Search results for: data analytics

Authors: Mohammad Sharifi Bohlouli

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Turkish language with many dialects is native or official language of great number of people all around the world. The Qashqaie dialect of Turkish language is spoken by the Qashqaie tribe mostly scattered in the southern part of Iran. This paper aims at analyzing the tense system of this dialect to detect the type and number of tense and aspects available to its speakers. To collect a reliable data, a group of 50 old native speakers were randomly chosen as the informants and different techniques such as; Shuy et al interviews, selective listening ,and eavesdropping were used. The results of data analysis showed that the tense system in the Qashqaie dialect of Turkish language includes 3 absolute tenses , 6 aspectual , and 2 subjunctive ones. The interesting part of the study is that Qashqaie dialect enables its speakers to make a kind of aspectual opposition through verb structure which seems to be almost impossible through verb forms in any other nonturkish languages. For example in the following examples sentences 1 &2 and 3&4 have the same translation In English although they are different in both meaning and structure. 1. Ali ensha yazirdi. 2. Ali ensha yazirmush. (Ali was writing a composition.) 3. Ali yadmishdi. 4. Ali yadmishimish. ( Ali had slept.) The changes in the verb structure in Qashqaie dialect enables its speakers to say that whether the doer of the action remembers the process of doing the action or not. So, it presents a new aspectual opposition as Observed /nonobserved. The research findings reveal many other regularities and linguistic features that can be useful for linguists interested in Turkish in general and for those interested in tense and aspect and also they can be helpful for different pedagogical purposes including teaching and translating.

Keywords: qashqaie dialect, tense, aspect, linguistics, Turkish Language

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Authors: Georges Ghazi, Magali Gelhaye, Ruxandra Botez

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Over the years, the Flight Management System (FMS) has experienced a continuous improvement of its many features, to the point of becoming the pilot’s primary interface for flight planning operation on the airplane. With the assistance of the FMS, the concept of distance and time has been completely revolutionized, providing the crew members with the determination of the optimized route (or flight plan) from the departure airport to the arrival airport. To accomplish this function, the FMS needs an accurate Aircraft Performance Model (APM) of the aircraft. In general, APMs that equipped most modern FMSs are established before the entry into service of an individual aircraft, and results from the combination of a set of ordinary differential equations and a set of performance databases. Unfortunately, an aircraft in service is constantly exposed to dynamic loads that degrade its flight characteristics. These degradations endow two main origins: airframe deterioration (control surfaces rigging, seals missing or damaged, etc.) and engine performance degradation (fuel consumption increase for a given thrust). Thus, after several years of service, the performance databases and the APM associated to a specific aircraft are no longer representative enough of the actual aircraft performance. It is important to monitor the trend of the performance deterioration and correct the uncertainties of the aircraft model in order to improve the accuracy the flight management system predictions. The basis of this research lies in the new ability to continuously update an Aircraft Performance Model (APM) during flight using an adaptive lookup table technique. This methodology was developed and applied to the well-known Cessna Citation X business aircraft. For the purpose of this study, a level D Research Aircraft Flight Simulator (RAFS) was used as a test aircraft. According to Federal Aviation Administration the level D is the highest certification level for the flight dynamics modeling. Basically, using data available in the Flight Crew Operating Manual (FCOM), a first APM describing the variation of the engine fan speed and aircraft fuel flow w.r.t flight conditions was derived. This model was next improved using the proposed methodology. To do that, several cruise flights were performed using the RAFS. An algorithm was developed to frequently sample the aircraft sensors measurements during the flight and compare the model prediction with the actual measurements. Based on these comparisons, a correction was performed on the actual APM in order to minimize the error between the predicted data and the measured data. In this way, as the aircraft flies, the APM will be continuously enhanced, making the FMS more and more precise and the prediction of trajectories more realistic and more reliable. The results obtained are very encouraging. Indeed, using the tables initialized with the FCOM data, only a few iterations were needed to reduce the fuel flow prediction error from an average relative error of 12% to 0.3%. Similarly, the FCOM prediction regarding the engine fan speed was reduced from a maximum error deviation of 5.0% to 0.2% after only ten flights.

Keywords: aircraft performance, cruise, trajectory optimization, adaptive lookup tables, Cessna Citation X

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Authors: Youngjae Jin, Daeshik Kim

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This paper describes a cycle accurate simulation results of weight values learned by an auto-encoder behavior model in terms of pre-route simulation. Given the results we visualized the first layer representations with natural images. Many common deep learning threads have focused on learning high-level abstraction of unlabeled raw data by unsupervised feature learning. However, in the process of handling such a huge amount of data, the learning method’s computation complexity and time limited advanced research. These limitations came from the fact these algorithms were computed by using only single core CPUs. For this reason, parallel-based hardware, FPGAs, was seen as a possible solution to overcome these limitations. We adopted and simulated the ready-made auto-encoder to design a behavior model in Verilog HDL before designing hardware. With the auto-encoder behavior model pre-route simulation, we obtained the cycle accurate results of the parameter of each hidden layer by using MODELSIM. The cycle accurate results are very important factor in designing a parallel-based digital hardware. Finally this paper shows an appropriate operation of behavior model based pre-route simulation. Moreover, we visualized learning latent representations of the first hidden layer with Kyoto natural image dataset.

Keywords: auto-encoder, behavior model simulation, digital hardware design, pre-route simulation, Unsupervised feature learning

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Authors: Jibril Mohammed, Usman Dadum Hamza, Abdulsalam Surajudeen, Baba Yahya Danjuma

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Considerable concerns have been raised over the presence of volatile organic compounds (VOCs) in water. In this study, coconut shell based activated carbon was produced through chemical activation with potassium acetate (PAAC) for adsorption of benzene and toluene. The porous carbons were characterized using Fourier transform infrared spectroscopy (FTIR), thermogravimetric analysis (TGA), scanning electron microscopy (SEM), proximate analysis, and ultimate analysis and nitrogen adsorption tests. Adsorption of benzene and toluene on the porous carbons were conducted at varying concentrations (50-250 mg/l). The high BET surface area of 622 m2/g and highly heteroporous adsorbent prepared gave good removal efficiencies of 79 and 82% for benzene and toluene respectively, with 32% yield. Equilibrium data were fitted to Langmuir, Freundlich and Temkin isotherms with all the models having R2 > 0.94. The equilibrium data were best represented by the Langmuir isotherm, with maximum adsorption capacity of 192 mg/g and 227 mg/g for benzene and toluene respectively. The Webber and Chakkravorti equilibrium parameter (RL) values are between 0 and 1 confirming the favourability of the Langmuir model. The adsorption kinetics was found to follow the pseudo-second-order kinetic model. The PAAC produced can be used effectively to salvage environmental pollution problems posed by VOCs through a sustainable process.

