• Title/Summary/Keyword: Memory Mapping

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An XML Data Management System and Its Application to Genome Databases (XML 데이타 관리시스템과 유전체 데이타베이스에의 응용)

  • 이경희;김태경;김선신;이충세;조완섭
    • Journal of KIISE:Databases
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    • v.31 no.4
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    • pp.432-443
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    • 2004
  • As the XML data has been widely used in the Internet, it is necessary to store and retrieve the XML data by using DBMSs. However, relational DBMSs suffer from the model difference between graph structure of the XML data and table forms in relational databases. We propose an ORDBMS-based DTD-dependent XML data management system Xing. Xing stores XML data in a DTD-dependent form in an object database. Since the object database schema has a graph structure and supports multi-valued attributes, mapping from an XML data model and queries into an object data model and OQLs is a simple problem. For rapid storing of large quantities of the XML data, we use SAX parser with customized Xing-tree which requires a small memory space compared with the DOM-tree. Xing also returns the query result in an XML document form. We have implemented the Xing system on top of UniSQL object-relational DBMS for the validity checking and performance comparison. For XML genome data from GenBank, and experimental evaluation shows that Xing can provide significant performance improvement (maximum 10 times) compared with the relational approach.

Understanding Neurogastroenterology From Neuroimaging Perspective: A Comprehensive Review of Functional and Structural Brain Imaging in Functional Gastrointestinal Disorders

  • Kano, Michiko;Dupont, Patrick;Aziz, Qasim;Fukudo, Shin
    • Journal of Neurogastroenterology and Motility
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    • v.24 no.4
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    • pp.512-527
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    • 2018
  • This review provides a comprehensive overview of brain imaging studies of the brain-gut interaction in functional gastrointestinal disorders (FGIDs). Functional neuroimaging studies during gut stimulation have shown enhanced brain responses in regions related to sensory processing of the homeostatic condition of the gut (homeostatic afferent) and responses to salience stimuli (salience network), as well as increased and decreased brain activity in the emotional response areas and reduced activation in areas associated with the top-down modulation of visceral afferent signals. Altered central regulation of the endocrine and autonomic nervous responses, the key mediators of the brain-gut axis, has been demonstrated. Studies using resting-state functional magnetic resonance imaging reported abnormal local and global connectivity in the areas related to pain processing and the default mode network (a physiological baseline of brain activity at rest associated with self-awareness and memory) in FGIDs. Structural imaging with brain morphometry and diffusion imaging demonstrated altered gray- and white-matter structures in areas that also showed changes in functional imaging studies, although this requires replication. Molecular imaging by magnetic resonance spectroscopy and positron emission tomography in FGIDs remains relatively sparse. Progress using analytical methods such as machine learning algorithms may shift neuroimaging studies from brain mapping to predicting clinical outcomes. Because several factors contribute to the pathophysiology of FGIDs and because its population is quite heterogeneous, a new model is needed in future studies to assess the importance of the factors and brain functions that are responsible for an optimal homeostatic state.

Development of Data Visualized Web System for Virtual Power Forecasting based on Open Sources based Location Services using Deep Learning (오픈소스 기반 지도 서비스를 이용한 딥러닝 실시간 가상 전력수요 예측 가시화 웹 시스템)

  • Lee, JeongHwi;Kim, Dong Keun
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.25 no.8
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    • pp.1005-1012
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    • 2021
  • Recently, the use of various location-based services-based location information systems using maps on the web has been expanding, and there is a need for a monitoring system that can check power demand in real time as an alternative to energy saving. In this study, we developed a deep learning real-time virtual power demand prediction web system using open source-based mapping service to analyze and predict the characteristics of power demand data using deep learning. In particular, the proposed system uses the LSTM(Long Short-Term Memory) deep learning model to enable power demand and predictive analysis locally, and provides visualization of analyzed information. Future proposed systems will not only be utilized to identify and analyze the supply and demand and forecast status of energy by region, but also apply to other industrial energies.

