• The KIPS Transactions:PartD
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• v.16D no.5
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• pp.767-790
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• 2009

Setting up a priorityfor an embedded system is greatly significant because a release plan at the early stage of product developments can properly be established through right decision making procedures based on the priorities. For instance, both dependencies among requirements and the aspects of product developers should be considered into the priorities to improve the embedded system. Especially, trade-offs among the requirements, which are quite different depending on H/W and S/W architecture styles they use, should be acknowledged without exception. However, the selection process on the priority has hitherto been fairly systematic in the existing environment where hardware and software are not being considered at once. Therefore, this paper suggests an dependency and aspect-based model and process for the requirements of the priority. For this, the paper analyzes the trade-offs between the requirements depending on the disparate Architecture styles of H/W and S/W, and it also reflects the viewpoints of the developers. For thelast thing, the model and process suggested will be applied to the case of the development of both cell phones and cameras to gain authenticity and reliability. In conclusion, the danger occurring when the release plan is constructed can be minimized by screening the priorities that optimizes the embedded system more explicitly.

• Journal of the Korea Society of Computer and Information
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• v.16 no.11
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• pp.25-34
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• 2011

In this paper we present an integrated design methodology for relational database based on object-oriented analysis and design. The integrated design methodology is based on business profile and has six phases. In the first phase, business use cases are identified and described by macroactivity diagrams and then the macroactivity diagrams are transformed to detailed business activity diagrams by using objects, object flows and business worker's responsibilities. In the third phase, the detailed business activity diagrams are transformed to business class diagrams that describe the static structure of the entire business system based on detailed business activity diagrams. In the four phase, the business class diagrams are transformed to class diagrams that represent the initial conceptual model of the target relational database. In the five phase, we add additional transformations on the class diagrams with generalization and specialization of associations, roles, activities, additional classes and redundant associations. Eventually, the final class diagrams are transformed to relational database schema. The methodology presented in this paper by applying that proposal for organic connection between object-oriented analysis and design methodology and relational database design methodology. And it will be able to deal with integration management. By the integrated design methodology, we can make more easily software systems based on relational database. In the case study, proposal integrated design methodology applied for a visa issuing system.

• Journal of Wetlands Research
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• v.20 no.4
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• pp.353-362
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• 2018

The purpose of this study is to suggest a structure plan for improving the utilization of inactive storage in the dam for overcoming the drought. Inactive storage in the dam is composed of the emergency storage and dead storage. The emergency storage can be used for the case of emergency such as drought. But, in general, the dead storage for sedimentation is not used even for the emergency. Therefore, this study considers the part of dead storage that the sedimentation is not progressed yet can be used during the severe drought period and is called "drought storage in a dam". The accurate Sediment Level(SL) analysis for the computation of the drought storage should be performed and so the present and future SL in the dam reservoir is estimated using SED-2D linked with RMA-2 model of SMS. After the consideration of additionally available storage capacity based on the estimated SL, the drought storage is finally determined. Present data based on historical data, future predicted future climate factors by Representative Concentrarion Pathways(RCP) 8.5 scenario. Then, using the TANK model, dam inflows were determined, and future period such as SL and drought storage were suggested. As the results, we have found that the available drought storage will be reduced in the future when we compare the present drought storage with the future one. This is due to a increase variability of climate change. Therefore, we should take the necessary study for the increase of available drought storage in the future.

• Journal of the Korean earth science society
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• v.30 no.6
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• pp.699-708
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• 2009

Recently as the interest in the development of domestic ore deposits has increased, we can easily find some studies on exploration geophysics-based ore-deposit survey in literature. Based on the fact that mineralized zone are generally more conductive than surrounding media, electrical resistivity survey among several geophysical surveys has been applied to investigate metallic ore deposits. Most of them are grounded on 2-D survey. However, 2-D inversion may lead to some misinterpretation for 3-D geological structures. In this study, we investigate the feasibility of the 3-D electrical resistivity survey to 3-D vein-type ore deposits. We first simulate 2-D dipole-dipole survey data for survey lines normal to the strike and 3-D pole-pole survey data, and then perform 3-D inversion. For 3-D ore-body structures, we assume a width-varying dyke, a wedge-shaped, and a fault model. The 3-D inversion results are compared to 2-D inversion results. By comparing 3-D inversion results for 2-D dipole-dipole survey data to 3-D inversion results for 3-D pole-pole survey data, we could note that the 2-D dipole-dipole survey data yield better inversion results than the 3-D pole-pole data, which is due to the main characteristic of the pole-pole array. From these results, we are convinced that if we have certain information on the direction of the strike, it would be desirable to apply 2-D dipole-diple survey for the survey lines normal to the strike. However, in most cases, we do not have any information on the direction of the strike, because we already developed the ore deposit with the outcrops and the remaining ore deposits are buried under the surface. In that case, performing 3-D pole-pole electrical resistivity survey would be a reasonable choice to obtain more accurate interpretation on ore body structure in spite of low resolution of pole-pole array.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.5B
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• pp.501-509
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• 2006

