• IEMEK Journal of Embedded Systems and Applications
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• v.10 no.4
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• pp.189-198
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• 2015

Most IoT-related approaches have tried to establish the relation by connecting the network between things. The proposed research will present how the pervasive interaction of eco-system formed by touching the objects between humans and things can be recognized on purpose. By collecting and sharing the detected patterns among all kinds of things, we can construct the environment which enables individualized interactions of different objects. To perform the aforementioned, we are going to utilize technical procedures such as event-driven signal processing, pattern matching for signal recognition, and hardware in the loop simulation. We will also aim to implement the prototype of sensor processor based on Arduino MCU, which can be integrated with system using Arduino-Matlab/Simulink hybrid-interoperation environment. In the experiment, we use piezo transducer to detect the vibration or vibrates the surface using acoustic wave, which has specific frequency spectrum and individualized signal shape in terms of time axis. The signal distortion in time and frequency domain is recorded into memory tracer within sensor processor to extract the meaningful pattern by comparing the stored with lookup table(LUT). In this paper, we will contribute the initial prototypes for the acoustic touch processor by using off-the-shelf MCU and the integrated framework based on Matlab/Simulink model to provide the individualization of the touch-sensing for the user on purpose.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.9
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• pp.1702-1709
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• 1994

In the postprocessing of Hangul recognition system, the storage structure of contextual information is an important matter for the recognition rate and speed of the entire system. Trie in general is used to represent the context as word dictionary, but the memory space efficiency of the structure is low. Therefore we propose a new structure for word dictionary that has better space efficiency and the equivalent merits of trie. Because Hangul is a compound language, the language can be represented by phonemes or by characters. In the representation by phonemes(P-mode) the retrieval is fast, but the space efficiency is low. In the representation by characters(C-mode) the space efficiency is high, but the retrieval is slow. In this paper the two representation methods are combined to form a hybrid representation(H-mode). At first an optimal level for the combination is selected by two characteristic curves of node utilization and dispersion. Then the input words are represented with trie structure by P-mode from the first to the optimal level, and the rest are represented with sequentially linked list structure by C-mode. The experimental results for the six kinds of word set show that the proposed structure is more efficient. This result is based on the fact that the retrieval for H-mode is as fast as P-mode and the space efficiency is as good as C-mode.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.6
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• pp.850-858
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• 2022

To deploy Gate Recurrent Units (GRU) on resource-constrained embedded devices, this paper presents a reconfigurable FPGA-based GRU accelerator that enables structured compression. Firstly, a dense GRU model is significantly reduced in size by hybrid quantization and structured top-k pruning. Secondly, the energy consumption on external memory access is greatly reduced by the proposed reuse computing pattern. Finally, the accelerator can handle a structured sparse model that benefits from the algorithm-hardware co-design workflows. Moreover, inference tasks can be flexibly performed using all functional dimensions, sequence length, and number of layers. Implemented on the Intel DE1-SoC FPGA, the proposed accelerator achieves 45.01 GOPs in a structured sparse GRU network without batching. Compared to the implementation of CPU and GPU, low-cost FPGA accelerator achieves 57 and 30x improvements in latency, 300 and 23.44x improvements in energy efficiency, respectively. Thus, the proposed accelerator is utilized as an early study of real-time embedded applications, demonstrating the potential for further development in the future.

• Journal of Korean Society of Steel Construction
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• v.27 no.2
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• pp.131-142
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• 2015

In this paper, we present an optimization of truss structures subjected to stress, buckling, and natural frequency constraints. The main objective of the present study is to propose an efficient HA-SA algorithm for solving the truss optimization subject to multiple constraints. The procedure of hybrid HA-SA is a search method which a design values in harmony memory of harmony search are used as an initial value designs in simulated annealing search method. The efficient optimization of HA-SA is illustrated through several optimization examples. The examples of truss structures are used 10-Bar truss, 52-Bar truss (Dome), and 72-Bar truss for natural frequency constraints, and used 18-Bar truss and 47-Bar (Tower) truss for stress and buckling constraints. The optimum results are compared to those of different techniques. The numerical results are demonstrated the advantages of the HA-SA algorithm in truss optimization with multiple constraints.

• The Transactions of the Korea Information Processing Society
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• v.3 no.7
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• pp.1719-1726
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• 1996

In the OR-parallel execution of logic programs, binding environments have a critical impact on the performance. Particularly, this is true for distributed execution on parallel systems with a non-single address space. The reason is that in such systems, the remote accesses across processing elements deteriorate the performance. To solve this problem, some binding methods were previously proposed specifically for a non-single address space. However, compared with the binding methods for a single address space, they are far less efficient due to the overhead of newly introduced operations such as environment closing and back-unification, In this paper, we propose a new binding environment is a hybrid that combines both the binding methods for a single address space and those for anon-single address space. It acomplishes high efficiency by making closing operations unnecessary both at unification and at back-unification, while mainthing the restricted accesses.

• International Journal of Computer Science & Network Security
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• v.23 no.4
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• pp.139-145
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• 2023

These days, protecting location privacy has become essential and really challenging, especially protecting it from smart applications and services that rely on Location-Based Services (LBS). As the technology and the services that are based on it are developed, the capability and the experience of the attackers are increased. Therefore, the traditional protection ways cannot be enough and are unable to fully ensure and preserve privacy. Previously, a hybrid approach to privacy has been introduced. It used an obfuscation technique, called Double-Obfuscation Approach (DOA), to improve the privacy level. However, this approach has some weaknesses. The most important ones are the fog nodes that have been overloaded due to the number of communications. It is also unable to prevent the Tracking and Identification attacks in the Mix-Zone technique. For these reasons, this paper introduces a developed and enhanced approach, called Multi-Obfuscation Approach (MOA that mainly depends on the communication between neighboring fog nodes to overcome the drawbacks of the previous approach. As a result, this will increase the resistance to new kinds of attacks and enhance processing. Meanwhile, this approach will increase the level of the users' privacy and their locations protection. To do so, a big enough memory is needed on the users' sides, which already is available these days on their devices. The simulation and the comparison prove that the new approach (MOA) exceeds the DOA in many Standards for privacy protection approaches.

