• Asian-Australasian Journal of Animal Sciences
• /
• 제33권12호
• /
• pp.2039-2049
• /
• 2020

Objective: This study was conducted to provide models to accurately predict nitrogen (N) and phosphorus (P) excretion of dairy cows on smallholder farms in Indonesia based on readily available farm data. Methods: The generic model in this study is based on the principles of the Lucas equation, describing the relation between dry matter intake (DMI) and faecal N excretion to predict the quantity of faecal N (Q_FN). Excretion of urinary N and faecal P were calculated based on National Research Council recommendations for dairy cows. A farm survey was conducted to collect input parameters for the models. The data set was used to calibrate the model to predict Q_FN for the specific case. The model was validated by comparing the predicted quantity of faecal N with the actual quantity of faecal N (Q_FNACT) based on measurements, and the calibrated model was compared to the Lucas equation. The models were used to predict N and P excretion of all 144 dairy cows in the data set. Results: Our estimate of true N digestibility equalled the standard value of 92% in the original Lucas equation, whereas our estimate of metabolic faecal N was -0.60 g/100 g DMI, with the standard value being -0.61 g/100 g DMI. Results of the model validation showed that the R² was 0.63, the MAE was 15 g/animal/d (17% from Q_FNACT), and the RMSE was 20 g/animal/d (22% from Q_FNACT). We predicted that the total N excretion of dairy cows in Indonesia was on average 197 g/animal/d, whereas P excretion was on average 56 g/animal/d. Conclusion: The proposed models can be used with reasonable accuracy to predict N and P excretion of dairy cattle on smallholder farms in Indonesia, which can contribute to improving manure management and reduce environmental issues related to nutrient losses.

• 한국지하수토양환경학회지:지하수토양환경
• /
• 제12권1호
• /
• pp.44-52
• /
• 2007

본 연구에서는 위해성평가 과정의 중요한 부분으로서 수행되는 오염물질의 지중(subsurface) 거동 모델의 이용에 관한 전반적인 내용을 고찰하였다. 모델의 종류, 그리고 모델을 선택하고 이용하기 위하여 선행되어야 할 부지조사 및 개념적 모델 수립에 대해서 살펴보았다. 모델 선택의 기준을 정리하였고 대표적 모델과 각 모델의 모의 가능한 부지 조건들을 소개하였다. 모델의 보정, 검증, 민감도 분석 등 모델 이용에 필요한 일련의 과정과 각 과정에서 유의하거나 고려하여야 할 점을 살펴보았다. 본 연구에서 검토한 바에 의하면, 모델 선택의 주요 기준은 모델링의 목표와 수준, 그리고 모델이 오염부지의 주요 현상을 모의할 수 있는지 여부지만, 모델이 실제 시스템을 적절히 모의할 수 있는지는 이러한 기준으로 판단할 수 없으며 모델 입력변수 등 부지 자료의 가용성 및 질적 수준에 따라 결정된다. 한편, 추정된 입력변수에 대하여 높은 민감도를 보인다거나 선택한 모델의 보정 및 검증이 만족스럽지 않은 경우 자료 측정으로 대신하거나 다른 모델로 전환하는 등 전략 수정을 할 필요가 있다.

• KIEAE Journal
• /
• 제16권1호
• /
• pp.89-94
• /
• 2016

This study is part of three-dimensional(3D) heat transfer analysis program developmental process. The program is being developed without it's own built in 3D-modeller. So 3D-model must be created from another 3D-modeller such as generic CAD programs and imported to the developed program. After that, according to the 3D-geometric data form imported model, 3D-mesh created for numerical calculation. But the 3D-model created from another 3D-modeller is likely to have errors in it's geometric data such as mismatch of position between vertexes or surfaces. these errors make it difficult to create 3D-mesh for calculation. These errors are must be detected and cured in the pre-process before creating 3D-mesh. So, in this study four kinds of filters and functions are developed and tested. Firstly, 'vertex error filter' is developed for detecting and curing for position data errors between vertexes. Secondly, 'normal vector error filter' is developed for errors of surface's normal vector in 3D-model. Thirdly, 'intersection filter' is developed for extracting and creating intersection surface between adjacent objects. fourthly, 'polygon-line filter' is developed for indicating outlines of object in 3D-model. the developed filters and functions were tested on several shapes of 3D-models. and confirmed applicability. these developed filters and functions will be applied to the developed program and tested and modified continuously for less errors and more accuracy.

