Search results for: neem tree leave

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: 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: 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: Emmanuel Okechukwu Nwafor, Folake Olubunmi Akintayo, Denis Alcides Rezende

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Decision tree models are versatile and interpretable machine learning algorithms widely used for both classification and regression tasks, which can be related to cities, whether physical or digital. The aim of this research is to assess how well decision tree algorithms can predict trip purposes in Makurdi, Nigeria, while also exploring their connection to the strategic digital city initiative. The research methodology involves formalizing household demographic and trips information datasets obtained from extensive survey process. Modelling and Prediction were achieved using Python Programming Language and the evaluation metrics like R-squared and mean absolute error were used to assess the decision tree algorithm's performance. The results indicate that the model performed well, with accuracies of 84% and 68%, and low MAE values of 0.188 and 0.314, on training and validation data, respectively. This suggests the model can be relied upon for future prediction. The conclusion reiterates that This model will assist decision-makers, including urban planners, transportation engineers, government officials, and commuters, in making informed decisions on transportation planning and management within the framework of a strategic digital city. Its application will enhance the efficiency, sustainability, and overall quality of transportation services in Makurdi, Nigeria.

Keywords: decision tree algorithm, trip purpose, intelligent transport, strategic digital city, travel pattern, sustainable transport

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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

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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

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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

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

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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

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Authors: Federico Hahn Schlam, Fermín Martínez Solís

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Leaf-cutting ants (Atta cephalotes) forage from mango tree leaves and flowers to feed their colony. Farmers find it difficult to control ants due to the great quantity of trees grown in commercial orchards. In this article, IoT can support farmers for ant detection in real time, as production losses can be considered of 324 US per tree.A wireless sensor network, WSN, was developed to warn the farmer from ant presence in trees during a night. Mango trees were gathered into groups of 9 trees, where the central tree holds the master microcontroller, and the other eight trees presented slave microcontrollers (nodes). At each node, anemitter diode-photodiode unitdetects ants climbing up. A capacitor is chargedand discharged after being sampled every ten minutes. The system usesBLE (Bluetooth Low Energy) to communicate between the master microcontroller by BLE.When ants were detected the number of the tree was transmitted via LoRa from the masterto the producer smartphone to warn him. In this paper, BLE, LoRa, and energy consumption were studied under variable vegetation in the orchard. During 2018, 19 trees were attacked by ants, and ants fed 26.3% of flowers and 73.7% of leaves.

Keywords: BLE, atta cephalotes, LoRa, WSN-smartphone, energy consumption

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Authors: Shokoufeh Abrisham, Seyed Mahmoud Hossieni, Elham Pishbin

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In this paper, a hybrid method based on the fault tree analysis (FTA) and Bayesian networks (BNs) are employed to evaluate the team performance quality of advanced cardiac life support (ACLS) procedures in emergency department. According to American Heart Association (AHA) guidelines, a category relying on staff action leading to clinical incidents and also some discussions with emergency medicine experts, a fault tree model for ACLS procedure is obtained based on the human performance. The obtained FTA model is converted into BNs, and some different scenarios are defined to demonstrate the efficiency and flexibility of the presented model of BNs. Also, a sensitivity analysis is conducted to indicate the effects of team leader presence and uncertainty knowledge of experts on the quality of ACLS. The proposed model based on BNs shows that how the results of risk analysis can be closed to reality comparing to the obtained results based on only FTA in medical procedures.

Keywords: advanced cardiac life support, fault tree analysis, Bayesian belief networks, numan performance, healthcare systems

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Authors: Wided Khiari, Adel Karaa

