• Title/Summary/Keyword: 컴퓨터화 평가 시스템

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Signifying Practices of Technoculture in the age of Data Capitalism: Cultural and Political Alternative after the Financial Crisis of 2008 (데이터자본주의 시대 테크노컬처의 의미화 실천: 2008년 글로벌 금융위기 이후의 문화정치적 대안)

  • Lim, Shan
    • The Journal of the Convergence on Culture Technology
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    • v.8 no.3
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    • pp.143-148
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    • 2022
  • The subject of this paper is the practical examples of technoculture that critically thinks network technology, a strong material foundation in the era of data capitalism in the 21st century, and appropriates its socio-cultural metaphor as an artistic potential. In order to analyze its alternatives and the meaning of cultural politics, this paper examines the properties and influence of data capitalism after the 2008 global financial crisis, and the cultural and artistic context formed by its reaction. The first case considered in this paper, Furtherfield's workshop, provided a useful example of how citizens can participate in social change through learning and education in which art and technology are interrelated. The second case, Greek hackerspace HSGR, developed network technology as a tool to overcome the crisis by proposing a new progressive cultural commons due to Greece's financial crisis caused by the global financial crisis and a decrease in the state's creative support. The third case, Paolo Cirio's project, promoted a critical citizenship towards the state and community systems as dominant types of social governance. These technoculture cases can be evaluated as efforts to combine and rediscover progressive political ideology and its artistic realization tradition in the context of cultural politics, paying attention to the possibility of signifying practices of network technology that dominates the contemporary economic system.

Performance Analysis of Implementation on Image Processing Algorithm for Multi-Access Memory System Including 16 Processing Elements (16개의 처리기를 가진 다중접근기억장치를 위한 영상처리 알고리즘의 구현에 대한 성능평가)

  • Lee, You-Jin;Kim, Jea-Hee;Park, Jong-Won
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.49 no.3
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    • pp.8-14
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    • 2012
  • Improving the speed of image processing is in great demand according to spread of high quality visual media or massive image applications such as 3D TV or movies, AR(Augmented reality). SIMD computer attached to a host computer can accelerate various image processing and massive data operations. MAMS is a multi-access memory system which is, along with multiple processing elements(PEs), adequate for establishing a high performance pipelined SIMD machine. MAMS supports simultaneous access to pq data elements within a horizontal, a vertical, or a block subarray with a constant interval in an arbitrary position in an $M{\times}N$ array of data elements, where the number of memory modules(MMs), m, is a prime number greater than pq. MAMS-PP4 is the first realization of the MAMS architecture, which consists of four PEs in a single chip and five MMs. This paper presents implementation of image processing algorithms and performance analysis for MAMS-PP16 which consists of 16 PEs with 17 MMs in an extension or the prior work, MAMS-PP4. The newly designed MAMS-PP16 has a 64 bit instruction format and application specific instruction set. The author develops a simulator of the MAMS-PP16 system, which implemented algorithms can be executed on. Performance analysis has done with this simulator executing implemented algorithms of processing images. The result of performance analysis verifies consistent response of MAMS-PP16 through the pyramid operation in image processing algorithms comparing with a Pentium-based serial processor. Executing the pyramid operation in MAMS-PP16 results in consistent response of processing time while randomly response time in a serial processor.

