• Korean Journal of Agricultural Science
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• v.43 no.2
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• pp.163-175
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• 2016

For the past decades, advances in computational devices have propelled mathematical modeling to become an effective tool for solving the black box of complex biological systems because of its prominent analytical power and comprehensive insight. Nevertheless, modeling is still limitedly used in the fields of agriculture and food which generally concentrate on producing experimental data rather than processing them. This study, hence, intends to introduce modeling in terms of its procedure types of structure, formulation, analyses, and software, with reviews of current notable studies from micro to macro scales so as to propose the modeling technique as a novel approach in discerning conundrums in agriculture and food systems. We expect this review to provide an eligible source for researchers who are willing to apply modeling techniques into the unexplored fields related to bio-systems that comprehensively include biology, nutrition, agriculture, food, animal science, and ecology.

• East Asian mathematical journal
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• v.36 no.2
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• pp.173-201
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• 2020

Mathematical modeling has been emphasized because it offers important opportunities for students to both apply their learning of mathematics to a situation and to explore the mathematics involved in the context of the situation. However, unlike its importance, mathematical modeling has not been grounded in typical mathematics classes because teachers do not have enough understanding of mathematical modeling and they are skeptical to implement it in their lessons. The current study analyzed the data, such as video recordings, slides, and surveys for teachers, collected in four lessons of teacher education in terms of mathematical modeling. The study reported different kinds of tasks that are authentic with regards to mathematical modeling. Furthermore, in teacher education, teachers' identities have separated a mode as learners and a mode as teachers and conflicts and intentional transition were observed. Analysis of the surveys shows what teachers think about mathematical modeling with their understanding of it. In teacher education, teachers achieved different kinds of modeling tasks and experience them which are helpful to enact mathematical modeling in their lessons. However, teacher education also needs to specifically offer what to do and how to do it for their lessons.

• IE interfaces
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• v.16 no.spc
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• pp.45-48
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• 2003

Entity-relationship modeling for designing relational database is a very complicated thinking process that requires extensive knowledge and experiences. It is very likely that designers make mistakes in this process. In order to minimize the mistakes, a systematic method to guide the thinking process is needed. In this research, an entity-relationship modeling system is developed, which resolves the whole process of information modeling, data modeling, and functional dependency relationship analysis into small and simple decision-making steps. Therefore, it can reduce the possibility of making decision errors and improve the efficiency of the modeling process. It's functionality and efficiency is verified through some modeling examples. It is expected that the modeling system can be commercialized, if some functions are added, such as detection, warning, and correction of decision errors, and educational help.

• Journal of Information Technology Applications and Management
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• v.17 no.3
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• pp.1-24
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• 2010

Most of enterprises depend on a data modeler during developing their management information systems. In formulating business requirements for information systems, they widely and naturally use the interview method between a data modeler and a field worker. But, the discrepancy between both parties would certainly cause information loss and distortion that lead to let the systems not faithful to real business works. To improve or avoid modeler-dependant data modeling process, many automated data design CASE tools have been introduced. However, since most of traditional CASE tools just support drawing works for conceptual data design, a data modeler could not generate an ERD faithful to real business works and a user could not use them without any knowledge on database. Although some CASE tools supported conceptual data design, they still required too much preliminary database knowledge for a user. Against these traditional CASE tools, we proposed a Requirement-Oriented Entity Relationship Model for automated data design tool, called ROERM. Based on Non-Stop Methodology, ROERM adopts inner systematic modules for complete and sound ERD that is faithful to real field works, where modules are composed of interaction modules with a user, rules of schema operations and sentence translations. In addition to structure design of ROERM, we also devise detailed algorithms and perform an experiment for a case study.

• Journal of the Korea Safety Management & Science
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• v.11 no.2
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• pp.137-144
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• 2009

EPCIS(EPC Information Services) system is a core component of EPCglobal Architecture Framework offering information of the freights, the time of awareness and the location of awareness on the EPCglobal Network. The role of EPCIS is to exchange information based on EPC. There are four kinds of event data which are object event data, aggregation event data, quantity event data, and transaction event data. These EPCIS events data are stored and managed in EPCIS repository. This study suggest the quantitative modeling about total number of EPCIS event data under the assumption to aware the RFID tags of items, cases(boxes), vehicles(carriers, forklifts, auto guided vehicles, rolltainers) at a time on the reading points. We also estimate the number of created EPCIS event data by the suggested quantitative modeling under scenario of process in the integrated logistics center based on RFID system And this study compare the TO-BE model with the AS-IS model about the total sizes of created EPCIS event data using the simulation, in which we suggested the TO-BE model as the development of the repository by skipping the overlapped records.

