• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• 제12권12호
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• pp.1098-1125
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• 2000

A review on the papers published in the Korean Journal of Air-Conditioning and Refrigerating Engineering in 1998 and 1999 has been done. Focus has been put on current status of research in the aspect of heating, cooling, ventilation, sanitation and building environment. The conclusions are as follows. 1) A review of the recent studies on fluid flow, turbomachinery and pipe-network shows that many experimental investigations are conducted in applications of impingement jets. Researches on turbulent flows, pipe flows, pipe-networks are focused on analyses of practical systems and prediction of system performance. The results of noise reduction in the turbomachinery are also reported. 2) A review of the recent studies on heat transfer analysis and heat exchanger shows that there were many papers on the channel flow with the application to the design of heat exchanger in the heat transfer analysis. Various experimental and numerical papers on heat exchanger were also published, however, there were few papers available for the analysis of whole system including heat exchanger. 3) A review of the recent studies on heat pump system have focused on the multi-type system and the heat pump cycle to utilize treated sewage as the heat source. The defrosting and the frosting behaviors in the fin-tube heat exchanger is experimentally examined by several authors. Several papers on the ice storage cooling system are presented to show the dynamic simulation program and optimal operation conditions. The study on the micro heat pipes for the cooling of high power electronic components is carried out to examine the characteristics of heat and mass transfer processed. In addition to these, new type of separate thermosyphon is studied experimentally. 4) The recent studies on refrigeration/air conditioning system have focused on the system performance and efficiency for new alternative refrigerants. New systems operating with natural refrigerants are drawing lots of attention. In addition to these, evaporation and condensation heat transfer characteristics of traditional and new refrigerants are investigated for plain tubes and also for microfin tubes. Capillary tubes and orifice are main topics of research as expansion devices and studies on thermophysical properties of new refrigerants and refrigerant/oil mixtures are widely carried out. 5) A review of the recent studies on absorption cooling system shows that numerous experimental and analytical studies on the improvement of absorber performance have been presented. Dynamic analysis of compressor have been performed to understand its vibration characteristics. However research works on tow-phase flow and heat transfer, which could be encountered in the refrigeration system and various phase-change heat exchanger, were seemed to be insufficient. 6) A review of recent studies on duct system shows that the methods for circuit analysis, and flow balancing have been presented. Researches on ventilation are focused on the measurement of ventilation efficiency, and variation of ventilation efficiency with ventilation methods by numerous experimental and numerical studies. Furthermore, many studies have been conducted in real building in order to estimate indoor thermal environments. Many research works to get some information for cooling tower design have been performed but are insufficient. 7) A review on the recent studies on architectural thermal environment and building mechanical systems design shows that thermal comfort analysis is sitting environment, thermal performance analysis of Korean traditional building structures., and evaluation of building environmental load have been performed. However research works to improve the performance of mechanical system design and construction technology were seemed to be insufficient.

• Journal of Korean Society of Disaster and Security
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• 제12권2호
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• pp.73-82
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• 2019

Recently, as the occurrence frequency of sudden floods due to climate change increased, the flood damage on riverside social infrastructures was extended so that there has been a threat of overflow. Therefore, a rapid prediction of potential flooding in riverside social infrastructure is necessary for administrators. However, most current flood forecasting models including hydraulic model have limitations which are the high accuracy of numerical results but longer simulation time. To alleviate such limitation, data driven models using artificial neural network have been widely used. However, there is a limitation that the existing models can not consider the time-series parameters. In this study the water surface elevation of the Hangang River bridge was predicted using the NARX model considering the time-series parameter. And the results of the ANN and RNN models are compared with the NARX model to determine the suitability of NARX model. Using the 10-year hydrological data from 2009 to 2018, 70% of the hydrological data were used for learning and 15% was used for testing and evaluation respectively. As a result of predicting the water surface elevation after 3 hours from the Hangang River bridge in 2018, the ANN, RNN and NARX models for RMSE were 0.20 m, 0.11 m, and 0.09 m, respectively, and 0.12 m, 0.06 m, and 0.05 m for MAE, and 1.56 m, 0.55 m and 0.10 m for peak errors respectively. By analyzing the error of the prediction results considering the time-series parameters, the NARX model is most suitable for predicting water surface elevation. This is because the NARX model can learn the trend of the time series data and also can derive the accurate prediction value even in the high water surface elevation prediction by using the hyperbolic tangent and Rectified Linear Unit function as an activation function. However, the NARX model has a limit to generate a vanishing gradient as the sequence length becomes longer. In the future, the accuracy of the water surface elevation prediction will be examined by using the LSTM model.

