Search results for: fruits trees

Authors: Erika Pigliapoco, Valerio Freschi, Alessandro Bogliolo

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This work presents a new phonetic transcription system based on a tree of hierarchical pronunciation rules expressed as context-specific grapheme-phoneme correspondences. The tree is automatically inferred from a phonetic dictionary by incrementally analyzing deeper context levels, eventually representing a minimum set of exhaustive rules that pronounce without errors all the words in the training dictionary and that can be applied to out-of-vocabulary words. The proposed approach improves upon existing rule-tree-based techniques in that it makes use of graphemes, rather than letters, as elementary orthographic units. A new linear algorithm for the segmentation of a word in graphemes is introduced to enable outof- vocabulary grapheme-based phonetic transcription. Exhaustive rule trees provide a canonical representation of the pronunciation rules of a language that can be used not only to pronounce out-of-vocabulary words, but also to analyze and compare the pronunciation rules inferred from different dictionaries. The proposed approach has been implemented in C and tested on Oxford British English and Basic English. Experimental results show that grapheme-based rule trees represent phonetically sound rules and provide better performance than letter-based rule trees.

Keywords: Automatic phonetic transcription, pronunciation rules, hierarchical tree inference.

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Authors: M. R. Gad El- Kareem, A. M. K. Abdel Aal, A. Y. Mohamed

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During 2011 and 2012 seasons, Zaghloul date palms received four sprays of silicon (Si) at 0.05 to 0.1% and selenium (Se) at 0.01 to 0.02%. Growth, nutritional status, yield as well as physical and chemical characteristics of the fruits in response to application of silicon and selenium were investigated. Single and combined applications of silicon at 0.05 to 0.1% and selenium at 0.01 to 0.02% was very effective in enhancing the leaf area, total chlorophylls, percentages of N, P and K in the leaves, yield, bunch weight as well as physical and chemical characteristics of the fruits in relative to the check treatment. Silicon was superior to selenium in this respect. Combined application was favorable than using each alone in this connection. Treating Zaghloul date palms four times with a mixture of silicon at 0.05% + selenium at 0.01% resulted in an economical yield and producing better fruit quality.

Keywords: Date Palms, Zaghloul, Silicon, Selenium, leaf area.

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Authors: Luay A. Fraiwan, Natheer Y. Khaswaneh, Khaldon Y. Lweesy

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Sleep stage scoring is the process of classifying the stage of the sleep in which the subject is in. Sleep is classified into two states based on the constellation of physiological parameters. The two states are the non-rapid eye movement (NREM) and the rapid eye movement (REM). The NREM sleep is also classified into four stages (1-4). These states and the state wakefulness are distinguished from each other based on the brain activity. In this work, a classification method for automated sleep stage scoring based on a single EEG recording using wavelet packet decomposition was implemented. Thirty two ploysomnographic recording from the MIT-BIH database were used for training and validation of the proposed method. A single EEG recording was extracted and smoothed using Savitzky-Golay filter. Wavelet packets decomposition up to the fourth level based on 20th order Daubechies filter was used to extract features from the EEG signal. A features vector of 54 features was formed. It was reduced to a size of 25 using the gain ratio method and fed into a classifier of regression trees. The regression trees were trained using 67% of the records available. The records for training were selected based on cross validation of the records. The remaining of the records was used for testing the classifier. The overall correct rate of the proposed method was found to be around 75%, which is acceptable compared to the techniques in the literature.

Keywords: Features selection, regression trees, sleep stagescoring, wavelet packets.

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Authors: Parvinder Singh Sandhu, Sumeet Kaur Sehra, Karmjit Kaur

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Phylogenetic tree is a graphical representation of the evolutionary relationship among three or more genes or organisms. These trees show relatedness of data sets, species or genes divergence time and nature of their common ancestors. Quality of a phylogenetic tree requires parsimony criterion. Various approaches have been proposed for constructing most parsimonious trees. This paper is concerned about calculating and optimizing the changes of state that are needed called Small Parsimony Algorithms. This paper has proposed enhanced small parsimony algorithm to give better score based on number of evolutionary changes needed to produce the observed sequence changes tree and also give the ancestor of the given input.

Keywords: Phylogenetic Analysis, Small Parsimony, EnhancedFitch Algorithm, Enhanced Sakoff Algorithm.

