• Journal of KIISE:Computer Systems and Theory
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• v.27 no.2
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• pp.177-187
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• 2000

In the past several years, many systems which adopted ring topology with high-speed unidirectional point-to-point links have emerged to overcome the limit of bus for interconnection network of clustered multiprocessor system. However, rapid increase of processor speed and performance improvement of local bus and memory system limit scalability of system with point-to-point link of standard bandwidth. Therefore, necessity to extend bandwidth is emphasized. In this paper, we adopt PANDA system as base model, which is clustering-based multiprocessor system. By simulating a model adopting commercial processor and local bus specification, we show that point-to-point link is bottleneck of system performance, and bandwidth expansion by more than 200% is needed. To expand bandwidth of interconnection network, it needs excessive design cost and time to develop new point-to-point link with doubled bandwidth. As an alternative to double bandwidth, we propose several ways to implement dual ring -simple dual ring, transaction-separated dual ring, direction-separated dual ring- by using off-the-shelf point-to-point links with IEEE standard bandwidth. We analyze pros. and cons. of each model compared with doubled-bandwidth single ring by simulation.

• The Bulletin of The Korean Astronomical Society
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• v.43 no.1
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• pp.34.2-35
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• 2018

Galaxy transition from star-forming to quiescent, accompanied with morphology transformation, is one of the key unresolved issues in extragalactic astronomy. Although several environmental mechanisms have been proposed, a deeper understanding of the impact of environment on galaxy transition still requires much exploration. My Ph.D. thesis focuses on which environmental mechanisms are primarily responsible for galaxy transition in different environments and looks at what happens during the transition phase using multi-wavelength photometric/spectroscopic data, from UV to mid-infrared (MIR), derived from several large surveys (GALEX, SDSS, and WISE) and our GMOS-North IFU observations. Our multi-wavelength approach provides new insights into the *late* stages of galaxy transition with a definition of the MIR green valley different from the optical green valley. I will present highlights from three areas in my thesis. First, through an in-depth study of environmental dependence of various properties of galaxies in a nearby supercluster A2199 (Lee et al. 2015), we found that the star formation of galaxies is quenched before the galaxies enter the MIR green valley, which is driven mainly by strangulation. Then, the morphological transformation from late- to early-type galaxies occurs in the MIR green valley. The main environmental mechanisms for the morphological transformation are galaxy-galaxy mergers and interactions that are likely to happen in high-density regions such as galaxy groups/clusters. After the transformation, early-type MIR green valley galaxies keep the memory of their last star formation for several Gyr until they move on to the next stage for completely quiescent galaxies. Second, compact groups (CGs) of galaxies are the most favorable environments for galaxy interactions. We studied MIR properties of galaxies in CGs and their environmental dependence (Lee et al. 2017), using a sample of 670 CGs identified using a friends-of-friends algorithms. We found that MIR [3.4]-[12] colors of CG galaxies are, on average, bluer than those of cluster galaxies. As CGs are located in denser regions, they tend to have larger early-type galaxy fractions and bluer MIR color galaxies. These trends can also be seen for neighboring galaxies around CGs. However, CG members always have larger early-type fractions and bluer MIR colors than their neighboring galaxies. These results suggest that galaxy evolution is faster in CGs than in other environments and that CGs are likely to be the best place for pre-processing. Third, post-starburst galaxies (PSBs) are an ideal laboratory to investigate the details of the transition phase. Their spectra reveal a phase of vigorous star formation activity, which is abruptly ended within the last 1 Gyr. Numerical simulations predict that the starburst, and thus the current A-type stellar population, should be localized within the galaxy's center (< kpc). Yet our GMOS IFU observations show otherwise; all five PSBs in our sample have Hdelta absorption line profiles that extend well beyond the central kpc. Most interestingly, we found a negative correlation between the Hdelta gradient slopes and the fractions of the stellar mass produced during the starburst, suggesting that stronger starbursts are more centrally-concentrated. I will discuss the results in relation with the origin of PSBs.