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This study aims to establish a typology of Tunisian listed firms according to their corporate governance characteristics and disclosure quality. The paper uses disclosed scores to examine corporate governance practices of Tunisian listed firms. A content analysis of 46 Tunisian listed firms from 2001 to 2010 has been carried out and a disclosure index developed to determine the level of disclosure of the companies. The disclosure quality is appreciated through the quantity and also through the nature (type) of information disclosed. Applying the decision tree method, the obtained tree diagrams provide ways to know the characteristics of a particular firm regardless of its level of disclosure. Obtained results show that the characteristics of corporate governance to achieve good quality of disclosure are not unique for all firms. These structures are not necessarily all of the recommendations of best practices, but converge towards the best combination. Indeed, in practice, there are companies which have a good quality of disclosure, but are not well-governed. However, we hope that by improving their governance system their level of disclosure may be better. These findings show, in a general way, a convergence towards the standards of corporate governance with a few exceptions related to the specificity of Tunisian listed firms and show the need for the adoption of a code for each context. These findings shed the light on corporate governance features that enhance incentives for good disclosure. It allows identifying, for each firm and in any date, corporate governance determinants of disclosure quality. More specifically, and all being equal, obtained tree makes a rule of decision for the company to know the level of disclosure based on certain characteristics of the governance strategy adopted by the latter.

Keywords: corporate governance, disclosure, decision tree, economics

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Authors: Hemlata Chitte, Anita Chorey, V. M. Bhale, Bharti Tijare

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A field experiment was conducted during kharif season of 2013-14 at Agronomy research farm, Dr. PDKV, Akola, to study the productivity and nitrogen use efficiency in cotton using organic nitrification inhibitors. The experiment was laid out in factorial randomized block design with three replications each having nine treatment combinations comprising three fertilizer levels viz., 75% RDF (F1), 100% RDF (F2) and 125% RDF (F3) and three nitrification inhibitors viz., neem cake @ 300 kgha-1 (N1), karanj cake @ 300 kgha-1 (N2) and control (N3). The result showed that various growth attributes viz., plant height, number of functional leaves plant-1, monopodial and sympodial branches and leaf area plant-1(dm2) were maximum in fertilizer level 125% RDF over fertilizer level 75% RDF and which at par with 100% RDF. In case of yield attributes and yield, number of bolls per plant, Seed cotton yield and stalk yield kg ha-1 significantly higher in fertilizer level 125% RDF over 100% RDF and 75% RDF. Uptake of NPK kg ha-1 after harvest of cotton crop was significantly higher in fertilizer level 125% RDF over 100% RDF and 75% RDF. Significantly highest nitrogen use efficiency was recorded with fertilizer level 75 % RDF as compared to 100 % RDF and lowest nitrogen use efficiency was recorded with 125% RDF level. Amongst nitrification inhibitors, karanj cake @ 300 kg ha-1 increases potentiality of growth characters, yield attributes, uptake of NPK and NUE as compared to control and at par with neem cake @ 300 kgha-1. Interaction effect between fertilizer level and nitrification inhibitors were found to be non significant at all growth attributes and uptake of nutrient but was significant in respect of seed cotton yield.

Keywords: cotton, fertilizer level, nitrification inhibitor and nitrogen use efficiency, nutrient uptake

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Authors: S. Ghorbani, N. I. Polushin

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Vibration during machining process is crucial since it affects cutting tool, machine, and workpiece leading to a tool wear, tool breakage, and an unacceptable surface roughness. This paper applies a nonparametric statistical method, single decision tree (SDT), to identify factors affecting on vibration in machining process. Workpiece material (AISI 1045 Steel, AA2024 Aluminum alloy, A48-class30 Gray Cast Iron), cutting tool (conventional, cutting tool with holes in toolholder, cutting tool filled up with epoxy-granite), tool overhang (41-65 mm), spindle speed (630-1000 rpm), feed rate (0.05-0.075 mm/rev) and depth of cut (0.05-0.15 mm) were used as input variables, while vibration was the output parameter. It is concluded that workpiece material is the most important parameters for natural frequency followed by cutting tool and overhang.