한냉혈관반응 측정에 관한 연구

  • 정종만;이영숙
    • Proceedings of the ESK Conference
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    • 1997.04a
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    • pp.203-211
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    • 1997
  • 본 연구는 기온$15^{\circ}C{\pm}1^{\circ}C$ $26^{\circ}C{\pm}1^{\circ}C$,습도$55%{\pm}5%$ 환경조건에서 손가락 끝마디 부분을 얼음물에 침지시킨후 구강온과 4부위 피부온, 손가락끝 피부온, 전신온냉감, 전신쾌적감, 손가락 끝 동통감의 변화를 젊은 남자 피험자와 노인남자 피험자를 대상으로 비교측정하고자 하였다. 본 학회에서는 젊은 남자피험자 그룹에 대하여 보고하고자 한다. 결과는 다 음과 같다. $15^{\circ}C{\pm}1^{\circ}C$에서 4부위 피부온을 보면 가슴과 상완은 손가락끝 침지시 약간 하강하고 다시 상승하지만 대퇴와 하퇴에서는 하강하고 그 상태가 유지된다. 특히 하퇴의 경우는 급격히 하강하는 경향을 보이고 있다. 손가락끝 피부온은 손가락 침지와 동시에 급격한 하강을 나타내나 손가락을 꺼낸후에 손가락 침지전의 온도로 회복되지는 않았다. 평균피부온을 보면 손가락 침지시 하강하는 경향을 보이고 있다. 전신 쾌적감은 약간 불쾌하게 나타났고, 전신온냉감은 서늘하다고나타났고 손가락끝의 동통 감은 매우 아프다고 나타났다. $26^{\circ}C{\pm}1^{\circ}C$에서 4부위 피부온을 보면 가슴 상완대퇴 하퇴 모두 손가락끝 침지시 약간 하강하고 낮은 상태로 유지되는 경향을 보이고 있다. 손가락끝 피부온은 손가락 침지시 급격한 하강을 나타내었고 손가락을 꺼낸후에도 침지의 온도로 회복이 되었다. 평균피부온은 손가락 침지후에 약간 하강하였지만 큰 차이는 없었다. 전신쾌적감은 약간 쾌적하게 나타났고 전신온냉감은 약간 따뜻하다라고 나타났으며 손가락끝의 동통감은 약간 아프다고쪽으로 나타났다.때문에 이를 디자인에 곧바로 적용시키기 어려운 점이 있다. 이에 본 연구는 기존의 바용성 평가를 위한 분석도구들이 갖는 문제 점들 해결하여 제품의 사용자 인터페이스 디자인 개발과정에서 활용할 수 있는 평가 분석도구를 개발하는 것을 목표로 한다. 이를 위해 첫째, 다양한 유형의 정보를 포함하는 비디오 정보를 선정하였따. 둘째, 데이터를 다양한 측면에서 추출할 수 있는 Data logger를 개발하였다. 셋째, 데이터를 시각적으로 정리하고 분석할 수 있는 도구를 제안한다. 마지막으로 인터페이스 디자인에서 여러 가지 디자인안을 도출해 내는 작업에 이용할 수 있는 종합화과정을 개발한다. 이러한 일련의 과정이 통합된 컴퓨터 시스템 안에서 이루어지도록 프로그램을 개발하여 정보의 유용성을 높일 수 있도록 한다.at the entropy index as a measurement of inter-business relatedness is not significant but technological relatedness index is significant. OLS estimates on pooled data were considerably different from FEM or REM estimates on panel data. By introducing interaction effect among the three variables for business portfolio properties, we obtained three findings. First, only VI (Vertical integration) has a significant positive correlation with ROS. Second, when using TFP growth as an depende

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Building Hierarchical Knowledge Base of Research Interests and Learning Topics for Social Computing Support (소셜 컴퓨팅을 위한 연구·학습 주제의 계층적 지식기반 구축)

  • Kim, Seonho;Kim, Kang-Hoe;Yeo, Woondong
    • The Journal of the Korea Contents Association
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    • v.12 no.12
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    • pp.489-498
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    • 2012
  • This paper consists of two parts: In the first part, we describe our work to build hierarchical knowledge base of digital library patron's research interests and learning topics in various scholarly areas through analyzing well classified Electronic Theses and Dissertations (ETDs) of NDLTD Union catalog. Journal articles from ACM Transactions and conference web sites of computing areas also are added in the analysis to specialize computing fields. This hierarchical knowledge base would be a useful tool for many social computing and information service applications, such as personalization, recommender system, text mining, technology opportunity mining, information visualization, and so on. In the second part, we compare four grouping algorithms to select best one for our data mining researches by testing each one with the hierarchical knowledge base we described in the first part. From these two studies, we intent to show traditional verification methods for social community miming researches, based on interviewing and answering questionnaires, which are expensive, slow, and privacy threatening, can be replaced with systematic, consistent, fast, and privacy protecting methods by using our suggested hierarchical knowledge base.

