Search results for: fuzzy cluster analysis
27338 A Study to Explore the Views of Students regarding E-Learning as an Instructional Tool at University Level
Authors: Zafar Iqbal
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This study involved students of 6th semester enrolled in a Bachelor of Computer Science Program at university level. In this era of science and technology, e-learning can be helpful for grassroots in providing them access to education tenant in less developed areas. It is a potential substitute of face-to-face teaching being used in different countries. The purpose of the study was to explore the views of students about e-learning (Facebook) as an instructional tool. By using purposive sampling technique an intact class of 30 students included both male and female were selected where e-learning was used as an instructional tool. The views of students were explored through qualitative approach by using focus group interviews. The approach was helpful to develop comprehensive understanding of students’ views towards e- learning. In addition, probing questions were also asked and recorded. Data was transcribed, generated nodes and then coded text against these nodes. For this purpose and further analysis, NVivo 10 software was used. Themes were generated and tangibly presented through cluster analysis. Findings were interesting and provide sufficient evidence that face book is a subsequent e-learning source for students of higher education. Students acknowledged it as best source of learning and it was aligned with their academic and social behavior. It was not time specific and therefore, feasible for students who work day time and can get on line access to the material when they got free time. There were some distracters (time wasters) reported by the students but can be minimized by little effort. In short, e-learning is need of the day and potential learning source for every individual who have access to internet living at any part of the globe.Keywords: e-learning, facebook, instructional tool, higher education
Procedia PDF Downloads 37027337 Study of Phenotypic Polymorphism and Detection of Genotypic Polymorphism in Menochilus sexmaculatus (Coleoptera: Insecta) Using RAPD PCR
Authors: Huma Balouch
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Menochilus sexmaculatus commonly known as six spotted zig zag ladybird, is an aphidophagus and the most misidentified Coccinellids due to the occurrence of numerous color variants. The correct identification of Menochilus sexmaculatus and its strains is necessary to implement the use of biological control. In the present study phenotypic and genotypic polymorphism was investigated in Menochilus sexmaculatus collected from Punjab, NWFP and Sindh provinces of Pakistan. Six different morphs of the species were distinguished by analyzing its Elytral color and spot pattern and then Polymerase Chain Reaction was used to generate random amplification of polymorphic DNA (RAPD) from six different types of Menochilus sexmaculatus. Forty primers (OPA & OPC Kit) were used to perform RAPD PCR on six different types of Menochilus sexmaculatus of which, seven primers revealed different patterns related to the Menochilus sexmaculatus types. These seven primers (OPA-04, OPA-09, OPA-18, OPC-04, OPC-12, OPC-15 and OPC-18) produced 111 clear polymorphic bands and 6 scorable strain specific markers. The cluster analysis applied to RAPD data showed high polymorphism among six types and it can be concluded that these six types are six polymorphic strains of the same species.Keywords: Menochilus sexmaculatus, aphidophagus, coccinellids, phenotypic and genotypic polymorphism, RAPD-PCR, strain specific markers
Procedia PDF Downloads 48727336 Variation of Phenolic Compounds in Latvian Apple Juices and Their Suitability for Cider Production
Authors: Rita Riekstina-Dolge, Zanda Kruma, Fredijs Dimins, Inta Krasnova, Daina Karklina
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Apple juice is the main raw material for cider production. In this study apple juices obtained from 14 dessert and crab apples grown in Latvia were investigated. For all samples total phenolic compounds, tannins and individual phenolic compounds content were determined. The total phenolic content of different variety apple juices ranged from 650mg L-1 to 4265mg L-1. Chlorogenic acid is the predominant phenolic compound in all juice samples and ranged from 143.99mg L-1 in ‘Quaker Beauty’ apple juice to 617.66mg L-1 in ‘Kerr’ juice. Some dessert and crab apple juices have similar phenolic composition, but in several varieties such as ‘Cornelie’, ‘Hyslop’ and ‘Riku’ it was significantly higher. For cider production it is better to blend different kinds of apple juices including apples rich in high phenol content ('Rick', 'Cornelie') and also, for successful fermentation, apples rich in sugars and soluble solids content should be used in blends.Keywords: apple juice, phenolic compounds, hierarchical cluster analysis, cider production
Procedia PDF Downloads 42627335 Factors Affecting Nutritional Status of Elderly People of Rural Nepal: A Community-Based Cross-Sectional Study
Authors: Man Kumar Tamang, Uday Narayan Yadav
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Background and objectives: Every country in the world is facing a demographic challenge due to drastic growth of population over 60 years. Adequate diet and nutritional status are important determinants of health in elderly populations. This study aimed to assess the nutritional status among the elderly population and factors associated with malnutrition at the community setting in rural Nepal. Methods: This is a community-based cross-sectional study among elderly of age 60 years or above in the three randomly selected VDCs of Morang district in eastern Nepal, between August and November, 2016. A multi stage cluster sampling was adopted with sample size of 345 of which 339 participated in the study. Nutritional status was assessed by MNA tool and associated socio-economic, demographic, psychological and nutritional factors were checked by binary logistic regression analysis. Results: Among 339 participants, 24.8% were found to be within normal nutritional status, 49.6% were at risk of malnutrition and 24.8% were malnourished. Independent factors associated with malnutrition status among the elderly people after controlling the cofounders in the bivariate analysis were: elderly who were malnourished were those who belonged to backward caste according to traditional Hindu caste system [OR=2.69, 95% CI: 1.17-6.21), being unemployed (OR=3.23, 95% CI: 1.63-6.41),who experienced any mistreatment from caregivers (OR=4.05, 95% CI: 1.90-8.60), being not involved in physical activity (OR=4.67, 95% CI: 1.87-11.66) and those taking medication for any co-morbidities. Conclusion: Many socio-economic, psychological and physiological factors affect nutritional status in our sample population and these issues need to be addressed for bringing improvement in elderly nutrition and health status.Keywords: elderly, eastern Nepal, malnutrition, nutritional status
Procedia PDF Downloads 29127334 Hierarchical Clustering Algorithms in Data Mining
Authors: Z. Abdullah, A. R. Hamdan
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Clustering is a process of grouping objects and data into groups of clusters to ensure that data objects from the same cluster are identical to each other. Clustering algorithms in one of the areas in data mining and it can be classified into partition, hierarchical, density based, and grid-based. Therefore, in this paper, we do a survey and review for four major hierarchical clustering algorithms called CURE, ROCK, CHAMELEON, and BIRCH. The obtained state of the art of these algorithms will help in eliminating the current problems, as well as deriving more robust and scalable algorithms for clustering.Keywords: clustering, unsupervised learning, algorithms, hierarchical
