Search results for: graphical password

Authors: Umedov Mekhroz, Griaznova Svetlana

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In connection with the growth of oncological diseases, the design of centers for diagnostics and the production of radiopharmaceuticals is the most relevant area of healthcare facilities. The design of new nuclear medicine centers should be carried out from the standpoint of solving the following tasks: the availability of medical care, functionality, environmental friendliness, sustainable development, improving the safety of drugs, the use of which requires special care, reducing the rate of environmental pollution, ensuring comfortable conditions for the internal microclimate, adaptability. The purpose of this article is to substantiate architectural and planning solutions, formulate recommendations and principles for the design of nuclear medicine centers and determine the connections between the production and medical functions of a building. The advantages of combining the production of radiopharmaceuticals and the department of medical care: less radiation activity is accumulated, the cost of the final product is lower, and there is no need to hire a transport company with a special license for transportation. A medical imaging department is a structural unit of a medical institution in which diagnostic procedures are carried out in order to gain an idea of the internal structure of various organs of the body for clinical analysis. Depending on the needs of a particular institution, the department may include various rooms that provide medical imaging using radiography, ultrasound diagnostics, and the phenomenon of nuclear magnetic resonance. The production of radiopharmaceuticals is an object intended for the production of a pharmaceutical substance containing a radionuclide and intended for introduction into the human body or laboratory animal for the purpose of diagnosis, evaluation of the effectiveness of treatment, or for biomedical research. The research methodology includes the following subjects: study and generalization of international experience in scientific research, literature, standards, teaching aids, and design materials on the topic of research; An integrated approach to the study of existing international experience of PET / CT scan centers and the production of radiopharmaceuticals; Elaboration of graphical analysis and diagrams based on the system analysis of the processed information; Identification of methods and principles of functional zoning of nuclear medicine centers. The result of the research is the identification of the design principles of nuclear medicine centers with the functions of the production of radiopharmaceuticals and the department of medical imaging. This research will be applied to the design and construction of healthcare facilities in the field of nuclear medicine.

Keywords: architectural planning solutions, functional zoning, nuclear medicine, PET/CT scan, production of radiopharmaceuticals, radiotherapy

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Authors: Sabri Serkan Gulluoglu

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The study is aimed at examining the effects of internet marketing with IPTV on human beings. Internet marketing with IPTV is emerging as an integral part of business strategies in today’s technologically advanced world and the business activities all over the world are influences with the emergence of this modern marketing tool. As the population of the Internet and on-line users’ increases, new research issues have arisen concerning the demographics and psychographics of the on-line user and the opportunities for a product or service. In recent years, we have seen a tendency of various services converging to the ubiquitous Internet Protocol based networks. Besides traditional Internet applications such as web browsing, email, file transferring, and so forth, new applications have been developed to replace old communication networks. IPTV is one of the solutions. In the future, we expect a single network, the IP network, to provide services that have been carried by different networks today. For finding some important effects of a video based technology market web site on internet, we determine to apply a questionnaire on university students. Recently some researches shows that in Turkey the age of people 20 to 24 use internet when they buy some electronic devices such as cell phones, computers, etc. In questionnaire there are ten categorized questions to evaluate the effects of IPTV when shopping. There were selected 30 students who are filling the question form after watching an IPTV channel video for 10 minutes. This sample IPTV channel is “buy.com”, it look like an e-commerce site with an integrated IPTV channel on. The questionnaire for the survey is constructed by using the Likert scale that is a bipolar scaling method used to measure either positive or negative response to a statement (Likert, R) it is a common system that is used is the surveys. By following the Likert Scale “the respondents are asked to indicate their degree of agreement with the statement or any kind of subjective or objective evaluation of the statement. Traditionally a five-point scale is used under this methodology”. For this study also the five point scale system is used and the respondents were asked to express their opinions about the given statement by picking the answer from the given 5 options: “Strongly disagree, Disagree, Neither agree Nor disagree, Agree and Strongly agree”. These points were also rates from 1-5 (Strongly disagree, Disagree, Neither disagree Nor agree, Agree, Strongly agree). On the basis of the data gathered from the questionnaire some results are drawn in order to get the figures and graphical representation of the study results that can demonstrate the outcomes of the research clearly.

Keywords: IPTV, internet marketing, online, e-commerce, video based technology

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Authors: Katarzyna Wyka, Dana Sylvan, JoAnn Difede

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Background and significance: The following disaster, population-based screening programs are routinely established to assess physical and psychological consequences of exposure. These data sets are highly skewed as only a small percentage of trauma-exposed individuals develop health issues. Commonly used statistical methodology in post-disaster mental health generally involves population-averaged models. Such models aim to capture the overall response to the disaster and its aftermath; however, they may not be sensitive enough to accommodate population heterogeneity in symptomatology, such as post-traumatic stress or depressive symptoms. Methods: We use an archival longitudinal data set from Weill-Cornell 9/11 Mental Health Screening Program established following the World Trade Center (WTC) terrorist attacks in New York in 2001. Participants are rescue and recovery workers who participated in the site cleanup and restoration (n=2960). The main outcome is the post-traumatic stress symptoms (PTSD) severity score assessed via clinician interviews (CAPS). For a detailed understanding of response to the disaster and its aftermath, we are adapting quantile regression methodology with particular focus on predictors of extreme distress and resilience to trauma. Results: The response variable was defined as the quantile of the CAPS score for each individual under two different scenarios specifying the unconditional quantiles based on: 1) clinically meaningful CAPS cutoff values and 2) CAPS distribution in the population. We present graphical summaries of the differential effects. For instance, we found that the effect of the WTC exposures, namely seeing bodies and feeling that life was in danger during rescue/recovery work was associated with very high PTSD symptoms. A similar effect was apparent in individuals with prior psychiatric history. Differential effects were also present for age and education level of the individuals. Conclusion: We evaluate the utility of quantile regression in disaster research in contrast to the commonly used population-averaged models. We focused on assessing the distribution of risk factors for post-traumatic stress symptoms across quantiles. This innovative approach provides a comprehensive understanding of the relationship between dependent and independent variables and could be used for developing tailored training programs and response plans for different vulnerability groups.

Keywords: disaster workers, post traumatic stress, PTSD, quantile regression

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Authors: Teodorica G. Ani

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Economic activity requires an encouraging regulatory environment and effective rules that are transparent and accessible to all. The World Bank has been publishing the annual Doing Business reports since 2004 to investigate the scope and manner of regulations that enhance business activity and those that constrain it. A streamlined business environment supporting the development of competitive small and medium enterprises (SMEs) may expand employment opportunities and improve the living conditions of low income households. Asia has emerged as one of the most attractive markets in the world. Economies in East Asia and the Pacific were among the most active in making it easier for local firms to do business. The study aimed to describe the ease of doing business and its effect to economic growth among selected economies in Asia for the year 2014. The study covered 29 economies in East Asia, Southeast Asia, South Asia and Middle Asia. Ease of doing business is measured by the Doing Business indicators (DBI) of the World Bank. The indicators cover ten aspects of the ease of doing business such as starting a business, dealing with construction permits, getting electricity, registering property, getting credit, protecting investors, paying taxes, trading across borders, enforcing contracts and resolving insolvency. In the study, Gross Domestic Product (GDP) was used as the proxy variable for economic growth. Descriptive research was the research design used. Graphical analysis was used to describe the income and doing business among selected economies. In addition, multiple regression was used to determine the effect of doing business to economic growth. The study presented the income among selected economies. The graph showed China has the highest income while Maldives produces the lowest and that observation were supported by gathered literatures. The study also presented the status of the ten indicators of doing business among selected economies. The graphs showed varying trends on how easy to start a business, deal with construction permits and to register property. Starting a business is easiest in Singapore followed by Hong Kong. The study found out that the variations in ease of doing business is explained by starting a business, dealing with construction permits and registering property. Moreover, an explanation of the regression result implies that a day increase in the average number of days it takes to complete a procedure will decrease the value of GDP in general. The research proposed inputs to policy which may increase the awareness of local government units of different economies on the simplification of the policies of the different components used in measuring doing business.