An Effective User-Profile Generation Method based on Identification of Informative Blocks in Web Document (웹 문서의 정보블럭 식별을 통한 효과적인 사용자 프로파일 생성방법)

  • Ryu, Sang-Hyun;Lee, Seung-Hwa;Jung, Min-Chul;Lee, Eun-Seok
    • Proceedings of the Korean Information Science Society Conference
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    • 2007.10c
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    • pp.253-257
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    • 2007
  • 최근 웹 상에 정보가 폭발적으로 증가함에 따라, 사용자의 취향에 맞는 정보를 선별하여 제공하는 추천 시스템에 대한 연구가 활발히 진행되고 있다. 추천시스템은 사용자의 관심정보를 기술한 사용자 프로파일을 기반으로 동작하기 때문에 정확한 사용자 프로파일의 생성은 매우 중요하다. 사용자의 암시적인 행동정보를 기반으로 취향을 분석하는 대표적인 연구로 사용자가 이용한 웹 문서를 분석하는 방법이 있다. 이는 사용자가 이용하는 웹 문서에 빈번하게 등장하는 단어를 기반으로 사용자의 프로파일을 생성하는 것이다. 그러나 최근 웹 문서는 사용자 취향과 관련 없는 많은 구성요소들(로고, 저작권정보 등)을 포함하고 있다. 따라서 이러한 내용들을 모두 포함하여 웹 문서를 분석한다면 생성되는 프로파일의 정확도는 낮아질 것이다. 따라서 본 논문에서는 사용자 기기에서 사용자의 웹 문서 이용내역을 분석하고, 동일한 사이트로부터 얻어진 문서들에서 반복적으로 등장하는 블록을 제거한 후, 정보블럭을 식별하여 사용자의 관심단어를 추출하는 새로운 프로파일 생성방법을 제안한다. 이를 통해 보다 정확하고 빠른 프로파일 생성이 가능해진다. 본 논문에서는 제안방법의 평가를 위해, 최근 구매활동이 있었던 사용자들이 이용한 웹 문서 데이터를 수집하였으며, TF-IDF 방법과 제안방법을 이용하여 사용자 프로파일을 각각 추출하였다. 그리고 생성된 사용자 프로파일과 구매데이터와의 연관성을 비교하였으며, 보다 정확한 프로파일이 추출되는 결과와 프로파일 분석시간이 단축되는 결과를 통해 제안방법의 유효성을 입증하였다.)으로 높은 점수를 보였으며 내장첨가량에 따른 관능특성에서는 온쌀죽은 내장 $2{\sim}5%$ 첨가, 반쌀죽은 내장 $3{\sim}5%$ 첨가구에서 유의적(p<0.05)으로 높은 점수를 보였으나 쌀가루죽은 내장 $1{\sim}2%$ 첨가구에서 유의적(p<0.05)으로 낮은 점수를 보였다. 이상의 연구 결과를 통해 온쌀은 2%, 반쌀은 3%, 쌀가루는 4%의 내장을 첨가하여 제조한 전복죽이 이화학적, 물성적 및 관능적으로 우수한 것으로 나타났다.n)방법의 결과와 비교하였다.다. 유비스크립트에서는 모바일 코드의 개념을 통해서 앞서 언급한 유비쿼터스 컴퓨팅 환경에서의 문제점을 해결하고자 하였다. 모바일 코드에서는 프로그램 코드가 네트워크를 통해서 컴퓨터를 이동하면서 수행되는 개념인데, 이는 물리적으로 떨어져있으면서 네트워크로 연결되어 있는 다양한 컴퓨팅 장치가 서로 연동하기 위한 모델에 가장 적합하다. 이는 기본적으로 배포(deploy)라는 단계가 필요 없게 되고, 새로운 버전의 프로그램이 작성될지라도 런타임에 코드가 직접 이동하게 되므로 버전 관리의 문제도 해결된다. 게다가 원격 함수를 매번 호출하지 않고 한번 이동된 코드가 원격지에서 모두 수행을 하게 되므로 성능향상에도 도움이 된다. 장소 객체(Place Object)와 원격 스코프(Remote Scope)는 앞서 설명한 특징을 직접적으로 지원하는 언어 요소이다. 장소 객체는 모바일 코드가 이동해서 수행될 계산 환경(computational environment

