• KIPS Transactions on Computer and Communication Systems
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• 제6권9호
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• pp.377-384
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• 2017

The performance improvement of a single core processor has reached its limit since the circuit density cannot be increased any longer due to overheating. Therefore, the multicore and manycore architectures have emerged as viable approaches and parallel programming becomes more important. Haskell, a purely functional language, is getting popular in this situation since it naturally supports parallel programming owing to its beneficial features including the implicit parallelism in evaluating expressions and the monadic tools supporting parallel constructs. However, the performance of Haskell parallel programs is strongly influenced by the performance of the run-time system including the garbage collector. Though a memory profiling tool namely GC-tune has been suggested, we need a more systematic way to use this tool. Since GC-tune finds the optimal memory size by executing the target program with all the different possible GC options, the GC-tuning time takes too long. This paper suggests a basic divide-and-conquer method to reduce the number of GC-tune executions by reducing the search area by one-quarter for every searching step. Applying this method to two parallel programs, a maximally independent set and a K-means programs, the memory tuning time is reduced by 7.78 times with accuracy 98% on average.

• The Journal of Society for e-Business Studies
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• 제24권4호
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• pp.119-133
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• 2019

Recently, the importance prediction of photovoltaic power (PV) is considered as an essential function for scheduling adjustments, deciding on storage size, and overall planning for stable operation of PV facility systems. In particular, since most of PV power is generated in peak time, PV power prediction in a peak time is required for the PV system operators that enable to maximize revenue and sustainable electricity quantity. Moreover, Prediction of the PV power output in peak time without meteorological information such as solar radiation, cloudiness, the temperature is considered a challenging problem because it has limitations that the PV power was predicted by using predicted uncertain meteorological information in a wide range of areas in previous studies. Therefore, this paper proposes the LSTM (Long-Short Term Memory) based the PV power prediction model only using the meteorological, seasonal, and the before the obtained PV power before peak time. In this paper, the experiment results based on the proposed model using the real-world data shows the superior performance, which showed a positive impact on improving the PV power in a peak time forecast performance targeted in this study.

• Journal of KIISE
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• 제43권4호
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• pp.450-459
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• 2016

Every year, RDFS data tends further toward scalability; hence, the manner of SPARQL processing needs to be changed for fast query. The query processing method of SPARQL has been studied using a scalable distributed processing framework. Current studies indicate that the query engine based on the scalable distributed processing framework i.e., Hadoop(MapReduce) is not suitable for real-time processing because of the repetitive tasks; in addition, it is difficult to construct a query engine based on an In-memory Distributed Query engine, because distributed structure on the low-level is required to be considered. In this paper, we proposed a method to construct a query engine for improving the speed of the query process with the mass triple data. The query engine processes the query of SPARQL using the SparkSQL, which is an In-memory based, distributed query processing framework. SparkSQL is a high-level distributed query engine that facilitates existing SQL statement. In order to process the SPARQL query, after generating the Algebra Tree using Jena, the Algebra Tree is required to be translated to Spark Algebra Tree for application in the Spark system, and construction of the system that generated the SparkSQL query. Furthermore, we proposed the design of triple property table based on DataFrame for more efficient query processing in the Spark system. Finally, we verified the validity through comparative evaluation with the query engine, which is the existing distributed processing framework.

• Journal of the Institute of Electronics Engineers of Korea CI
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• 제48권5호
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• pp.74-82
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• 2011

SSD has a limitation of number of erase/write cycles and does not allow in-place update unlike the hard disk because SSD is composed of an array of NAND flash memory. Thus, FTL is used to effectively manage SSD of having different characteristics from traditional disk. FTL has page, block, log-block mapping method. Among then, when log-block mapping method such as BAST and FAST is used, the performance of SSD is degraded because frequent merge operations cause lots of pages to be copied and deleted. This paper proposes a data allocation and replacement method based on access frequency by allocating PRAM as checking area of access frequency, log blocks, storing region of hot data in SSD. The proposed method can enhance the performance and lifetime of SSD by storing cold data to flash memory and storing log blocks and frequently accessed data to PRAM and then reducing merge and erase operations. Besides, a data replacement method is used to increase utilization of PRAM which has limitation of capacity. The experimental results show that the ratio of erase operations of the proposed method is 46%, 38% smaller than those of BAST and FAST and the write performance of the proposed method is 34%, 19% higher than those of BAST and FAST, and the read performance of the proposed method is 5%, 3% higher than those of BAST and FAST, respectively.

• Journal of the Institute of Convergence Signal Processing
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• 제16권4호
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• pp.139-148
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• 2015

In this paper, the optimum coding method is proposed by using open library in order to improve the performance of a software correlator developed for Korea-Japan Joint VLBI Correlator(KJJVC). The correlation system for VLBI observing system is generally implemented with hardware using ASIC or FPGA because the computational quantity is increased geometrically according to the participated observatory number. However, the software correlation system is recently constructed at a massive server such as a cluster using software according to the development of computing power. Since VLBI correlator implemented with hardware is able to conduct data processing with real-time or quasi real-time compared with mostly observational time, software correlation has to perform optimal data processing in coding work so as to have the same performance as that of the hardware. Therefore, in this paper, the experimental comparison was conducted by open-source based fftw library released in FFT processing stage, which is the most important part of the correlator system for performing optimum coding work in software development phase, such as general method using fftw library or methods using SSE(Streaming SIMD Extensions), shared memory, or OpenMP, and method using merged techniques listed above. Through the experimental results, the proposed optimum coding method for improving the performance of developed software correlator using fftw library, shared memory and OpenMP is effectively confirmed by reducing correlation time compared with conventional method.

