• The Journal of the Korea Contents Association
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• v.18 no.2
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• pp.147-157
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• 2018

Recently, with the advancement of network technologies, and the activation of IoT and social network services, many graph stream data have been generated. As the relationship between objects in the graph streams changes dynamically, studies have been conducting to detect or analyze the change of the graph. In this paper, we propose a scheme to incrementally detect frequent patterns by using frequent patterns information detected in previous sliding windows. The proposed scheme calculates values that represent whether the frequent patterns detected in previous sliding windows will be frequent in how many future silding windows. By using the values, the proposed scheme reduces the overall amount of computation by performing only necessary calculations in the next sliding window. In addition, only the patterns that are connected between the patterns are recognized as one pattern, so that only the more significant patterns are detected. We conduct various performance evaluations in order to show the superiority of the proposed scheme. The proposed scheme is faster than existing similar scheme when the number of duplicated data is large.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.5
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• pp.587-592
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• 2018

Because the brightness of an AMOLED is determined by the flowing current, each pixel of AMOLED operates via A current driving method. Therefore, it is necessary to supply power to adjust the amount of current according to THE user's requirement for AMOLED driving. In this study, an IP driver block was designed and a simulation was conducted for an AMOLED display, which supplies power as selected by users. The IP driver design focused on regulating the output power due to the OLED characteristics for the diode electric current according to the voltage to be activated by pulse-skipping mode (PSM) under low loads, and 1.5 MHz pulse-width modulation (PWM) for medium/high loads. The IP driver was designed to eliminate the ringing effects appearing from the dis-continue mode (DCM) of the step-up converter. The ringing effects destroy the power switch within the IC, or increase the EMI to the surrounding elements. The IP driver design minimized this through a ringing killer circuit. Mobile applications were considered to enable true shut-down capability by designing the standby current to fall below $1{\mu}A$ to disable it. The driver proposed in this paper can be applied effectively to the same system as the AMOLED display dual power management circuit.

• KIPS Transactions on Software and Data Engineering
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• v.4 no.12
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• pp.543-548
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• 2015

Recently top-k query processing has been extremely important along with the explosion of data produced by a variety of applications. Top-k queries return the best k results ordered by a user-provided monotone scoring function. As cloud computing service has been getting more popular than ever, a hot attention has been paid to cloud-based data outsourcing in which clients' data are stored and managed by the cloud. The cloud-based data outsourcing, though, exposes a critical secuity concern of sensitive data, resulting in the misuse of unauthorized users. Hence it is essential to encrypt sensitive data before outsourcing the data to the cloud. However, there has been little attention to efficient top-k processing on the encrypted cloud data. In this paper we propose a novel top-k processing algorithm that can efficiently process a large amount of encrypted data in the cloud. The main idea of the algorithm is to prune unpromising intermediate results at the early phase without decrypting the encrypted data by leveraging an order-preserving encrypted technique. Experiment results show that the proposed top-k processing algorithm significantly reduces the overhead of client systems from 10X to 10000X.

• Journal of Convergence for Information Technology
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• v.10 no.3
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• pp.195-199
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• 2020

This study examined the effect of the nervous-system-stimulating caffeine on the nerve conduction velocity. The purpose of this study is to investigate the effect of caffeine that stimulates the nervous system on nerve conduction test. Although both measurement intervals did not show statistically significant differences when comparing the pre- and post-NCV values within the control and individual experimental groups, it was found that the nerve conductivity in the Axilla-Above Elbow section increased significantly after caffeine intake for the experimental group. Caffeine intake, which has increased the nerve conduction velocity (NCV), was determined to play roles in improving motor skills, muscle strength and nerve performance by temporarily increasing the nerve conduction velocity. Through this study, we learned that caffeine has an influence on the peripheral nervous system as it helps to improve the nerve conduction velocity. upon an appropriate amount of caffeine intake. We hope that these results will help develop treatment and diagnostic methods for patients with nerve dysfunction and myofunctional disorders.

• The KIPS Transactions:PartD
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• v.16D no.1
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• pp.27-42
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• 2009

In realizing ubiquitous computing, techniques of efficiently using the limited resource at client such as mobile devices are required. With a mobile device with limited amount of memory, the techniques of XML stream query processing should be employed to process queries over a large volume of XML data. Recently, several techniques were proposed which fragment XML documents into XML fragments and stream them for query processing at client. During query processing, there could be great difference in resource usage (query processing time and memory usage) depending on how the source XML documents are fragmented. As such, an efficient fragmentation technique is needed. In this paper, we propose an XML fragmentation technique whereby resource efficiency in query processing at client could be enhanced. For this, we first present a cost model of query processing over XML fragment stream. Then, we propose an algorithm for resource-efficient XML fragmentation. Through implementation and experiments, we showed that our fragmentation technique outperformed previous techniques both in processing time and memory usage. The contribution of this paper is to have made the techniques of query processing over XML fragment stream more feasible for practical use.