Keywords: doing business, economic growth, gross domestic product, Asia

Procedia PDF Downloads 352

Authors: Sara Ignoto, Elena M. Scalisi, Carmen Sica, Martina Contino, Greta Ferruggia, Antonio Salvaggio, Santi C. Pavone, Gino Sorbello, Loreto Di Donato, Roberta Pecoraro, Maria V. Brundo

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The new fifth generation technology (5G), which should favor high data-rate connections (1Gbps) and latency times lower than the current ones (<1ms), has the characteristic of working on different frequency bands of the radio wave spectrum (700 MHz, 3.6-3.8 GHz and 26.5-27.5 GHz), thus also exploiting higher frequencies than previous mobile radio generations (1G-4G). The higher frequency waves, however, have a lower capacity to propagate in free space and therefore, in order to guarantee the capillary coverage of the territory for high reliability applications, it will be necessary to install a large number of repeaters. Following the introduction of this new technology, there has been growing concern in recent years about the possible harmful effects on human health and several studies were published using several animal models. This study aimed to observe the possible short-term effects induced by 5G-millimeter waves on heartbeat of early life stages of Danio rerio using DanioScope software (Noldus). DanioScope is the complete toolbox for measurements on zebrafish embryos and larvae. The effect of substances can be measured on the developing zebrafish embryo by a range of parameters: earliest activity of the embryo’s tail, activity of the developing heart, speed of blood flowing through the vein, length and diameters of body parts. Activity measurements, cardiovascular data, blood flow data and morphometric parameters can be combined in one single tool. Obtained data are elaborate and provided by the software both numerical as well as graphical. The experiments were performed at 27 GHz by a no commercial high gain pyramidal horn antenna. According to OECD guidelines, exposure to 5G-millimeter waves was tested by fish embryo toxicity test within 96 hours post fertilization, Observations were recorded every 24h, until the end of the short-term test (96h). The results have showed an increase of heartbeat rate on exposed embryos at 48h hpf than control group, but this increase has not been shown at 72-96 h hpf. Nowadays, there is a scant of literature data about this topic, so these results could be useful to approach new studies and also to evaluate potential cardiotoxic effects of mobile radiofrequency.

Keywords: Danio rerio, DanioScope, cardiotoxicity, millimeter waves.

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Authors: S. Jurado, E. Pazmino

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Determination of the medial axis of a porous media sample is a non-trivial problem of interest for several disciplines, e.g., hydrology, fluid dynamics, contaminant transport, filtration, oil extraction, etc. However, the computational tools available for researchers are limited and restricted. The primary aim of this work was to develop a series of algorithms to extract porosity, medial axis structure, and pore-throat size distributions from porous media domains. A complementary objective was to provide the algorithms as free computational software available to the academic community comprising researchers and students interested in 3D data processing. The burn algorithm was tested on porous media data obtained from High-Resolution X-Ray Microtomography (HRXMT) and idealized computer-generated domains. The real data and idealized domains were discretized in voxels domains of 550³ elements and binarized to denote solid and void regions to determine porosity. Subsequently, the algorithm identifies the layer of void voxels next to the solid boundaries. An iterative process removes or 'burns' void voxels in sequence of layer by layer until all the void space is characterized. Multiples strategies were tested to optimize the execution time and use of computer memory, i.e., segmentation of the overall domain in subdomains, vectorization of operations, and extraction of single burn layer data during the iterative process. The medial axis determination was conducted identifying regions where burnt layers collide. The final medial axis structure was refined to avoid concave-grain effects and utilized to determine the pore throat size distribution. A graphic user interface software was developed to encompass all these algorithms, including the generation of idealized porous media domains. The software allows input of HRXMT data to calculate porosity, medial axis, and pore-throat size distribution and provide output in tabular and graphical formats. Preliminary tests of the software developed during this study achieved medial axis, pore-throat size distribution and porosity determination of 100³, 320³ and 550³ voxel porous media domains in 2, 22, and 45 minutes, respectively in a personal computer (Intel i7 processor, 16Gb RAM). These results indicate that the software is a practical and accessible tool in postprocessing HRXMT data for the academic community.

Keywords: medial axis, pore-throat distribution, porosity, porous media

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Authors: Yamina Boughari, Ruxandra Mihaela Botez, Florian Theel, Georges Ghazi

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Clearance of flight control laws of a civil aircraft is a long and expensive process in the Aerospace industry. Thousands of flight combinations in terms of speeds, altitudes, gross weights, centers of gravity and angles of attack have to be investigated, and proved to be safe. Nonetheless, in this method, a worst flight condition can be easily missed, and its missing would lead to a critical situation. Definitively, it would be impossible to analyze a model because of the infinite number of cases contained within its flight envelope, that might require more time, and therefore more design cost. Therefore, in industry, the technique of the flight envelope mesh is commonly used. For each point of the flight envelope, the simulation of the associated model ensures the satisfaction or not of specifications. In order to perform fast, comprehensive and effective analysis, other varying parameters models were developed by incorporating variations, or uncertainties in the nominal models, known as Linear Fractional Representation LFR models; these LFR models were able to describe the aircraft dynamics by taking into account uncertainties over the flight envelope. In this paper, the LFRs models are developed using the speeds and altitudes as varying parameters; The LFR models were built using several flying conditions expressed in terms of speeds and altitudes. The use of such a method has gained a great interest by the aeronautical companies that have seen a promising future in the modeling, and particularly in the design and certification of control laws. In this research paper, we will focus on the Cessna Citation X open loop stability analysis. The data are provided by a Research Aircraft Flight Simulator of Level D, that corresponds to the highest level flight dynamics certification; this simulator was developed by CAE Inc. and its development was based on the requirements of research at the LARCASE laboratory. The acquisition of these data was used to develop a linear model of the airplane in its longitudinal and lateral motions, and was further used to create the LFR’s models for 12 XCG /weights conditions, and thus the whole flight envelope using a friendly Graphical User Interface developed during this study. Then, the LFR’s models are analyzed using Interval Analysis method based upon Lyapunov function, and also the ‘stability and robustness analysis’ toolbox. The results were presented under the form of graphs, thus they have offered good readability, and were easily exploitable. The weakness of this method stays in a relatively long calculation, equal to about four hours for the entire flight envelope.

Keywords: flight control clearance, LFR, stability analysis, robustness analysis

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Authors: James Rigor Camacho, Wansu Lim

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Over the last few years, the development of new wearable and processing technologies has accelerated in order to harness physiological data such as electroencephalograms (EEGs) for EEG-based applications. EEG has been demonstrated to be a source of emotion recognition signals with the highest classification accuracy among physiological signals. However, when emotion recognition systems are used for real-time classification, the training unit is frequently left to run offline or in the cloud rather than working locally on the edge. That strategy has hampered research, and the full potential of using an edge AI device has yet to be realized. Edge AI devices are computers with high performance that can process complex algorithms. It is capable of collecting, processing, and storing data on its own. It can also analyze and apply complicated algorithms like localization, detection, and recognition on a real-time application, making it a powerful embedded device. The NVIDIA Jetson series, specifically the Jetson Nano device, was used in the implementation. The cEEGrid, which is integrated to the open-source brain computer-interface platform (OpenBCI), is used to collect EEG signals. An EEG-based real-time emotion recognition system on Edge AI is proposed in this paper. To perform graphical spectrogram categorization of EEG signals and to predict emotional states based on input data properties, machine learning-based classifiers were used. Until the emotional state was identified, the EEG signals were analyzed using the K-Nearest Neighbor (KNN) technique, which is a supervised learning system. In EEG signal processing, after each EEG signal has been received in real-time and translated from time to frequency domain, the Fast Fourier Transform (FFT) technique is utilized to observe the frequency bands in each EEG signal. To appropriately show the variance of each EEG frequency band, power density, standard deviation, and mean are calculated and employed. The next stage is to identify the features that have been chosen to predict emotion in EEG data using the K-Nearest Neighbors (KNN) technique. Arousal and valence datasets are used to train the parameters defined by the KNN technique.Because classification and recognition of specific classes, as well as emotion prediction, are conducted both online and locally on the edge, the KNN technique increased the performance of the emotion recognition system on the NVIDIA Jetson Nano. Finally, this implementation aims to bridge the research gap on cost-effective and efficient real-time emotion recognition using a resource constrained hardware device, like the NVIDIA Jetson Nano. On the cutting edge of AI, EEG-based emotion identification can be employed in applications that can rapidly expand the research and implementation industry's use.

