• Journal of KIISE:Computer Systems and Theory
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• v.33 no.5
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• pp.306-315
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• 2006

In general, the hit ratio of the first level cache is one of the most important factors in determining the performance of computer systems. Prefetching from lower level memory structure is one of the most useful techniques for improving the hit ratio of the first level cache. In this paper, we propose a prefetch on continuous same page access (CSPA) scheme which improves the prefetch efficiency of the instruction cache and reduces prefetch cost at the same time. The proposed CSPA scheme traces the page addresses of executed instructions to count how many times the same memory page is accessed continuously. To increase the prefetch efficiency, the CSPA scheme initiates prefetch only if the number of accesses to the same page exceeds the threshold value. Generally, the size of a L1 cache block is smaller than that of a L2 cache block. Therefore, one L2 cache block contains a number of L1 cache blocks. To reduce the number of unnecessary accesses to the L2 cache due to prefetch, the CSPA scheme enables prefetch only when the missed L1 block and the prefetch L1 block are in the same L2 cache block, leading to reduced prefetch cost. According to our simulations, the proposed prefetching scheme improves the performance by up to 6.7%.

• Journal of the Korean Society for Library and Information Science
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• v.49 no.3
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• pp.155-183
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• 2015

The rapid growth of information technologies and data networks has increased the volume of data generated from scholarly research and the possibilities of re-using and sharing such data. However, there is a serious problem of management and sharing of research data due to the lack of facilitating policies and supporting infrastructure. In particular, few data repositories exist that support systematic collection and sharing of research data in the humanities. In this regard, the Korea Research Memory (KRM) established by the Korea Research Foundation is a rare exception. The purpose of this research is to present specific processes and strategies that can facilitate the data collection, reuse and preservation through the KRM using task analysis and source document gathering as main focal points. In addition, in order for the effective collection and sharing of research data, the following recommendations are proposed: 1) the need for the adoption of data management plan related policies that govern the collection and sharing of research data generated from publicly funded research projects, 2) the need for training and support services for individual researchers and research institutes, 3) the need for training data specialists, and 4) the citation scheme and structure designed for research data.

• Journal of KIISE:Computer Systems and Theory
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• v.29 no.4
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• pp.232-243
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• 2002

There are many methods for improving TLB (translation lookaside buffer) performance, such as increasing the number of entry in TLB, supporting large page or multiple page sizes. The best way is to support multiple page sizes, but any operating system doesn't support multiple page sizes in user mode. So, we propose the new structure of TLB supporting two pages to obtain the effect of multiple page sizes with high performance and at low cost without operating system support. we propose a new TLB structure supporting two page sizes dynamically and selectively for high performance and low cost design without any operating system support. For high performance, a promotion-TLB is designed by supporting two page sizes. Also in order to attain low power consumption, a banked-TLB is constructed by dividing one fully associative TLB space into two sub-fully associative TLBs. These two banked-TLB structures are integrated into a banked-promotion TLB as a low power and high performance TLB structure for embedded processors. According to the results of comparison and analysis, a similar performance can be achieved by using fewer TLB entries and also power consumption can be reduced by around 50% comparing with the fully associative TLB.

• Korean Journal of Remote Sensing
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• v.13 no.1
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• pp.13-30
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• 1997

Recent improvements of satellite remote sensing sensors which are represented by hyperspectral imaging sensors and high spatial resolution sensors provide a large amount of data, typically several hundred megabytes per one scene. Moreover, increasing information exchange via internet and information super-highway requires the developments of more active service systems for processing and analysing of remote sensing data in order to provide value-added products. In this sense, an advanced satellite data processing system is being developed to achive high performance in computing speed and efficieney in processing a huge volume of data, and to make possible network computing and easy improving, upgrading and managing of systems. JAVA internet programming language provides several advantages for developing software such as object-oriented programming, multi-threading and robust memory managent. Using these features, a satellite data processing system named as GeoPixel has been developing using JAVA language. The GeoPixel adopted newly developed techniques including object-pipe connect method between each process and multi-threading structure. In other words, this system has characteristics such as independent operating platform and efficient data processing by handling a huge volume of remote sensing data with robustness. In the evaluation of data processing capability, the satisfactory results were shown in utilizing computer resources(CPU and Memory) and processing speeds.