Keywords: cutting condition, vibration, natural frequency, decision tree, CART algorithm

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Authors: Aremu Abdulmujeeb Babatunde

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Background: Low back pain was not only considered to be the most common reason for functional disability worldwide, but also estimated to have affected 90% of the universal population. This study aimed at determining the prevalence, consequences and socio-demographic factors associated with low back pain. Methods; A cross-sectional survey was employed and a total number of 150 self-structured questionnaire was distributed among healthcare workers and this was used to determine the prevalence of low back pain and work related absenteeism. Data was entered using Epi info soft-ware and analyzed using SPSS. Results; An overall response rate of 84% (n = 140) was achieved. The study established that majority (37%) of the respondents were in the age bracket of 20-39 years, 57% female (n=59) and 64% of them were married. the pint prevalence was 84%, 31% of the respondents took leave from work as a result of low back pain. There was high prevalence of sick leave among nursing staff 45.2%, Chi-square test shows that there was a statistically significant association between the respondents occupations and daily time spent during their work (P value 0.011 and 0.042) respectively. Socio-demographic factors like age, marital status and gender were not statistically significant at P<0.05. Conclusions; The medical and socio-professional consequences of low back pain among healthcare workers was as a result of their occupation designations and the daily time spent in carry out this occupations.

Keywords: low back pain, healthcare workers, prevalence, sick leave

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Authors: P. N. Guru, C. S. Patil

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The experiment was conducted during Kharif 2016 at Hingoni, Ahmednagar (dist.), Maharashtra (India) to evaluate the novel molecules of acaricides against mites in polyhouse capsicum. The study was planned with randomized block design (RBD) and included nine treatments replicated thrice with 30 m² each plot size. The crop (var. Bachata) was raised according to the standard package of practices except plant protection measures. The molecules viz., spiromesifen 22.9SC (95 gm a.i. ha⁻¹), fenpyroximate 5EC (15 gm a.i. ha⁻¹), hexythiazox 5.45EC (15 gm a.i. ha⁻¹), diafenthiuron 50WP (300 gm a.i. ha⁻¹), chlorfenapyr 10SC (75 gm a.i. ha⁻¹) were compared with a standard acaricide, dicofol 18.5EC (500 gm a.i. ha⁻¹) and biopesticides like Verticillium lecanii (2 g/l), Metarhizium anisopliae (2 g/l) and Neem oil 10,000ppm (2ml/l). In total three sprays were given after 30, 50 and 70 days after transplanting (DAT) at an interval of 20 days. The insecticidal solutions were prepared in water by diluting required concentration of chemical and applied using knapsack sprayer with hollow cone nozzle @ 500L of solution per hectare. The mites were counted per 4 cm² in three leaves from randomly selected five plants in each plot at 1 day before treatment (precount) and 1, 3, 5, 7, 10 and 15 days after treatment. The results revealed that fenpyroximate 5EC found best by recording significantly least mite population (2.72/4 cm² leaf area) followed by hexythiazox 5.45EC and spiromesifen 22.9SC (3.78 and 3.82 per 4 cm² leaf area, respectively) and followed by remaining treatments chlorfenapyr 10SC (4.13/4 cm² leaf area), diafenthiuron 50WP (4.32/4 cm² leaf area), and dicofol 18.5EC (4.48/4 cm² leaf area). Among the biopesticides tested Neem oil and Verticillium lecanii were found to be superior to Metarhizium anisopliae. Overall, newer molecules like fenpyroximate, hexythiazox, spiromesifen, diafenthiuron, and Chlorfenapyr can be used for the effective management of mites under polyhouse capsicum.

Keywords: acaricides, capsicum, mites, spiromesifen

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Authors: Intisar S. A. Elzein

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In Saudi Arabia parts of Nigella sativa, and Calotropis procera are commonly used in folk medicine for the treatment of asthma, bronchitis, cough, eczema and other diseases. The purpose of the study is to identify chemical constituents of Nigella sativa seed and Calotropis procera leave isolated by the bioassay guided fractionation process and find out their relevance to the alleged efficacy of the plant in treating asthma. The medicinal properties of both plants for asthma treatment referred to the rich abundance of thymoquinone and phytol compounds isolated from the essential oil of their seed and leave extracts, which they can form a part of molecules of vitamin K.