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Authors: İsmail Hakkı Kalyoncu, Nilda Ersoy, Ayşe Yalcın Elidemir, Cansu Dolek

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Some physico-chemical characteristics and mineral composition of 'Karayemis' (Prunus laurocerasus L.) fruits which grown naturally in Norteast Turkey was studied. 28 minerals ( Al, Mg, B, Mn, Co, Na, Ca, Ni, Cd, P, Cr, Pb, Cu, S, Fe, Zn, K, Sr, Li, As, V, Ag, Ba, Br, Ga, In, Se, Ti) were analyzed and 19 minerals were present at ascertainable levels. Karayemis fruit was richest in potassium (7938.711 ppm), magnesium (1242.186 ppm) and calcium (1158.853 ppm). And some physico-chemical characteristics of Karayemis fruit was investigated. Fruit length, fruit width, fruit thickness, fruit weight, total soluble solids, colour, protein, crude ash, crude fiber, crude oil values were determined as 2.334 cm, 1.884 cm, 2.112 cm, 5.35 g, 20.1 %, S99M99Y99, 0.29 %, 0.22 %, 6.63 % and 0.001 %, respectively. The seed of fruit mean weight, length, width and thickness were found to be 0.41 g, 1.303 cm, 0.921 cm and 0.803, respectively.

Keywords: Prunus laurocerasus L., physico-chemical properties, nutritional properties.

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Authors: Frank Emmert-Streib, Matthias Dehmer, Jing Liu, Max Muhlhauser

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The major objective of this paper is to introduce a new method to select genes from DNA microarray data. As criterion to select genes we suggest to measure the local changes in the correlation graph of each gene and to select those genes whose local changes are largest. More precisely, we calculate the correlation networks from DNA microarray data of cervical cancer whereas each network represents a tissue of a certain tumor stage and each node in the network represents a gene. From these networks we extract one tree for each gene by a local decomposition of the correlation network. The interpretation of a tree is that it represents the n-nearest neighbor genes on the n-th level of a tree, measured by the Dijkstra distance, and, hence, gives the local embedding of a gene within the correlation network. For the obtained trees we measure the pairwise similarity between trees rooted by the same gene from normal to cancerous tissues. This evaluates the modification of the tree topology due to tumor progression. Finally, we rank the obtained similarity values from all tissue comparisons and select the top ranked genes. For these genes the local neighborhood in the correlation networks changes most between normal and cancerous tissues. As a result we find that the top ranked genes are candidates suspected to be involved in tumor growth. This indicates that our method captures essential information from the underlying DNA microarray data of cervical cancer.

Keywords: Graph similarity, generalized trees, graph alignment, DNA microarray data, cervical cancer.

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Authors: M. Grabowski, K. Macnar, J. Skrzyński

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Huge losses in apple production are caused by pathogens that cannot be seen shortly after harvest. After-harvest thermotherapy treatments can considerably improve control of storage diseases on apples and become an alternative to chemical pesticides. In the years 2010-2012 carried out research in this area. Apples of 'Topaz' cultivar were harvested at optimal maturity time for long storage and subject to water bath treatment at 45, 50, 52, 55°C for 60, 120, 180 and 240 seconds. The control was untreated fruits. After 12 and 24 weeks and during so called simulated trade turnover the fruits were checked for their condition and the originators of diseases were determined by using the standard phytopathological methods. The most common originator of 'Topaz' apple infection during storage were the fungi of genus Gloeosporium. In this paper it was proven that for effective protection of 'Topaz' apples against diseases, thermotherapy by using water treatments at temperature range of 50-52°C is quite sufficient.

Keywords: apple storage diseases, prolonged fruit storage, 'Topaz' apples, thermotherapeutic treatments.

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Authors: Langa Hendrick Musawenkosi, Twala Bhekisipho

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The success or failure of students is a concern for every academic institution, college, university, governments and students themselves. Several approaches have been researched to address this concern. In this paper, a view is held that when a student enters a university or college or an academic institution, he or she enters an academic environment. The academic environment is unique concept used to develop the solution for making predictions effectively. This paper presents a model to determine the propensity of a student to succeed or fail in the French South African Schneider Electric Education Center (FSASEC) at the Vaal University of Technology (VUT). The Decision Tree algorithm is used to implement the model at FSASEC.