Keywords: adsorption, equilibrium and kinetics studies, potassium acetate, water treatment

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Authors: Ahmed Elaksher, Islam Omar

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For many years, Mars surface has been a mystery for scientists. Lately with the help of geospatial data and photogrammetric procedures researchers were able to capture some insights about this planet. Two of the most imperative data sources to explore Mars are the The High Resolution Imaging Science Experiment (HiRISE) and the Mars Orbiter Laser Altimeter (MOLA). HiRISE is one of six science instruments carried by the Mars Reconnaissance Orbiter, launched August 12, 2005, and managed by NASA. The MOLA sensor is a laser altimeter carried by the Mars Global Surveyor (MGS) and launched on November 7, 1996. In this project, we used MOLA-based DEMs to orthorectify HiRISE optical images for generating a more accurate and trustful surface of Mars. The MOLA data was interpolated using the kriging interpolation technique. Corresponding tie points were digitized from both datasets. These points were employed in co-registering both datasets using GIS analysis tools. In this project, we employed three different 3D to 2D transformation models. These are the parallel projection (3D affine) transformation model; the extended parallel projection transformation model; the Direct Linear Transformation (DLT) model. A set of tie-points was digitized from both datasets. These points were split into two sets: Ground Control Points (GCPs), used to evaluate the transformation parameters using least squares adjustment techniques, and check points (ChkPs) to evaluate the computed transformation parameters. Results were evaluated using the RMSEs between the precise horizontal coordinates of the digitized check points and those estimated through the transformation models using the computed transformation parameters. For each set of GCPs, three different configurations of GCPs and check points were tested, and average RMSEs are reported. It was found that for the 2D transformation models, average RMSEs were in the range of five meters. Increasing the number of GCPs from six to ten points improve the accuracy of the results with about two and half meters. Further increasing the number of GCPs didn’t improve the results significantly. Using the 3D to 2D transformation parameters provided three to two meters accuracy. Best results were reported using the DLT transformation model. However, increasing the number of GCPS didn’t have substantial effect. The results support the use of the DLT model as it provides the required accuracy for ASPRS large scale mapping standards. However, well distributed sets of GCPs is a key to provide such accuracy. The model is simple to apply and doesn’t need substantial computations.

Keywords: mars, photogrammetry, MOLA, HiRISE

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Authors: Paul Moses Ndegwa, Teresia Kabucho, Lucy Wanjiru, Esther Wanjiru, Brian Githaiga, Jecinta Wambui

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Health outcome has improved in the country since 2013 following the adoption of the new constitution in Kenya with devolved governance with administration and health planning functions transferred to county governments. 2018-2022 development agenda prioritized universal healthcare coverage, food security, and nutrition, however, the emergence of Covid-19 and the increase of non-communicable diseases pose a challenge and constrain in an already overwhelmed health system. A study was conducted July-November 2021 to establish key challenges in achieving universal healthcare coverage within the county and best practices for improved non-communicable disease control. 14 health workers ranging from nurses, doctors, public health officers, clinical officers, and pharmaceutical technologists were purposely engaged to provide critical information through questionnaires by a trained duo observing ethical procedures on confidentiality. Data analysis. Communicable diseases are major causes of morbidity and mortality. Non-communicable diseases contribute to approximately 39% of deaths. More than 45% of the population does not have access to safe drinking water. Study noted geographic inequality with respect to distribution and use of health resources including competing non-health priorities. 56% of health workers are nurses, 13% clinical officers, 7% doctors, 9%public health workers, 2% are pharmaceutical technologists. Poor-quality data limits the validity of disease-burdened estimates and research activities. Risk factors include unsafe water, sanitation, hand washing, unsafe sex, and malnutrition. Key challenge in achieving universal healthcare coverage is the rise in the relative contribution of non-communicable diseases. Improve targeted disease control with effective and equitable resource allocation. Develop high infectious disease control mechanisms. Improvement of quality data for decision making. Strengthen electronic data-capture systems. Increase investments in the health workforce to improve health service provision and achievement of universal health coverage. Create a favorable environment to retain health workers. Fill in staffing gaps resulting in shortages of doctors (7%). Develop a multi-sectional approach to health workforce planning and management. Need to invest in mechanisms that generate contextual evidence on current and future health workforce needs. Ensure retention of qualified, skilled, and motivated health workforce. Deliver integrated people-centered health services.

Keywords: multi-sectional approach, equity, people-centered, health workforce retention

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Authors: Priyal Motwani, Garvit Goel

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In this study, we have studied and analysed the transaction data of investors of a mutual fund investment company based in India. Based on the data available, we have identified the top four biases that affect the investors of the emerging market economies through regression analysis and three uniquely defined ratios. We found that the four most prominent biases that affected the investment making decisions in India are– Chauffer Knowledge, investors tend to make ambitious decisions about sectors they know little about; Bandwagon effect – the response of the market indices to macroeconomic events are more profound and seem to last longer compared to western markets; base-rate neglect – judgement about stocks are too much based on the most recent development ignoring the long-term fundamentals of the stock; availability bias – lack of proper communication channels of market information lead people to be too reliant on limited information they already have. After segregating the investors into six groups, the results have further been studied to identify a correlation among the demographics, gender and unique cultural identity of the derived groups and the corresponding prevalent biases. On the basis of the results obtained from the derived groups, our study recommends six methods, specific to each group, to educate the investors about the prevalent biases and their role in investment decision making.