Keywords: edge AI device, EEG, emotion recognition system, supervised learning algorithm, sensors

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Authors: Ali Abdul Kadhim, Fue Lien

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Solid particle distribution on an impingement surface has been simulated utilizing a graphical processing unit (GPU). In-house computational fluid dynamics (CFD) code has been developed to investigate a 3D turbulent impinging jet using the lattice Boltzmann method (LBM) in conjunction with large eddy simulation (LES) and the multiple relaxation time (MRT) models. This paper proposed an improvement in the LBM-cellular automata (LBM-CA) probabilistic method. In the current model, the fluid flow utilizes the D3Q19 lattice, while the particle model employs the D3Q27 lattice. The particle numbers are defined at the same regular LBM nodes, and transport of particles from one node to its neighboring nodes are determined in accordance with the particle bulk density and velocity by considering all the external forces. The previous models distribute particles at each time step without considering the local velocity and the number of particles at each node. The present model overcomes the deficiencies of the previous LBM-CA models and, therefore, can better capture the dynamic interaction between particles and the surrounding turbulent flow field. Despite the increasing popularity of LBM-MRT-CA model in simulating complex multiphase fluid flows, this approach is still expensive in term of memory size and computational time required to perform 3D simulations. To improve the throughput of each simulation, a single GeForce GTX TITAN X GPU is used in the present work. The CUDA parallel programming platform and the CuRAND library are utilized to form an efficient LBM-CA algorithm. The methodology was first validated against a benchmark test case involving particle deposition on a square cylinder confined in a duct. The flow was unsteady and laminar at Re=200 (Re is the Reynolds number), and simulations were conducted for different Stokes numbers. The present LBM solutions agree well with other results available in the open literature. The GPU code was then used to simulate the particle transport and deposition in a turbulent impinging jet at Re=10,000. The simulations were conducted for L/D=2,4 and 6, where L is the nozzle-to-surface distance and D is the jet diameter. The effect of changing the Stokes number on the particle deposition profile was studied at different L/D ratios. For comparative studies, another in-house serial CPU code was also developed, coupling LBM with the classical Lagrangian particle dispersion model. Agreement between results obtained with LBM-CA and LBM-Lagrangian models and the experimental data is generally good. The present GPU approach achieves a speedup ratio of about 350 against the serial code running on a single CPU.

Keywords: CUDA, GPU parallel programming, LES, lattice Boltzmann method, MRT, multi-phase flow, probabilistic model

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Authors: Kibrom Hadush

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Countries like Ethiopia, whose economy is mainly rain-fed dependent agriculture, are highly vulnerable to climate variability and weather extremes. Sub-seasonal (monthly) and dekadal forecasts are hence critical for crop production and water resource management. Therefore, this paper was conducted to study the predictability and variability of Kiremt rainfall over the northern half of Ethiopia on monthly and dekadal time scales in association with global Sea Surface Temperature (SST) at different lag time. Trends in rainfall have been analyzed on annual, seasonal (Kiremt), monthly, and dekadal (June–September) time scales based on rainfall records of 36 meteorological stations distributed across four homogenous zones of the northern half of Ethiopia for the period 1992–2017. The results from the progressive Mann–Kendall trend test and the Sen’s slope method shows that there is no significant trend in the annual, Kiremt, monthly and dekadal rainfall total at most of the station's studies. Moreover, the rainfall in the study area varies spatially and temporally, and the distribution of the rainfall pattern increases from the northeast rift valley to northwest highlands. Methods of analysis include graphical correlation and multiple linear regression model are employed to investigate the association between the global SSTs and Kiremt rainfall over the homogeneous rainfall zones and to predict monthly and dekadal (June-September) rainfall using SST predictors. The results of this study show that in general, SST in the equatorial Pacific Ocean is the main source of the predictive skill of the Kiremt rainfall variability over the northern half of Ethiopia. The regional SSTs in the Atlantic and the Indian Ocean as well contribute to the Kiremt rainfall variability over the study area. Moreover, the result of the correlation analysis showed that the decline of monthly and dekadal Kiremt rainfall over most of the homogeneous zones of the study area are caused by the corresponding persistent warming of the SST in the eastern and central equatorial Pacific Ocean during the period 1992 - 2017. It is also found that the monthly and dekadal Kiremt rainfall over the northern, northwestern highlands and northeastern lowlands of Ethiopia are positively correlated with the SST in the western equatorial Pacific, eastern and tropical northern the Atlantic Ocean. Furthermore, the SSTs in the western equatorial Pacific and Indian Oceans are positively correlated to the Kiremt season rainfall in the northeastern highlands. Overall, the results showed that the prediction models using combined SSTs at various ocean regions (equatorial and tropical) performed reasonably well in the prediction (With R2 ranging from 30% to 65%) of monthly and dekadal rainfall and recommends it can be used for efficient prediction of Kiremt rainfall over the study area to aid with systematic and informed decision making within the agricultural sector.

Keywords: dekadal, Kiremt rainfall, monthly, Northern Ethiopia, sea surface temperature

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Authors: A. Dudek, P. Tylec, G. Torbicz, P. Duda, K. Proniewska, P. Major, M. Pedziwiatr

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Background: Conservative treatments of obesity, based only on a proper diet and physical activity, without the support of an interdisciplinary team of specialist does not bring satisfactory bariatric results. Long-term maintenance of a proper metabolic results after rapid weight loss due to bariatric surgery requires engagement from patients. Mobile health tool may offer alternative model that enhance participant engagement in keeping the therapy. Objective: We aimed to assess the influence of constant monitoring and subsequent motivational alerts in perioperative period and on post-operative effects in the bariatric patients. As well as the study was designed to identify factors conductive urge to change lifestyle after surgery. Methods: This prospective clinical control study was based on a usage of a designed prototype of bariatric mHealth system. The prepared application comprises central data management with a comprehensible interface dedicated for patients and data transfer module as a physician’s platform. Motivation system of a platform consist of motivational alerts, graphic outcome presentation, and patient communication center. Generated list of patients requiring urgent consultation and possibility of a constant contact with a specialist provide safety zone. 31 patients were enrolled in continuous monitoring program during a 6-month period along with typical follow-up visits. After one year follow-up, all patients were examined. Results: There were 20 active users of the proposed monitoring system during the entire duration of the study. After six months, 24 patients took a part in a control by telephone questionnaires. Among them, 75% confirmed that the application concept was an important element in the treatment. Active users of the application indicated as the most valuable features: motivation to continue treatment (11 users), graphical presentation of weight loss, and other parameters (7 users), the ability to contact a doctor (3 users). The three main drawbacks are technical errors (9 users), tedious questionnaires inside the application (5 users), and time-consuming tasks inside the system (2 users). Conclusions: Constant monitoring and successive motivational alerts to continue treatment is an appropriate tool in the treatment after bariatric surgery, mainly in the early post-operative period. Graphic presentation of data and continuous connection with a clinical staff seemed to be an element of motivation to continue treatment and a sense of security.

