• The Journal of Bigdata
• /
• v.6 no.2
• /
• pp.169-179
• /
• 2021

Consumers' food consumption behavior is likely to be affected not only by structured data such as consumer panel data but also by unstructured data such as mass media and social media. In this study, a deep learning-based consumption prediction model is generated and verified for the fusion data set linking structured data and unstructured data related to food consumption. The results of the study showed that model accuracy was improved when combining structured data and unstructured data. In addition, unstructured data were found to improve model predictability. As a result of using the SHAP technique to identify the importance of variables, it was found that variables related to blog and video data were on the top list and had a positive correlation with the amount of paprika purchased. In addition, according to the experimental results, it was confirmed that the machine learning model showed higher accuracy than the deep learning model and could be an efficient alternative to the existing time series analysis modeling.

• Proceedings of the Materials Research Society of Korea Conference
• /
• 2007.11a
• /
• pp.153.2-153.2
• /
• 2007

• Geomechanics and Engineering
• /
• v.18 no.2
• /
• pp.133-140
• /
• 2019

Strain-rate and temperature have significant effects on the one-dimensional (1D) compression behavior of soils. This paper focuses on the bonding degradation effect of soil structure on the time and temperature dependent behavior of soft structured clay. The strain-rate and temperature dependency of preconsolidation pressure are investigated in double logarithm plane and a thermal viscoplastic model considering the combined effect of strain-rate and temperature is developed to describe the mechanical behavior of unstructured clay. By incorporating the bonding degradation, the model is extended that can be suitable for structured clay. The extended model is used to simulate CRS (Constant Rate of Strain) tests conducted on structural Berthierville clay with different strain-rates and temperatures. The comparisons between predicted and experimental results show that the extended model can reasonably describe the effect of bonding degradation on the stain-rate and temperature dependent behavior of soft structural clay under 1D condition. Although the model is proposed for 1D analysis, it can be a good base for developing a more general 3D model.

• Proceedings of the Korea Society for Simulation Conference
• /
• 2001.10a
• /
• pp.44-49
• /
• 2001

This paper is concerned with development of a multi-attribute structured decision model. In this study, we used AHP(analytic hierarchy process) and fuzzy set ranking methodology to overcome the multi-attributes structured decision problems ; such as multi-objective, multi-criterion, and multi-attributes. We proposed a 2-step approach : 1) individual evaluation and 2) integration of individual evaluations. In the first step, we define the performance factors and construct ana]isis structure, and in the second step performance evaluation by individual evaluators, and in second step, the results of individual evaluations are integrate. Also we developed a systematic and practical computer program to solve the problems according to the proposed methods. The proposed approach was known to be effective through a set of sample problems.

• Proceedings of the Korean Society for Bioinformatics Conference
• /
• 2005.09a
• /
• pp.151-155
• /
• 2005

Recently, systems biology has been increasingly applied to gain insights into the complexity of living organisms. Many inaccessible biological information and hidden evidences fur example flux distribution of the metabolites are simply revealed by investigation of artificial cell behaviors. Most bio-models are models of single cell organisms that cannot handle the multi-cellular organisms like plants. Herein, a structured and multi-cellular model of potato was developed to comprehend the root starch biosynthesis. On the basis of simplest plant cell biology, a potato structured model on the platform of Berkley Madonna was divided into three parts: photosynthetic (leaf), non-photosynthetic (tuber) and transportation (phloem) cells. The model of starch biosynthesis begins with the fixation of CO$_2$ from atmosphere to the Calvin cycle. Passing through a series of reactions, triose phosphate from Calvin cycle is converted to sucrose which is transported to sink cells and is eventually formed the amylose and amylopectin (starch constituents). After validating the model with data from a number of literatures, the results show that the structured model is a good representative of the studied system. The result of triose phosphate (DHAP and GAP) elevation due to lessening the aldolase activity is an illustration of the validation. Furthermore, the representative model was used to gain more understanding of starch production process such as the effect of CO$_2$ uptake on qualitative and quantitative aspects of starch biosynthesis.

• Advanced Industrial SCIence
• /
• v.1 no.1
• /
• pp.7-15
• /
• 2022

To adopt the development in the medical scenario IoT developed towards the advancement with the processing of a large amount of medical data defined as an Internet of Medical Things (IoMT). The vast range of collected medical data is stored in the cloud in the structured manner to process the collected healthcare data. However, it is difficult to handle the huge volume of the healthcare data so it is necessary to develop an appropriate scheme for the healthcare structured data. In this paper, a machine learning mode for processing the structured heath care data collected from the IoMT is suggested. To process the vast range of healthcare data, this paper proposed an MTGPLSTM model for the processing of the medical data. The proposed model integrates the linear regression model for the processing of healthcare information. With the developed model outlier model is implemented based on the FinTech model for the evaluation and prediction of the COVID-19 healthcare dataset collected from the IoMT. The proposed MTGPLSTM model comprises of the regression model to predict and evaluate the planning scheme for the prevention of the infection spreading. The developed model performance is evaluated based on the consideration of the different classifiers such as LR, SVR, RFR, LSTM and the proposed MTGPLSTM model and the different size of data as 1GB, 2GB and 3GB is mainly concerned. The comparative analysis expressed that the proposed MTGPLSTM model achieves ~4% reduced MAPE and RMSE value for the worldwide data; in case of china minimal MAPE value of 0.97 is achieved which is ~ 6% minimal than the existing classifier leads.

