Search results for: dendrogram and cluster analysis

Authors: Akshay Agrawal, Anand K. Srivastava

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The increasing amount of XML datasets available to casual users increases the necessity of investigating techniques to extract knowledge from these data. Data mining is widely applied in the database research area in order to extract frequent correlations of values from both structured and semi-structured datasets. The increasing availability of heterogeneous XML sources has raised a number of issues concerning how to represent and manage these semi structured data. In recent years due to the importance of managing these resources and extracting knowledge from them, lots of methods have been proposed in order to represent and cluster them in different ways.

Keywords: XML, similarity measure, clustering, cluster quality, semantic clustering

Procedia PDF Downloads 350

Authors: Said Baadel, Fadi Thabtah, Joan Lu

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Clustering involves the partitioning of n objects into k clusters. Many clustering algorithms use hard-partitioning techniques where each object is assigned to one cluster. In this paper, we propose an overlapping algorithm MCOKE which allows objects to belong to one or more clusters. The algorithm is different from fuzzy clustering techniques because objects that overlap are assigned a membership value of 1 (one) as opposed to a fuzzy membership degree. The algorithm is also different from other overlapping algorithms that require a similarity threshold to be defined as a priority which can be difficult to determine by novice users.

Keywords: data mining, k-means, MCOKE, overlapping

Procedia PDF Downloads 538

Authors: Robin Singh, Mayank Nautiyal, Priyank Jain, Vatasta Koul, Vaibhav Sharma

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The curiosity to investigate the space and its mysteries was dependably the main impetus of human interest, as the particle of livings exists from the "debut de l'Univers" (beginning of the Universe) typified with its few other living things. The sharp drive to uncover the secrets of stars and their unusual deportment was dependably an ignitor of stars investigation. As humankind lives in civilizations and states, stars likewise live in provinces named ‘clusters’. Clusters are separates into 2 composes i.e. open clusters and globular clusters. An open cluster is a gathering of thousand stars that were moulded from a comparable goliath sub-nuclear cloud and for the most part; contain Propulsion I (extremely metal-rich) and Propulsion II (mild metal-rich), where globular clusters are around gathering of more than thirty thousand stars that circles a galactic focus and basically contain Propulsion III (to a great degree metal-poor) stars. Futurology of this paper lies in the spectroscopic investigation of globular clusters like M92 and NGC419 and open clusters like M34 and IC2391 in different color bands by using software like VIREO virtual observatory, Aladin, CMUNIWIN, and MS-Excel. Assessing the outcome Hertzsprung-Russel (HR) diagram with exemplary cosmological models like Einstein model, De Sitter and Planck survey demonstrate for a superior age estimation of respective clusters. Colour-Magnitude Diagram of these clusters was obtained by photometric analysis in g and r bands which further transformed into BV bands which will unravel the idea of stars exhibit in the individual clusters.

Keywords: color magnitude diagram, globular clusters, open clusters, Einstein model

Procedia PDF Downloads 202

Authors: Getachew Weldemichael, Sentayehu Alamerew, Leta Tulu, Gezahegn Berecha

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Coffee quality improvement program is becoming the focus of coffee research, as the world coffee consumption pattern shifted to high-quality coffee. However, there is limited information on the genetic variation of C. Arabica for quality improvement in potential specialty coffee growing areas of Ethiopia. Therefore, this experiment was conducted with the objectives of determining the magnitude of variation among 105 coffee accessions collected from east Wollega coffee growing areas and assessing correlations between the different coffee qualities attributes. It was conducted in RCRD with three replications. Data on green bean physical characters (shape and make, bean color and odor) and organoleptic cup quality traits (aromatic intensity, aromatic quality, acidity, astringency, bitterness, body, flavor, and overall standard of the liquor) were recorded. Analysis of variance, clustering, genetic divergence, principal component and correlation analysis was performed using SAS software. The result revealed that there were highly significant differences (P<0.01) among the accessions for all quality attributes except for odor and bitterness. Among the tested accessions, EW104 /09, EW101 /09, EW58/09, EW77/09, EW35/09, EW71/09, EW68/09, EW96 /09, EW83/09 and EW72/09 had the highest total coffee quality values (the sum of bean physical and cup quality attributes). These genotypes could serve as a source of genes for green bean physical characters and cup quality improvement in Arabica coffee. Furthermore, cluster analysis grouped the coffee accessions into five clusters with significant inter-cluster distances implying that there is moderate diversity among the accessions and crossing accessions from these divergent inter-clusters would result in hetrosis and recombinants in segregating generations. The principal component analysis revealed that the first three principal components with eigenvalues greater than unity accounted for 83.1% of the total variability due to the variation of nine quality attributes considered for PC analysis, indicating that all quality attributes equally contribute to a grouping of the accessions in different clusters. Organoleptic cup quality attributes showed positive and significant correlations both at the genotypic and phenotypic levels, demonstrating the possibility of simultaneous improvement of the traits. Path coefficient analysis revealed that acidity, flavor, and body had a high positive direct effect on overall cup quality, implying that these traits can be used as indirect criteria to improve overall coffee quality. Therefore, it was concluded that there is considerable variation among the accessions, which need to be properly conserved for future improvement of the coffee quality. However, the variability observed for quality attributes must be further verified using biochemical and molecular analysis.

