Search results for: tree density

Authors: Nieves M. C. Talavera-Prieto, Abel G. M. Ferreira, António T. G. Portugal, Rui J. Moreira, Jaime B. Santos

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The knowledge of biodiesel density over large ranges of temperature and pressure is important for predicting the behavior of fuel injection and combustion systems in diesel engines, and for the optimization of such systems. In this study, cottonseed oil was transesterified into biodiesel and its density was measured at temperatures between 288 K and 358 K and pressures between 0.1 MPa and 30 MPa, with expanded uncertainty estimated as ±1.6 kg.m^-3. Experimental pressure-volume-temperature (pVT) cottonseed data was used along with literature data relative to other 18 biodiesels, in order to build a database used to test the correlation of density with temperarure and pressure using the Goharshadi–Morsali–Abbaspour equation of state (GMA EoS). To our knowledge, this is the first that density measurements are presented for cottonseed biodiesel under such high pressures, and the GMA EoS used to model biodiesel density. The new tested EoS allowed correlations within 0.2 kg•m-3 corresponding to average relative deviations within 0.02%. The built database was used to develop and test a new full predictive model derived from the observed linear relation between density and degree of unsaturation (DU), which depended from biodiesel FAMEs profile. The average density deviation of this method was only about 3 kg.m-3 within the temperature and pressure limits of application. These results represent appreciable improvements in the context of density prediction at high pressure when compared with other equations of state.

Keywords: biodiesel density, correlation, equation of state, prediction

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Authors: K. S. Parlak, E. Turan

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The separation of marbles according to the pattern quality is a process made according to expert decision. The classification phase is the most critical part in terms of economic value. In this study, a self-learning system is proposed which performs the classification of marbles quickly and with high success. This system performs ten feature extraction by taking ten marble images from the camera. The marbles are classified by decision tree method using the obtained properties. The user forms the training set by training the system at the marble classification stage. The system evolves itself in every marble image that is classified. The aim of the proposed system is to minimize the error caused by the person performing the classification and achieve it quickly.

Keywords: decision tree, feature extraction, k-means clustering, marble classification

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Authors: Mehran Asadi, Afrand Agah

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In data mining, partitioning is used as a fundamental tool for classification. With the help of partitioning, we study the structure of data, which allows us to envision decision rules, which can be applied to classification trees. In this research, we used online social network dataset and all of its attributes (e.g., Node features, labels, etc.) to determine what constitutes an above average chance of being a divergent node. We used the R statistical computing language to conduct the analyses in this report. The data were found on the UC Irvine Machine Learning Repository. This research introduces the basic concepts of classification in online social networks. In this work, we utilize overfitting and describe different approaches for evaluation and performance comparison of different classification methods. In classification, the main objective is to categorize different items and assign them into different groups based on their properties and similarities. In data mining, recursive partitioning is being utilized to probe the structure of a data set, which allow us to envision decision rules and apply them to classify data into several groups. Estimating densities is hard, especially in high dimensions, with limited data. Of course, we do not know the densities, but we could estimate them using classical techniques. First, we calculated the correlation matrix of the dataset to see if any predictors are highly correlated with one another. By calculating the correlation coefficients for the predictor variables, we see that density is strongly correlated with transitivity. We initialized a data frame to easily compare the quality of the result classification methods and utilized decision trees (with k-fold cross validation to prune the tree). The method performed on this dataset is decision trees. Decision tree is a non-parametric classification method, which uses a set of rules to predict that each observation belongs to the most commonly occurring class label of the training data. Our method aggregates many decision trees to create an optimized model that is not susceptible to overfitting. When using a decision tree, however, it is important to use cross-validation to prune the tree in order to narrow it down to the most important variables.

Keywords: online social networks, data mining, social cloud computing, interaction and collaboration

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Authors: Bachir Chemani, Rachid Halfaoui

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The aim of work is to define the distribution density of winding yarn on cylindrical and conical bobbins. It is known that parallel winding gives greater density and more regular distribution, but the unwinding of yarn is much more difficult for following process. The conical spool has an enormous advantage during unwinding and may contain a large amount of yarns, but the density distribution is not regular because of difference in diameters. The variation of specific density over the reel height is explained generally by the sudden change of winding speed due to direction movement variation of yarn. We determined the conditions of uniform winding and developed a calculate model to the change of the specific density of winding wire over entire spool height.

