• 전자공학회논문지 IE
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• v.46 no.1
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• pp.31-36
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• 2009

This study was to simulate it that the sending receiving vehicles run on the general national roads with the one-way two-lanes at 80[km/h] speed. This study was to select 280[m] radius of curvature based on the statistical data with high rate of traffic accidents, 140[m] length of direct roads considering the stopping stadia, 90[m] length of curve, and 8 points of curved roads at 11.25[m] intervals. As a result above, when the distance between the sending and receiving vehicles became more than 111[m], the propagation path of reflected wave by the adjacent vehicles became longer than the propagation path of reflected wave by the left/right reflectors because the number of repeated reflection increased. In this study, the repeated reflection for the propagation's reach to the receiving vehicles was about $1{\sim}2$[times] as it supposed it less than 111[m]. Accordingly, it found out that the propagation path of reflected wave received through the left/right reflectors was about $1{\sim}1.5[m]$ larger than the reflected wave produced by the adjacent vehicles regardless of lanes on which the sending and receiving vehicles were located.

• Journal of Korean Society of Transportation
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• v.27 no.5
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• pp.209-221
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• 2009

Travel time estimation under given traffic conditions is important for providing drivers with travel time prediction information. But the present expressway travel time estimation process cannot calculate a reliable travel time. The objective of this study is to estimate the path travel time spent in a through lane between origin tollgates and destination tollgates on an expressway as a prerequisite result to offer reliable prediction information. Useful and abundant toll collection system (TCS) data were used. When estimating the path travel time, the path travel time is estimated combining the link travel time obtained through a preprocessing process. In the case of a lack of TCS data, the TCS travel time for previous intervals is referenced using the linear interpolation method after analyzing the increase pattern for the travel time. When the TCS data are absent over a long-term period, the dynamic travel time using the VDS time space diagram is estimated. The travel time estimated by the model proposed can be validated statistically when compared to the travel time obtained from vehicles traveling the path directly. The results show that the proposed model can be utilized for estimating a reliable travel time for a long-distance path in which there are a variaty of travel times from the same departure time, the intervals are large and the change in the representative travel time is irregular for a short period.

• Journal of Internet Computing and Services
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• v.14 no.5
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• pp.69-76
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• 2013

The incidence of globally infectious and pathogenic diseases such as H1N1 (swine flu) and Avian Influenza (AI) has recently increased. An infectious disease is a pathogen-caused disease, which can be passed from the infected person to the susceptible host. Pathogens of infectious diseases, which are bacillus, spirochaeta, rickettsia, virus, fungus, and parasite, etc., cause various symptoms such as respiratory disease, gastrointestinal disease, liver disease, and acute febrile illness. They can be spread through various means such as food, water, insect, breathing and contact with other persons. Recently, most countries around the world use a mathematical model to predict and prepare for the spread of infectious diseases. In a modern society, however, infectious diseases are spread in a fast and complicated manner because of rapid development of transportation (both ground and underground). Therefore, we do not have enough time to predict the fast spreading and complicated infectious diseases. Therefore, new system, which can prevent the spread of infectious diseases by predicting its pathway, needs to be developed. In this study, to solve this kind of problem, an integrated monitoring system, which can track and predict the pathway of infectious diseases for its realtime monitoring and control, is developed. This system is implemented based on the conventional mathematical model called by 'Susceptible-Infectious-Recovered (SIR) Model.' The proposed model has characteristics that both inter- and intra-city modes of transportation to express interpersonal contact (i.e., migration flow) are considered. They include the means of transportation such as bus, train, car and airplane. Also, modified real data according to the geographical characteristics of Korea are employed to reflect realistic circumstances of possible disease spreading in Korea. We can predict where and when vaccination needs to be performed by parameters control in this model. The simulation includes several assumptions and scenarios. Using the data of Statistics Korea, five major cities, which are assumed to have the most population migration have been chosen; Seoul, Incheon (Incheon International Airport), Gangneung, Pyeongchang and Wonju. It was assumed that the cities were connected in one network, and infectious disease was spread through denoted transportation methods only. In terms of traffic volume, daily traffic volume was obtained from Korean Statistical Information Service (KOSIS). In addition, the population of each city was acquired from Statistics Korea. Moreover, data on H1N1 (swine flu) were provided by Korea Centers for Disease Control and Prevention, and air transport statistics were obtained from Aeronautical Information Portal System. As mentioned above, daily traffic volume, population statistics, H1N1 (swine flu) and air transport statistics data have been adjusted in consideration of the current conditions in Korea and several realistic assumptions and scenarios. Three scenarios (occurrence of H1N1 in Incheon International Airport, not-vaccinated in all cities and vaccinated in Seoul and Pyeongchang respectively) were simulated, and the number of days taken for the number of the infected to reach its peak and proportion of Infectious (I) were compared. According to the simulation, the number of days was the fastest in Seoul with 37 days and the slowest in Pyeongchang with 43 days when vaccination was not considered. In terms of the proportion of I, Seoul was the highest while Pyeongchang was the lowest. When they were vaccinated in Seoul, the number of days taken for the number of the infected to reach at its peak was the fastest in Seoul with 37 days and the slowest in Pyeongchang with 43 days. In terms of the proportion of I, Gangneung was the highest while Pyeongchang was the lowest. When they were vaccinated in Pyeongchang, the number of days was the fastest in Seoul with 37 days and the slowest in Pyeongchang with 43 days. In terms of the proportion of I, Gangneung was the highest while Pyeongchang was the lowest. Based on the results above, it has been confirmed that H1N1, upon the first occurrence, is proportionally spread by the traffic volume in each city. Because the infection pathway is different by the traffic volume in each city, therefore, it is possible to come up with a preventive measurement against infectious disease by tracking and predicting its pathway through the analysis of traffic volume.

