• Journal of Environmental Health Sciences
• /
• v.42 no.4
• /
• pp.280-292
• /
• 2016

Objectives: The objective of this study was to build COD regression models for the Han River and evaluate water quality. Methods: Water quality data sets for the dry season (as of January) during a four-year period (2012-2015) were collected from the database of the Han River automatic water quality monitoring stations. Statistical techniques, including combined genetic algorithm-multiple linear regression (GA-MLR) were used to build five-descriptor COD models. Multivariate statistical techniques such as principal component analysis (PCA) and cluster analysis (CA) are useful tools for extracting meaningful information. Results: The $r^2$ of the best COD models provided significant high values (> 0.8) between 2012 and 2015. Total organic carbon (TOC) was a surrogate indicator for COD (as COD/TOC) with high reliability ($r^2=0.63$ in 2012, $r^2=0.75$ for 2013, $r^2=0.79$ for 2014 and $r^2=0.85$ for 2015). The ratios of COD/TOC were calculated as 2.08 in 2012, 1.79 in 2013, 1.52 and 1.45 in 2015, indicating that biodegradability in the water body of the Han River was being sustained, thereby further improving water quality. The BOD/COD ratio supported these findings. The cluster analysis revealed higher annual levels of microorganisms and phosphorous at stations along the Hangang-Seoul and Hantangang areas. Nevertheless, the overall water quality over the last four years showed an observable trend toward continuous improvement. These findings also suggest that non-point pollution control strategies should consider the influence of upstreams and downstreams to protect water quality in the Han River. Conclusion: This data analysis procedure provided an efficient and comprehensive tool to interpret complex water quality data matrices. Results from a trend analysis provided much important information about sources and parameters for Han River water quality management.

• Journal of The Korean Astronomical Society
• /
• v.35 no.4
• /
• pp.197-208
• /
• 2002

Five contemporary pre-main sequence (PMS) evolution model grids are compared with the photo-metric data for a nearly complete sample of low-mass members in NGC 2264. From amongst the grids compared, the models of Baraffe et al. (1998) prove to be the most reliable in mass-age distribution. To overcome the limited mass range of the models of Baraffe et al. we derived a simple transformation relation between the mass of a PMS star from Swenson et al. (1994) and that from Baraffe et al., and applied it to the PMS stars in NGC 2264 and the Orion nebula cluster (ONC). The resulting initial mass function (IMF) of the ONC shows that the previous interpretation of the IMF is not a real feature, but an artifact caused by the evolution models adopted. The IMFs of both clusters are in a good agreement with the IMF of the field stars in the solar neighborhood. This result supports the idea proposed by Lada, Strom, & Myers (1993) that the field stars originate from the stars that are formed in clusters and spread out as a result of dynamical dissociation. Nevertheless, the IMFs of OB associations and young open clusters show diverse behavior. For the low-mass regime, the current observations suffer from difficulties in membership assignment and sample incompleteness. From this, we conclude that a more thorough study of young open clusters is necessary in order to make any definite conclusions on the existence of a universal IMF.

• The Journal of the Korea Contents Association
• /
• v.6 no.1
• /
• pp.23-30
• /
• 2006

A clustering method for temporal data takes a model-based approach. This uses automata based model for each cluster. It is necessary to construct global models for a set of data in order to elicit individual models for the cluster. The preparation for building individual models is completed by determining the number of clusters inherent in the data set. In this paper, BIC(Bayesian Information Criterion) approximation is used to determine the number clusters and confirmed its applicability. A search technique to improve efficiency is also suggested by analyzing the relationship between data size and BIC values. A number of experiments have been performed to check its validity using artificially generated data sets. BIC approximation measure has been confirmed that it suggests best number of clusters through experiments provided that the number of data is relatively large.

• International Journal of Control, Automation, and Systems
• /
• v.6 no.6
• /
• pp.928-938
• /
• 2008

This study presents an approach for approximation an unknown function from a numerical data set based on the synthesis of a neuro-fuzzy model. An adaptive input data space parting method, which is used for building hyperbox-shaped clusters in the input data space, is proposed. Each data cluster is implemented here as a fuzzy set using a membership function MF with a hyperbox core that is constructed from a min vertex and a max vertex. The focus of interest in proposed approach is to increase degree of fit between characteristics of the given numerical data set and the established fuzzy sets used to approximate it. A new cutting procedure, named NCP, is proposed. The NCP is an adaptive cutting procedure using a pure function $\Psi$ and a penalty function $\tau$ for direction the input data space parting process. New algorithms named CSHL, HLM1 and HLM2 are presented. The first new algorithm, CSHL, built based on the cutting procedure NCP, is used to create hyperbox-shaped data clusters. The second and the third algorithm are used to establish adaptive neuro- fuzzy inference systems. A series of numerical experiments are performed to assess the efficiency of the proposed approach.

• The Bulletin of The Korean Astronomical Society
• /
• v.40 no.1
• /
• pp.79.3-80
• /
• 2015

Galaxy overdensities such as galaxy clusters and superclusters are the largest gravitationally bound systems in the Universe. Since they contain many different levels of local densities, they are excellent places to test galaxy evolution models in connection to the environments. The environment studies of galaxies at z ~ 1 are important because the environmental quenching seems to be an important mechanism to reduce star formation activities in galaxies at z < 1. However, there have been not many studies about high redshift galaxy clusters at z ~ 1 because of the lack of wide and deep multi-wavelength data. We have used the multi-wavelength data from the UKIDSS DXS (J and K band), the SWIRE (4 IRAC bands), and the PAN-STARRS (g, r, i, z, y bands) in the ELAIS-N1 field. We identified galaxy cluster candidates at 0.2 < z < 1.6 using the multi-wavelength data. We found several superclusters where cluster candidates are concentrated on few tens of Mpc scale. Interestingly, some of the supercluster candidates consist of galaxy clusters which have high blue galaxy. We will present high redshift galaxy cluster and supercluster candidates in ELAIS-N1 field and galaxy properties in different environments including dense clusters and fields.