• Biomolecules & Therapeutics
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• v.27 no.3
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• pp.327-335
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• 2019

As the elderly population is increasing, Alzheimer's disease (AD) has become a global issue and many clinical trials have been conducted to evaluate treatments for AD. As these clinical trials have been conducted and have failed, the development of new theraphies for AD with fewer adverse effects remains a challenge. In this study, we examined the effects of Theracurmin on cognitive decline using 5XFAD mice, an AD mouse model. Theracurmin is more bioavailable form of curcumin, generated with submicron colloidal dispersion. Mice were treated with Theracurmin (100, 300 and 1,000 mg/kg) for 12 weeks and were subjected to the novel object recognition test and the Barnes maze test. Theracurmin-treated mice showed significant amelioration in recognition and spatial memories compared those of the vehicle-treated controls. In addition, the antioxidant activities of Theracurmin were investigated by measuring the superoxide dismutase (SOD) activity, malondialdehyde (MDA) and glutathione (GSH) levels. The increased MDA level and decreased SOD and GSH levels in the vehicle-treated 5XFAD mice were significantly reversed by the administration of Theracurmin. Moreover, we observed that Theracurmin administration elevated the expression levels of synaptic components, including synaptophysin and post synaptic density protein 95, and decreased the expression levels of ionized calcium-binding adapter molecule 1 (Iba-1), a marker of activated microglia. These results suggest that Theracurmin ameliorates cognitive function by increasing the expression of synaptic components and by preventing neuronal cell damage from oxidative stress or from the activation of microglia. Thus, Theracurmin would be useful for treating the cognitive dysfunctions observed in AD.

• Journal of Service Research and Studies
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• v.13 no.2
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• pp.99-113
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• 2023

In a customer-based industry, customer retention is the competitiveness of a company, and improving customer retention improves the competitiveness of the company. Therefore, accurate prediction and management of potential dormant customers is paramount to increasing the competitiveness of the enterprise. In particular, there are numerous competitors in the domestic card industry, and the government is introducing an automatic closing system for dormant card management. As a result of these social changes, the card industry must focus on better predicting and managing potential dormant cards, and better predicting dormant customers is emerging as an important challenge. In this study, the Recurrent Neural Network (RNN) methodology was used to predict potential dormant customers in the card industry, and in particular, Long-Short Term Memory (LSTM) was used to efficiently learn data for a long time. In addition, to redefine the variables needed to predict dormant customers in the card industry, Unified Theory of Technology (UTAUT), an integrated technology acceptance theory, was applied to redefine and group the variables used in the model. As a result, stable model accuracy and F-1 score were obtained, and Hit-Ratio proved that models using LSTM can produce stable results compared to other algorithms. It was also found that there was no moderating effect of demographic information that could occur in UTAUT, which was pointed out in previous studies. Therefore, among variable selection models using UTAUT, dormant customer prediction models using LSTM are proven to have non-biased stable results. This study revealed that there may be academic contributions to the prediction of dormant customers using LSTM algorithms that can learn well from previously untried time series data. In addition, it is a good example to show that it is possible to respond to customers who are preemptively dormant in terms of customer management because it is predicted at a time difference with the actual dormant capture, and it is expected to contribute greatly to the industry.

• Smart Media Journal
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• v.12 no.10
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• pp.63-70
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• 2023

Recently, energy consumption for heating costs, which is 35% of smart farm energy costs, has increased, requiring energy consumption efficiency, and the importance of new and renewable energy is increasing due to concerns about the realization of electricity bills. Renewable energy belongs to hydropower, wind, and solar power, of which solar energy is a power generation technology that converts it into electrical energy, and this technology has less impact on the environment and is simple to maintain. In this study, based on the greenhouse heat storage tank and heat pump data, the factors that affect the heat storage tank are selected and a heat storage tank supply temperature prediction model is developed. It is predicted using Long Short-Term Memory (LSTM), which is effective for time series data analysis and prediction, and XGBoost model, which is superior to other ensemble learning techniques. By predicting the temperature of the heat pump heat storage tank, energy consumption may be optimized and system operation may be optimized. In addition, we intend to link it to the smart farm energy integrated operation system, such as reducing heating and cooling costs and improving the energy independence of farmers due to the use of solar power. By managing the supply of waste heat energy through the platform and deriving the maximum heating load and energy values required for crop growth by season and time, an optimal energy management plan is derived based on this.