Procedia PDF Downloads 87727333 Phenotype Prediction of DNA Sequence Data: A Machine and Statistical Learning Approach
Authors: Mpho Mokoatle, Darlington Mapiye, James Mashiyane, Stephanie Muller, Gciniwe Dlamini
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Great advances in high-throughput sequencing technologies have resulted in availability of huge amounts of sequencing data in public and private repositories, enabling a holistic understanding of complex biological phenomena. Sequence data are used for a wide range of applications such as gene annotations, expression studies, personalized treatment and precision medicine. However, this rapid growth in sequence data poses a great challenge which calls for novel data processing and analytic methods, as well as huge computing resources. In this work, a machine and statistical learning approach for DNA sequence classification based on $k$-mer representation of sequence data is proposed. The approach is tested using whole genome sequences of Mycobacterium tuberculosis (MTB) isolates to (i) reduce the size of genomic sequence data, (ii) identify an optimum size of k-mers and utilize it to build classification models, (iii) predict the phenotype from whole genome sequence data of a given bacterial isolate, and (iv) demonstrate computing challenges associated with the analysis of whole genome sequence data in producing interpretable and explainable insights. The classification models were trained on 104 whole genome sequences of MTB isoloates. Cluster analysis showed that k-mers maybe used to discriminate phenotypes and the discrimination becomes more concise as the size of k-mers increase. The best performing classification model had a k-mer size of 10 (longest k-mer) an accuracy, recall, precision, specificity, and Matthews Correlation coeffient of 72.0%, 80.5%, 80.5%, 63.6%, and 0.4 respectively. This study provides a comprehensive approach for resampling whole genome sequencing data, objectively selecting a k-mer size, and performing classification for phenotype prediction. The analysis also highlights the importance of increasing the k-mer size to produce more biological explainable results, which brings to the fore the interplay that exists amongst accuracy, computing resources and explainability of classification results. However, the analysis provides a new way to elucidate genetic information from genomic data, and identify phenotype relationships which are important especially in explaining complex biological mechanisms.Keywords: AWD-LSTM, bootstrapping, k-mers, next generation sequencing
Procedia PDF Downloads 16127332 Phenotype Prediction of DNA Sequence Data: A Machine and Statistical Learning Approach
Authors: Darlington Mapiye, Mpho Mokoatle, James Mashiyane, Stephanie Muller, Gciniwe Dlamini
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Great advances in high-throughput sequencing technologies have resulted in availability of huge amounts of sequencing data in public and private repositories, enabling a holistic understanding of complex biological phenomena. Sequence data are used for a wide range of applications such as gene annotations, expression studies, personalized treatment and precision medicine. However, this rapid growth in sequence data poses a great challenge which calls for novel data processing and analytic methods, as well as huge computing resources. In this work, a machine and statistical learning approach for DNA sequence classification based on k-mer representation of sequence data is proposed. The approach is tested using whole genome sequences of Mycobacterium tuberculosis (MTB) isolates to (i) reduce the size of genomic sequence data, (ii) identify an optimum size of k-mers and utilize it to build classification models, (iii) predict the phenotype from whole genome sequence data of a given bacterial isolate, and (iv) demonstrate computing challenges associated with the analysis of whole genome sequence data in producing interpretable and explainable insights. The classification models were trained on 104 whole genome sequences of MTB isoloates. Cluster analysis showed that k-mers maybe used to discriminate phenotypes and the discrimination becomes more concise as the size of k-mers increase. The best performing classification model had a k-mer size of 10 (longest k-mer) an accuracy, recall, precision, specificity, and Matthews Correlation coeffient of 72.0 %, 80.5 %, 80.5 %, 63.6 %, and 0.4 respectively. This study provides a comprehensive approach for resampling whole genome sequencing data, objectively selecting a k-mer size, and performing classification for phenotype prediction. The analysis also highlights the importance of increasing the k-mer size to produce more biological explainable results, which brings to the fore the interplay that exists amongst accuracy, computing resources and explainability of classification results. However, the analysis provides a new way to elucidate genetic information from genomic data, and identify phenotype relationships which are important especially in explaining complex biological mechanismsKeywords: AWD-LSTM, bootstrapping, k-mers, next generation sequencing
Procedia PDF Downloads 14727331 Identification of Watershed Landscape Character Types in Middle Yangtze River within Wuhan Metropolitan Area
Authors: Huijie Wang, Bin Zhang
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In China, the middle reaches of the Yangtze River are well-developed, boasting a wealth of different types of watershed landscape. In this regard, landscape character assessment (LCA) can serve as a basis for protection, management and planning of trans-regional watershed landscape types. For this study, we chose the middle reaches of the Yangtze River in Wuhan metropolitan area as our study site, wherein the water system consists of rich variety in landscape types. We analyzed trans-regional data to cluster and identify types of landscape characteristics at two levels. 55 basins were analyzed as variables with topography, land cover and river system features in order to identify the watershed landscape character types. For watershed landscape, drainage density and degree of curvature were specified as special variables to directly reflect the regional differences of river system features. Then, we used the principal component analysis (PCA) method and hierarchical clustering algorithm based on the geographic information system (GIS) and statistical products and services solution (SPSS) to obtain results for clusters of watershed landscape which were divided into 8 characteristic groups. These groups highlighted watershed landscape characteristics of different river systems as well as key landscape characteristics that can serve as a basis for targeted protection of watershed landscape characteristics, thus helping to rationally develop multi-value landscape resources and promote coordinated development of trans-regions.Keywords: GIS, hierarchical clustering, landscape character, landscape typology, principal component analysis, watershed
Procedia PDF Downloads 22127330 The Appraisal of Construction Sites Productivity: In Kendall’s Concordance
Authors: Abdulkadir Abu Lawal
