• The Southeast Asian review
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• v.20 no.3
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• pp.41-64
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• 2010

The recent global financial crisis triggered by the sub-prime mortgage debacle in the United States hit hard most ASEAN countries that have just recovered from the unprecedented economic crisis ten years ago. This paper, using individual time-series and panel data from 1990 to 2009, intends to investigate and compare the impacts of the two aforementioned economic crises on trade in the four developing ASEAN countries that encompass Indonesia, Malaysia, the Philippines and Thailand. In doing so, the paper traces the behaviors of main macroeconomic variables before and after the crises on graphs, and then estimates classical export and import demand functions that include real exchange rate, home and foreign GDPs as explanatory variables. In the estimation functions, two dummy variables are added to consider the effects of the two economic crises separately. Individual country data analyses reveal that by and large the 1997 economic crisis seems hit those ASEAN countries' exports and imports harder than the recent global financial crisis. Surprisingly the recent financial crisis turns out more or less statistically insignificant for those countries' export and import performances. The fixed effect model estimation using panel data of those four ASEAN countries also shows that the 1997 economic crisis had affected exports and imports of those countries negatively while the recent global financial crisis was not statistically significant. These results indicate that overall the effect from the 1997 crisis was more devastating than that of the recent global crisis for those ASEAN countries.

• International Journal of Control, Automation, and Systems
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• v.4 no.1
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• pp.53-62
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• 2006

In this paper, ATM network congestion control with explicit rate feedback is considered. In ATM networks, delays commonly appear in data transmission and have to be considered in congestion control design. In this paper, a bounded single round delay on the return path is considered. Our objective is to design an explicit rate feedback control that achieves a robust optimal $H_2$ performance regardless of the bounded time-varying delays. An optimization approach in terms of linear matrix inequalities (LMIs) is given. Saturation in source rate and queue buffer is also taken into consideration in the proposed design. Simulations for the cases of single source and multiple sources are presented to demonstrate the effectiveness of the design.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.3
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• pp.575-580
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• 2017

In these days, the big-size and high resolution multimedia file is widely used through networks. To transfer and service effectively, the internet network technology is necessary to substitute broadcasting. Normally Content Delivery Network(CDN) is widely used in conventional internet for multimedia services. But it has a small bandwidth to service. So to solve this problems, many researchers have suggest the protocol for download, content distribution/saving, server synchronization, caching, pushing rate, and streaming etc. But all of these has some defects like low resolution, packets loss and delay, real application implementations etc. So, this paper suggests a new method of network protocol based on P2P collaboration and user's content using information. And it evaluated the performance of suggested method. As the results, it showed the effectiveness of 4 performances indices : download speed, decreasing rate of connected user in same time, adaptive hit ratio, traffic decreasing rate.

• Asia pacific journal of information systems
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• v.20 no.1
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• pp.81-99
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• 2010