The safety of levee that depends on the river flood elevation has been regarded as very important keys to build up various flood prevention systems. However, deterministic methods for computation of water surface profile cannot reflect the effect of possible inaccuracies in the input parameters. The purpose of this study is to develop a methodology of uncertainty computation of design flood level based on steady flow analysis and Monte Carlo simulation. This study addresses the uncertainty of water surface elevation by Manning's coefficients, design discharges, river cross sections and boundary condition. Monte Carlo simulation with the variations of these parameters is performed to quantify the variations of water surface elevations in a river. The proposed model has been applied to the Kumho-river. The reliability analysis was performed within 38.5 km (95 sections) reach considered the variations of the above-mentioned parameters. Overtopping risks were evaluated by comparing the elevations of the flood condition with the those of the levees. The results show that there is a necessity which will raise the levee elevation between 1 cm and 56 cm at 7 sections. The model can be used for preparing flood risk maps, flood forecasting systems and establishing flood disaster mitigation plans as well as complement of conventional levee design.

• Information Systems Review
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• v.20 no.4
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• pp.59-78
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• 2018

With the advent of the various device types and marketing communication, customer's search and purchase behavior have become more complex and segmented. However, extant research on multichannel marketing effects of the purchase funnel has not reflected the specific features of device User Interface (UI) and User Experience (UX). In this study, we analyzed the marketing channel effects of multi-device shoppers using a unique click stream dataset from global online retailers. We examined device types that activate online shopping and compared the differences between marketing channels that promote visits. In addition, we estimated the direct and indirect effects on visits and purchase revenue through customer's accumulated experience and channel conversions. The findings indicate that the same customer selects a different marketing channel according to the device selection. These results can help retailers gain a better understanding of customers' decision-making process in multi-marketing channel environment and devise the optimal strategy taking into account various device types. Our empirical analyses yield business implications based on the significant results from global big data analytics and contribute academically meaningful theoretical framework using an economic model. We also provide strategic insights attributed to the practical value of an online marketing manager.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.131-145
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• 2020

In line with the trend of industrial innovation, IoT technology utilized in a variety of fields is emerging as a key element in creation of new business models and the provision of user-friendly services through the combination of big data. The accumulated data from devices with the Internet-of-Things (IoT) is being used in many ways to build a convenience-based smart system as it can provide customized intelligent systems through user environment and pattern analysis. Recently, it has been applied to innovation in the public domain and has been using it for smart city and smart transportation, such as solving traffic and crime problems using CCTV. In particular, it is necessary to comprehensively consider the easiness of securing real-time service data and the stability of security when planning underground services or establishing movement amount control information system to enhance citizens' or commuters' convenience in circumstances with the congestion of public transportation such as subways, urban railways, etc. However, previous studies that utilize image data have limitations in reducing the performance of object detection under private issue and abnormal conditions. The IoT device-based sensor data used in this study is free from private issue because it does not require identification for individuals, and can be effectively utilized to build intelligent public services for unspecified people. Especially, sensor data stored by the IoT device need not be identified to an individual, and can be effectively utilized for constructing intelligent public services for many and unspecified people as data free form private issue. We utilize the IoT-based infrared sensor devices for an intelligent pedestrian tracking system in metro service which many people use on a daily basis and temperature data measured by sensors are therein transmitted in real time. The experimental environment for collecting data detected in real time from sensors was established for the equally-spaced midpoints of 4×4 upper parts in the ceiling of subway entrances where the actual movement amount of passengers is high, and it measured the temperature change for objects entering and leaving the detection spots. The measured data have gone through a preprocessing in which the reference values for 16 different areas are set and the difference values between the temperatures in 16 distinct areas and their reference values per unit of time are calculated. This corresponds to the methodology that maximizes movement within the detection area. In addition, the size of the data was increased by 10 times in order to more sensitively reflect the difference in temperature by area. For example, if the temperature data collected from the sensor at a given time were 28.5℃, the data analysis was conducted by changing the value to 285. As above, the data collected from sensors have the characteristics of time series data and image data with 4×4 resolution. Reflecting the characteristics of the measured, preprocessed data, we finally propose a hybrid algorithm that combines CNN in superior performance for image classification and LSTM, especially suitable for analyzing time series data, as referred to CNN-LSTM (Convolutional Neural Network-Long Short Term Memory). In the study, the CNN-LSTM algorithm is used to predict the number of passing persons in one of 4×4 detection areas. We verified the validation of the proposed model by taking performance comparison with other artificial intelligence algorithms such as Multi-Layer Perceptron (MLP), Long Short Term Memory (LSTM) and RNN-LSTM (Recurrent Neural Network-Long Short Term Memory). As a result of the experiment, proposed CNN-LSTM hybrid model compared to MLP, LSTM and RNN-LSTM has the best predictive performance. By utilizing the proposed devices and models, it is expected various metro services will be provided with no illegal issue about the personal information such as real-time monitoring of public transport facilities and emergency situation response services on the basis of congestion. However, the data have been collected by selecting one side of the entrances as the subject of analysis, and the data collected for a short period of time have been applied to the prediction. There exists the limitation that the verification of application in other environments needs to be carried out. In the future, it is expected that more reliability will be provided for the proposed model if experimental data is sufficiently collected in various environments or if learning data is further configured by measuring data in other sensors.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.57-71
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• 2013

