• Science of Emotion and Sensibility
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• v.8 no.4
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• pp.423-433
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• 2005

The computer hardware development has provided many chances of emergence between art and technology. In many cases today's interactive artworks cannot be completed without audience's participation. The interactive production process with technical supplementation can be celled feedback. Mr. Nam Jun Paik showed 'Participant TV' that interacts with audience's response in real time. It means artwork changes with the constantly changing value from the data set from human visual perception. Dan Graham showed another feedback related work, which delays 5second playback in mirror that implies consequence of time. Today's media art has to sublimate coincidence, time ant audience into philosophical artwork through consonance that comes with video and sound as we can see from Bill Viola. Stelarc produced artworks. That use input data that is weak signals from brain, muscles. Through a terminal display with player, body expanded meaning of media. Jeffrey Shaw's 'Legible City' provided a fabrication of the reality with the interaction of bicycle's pedal speed and steering direction that is controlled by 4river. RE:MARK used microphone as input device as Edmond Couchot's 'Je same a la vent' and Nam Jun Paik's 'Participant TV' did. There is no communication without feedback between human being. The reality makes audience involved into artworks. That is the reason why feedback has to be natural. Through the feedback process, the originality of the idea is altered by audience. The feedback is not just part of flesh of artwork rather skeleton of it. Technological showoff cannot be art itself The perfection of technological application plan helps feedback that interacts with audience naturally in order that audience hoes not feel the feedback as artificial plan. Interactive media art has to be evolved into new media form with new integration feedback technology.

• Korean Journal of Agricultural and Forest Meteorology
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• v.1 no.2
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• pp.119-126
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• 1999

A numerical model using soil surface energy balance and soil heat flow equations to estimate mulched soil temperature was developed. The required inputs data include weather data, such as global solar radiation, air temperature, wind speed, atmospheric water vapor pressure, the optical properties of mulching material, and soil physical properties. The observed average soil temperature at 50 cm depth was used as the initial value of soil temperature at each depth. Soil temperature was simulated starting at 0 hour at an interval of 10 minutes. The model reliably described the variation of soil temperature with time progress and soil depth. The correlation between the estimated and measured temperature yielded coefficient values of 0.961, 0.966 for 5cm and 10cm depth of the bare soil, respectively, 0.969, 0.965 for the paper mulched soil, and 0.915, 0.938 for the black polyethylene film mulched soil. The percentages of absolute differences less than 2$^{\circ}$C between soil temperatures measured and simulated at 10 minute interval were 97.4% and 98.5% for 5 cm and 10cm for the bare soil, respectively, and 95.8% and 97.4% for the paper mulched soil, and 70.1% and 92.5% for the polyethylene film mulched soil. The results indicated that the model was able to predict the soil temperature fairly well under mulched condition. However, in the night time, the model performance was a little poor as compared with day time due to the difficulty of accurate determination of the atmospheric long wave radiation.

• Journal of the Korean Geotechnical Society
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• v.32 no.10
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• pp.17-29
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• 2016

A debris flow analysis model has been developed to simulate the erosion and entrainment of soil layer. Special attention is given to the model which represents strength softening behaviour of soil layer due to velocity of deformation. The 3D FE analysis by Coupled Eulerian-Lagrangian (CEL) model is conducted to simulate the debris flow. The model is validated using published data on laboratory experiment (Mangeny et al., 2010). It has been definitely shown that proposed model is in good agreement with the results of laboratory data. Futhermore, the FE analysis is conducted to ensure capability of simulating the real scale debris flow. The result of Ramian watershed, Korea shows that the debris flow has increased the volume and speed and it is in good agreement with field investigation. Based on this, it is confirmed that proposed model shows good agreement of the behavior of the actual and analytical debris flow.

