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Cha, Y.,Park, S. S.,Kim, K.,Byeon, M.,Stow, C. A. Wiley 2014 Water resources research Vol.50 No.3
There have been increasing reports of harmful algal blooms (HABs) worldwide. However, the factors that influence cyanobacteria dominance and HAB formation can be site-specific and idiosyncratic, making prediction challenging. The drivers of cyanobacteria blooms in Lake Paldang, South Korea, the summer climate of which is strongly affected by the East Asian monsoon, may differ from those in well-studied North American lakes. Using the observational data sampled during the growing season in 2007-2011, a Bayesian hurdle Poisson model was developed to predict cyanobacteria abundance in the lake. The model allowed cyanobacteria absence (zero count) and nonzero cyanobacteria counts to be modeled as functions of different environmental factors. The model predictions demonstrated that the principal factor that determines the success of cyanobacteria was temperature. Combined with high temperature, increased residence time indicated by low outflow rates appeared to increase the probability of cyanobacteria occurrence. A stable water column, represented by low suspended solids, and high temperature were the requirements for high abundance of cyanobacteria. Our model results had management implications; the model can be used to forecast cyanobacteria watch or alert levels probabilistically and develop mitigation strategies of cyanobacteria blooms.
Cha, Y.,Park, M.H.,Lee, S.H.,Kim, J.H.,Cho, K.H. Pergamon Press 2016 Water research Vol.100 No.-
Bacteria are a primary contaminant in natural surface water. The instream concentration of fecal coliform, a potential indicator of pathogens, is influenced by meteorological conditions and land-use characteristics. However, the relationships between these conditions and fecal coliforms are not fully understood. Furthermore, the sources of large variability in fecal coliform counts, e.g., temporal or spatial sources, remain unexplained, especially at large scales. This study proposes the use of Bayesian overdispersed Poisson models, whereby the combined effects of temperature, rainfall, and land-use characteristics on fecal coliform concentration are quantified with predictive uncertainty, and the sources of variability in fecal coliform concentration are assessed. The models were developed using 8-year weekly observations of fecal coliforms obtained from the Wachusett Reservoir watershed in Massachusetts, USA. The results highlight the importance of interactions among meteorological and land-use characteristics in controlling the instream fecal coliform concentration; the increase in fecal coliform concentration with temperature increase was more drastic when rainfall occurred. Also, the responses of fecal coliforms to temperature increases were more pronounced in forest-dominated than in urban-dominated areas. In contrast, the fecal coliform concentration increased more rapidly with rainfall increases in urban-dominated than in forest-dominated areas. The models also demonstrate that among the sources of variability, the monthly component made the most significant contribution to the variability in fecal coliform concentrations. Our results suggest that seasonally dependent processes, including surface runoff, are critical factors that regulate fecal coliform concentration in streams.
Goal-balancing process for goal formation in the fractal manufacturing system
Cha, Y.,Shin, M.,Ryu, K.,Jung, M. Taylor Francis 2007 INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH - Vol.45 No.20
<P> The coordination architecture and mechanisms are proposed for the goal-balancing process (GBP), which is one of the components of goal-formation process (GFP) in the fractal manufacturing system (FrMS). Since each agent in the FrMS generates, achieves and modifies its own goal autonomously during the coordination process with other agents, it is necessary to develop a systematic methodology for the goal-formations in a manufacturing system: GFP takes charge of this methodology, which enables the formation of and the changes in goal through coordination between agents in real-time in the distributed and dynamic systems. The GFP is composed of three sub-processes: the goal-generating process (GGP), the goal-harmonizing process (GHP), and the GBP. The GGP makes and propagates goals for all fractals. The GHP then eliminates or reduces possible conflicts and interferences between goals generated in GGP. The GBP is the post-process of GHP; it refines the fractal's goal, which has been ridded of conflict during the GHP to enhance the global performance of the system, rather than maximizing the performance of each fractal. For the development of the GBP we proposed a mechanism for unit goal-balancing process (UGBP), which is the basic process of GBP that adopts the, fuzzy decision-making, and distributed problem solving approaches.</P>
휴대형 3D 그래픽 가속기를 위한 저전력/저면적 잔술 연산기
김체현,신경욱 금오공과대학교 2005 論文集 Vol.26 No.-
본 논문에서는 휴대형 3D 그래픽 가속기를 위한 저전력,저면적 벡터 처리기(Vector Processing Unit; VPU, 누승기(Powering Unit) 등의 산술 연산기를 설계하였다. 설계된 연산기는 부동소수점 대신 OpenGl.rES에서 권장하는 16.16의 고정소수점 방식을 사용하여 모바일 환경에서 저전력,저면적으로 동작하도록 하였다. 벡터 처리기는 RB(Redundant Binary) 수체계기반으로 설계하였으며 일반적인 승산기 4개와 가산기 3개로 구현하는 방식과 비교하여 10%의 면적 감소를 이루었다. 누승기는 LNS(Logarithm Number System) 기반으로 설계 하였으며, 부동소수점과 룩업테이블(Look-Up Table; LUT)로 구현하는 방식과 비교하여 80% 의 면적 감소를 이루었다. 또한 연산 정밀도를 높이기 위해 이진수-로그 변환 시 6-영역의 근사화 방식을 사용하여 평균 퍼센트 오차가 1.6% 로 평가되었다. This paper describes a design of low-power/small-area arithmetic circuits which are vector processing unit and powering unit for mobile 3D graphic accelerator. To achieve area-efficient and low-power implementation that is an essential consideration for mobile environment, the fixed-point format of 16.16 is adopted instead of conventional floating-point format. The vector processing unit is designed using redundant binary arithmetic, resulting 10% gate count reduction compared with conventional method using four multipliers and three adders. The powering unit that is based on logarithm number system reduces gate count of about 80% when compared with lookup table implementation of floating-point powering unit. To minimize average percent error to 1.6%, six. region approximation method is employed.