Lately, in consumers' markets the number of new items is rapidly increasing at an overwhelming rate while consumers have limited access to information about those new products in making a sensible, well-informed purchase. Therefore, item providers and customers need a system which recommends right items to right customers. Also, whenever new items are released, for instance, the recommender system specializing in new items can help item providers locate and identify potential customers. Currently, new items are being added to an existing system without being specially noted to consumers, making it difficult for consumers to identify and evaluate new products introduced in the markets. Most of previous approaches for recommender systems have to rely on the usage history of customers. For new items, this content-based (CB) approach is simply not available for the system to recommend those new items to potential consumers. Although collaborative filtering (CF) approach is not directly applicable to solve the new item problem, it would be a good idea to use the basic principle of CF which identifies similar customers, i,e. neighbors, and recommend items to those customers who have liked the similar items in the past. This research aims to suggest a hybrid recommendation procedure based on the preference boundary of target customer. We suggest the hybrid recommendation procedure using the preference boundary in the feature space for recommending new items only. The basic principle is that if a new item belongs within the preference boundary of a target customer, then it is evaluated to be preferred by the customer. Customers' preferences and characteristics of items including new items are represented in a feature space, and the scope or boundary of the target customer's preference is extended to those of neighbors'. The new item recommendation procedure consists of three steps. The first step is analyzing the profile of items, which are represented as k-dimensional feature values. The second step is to determine the representative point of the target customer's preference boundary, the centroid, based on a personal information set. To determine the centroid of preference boundary of a target customer, three algorithms are developed in this research: one is using the centroid of a target customer only (TC), the other is using centroid of a (dummy) big target customer that is composed of a target customer and his/her neighbors (BC), and another is using centroids of a target customer and his/her neighbors (NC). The third step is to determine the range of the preference boundary, the radius. The suggested algorithm Is using the average distance (AD) between the centroid and all purchased items. We test whether the CF-based approach to determine the centroid of the preference boundary improves the recommendation quality or not. For this purpose, we develop two hybrid algorithms, BC and NC, which use neighbors when deciding centroid of the preference boundary. To test the validity of hybrid algorithms, BC and NC, we developed CB-algorithm, TC, which uses target customers only. We measured effectiveness scores of suggested algorithms and compared them through a series of experiments with a set of real mobile image transaction data. We spilt the period between 1st June 2004 and 31st July and the period between 1st August and 31st August 2004 as a training set and a test set, respectively. The training set Is used to make the preference boundary, and the test set is used to evaluate the performance of the suggested hybrid recommendation procedure. The main aim of this research Is to compare the hybrid recommendation algorithm with the CB algorithm. To evaluate the performance of each algorithm, we compare the purchased new item list in test period with the recommended item list which is recommended by suggested algorithms. So we employ the evaluation metric to hit the ratio for evaluating our algorithms. The hit ratio is defined as the ratio of the hit set size to the recommended set size. The hit set size means the number of success of recommendations in our experiment, and the test set size means the number of purchased items during the test period. Experimental test result shows the hit ratio of BC and NC is bigger than that of TC. This means using neighbors Is more effective to recommend new items. That is hybrid algorithm using CF is more effective when recommending to consumers new items than the algorithm using only CB. The reason of the smaller hit ratio of BC than that of NC is that BC is defined as a dummy or virtual customer who purchased all items of target customers' and neighbors'. That is centroid of BC often shifts from that of TC, so it tends to reflect skewed characters of target customer. So the recommendation algorithm using NC shows the best hit ratio, because NC has sufficient information about target customers and their neighbors without damaging the information about the target customers.

• Journal of the Korea Society of Computer and Information
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• v.25 no.3
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• pp.11-17
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• 2020

In this paper, we propose practical results for cache replacement policy by measuring cache hit and search time for each replacement algorithm through cache simulation. Thus, the structure of each cache memory and the four types of alternative policies of FIFO, LFU, LRU and Random were implemented in software to analyze the characteristics of each technique. The paper experiment showed that the LRU algorithm showed hit rate and search time of 36.044% and 577.936ns in uniform distribution, 45.636% and 504.692ns in deflection distribution, while the FIFO algorithm showed similar performance to the LRU algorithm at 36.078% and 554.772ns in even distribution and 45.662% and 489.574ns in bias distribution. Then LFU followed, Random algorithm was measured at 30.042% and 622.866ns at even distribution, 36.36% at deflection distribution and 553.878ns at lowest performance. The LRU replacement method commonly used in cache memory has the complexity of implementation, but it is the most efficient alternative to conventional alternative algorithms, indicating that it is a reasonable alternative method considering the reference information of data.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.10
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• pp.2430-2447
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• 2013