Over a billion people in the world generate new news minute by minute. People forecasts some news but most news are from unexpected events such as natural disasters, accidents, crimes. People spend much time to watch a huge amount of news delivered from many media because they want to understand what is happening now, to predict what might happen in the near future, and to share and discuss on the news. People make better daily decisions through watching and obtaining useful information from news they saw. However, it is difficult that people choose news suitable to them and obtain useful information from the news because there are so many news media such as portal sites, broadcasters, and most news articles consist of gossipy news and breaking news. User interest changes over time and many people have no interest in outdated news. From this fact, applying users' recent interest to personalized news service is also required in news service. It means that personalized news service should dynamically manage user profiles. In this paper, a content-based news recommendation system is proposed to provide the personalized news service. For a personalized service, user's personal information is requisitely required. Social network service is used to extract user information for personalization service. The proposed system constructs dynamic user profile based on recent user information of Facebook, which is one of social network services. User information contains personal information, recent articles, and Facebook Page information. Facebook Pages are used for businesses, organizations and brands to share their contents and connect with people. Facebook users can add Facebook Page to specify their interest in the Page. The proposed system uses this Page information to create user profile, and to match user preferences to news topics. However, some Pages are not directly matched to news topic because Page deals with individual objects and do not provide topic information suitable to news. Freebase, which is a large collaborative database of well-known people, places, things, is used to match Page to news topic by using hierarchy information of its objects. By using recent Page information and articles of Facebook users, the proposed systems can own dynamic user profile. The generated user profile is used to measure user preferences on news. To generate news profile, news category predefined by news media is used and keywords of news articles are extracted after analysis of news contents including title, category, and scripts. TF-IDF technique, which reflects how important a word is to a document in a corpus, is used to identify keywords of each news article. For user profile and news profile, same format is used to efficiently measure similarity between user preferences and news. The proposed system calculates all similarity values between user profiles and news profiles. Existing methods of similarity calculation in vector space model do not cover synonym, hypernym and hyponym because they only handle given words in vector space model. The proposed system applies WordNet to similarity calculation to overcome the limitation. Top-N news articles, which have high similarity value for a target user, are recommended to the user. To evaluate the proposed news recommendation system, user profiles are generated using Facebook account with participants consent, and we implement a Web crawler to extract news information from PBS, which is non-profit public broadcasting television network in the United States, and construct news profiles. We compare the performance of the proposed method with that of benchmark algorithms. One is a traditional method based on TF-IDF. Another is 6Sub-Vectors method that divides the points to get keywords into six parts. Experimental results demonstrate that the proposed system provide useful news to users by applying user's social network information and WordNet functions, in terms of prediction error of recommended news.

• The Journal of Society for e-Business Studies
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• v.20 no.4
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• pp.209-225
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• 2015

Research and development projects in railroad domain are different from those in other domains in terms of their close relationship with laws. Some cases are reported that new technologies from R&D projects could not be industrialized because of relevant laws restricting them. This problem comes from the fact that researchers don't know exactly what laws can affect the result of R&D projects. To deal with this problem, we suggest a model for law retrieval system that can be used by researchers of railroad R&D projects to find related legislation. Input of this system is a research plan describing the main contents of projects. After laws related to the R&D project is provided with their rankings, which are assigned by scores we developed. A ranking of a law means its order of priority to be checked. By using this system, researchers can search the laws that may affect R&D projects throughout all the stages of project cycle. So, using our system model, researchers can get a list of laws to be considered before the project they participate ends. As a result, they can adjust their project direction by checking the law list, avoiding their elaborate projects being useless.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.12
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• pp.6447-6454
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• 2013

Seawater intake systems have significant problems due to seawater pollution, suspended solids, unstable intake and maintenance etc. An underground type seawater intake system was newly developed to overcome the existing weaknesses and was facilitated in Gyukpo port. In this study, to check the performance of the new system, the samples for water quality and the 3-D numerical modeling test were conducted. The five times test included the COD, total nitrogen, total phosphorus, pH, and suspended solid for the intake system. The analyses show that the COD, total nitrogen, total phosphorus, PH showedminor changes before and after. On the other hand, the change in suspended solids was significant and water was purified below 5 mg/l, first level fisheries water, after. The numerical model adopted the RNG $k-{\epsilon}$ algorithm and the CFX model based on the finite volume method. The porosity algorithm was used to reproduce filtered-sand, outer diameter, and thickness. The numerical results showed that the double pipe is advantageous in that it provides a uniform pressure between the inner and outer pipe for the flow to be stable. In addition, the use of multiple intake pipes did not interfere with the discharge reduction of 0.98 at the both intake pipes compared with the central intake pipe.