Search results for: statistical data

Authors: Takayuki Konishi, Kakeru Yazawa, Mariko Kondo

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This study examines developmental change in the production of epenthetic vowels by Japanese learners of English in relation to acquisition of L2 English speech rhythm. Seventy-two Japanese learners of English in the J-AESOP corpus were divided into lower- and higher-level learners according to their proficiency score and the frequency of vowel epenthesis. Three learners were excluded because no vowel epenthesis was observed in their utterances. The analysis of their read English speech data showed no statistical difference between lower- and higher-level learners, implying the absence of any developmental change in durations of epenthetic vowels. This result, together with the findings of previous studies, will be discussed in relation to the transfer of L1 phonology and manifestation of L2 English rhythm.

Keywords: vowel epenthesis, Japanese learners of English, L2 speech corpus, speech rhythm

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Authors: Ibraheem Musa Oluwatoyin, Olawuni Adisa, Abdulraheem Yinusa Owolabi

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Nigeria's sports industry has grown, but ineffective management, inadequate marketing, and limited stakeholder engagement hinder progress. Effective marketing strategies are crucial, yet empirical research on their impact on Nigerian sports managers is scarce. This study investigates the impact of sports and entertainment marketing strategies on the professional practices of sports managers in Nigeria, employing a quantitative research design grounded in the Theory of Planned Behavior. The target population comprises 1,108 sports managers across various organizations in Nigeria, with a stratified random sample of 301 participants, ensuring representativeness based on organizational type (sports commissions/councils) and geographical zones. Data was collected using a structured questionnaire, which included sections on demographic information, the evaluation of marketing strategies, and their impact on decision-making, operational efficiency, stakeholder engagement, and performance. The questionnaire items were adapted from validated scales in marketing and sports management literature, achieving a Cronbach’s alpha of 0.85, indicating high internal consistency. Data collection occurred over eight weeks through both online and face-to-face surveys, ensuring ethical compliance with informed consent and data anonymization. Descriptive and inferential statistical methods, including Pearson Product Moment Correlation (PPMC), were employed for data analysis. The PPMC analyses revealed statistically significant relationships between digital platform marketing (r = 0.63, p = 0.000), sports marketing experience (r = 0.51, p = 0.000), and producing engaging sports content (r = 0.61, p = 0.000) with professional practices. These results suggest that digital platform marketing, sports marketing experience, and the creation of engaging content significantly enhance the effectiveness and performance of sports managers in Nigeria. The study contributes valuable insights for stakeholders in Nigeria’s sports industry, providing actionable recommendations for improving sports management practices through strategic marketing approaches.

Keywords: professional practice, digital platform, experience sports marketing, producing engaging sports content

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Authors: Samson Olusegun Apantaku, Adetayo K. Aromolaran, Giyatt Hammed

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The study assessed the use of participatory research methods among Federal University of Agriculture Abeokuta, Nigeria (FUNAAB) researchers. Simple random sampling technique was used to select one hundred and twenty respondents from the study area. Data were collected using a questionnaire. Data collected were subjected to descriptive and inferential statistical analyses. Results showed that 75.8% of the respondents were males while only 21.3% were female. The mean age of the respondents was 38.8 years and most (77.5%) of them were married. 15% of the respondents were in professorial cadre, 21.7% and 20% of the respondents were senior lecturers/fellow and lecturer/research fellow I&II respectively. The results further revealed that 93.3% of the respondents were aware of participatory research methods and 82.5% of the respondents have utilized it before. The average period of usage was 2.7 years and participation by consultation (86.7%) and interactive participation (76.7%) were mostly used. Most (94.2%) indicated that fund was the major hindrance to the use of participatory research methods. The result of correlation analysis showed that there was significant relationship between the years of research experience, designation post (status) of the respondents and usage of participatory research methods (r = 0.034, 0.031, p < 0.05). The study concluded that most of the researchers were aware of and used participatory research methods, which could influence the quality of their research or make it acceptable to the end users. It was recommended that more funds should be made available and accessible for participatory research. All researchers should be trained and encouraged to make use of participatory research methods in their research activities so as to achieve effective research and capacity building that could enhance adoption of technologies and increase agricultural production in the country. Farmers’ capacity to participate in agricultural research should also be enhanced.

Keywords: participatory research, participatory research methods, awareness, utilization

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Authors: L. Edirisinghe, P. Mukherjee, H. Edirisinghe

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Virtual Container Yard (VCY) is a modern concept that helps to reduce the empty container repositioning cost of carriers. The concept of VCY is based on container interchange between shipping lines. Although this mechanism has been theoretically accepted by the shipping community as a feasible solution, it has not yet achieved the necessary momentum among container shipping lines (CSL). This paper investigates whether there is any legal influence on this industry myopia about the VCY. It is believed that this is the first publication that focuses on the legal aspects of container exchange between carriers. Not much literature on this subject is available. This study establishes with statistical evidence that there is a phobia prevailing in the shipping industry that exchanging containers with other carriers may lead to various legal implications. The complexity of exchange is two faceted. CSLs assume that offering a container to another carrier (obviously, a competitor in terms of commercial context) or using a container offered by another carrier may lead to undue legal implications. This research reveals that this fear is reflected through four types of perceived components, namely: shipping associate; warehouse associate; network associate; and trading associate. These components carry eighteen subcomponents that comprehensively cover the entire process of a container shipment. The statistical explanation has been supported through regression analysis; INCO terms were used to illustrate the shipping process.

