• Journal of Korea Foundry Society
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• v.30 no.1
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• pp.34-45
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• 2010

The effects of alloy elements and cooling rate on the solidification path and the formation behavior of $\beta$ phase in Fe-containing Al-Si alloys were studied based on the thermodynamic analysis and the pertinent experiments. The thermodynamic calculation was systematically performed by using Thermo-Calc program. For the thermodynamic analysis in high alloy region of Al-Si-Fe ternary system, a thermodynamic database for Thermo-Calc was correctly updated and revised by the collected up-to-date references. For the thermodynamic-based prediction of various solidification paths in Fe-containing Al-Si system, liquidus projection of Al-Si-Fe ternary system, including isotherms, invariant, monovariant, bivariant reactions and equilibrium temperatures, was calculated and analyzed as functions of composition and temperature. The calculated results were compared to the experimental results using various casting specimens. In order to analyze various solidification sequences as functions of Si and Fe content, 4 representative alloy compositions, low Fe content in both low and high Si contents and high Fe content again in both low and high Si contents, were designed in this study. For better understanding of the influence of cooling rate on the formation behavior of $\beta$ phase, 4 alloys were solidified under furnace and rapidly cooled conditions. Cooling curves of solidified alloys were recorded by thermal analysis. Various important solidification events were evaluated using the first derivative-cooling curves. Microstructures of the casting samples were studied by the combined analysis of optical microscopy (OM) and scanning electron microscopy (SEM).

• The KIPS Transactions:PartD
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• v.16D no.4
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• pp.621-630
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• 2009

In recent years, there have been many attempts to connect the latest RFID (Radio Frequency Identification) technology with EIS (Enterprise Information System) and utilize them. However, in most cases the focus is only on the simultaneous multiple reading capability of the RFID technology neglecting the management of massive data created from the reader. As a result, it is difficult to obtain time-related information such as flow prediction and analysis in process control. In this paper, we suggest a new method called 'procedure tree', an enhanced and complementary version of PathTree which is one of RFID data mining techniques, to manage massive RFID data sets effectively and to perform a real-time process control efficiently. We will evaluate efficiency of the proposed system after applying real-time process management system connected with the RFID-based EIS. Through the suggested method, we are able to perform such tasks as prediction or tracking of process flow for real-time process control and inventory management efficiently which the existing RFID-based production system could not have done.

• Journal of the Korea Society of Computer and Information
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• v.14 no.11
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• pp.159-167
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• 2009

The vehicles play a significant role in modern people's life as economy grows. The development of car navigation system(CNS) provides various convenience because it shows the driver where they are and how to get to the destination from the point of source. However, the existing map-based CNS does not consider any environments such as traffic congestion. Given the same starting point and destination, the system always provides the same route and the required time. This paper proposes a path planning method with traffic prediction by applying historical driving information to the Fuzzy theory and Bayesian update. Fuzzy theory classifies the historical driving information into groups of leaving time and speed rate, and the traffic condition of each time zone is calculated by Bayesian update. An ellipse area including starting and destination points is restricted in order to reduce the calculation time. The accuracy and practicality of the proposed scheme are verified by several experiments and comparisons with real navigation.

• Journal of the Korea Society of Computer and Information
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• v.27 no.8
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• pp.61-68
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• 2022

In this paper, we propose a system to predict the GPS trajectory of a pedestrian based on a deep learning model. Pedestrian trajectory prediction is a study that can prevent pedestrian danger and collision situations through notifications, and has an impact on business such as various marketing. In addition, it can be used not only for pedestrians but also for path prediction of unmanned transportation, which is receiving a lot of spotlight. Among various trajectory prediction methods, this paper is a study of trajectory prediction using GPS data. It is a deep learning model-based study that predicts the next route by learning the GPS trajectory of pedestrians, which is time series data. In this paper, we presented a data set construction method that allows the deep learning model to learn the GPS route of pedestrians, and proposes a trajectory prediction deep learning model that does not have large restrictions on the prediction range. The parameters suitable for the trajectory prediction deep learning model of this study are presented, and the model's test performance are presented.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.5
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• pp.113-118
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• 2015

Mobile wireless networks have received a lot of attention as a future wireless network due to its rapid deployment without communication infrastructure. In these networks communication path between two arbitrary nodes break down because some links in the path are beyond transmission range($r_0$) due to the mobility of the nodes. The set of total path break down time(${\bigcup}T_i$), which is the union of path break down time of every node pair, can be a good measure of the connectivity of the dynamic mobile wireless network. In this paper we show that the distribution of the total path break down time can be approximated as a exponential probability density function and confirms it through experimental data. Statistical knowledge of break down time enables quantitative prediction of delay, packet loss between two nodes, thus provides confidence in the simulation results of mobile wireless networks.