Keywords: accessions, Coffea arabica, cluster analysis, correlation, principal component

Procedia PDF Downloads 138

Authors: Zhou Mo, Dennis Chow

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In the dynamic positioning system (DPS) for vessels, the reliable information transmission between each note basically relies on the wireless protocols. From the perspective of cluster-based routing protocols for wireless sensor networks, the data fusion technology based on the sleep scheduling mechanism and remaining energy in network layer is proposed, which applies the sleep scheduling mechanism to the routing protocols, considering the remaining energy of node and location information when selecting cluster-head. The problem of uneven distribution of nodes in each cluster is solved by the Equilibrium. At the same time, Classified Forwarding Mechanism as well as Redelivery Policy strategy is adopted to avoid congestion in the transmission of huge amount of data, reduce the delay in data delivery and enhance the real-time response. In this paper, a simulation test is conducted to improve the routing protocols, which turn out to reduce the energy consumption of nodes and increase the efficiency of data delivery.

Keywords: DPS for vessel, wireless sensor network, data fusion, routing protocols

Procedia PDF Downloads 497

Authors: Fayyaz Rasool, Naureen Aziz Qureshi, Shakeela Parveen

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Labeo rohita populations from five geographical locations from the hatchery and riverine system of Punjab-Pakistan were studied for the clustering on the basis of similarities and differences based on morphometric parameters within the species. Agglomerative Hierarchical Clustering (AHC) was done by using Pearson Correlation Coefficient and Unweighted Pair Group Method with Arithmetic Mean (UPGMA) as Agglomeration method by XLSTAT 2012 version 1.02. A dendrogram with the data on the morphometrics of the representative samples of each site divided the populations of Labeo rohita in to five major clusters or classes. The variance decomposition for the optimal classification values remained as 19.24% for within class variation, while 80.76% for the between class differences. The representative central objects of the each class, the distances between the class centroids and also the distance between the central objects of the classes were generated by the analysis. A measurable distinction between the classes of the populations of the Labeo rohita was indicated in this study which determined the impacts of changing environment and other possible factors influencing the variation level among the populations of the same species.

Keywords: AHC, Labeo rohita, hatchery, riverine, morphometric

Procedia PDF Downloads 421

Authors: Shweta Jha, Nandita Chaube

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The concept of self has a major role to play in the study of personality which drives the current study in its present form. This is a case of Miss S, a 17-year-old Hindu, currently in eleventh standard, with no family history of mental illness but with a past history of inability to manage relationships, multiple emotional and sexual relationships, repeated self harming behaviour, and sexual abuse over a period of 2 months at the age of 10 years. She comes with a psychiatric history of one episode of dissociative fall followed by a stressful event which left the patient with many psychological disturbances matching the criterion of Cluster B and C traits. Current episode precipitated due to the relationship failure, predisposing factor is her personality traits, and poor social and family support. Considering the patient’s aspiration for positivity and demand of the therapy, ventilation sessions were carried out which made her capable of understanding and dealing with her negative emotions, also strengthened mother child bond, helped her maintain meaningful and healthy relationships, also helped her increase her problem solving ability and adaptive coping skills making her feel more positive and acceptable towards herself, family members and others.

Keywords: cluster B and C traits, personality, therapy, self

Procedia PDF Downloads 266

Authors: Zhou Mo, Dennis Chow

Abstract:

In the dynamic positioning system (DPS) for vessels, the reliable information transmission between each note basically relies on the wireless protocols. From the perspective of cluster-based routing pro-tocols for wireless sensor networks, the data fusion technology based on the sleep scheduling mechanism and remaining energy in network layer is proposed, which applies the sleep scheduling mechanism to the routing protocols, considering the remaining energy of node and location information when selecting cluster-head. The problem of uneven distribution of nodes in each cluster is solved by the Equilibrium. At the same time, Classified Forwarding Mechanism as well as Redelivery Policy strategy is adopted to avoid congestion in the transmission of huge amount of data, reduce the delay in data delivery and enhance the real-time response. In this paper, a simulation test is conducted to improve the routing protocols, which turns out to reduce the energy consumption of nodes and increase the efficiency of data delivery.

Keywords: DPS for vessel, wireless sensor network, data fusion, routing protocols

Procedia PDF Downloads 425

Authors: Sofia Barbosa, Mariana Pinto, José António Almeida, Edgar Carvalho, Catarina Diamantino

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The aim of this work was to test a methodology able to generate spatial-temporal maps that can synthesize simultaneously the trends of distinct hydrochemical indicators in an old radium-uranium tailings dam deposit. Multidimensionality reduction derived from principal component analysis and subsequent data aggregation derived from clustering analysis allow to identify distinct hydrochemical behavioural profiles and to generate synthetic evolutionary hydrochemical maps.

