• Journal of Service Research and Studies
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• v.3 no.2
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• pp.53-60
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• 2013

Datamining from the large data in the form of various techniques for obtaining information have been developed. In recent years one of the most sought areas of pattern recognition and machine learning method is created with most of existing learning algorithms based on categorical attributes to a rule or decision model. However, the real-world data, it may consist of numeric attributes in many cases. In addition it contains attributes with numerical values to the normal categorical attribute. In this case, therefore, it is required processes in order to use the data to learn an appropriate value for the type attribute. In this paper, the domain of the numeric attributes are divided into several segments using learning algorithm techniques of discritization. It is described Clustering with other data mining techniques. Large amount of first cluster with characteristics is similar records from the database into smaller groups that split multiple given finite patterns in the pattern space. It is close to each other of a set of patterns that together make up a bunch. Among the set without specifying a particular category in a given data by extracting a pattern. It will be described similar grouping of data clustering technique to classify the data.

• Journal of Korean Society of Transportation
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• v.33 no.1
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• pp.70-80
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• 2015

In recent years, tram has been the focus of a new mode of public transportation that can solve traffic jams and decrease public transit usage and environmental problem. This research is in the works to develop a tram signal controller and signal control strategies, and aim to resolve the problem of what could happen if a tram system was installed in general road. We developed the hierarchical signal control strategies to obtain a minimum tram bandwidth and to minimize vehicle delay, in order to perform a priority control to include passive and active signal priority control strategies. The strategies was produced for S/W and H/W, it is based in standard traffic signal controller. We conducted a micro simulation test to evaluate the hierarchical signal control strategies, which showed that the developed optimization model is effective to prevent a tram's stop in intersection, to reduce a tram's travel time and vehicle's delay.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.3
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• pp.116-126
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• 2015

In a distributed heterogeneous computing system, the performance of a parallel application greatly depends on its task scheduling algorithm. Therefore, in order to improve the performance, it is essential to consider some factors that can have effect on the performance of the parallel application in a given environment. One of the most important factors that affects the total execution time is a critical path. In this paper, we propose the CLTS algorithm for a task scheduling. The CLTS sets the priorities of all nodes to improve overall performance by applying leveling method to improve parallelism of task execution and by reducing the delay caused by waiting for execution of critical nodes in priority phase. After that, it conditionally uses insertion based policy or duplication based policy in processor allocation phase to reduce total schedule time. To evaluate the performance of the CLTS, we compared the CLTS with the DCPD and the HCPFD in our simulation. The results of the simulations show that the CLTS is better than the HCPFD by 7.29% and the DCPD by 8.93%. with respect to the average SLR, and also better than the HCPFD by 9.21% and the DCPD by 7.66% with respect to the average speedup.

• Journal of Internet Computing and Services
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• v.10 no.5
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• pp.41-47
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• 2009

Routing through a backbone, which is responsible for performing and managing multipoint communication, reduces the communication overhead and overall energy consumption in wireless sensor networks. However, the backbone nodes will need extra functionality and therefore consume more energy compared to the other nodes. The power consumption imbalance among sensor nodes may cause a network partition and failures where the transmission from some sensors to the sink node could be blocked. Hence optimal construction of the backbone is one of the pivotal problems in sensor network applications and can drastically affect the network's communication energy dissipation. In this paper a distributed algorithm is proposed to generate backbone trees through robust multi-hop clusters in wireless sensor networks. The main objective is to form a properly designed backbone through multi-hop clusters by considering energy level and degree of each node. Our improved cluster head selection method ensures that energy is consumed evenly among the nodes in the network, thereby increasing the network lifetime. Comprehensive computer simulations have indicated that the newly proposed scheme gives approximately 10.36% and 24.05% improvements in the performances related to the residual energy level and the degree of the cluster heads respectively and also prolongs the network lifetime.