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For the dearth of reliable cardinal numerical data, the linked phenomena in productivity indices such as operational costs and company turnovers, etc. could not be investigated. This would not give us insight to the root of productivity problems at unique sites. So, ordinal ranking by professionals who were most directly involved with construction sites was applied for Kendall’s concordance. Responses gathered from independent architects, builders/engineers, and quantity surveyors were herein analyzed. They were responses based on factors that affect sites productivity, and these factors were categorized as head office factors, resource management effectiveness factors, motivational factors, and training/skill development factors. It was found that productivity is low and has to be improved in order to facilitate Nigerian efforts in bridging its infrastructure deficit. The significance of this work is underlined with the Kendall’s coefficient of concordance of 0.78, while remedial measures must be emphasized to stimulate better productivity. Further detailed study can be undertaken by using Fuzzy logic analysis on wider Delphi survey.Keywords: factors, Kendall's coefficient of concordance, magnitude of agreement, percentage magnitude of dichotomy, ranking variables
Procedia PDF Downloads 61827329 Growth of Droplet in Radiation-Induced Plasma of Own Vapour
Authors: P. Selyshchev
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The theoretical approach is developed to describe the change of drops in the atmosphere of own steam and buffer gas under irradiation. It is shown that the irradiation influences on size of stable droplet and on the conditions under which the droplet exists. Under irradiation the change of drop becomes more complex: the not monotone and periodical change of size of drop becomes possible. All possible solutions are represented by means of phase portrait. It is found all qualitatively different phase portraits as function of critical parameters: rate generation of clusters and substance density.Keywords: irradiation, steam, plasma, cluster formation, liquid droplets, evolution
Procedia PDF Downloads 43227328 Research on the Ecological Impact Evaluation Index System of Transportation Construction Projects
Authors: Yu Chen, Xiaoguang Yang, Lin Lin
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Traffic engineering construction is an important infrastructure for economic and social development. In the process of construction and operation, the ability to make a correct evaluation of the project's environmental impact appears to be crucial to the rational operation of existing transportation projects, the correct development of transportation engineering construction and the adoption of corresponding measures to scientifically carry out environmental protection work. Most of the existing research work on ecological and environmental impact assessment is limited to individual aspects of the environment and less to the overall evaluation of the environmental system; in terms of research conclusions, there are more qualitative analyses from the technical and policy levels, and there is a lack of quantitative research results and quantitative and operable evaluation models. In this paper, a comprehensive analysis of the ecological and environmental impacts of transportation construction projects is conducted, and factors such as the accessibility of data and the reliability of calculation results are comprehensively considered to extract indicators that can reflect the essence and characteristics. The qualitative evaluation indicators were screened using the expert review method, the qualitative indicators were measured using the fuzzy statistics method, the quantitative indicators were screened using the principal component analysis method, and the quantitative indicators were measured by both literature search and calculation. An environmental impact evaluation index system with the general objective layer, sub-objective layer and indicator layer was established, dividing the environmental impact of the transportation construction project into two periods: the construction period and the operation period. On the basis of the evaluation index system, the index weights are determined using the hierarchical analysis method, and the individual indicators to be evaluated are dimensionless, eliminating the influence of the original background and meaning of the indicators. Finally, the thesis uses the above research results, combined with the actual engineering practice, to verify the correctness and operability of the evaluation method.Keywords: transportation construction projects, ecological and environmental impact, analysis and evaluation, indicator evaluation system
Procedia PDF Downloads 9727327 Genetic Diversity Based Population Study of Freshwater Mud Eel (Monopterus cuchia) in Bangladesh
Authors: M. F. Miah, K. M. A. Zinnah, M. J. Raihan, H. Ali, M. N. Naser
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As genetic diversity is most important for existing, breeding and production of any fish; this study was undertaken for investigating genetic diversity of freshwater mud eel, Monopterus cuchia at population level where three ecological populations such as flooded area of Sylhet (P1), open water of Moulvibazar (P2) and open water of Sunamganj (P3) districts of Bangladesh were considered. Four arbitrary RAPD primers (OPB-12, C0-4, B-03 and OPB-08) were screened and RAPD banding patterns were analyzed among the populations considering 15 individuals of each population. In total 174, 138 and 149 bands were detected in the populations of P1, P2 and P3 respectively; however, each primer revealed less number of bands in each population. 100% polymorphic loci were recorded in P2 and P3 whereas only one monomorphic locus was observed in P1, recorded 97.5% polymorphism. Different genetic parameters such as inter-individual pairwise similarity, genetic distance, Nei genetic similarity, linkage distances, cluster analysis and allelic information, etc. were considered for measuring genetic diversity. The average inter-individual pairwise similarity was recorded 2.98, 1.47 and 1.35 in P1, P2 and P3 respectively. Considering genetic distance analysis, the highest distance 1 was recorded in P2 and P3 and the lowest genetic distance 0.444 was found in P2. The average Nei genetic similarity was observed 0.19, 0.16 and 0.13 in P1, P2 and P3, respectively; however, the average linkage distance was recorded 24.92, 17.14 and 15.28 in P1, P3 and P2 respectively. Based on linkage distance, genetic clusters were generated in three populations where 6 clades and 7 clusters were found in P1, 3 clades and 5 clusters were observed in P2 and 4 clades and 7 clusters were detected in P3. In addition, allelic information was observed where the frequency of p and q alleles were observed 0.093 and 0.907 in P1, 0.076 and 0.924 in P2, 0.074 and 0.926 in P3 respectively. The average gene diversity was observed highest in P2 (0.132) followed by P3 (0.131) and P1 (0.121) respectively.Keywords: genetic diversity, Monopterus cuchia, population, RAPD, Bangladesh
Procedia PDF Downloads 49727326 Volatility Switching between Two Regimes
Authors: Josip Visković, Josip Arnerić, Ante Rozga