• The KIPS Transactions:PartA
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• v.14A no.7
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• pp.421-434
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• 2007

Among many other CG generated natural scenes, the representation of ocean surfaces is one of the most complicated and time-consuming problem because of its large extent and complex surface movement. We present a hybrid method to represent and animate unbound deep-water ocean surfaces by utilizing graphics processor as both simulation and rendering core. Our technique is mainly based on spectral approaches that generate a high-detailed height field using Fourier transform on a 2D regular grid. Additionally, we incorporate Gerstner model and generate low-detailed height field on a 2D projected grid in order to represent large waves and main structure of ocean surface. There is no interruption between CPU and GPU, and no need to transfer simulation results from the system memory to graphics hardware because the entire simulation and rending processes are done on graphics processor. As a result we can synthesize and render realistic water surfaces in real-time. Proposed techniques are readily adoptable to real-time applications such as computer games that have heavy work load on CPU but still demand plausible natural scenes.

• The KIPS Transactions:PartC
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• v.11C no.3
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• pp.301-308
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• 2004

Misuse IDS is known to have an acceptable accuracy but suffers from high rates of false alarms. We show a behavior based alarm reduction with a memory-based machine learning technique. Our extended form of IBL, (XIBL) examines SNORT alarm signals if that signal is worthy sending signals to security manager. An experiment shows that there exists an apparent difference between true alarms and false alarms with respect to XIBL behavior This gives clear evidence that although an attack in the network consists of a sequence of packets, decisions over Individual packet can be used in conjunction with misuse IDS for better performance.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.5
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• pp.365-369
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• 2009

Overlapping windows are generally used for queries to process continuous data streams. Nevertheless, existing approaches discussed join algorithms only for basic types of windows such as tumbling windows and tuple-driven windows. In this paper, we propose an efficient join algorithm for overlapping windows, which are considered as a more general type of windows. The proposed algorithm is based on an incremental window join. It focuses on producing join results continuously when the memory overflow frequently occurs. It consists of (1) a method to use both of the incremental and full joins selectively, (2) a victim selection algorithm to minimize latency of join processing and (3) an idle time professing algorithm. We show through our experiments that the selective use of incremental and full joins provides better performance than using one of them only.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.150-150
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• 2023

기작기반의 역학적 모델과 자료기반의 딥러닝 모델은 수질예측에 다양하게 적용되고 있으나, 각각의 모델은 고유한 구조와 가정으로 인해 장·단점을 가지고 있다. 특히, 딥러닝 모델은 우수한 예측 성능에도 불구하고 훈련자료가 부족한 경우 오차와 과적합에 따른 분산(variance) 문제를 야기하며, 기작기반 모델과 달리 물리법칙이 결여된 예측 결과를 생산할 수 있다. 본 연구의 목적은 주요 상수원인 댐 저수지를 대상으로 수심별 수온과 탁도를 예측하기 위해 기작기반과 자료기반 모델의 장점을 융합한 PGDL(Process-Guided Deep Learninig) 모델을 개발하고, 물리적 법칙 만족도와 예측 성능을 평가하는데 있다. PGDL 모델 개발에 사용된 기작기반 및 자료기반 모델은 각각 CE-QUAL-W2와 순환 신경망 딥러닝 모델인 LSTM(Long Short-Term Memory) 모델이다. 각 모델은 2020년 1월부터 12월까지 소양강댐 댐 앞의 K-water 자동측정망 지점에서 실측한 수온과 탁도 자료를 이용하여 각각 보정하고 훈련하였다. 수온 및 탁도 예측을 위한 PGDL 모델의 주요 알고리즘은 LSTM 모델의 목적함수(또는 손실함수)에 실측값과 예측값의 오차항 이외에 역학적 모델의 에너지 및 질량 수지 항을 제약 조건에 추가하여 예측결과가 물리적 보존법칙을 만족하지 않는 경우 penalty를 부가하여 매개변수를 최적화시켰다. 또한, 자료 부족에 따른 LSTM 모델의 예측성능 저하 문제를 극복하기 위해 보정되지 않은 역학적 모델의 모의 결과를 모델의 훈련자료로 사용하는 pre-training 기법을 활용하여 실측자료 비율에 따른 모델의 예측성능을 평가하였다. 연구결과, PGDL 모델은 저수지 수온과 탁도 예측에 있어서 경계조건을 통한 에너지와 질량 변화와 저수지 내 수온 및 탁도 증감에 따른 공간적 에너지와 질량 변화의 일치도에 있어서 LSTM보다 우수하였다. 또한 역학적 모델 결과를 LSTM 모델의 훈련자료의 일부로 사용한 PGDL 모델은 적은 양의 실측자료를 사용하여도 CE-QUAL-W2와 LSTM 보다 우수한 예측 성능을 보였다. 연구결과는 다차원의 역학적 수리수질 모델과 자료기반 딥러닝 모델의 장점을 결합한 새로운 모델링 기술의 적용 가능성을 보여주며, 자료기반 모델의 훈련자료 부족에 따른 예측 성능 저하 문제를 극복하기 위해 역학적 모델이 유용하게 활용될 수 있음을 시사한다.