Keywords: textile, cylindrical bobbins, conical bobbins, parallel winding, cross winding

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Authors: Nur Amira nor Arifin, Tashia Marie Anthony, Mohd Ruzlin Mokhtar, Huzainie Shafi Abd Halim

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Cross-linked polyethylene (XLPE) material is being used as the cable insulation for the past decades due to its higher working temperature of 90 ˚C and some other advantages. However, the use of XLPE as an insulating material for underground distribution cables may have subjected to the unforeseeable weather and uncontrollable environmental condition. These unfavorable condition when combine with high electric field may lead to the initiation and growth of water tree in XLPE insulation. There are several studies on numerous nanofillers incorporate into polymer matrix to hinder the growth of tree propagation. Hence, in this study aims to investigate the effect of MgO and rubber nanofillers at different concentration on the electrical tree of XLPE. The nanofillers and XLPE were mixed and later extruded. After extrusion, the material were then fabricated into the desired shape for experimental purposes. The result shows that the electrical tree propagation of XLPE filled with optimize concentration of nanofillers were much slower compared to pure XLPE. In this paper, the effect of nanofillers towards electrical treeing characteristic will be discussed.

Keywords: electrical trees, nanofillers, polymer nanocomposites, XLPE

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Authors: Nubwimana Rachel, Mugabowindekwe Maurice

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Trees play a crucial role in maintaining biodiversity and providing various ecological services. Traditional methods of counting trees are time-consuming, and there is a need for more efficient techniques. However, deep learning makes it feasible to identify the multi-scale elements hidden in aerial imagery. This research focuses on the application of deep learning techniques for tree detection and counting in both forest and non-forest areas through the exploration of the deep learning application for automated tree detection and counting using satellite imagery. The objective is to identify the most effective model for automated tree counting. We used different deep learning models such as YOLOV7, SSD, and UNET, along with Generative Adversarial Networks to generate synthetic samples for training and other augmentation techniques, including Random Resized Crop, AutoAugment, and Linear Contrast Enhancement. These models were trained and fine-tuned using satellite imagery to identify and count trees. The performance of the models was assessed through multiple trials; after training and fine-tuning the models, UNET demonstrated the best performance with a validation loss of 0.1211, validation accuracy of 0.9509, and validation precision of 0.9799. This research showcases the success of deep learning in accurate tree counting through remote sensing, particularly with the UNET model. It represents a significant contribution to the field by offering an efficient and precise alternative to conventional tree-counting methods.

Keywords: remote sensing, deep learning, tree counting, image segmentation, object detection, visualization

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Authors: Mayuri Roy Choudhury

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In recent times the concept of agrivoltaics has gained popularity due to the dual use of land and the added value provided by photovoltaics in terms of renewable energy and crop production on farms. However, the transition towards agrivoltaics has been slow, and our research tries to investigate the obstacles leading towards the slow progress of agrivoltaics. We applied data science decision tree algorithms to quantify qualitative perceptions of farmers in the United States for agrivoltaics. To date, there has not been much research that mentions farmers' perceptions, as most of the research focuses on the benefits of agrivoltaics. Our study adds value by putting forward the voices of farmers, which play a crucial towards the transition to agrivoltaics in the future. Our results show a mixture of responses in favor of agrivoltaics. Furthermore, it also portrays significant concerns of farmers, which is useful for decision-makers when it comes to formulating policies for agrivoltaics.

Keywords: agrivoltaics, decision-tree algorithms, farmers perception, transition

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Authors: P. Defossez, J. M. Bonnefond, D. Garrigou, P. Trichet, F. Danjon

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Windstorm damage to European forests has ecological, social and economic consequences of major importance. Most trees during storms are uprooted. While a large amount of work has been done over the last decade on understanding the aerial tree response to turbulent wind flow, much less is known about the root-soil interface, and the impact of soil moisture and root-soil system fatiguing on tree uprooting. Anchorage strength is expected to be reduced by water-logging and heavy rain during storms due to soil strength decrease with soil water content. Our paper is focused on the maritime pine cultivated on sandy soil, as a representative species of the Forêt des Landes, the largest cultivated forest in Europe. This study aims at providing knowledge on the effects of soil saturation on root anchorage. Pulling experiments on trees were performed to characterize the resistance to wind by measuring the critical bending moment (Mc). Pulling tests were performed on 12 maritime pines of 13-years old for two unsaturated soil conditions that represent the soil conditions expected in winter when wind storms occur in France (w=11.46 to 23.34 % gg⁻¹). A magnetic field digitizing technique was used to characterize the three-dimensional architecture of root systems. The soil mechanical properties as function of soil water content were characterized by laboratory mechanical measurements as function of soil water content and soil porosity on remolded samples using direct shear tests at low confining pressure ( < 15 kPa). Remarkably Mc did not depend on w but mainly on the root system morphology. We suggested that the importance of soil water conditions on tree anchorage depends on the tree size. This study gives a new insight on young tree anchorage: roots may sustain by themselves anchorage, whereas adhesion between roots and surrounding soil may be negligible in sandy soil.