Keywords: asthma, Calotropis procera, chemical constituents, Nigella sativa, vitamin K

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Authors: Jae-Hyun Ro, Jong-Kwang Kim, Chang-Hee Kang, Hyoung-Kyu Song

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In multiple input multiple output-orthogonal frequency division multiplexing (MIMO-OFDM) systems, QR decomposition-M algorithm (QRD-M) has suboptimal error performance. However, the QRD-M has still high complexity due to many calculations at each layer in tree structure. To reduce the complexity of the QRD-M, proposed QRD-M modifies existing tree structure by eliminating unnecessary candidates at almost whole layers. The method of the elimination is discarding the candidates which have accumulated squared Euclidean distances larger than calculated threshold. The simulation results show that the proposed QRD-M has same bit error rate (BER) performance with lower complexity than the conventional QRD-M.

Keywords: complexity, MIMO-OFDM, QRD-M, squared Euclidean distance

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Authors: Ehsan Mehryaar

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The rate of penetration is (RoP) one of the vital factors in the cost and time of tunnel boring projects; therefore, predicting it can lead to a substantial increase in the efficiency of the project. RoP is heavily dependent geological properties of the project site and TBM properties. In this study, 151-point data from Queen’s water tunnel is collected, which includes unconfined compression strength, peak slope index, angle with weak planes, and distance between planes of weaknesses. Since the size of the data is small, it was observed that it is imbalanced. To solve that problem synthetic minority oversampling technique is utilized. The model based on the model tree is proposed, where each leaf consists of a support vector machine model. Proposed model performance is then compared to existing empirical equations in the literature.

Keywords: Model tree, SMOTE, rate of penetration, TBM(tunnel boring machine), SVM

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Authors: Olatunde Sunday Eludoyin, Charles Obiechina Olisa

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The study examined the spatial interactions between earthworm abundance (EA) and tree growth characteristics in ecological belts of Western Niger Delta, Nigeria. Eight 20m x 20m quadrat were delimited in the natural vegetation in each of the rainforest (RF), mangrove (M), fresh water swamp (FWS), and guinea savanna (GS) ecological belts to gather data about the tree species (TS) characteristics which included individual number of tree species (IN), diversity (Di), density (De) and richness (Ri). Three quadrats of 1m x 1m were delineated in each of the 20m x 20m quadrats to collect earthworm species the topsoil (0-15cm), and subsoil (15-30cm) and were taken to laboratory for further analysis. Descriptive statistics and inferential statistics were used for data analysis. Findings showed that a total of 19 earthworm species was found, with 58.5% individual species recorded in the topsoil and 41.5% recorded in the subsoil. The total population ofEudriliuseugeniae was predominantly highest in both topsoil (38.4%) and subsoil (27.1%). The total population of individual species of earthworm was least in GS in the topsoil (11.9%) and subsoil (8.4%). A total of 40 different species of TS was recorded, of which 55.5% were recorded in FWS, while RF was significantly highest in the species diversity(0.5971). Regression analysis revealed that Ri, IN, DBH, Di, and De of trees explained 65.9% of the variability of EA in the topsoil, while 46.9 % of the variability of earthworm abundance was explained by the floristic parameters in the subsoil.Similarly, correlation statistics revealed that in the topsoil, EA is positively and significantly correlated with Ri (r=0.35; p<0.05), IN (r=0.523; p<0.05) and De (r=0.469; p<0.05) while DBH was negatively and significantly correlated with earthworm abundance (r=-0.437; p<0.05). In the subsoil, only Ri and DBH correlated significantly with EA. The study concluded that EA in the study locations was highly influenced by tree growth species especially Ri, IN, DBH, Di, and De. The study recommended that the TSabundance should be improved in the study locations to ensure the survival of earthworms for ecosystem functions.