Keywords: bariatric surgery, mHealth, mobile health tool, obesity

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Authors: Kamal Ray, Tapati Bhattacharya

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Private use of public office for private gain could be a tentative definition of corruption and most distasteful event of corruption is that it is not there, nor that it is pervasive, but it is socially acknowledged in the global economy, especially in the developing nations. We attempted to assess the interrelationship between the Corruption perception index (CPI) and the principal components of governance indicators as per World Bank like Control of Corruption (CC), rule of law (RL), regulatory quality (RQ) and government effectiveness (GE). Our empirical investigation concentrates upon the degree of reflection of governance indicators upon the CPI in order to single out the most powerful corruption-generating indicator in the selected countries. We have collected time series data on above governance indicators such as CC, RL, RQ and GE of the selected eleven countries from the year of 1996 to 2012 from World Bank data set. The countries are USA, UK, France, Germany, Greece, China, India, Japan, Thailand, Brazil, and South Africa. Corruption Perception Index (CPI) of the countries mentioned above for the period of 1996 to 2012is also collected. Graphical method of simple line diagram against the time series data on CPI is applied for quick view for the relative positions of different trend lines of different nations. The correlation coefficient is enough to assess primarily the degree and direction of association between the variables as we get the numerical data on governance indicators of the selected countries. The tool of Granger Causality Test (1969) is taken into account for investigating causal relationships between the variables, cause and effect to speak of. We do not need to verify stationary test as length of time series is short. Linear regression is taken as a tool for quantification of a change in explained variables due to change in explanatory variable in respect of governance vis a vis corruption. A bilateral positive causal link between CPI and CC is noticed in UK, index-value of CC increases by 1.59 units as CPI increases by one unit and CPI rises by 0.39 units as CC rises by one unit, and hence it has a multiplier effect so far as reduction in corruption is concerned in UK. GE causes strongly to the reduction of corruption in UK. In France, RQ is observed to be a most powerful indicator in reducing corruption whereas it is second most powerful indicator after GE in reducing of corruption in Japan. Governance-indicator like GE plays an important role to push down the corruption in Japan. In China and India, GE is proactive as well as influencing indicator to curb corruption. The inverse relationship between RL and CPI in Thailand indicates that ongoing machineries related to RL is not complementary to the reduction of corruption. The state machineries of CC in S. Africa are highly relevant to reduce the volume of corruption. In Greece, the variations of CPI positively influence the variations of CC and the indicator like GE is effective in controlling corruption as reflected by CPI. All the governance-indicators selected so far have failed to arrest their state level corruptions in USA, Germany and Brazil.

Keywords: corruption perception index, governance indicators, granger causality test, regression

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Authors: Nicoly Coelho, Eduardo Vieira Vilas Boas, Paulo Orestes Formigoni

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Faced with the remarkable developments in the various segments of modern engineering, provided by the increasing technological development, professionals of all educational areas need to overcome the difficulties generated due to the good understanding of those who are starting their academic journey. Aiming to overcome these difficulties, this article aims at an introduction to the basic study of numerical methods applied to fluid mechanics and thermodynamics, demonstrating the modeling and simulations with its substance, and a detailed explanation of the fundamental numerical solution for the use of finite difference method, using SCILAB, a free software easily accessible as it is free and can be used for any research center or university, anywhere, both in developed and developing countries. It is known that the Computational Fluid Dynamics (CFD) is a necessary tool for engineers and professionals who study fluid mechanics, however, the teaching of this area of knowledge in undergraduate programs faced some difficulties due to software costs and the degree of difficulty of mathematical problems involved in this way the matter is treated only in postgraduate courses. This work aims to bring the use of DFC low cost in teaching Transport Phenomena for graduation analyzing a small classic case of fundamental thermodynamics with Scilab® program. The study starts from the basic theory involving the equation the partial differential equation governing heat transfer problem, implies the need for mastery of students, discretization processes that include the basic principles of series expansion Taylor responsible for generating a system capable of convergence check equations using the concepts of Sassenfeld, finally coming to be solved by Gauss-Seidel method. In this work we demonstrated processes involving both simple problems solved manually, as well as the complex problems that required computer implementation, for which we use a small algorithm with less than 200 lines in Scilab® in heat transfer study of a heated plate in rectangular shape on four sides with different temperatures on either side, producing a two-dimensional transport with colored graphic simulation. With the spread of computer technology, numerous programs have emerged requiring great researcher programming skills. Thinking that this ability to program DFC is the main problem to be overcome, both by students and by researchers, we present in this article a hint of use of programs with less complex interface, thus enabling less difficulty in producing graphical modeling and simulation for DFC with an extension of the programming area of experience for undergraduates.

Keywords: numerical methods, finite difference method, heat transfer, Scilab

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Authors: Virginia Vettori, Chiara Lorini, Vieri Lastrucci, Giulia Di Pisa, Alessia De Blasi, Sara Giuggioli, Guglielmo Bonaccorsi

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The design of the Nutrition Literacy Assessment Instrument (NLit) responds to the need to provide a tool to adequately assess the construct of nutrition literacy (NL), which is strictly connected to the quality of the diet and nutritional health status. The NLit was originally developed and validated in the US context, and it was recently validated for Italian people too (NLit-IT), involving a sample of N = 74 adults. The results of the cross-cultural adaptation of the tool confirmed its validity since it was established that the level of NL contributed to predicting the level of adherence to the Mediterranean Diet (convergent validity). Additionally, results obtained proved that Internal Consistency and reliability of the NLit-IT were good (Cronbach’s alpha (ρT) = 0.78; 95% CI, 0.69–0.84; Intraclass Correlation Coefficient (ICC) = 0.68, 95% CI, 0.46–0.85). However, the Subscale 3 of the NLit-IT “Household Food Measurement” showed lower values of ρT and ICC (ρT = 0.27; 95% CI, 0.1–0.55; ICC = 0.19, 95% CI, 0.01–0.63) than the entire instrument. Subscale 3 includes nine items which are constituted by written questions and the corresponding pictures of the meals. In particular, items 2, 3, and 8 of Subscale 3 had the lowest level of correct answers. The purpose of the present study was to identify the factors that influenced the Internal Consistency and reliability of Subscale 3 of NLit-IT using the methodology of a focus group. A panel of seven experts was formed, involving professionals in the field of public health nutrition, dietetics, and health promotion and all of them were trained on the concepts of nutrition literacy and food appearance. A member of the group drove the discussion, which was oriented in the identification of the reasons for the low levels of reliability and Internal Consistency. The members of the group discussed the level of comprehension of the items and how they could be readapted. From the discussion, it emerges that the written questions were clear and easy to understand, but it was observed that the representations of the meal needed to be improved. Firstly, it has been decided to introduce a fork or a spoon as a reference dimension to better understand the dimension of the food portion (items 1, 4 and 8). Additionally, the flat plate of items 3 and 5 should be substituted with a soup plate because, in the Italian national context, it is common to eat pasta or rice on this kind of plate. Secondly, specific measures should be considered for some kind of foods such as the brick of yogurt instead of a cup of yogurt (items 1 and 4). Lastly, it has been decided to redo the photos of the meals basing on professional photographic techniques. In conclusion, we noted that the graphical representation of the items strictly influenced the level of participants’ comprehension of the questions; moreover, the research group agreed that the level of knowledge about nutrition and food portion size is low in the general population.

Keywords: nutritional literacy, cross cultural adaptation, misinformation, food design

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Authors: Takahiro Nishimura, Kouki Doi, Hiroshi Fujimoto

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Touch-sensitive screens that serve as displays and input devices have been adopted in many portable terminals such as smartphones and personal media players, and the market of touch-sensitive screens has expanded greatly. One of the advantages of touch-sensitive screen is the flexibility in the graphical user interface (GUI) design, and it is imperative to design an appropriate GUI to realize an easy-to-use interface. Moreover, it is important to evaluate the relationship between pointing performance and GUI design. There is much knowledge regarding easy-to-use GUI designs for portable terminals with touch-sensitive screens, and most have focused on GUI design approaches for women or children with small hands. In contrast, GUI design approaches for users with large hands have not received sufficient attention. In this study, to obtain knowledge that contributes to the establishment of individualized easy-to-use GUI design guidelines, we conducted experiments to investigate the relationship between thumb length and pointing performance on portable terminals with touch-sensitive screens. In this study, fourteen college students who participated in the experiment were divided into two groups based on the length of their thumbs. Specifically, we categorized the participants into two groups, thumbs longer than 64.2 mm into L (Long) group, and thumbs longer than 57.4 mm but shorter than 64.2 mm into A (Average) group, based on Japanese anthropometric database. They took part in this study under the authorization of Waseda University’s ‘Ethics Review Committee on Research with Human Subjects’. We created an application for the experimental task and implemented it on the projected capacitive touch-sensitive screen portable terminal (iPod touch (4th generation)). The display size was 3.5 inch and 960 × 640 - pixel resolution at 326 ppi (pixels per inch). This terminal was selected as the experimental device, because of its wide use and market share. The operational procedure of the application is as follows. First, the participants placed their thumb on the start position. Then, one cross-shaped target in a 10 × 7 array of 70 positions appeared at random. The participants pointed the target with their thumb as accurately and as fast as possible. Then, they returned their thumb to the start position and waited. The operation ended when this procedure had been repeated until all 70 targets had each been pointed at once by the participants. We adopted the evaluation indices for absolute error, variable error, and pointing time to investigate pointing performance when using the portable terminal. The results showed that pointing performance varied with thumb length. In particular, on the lower right side of the screen, the performance of L group with long thumb was low. Further, we presented an approach for designing easy-to- use button GUI for users with long thumbs. The contributions of this study include revelation of the relationship between pointing performance and user’s thumb length when using a portable terminal in terms of accuracy, precision, and speed of pointing. We hope that these findings contribute to an easy-to-use GUI design for users with large hands.