• Journal of IKEEE
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• v.27 no.4
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• pp.644-649
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• 2023

As the cell spacing decreases during the scaling process of DRAM(Dynamic Random Access Memory), the reduction in STI(Shallow Trench Isolation) thickness leads to an increase in sub-threshold leakage due to the passing word line effect. The increase in sub-threshold leakage current caused by the voltage applied to adjacent passing word lines affects the data retention time and increases the number of refresh operations, thereby contributing to higher power consumption in DRAM. In this paper, we identify the causes of the passing word line effect through TCAD Simulation. As a result, we confirm the DRAM operational conditions under which the passing word line effect occurs, and observe that this effect alters the proportion of the total leakage current attributable to different causes. Through this, we recognize the necessity to consider not only leakage currents due to GIDL(Gate Induced Drain Leakage) but also sub-threshold leakage currents, providing guidance for improving DRAM structure.

• Journal of Ginseng Research
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• v.47 no.5
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• pp.662-671
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• 2023

Background: 20(S)-protopanaxadiol (PPD), a ginsenoside metabolite, has prominent benefits for the central nervous system, especially in improving learning and memory. However, its transcriptional targets in brain tissue remain unknown. Methods: In this study, we first used mass spectrometry-based drug affinity responsive target stability (DARTS) to identify the potential proteins of ginsenosides and intersected them with the transcription factor library. Second, the transcription factor PURA was confirmed as a target of PPD by biolayer interferometry (BLI) and molecular docking. Next, the effect of PPD on the transcriptional levels of target genes of PURA in brain tissues was determined by qRT-PCR. Finally, bioinformatics analysis was used to analyze the potential biological features of these target proteins. Results: The results showed three overlapping transcription factors between the proteomics of DARTS and transcription factor library. BLI analysis further showed that PPD had a higher direct interaction with PURA than parent ginsenosides. Subsequently, BLI kinetic analysis, molecular docking, and mutations in key amino acids of PURA indicated that PPD specifically bound to PURA. The results of qRT-PCR showed that PPD could increase the transcription levels of PURA target genes in brain. Finally, bioinformatics analysis showed that these target proteins were involved in learning and memory function. Conclusion: The above-mentioned findings indicate that PURA is a transcription target of PPD in brain, and PPD upregulate the transcription levels of target genes related to cognitive dysfunction by binding PURA, which could provide a chemical and biological basis for the study of treating cognitive impairment by targeting PURA.

• The Journal of Korean society of community based occupational therapy
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• v.2 no.1
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• pp.49-63
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• 2012

Objective : The purpose of study was to verify the clinical effect of a Korean Computer-based cognitive rehabilitation program(called CoTras) for recovering the visual perception function and ADL in stroke. Methods : A CBCRT was applied to 14 Stoke patients who rehabilitation professional medical treatment hospital. All participant were evaluated with four standardized assessment tolls(Motor-Free Visual Perception Test; MVPT, Korean version of Mini-Mental State Examination; MMSE-K, Assesment of Motor and Process Skills: AMPS) before and after the planned computer based cognitive rehabilitation sessions. Results : A significant effect was confirmed (p<.05) from the CBCRT which visual perception function. By each entry comparative result, visual memory, figure ground, visual close, spatial relation, visual discrimination, were the order of treatment. Neither was found any significant effect in improving process skills from AMPS. Conclusion : These results indicate that CoTras have effects on improving visual perception and ADL performance in stroke patients. Will be able to present with the fundamental data CoTras will be able to contribute to increase visual perception function & ADL performance to the stroke patient who has visual perception dysfunction.