Keywords: interactions, earthworm abundance, tree growth, ecological zones, western niger delta

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Authors: Marinos Xagoraris, Elisavet Lazarou, Eleftherios Alissandrakis, Christos S. Pappas, Petros A. Tarantilis

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Strawberry tree (Arbutus unedo L.) and autumn heather (Erica manipuliflora Salisb.) are important beekeeping plants of Greece. Six monofloral honeys (four strawberry tree, two autumn heather) were analyzed by means of Solid Phase Micro-Extraction (SPME, 60 min, 60 oC) followed by Gas Chromatography coupled to Mass Spectrometry (GC-MS) for the purpose of assessing the botanical origin. A Divinylbenzene/Carboxen/Polydimethylsiloxane (DVB/CAR/PDMS) fiber was employed, and benzophenone was used as internal standard. The volatile compounds with higher concentration (μg/ g of honey expressed as benzophenone) from strawberry tree honey samples, were α-isophorone (2.50-8.12); 3,4,5-trimethyl-phenol (0.20-4.62); 2-hydroxy-isophorone (0.06-0.53); 4-oxoisophorone (0.38-0.46); and β-isophorone (0.02-0.43). Regarding heather honey samples, the most abundant compounds were 1-methoxy-4-propyl-benzene (1.22-1.40); p-anisaldehyde (0.97-1.28); p-anisic acid (0.35-0.58); 2-furaldehyde (0.52-0.57); and benzaldehyde (0.41-0.56). Norisoprenoids are potent floral markers for strawberry-tree honey. β-isophorone is found exclusively in the volatile fraction of this type of honey, while also α-isophorone, 4-oxoisophorone and 2-hydroxy-isophorone could be considered as additional marker compounds. The analysis of autumn heather honey revealed that phenolic compounds are the most abundant and p-anisaldehyde; 1-methoxy-4-propyl-benzene; and p-anisic acid could serve as potent marker compounds. In conclusion, marker compounds for the determination of the botanical origin for these honeys could be identified as several norisoprenoids and phenolic components were found exclusively or in higher concentrations compared to common Greek honey varieties.

Keywords: SPME/GC-MS, volatile compounds, heather honey, strawberry tree honey

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Authors: Sahari Japar, Rodney Jammy, M. A. Maleque

Abstract:

The fabrication of melaleuca alternifolia fibre reinforced thermoplastic starch composites was successfully done. This paper aims to show the effect of melaleuca alternifolia fibres on mechanical and physical properties of composites by using starch as a matrix. The fibres were extracted from three different part i.e. tea tree trunk (TTT), tea tree bunch (TTB) and tea tree leaf (TTL) and combined with tapioca starch by casting method. All composites showed superior mechanical properties in comparison to TS. The addition of 5% (v/v) fibres as a filler to TS led to the improvement in young’s modulus by 350% for TTB/TS, 282% for TTT/TS and 220% for TTL/TS. The tensile strength also increased to 34.39% for TTL/TS, 82.80% for TTB/TS and 203.18% for TTT/TS respectively. The trend can be correlated to the amount of cellulose in the fibres. For physical properties, it can be seen that, with the addition of fibres, the water absorption and swelling of composites decreased. The addition of melaleuca alternifolia fibre improved mechanical and physical properties of thermoplastic starch composites.

Keywords: melaleuca alternifolia, fibre, starch, mechanical, physical

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Authors: Saba Arif, Anam Nadeem, Roman Kalvin, Muzaffar Ali, Burhan Ali, Juntakan Taweekun

Abstract:

Globally transportation sector accounts for around 25% of energy demand and nearly 62% of oil consumed. Therefore, new energy sources are required to introduce for this huge demand replenishment of depleting conventional energy sources. Currently, biofuels such as Jatropha trees as an energy carrier for transportation sector are being utilized effectively round the globe. However, climate conditions at low altitudes with an average annual temperature above 20 degrees Celsius and rainfall of 300-1000mm are considered the most suitable environment for the efficient growth of Jatropha trees. The current study is providing a theoretical survey-based analysis to investigate the effect of rate of cultivation of jatropha trees on the reduction of fuel prices and its environmental benefits. The resulted study shows that jatropha tree’s 100 kg seeds give 80kg oil and the conversion process cost is very small as 890 PKR. Moreover, the extraction of oil from Jatropha tree is tax-free compared to other fuels. The analysis proved very essential for potential assessment of Jatropha regarding future energy fuel for transportation sector at global level. Additionally, it can be very beneficial for increment in the total amount of transportation fuel in Pakistan.