Keywords: pointing performance, portable terminal, thumb length, touch-sensitive screen

Procedia PDF Downloads 136

Authors: Austin P. Hopkins, R. Daren Harmel, Jim A Ippolito, P. J. A. Kleinman, D. Sahoo

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Field-scale runoff and water quality data are critical to understanding the fate and transport of nutrients applied to agricultural lands and minimizing their off-site transport because it is at that scale that agricultural management decisions are typically made based on hydrologic, soil, and land use factors. However, regional influences such as precipitation, temperature, and prevailing cropping systems and land use patterns also impact nutrient runoff. In the present study, the recently-updated MANAGE (Measured Annual Nutrient loads from Agricultural Environments) database was used to conduct an ecoregion-level analysis of nitrogen and phosphorus runoff from agricultural lands in the North America. Specifically, annual N and P runoff loads for cropland and grasslands in North American Level II EPA ecoregions were presented, and the impact of factors such as land use, tillage, and fertilizer timing and placement on N and P runoff were analyzed. Specifically we compiled annual N and P runoff load data (i.e., dissolved, particulate, and total N and P, kg/ha/yr) for each Level 2 EPA ecoregion and for various agricultural management practices (i.e., land use, tillage, fertilizer timing, fertilizer placement) within each ecoregion to showcase the analyses possible with the data in MANAGE. Potential differences in N and P runoff loads were evaluated between and within ecoregions with statistical and graphical approaches. Non-parametric analyses, mainly Mann-Whitney tests were conducted on median values weighted by the site years of data utilizing R because the data were not normally distributed, and we used Dunn tests and box and whisker plots to visually and statistically evaluate significant differences. Out of the 50 total North American Ecoregions, 11 were found that had significant data and site years to be utilized in the analysis. When examining ecoregions alone, it was observed that ER 9.2 temperate prairies had a significantly higher total N at 11.7 kg/ha/yr than ER 9.4 South Central Semi Arid Prairies with a total N of 2.4. When examining total P it was observed that ER 8.5 Mississippi Alluvial and Southeast USA Coastal Plains had a higher load at 3.0 kg/ha/yr than ER 8.2 Southeastern USA Plains with a load of 0.25 kg/ha/yr. Tillage and Land Use had severe impacts on nutrient loads. In ER 9.2 Temperate Prairies, conventional tillage had a total N load of 36.0 kg/ha/yr while conservation tillage had a total N load of 4.8 kg/ha/yr. In all relevant ecoregions, when corn was the predominant land use, total N levels significantly increased compared to grassland or other grains. In ER 8.4 Ozark-Ouachita, Corn had a total N of 22.1 kg/ha/yr while grazed grassland had a total N of 2.9 kg/ha/yr. There are further intricacies of the interactions that agricultural management practices have on one another combined with ecological conditions and their impacts on the continental aquatic nutrient loads that still need to be explored. This research provides a stepping stone to further understanding of land and resource stewardship and best management practices.

Keywords: water quality, ecoregions, nitrogen, phosphorus, agriculture, best management practices, land use

Procedia PDF Downloads 52

Authors: Mikko Salminen, Niklas Ravaja

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Previous studies have shown that emotional intelligence (EI) has an important role in leadership and social interaction. On the other hand, physiological synchronization between two interacting participants has been related to, for example, intensity of the interaction, and interestingly also to empathy. It is suggested that the amount of covariation in physiological signals between the two interacting persons would also be related to how the discussion is perceived subjectively. To study the interrelations between physiological synchronization, emotional intelligence, and subjective perception of the interaction, performance review discussions between real manager – subordinate dyads were studied using psychophysiological measurements and self-reports. The participants consisted of 40 managers, of which 24 were female, and 78 of their subordinates, of which 45 were female. The participants worked in various fields, for example banking, education, and engineering. The managers had a normal performance review discussion with two subordinates, except two managers who, due to scheduling issues, had discussion with only one subordinate. The managers were on average 44.5 years old, and the subordinates on average 45.5 years old. Written consent, in accordance with the Declaration of Helsinki, was obtained from all the participants. After the discussion, the participants filled a questionnaire assessing their emotions during the discussion. This included a self-assessment manikin (SAM) scale for the emotional valence during the discussion, with a 9-point graphical scale representing a manikin whose facial expressions ranged from smiling and happy to frowning and unhappy. In addition, the managers filled EI360, a 37-item self-report trait emotional intelligence questionnaire. The psychophysiological activity of the participants was recorded using two Varioport-B portable recording devices. Cardiac activity (ECG, electrocardiogram) was measured with two electrodes placed on the torso. Inter-beat interval (IBI, time between two successive heart beats) was calculated from the ECG signals. The facial muscle activation (EMG, electromyography) was recorded on three sites of the left side of the face: zygomaticus major (cheek muscle), orbicularis oculi (periocular muscle), and corrugator supercilii (frowning muscle). The facial-EMG signals were rectified and smoothed, and cross-coherences were calculated between members of each dyad, for all the three EMG signals, for the baseline and discussion periods. The values were natural-log transformed to normalize the distributions. Higher cross-coherence during the discussion between the manager’s and the subordinate’s zygomatic muscles was related to more positive valence self-reported emotions, F(1; 66,137) = 7,051; p=0,01. Thus, synchronized cheek muscle activation, either due to synchronous smiling or talking, was related to more positive perception of the discussion. In addition, higher IBI synchronization between the manager and the subordinate during the discussion was related to the manager’s higher self-reported emotional intelligence, F(1; 27,981)=4,58; p=0,041. That is, the EI was related to synchronous cardiac activity and possibly to similar physiological arousal levels. The results imply that the psychophysiological synchronization could be a potentially useful index in the study of social interaction and a valuable tool in the coaching of leadership skills in organizational contexts.