• Journal of the Korea Society for Simulation
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• v.19 no.1
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• pp.53-61
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• 2010

In wireless sensor networks(WSNs) individual sensor nodes are subject to security compromises. An adversary can physically capture sensor nodes and obtain the security information. And the adversary injects false reports into the network using compromised nodes. If undetected, these false reports are forwarded to the base station. False reports injection attacks can not only result in false alarms but also depletion of the limited amount of energy in battery powered sensor nodes. To combat these false reports injection attacks, several filtering schemes have been proposed. The statistical en-routing filtering(SEF) scheme can detect and drop false reports during the forwarding process. In SEF, The number of the message authentication codes(threshold) is important for detecting false reports and saving energy. In this paper, we propose a dynamic threshold determination method for energy efficient SEF using fuzzy-logic in wireless sensor networks. The proposed method consider false reports rate and the number of compromised partitions. If low rate of false reports in the networks, the threshold should low. If high rate of false reports in networks, the threshold should high. We evaluated the proposed method’s performance via simulation.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.4
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• pp.149-158
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• 2023

As data utilization is becoming more important recently, the importance of data centers is also increasing. However, the data center is a problem in terms of environment and economy because it is a massive power-consuming facility that runs 24 hours a day. Recently, studies using deep learning techniques to reduce power used in data centers or servers or predict traffic have been conducted from various perspectives. However, the amount of traffic data processed by the server is anomalous, which makes it difficult to manage the server. In addition, many studies on dynamic server management techniques are still required. Therefore, in this paper, we propose a dynamic server management technique based on Long-Term Short Memory (LSTM), which is robust to time series data prediction. The proposed model allows servers to be managed more reliably and efficiently in the field environment than before, and reduces power used by servers more effectively. For verification of the proposed model, we collect transmission and reception traffic data from six of Wikipedia's data centers, and then analyze and experiment with statistical-based analysis on the relationship of each traffic data. Experimental results show that the proposed model is helpful for reliably and efficiently running servers.

• Journal of KIISE
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• v.41 no.11
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• pp.943-957
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• 2014

Removing noise, called denoising, is an essential factor for the more intuitive and more accurate results in boundary image matching. This paper deals with a partial denoising problem that tries to allow a limited amount of partial noise embedded in boundary images. To solve this problem, we first define partial denoising time-series which can be generated from an original image time-series by removing a variety of partial noises and propose an efficient mechanism that quickly obtains those partial denoising time-series in the time-series domain rather than the image domain. We next present the partial denoising distance, which is the minimum distance from a query time-series to all possible partial denoising time-series generated from a data time-series, and we use this partial denoising distance as a similarity measure in boundary image matching. Using the partial denoising distance, however, incurs a severe computational overhead since there are a large number of partial denoising time-series to be considered. To solve this problem, we derive a tight lower bound for the partial denoising distance and formally prove its correctness. We also propose range and k-NN search algorithms exploiting the partial denoising distance in boundary image matching. Through extensive experiments, we finally show that our lower bound-based approach improves search performance by up to an order of magnitude in partial denoising-based boundary image matching.

• Journal of KIISE:Computing Practices and Letters
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• v.14 no.2
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• pp.191-195
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• 2008

This paper proposes a technique for improving IEEE 802.11e EDCA's performance by dynamically adjusting each class's contention window size based on each class's traffic amount. For providing differentiated service differently from 802.11, 802.11e EDCA maintains four classes each of which specifies different static minimum and maximum contention window sizes. Since the initial window sites significantly affect the 802.11e performance, several window adjustment schemes have been proposed. One of the schemes known as CWminAS (CWmin Adaptation Scheme) dynamically and synchronously determines the four windows' site based on the periodically measured collision rate. This method, however, can lower the send probability of high priority classes since it can't differentiate their collisions from those of low priority classes, leading to the channel underutilization. For solving this problem, we propose ACATICT(Adaptive Contention-window Adjustment Technique based on Individual Class Traffic) algorithm which adapts each class window size based on each individual collision rate rather than one average collision rate. Our simulation experiments show that ACATICT achieves better utilization by around 10% at maximum.

• The KIPS Transactions:PartA
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• v.16A no.3
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• pp.169-180
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• 2009

With fixed sinks, the network stability could be improved while the network life time could be decreased by the rapid energy dissipation around the fixed sink because of the concentrated network traffic from sensor nodes to the fixed sink in wireless sensor network. To address this problem, mobile sinks, which decentralize the network traffic, has received a lot of attention from many researchers recently. Since a mobile sink has a limited period to communicate with each sensor nodes, it is necessary for a scheduling algorithm to provide the fairness of data collection from each sensor nodes. In the paper, we propose the new scheduling algorithm, ASF(Availability based Scheduling scheme for Fair data collection), for the fair data collection by a mobile in the sensor networks. The ASF takes account of the distance between each sensor nodes and the mobile sink as scheduling metric, as well as the amount of collected data from each sensor nodes. Experiment results shows that the ASF improves the fairness of data collection among the sensor nodes, comparing to existing algorithm.