Keywords: roots, sandy soil, shear strength, tree anchorage, unsaturated soil

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Authors: Michaela Chovancova, Pavel Niedoba

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For the treatment of acute and chronic lung diseases it is preferred to deliver medicaments by inhalation. The drug is delivered directly to tracheobronchial tree. This way allows the given medicament to get directly into the place of action and it makes rapid onset of action and maximum efficiency. The transport of aerosol particles in the particular part of the lung is influenced by their size, anatomy of the lungs, breathing pattern and airway resistance. This article deals with calculation of airway resistance in the lung model of Horsfield. It solves the problem of determination of the pressure losses in bifurcation and thus defines the pressure drop at a given location in the bronchial tree. The obtained data will be used as boundary conditions for transport of aerosol particles in a central part of bronchial tree realized by Computational Fluid Dynamics (CFD) approach. The results obtained from CFD simulation will allow us to provide information on the required particle size and optimal inhalation technique for particle transport into particular part of the lung.

Keywords: human lungs, bronchial tree, pressure losses, airways resistance, flow, breathing

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Authors: Nigus Maregu Demewoz, Shu-Kai Yeh

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Low-density nanocellular foam is a fascinating new-generation advanced material due to its mechanical strength and thermal insulation properties. In nanocellular foam, reducing the density increases the insulation ability. However, producing a nanocellular foam of densities less than 0.3 with a cell size of less than 100 nm is very challenging. In this study, poly (methyl methacrylate) (PMMA) was blended with Polyether block amide (PEBAX) to study the effects of PEBAX on the nanocellular foam structure of the PMMA matrix. We added 2 wt% of PEBAX in the PMMA matrix, and the PEBAX nanostructured domain size of 45 nm was well dispersed in the PMMA matrix. The foaming result produced a new generation special bouquet-like nanocellular foam of cell size less than 50 nm with a relative density of 0.24. Also, we were able to produce a nanocellular foam of a relative density of about 0.17. In addition to thermal insulation applications, bouquet-like nanocellular foam may be expected for filtration applications.

Keywords: nanocellular foam, low-density, cell size, relative density, PMMA/PEBAX

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Authors: Nigus Maregu Demewoz, Shu-Kai Yeh

Abstract:

Low-density nanocellular foam is a fascinating new-generation advanced material due to its mechanical strength and thermal insulation properties. In nanocellular foam, reducing the density increases the insulation ability. However, producing a nanocellular foam of densities less than 0.3 with a cell size of less than 100 nm is very challenging. In this study, poly (methyl methacrylate) (PMMA) was blended with Polyether block amide (PEBAX) to study the effects of PEBAX on the nanocellular foam structure of the PMMA matrix. We added 2 wt% of PEBAX in the PMMA matrix, and the PEBAX nanostructured domain size of 45 nm was well dispersed in the PMMA matrix. The foaming result produced a new generation special bouquet-like nanocellular foam of cell size less than 50 nm with a relative density of 0.24. Also, we were able to produce a nanocellular foam of a relative density of about 0.17. In addition to thermal insulation applications, bouquet-like nanocellular foam may be expected for filtration applications.

Keywords: nanocellular foam, low-density, cell size, relative density, PMMA/PEBAX blend

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Authors: Yunmi Park, Mahn-Jo Kim

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The purpose of this research is to find out the effect of raising poultry in environment-friendly producing area to fruit quality and crop within chestnut tree yield. This study was conducted on chestnut tree cultivation sites raising poultry at intervals of five to ten days for three years in the mountainous area which was located in the middle corner of Chungcheongbuk-do province, Korea. The quality of chestnut fruit and the control effects of harmful insects have been investigated between the sites raising poultry and control sites for three years. As a result, the harvest yielded were two to five kilograms higher in the chestnut tree cultivation sites raising poultry compared with the control site without poultry. Also, for the purposes of determining the price when selling, the ratio of the biggest fruit is higher by 3% to 14% in the chestnut tree cultivation sites raising poultry. In order to investigate the effects of pest control through raising poultry, the ratio of harmful insect species to treatment sites was relatively low compared to control site. The appreciable result is that the control effect of larvae of the chestnut leaf-cut weevil was higher in the position where raising the poultry of 4 to 5 weeks compared to the position where raising the poultry of 12 weeks. This study found that the spread of poultry in the cultivation of chestnut trees increased the fruit quality by improving the size of fruits and lowering the dosage of harmful insect, chestnut leaf-cut weevil. Also, the eco-friendly chicken produced by these mountainous regions is expected to contribute to enhancing the incomes of the farmers by differentiating themselves from existing products.

