• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.7
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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.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.8 no.5
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• pp.173-179
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• 2008

An ad hoc network is multi-hop wireledss formed by mobile node without infrastructure. Due to the mobility of nodes in mobile ad hoc networks, the topology of network changes frequently. In this environments, multicast protocols are faced with the challenge of producing multi-hop routes and limitation of bandwidth. We compare the performance of two multicast routing protocols for mobile ad hoc networks - Serial Multiple Disjoint Tree Multicast Routing Protocol (Serial MDTMR) and Adaptive Core Multicast Routing Protocol (ACMRP). The simulator is implemented with GloMoSim.

• Journal of Microbiology and Biotechnology
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• v.29 no.5
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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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• v.50 no.2
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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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• v.23 no.9
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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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• v.13 no.5
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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.

• The Korean Journal of Food And Nutrition
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• v.22 no.1
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• pp.103-109
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• 2009

In order to isolate antibiotic producing microorganisms, several actinomycetes were isolated from soil samples. The aerial hyphae of Y-88 strain were gray in color with tree types. Under the microscopic examination, the Y-88 isolate formed a spiral aerial spore mass with a smooth surface and a rectiflexibilis type of spore chain. Y-88 utilized glucose, fructose, arabinose, and sucrose, but not rhamnose, raffinose, mannitol, or inositol. In addition, Y-88 produced melanin on the tyrosine agar and the strain could utilize L-valine, L-phenylalanine, and L-hydroxyproline. Based on these results and the cultural and physiological characteristics described in the Bergey's Manual, the Actinomycetes, Y-88, was identificated as a Streptomyces species. The optimum medium conditions for this antibiotic producing Streptomyces sp. Y-88 was 1.6% soluble starch, 0.6% glucose, 0.6% beef extract, 0.01% $K_2HPO_4$, 0.01% $MgSO_4$ $7H_2O$, and 0.01% $ZnSO_4$ $7H_2O$ at an initial pH of 4.0, and 25$^{\circ}C$.

• The Transactions of the Korea Information Processing Society
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• v.5 no.4
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• pp.1033-1043
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• 1998

In this paper, we present an improved multicasting path assignment algorithm based on the minimum cost spanning tree. In the method presented in this paper, a multicasting path is assigned preferentially when a node to be received is found among the next degree nodes of the searching node in the multicasting path assignment of the constrained steiner tree (CST). If nodes of the legacy group exist between nodes of the new group, a new path among the nodes of new group is assigned as long as the nodes may be excluded from the new multicasting path assignment taking into consideration characteristics of nodes in the legacy group. In assigning the multicasting path additionally, where the source and destination nodes which can be set for the new multicasting path exist in the domain of identical network (local area network) and conditions for degree constraint are satisfied, a method of producing and assigning a new multicasting path is used. The results of comparison of CST with MCSTOP, MCSTOp algorithm enhanced performance capabilities about the communication cost, the propagation delay, and the computation time for the multicasting assignment paths more than CST algorithm. Further to this, research activities need study for the application of the international standard protocol(multicasting path assignment technology in the multipoint communication service (MCS) of the ITU-T T.120).

• Journal of Forest and Environmental Science
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• v.24 no.1
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• pp.47-51
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• 2008

The first pruning works of planted trees on forest area carry out when tree height reached at 6 meters. And the second works carry out when it grow to 12~13 meters of tree height. Pruning works are necessary for producing straight log without knar by tool or machine. Generally, the mechanized pruning works Self-propelled pruning machine, chain pruning saw and other tools are used in mechanized pruning works. However, manual pruning saw which is usually using pruning tool was for this study. To investigate the pruning works efficiency, Pinus densiflora, Pinus koraiensis and Pinus rigida which were distributed in Kangwon-Do was surveyed. Height of surveyed the trees were 10~16 meters and its pruning works range were 6.2~6.7 meters of tree height. As results, pruning works efficiency of Pinus densiflora, Pinus koraiensis and Pinus rigida were 3.14 min/tree, 5.06 min/tree and 4.44 min/tree, respectively. Also, possible pruning works of man-day for Pinus densiflora, Pinus koraiensis and Pinus rigida was 104, 64, and 81 trees, respectively.

• Journal of Korean Society for Quality Management
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• v.46 no.3
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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.