Keywords: virtual container yard, legal, maritime law, inventory

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Authors: Perihan Hazel Kaya, Mustafa Göktuğ Kaya

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Turkey has been a busy destination for immigration and it will always be as it is the geographical and cultural exit door of the East and the entrance door of the West. Among these immigrations, we can see the victims of human trafficking, human smuggling, refugees and those who came here to work and live. Human smuggling, which is one of the movements of illegal immigration, is the specific subject of this work. The fact that our country lies on the transportation destinations between the continents of Asia, Europe and Africa, the crime of human smuggling is highly committed in our country. The aim of the victims of human smuggling is to go to a more developed country to have higher standards of living, to get a better job and to escape from the economic and social instability of their countries. The human smuggling, which has gathered pace due to the improvements in communication and transportation, is not a regional issue and has become one of the most important problems for almost all countries. Accordingly, the reasons, methods and extent of human smuggling will be dealt firstly. Later, it will be studied why Turkey is preffered in human smuggling. Finally, statistical data will be given to show how much human smuggling has gone far in Turkey and the study will be finished with that what is being done and what can be done to prevent it.

Keywords: human smuggling, immigration, immigrator, human trafficking, Turkey

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Authors: Mohamed Nabhan

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The research aims to build a measure of sensory preferences for (wrestling and boxing) players. The researchers used the descriptive approach and a sample of (8) consisting of (40) wrestling players, (40) boxing players with different scales, and they were chosen in a deliberate random way, and the most important results were that there were statistically significant differences between wrestlers and boxers in the sensory preferences of their senses. There is no indication in the sensory preferences for the senses of “sight and hearing” and that the significance is in favor of the wrestlers in the senses of “sight and touch,” and there is a convergence in the sense of hearing. Through the value of the averagesAfter collecting the data and statistical treatments and the results reached by the researcher, it was possible to reach: The following conclusions and recommendations: There are differences between wrestling and boxing players in their sensory preferences, the senses used in learning, due to several reasons, the most important of which may be as follows:- Scales for the player and for each sport separately. The nature of the game, the performance of skills, and dealing with the opponent or competitor.Tools used in performance and training.

Keywords: sensory preferences, sensory scale, wrestling players, boxing players

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Authors: Ankur Mundhra, Shubhadeep Chakraborty, Y. R. Singh, Vishal Das

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Seismic data scaling affects the dynamic range of a data and with present day lower costs of storage and higher reliability of Hard Disk data, scaling is not suggested. However, in dealing with data of different vintages, which perhaps were processed in 16 bits or even 8 bits and are need to be processed with 32 bit available data, scaling is performed. Also, scaling amplifies low amplitude events in deeper region which disappear due to high amplitude shallow events that saturate amplitude scale. We have focused on significance of scaling data to aid interpretation. This study elucidates a proper seismic loading procedure in workstations without using default preset parameters as available in most software suites. Differences and distribution of amplitude values at different depth for seismic data are probed in this exercise. Proper loading parameters are identified and associated steps are explained that needs to be taken care of while loading data. Finally, the exercise interprets the un-certainties which might arise when correlating scaled and unscaled versions of seismic data with synthetics. As, seismic well tie correlates the seismic reflection events with well markers, for our study it is used to identify regions which are enhanced and/or affected by scaling parameter(s).

Keywords: clipping, compression, resolution, seismic scaling

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Authors: Elham Taghizade Sigarodi, Ani Mirzakhanian

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Journalism atmosphere in present era is highly competitive so that what matters the most is “the speed of news broadcasting”. The first newspaper that lets out the news is therefore of higher validity. The value of the news is in fact in its truthfulness. Expressing the facts and reality is an accepted norm in professional media arena and it is as well considered the acceptable and trustworthy language for journalism. However, different conditions generate self-censorship. The present study seeks to explore the relationship between self-censorship and satisfaction of Iran newspaper’s readers. Thus, the statistical population including journalists of Iran newspaper for Tehran’s readers was estimated 384 persons based on Morgan table. Through cluster sampling, 50 journalists were selected so that totally the sample size was 434 persons and questionnaire was applied for data analysis and based on Alpha Chronbache, it was supported. Through Pierson correlation, the main and all subsidiary hypotheses were supported except the forth one.

Keywords: newspaper, satisfaction of audiences, self-censorship, journalists

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Authors: Leila Khosravi

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A major part of the drinking water in North West of Iran is supplied from Mahabad reservoir 80 km northwest of Mahabad. This reservoir collects water from 750 km-catchment which is undergoing accelerated changes due to deforestation and urbanization. The main objective of this study is to develop a catchment modeling platform which translates ongoing land-use changes, soil data, precipitation and evaporation into surface runoff of the river discharging into the reservoir: Soil and Water Assessment Tool, SWAT, model along with hydro -meteorological records of 1997–2011. A variety of statistical indices were used to evaluate the simulation results for both calibration and validation periods; among them, the robust Nash–Sutcliffe coefficients were found to be 0.52 and 0.62 in the calibration and validation periods, respectively. This project has developed a reliable modeling platform with the benchmark land physical conditions of the Mahabad dam basin.