Keywords: emotional intelligence, leadership, psychophysiology, social interaction, synchronization

Procedia PDF Downloads 296

Authors: Mercedes Bertotto, Marcelo Bello, Hector Goicoechea, Veronica Fusca

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The National Service of Agri-Food Health and Quality (SENASA), controls honey to detect contamination by synthetic or natural chemical substances and establishes and controls the traceability of the product. The utility of near-infrared spectroscopy for the detection of adulteration of honey with high fructose corn syrup (HFCS) was investigated. First of all, a mixture of different authentic artisanal Argentinian honey was prepared to cover as much heterogeneity as possible. Then, mixtures were prepared by adding different concentrations of high fructose corn syrup (HFCS) to samples of the honey pool. 237 samples were used, 108 of them were authentic honey and 129 samples corresponded to honey adulterated with HFCS between 1 and 10%. They were stored unrefrigerated from time of production until scanning and were not filtered after receipt in the laboratory. Immediately prior to spectral collection, honey was incubated at 40°C overnight to dissolve any crystalline material, manually stirred to achieve homogeneity and adjusted to a standard solids content (70° Brix) with distilled water. Adulterant solutions were also adjusted to 70° Brix. Samples were measured by NIR spectroscopy in the range of 650 to 7000 cm⁻¹. The technique of specular reflectance was used, with a lens aperture range of 150 mm. Pretreatment of the spectra was performed by Standard Normal Variate (SNV). The ant colony optimization genetic algorithm sample selection (ACOGASS) graphical interface was used, using MATLAB version 5.3, to select the variables with the greatest discriminating power. The data set was divided into a validation set and a calibration set, using the Kennard-Stone (KS) algorithm. A combined method of Potential Functions (PF) was chosen together with Partial Least Square Linear Discriminant Analysis (PLS-DA). Different estimators of the predictive capacity of the model were compared, which were obtained using a decreasing number of groups, which implies more demanding validation conditions. The optimal number of latent variables was selected as the number associated with the minimum error and the smallest number of unassigned samples. Once the optimal number of latent variables was defined, we proceeded to apply the model to the training samples. With the calibrated model for the training samples, we proceeded to study the validation samples. The calibrated model that combines the potential function methods and PLSDA can be considered reliable and stable since its performance in future samples is expected to be comparable to that achieved for the training samples. By use of Potential Functions (PF) and Partial Least Square Linear Discriminant Analysis (PLS-DA) classification, authentic honey and honey adulterated with HFCS could be identified with a correct classification rate of 97.9%. The results showed that NIR in combination with the PT and PLS-DS methods can be a simple, fast and low-cost technique for the detection of HFCS in honey with high sensitivity and power of discrimination.

Keywords: adulteration, multivariate analysis, potential functions, regression

Procedia PDF Downloads 97

Authors: Rajinder Kumar Gupta, Rajni Kant Agrawal, Jaganniwas

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One of the most frightening phenomena of nature is the occurrence of earthquake as it has terrible and disastrous effects. Many earthquakes occur every day worldwide. There is need to have knowledge regarding the trends in earthquake occurrence worldwide. The recoding and interpretation of data obtained from the establishment of the worldwide system of seismological stations made this possible. From the analysis of recorded earthquake data, the earthquake parameters and source parameters can be computed and the earthquake catalogues can be prepared. These catalogues provide information on origin, time, epicenter locations (in term of latitude and longitudes) focal depths, magnitude and other related details of the recorded earthquakes. Theses catalogues are used for seismic hazard estimation. Manual interpretation and analysis of these data is tedious and time consuming. A geographical information system is a computer based system designed to store, analyzes and display geographic information. The implementation of integrated GIS technology provides an approach which permits rapid evaluation of complex inventor database under a variety of earthquake scenario and allows the user to interactively view results almost immediately. GIS technology provides a powerful tool for displaying outputs and permit to users to see graphical distribution of impacts of different earthquake scenarios and assumptions. An endeavor has been made in present study to compile the earthquake data for the whole world in visual Basic on ARC GIS Plate form so that it can be used easily for further analysis to be carried out by earthquake engineers. The basic data on time of occurrence, location and size of earthquake has been compiled for further querying based on various parameters. A preliminary analysis tool is also provided in the user interface to interpret the earthquake recurrence in region. The user interface also includes the seismic hazard information already worked out under GHSAP program. The seismic hazard in terms of probability of exceedance in definite return periods is provided for the world. The seismic zones of the Indian region are included in the user interface from IS 1893-2002 code on earthquake resistant design of buildings. The City wise satellite images has been inserted in Map and based on actual data the following information could be extracted in real time: • Analysis of soil parameters and its effect • Microzonation information • Seismic hazard and strong ground motion • Soil liquefaction and its effect in surrounding area • Impacts of liquefaction on buildings and infrastructure • Occurrence of earthquake in future and effect on existing soil • Propagation of earth vibration due of occurrence of Earthquake GIS based earthquake information system has been prepared for whole world in Visual Basic on ARC GIS Plate form and further extended micro level based on actual soil parameters. Individual tools has been developed for liquefaction, earthquake frequency etc. All information could be used for development of infrastructure i.e. multi story structure, Irrigation Dam & Its components, Hydro-power etc in real time for present and future.

Keywords: GIS based earthquake information system, microzonation, analysis and real time information about liquefaction, infrastructure development

Procedia PDF Downloads 289

Authors: Mona Isazad Mashinchi, Davood Roshan Sangachin, Francis J. Sullivan, Dietrich Rebholz-Schuhmann

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Background: Decision-making processes are nowadays driven by data, data analytics and Business Intelligence (BI). BI as a software platform can provide a wide variety of capabilities such as organization memory, information integration, insight creation and presentation capabilities. Visualizing data through dashboards is one of the BI solutions (for a variety of areas) which helps managers in the decision making processes to expose the most informative information at a glance. In the healthcare domain to date, dashboard presentations are more frequently used to track performance related metrics and less frequently used to monitor those quality parameters which relate directly to patient outcomes. Providing effective and timely care for patients and improving the health outcome are highly dependent on presenting and visualizing data and information. Objective: In this research, the focus is on the presentation capabilities of BI to design a dashboard for prostate cancer (PC) data that allows better decision making for the patients, the hospital and the healthcare system related to a cancer dataset. The aim of this research is to customize a retrospective PC dataset in a dashboard interface to give a better understanding of data in the categories (risk factors, treatment approaches, disease control and side effects) which matter most to patients as well as other stakeholders. By presenting the outcome in the dashboard we address one of the major targets of a value-based health care (VBHC) delivery model which is measuring the value and presenting the outcome to different actors in HC industry (such as patients and doctors) for a better decision making. Method: For visualizing the stored data to users, three interactive dashboards based on the PC dataset have been developed (using the Tableau Software) to provide better views to the risk factors, treatment approaches, and side effects. Results: Many benefits derived from interactive graphs and tables in dashboards which helped to easily visualize and see the patients at risk, better understanding the relationship between patient's status after treatment and their initial status before treatment, or to choose better decision about treatments with fewer side effects regarding patient status and etc. Conclusions: Building a well-designed and informative dashboard is related to three important factors including; the users, goals and the data types. Dashboard's hierarchies, drilling, and graphical features can guide doctors to better navigate through information. The features of the interactive PC dashboard not only let doctors ask specific questions and filter the results based on the key performance indicators (KPI) such as: Gleason Grade, Patient's Age and Status, but may also help patients to better understand different treatment outcomes, such as side effects during the time, and have an active role in their treatment decisions. Currently, we are extending the results to the real-time interactive dashboard that users (either patients and doctors) can easily explore the data by choosing preferred attribute and data to make better near real-time decisions.

Keywords: business intelligence, dashboard, decision making, healthcare, prostate cancer, value-based healthcare

Procedia PDF Downloads 119

Authors: Caspar Goeke, Holger Finger, Dorena Diekamp, Peter König

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Online-based research has recently gained increasing attention from various fields of research in the cognitive sciences. Technological advances in the form of online crowdsourcing (Amazon Mechanical Turk), open data repositories (Open Science Framework), and online analysis (Ipython notebook) offer rich possibilities to improve, validate, and speed up research. However, until today there is no cross-platform integration of these subsystems. Furthermore, implementation of online studies still suffers from the complex implementation (server infrastructure, database programming, security considerations etc.). Here we propose and test a new JavaScript framework that enables researchers to conduct any kind of behavioral research in the browser without the need to program a single line of code. In particular our framework offers the possibility to manipulate and combine the experimental stimuli via a graphical editor, directly in the browser. Moreover, we included an action-event system that can be used to handle user interactions, interactively change stimuli properties or store participants’ responses. Besides traditional recordings such as reaction time, mouse and keyboard presses, the tool offers webcam based eye and face-tracking. On top of these features our framework also takes care about the participant recruitment, via crowdsourcing platforms such as Amazon Mechanical Turk. Furthermore, the build in functionality of google translate will ensure automatic text translations of the experimental content. Thereby, thousands of participants from different cultures and nationalities can be recruited literally within hours. Finally, the recorded data can be visualized and cleaned online, and then exported into the desired formats (csv, xls, sav, mat) for statistical analysis. Alternatively, the data can also be analyzed online within our framework using the integrated Ipython notebook. The framework was designed such that studies can be used interchangeably between researchers. This will support not only the idea of open data repositories but also constitutes the possibility to share and reuse the experimental designs and analyses such that the validity of the paradigms will be improved. Particularly, sharing and integrating the experimental designs and analysis will lead to an increased consistency of experimental paradigms. To demonstrate the functionality of the framework we present the results of a pilot study in the field of spatial navigation that was conducted using the framework. Specifically, we recruited over 2000 subjects with various cultural backgrounds and consequently analyzed performance difference in dependence on the factors culture, gender and age. Overall, our results demonstrate a strong influence of cultural factors in spatial cognition. Such an influence has not yet been reported before and would not have been possible to show without the massive amount of data collected via our framework. In fact, these findings shed new lights on cultural differences in spatial navigation. As a consequence we conclude that our new framework constitutes a wide range of advantages for online research and a methodological innovation, by which new insights can be revealed on the basis of massive data collection.