Keywords: chestnut tree, environment-friendly, fruit quality, raising poultry

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Authors: Marlene Yu Lilin Wätzold, Wisnu Harto Adiwijoyo, Meike Wollni

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Land-use conversion from tropical forests to cash crop production in the form of monocultures has drastic consequences for biodiversity. Meanwhile, high dependence on cash crop production is often associated with a decrease in other food crop production, thereby affecting household dietary diversity. Additionally, deforestation rates have been found to reduce households’ dietary diversity, as forests often offer various food sources. Agroforestry systems are seen as a potential solution to improve local biodiversity as well as provide a range of provisioning ecosystem services, such as timber and other food crops. While a number of studies have analyzed the effects of agroforestry on biodiversity, as well as household livelihood indicators, little is understood between potential trade-offs or synergies between the two. This interdisciplinary study aims to fill this gap by assessing cacao agroforestry’s role in enhancing local bird diversity, as well as farm household dietary diversity. Additionally, we will take a landscape perspective and investigate in what ways the landscape composition, such as the proximity to forests and forest patches, are able to contribute to the local bird diversity, as well as households’ dietary diversity. Our study will take place in two agro-ecological zones in Ghana, based on household surveys of 500 cacao farm households. Using a subsample of 120 cacao plots, we will assess the degree of shade tree diversity and density using drone flights and a computer vision tree detection algorithm. Bird density and diversity will be assessed using sound recordings that will be kept in the cacao plots for 24 hours. Landscape compositions will be assessed via remote sensing images. The results of our study are of high importance as they will allow us to understand the effects of agroforestry and landscape composition in improving simultaneous ecosystem services.

Keywords: agroforestry, biodiversity, landscape composition, nutrition

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Authors: Yunwei Tang, Linhai Jing, Hui Li, Qingjie Liu, Xiuxia Li, Qi Yan, Haifeng Ding

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The giant panda (Ailuropoda melanoleuca) is an endangered species, mainly live in central China, where bamboos act as the main food source of wild giant pandas. Knowledge of spatial distribution of bamboos therefore becomes important for identifying the habitat of giant pandas. There have been ongoing studies for mapping bamboos and other tree species using remote sensing. WorldView-2 (WV-2) is the first high resolution commercial satellite with eight Multi-Spectral (MS) bands. Recent studies demonstrated that WV-2 imagery has a high potential in classification of tree species. The advanced classification techniques are important for utilising high spatial resolution imagery. It is generally agreed that object-based image analysis is a more desirable method than pixel-based analysis in processing high spatial resolution remotely sensed data. Classifiers that use spatial information combined with spectral information are known as contextual classifiers. It is suggested that contextual classifiers can achieve greater accuracy than non-contextual classifiers. Thus, spatial correlation can be incorporated into classifiers to improve classification results. The study area is located at Wuyipeng area in Wolong, Sichuan Province. The complex environment makes it difficult for information extraction since bamboos are sparsely distributed, mixed with brushes, and covered by other trees. Extensive fieldworks in Wuyingpeng were carried out twice. The first one was on 11th June, 2014, aiming at sampling feature locations for geometric correction and collecting training samples for classification. The second fieldwork was on 11th September, 2014, for the purposes of testing the classification results. In this study, spectral separability analysis was first performed to select appropriate MS bands for classification. Also, the reflectance analysis provided information for expanding sample points under the circumstance of knowing only a few. Then, a spatially weighted object-based k-nearest neighbour (k-NN) classifier was applied to the selected MS bands to identify seven land cover types (bamboo, conifer, broadleaf, mixed forest, brush, bare land, and shadow), accounting for spatial correlation within classes using geostatistical modelling. The spatially weighted k-NN method was compared with three alternatives: the traditional k-NN classifier, the Support Vector Machine (SVM) method and the Classification and Regression Tree (CART). Through field validation, it was proved that the classification result obtained using the spatially weighted k-NN method has the highest overall classification accuracy (77.61%) and Kappa coefficient (0.729); the producer’s accuracy and user’s accuracy achieve 81.25% and 95.12% for the bamboo class, respectively, also higher than the other methods. Photos of tree crowns were taken at sample locations using a fisheye camera, so the canopy density could be estimated. It is found that it is difficult to identify bamboo in the areas with a large canopy density (over 0.70); it is possible to extract bamboos in the areas with a median canopy density (from 0.2 to 0.7) and in a sparse forest (canopy density is less than 0.2). In summary, this study explores the ability of WV-2 imagery for bamboo extraction in a mountainous region in Sichuan. The study successfully identified the bamboo distribution, providing supporting knowledge for assessing the habitats of giant pandas.

Keywords: bamboo mapping, classification, geostatistics, k-NN, worldview-2

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Authors: Fahd Sabry Esmail, M. Badr Senousy, Mohamed Ragaie

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In recent years, there has been an explosion in the rate of using technology that help discovering the diseases. For example, DNA microarrays allow us for the first time to obtain a "global" view of the cell. It has great potential to provide accurate medical diagnosis, to help in finding the right treatment and cure for many diseases. Various classification algorithms can be applied on such micro-array datasets to devise methods that can predict the occurrence of Leukemia disease. In this study, we compared the classification accuracy and response time among eleven decision tree methods and six rule classifier methods using five performance criteria. The experiment results show that the performance of Random Tree is producing better result. Also it takes lowest time to build model in tree classifier. The classification rules algorithms such as nearest- neighbor-like algorithm (NNge) is the best algorithm due to the high accuracy and it takes lowest time to build model in classification.