Keywords: Academic environment model, decision trees, FSASEC, K-nearest neighbor, machine learning, popularity index, support vector machine.

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Authors: S. Housseno, A. Simonet, M. Simonet

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Semantic query optimization consists in restricting the search space in order to reduce the set of objects of interest for a query. This paper presents an indexing method based on UB-trees and a static analysis of the constraints associated to the views of the database and to any constraint expressed on attributes. The result of the static analysis is a partitioning of the object space into disjoint blocks. Through Space Filling Curve (SFC) techniques, each fragment (block) of the partition is assigned a unique identifier, enabling the efficient indexing of fragments by UB-trees. The search space corresponding to a range query is restricted to a subset of the blocks of the partition. This approach has been developed in the context of a KB-DBMS but it can be applied to any relational system.

Keywords: Index, Range query, UB-tree, Space Filling Curve, Query optimization, Views, Database, Integrity Constraint, Classification.

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Authors: Indradip Banerjee, Souvik Bhattacharyya, Gautam Sanyal

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‘Steganalysis’ is one of the challenging and attractive interests for the researchers with the development of information hiding techniques. It is the procedure to detect the hidden information from the stego created by known steganographic algorithm. In this paper, a novel feature based image steganalysis technique is proposed. Various statistical moments have been used along with some similarity metric. The proposed steganalysis technique has been designed based on transformation in four wavelet domains, which include Haar, Daubechies, Symlets and Biorthogonal. Each domain is being subjected to various classifiers, namely K-nearest-neighbor, K* Classifier, Locally weighted learning, Naive Bayes classifier, Neural networks, Decision trees and Support vector machines. The experiments are performed on a large set of pictures which are available freely in image database. The system also predicts the different message length definitions.

Keywords: Steganalysis, Moments, Wavelet Domain, KNN, K*, LWL, Naive Bayes Classifier, Neural networks, Decision trees, SVM.

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Authors: Sahar Elkaee Behjati

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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.

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Authors: N. Affi, A. El Fadl, M. El Otmani, M.C. Benismail, L.M. Idrissi

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The object of the present research was to assess the effects of partial rootzone drying (PRD) on tomato growth, productivity, biomass allocation and water use efficiency (WUE). Plants were grown under greenhouse, on a sand substrate. Three treatments were applied: a control that was fully and conventionally irrigated, PRD-70 and PRD-50 in which, respectively, 70% and 50% of water requirements were supplied using PRD. Alternation of irrigation between the two root halves took place each three days. The Control produces the highest total yield (252tons/ha). In terms of fruit number, PRD-50 showed 23% and 16% less fruits than PRD-70 and control, respectively. Fruit size was affected by treatment with PRD-50 treatment producing 66% and 53% more class 3 fruits than, control and PRD-70, respectively. For plant growth, the difference was not significant when comparing control to PRD-70 but was significant when comparing PRD-70 and control to PRD-50. No effect was on total biomass but root biomass was higher for stressed plants compared to control. WUE was 66% and 27% higher for PRD-50 and PRD-70 respectively compared to control.

Keywords: Biomass, growth, partial rootzone drying, water use efficiency yield.

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Authors: Prakash G L, Thejaswini M, S H Manjula, K R Venugopal, L M Patnaik

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Computing and maintaining network structures for efficient data aggregation incurs high overhead for dynamic events where the set of nodes sensing an event changes with time. Moreover, structured approaches are sensitive to the waiting time that is used by nodes to wait for packets from their children before forwarding the packet to the sink. An optimal routing and data aggregation scheme for wireless sensor networks is proposed in this paper. We propose Tree on DAG (ToD), a semistructured approach that uses Dynamic Forwarding on an implicitly constructed structure composed of multiple shortest path trees to support network scalability. The key principle behind ToD is that adjacent nodes in a graph will have low stretch in one of these trees in ToD, thus resulting in early aggregation of packets. Based on simulations on a 2,000-node Mica2- based network, we conclude that efficient aggregation in large-scale networks can be achieved by our semistructured approach.

Keywords: Aggregation, Packet Merging, Query Processing.