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SINR Maximizing Collaborative Beamforming with Enhanced Robustness Against Antenna Correlation (안테나 간 상관도에 강건한 SINR 최대화 협력적 빔포밍 기법)

  • Kim, Jae-Won;Sung, Won-Jin
    • Journal of the Institute of Electronics Engineers of Korea TC
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    • v.46 no.4
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    • pp.95-103
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    • 2009
  • In this paper, a generation method of transmit and receive beamforming vectors based on base station cooperation is proposed which maximizes the user SINR in mobile cellular multi-user MIMO systems. There are two main sources of interference which deteriorate the performance of the system, i.e. the inter-user interference caused by the usage of the same radio resource for multiple users in the system, and the inter-cluster interference from neighboring base stations which are not participating in cooperative transmission. The proposed scheme cancels out the inter-user interference by using the block diagonalization(BD) method, and mitigate the inter-cluster interference by using optimal transmit and receive beamforming vectors based on optimal combining(OC) with the statistic information of inter-cluster interference. We perform computer simulations to verify the performance of the proposed scheme, and compare the result to the conventional performance obtained from utilizing the receiver side information only or utilizing the information from neither sides. The performance evaluations are conducted not only over the independent MIMO channels, but over correlated MIMO channels to demonstrate the robustness of the proposed scheme over the channels with correlation among antennas.

MICROLEAKAGE OF THE CLASS V CAVITY ACCORDING TO RESTORATION SITE AND CAVITY SIZE USING SEM AND THREE-DIMENSIONAL RECONSTRUCTION TECHNIQUES (SEM과 3차원 재구성법을 이용한 수복면의 위치와 와동 크기에 따른 미세누출도 분석)

  • Yang, In-Seo;Shin, Dong-Hoon
    • Restorative Dentistry and Endodontics
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    • v.30 no.2
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    • pp.112-120
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    • 2005
  • This study was done to evaluate whether there were any differences in microleakage of class V composite restorations according to restoration site and cavity size. Total sixty-four restorations were made in molar teeth using Esthet-X. Small ($2\;{\times}\;2\;{\times}\;1.5\;mm$) and large ($4{\times}2{\times}1.5\;mm$) restorations were made at the buccal/lingual surface and the proximal surface each. After 1,000 times of thermocycling ($5^{\circ}\;-\;55^{\circ}C$), resin replica was made and the percentage of marginal gap to the whole periphery of the restoration was estimated from SEM evaluation. Thermocycled tooth was dye penetrated with $50\%$ silver nitrate solution. After imbedding in an auto-curing resin, it was serially ground with a thickness of 0.25 mm. Volumetric microleakage was estimated after reconstructing three dimensionally. Two-way ANOVA and independent T-test for dye volume, Mann-Whitney U test for the percentage of marginal gap, Spearman's rho test for the relationship between two techniques were used, The results were as follows : 1. The site and size of the restoration affected on the microleakage of restoration. Namely, much more leakage was seen in the proximal and the large restorations rather than the buccal/lingual and the small restorations. 2. Close relationship was found between two techniques (Correlation coefficient = 0.614/ P = 0.000). Within the limits of this study, it was noted that proximal and the large restorations leaked more than buccal/lingual and the small restorations. Therefore, it should be strictly recommended large exposure of margins should be avoided by reducing unnecessary tooth reduction.

Improving Bidirectional LSTM-CRF model Of Sequence Tagging by using Ontology knowledge based feature (온톨로지 지식 기반 특성치를 활용한 Bidirectional LSTM-CRF 모델의 시퀀스 태깅 성능 향상에 관한 연구)

