• Journal of Korea Multimedia Society
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• v.12 no.5
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• pp.745-756
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• 2009

An autonomous virtual character can conduct itself like a human after recognizing and interpreting the virtual environment. Artificial vision is mainly used in the recognition of the environment for a virtual character. The present artificial vision that has been developed takes all the information at once from everything that comes into view. However, this can reduce the efficiency and reality of the system by saving too much information at once, and it also causes problems because the speed slows down in the dynamic environment of the game. Therefore, to construct a vision system similar to that of humans, a visual observation system which saves only the required information is needed. For that reason, this research focuses on the descriptive artificial intelligence engine which detects the most important information visually recognized by the character in the virtual world and saves it into the memory by degrees. In addition, a visual system is constructed in accordance with an image transaction theory to make it sense and recognize human feelings. This system finds the attention area of moving objects quickly and effectively through the experiment of the virtual environment with three dynamic dimensions. Also the experiment enhanced processing speed more than 1.6 times.

• Nutrition Research and Practice
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• v.8 no.5
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• pp.501-508
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• 2014

BACKGROUND/OBJECTIVES: Rubus Coreanus Miquel (RCM), used as a traditional Korean medicine, reduces chronic inflammatory diseases such as cancer and rheumatoid arthritis. However, its mechanism has not been elucidated. In this study, we examine the anti-inflammatory effects of RCM and their possible mechanisms using RAW 264.7 cells. MATERIALS/METHODS: Unripe RCM ethanol extract (UE), unripe RCM water extract (UH), ripe RCM ethanol extract (RE), and ripe RCM water extract (RH) were prepared. Inflammatory response was induced with LPS treatment, and expression of pro-inflammatory mediators (iNOS, COX-2, TNF-${\alpha}$, IL-$1{\beta}$, and IL-6) and NO and $PGE_2$ productions were assessed. To determine the anti-inflammatory mechanism of RCM, we measured NF-${\kappa}B$ and MAPK activities. RESULTS: UE and UH treatment significantly reduced NF-${\kappa}B$ activation and JNK and p38 phosphorylation and reduced transcriptional activities decreased iNOS, COX-2, and pro-inflammatory cytokines expressions, and NO and $PGE_2$ productions. RE and RH treatments reduced IL-$1{\beta}$ and IL-6 expressions through suppressions of JNK and p38 phosphorylation. CONCLUSIONS: In this study, we showed that RCM had anti-inflammatory effects by suppression of pro-inflammatory mediator expressions. Especially, unripe RCM showed strong anti-inflammatory effects through suppression of NF-${\kappa}B$ and MAPK activation. These findings suggest that unripe RCM might be used as a potential functional material to reduce chronic inflammatory responses.

• Journal of KIISE
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• v.41 no.10
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• pp.762-773
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• 2014

As the web of data is increasingly producing large RDFS datasets, it becomes essential in building scalable reasoning engines over large triples. There have been many researches used expensive distributed framework, such as Hadoop, to reason over large RDFS triples. However, in many cases we are required to handle millions of triples. In such cases, it is not necessary to deploy expensive distributed systems because logic program based reasoners in a single machine can produce similar reasoning performances with that of distributed reasoner using Hadoop. In this paper, we propose a scalable RDFS reasoner using logical programming methods in a single machine and compare our empirical results with that of distributed systems. We show that our logic programming based reasoner using a single machine performs as similar as expensive distributed reasoner does up to 200 million RDFS triples. In addition, we designed a meta data structure by decomposing the ontology triples into separate sectors. Instead of loading all the triples into a single model, we selected an appropriate subset of the triples for each ontology reasoning rule. Unification makes it easy to handle conjunctive queries for RDFS schema reasoning, therefore, we have designed and implemented RDFS axioms using logic programming unifications and efficient conjunctive query handling mechanisms. The throughputs of our approach reached to 166K Triples/sec over LUBM1500 with 200 million triples. It is comparable to that of WebPIE, distributed reasoner using Hadoop and Map Reduce, which performs 185K Triples/sec. We show that it is unnecessary to use the distributed system up to 200 million triples and the performance of logic programming based reasoner in a single machine becomes comparable with that of expensive distributed reasoner which employs Hadoop framework.