Keywords: Contamination plume migration, K-means of PCA scores, groundwater and mine water monitoring, spatial-temporal hydrochemical trends

Procedia PDF Downloads 196

Authors: Madhuka G. P. D. Udantha, Gihan V. Dias, Surangika Ranathunga

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Today Websites contain very interesting applications. But there are only few methodologies to analyze User navigations through the Websites and formulating if the Website is put to correct use. The web logs are only used if some major attack or malfunctioning occurs. Web Logs contain lot interesting dealings on users in the system. Analyzing web logs has become a challenge due to the huge log volume. Finding interesting patterns is not as easy as it is due to size, distribution and importance of minor details of each log. Web logs contain very important data of user and site which are not been put to good use. Retrieving interesting information from logs gives an idea of what the users need, group users according to their various needs and improve site to build an effective and efficient site. The model we built is able to detect attacks or malfunctioning of the system and anomaly detection. Logs will be more complex as volume of traffic and the size and complexity of web site grows. Unsupervised techniques are used in this solution which is fully automated. Expert knowledge is only used in validation. In our approach first clean and purify the logs to bring them to a common platform with a standard format and structure. After cleaning module web session builder is executed. It outputs two files, Web Sessions file and Indexed URLs file. The Indexed URLs file contains the list of URLs accessed and their indices. Web Sessions file lists down the indices of each web session. Then DBSCAN and EM Algorithms are used iteratively and recursively to get the best clustering results of the web sessions. Using homogeneity, completeness, V-measure, intra and inter cluster distance and silhouette coefficient as parameters these algorithms self-evaluate themselves to input better parametric values to run the algorithms. If a cluster is found to be too large then micro-clustering is used. Using Cluster Signature Module the clusters are annotated with a unique signature called finger-print. In this module each cluster is fed to Associative Rule Learning Module. If it outputs confidence and support as value 1 for an access sequence it would be a potential signature for the cluster. Then the access sequence occurrences are checked in other clusters. If it is found to be unique for the cluster considered then the cluster is annotated with the signature. These signatures are used in anomaly detection, prevent cyber attacks, real-time dashboards that visualize users, accessing web pages, predict actions of users and various other applications in Finance, University Websites, News and Media Websites etc.

Keywords: anomaly detection, clustering, pattern recognition, web sessions

Procedia PDF Downloads 260

Authors: Kerem Rızvanoglu, Serhat Güney, Betül Aydoğan, Emre Kızılkaya, Ayşegül Boyalı, Onurcan Güden

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This study investigates the urban experience of international students coming to Istanbul with exchange programs and reveals how locative media applications accompany their urban experiences. The sample of the research consists of international students who lived, perceived, and conceived the city on a daily basis during the academic year of 2022. Focusing on this particular sample would demonstrate the opportunities and authentic experiences offered by the city as well as the prevalent urban problems for the foreigners. In this regard, international students' urban experience in Istanbul, the blockages they encounter as resident tourists, the hotspots that the city offers, and the role of locative media in enriching the urban experience are the main axes to be evaluated. In the first step of the multi-staged research, we conduct an online qualitative survey with a sample; then, we evaluate the data obtained from the survey using cluster analysis to identify the urban experience, consumption habits, and tastes. In the final stage, digital ethnographic fieldwork will be carried out with representative personas identified by the cluster analysis. With this field research on the urban experience accompanied by locative media applications, suggestions will be developed by evaluating the opportunities these applications offer to enrich the urban practice of foreigners.

Keywords: digital ethnography, international students, locative media applications, urban experience

Procedia PDF Downloads 117

Authors: J. S. Saini, P. P. K. Sandhu

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The multi-hop nature of Wireless Mesh Networks and the hasty progression of throughput demands results in multi- channels and multi-radios structures in mesh networks, but the main problem of co-channels interference reduces the total throughput, specifically in multi-hop networks. Quality of Service mentions a vast collection of networking technologies and techniques that guarantee the ability of a network to make available desired services with predictable results. Quality of Service (QoS) can be directed at a network interface, towards a specific server or router's performance, or in specific applications. Due to interference among various transmissions, the QoS routing in multi-hop wireless networks is formidable task. In case of multi-channel wireless network, since two transmissions using the same channel may interfere with each other. This paper has considered the Destination Sequenced Distance Vector (DSDV) routing protocol to locate the secure and optimised path. The proposed technique also utilizes the Lempel–Ziv–Welch (LZW) based lossless data compression and intra cluster data aggregation to enhance the communication between the source and the destination. The use of clustering has the ability to aggregate the multiple packets and locates a single route using the clusters to improve the intra cluster data aggregation. The use of the LZW based lossless data compression has ability to reduce the data packet size and hence it will consume less energy, thus increasing the network QoS. The MATLAB tool has been used to evaluate the effectiveness of the projected technique. The comparative analysis has shown that the proposed technique outperforms over the existing techniques.