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Authors: Taimur Qureshi, Djamel A Zighed

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Many supervised induction algorithms require discrete data, even while real data often comes in a discrete and continuous formats. Quality discretization of continuous attributes is an important problem that has effects on speed, accuracy and understandability of the induction models. Usually, discretization and other types of statistical processes are applied to subsets of the population as the entire population is practically inaccessible. For this reason we argue that the discretization performed on a sample of the population is only an estimate of the entire population. Most of the existing discretization methods, partition the attribute range into two or several intervals using a single or a set of cut points. In this paper, we introduce a technique by using resampling (such as bootstrap) to generate a set of candidate discretization points and thus, improving the discretization quality by providing a better estimation towards the entire population. Thus, the goal of this paper is to observe whether the resampling technique can lead to better discretization points, which opens up a new paradigm to construction of soft decision trees.

Keywords: Bootstrap, discretization, resampling, soft decision trees.

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Authors: Siti Khairunniza-Bejo, Yusnida Yusoff, Nik Salwani Nik Yusoff, Idris Abu Seman, Mohamad Izzuddin Anuar

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Most of the oil palm plantations have been threatened by Basal Stem Rot (BSR) disease which causes serious economic impact. This study was conducted to identify the healthy and BSRinfected oil palm tree using thirteen color indices. Multispectral and thermal camera was used to capture 216 images of the leaves taken from frond number 1, 9 and 17. Indices of normalized difference vegetation index (NDVI), red (R), green (G), blue (B), near infrared (NIR), green – blue (GB), green/blue (G/B), green – red (GR), green/red (G/R), hue (H), saturation (S), intensity (I) and thermal index (T) were used. From this study, it can be concluded that G index taken from frond number 9 is the best index to differentiate between the healthy and BSR-infected oil palm trees. It not only gave high value of correlation coefficient (R=-0.962), but also high value of separation between healthy and BSR-infected oil palm tree. Furthermore, power and S model developed using G index gave the highest R2 value which is 0.985.

Keywords: Oil palm, image processing, disease, leaves.

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Authors: Jürgen Roßmann, Gerrit Alves

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In today-s world, the efficient utilization of wood resources comes more and more to the mind of forest owners. It is a very complex challenge to ensure an efficient harvest of the wood resources. This is one of the scopes the project “Virtual Forest II" addresses. Its core is a database with data about forests containing approximately 260 million trees located in North Rhine-Westphalia (NRW). Based on this data, tree growth simulations and wood mobilization simulations can be conducted. This paper focuses on the latter. It describes a discrete-event-simulation with an attached 3-D real time visualization which simulates timber harvest using trees from the database with different crop resources. This simulation can be displayed in 3-D to show the progress of the wood crop. All the data gathered during the simulation is presented as a detailed summary afterwards. This summary includes cost-benefit calculations and can be compared to those of previous runs to optimize the financial outcome of the timber harvest by exchanging crop resources or modifying their parameters.

Keywords: Timber harvest, simulation, 3-D, optimization.

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Authors: Lai Hoe Ang, Lai Kuen Tang, Wai Mun Ho, Ting Fui Hui, Gary W. Theseira

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Contamination of heavy metals in tin tailings has caused an interest in the scientific approach of their remediation. One of the approaches is through phytoremediation, which is using tree species to extract the heavy metals from the contaminated soils. Tin tailings comprise of slime and sand tailings. This paper reports only on the finding of the four timber species namely Acacia mangium, Hopea odorata, Intsia palembanica and Swietenia macrophylla on the removal of cadmium (Cd) and lead (Pb) from the slime tailings. The methods employed for sampling and soil analysis are established methods. Six trees of each species were randomly selected from a 0.25 ha plot for extraction and determination of their heavy metals. The soil samples were systematically collected according to 5 x 5 m grid from each plot. Results showed that the concentration of heavy metals in soils and trees varied according to species. Higher concentration of heavy metals was found in the stem than the primary roots of all the species. A. Mangium accumulated the highest total amount of Pb per hectare basis.

Keywords: Cd, Pb, Phytoremediation of slimetailings, timber species.