• The KIPS Transactions:PartD
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• v.10D no.1
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• pp.1-12
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• 2003

Recently, there have been many indexing schemes for multimedia data such as image, video data. But recent database applications, for example data mining and multimedia database, are required to support multi-user environment. In order for indexing schemes to be useful in multi-user environment, a concurrency control algorithm is required to handle it. So we propose a concurrency control algorithm that can be applied to CBF (cell-based filtering method), which uses the signature of the cell for alleviating the dimensional curse problem. In addition, we extend the SHORE storage system of Wisconsin university in order to handle high-dimensional data. This extended SHORE storage system provides conventional storage manager functions, guarantees the integrity of high-dimensional data and is flexible to the large scale of feature vectors for preventing the usage of large main memory. Finally, we implement the web-based image retrieval system by using the extended SHORE storage system. The key feature of this system is platform-independent access to the high-dimensional data as well as functionality of efficient content-based queries. Lastly. We evaluate an average response time of point query, range query and k-nearest query in terms of the number of threads.

• Journal of Life Science
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• v.27 no.11
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• pp.1308-1314
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• 2017

The Chinese red-headed centipede Scolopendra subspinipes mutilans, a member of the arthropod class Chilopoda, is a traditional medicine used for the treatment of several allergic diseases, such as atopy. S. subspinipes mutilans samples were collected from different regions of South Korea: Sancheong, Gyeongnam; Yeonggwang, Jeonnam and Jeju-do. The nutritional values of the centipedes were analyzed to extend the species' applications. The crude protein and fat contents of all samples were high and ranged from 54.9-55.8% and from 26.8-30.6%, respectively. Essential amino acids were present; lysine was the most common and accounted for 3.4-3.6% of the essential amino acids. Glutamic acid, which assists in improving concentration, memory and other cognitive abilities, was the most common non-essential amino acid at 6.8-7.1%. It had a similar content percentage in all three regions' samples. Additionally, unsaturated fatty acids were present, and oleic acid, which prevents cancer and cardiac disease, was the most common at 41.3-48.6% of each sample. Mercury, a hazardous substance, was detected at a range of 0.08-0.11 mg/kg in all samples; the amount was lower than the standard food allowance. Additionally, no pathogenic microorganisms, such as Escherichia coli and Salmonella spp., were detected. There were no significant differences between the nutritional factors of the S. subspinipes mutilans samples from the three regions. Based on the nutritional analysis, Chinese red-headed centipedes have the potential to be food and medicinal ingredients due to their proteins, essential amino acids, unsaturated fatty acids and nutritive capacities.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.43 no.7 s.349
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• pp.1-13
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• 2006

In this paper, we introduce a novel key management scheme that is based on the key pre-distribution but provides the key re-distribution method, in order to manage keys for message encryption and authentication of lower-layer sensor nodes on hierarchical mobile sensor networks. The characteristics of our key management are as follows: First, the role of key management is distributed to aggregator nodes as well as a sink node, to overcome the weakness of centralized management. Second, a sink node generates keys using regression model, thus it stores only the information for calculating the keys using the key information received from nodes, but does not store the relationship between a node and a key, and the keys themselves. As the disadvantage of existing key pre-distributions, they do not support the key re-distribution after the deployment of nodes, and it is hard to extend the key information in the case that sensor nodes in the network enlarge. Thirdly, our mechanism provides the resilience to node capture(${\lambda}$-security), also provided by the existing key pre-distributions, and fourth offers the key freshness through key re-distribution, key distribution to mobile nodes, and scalability to make up for the weak points in the existing key pre-distributions. Fifth, our mechanism does not fix the relationship between a node and a key, thus supports the anonymity and untraceability of mobile nodes. Lastly, we compare ours with existing mechanisms, and verify our performance through the overhead analysis of communication, computation, and memory.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.10
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• pp.1277-1286
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• 2018

In this paper, we provide flexible scalability of computing resources in cloud environment and Apache Hadoop based cloud environment for analysis of public medical information big data. In fact, it includes the ability to quickly and flexibly extend storage, memory, and other resources in a situation where log data accumulates or grows over time. In addition, when real-time analysis of accumulated unstructured log data is required, the system adopts Hadoop-based analysis module to overcome the processing limit of existing analysis tools. Therefore, it provides a function to perform parallel distributed processing of a large amount of log data quickly and reliably. Perform frequency analysis and chi-square test for big data analysis. In addition, multivariate logistic regression analysis of significance level 0.05 and multivariate logistic regression analysis of meaningful variables (p<0.05) were performed. Multivariate logistic regression analysis was performed for each model 3.