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Based on the fact that volatility is time varying in high frequency data and that periods of high volatility tend to cluster, the most successful and popular models in modelling time varying volatility are GARCH type models. When financial returns exhibit sudden jumps that are due to structural breaks, standard GARCH models show high volatility persistence, i.e. integrated behaviour of the conditional variance. In such situations models in which the parameters are allowed to change over time are more appropriate. This paper compares different GARCH models in terms of their ability to describe structural changes in returns caused by financial crisis at stock markets of six selected central and east European countries. The empirical analysis demonstrates that Markov regime switching GARCH model resolves the problem of excessive persistence and outperforms uni-regime GARCH models in forecasting volatility when sudden switching occurs in response to financial crisis.Keywords: central and east European countries, financial crisis, Markov switching GARCH model, transition probabilities
Procedia PDF Downloads 22027325 A Simple User Administration View of Computing Clusters
Authors: Valeria M. Bastos, Myrian A. Costa, Matheus Ambrozio, Nelson F. F. Ebecken
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In this paper a very simple and effective user administration view of computing clusters systems is implemented in order of friendly provide the configuration and monitoring of distributed application executions. The user view, the administrator view, and an internal control module create an illusionary management environment for better system usability. The architecture, properties, performance, and the comparison with others software for cluster management are briefly commented.Keywords: big data, computing clusters, administration view, user view
Procedia PDF Downloads 32427324 Eco-Environmental Vulnerability Evaluation in Mountain Regions Using Remote Sensing and Geographical Information System: A Case Study of Pasol Gad Watershed of Garhwal Himalaya, India
Authors: Suresh Kumar Bandooni, Mirana Laishram
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The Mid Himalaya of Garhwal Himalaya in Uttarakhand (India) has a complex Physiographic features withdiversified climatic conditions and therefore it is suspect to environmental vulnerability. Thenatural disasters and also anthropogenic activities accelerate the rate of environmental vulnerability. To analyse the environmental vulnerability, we have used geoinformatics technologies and numerical models and it is adoptedby using Spatial Principal Component Analysis (SPCA). The model consist of many factors such as slope, landuse/landcover, soil, forest fire risk, landslide susceptibility zone, human population density and vegetation index. From this model, the environmental vulnerability integrated index (EVSI) is calculated for Pasol Gad Watershed of Garhwal Himalaya for the years 1987, 2000, and 2013 and the Vulnerability is classified into five levelsi.e. Very low, low, medium, high and very highby means of cluster principle. The resultsforeco-environmental vulnerability distribution in study area shows that medium, high and very high levels are dominating in the area and it is mainly caused by the anthropogenic activities and natural disasters. Therefore, proper management forconservation of resources is utmost necessity of present century. It is strongly believed that participation at community level along with social worker, institutions and Non-governmental organization (NGOs) have become a must to conserve and protect the environment.Keywords: eco-environment vulnerability, spatial principal component analysis, remote sensing, geographic information system, institutions, Himalaya
Procedia PDF Downloads 25427323 Modeling and Analyzing Controversy in Large-Scale Cyber-Argumentation
Authors: Najla Althuniyan
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Online discussions take place across different platforms. These discussions have the potential to extract crowd wisdom and capture the collective intelligence from a different perspective. However, certain phenomena, such as controversy, often appear in online argumentation that makes the discussion between participants heated. Heated discussions can be used to extract new knowledge. Therefore, detecting the presence of controversy is an essential task to determine if collective intelligence can be extracted from online discussions. This paper uses existing measures for estimating controversy quantitatively in cyber-argumentation. First, it defines controversy in different fields, and then it identifies the attributes of controversy in online discussions. The distributions of user opinions and the distance between opinions are used to calculate the controversial degree of a discussion. Finally, the results from each controversy measure are discussed and analyzed using an empirical study generated by a cyber-argumentation tool. This is an improvement over the existing measurements because it does not require ground-truth data or specific settings and can be adapted to distribution-based or distance-based opinions.Keywords: online argumentation, controversy, collective intelligence, agreement analysis, collaborative decision-making, fuzzy logic
Procedia PDF Downloads 11227322 Volatile Compounds and Sensory Characteristics of Herbal Teas and Bush Tea Blends with Selected Herbal Teas South Africa
Authors: Florence Malongane, Lyndy J. McGaw, Legesse K. Debusho, Fhatuwani N. Mudau
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Rooibos (Aspalathus linearis (Burm.f.) R.Dahlgren), honeybush (Cyclopia Vent. species), bush tea (Athrixia phylicoides DC.) and special tea (Monsonia burkeana) are traditionally consumed herbal teas in South Africa. The volatile and sensory qualities of rooibos and honeybush tea have previously been described although there is a dearth of information regarding the sensory attributes and volatile compounds analysis of special tea and bush tea. The objective of this study was to describe the sensory properties, compare the differences in descriptive sensory analysis (DSA) and volatile compounds of bush tea, special, rooibos, honeybush and the blend of bush tea with special, honeybush and rooibos in a 1:1 ratio and subsequently to determine the influence of blending bush tea with other herbal teas. DSA was used to assess the sensory attributes of the teas while gas chromatography–mass spectrometry (GC-MS) was used to quantitatively determine the volatile components of the teas. Rooibos tea and honeybush tea had an overall sweet-caramel, honey-sweet, perfume floral and woody aroma with slight astringency, consistent with the taste and aftertaste attributes. In contrast, bush tea and special tea depicted green-cut grass, dry green herbal, cooked spinach aroma as well as taste and aftertaste characteristics. GC-MS analyses revealed that the seven tea samples had similar major volatiles, including 2-furanmethanol, 2-methoxy-4-vinylphenol, acetic acid, D-limonene terpene and phytol. Cluster analysis revealed that the sweet and woody flavour of honeybush and rooibos were ascribed to the presence of á-myrcene, phenylethyl alcohol, phytol and vanillin. The bitter, medicinal flavour attributes of special tea were attributed to (-)-carvone. Blending of bush tea with rooibos and honeybush tea toned down its aversive flavour components, typically the bitter, green-cut grass and herbal properties, thus minimising the possibility of consumer aversion.Keywords: bush tea, rooibos tea, honeybush tea, sensory, volatile compounds
Procedia PDF Downloads 17727321 Online Classroom Instruction and Collaborative Learning: Problems and Prospects Among Undergraduate Students of Obafemi Awolowo University, Ile-Ife, Nigeria
Authors: Bello Theodora O., Animola Odunayo V., Owoade Johnson T.