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Authors: Dejan Prvulović, Djordje Malenčić, Milan Popović, Mirjana Ljubojević, Vladislav Ognjanov

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Sweet cherries (Prunus avium L.) contain various phenolic compounds which contribute to total antioxidant activity. Total polyphenols, tannins, flavonoids and anthocyanins, and antioxidant capacity in a fruits of a number of selected sweet cherry genotypes were investigated. Total polyphenols content ranged from 4.12 to 8.34 mg gallic acid equivantents/g dry fruit weight and total tannins content ranged from 0.19 to 1.95 mg gallic acid equivalent/g dry fruit weight. Total flavonoids were within the range 0.42-1.56 mg of rutin equivalents/g dry fruit weight and total anthocyanins content were between 0.35 and 0.69 mg cyanidin 3-glucoside equivalent/ g dry fruit weight. Although sweet cherry fruits are a significant source of different phenolic compounds, antioxidant activity of sweet cherries is not related only with the total polyphenolics, flavonoids or anthocyanins.

Keywords: antioxidant activity, polyphenols, Prunus avium L., sweet cherry

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Authors: F. Z. Yekeler, H. Ozyurek, C. E. Tamer

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Fruits and vegetables are the essentials of a healthy diet, mainly because of their antioxidant properties contributing to disease blockage especially for some certain types of cancer. Being a favourite fruit, citrus are produced for economic and commercial purposes worldwide. Particularly, lemon fruit (Citrus limon L.), has an important place in export products of Turkey. Lemon has a great importance on human nutrition with regard to being a source of nutrients, flavonoids, vitamin C and minerals. It is used for food flavouring and pickling and also processed for lemonade. By processing citrus into fruit juices, consumption may increase and also become easier. Like many fruits and vegetables lemons are cheap and abundant during harvesting period, while they are quite expensive in other seasons. Lemon juice and concentrate production allows consumers to get benefits from lemon fruit in any time of the year. Lemonade is getting in to the focus of consumers’ attention preferring non-carbonated drinks. The demand of healthy, convenient functional foods affects consumer trends through innovative products. For this reason, lemonade could be enriched with different natural herb extracts such as ginger (Zingiber officinale), linden (Tilia cordata), and mint (Mentha piperita).

Keywords: Lemonade, herb extracts, antioxidant activity.

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Authors: K. Praraththajariya

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The main purpose of this research was to study how to communicate the identity of the Amphawa district, Samut Songkram province for sustainable tourism. The qualitative data was collected through studying related materials, exploring the area, in-depth interviews with three groups of people: three directly responsible officers who were key informants of the district, twenty foreign tourists and five Thai tourist guides. A content analysis was used to analyze the qualitative data. The two main findings of the study were as follows: 1. The identity of the Amphawa District, Samut Songkram province is the area controlled by Amphawa sub district (submunicipality). The working unit which runs and looks after Amphawa sub district administration is known as the Amphawa mayor. This establishment was built to be a resort for normal people and tourists visiting the Amphawa district near the Maekong River consisting of rest accommodations. Along the river there is a restaurant where food and drinks are served, rich mangrove forests, a learning center, fireflies and cork trees. The Amphawa district was built to honor and commemorate King Rama II and is where the greatest number of fireflies and cork trees can be seen in Thailand from May to October each year. 2. The communication of the identity of Amphawa District, Samut Songkram Province which the researcher could find and design to present in English materials can be summed up in 5 items: 1) The history of the Amphawa District, Samut Songkram province 2) The history of King Rama II Memorial Park 3) The identity of Amphawa Floating Market 4) The Learning center of Ecosystem: Fireflies and Cork Trees 5) How to keep Amphawa District, Samut Songkram Province for sustainable tourism.

Keywords: Foreigner tourists, signified, semiotics, sustainable tourism.

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Authors: Çiğdem Bakır, Mecit Yüzkat

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With the increasing emphasis on water quality worldwide, the search for and expanding the market for new and intelligent monitoring systems has increased. The current method is the laboratory process, where samples are taken from bodies of water, and tests are carried out in laboratories. This method is time-consuming, a waste of manpower and uneconomical. To solve this problem, we used machine learning methods to detect water pollution in our study. We created decision trees with the Orange3 software used in the study and tried to determine all the factors that cause water pollution. An automatic prediction model based on water quality was developed by taking many model inputs such as water temperature, pH, transparency, conductivity, dissolved oxygen, and ammonia nitrogen with machine learning methods. The proposed approach consists of three stages: Preprocessing of the data used, feature detection and classification. We tried to determine the success of our study with different accuracy metrics and the results were presented comparatively. In addition, we achieved approximately 98% success with the decision tree.