Keywords: jatropha tree, environmental impact, energy contents, theoretical survey

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Authors: Sahar Elkaee Behjati

Abstract:

Air pollution, particularly with dust, is one of the biggest issues Tehran is dealing with, and the city's green space which consists of trees has a critical role in absorption of it. The question this study aimed to investigate was which tree species the highest uptake capacity of the dust and carbon have suspended in the air. On this basis, 30 samples of trees from two different districts in Tehran were collected, and after washing and centrifuging, the samples were oven dried. The results of the study revealed that Ulmus minor had the highest amount of deposited dust in both districts. In addition, it was found that in Chamran district Ailanthus altissima and in Gandi district Ulmus minor has had the highest absorption of deposited carbon. Therefore, it could be argued that decision making on the selection of species for urban green spaces should take the above-mentioned parameters into account.

Keywords: dust, leaves, uptake total carbon, Tehran, tree species

Procedia PDF Downloads 138

Authors: Ying-Chu Chen

Abstract:

Waste to energy (WTE) technology is becoming increasingly important throughout the world. There are 24 WTE plants in operation in Taiwan that might be ranked the top in density (number of MSW incinerators/area) in the world. Many problems exist in WTE plants, such as low-quality construction, leakage of pipelines, irregular feedings, and lack of maintenance. These problems should be identified and analyzed for effective implementation and efficient operation of WTE plants. This research applies a fault tree analysis (FTA) to identify failures and evaluate their effects on the operation of WTE plants from a technical point of view. Five subsystems of a WTE plant were defined, including loading system, incineration system, effluent disposal system, structural components, and control system. This research results proved that FTA is suitable for WTE evaluation and is an effective analysis tool for technical evaluation in the field of WTE technology.

Keywords: delphi method, fault tree approach, municipal solid waste, waste to energy, WTE

Procedia PDF Downloads 564

Authors: John Narh

Abstract:

There is high rate of deforestation in Ghana due to agricultural expansion, illegal mining and illegal logging. While it is attempting to address the illegalities, Ghana has also initiated a reforestation program known as the Modified Taungya System (MTS). Within the MTS framework, farmers are allocated degraded forestland and provided with tree seedlings to practice agroforestry until the trees form canopy. Yet, the political, ecological and economic models that inform the selection of tree species, the motivations of participating farmers as well as the factors that accounts for differential access to the land and performance of farmers engaged in the program lie underexplored. Using a sequential explanatory mixed methods approach in five forest-fringe communities in the Eastern Region of Ghana, the study reveals that economic factors and Ghana’s commitment to international conventions on the environment underpin the selection of tree species for the MTS program. Social network and access to remittances play critical roles in having access to, and enhances poor farmers’ chances in the program respectively. Farmers are more motivated by the access to degraded forestland to cultivate food crops than having a share in the trees that they plant. As such, in communities where participating farmers are not informed about their benefit in the tree that they plant, the program is largely unsuccessful.

Keywords: translocality, deforestation, forest management, social network

Procedia PDF Downloads 96

Authors: Kritiyaporn Kunsook

Abstract:

Machine learning algorithms (MLAs) such us artificial neural networks (ANNs), decision tree, support vector machines (SVMs), Naïve Bayes, and ensemble classifier by voting are powerful data driven methods that are relatively less widely used in the mapping of technique of system, and thus have not been comparatively evaluated together thoroughly in this field. The performances of a series of MLAs, ANNs, decision tree, SVMs, Naïve Bayes, and ensemble classifier by voting in technique of hydroponic systems prospectively modeling are compared based on the accuracy of each model. Classification of hydroponic systems only covers the test samples from vegetables grown with Nutrient film technique (NFT) and Deep flow technique (DFT). The feature, which are the characteristics of vegetables compose harvesting height width, temperature, require light and color. The results indicate that the classification performance of the ANNs is 98%, decision tree is 98%, SVMs is 97.33%, Naïve Bayes is 96.67%, and ensemble classifier by voting is 98.96% algorithm respectively.

Keywords: artificial neural networks, decision tree, support vector machines, naïve Bayes, ensemble classifier by voting

Procedia PDF Downloads 371