• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권7호
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• pp.3329-3350
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• 2017

Installing caching and computing facilities in mobile edge networks is a promising solution to cope with the challenging capacity and delay requirements imposed on future mobile communication systems. The problem of optimal facility placement in mobile edge networks has not been fully studied in the literature. This is a non-trivial problem because the mobile edge network has a unidirectional topology, making existing solutions inapplicable. This paper considers the problem of optimal placement of a fixed number of facilities in a mobile edge network with an arbitrary tree topology and an arbitrary demand distribution. A low-complexity sequential algorithm is proposed and proved to be convergent and optimal in some cases. The complexity of the algorithm is shown to be $O(H^2{\gamma})$, where H is the height of the tree and ${\gamma}$ is the number of facilities. Simulation results confirm that the proposed algorithm is effective in producing near-optimal solutions.

• 한국인터넷방송통신학회논문지
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• 제8권5호
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• pp.173-179
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• 2008

애드 혹 네트워크는 인프라스트럭쳐를 가지지 않는 멀티 홉의 무선 모바일 노드들로 구성된다. 모바일 애드 혹 네트워크상의 노드들의 이동성 때문에 네트워크의 토폴로지는 빈번히 변화한다. 이러한 환경에서 멀티캐스트 프로토콜은 멀티 홉 경로 생성 및 대역폭 제한이라는 문제에 직면하게 된다. 많은 멀티캐스트 라우팅 프로토콜들이 이미 제안되었다. 우리는 두 가지 애드 훅 멀티캐스트 라우팅 프로토콜 - Serial Multiple Disjoint Tree Multicast Routing Protocol(Serial MDTRP)와 Adaptive Core Multicast Routing Protocol(ACMRP)의 성능을 비교분석하였다. 비교분석에 사용된 시뮬레이션툴은 GloMoSim을 사용하였다.

• Journal of Microbiology and Biotechnology
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• 제29권5호
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• pp.731-738
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• 2019

Endophytic fungi are an important component of plant microbiota, and have the excellent capacity for producing a broad variety of bioactive metabolites. These bioactive metabolites not only affect the survival of the host plant, but also provide valuable lead compounds for novel drug discovery. In this study, forty-two endophytic filamentous fungi were isolated from Ficus elastica leaves, and further identified as seven individual taxa by ITS-rDNA sequencing. The antimicrobial activity of these endophytic fungi was evaluated against five pathogenic microorganisms. Two strains, Fes1711 (Penicillium funiculosum) and Fes1712 (Trichoderma harzianum), displayed broad-spectrum bioactivities. Our following study emphasizes the isolation, identification and bioactivity testing of chemical metabolites produced by T. harzianum Fes1712. Two new isocoumarin derivatives (1 and 2), together with three known compounds (3-5) were isolated, and their structures were elucidated using NMR and MS. Compounds 1 and 2 exhibited inhibitory activity against Escherichia coli. Our findings reveal that endophytic fungi from the rubber tree F. elastica leaves exhibit unique characteristics and are potential producers of novel natural bioactive products.

• Mycobiology
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• 제50권2호
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• pp.132-141
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• 2022

Amylomyces rouxii is commonly found as amylolytic fungi in tapai fermentation. However, its diversity is rarely reported despite being often used for food production in Southeast Asia. This research aims to analyze the genetic diversity and the distribution pattern of A. rouxii from Ragi tapai in Java Island, Indonesia. We isolated the fungus from samples obtained from Ragi tapai producing centers in Bandung, Sumedang, Muntilan, Blora, Yogyakarta, and Bondowoso. The obtained isolates were molecularly identified based on the ribosomal regions ITS1/ITS2 and D1/D2, then analyzed for phylogenetic tree reconstruction, genetic distance, genetic variation, and haplotype networking. Six isolates showed specific morphological traits of A. rouxii. However, phylogenetic tree reconstruction on the ribosomal genes showed that the isolates were grouped into two different clades related to two species. Clade A included BDG, SMD, and MTL isolates related to A. rouxii, whereas clade B included YOG, BLR, and BDS isolates related to Mucor indicus. The genetic distances between clades for ITS1/ITS2 and D1/D2 were 0.6145 and 0.1556, respectively. In conclusion, we confirmed the genetic diversity of molds from Ragi tapai in Java Island and showed that the isolates are not only related to A. rouxii as reported before.