Keywords: simulation, surface runoff, Mahabad dam, SWAT model

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Authors: Riccardo Pasquali, Keith Harlin, Mark Muller

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The ShallowTherm project is focussed on developing and applying a methodology for extrapolating relatively sparsely sampled thermal conductivity measurements across Ireland using mapped Litho-Electrical (LE) units. The primary data used consist of electrical resistivities derived from the Geological Survey Ireland Tellus airborne electromagnetic dataset, GIS-based maps of Irish geology, and rock thermal conductivities derived from both the current Irish Ground Thermal Properties (IGTP) database and a new programme of sampling and laboratory measurement. The workflow has been developed across three case-study areas that sample a range of different calcareous, arenaceous, argillaceous, and volcanic lithologies. Statistical analysis of resistivity data from individual geological formations has been assessed and integrated with detailed lithological descriptions to define distinct LE units. Thermal conductivity measurements from core and hand samples have been acquired for every geological formation within each study area. The variability and consistency of thermal conductivity measurements within each LE unit is examined with the aim of defining a characteristic thermal conductivity (or range of thermal conductivities) for each LE unit. Mapping of LE units, coupled with characteristic thermal conductivities, provides a method of defining thermal conductivity properties at a regional scale and facilitating the design of ground source heat pump closed-loop collectors.

Keywords: thermal conductivity, ground source heat pumps, resistivity, heat exchange, shallow geothermal, Ireland

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Authors: Razzaghifard P., Arya F., Chen S. Chien-I, Abdi B., Razzaghifard V., Arya A. H., Nazary A., Hosseinpour H., Ghabelnezam K.

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E-learning, also known as online learning, has indicated increased growth in recent years. One of the critical factors in the successful application of e-learning in higher education is students’ perceptions towards it. The main purpose of this paper is to investigate the perceptions of engineering students about e-learning in the UK. For the purpose of the present study, 145 second-year engineering students were randomly selected from the total population of 1280 participants. The participants were asked to complete a questionnaire containing 16 items. The data collected from the questionnaire were analyzed through the Statistical Package for Social Science (SPSS) software. The findings of the study revealed that the majority of participants have negative perceptions of e-learning. Most of the students had trouble interacting effectively during online classes. Furthermore, the majority of participants had negative experiences with the learning platform they used during e-learning. Suggestions were made on what could be done to improve the students’ perceptions of e-learning.

Keywords: e-learning, higher, education, engineering education, online learning

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Authors: I. Dangeard, S. Meineri, M. Dupré

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large body of research on energy consumption reveals that regular information on energy consumption produces a positive effect on behavior. The present research aims to test this feedback paradigm on waste management. A small-scale experiment on residual household waste was performed in a large french urban area, in partnership with local authorities, as part of the development of larger-scale project. A two-step door-to-door recruitment scheme led to 85 households answering a questionnaire. Among them, 54 accepted to participate in a study on waste (second step). Participants were then randomly assigned to one of the 3 experimental conditions : self-reported feedback on curbside waste, external feedback on waste weight based on information technologies, and no feedback for the control group. An additional control group was added, including households who were not requested to answer the questionnaire. Household residual waste was collected every week, and tags on curbside bins fed a database with waste weight of households. The feedback period lasted 14 weeks (february-may 2014). Quantitative data on waste weight were analysed, including these 14 weeks and the 7 previous weeks. Households were then contacted by phone in order to confirm the quantitative results. Regarding the recruitment questionnaire, results revealed high pro-environmental attitude on the NEP scale, high recycling behavior level and moderate level of source reduction behavior on the adapted 3R scale, but no statistical difference between the 3 experimental groups. Regarding the feedback manipulation paradigm, waste weight reveals important differences between households, but doesn't prove any statistical difference between the experimental conditions. Qualitative phone interviews confirm that recycling is a current practice among participants, whereas source reduction of waste is not, and mainly appears as a producer problem of packaging limitation. We conclude that triggering waste prevention behaviors among recycling households involves long-term feedback and should promote benchmarking, in order to clearly set waste reduction as an objective to be managed through feedback figures.

