretical contribution but also has a contribution from the practical point of view that can be used in actual broadcasting companies. In this study, we collected data of 280 TV mini-series dramas, broadcasted over the terrestrial channels for 10 years from 2003 to 2012. From the data, we selected the most highly ranked and the least highly ranked 45 TV drama and analyzed the viewing patterns of them by 11-step. The various assumptions and conditions for modeling are based on existing studies, or by the opinions of actual broadcasters and by data mining techniques. Then, we developed a prediction model by measuring the viewing-time distance (difference) using Euclidean and Correlation method, which is termed in our study similarity (the sum of distance). Through the similarity measure, we predicted the success of dramas from the viewer's initial viewing-time pattern distribution using 1~5 episodes. In order to confirm that the model is shaken according to the measurement method, various distance measurement methods were applied and the model was checked for its dryness. And when the model was established, we could make a more predictive model using a grid search. Furthermore, we classified the viewers who had watched TV drama more than 70% of the total airtime as the "passionate viewer" when a new drama is broadcasted. Then we compared the drama's passionate viewer percentage the most highly ranked and the least highly ranked dramas. So that we can determine the possibility of blockbuster TV mini-series. We find that the initial viewing-time pattern is the key factor for the prediction of blockbuster dramas. From our model, block-buster dramas were correctly classified with the 75.47% accuracy with the initial viewing-time pattern analysis. This paper shows high prediction rate while suggesting audience rating method different from existing ones. Currently, broadcasters rely heavily on some famous actors called so-called star systems, so they are in more severe competition than ever due to rising production costs of broadcasting programs, long-term recession, aggressive investment in comprehensive programming channels and large corporations. Everyone is in a financially difficult situation. The basic revenue model of these broadcasters is advertising, and the execution of advertising is based on audience rating as a basic index. In the drama, there is uncertainty in the drama market that it is difficult to forecast the demand due to the nature of the commodity, while the drama market has a high financial contribution in the success of various contents of the broadcasting company. Therefore, to minimize the risk of failure. Thus, by analyzing the distribution of the first-time viewing time, it can be a practical help to establish a response strategy (organization/ marketing/story change, etc.) of the related company. Also, in this paper, we found that the behavior of the audience is crucial to the success of the program. In this paper, we define TV viewing as a measure of how enthusiastically watching TV is watched. We can predict the success of the program successfully by calculating the loyalty of the customer with the hot blood. This way of calculating loyalty can also be used to calculate loyalty to various platforms. It can also be used for marketing programs such as highlights, script previews, making movies, characters, games, and other marketing projects.

Evaluation for applicability of river depth measurement method depending on vegetation effect using drone-based spatial-temporal hyperspectral image (드론기반 시공간 초분광영상을 활용한 식생유무에 따른 하천 수심산정 기법 적용성 검토)

  • Gwon, Yeonghwa;Kim, Dongsu;You, Hojun
    • Journal of Korea Water Resources Association
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    • v.56 no.4
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    • pp.235-243
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    • 2023
  • Due to the revision of the River Act and the enactment of the Act on the Investigation, Planning, and Management of Water Resources, a regular bed change survey has become mandatory and a system is being prepared such that local governments can manage water resources in a planned manner. Since the topography of a bed cannot be measured directly, it is indirectly measured via contact-type depth measurements such as level survey or using an echo sounder, which features a low spatial resolution and does not allow continuous surveying owing to constraints in data acquisition. Therefore, a depth measurement method using remote sensing-LiDAR or hyperspectral imaging-has recently been developed, which allows a wider area survey than the contact-type method as it acquires hyperspectral images from a lightweight hyperspectral sensor mounted on a frequently operating drone and by applying the optimal bandwidth ratio search algorithm to estimate the depth. In the existing hyperspectral remote sensing technique, specific physical quantities are analyzed after matching the hyperspectral image acquired by the drone's path to the image of a surface unit. Previous studies focus primarily on the application of this technology to measure the bathymetry of sandy rivers, whereas bed materials are rarely evaluated. In this study, the existing hyperspectral image-based water depth estimation technique is applied to rivers with vegetation, whereas spatio-temporal hyperspectral imaging and cross-sectional hyperspectral imaging are performed for two cases in the same area before and after vegetation is removed. The result shows that the water depth estimation in the absence of vegetation is more accurate, and in the presence of vegetation, the water depth is estimated by recognizing the height of vegetation as the bottom. In addition, highly accurate water depth estimation is achieved not only in conventional cross-sectional hyperspectral imaging, but also in spatio-temporal hyperspectral imaging. As such, the possibility of monitoring bed fluctuations (water depth fluctuation) using spatio-temporal hyperspectral imaging is confirmed.

Index-based Searching on Timestamped Event Sequences (타임스탬프를 갖는 이벤트 시퀀스의 인덱스 기반 검색)

  • 박상현;원정임;윤지희;김상욱
    • Journal of KIISE:Databases
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    • v.31 no.5
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    • pp.468-478
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    • 2004
  • It is essential in various application areas of data mining and bioinformatics to effectively retrieve the occurrences of interesting patterns from sequence databases. For example, let's consider a network event management system that records the types and timestamp values of events occurred in a specific network component(ex. router). The typical query to find out the temporal casual relationships among the network events is as fellows: 'Find all occurrences of CiscoDCDLinkUp that are fellowed by MLMStatusUP that are subsequently followed by TCPConnectionClose, under the constraint that the interval between the first two events is not larger than 20 seconds, and the interval between the first and third events is not larger than 40 secondsTCPConnectionClose. This paper proposes an indexing method that enables to efficiently answer such a query. Unlike the previous methods that rely on inefficient sequential scan methods or data structures not easily supported by DBMSs, the proposed method uses a multi-dimensional spatial index, which is proven to be efficient both in storage and search, to find the answers quickly without false dismissals. Given a sliding window W, the input to a multi-dimensional spatial index is a n-dimensional vector whose i-th element is the interval between the first event of W and the first occurrence of the event type Ei in W. Here, n is the number of event types that can be occurred in the system of interest. The problem of‘dimensionality curse’may happen when n is large. Therefore, we use the dimension selection or event type grouping to avoid this problem. The experimental results reveal that our proposed technique can be a few orders of magnitude faster than the sequential scan and ISO-Depth index methods.hods.

