• Journal of KIISE:Computer Systems and Theory
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• v.27 no.8
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• pp.741-751
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• 2000

To achieve high performance by exploiting instruction level parallelism aggressively in superscalar processors, it is necessary to overcome the limitation imposed by control dependences and data dependences which prevent instructions from executing parallel. Value prediction is a technique that breaks data dependences by predicting the outcome of an instruction and executes speculatively its data dependent instruction based on the predicted outcome. In this paper, a hybrid value prediction scheme with dynamic classification mechanism is proposed. We design a hybrid predictor by combining the last predictor, a stride predictor and a two-level predictor. The choice of a predictor for each instruction is determined by a dynamic classification mechanism. This makes each predictor utilized more efficiently than the hybrid predictor without dynamic classification mechanism. To show performance improvements of our scheme, we simulate the SPECint95 benchmark set by using execution-driven simulator. The results show that our scheme effect reduce of 45% hardware cost and 16% prediction accuracy improvements comparing with the conventional hybrid prediction scheme and two-level value prediction scheme.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.1
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• pp.107-116
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• 2012

The purpose of this study is to identify the impact on the tourism satisfaction of development approach factors in cultural tourism destination. Based upon the results of empirical analysis, the development approach factors in cultural tourism destination such as tourism convenience, tourism activity, tourism potentiality, tourism resources value have high significant correlation with tourism satisfaction. The priority order sets of the impact on the tourism satisfaction of development approach factors in cultural tourism destination should be related to the tourism benefit, the tourism activity, and the tourism resources value. And they can be used to promote the efficiency of cultural tourism development.

• The KIPS Transactions:PartD
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• v.9D no.6
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• pp.1137-1144
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• 2002

Possibility of federation improvement requires flexibility and adaptability of member federates. Moreover, to develop and convert a non-HLA(High Level Architecture) compliant model as a HLA federate and allow this federate to be integrated with a changeable federation, more time and efforts will be necessary. In this research, I proposed a method to design and implement a ROM (RTI Object Model) Framework as a solution to this problem. ROM completely separates RTI (Run-Time Infrastructure) programming and simulation programming therefore providing epochal efficiencies in cost and productivity to the development a HLA federate that supports a changeable FOM. That is, ROM contains two layers : 1) a management layer that manages RTI services between the RTI and the federate and 2) a Foundation Class layer that actually updates/reflects objects and interactions. These two layers allow federate developers to use more generalized HLA services and automates the iterative, low-level RTI programming process.

• The Transactions of the Korea Information Processing Society
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• v.6 no.6
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• pp.1667-1677
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• 1999

An effective allocation of requested number of processors to newly incoming tasks in two-dimensional (2D) mesh interconnection networks is very important for achieving the desired high performance and resource utilization. It also needs to guarantee the complete recognition of the free submeshes based on contiguous and available processors with minimum overhead. An efficient task allocation algorithm for 2D meshes is presented in this paper. By employing a new approach for searching the one-dimensional array, the proposed algorithm can find the available submesh without the scanning of the entire 2D array unlike earlier designs. As a result, the new algorithm can significantly reduce the task allocation time. Comprehensive computer simulation shows that the average allocation time and waiting delay are much smaller than earlier irrespective of the size of meshes. The hardware overhead is comparable to other algorithms.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.12
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• pp.1771-1779
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• 2016

In these days, the world is getting connected to the internet like a sophisticated net, such an environment gives a suitable environment for cyber attackers, so-called cyber-terrorists. As a result, a number of cyber attacks has significantly increased and researches to find cyber attack traffics in the field of network monitoring has also been proceeding. But cyber attack traffics have been appearing in new forms in every attack making it harder to monitor. This paper suggests a method of tracking down cyber attack traffic sources by defining relational information flow of traffic data from highest cascaded and grouped relational flow. The result of applying this cyber attack source tracking method to real cyber attack traffic, was found to be reliable with quality results.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.6
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• pp.2631-2638
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• 2013

In this study, to understand the technology development trend of super-speed maglev, the patents applied by major countries are analyzed. And based on the analyzed results, the domestic technology development direction are suggested. For patent analysis, the major technologies for super-speed maglev are classified into 14 parts. Then, through the quantitative analysis method such as number, increase rate and share rate, the overview of technology development and focused parts by each country are investigated. Also through the qualitative analysis method such as concentration degree, citation index and market share index, the technology level and market securing ability of each country are anticipated. Considering the analyzed results and technology development trend, the domestic technology development direction such as priority development fields and methods are proposed.

