• Journal of IKEEE
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• v.11 no.4
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• pp.348-357
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• 2007

Due to the improved performance and cost of personal mobile devices and rapid progress of wireless communication technology, the number of users who utilize these devices is increasing. This trend requires various types of services be available to users. So far, there have been many solutions provided for the shortest path problem. But, technologies which can offer various recommendation services to user depending on user’s current location are focused on Euclidean spaces rather than road network. Thus, in this paper, we extend the previous work to satisfy this requirement on road network database. Our proposed scheme requires pre-computation for the efficient query processing. In the preprocessing step, we first partition the input road network into a fixed number of Voronoi polygons and then pre-compute routing information for each polygon. In the meantime, we select the number of Voronoi polygons in proposition to the scale of road network. Through this selection, the required size of pre-computation is linearly increasing to the size of road network. Using this pre-computated information, we can process queries more quickly. Through experiments, we have shown that our proposed scheme can achieve excellent performance in terms of scheduling time and the number of visited nodes.

• Journal of the Korea Society for Simulation
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• v.15 no.4
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• pp.119-128
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• 2006

A turnout system which permits trains to pass from one track to another is a combination of the switch, the crossing, lead rails which are necessary to connect the switch and the crossing, two guard rails and a switch machine for operating the switch. A turnout is the sole moving part among the railway components and has complex configuration, so the safety has always been raised an issue. In Korea, it is planned to adopt the high speed tilting train, which operates at the maximum speed of 200km/h, at conventional lines by the year of 2010. However, for the application of the tilting train to conventional lines, it is prerequisite to establish a stable turnout system allowing the tilting train to pass through it without reducing speed. Therefore, the improved turnout system for the speed-up of conventional lines has been developed and the prototype of the turnout system has been constructed. In this study, simulation of noise and vibration around the improved turnout system was performed in order to predict the generation level of noise and vibration due to passing of the tilting train through the turnout system.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.11 no.1
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• pp.56-67
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• 1999

It is desired to use a domestically manufactured ocean data buoy for the long-term operational ocean monitoring. The ocean data buoy manufacturing technology was introduced through the research cooperation with the Qingkong University of Taiwan. The introduced ocean data buoy system was further expanded and improved for more efficient application for the marine environmental monitoring in Korea. The size of the ocean data buoy is 2.5 m in diameter, which is smaller compared to the NOAA's 3.0 m discus buoy to allow easy land transportation and ocean deployment as well. From the dynamic response test of the buoy carried out numerically, it was shown that the measurement of waves with period greater than 4 seconds is acceptable. The measurement and control system of the data buoy were improved to increase the number of measuring parameters, to reduce power consumption and to enhance better data analysis and management. Each component of the improved data buoy system was described in detail in this paper. Water quality sensors of water temperature, salinity, DO, pH and turbidity were added to the system in addition to the marine meteorological sensors of wind speed and direction, air temperature, humidity, air pressure and wave. Inmarsat satellite communication system is used for the real-time data telemetry from the buoy deployed offshore. A field performance test of the improved and domestically manufactured buoy was carried out for a month at the open sea off Pohang together with DatawelI's Wave-rider buoy to compare the wave data. The results of the test were satisfactory.

• Journal of Korea Multimedia Society
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• v.9 no.5
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• pp.595-605
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• 2006

In this thesis, GPS and the electronic mapping were used to realize such a system by recognizing license plate numbers and identifying the location of objects that move at synchronous times with simulated movement in the electronic map. As well, throughout the study, a camera attached to a PDA, one of the mobile devices, automatically recognized and confirmed acquired license plate numbers from the front and back of each car. Using this mobile technique in a wireless network, searches for specific plate numbers and information about the location of the car is transmitted to a remote server. The use of such a GPS-based system allows for the measurement of topography and the effective acquisition of a car's location. The information is then transmitted to a central controlling center and stored as text to be reproduced later in the form of diagrams. Getting positional information through GPS and using image-processing with a PDA makes it possible to estimate the correct information of a car's location and to transmit the specific information of the car to a control center simultaneously, so that the center will get information such as type of the car, possibility of the defects that a car might have, and possibly to offer help with those functions. Such information can establish a mobile system that can recognize and accurately trace the location of cars.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.10
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• pp.373-380
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• 2022