• Journal of the Korean Institute of Landscape Architecture
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• 제51권3호
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• pp.70-82
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• 2023

The recent surge of IT and data acquisition is shifting the paradigm in all aspects of life, and these advances are also affecting academic fields. Research topics and methods are being improved through academic exchange and connections. In particular, data-based research methods are employed in various academic fields, including landscape architecture, where continuous research is needed. Therefore, this study aims to investigate the possibility of developing a landscape preference evaluation and prediction model using machine learning, a branch of Artificial Intelligence, reflecting the current situation. To achieve the goal of this study, machine learning techniques were applied to the landscaping field to build a landscape preference evaluation and prediction model to verify the simulation accuracy of the model. For this, wind power facility landscape images, recently attracting attention as a renewable energy source, were selected as the research objects. For analysis, images of the wind power facility landscapes were collected using web crawling techniques, and an analysis dataset was built. Orange version 3.33, a program from the University of Ljubljana was used for machine learning analysis to derive a prediction model with excellent performance. IA model that integrates the evaluation criteria of machine learning and a separate model structure for the evaluation criteria were used to generate a model using kNN, SVM, Random Forest, Logistic Regression, and Neural Network algorithms suitable for machine learning classification models. The performance evaluation of the generated models was conducted to derive the most suitable prediction model. The prediction model derived in this study separately evaluates three evaluation criteria, including classification by type of landscape, classification by distance between landscape and target, and classification by preference, and then synthesizes and predicts results. As a result of the study, a prediction model with a high accuracy of 0.986 for the evaluation criterion according to the type of landscape, 0.973 for the evaluation criterion according to the distance, and 0.952 for the evaluation criterion according to the preference was developed, and it can be seen that the verification process through the evaluation of data prediction results exceeds the required performance value of the model. As an experimental attempt to investigate the possibility of developing a prediction model using machine learning in landscape-related research, this study was able to confirm the possibility of creating a high-performance prediction model by building a data set through the collection and refinement of image data and subsequently utilizing it in landscape-related research fields. Based on the results, implications, and limitations of this study, it is believed that it is possible to develop various types of landscape prediction models, including wind power facility natural, and cultural landscapes. Machine learning techniques can be more useful and valuable in the field of landscape architecture by exploring and applying research methods appropriate to the topic, reducing the time of data classification through the study of a model that classifies images according to landscape types or analyzing the importance of landscape planning factors through the analysis of landscape prediction factors using machine learning.

• Cartoon and Animation Studies
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• 통권20호
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• pp.75-86
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• 2010

Recently, as the number of female players has increased rapidly, the electronic gaming industry has begun to look at ways to appeal to the largely untapped female market. According to the latest game market investigative report by China Internet Network Information Center (CNNIC), the total number of game players in China increased by 24.8% in 2009, reached 69,130,000 people, and 38.9% of them are female players. This growth in the number of female player is corroborated by a series of investigative reports from IResearch Company in Shanghai, China: from 2003 to 2009, the number of female players grew from 8% to more than 49%. Therefore, no matter how much attention the game production companies have given to male players or how they have ignored the female players before, the companies would be sensible to face up this reality and adjust their marketing policy a bit more. This article analyzes gender preferences in video games which shows that male players are more likely to be attracted to elements of aggression, violence, competition and fast action in electronic game-playing, while female players are drawn to emotional and social aspects of the games such as an understanding of character relationships. The literatures cited indicates that female players also show apparent preference for games with familiar environments, games that allow players to work together, games that have more than one way to win, and games in which characters do not die. It also discusses the characteristics of female-friendly games from the aspect of emotion, pointing out that the simulation games involving pet, dressing-up, and social simulation games are very popular with female players. Because these are the most suitable game types to fill with emotions of love, share, jealousy, superiority, mystery, these are absolutely attractive to female players. Finally, in accord with the above, I propose some principles of designing female-oriented games, including presenting a good-looking leading character, making the story interesting with "live" NPCs(Non-Playing Characters), and finding ways to satisfy female nature instincts such as taking care of others and the inborn interest of classifying and selecting.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• 제8권3호
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• pp.52-63
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• 2009

