• IEMEK Journal of Embedded Systems and Applications
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• v.11 no.2
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• pp.125-134
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• 2016

NAND flash memory has unique characteristics like as 'out-place-update' and limited lifetime compared with traditional storage systems. According to out-of-place update scheme, a number of invalid (or called dead) pages can be generated. In this case, garbage collection is needed to reclaim invalid pages. Because garbage collection results in not only erase operations but also copy operations of valid (or called live) pages to other blocks, many garbage collection techniques have proposed to reduce the overhead and to increase the lifetime of NAND Flash systems. This techniques sometimes select victim blocks including cold data for the wear leveling. However, most of them overlook the cost of selecting victim blocks including cold data. In this paper, we propose a garbage collection technique named CAPi (Cost Age with Proportion of invalid pages). Considering the additional overhead of what to select victim blocks including cold data, CAPi improves the response time in garbage collection and increase the lifetime in memory systems. Additionally, the proposed scheme also improves the efficiency of garbage collection by separating cold data from hot data in valid pages. In experimental evaluation, we showed that CAPi yields up to, at maximum, 73% improvement in lifetime compared with existing garbage collections.

• Journal of the Institute of Convergence Signal Processing
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• v.8 no.3
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• pp.149-155
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• 2007

In this paper, we propose an real-time implementation of JPEG2000 codec on the ARM9 processor. The implemented codec is designed to separate control codes from data management codes in order to use effectively the system resources such as processor and memory. Especially, in embedded situations like cellular phones it is very important to provide good services using limited processor and internal memory. Since ARM9 series processors do not provide floating-point, large amount of computational time is required to perform the operation which needs highly repetitive floating-point computations like DWT(discrete wavelet transform). The proposed codec was programed using fixed-point to overcome this weakness. Also code optimization considering cache memory was applied to further improve the computational speed.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2001.11a
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• pp.17-20
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• 2001

Nonvolatile semiconductor memory devices with reoxidized nitrided oxide(RONO) gate dielectric were fabricated, and nitrogen distribution and bonding species which contributing memory characteristics were analyzed. Also, memory characteristics of devices according to anneal temperatures were investigated. The devices were fabricated by 0.35$\mu\textrm{m}$ retrograde twin well CMOS processes. The processes could be simple by in-situ process of nitridation anneal and reoxidation. The nitrogen distribution and bonding state of gate dielectric were investigated by Dynamic Secondary Ion Mass Spectrometry(D-SIMS), Time-of-Flight Secondary ton Mass Spectrometry(ToF-SIMS), and X-ray Photoelectron Spectroscopy(XPS). Nitrogen concentrations are proportional to nitridation anneal temperatures and the more time was required to form the same reoxidized layer thickness. ToF-SIMS results show that SiON species are detected at the initial oxide interface and Si$_2$NO species near the new Si-SiO$_2$ interface that formed after reoxidation. As the anneal temperatures increased, the device showed worse retention and degradation properties. These could be said that nitrogen concentration near initial interface is limited to a certain quantity, so excess nitrogen are redistributed near the Si-SiO$_2$ interface and contributed to electron trap generation.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.183-183
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• 2020

Accurate quantitative precipitation estimation plays an important role in hydrological modelling and prediction. Instantaneous quantitative precipitation estimation (QPE) by utilizing the weather radar data is a great applicability for operational hydrology in a catchment. Previously, regression technique performed between reflectivity (Z) and rain intensity (R) is used commonly to obtain radar QPEs. A novel, recent approaching method which might be applied in hydrological area for QPE is Long Short-Term Memory (LSTM) Networks. LSTM networks is a development and evolution of Recurrent Neuron Networks (RNNs) method that overcomes the limited memory capacity of RNNs and allows learning of long-term input-output dependencies. The advantages of LSTM compare to RNN technique is proven by previous works. In this study, LSTM networks is used to estimate the quantitative precipitation from weather radar for an urban catchment in South Korea. Radar information and rain-gauge data are used to evaluate and verify the estimation. The estimation results figure out that LSTM approaching method shows the accuracy and outperformance compared to Z-R relationship method. This study gives us the high potential of LSTM and its applications in urban hydrology.

• Nuclear Engineering and Technology
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• v.52 no.11
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• pp.2667-2677
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• 2020

A domain decomposition (DD) scheme for GPU-based Monte Carlo (MC) calculation which is essential for whole-core depletion is introduced within the framework of the modified history-based tracking algorithm. Since GPU-offloaded MC calculations suffer from limited memory capacity, employing DDMC is inevitable for the simulation of depleted cores which require large storage to save hundreds of newly generated isotopes. First, an automated domain decomposition algorithm named wheel clustering is devised such that each subdomain contains nearly the same number of fuel assemblies. Second, an innerouter iteration algorithm allowing overlapped computation and communication is introduced which enables boundary neutron transactions during the tracking of interior neutrons. Third, a bank update scheme which is to include the boundary sources in a way to be adequate to the peculiar data structures of the GPU-based neutron tracking algorithm is presented. The verification and demonstration of the DDMC method are done for 3D full-core problems: APR1400 fresh core and a mock-up depleted core. It is confirmed that the DDMC method performs comparably with the standard MC method, and that the domain decomposition scheme is essential to carry out full 3D MC depletion calculations with limited GPU memory capacities.