• Journal of Intelligence and Information Systems
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• v.11 no.3
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• pp.25-43
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• 2005

In modern automated container terminals, automated guided vehicle (AGV) systems are considered a viable option for the horizontal tansportation of containers between the stacking yard and the quayside cranes. AGVs in a container terminal move rather freely and do not follow fixed guide paths. For an efficient operation of such AGVs, however, a sophisticated traffic management system is required. Although the flexible routing scheme allows us to find the shortest possible routes for each of the AGVs, it may incur many coincidental encounters and path intersections of the AGVs, leading to collisions or deadlocks. However, the computational cost of perfect prediction and avoidance of deadlocks is prohibitively expensive for a real time application. In this paper, we propose a traffic control method that predicts and avoids some simple, but at the same time the most frequently occurring, cases of deadlocks between two AGVs. More complicated deadlock situations are not predicted ahead of time but detected and resolved after they occur. Our method is computationally cheap and readily applicable to real time applications. The efficiency and effectiveness of our proposed methods have been validated by simulation.

• Journal of the Korea Society of Computer and Information
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• v.28 no.10
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• pp.1-8
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• 2023

If there is a defect in the wheel bearing, which is a major part of the car, it can cause problems such as traffic accidents. In order to solve this problem, big data is collected and monitoring is conducted to provide early information on the presence or absence of wheel bearing failure and type of failure through predictive diagnosis and management technology. System development is needed. In this paper, to implement such an intelligent wheel hub bearing maintenance system, we develop an embedded system equipped with sensors for monitoring reliability and soundness and algorithms for predictive diagnosis. The algorithm used acquires vibration signals from acceleration sensors installed in wheel bearings and can predict and diagnose failures through big data technology through signal processing techniques, fault frequency analysis, and health characteristic parameter definition. The implemented algorithm applies a stable signal extraction algorithm that can minimize vibration frequency components and maximize vibration components occurring in wheel bearings. In noise removal using a filter, an artificial intelligence-based soundness extraction algorithm is applied, and FFT is applied. The fault frequency was analyzed and the fault was diagnosed by extracting fault characteristic factors. The performance target of this system was over 12,800 ODR, and the target was met through test results.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.42 no.2
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• pp.523-535
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• 2017

Local intelligent services aim at controlling local services such as cooling or lightening services in a certain local area, using Internet-of-Things (IoT) sensor data in the area. As the IoT paradigm has evolved, local intelligent services have gained increasing attention. However, most of the local intelligent service mechanism proposed so far do not directly take the users' presence and service preference information into account for controlling local services. This study proposes an individual presence-and-preference-based local service system (IPP-LISS). We present a intelligent service control algorithm and implement a prototype system of IPP-LISS. Typically, the intelligence part of IPP-LISS including the prediction models, is generated on remote server in the cloud because of their compute-intense aspect. However, this can cause huge data traffic between IoT devices and servers in the cloud. The emerging mobile edge computing technology will be a promising solution of this challenge of IPP-LISS. In this paper, we implement IPP-LISS in the cloud, and then, based on the implementation result, we discuss applying the mobile edge computing technology to the IPP-LISS application.

• International Journal of High-Rise Buildings
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• v.1 no.1
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• pp.15-19
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• 2012

Occupant footfalls are often the most critical source of floor vibration on upper floors of buildings. Floor motions can degrade the performance of imaging equipment, disrupt sensitive research equipment, and cause discomfort for the occupants. It is essential that low-vibration environments be provided for functionality of sensitive spaces on floors above grade. This requires a sufficiently stiff and massive floor structure that effectively resists the forces exerted from user traffic. Over the past 25 years, generic vibration limits have been developed, which provide frequency dependent sensitivities for wide classes of equipment, and are used extensively in lab design for healthcare and research facilities. The same basis for these curves can be used to quantify acceptable limits of vibration for human comfort, depending on the intended occupancy of the space. When available, manufacturer's vibration criteria for sensitive equipment are expressed in units of acceleration, velocity or displacement and can be specified as zero-to-peak, peak-to-peak, or root-mean-square (rms) with varying frequency ranges and resolutions. Several approaches to prediction of floor vibrations are currently applied in practice. Each method is traceable to fundamental structural dynamics, differing only in the level of complexity assumed for the system response, and the required information for use as model inputs. Three commonly used models are described, as well as key features they possess that make them attractive to use for various applications. A case study is presented of a tall building which has fitness areas on two of the upper floors. The analysis predicted that the motions experienced would be within the given criteria, but showed that if the floor had been more flexible, the potential exists for a locked-in resonance response which could have been felt over large portions of the building.

