• Proceedings of the Korea Information Processing Society Conference
• /
• 2020.11a
• /
• pp.20-23
• /
• 2020

This research is to design an effective prefetching method required for DRAM-PCM hybrid main memory systems especially used for big data applications and massive-scale computing environment. Conventional prefetchers perform well with regular memory access patterns. However, workloads such as graph processing show extremely irregular memory access characteristics and thus could not be prefetched accurately. Therefore, this research proposes an efficient dynamical prefetching algorithm based on the regression method. We have designed an intelligent prefetch engine that can identify the characteristics of the memory access sequences. It can perform regular, linear regression or polynomial regression predictive analysis based on the memory access sequences' characteristics, and dynamically determine the number of pages required for prefetching. Besides, we also present a DRAM-PCM hybrid memory structure, which can reduce the energy cost and solve the conventional DRAM memory system's thermal problem. Experiment result shows that the performance has increased by 40%, compared with the conventional DRAM memory structure.

• Journal of the Korea Computer Graphics Society
• /
• v.8 no.3
• /
• pp.17-23
• /
• 2002

Motion capture system is widely used nowadays in the entertainment industry like movies, computer games and broadcasting. This system consist of several high resolution and high speed CCD cameras and expensive frame grabbing hardware for image acquisition. KAIST VR laboratory focused on low cost system for a few years and have been developed a LAN based optical motion capture system. But, by using low cost system some problems like occlusion, noise and swapping of markers' trajectory can be occurred. And more labor intensive work is needed for post-processing process. In this thesis, we propose a trajectory rectification algorithm by confidence model of markers attached on actor. Confidence model is based on graph structure and consist of linkage, marker and frame confidence. To reduce the manual work in post-processing, we have to reconstruct the marker graph by maximizing the frame confidence.

• Journal of Information Technology Applications and Management
• /
• v.22 no.3
• /
• pp.65-81
• /
• 2015

This study reports a preliminary finding of the types and numbers of graphs being presented in the annual reports of about thirty top listed companies trading publicly in the stock markets of three countries-Thailand (SET), Malaysia (BM), and Singapore (SGX)-that were chosen based on their inclusion in the ASEAN Stars Index under the ASEAN Trading Link project. A total of 6,753 graphs from nineteen sectors were extracted and examined. Banking, real estate, and telecommunications are ranked the three most condense sectors, accounting for 50.2% of the total number of graphs observed. The three most used graphs are the Conservative Bar, Donut graph and Stack Bar. Less than one percent of Infographic type graphs were used. The five most depicted graphed variables are Asset, Revenue, Net profit, Liability, and Dividend. Using rudimentary framework to detect distorted or misleading statistical graphs, the study found 60.6% of the graphs distorted across the three markets, SET, BM, and SGX. BM ranked first in percentages of graphs being distortedly presented (73%). The other two markets, SET and SGX, have about the same proportions, 53.88% and 53.03%, respectively. Likewise, the proportions of Well-designed versus Inappropriate-designed graphs of the latter two markets are a little over one time (SET = 1 : 1.17; SGX = 1 : 1.13), whereas the proportion is almost triple for the BM market (BM = 1 : 2.70). In addition, the trend of distorted graphs found is slightly increasing as the longevity of the ASEAN Stars Index increases. One possible explanation for the relatively equal proportion of inappropriate graphs found is that SET is the smallest market and SGX, though the largest, is the most regulated market. BM, on the other hand, may want to present their financial data in the most attractive manner to prospective investors, thus, regulatory constraints and governance structure are still lenient.

• The Journal of the Korea Contents Association
• /
• v.12 no.12
• /
• pp.126-134
• /
• 2012

The researchers of this study closely looked into the methods for cognitive-scientific approach to problems of marine design at a time when the overall values of marine cultures are acknowledged in full scale. To that end, the researchers analyzed the problems and problem-solving process for the initial approach to marine design. At the same time, the researchers made the matrix of the design-developmental directions by cognitive scientific approach. After selecting the subjects, the researchers collected verbal protocol and behavior protocol which were shown in the process of a designer's thinking. This was for the sake of protocol analysis which is the representative research technique of cognitive science. Based on the collected data, the researchers empirically analyzed the behavior patterns shown in the marine design process so as to develop the design behavior-graph pattern of designers in an objective and systematic way. The behavior graph was helpful for looking into the initial developmental directions of design and for predicting cognitive structure of designers. The researchers hope that this study will become a fundamental material for predicting cognitive directions of designer for planning and designing the marine design.