Keywords: eco-feedback, household waste, waste reduction, experimental research

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Authors: Behnaz Moradijamei, Michael Higgins

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Identifying community structure is a critical task in analyzing social media data sets often modeled by networks. Statistical models such as the stochastic block model have proven to explain the structure of communities in real-world network data. In this work, we develop a goodness-of-fit test to examine community structure's existence by using a distinguishing property in networks: cyclic structures are more prevalent within communities than across them. To better understand how communities are shaped by the cyclic structure of the network rather than just the number of edges, we introduce a novel method for deciding on the existence of communities. We utilize these structures by using renewal non-backtracking random walk (RNBRW) to the existing goodness-of-fit test. RNBRW is an important variant of random walk in which the walk is prohibited from returning back to a node in exactly two steps and terminates and restarts once it completes a cycle. We investigate the use of RNBRW to improve the performance of existing goodness-of-fit tests for community detection algorithms based on the spectral properties of the adjacency matrix. Our proposed test on community structure is based on the probability distribution of eigenvalues of the normalized retracing probability matrix derived by RNBRW. We attempt to make the best use of asymptotic results on such a distribution when there is no community structure, i.e., asymptotic distribution under the null hypothesis. Moreover, we provide a theoretical foundation for our statistic by obtaining the true mean and a tight lower bound for RNBRW edge weights variance.

Keywords: hypothesis testing, RNBRW, network inference, community structure

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Authors: Amanda T. Badaró, Douglas F. Barbin, Sofia T. Garcia, Maria Teresa P. S. Clerici, Amanda R. Ferreira

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Food fortification is the intentional addition of a nutrient in a food matrix and has been widely used to overcome the lack of nutrients in the diet or increasing the nutritional value of food. Fortified food must meet the demand of the population, taking into account their habits and risks that these foods may cause. Wheat and its by-products, such as semolina, has been strongly indicated to be used as a food vehicle since it is widely consumed and used in the production of other foods. These products have been strategically used to add some nutrients, such as fibers. Methods of analysis and quantification of these kinds of components are destructive and require lengthy sample preparation and analysis. Therefore, the industry has searched for faster and less invasive methods, such as Near-Infrared Spectroscopy (NIR). NIR is a rapid and cost-effective method, however, it is based on indirect measurements, yielding high amount of data. Therefore, NIR spectroscopy requires calibration with mathematical and statistical tools (Chemometrics) to extract analytical information from the corresponding spectra, as Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA). PCA is well suited for NIR, once it can handle many spectra at a time and be used for non-supervised classification. Advantages of the PCA, which is also a data reduction technique, is that it reduces the data spectra to a smaller number of latent variables for further interpretation. On the other hand, LDA is a supervised method that searches the Canonical Variables (CV) with the maximum separation among different categories. In LDA, the first CV is the direction of maximum ratio between inter and intra-class variances. The present work used a portable infrared spectrometer (NIR) for identification and classification of pure and fiber-fortified semolina samples. The fiber was added to semolina in two different concentrations, and after the spectra acquisition, the data was used for PCA and LDA to identify and discriminate the samples. The results showed that NIR spectroscopy associate to PCA was very effective in identifying pure and fiber-fortified semolina. Additionally, the classification range of the samples using LDA was between 78.3% and 95% for calibration and 75% and 95% for cross-validation. Thus, after the multivariate analysis such as PCA and LDA, it was possible to verify that NIR associated to chemometric methods is able to identify and classify the different samples in a fast and non-destructive way.

Keywords: Chemometrics, fiber, linear discriminant analysis, near-infrared spectroscopy, principal component analysis, semolina

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Authors: Benjamin Osae Agyei, Hypolite Bayor

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This present experiment was carried out during the 2012 cropping season, at the Farming for the Future Experimental Field of the University for Development Studies, Nyankpala Campus in the Northern Region of Ghana. The objective of the experiment was to determine the carrot growth and yield responses to poultry manure and N.P.K (15:15:15). Six treatments (Control (no amendment), 20 t/ha poultry manure (PM), 40 t/ha PM, 70 t/ha PM, 35 t/ha PM + 0.11t/ha N.P.K and 0.23 t/ha N.P.K) with three replications for each were laid in a Randomized Complete Block Design (RCBD). Data were collected on plant height, number of leaves per plant, canopy spread, root diameter, root weight, and root length. Microsoft Excel and Genstat Statistical Package (9^th edition) were used for the data analysis. The treatment means were compared by using Least Significant Difference at 10%. Generally, the results showed that there were no significant differences (P>0.1) among the treatments with respect to number of leaves per plant, root diameter, root weight, and root length. However, significant differences occurred among plant heights and canopy spreads. Plant height treated with 40 t/ha PM at the fourth week after planting and canopy spread at eight weeks after planting and ten weeks after planting by 70 t/ha PM and 20 t/ha PM respectively showed significant difference (P<0.1). The study recommended that any of the amended treatments can be applied at their recommended rates to plots for carrot production, since there were no significant differences among the treatments.