• Journal of the Korean Geographical Society
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• v.37 no.3
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• pp.237-246
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• 2002

This study classified wintertime bioclimatic zones of South Korea based on daytime and nighttime distribution of wind chill index calculated from climate data during the coldest month for latest 30 years (1971- 2000). The results show that the winter daytime and nighttime wind chill index were influenced by climatic factors such as elevation, land-sea breeze, topology, and sea currents etc. as well as climatic components such as temperature, wind speed, and sunshine, so that South Korea was divided into five bioclimatic zones; Cool day- cold night zone, Keen day- Cold night zone, Keen day-Very Cold night zone, Cold day and night zone, and Cold day-Extremely Cold night zone. Especially, coasts and island areas, except for south coast of Korea, shows Keen bioclimatic response during daytime and Very Cold bioclimatic response during nighttime. This indicates that coasts and island areas, except for south coast of Korea are affected by moonson and land-sea breeze. In addition, highly elevated Daegwallyeong shows Cold bioclimatic response during daytime and Extremely Cold during nighttime due to the influence of adiabatic temperature lapse rate and monsoon. This study offers basic data necessary to make decisions concerning insulation such as clothing and architect etc. by classifying winter bioclimatic zones of South Korea based on various daytime and nighttime distribution of wind chill.

• Korean Chemical Engineering Research
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• v.53 no.2
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• pp.236-242
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• 2015

We present two data-driven modeling methods, partial least square (PLS) and artificial neural network (ANN), to predict the major operating and performance variables of a polymer electrolyte membrane (PEM) fuel cell stack. PLS and ANN models were constructed using the experimental data obtained from the testing of a 30 kW-class PEM fuel cell stack, and then were compared with each other in terms of their prediction and computational performances. To reduce the complexity of the models, we combined a variables importance on PLS projection (VIP) as a variable selection method into the modeling procedure in which the predictor variables are selected from a set of input operation variables. The modeling results showed that the ANN models outperformed the PLS models in predicting the average cell voltage and cathode outlet temperature of the fuel cell stack. However, the PLS models also offered satisfactory prediction performances although they can only capture linear correlations between the predictor and output variables. Depending on the degree of modeling accuracy and speed, both ANN and PLS models can be employed for performance predictions, offline and online optimizations, controls, and fault diagnoses in the field of PEM fuel cell designs and operations.

• Journal of the Korea Society of Computer and Information
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• v.20 no.6
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• pp.1-11
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• 2015

Recently, NAND flash memories are used for storage devices because of fast access speed and low-power. However, applications of FTL on low power computing devices lead to heavy workloads which result in a memory requirement and an implementation overhead. Consequently, studies of B+-Tree on embedded devices without the FTL have been proposed. The studies of B+-Tree are optimized for performance of inserting and updating records, considering to disadvantages of the NAND flash memory that it can not support in-place update. However, if a general garbage collection method is applied to the previous studies of B+-Tree, a performance of the B+-Tree is reduced, because it generates a rearrangement of the B+-Tree by changing of page positions on the NAND flash memory. Therefor, we propose a novel garbage collection method which can apply to the B+-Tree based on the NAND flash memory without the FTL. The proposed garbage collection method does not generate a rearrangement of the B+-Tree by using a block information table and a proxy block. We implemented the B+-Tree and ${\mu}$-Tree with the proposed garbage collection on physical devices with the NAND flash memory. In experiment results, the proposed garbage collection scheme compared to greedy algorithm garbage collection scheme increased the number of inserted keys by up to about 73% on B+-Tree and decreased elapsed time of garbage collection by up to about 39% on ${\mu}$-Tree.

• Journal of the Korea Society for Simulation
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• v.17 no.4
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• pp.199-208
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• 2008

Lately, since Complementary Metal Oxide Semiconductor(CMOS) image sensor system has low power, low cost and been miniaturized, hardware and applied software studies using these strengths are being carrying on actively. However, the products equipped with CMOS image sensor based polling method yet has several problems in degree of completeness of applied software and firmware, compared with hardware’s. CMOS image sensor system has an ineffective synchronous problem due to superfluous message exchange. Also when a sending of data is delayed continually, overhead of re-sending is large. So because of these, it has a problem in structural stability according to Polling Method. In this study, polling cycle was subdivided in high-speed synchronization method of firmware -based through MCU and synchronization method of Stepwise was proposed. Also, re-connection and data sending were advanced more efficiently by using interrupt way. In conclusion, the proposed method showed more than 20 times better performance in synchronization time and error connection. Also, a board was created by using C328R board of CMOS image sensor-based and ATmega128L which has low power, MCU and camera modules of proposed firmware were compared with provided software and analyzed in synchronization time and error connection.