• International Journal of Computer Science & Network Security
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• 제23권9호
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• pp.17-28
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• 2023

Today Agriculture segment is a significant supporter of Indian economy as it represents 18% of India's Gross Domestic Product (GDP) and it gives work to half of the nation's work power. Farming segment are required to satisfy the expanding need of food because of increasing populace. Therefore, to cater the ever-increasing needs of people of nation yield prediction is done at prior. The farmers are also benefited from yield prediction as it will assist the farmers to predict the yield of crop prior to cultivating. There are various parameters that affect the yield of crop like rainfall, temperature, fertilizers, ph level and other atmospheric conditions. Thus, considering these factors the yield of crop is thus hard to predict and becomes a challenging task. Thus, motivated this work as in this work dataset of different states producing different crops in different seasons is prepared; which was further pre-processed and there after machine learning techniques Gradient Boosting Regressor, Random Forest Regressor, Decision Tree Regressor, Ridge Regression, Polynomial Regression, Linear Regression are applied and their results are compared using python programming.

• Advances in nano research
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• 제13권5호
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• pp.499-512
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• 2022

This study investigates the efficiency of ensemble machine learning for predicting the lightweight-aggregate concrete (LWC) characteristics. A stacking ensemble (STEN) approach was proposed to estimate the dry density (DD) and 28 days compressive strength (Fc-28) of LWC using two meta-models called random forest regressor (RFR) and extra tree regressor (ETR), and two novel ensemble models called STEN-RFR and STEN-ETR, were constructed. Four standalone machine learning models including artificial neural network, gradient boosting regression, K neighbor regression, and support vector regression were used to compare the performance of the proposed models. For this purpose, a sum of 140 LWC mixtures with 21 influencing parameters for producing LWC with a density less than 1000 kg/m³, were used. Based on the experimental results with multiple performance criteria, it can be concluded that the proposed STEN-ETR model can be used to estimate the DD and Fc-28 of LWC. Moreover, the STEN-ETR approach was found to be a significant technique in prediction DD and Fc-28 of LWC with minimal prediction error. In the validation phase, the accuracy of the proposed STEN-ETR model in predicting DD and Fc-28 was found to be 96.79% and 81.50%, respectively. In addition, the significance of cement, water-cement ratio, silica fume, and aggregate with expanded glass variables is efficient in modeling DD and Fc-28 of LWC.

• 한국식품영양학회지
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• 제22권1호
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• pp.103-109
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• 2009

현재까지 미생물에 의해 생산되는 10,000여 종의 항생물질 가운데 약 2/3 에 해당하는 64% 정도가 방선균으로부터 발견되었다. 따라서 토양 중에 널리 분포하고 있는 방선균을 분리하여 광범위 항생물질 생산능이 가강 우수한 Y-88을 최종 선정하였다. 이 균을 형태학적, 생리상 및 배양학적으로 동정한 결과 Streptomyces 속으로 밝혀져 Streptomyces sp. Y-88 이라 명명하였다. Y-88로부터 항생물질 생산 최적 배양조건을 검토한 결과 soluble starch 1.6%, glucose 1.6%, beef extract 0.6%, $K_2HPO_4$, $MgSO_4$ $7H_2O$ 및 $ZnSO_4$ $7H_2O$가 각각 0.01%였으며, 최적 pH4.0, 배양온도 25$^{\circ}C$ 그리고 배양시간으로 위의 조건에 30시간에서 항생물질 생산이 빠른 것으로 나타났다.