• International journal of advanced smart convergence
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• v.6 no.4
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• pp.88-95
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• 2017

The conventional scan methods are based on a laser scanner and a depth camera, which requires high cost and complicated post-processing. Whereas in photometric scanning method, the 3D modeling data is acquired through multi-view images. This is advantageous compared to the other methods. The quality of a photometric 3D model depends on the environmental conditions or the object characteristics, but the quality is lower as compared to other methods. Therefore, various methods for improving the quality of photometric scanning are being studied. In this paper, we aim to investigate the effect of illumination conditions on the quality of photometric scanning data. To do this, 'Moai' statue is 3D printed with a size of $600(H){\times}1,000(V){\times}600(D)$. The printed object is photographed under the hard light and soft light environments. We obtained the modeling data by photometric scanning method and compared it with the ground truth of 'Moai'. The 'Point-to-Point' method used to analyseanalyze the modeling data using open source tool 'CloudCompare'. As a result of comparison, it is confirmed that the standard deviation value of the 3D model generated under the soft light is 0.090686 and the standard deviation value of the 3D model generated under the hard light is 0.039954. This proves that the higher quality 3D modeling data can be obtained in a hard light environment. The results of this paper are expected to be applied for the acquisition of high-quality data.

• Journal of Korean Society for Geospatial Information Science
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• v.16 no.2
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• pp.57-65
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• 2008

The improvement of the performance in laser radar simulation requires fast retrievals of the spatial locations and attributes of objects in response to the laser signals of the simulators. Since the data used in simulation are complex 3D objects such as terrain, buildings and vehicles, and are of large sizes, commonly used 3D modeling tools are not suitable for this use. We proposed a method to store such 3D objects in a database, perform required queries and integrate with visualization tools. We showed the processes for the data modeling based on 3D topological concepts and then building a spatial DBMS. Also, we illustrated the process for accessing and visualizing the stored data using VRML and performed test computations using some laser signal data. With further enhancement on data modeling and LOD problems in visualization, the proposed method will be practically applied in different situations including laser simulation.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.11
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• pp.1505-1510
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• 2018

Product modeling technology for graphics is rapidly developing. And 3D data application and usability are increasing.modeling of product design is a very important factor in constructing. 3D modeling in product design takes a lot of production time. Recently, the reverse design method is very useful because of application of 3D data and shortening of production time. In this study, first, 3D point cloud and mesh data are generated using photographs based on image data. The second is to modify the design and the third is to make the prototype with the 3D printer. This product design and production process suggests the utilization and possibility of image data, the shortening of 3D modeling production time and efficient processes. Also, the product design process proposes a model of a new product development system to adapt to the production environment.

• The Journal of Bigdata
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• v.7 no.1
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• pp.99-111
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• 2022

A simulation technique can be used to analyze performance measures and support decision makings in manufacturing systems considering operational uncertainty and complexity. The simulation requires an input modeling procedure to reflect the target system's characteristics. However, data collection to build a simulation is quite limited when a target system includes manual productions with a lot of operational time such as construction equipment assembly lines. This study proposes a procedure for simulation input modeling using video data when it is difficult to collect enough input data to fit a probability distribution. We conducted a video-data analysis and specify input distributions for the simulation. Based on the proposed procedure, simulation experiments were conducted to evaluate key performance measures of the target system. We also expect that the proposed procedure may help simulation-based decision makings when obtaining input data for a simulation modeling is quite challenging.

• Journal of the Korea Society of Computer and Information
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• v.29 no.7
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• pp.73-80
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• 2024

In this paper, we proposes a method to improve the accuracy of predicting the Korea Composite Stock Price Index (KOSPI) by combining topic modeling and Long Short-Term Memory (LSTM) neural networks. In this paper, we use the Latent Dirichlet Allocation (LDA) technique to extract ten major topics related to interest rate increases and decreases from financial news data. The extracted topics, along with historical KOSPI index data, are input into an LSTM model to predict the KOSPI index. The proposed model has the characteristic of predicting the KOSPI index by combining the time series prediction method by inputting the historical KOSPI index into the LSTM model and the topic modeling method by inputting news data. To verify the performance of the proposed model, this paper designs four models (LSTM_K model, LSTM_KNS model, LDA_K model, LDA_KNS model) based on the types of input data for the LSTM and presents the predictive performance of each model. The comparison of prediction performance results shows that the LSTM model (LDA_K model), which uses financial news topic data and historical KOSPI index data as inputs, recorded the lowest RMSE (Root Mean Square Error), demonstrating the best predictive performance.