This paper presents a deep learning based group synchronization that supports networked immersive interactions between remote users. The goal of group synchronization is to enable all participants to synchronously interact with others for increasing user presence Most previous methods focus on NTP-based clock synchronization to enhance time accuracy. Moving average filters are used to control media playout time on the synchronization server. As an example, the exponentially weighted moving average(EWMA) would be able to track and estimate accurate playout time if the changes in input data are not significant. However it needs more time to be stable for any given change over time due to codec and system loads or fluctuations in network status. To tackle this problem, this work proposes the Deep Group Synchronization(DeepGroupSync), a group synchronization based on deep learning that models important features from the data. This model consists of two Gated Recurrent Unit(GRU) layers and one fully-connected layer, which predicts an optimal playout time by utilizing the sequential playout delays. The experiments are conducted with an existing method that uses the EWMA and the proposed method that uses the DeepGroupSync. The results show that the proposed method are more robust against unpredictable or rapid network condition changes than the existing method.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.34 no.4
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• pp.747-761
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• 2024

Recently, modern vehicles have been controlled by Electronic Control Units (ECUs), by which the safety and convenience of drivers are highly improved. It is known that a luxury vehicle has more than 100 ECUs to electronically control its function. However, the modern vehicles are getting targeted by cyber attacks because of this computer-based automotive system. To address the cyber attacks, automotive manufacturers have been developing some methods for securing their vehicles, such as automotive Intrusion Detection System (IDS). This development is only allowed to the automotive manufacturers because they have databases for their in-vehicle network (i.e., DBC Format File) which are highly confidential. This confidentiality poses a significant challenge to external researchers who attempt to conduct automotive security researches. To handle this restricted information, in this paper, we propose a method to partially understand the DBC Format File by analyzing in-vehicle network traffics. Our method is designed to analyze Controller Area Network (CAN) traffics so that checksum signals are identified in CAN Frame Data Field. Also, our method creates a Lookup Set by which a checksum signal is correctly estimated for a given message. We validate our method with the publicly accessible dataset as well as one from a real vehicle.

• Korean Chemical Engineering Research
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• v.60 no.2
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• pp.249-254
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• 2022

With the rapid advance of the semiconductor and Information and communication technologies, remote environment monitoring technology, which can detect and analyze surrounding environmental conditions with various types of sensors and wireless communication technologies, is also drawing attention. However, since the conventional remote environmental monitoring systems require external power supplies, it causes time and space limitations on comfortable usage. In this study, we proposed the concept of the self-powered remote environmental monitoring system by supplying the power with the levitation-electromagnetic generator (L-EMG), which is rationally designed to effectively harvest biomechanical energy in consideration of the mechanical characteristics of biomechanical energy. In this regard, the proposed L-EMG is designed to effectively respond to the external vibration with the movable center magnet considering the mechanical characteristics of the biomechanical energy, such as relatively low-frequency and high amplitude of vibration. Hence the L-EMG based on the fragile force equilibrium can generate high-quality electrical energy to supply power. Additionally, the environmental detective sensor and wireless transmission module are composed of the micro control unit (MCU) to minimize the required power for electronic device operation by applying the sleep mode, resulting in the extension of operation time. Finally, in order to maximize user convenience, a mobile phone application was built to enable easy monitoring of the surrounding environment. Thus, the proposed concept not only verifies the possibility of establishing the self-powered remote environmental monitoring system using biomechanical energy but further suggests a design guideline.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.46 no.3
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• pp.75-85
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• 2009

This work proposes a 13b 100MS/s 0.13um CMOS ADC for 3G communication systems such as two-carrier W-CDMA applications simultaneously requiring high resolution, low power, and small size at high speed. The proposed ADC employs a four-step pipeline architecture to optimize power consumption and chip area at the target resolution and sampling rate. Area-efficient high-speed high-resolution gate-bootstrapping circuits are implemented at the sampling switches of the input SHA to maintain signal linearity over the Nyquist rate even at a 1.0V supply operation. The cascode compensation technique on a low-impedance path implemented in the two-stage amplifiers of the SHA and MDAC simultaneously achieves the required operation speed and phase margin with more reduced power consumption than the Miller compensation technique. Low-glitch dynamic latches in sub-ranging flash ADCs reduce kickback-noise referred to the differential input stage of the comparator by isolating the input stage from output nodes to improve system accuracy. The proposed low-noise current and voltage references based on triple negative T.C. circuits are employed on chip with optional off-chip reference voltages. The prototype ADC in a 0.13um 1P8M CMOS technology demonstrates the measured DNL and INL within 0.70LSB and 1.79LSB, respectively. The ADC shows a maximum SNDR of 64.5dB and a maximum SFDR of 78.0dB at 100MS/s, respectively. The ABC with an active die area of $1.22mm^2$ consumes 42.0mW at 100MS/s and a 1.2V supply, corresponding to a FOM of 0.31pJ/conv-step.