Keywords: WMNS, QOS, flooding, collision avoidance, LZW, congestion control

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Authors: Lidija R. Jevrić, Sanja O. Podunavac-Kuzmanović, Strahinja Z. Kovačević

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This study considers the selection of the most suitable in silico molecular descriptors that could be used for s-triazine pesticides characterization. Suitable descriptors among topological, geometrical and physicochemical are used for quantitative structure-retention relationships (QSRR) model establishment. Established models were obtained using linear regression (LR) and multiple linear regression (MLR) analysis. In this paper, MLR models were established avoiding multicollinearity among the selected molecular descriptors. Statistical quality of established models was evaluated by standard and cross-validation statistical parameters. For detection of similarity or dissimilarity among investigated s-triazine pesticides and their classification, principal component analysis (PCA) and hierarchical cluster analysis (HCA) were used and gave similar grouping. This study is financially supported by COST action TD1305.

Keywords: chemometrics, classification analysis, molecular descriptors, pesticides, regression analysis

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Authors: Abdul Hadi Butt, Asfandyar Arshad

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The purpose of this paper is to study the thrust variation in different configurations of clustered nozzles. It involves the design and analysis of clustered configuration of nozzles using Ansys fluent. Clustered nozzles with different configurations are simulated and compared on basis of effective exhaust thrust. Mixing length for the flow interaction is also calculated. Further clustered configurations are analyzed over different altitudes. An optimum value of the thrust among different configurations is proposed at the end of comparisons.

Keywords: CD nozzle, cluster, thrust, fluent, ANSYS

Procedia PDF Downloads 378

Authors: Maximilian A. Richter

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The public authority needs to understand the role and impacts of autonomous vehicle (AV) on the mobility system. At present, however, research shows that the impact of AV on cities varies. As a consequence, it is difficult to make recommendations to policymakers on how they should prepare for the future when so much remains unknown about this technology. The study aims to provide an overview of the literature on how autonomous vehicles will affect the cities and traffic of the future. To this purpose, the most important studies are first selected, and their results summarized. Further on, it will be clarified which advantages AV have for cities and how it can lead to an improvement in the current problems/challenges of cities. To achieve the research aim and objectives, this paper approaches a literature review. For this purpose, in a first step, the most important studies are extracted. This is limited to studies that are peer-reviewed and have been published in high-ranked journals such as the Journal of Transportation: Part A. In step 2, the most important key performance indicator (KPIs) (such as traffic volume or energy consumption) are selected from the literature research. Due to the fact that different terms are used in the literature for similar statements/KPIs, these must first be clustered. Furthermore, for each cluster, the changes from the respective studies are compiled, as well as their survey methodology. In step 3, a sensitivity analysis per cluster is made. Here, it will be analyzed how the different studies come to their findings and on which assumptions, scenarios, and methods these calculations are based. From the results of the sensitivity analysis, the success factors for the implementation of autonomous vehicles are drawn, and statements are made under which conditions AVs can be successful.

Keywords: autonomous vehicles, city of the future, literature review, traffic simulations

Procedia PDF Downloads 81

Authors: Rabia Waseem, Low Kah Hin, Najihah Mohamed Hashim

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The variability in the chemical components of the Syzygium species essential oils has been evaluated. The leaves of Syzygium species have been collected from Perak, Malaysia. The essential oils extracted by using the conventional Hydro-distillation extraction procedure and analyzed by using Gas chromatography System attached with Mass Spectrometry (GCMS). Twenty-seven constituents were found in Syzygium species in which the major constituents include: α-Pinene (3.94%), α-Thujene (2.16%), α-Terpineol (2.95%), g-Elemene (2.89%) and D-Limonene (14.59%). The aim of this study was the comparison between the evaluated data and existing literature to fortify the major variability through statistical analysis.

Keywords: chemotaxonomy, cluster analysis, essential oil, medicinal plants, statistical analysis

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Authors: G. Tamilpavai, C. Vishnuppriya

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Bioinformatics is an active research area which combines biological matter as well as computer science research. The longest common subsequence (LCSS) is one of the major challenges in various bioinformatics applications. The computation of the LCSS plays a vital role in biomedicine and also it is an essential task in DNA sequence analysis in genetics. It includes wide range of disease diagnosing steps. The objective of this proposed system is to find the longest common subsequence which presents in a normal and various disease affected human DNA sequence using Self Organizing Map (SOM) and LCSS. The human DNA sequence is collected from National Center for Biotechnology Information (NCBI) database. Initially, the human DNA sequence is separated as k-mer using k-mer separation rule. Mean and median values are calculated from each separated k-mer. These calculated values are fed as input to the Self Organizing Map for the purpose of clustering. Then obtained clusters are given to the Longest Common Sub Sequence (LCSS) algorithm for finding common subsequence which presents in every clusters. It returns nx(n-1)/2 subsequence for each cluster where n is number of k-mer in a specific cluster. Experimental outcomes of this proposed system produce the possible number of longest common subsequence of normal and disease affected DNA data. Thus the proposed system will be a good initiative aid for finding disease causing sequence. Finally, performance analysis is carried out for different DNA sequences. The obtained values show that the retrieval of LCSS is done in a shorter time than the existing system.