• Journal of Korean Society for Geospatial Information Science
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• v.23 no.3
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• pp.23-29
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• 2015

Due to the characteristics of landslide disasters including debris flow, the rapid speed to downward and difficulty to respond or evacuate from them, it is imperative to identify their potential hazards and prepare the reduction plans. However, the current landslide hazards generated by a variety of methods has been raised its accuracy because of the complexity of input data and their analyses, and the simplification of the landslide model. The main objective of this study is, therefore, to evaluate the preliminary landslide hazard based on the identification of geomorphological features. Especially, two methodologies based on the statistics of the directional data, Vector dispersion and Planarity analyses, are used to find some relationships between geomorphological characteristics and the landslide hazard. Results show that both methods well discriminate geomorphological features between stable and unstable domains in the landslide areas. Geomorphological features are closely related to the landslide hazard and it is imperative to maximize their characteristics by adapting multiple models rather than individual model only. In conclusions, the mechanism of landslide is not determined solely by a simple cause but the complex natural phenomenon caused by the interactions of the numerous factors and it is of primary importance to require additional researches for the outbreaking mechanism that are based on various methodologies.

• Journal of Korea Foresty Energy
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• v.23 no.2
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• pp.1-8
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• 2004

This study looked into the change of tree growth of seven forest growth monitoring plots which were set up at the Undulyeong Hongchungun Kangwondo, and was accomplished to offer the basic data for the forest administration calculating carbon storage and removal in the Undulyeong area. Annual height and DBH growth were slowly progressed in the Pinus koraiensis and Larix kaempferi stand which was young stand, but the growth rate of the other stands was lower than those young stand. The diameter class of the mixed forest and Qurcus mongilica stand was predicted to be similar to the now and Pinus koraiensis and Larix kaempferi stand was predicted to move now diameter class to the high diameter class because thickening growth speed of the those stands were rapid. Now the end of 2003, total carbon storage of the Undulyeong model forest increased 149,000TC$(2.7\%)$ compared with the previous year. Seeing by forest types, occupied broad-leaved forest$(50\%)$, mixed forest$(34\%)$ and coniferous forest. During in 2003, total carbon which was removed and stored according to growth of the forest was 156,813TC and net carbon removal(148,664TC) increased into 2,613TC$(1.8\%)$ compared with the previous year. Seeing by forest types, occupied coniferous forest$(3.3\%)$, mixed forest$(3.1\%)$, broad-leaved forest$(2.8\%)$. Resultingly, the Undulyeong model forest is acting to net removal resource when see as green-gas side and net carbon removal are showing the tendency to increase recently little by little.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.4
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• pp.153-163
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• 2017

This research is based on the previous research that personally preferred safe distance, rotating angle and speed are differentiated. Thus, we use machine learning model for recognizing maneuvering modes trained per personal or per similar driving pattern groups, and we evaluate automatic driving according to maneuvering modes. By utilizing driving knowledge, we subdivided 8 kinds of longitudinal modes and 4 kinds of lateral modes, and by combining the longitudinal and lateral modes, we build 21 kinds of maneuvering modes. we train the labeled data set per time stamp through RNN, LSTM and Bi-LSTM models by the trips of drivers, which are supervised deep learning models, and evaluate the maneuvering modes of automatic driving for the test data set. The evaluation dataset is aggregated of living trips of 3,000 populations by VTTI in USA for 3 years and we use 1500 trips of 22 people and training, validation and test dataset ratio is 80%, 10% and 10%, respectively. For recognizing longitudinal 8 kinds of maneuvering modes, RNN achieves better accuracy compared to LSTM, Bi-LSTM. However, Bi-LSTM improves the accuracy in recognizing 21 kinds of longitudinal and lateral maneuvering modes in comparison with RNN and LSTM as 1.54% and 0.47%, respectively.