88 resultados para Evolving tree


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The effects of ultrasonic wave on tapping surface of ‘PR107’ rubber tree were studied. Daily production and cumulative production of latex were measured to estimate the effects of ultrasonic wave on latex production. The solid substance content, dry rubber content and mechanical stability of latex were determined to study the effects of ultrasonic wave on latex quality. Results showed that ultrasonic wave could increase both daily and cumulative production of latex and maintain latex basic quality. The daily production of latex was increased and appeared two peaks both in the ultrasound-treated rubber tree and the one with no treatment. The first peak appeared on the fifth day, and the latex production by ultrasound was 212.34 ml and the control was 141.75 ml The second peak appeared with the production 266.59 ml on the seventeenth day by ultrasound, while the control appeared on the thirteenth day with production of 193.5 ml. The latex cumulative production of ultrasound-treated trees was 209.56 ml higher than that of control in one month. There was little change in solid substance content and dry rubber content between different ultrasonic time. The best mechanical stability of latex was obtained by ultrasound-treating the rubber tree for 4-6 min. it was proved that the ultrasound was helpful in improving the latex production and quality. The application of ultrasonic wave on rubber tree is novel, and its mechanism is worth further research.

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This article discusses the role of community consultation in the process of developing a community museum in the Kelabit Highlands in Sarawak. It reflects on the relationships between heritage conservation, cultural tourism and competing community aspirations.   

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In this paper the Binary Search Tree Imposed Growing Self Organizing Map (BSTGSOM) is presented as an extended version of the Growing Self Organizing Map (GSOM), which has proven advantages in knowledge discovery applications. A Binary Search Tree imposed on the GSOM is mainly used to investigate the dynamic perspectives of the GSOM based on the inputs and these generated temporal patterns are stored to further analyze the behavior of the GSOM based on the input sequence. Also, the performance advantages are discussed and compared with that of the original GSOM.

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Differential privacy is a strong definition for protecting individual privacy in data releasing and mining. However, it is a rigid definition introducing a large amount of noise to the original dataset, which significantly decreases the quality of data mining results. Recently, how to design a suitable data releasing algorithm for data mining purpose is a hot research area. In this paper, we propose a differential private data releasing algorithm for decision tree construction. The proposed algorithm provides a non-interactive data releasing method through which miner can obtain the complete dataset for data mining purpose. With a given privacy budget, the proposed algorithm generalizes the original dataset, and then specializes it in a differential privacy constrain to construct decision trees. As the designed novel scheme selection operation can fully utilize the allocated privacy budget, the data set released by the proposed algorithm can yield better decision tree models than other method. Experimental results demonstrate that the proposed algorithm outperforms existing methods for private decision tree construction.

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Cardiac complications of diabetes require continuous monitoring since they may lead to increased morbidity or sudden death of patients. In order to monitor clinical complications of diabetes using wearable sensors, a small set of features have to be identified and effective algorithms for their processing need to be investigated. This article focuses on detecting and monitoring cardiac autonomic neuropathy (CAN) in diabetes patients. The authors investigate and compare the effectiveness of classifiers based on the following decision trees: ADTree, J48, NBTree, RandomTree, REPTree, and SimpleCart. The authors perform a thorough study comparing these decision trees as well as several decision tree ensembles created by applying the following ensemble methods: AdaBoost, Bagging, Dagging, Decorate, Grading, MultiBoost, Stacking, and two multi-level combinations of AdaBoost and MultiBoost with Bagging for the processing of data from diabetes patients for pervasive health monitoring of CAN. This paper concentrates on the particular task of applying decision tree ensembles for the detection and monitoring of cardiac autonomic neuropathy using these features. Experimental outcomes presented here show that the authors' application of the decision tree ensembles for the detection and monitoring of CAN in diabetes patients achieved better performance parameters compared with the results obtained previously in the literature.

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This thesis (creative practice/exegesis) argues that fantasy fiction can function as a progressive socio-political literature. Using the Marxist theory of the Frankfurt School it explores the relationship between fantasy and science fiction via utopian/dystopian representation. Through this dialogue a new understanding of the genre is voiced.