Keywords: clustering, k-mers, longest common subsequence, SOM

Procedia PDF Downloads 234

Authors: Monisha Isaac

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Use of molecular markers for selecting plants with desired traits has been started long back. Due to their heritable characteristics, they are useful for identification and characterization of specific genotypes. The study involves various types of molecular markers used to select multiple desired characters in plants, their properties, and advantages to improve crop productivity in adverse climatological conditions for the purpose of providing food security to fast-growing global population. The study shows that genetic similarities obtained from molecular markers provide more accurate information and the genetic diversity can be better estimated from the genetic relationship obtained from the dendrogram. The information obtained from markers assisted characterization is more suitable for the crops of economic importance like sugarcane.

Keywords: molecular markers, crop productivity, genetic diversity, genotype

Procedia PDF Downloads 485

Authors: Fawad Ali

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Toxic heavy metal contamination has a negative impact on soil quality which ultimately pollutes the agriculture system. In the current work, we analyzed uptake of various heavy metals by dietary vegetables grown in wastewater irrigated areas of Swabi city. The samples of soil and vegetables were analyzed for heavy metals viz Cd, Cr, Mn, Fe, Ni, Cu, Zn and Pb using Atomic Absorption Spectrophotometer. High levels of metals were found in wastewater irrigated soil and vegetables in the study area. Especially the concentrations of Pb and Cd in the dietary vegetable crossed the permissible level of World Health Organization. Substantial positive correlation was found among the soil and vegetable contamination. Transfer factor for some metals including Cr, Zn, Mn, Ni, Cd and Cu was greater than 0.5 which shows enhanced accumulation of these metals due to contamination by domestic discharges and industrial effluents. Linear regression analysis indicated significant correlation of heavy metals viz Pb, Cr, Cd, Ni, Zn, Cu, Fe and Mn in vegetables with concentration in soil of 0.964 at P≤0.001. Abelmoschus esculentus indicated Health Risk Index (HRI) of Pb >1 in adults and children. The source identification analysis carried out by Principal Component Analysis (PCA) and Cluster Analysis (CA) showed that ground water and soil were being polluted by the trace metals coming out from industries and domestic wastes. Hierarchical cluster analysis (HCA) divided metals into two clusters for wastewater and soil but into five clusters for soil of control area. PCA extracted two factors for wastewater, each contributing 61.086 % and 16.229 % of the total 77.315 % variance. PCA extracted two factors, for soil samples, having total variance of 79.912 % factor 1 and factor 2 contributed 63.889 % and 16.023 % of the total variance. PCA for sub soil extracted two factors with a total variance of 76.136 % factor 1 being 61.768 % and factor 2 being 14.368 %of the total variance. High pollution load index for vegetables in the study area due to metal polluted soil has opened a study area for proper legislation to protect further contamination of vegetables. This work would further reveal serious health risks to human population of the study area.

Keywords: health risk, vegetables, wastewater, atomic absorption sepctrophotometer

Procedia PDF Downloads 38

Authors: K. Prasanth, S. Hafeezullah Khan, B. Haribalakrishnan, D. Arun, S. Jayapriya, S. Dhivya, N. Vijayarangan

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The main goal of our approach is to find the optimum positions for the sensor nodes, reinforcing the communications in points where certain lack of connectivity is found. Routing is the major problem in sensor network’s data transfer between nodes. We are going to provide an efficient routing technique to make data signal transfer to reach the base station soon without any interruption. Clustering and routing are the two important key factors to be considered in case of WSN. To carry out the communication from the nodes to their cluster head, we propose a parameterizable protocol so that the developer can indicate if the routing has to be sensitive to either the link quality of the nodes or the their battery levels.

Keywords: clusters, routing, wireless sensor networks, three phases, sensor networks

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Authors: Amani Tahat, Serdal Kirmizialtin