In recent years, HTTP adaptive streaming (HAS) has attracted considerable attention as the state-of-the-art technology for video transport. HAS dynamically adjusts the quality of video streaming according to the network bandwidth and device capability of users. Content-Centric Networking (CCN) has also emerged as a future Internet architecture, which is a novel communication paradigm that integrates content delivery as a native network primitive. These trends have led to the new research issue of harmonizing HAS with the in-network caching provided by CCN routers. Previous research has shown that the performance of HAS can be improved by using the H.264/SVC(scalable video codec) in the in-network caching environments. However, the previous study did not address the misbehavior that causes video freeze when overestimating the available network bandwidth, which is attributable to the high cache hit rate. Thus, we propose a new SVC-based adaptation algorithm that utilizes a drop timer. Our approach aims to stop the downloading of additional enhancement layers that are not cached in the local CCN routers in a timely manner, thereby preventing excessive consumption of the video buffer. We implemented our algorithm in the SVC-HAS client and deployed a testbed that could run Smooth-Streaming, which is one of the most popular HAS solutions, over CCNx, which is the reference implementation of CCN. Our experimental results showed that the proposed scheme (SLA) could avoid video freeze in an effective manner, but without reducing the high hit rate on the CCN routers or affecting the high video quality on the SVC-HAS client.

• Korean Journal of Environment and Ecology
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• v.20 no.3
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• pp.319-330
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• 2006

It is imperative that pictograms as pictorial information be empirically tested in order to establish whether the users do indeed associate the appropriate referent in an actual usage situation. The experiment employing the Multiple Index Approach was conducted in a class room with 64 subjects to evaluate tourism and recreation related pictograms. Performance data(hit rate, false alarm and missing value) of 25 pictograms were collected and the average hit rate as a prime index of pictogram associativeness was 65.82%. The matrix analysis showed 14 pictograms were high in subjective certainty and subjective suitability. The other 11, which were low in both criteria may require prior learning or improvement of the pictogram designs to represent their meanings more distinctively.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.1
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• pp.128-136
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• 2008

In this paper, we propose a new cache structure for effective error correction of soft error. We added check bit and SEEB(soft error evaluation block) to evaluate the status of cache line. The SEEB stores result of parity check into the two-bit shit register and set the check bit to '1' when parity check fails twice in the same cache line. In this case the line where parity check fails twice is treated as a vulnerable to soft error. When the data is filled into the cache, the new replacement algorithm is suggested that it can only use the valid block determined by SEEB. This structure prohibits the vulnerable line from being used and contributes to efficient use of cache by the reuse of line where parity check fails only once can be reused. We tried to minimize the side effect of the proposed cache and the experimental results, using SPEC2000 benchmark, showed 3% degradation in hit rate, 15% timing overhead because of parity logic and 2.7% area overhead. But it can be considered as trivial for SEEB because almost tolerant design inevitably adopt this parity method even if there are some overhead. And if only parity logic is used then it can have $5%{\sim}10%$ advantage than ECC logic. By using this proposed cache, the system will be protected from the threat of soft error in cache and the hit rate can be maintained to the level without soft error in the cache.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.2
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• pp.137-143
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• 2015

During the past 30 years, DRAM has been used for the reasons of economic efficiency of the production. Recently, PRAM has been emerged to overcome the shortcomings of DRAM. In this paper, we propose a technique that can reduce energy consumption by use of a narrow values to the write operation of PRAM. For this purpose, we describe the data compression method using a narrow value and the architecture of PRAM, We also experiment under the Simplescalar 3.0e simulator and SPEC CPU2000 benchmark environments. According to the experiments, the data hit rate of PRAM was increased by 39.4% to 67.7% and energy consumption was reduced by 9.2%. In order to use the proposed technique, it requires 3.12% of space overhead per word, and some additional hardware modules.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.30 no.7
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• pp.68-80
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• 2002

An approach for composing a performance optimized computational code is suggested for latest microprocessors. The concept of the code optimization, called here as localization, is maximizing the utilization of the second level cache that is common to all the latest computer system, and minimizing the access to system main memory. In this study, the localized optimization of LU-SGS (Lower-Upper Symmetric Gauss-Seidel) code for the solution of fluid dynamic equations was carried out in three different levels and tested for several different microprocessor architectures most widely used in these days. The test results of localized optimization showed a remarkable performance gain up to 7.35 times faster solution, depending on the system, than the baseline algorithm for producing exactly the same solution on the same computer system.