Keywords: data mining, classification techniques, decision tree, classification rule, leukemia diseases, microarray data

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Authors: Todor Penchev, Dimitar Karastojanov, Ivan Altaparmakov

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For briquetting of metal chips are used hydraulic and mechanical presses. The density of the briquettes in this case is about 60% - 70 % on the density of solid metal. In this work are presented the results of experimental studies for briquetting of metal chips, by using a new technology for impact briquetting. The used chips are by Armco iron, steel, cast iron, copper, aluminum and brass. It has been found that: (i) in a controlled impact the density of the briquettes can be increases up to 30%; (ii) at the same specific impact energy Es (J/sm3) the density of the briquettes increases with increasing of the impact velocity; (iii), realization of the repeated impact leads to decrease of chips density, which can be explained by distribution of elastic waves in the briquette.

Keywords: briquetting, chips briquetting, impact briquetting, controlled impact

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Authors: Soon-Mi Park, Ihn Sook Jeong

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This retrospective study was aimed to identify risk factors of intravenous (IV) infiltration for hospitalized children. The participants were 1,174 children for test and 424 children for validation, who admitted to a general hospital, received peripheral intravenous injection therapy at least once and had complete records. Data were analyzed with frequency and percentage or mean and standard deviation were calculated, and decision tree analysis was used to screen for the most important risk factors for IV infiltration for hospitalized children. The decision tree analysis showed that the most important traditional risk factors for IV infiltration were the use of ampicillin/sulbactam, IV insertion site (lower extremities), and medical department (internal medicine) both in the test sample and validation sample. The correct classification was 92.2% in the test sample and 90.1% in the validation sample. More careful attention should be made to patients who are administered ampicillin/sulbactam, have IV site in lower extremities and have internal medical problems to prevent or detect infiltration occurrence.

Keywords: decision tree analysis, intravenous infiltration, child, validation

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Authors: Quynhan Tran, Hong Fan, Quockhanh Pham

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Automatic map generalization is a well-known problem in cartography. The development of map generalization research accompanied the development of cartography. The traditional map is plotted manually by cartographic experts. The paper studies none-scale automation generalization of resident polygons and house marker symbol, proposes methodology to evaluate the result maps based on minimal spanning tree. In this paper, the minimal spanning tree before and after map generalization is compared to evaluate whether the generalization result maintain the geographical distribution of features. The minimal spanning tree in vector format is firstly converted into a raster format and the grid size is 2mm (distance on the map). The statistical number of matching grid before and after map generalization and the ratio of overlapping grid to the total grids is calculated. Evaluation experiments are conduct to verify the results. Experiments show that this methodology can give an objective evaluation for the feature distribution and give specialist an hand while they evaluate result maps of none-scale automation generalization with their eyes.

Keywords: automatic cartography generalization, evaluation model, geographic feature distribution, minimal spanning tree

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Authors: Tadesse Desta Gidey, Gebregziabher Kahsay, Pooran Singh

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This work focuses on the theoretical investigation of the coexistence of superconductivity and Spin Density Wave (SDW)in Ferropnictide Ba₁₋ₓKₓFe₂As₂. By developing a model Hamiltonian for the system and by using quantum field theory Green’s function formalism, we have obtained mathematical expressions for superconducting transition temperature TC), spin density wave transition temperature (Tsdw), superconductivity order parameter (Sc), and spin density wave order parameter (sdw). By employing the experimental and theoretical values of the parameters in the obtained expressions, phase diagrams of superconducting transition temperature (TC) versus superconducting order parameter (Sc) and spin density wave transition temperature (Tsdw), versus spin density wave order parameter (sdw) have been plotted. By combining the two phase diagrams, we have demonstrated the possible coexistence of superconductivity and spin density wave (SDW) in ferropnictide Ba1−xKxFe2As2.

Keywords: Superconductivity, Spin density wave, Coexistence, Green function, Pnictides, Ba₁₋ₓKₓFe₂As₂

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Authors: Hong Li, Tingxian Li, Xudong Wang, Fengliang Zhao

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Unreliable flowering of chilling-required longan (Dimocarpus longan) due to increased air-temperatures have been the common concerns in the tropical areas. Our objectives were to assess the efficiency of chemicals in longan tree flowering and bearing using Growing Degree Days (GDD). The 2-year study was contacted in the tropical Haihan Island during 2012-2013. At pruning (August) the GDD values were started to count. The KClO3 treatments were applied to the root zones under the canopies at GDD 1300ºC while KH2PO4 rates were applied to the leaves at fruit setting at GDD 3000ºC and GDD 4000ºC. The results showed that total cumulative GDD was 6050ºC for longan. The GDD-guided KClO3 applications induced significant tree budding and flowering. The GDD-guided KH2PO4 applications stimulated higher leaf photosynthesis, carbonxylation efficiency, marketable fruit yield and quality (K+ and sugar) (P<0.05). It was concluded that the GDD-based model could efficiently support longan reliable flowering and bearing.