Keywords: poultry manure, N.P.K., soil amendment, growth, yield, carrot

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Authors: Keshav Dubey, Swajeeth Panchangam, Arun Rajendran, Swarnim Gupta

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In the semiconductor capital equipment industry, effective modeling of repairable system reliability is crucial for optimizing maintenance strategies and ensuring operational efficiency. However, repairable system reliability modeling using a renewal process is not as popular in the semiconductor equipment industry as it is in the locomotive and automotive industries. Utilization of this approach will help optimize maintenance practices. This paper presents a structured framework that leverages both parametric and non-parametric approaches to model the reliability of repairable subsystems based on operational data, maintenance schedules, and system-specific conditions. Data is organized at the equipment ID level, facilitating trend testing to uncover failure patterns and system degradation over time. For non-parametric modeling, the Mean Cumulative Function (Mean Cumulative Function) approach is applied, offering a flexible method to estimate the cumulative number of failures over time without assuming an underlying statistical distribution. This allows for empirical insights into subsystem failure behavior based on historical data. On the parametric side, virtual age modeling, along with Homogeneous and Non-Homogeneous Poisson Process (Homogeneous Poisson Process and Non-Homogeneous Poisson Process) models, is employed to quantify the effect of repairs and the aging process on subsystem reliability. These models allow for a more structured analysis by characterizing repair effectiveness and system wear-out trends over time. A comparison of various Generalized Renewal Process (GRP) approaches highlights their utility in modeling different repair effectiveness scenarios. These approaches provide a robust framework for assessing the impact of maintenance actions on system performance and reliability. By integrating both parametric and non-parametric methods, this framework offers a comprehensive toolset for reliability engineers to better understand equipment behavior, assess the effectiveness of maintenance activities, and make data-driven decisions that enhance system availability and operational performance in semiconductor fabrication facilities.

Keywords: reliability, maintainability, homegenous poission process, repairable system

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Authors: Diego Rodrigues, Marcelo Lisboa, Elismar Batista, Marcos Dias

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Based on data on child labor, this work arises questions about how to understand and locate the factors that make up the child labor rates, and which properties are important to analyze these cases. Using data mining techniques to discover valid patterns on Brazilian social databases were evaluated data of child labor in the State of Tocantins (located north of Brazil with a territory of 277000 km2 and comprises 139 counties). This work aims to detect factors that are deterministic for the practice of child labor and their relationships with financial indicators, educational, regional and social, generating information that is not explicit in the government database, thus enabling better monitoring and updating policies for this purpose.

Keywords: social data, government decision making, association of social data, data mining

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Authors: Zhi Zhu, Boquan Zhang, Tian Jing, Jingjing Li, Tao Wang

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Data assimilation is a model and data hybrid-driven method that dynamically fuses new observation data with a numerical model to iteratively approach the real system state. It is widely used in state prediction and parameter inference of continuous systems. Because of the discrete event system’s non-linearity and non-Gaussianity, traditional Kalman Filter based on linear and Gaussian assumptions cannot perform data assimilation for such systems, so particle filter has gradually become a technical approach for discrete event simulation data assimilation. Hence, we proposed a particle filter-based discrete event simulation data assimilation method and took the unmanned aerial vehicle (UAV) maintenance service system as a proof of concept to conduct simulation experiments. The experimental results showed that the filtered state data is closer to the real state of the system, which verifies the effectiveness of the proposed method. This research can provide a reference framework for the data assimilation process of other complex nonlinear systems, such as discrete-time and agent simulation.

Keywords: discrete event simulation, data assimilation, particle filter, model and data-driven

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Authors: Subir Gupta, Subhas Ganguly

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In this paper, we demonstrate the new area of application of image processing in metallurgical images to develop the more opportunity for structure-property correlation based approaches of alloy design. The present exercise focuses on the development of image processing tools suitable for phrase segmentation, grain boundary detection and recognition of micro-constituents in SEM micrographs of ferrite and pearlite steels. A comprehensive data of micrographs have been experimentally developed encompassing the variation of ferrite and pearlite volume fractions and taking images at different magnification (500X, 1000X, 15000X, 2000X, 3000X and 5000X) under scanning electron microscope. The variation in the volume fraction has been achieved using four different plain carbon steel containing 0.1, 0.22, 0.35 and 0.48 wt% C heat treated under annealing and normalizing treatments. The obtained data pool of micrographs arbitrarily divided into two parts to developing training and testing sets of micrographs. The statistical recognition features for ferrite and pearlite constituents have been developed by learning from training set of micrographs. The obtained features for microstructure pattern recognition are applied to test set of micrographs. The analysis of the result shows that the developed strategy can successfully detect the micro constitutes across the wide range of magnification and variation of volume fractions of the constituents in the structure with an accuracy of about +/- 5%.

Keywords: SEM micrograph, metallurgical image processing, ferrite pearlite steel, microstructure

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Authors: Chang Hsueh-Sheng, Chen Tzu-Ling

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Earthquake is an unpredictable natural disaster and intensive earthquakes have caused serious impacts on social-economic system, environmental and social resilience. Conventional ways to mitigate earthquake disaster are to enhance building codes and advance structural engineering measures. However, earthquake-induced ground damage such as liquefaction, land subsidence, landslide happen on places nearby earthquake prone or poor soil condition areas. Therefore, this study uses spatial statistical analysis to explore the spatial pattern of damaged buildings. Afterwards, principle components analysis (PCA) is applied to categorize the similar features in different kinds of clustered patterns. The results show that serious landslide prone area, close to fault, vegetated ground surface and mudslide prone area are common in those highly damaged buildings. In addition, the oldest building might not be directly referred to the most vulnerable one. In fact, it seems that buildings built between 1974 and 1989 become more fragile during the earthquake. The incorporation of both spatial statistical analyses and PCA can provide more accurate information to subsidize retrofit programs to enhance earthquake resistance in particular areas.