Keywords: Bandwagon effect, behavioural biases, Chauffeur knowledge, demographics, investor literacy, mutual funds

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Authors: Nazli Hardy

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Multidisciplinary application of computer science, interactive database-driven web application, the Internet of Things (IoT) represents a digital ecosystem that has pervasive technological, social, and economic, impact on the human population. It is a long-term technology, and its development is built around the connection of everyday objects, to the Internet. It is estimated that by 2020, with billions of people connected to the Internet, the number of connected devices will exceed 50 billion, and thus IoT represents a paradigm shift in in our current interconnected ecosystem, a communication shift that will unavoidably affect people, businesses, consumers, clients, employees. By nature, in order to provide a cohesive and integrated service, connected devices need to collect, aggregate, store, mine, process personal and personalized data on individuals and corporations in a variety of contexts and environments. A significant factor in this paradigm shift is the necessity for secure and appropriate transmission, processing and storage of the data. Thus, while benefits of the applications appear to be boundless, these same opportunities are bounded by concerns such as trust, privacy, security, loss of control, and related issues. This poster and presentation look at a multi-factor authentication (MFA) mechanisms that need to change from the login-password tuple to an Identity and Access Management (IAM) model, to the more cohesive to Identity Relationship Management (IRM) standard. It also compares and contrasts messaging protocols that are appropriate for the IoT ecosystem.

Keywords: Internet of Things (IoT), authentication, protocols, survey

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Authors: Nikita Katyal, Shaurya Uppal

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This paper tackles the significant challenge of accurately classifying customers within a retailer’s customer base. Accurate classification is essential for developing targeted marketing strategies that effectively engage this important demographic. To address this issue, we propose a method that utilizes Large Language Models (LLMs). By employing LLMs, we analyze the metadata associated with product purchases derived from historical data to identify key product categories that act as distinguishing factors. These categories, such as baby food, eldercare products, or family-sized packages, offer valuable insights into the likely household composition of customers, including families with babies, families with kids/teenagers, families with pets, households caring for elders, or mixed households. We segment high-confidence customers into distinct categories by integrating historical purchase behavior with LLM-powered product classification. This paper asserts that life stage segmentation can significantly enhance e-commerce businesses’ ability to target the appropriate customers with tailored products and campaigns, thereby augmenting sales and improving customer retention. Additionally, the paper details the data sources, model architecture, and evaluation metrics employed for the segmentation task.

Keywords: LLMs, segmentation, product tags, fine-tuning, target segments, marketing communication

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Authors: S. Jigna, K. Nanda Kumar, T. Anna

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Being a major contributor to the Indian economy and a critical facilitator for the country’s digital India vision, the Indian telecommunications industry is also a major source of employment for the country. Since the last few years, the Indian telecommunication service providers (TSPs), however, are facing business challenges related to increasing competition, losses, debts, and decreasing revenue. The strategic use of digital technologies for a successful digital transformation has the potential to equip organizations to meet these business challenges. Despite an increased focus on digital transformation, the telecom service providers globally, including Indian TSPs, have seen limited success so far. The purpose of this research was thus to identify the factors that are critical for the digital transformation and to what extent they influence the successful digital transformation of the Indian TSPs. The literature review of more than 300 digital transformation-related articles, mostly from 2013-2019, demonstrated a lack of an empirical model consisting of factors for the successful digital transformation of the TSPs. This study theorizes a research framework grounded in multiple theories, and a research model consisting of 7 constructs that may be influencing business success during the digital transformation of the organization was proposed. The questionnaire survey of senior managers in the Indian telecommunications industry was seeking to validate the research model. Based on 294 survey responses, the validation of the Structural equation model using the statistical tool ADANCO 2.1.1 was found to be robust. Results indicate that Digital Capabilities, Digital Strategy, and Corporate Level Data Strategy in that order has a strong influence on the successful Business Performance, followed by IT Function Transformation, Digital Innovation, and Transformation Management respectively. Even though Digital Organization did not have a direct significance on Business Performance outcomes, it had a strong influence on IT Function Transformation, thus affecting the Business Performance outcomes indirectly. Amongst numerous practical and theoretical contributions of the study, the main contribution for the Indian TSPs is a validated reference for prioritizing the transformation initiatives in their strategic roadmap. Also, the main contribution to the theory is the possibility to use the research framework artifact of the present research for quantitative validation in different industries and geographies.

Keywords: corporate level data strategy, digital capabilities, digital innovation, digital strategy

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Authors: Rana Mohamed

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Despite youth in Egypt were away from political life for a long time; they are able to make a tangible difference in political status. Purpose: This exploratory study aims to determine whether and how much the prevailing political culture influence participatory behavior with a special focus on political awareness factors among university students in Egypt. Methodology: The study employed several data collection methods to ensure the validity of the results, quantitative and qualitative, verifying the positive relationships between the levels of political awareness and political participation and between political values in society and the level of political participation among university students. For achieving the objectives of the paper in the light of the pool of available literature and data, the study adopts system analysis method to apply input-output and conversions associated with the phenomena of political participation to analyze the different factors that have an effect upon the prevailing political culture and the patterns of values in Egyptian society. Findings: The result reveals that the level of political awareness and political participation for students were low, with a statistically significant relationship. In addition, the patterns of values in Egyptian culture significantly influence the levels of student participation. Therefore, the study recommends formulating policies that aim to increase awareness levels and integrate youth into the political process. Originality/Value: The importance of the academic study stems from addressing one of the central issues in political science; this study measures the change in the Egyptian patterns of culture and values among university students.

Keywords: political awareness, political participation, civic culture, citizenship, Egyptian universities, political knowledge

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Authors: Rajvir Kaur, Jeewani Anupama Ginige

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With recent trends in Big Data and advancements in Information and Communication Technologies, the healthcare industry is at the stage of its transition from clinician oriented to technology oriented. Many people around the world die of cancer because the diagnosis of disease was not done at an early stage. Nowadays, the computational methods in the form of Machine Learning (ML) are used to develop automated decision support systems that can diagnose cancer with high confidence in a timely manner. This paper aims to carry out the comparative evaluation of a selected set of ML classifiers on two existing datasets: breast cancer and cervical cancer. The ML classifiers compared in this study are Decision Tree (DT), Support Vector Machine (SVM), k-Nearest Neighbor (k-NN), Logistic Regression, Ensemble (Bagged Tree) and Artificial Neural Networks (ANN). The evaluation is carried out based on standard evaluation metrics Precision (P), Recall (R), F1-score and Accuracy. The experimental results based on the evaluation metrics show that ANN showed the highest-level accuracy (99.4%) when tested with breast cancer dataset. On the other hand, when these ML classifiers are tested with the cervical cancer dataset, Ensemble (Bagged Tree) technique gave better accuracy (93.1%) in comparison to other classifiers.