A Descriptive Study of Oral Health Knowledge & Behaviors in Middle School Students (일부지역 중학생의 구강건강 지식 및 행동에 관한 조사연구)

  • Yoo, Jung-Sook;Kim, Jung-Hee;Han, Su-Jin;Sim, Sang-Hyo;Kim, Yoon-Shin
    • The Journal of Korean Society for School & Community Health Education
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    • v.9 no.1
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    • pp.85-97
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    • 2008
  • Objectives: This study was designed to understand the oral health knowledge & conduct of middle-school students, search for the learning objective and the educational method in line with the subjects and of utilizing as the basic data for an effective oral health-care program. Methods: The samples to achieve the purpose of this research are composed of 139 students in middle-school, OO county. Chungcheongbuk-do, the number of male students 64, and female students 75. Data were statistically analyzed by frequency analysis, $x^2$-test or Fisher's exact test by using SPSS WIN Ver. 12.0. Results: Among items on oral-health knowledge in middle-school students. the awareness ratio on a cause and preventive method for oral disease was surveyed to be lower than the awareness ratio on symptoms of oral disease. As a result of examining by comparing knowledge and behavior on the time of tooth brush. both awareness and behavior were the level of 50% or less than it. In particular, 46.2% perceived after lunch. but practice just accounted for 33.0%. The frequency of tooth brush a day was the largest in a case(47.5%) of doing twice a day. However. there was also the response (5.8%) with saying of brushing once or not brushing even once. Thus, the practice of tooth brush was surveyed to be very low even if being a minority of students. The frequency of taking a light meal was 68.8% in less than twice a day. However, even students of taking more than five times were surveyed to be 9.8%. Out of the whole-body health in over 50%-59.9%. the oral health was surveyed to be perceived to be very important. Compared to the awareness level on importance of a tooth, the ratio of visiting a dentistry was analyzed to be very low. Conclusions: The study results suggest that the school oral-health project was examined to have the necessity of being expanded and carried out even in middle-and-high schools, by which the specific oral-health promotion program including oral-health education in this period is developed.

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Analysis and Evaluation of Frequent Pattern Mining Technique based on Landmark Window (랜드마크 윈도우 기반의 빈발 패턴 마이닝 기법의 분석 및 성능평가)

  • Pyun, Gwangbum;Yun, Unil
    • Journal of Internet Computing and Services
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    • v.15 no.3
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    • pp.101-107
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    • 2014
  • With the development of online service, recent forms of databases have been changed from static database structures to dynamic stream database structures. Previous data mining techniques have been used as tools of decision making such as establishment of marketing strategies and DNA analyses. However, the capability to analyze real-time data more quickly is necessary in the recent interesting areas such as sensor network, robotics, and artificial intelligence. Landmark window-based frequent pattern mining, one of the stream mining approaches, performs mining operations with respect to parts of databases or each transaction of them, instead of all the data. In this paper, we analyze and evaluate the techniques of the well-known landmark window-based frequent pattern mining algorithms, called Lossy counting and hMiner. When Lossy counting mines frequent patterns from a set of new transactions, it performs union operations between the previous and current mining results. hMiner, which is a state-of-the-art algorithm based on the landmark window model, conducts mining operations whenever a new transaction occurs. Since hMiner extracts frequent patterns as soon as a new transaction is entered, we can obtain the latest mining results reflecting real-time information. For this reason, such algorithms are also called online mining approaches. We evaluate and compare the performance of the primitive algorithm, Lossy counting and the latest one, hMiner. As the criteria of our performance analysis, we first consider algorithms' total runtime and average processing time per transaction. In addition, to compare the efficiency of storage structures between them, their maximum memory usage is also evaluated. Lastly, we show how stably the two algorithms conduct their mining works with respect to the databases that feature gradually increasing items. With respect to the evaluation results of mining time and transaction processing, hMiner has higher speed than that of Lossy counting. Since hMiner stores candidate frequent patterns in a hash method, it can directly access candidate frequent patterns. Meanwhile, Lossy counting stores them in a lattice manner; thus, it has to search for multiple nodes in order to access the candidate frequent patterns. On the other hand, hMiner shows worse performance than that of Lossy counting in terms of maximum memory usage. hMiner should have all of the information for candidate frequent patterns to store them to hash's buckets, while Lossy counting stores them, reducing their information by using the lattice method. Since the storage of Lossy counting can share items concurrently included in multiple patterns, its memory usage is more efficient than that of hMiner. However, hMiner presents better efficiency than that of Lossy counting with respect to scalability evaluation due to the following reasons. If the number of items is increased, shared items are decreased in contrast; thereby, Lossy counting's memory efficiency is weakened. Furthermore, if the number of transactions becomes higher, its pruning effect becomes worse. From the experimental results, we can determine that the landmark window-based frequent pattern mining algorithms are suitable for real-time systems although they require a significant amount of memory. Hence, we need to improve their data structures more efficiently in order to utilize them additionally in resource-constrained environments such as WSN(Wireless sensor network).