Recently in Korea, in the case of metropolis, the urban signalized intersections are controlled by traffic information center or ITS center. Cheon-an City also established traffic information center through the 1st.-$\sim$3rd. ITS public construction and has managed this center that includes bus information service, traffic information collection and providing service, parking information service, and traffic responsive control system. In the Cheon-an metropolitan traffic signal operation, traffic signal controllers were grouped by the each main traffic flow axes and performed with coordinated signal timing for the signalized arterials, and also cycle and split changed by realtime traffic demands. Cheon-an urban traffic responsive control system was evaluated by intersection delay and speed, then it was verified that the delay decreased and vehicle speed improved. However, the rural signal control system to connect adjacency town was evaluated to have lower status than urban area due to the unimproved TOD (Time of day) plan. Therefore actuated signal control was examined for substitutive control system in isolated signal intersection. The aim of this article is to compare actuated signal control with TOD mode in the rural intersection of Cheon-an and to fine superiority of these two control mode, with evaluation of vehicle delay by using HCM(2000) method and by micro-simulation CORSlM. The result of field test show that actuated signal control gave better performance in delay comparison than the existing TOD signal control. And simulation outcome verified that non-optimized TOD has higher delay than optimized TOD mode, non-optimal actuated mode, and optimal actuated signal control mode. Particularly, these three modes delays had not different values according to the paired sample t-test. This is because small traffic demands were loaded in each links. This suggested actuated signal control is expected to be more effective than TOD mode in some rural isolated intersections which frequently need to survey for traffic volume.

• Journal of Intelligence and Information Systems
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• 제16권4호
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• pp.1-19
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• 2010

In offline environment, unlike traditional advertising model through TV, newspaper, and radio, online advertising model draws instantaneous responses from potential consumers and it is convenient to assess. This kind of characteristics of Internet advertising model has driven the growth of advertising model among various Internet business models. There are, conventionally classified, CPM (Cost Per Mile), CPC (Cost Per Click), and CPS (Cost Per Sales) models as Internet advertising expenditure model. These can be examined in manners regarding risks that stakeholders should stand and degree of responsibility. CPM model that is based on number of advertisement exposure is mechanically exposed to users but not actually recognized by users resulting in risk of wasted expenditure by advertisers without any advertising effect. While on aspect of media, CPS model that is based on conversion action is the most risky model because of the conversion action such as product purchase is determined by capability of advertisers not that of media. In this regard, while there are issue of CPM and CPS models disadvantageously affecting only one side of Internet advertising business model value network, CPC model has been evaluated as reasonable both to advertisers and media, and occupied the largest segment of Internet advertising market. However, CPC model also can cause fraudulent behavior such as click fraud because of the competition or dishonest amount of advertising expenditure. On the user aspect, unintentionally accessed advertisements can lead to more inappropriate expenditure from advertisers. In this paper, we suggest "CPCD"(Cost Per Coupon Download) model. This goes beyond simple clicking of advertisements and advertising expenditure is exerted when users download a coupon from advertisers, which is a concept in between CPC and CPS models. To achieve the purpose, we describe the scenario of advertiser perspective, processes, participants and their benefits of CPCD model. Especially, we suggest the new value in online coupon; "possibility of storage" and "complement for delivery to the target group". We also analyze the working condition for advertiser by a comparison of CPC and CPCD models through advertising expenditure simulation. The result of simulation implies that the CPCD model suits more properly to advertisers with medium-low price products rather than that of high priced goods. This denotes that since most of advertisers in CPC model are dealing with medium-low priced products, the result is very interesting. At last, we contemplate applicability of CPCD model in ubiquitous environment.

• Journal of KIISE:Computing Practices and Letters
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• 제8권1호
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• pp.88-95
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• 2002

In recent years, the security of hardware and software systems is one of the most essential factor of our safe network community. As elliptic Curve Cryptosystems proposed by N. Koblitz and V. Miller independently in 1985, require fewer bits for the same security as the existing cryptosystems, for example RSA, there is a net reduction in cost size, and time. In this thesis, we propose an efficient hardware architecture of underlying field arithmetic processor for Elliptic Curve Cryptosystems, and a very useful method for implementing the architecture, especially multiplicative inverse operator over GF$GF (2^m)$ onto FPGA and futhermore VLSI, where the method is based on optimized unit operation components. We optimize the arithmetic processor for speed so that it has a resonable number of gates to implement. The proposed architecture could be applied to any finite field $F_{2m}$. According to the simulation result, though the number of gates are increased by a factor of 8.8, the multiplication speed We optimize the arithmetic processor for speed so that it has a resonable number of gates to implement. The proposed architecture could be applied to any finite field $F_{2m}$. According to the simulation result, though the number of gates are increased by a factor of 8.8, the multiplication speed and inversion speed has been improved 150 times, 480 times respectively compared with the thesis presented by Sarwono Sutikno et al. [7]. The designed underlying arithmetic processor can be also applied for implementing other crypto-processor and various finite field applications.