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Trajectory fragment methods such as Markov State Models (MSM), Milestoning (MS) and Transition Path sampling are the prime choice of extending the timescale of all atom Molecular Dynamics simulations. In these approaches, a set of structures that covers the accessible phase space has to be chosen a priori using cluster analysis. Structural clustering serves to partition the conformational state into natural subgroups based on their similarity, an essential statistical methodology that is used for analyzing numerous sets of empirical data produced by Molecular Dynamics (MD) simulations. Local transition kernel among these clusters later used to connect the metastable states using a Markovian kinetic model in MSM and a non-Markovian model in MS. The choice of clustering approach in constructing such kernel is crucial since the high dimensionality of the biomolecular structures might easily confuse the identification of clusters when using the traditional hierarchical clustering methodology. Of particular interest, in the case of MS where the milestones are very close to each other, accurate determination of the milestone identity of the trajectory becomes a challenging issue. Throughout this work we present two cluster analysis methods applied to the cis–trans isomerism of dinucleotide AA. The choice of nucleic acids to commonly used proteins to study the cluster analysis is two fold: i) the energy landscape is rugged; hence transitions are more complex, enabling a more realistic model to study conformational transitions, ii) Nucleic acids conformational space is high dimensional. A diverse set of internal coordinates is necessary to describe the metastable states in nucleic acids, posing a challenge in studying the conformational transitions. Herein, we need improved clustering methods that accurately identify the AA structure in its metastable states in a robust way for a wide range of confused data conditions. The single linkage approach of the hierarchical clustering available in GROMACS MD-package is the first clustering methodology applied to our data. Self Organizing Map (SOM) neural network, that also known as a Kohonen network, is the second data clustering methodology. The performance comparison of the neural network as well as hierarchical clustering method is studied by means of computing the mean first passage times for the cis-trans conformational rates. Our hope is that this study provides insight into the complexities and need in determining the appropriate clustering algorithm for kinetic analysis. Our results can improve the effectiveness of decisions based on clustering confused empirical data in studying conformational transitions in biomolecules.

Keywords: milestoning, self organizing map, single linkage, structure clustering

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Authors: Reza Talebi

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Wheat (Triticum aestivum) is one of the most important food staples in Iran. Understanding genetic variability among the landrace wheat germplasm is important for breeding. Landraces endemic to Iran are a genetic resource that is distinct from other wheat germplasm. In this study, 60 Iranian landrace wheat accessions were characterized AFLP and ISSR markers. Twelve AFLP primer pairs detected 128 polymorphic bands among the sixty genotypes. The mean polymorphism rate based on AFLP data was 31%; however, a wide polymorphism range among primer pairs was observed (22–40%). Polymorphic information content (PIC value) calculated to assess the informativeness of each marker ranged from 0.28 to 0.4, with a mean of 0.37. According to AFLP molecular data, cluster analysis grouped the genotypes in five distinct clusters. .ISSR markers generated 68 bands (average of 6 bands per primer), which 31 were polymorphic (45%) across the 60 wheat genotypes. Polymorphism information content (PIC) value for ISSR markers was calculated in the range of 0.14 to 0.48 with an average of 0.33. Based on data achieved by ISSR-PCR, cluster analysis grouped the genotypes in three distinct clusters. Both AFLP and ISSR markers able to showed that high level of genetic diversity in Iranian landrace wheat accessions has maintained a relatively constant level of genetic diversity during last years.

Keywords: wheat, genetic diversity, AFLP, ISSR

Procedia PDF Downloads 420

Authors: Sahar Elsaleh, Ghada Farhat, Shaikha Al-Derham, Fasih Alam

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Background: Cesarean section (CS) delivery is one of the major concerns both in developing and developed countries. The rate of CS deliveries are on the rise globally, and especially in Qatar. Many socio-economic, demographic, clinical and institutional factors play an important role for cesarean sections. This study aims to investigate factors affecting the prevalence of CS among women in Qatar using the UNICEF’s Multiple Indicator Cluster Survey (MICS) 2012 database. Methods: The study has focused on the women’s questionnaire of the MICS, which was successfully distributed to 5699 participants. Following study inclusion and exclusion criteria, a final sample of 761 women aged 19- 49 years who had at least one delivery of giving birth in their lifetime before the survey were included. A number of socio-economic, demographic, clinical and institutional factors, identified through literature review and available in the data, were considered for the analyses. Bivariate and multivariate logistic regression models, along with a multi-level modeling to investigate clustering effect, were undertaken to identify the factors that affect CS prevalence in Qatar. Results: From the bivariate analyses the study has shown that, a number of categorical factors are statistically significantly associated with the dependent variable (CS). When identifying the factors from a multivariate logistic regression, the study found that only three categorical factors -‘age of women’, ‘place at delivery’ and ‘baby weight’ appeared to be significantly affecting the CS among women in Qatar. Although the MICS dataset is based on a cluster survey, an exploratory multi-level analysis did not show any clustering effect, i.e. no significant variation in results at higher level (households), suggesting that all analyses at lower level (individual respondent) are valid without any significant bias in results. Conclusion: The study found a statistically significant association between the dependent variable (CS delivery) and age of women, frequency of TV watching, assistance at birth and place of birth. These results need to be interpreted cautiously; however, it can be used as evidence-base for further research on cesarean section delivery in Qatar.