  • Jin, Seunghee;Jang, Heewon;Kim, Wooju
    • Journal of Intelligence and Information Systems
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    • v.24 no.1
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    • pp.253-266
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    • 2018
  • This paper proposes a methodology applying sequence tagging methodology to improve the performance of NER(Named Entity Recognition) used in QA system. In order to retrieve the correct answers stored in the database, it is necessary to switch the user's query into a language of the database such as SQL(Structured Query Language). Then, the computer can recognize the language of the user. This is the process of identifying the class or data name contained in the database. The method of retrieving the words contained in the query in the existing database and recognizing the object does not identify the homophone and the word phrases because it does not consider the context of the user's query. If there are multiple search results, all of them are returned as a result, so there can be many interpretations on the query and the time complexity for the calculation becomes large. To overcome these, this study aims to solve this problem by reflecting the contextual meaning of the query using Bidirectional LSTM-CRF. Also we tried to solve the disadvantages of the neural network model which can't identify the untrained words by using ontology knowledge based feature. Experiments were conducted on the ontology knowledge base of music domain and the performance was evaluated. In order to accurately evaluate the performance of the L-Bidirectional LSTM-CRF proposed in this study, we experimented with converting the words included in the learned query into untrained words in order to test whether the words were included in the database but correctly identified the untrained words. As a result, it was possible to recognize objects considering the context and can recognize the untrained words without re-training the L-Bidirectional LSTM-CRF mode, and it is confirmed that the performance of the object recognition as a whole is improved.

A Study of Various Filter Setups with FBP Reconstruction for Digital Breast Tomosynthesis (디지털 유방단층영상합성법의 FBP 알고리즘 적용을 위한 다양한 필터 조합에 대한 연구)

  • Lee, Haeng-Hwa;Kim, Ye-Seul;Lee, Youngjin;Choi, Sunghoon;Lee, Seungwan;Park, Hye-Suk;Kim, Hee-Joung;Choi, Jae-Gu;Choi, Young-Wook
    • Progress in Medical Physics
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    • v.25 no.4
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    • pp.271-280
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    • 2014
  • Recently, digital breast tomosynthesis (DBT) has been investigated to overcome the limitation of conventional mammography for overlapping anatomical structures and high patient dose with cone-beam computed tomography (CBCT). However incomplete sampling due to limited angle leads to interference on the neighboring slices. Many studies have investigated to reduce artifacts such as interference. Moreover, appropriate filters for tomosynthesis have been researched to solve artifacts resulted from incomplete sampling. The primary purpose of this study is finding appropriate filter scheme with FBP reconstruction for DBT system to reduce artifacts. In this study, we investigated characteristics of various filter schemes with simulation and prototype digital breast tomosynthesis under same acquisition parameters and conditions. We evaluated artifacts and noise with profiles and COV (coefficinet of variation) to study characteristic of filter. As a result, the noise with parameter 0.25 of Spectral filter reduced by 10% in comparison to that with only Ramp-lak filter. Because unbalance of information reduced with decreasing B of Slice thickness filter, artifacts caused by incomplete sampling reduced. In conclusion, we confirmed basic characteristics of filter operations and improvement of image quality by appropriate filter scheme. The results of this study can be utilized as base in research and development of DBT system by providing information that is about noise and artifacts depend on various filter schemes.

A Study on Intelligent Skin Image Identification From Social media big data

  • Kim, Hyung-Hoon;Cho, Jeong-Ran
    • Journal of the Korea Society of Computer and Information
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    • v.27 no.9
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    • pp.191-203
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    • 2022
  • In this paper, we developed a system that intelligently identifies skin image data from big data collected from social media Instagram and extracts standardized skin sample data for skin condition diagnosis and management. The system proposed in this paper consists of big data collection and analysis stage, skin image analysis stage, training data preparation stage, artificial neural network training stage, and skin image identification stage. In the big data collection and analysis stage, big data is collected from Instagram and image information for skin condition diagnosis and management is stored as an analysis result. In the skin image analysis stage, the evaluation and analysis results of the skin image are obtained using a traditional image processing technique. In the training data preparation stage, the training data were prepared by extracting the skin sample data from the skin image analysis result. And in the artificial neural network training stage, an artificial neural network AnnSampleSkin that intelligently predicts the skin image type using this training data was built up, and the model was completed through training. In the skin image identification step, skin samples are extracted from images collected from social media, and the image type prediction results of the trained artificial neural network AnnSampleSkin are integrated to intelligently identify the final skin image type. The skin image identification method proposed in this paper shows explain high skin image identification accuracy of about 92% or more, and can provide standardized skin sample image big data. The extracted skin sample set is expected to be used as standardized skin image data that is very efficient and useful for diagnosing and managing skin conditions.