• Journal of The Korean Astronomical Society
• /
• v.17 no.1
• /
• pp.1-14
• /
• 1984

Analyses of an integrated form $N(\tau)={\int}_{\tau}^{\infty}n(\tau)d{\tau}$ of the distribution of cluster ages, rather than its differential form $n(\tau)$, demonstrate that the observed distribution has clusters older than about 500 million years in a significant excess over theoretical model distributions. Considerations on cluster disruption processes show that a single disruption time-scale, frequently employed by current theoretical models, is no longer an adequate parameter for describing survival probability of clusters over wide age range, because different initial conditions of these clusters produce corresponding spreads in their lifetimes. To take into account for the spread in initial conditions, we have introduced an age-dependent disruption time, and deduced its age-dependence from the present-day age distribution of clusters. Results show a distinct two-stage variation: The newly introduced disruption time stays constant at about 50 million years for clusters younger than about 100 million years, while for clusters older than that it increases monotonically with the cluster age. This leads us to conclude that clusters experience different types of disrupting causes as they get old.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.14 no.4
• /
• pp.1419-1436
• /
• 2020

For an energy harvesting sensor network, when the network lifetime is not the only primary goal, maximizing the network performance under environmental energy harvesting becomes a more critical issue. However, clustering protocols that aim at providing maximum information throughput have not been thoroughly explored in Energy Harvesting Wireless Sensor Networks (EH-WSNs). In this paper, clustering protocols are studied for maximizing the data transmission in the whole network. Based on a long short-term memory (LSTM) energy predictor and node energy consumption and supplement models, an uneven clustering protocol is proposed where the cluster head selection and cluster size control are thoroughly designed for this purpose. Simulations and results verify that the proposed scheme can outperform some classic schemes by having more data packets received by the cluster heads (CHs) and the base station (BS) under these energy constraints. The outcomes of this paper also provide some insights for choosing clustering routing protocols in EH-WSNs, by exploiting the factors such as uneven clustering size, number of clusters, multiple CHs, multihop routing strategy, and energy supplementing period.

• International Journal of Precision Engineering and Manufacturing
• /
• v.9 no.3
• /
• pp.59-63
• /
• 2008

A static load analysis of twin-screw kneaders is required not only for the dynamic analysis, but also because it is the basis of the stiffness and strength calculations that are essential for the design of bearings. In this paper, the static loads of twin-screw kneaders are analyzed, and a mathematical model of the force and torque moments is presented using a numerical integration method based on differential geometry theory. The calculations of the force and torque moments of the twin-screw kneader are given. The results show that the $M_x$ and $M_y$ components of the fluid resistance torque of the rotors change periodically in each rotation cycle, but the $M_z$ component remains constant. The axis forces $F_z$ in the female and male rotors are also constant. The static load calculated by the proposed method tends to be conservative compared to traditional methods. The proposed method not only meets the static load analysis requirements for twin-screw kneaders, but can also be used as a static load analysis method for screw pumps and screw compressors.

• Journal of Environmental Science International
• /
• v.19 no.10
• /
• pp.1229-1235
• /
• 2010

Three meteor-statistical forecasting models - the transfer function model, the time-series autoregressive model and the neural networks model - were tested to develop a daily forecasting model for Jejudo, where the need and demand for wind power forecasting has increased. All the meteorological observation sites in Jejudo have been classified into 6 groups using a cluster analysis. Four pairs of observation sites among them, all having strong wind speed correlation within the same meteorological group, were chosen for a model test. In the development of the wind speed forecasting model for Jejudo, it was confirmed that not only the use a wind dataset at the objective site itself, but the introduction of another wind dataset at the nearest site having a strong wind speed correlation within the same group, would enhance the goodness to fit of the forecasting. A transfer function model and a neural network model were also confirmed to offer reliable predictions, with the similar goodness to fit level.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.5 no.1
• /
• pp.5-23
• /
• 2011

One inevitable problem in Ad Hoc networks is the limited battery capacity, which explains why portable devices might shut down suddenly when the power of hardware is depleted. Hence, how to decrease the power consumption is an important issue in ad hoc networks. With the development of wireless technology, mobile devices can transmit voices, surf the Internet, download entertaining stuffs, and even support some P2P applications, like sharing real-time streaming. In order to keep the quality stable, the transmission must be continuous and it is thus necessary to select some managers to coordinate all nodes in a P2P community. In addition to assigning jobs to the staffs (children) when needed, these managers (ancestors) are able to reappoint jobs in advance when employees retire. This paper proposed a mechanism called Cluster-based Power Management (CPM) to stabilize the transmissions and increase Time to Live (TTL) of mobile hosts. In our new proposed method, we establish the clusters according to every node's joining order and capability, and adjust their sleep time dynamically through three different mathematical models. Our simulation results reveal that this proposed scheme not only reduces the power consumption efficiently, but also increases the total TTLs evidently.