• 한국정보처리학회논문지
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• 제5권4호
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• pp.1033-1043
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• 1998

본 논문에서는 최소 비용 신장 트리(minimum cost spanning tree를 기반으로 최적 경로를 지원할 수 있는 새로운 멀티케스트 경로 배정 알고리즘을 제안하였다 본 논문에서 제안한 MCSTOP(Multicasting Path Assignment using the MInimum Cost Spanning Tree and the Optimum Path Generation) 알고리즘은 송신 노드나 이미 선정된 노드의 하위 노드들 중에서 새로운 그룹의 수신 노드가 발견되면 우선적으로 멀티캐스트 경로를 배정하는 방법을 적용하였다. 새로운 그룹의 멀티캐스트 배정과정에서 새로운 그룹의 수신 노드들 사이에 타 그룹의 노드가 발생될 수 있다. 이러한 경우가 발생되면, MCSTOP 알고리즘에서는 새로운 그룹의 송신 노드와 수신 노드가 동일한 네트워크 영역(예. LAN 영역)과 치수 제한조건이 만족되면 새로운 가상 경로를 생성하여 최적 경로를 배정하도록 하였다. MCSTOP 알고리즘은 가상 경로로 설정된 노드들 사이에 존재하는 타 그룹 노드가 네트워크에서 탈퇴하여도 영향을 받지 않게 되므로, 새로운 그룹에 대한 멀티캐스트 경로의 재구성을 최소화 시킬 수 있었다. 또한, 검증 결과 MCSTOP알고리즘은 멀티 캐스트 배정 경로를 위한 계산시간, 통신비용 그리고 데이터 전달지연시간 등이 CST(Constrained Steiner Tree) 알고리즘보다 성능 향상을 보였다. 추후 연구 사항으로는 데이터 회의를 지원하기 위한 그룹 통신 프로토콜로써 ITU-TT.120 시리즈의 MCS(Multipoint Communication Service)와 같은 국제 표준 프로토콜에 적용하기 위한 연구가 필요하다.

• Journal of Forest and Environmental Science
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• 제24권1호
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• pp.47-51
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• 2008

가지치기 작업은 보통 묘목의 식재 후 수고가 6 m 전후일 때 1차 작업을 실시하고 수고 12~13 m 전후일 때 2차 작업을 실시한다. 옹이가 없고 통직한 목재를 생산하기 위해서는 도구나 기계에 의하여 가지치기 작업이 필요하다. 가지치기 작업방법에는 자동지타기를 이용하거나 동력 고지톱을 이용하는 등 여러 가지 방법이 있지만 본 연구에서는 가지치기 작업에 일반적으로 가장 많이 활용하고 있는 인력고지톱에 의한 가지치기작업을 조사하였다. 조사수종은 강원도 지역을 중심으로 분포하고 있는 소나무, 잣나무, 리기다소나무를 대상으로 하였다. 조사대상 수고는 10~16 m 내외로서 가지치기 후 지하고의 높이는 6.2~6.7 m 내외로서 인력고지톱에 의한 가지치기 작업능률은 4~6 m의 작업높이의 경우 1본당 소나무 3.46분, 잣나무 5.06분, 리기다소나무 4.44분이 소요되었고, 1일 작업능률은 소나무 104본, 잣나무 64본, 리기다소나무 81본으로 나타났다.

• 품질경영학회지
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• 제46권3호
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• pp.739-752
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• 2018

Purpose: The purpose of this study was to investigate the relationship between kiln processing parameters and NOx emissions that occur in the sintering and calcination steps of the cement manufacturing process and to derive the main factors responsible for producing emissions outside emission limit criteria, as determined by category models and classification rules, using data mining techniques. The results from this study are expected to be useful as guidelines for NOx emission control standards. Methods: Data were collected from Precalciner Kiln No.3 used in one of the domestic cement plants in Korea. Thirty-four independent variables affecting NOx generation and dependent variables that exceeded or were below the NOx emiision limit (>1 and <0, respectively) were examined during kiln processing. These data were used to construct a detection model of NOx emission, in which emissions exceeded or were below the set limits. The model was validated using SPSS MODELER 18.0, artificial neural network, decision treee (C5.0), and logistic regression analysis data mining techniques. Results: The decision tree (C5.0) algorithm best represented NOx emission behavior and was used to identify 10 processing variables that resulted in NOx emissions outside limit criteria. Conclusion: The results of this study indicate that the decision tree (C5.0) can be applied for real-time monitoring and management of NOx emissions during the cement firing process to satisfy NOx emission control standards and to provide for a more eco-friendly cement product.