• Proceedings of the IEEK Conference
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• 2005.11a
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• pp.1083-1086
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• 2005

Modern superscalar processors exploit Instruction Level Parallelism to achieve high performance by speculative techniques such as branch prediction. The indirect branch target prediction is very difficult compared to the prediction of direct branch target and branch direction, since it has dynamically polymorphic target. We present a accurate and hardware-efficient indirect branch target predictor. It can reduce the tags which has to be stored in the Indirect Branch Target Cache without a sacrifice of the prediction accuracy. We implement the proposed scheme on SimpleScalar and show the efficiency running SPEC95 benchmarks.

• Proceedings of the IEEK Conference
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• 2004.08c
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• pp.499-502
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• 2004

A two-stage Class E power amplifier operated at 2.44GHz is designed in 0.25-$\mu$m CMOS process for Class-l Bluetooth application. The power amplifier employs c1ass-E topology to exploit its soft-switching property for high efficiency. A preamplifter with common-mode configuration is used to drive the output-stage of Class-E type. The amplifier delivers 20-dBm output power with 70$\%$ PAE (power -added-efficiency) at 2-V supply voltage.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.8
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• pp.3672-3688
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• 2016

The nonorthogonality between the real and imaginary FBMC/OQAM modulated signals complicates the channel estimation (CE) process, and conventional OFDM CE methods cannot be directly applied to FBMC/OQAM. The conventional preamble-based CE schemes in FBMC/OQAM systems are mainly based on the interference approximation method (IAM) to improve the estimation performance. In this paper, we develop a novel preamble structure to improve the CE performance. We exploit the symmetry pattern to cancel interference and take into account the interference weights in this symmetric structure. The conventional preamble and the proposed preamble are compared via simulations in the IEEE 802.22, 3GPP Vehicular A and Pedestrian A channels. Numerical simulation results demonstrate that the proposed preamble can achieve better bit error ratio (BER) and mean squared error (MSE) performance under the three channel models considered.

• Journal of Information Processing Systems
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• v.12 no.1
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• pp.149-168
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• 2016

The Active Appearance Model (AAM) is a class of deformable models, which, in the segmentation process, integrates the priori knowledge on the shape and the texture and deformation of the structures studied. This model in its sequential form is computationally intensive and operates on large data sets. This paper presents another framework to implement the standard version of the AAM model. We suggest a distributed and parallel approach justified by the characteristics of the model and their potentialities. We introduce a schema for the representation of the overall model and we study of operations that can be parallelized. This approach is intended to exploit the benefits build in the area of advanced image processing.

• Journal of Information Science Theory and Practice
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• v.5 no.3
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• pp.31-47
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• 2017

The narrow-down approach, separately composed of search and classification stages, is an effective way of dealing with large-scale hierarchical text classification. Recent approaches introduce methods of incorporating global, local, and path information extracted from web taxonomies in the classification stage. Meanwhile, in the case of utilizing path information, there have been few efforts to address existing limitations and develop more sophisticated methods. In this paper, we propose an expansion method to effectively exploit category path information based on the observation that the existing method is exposed to a term mismatch problem and low discrimination power due to insufficient path information. The key idea of our method is to utilize relevant information not presented on category paths by adding more useful words. We evaluate the effectiveness of our method on state-of-the art narrow-down methods and report the results with in-depth analysis.

• Journal of Computing Science and Engineering
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• v.8 no.4
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• pp.215-227
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• 2014

In modern computer architectures, caches are widely used to shorten the gap between processor speed and memory access time. However, caches are time-unpredictable, and thus can significantly increase the complexity of worst-case execution time (WCET) analysis, which is crucial for real-time systems. This paper proposes a time-predictable two-level scratchpad-based architecture and an ILP-based static memory objects assignment algorithm to support real-time computing. Moreover, to exploit the load/store latencies that are known statically in this architecture, we study a Scratch-pad Sensitive Scheduling method to further improve the performance. Our experimental results indicate that the performance and energy consumption of the two-level scratchpad-based architecture are superior to the similar cache based architecture for most of the benchmarks we studied.

• The Korean Journal of Ecology
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• v.19 no.1
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• pp.81-91
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• 1996

The sicence of ecology was introduced into Korea as a part of biology translated into Chinese or Korean from western biology textbooks imported by way of China or directly from the West at the end of 19th c. to the beginning of 20th c. After the Japanese annexation of Korea in 1910, Japanese technologists had studied applied ecology to exploit the natural resources of Korea. Reforestation, begetation eclogy, riparian vegetation, etc. were investigated by workers from the West. Such ecological researches, however, did not contribute to the introduction of ecology into Korea, and the anture of the Korean peninsula was utilized by foreign ecologists as ecological research sites. Several Korean ecologists, not many, worked actively at the end of Japanese rule, and contributed to the settlement ecology in Korea since 1945.

• 한국공간정보시스템학회:학술대회논문집
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• 2005.11a
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• pp.61-66
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• 2005

Spatiotemporal data mining represents the confluence of several fields including spatiotemporal databases, machine loaming, statistics, geographic visualization, and information theory. Exploration of spatial data mining and temporal data mining has received much attention independently in knowledge discovery in databases and data mining research community. In this paper, we introduce an algorithm Max_MOP for discovering moving sequences in mobile environment. Max_MOP mines only maximal frequent moving patterns. We exploit the characteristic of the problem domain, which is the spatiotemporal proximity between activities, to partition the spatiotemporal space. The task of finding moving sequences is to consider all temporally ordered combination of associations, which requires an intensive computation. However, exploiting the spatiotemporal proximity characteristic makes this task more cornputationally feasible. Our proposed technique is applicable to location-based services such as traffic service, tourist service, and location-aware advertising service.

• Proceedings of the KIEE Conference
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• 1990.11a
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• pp.19-22
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• 1990

In this paper, in order to reduce the cogging torque in a permanent motor, a method to optimize the shape of permanent magnet and iron pole is presented. Because the cogging torque comes from the irregular system energy variation according to the rotor position, system energy variation is taken as object function and the object function is minimized to optimize the shape. The positions of permanent magnet surface and iron pole surface are chosen as design parameters and sensitivity of object function with respect to design parameter is calculated. The shape is changed according to sensitivity. Sensitivity can be generated by methods that exploit the FEM formulation. A numerical example shows that about 90% of the original cogging torque is reduced.

• IMMUNE NETWORK
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• v.8 no.4
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• pp.107-123
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• 2008

It has now been well documented in a variety of models that T regulatory T cells (Treg cells) play a pivotal role in the maintenance of self-tolerance, T cell homeostasis, tumor, allergy, autoimmunity, allograft transplantation and control of microbial infection. Recently, Treg cell are isolated and can be expanded in vitro and in vivo, and their role is the subject of intensive investigation, particularly on the possible Treg cell therapy for various immune-mediated diseases. A growing body of evidence has demonstrated that Treg cells can prevent or even cure a wide range of diseases, including tumor, allergic and autoimmune diseases, transplant rejection, graft-versus-host disease. Currently, a large body of data in the literature has been emerging and provided evidence that clear understanding of Treg cell work will present definite opportunities for successful Treg cell immunotherapy for the treatment of a broad spectrum of diseases. In this Review, I briefly discuss the biology of Treg cells, and summarize efforts to exploit Treg cell therapy for autoimmune diseases. This article also explores recent observations on pharmaceutical agents that abrogate or enhance the function of Treg cells for manipulation of Treg cells for therapeutic purpose.