Keywords: earthquake disaster, spatial statistic analysis, principle components analysis (pca), clustered patterns

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Authors: Madhusudan Purohit, Stephen Philip, Bharathkumar Inturi

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In this paper we report the quantitative structure activity relationship of novel bis-triazole derivatives for predicting the activity profile. The full model encompassed a dataset of 46 Bis- triazoles. Tripos Sybyl X 2.0 program was used to conduct CoMSIA QSAR modeling. The Partial Least-Squares (PLS) analysis method was used to conduct statistical analysis and to derive a QSAR model based on the field values of CoMSIA descriptor. The compounds were divided into test and training set. The compounds were evaluated by various CoMSIA parameters to predict the best QSAR model. An optimum numbers of components were first determined separately by cross-validation regression for CoMSIA model, which were then applied in the final analysis. A series of parameters were used for the study and the best fit model was obtained using donor, partition coefficient and steric parameters. The CoMSIA models demonstrated good statistical results with regression coefficient (r2) and the cross-validated coefficient (q2) of 0.575 and 0.830 respectively. The standard error for the predicted model was 0.16322. In the CoMSIA model, the steric descriptors make a marginally larger contribution than the electrostatic descriptors. The finding that the steric descriptor is the largest contributor for the CoMSIA QSAR models is consistent with the observation that more than half of the binding site area is occupied by steric regions.

Keywords: 3D QSAR, CoMSIA, triazoles, novel heterocycles

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Authors: Agnes Anyango Andollo, Jane Achieng Achola

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The use of Information and Communication Technologies (ICTs) has become one of the driving forces in facilitation of learning in most colleges. The ability to effectively harness the technology varies from college to college. The study objective was to determine the lecturers’, institutional attributes and policies that influence the utilization of ICT by the lecturers’. A cross sectional survey design was employed in order to empirically investigate the extent to which lecturers’ personal, institutional attributes and policies influence the utilization of ICT to facilitate learning. The target population of the study was 295 lecturers who facilitate learning at KMTC-Nairobi. Structured self-administered questionnaire was given to the lecturers. Quantitative data was scrutinized for completeness, accuracy and uniformity then coded. Data were analyzed in frequencies and percentages using Statistical Package for Social Sciences (SPSS) version 19, this was a reliable tool for quantitative data analysis. A total of 155 completed questionnaires administered were obtained from the respondents for the study that were subjected to analysis. The study found out that 93 (60%) of the respondents were male while 62 (40%) of the respondents were female. Individual’s educational level, age, gender and educational experience had the greatest impact on use of ICT. Lecturers’ own beliefs, values, ideas and thinking had moderate impact on use of ICT. And that institutional support by provision of resources for ICT related training such as internet, computers, laptops and projectors had moderate impact (p = 0.049) at 5% significant level on use of ICT. The study concluded that institutional attributes and ICT policy were keys to utilization of ICT by lecturers at KMTC Nairobi also mandatory policy on use of ICT by lecturers to facilitate learning was key. It recommended that policies should be put in place for Technical support to lecturers when in problem during utilization of ICT and also a mechanism should be put in place to make the use of ICT in teaching and learning mandatory.

Keywords: policy, computers education, medical training institutions, ICTs

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Authors: Sadam Alwadi

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Outlier values become a problem that frequently occurs in the data observation or recording process. Thus, the need for data imputation has become an essential matter. In this work, it will make use of the methods described in the prior work to detect the outlier values based on a collection of stock market data. In order to implement the detection and find some solutions that maybe helpful for investors, real closed price data were obtained from the Amman Stock Exchange (ASE). Tukey and Maximum Overlapping Discrete Wavelet Transform (MODWT) methods will be used to impute the detect the outlier values.

Keywords: outlier values, imputation, stock market data, detecting, estimation

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Authors: Artemis Louppis, Michalis Constantinou, Ioanna Kosma, Federica Blando, Michael Kontominas, Anastasia Badeka

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The aim of the present study was to differentiate yellow prickly pear according to geographical origin based on the combination of mineral content, physicochemical parameters, vitamins and antioxidants. A total of 240 yellow prickly pear samples from Cyprus, Spain, Italy and Greece were analyzed for pH, titratable acidity, electrical conductivity, protein, moisture, ash, fat, antioxidant activity, individual antioxidants, sugars and vitamins by UPLC-MS/MS as well as minerals by ICP-MS. Statistical treatment of the data included multivariate analysis of variance followed by linear discriminant analysis. Based on results, a correct classification of 66.7% was achieved using the cross validation by mineral content while 86.1% was achieved using the cross validation method by combination of all analytical parameters.