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With the advent of Covid-19, online classroom instruction became a very important mode of instruction delivery during which learners were engaged in both collaborative and online interactive learning process, but along with it are challenges as well as its deliverables. This study therefore investigated the various online platform used by the students for learning among fresh undergraduate students of Obafemi Awolowo University, Ile-Ife, Osun Sate. It also assessed the student’s perception towards online learning in the university and examined the influence of collaborative learning among the students. Lastly, it examined the problems that are associated with collaborative online learning instruction in the university. These were with a view to providing empirical information on problems and prospects of online classroom instruction among fresh undergraduate physical science students of Obafemi Awolowo University, Ile-Ife. The study employed a descriptive survey research technique. The population comprised all the fresh undergraduates in physical science departments of Obafemi Awolowo University, Ile-Ife. The sample consisted two hundred freshmen in physical science departments of Obafemi Awolowo University, Ile-Ife, who were selected using simple random techniques. During the selection, a questionnaire was used to collect data from the respondents. The data were analyzed using appropriate descriptive of frequency, simple percentage, and mean. Results showed that Google Meet 149(74.5%), Telegram 120(60.0%), and Google Classroom 143(71.5%), are the prominent online classroom instruction used by the students in Obafemi Awolowo University, Ile-Ife. The results also showed that the freshmen’s perception towards online classroom instruction in Obafemi Awolowo University, Ile-Ife is low with cluster mean of 2.97. It further revealed that collaborative learning enhances the learning ability of below average learners more than that of the above average and average students (73.6%). Finally, the result showed that they are affirmative of the problems associated with online classroom instruction in Obafemi Awolowo University, Ile-Ife with cluster mean of 3.01. The result concluded that most Online platform used by the fresher’s students in Obafemi Awolowo University, Ile-Ife are Google Meet, Telegram and Google Classroom. The students have negatives perception towards online classroom instruction and the students are affirmative of the problems associated with online classroom instruction among physical science freshmen in Obafemi Awolowo University, Ile-Ife.Keywords: online, instruction, freshmen, physical science, collaborative
Procedia PDF Downloads 5327320 On Stochastic Models for Fine-Scale Rainfall Based on Doubly Stochastic Poisson Processes
Authors: Nadarajah I. Ramesh
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Much of the research on stochastic point process models for rainfall has focused on Poisson cluster models constructed from either the Neyman-Scott or Bartlett-Lewis processes. The doubly stochastic Poisson process provides a rich class of point process models, especially for fine-scale rainfall modelling. This paper provides an account of recent development on this topic and presents the results based on some of the fine-scale rainfall models constructed from this class of stochastic point processes. Amongst the literature on stochastic models for rainfall, greater emphasis has been placed on modelling rainfall data recorded at hourly or daily aggregation levels. Stochastic models for sub-hourly rainfall are equally important, as there is a need to reproduce rainfall time series at fine temporal resolutions in some hydrological applications. For example, the study of climate change impacts on hydrology and water management initiatives requires the availability of data at fine temporal resolutions. One approach to generating such rainfall data relies on the combination of an hourly stochastic rainfall simulator, together with a disaggregator making use of downscaling techniques. Recent work on this topic adopted a different approach by developing specialist stochastic point process models for fine-scale rainfall aimed at generating synthetic precipitation time series directly from the proposed stochastic model. One strand of this approach focused on developing a class of doubly stochastic Poisson process (DSPP) models for fine-scale rainfall to analyse data collected in the form of rainfall bucket tip time series. In this context, the arrival pattern of rain gauge bucket tip times N(t) is viewed as a DSPP whose rate of occurrence varies according to an unobserved finite state irreducible Markov process X(t). Since the likelihood function of this process can be obtained, by conditioning on the underlying Markov process X(t), the models were fitted with maximum likelihood methods. The proposed models were applied directly to the raw data collected by tipping-bucket rain gauges, thus avoiding the need to convert tip-times to rainfall depths prior to fitting the models. One advantage of this approach was that the use of maximum likelihood methods enables a more straightforward estimation of parameter uncertainty and comparison of sub-models of interest. Another strand of this approach employed the DSPP model for the arrivals of rain cells and attached a pulse or a cluster of pulses to each rain cell. Different mechanisms for the pattern of the pulse process were used to construct variants of this model. We present the results of these models when they were fitted to hourly and sub-hourly rainfall data. The results of our analysis suggest that the proposed class of stochastic models is capable of reproducing the fine-scale structure of the rainfall process, and hence provides a useful tool in hydrological modelling.Keywords: fine-scale rainfall, maximum likelihood, point process, stochastic model
Procedia PDF Downloads 26827319 Experts' Perception of Secondary Education Quality Management Challenges in Ethiopia
Authors: Aklilu Alemu, Tak Cheung Chan
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Following the intensification of secondary education in the developing world, the attention of Ethiopia has currently shifted to its quality education and its management. This study is aimed to explore experts’ perceptions of quality management challenges in secondary education in Ethiopia. The researchers employed a case study design recruiting participating supervisors from the Ministry of Education, region, zone, wereda, and cluster by using a purposeful sampling technique. Twenty-six interviewees took part in this study. The researchers employed NVivo 8 versions together with a thematic analysis process to analyze the data. This study revealed that major problems that affected quality management practices in Ethiopia were: lack of qualified experts at all levels; lack of accountability in every echelon; the changing nature of teacher education; the ineffectiveness of teacher-licensing programs; and lack of educational budget and the problem of utilizing this limited budget. The study concluded that the experts at different levels were not genuinely fulfilling their roles and responsibilities. Therefore, the Ministry of Finance and Economic Development, together with the concerned parties, needs to reconsider budget allocation for secondary education.Keywords: education quality, Ethiopia, quality challenge, quality management, secondary education
Procedia PDF Downloads 20827318 Molecular Topology and TLC Retention Behaviour of s-Triazines: QSRR Study
Authors: Lidija R. Jevrić, Sanja O. Podunavac-Kuzmanović, Strahinja Z. Kovačević
