• Title/Summary/Keyword: behavior profiling

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Thickness and Surface Measurement of Transparent Thin-Film Layers using White Light Scanning Interferometry Combined with Reflectometry

  • Jo, Taeyong;Kim, KwangRak;Kim, SeongRyong;Pahk, HeuiJae
    • Journal of the Optical Society of Korea
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    • v.18 no.3
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    • pp.236-243
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    • 2014
  • Surface profiling and film thickness measurement play an important role for inspection. White light interferometry is widely used for engineering surfaces profiling, but its applications are limited primarily to opaque surfaces with relatively simple optical reflection behavior. The conventional bucket algorithm had given inaccurate surface profiles because of the phase error that occurs when a thin-film exists on the top of the surface. Recently, reflectometry and white light scanning interferometry were combined to measure the film thickness and surface profile. These techniques, however, have found that many local minima exist, so it is necessary to make proper initial guesses to reach the global minimum quickly. In this paper we propose combing reflectometry and white light scanning interferometry to measure the thin-film thickness and surface profile. The key idea is to divide the measurement into two states; reflectometry mode and interferometry mode to obtain the thickness and profile separately. Interferogram modeling, which considers transparent thin-film, was proposed to determine parameters such as height and thickness. With the proposed method, the ambiguity in determining the thickness and the surface has been eliminated. Standard thickness specimens were measured using the proposed method. Multi-layered film measurement results were compared with AFM measurement results. The comparison showed that surface profile and thin-film thickness can be measured successfully through the proposed method.

Predicting User Profile based on user behaviors (모바일 사용자 행태 기반 프로파일 예측)

  • Sim, Myo-Seop;Lim, Heui-Seok
    • Journal of the Korea Convergence Society
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    • v.11 no.7
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    • pp.1-7
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    • 2020
  • As the performance of mobile devices has dramatically improved, users can perform many tasks in a mobile environment. This means that the use of behavior information stored in the mobile device can tell a lot of users. For example, a user's text message and frequently used application information (behavioral information) can be utilized to create useful information, such as whether the user is interested in parenting(profile prediction). In this study, I investigate the behavior information of the user that can be collected in the mobile device and propose the item that can profile the user. And I also suggest ideas about how to utilize profiling information.

Micro Forming of Bulk Metallic Glass using the Deformation Behavior in the Supercooled Liquid Region (과냉각 액체 영역에서의 변형거동을 이용한 벌크 비정질 합금의 미세성형 기술 개발)

  • 옥명렬;서진유;홍경태
    • Transactions of Materials Processing
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    • v.13 no.1
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    • pp.9-14
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    • 2004
  • Recently, various bulk metallic glasses (BMG's) having good mechanical and chemical properties were developed. BMG's can easily be deformed in the supercooled liquid region, via viscous flow mechanism. By using the viscous flow, the very low pressure is needed to deform the materials. In this study, we investigated the structural transition and deformation behavior of Vitreloy 1 (Zr/sub 41.2/Ti/sub 13.8/Cu/sub 12.5/Ni/sub 10/Be/sub 22.5/) using TMA and DSC. We applied the results to the micro forming process. The forming condition was chosen based on the viscosity data from TMA, and Si wafer with micro patterns on the surface was used as a forming die. The deformed surface was analyzed by SEM and 3D Surface Profiling System. The alloy showed good replication of the patterns. Quantitative measurement of roughness was useful to evaluate the replication. Surface condition of the deformed surface was determined by the initial surface condition.