• Spatial Information Research
• /
• 제13권3호
• /
• pp.221-237
• /
• 2005

이 논문에서는 시간지리학 모형을 위한 객체관계형 시공간데이터베이스를 구현하고, 이를 통해 시공간경로, 시공간프리즘, 시공간접근성에 대한 질의 및 시각화를 수행하는 GIS 컴퓨팅을 연구한다. 이러한 GIS 컴퓨팅환경은 (i) 시공간데이터베이스의 자료원이 되는 개인통행자료를 수집하는 모바일 애플리케이션, (ii) 시간지리학 모형을 포함하는 객체관계형 시공간데이터베이스 서버, (iii) 시공간데이터베이스와 연동하여 시간지리학 모형에 대한 질의와 시각화를 수행하는 3D 클라이언트로 구성된다. 시공간 개인통행자료는 GPS-PDA 클라이언트를 통해 일정시간 간격으로 자동 수집되고, 시공간자료관리 미들웨어의 중개를 거쳐 좌표변환 및 DB전송이 이루어진다. 일반 DBMS를 확장하여 구현한 시공간데이터베이스는 시간지리학 응용을 위한 시공간 객체 및 시공간함수를 포함하며, 이를 이용하여 시공간 SQL을 구성할 수 있다. 질의 및 시각화 클라이언트는 시공간경로, 시공간프리즘, 시공간접근성에 대한 SQL 질의 결과를 X-Y 공간축과 T 시간축으로 이루어진 시공간입방체를 통해 표현한다. 이 논문에서는 시간지리학 모형을 위한 모바일 GIS와 DBMS의 연동 가능성을 확인하였으며, 시공간객체와 시공간함수를 포함하는 객체관계형 시공간데이터베이스의 구현을 통해 대용량 자료처리를 위한 데이터베이스 기반의 시간지리학 데이터베이스 모델을 수립하였다.

• International Journal of Control, Automation, and Systems
• /
• 제1권2호
• /
• pp.194-202
• /
• 2003

In this paper, we introduce a category of Multi-FNN (Fuzzy-Neural Networks) models, analyze the underlying architectures and propose a comprehensive identification framework. The proposed Multi-FNNs dwell on a concept of fuzzy rule-based FNNs based on HCM clustering and evolutionary fuzzy granulation, and exploit linear inference being treated as a generic inference mechanism. By this nature, this FNN model is geared toward capturing relationships between information granules known as fuzzy sets. The form of the information granules themselves (in particular their distribution and a type of membership function) becomes an important design feature of the FNN model contributing to its structural as well as parametric optimization. The identification environment uses clustering techniques (Hard C - Means, HCM) and exploits genetic optimization as a vehicle of global optimization. The global optimization is augmented by more refined gradient-based learning mechanisms such as standard back-propagation. The HCM algorithm, whose role is to carry out preprocessing of the process data for system modeling, is utilized to determine the structure of Multi-FNNs. The detailed parameters of the Multi-FNN (such as apexes of membership functions, learning rates and momentum coefficients) are adjusted using genetic algorithms. An aggregate performance index with a weighting factor is proposed in order to achieve a sound balance between approximation and generalization (predictive) abilities of the model. To evaluate the performance of the proposed model, two numeric data sets are experimented with. One is the numerical data coming from a description of a certain nonlinear function and the other is NOx emission process data from a gas turbine power plant.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제6권10호
• /
• pp.2708-2730
• /
• 2012

The growing concern for the protection of personal information has made it critical to implement effective technologies for privacy and data management. By observing the limitations of existing approaches, we found that there is an urgent need for a flexible, privacy-aware system that is able to meet the privacy preservation needs at both the role levels and the personal levels. We proposed a conceptual system that considered these two requirements: a graph-based, access control model to safeguard patient privacy. We present a case study of the healthcare field in this paper. While our model was tested in the field of healthcare, it is generic and can be adapted to use in other fields. The proof-of-concept demos were also provided with the aim of valuating the efficacy of our system. In the end, based on the hospital scenarios, we present the experimental results to demonstrate the performance of our system, and we also compared those results to existing privacy-aware systems. As a result, we ensured a high quality of medical care service by preserving patient privacy.