• Journal of Internet Computing and Services
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• v.10 no.5
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• pp.65-78
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• 2009

The most commonly adopted approach to find valuable information from tree data is to extract frequently occurring subtree patterns from them. Because mining frequent tree patterns has a wide range of applications such as xml mining, web usage mining, bioinformatics, and network multicast routing, many algorithms have been recently proposed to find the patterns. However, existing tree mining algorithms suffer from several serious pitfalls in finding frequent tree patterns from massive tree datasets. Some of the major problems are due to (1) modeling data as hierarchical tree structure, (2) the computationally high cost of the candidate maintenance, (3) the repetitious input dataset scans, and (4) the high memory dependency. These problems stem from that most of these algorithms are based on the well-known apriori algorithm and have used anti-monotone property for candidate generation and frequency counting in their algorithms. To solve the problems, we base a pattern-growth approach rather than the apriori approach, and choose to extract maximal frequent subtree patterns instead of frequent subtree patterns. The proposed method not only gets rid of the process for infrequent subtrees pruning, but also totally eliminates the problem of generating candidate subtrees. Hence, it significantly improves the whole mining process.

• The KIPS Transactions:PartC
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• v.13C no.7 s.110
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• pp.803-812
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• 2006

This paper analytically evaluates the FEC(Forward Error Correction) symbol size's effect on the performance and energy consumption of 802.11 protocol with the block FEC algorithm over WSN(Wireless Sensor Network). Since the basic recovery unit of block FEC algorithms is symbols not bits, the FEC symbol size affects the packet correction rate even with the same amount of FEC check bits over a given WSN channel. Precisely, when the same amount of FEC check bits are allocated, the small-size symbols are effective over channels with frequent short bursts of propagation errors while the large ones are good at remedying the long rare bursts. To estimate the effect of the FEC symbol site, the paper at first models the WSN channel with Gilbert model based on real packet traces collected over TIP50CM sensor nodes and measures the energy consumed for encoding and decoding the RS (Reed-Solomon) code with various symbol sizes. Based on the WSN channel model and each RS code's energy expenditure, it analytically calculates the transmission efficiency and power consumption of 802.11 equipped with RS code. The computational analysis combined with real experimental data shows that the RS symbol size makes a difference of up to 4.2% in the transmission efficiency and 35% in energy consumption even with the same amount of FEC check bits.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.11
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• pp.836-840
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• 2009

Many researchers have studied flash memory in order to replace hard disk storages. Many FTL algorithms have been proposed to overcome physical constraints of flash memory such as erase-before-write, wear leveling, and poor write performance. Therefore, these constraints should be considered for testing FTL algorithms and the performance evaluation of flash memory. As doing the experiments, we suffer from several problems with costs and settings in experimental configuration. When we, for example, replay the traces of Oracle to evaluate the I/O performance with flash memory, it is hard to extract exact traces of I/O operations in Oracle. Since there are only write operations in the log, it is impossible to gather read operations. In MySQL and SQLite, we can gather the read operations by changing I/O functions in the source codes. But it is not easy to search for the exact points about I/O and even if we can find out the points, we might get wrong results depending on how we modify source codes to get I/O traces. The FlaSim proposed in this paper removes the difficulties when we evaluate the performance of FTL algorithms and flash memory. Our Linux drivers emulate the flash memory as a hard disk. And we can easily obtain the usage statistics of flash memory such as the number of write, read, and erase operations. The FlaSim can be gracefully extended to support the additional modules implemented by novel algorithms and ideas. In this paper, we describe the structure of FTL emulator, development tools and operating methods. We expect this emulator to be helpful for many experiments and research with flash memory.