• Journal of KIISE
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• v.42 no.3
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• pp.307-319
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• 2015

Current ontology studies use the Hadoop distributed storage framework to perform map-reduce algorithm-based reasoning for scalable ontologies. In this paper, however, we propose a novel approach for scalable Web Ontology Language (OWL) Horst Lite ontology reasoning, based on distributed cluster memories. Rule-based reasoning, which is frequently used for scalable ontologies, iteratively executes triple-format ontology rules, until the inferred data no longer exists. Therefore, when the scalable ontology reasoning is performed on computer hard drives, the ontology reasoner suffers from performance limitations. In order to overcome this drawback, we propose an approach that loads the ontologies into distributed cluster memories, using Spark (a memory-based distributed computing framework), which executes the ontology reasoning. In order to implement an appropriate OWL Horst Lite ontology reasoning system on Spark, our method divides the scalable ontologies into blocks, loads each block into the cluster nodes, and subsequently handles the data in the distributed memories. We used the Lehigh University Benchmark, which is used to evaluate ontology inference and search speed, to experimentally evaluate the methods suggested in this paper, which we applied to LUBM8000 (1.1 billion triples, 155 gigabytes). When compared with WebPIE, a representative mapreduce algorithm-based scalable ontology reasoner, the proposed approach showed a throughput improvement of 320% (62k/s) over WebPIE (19k/s).

• Korean Journal of Remote Sensing
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• v.30 no.4
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• pp.493-503
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• 2014

A hierarchical classification scheme, which can reduce the spectral ambiguity and also reflect crop cultivation patterns from past land-cover maps, is presented for the purpose of the early production of crop classification maps in large-scale crop areas. Specifically, the effects of mixed pixels are minimized not only by applying a hierarchical classification approach based on different spectral characteristics from crop growth cycles, but also by considering temporal contextual information derived from past crop cultivation patterns. The applicability of the presented classification scheme was evaluated by a case study of Iowa State in USA with time-series MODIS 250 m Normalized Difference Vegetation Index(NDVI) data sets and past Cropland Data Layers(CDLs). Corn and soybean, which are major crop types in the study area and also display spectral similarity, could be properly classified by applying different classification stages and accounting for past crop cultivation patterns. The classification result by the presented scheme showed increases of minimum 7.68%p and maximum 20.96%p in overall accuracy, compared with one based on purely spectral information. In addition, the combination of temporal contextual information during classification was less affected by the number of NDVI data sets and the best overall accuracy of 86.63% was achieved. Thus, it is expected that this classification scheme can be effectively used for the early production of large-area crop classification maps in major feed-grain importing countries.

• Journal of Broadcast Engineering
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• v.12 no.1 s.34
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• pp.11-27
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• 2007

T-DMB(Terrestrial-Digital Multimedia Broadcasting) for portable and mobile broadcasting service was officially launched in the metropolitan area of Korea in December 2005. The development of interactive data services and the expansion of T-DMB network have been now progressed, and the regional T-DMB broadcasters will be selected in the near future. Although it is important to evaluate service area and reduce a fringe area for optimizing RF coverage of T-DMB, there was no professional system to support those works, and therefore lots of resources in budget, manpower and time were required. The measurement considering characteristics of SFN(Single Frequency Network) is essential in the implementation of T-DMB network which needs to control synchronization, spacing and output power of transmitters. In addition, mobile measurement, enough measured parameters for many-sided analysis of reception quality, efficient management of enormous measured data and representation of measured results on the electronic map are also important in evaluating service area. In this paper, we derived requirements for a new measurement system in T-DMB by considering the above details, and we proposed and developed an integrated measurement and analysis system. The developed system was applied to the implementation of T-DMB network of KBS and field tests, and it proved its efficiency and accuracy in result.

• Journal of Microbiology and Biotechnology
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• v.28 no.11
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• pp.1916-1927
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• 2018

Corynebacterium glutamicum is an excellent platform for the production of amino acids, and is widely used in the fermentation industry. Most industrial strains are traditionally obtained by repeated processes of random mutation and selection, but the genotype of these strains is often unclear owing to the absence of genomic information. As such, it is difficult to improve the growth and amino acid production of these strains via metabolic engineering. In this study, we generated a complete genome map of an industrial L-valine-producing strain, C. glutamicum XV. In order to establish the relationship between genotypes and physiological characteristics, a comparative genomic analysis was performed to explore the core genome, structural variations, and gene mutations referring to an industrial L-leucine-producing strain, C. glutamicum CP, and the widely used C. glutamicum ATCC 13032. The results indicate that a 36,349 bp repeat sequence in the CP genome contained an additional copy each of lrp and brnFE genes, which benefited the export of L-leucine. However, in XV, the kgd and panB genes were disrupted by nucleotide insertion, which increase the availability of precursors to synthesize L-valine. Moreover, the specific amino acid substitutions in key enzymes increased their activities. Additionally, a novel strategy is proposed to remodel central carbon metabolism and reduce pyruvate consumption without having a negative impact on cell growth by introducing the CP-derived mutant $H^+$/citrate symporter. These results further our understanding regarding the metabolic networks in these strains and help to elucidate the influence of different genotypes on these processes.