• Journal of KIISE:Computer Systems and Theory
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• v.37 no.3
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• pp.147-160
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• 2010

The system virtualization shows interest in the consolidation of servers for the efficient utilization of system resources. There are many various researches to utilize a server machine more efficiently through the system virtualization technique, and improve performance of the virtualization software. These researches have studied with the activity to control the resource allocation of virtual machines dynamically focused on CPU, or to manage resources in the cross-machine using the migration. However, the researches of the memory management have been wholly lacking. In this respect, the use of memory is limited to allocate the memory statically to virtual machine in server consolidation. Unfortunately, the static allocation of the memory causes a great quantity of the idle memory and decreases the memory utilization. The underutilization of the memory makes other side effects such as the load of other system resources or the performance degradation of services in virtual machines. In this paper, we suggest the dynamic allocation of the memory in Xen to control the memory allocation of virtual machines for the utilization without the performance degradation. Using AR model for the prediction of the memory usage and ACO (Ant Colony Optimization) algorithm for optimizing the memory utilization, the system operates more virtual machines without the performance degradation of servers. Accordingly, we have obtained 1.4 times better utilization than the static allocation.

• 한국정보디스플레이학회:학술대회논문집
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• 2004.08a
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• pp.37-40
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• 2004

Electrochromic displays offer the possibility of providing high brightness in reflective mode due to the fact that no polarization of the incident or reflected light is required. The use of appropriately roughened reflective layers can enable the diffuse or Lambertian reflection of light. truly imitating the optical nature of paper as a reading medium. Furthermore, the use of an electrochromic system, essentially an electrochemical device, allows for the integration of charge storage layers, endowing such devices with an on-state memory and associated low power consumption. In this paper we describe the $NanoChromics^{TM}$ system and overview the several strategies employed towards the migration of this technology to flexible display formats.

• Journal of Information Processing Systems
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• v.18 no.4
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• pp.480-488
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• 2022

Images of tobacco retail licenses have complex unstructured characteristics, which is an urgent technical problem in the robot process automation of tobacco marketing. In this paper, a novel recognition approach using a double attention mechanism is presented to realize the automatic recognition and information extraction from such images. First, we utilized a DenseNet network to extract the license information from the input tobacco retail license data. Second, bi-directional long short-term memory was used for coding and decoding using a continuous decoder integrating dual attention to realize the recognition and information extraction of tobacco retail license images without segmentation. Finally, several performance experiments were conducted using a largescale dataset of tobacco retail licenses. The experimental results show that the proposed approach achieves a correction accuracy of 98.36% on the ZY-LQ dataset, outperforming most existing methods.

• Journal of KIISE:Software and Applications
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• v.32 no.8
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• pp.819-833
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• 2005

Code size reduction is ever becoming more important for compilers targeting embedded processors because these processors are often severely limited by storage constraints and thus the reduced code size can have a positively significant Impact on their performance. Various code size reduction techniques have different motivations and a variety of application contexts utilizing special hardware features of their target processors. In this work, we propose a novel technique that fully utilizes a set of hardware instructions, called the multiple load/store (MLS), that are specially featured for reducing code size by minimizing the number of memory operations in the code. To take advantage of this feature, many microprocessors support the MLS instructions, whereas no existing compilers fully exploit the potential benefit of these instructions but only use them for some limited cases. This is mainly because optimizing memory accesses with MLS instructions for general cases is an NP-hard problem that necessitates complex assignments of registers and memory off-sets for variables in a stack frame. Our technique uses a couple of heuristics to efficiently handle this problem in a polynomial time bound.

• Journal of the Korea Convergence Society
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• v.9 no.11
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• pp.23-28
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• 2018

Recent approaches to Relation Extraction methods mostly tend to be limited to mention level relation extractions. These types of methods, while featuring high performances, can only extract relations limited to a single sentence or so. The inability to extract these kinds of data is a terrible amount of information loss. To tackle this problem this paper presents an Augmented External Memory Neural Network model to enable Global Relation Extraction. the proposed model's Global relation extraction is done by first gathering and analyzing the mention level relation extraction by the Augmented External Memory. Additionally the proposed model shows high level of performances in korean due to the fact it can take the often omitted subjects and objectives into consideration.