• 한국컴퓨터정보학회논문지
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• 제23권5호
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• pp.9-14
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• 2018

For an efficient management of electricity market and power systems, accurate forecasts for electricity demand are essential. Since there are many factors, either known or unknown, determining the realized loads, it is difficult to forecast the demands with the past time series only. In this paper we perform a cluster analysis on electricity demand data collected from Jan. 2000 to Dec. 2017. Our purpose of clustering on electricity demand data is that each cluster is expected to consist of data whose latent variables are same or similar values. Then, if properly clustered, it is possible to develop an accurate forecasting model for each cluster separately. To validate the feasibility of this approach for building better forecasting models, we clustered data with t-SNE. To apply t-SNE to time series data effectively, we adopt the dynamic time warping as a similarity measure. From the result of experiments, we found that several clusters are well observed and each cluster can be interpreted as a mix of well-known factors such as trends, seasonality and holiday effects and other unknown factors. These findings can motivate the approaches which build forecasting models with respect to each cluster independently.

• Journal of applied mathematics & informatics
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• 제41권4호
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• pp.861-868
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• 2023

Nonlinear network creates complex homotopy structural communication in wireless network medium because of complex distribution approach. Due to this multicast topological connection structure, the queuing probability was non regular principles to create routing structures. To resolve this problem, we propose a Co-cluster homotopy queuing model (Co-CHQT) for Nonlinear Algebraic Topological Structure (NLTS-) for improving poison distribution network communication. Initially this collects the routing propagation based on Nonlinear Distance Theory (NLDT) to estimate the nearest neighbor network nodes undernon linear at x_(a,b)→ax²+bx² = c. Then Quillen Network Decomposition Theorem (QNDT) was applied to sustain the non-regular routing propagation to create cluster path. Each cluster be form with co variance structure based on Two unicast 2(n+1)-Z2(n+1)-Z network. Based on the poison distribution theory X_(a,b) ≠ µ(C), at number of distribution routing strategies weights are estimated based on node response rate. Deriving shorte;'l/st path from behavioral of the node response, Hilbert -Krylov subspace clustering estimates the Cluster Head (CH) to the routing head. This solves the approximation routing strategy from the nonlinear communication depending on Max- equivalence theory (Max-T). This proposed system improves communication to construction topological cluster based on optimized level to produce better performance in distance theory, throughput latency in non-variation delay tolerant.

• Journal of Preventive Medicine and Public Health
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• 제57권3호
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• pp.234-241
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• 2024

Objectives: Health development is a key element of national development. The goal of improving health development at the societal level will be readily achieved if it is directed from the smallest social unit, namely the family. This was the goal of the Healthy Indonesia Program with a Family Approach. The objective of the study was to analyze variables of family health indicators across all provinces in Indonesia to identify provincial disparities based on the status of healthy families. Methods: This study examined secondary data for 2021 from the Indonesia Health Profile, provided by the Ministry of Health of the Republic of Indonesia, and from the 2021 welfare statistics by Statistics Indonesia (BPS). From these sources, we identified 10 variables for analysis using the k-means method, a non-hierarchical method of cluster analysis. Results: The results of the cluster analysis of healthy family indicators yielded 5 clusters. In general, cluster 1 (Papua and West Papua Provinces) had the lowest average achievements for healthy family indicators, while cluster 5 (Jakarta Province) had the highest indicator scores. Conclusions: In Indonesia, disparities in healthy family indicators persist. Nutrition, maternal health, and child health are among the indicators that require government attention.