A Study on Green Consumer Segmentation Based on Socio-Demographics and Behavioral Responses: Renewing the Relationships between Socio-demographics and Green Behavior

  • Kim, Young Doo
    • Asia Marketing Journal
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    • v.17 no.1
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    • pp.1-26
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    • 2015
  • In the 21st century, green consumer behavior, playing one of the core roles of sustainability, is still an important issue to green-related stakeholders. Because one of the major objectives of green-consumer research is an improvement of behaviors aligned with greening, this paper revisited socio-demographic variables and shed light on segmenting and profiling green consumers based on their connectedness between socio-demographic variables and green behaviors. Using correlations, factor analysis, analysis of variance, k-means cluster analysis and χ2-tests, this paper shows that socio-demographic variables differentially impact green-consumer behaviors. In order to profile green consumers, this paper additionally attempts to segment green-consumer groups. The results also coincide with former findings that socio-demographic variables relate significantly with segmented green-consumer group behaviors. General findings are summarized as: 1) older people used green practices more strongly than younger people, 2) females demonstrated better energy-saving and recycling practices compared to males, 3) marital status also significantly influenced green-related behaviors, 4) subjective social class had a significant influence on green-related behaviors, 5) education level and income, however, weakly influenced or showed no impact on green-related behaviors, and 6) a green consumer was classified as an 'active green consumer,' 'utilitarian green consumer,' or 'inactivated green consumer.' The utilitarian green consumer group distinctively behaved more strongly in energy-saving and recycling practices compared to the inactivated green consumer group, whereas active green consumers behaved more strongly on the whole, when compared to those in the inactivated green consumer group.

User Behavior Profiling based on Continuous Data Mining (TV-Anytime 메타데이터 연속 데이터 마이닝을 이용한 시청 선호도 프로파일 생성 기법)

  • Shin Se-Jung;Lee Won-Suk
    • Proceedings of the Korea Information Processing Society Conference
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    • 2006.05a
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    • pp.403-406
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    • 2006
  • 최근 시작된 국내 디지털 지상파 방송으로 이제 본격적인 디지털 방송 시대가 열리게 되었다. 디지털 방송 서비스는 다매체, 다채널을 통한 방송 프로그램의 증가와 양방향 TV 방송 서비스로 인해 사용자에게 다양한 방송 프로그램의 선택과 개인별 맞춤형 시청 기회를 제공함으로써 새로운 방송 서비스 환경을 필요로 하게 되었다. 이에 본 논문에서는 맞춤형 DTV(Digital TV) 방송 서비스를 제공하기 위하여 TV-Anytime 영상 메타데이터에 대한 연속 데이터 마이닝 기법을 이용하여 시청 선호도 프로파일을 생성하는 효율적인 기법을 제안한다. 또한, 내장형 운영체제 기반의 사용자 디스플레이 모듈을 제공하며, 실험을 통하여 본 논문에서 제안하는 방법의 효율성을 고증한다.

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Non-Destructive Evaluation for Material of Thermal Barrier Coatings (단열 코팅재료의 비파괴 평가기법)

  • Lee Chul-Ku;Kim Tae-Hyung
    • Transactions of the Korean Society of Machine Tool Engineers
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    • v.14 no.1
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    • pp.44-51
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    • 2005
  • Material degradation is a multibillion-dollar problem which affects all the industries amongst others. The last decades have seen the development of newer and more effective techniques such as Focused-ion beam(FIB), Transmission electron microscopy(TEM), Secondary-ion mass spectroscopy(SIMS), auger electron spectroscopy(AES), X-ray Photoelectron spectroscopy(XPS) , Electrochemical impedance spectroscopy(EIS), Photo- stimulated luminescence spectroscopy(PSLS), etc. to study various forms of material degradation. These techniques are now used routinely to obtain information on the chemical state, depth profiling, composition, stress state, etc. to understand the degradation behavior. This paper describes the use of these techniques specifically applied to materials degradation and failure analysis.

Interdiffusion at Interfaces of Polymers with Dissimilar Physical Properties

  • 정재명;박형석
    • Bulletin of the Korean Chemical Society
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    • v.18 no.7
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    • pp.720-729
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    • 1997
  • The interface between two different polymers is characterized theoretically by using a model. This model is based on the assumption that the monomeric friction coefficients of the two polymers are identical but a strong function of the matrix composition. This model predicts that the concentration profiles are highly asymmetric with substantial swelling of the slower-diffusing component by the faster component. To predict the behavior of interdiffusion, three quantities are used: distance of interface Z*(t) due to the swelling, interfacial width W(t) which is most sensitive to the detailed composition profiling, and mass transport M(t) due to interdiffusion. It is found that the more dissimilar polymer pairs, the faster the movement of the interface, the quicker its interfacial width saturates to a limiting value and the slower its mass transport. These results are in qualitative agreement with some experiments.