• 전자공학회논문지 IE
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• v.44 no.1
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• pp.27-32
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• 2007

This study was to suggest the predictive model of propagation, considering the effect by the multipath waves produced by the sending and receiving vehicles' left/right reflectors and the adjacent vehicles when the communication between the vehicles on the one-way two-lanes road in the urban city with a lot of traffic jams. Then, the radius of curved road was 600[m], the length of curved roads $52.4\sim471.2[m]$, and the bridge's pier of road was $5o\sim45o$. Also, it was simulated by changing the receiving vehicle located on the curved road's gap from minimum 3.3[m] to maximum 29.5[m], corresponding to the change of distance of the bridge's pier of road and curved road. As a result of this research above, in case of $5o\sim15o$ bridge's pier of road, it was within l[dB] regardless of the receiving vehicle's position on the curved road in case of propagation path loss. In case of $15o\sim45o$, it was approximately $1\sim8[dB]$ as the bridge's pier of road is changed. And, in case of propagation path, it found out that it was changed to $0.4\sim120[m]$ according to the change of bridge's pier of road. Then, the delay time of propagation was 400[nsec] as it produced 120[m] in the difference of propagation path.

• Journal of KIISE:Computer Systems and Theory
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• v.37 no.5
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• pp.292-303
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• 2010

On-chip cache memories play an important role in both performance and energy consumption points of view in resource-constrained embedded systems by filtering many off-chip memory accesses. We propose a 2-level data cache architecture with a low energy-delay product tailored for the embedded systems. The L1 data cache is small and direct-mapped, and employs a write-through policy. In contrast, the L2 data cache is set-associative and adopts a write-back policy. Consequently, the L1 data cache is accessed in one cycle and is able to provide high cache bandwidth while the L2 data cache is effective in reducing global miss rate. To reduce the penalty of high miss rate caused by the small L1 cache and power consumption of address generation, we propose an ECP(Early Cache hit Predictor) scheme. The ECP predicts if the L1 cache has the requested data using both fast address generation and L1 cache hit prediction. To reduce high energy cost of accessing the L2 data cache due to heavy write-through traffic from the write buffer laid between the two cache levels, we propose a one-way write scheme. From our simulation-based experiments using a cycle-accurate simulator and embedded benchmarks, the proposed 2-level data cache architecture shows average 3.6% and 50% improvements in overall system performance and the data cache energy consumption.

• Journal of Intelligence and Information Systems
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• v.27 no.4
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• pp.23-48
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• 2021

The Korean economy has achieved continuous economic growth for the past several decades thanks to the government's export strategy policy. This increase in exports is playing a leading role in driving Korea's economic growth by improving economic efficiency, creating jobs, and promoting technology development. Traditionally, the main factors affecting Korea's exports can be found from two perspectives: economic factors and industrial structural factors. First, economic factors are related to exchange rates and global economic fluctuations. The impact of the exchange rate on Korea's exports depends on the exchange rate level and exchange rate volatility. Global economic fluctuations affect global import demand, which is an absolute factor influencing Korea's exports. Second, industrial structural factors are unique characteristics that occur depending on industries or products, such as slow international division of labor, increased domestic substitution of certain imported goods by China, and changes in overseas production patterns of major export industries. Looking at the most recent studies related to global exchanges, several literatures show the importance of cultural aspects as well as economic and industrial structural factors. Therefore, this study attempted to develop a forecasting model by considering cultural factors along with economic and industrial structural factors in calculating the import volume of each country from Korea. In particular, this study approaches the influence of cultural factors on imports of Korean products from the perspective of PUSH-PULL framework. The PUSH dimension is a perspective that Korea develops and actively promotes its own brand and can be defined as the degree of interest in each country for Korean brands represented by K-POP, K-FOOD, and K-CULTURE. In addition, the PULL dimension is a perspective centered on the cultural and psychological characteristics of the people of each country. This can be defined as how much they are inclined to accept Korean Flow as each country's cultural code represented by the country's governance system, masculinity, risk avoidance, and short-term/long-term orientation. The unique feature of this study is that the proposed final prediction model can be selected based on Design Principles. The design principles we presented are as follows. 1) A model was developed to reflect interest in Korea and cultural characteristics through newly added data sources. 2) It was designed in a practical and convenient way so that the forecast value can be immediately recalled by inputting changes in economic factors, item code and country code. 3) In order to derive theoretically meaningful results, an algorithm was selected that can interpret the relationship between the input and the target variable. This study can suggest meaningful implications from the technical, economic and policy aspects, and is expected to make a meaningful contribution to the export support strategies of small and medium-sized enterprises by using the import forecasting model.