• Title/Summary/Keyword: Memory grouping

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Grouping-based 3D Animation Data Compression Method (군집화 기반 3차원 애니메이션 데이터 압축 기법)

  • Choi, Young-Jin;Yeo, Du-Hwan;Klm, Hyung-Seok;Kim, Jee-In
    • 한국HCI학회:학술대회논문집
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    • 2008.02a
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    • pp.461-468
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    • 2008
  • The needs for visualizing interactive multimedia contents on portable devices with realistic three dimensional shapes are increasing as new ubiquitous services are coming into reality. Especially in digital fashion applications with virtual reality technologies for clothes of various forms on different avatars, it is required to provide very high quality visual models over mobile networks. Due to limited network bandwidths and memory spaces of portable devices, it is very difficult to transmit visual data effectively and render realistic appearance of three dimensional images. In this thesis, we propose a compression method to reduce three dimensional data for digital fashion applications. The three dimensional model includes animation of avatar which require very large amounts of data over time. Our proposed method utilizes temporal and spatial coherence of animation data, to reduce the amount. By grouping vertices from three dimensional models, the entire animation is represented by a movement path of a few representative vertices. The existing three dimensional model compression approaches can get benefits from the proposed method by reducing the compression sources through grouping. We expect that the proposed method to be applied not only to three dimensional garment animations but also to generic deformable objects.

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The effect of semantic categorization of episodic memory on encoding of subordinate details: An fMRI study (일화 기억의 의미적 범주화가 세부 기억의 부호화에 미치는 영향에 대한 자기공명영상 분석 연구)

  • Yi, Darren Sehjung;Han, Sanghoon
    • Korean Journal of Cognitive Science
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    • v.28 no.4
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    • pp.193-221
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    • 2017
  • Grouping episodes into semantically related categories is necessary for better mnemonic structure. However, the effect of grouping on memory of subordinate details was not clearly understood. In an fMRI study, we tested whether attending superordinate during semantic association disrupts or enhances subordinate episodic details. In each cycle of the experiment, five cue words were presented sequentially with two related detail words placed underneath for each cue. Participants were asked whether they could imagine a category that includes the previously shown cue words in each cycle, and their confidence on retrieval was rated. Participants were asked to perform cued recall tests on presented detail words after the session. Behavioral data showed that reaction times for categorization tasks decreased and confidence levels increased in the third trial of each cycle, thus this trial was considered to be an important insight where a semantic category was believed to be successfully established. Critically, the accuracy of recalling detail words presented immediately prior to third trials was lower than those of followed trials, indicating that subordinate details were disrupted during categorization. General linear model analysis of the trial immediately prior to the completion of categorization, specifically the second trial, revealed significant activation in the temporal gyrus and inferior frontal gyrus, areas of semantic memory networks. Representative Similarity Analysis revealed that the activation patterns of the third trials were more consistent than those of the second trials in the temporal gyrus, inferior frontal gyrus, and hippocampus. Our research demonstrates that semantic grouping can cause memories of subordinate details to fade, suggesting that semantic retrieval during categorization affects the quality of related episodic memory.

A Global IPv6 Unicast Address Lookup Scheme Using Variable Multiple Hashing (가변적인 복수 해슁을 이용한 글로벌 IPv6 유니캐스트 주소 검색 구조)

  • Park Hyun-Tae;Moon Byung-In;Kang Sung-Ho
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.31 no.5B
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    • pp.378-389
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    • 2006
  • An IP address lookup scheme has become a critical issue increasingly for high-speed networking techniques due to the advent of IPv6 based on 128bit. In this paper, a novel global IPv6 unicast address lookup scheme is proposed for next generation internet routers. The proposed scheme perform a variable multiple hashing based on prefix grouping. Accordingly, it should not only minimize overflows with the proper number of memory modules, but also reduce a memory size required to organize forwarding tables. It has the fast building and searching mechanisms for forwarding tables during only a single memory access. Besides, it is easy to update forwarding tables incrementally. In the simulation using CERNET routing data as a 6bone test phase, we compared the proposed scheme with a similar scheme using a uniform multiple hashing. As a result, we verified that the number of overflows is reduced by 50% and the size of memory for forwarding tables is shrunken by 15% with 8 tables.