Keywords: geographical differentiation, prickly pear, chemometrics, analytical techniques

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Authors: Johnson Opoku-Asante, Emmanuel Bobobee, Joseph Akowuah, Eric Amoah Asante

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In recent years, the issue of postharvest losses has become a serious concern in Sub-Saharan Africa. Postharvest technology development and adaptation need urgent attention, particularly for small and medium-scale rice farmers in Africa. However, to better develop any postharvest technology, knowledge of the mechanical properties of different varieties of paddy rice is vital. There is also the issue of the development of new rice cultivars. The objectives of this research are to (1) determine the mechanical properties of the selected paddy rice varieties at varying moisture content. (2) conduct a comparative analysis of the mechanical properties of selected rice paddy for different variety-moisture content interactions. (3) determine the significant statistical differences between the mean values of the various variety-moisture content interactions The mechanical properties of AGRA rice, CRI-Amankwatia, CRI-Enapa and CRI-Dartey, four local varieties developed by Crop Research Institute of Ghana are compared at 11.5%, 13.0% and 16.5% dry basis moisture content. The mechanical properties measured are Sphericity, Aspect ratio, Grain mass, 1000 Grain mass, Bulk Density, True Density, Porosity and Angle of Repose. Samples were collected from the Kwadaso Agric College of the CRI in Kumasi. The samples were threshed manually and winnowed before conducting the experiment. The moisture content was determined on a dry basis using the Moistex Screw-Type Digital Grain Moisture Meter. Other equipment used for data collection were venire calipers and Citizen electronic scale. A 4×3 factorial arrangement was used in a completely randomized design in three replications. Tukey's HSD comparisons test was conducted during data analysis to compare all possible pairwise combinations of the various varieties’ moisture content interaction. From the results, it was concluded that Sphericity recorded 0.391 mm³ to 0.377 mm³ for CRI-Dartey at 16.5% and CRI-Enapa at 13.5%, respectively, whereas Aspect Ratio recorded 0.298 mm³ to 0.269 mm³ for CRI-Dartey at 16.5% and CRI-Enapa at 13.5% respectively. For grain mass, AGRA rice at 13.0% also recorded 0.0312 g as the highest score and CRI-Enapa at 13.0% obtained 0.0237 as the lowest score. For the GM1000, it was observed that it ranges from 29.33 g for CRI-Amankwatia at 16.5% moisture content to 22.54 g for CRI-Enapa at 16.5% interactions. Bulk Density ranged from 654.0 kg/m³ to 422.9 kg/m³ for CRI-Amankwatia at 16.5% and CRI-Enapa at 11.5% as the highest and lowest recordings, respectively. It was also observed that the true Density ranges from 1685.8 kg/m3 for AGRA rice at 13.0% moisture content to 1352.5 kg/m³ for CRI-Enapa at 16.5% interactions. In the case of porosity, CRI-Enapa at 11.5% received the highest score of 70.83% and CRI-Amankwatia at 16.5 received the lowest score of 55.88%. Finally, in the case of Angle of Repose, CRI-Amankwatia at 16.5% recorded the highest score of 47.3o and CRI-Enapa at 11.5% recorded the least score of 34.27o. In all cases, the difference in mean value was less than the LSD. This indicates that there were no significant statistical differences between their mean values, indicating that technologies developed and adapted for one variety can equally be used for all the other varieties.

Keywords: angle of repose, aspect ratio, bulk density, porosity, sphericity, mechanical properties

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Authors: Abderrazak Bannari, Ghadeer Kadhem

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The objectives of this paper are the validation and the evaluation of MBES-CARIS BASE surface data performance for bathymetric mapping of shallow water in the Kingdom of Bahrain. The latter is an archipelago with a total land area of about 765.30 km², approximately 126 km of coastline and 8,000 km² of marine area, located in the Arabian Gulf, east of Saudi Arabia and west of Qatar (26° 00’ N, 50° 33’ E). To achieve our objectives, bathymetric attributed grid files (X, Y, and depth) generated from the coverage of ship-track MBSE data with 300 x 300 m cells, processed with CARIS-HIPS, were downloaded from the General Bathymetric Chart of the Oceans (GEBCO). Then, brought into ArcGIS and converted into a raster format following five steps: Exportation of GEBCO BASE surface data to the ASCII file; conversion of ASCII file to a points shape file; extraction of the area points covering the water boundary of the Kingdom of Bahrain and multiplying the depth values by -1 to get the negative values. Then, the simple Kriging method was used in ArcMap environment to generate a new raster bathymetric grid surface of 30×30 m cells, which was the basis of the subsequent analysis. Finally, for validation purposes, 2200 bathymetric points were extracted from a medium scale nautical map (1:100 000) considering different depths over the Bahrain national water boundary. The nautical map was scanned, georeferenced and overlaid on the MBES-CARIS generated raster bathymetric grid surface (step 5 above), and then homologous depth points were selected. Statistical analysis, expressed as a linear error at the 95% confidence level, showed a strong correlation coefficient (R² = 0.96) and a low RMSE (± 0.57 m) between the nautical map and derived MBSE-CARIS depths if we consider only the shallow areas with depths of less than 10 m (about 800 validation points). When we consider only deeper areas (> 10 m) the correlation coefficient is equal to 0.73 and the RMSE is equal to ± 2.43 m while if we consider the totality of 2200 validation points including all depths, the correlation coefficient is still significant (R² = 0.81) with satisfactory RMSE (± 1.57 m). Certainly, this significant variation can be caused by the MBSE that did not completely cover the bottom in several of the deeper pockmarks because of the rapid change in depth. In addition, steep slopes and the rough seafloor probably affect the acquired MBSE raw data. In addition, the interpolation of missed area values between MBSE acquisition swaths-lines (ship-tracked sounding data) may not reflect the true depths of these missed areas. However, globally the results of the MBES-CARIS data are very appropriate for bathymetric mapping of shallow water areas.