Keywords: artificial neural networks, breast cancer, classifiers, cervical cancer, f-score, machine learning, precision, recall

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Authors: Tan Swee Liang

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This paper studies the two-way relationship between fintech credit and banking efficiency using the Generalized panel Method of Moment (GMM) estimation in structural equation modeling (SEM). Banking system efficiency, defined as its ability to produce the existing level of outputs with minimal inputs, is measured using input-oriented data envelopment analysis (DEA), where the whole banking system of an economy is treated as a single DMU. Banks are considered an intermediary between depositors and borrowers, utilizing inputs (deposits and overhead costs) to provide outputs (increase credits to the private sector and its earnings). Analysis of the interrelationship between fintech credit and bank efficiency is conducted to determine the impact in different country groupings (ASEAN, Asia and OECD), in particular the banking system response to fintech credit platforms. Our preliminary results show that banks do respond to the greater pressure caused by fintech platforms to enhance their efficiency, but differently across the different groups. The author’s earlier research on ASEAN-5 high bank overhead costs (as a share of total assets) as the determinant of economic growth suggests that expenses may not have been channeled efficiently to income-generating activities. One practical implication of the findings is that policymakers should enable alternative financing, such as fintech credit, as a warning or encouragement for banks to improve their efficiency.

Keywords: fintech lending, banking efficiency, data envelopment analysis, structural equation modeling

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Authors: Charity Ngoatle, Tebogo M. Mothiba, Mahlapahlapana J. Themane

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Misapprehension of medications instructions due to poor health literacy is common in diabetic patients, predominantly leading to suboptimal medication therapy caused by taking less than expected, or getting inadequate medication concentration. Globally, 50% of adults have been reported to have misunderstood medication instructions which could be the cause of not using medication as prescribed. Reading material has been found not to improve people’s knowledge to the extent where they would be informed and knowledgeable about their health. This, therefore, depicts that instructive materials alone cannot improve health literacy but further patient education is still needed to explain what the information really mean. The aim of this study was to investigate patients’ interpretation of prescribed medication instructions at Makanye Clinic in Limpopo Province, South Africa. The study used a mixed method approach. A non-probability purposive and simple random sampling strategies will be used to select ten (10) participants for the pilot study. Semi-structured interviews with a guide and self- administered structured questionnaires will be used to collect data. Tesch’s eight steps for qualitative data analysis and SPSS version 24 with descriptive statistics will be adopted. The preliminary findings from other studies show that: (a) poor health literacy negatively affect medication adherence, (b) general literacy influence health literacy, and (c) there are poor health outcomes and medication adverse effects due to poor medication comprehension.

Keywords: instructions, diabetes mellitus, patients, prescribed medication

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Authors: Joachim F. Sartor

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According to German guidelines, external natural catchments are greater sub-catchments without significant portions of impervious areas, which possess a surface drainage system and empty in a sewer network. Basically, such catchments should be disconnected from sewer networks, particularly from combined systems. If this is not possible due to local conditions, their flow hydrographs have to be considered at the design of sewer systems, because the impact may be significant. Since there is a lack of sufficient measurements of storm-runoff events for such catchments and hence verified simulation methods to analyze their design flows, German standards give only general advices and demands special considerations in such cases. Compared to urban sub-catchments, external natural catchments exhibit greatly different flow characteristics. With increasing area size their hydrological behavior approximates that of rural catchments, e.g. sub-surface flow may prevail and lag times are comparable long. There are few observed peak flow values and simple (mostly empirical) approaches that are offered by literature for Central Europe. Most of them are at least helpful to crosscheck results that are achieved by simulation lacking calibration. Using storm-runoff data from five monitored rural watersheds in the west of Germany with catchment areas between 0.33 and 1.07 km2 , the author investigated by multiple event simulation three different approaches to determine the rainfall excess. These are the modified SCS variable run-off coefficient methods by Lutz and Zaiß as well as the soil moisture model by Ostrowski. Selection criteria for storm events from continuous precipitation data were taken from recommendations of M 165 and the runoff concentration method (parallel cascades of linear reservoirs) from a DWA working report to which the author had contributed. In general, the two run-off coefficient methods showed results that are of sufficient accuracy for most practical purposes. The soil moisture model showed no significant better results, at least not to such a degree that it would justify the additional data collection that its parameter determination requires. Particularly typical convective summer events after long dry periods, that are often decisive for sewer networks (not so much for rivers), showed discrepancies between simulated and measured flow hydrographs.

Keywords: external natural catchments, sewer network design, storm-runoff modelling, urban drainage

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Authors: Meghan E. Murray, Carri R. Tolmie

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This study aims to identify potential factors and widely applicable best practices that can contribute to improving corporate social responsibility (CSR) and corporate performance for firms by exploring the relationship between transformational leadership, spiritual intelligence, and emotional intelligence. Corporate social responsibility is when companies are cognizant of the impact of their actions on the economy, their communities, the environment, and the world as a whole while executing business practices accordingly. The prevalence of CSR has continuously strengthened over the past few years and is now a common practice in the business world, with such efforts coinciding with what stakeholders and the public now expect from corporations. Because of this, it is extremely important to be able to pinpoint factors and best practices that can improve CSR within corporations. One potential factor that may lead to improved CSR is spiritual intelligence (SQ), or the ability to recognize and live with a purpose larger than oneself. Spiritual intelligence is a measurable skill, just like emotional intelligence (EQ), and can be improved through purposeful and targeted coaching. This research project consists of two studies. Study 1 is a case study comparison of a benefit corporation and a non-benefit corporation. This study will examine the role of SQ and EQ as moderators in the relationship between the transformational leadership of employees within each company and the perception of each firm’s CSR and corporate performance. Project methodology includes creating and administering a survey comprised of multiple pre-established scales on transformational leadership, spiritual intelligence, emotional intelligence, CSR, and corporate performance. Multiple regression analysis will be used to extract significant findings from the collected data. Study 2 will dive deeper into spiritual intelligence itself by analyzing pre-existing data and identifying key relationships that may provide value to companies and their stakeholders. This will be done by performing multiple regression analysis on anonymized data provided by Deep Change, a company that has created an advanced, proprietary system to measure spiritual intelligence. Based on the results of both studies, this research aims to uncover best practices, including the unique contribution of spiritual intelligence, that can be utilized by organizations to help enhance their corporate social responsibility. If it is found that high spiritual and emotional intelligence can positively impact CSR effort, then corporations will have a tangible way to enhance their CSR: providing targeted employees with training and coaching to increase their SQ and EQ.