Keywords: canopy nutrition, flowering induction, growing degree days, longan, oxidant KClO3, tree physiology

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Authors: K. Umbleja, M. Ichino, H. Yaguchi

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In this paper, we propose a coloring method for multivariate data visualization by using parallel coordinates based on dissimilarity and tree structure information gathered during hierarchical clustering. The proposed method is an extension for proximity-based coloring that suffers from a few undesired side effects if hierarchical tree structure is not balanced tree. We describe the algorithm by assigning colors based on dissimilarity information, show the application of proposed method on three commonly used datasets, and compare the results with proximity-based coloring. We found our proposed method to be especially beneficial for symbolic data visualization where many individual objects have already been aggregated into a single symbolic object.

Keywords: data visualization, dissimilarity-based coloring, proximity-based coloring, symbolic data

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Authors: Houman Tamaddon, Mehrdad Behnia, Masud Behnia

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An accurate study of blood flow is associated with an accurate vascular pattern and geometrical properties of the organ of interest. Due to the complexity of vascular networks and poor accessibility in vivo, it is challenging to reconstruct the entire vasculature of any organ experimentally. The objective of this study is to introduce an innovative approach for the reconstruction of a full vascular tree from available morphometric data. Our method consists of implementing morphometric data on those parts of the vascular tree that are smaller than the resolution of medical imaging methods. This technique reconstructs the entire arterial tree down to the capillaries. Vessels greater than 2 mm are obtained from direct volume and surface analysis using contrast enhanced computed tomography (CT). Vessels smaller than 2mm are reconstructed from available morphometric and distensibility data and rearranged by applying Murray’s Laws. Implementation of morphometric data to reconstruct the branching pattern and applying Murray’s Laws to every vessel bifurcation simultaneously, lead to an accurate vascular tree reconstruction. The reconstruction algorithm generates full arterial tree topography down to the first capillary bifurcation. Geometry of each order of the vascular tree is generated separately to minimize the construction and simulation time. The node-to-node connectivity along with the diameter and length of every vessel segment is established and order numbers, according to the diameter-defined Strahler system, are assigned. During the simulation, we used the averaged flow rate for each order to predict the pressure drop and once the pressure drop is predicted, the flow rate is corrected to match the computed pressure drop for each vessel. The final results for 3 cardiac cycles is presented and compared to the clinical data.

Keywords: blood flow, morphometric data, vascular tree, Strahler ordering system

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Authors: J. K. Alhassan, B. Attah, S. Misra

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Human beings have the ability to make logical decisions. Although human decision - making is often optimal, it is insufficient when huge amount of data is to be classified. medical dataset is a vital ingredient used in predicting patients health condition. In other to have the best prediction, there calls for most suitable machine learning algorithms. This work compared the performance of Artificial Neural Network (ANN) and Decision Tree Algorithms (DTA) as regards to some performance metrics using diabetes data. The evaluations was done using weka software and found out that DTA performed better than ANN. Multilayer Perceptron (MLP) and Radial Basis Function (RBF) were the two algorithms used for ANN, while RegTree and LADTree algorithms were the DTA models used. The Root Mean Squared Error (RMSE) of MLP is 0.3913,that of RBF is 0.3625, that of RepTree is 0.3174 and that of LADTree is 0.3206 respectively.

Keywords: artificial neural network, classification, decision tree algorithms, diabetes mellitus

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Authors: Dairo Jose Hernandez Paez

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The quantum theory of atoms in molecules (QTAIM) allows us to obtain topological information on electronic density in quantum mechanical systems. The QTAIM starts by considering the electron density as a continuous mathematical object. On the other hand, the discretization of electron density is also a mathematical object, which, from discrete mathematics, would allow a new approach to its topological study. From this point of view, it is necessary to develop a series of steps that provide the theoretical support that guarantees its application. Some of the steps that we consider most important are mentioned below: (1) obtain good representations of the electron density through computational calculations, (2) design a methodology for the discretization of electron density, and construct the simplicial complex. (3) Make an analysis of the discrete vector field associating the simplicial complex. (4) Finally, in this research, we propose to use the discrete Morse theory as a mathematical tool to carry out studies of electron density topology.