An Efficient Test Compression Scheme based on LFSR Reseeding (효율적인 LFSR 리시딩 기반의 테스트 압축 기법)

  • Kim, Hong-Sik;Kim, Hyun-Jin;Ahn, Jin-Ho;Kang, Sung-Ho
    • Journal of the Institute of Electronics Engineers of Korea SD
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    • v.46 no.3
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    • pp.26-31
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    • 2009
  • A new LFSR based test compression scheme is proposed by reducing the maximum number of specified bits in the test cube set, smax, virtually. The performance of a conventional LFSR reseeding scheme highly depends on smax. In this paper, by using different clock frequencies between an LFSR and scan chains, and grouping the scan cells, we could reduce smax virtually. H the clock frequency which is slower than the clock frequency for the scan chain by n times is used for LFSR, successive n scan cells are filled with the same data; such that the number of specified bits can be reduced with an efficient grouping of scan cells. Since the efficiency of the proposed scheme depends on the grouping mechanism, a new graph-based scan cell grouping heuristic has been proposed. The simulation results on the largest ISCAS 89 benchmark circuit show that the proposed scheme requires less memory storage with significantly smaller area overhead compared to the previous test compression schemes.

Finding Smartphone's Factors which Affect Satisfaction or Dissatisfaction based on KANO Model (KANO 모델을 활용한 스마트폰의 만족 및 불만족 요인 분석)

  • Lee, Sang-Gun;Lee, Sin-Seok;Kang, Ju-Young
    • The Journal of Information Systems
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    • v.20 no.3
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    • pp.257-277
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    • 2011
  • The current study categorizes factors of smartphone into three, using KANO model: attractive factors which cause only product satisfaction, must-be factors for dissatisfaction, and one-dimensional factors for both. Based on it, it presents a new model for the effects that smartphone factors have on satisfaction or dissatisfaction. The purpose is to theoretically explain that smartphone factors on which companies and users place a high value can actually affect satisfaction or dissatisfaction. After choosing 15 factors out of 25 which had been selected through literature study, these were divided into attractive, must-be, and one-dimensional ones. 93 out of 109 questionnaires returned were used for analysis. After frequency analysis using SPSS were conducted on the surveys, the factors were grouped, based on KANO table. The grouping results are as follows. Attractive factors include 'expansion slots for external memory, battery desorption, brand awareness, mobile banking and internet telephony'. Must-be ones include 'multi-touch, information security, entertainment, information retrieval, location based service and SNS. Finally, 'screen visibility, size of internal memory, the amount of internal memory, battery life, and response to after-sales service' are classified as one-dimensional factors. A critical finding of this paper is that since the results are different depending on the operating system of smartphones, it must be taken into consideration in studies on smartphones. The wide and rapid spread of smartphones has changed people's lifestyle as well as business environment, which forces companies to compete with each other to adapt to the changed circumstances. In this competitive system, studies on smartphone factors of satisfaction and dissatisfaction are essential for firms to establish a new strategy. From this point of view, the present paper is expected to be a basic material for enterprises not only to develop goods and services that maximize customer satisfaction and minimize dissatisfaction, but also to establish the future business strategy.

Sigma Hub for Efficiently Integrating USB Storages (USB 저장장치의 효율적인 통합을 위한 시그마 허브)

  • Choi, O-Hoon;Lim, Jung-Eun;Na, Hong-Seok;Baik, Doo-Kwon
    • Journal of KIISE:Databases
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    • v.35 no.6
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    • pp.533-543
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    • 2008
  • With technological advances for storage volume size of a semiconductor memory, USB storage is made as products to support a high capacity storage. Hereby, consumers discard pint-sized USB storages which they already had, or do not use them efficiently. To integrate and unify these pint-sized USB storages as one big USB storage, we proposed Sigma Hub. It can be grouping multiple USB storages, which have each different volume size of memory storage, as logical unity Storage through USB Hub. The proposed Sigma Hub includes Sigma Controller as a core management module to unify the multiple USB storages in transaction level layer. Sigma controller can efficiently control transaction packet in Sigma Hub through a USB Storage-Integration algorithms which ensure an integrity for data read and write processes. Consequently, Sigma Hub enables the use of USB storage that is logical unity.