• Journal of KIISE:Information Networking
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• v.35 no.2
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• pp.99-111
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• 2008

In recent years, the needs for WLANs(Wireless Local Area Networks) technology which can access to Internet anywhere have been dramatically increased particularly in SOHO(Small Office Home Office) and Hot Spot. However, unlike wired networks, there are some unique characteristics of wireless networks. These characteristics include the burst packet losses due to unreliable wireless channel. Note that burst packet losses, which occur when the distance between the wireless station and the AP(Access Point) increase or when obstacles move temporarily between the station and AP, are very frequent in 802.11 networks. Conversely, due to burst packet losses, the performance of 802.11 networks are not always as sufficient as the current application require, particularly when they use TCP at the transport layer. The high packet loss rate over wireless links can trigger unnecessary execution of TCP congestion control algorithm, resulting in performance degradation. In order to overcome the limitations of WLANs environment, MAC-layer LDA(Loss Differentiation Algorithm)has been proposed. MAC-layer LDA prevents TCP's timeout by increasing CRD(Consecutive Retry Duration) higher than burst packet loss duration. However, in the wireless channel with high packet loss rate, MAC-layer LDA does not work well because of two reason: (a) If the CRD is lower than burst packet loss duration due to the limited increase of retry limit, end-to-end performance is degraded. (b) energy of mobile device and bandwidth utilization in the wireless link are wasted unnecessarily by Reducing the drainage speed of the network buffer due to the increase of CRD. In this paper, we propose a new retransmission module based on Cross-layer approach, called BLD(Burst Loss Detection) module, to solve the limitation of previous link layer retransmission schemes. BLD module's algorithm is retransmission mechanism at IEEE 802.11 networks and performs retransmission based on the interaction between retransmission mechanisms of the MAC layer and TCP. From the simulation by using ns-2(Network Simulator), we could see more improved TCP throughput and energy efficiency with the proposed scheme than previous mechanisms.

• Journal of radiological science and technology
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• v.26 no.1
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• pp.71-82
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• 2003

In this paper, I proposed a classifier of liver cirrhotic step using T1-weighted MRI(magnetic resonance imaging) and hierarchical neural network. The data sets for classification of each stage, which were normal, 1type, 2type and 3type, were obtained in Pusan National University Hospital from June 2001 to december 2001. And the number of data was 46. We extracted liver region and nodule region from T1-weighted MR liver image. Then objective interpretation classifier of liver cirrhotic steps in T1-weighted MR liver images. Liver cirrhosis classifier implemented using hierarchical neural network which gray-level analysis and texture feature descriptors to distinguish normal liver and 3 types of liver cirrhosis. Then proposed Neural network classifier teamed through error back-propagation algorithm. A classifying result shows that recognition rate of normal is 100%, 1type is 82.3%, 2type is 86.7%, 3type is 83.7%. The recognition ratio very high, when compared between the result of obtained quantified data to that of doctors decision data and neural network classifier value. If enough data is offered and other parameter is considered, this paper according to we expected that neural network as well as human experts and could be useful as clinical decision support tool for liver cirrhosis patients.

• Journal of Internet Computing and Services
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• v.9 no.3
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• pp.141-158
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• 2008

In this paper, we developed the GML Map Server which visualized the map based on GML as international standard for exchanging the common format map and for interoperability of GIS information. And also, it should transmit effectively GML map into the mobile device by using dynamic map partition and caching. It manages a partition based on the visualization area of a mobile device in order to visualize the map to a mobile device in real time, and transmits the partition area by serializing it for the benefit of transmission. Also, the received partition area is compounded in a mobile device and is visualized by being partitioned again as four visible areas based on the display of a mobile device. Then, the area is managed by applying a caching algorithm in consideration of repetitiveness for a received map for the efficient operation of resources. Also, in order to prevent the delay in transmission time as regards the instance density area of the map, an adaptive map partition mechanism is proposed for maintaining the regularity of transmission time. GML Map Server can trace the position of mobile device with WIPI environment in this paper. The field emulator can be created mobile devices and mobile devices be moved and traced it's position instead of real-world. And we developed POIM(POI Management) for management hierarchically POI information and for the efficiency POI search by using the individual tagging technology with visual interface.