• The Journal of the Acoustical Society of Korea
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• v.27 no.8
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• pp.435-442
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• 2008

The n-gram model is appropriate for languages, such as English, in which the word-order is grammatically rigid. However, it is not suitable for Korean in which the word-order is relatively free. Previous work proposed a twoply HMM that reflected the characteristics of Korean but failed to reflect word-order structures among words. In this paper, we define a new segment unit which combines two words in order to reflect the characteristic of word-order among adjacent words that appear in verbal morphemes. Moreover, we propose a two-path language model that estimates probabilities depending on the context based on the proposed segment unit. Experimental results show that the proposed two-path language model yields 25.68% perplexity improvement compared to the previous Korean language models and reduces 94.03% perplexity for the prediction of verbal morphemes where words are combined.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.7 no.3
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• pp.219-229
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• 1996

Path loss prediction method, one of the most essential parts in measuring the service area in mobile telecommunication, has been developed for many years. But, wave propagation depends on many kinds of environmental factors such as frequency, distance, the heights of transmitting and receiving antenna and the terrain status(buildings in large city, hilly terrain, mountain). These are the main reasons that the propagation models developed in foreign environments can not fit into Korean propagation condition. In this paper, therefore, we performed the measurement in Korean terrain environment in pager frequency band after deviding the terrain characteristics into six types. With this measured data, we derived several curves that follows the long-term wave progagation behavior and developed the wave propagftion prediction model which calculates the field strength at any point in the service area. The proposed model estimates the field strength in two categories, LOS(line-of-sight), or non LOS. We applied this model using the digital terrain data base and compared with the measured data. The result shows that the errors were between 3~9dB, which turned out to be practical.

• Journal of Korea Water Resources Association
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• v.36 no.1
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• pp.45-59
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• 2003

The method in this study, which is more efficiency than the existing method, propose the optimal rehabilitation model based on the deterioration prediction of the laying pipe by using the deterioration survey method of the water distribution system. The deterioration prediction model divides the deterioration degree of each pipe into 5 degree by using the probabilistic neural network. Also, the optimal residual durability is estimated by the calculated deterioration degree in each pipe and pipe diameter. The optimal rehabilitation model by integer programming base on the shortest path can calculate a time and cost of maintenance, rehabilitation, and replacement. Also, the model is divided into budget constraint and no budget constraint. Consequently, the model proposed by the study can be utilized as the quantitative method for the management of the water distribution system.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.3
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• pp.483-488
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• 2019

The propagation prediction model of the earth-space communication link used as an international standard was used to calculate and analyze the total losses on the communication path. The standard definition and scope of ITU-R Rec. were analyzed for each parameter(rain, scintillation, atmospheric gas, clouds) used to calculate the total loss. The total losses were calculated using the standard model for each parameter and the statistical data provided by ITU-R, and the results were analyzed using the validation examples data. The rain losses were calculated using long-term local rainfall attenuation statistics data measured in the region, and compared with the calculation results using a rainfall map in the ITU-R Recommendation. The data of Cheollian satellites for the L-Band and Ka-Band were used to calculate the rainfall attenuation. In the range of 0.01% to 0.1%, it was found to have a greater attenuation slope when using local data than attenuation by the model of ITU-R.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.39 no.7
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• pp.693-700
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• 2015

To estimate the fatigue crack propagation behavior of compact tension shear (CTS) specimen under mixed-mode loads, crack path prediction theories and Tanaka's equation were applied. The stress intensity factor at a newly created crack tip was calculated using a finite element method via ANSYS, and the crack path and crack increment were then obtained from the crack path prediction theories, Tanaka's equation, and the Paris' equation, which were preprogrammed in Microsoft Excel. A new method called the finite element crack tip updating method (FECTUM) was developed. In this method, the finite element method and Microsoft Excel are used to calculate the stress intensity factors and the crack path, respectively, at the crack tip per each crack increment. The developed FECTUM was applied to simulate the fatigue crack propagation of a single-edge notched bending (SENB) specimen under eccentric three-point bending loads. The results showed that the number of cycles to failure of the specimen obtained experimentally and numerically were in good agreement within an error range of less than 3%.