An Efficient Array Algorithm for VLSI Implementation of Vector-radix 2-D Fast Discrete Cosine Transform (Vector-radix 2차원 고속 DCT의 VLSI 구현을 위한 효율적인 어레이 알고리듬)

  • 신경욱;전흥우;강용섬
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.18 no.12
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    • pp.1970-1982
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    • 1993
  • This paper describes an efficient array algorithm for parallel computation of vector-radix two-dimensional (2-D) fast discrete cosine transform (VR-FCT), and its VLSI implementation. By mapping the 2-D VR-FCT onto a 2-D array of processing elements (PEs), the butterfly structure of the VR-FCT can be efficiently importanted with high concurrency and local communication geometry. The proposed array algorithm features architectural modularity, regularity and locality, so that it is very suitable for VLSI realization. Also, no transposition memory is required, which is invitable in the conventional row-column decomposition approach. It has the time complexity of O(N+Nnzp-log2N) for (N*N) 2-D DCT, where Nnzd is the number of non-zero digits in canonic-signed digit(CSD) code, By adopting the CSD arithmetic in circuit desine, the number of addition is reduced by about 30%, as compared to the 2`s complement arithmetic. The computational accuracy analysis for finite wordlength processing is presented. From simulation result, it is estimated that (8*8) 2-D DCT (with Nnzp=4) can be computed in about 0.88 sec at 50 MHz clock frequency, resulting in the throughput rate of about 72 Mega pixels per second.

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OpenGL ES 1.1 Implementation Using OpenGL (OpenGL을 이용한 OpenGL ES 1.1 구현)

  • Lee, Hwan-Yong;Baek, Nak-Hoon
    • The KIPS Transactions:PartA
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    • v.16A no.3
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    • pp.159-168
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    • 2009
  • In this paper, we present an efficient way of implementing OpenGL ES 1.1 standard for the environments with hardware-supported OpenGL API, such as desktop PCs. Although OpenGL ES was started from the existing OpenGL features, it becomes a new three-dimensional graphics library customized for embedded systems through introducing fixed-point arithmetic operations, buffer management with fixed-point data type supports, completely new texture mapping functionalities and others. Currently, it is the official three dimensional graphics library for Google Android, Apple iPhone, PlayStation3, etc. In this paper, we achieved improvements on the arithmetic operations for the fixed-point number representation, which is the most characteristic data type for OpenGL ES. For the conversion of fixed-point data types to the floating-point number representations for the underlying OpenGL, we show the way of efficient conversion processes even with satisfying OpenGL ES standard requirements. We also introduced a simple memory management scheme to mange the converted data for the buffer containing fixed-point numbers. In the case of texture processing, the requirements in both standards are quite different and thus we used completely new software-implementations. Our final implementation result of OpenGL ES library provides all of over than 200 functions in OpenGL ES 1.1 standard and completely passed its conformance test, to show its compliance with the standard. From the efficiency viewpoint, we measured its execution times for several OpenGL ES-specific application programs and achieved at most 33.147 times improvements, to become the fastest one among the OpenGL ES implementations in the same category.

On the Performance of Sample-Adaptive Product Quantizer for Noisy Channels (표본적응 프러덕트 양자기의 전송로 잡음에서의 성능 분석에 관한 연구)

  • Kim Dong Sik
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.42 no.3 s.303
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    • pp.81-90
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    • 2005
  • When we transmit signals, which are quantized by the vector quantizer (VQ), through noisy channels, the overall performance of the coding system is very dependent on the employed quantization scheme and the channel error effect. In order to design an optimal coding system, the source and channel coding scheme should be jointly optimized as in the channel-optimized VQ. As a suboptimal approach, we may consider the robust VQ (RVQ). In RVQ, we consider developing an index assignment function for mapping the output of quantizers to channel symbols so that the effect of the channel errors is minimized. Recently, a VQ, which can reduce the encoding complexity and is called the sample-adaptive product quantizer (SAPQ), has been proposed. SAPQ has very similar quantizer structure as to the product quantizer (PQ). However, the quantization performance can be better than PQ. Further, the encoding complexity and the memory requirement for the codebooks are lower than the regular full-search VQ case. In this paper, SAPQ is employed in order to design an RVQ to channel errors by reducing the vector dimension. Discussions on the codebook structure of SAPQ and experiments are introduced in an aspect of robustness to noisy channels.

A Study on the Development of Intelligent Markup Indicator (IMI) Technology for Underground Facilities Management Using IoT (IoT를 이용한 지하매설물관리용 지능형표지기(IMI) 기술개발에 관한 연구)

  • Kim, Tai-Dal
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.17 no.3
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    • pp.129-136
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    • 2017
  • Geographic Information System The geographic information system (GIS) has been limited to the government and some public sectors. Recently, the market has been diversified by combining with other areas such as mobile and CRM (Customer Relationship Management). The development direction of GIS technology in the 21st century is Web GIS, 3D GIS, mobile GIS, LBS, etc. as general technology for GIS application system development and spatial information service. In this study, we developed a new concept marking nail (a marking nail with built - in intelligent storage memory device) from the function of simple positioning of a marking nail related to a previously used underground item,, Burial depth, pipe thickness, piping material, management agency, contractor, contact, etc.) and store it in DB server, if necessary.Make it available in the right place. Through this research, it is possible to prevent and minimize various accidents caused by irregular excavation works, etc., and to provide information for establishing countermeasures related to sink holes. In order to provide systematic and reliable information on underground burial management, it was proposed to input information conveniently in the field, and the purpose was to reduce the incidence of buried underground pipes absolutely.