Keywords: discrete mathematics, Discrete Morse theory, electronic density, computational calculations

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Authors: Aswandi Anas Husin, Cut Rizlani Kholibrina

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Harvesting camphor resin has been carried out since the beginning of civilization on the west coast of Sumatra. Oil or crystals that containing borneol are harvested from the camphor tree (Dryobalanops aromatica). Non-timber forest products are utilized for the manufacture of fragrances, antiseptics, anti-inflammatory, analgesic as well as effective for the treatment of blocked arteries. Based on exploration on the west coast of Sumatra, these endemic tree species were found remaining growing in groups on small spots in the lowlands to the hills. Some populations are found at an altitude of 700 meters above sea level in Kadabuhan, Jongkong and Sultan Daulat in Subulussalam district, Singkohor and Lake Paris in Aceh Singkil district, and Sirandorung and Manduamas in the north of Barus, Central Tapanuli district. These multi-purpose tree species was also identified as being able to adapt to the Singkil Peat Swamp. The decline in tree population has a direct impact on reducing their productivity. Conventionally, the crystals are harvested by cutting and splitting the stem into wooden blocks. In this way about 1.5-2.5 kg of crystals are obtained with various qualities. Camphor retrieval can also be done by making a notch on a standing tree trunk and collecting liquid resin (ombil) that is removed from the injured resin channel. Twigs and leaves also contain borneol. The aromatic content in this section opens opportunities for the supply of borneol through the distillation process. Vegetative propagation technology is needed to overcome the limitations of available seeds. This breeding strategy for vulnerable species starts with gathering genetic material from various provenances which are then used to support the provision of basic populations, breeding populations, multiplication populations and production populations for extensive development of camphor tree plantations

Keywords: camphor, conservation, natural borneol, productivity, vulnerable species

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Authors: Dharell B. Siano, Wendy C. Mateo, Victorino T. Taylan, Francisco D. Cuaresma

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Biofuel is one of the renewable energy sources adapted by the Philippine government in order to lessen the dependency on foreign fuel and to reduce carbon dioxide emissions. Rain tree pods were seen to be a promising source of bioethanol since it contains significant amount of fermentable sugars. The study was conducted to establish the complete procedure in processing rain tree pods for village level hydrous bioethanol production. Production processes were done for village level hydrous bioethanol production from collection, drying, storage, shredding, dilution, extraction, fermentation, and distillation. The feedstock was sundried, and moisture content was determined at a range of 20% to 26% prior to storage. Dilution ratio was 1:1.25 (1 kg of pods = 1.25 L of water) and after extraction process yielded a sugar concentration of 22 ⁰Bx to 24 ⁰Bx. The dilution period was three hours. After three hours of diluting the samples, the juice was extracted using extractor with a capacity of 64.10 L/hour. 150 L of rain tree pods juice was extracted and subjected to fermentation process using a village level anaerobic bioreactor. Fermentation with yeast (Saccharomyces cerevisiae) can fasten up the process, thus producing more ethanol at a shorter period of time; however, without yeast fermentation, it also produces ethanol at lower volume with slower fermentation process. Distillation of 150 L of fermented broth was done for six hours at 85 °C to 95 °C temperature (feedstock) and 74 °C to 95 °C temperature of the column head (vapor state of ethanol). The highest volume of ethanol recovered was established at with yeast fermentation at five-day duration with a value of 14.89 L and lowest actual ethanol content was found at without yeast fermentation at three-day duration having a value of 11.63 L. In general, the results suggested that rain tree pods had a very good potential as feedstock for bioethanol production. Fermentation of rain tree pods juice can be done with yeast and without yeast.

Keywords: fermentation, hydrous bioethanol, fermentation, rain tree pods, village level

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Authors: Shreya Pare, Parvin Akhter

Abstract:

Remotely sensing image classification becomes a very challenging task owing to the high dimensionality of hyperspectral images. The pixel-wise classification methods fail to take the spatial structure information of an image. Therefore, to improve the performance of classification, spatial information can be integrated into the classification process. In this paper, the multilevel thresholding algorithm based on a modified fuzzy entropy function is used to perform the segmentation of hyperspectral images. The fuzzy parameters of the MFE function have been optimized by using a new meta-heuristic algorithm based on the Tree-Search algorithm. The segmented image is classified by a large distribution machine (LDM) classifier. Experimental results are shown on a hyperspectral image dataset. The experimental outputs indicate that the proposed technique (MFE-TSA-LDM) achieves much higher classification accuracy for hyperspectral images when compared to state-of-art classification techniques. The proposed algorithm provides accurate segmentation and classification maps, thus becoming more suitable for image classification with large spatial structures.