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Quantitative structure-retention relationship (QSRR) analysis was used to predict the chromatographic behavior of s-triazine derivatives by using theoretical descriptors computed from the chemical structure. Fundamental basis of the reported investigation is to relate molecular topological descriptors with chromatographic behavior of s-triazine derivatives obtained by reversed-phase (RP) thin layer chromatography (TLC) on silica gel impregnated with paraffin oil and applied ethanol-water (φ = 0.5-0.8; v/v). Retention parameter (RM0) of 14 investigated s-triazine derivatives was used as dependent variable while simple connectivity index different orders were used as independent variables. The best QSRR model for predicting RM0 value was obtained with simple third order connectivity index (3χ) in the second-degree polynomial equation. Numerical values of the correlation coefficient (r=0.915), Fisher's value (F=28.34) and root mean square error (RMSE = 0.36) indicate that model is statistically significant. In order to test the predictive power of the QSRR model leave-one-out cross-validation technique has been applied. The parameters of the internal cross-validation analysis (r2CV=0.79, r2adj=0.81, PRESS=1.89) reflect the high predictive ability of the generated model and it confirms that can be used to predict RM0 value. Multivariate classification technique, hierarchical cluster analysis (HCA), has been applied in order to group molecules according to their molecular connectivity indices. HCA is a descriptive statistical method and it is the most frequently used for important area of data processing such is classification. The HCA performed on simple molecular connectivity indices obtained from the 2D structure of investigated s-triazine compounds resulted in two main clusters in which compounds molecules were grouped according to the number of atoms in the molecule. This is in agreement with the fact that these descriptors were calculated on the basis of the number of atoms in the molecule of the investigated s-triazine derivatives.Keywords: s-triazines, QSRR, chemometrics, chromatography, molecular descriptors
Procedia PDF Downloads 38827317 Comparison of Rainfall Trends in the Western Ghats and Coastal Region of Karnataka, India
Authors: Vinay C. Doranalu, Amba Shetty
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In recent days due to climate change, there is a large variation in spatial distribution of daily rainfall within a small region. Rainfall is one of the main end climatic variables which affect spatio-temporal patterns of water availability. The real task postured by the change in climate is identification, estimation and understanding the uncertainty of rainfall. This study intended to analyze the spatial variations and temporal trends of daily precipitation using high resolution (0.25º x 0.25º) gridded data of Indian Meteorological Department (IMD). For the study, 38 grid points were selected in the study area and analyzed for daily precipitation time series (113 years) over the period 1901-2013. Grid points were divided into two zones based on the elevation and situated location of grid points: Low Land (exposed to sea and low elevated area/ coastal region) and High Land (Interior from sea and high elevated area/western Ghats). Time series were applied to examine the spatial analysis and temporal trends in each grid points by non-parametric Mann-Kendall test and Theil-Sen estimator to perceive the nature of trend and magnitude of slope in trend of rainfall. Pettit-Mann-Whitney test is applied to detect the most probable change point in trends of the time period. Results have revealed remarkable monotonic trend in each grid for daily precipitation of the time series. In general, by the regional cluster analysis found that increasing precipitation trend in shoreline region and decreasing trend in Western Ghats from recent years. Spatial distribution of rainfall can be partly explained by heterogeneity in temporal trends of rainfall by change point analysis. The Mann-Kendall test shows significant variation as weaker rainfall towards the rainfall distribution over eastern parts of the Western Ghats region of Karnataka.Keywords: change point analysis, coastal region India, gridded rainfall data, non-parametric
Procedia PDF Downloads 28927316 Undernutrition Among Children Below Five Years of Age in Uganda: A Deep Dive into Space and Time
Authors: Vallence Ngabo Maniragaba
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This study aimed at examining the variations of undernutrition among children below 5 years of age in Uganda. The approach of spatial and spatiotemporal analysis helped in identifying cluster patterns, hot spots and emerging hot spots. Data from the 6 Uganda Demographic and Health Surveys spanning from 1990 to 2016 were used with the main outcome variable being undernutrition among children <5 years of age. All data that were relevant to this study were retrieved from the survey datasets and combined with the 214 shape files for the districts of Uganda to enable spatial and spatiotemporal analysis. Spatial maps with the spatial distribution of the prevalence of undernutrition, both in space and time, were generated using ArcGIS Pro version 2.8. Moran’s I, an index of spatial autocorrelation, rules out doubts of spatial randomness in order to identify spatially clustered patterns of hot or cold spot areas. Furthermore, space-time cubes were generated to establish the trend in undernutrition as well as to mirror its variations over time and across Uganda. Moreover, emerging hot spot analysis was done to help identify the patterns of undernutrition over time. The results indicate a heterogeneous distribution of undernutrition across Uganda and the same variations were also evident over time. Moran’s I index confirmed spatial clustered patterns as opposed to random distributions of undernutrition prevalence. Four hot spot areas, namely; the Karamoja, the Sebei, the West Nile and the Toro regions were significantly evident, most of the central parts of Uganda were identified as cold spot clusters, while most of Western Uganda, the Acholi and the Lango regions had no statistically significant spatial patterns by the year 2016. The spatio-temporal analysis identified the Karamoja and Sebei regions as clusters of persistent, consecutive and intensifying hot spots, West Nile region was identified as a sporadic hot spot area while the Toro region was identified with both sporadic and emerging hotspots. In conclusion, undernutrition is a silent pandemic that needs to be handled with both hands. At 31.2 percent, the prevalence is still very high and unpleasant. The distribution across the country is nonuniform with some areas such as the Karamoja, the West Nile, the Sebei and the Toro regions being epicenters of undernutrition in Uganda. Over time, the same areas have experienced and exhibited high undernutrition prevalence. Policymakers, as well as the implementers, should bear in mind the spatial variations across the country and prioritize hot spot areas in order to have efficient, timely and region-specific interventions.Keywords: undernutrition, spatial autocorrelation, hotspots analysis, geographically weighted regressions, emerging hotspots analysis, under-fives, Uganda
Procedia PDF Downloads 8027315 An Intelligent Controller Augmented with Variable Zero Lag Compensation for Antilock Braking System
Authors: Benjamin Chijioke Agwah, Paulinus Chinaenye Eze