• The KIPS Transactions:PartB
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• v.13B no.5 s.108
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• pp.561-568
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• 2006

WPS(Wearable Personal Station) for next generation PC can define as a core terminal of 'Ubiquitous Computing' that include information processing and network function and overcome spatial limitation in acquisition of new information. As a way to acquire significant dynamic gesture data of user from haptic devices, traditional gesture recognizer based on desktop-PC using wire communication module has several restrictions such as conditionality on space, complexity between transmission mediums(cable elements), limitation of motion and incommodiousness on use. Accordingly, in this paper, in order to overcome these problems, we implement hand gesture recognition system using fuzzy algorithm and neural network for Post PC(the embedded-ubiquitous environment using blue-tooth module and WPS). Also, we propose most efficient and reasonable hand gesture recognition interface for Post PC through evaluation and analysis of performance about each gesture recognition system. The proposed gesture recognition system consists of three modules: 1) gesture input module that processes motion of dynamic hand to input data 2) Relational Database Management System(hereafter, RDBMS) module to segment significant gestures from input data and 3) 2 each different recognition modulo: fuzzy max-min and neural network recognition module to recognize significant gesture of continuous / dynamic gestures. Experimental result shows the average recognition rate of 98.8% in fuzzy min-nin module and 96.7% in neural network recognition module about significantly dynamic gestures.

• Journal of Intelligence and Information Systems
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• v.21 no.4
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• pp.17-35
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• 2015

Demand forecasting is the activity of estimating the quantity of a product or service that consumers will purchase for a certain period of time. Developing precise forecasting models are considered important since corporates can make strategic decisions on new markets based on future demand estimated by the models. Many studies have developed market growth curve models, such as Bass, Logistic, Gompertz models, which estimate future demand when a market is in its early stage. Among the models, Bass model, which explains the demand from two types of adopters, innovators and imitators, has been widely used in forecasting. Such models require sufficient demand observations to ensure qualified results. In the beginning of a new market, however, observations are not sufficient for the models to precisely estimate the market's future demand. For this reason, as an alternative, demands guessed from those of most adjacent markets are often used as references in such cases. Reference markets can be those whose products are developed with the same categorical technologies. A market's demand may be expected to have the similar pattern with that of a reference market in case the adoption pattern of a product in the market is determined mainly by the technology related to the product. However, such processes may not always ensure pleasing results because the similarity between markets depends on intuition and/or experience. There are two major drawbacks that human experts cannot effectively handle in this approach. One is the abundance of candidate reference markets to consider, and the other is the difficulty in calculating the similarity between markets. First, there can be too many markets to consider in selecting reference markets. Mostly, markets in the same category in an industrial hierarchy can be reference markets because they are usually based on the similar technologies. However, markets can be classified into different categories even if they are based on the same generic technologies. Therefore, markets in other categories also need to be considered as potential candidates. Next, even domain experts cannot consistently calculate the similarity between markets with their own qualitative standards. The inconsistency implies missing adjacent reference markets, which may lead to the imprecise estimation of future demand. Even though there are no missing reference markets, the new market's parameters can be hardly estimated from the reference markets without quantitative standards. For this reason, this study proposes a case-based expert system that helps experts overcome the drawbacks in discovering referential markets. First, this study proposes the use of Euclidean distance measure to calculate the similarity between markets. Based on their similarities, markets are grouped into clusters. Then, missing markets with the characteristics of the cluster are searched for. Potential candidate reference markets are extracted and recommended to users. After the iteration of these steps, definite reference markets are determined according to the user's selection among those candidates. Then, finally, the new market's parameters are estimated from the reference markets. For this procedure, two techniques are used in the model. One is clustering data mining technique, and the other content-based filtering of recommender systems. The proposed system implemented with those techniques can determine the most adjacent markets based on whether a user accepts candidate markets. Experiments were conducted to validate the usefulness of the system with five ICT experts involved. In the experiments, the experts were given the list of 16 ICT markets whose parameters to be estimated. For each of the markets, the experts estimated its parameters of growth curve models with intuition at first, and then with the system. The comparison of the experiments results show that the estimated parameters are closer when they use the system in comparison with the results when they guessed them without the system.