• Journal of the Korea Convergence Society
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• 제12권11호
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• pp.457-466
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• 2021

This study sought to identify the effectiveness of training programs by developing mobile app-based training programs to enhance memory, attention, and language function, which is known to be vulnerable to menopause women. It was conducted on 40 Climacteric woman between 40 to 60 years complaining about cognitive function decline. The mobile app-based cognitive training was an 8 week program. There were a total of 24 sessions and each session took 20-30 minutes, three times per week. The survey was carried out including a baseline study pre and post intervention study. The research variables were objective cognitive function (overall cognitive function, memory, attention, and language function), subjective cognitive function and quality of life. The cognitive training program showed a significant increase in overall cognitive function(t=-8.688, p<.001), memory(t=-4.765, p<.001), attention : number of correct answers(t=-7.293, p<.001), language high frequency response speed(Z=-2.179, p=.036), language low frequency response speed(Z=-2.737, p=.009) and quality of life (t=-3.358, p=.002). However, there was no significant difference in the scores for subjective cognitive function. The cognitive training program was found to be an effective intervention for improving the cognitive function of Climacteric women. It could be used as a cognitive intervention tool that is accessible at home without expert help.

• Journal of the Korean Society for information Management
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• 제39권4호
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• pp.159-189
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• 2022

The research aims to recommend strategies to promote PR activities of 'the Memory of the World(MoW)' on the websites. To achieve the goal, the researchers analyzed the current conditions of online PRs of the MoW in S. Korea by developing the standards/elements for analysis. The research examined the two main concepts of MoW and extracted the three core standards/elements for evaluating current online PRs of MoW through reviewing earlier studies: contents of PRs, ways of PRs, and features of media. The research examined PR activities on the 21 websites of 11 institutions which manage MoW in South Korea. The research found the significant features of the online PRs and suggested detailed strategies for improving the online PRs of MoW: first, it is required to emphasize the values of both preservation and utilization of MoW equally. Second, it is necessary to promote the PRs of MoW by using the way of 'user segmentation'. Third, it needs to develop the unit systems and/or services to integrate with related documentary heritages so that users can access documentary heritages effectively and efficiently. Finally, it is required to develop the guidelines or/and manuals to conduct and promote the PRs of the MoW by providing specific directions and methods of publicities.

• IEIE Transactions on Smart Processing and Computing
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• 제2권6호
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• pp.367-372
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• 2013

Cloud computing technology has been developing at an increasing expansion rate. Today most of firms are using this technology, making improving the quality of service one of the most important issues. To achieve this, the system must operate efficiently with less idle time and without deteriorating the customer satisfaction. This paper focuses on enhancing the efficiency of a conventional Genetic Algorithm (GA) for task scheduling in cloud computing using Fuzzy Logic (FL). This study collected a group of task schedules and assessed the quality of each task schedule with the user expectation. The work iterates the best scheduling order genetic operations to make the optimal task schedule. General GA takes considerable time to find the correct scheduling order when all the fitness function parameters are the same. GA is an intuitive approach for solving problems because it covers all possible aspects of the problem. When this approach is combined with fuzzy logic (FL), it behaves like a human brain as a problem solver from an existing database (Memory). The present scheme compares GA with and without FL. Using FL, the proposed system at a 100, 400 and 1000 sample size*5 gave 70%, 57% and 47% better improvement in the task time compared to GA.

• Journal of IKEEE
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• 제16권3호
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• pp.265-273
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• 2012

Data stability and leakage power dissipation have become a critical issue in scaled SRAM design. In this paper, an advanced 8T SRAM cell improving the read and write stability of data storage elements as well as reducing the leakage current in the idle mode is presented. During the read operation, the bit-cell keeps the noise-vulnerable data 'low' node voltage close to the ground level, and thus producing near-ideal voltage transfer characteristics essential for robust read functionality. In the write operation, a negative bias on the cell facilitates to change the contents of the bit. Unlike the conventional 6T cell, there is no conflicting read and write requirement on sizing the transistors. In the standby mode, the built-in stacked device in the 8T cell reduces the leakage current significantly. The 8T SRAM cell implemented in a 130 nm CMOS technology demonstrates almost 100 % higher read stability while bearing 20 % better write-ability at 1.2 V typical condition, and a reduction by 45 % in leakage power consumption compared to the standard 6T cell. The stability enhancement and leakage power reduction provided with the proposed bit-cell are confirmed under process, voltage and temperature variations.

• Proceedings of the Korean Vacuum Society Conference
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• 한국진공학회 2016년도 제50회 동계 정기학술대회 초록집
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• pp.290.2-290.2
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• 2016

Recently, organic thin-film transistors have been widely researched for organic light-emitting diode panels, memory devices, logic circuits for flexible display because of its virtue of mechanical flexibility, low fabrication cost, low process temperature, and large area production. In order to achieve high performance OTFTs, increase in accumulation carrier mobility is a critical factor. Post-fabrication thermal annealing process has been known as one of the methods to achieve this by improving the crystal quality of organic semiconductor materials In this paper, we researched the properties of pentacene films with X-Ray Diffraction (XRD) and Atomic Force Microscope (AFM) analyses as different annealing temperature in N2 ambient. Electrical characterization of the pentacene based thin film transistor was also conducted by transfer length method (TLM) with different annealing temperature in Al- and Ti-pentacene junctions to confirm the Fermi level pinning phenomenon. For Al- and Ti-pentacene junctions, is was found that as the surface quality of the pentacene films changed as annealing temperature increased, the hole-barrier height (h-BH) that were controlled by Fermi level pinning were effectively reduced.