• 한국지하수토양환경학회지:지하수토양환경
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• 제14권5호
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• pp.18-28
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• 2009

다양한 물리화학적 특성을 지닌 12개의 유기오염물이 저표면적의 무기물 지반 수착제로 수착 시 12개의 유기오염물을 적은 수의 pseudocompound로 집략화하는 접근법(lumped approach)의 타당성과 정확성을 평가하였다. 집략화 접근법은 복잡한 혼합 유기오염물의 수착 거동을 근거로 통계적인 처리방법인 집략분석(cluster analysis)을 통해 개발되었다. 집략화 접근법을 이용해 수용액상에서 복잡한 혼합 유기오염물이 친수성 무기물로 수착 시 감소된 수의 집략화된 오염물(pseudocompound)과 집략화된 오염물의 수착 매개변수($K_f$, n)를 이용하여 복잡한 혼합 유기오염물의 수착을 설명할 수 있었다. 또한, 실험을 수행하지 않고(a priori) 복잡한 혼합 유기오염물 내 각 유기오염물의 특성(${\gamma_w}^{sat}$)을 근거로 pseudocompound를 예측할 수 있었다. 따라서 집략화 접근법은 복잡한 혼합 유기오염물의 수착거동을 단순화하여 반응관련 매개변수 산출에 필요한 시간과 비용을 감소시켜주고 통계적으로 정확성이 동일한 범위 내의 실용적인 수착 결과를 제공해 줄 수 있다. 향후 더 많은 반응 인자소결합크기, 수착제 내 반응 지점 수 및 반응성 그룹 등)를 고려한 다중회귀분석(multiple regression analysis)을 통해 집략화 접근법(lumped approach)의 정확도를 높일 필요가 있다고 판단된다.

• 융합신호처리학회논문지
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• 제12권1호
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• pp.38-43
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• 2011

센서 네트워크에서 사용되는 동적 클러스터링 방식은 주기적으로 클러스터 구조가 바뀌는 셋업과정으로 인한 에너지 소모가 크다. 셋업과정은 보안적용을 해야 할 경우 보안 키가 주기적으로 재 생성되는 등 클러스터 구성 이외에 추가적인 에너지 낭비가 발생한다. 본 논문은 최초에 구성된 클러스터 알고리즘과 이후 반복적으로 발생되는 클러스터 재셋업 알고리즘을 달리하는 하이브리드 방식을 제안한다. 재 셋업에서는 고정된 클러스터 내에서 순환적으로 클러스터 헤드노드를 선출하는 순환적 클러스터 헤드선정(RRCH: Round-Robin Cluster Header)방식을 이용하여 에너지 소모를 줄인다. 보안키 생성 및 적용으로 추가되는 에너지 소모는 클러스터가 지속적으로 고정되기 때문에 최초 클러스터 형성 때 사전 배포하는 방식으로 해결된다. 본 논문에서 제안한 방식의 타당성을 확인하기 위해 모의실험을 실시하였다. 라운드 구간을 100번 반복하여 클러스터 구성과 데이터 전송을 포함한 전체 에너지 소모량을 측정하였다. 결과는 제안한 방식이 LEACH방식보다 평균 26.5%, HEED방식보다 평균 20% 적게 소모되는 것을 확인하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제8권2호
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• pp.664-677
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• 2014

Wind energy has proven its viability by the emergence of countless wind turbines around the world which greatly contribute to the increased electrical generating capacity of wind farm operators. These infrastructures are usually deployed in not easily accessible areas; therefore, maintenance routines should be based on a well-guided decision so as to minimize cost. To aid operators prior to the maintenance process, a condition monitoring system should be able to accurately reflect the actual state of the wind turbine and its major components in order to execute specific preventive measures using as little resources as possible. In this paper, we propose a fault detection approach which combines cluster analysis and frequent pattern mining to accurately reflect the deteriorating condition of a wind turbine and to indicate the components that need attention. Using SCADA data, we extracted operational status patterns and developed a rule repository for monitoring wind turbine systems. Results show that the proposed scheme is able to detect the deteriorating condition of a wind turbine as well as to explicitly identify faulty components.