Keywords: cultural differences, crowdsourcing, JavaScript framework, methodological innovation, online data collection, online study, spatial cognition

Procedia PDF Downloads 226

Authors: Manana Lobzhanidze

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The COVID-19 pandemic has made significant changes in migration processes, notably changes in the study migration process. The constraints caused by the COVID-19 pandemic led to changes in the studying process, which negatively affected its efficiency. The educational process has partially or completely shifted to distance learning; Both labor and study migration have increased significantly in the world. The employment and education market has become global and consequently, a number of challenges have arisen for employers, researchers, and businesses. The role of preparing qualified personnel in achieving high productivity is justified, the benefits for employers and employees are assessed on the one hand, and the role of study migration for the country’s development is examined on the other hand. Research methods. The research is based on methods of analysis and synthesis, quantitative and qualitative, groupings, relative and mean quantities, graphical representation, comparison, analysis and etc. In-depth interviews were conducted with experts to determine quantitative and qualitative indicators. Research findings. Factors affecting study migration are analysed in the paper and the environment that stimulates migration is explored. One of the driving forces of migration is considered to be the desire for receiving higher pay. Levels and indicators of study migration are studied by country. Comparative analysis has found that study migration rates are high in countries where the price of skilled labor is high. The productivity of individuals with low skills is low, which negatively affects the economic development of countries. It has been revealed that students leave the country to improve their skills during study migration. The process mentioned in the article is evaluated as a positive event for a developing country, as individuals are given the opportunity to share the technology of developed countries, gain knowledge, and then introduce it in their own country. The downside of study migration is the return of a small proportion of graduates from developed economies to their home countries. The article concludes that countries with emerging economies devote less resources to research and development, while this is a priority in developed countries, allowing highly skilled individuals to use their skills efficiently. The paper studies the national education system examines the level of competition in the education market and the indicators of educational migration. The level of competition in the education market and the indicators of educational migration are studied. The role of qualified personnel in achieving high productivity is substantiated, the benefits of employers and employees are assessed on the one hand, and the role of study migration in the development of the country is revealed on the other hand. The paper also analyzes the level of competition in the education and labor markets and identifies indicators of study migration. During the pandemic period, there was a great demand for the digital technologies. Open access to a variety of comprehensive platforms will significantly reduce study migration to other countries. As a forecast, it can be said that the intensity of the use of e-learning platforms will be increased significantly in the post-pandemic period. The paper analyzes the positive and negative effects of study migration on economic development, examines the challenges of study migration in light of the COVID-19 pandemic, suggests ways to avoid negative consequences, and develops recommendations for improving the study migration process in the post-pandemic period.

Keywords: study migration, COVID-19 pandemic, factors affecting migration, economic development, post-pandemic migration

Procedia PDF Downloads 102

Authors: D. Madhushanka, Y. Liu, H. C. Fernando

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Fires are one of the foremost factors of land surface disturbance in diverse ecosystems, causing soil erosion and land-cover changes and atmospheric effects affecting people's lives and properties. Generally, the severity of the fire is calculated as the Normalized Burn Ratio (NBR) index. This is performed manually by comparing two images obtained afterward. Then by using the bitemporal difference of the preprocessed satellite images, the dNBR is calculated. The burnt area is then classified as either unburnt (dNBR<0.1) or burnt (dNBR>= 0.1). Furthermore, Wildfire Severity Assessment (WSA) classifies burnt areas and unburnt areas using classification levels proposed by USGS and comprises seven classes. This procedure generates a burn severity report for the area chosen by the user manually. This study is carried out with the objective of producing an automated tool for the above-mentioned process, namely the World Wildfire Severity Assessment Tool (WWSAT). It is implemented in Google Earth Engine (GEE), which is a free cloud-computing platform for satellite data processing, with several data catalogs at different resolutions (notably Landsat, Sentinel-2, and MODIS) and planetary-scale analysis capabilities. Sentinel-2 MSI is chosen to obtain regular processes related to burnt area severity mapping using a medium spatial resolution sensor (15m). This tool uses machine learning classification techniques to identify burnt areas using NBR and to classify their severity over the user-selected extent and period automatically. Cloud coverage is one of the biggest concerns when fire severity mapping is performed. In WWSAT based on GEE, we present a fully automatic workflow to aggregate cloud-free Sentinel-2 images for both pre-fire and post-fire image compositing. The parallel processing capabilities and preloaded geospatial datasets of GEE facilitated the production of this tool. This tool consists of a Graphical User Interface (GUI) to make it user-friendly. The advantage of this tool is the ability to obtain burn area severity over a large extent and more extended temporal periods. Two case studies were carried out to demonstrate the performance of this tool. The Blue Mountain national park forest affected by the Australian fire season between 2019 and 2020 is used to describe the workflow of the WWSAT. This site detected more than 7809 km2, using Sentinel-2 data, giving an error below 6.5% when compared with the area detected on the field. Furthermore, 86.77% of the detected area was recognized as fully burnt out, of which high severity (17.29%), moderate-high severity (19.63%), moderate-low severity (22.35%), and low severity (27.51%). The Arapaho and Roosevelt National Forest Park, California, the USA, which is affected by the Cameron peak fire in 2020, is chosen for the second case study. It was found that around 983 km2 had burned out, of which high severity (2.73%), moderate-high severity (1.57%), moderate-low severity (1.18%), and low severity (5.45%). These spots also can be detected through the visual inspection made possible by cloud-free images generated by WWSAT. This tool is cost-effective in calculating the burnt area since satellite images are free and the cost of field surveys is avoided.

Keywords: burnt area, burnt severity, fires, google earth engine (GEE), sentinel-2

Procedia PDF Downloads 197

Authors: Salvatore Brischetto, Domenico Cesare

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Major improvements in future aircraft and spacecraft could be those dependent on an increasing use of conventional and unconventional multilayered structures embedding composite materials, functionally graded materials, piezoelectric or piezomagnetic materials, and soft foam or honeycomb cores. Layers made of such materials can be combined in different ways to obtain structures that are able to fulfill several structural requirements. The next generation of aircraft and spacecraft will be manufactured as multilayered structures under the action of a combination of two or more physical fields. In multifield problems for multilayered structures, several physical fields (thermal, hygroscopic, electric and magnetic ones) interact each other with different levels of influence and importance. An exact 3D shell model is here proposed for these types of analyses. This model is based on a coupled system including 3D equilibrium equations, 3D Fourier heat conduction equation, 3D Fick diffusion equation and electric and magnetic divergence equations. The set of partial differential equations of second order in z is written using a mixed curvilinear orthogonal reference system valid for spherical and cylindrical shell panels, cylinders and plates. The order of partial differential equations is reduced to the first one thanks to the redoubling of the number of variables. The solution in the thickness z direction is obtained by means of the exponential matrix method and the correct imposition of interlaminar continuity conditions in terms of displacements, transverse stresses, electric and magnetic potentials, temperature, moisture content and transverse normal multifield fluxes. The investigated structures have simply supported sides in order to obtain a closed form solution in the in-plane directions. Moreover, a layerwise approach is proposed which allows a 3D correct description of multilayered anisotropic structures subjected to field loads. Several results will be proposed in tabular and graphical formto evaluate displacements, stresses and strains when mechanical loads, temperature gradients, moisture content gradients, electric potentials and magnetic potentials are applied at the external surfaces of the structures in steady-state conditions. In the case of inclusions of piezoelectric and piezomagnetic layers in the multilayered structures, so called smart structures are obtained. In this case, a free vibration analysis in open and closed circuit configurations and a static analysis for sensor and actuator applications will be proposed. The proposed results will be useful to better understand the physical and structural behaviour of multilayered advanced composite structures in the case of multifield interactions. Moreover, these analytical results could be used as reference solutions for those scientists interested in the development of 3D and 2D numerical shell/plate models based, for example, on the finite element approach or on the differential quadrature methodology. The correct impositions of boundary geometrical and load conditions, interlaminar continuity conditions and the zigzag behaviour description due to transverse anisotropy will be also discussed and verified.