Keywords: corporate social responsibility, CSR, corporate performance, emotional intelligence, EQ, spiritual intelligence, SQ, transformational leadership

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Authors: Simon Quick, John Lyle

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Psychology-based research has been a characteristic of empirical enquiry in sport coaching for over fifty years and cognitive function is widely accepted as a fundamental component of sport coaching expertise. Within the academic literature, much empirical research on coaches’ cognitions has tended to adopt retrospective approaches, such as post-session interviews or stimulated recall, thus capturing coaches’ cognitions after the incident, training session or competition. Such methods are prone to a variety of issues, including memory decay and the reordering of accounts. The aim of this research was to overcome the limitations that exist with retrospective approaches and, rather, to capture coaching cognitions in situ using Think Aloud Protocol. Data that were captured was broken down into meaning units and analysed using a Thematic Analysis. Situated in the practice of 6 experienced rugby coaches, findings revealed that Think Aloud Protocol generated rich data, although problematic in a site of enquiry confounded by multiple social interactions and requiring coaches to provide frequent instruction and feedback. The resultant interaction between cognition and action is conceptualised by the tentative offering of a model that situates these elements in conjunction with cognitive triggers and thresholds. The implications of these findings can help academics and coaches to understand the dynamic relationship between types of coaching cognitions and the complexity of the coaching environment.

Keywords: sports coaching, Psychology, Pedagogy, cognition

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Authors: P. O. Fatoki, R. S. Olaleye, B. O. Adeniji

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The study investigated farmers’ perception of the effects of climate change on rice production in Nasarawa State, Nigeria. Multi-stage sampling technique was used in selecting a total of 248 rice farmers from the study area. Data for the study were collected through the use of interview schedule. The data were analysed using both descriptive and inferential statistics. Results showed that majority (71.8%) of the respondents were married and the mean age of the respondents was 44.54 years. The results also showed that most adapted strategies for mitigating the effects of climate change on rice production were change of planting and harvesting date (67.7%), movement to another site (63.7%) and increased or reduced land size (58.5%). Relationship between the roles of extension agents in mitigating climate change effects on rice production and farmers’ perception were significant as revealed Chi-Square analysis from the study ; Dissemination of information ( = 2.16, P < 0.05) and use of demonstration methods ( = 2.15, P < 0.05). Poisson regression analysis revealed that educational status, farm size, experience and yield had significant relationship with the perception of the effects of climate change at 0.01 significance level while household size was as well significant at 0.05. It is recommended that some of the adaptive strategies and practices for mitigating the effects of climate change in rice production should be improved, while the extension outfits should be strengthened to ensure adequate dissemination of relevant information on climate change with a view to mitigate its effects on rice production.

Keywords: perception, rice farmers, climate change, mitigation, adaptive strategies

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Authors: Francia Martinez

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This study documents and demonstrates the profound impact of the high status of American English and culture in Colombian commercial landscape due to the globalization and commodification of English. It also documents and describes how Colombian advertisers make use of various language and visual mechanisms in the commercial linguistic landscape to convey messages, create an image with which the target audience can identify, and build a relationship with that target audience. The data (in the form of pictures) were collected in different cities in Colombia and were classified and organized into different categories for the reliability and validity of the analysis. The research questions were: do the ubiquity and high status of American English and culture play a major role in the Colombian commercial linguistic landscape? If so, how?, what roles do national and local culture and language (Spanish) play in the commercial linguistic landscape?, and what different linguistic and visual strategies do Colombian advertisers employ to reach their target audience? Based on data analysis and results, American and local culture and icons play a major role when Colombian advertisers create and design their commercial logos and ads to get consumers’ attention and establish a rapport with them in a successful way. In order to achieve their objectives, Colombian advertisers rely on creative linguistic and visual techniques in their ads, such as puns, humor, irony, comparisons, metaphors, mocking, exaggeration, parody, personification, sarcasm, satire, allusion, onomatopoeias, and imitation (copycat or cloning).

Keywords: Colombian ads, linguistic landscape, rhetorical devices, sociolinguistics

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Authors: Rajashree Bothale, Venkateswara Rao

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Indian Himalayas also known as third pole with 0.9 Million SQ km area, contain the largest reserve of ice and snow outside poles and affect global climate and water availability in the perennial rivers. The variations in the extent of snow are indicative of climate change. The snow melt is sensitive to climate change (warming) and also an influencing factor to the climate change. A study of the spatio-temporal dynamics of snow cover and melt/freeze conditions is carried out using space based observations in visible and microwave bands. An analysis period of 2003 to 2015 is selected to identify and map the changes and trend in snow cover using Indian Remote Sensing (IRS) Advanced Wide Field Sensor (AWiFS) and Moderate Resolution Imaging Spectroradiometer(MODIS) data. For mapping of wet snow, microwave data is used, which is sensitive to the presence of liquid water in the snow. The present study uses Ku-band scatterometer data from QuikSCAT and Oceansat satellites. The enhanced resolution images at 2.25 km from the 13.6GHz sensor are used to analyze the backscatter response to dry and wet snow for the period of 2000-2013 using threshold method. The study area is divided into three major river basins namely Brahmaputra, Ganges and Indus which also represent the diversification in Himalayas as the Eastern Himalayas, Central Himalayas and Western Himalayas. Topographic variations across different zones show that a majority of the study area lies in 4000–5500 m elevation range and the maximum percent of high elevated areas (>5500 m) lies in Western Himalayas. The effect of climate change could be seen in the extent of snow cover and also on the melt/freeze status in different parts of Himalayas. Melt onset day increases from east (March11+11) to west (May12+15) with large variation in number of melt days. Western Himalayas has shorter melt duration (120+15) in comparison to Eastern Himalayas (150+16) providing lesser time for melt. Eastern Himalaya glaciers are prone for enhanced melt due to large melt duration. The extent of snow cover coupled with the status of melt/freeze indicating solar radiation can be used as precursor for monsoon prediction.