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Antilock braking system (ABS) is one of the important contributions by the automobile industry, designed to ensure road safety in such way that vehicles are kept steerable and stable when during emergency braking. This paper presents a wheel slip-based intelligent controller with variable zero lag compensation for ABS. It is required to achieve a very fast perfect wheel slip tracking during hard braking condition and eliminate chattering with improved transient and steady state performance, while shortening the stopping distance using effective braking torque less than maximum allowable torque to bring a braking vehicle to a stop. The dynamic of a vehicle braking with a braking velocity of 30 ms⁻¹ on a straight line was determined and modelled in MATLAB/Simulink environment to represent a conventional ABS system without a controller. Simulation results indicated that system without a controller was not able to track desired wheel slip and the stopping distance was 135.2 m. Hence, an intelligent control based on fuzzy logic controller (FLC) was designed with a variable zero lag compensator (VZLC) added to enhance the performance of FLC control variable by eliminating steady state error, provide improve bandwidth to eliminate the effect of high frequency noise such as chattering during braking. The simulation results showed that FLC- VZLC provided fast tracking of desired wheel slip, eliminate chattering, and reduced stopping distance by 70.5% (39.92 m), 63.3% (49.59 m), 57.6% (57.35 m) and 50% (69.13 m) on dry, wet, cobblestone and snow road surface conditions respectively. Generally, the proposed system used effective braking torque that is less than the maximum allowable braking torque to achieve efficient wheel slip tracking and overall robust control performance on different road surfaces.Keywords: ABS, fuzzy logic controller, variable zero lag compensator, wheel slip tracking
Procedia PDF Downloads 14327314 Effective Wind-Induced Natural Ventilation in a Residential Apartment Typology
Authors: Tanvi P. Medshinge, Prasad Vaidya, Monisha E. Royan
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In India, cooling loads in residential sector is a major contributor to its total energy consumption. Due to the increasing cooling need, the market penetration of air-conditioners is further expected to rise. Natural Ventilation (NV), however, possesses great potential to save significant energy consumption especially for residential buildings in moderate climates. As multifamily residential apartment buildings are designed by repetitive use of prototype designs, deriving individual NV based design prototype solutions for a combination of different wind incidence angles and orientations would provide significant opportunity to address the rise in cooling loads by residential sector. This paper presents the results of NV performance of a selected prototype apartment design with a cluster of four units in Pune, India, and an attempt to improve the NV performance through design modifications. The water table apparatus, a physical modelling tool, is used to study the flow patterns and simulate wind-induced NV performance. Quantification of NV performance is done by post processing images captured from video recordings in terms of percentage of area with good and poor access to ventilation. NV performance of the existing design for eight wind incidence angles showed that of the cluster of four units, the windward units showed good access to ventilation for all rooms, and the leeward units had lower access to ventilation with the bedrooms in the leeward units having the least access. The results showed improved performance in all the units for all wind incidence angles to more than 80% good access to ventilation. Some units showed an additional improvement to more than 90% good access to ventilation. This process of design and performance evaluation improved some individual units from 0% to 100% for good access to ventilation. The results demonstrate the ease of use and the power of the water table apparatus for performance-based design to simulate wind induced NV.Keywords: fluid dynamics, prototype design, natural ventilation, simulations, water table apparatus, wind incidence angles
Procedia PDF Downloads 22127313 Geostatistical Simulation of Carcinogenic Industrial Effluent on the Irrigated Soil and Groundwater, District Sheikhupura, Pakistan
Authors: Asma Shaheen, Javed Iqbal
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The water resources are depleting due to an intrusion of industrial pollution. There are clusters of industries including leather tanning, textiles, batteries, and chemical causing contamination. These industries use bulk quantity of water and discharge it with toxic effluents. The penetration of heavy metals through irrigation from industrial effluent has toxic effect on soil and groundwater. There was strong positive significant correlation between all the heavy metals in three media of industrial effluent, soil and groundwater (P < 0.001). The metal to the metal association was supported by dendrograms using cluster analysis. The geospatial variability was assessed by using geographically weighted regression (GWR) and pollution model to identify the simulation of carcinogenic elements in soil and groundwater. The principal component analysis identified the metals source, 48.8% variation in factor 1 have significant loading for sodium (Na), calcium (Ca), magnesium (Mg), iron (Fe), chromium (Cr), nickel (Ni), lead (Pb) and zinc (Zn) of tannery effluent-based process. In soil and groundwater, the metals have significant loading in factor 1 representing more than half of the total variation with 51.3 % and 53.6 % respectively which showed that pollutants in soil and water were driven by industrial effluent. The cumulative eigen values for the three media were also found to be greater than 1 representing significant clustering of related heavy metals. The results showed that heavy metals from industrial processes are seeping up toxic trace metals in the soil and groundwater. The poisonous pollutants from heavy metals turned the fresh resources of groundwater into unusable water. The availability of fresh water for irrigation and domestic use is being alarming.Keywords: groundwater, geostatistical, heavy metals, industrial effluent
Procedia PDF Downloads 22527312 Bacterial Diversity in Human Intestinal Microbiota and Correlations with Nutritional Behavior, Physiology, Xenobiotics Intake and Antimicrobial Resistance in Obese, Overweight and Eutrophic Individuals
Authors: Thais O. de Paula, Marjorie R. A. Sarmiento, Francis M. Borges, Alessandra B. Ferreira-Machado, Juliana A. Resende, Dioneia E. Cesar, Vania L. Silva, Claudio G. Diniz
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Obesity is currently a worldwide public health threat, being considered a pandemic multifactorial disease related to the human gut microbiota (GM). Add to that GM is considered an important reservoir of antimicrobial resistance genes (ARG) and little is known on GM and ARG in obesity, considering the altered physiology and xenobiotics intake. As regional and social behavior may play important roles in GM modulation, and most of the studies are based on small sample size and various methodological approaches resulting in difficulties for data comparisons, this study was focused on the investigation of GM bacterial diversity in obese (OB), overweight (OW) and eutrophic individuals (ET) considering their nutritional, clinical and social characteristics; and comparative screening of AGR related to their physiology and xenobiotics intake. Microbial community was accessed by FISH considering phyla as a taxonomic level, and PCR-DGGE followed by dendrograms evaluation (UPGMA method) from fecal metagenome of 72 volunteers classified according to their body mass index (BMI). Nutritional, clinical, social parameters and xenobiotics intake were recorded for correlation analysis. The fecal metagenome was also used as template for PCR targeting 59 different ARG. Overall, 62% of OB were hypertensive, and 12% or 4% were, regarding the OW and ET individuals. Most of the OB were rated as low income (80%). Lower relative bacterial densities were observed in the OB compared to ET for almost all studied taxa (p < 0.05) with Firmicutes/Bacteroidetes ratio increased in the OB group. OW individuals