Keywords: Decision tree, water quality, water pollution, machine learning.

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Authors: Deepak K. Semwal, Ruchi B. Semwal, Aijaz Ahmad, Guy P. Kamatou, Alvaro M. Viljoen

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Kigelia africana (Lam.) Benth. (Bignoniaceae) is a reputed traditional remedy for various human ailments such as skin diseases, microbial infections, melanoma, stomach troubles, metabolic disorders, malaria and general pains. In spite of the fruit being widely used for purposes related to its antibacterial and antifungal properties, the chemical constituents associated with the activity have not been fully identified. To elucidate the active principles, we evaluated the antimicrobial activity of fruit extracts and purified fractions against Staphylococcus aureus, Enterococcus faecalis, Moraxella catarrhalis, Escherichia coli, Candida albicans and Candida tropicalis. Shade-dried fruits were powdered and extracted with hydroalcoholic (1:1) mixture by soaking at room temperature for 72 h. The crude extract was further fractionated by column chromatography, with successive elution using hexane, dichloromethane, ethyl acetate, acetone and methanol. The dichloromethane and ethyl acetate fractions were combined and subjected to column chromatography to furnish a wax and oil from the eluates of 20% and 40% ethyl acetate in hexane, respectively. The GC-MS and GC×GC-MS results revealed that linoleic acid, linolenic acid, palmitic acid, arachidic acid and stearic acid were the major constituents in both oil and wax. The crude hydroalcoholic extract exhibited the strongest activity with MICs of 0.125-0.5 mg/mL, followed by the ethyl acetate (MICs = 0.125-1.0 mg/mL), dichloromethane (MICs = 0.250-2.0 mg/mL), hexane (MICs = 0.25- 2.0 mg/mL), acetone (MICs = 0.5-2.0 mg/mL) and methanol (MICs = 1.0-2.0 mg/mL), whereas the wax (MICs = 2.0-4.0 mg/mL) and oil (MICs = 4.0-8.0 mg/mL) showed poor activity. The study concludes that synergistic interactions of chemical constituents could be responsible for the antimicrobial activity of K. africana fruits, which needs a more holistic approach to understand the mechanism of its antimicrobial activity.

Keywords: Kigelia Africana, traditional medicine, antimicrobial activity, Candida albicans, palmitic acid, synergistic interaction.

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Authors: Zainoldin, K.H., Baba, A.S.

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Yogurt is a coagulated milk product obtained from the lactic acid fermentation by the action of Lactobacillus bulgaricus and Streptococcus thermophilus. The additions of fruits into milk may enhance the taste and the therapeutical values of milk products. However fruits also may change the fermentation behaviour. In this present study, the changes in physicochemical, the peptide concentration, total phenolics content and the antioxidant potential of yogurt upon the addition of Hylocereus polyrhizus and Hylocereus undatus (white and red dragon fruit) were investigated. Fruits enriched yogurt (10%, 20%, 30% w/w) were prepared and the pH, TTA, syneresis measurement, peptide concentration, total phenolics content and DPPH antioxidant inhibition percentage were determined. Milk fermentation rate was enhanced in red dragon fruit yogurt for all doses (-0.3606 - -0.4126 pH/h) while only white dragon fruit yogurt with 20% and 30% (w/w) composition showed increment in fermentation rate (-0.3471 - -0.3609 pH/h) compared to plain yogurt (-0.3369pH/h). All dragon fruit enriched yogurts generally showed lower pH readings (pH 3.95 - 4.03) compared to plain yogurt (pH 4.05). Both fruit yogurts showed a higher lactic acid percentage (1.14-1.23%) compared to plain yogurt (1.08%). Significantly higher syneresis percentage (57.19 - 70.32%) compared to plain yogurt (52.93%) were seen in all fruit enriched yogurts. The antioxidant activity of plain yogurt (19.16%) was enhanced by the presence of white and red dragon fruit (24.97- 45.74%). All fruit enriched yogurt showed an increment in total phenolic content (36.44 - 64.43mg/ml) compared to plain yogurt (20.25mg/ml). However, the addition of white and red dragon fruit did not enhance the proteolysis of milk during fermentation. Therefore, it could be concluded that the addition of white and red dragon fruit into yogurt enhanced the milk fermentation rate, lactic acid content, syneresis percentage, antioxidant activity, and total phenolics content in yogurt.