• 농업과학연구
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• 제45권3호
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• pp.547-559
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• 2018

Consumers are becoming increasingly interested in what kind of value their food has. Many studies have focused on consumers' preferences and willingness to pay for specific food values. However, few studies have asked consumers to consider or rank the importance of different food values. This paper determined consumers' food values by implementing the best-worst scaling approach and segmented consumers based on the relative importance of general food values that consumers place on them. Among a list of eleven food values (taste, safety, origin, appearance, price, environmental impact, naturalness, convenience, nutrition, fairness, and habit) which was compiled from previous studies on food preferences, on average, safety, nutrition, taste, and price were the most important values to consumers, whereas fairness, habit, appearance, convenience, origin, and environmental impact were the least important values. However, significant variation exists among consumers in terms of the relative importance of food values. To investigate the heterogeneity among consumers, a Latent Class Analysis was performed to classify consumers into subgroups based on responses to questions. Two latent classes were found and characterized as 'safety-nutrition' and 'taste-price'. The 'safety-nutrition' cluster represents 61% of the sample and a group of people who find safety and nutrition centered values to be the most important. Another cluster represents about 39% of the sample, and relative to the first group, this group finds price and taste values to be more important.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권9호
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• pp.4063-4086
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• 2016

Cloud computing is a robust technology, which facilitate to resolve many parallel distributed computing issues in the modern Big Data environment. Hadoop is an ecosystem, which process large data-sets in distributed computing environment. The HDFS is a filesystem of Hadoop, which process data blocks to the cluster nodes. The data block placement has become a bottleneck to overall performance in a Hadoop cluster. The current placement policy assumes that, all Datanodes have equal computing capacity to process data blocks. This computing capacity includes availability of same storage media and same processing performances of a node. As a result, Hadoop cluster performance gets effected with unbalanced workloads, inefficient storage-tier, network traffic congestion and HDFS integrity issues. This paper proposes a storage-tier-aware Robust Data Placement (RDP) scheme, which systematically resolves unbalanced workloads, reduces network congestion to an optimal state, utilizes storage-tier in a useful manner and minimizes the HDFS integrity issues. The experimental results show that the proposed approach reduced unbalanced workload issue to 72%. Moreover, the presented approach resolve storage-tier compatibility problem to 81% by predicting storage for block jobs and improved overall data block placement by 78% through pre-calculated computing capacity allocations and execution of map files over respective Namenode and Datanodes.

• 한국산업정보학회논문지
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• 제9권4호
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• pp.32-40
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• 2004

본 연구는 중소기업이 제작한 농기계인 예취기의 사용설명서를 대상으로 SD법을 이용하여 특성을 조사하고, 통계학적인 방법을 이용하여 응답자, 설명서 및 제품별 특성을 분석하였다 기존의 감성공학적 연구들이 단순한 SD법에 의한 수치분석을 제시한 것은 단편적인 분석에 그치고 있으나, 본 연구에서는 군집분석(클러스터 분석)을 이용하여 응답자의 특성을 조사하고, 요인분석을 통해서 설문지의 특성을 도출한 다음, 각 제품 설명서의 특성을 추출하여, 그 방법론을 제시하였다. 실증분석을 위해 평가지를 작성하여 다양한 연령층의 29명을 대상으로 설명서를 평가하게 하고 그 결과를 분석하였다.

• 농촌계획
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• 제22권2호
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• pp.45-55
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• 2016

From 1970, the concept of ecotourism is introduced, lots of studies in ecotourism appeared. Review these studies are necessary for future ecotourism studies. Some review studies on ecotourism are existed. However, these approach also limitation of subjectivities and some sorts of papers has not been reviewed. This study use keyword network analysis which is used as big data analysis to overcome the limitation. Foreign 2455 studies and domestic 163 studies which have ecotoursim in keywords, are analyzed for reviewing. As a result, 3 cluster('Sustainable tourism development', 'Ecological conservation', 'Ecotourist analysis' appeared, in ecotourism studies. In addition, this cluster has deep relationship with region. 'Sustainable tourism development' is related to Eurasia, Australia, Europe. 'Ecological conservation' is related to Africa. 'Ecotourism analysis' is related to North America. Especially 'Resident participation', 'Stakeholder' are appeared many times in Asia region. These results show that ecotourism studies are interpreted in regional contexts. It means that although only one word 'ecotourism' is used in different contexts, regional approach are needed for exact use. In Korea, the keywords are focused on ecotourists and developments. As Korea has lots of ecotour village, resident participation studies have to be supplemented.