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Dynamic Evolving Neural-Fuzzy Inference System (DENFIS) is a Takagi-Sugeno-type fuzzy inference system for online learning which can be applied for dynamic time series prediction. To the best of our knowledge, this is the first time that DENFIS has been used for rainfall-runoff (R-R) modeling. DENFIS model results were compared to the results obtained from the physically-based Storm Water Management Model (SWMM) and an Adaptive Network-based Fuzzy Inference System (ANFIS) which employs offline learning. Data from a small (5.6 km2) catchment in Singapore, comprising 11 separated storm events were analyzed. Rainfall was the only input used for the DENFIS and ANFIS models and the output was discharge at the present time. It is concluded that DENFIS results are better or at least comparable to SWMM, but similar to ANFIS. These results indicate a strong potential for DENFIS to be used in R-R modeling.

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Muscarinic receptors are known to regulate several important physiologic processes in the eye. Antagonists to these receptors such as atropine and pirenzepine are effective at stopping the excessive ocular growth that results in myopia. However, their site of action is unknown. This study details ocular muscarinic subtype expression within a well documented model of eye growth and investigates their expression during early stages of myopia induction. Total RNA was isolated from tree shrew corneal, iris/ciliary body, retinal, choroidal, and scleral tissue samples and was reverse transcribed. Using tree shrew-specific primers to the five muscarinic acetylcholine receptor subtypes (CHRM1-CHRM5), products were amplified using polymerase chain reaction (PCR) and their identity confirmed using automated sequencing. The expression of the receptor proteins (M1-M5) were also explored in the retina, choroid, and sclera using immunohistochemistry. Myopia was induced in the tree shrew for one or five days using monocular deprivation of pattern vision, and the expression of the receptor subtypes was assessed in the retina, choroid, and sclera using real-time PCR. All five muscarinic receptor subtypes were expressed in the iris/ciliary body, retina, choroid, and sclera while gene products corresponding to CHRM1, CHRM3, CHRM4, and CHRM5 were present in the corneal samples. The gene expression data were confirmed by immunohistochemistry with the M1-M5 proteins detected in the retina, choroid, and sclera. After one or five days of myopia development, muscarinic receptor gene expression remained unaltered in the retinal, choroidal, and scleral tissue samples. This study provides a comprehensive profile of muscarinic receptor gene and protein expression in tree shrew ocular tissues with all receptor subtypes found in tissues implicated in the control of eye growth. Despite the efficacy of muscarinic antagonists at inhibiting myopia development, the genes of the muscarinic receptor subtypes are neither regulated early in myopia (before measurable axial elongation) nor after significant structural change.

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Nicotiana glauca (Argentinean tree tobacco) is atypical within the genus Nicotiana, accumulating predominantly anabasine rather than nicotine and/or nornicotine as the main component of its leaf pyridine alkaloid fraction. The current study examines the role of the A622 gene from N. glauca (NgA622) in alkaloid production and utilises an RNAi approach to down-regulate gene expression and diminish levels of A622 protein in transgenic tissues. Results indicate that RNAi-mediated reduction in A622 transcript levels markedly reduces the capacity of N. glauca to produce anabasine resulting in plants with scarcely any pyridine alkaloids in leaf tissues, even after damage to apical tissues. In addition, analysis of hairy roots containing the NgA622-RNAi construct shows a substantial reduction in both anabasine and nicotine levels within these tissues, even if stimulated with methyl jasmonate, indicating a role for the A622 enzyme in the synthesis of both alkaloids in roots of N. glauca. Feeding of Nicotinic Acid (NA) to hairy roots of N. glauca containing the NgA622-RNAi construct did not restore capacity for synthesis of anabasine or nicotine. Moreover, treatment of these hairy root lines with NA did not lead to an increase in anatabine levels, unlike controls. Together, these results strongly suggest that A622 is an integral component of the final enzyme complex responsible for biosynthesis of all three pyridine alkaloids in Nicotiana.