• Korean Journal of Mineralogy and Petrology
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• 제34권3호
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• pp.157-167
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• 2021

Lead (Pb) is one of the key trace elements, exhibiting a peculiar partitioning behavior into silicate melts in contact with minerals. Partitioning behaviors of Pb between silicate mineral and melt have been known to depend on melt composition and thus, the atomic structures of corresponding silicate liquids. Despite the importance, detailed structural studies of Pb-bearing silicate melts are still lacking due to experimental difficulties. Here, we explored the effect of lead content on the atomic structures, particularly the evolution of silicate networks in Pb-bearing sodium metasilicate ([(PbO)_x(Na₂O)_1-x]·SiO₂) glasses as a model system for trace metal bearing natural silicate melts, using ²⁹Si solid-state nuclear magnetic resonance (NMR) spectroscopy. As the PbO content increases, the ²⁹Si peak widths increase, and the maximum peak positions shift from -76.2, -77.8, -80.3, -81.5, -84.6, to -87.7 ppm with increasing PbO contents of 0, 0.25, 0.5, 0.67, 0.86, and 1, respectively. The ²⁹Si MAS NMR spectra for the glasses were simulated with Gaussian functions for Qⁿ species (SiO₄ tetrahedra with n BOs) for providing quantitative resolution. The simulation results reveal the evolution of each Qⁿ species with varying PbO content. Na-endmember Na₂SiO₃ glass consists of predominant Q² species together with equal proportions of Q¹ and Q³. As Pb replaces Na, the fraction of Q² species tends to decrease, while those for Q¹ and Q³ species increase indicating an increase in disproportionation among Qⁿ species. Simulation results on the ²⁹Si NMR spectrum showed increases in structural disorder and chemical disorder as evidenced by an increase in disproportionation factor with an increase in average cation field strengths of the network modifying cations. Changes in the topological and configurational disorder of the model silicate melt by Pb imply an intrinsic origin of macroscopic properties such as element partitioning behavior.

• KSCE Journal of Civil and Environmental Engineering Research
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• 제30권1B호
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• pp.41-51
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• 2010

In this study, runoff simulation was carried out in the area of Bisan 7-dong, Seo-gu, Daegu as drainage basin and the effects of the installation of underground storage facilities were analyzed during heavy rainfall. SWMM model was used for the runoff and pipe network analysis on Typhoon Maemi, 2003. 2-D inundation analysis model based on diffusion wave was employed for inundation analysis and to verify computed inundation areas with observed inundation trace map. The simulation results agree with observed in terms of inundation area and depth. Also, the effects of flood damage mitigation were analyzed through the overflow discharge and 2-D inundation analysis, depending upon whether the underground storage facility is installed or not. When the underground storage facility ($W:120m{\times}L:180m{\times}H:1.7m$) is installed, volume of overflow could be reduced by 72% and flooding area could be reduced by 40.1%. When the underground storage facility ($W:120m{\times}L:180 m{\times}H:2.0m$) is installed, volume of overflow could be reduced by 84.8% and flooding area could be reduced by 50.6%. When the underground storage facility ($W:120m{\times}L:180m{\times}H:2.2m$) is installed, volume of overflow could be reduced by 94% and flooding area could be reduced by 91.2%. There is no overflow of manhole, when the height of storage facility is 2.5 m. It is expected that the study results presented through quantitative analysis on the effects of underground facilities can be used as base data for socially and economically effective installation of underground facilities to prevent flood damage.