Keywords: cesarean section, factors, multiple indicator cluster survey, MICS database, Qatar

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Authors: Mehdi Nasr Esfahani, Abdal-Rasool Gholamalian, Abdelfattah A. Dababat

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Wheat, Triticum aestivum L. is one of the most important and strategic crops in the human diet. Several diseases threaten this particular crop. Common root rot disease of wheat by a fungal agent, Bipolaris sorokiniana is one of the important diseases, causing considerable losses worldwide. Resistant sources are the only feasible and effective method of control for managing diseases. In this study, the response of 33 domestic and exotic wheat genotypes, including cultivars and promising lines were screened to B. sorokiniana at greenhouse and field conditions, based on five scoring scale indexes of 0 to 100 severity percentage. The screening was continued on resistant wheat genotypes and repeated several times to confirm the greenhouse and field results. Statistical and cluster analysis of data was performed using SAS and SPSS software, respectively. The results showed that, the response of wheat genotypes to the disease in the greenhouse and field conditions was highly significant. The highest rate of common root rot disease infection, B. sorokiniana in the greenhouse and field, was of CVS. Karkheh and Beck Cross-Roshan with 60.83% and 59.16% disease severity respectively, and the lowest one were in cv. Alvand with 18.33%, followed by cv. Baharan with 19.16% disease severity, with a highly significant difference respectively. The remaining wheat genotypes were located in between these two highest and lowest infected groups to B. sorokiniana significantly. There was a high correlation coefficient between the related statistical groups and cluster analysis.

Keywords: wheat, rot, root, crown, fungus, genotype, resistance

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Authors: Minami Ito, Akihiro Iijima

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On March 11, 2011, the Great East Japan Earthquake occurred off the coast of Sanriku, Japan. It is important to build a sustainable society through the reconstruction process rather than simply restoring the infrastructure. To compare the goals of reconstruction plans of quake-stricken municipalities, Japanese language morphological analysis was performed by using text mining techniques. Frequently-used nouns were sorted into four main categories of “life”, “disaster prevention”, “economy”, and “harmony with environment”. Because Soma City is affected by nuclear accident, sentences tagged to “harmony with environment” tended to be frequent compared to the other municipalities. Results from cluster analysis and principle component analysis clearly indicated that the local government reinforces the efforts to reduce risks from radiation exposure as a top priority.

Keywords: eco-friendly reconstruction, harmony with environment, decontamination, nuclear disaster

Procedia PDF Downloads 197

Authors: Fayyaz Rasool, Shakeela Parveen

Abstract:

The studies on genetic diversity of Labeo rohita by using molecular markers were carried out to investigate the genetic structure by RAPAD marker and the levels of polymorphism and similarity amongst the different groups of five populations of wild and farmed types. The samples were collected from different five locations as representatives of wild and hatchery raised populations. RAPAD data for Jaccard’s coefficient by following the un-weighted Pair Group Method with Arithmetic Mean (UPGMA) for Hierarchical Clustering of the similar groups on the basis of similarity amongst the genotypes and the dendrogram generated divided the randomly selected individuals of the five populations into three classes/clusters. The variance decomposition for the optimal classification values remained as 52.11% for within class variation, while 47.89% for the between class differences. The Principal Component Analysis (PCA) for grouping of the different genotypes from the different environmental conditions was done by Spearman Varimax rotation method for bi-plot generation of the co-occurrence of the same genotypes with similar genetic properties and specificity of different primers indicated clearly that the increase in the number of factors or components was correlated with the decrease in eigenvalues. The Kaiser Criterion based upon the eigenvalues greater than one, first two main factors accounted for 58.177% of cumulative variability.

Keywords: variation, clustering, PCA, wild, hatchery, RAPAD, Labeo rohita

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Authors: Nutthapat Kaewrattanapat, Wannarat Bunchongkien

Abstract:

The purposes of this research are to study and develop the algorithm of Thai spoonerism words by semi-automatic computer programs, that is to say, in part of data input, syllables are already separated and in part of spoonerism, the developed algorithm is utilized, which can establish rules and mechanisms in Thai spoonerism words for bi-syllables by utilizing analysis in elements of the syllables, namely cluster consonant, vowel, intonation mark and final consonant. From the study, it is found that bi-syllable Thai spoonerism has 1 case of spoonerism mechanism, namely transposition in value of vowel, intonation mark and consonant of both 2 syllables but keeping consonant value and cluster word (if any). From the study, the rules and mechanisms in Thai spoonerism word were applied to develop as Thai spoonerism word software, utilizing PHP program. the software was brought to conduct a performance test on software execution; it is found that the program performs bi-syllable Thai spoonerism correctly or 99% of all words used in the test and found faults on the program at 1% as the words obtained from spoonerism may not be spelling in conformity with Thai grammar and the answer in Thai spoonerism could be more than 1 answer.

Keywords: algorithm, spoonerism, computational linguistics, Thai spoonerism

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Authors: Johannes J. Schneider, Mathias S. Weyland, Peter Eggenberger Hotz, William D. Jamieson, Oliver Castell, Alessia Faggian, Rudolf M. Füchslin

Abstract:

Agglomerations of polydisperse systems of spherical particles are created in computer simulations using a simplified stochastic-hydrodynamic model: Particles sink to the bottom of the cylinder, taking into account gravity reduced by the buoyant force, the Stokes friction force, the added mass effect, and random velocity changes. Two types of particles are considered, with one of them being able to create connections to neighboring particles of the same type, thus forming a network within the agglomeration at the bottom of a cylinder. Decreasing the fraction of these particles, a percolation transition occurs. The critical regime is determined by investigating the maximum cluster size and the percolation susceptibility.

