A similarity measure on tree structured business data

In many business situations, products or user profile data are so complex that they need to be described by use of tree structures. Evaluating the similarity between tree-structured data is essential in many applications, such as recommender systems. To evaluate the similarity between two trees, concept corresponding nodes should be identified by constructing an edit distance mapping between them. Sometimes, the intension of one concept includes the intensions of several other concepts. In that situation, a one-to-many mapping should be constructed from the point of view of structures. This paper proposes a tree similarity measure model that can construct this kind of mapping. The similarity measure model takes into account all the information on nodes’ concepts, weights, and values. The conceptual similarity and the value similarity between two trees are evaluated based on the constructed mapping, and the final similarity measure is assessed as a weighted sum of their conceptual and value similarities. The effectiveness of the proposed similarity measure model is shown by an illustrative example and is also demonstrated by applying it into a recommender system.

Ground-based survey methods both overestimate and underestimate the abundance of suitable tree-cavities for the endangered Swift Parrot

Most cavity-dependent species select tree-cavities with a narrow range of characteristics so that only a small subset of available cavities may be suitable for any species. Most surveys for tree-cavities are done from the ground using binoculars to reduce effort, but this technique is prone to error. These errors are likely to contribute to the loss of the cavity resource when used to inform conservation efforts for cavity-dependent species. The Swift Parrot (Lathamus discolor) is an endangered migratory bird threatened by ongoing removal of cavity-bearing trees by production forestry. We climbed trees with cavities used for nesting by Swift Parrots and determined that they prefer cavities with small entrances, deep chambers and wide floors. Such cavities are rare and occur in large trees that support higher than average numbers of tree-cavities. Importantly, cavities used by Swift Parrots were also likely to be both overestimated and underestimated using ground-based surveys, and without calibration by climbing, the size and direction of survey error could not be determined. We conclude that the most effective way to gain detailed information about the characteristics and abundance of tree-cavities is to climb a representative sample of trees to calibrate ground-based methods for a specific ecosystem.

Rubber latex yield and physiology of rubber tree with tea tree oil treatments

To examine the effects of tea tree oil on rubber latex yield and the resulting latex physiological parameters of rubber tree （Hevea brasiliensis），clean water and 20%，40%，60%，80% and 100% of tea tree oil were applied on the tapping cut of rubber trees. The data were analyzed by Duncan test and its results showed that when compared to clean water （ck），80% and 100% of tea tree oil stimulation significantly promoted rubber latex yield（P＜0.05）. In addition，the latex physiological parameters changed with the sucrose content（P＜0.01），magnesium ion content （P＜0.01） and inorganic phosphorus content （P＜0.01） of latex significantly increasing and thiol content significantly deceasing （P＜0.01）. The effect of tea tree oil treatments on rubber yield was similar to the impact of 0.5% ethrel stimulation. However，compared to ethrel stimulation，100% tea tree oil treatment significantly increased dry rubber and sucrose contents （P＜0.01） and decreased thiol content （P＜0.01）. Thus，tea tree oil treatment involved different latex yield promotion mechanisms than that of ethrel stimulation.

Enhancing an evolving tree-based text document visualization model with fuzzy c-Means clustering

An improved evolving model, i.e., Evolving Tree (ETree) with Fuzzy c-Means (FCM), is proposed for undertaking text document visualization problems in this study. ETree forms a hierarchical tree structure in which nodes (i.e., trunks) are allowed to grow and split into child nodes (i.e., leaves), and each node represents a cluster of documents. However, ETree adopts a relatively simple approach to split its nodes. Thus, FCM is adopted as an alternative to perform node splitting in ETree. An experimental study using articles from a flagship conference of Universiti Malaysia Sarawak (UNIMAS), i.e., Engineering Conference (ENCON), is conducted. The experimental results are analyzed and discussed, and the outcome shows that the proposed ETree-FCM model is effective for undertaking text document clustering and visualization problems.

Effect of ultrasonic wave on latex production and quality of rubber tree

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.

Growing Self Organizing Map with an Imposed Binary Search Tree for Discovering Temporal Input Patterns

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.

An effective deferentially private data releasing algorithm for decision tree

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.

Empirical investigation of decision tree ensembles for monitoring cardiac complications of diabetes

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.

Expression of muscarinic receptor subtypes in tree shrew ocular tissues and their regulation during the development of myopia

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.