• Journal of KIISE:Software and Applications
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• v.30 no.12
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• pp.1185-1192
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• 2003

In the component assembly and composition technique of software architecture, It is operated that the existing composition techniques based on architecture, ACME, Wright etc., used in FIFO with the direct connection structure between components through connector's Role. But, when the non-synchronizing request of components that have different characteristics occurs, the FIFO techniques is applied to the connector is difficult to process and operate effectively because of the high performance component waiting the sequence order if the low performance component is allocated first. Thus, the allocated request process according to the priority considering the characteristics of each call components in connector is necessary to improve the operation of assembled component. In this research, we extend the connector part that is available in multiplex connection structure based on existent Wright specification. For service process requested from component, the connector part is designed and implemented to operating with priority sequence through calculating the weight of CPU use rate, bean requesting process time and memory use rate among the efficiency elements of assembled components. To verify the efficiency if this designed connector, we implemented 20 samples EJB components that have different efficiency characteristics and applied these samples components to designed connector. The operating results with this designed connector show that the efficient operation of whole system is possible though the processing time takes 481ms more than the time of the existing FIFO techniques.

• The KIPS Transactions:PartA
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• v.16A no.2
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• pp.69-78
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• 2009

One of the most effective way to improve cache performance is to exploit both temporal and spatial locality given by any program executive characteristics. In this paper we present a high performance and low power cache structure with a bank selection mechanism that enhances exploitation of spatial and temporal locality. The proposed cache system consists of two parts, i.e., a main direct-mapped cache with a small block size and a fully associative buffer with a large block size as a multiple of the small block size. Especially, the main direct-mapped cache is constructed as two banks for low power consumption and stores a small block which is selected from fully associative buffer by the proposed bank selection algorithm. By using the bank selection algorithm and three state bits, We selectively extend the lifetime of those small blocks with high temporal locality by storing them in the main direct-mapped caches. This approach effectively reduces conflict misses and cache pollution at the same time. According to the simulation results, the average miss ratio, compared with the Victim and STAS caches with the same size, is improved by about 23% and 32% for Mibench applications respectively. The average memory access time is reduced by about 14% and 18% compared with the he victim and STAS caches respectively. It is also shown that energy consumption of the proposed cache is around 10% lower than other cache systems that we examine.

• Spatial Information Research
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• v.20 no.5
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• pp.99-109
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• 2012

Recently, due to the growth of social media and spread of smart-phone, the amount of data has considerably increased by full use of SNS (Social Network Service). According to it, the Big Data concept is come up and many researchers are seeking solutions to make the best use of big data. To maximize the creative value of the big data held by many companies, it is required to combine them with existing data. The physical and theoretical storage structures of data sources are so different that a system which can integrate and manage them is needed. In order to process big data, MapReduce is developed as a system which has advantages over processing data fast by distributed processing. However, it is difficult to construct and store a system for all key words. Due to the process of storage and search, it is to some extent difficult to do real-time processing. And it makes extra expenses to process complex event without structure of processing different data. In order to solve this problem, the existing Complex Event Processing System is supposed to be used. When it comes to complex event processing system, it gets data from different sources and combines them with each other to make it possible to do complex event processing that is useful for real-time processing specially in stream data. Nevertheless, unstructured data based on text of SNS and internet articles is managed as text type and there is a need to compare strings every time the query processing should be done. And it results in poor performance. Therefore, we try to make it possible to manage unstructured data and do query process fast in complex event processing system. And we extend the data complex function for giving theoretical schema of string. It is completed by changing the string key word into integer type with filtering which uses keyword set. In addition, by using the Complex Event Processing System and processing stream data at real-time of in-memory, we try to reduce the time of reading the query processing after it is stored in the disk.