Keywords: binary system, maximum cluster size, percolation, polydisperse

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Authors: Lillian Musila, Valerie Oundo, Daniel Erwin, Willie Sang

Abstract:

Staphylococcus aureus infections are a major cause of nosocomial infections in Kenya. Methicillin resistant S. aureus (MRSA) infections are a significant burden to public health and are associated with considerable morbidity and mortality. At a hospital in Western Kenya two clusters of MRSA cases emerged within short periods of time. In this study we explored whether these clusters represented a nosocomial outbreak by characterizing the isolates using phenotypic and molecular assays and examining epidemiological data to identify possible transmission patterns. Specimens from the site of infection of the subjects were collected, cultured and S. aureus isolates identified phenotypically and confirmed by APIStaph™. MRSA were identified by cefoxitin disk screening per CLSI guidelines. MRSA were further characterized based on their antibiotic susceptibility patterns and spa gene typing. Characteristics of cases with MRSA isolates were compared with those with MSSA isolated around the same time period. Two cases of MRSA infection were identified in the two week period between 21 April and 4 May 2015. A further 2 MRSA isolates were identified on the same day on 7 September 2015. The antibiotic resistance patterns of the two MRSA isolates in the 1st cluster of cases were different suggesting that these were distinct isolates. One isolate had spa type t2029 and the other had a novel spa type. The 2 isolates were obtained from urine and an open skin wound. In the 2nd cluster of MRSA isolates, the antibiotic susceptibility patterns were similar but isolates had different spa types: one was t037 and the other a novel spa type different from the novel MRSA spa type in the first cluster. Both cases in the second cluster were admitted into the hospital but one infection was community- and the other hospital-acquired. Only one of the four MRSA cases was classified as an HAI from an infection acquired post-operatively. When compared to other S. aureus strains isolated within the same time period from the same hospital only one spa type t2029 was found in both MRSA and non-MRSA strains. None of the cases infected with MRSA in the two clusters shared any common epidemiological characteristic such as age, sex or known risk factors for MRSA such as prolonged hospitalization or institutionalization. These data suggest that the observed MRSA clusters were multi strain clusters and not an outbreak of a single strain. There was no clear relationship between the isolates by spa type suggesting that no transmission was occurring within the hospital between these cluster cases but rather that the majority of the MRSA strains were circulating in the community. There was high diversity of spa types among the MRSA strains with none of the isolates sharing spa types. Identification of disease clusters in space and time is critical for immediate infection control action and patient management. Spa gene typing is a rapid way of confirming or ruling out MRSA outbreaks so that costly interventions are applied only when necessary.

Keywords: cluster, Kenya, MRSA, spa typing

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Authors: Laura A. Rodriguez-Villamizar, Alvaro Osornio-Vargas, Brian H. Rowe, Rhonda J. Rosychuk

Abstract:

Introduction/Objectives: The Census Metropolitan Area of Edmonton (CMAE) has important industrial emissions to the air from the Industrial Heartland Alberta (IHA) at the Northeast and the coal-fired power plants (CFPP) at the West. The objective of the study was to explore the presence of clusters of children asthma ED visits in the areas around the IHA and the CFPP. Methods: Retrospective data on children asthma ED visits was collected at the dissemination area (DA) level for children between 2 and 14 years of age, living in the CMAE between April 1, 2004, and March 31, 2010. We conducted a spatial analysis of disease clusters around putative sources with count (ecological) data using descriptive, hypothesis testing, and multivariable modeling analysis. Results: The mean crude rate of asthma ED visits was 9.3/1,000 children population per year during the study period. Circular spatial scan test for cases and events identified a cluster of children asthma ED visits in the DA where the CFPP are located in the Wabamum area. No clusters were identified around the IHA area. The multivariable models suggest that there is a significant decline in risk for children asthma ED visits as distance increases around the CFPP area this effect is modified at the SE direction with mean angle 125.58 degrees, where the risk increases with distance. In contrast, the regression models for IHA suggest that there is a significant increase in risk for children asthma ED visits as distance increases around the IHA area and this effect is modified at SW direction with mean angle 216.52 degrees, where the risk increases at shorter distances. Conclusions: Different methods for detecting clusters of disease consistently suggested the existence of a cluster of children asthma ED visits around the CFPP but not around the IHA within the CMAE. These results are probably explained by the direction of the air pollutants dispersion caused by the predominant and subdominant wind direction at each point. The use of different approaches to detect clusters of disease is valuable to have a better understanding of the presence, shape, direction and size of clusters of disease around pollution sources.

Keywords: air pollution, asthma, disease cluster, industry

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