Keywords: Indian Himalaya, Scatterometer, Snow Melt/Freeze, AWiFS, Cryosphere

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Authors: Harpal Singh, Sakshi Batra

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The widespread and easy accesses to multimedia contents and possibility to make numerous copies without loss of significant fidelity have roused the requirement of digital rights management. Thus this problem can be effectively solved by Digital watermarking technology. This is a concept of embedding some sort of data or special pattern (watermark) in the multimedia content; this information will later prove ownership in case of a dispute, trace the marked document’s dissemination, identify a misappropriating person or simply inform user about the rights-holder. The primary motive of digital watermarking is to embed the data imperceptibly and robustly in the host information. Extensive counts of watermarking techniques have been developed to embed copyright marks or data in digital images, video, audio and other multimedia objects. With the development of digital video-based innovations, copyright dilemma for the multimedia industry increases. Video watermarking had been proposed in recent years to serve the issue of illicit copying and allocation of videos. It is the process of embedding copyright information in video bit streams. Practically video watermarking schemes have to address some serious challenges as compared to image watermarking schemes like real-time requirements in the video broadcasting, large volume of inherently redundant data between frames, the unbalance between the motion and motionless regions etc. and they are particularly vulnerable to attacks, for example, frame swapping, statistical analysis, rotation, noise, median and crop attacks. In this paper, an effective, robust and imperceptible video watermarking algorithm is proposed based on hybridization of powerful mathematical transforms; Fractional Fourier Transform (FrFT), Discrete Wavelet transforms (DWT) and Singular Value Decomposition (SVD) using redundant wavelet. This scheme utilizes various transforms for embedding watermarks on different layers by using Hybrid systems. For this purpose, the video frames are portioned into layers (RGB) and the watermark is being embedded in two forms in the video frames using SVD portioning of the watermark, and DWT sub-band decomposition of host video, to facilitate copyright safeguard as well as reliability. The FrFT orders are used as the encryption key that allows the watermarking method to be more robust against various attacks. The fidelity of the scheme is enhanced by introducing key generation and wavelet based key embedding watermarking scheme. Thus, for watermark embedding and extraction, same key is required. Therefore the key must be shared between the owner and the verifier via some safe network. This paper demonstrates the performance by considering different qualitative metrics namely Peak Signal to Noise ratio, Structure similarity index and correlation values and also apply some attacks to prove the robustness. The Experimental results are presented to demonstrate that the proposed scheme can withstand a variety of video processing attacks as well as imperceptibility.

Keywords: discrete wavelet transform, robustness, video watermarking, watermark

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Authors: Ivan Samokhin

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A new two-factor model of school students’ capacity levels is proposed. It considers the academic productivity and emotional condition of children taking part in the study process. Each basic level reflects the correlation of these two factors. The teacher decides whether the required result is achieved or not and write down the grade (from 'A' to 'F') in the register. During the term, the teacher can estimate the students’ progress with any intervals, but it is not desirable to exceed a two-week period (with primary school being an exception). Each boy or girl should have a special notebook to record the emotions which they feel studying a subject. The children can make their notes the way they like it – for example, using a ten-point scale or a short verbal description. It is recommended to record the emotions twice a day: after the lesson and after doing the homework. Before the students start doing this, they should be instructed by a school psychologist, who has to emphasize that an attitude to the subject – not to a person in charge of it – is relevant. At the end of the term, the notebooks are given to the teacher, who is now able to make preliminary conclusions about academic results and psychological comfort of each student. If necessary, some pedagogical measures can be taken. The data about a supposed capacity level is available for the teacher and the school administration. In certain cases, this information can be also revealed to the student’s parents, while the student learns it only after receiving a school-leaving certificate (until this moment, the results are not considered ultimate). Then a person may take these data into consideration when choosing his/her future area of higher education. We single out four main capacity levels: 'nominally low', 'inclination', 'ability' and 'gift'.

Keywords: academic productivity, capacity level, emotional condition, school students

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Authors: Mohamed A. Saleem

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Using mostly seismic data, this study intends to show some examples of igneous intrusions found in some areas of the Sirt Basin and explore the period of their emplacement as well as the interrelationships between these sills. The study area is located in the south of the Zallah Trough, south-west Sirt basin, Libya. It is precisely between the longitudes 18.35ᵒ E and 19.35ᵒ E, and the latitudes 27.8ᵒ N and 28.0ᵒ N. Based on a variety of criteria that are usually used as marks on the igneous intrusions, twelve igneous intrusions (Sills), have been detected and analysed using 3D seismic data. One or more of the following were used as identification criteria: the high amplitude reflectors paired with abrupt reflector terminations, vertical offsets, or what is described as a dike-like connection, the violation, the saucer form, and the roughness. Because of their laying between the hosting layers, the majority of these intrusions are classified as sills. Another distinguishing feature is the intersection geometry link between some of these sills. Every single sill has given a name just to distinguish the sills from each other such as S-1, S-2, and …S-12. To avoid the repetition of description, the common characteristics and some statistics of these sills are shown in summary tables, while the specific characters that are not common and have been noticed for each sill are shown individually. The sills, S-1, S-2, and S-3, are approximately parallel to one other, with the shape of these sills being governed by the syncline structure of their host layers. The faults that dominated the strata (pre-upper Cretaceous strata) have a significant impact on the sills; they caused their discontinuity, while the upper layers have a shape of anticlines. S-1 and S-10 are the group's deepest and highest sills, respectively, with S-1 seated near the basement's top and S-10 extending into the sequence of the upper cretaceous. The dramatic escalation of sill S-4 can be seen in N-S profiles. The majority of the interpreted sills are influenced and impacted by a large number of normal faults that strike in various directions and propagate vertically from the surface to the basement's top. This indicates that the sediment sequences were existed before the sill’s intrusion, were deposited, and that the younger faults occurred more recently. The pre-upper cretaceous unit is the current geological depth for the Sills S-1, S-2 … S-9, while Sills S-10, S-11, and S-12 are hosted by the Cretaceous unit. Over the sills S-1, S-2, and S-3, which are the deepest sills, the pre-upper cretaceous surface has a slightly forced folding, these forced folding is also noticed above the right and left tips of sill S-8 and S-6, respectively, while the absence of these marks on the above sequences of layers supports the idea that the aforementioned sills were emplaced during the early upper cretaceous period.