• KIEAE Journal
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• v.15 no.2
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• pp.19-26
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• 2015

Purpose: Maximizing human comfort in design of medical environments depends immensely on specialized architects particularly critical care design; the study proposes Evidence-Based Design as an apparent analog to Evidence-Based Medicine. Healthcare facility designs are substantially based on the findings of study in an effort to design environments that augment care by improving patient safety and being therapeutic. On SPSS (Statistical Package for Social Science) t-test is applied to simulate two independent variables of PDR (Pre Design-Research) and POE (Post- Occupancy Evaluation). PDR is conducted on relatively new hospital Hallym University Dongtan Sacred Heart Hospital to analyse visibility from researchers' point of view, here the ICU is arranged in I-Shape. POE is applied on Dongguk University Ilsan Hospital to simulate walking on LogWare where two NS are designed based on L- Shape and Seoul St. Mary's Hospital, The Catholic University of Korea where five NS are functional for ICU Intensive Care Unit, Surgical Intensive Care Unit (SICU), Medical Intensive Care Unit (MICU), Critical Care Unit (CCU), Korean Oriental Medical Care Unit which are mostly arranged in U-Shape, and walking pattern is recognized to be in a zigzag path. Method: T-Test is applied on two dependent communication variables: walkability and visibility, with confidence interval of 95%. This study systematically analyses the Nurse Station (NS) typo-morphology, and simulates nurse horizontal circulation, by computing round route visits to patient's bed, then estimating minimum round route on LogWare stop sequence software. The visual connectivity is measured on depth map graphs. Hence the aim is to reduce staff stress and fatigue for better patients care by minimizing staff horizontal travel time and to facilitate nurse walk path and support space distribution by increasing effectiveness in delivering care. Result: Applying visibility graph and isovist field on space syntax on I- Shape, L- Shape and U- Shape ICU (SICU, MICU and CCU) configuration, I-shape facilitated 20% more patients in linear view as they stir to rise from their beds from nurse station compared to U-shape. In conclusion, it was proved that U-Shape supply minimum walking and maximum visibility; and L shape provides just visibility as the nurse is at pivot. I shape provides panoramic view from the Nurse Station but very rigorous walking.

• Journal of KIISE:Software and Applications
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• v.36 no.12
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• pp.967-976
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• 2009

In this paper, we propose an automatic lower extremity vessel extraction based on rigid registration and bone elimination techniques in CT and CT angiography images. First, automatic partitioning of the lower extremity based on the anatomy is proposed to consider the local movement of the bone. Second, rigid registration based on distance map is performed to estimate the movement of the bone between CT and CT angiography images. Third, bone elimination and vessel masking techniques are proposed to remove bones in CT angiography image and to prevent the vessel near to bone from eroding. Fourth, post-processing based on vessel tracking is proposed to reduce the effect of misalignment and noises like a cartilage. For the evaluation of our method, we performed the visual inspection, accuracy measures and processing time. For visual inspection, the results of applying general subtraction, registered subtraction and proposed method are compared using volume rendering and maximum intensity projection. For accuracy evaluation, intensity distributions of CT angiography image, subtraction based method and proposed method are analyzed. Experimental result shows that bones are accurately eliminated and vessels are robustly extracted without the loss of other structure. The total processing time of thirteen patient datasets was 40 seconds on average.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.4
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• pp.181-196
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• 2019

Floods can be caused by a variety of factors, and the main cause of floods is the exceeding of urban drainage system or river capacity. In addition, rainfall frequently occurs that causes large watershed runoff. Since the existing methodology of preparing for flood risk map is based on hydraulic and hydrological modeling, it is difficult to analyse for a large area because it takes a long time due to the extensive data collection and complex analysis process. In order to overcome this problem, this study proposes a methodology of mapping for flood vulnerable area that considered the surface runoff mechanism. This makes it possible to reduce the time and effort required to estimate flood vulnerabilities and enable detailed analysis of large areas. The target area is Seoul, and it was confirmed that flood damage is likely to occur near selected vulnerable areas by verifying using 2×2 confusion matrix and ROC curve. By selecting and prioritizing flood vulnerable areas through the surface runoff mechanism proposed in this study, the establishment of systematic disaster prevention measures and efficient budget allocation will be possible.