An Agent System for Supporting Adaptive Web Surfing (적응형 웹 서핑 지원을 위한 에이전트 시스템)

  • Kook, Hyung-Joon
    • The KIPS Transactions:PartB
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    • v.9B no.4
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    • pp.399-406
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    • 2002
  • The goal of this research has been to develop an adaptive user agent for web surfing. To achieve this goal, the research has concentrated on three issues: collection of user data, construction and improvement of user profile, and adaptation by applying the user profile. The main outcome from the research is a prototype system that provides the functional definition and componential design scheme for an adaptive user agent for the web environment. Internally, the system achieves its operational goal from the cooperation of two independent agents. They are IIA (Interactive Interface Agent) and UPA (User Profiling Agent). As a tool for providing a user-friendly interface environment, the IIA employs the Keyword Index, which is a list of index terms of a webpage as well as a keyword menu for subsequent queries, and the Suggest Link, which is a hierarchical list of URLs showing the past browsing procedure of the user. The UPA reflects in the User Profile, both the static and the dynamic information obtained from the user's browsing behavior. In particular, a user's interests are represented in the form of Interest Vectors which, based on the similarity of the vectors, is subject to update and creation, thus dynamically profiling the user's ever-shifting interests.

Research on illegal copyright distributor tracking and profiling technology (불법저작물 유포자 행위분석 프로파일링 기술 연구)

  • Kim, Jin-gang;Hwang, Chan-woong;Lee, Tae-jin
    • Journal of Internet Computing and Services
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    • v.22 no.3
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    • pp.75-83
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    • 2021
  • With the development of the IT industry and the increase of cultural activities, the demand for works increases, and they can be used easily and conveniently in an online environment. Accordingly, copyright infringement is seriously occurring due to the ease of copying and distribution of works. Some special types of Online Service Providers (OSP) use filtering-based technology to protect copyrights, but they can easily bypass them, and there are limits to blocking all illegal works, making it increasingly difficult to protect copyrights. Recently, most of the distributors of illegal works are a certain minority, and profits are obtained by distributing illegal works through many OSP and majority ID. In this paper, we propose a profiling technique for heavy uploader, which is a major analysis target based on illegal works. Creates a feature containing information on overall illegal works and identifies major heavy uploader. Among these, clustering technology is used to identify heavy uploader that are presumed to be the same person. In addition, heavy uploaders with high priority can be analyzed through illegal work Distributor tracking and behavior analysis. In the future, it is expected that copyright damage will be minimized by identifying and blocking heavy uploader that distribute a large amount of illegal works.

Clustering Normal User Behavior for Anomaly Intrusion Detection (비정상행위 탐지를 위한 사용자 정상행위 클러스터링 기법)

  • Oh, Sang-Hyun;Lee, Won-Suk
    • The KIPS Transactions:PartC
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    • v.10C no.7
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    • pp.857-866
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    • 2003
  • For detecting an intrusion based on the anomaly of a user's activities, previous works are concentrated on statistical techniques in order to analyze an audit data set. However. since they mainly analyze the average behavior of a user's activities, some anomalies can be detected inaccurately. In this paper, a new clustering algorithm for modeling the normal pattern of a user's activities is proposed. Since clustering can identify an arbitrary number of dense ranges in an analysis domain, it can eliminate the inaccuracy caused by statistical analysis. Also, clustering can be used to model common knowledge occurring frequently in a set of transactions. Consequently, the common activities of a user can be found more accurately. The common knowledge is represented by the occurrence frequency of similar data objects by the unit of a transaction as veil as the common repetitive ratio of similar data objects in each transaction. Furthermore, the proposed method also addresses how to maintain identified common knowledge as a concise profile. As a result, the profile can be used to detect any anomalous behavior In an online transaction.