Selective Skin Tone Reproduction using Preferred Skin Colors (선호 피부색을 사용한 선택적인 피부색 재현 기법)

  • Kim, Dae-Chul;Kyung, Wang-Jun;Ha, Yeong-Ho
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.49 no.4
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    • pp.10-15
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    • 2012
  • In a color image, people and especially facial patterns are important and interesting visual objects. Thus, effective skin color reproduction is essential, as skin color is a key memory color in color application systems. Previous studies suggested skin color reproduction by mapping only to the center value of preferred skin region. However, it is not suitable to determine one preference color because preference color from the observer's preference test is not dominant. In this paper, skin color reproduction using multiple preferred skin colors for each race is proposed. The proposed method first defines multiple preferred skin colors for each race according to their luminance level. After that, skin region is detected in an image. The race is then selected by calculating distance between average chromaticity of detected region and that of each racial skin from a database to assign preferred skin color for each race. Next, each corresponding preferred skin color is determined for each selected race. Finally, input skin color is proportionally mapped toward preferred skin color according to the difference between the input skin color and the preferred skin color for a smoothly reproduced skin color. In the experimental results, the proposed method gives better color correction on the objective and subjective evaluation than the previous methods.

Analysis on the Performance and Temperature of the 3D Quad-core Processor according to Cache Organization (캐쉬 구성에 따른 3차원 쿼드코어 프로세서의 성능 및 온도 분석)

  • Son, Dong-Oh;Ahn, Jin-Woo;Choi, Hong-Jun;Kim, Jong-Myon;Kim, Cheol-Hong
    • Journal of the Korea Society of Computer and Information
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    • v.17 no.6
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    • pp.1-11
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    • 2012
  • As the process technology scales down, multi-core processors cause serious problems such as increased interconnection delay, high power consumption and thermal problems. To solve the problems in 2D multi-core processors, researchers have focused on the 3D multi-core processor architecture. Compared to the 2D multi-core processor, the 3D multi-core processor decreases interconnection delay by reducing wire length significantly, since each core on different layers is connected using vertical through-silicon via(TSV). However, the power density in the 3D multi-core processor is increased dramatically compared to that in the 2D multi-core processor, because multiple cores are stacked vertically. Unfortunately, increased power density causes thermal problems, resulting in high cooling cost, negative impact on the reliability. Therefore, temperature should be considered together with performance in designing 3D multi-core processors. In this work, we analyze the temperature of the cache in quad-core processors varying cache organization. Then, we propose the low-temperature cache organization to overcome the thermal problems. Our evaluation shows that peak temperature of the instruction cache is lower than threshold. The peak temperature of the data cache is higher than threshold when the cache is composed of many ways. According to the results, our proposed cache organization not only efficiently reduces the peak temperature but also reduces the performance degradation for 3D quad-core processors.

Mobile Cloud Context-Awareness System based on Jess Inference and Semantic Web RL for Inference Cost Decline (추론 비용 감소를 위한 Jess 추론과 시멘틱 웹 RL기반의 모바일 클라우드 상황인식 시스템)

  • Jung, Se-Hoon;Sim, Chun-Bo
    • KIPS Transactions on Software and Data Engineering
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    • v.1 no.1
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    • pp.19-30
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    • 2012
  • The context aware service is the service to provide useful information to the users by recognizing surroundings around people who receive the service via computer based on computing and communication, and by conducting self-decision. But CAS(Context Awareness System) shows the weak point of small-scale context awareness processing capacity due to restricted mobile function under the current mobile environment, memory space, and inference cost increment. In this paper, we propose a mobile cloud context system with using Google App Engine based on PaaS(Platform as a Service) in order to get context service in various mobile devices without any subordination to any specific platform. Inference design method of the proposed system makes use of knowledge-based framework with semantic inference that is presented by SWRL rule and OWL ontology and Jess with rule-based inference engine. As well as, it is intended to shorten the context service reasoning time with mapping the regular reasoning of SWRL to Jess reasoning engine by connecting the values such as Class, Property and Individual which are regular information in the form of SWRL to Jess reasoning engine via JessTab plug-in in order to overcome the demerit of queries reasoning method of SparQL in semantic search which is a previous reasoning method.