Keywords: classification, hyperspectral images, large distribution margin, modified fuzzy entropy function, multilevel thresholding, tree search algorithm, hyperspectral image classification using tree search algorithm

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Authors: Yaojun Wang, Yaoqing Wang

Abstract:

Stock selection is an important decision-making problem. Many machine learning and data mining technologies are employed to build automatic stock-selection system. A profitable stock-selection system should consider the stock’s investment value and the market timing. In this paper, we present a hybrid system including both engage for stock selection. This system uses a case-based reasoning (CBR) model to execute the stock classification, uses a decision-tree model to help with market timing and stock selection. The experiments show that the performance of this hybrid system is better than that of other techniques regarding to the classification accuracy, the average return and the Sharpe ratio.

Keywords: case-based reasoning, decision tree, stock selection, machine learning

Procedia PDF Downloads 382

Authors: Abraha Hatsey, Nesibu Yahya, Abeje Eshete

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Ethiopian Orthodox Tewahido Church has a long tradition of conserving the Church vegetation and is an area treated as a refugee camp for many endangered indigenous tree species in Northern Ethiopia. Though around 36,000 churches exist in Ethiopia, only a few churches have been studied so far. Thus, this study assessed the land use land cover change of 3km buffer (1986-2018) and the woody species diversity and regeneration status of Tsimur St. Gebriel monastery in Tigray region, Northern Ethiopia. For vegetation study, systematic sampling was used with 100m spacing between plots and between transects. Plot size was 20m*20m for the main plot and 2 subplots (5m*5m each) for the regeneration study. Tree height, diameter at breast height(DBH) and crown area were measured in the main plot for all trees with DBH ≥ 5cm. In the subplots, all seedlings and saplings were counted with DBH < 5cm. The data was analyzed on excel and Pass biodiversity software for diversity and evenness analysis. The major land cover classes identified include bare land, farmland, forest, shrubland and wetland. The extents of forest and shrubland were declined considerably due to bare land and agricultural land expansions within the 3km buffer, indicating an increasing pressure on the church forest. Regarding the vegetation status, A total of 19 species belonging to 13 families were recorded in the monastery. The diversity (H’) and evenness recorded were 2.4 and 0.5, respectively. The tree density (DBH ≥ 5cm) was 336/ha and a crown cover of 65%. Olea europaea was the dominant (6.4m2/ha out of 10.5m2 total basal area) and a frequent species (100%) with good regeneration in the monastery. The rest of the species are less frequent and are mostly confined to water sources with good site conditions. Juniperus procera (overharvested) and the other indigenous species were with few trees left and with no/very poor regeneration status. The species having poor density, frequency and regeneration (Junperus procera, Nuxia congesta Fersen and Jasminium abyssinica) need prior conservation and enrichment planting. The indigenous species could also serve as a potential seed source for the reproduction and restoration of nearby degraded landscapes. The buffer study also demonstrated expansion of agriculture and bare land, which could be a threat to the forest of the isolated monastery. Hence, restoring the buffer zone is the only guarantee for the healthy existence of the church forest.

Keywords: church forests, regeneration, land use change, vegetation status

Procedia PDF Downloads 168

Authors: Wiwin Tyas Istikowati, Futoshi Ishiguri, Haruna Aisho, Budi Sutiya, Imam Wahyudi, Kazuya Iizuka, Shinso Yokota

Abstract:

The objective of this study was to investigate the anatomical characteristics of three native fast-growing species, terap (Artocarpus elasticus Reinw. ex Blume), medang (Neolitsea latifolia (Blume) S. Moore), and balik angin (Alphitonia excelsa (Fenzel) Reissek ex Benth) growing in the secondary forest in South Kalimantan, Indonesia for evaluating the possibility of tree breeding for wood quality. Cell lengths were investigated for 5 trees in each species at several different height positions (1.0, 3.0, 5.0, 7.0, 9.0, and 11.0 m above the ground). The mean values of fiber and vessel element lengths in terap, medang, and balik angin were 1.52 and 0.44, 1.16 and 0.53, and 1.02 and 0.49 mm, respectively. Fiber length in terap and balik angin gradually increased from pith to bark, whereas it increased up to 2 cm and then became nearly constant to the bark in medang. Vessel element length was almost constant from pith to bark in terap and balik angin, while slightly increased from pith to bark in medang. Fiber length in terap has a fluctuation pattern from ground level to top of the tree. It decreased up to 3 m above the ground, increased up to 5 m, and then decreased to the top of the tree. On the other hand, vessel element length slightly increased up to 5 m above the ground, and then decreased to the top of the tree. Both fiber and vessel element lengths in medang were almost constant from ground level to top of the tree, whereas decreased from ground level to top of the tree in balik angin. Significant difference at 1% level among trees was found in both fiber and vessel element length in both radial and longitudinal directions for terap and medang. Based on obtained results, it is concluded that the wood quality in fiber and vessel element lengths of terap and medang can be improved by tree breeding programs.

Keywords: anatomical properties, fiber length, vessel elements length, fast-growing species

Procedia PDF Downloads 300