Keywords: bathymetry mapping, multibeam echosounder systems, CARIS-HIPS, shallow water

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Authors: P. Jayashree, S. Rajkumar

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With social networks and smart devices generating a multitude of data, effective data management is the need of the hour for networks and cloud applications. Some applications need effective storage while some other applications need effective communication over networks and data reduction comes as a handy solution to meet out both requirements. Most of the data compression techniques are based on data statistics and may result in either lossy or lossless data reductions. Though lossy reductions produce better compression ratios compared to lossless methods, many applications require data accuracy and miniature details to be preserved. A variety of data compression algorithms does exist in the literature for different forms of data like text, image, and multimedia data. In the proposed work, a generic progressive compression algorithm, based on probabilistic encoding, called PEINS is projected as an enhancement over irrational number stored coding technique to cater to storage issues of increasing data volumes as a cost effective solution, which also offers data security as a secondary outcome to some extent. The proposed work reveals cost effectiveness in terms of better compression ratio with no deterioration in compression time.

Keywords: compression ratio, generic compression, irrational number storage, probabilistic encoding

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Authors: Femi Elegbeleye, Omobayo Esan, Muienge Mbodila, Patrick Bowe

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This paper focused on cost effective storage architecture using fog and cloud data storage gateway and presented the design of the framework for the data privacy model and data analytics framework on a real-time analysis when using machine learning method. The paper began with the system analysis, system architecture and its component design, as well as the overall system operations. The several results obtained from this study on data privacy model shows that when two or more data privacy model is combined we tend to have a more stronger privacy to our data, and when fog storage gateway have several advantages over using the traditional cloud storage, from our result shows fog has reduced latency/delay, low bandwidth consumption, and energy usage when been compare with cloud storage, therefore, fog storage will help to lessen excessive cost. This paper dwelt more on the system descriptions, the researchers focused on the research design and framework design for the data privacy model, data storage, and real-time analytics. This paper also shows the major system components and their framework specification. And lastly, the overall research system architecture was shown, its structure, and its interrelationships.

Keywords: IoT, fog, cloud, data analysis, data privacy

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Authors: Mona Rezaei, Habib Honari, Mehrzad Hamidi, Fatemeh Kiani

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Make strong brands has become a priority for many organizations in marketing. Brand is an important indicator of marketing status. Brand Strength is in kept customer, profit, brand development and gain competitive advantage and In fact it is a concept that was created from a consumer perspective. It is assumed that the creation of a strong brand is creating numerous marketing benefits. The purpose of this study was to evaluate the psychometric characteristics of the questionnaire the most strong sports brands in the consumer society. Questionnaire was conducted to a sample of 340 customers of sports brands. Psychometric parameters were determined by using appropriate statistical methods. The results of the factor analysis and Varimax rotation revealed five factors of strong brands. The results confirms that questionnaire structure have acceptable associated to the data and confirmed all indicators of the model. Reliability (859/0) was satisfactory. According to calculated psychometric indices, this questionnaire could be appropriate to assess the most strong sports brands.

Keywords: reliability, strong brand, sport brands, psychometric

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Authors: Punam Shaw

Abstract:

Relationship often refers to the acquaintance or association between two or more things, which are interrelated and interdependent. The socio-economic status is obviously a blending of two states, would, therefore, be a ranking of an individual by the society he or she lives in, and in terms of his/her material belonging, cultural possessions along with the degree of respect, power and influence wield. Hence, education, income and occupation of an individual play a significant role in society. Positive mental attitude leads to achieve the set goal, and improve performance particularly in team cohesiveness, which may be determined by various interrelated aspects, which can predict the future assessment in their respective field accordingly. The study intended to examine and explore the relationship between Socio-economic Status and Mental Toughness of cricketers. For the present study descriptive survey research method was used and selected 40 (male=20 female=20) U-17 years registered players under Cricket Association of Bengal (CAB), as the sample population. Modified Socio-Economic Status Scale was used to collect the data regarding players, socioeconomic Status and to assess the mental toughness; Scott Barry Kaufman questionnaire was used. The data had been analysed through applying Pearson’s Correlation Coefficient and t-test as statistical techniques. The findings of the study showed that there is a positive correlation between socioeconomic Status and Mental Toughness among cricketers, it was found that significant difference was presented between male and female SES group. It was further revealed that there is no significant difference between male and female cricketers and in their different socioeconomic class with respect to their mental toughness.

Keywords: cricketers, mental toughness, relationship, socio-economic status

Procedia PDF Downloads 126