• Asia Marketing Journal
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• 제14권1호
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• pp.83-98
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• 2012

In a market where new and used cars are competing with each other, we would run the risk of obtaining biased estimates of cross elasticity between them if we focus on only new cars or on only used cars. Unfortunately, most of previous studies on the automobile industry have focused on only new car models without taking into account the effect of used cars' pricing policy on new cars' market shares and vice versa, resulting in inadequate prediction of reactive pricing in response to competitors' rebate or price discount. However, there are some exceptions. Purohit (1992) and Sullivan (1990) looked into both new and used car markets at the same time to examine the effect of new car model launching on the used car prices. But their studies have some limitations in that they employed the average used car prices reported in NADA Used Car Guide instead of actual transaction prices. Some of the conflicting results may be due to this problem in the data. Park (1998) recognized this problem and used the actual prices in his study. His work is notable in that he investigated the qualitative effect of new car model launching on the pricing policy of the used car in terms of reinforcement of brand equity. The current work also used the actual price like Park (1998) but the quantitative aspect of competitive price promotion between new and used cars of the same model was explored. In this study, I develop a model that assumes that the cross elasticity between new and used cars of the same model is higher than those amongst new cars and used cars of the different model. Specifically, I apply the nested logit model that assumes the car model choice at the first stage and the choice between new and used cars at the second stage. This proposed model is compared to the IIA (Independence of Irrelevant Alternatives) model that assumes that there is no decision hierarchy but that new and used cars of the different model are all substitutable at the first stage. The data for this study are drawn from Power Information Network (PIN), an affiliate of J.D. Power and Associates. PIN collects sales transaction data from a sample of dealerships in the major metropolitan areas in the U.S. These are retail transactions, i.e., sales or leases to final consumers, excluding fleet sales and including both new car and used car sales. Each observation in the PIN database contains the transaction date, the manufacturer, model year, make, model, trim and other car information, the transaction price, consumer rebates, the interest rate, term, amount financed (when the vehicle is financed or leased), etc. I used data for the compact cars sold during the period January 2009- June 2009. The new and used cars of the top nine selling models are included in the study: Mazda 3, Honda Civic, Chevrolet Cobalt, Toyota Corolla, Hyundai Elantra, Ford Focus, Volkswagen Jetta, Nissan Sentra, and Kia Spectra. These models in the study accounted for 87% of category unit sales. Empirical application of the nested logit model showed that the proposed model outperformed the IIA (Independence of Irrelevant Alternatives) model in both calibration and holdout samples. The other comparison model that assumes choice between new and used cars at the first stage and car model choice at the second stage turned out to be mis-specfied since the dissimilarity parameter (i.e., inclusive or categroy value parameter) was estimated to be greater than 1. Post hoc analysis based on estimated parameters was conducted employing the modified Lanczo's iterative method. This method is intuitively appealing. For example, suppose a new car offers a certain amount of rebate and gains market share at first. In response to this rebate, a used car of the same model keeps decreasing price until it regains the lost market share to maintain the status quo. The new car settle down to a lowered market share due to the used car's reaction. The method enables us to find the amount of price discount to main the status quo and equilibrium market shares of the new and used cars. In the first simulation, I used Jetta as a focal brand to see how its new and used cars set prices, rebates or APR interactively assuming that reactive cars respond to price promotion to maintain the status quo. The simulation results showed that the IIA model underestimates cross elasticities, resulting in suggesting less aggressive used car price discount in response to new cars' rebate than the proposed nested logit model. In the second simulation, I used Elantra to reconfirm the result for Jetta and came to the same conclusion. In the third simulation, I had Corolla offer $1,000 rebate to see what could be the best response for Elantra's new and used cars. Interestingly, Elantra's used car could maintain the status quo by offering lower price discount ($160) than the new car ($205). In the future research, we might want to explore the plausibility of the alternative nested logit model. For example, the NUB model that assumes choice between new and used cars at the first stage and brand choice at the second stage could be a possibility even though it was rejected in the current study because of mis-specification (A dissimilarity parameter turned out to be higher than 1). The NUB model may have been rejected due to true mis-specification or data structure transmitted from a typical car dealership. In a typical car dealership, both new and used cars of the same model are displayed. Because of this fact, the BNU model that assumes brand choice at the first stage and choice between new and used cars at the second stage may have been favored in the current study since customers first choose a dealership (brand) then choose between new and used cars given this market environment. However, suppose there are dealerships that carry both new and used cars of various models, then the NUB model might fit the data as well as the BNU model. Which model is a better description of the data is an empirical question. In addition, it would be interesting to test a probabilistic mixture model of the BNU and NUB on a new data set.