• Journal of KIISE
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• v.44 no.7
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• pp.680-685
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• 2017

The emergence of online media and their data has enabled data-driven methods to solve challenging and complex tasks such as rumor classification problems. Recently, deep learning based models have been shown as one of the fastest and the most accurate algorithms to solve such problems. These new models, however, either rely on complete data or several days-worth of data, limiting their applicability in real time. In this study, we go beyond this limit and test the possibility of super early rumor detection via recurrent neural networks (RNNs). Our model takes in social media streams as time series input, along with basic meta-information about the rumongers including the follower count and the psycholinguistic traits of rumor content itself. Based on analyzing millions of social media posts on 498 real rumors and 494 non-rumor events, our RNN-based model detected rumors with only 30 initial posts (i.e., within a few hours of rumor circulation) with remarkable F1 score of 0.74. This finding widens the scope of new possibilities for building a fast and efficient rumor detection system.

• Journal of KIISE
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• v.45 no.1
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• pp.30-35
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• 2018

GuessWhat?! is a game in which two machine players, composed of questioner and answerer, ask and answer yes-no-N/A questions about the object hidden for the answerer in the image, and the questioner chooses the correct object. GuessWhat?! has received much attention in the field of deep learning and artificial intelligence as a testbed for cutting-edge research on the interplay of computer vision and dialogue systems. In this study, we discuss the objective function and characteristics of the GuessWhat?! game. In addition, we propose a simple solver for GuessWhat?! using a simple rule-based algorithm. Although a human needs four or five questions on average to solve this problem, the proposed method outperforms state-of-the-art deep learning methods using only two questions, and exceeds human performance using five questions.

• Journal of the Institute of Convergence Signal Processing
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• v.13 no.1
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• pp.44-49
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• 2012

The indirect-contact ECG measurement is a newly developed method for unconstrained and nonconscious measurement in daily Life. This study is the first step to reducing the large background noise appearing in indirect-contact ECG. This study built the thermal noise model of capacitively coupled active electrode which is used in indirect-contact ECG. The results show that the level of thermal noise estimated by the thermal noise model is much the same as that of actual background noise for the capacitively coupled active electrode alone. By applying the actual electrical properties of a sample cotton cloth to the thermal noise model, the theoretical level of thermal noise in the indirect-contact ECG was estimated. The results also show that the level of op-amp's intrinsic noise is so small that it can be negligible in comparison with thermal noise of resistors. The relationship between the level of thermal noise and the resistance of the bias resistor was derived, and it is the base for the further study how to choice the optimal resistance for the bias resistor.

• The Journal of the Korea Contents Association
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• v.11 no.11
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• pp.241-252
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• 2011

This study analyzed the factors of the physical and social characteristics, self-esteem as well as life satisfaction of elderly women, and analyzed the effects of the physical and social characteristics on self-esteem and life satisfaction. The survey was conducted from January 10 to February 10, 2011 among the elderly women aged 60 or older in the Guri-si and its environs of Gyeonggi-do, and 380 responses were used in the data analysis. The statistical analysis methods were frequency analysis, factor analysis, reliability analysis, correlation analysis, t-test, ANOVA, and multiple regression analysis. As a result, the physical characteristics of elderly women were classified by the activities of daily living(ADL), physical function, and disease status. The social characteristics of elderly women were classified by the religious and social activities. ADL, physical function, religious and social activities were shown to influence the self-esteem. In addition, ADL, physical function, and religious activities influenced the life satisfaction of elderly women.