• Ocean Systems Engineering
• /
• 제9권3호
• /
• pp.261-285
• /
• 2019

Nowadays in offshore industry there are emerging hazards with vague property such as act of terrorism, act of war, unforeseen natural disasters such as tsunami, etc. Therefore industry professionals such as offshore energy insurers, safety engineers and risk managers in order to determine the failure rates and frequencies for the potential hazards where there is no data available, they need to use an appropriate method to overcome this difficulty. Furthermore in conventional risk based analysis models such as when using a fault tree analysis, hazards with vague properties are normally waived and ignored. In other word in previous situations only a traditional probability based fault tree analysis could be implemented. To overcome this shortcoming fuzzy set theory is applied to fault tree analysis to combine the known and unknown data in which the pre-combined result will be determined under a fuzzy environment. This has been fulfilled by integration of a generic bow-tie based risk analysis model into the risk assessment phase of the Risk Management (RM) cycles as a backbone of the phase. For this reason Fault Tree Analysis (FTA) and Event Tree Analysis (ETA) are used to analyse one of the significant risk factors associated in offshore terminals. This process will eventually help the insurers and risk managers in marine and offshore industries to investigate the potential hazards more in detail if there is vagueness. For this purpose a case study of offshore terminal while coinciding with the nature of the Caspian Sea was decided to be examined.

• Journal of Computing Science and Engineering
• /
• 제3권1호
• /
• pp.27-58
• /
• 2009

Aggregation join queries are an important class of queries over data streams. These queries involve both join and aggregation operations, with window-based joins followed by an aggregation on the join output. All existing research address join query optimization and aggregation query optimization as separate problems. We observe that, by putting them within the same scope of query optimization, more efficient query execution plans are possible through more versatile query transformations. The enabling idea is to perform aggregation before join so that the join execution time may be reduced. There has been some research done on such query transformations in relational databases, but none has been done in data streams. Doing it in data streams brings new challenges due to the incremental and continuous arrival of tuples. These challenges are addressed in this paper. Specifically, we first present a query processing model geared to facilitate query transformations and propose a query transformation rule specialized to work with streams. The rule is simple and yet covers all possible cases of transformation. Then we present a generic query processing algorithm that works with all alternative query execution plans possible with the transformation, and develop the cost formulas of the query execution plans. Based on the processing algorithm, we validate the rule theoretically by proving the equivalence of query execution plans. Finally, through extensive experiments, we validate the cost formulas and study the performances of alternative query execution plans.

• 대한기계학회논문집B
• /
• 제21권8호
• /
• pp.1024-1033
• /
• 1997

The past several years have witnessed an ever-increasing acceptance and adoption of parallel processing, both for high performance scientific computing as well as for more general purpose applications. Furthermore with increasing needs to perform the complex flow calculations in an efficient manner, the use of the message passing model on distributed networks has emerged as an important alternative to the expensive supercomputers. This work attempts to provide a generic framework to enable the parallelization of all CFD-related works using the master-slave model. This framework consists of (1) input geometry, (2) domain decomposition, (3) grid generation, (4) flow computations, (5) flow visualization, and (6) output display as the sequential components, but performs computations for (2) to (5) in parallel on the workstation clustering. The flow computations are parallized by having multiple copies of the flow-code to solve a PDE on different spatial regions on different processors, while their flow data are exchanged across the region boundaries, and the solution is time-stepped. The Parallel Virtual Machine (PVM) is used for distributed communication in this work.

• Nuclear Engineering and Technology
• /
• 제51권8호
• /
• pp.1916-1938
• /
• 2019

The objective of this paper is to discuss the modeling principles of phenomena governing core degradation/melting and in-vessel melt relocation during severe accidents in light water reactors. The proposed modeling approach has been applied in the development of a new accident simulation package, COMPASS (COre Meltdown Progression Accident Simulation Software). COMPASS can be used either as a stand-alone tool to simulate in-vessel meltdown progression up to and including RPV failure, or as a component of an integrated simulation package being developed in Korea for the APR1400 reactor. Interestingly, since the emphasis in the development of COMPASS modeling framework has been on capturing generic mechanistic aspects of accident progression in light water reactors, several parts of the overall model should be useful for future accident studies of other reactor designs, both PWRs and BWRs. The issues discussed in the paper include the overall structure of the model, the rationale behind the formulation of the governing equations and the associated simplifying assumptions, as well as the methodology used to verify both the physical and numerical consistencies of the overall solver. Furthermore, the results of COMPASS validation against two experimental data sets (CORA and PHEBUS) are shown, as well as of the predicted accident progression at TMI-2 reactor.