showed a bacterial density representative of GM more likely to the OB. All the participants were clustered in 3 different groups based on the PCR-DGGE fingerprint patterns (C1, C2, C3), being OB mostly grouped in C1 (83.3%) and ET mostly grouped in C3 (50%). The cluster C2 showed to be transitional. Among 27 ARG detected, a cluster of 17 was observed in all groups suggesting a common core. In general, ARG were observed mostly within OB individuals followed by OW and ET. The ratio between ARG and bacterial groups may suggest that AGR were more related to enterobacteria. Positive correlations were observed between ARG and BMI, calories and xenobiotics intake (especially use of sweeteners). As with nutritional and clinical characteristics, our data may suggest that GM of OW individuals behave in a heterogeneous pattern, occasionally more likely to the OB or to the ET. Regardless the regional and social behaviors of our population, the methodological approaches in this study were complementary and confirmatory. The imbalance of GM over the health-disease interface in obesity is a matter of fact, but its influence in host's physiology is still to be clearly elucidated to help understanding the multifactorial etiology of obesity. Although the results are in agreement with observations that GM is altered in obesity, the altered physiology in OB individuals seems to be also associated to the increased xenobiotics intake and may interfere with GM towards antimicrobial resistance, as observed by the fecal metagenome and ARG screening. Support: FAPEMIG, CNPQ, CAPES, PPGCBIO/UFJF.Keywords: antimicrobial resistance, bacterial diversity, gut microbiota, obesity
Procedia PDF Downloads 16127311 Revealing the Genome Based Biosynthetic Potential of a Streptomyces sp. Isolate BR123 Presenting Broad Spectrum Antimicrobial Activities
Authors: Neelma Ashraf
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Actinomycetes, particularly genus Streptomyces is of great importance due to their role in the discovery of new natural products, particularly antimicrobial secondary metabolites in the medicinal science and biotechnology industry. Different Streptomyces strains were isolated from Helianthus annuus plants and tested for antibacterial and antifungal activities. The most promising five strains were chosen for further investigation, and growth conditions for antibiotic synthesis were optimised. The supernatants were extracted in different solvents, and the extracted products were analyzed using liquid chromatography-mass spectrometry (LC-MS) and biological testing. From one of the potent strains Streptomyces globusus sp. BR123, a compound lavendamycin was identified using these analytical techniques. In addition, this potent strain also produces a strong antifungal polyene compound with a quasimolecular ion of 2072. Streptomyces sp. BR123 was genome sequenced because of its promising antimicrobial potential in order to identify the gene cluster responsible for analyzed compound “lavendamycin”. The genome analysis yielded candidate genes responsible for the production of this potent compound. The genome sequence of 8.15 Mb of Streptomyces sp. isolate BR123 with a GC content of 72.63% and 8103 protein coding genes was attained. Many antimicrobial, antiparasitic, and anticancerous compounds were detected through multiple biosynthetic gene clusters predicted by in-Silico analysis. Though, the novelty of metabolites was determined through the insignificant resemblance with known biosynthetic gene clusters. The current study gives insight into the bioactive potential of Streptomyces sp. isolate BR123 with respect to the synthesis of bioactive secondary metabolites through genomic and spectrometric analysis. Moreover, the comparative genome study revealed the connection of isolate BR123 with other Streptomyces strains, which could expand the knowledge of this genus and the mechanism involved in the discovery of new antimicrobial metabolites.Keywords: streptomyces, secondary metabolites, genome, biosynthetic gene clusters, high performance liquid chromatography, mass spectrometry
Procedia PDF Downloads 6427310 Exploring Management of the Fuzzy Front End of Innovation in a Product Driven Startup Company
Authors: Dmitry K. Shaytan, Georgy D. Laptev
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In our research we aimed to test a managerial approach for the fuzzy front end (FFE) of innovation by creating controlled experiment/ business case in a breakthrough innovation development. The experiment was in the sport industry and covered all aspects of the customer discovery stage from ideation to prototyping followed by patent application. In the paper we describe and analyze mile stones, tasks, management challenges, decisions made to create the break through innovation, evaluate overall managerial efficiency that was at the considered FFE stage. We set managerial outcome of the FFE stage as a valid product concept in hand. In our paper we introduce hypothetical construct “Q-factor” that helps us in the experiment to distinguish quality of FFE outcomes. The experiment simulated for entrepreneur the FFE of innovation and put on his shoulders responsibility for the outcome of valid product concept. While developing managerial approach to reach the outcome there was a decision to look on product concept from the cognitive psychology and cognitive science point of view. This view helped us to develop the profile of a person whose projection (mental representation) of a new product could optimize for a manager or entrepreneur FFE activities. In the experiment this profile was tested to develop breakthrough innovation for swimmers. Following the managerial approach the product concept was created to help swimmers to feel/sense water. The working prototype was developed to estimate the product concept validity and value added effect for customers. Based on feedback from coachers and swimmers there were strong positive effect that gave high value for customers, and for the experiment – the valid product concept being developed by proposed managerial approach for the FFE. In conclusions there is a suggestion of managerial approach that was derived from experiment.Keywords: concept development, concept testing, customer discovery, entrepreneurship, entrepreneurial management, idea generation, idea screening, startup management
Procedia PDF Downloads 43727309 The Nonlinear Optical Properties Analysis of AlPc-Cl Organic Compound
Authors: M. Benhaliliba, A. Ben Ahmed, C.E. Benouis, A.Ayeshamariam
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The properties of nonlinear optical NLOs are examined, and the results confirm the 2.19 eV HOMO-LUMO mismatch. In the Al-Pc cluster, certain functional bond lengths and bond angles have been observed. The Quantum chemical method (DFT and TD-DFT) and Vibrational spectra properties of AlPc are studied. X-ray pattern reveals the crystalline structure along with the (242) orientation of the AlPc organic thin layer. UV-Vis shows the frequency selective behavior of the device. The absorbance of such layer exhibits a high value within the UV range and two consecutive peaks within visible range. Spin coating is used to make an organic diode based on the Aluminium-phthalocynanine (AlPc-Cl) molecule. Under dark and light conditions, electrical characterization of Ag/AlPc/Si/Au is obtained. The diode's high rectifying capability (about 1x104) is subsequently discovered. While the height barrier is constant and saturation current is greatly reliant on light, the ideality factor of such a diode increases to 6.9 which confirms the non-ideality of such a device. The Cheung-Cheung technique is employed to further the investigation and gain additional data such as series resistance and barrier height.Keywords: AlPc-Cl organic material, nonlinear optic, optical filter, diode
Procedia PDF Downloads 129