• The Journal of Korean Association of Computer Education
• /
• v.9 no.6
• /
• pp.41-51
• /
• 2006

Educators have recognized the usefulness of the e-BBS(electronic-Bulletin Board System) as an asynchronous communication medium for collaborative learning. However, theoretical outcomes to understand the structural analysis of thc e-BBS are not adequate enough. As a consequence, we are left with inadequate supportive tools to understand complex communication phenomena and to assist teachers to guide students to educational purposes. This can cause teachers to have a laissez-faire approach using BBS as a communication medium for education due to the lack of understanding the structural and overall situation. To address this issue, this paper presents a theoretical foundation to help understand the structure of discussion activities via the e-BBS and then presents a computational model, based on the structural analysis, for the behavioral analysis of participants. The formal representation of bi-directional discussion activities is realized by devising two graphs - the reply graph and the connection graph. Various measurements and statistics for the analysis are presented in the paper. To clarify the analysis, we classify the results produced through the analysis of discussion activities and participants' behaviors.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.10 no.3
• /
• pp.950-975
• /
• 2016

Device-to-Device (D2D) communication underlaying cellular networks is a promising add-on component for future radio communication systems. It provides more access opportunities for local device pairs and enhances system throughput (ST), especially when mobile relays (MR) are further enabled to facilitate D2D links when the channel condition of their desired links is unfavorable. However, mutual interference is inevitable due to spectral reuse, and moreover, selecting a suitable transmission mode to benefit the correlated resource allocation (RA) is another difficult problem. We aim to optimize ST of the hybrid system via joint consideration of mode selection (MS) and RA, which includes admission control (AC), power control (PC), channel assignment (CA) and relay selection (RS). However, the original problem is generally NP-hard; therefore, we decompose it into two parts where a hierarchical structure exists: (i) PC is mode-dependent, but its optimality can be perfectly addressed for any given mode with additional AC design to achieve individual quality-of-service requirements. (ii) Based on that optimality, the joint design of MS, CA and RS can be viewed from the graph perspective and transferred into the maximum weighted independent set problem, which is then approximated by our greedy algorithm in polynomial-time. Thanks to the numerical results, we elucidate the efficacy of our mechanism and observe a resulting gain in MR-aided D2D communication.

• Journal of the Korea Computer Graphics Society
• /
• v.20 no.2
• /
• pp.25-32
• /
• 2014

We present an example-based approach to synthesizing physically simulated Rube Goldberg machines in which a series of rigid body elements are sequentially triggered and driven along the causal chain. Given a set of elements, our goal is to automatically instantiate and arrange those elements to meet the user-specified requirements including the start and end positions, and the boundary of movement. To do so, we first sample small-scale machines consisting of only a few elements randomly, and represent the connectivity between every pair of components as a graph structure. Searching over possible paths in this graph solves our problem by finding a path that can be unrolled to satisfy the given requirements, and then assembling components sequentially along the solution path. In order to ensure that the machine works precisely in a physically simulated environment, we finally elaborate the layout of assembled components by a simple greedy algorithm. We demonstrate the usefulness of our approach by displaying a large diversity of Rube Goldberg machines built with only five kinds of elements.

• Journal of Korea Multimedia Society
• /
• v.6 no.6
• /
• pp.1088-1099
• /
• 2003

The syntax-directed translation using semantic actions is frequently used in construction of compiler for text programming languages. it is very useful for the language designers to develop compiler back-end using a syntax structure of a source programming language. Due to the lack of the integrated representation method for a parse tree node and modeling method of syntax structures, it is very hard to construct compiler using syntax-directed translation in visual languages. In this Paper, we propose a visual language compiler generation method for constructing a visual languages compiler automatically, using syntax-directed translation. Our method uses the Picture Layout Grammar as a underlying grammar formalism. This grammar allows our approach to generate parser efficiently u sing And-Or-Waiting Graph and encapsulating syntax definition as one unit. Unlike other systems, we suggest separating the specification and the generation of semantic actions. Because of this, it provides a very efficient method for modification.

• Journal of KIISE:Computer Systems and Theory
• /
• v.27 no.6
• /
• pp.608-618
• /
• 2000

We consider the problem of placing resources in a distributed computing system so that certain performance requirements may be met while minimizing the number of required resource copies, irrespective of node or link failures. To meet the requirements for high performance and high availability, minimum number of resource copies should be placed in such a way that each node has at least two copies on the node or its neighbor nodes. This is called the fault-tolerant resource placement problem in this paper. The structure of a parallel or a distributed computing system is represented by a graph. The fault-tolerant placement problem is first transformed into the problem of finding the smallest fault-tolerant dominating set in a graph. The dominating set problem is known to be NP-complete. In this paper, searching for the smallest fault-tolerant dominating set is formulated as a state-space search problem, which is then solved optimally with the well-known A* algorithm. To speed up the search, we derive heuristic information by analyzing the properties of fault-tolerant dominating sets. Some experimental results on various regular and random graphs show that the search time can be reduced dramatically using the heuristic information.

• The Korean Journal of Applied Statistics
• /
• v.33 no.3
• /
• pp.309-320
• /
• 2020

Bayesian networks, also known as directed acyclic graphs (DAG), are used in many areas of medicine, meteorology, and genetics because relationships between variables can be modeled with graphs and probabilities. In particular, Bayesian network classifiers, which are used to predict discrete data, have recently become a new method of data mining. Bayesian networks can be grouped into different models that depend on structured learning methods. In this study, Bayesian network models are learned with various properties of structure learning. The models are compared to the simplest method, the naïve Bayes model. Classification results are compared by applying learned models to various real data. This study also compares the relationships between variables in the data through graphs that appear in each model.