• Journal of the Korea Society for Simulation
• /
• v.21 no.2
• /
• pp.19-30
• /
• 2012

In recent decades, it has been known that the Discrete Event System Specification, or DEVS, formalism provides sound semantics to design a modular and hierarchical model of a discrete event system. In spite of this benefit, practitioners have difficulties in applying the semantics to real-world systems modeling because DEVS needs to specify a large size of sets of events and/or states in an unstructured form. To resolve the difficulties, this paper proposes an extension of the DEVS formalism, called the Structured DEVS formalism, with an associated graphical representation, called the DEVS diagram, by means of structural representation of such sets based on closure property of set theory. The proposed formalism is proved to be equivalent to the original DEVS formalism in their model specification, yet the new formalism specifies sets in a structured form with a concept of phases, variables and ports. A simplified example of the structured DEVS with the DEVS diagram shows the effectiveness of the proposed formalism which can be easily implemented in an objected-oriented simulation environment.

• Asia pacific journal of information systems
• /
• v.19 no.2
• /
• pp.73-94
• /
• 2009

The general aspects for the future warfare shows that the concept of firepower and maneuver centric warfare has been replacing with that of information and knowledge centric warfare. Thus, some developed countries are now trying to establish the information systems to perform intelligent warfare and innovate defense operations. The C4I(Command, Control, Communication, Computers and Intelligence for the Warrior) systems make it possible to do modern and systematic war operations. The basic idea of this study is to investigate how TAM(Technology Acceptance Model) can explain the acceptance behavior in military organizations. Because TAM is inadequate in explaining the acceptance processes forcomplex technologies and strict organizations, a revised research model based upon TAM was developed in order to assess the usage of the C4I system. The purpose of this study is to investigate factors affecting the usage of C4I in the Korean Army. The research model, based upon TAM, was extended through a belief construct such as self-efficacy as one of mediating variables. The self-efficacy has been used as a mediating variable for technology acceptance, and the variable was included in the research model. The external variables were selected on the basis of previous research. The external variables can be classified into following: 1) technological, 2) organizational, and 3) environmental factors on the basis of TOE(Technology-Organization-Environment) framework. The technological factor includes the information quality and the task-technology fitness. The organizational factor includes the influence of senior colleagues. The environmental factor includes the education/train data. The external variables are considered very important for explaining the behavior patterns of information technology or systems. A structured questionnaire was developed and administrated to those who were using the C4I system. Total 329 data were used for statistical data analyses. A confirmatory factor analysis and structured equation model were used as main statistical methods. Model fitness Indexes for measurement and structured models were verified before all 18 hypotheses were tested. This study shows that the perceived usefulness and the self-efficacy played their roles more than the perceived ease of use did in TAM. In military organizations, the perceived usefulness showed its mediating effects between external variables and dependent variable, but the perceived ease of use did not. These results imply that the perceived usefulness can explain the acceptance processes better than the perceived ease of use in the army. The self-efficacy was also used as one of the three mediating variables, and showed its mediating effects in explaining the acceptance processes. Such results also show that the self-efficacy can be selected as one possible belief construct in TAM. The perceived usefulness was influenced by such factors as senior colleagues, the information quality, and the task-technology fitness. The self-efficacy was affected by education/train and task-technology fitness. The actual usage of C4I was influenced not by the perceived ease of use but by the perceived usefulness and selfefficacy. This study suggests the followings: (1) An extended TAM can be applied to such strict organizations as the army; (2) Three mediation variables are included in the research model and tested at real situations; and (3) Several other implications are discussed.

• Journal of Mechanical Science and Technology
• /
• v.15 no.12
• /
• pp.1609-1615
• /
• 2001

This paper presents the characteristics of a general structured observer and presents an estimation algorithm for a system with external disturbances which are added to the input of the system. By using a disturbance model, the general structured observer can estimate the states of the system is spite of disturbances, where the system is affected from external disturbances. Also, the general structured observer can include the function of a PI observer or high gain observer by properly adjusting the observer's gain matrices. The existence condition for the observer is derived, which can be checked by the system's observability condition and the pole-zero cancellation of the system's polynomial matrix. Through a numerical example, it is verified that the proposed observer is effective estimating the system and the input disturbance.

• Journal of Microbiology and Biotechnology
• /
• v.23 no.2
• /
• pp.195-204
• /
• 2013

While structured packing modules are known to be efficient for surface wetting and gas-liquid exchange in abiotic surface catalysis, this model study explores structured packing as a growth surface for catalytic biofilms. Microbial biofilms have been proposed as selfimmobilized and self-regenerating catalysts for the production of chemicals. A concern is that the complex and dynamic nature of biofilms may cause fluctuations in their catalytic performance over time or may affect process reproducibility. An aerated continuous trickle-bed biofilm reactor system was designed with a 3 L structured packing, liquid recycling and pH control. Pseudomonas diminuta established a biofilm on the stainless steel structured packing with a specific surface area of 500 $m^2m^{-3}$ and catalyzed the oxidation of ethylene glycol to glycolic acid for over two months of continuous operation. A steady-state productivity of up to 1.6 $gl^{-1}h^{-1}$ was achieved at a dilution rate of 0.33 $h^{-1}$. Process reproducibility between three independent runs was excellent, despite process interruptions and activity variations in cultures grown from biofilm effluent cells. The results demonstrate the robustness of a catalytic biofilm on structured packing, despite its dynamic nature. Implementation is recommended for whole-cell processes that require efficient gas-liquid exchange, catalyst retention for continuous operation, or improved catalyst stability.