Keywords: Sirt Basin, Zallah Trough, igneous intrusions, seismic data

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Authors: Panagiotis Karadimos, Leonidas Anthopoulos

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Predicting the actual cost and duration in construction projects concern a continuous and existing problem for the construction sector. This paper addresses this problem with modern methods and data available from past public construction projects. 39 bridge projects, constructed in Greece, with a similar type of available data were examined. Considering each project’s attributes with the actual cost and the actual duration, correlation analysis is performed and the most appropriate predictive project variables are defined. Additionally, the most efficient subgroup of variables is selected with the use of the WEKA application, through its attribute selection function. The selected variables are used as input neurons for neural network models through correlation analysis. For constructing neural network models, the application FANN Tool is used. The optimum neural network model, for predicting the actual cost, produced a mean squared error with a value of 3.84886e-05 and it was based on the budgeted cost and the quantity of deck concrete. The optimum neural network model, for predicting the actual duration, produced a mean squared error with a value of 5.89463e-05 and it also was based on the budgeted cost and the amount of deck concrete.

Keywords: actual cost and duration, attribute selection, bridge construction, neural networks, predicting models, FANN TOOL, WEKA

Procedia PDF Downloads 134

Authors: Paul Buchana, Patrick E. Mc Sharry

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In 2017 there will be about 38 wind farms in the North Sea belonging to 5 different countries. The North Sea is ideal for offshore wind power generation and is thus attractive to offshore wind energy developers and investors. With concerns about the potential for offshore wind turbines to sustain substantial damage as a result of extreme weather conditions, particularly windstorms, this poses a unique challenge to insurers and reinsurers as to adequately quantify the risk and offer appropriate insurance cover for these assets. The need to manage this risk also concerns regulators, who provide the oversight needed to ensure that if a windstorm or a series of storms occur in this area over a one-year time frame, the insurers of these assets in the EU remain solvent even after meeting consequent damage costs. In this paper, using available European windstorm data for the past 33 years and actual wind farm locations together with information pertaining to each of the wind farms (number of turbines, total capacity and financial value), we present a Monte Carlo simulation approach to assess the number of turbines that would be buckled in each of the wind farms using maximum wind speeds reaching each of them. These wind speeds are drawn from historical windstorm data. From the number of turbines buckled, associated financial loss and output capacity can be deduced. The results presented in this paper are targeted towards offshore wind energy developers, insurance and reinsurance companies and regulators.

Keywords: catastrophe modeling, North Sea wind farms, offshore wind power, risk analysis

Procedia PDF Downloads 299

Authors: Maher El-Masri, Jamie Crawley, Judy Bornais, Abeer Omar

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Background: Misuse of Emergency Department (ED) for non-urgent healthcare results in unnecessary crowdedness that can result in long ED waits and delays in treatment, diversion of ambulances to other hospitals, poor health outcomes for patients, and increased risk of death Objectives: The main purpose of this study was to explore the independent predictors of non-urgent ED visits in Erie St. Clair LHIN. Secondary purposes of the study include comparison of the rates of non-urgent ED visits between urban and rural hospitals Design: A secondary analysis of archived population-based data on 597,373 ED visits in southwestern Ontario Results The results suggest that older (OR = .992; 95% CI .992 – .993) and female patients (OR = .940; 95% CI .929 - .950) were less likely to visit ED for non-urgent causes. Non-urgent ED visits during the winter, spring, and fall were 13%, 5.8%, and 7.5%, respectively, lesser than they were during the summer time. The data further suggest that non-urgent visits were 19.6% and 21.3% less likely to occur in evening and overnight shifts compared to the day shift. Non-urgent visits were 2.76 times more likely to present to small community hospitals than large community hospitals. Health care providers were 1.92 times more likely to refer patients with non-urgent health problem to the ED than the decision taken by patients, family member or caretakers. Conclusion: In conclusion, our study highlights a number of important factors that are associated with inappropriate use of ED visits for non-urgent health problems. Knowledge of these factors could be used to address the issue of unnecessary ED crowdedness.

Keywords: emergency department, non-urgent visits, predictors, logistic regression

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Authors: Eashwari Dahoe, Jody Scheuer, Harm-Jan Vink

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Alzheimer's disease is a progressive brain condition and is the most common form of dementia. Dementia is a global concern. It is an increasing crisis due to the worldwide aging population. The disease alters the body in different stages leading to several issues. The most common issues result in memory loss, responsive decline, and social decline. During the various stages, the dementia patient must be supported more in performing daily tasks. Eventually, the patient will have to be cared for entirely. There are many efforts in various domains to support this brain condition. This study focuses on the connection between three generations of solutions in the domain of technology and the struggles they tackle. To gather information regarding the struggles seniors with dementia face data has been acknowledged through reading scientific articles. The struggles are extracted from these articles and classified into various category struggles. To gather information regarding the three generations of technology data has been acknowledged through reading scientific articles regarding the generations. After understanding the difference between the three generations, international technological solutions from the past 20 years are connected to the generation they fit. This info is mainly collected through research on companies that aim to improve the lives of senior citizens with early stages of dementia. Eventually, the technological solutions (divided by generations) are linked to the struggles they tackle. By connecting the struggles and the solutions , it is hoped that this paper contributes to an informative overview of the currently available technological solutions and the struggles they tackle.