Keywords: Antioxidant activity, Hylocereus polyrhizus, Hylocereus undatus, yogurt

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Authors: S. M. Feroz, K. Yoshimura, A. Hagihara

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The forest stand consisted of four layers. The species composition between the third and the bottom layers was almost similar, whereas it was almost exclusive between the top and the lower three layers. The values of Shannon-s index H' and Pielou-s index J ' tended to increase from the bottom layer upward, except for H' -value of the top layer. The values of H' and J ' were 4.21 bit and 0.73, respectively, for the total stand. High woody species diversity of the forest depended on large trees in the upper layers, which trend was different from a subtropical evergreen broadleaf forest grown in silicate habitat in the northern part of Okinawa Island. The spatial distribution of trees was overlapped between the third and the bottom layers, whereas it was independent or slightly exclusive between the top and the lower three layers. Mean tree weight of each layer decreased from the top toward the bottom layer, whereas the corresponding tree density increased from the top downward. This relationship was analogous to the process of self-thinning plant populations.

Keywords: Canopy multi-layering, limestone habitat, mean tree weight-density relationship, species diversity, subtropical forest.

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Authors: Hanife Genç

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The olive fruit fly, Bactrocera oleae (Rossi), is an economically important and endemic pest in olive (Oleae europae) orchards in Turkey. The aim of this study was to determine olive fruit fly infestation in different olive cultivars in the laboratory. Olive fly infested fruits were collected in Çanakkale province to establish wild fly population. After having reproductive olive fly colonies, 14 olive cultivars were tested in the controlled laboratory conditions, at 23±2 °C, 65% RH and 16:8 h (light: dark) photoperiod. The olive samples from 14 different olive cultivars were collected in October 2015, in Campus of Dardanos, Çanakkale Onsekiz Mart University. Observations were carried out detecting some biological parameters such as the number of oviposition stings, active infestation, total infestation, the number of pupae and the adult emergence. The results indicated that oviposition stings were not associated with pupal yield. A few pupae were found within olive fruits which were not able to exit. Screening of the varieties suggested that less susceptible cultivar to olive fruit fly attacks was Arbequin while Gemlik-2M 2/3 showed significant susceptibility. Ovipositional preference of olive fly females and the success of larval development in different olive varieties are crucial for establishing new olive orchards to prevent high olive fruit fly infestation.

Keywords: Infestation, olive fruit fly, olive cultivars, oviposition sting.

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Authors: Omer Nebil Yaveroglu, Tolga Can

Abstract:

In this study, a high accuracy protein-protein interaction prediction method is developed. The importance of the proposed method is that it only uses sequence information of proteins while predicting interaction. The method extracts phylogenetic profiles of proteins by using their sequence information. Combining the phylogenetic profiles of two proteins by checking existence of homologs in different species and fitting this combined profile into a statistical model, it is possible to make predictions about the interaction status of two proteins. For this purpose, we apply a collection of pattern recognition techniques on the dataset of combined phylogenetic profiles of protein pairs. Support Vector Machines, Feature Extraction using ReliefF, Naive Bayes Classification, K-Nearest Neighborhood Classification, Decision Trees, and Random Forest Classification are the methods we applied for finding the classification method that best predicts the interaction status of protein pairs. Random Forest Classification outperformed all other methods with a prediction accuracy of 76.93%

Keywords: Protein Interaction Prediction, Phylogenetic Profile, SVM , ReliefF, Decision Trees, Random Forest Classification

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Authors: Miguel García-Ferrús, Ana González, María A. Ferrús

Abstract:

The most demanded organic foods worldwide are those that are consumed fresh, such as fruits and vegetables. However, there is a knowledge gap about some aspects of organic food microbiological quality and safety. Organic fruits and vegetables are more exposed to pathogenic microorganisms due to surface contact with natural fertilizers such as animal manure, wastes and vermicompost used during farming. Therefore, the objective of this work was to study the contamination of organic fresh green leafy vegetables by two emergent pathogens, Arcobacter spp. and Helicobacter pylori. For this purpose, a total of 24 vegetable samples, 13 lettuce and 11 spinach were acquired from 10 different ecological supermarkets and greengroceries and analyzed by culture and PCR. Arcobacter spp. was detected in five samples (20%) by PCR, four spinach and one lettuce. One spinach sample was found to be also positive by culture. For H. pylori, the H. pylori VacA gene-specific band was detected in 12 vegetable samples (50%), 10 lettuces and two spinach. Isolation in the selective medium did not yield any positive result, possibly because of low contamination levels together with the presence of the organism in its viable but non-culturable form. Results showed significant levels of H. pylori and Arcobacter contamination in organic vegetables that are generally consumed raw, which seems to confirm that these foods can act as transmission vehicles to humans.

Keywords: Arcobacter spp., Helicobacter pylori, organic vegetables, Polymerase Chain Reaction, PCR.

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Authors: Ameur Abdelkader, Abed Bouarfa Hafida

Abstract:

Since its inception, predictive analysis has revolutionized the IT industry through its robustness and decision-making facilities. It involves the application of a set of data processing techniques and algorithms in order to create predictive models. Its principle is based on finding relationships between explanatory variables and the predicted variables. Past occurrences are exploited to predict and to derive the unknown outcome. With the advent of big data, many studies have suggested the use of predictive analytics in order to process and analyze big data. Nevertheless, they have been curbed by the limits of classical methods of predictive analysis in case of a large amount of data. In fact, because of their volumes, their nature (semi or unstructured) and their variety, it is impossible to analyze efficiently big data via classical methods of predictive analysis. The authors attribute this weakness to the fact that predictive analysis algorithms do not allow the parallelization and distribution of calculation. In this paper, we propose to extend the predictive analysis algorithm, Classification And Regression Trees (CART), in order to adapt it for big data analysis. The major changes of this algorithm are presented and then a version of the extended algorithm is defined in order to make it applicable for a huge quantity of data.

Keywords: Predictive analysis, big data, predictive analysis algorithms. CART algorithm.

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Authors: Ahmed M. Elhabashy, A. Baes Mohamed, Abou El Nasr Mohamad

Abstract:

Distributed Computing Systems are usually considered the most suitable model for practical solutions of many parallel algorithms. In this paper an enhanced distributed system is presented to improve the time complexity of Binary Indexed Trees (BIT). The proposed system uses multi-uniform processors with identical architectures and a specially designed distributed memory system. The analysis of this system has shown that it has reduced the time complexity of the read query to O(Log(Log(N))), and the update query to constant complexity, while the naive solution has a time complexity of O(Log(N)) for both queries. The system was implemented and simulated using VHDL and Verilog Hardware Description Languages, with xilinx ISE 10.1, as the development environment and ModelSim 6.1c, similarly as the simulation tool. The simulation has shown that the overhead resulting by the wiring and communication between the system fragments could be fairly neglected, which makes it applicable to practically reach the maximum speed up offered by the proposed model.

Keywords: Binary Index Tree (BIT), Least Significant Bit (LSB), Parallel Adder (PA), Very High Speed Integrated Circuits HardwareDescription Language (VHDL), Distributed Parallel Computing System(DPCS).

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Authors: S. M. Kamruzzaman, Md. Monirul Islam

Abstract:

Although backpropagation ANNs generally predict better than decision trees do for pattern classification problems, they are often regarded as black boxes, i.e., their predictions cannot be explained as those of decision trees. In many applications, it is desirable to extract knowledge from trained ANNs for the users to gain a better understanding of how the networks solve the problems. A new rule extraction algorithm, called rule extraction from artificial neural networks (REANN) is proposed and implemented to extract symbolic rules from ANNs. A standard three-layer feedforward ANN is the basis of the algorithm. A four-phase training algorithm is proposed for backpropagation learning. Explicitness of the extracted rules is supported by comparing them to the symbolic rules generated by other methods. Extracted rules are comparable with other methods in terms of number of rules, average number of conditions for a rule, and predictive accuracy. Extensive experimental studies on several benchmarks classification problems, such as breast cancer, iris, diabetes, and season classification problems, demonstrate the effectiveness of the proposed approach with good generalization ability.

Keywords: Backpropagation, clustering algorithm, constructivealgorithm, continuous activation function, pruning algorithm, ruleextraction algorithm, symbolic rules.

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