Improved Grouping and Buffer Sharing Method in VOD Server (주문형 비디오 서버에서의 개선된 그룹핑과 버퍼 공유 기법)

  • Jeong, Hong-Gi;Park, Seung-Gyu
    • Journal of KIISE:Information Networking
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    • v.27 no.4
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    • pp.489-497
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    • 2000
  • 주문형 비디오(Video On Demand)서버의 구현은 현재까지도 많은 부분에 한계를 가지고 있으며 이를 해결하기 위한 연구들이 활발히 진행되고 있다. 주문형 비디오 서비스의 한계는 대부분이 자원(디스크, 버퍼)의 제한 때문에 발생하고 있으며 디스크어레이(Disk Array)나, 메모리 뱅크(Memory Bank)와 같은 특수한 하드웨어를 사용하여 해결하고 있다. 또한 이와 아울러 그룹핑이나 버퍼 공유기법과 같은 소프트웨어적인 방법도 제안되었다. 본논문에서는 주분형 비디오 서버의 한계 중 디스크대역폭과 버퍼공간의 한계점에 의한 문제를 해결하기위하여 개선된 그룹핑 방법과 버퍼 공유 및 관리 방법을 제안한다. 제안하는 그룹핑 방법은 비디오의 인기도에 기반을 둔 방법을 사용하며 버퍼 공유방법은 버퍼의 크기 및 디스크의 대역폭 가용량에 따라 적응적으로 병합 분할하는 방법을 사용한다, 제안하는 병합 분할 방법은 피기백킹(piggy-backing)개념을 도입하였으며 시뮬레이션을 통해 제안하 방법의 우수성을 보였다.

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Group Model Clustering Method for Model Downsizing (모델 축소를 위한 그룹 모델 클러스터링 방법에 대한 연구)

  • Park, Mi-Na;Ha, Jin-Young
    • Journal of Industrial Technology
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    • v.28 no.A
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    • pp.185-189
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    • 2008
  • Practical pattern recognition systems should overcome very large class problem. Sometimes it is almost impossible to build every model for every class due to memory and time constraints. For this case, grouping similar models will be helpful. In this paper, we propose GMC(Group Model Clustering) to build a large class Chinese character recognition system. We built hidden Markov models for 10% of total classes, then classify the rest of classes into already trained group classes. Finally group models are trained using group model clustered data. Recognition is performed using only group models, in order to achieve reduced model size and improved recognition speed.

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Prosody in Spoken Language Processing

  • Schafer Amy J.;Jun Sun-Ah
    • Proceedings of the Acoustical Society of Korea Conference
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    • spring
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    • pp.7-10
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    • 2000
  • Studies of prosody and sentence processing have demonstrated that prosodic phrasing can exhibit strong effects on processing decisions in English. In this paper, we tested Korean sentence fragments containing syntactically ambiguous Adj-N1-N2 strings in a cross-modal naming task. Four accentual phrasing patterns were tested: (a) the default phrasing pattern, in which each word forms an accentual phrase; (b) a phrasing biased toward N1 modification; (c) a phrasing biased toward complex-NP modification; and (d) a phrasing used with adjective focus. Patterns (b) and (c) are disambiguating phrasings; the other two are commonly found with both interpretations and are thus ambiguous. The results showed that the naming time of items produced in the prosody contradicting the semantic grouping is significantly longer than that produced in either default or supporting prosody, We claim that, as in English, prosodic information in Korean is parsed into a well-formed prosodic representation during the early stages of processing. The partially constructed prosodic representation produces incremental effects on syntactic and semantic processing decisions and is retained in memory to influence reanalysis decisions.

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K-means Clustering for Environmental Indicator Survey Data

  • Park, Hee-Chang;Cho, Kwang-Hyun
    • 한국데이터정보과학회:학술대회논문집
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    • 2005.04a
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    • pp.185-192
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    • 2005
  • There are many data mining techniques such as association rule, decision tree, neural network analysis, clustering, genetic algorithm, bayesian network, memory-based reasoning, etc. We analyze 2003 Gyeongnam social indicator survey data using k-means clustering technique for environmental information. Clustering is the process of grouping the data into clusters so that objects within a cluster have high similarity in comparison to one another. In this paper, we used k-means clustering of several clustering techniques. The k-means clustering is classified as a partitional clustering method. We can apply k-means clustering outputs to environmental preservation and environmental improvement.

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