Keywords: Alzheimer’s disease, technological solutions to support dementia, struggles of seniors with dementia, struggles of dementia

Procedia PDF Downloads 109

Authors: Roven Tumaneng, Angelica Kristina Monzon, Ralph Sedricke Lapuz, Jose Don De Alban, Jennica Paula Masigan, Joanne Rae Pales, Laila Monera Pornel, Dennis Tablazon, Rizza Karen Veridiano, Jackie Lou Wenceslao, Edmund Leo Rico, Neil Aldrin Mallari

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Most protected area management plans in the Philippines, particularly the smaller and more remote islands suffer from insufficient baseline data, which should provide the bases for formulating measureable conservation targets and appropriate management interventions for these protected areas. Attempts to synthesize available data particularly on cultural and socio-economic characteristic of local peoples within and outside protected areas also suffer from the lack of comprehensive and detailed inventories, which should be considered in designing adaptive management interventions to be used for those protected areas. Mt Guiting-guiting Natural Park (MGGNP) located in Sibuyan Island is one of the poorly studied protected areas in the Philippines. In this study, we determined the highly biologically important areas of the protected area using Maximum Entropy approach (MaxEnt) from environmental predictors (i.e., topographic, bioclimatic,land cover, and soil image layers) derived from global remotely sensed data and point occurrence data of species of birds and trees recorded during field surveys on the island. A total of 23 trigger species of birds and trees was modeled and stacked to generate species richness maps for biological high conservation value areas (HCVAs). Forest habitat change was delineated using dual-polarised L-band ALOS-PALSAR mosaic data at 25 meter spatial resolution, taken at two acquisition years 2007 and 2009 to provide information on forest cover ad habitat change in the island between year 2007 and 2009. Determining the livelihood guilds were also conducted using the data gathered from171 household interviews, from which demographic and livelihood variables were extracted (i.e., age, gender, number of household members, educational attainment, years of residency, distance from forest edge, main occupation, alternative sources of food and resources during scarcity months, and sources of these alternative resources).Using Principal Component Analysis (PCA) and Kruskal-Wallis test, the diversity and patterns of forest resource use by people in the island were determined with particular focus on the economic activities that directly and indirectly affect the population of key species as well as to identify levels of forest resource use by people in different areas of the park.Results showed that there are gaps in the area occupied by the natural park, as evidenced by the mismatch of the proposed HCVAs and the existing perimeters of the park. We found out that subsistence forest gathering was the possible main driver for forest degradation out of the eight livelihood guilds that were identified in the park. Determining the high conservation areas and identifyingthe anthropogenic factors that influence the species richness and abundance of key species in the different management zone of MGGNP would provide guidance for the design of a protected area management plan and future monitoring programs. However, through intensive communication and consultation with government stakeholders and local communities our results led to setting conservation targets in local development plans and serve as a basis for the reposition of the boundaries and reconfiguration of the management zones of MGGNP.

Keywords: conservation gaps, livelihood guilds, MaxEnt, protected area

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Authors: Bezuglov Eduard, Achkasov Evgeniy, Emanov Anton, Shagiakhmetova Larisa, Pirmakhanov Bekzhan, Morgans Ryland

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Background: Previous studies have found that there is a wide range of the relative age effect (RAE) in young athletes, which is dependent on age and gender. However, there is currently scant data comparing the prevalence of the RAE in successful athletes across different age groups from the same sport during the same time period. We aimed to compare the prevalence of the RAE in different age groups of successful athletes. Materials and methods: The date of birth of all youth (under 18 years old) and senior (20 years and above) male and female track and field athletes were analyzed. All athletes had entered the World Top 20 rankings in disciplines where performance rules were the same at youth and adult levels. Data were collected from the website www. tilostopaja.eu between 1999 and 2006. Results: A significant prevalence of RAE in successful youth track and field athletes were reported. Early-born (61,1%) and late-born (38,9%) athletes were represented respectively (χ2 = 131,1, p < 0,001, ϖ = 0,24). The RAE is not significant in successful senior track and field athletes. Athletes born in the first half of the year are only 0.4% more prevalent than athletes born in the second half of the year (50,2% and 49,8%, respectively). Olympic Games and World Championship medalists are more often late-born athletes (44,1% and 55,9%, respectively) (p = 0,014, χ2 = 6,1, ϖ = 0,20). Conclusion: The RAE is only prevalent in successful young track and field athletes. The RAE was not observed in successful senior track and field athletes, regardless of gender, in any of the analyzed discipline groups. The RAE reverse was observed in successful senior track and field athletes.

Keywords: relative age effect, track, and field, talent identification, underdog effect

Procedia PDF Downloads 154

Authors: Yasaman Sanayei, Alireza Bahiraie

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This paper presents a systematic methodology based on the application of artificial neural networks for sequencing batch reactor (SBR). The SBR is a fill-and-draw biological wastewater technology, which is specially suited for nutrient removal. Employing reactive dye by Sphingomonas paucimobilis bacteria at sequence batch reactor is a novel approach of dye removal. The influent COD, MLVSS, and reaction time were selected as the process inputs and the effluent COD and BOD as the process outputs. The best possible result for the discrete pole parameter was a= 0.44. In orderto adjust the parameters of ANN, the Levenberg-Marquardt (LM) algorithm was employed. The results predicted by the model were compared to the experimental data and showed a high correlation with R2> 0.99 and a low mean absolute error (MAE). The results from this study reveal that the developed model is accurate and efficacious in predicting COD and BOD parameters of the dye-containing wastewater treated by SBR. The proposed modeling approach can be applied to other industrial wastewater treatment systems to predict effluent characteristics. Note that SBR are normally operated with constant predefined duration of the stages, thus, resulting in low efficient operation. Data obtained from the on-line electronic sensors installed in the SBR and from the control quality laboratory analysis have been used to develop the optimal architecture of two different ANN. The results have shown that the developed models can be used as efficient and cost-effective predictive tools for the system analysed.

Keywords: artificial neural network, COD removal, SBR, Sphingomonas paucimobilis

Procedia PDF Downloads 413