Keywords: composite structures, 3D shell model, stress analysis, multifield loads, exponential matrix method, layer wise approach

Procedia PDF Downloads 33

Authors: M. Mueller, M. Kuehn, M. Voelker

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In small and medium-sized enterprises (SMEs), the challenge is to create a well-grounded and reliable basis for process analysis, optimization and planning due to a lack of data. SMEs have limited access to methods with which they can effectively and efficiently analyse processes and identify cause-and-effect relationships in order to generate the necessary database and derive optimization potential from it. The implementation of digitalization within the framework of Industry 4.0 thus becomes a particular necessity for SMEs. For these reasons, the abstract presents an analysis methodology that is subject to the objective of developing an SME-appropriate methodology for efficient, temporarily feasible data collection and evaluation in flexible production and logistics systems as a basis for process analysis and optimization. The overall methodology focuses on retrospective, event-based tracing and analysis of material flow objects. The technological basis consists of Bluetooth low energy (BLE)-based transmitters, so-called beacons, and smart mobile devices (SMD), e.g. smartphones as receivers, between which distance data can be measured and derived motion profiles. The distance is determined using the Received Signal Strength Indicator (RSSI), which is a measure of signal field strength between transmitter and receiver. The focus is the development of a software-based methodology for interpretation of relative movements of transmitters and receivers based on distance data. The main research is on selection and implementation of pattern recognition methods for automatic process recognition as well as methods for the visualization of relative distance data. Due to an existing categorization of the database regarding process types, classification methods (e.g. Support Vector Machine) from the field of supervised learning are used. The necessary data quality requires selection of suitable methods as well as filters for smoothing occurring signal variations of the RSSI, the integration of methods for determination of correction factors depending on possible signal interference sources (columns, pallets) as well as the configuration of the used technology. The parameter settings on which respective algorithms are based have a further significant influence on result quality of the classification methods, correction models and methods for visualizing the position profiles used. The accuracy of classification algorithms can be improved up to 30% by selected parameter variation; this has already been proven in studies. Similar potentials can be observed with parameter variation of methods and filters for signal smoothing. Thus, there is increased interest in obtaining detailed results on the influence of parameter and factor combinations on data quality in this area. The overall methodology is realized with a modular software architecture consisting of independently modules for data acquisition, data preparation and data storage. The demonstrator for initialization and data acquisition is available as mobile Java-based application. The data preparation, including methods for signal smoothing, are Python-based with the possibility to vary parameter settings and to store them in the database (SQLite). The evaluation is divided into two separate software modules with database connection: the achievement of an automated assignment of defined process classes to distance data using selected classification algorithms and the visualization as well as reporting in terms of a graphical user interface (GUI).

Keywords: event-based tracing, machine learning, process classification, parameter settings, RSSI, signal smoothing

Procedia PDF Downloads 98

Authors: Hugo Daneluzzo, Christelle Rabbat, Alan Jean-Marie

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Water electrolysis is one of the most advanced technologies for producing hydrogen and can be easily combined with electricity from different sources. Under the influence of electric current, water molecules can be split into oxygen and hydrogen. The production of hydrogen by water electrolysis favors the integration of renewable energy sources into the energy mix by compensating for their intermittence through the storage of the energy produced when production exceeds demand and its release during off-peak production periods. Among the various electrolysis technologies, anion exchange membrane (AEM) electrolyser cells are emerging as a reliable technology for water electrolysis. Modeling and simulation are effective tools to save time, money, and effort during the optimization of operating conditions and the investigation of the design. The modeling and simulation become even more important when dealing with multiphysics dynamic systems. One of those systems is the AEM electrolysis cell involving complex physico-chemical reactions. Once developed, models may be utilized to comprehend the mechanisms to control and detect flaws in the systems. Several modeling methods have been initiated by scientists. These methods can be separated into two main approaches, namely equation-based modeling and graph-based modeling. The former approach is less user-friendly and difficult to update as it is based on ordinary or partial differential equations to represent the systems. However, the latter approach is more user-friendly and allows a clear representation of physical phenomena. In this case, the system is depicted by connecting subsystems, so-called blocks, through ports based on their physical interactions, hence being suitable for multiphysics systems. Among the graphical modelling methods, the bond graph is receiving increasing attention as being domain-independent and relying on the energy exchange between the components of the system. At present, few studies have investigated the modelling of AEM systems. A mathematical model and a bond graph model were used in previous studies to model the electrolysis cell performance. In this study, experimental data from literature were simulated using OpenModelica using bond graphs and mathematical approaches. The polarization curves at different operating conditions obtained by both approaches were compared with experimental ones. It was stated that both models predicted satisfactorily the polarization curves with error margins lower than 2% for equation-based models and lower than 5% for the bond graph model. The activation polarization of hydrogen evolution reactions (HER) and oxygen evolution reactions (OER) were behind the voltage loss in the AEM electrolyzer, whereas ion conduction through the membrane resulted in the ohmic loss. Therefore, highly active electro-catalysts are required for both HER and OER while high-conductivity AEMs are needed for effectively lowering the ohmic losses. The bond graph simulation of the polarisation curve for operating conditions at various temperatures has illustrated that voltage increases with temperature owing to the technology of the membrane. Simulation of the polarisation curve can be tested virtually, hence resulting in reduced cost and time involved due to experimental testing and improved design optimization. Further improvements can be made by implementing the bond graph model in a real power-to-gas-to-power scenario.

Keywords: hydrogen production, anion-exchange membrane, electrolyzer, mathematical modeling, multiphysics modeling

Procedia PDF Downloads 52

Authors: Teodora Vukovic, Christoph Hottiger, Noah Bubenhofer

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The development of VIAN-DH aims at bridging two linguistic approaches: conversation analysis/interactional linguistics (IL), so far a dominantly qualitative field, and computational/corpus linguistics and its quantitative and automated methods. Contemporary IL investigates the systematic organization of conversations and interactions composed of speech, gaze, gestures, and body positioning, among others. These highly integrated multimodal behaviour is analysed based on video data aimed at uncovering so called “multimodal gestalts”, patterns of linguistic and embodied conduct that reoccur in specific sequential positions employed for specific purposes. Multimodal analyses (and other disciplines using videos) are so far dependent on time and resource intensive processes of manual transcription of each component from video materials. Automating these tasks requires advanced programming skills, which is often not in the scope of IL. Moreover, the use of different tools makes the integration and analysis of different formats challenging. Consequently, IL research often deals with relatively small samples of annotated data which are suitable for qualitative analysis but not enough for making generalized empirical claims derived quantitatively. VIAN-DH aims to create a workspace where many annotation layers required for the multimodal analysis of videos can be created, processed, and correlated in one platform. VIAN-DH will provide a graphical interface that operates state-of-the-art tools for automating parts of the data processing. The integration of tools that already exist in computational linguistics and computer vision, facilitates data processing for researchers lacking programming skills, speeds up the overall research process, and enables the processing of large amounts of data. The main features to be introduced are automatic speech recognition for the transcription of language, automatic image recognition for extraction of gestures and other visual cues, as well as grammatical annotation for adding morphological and syntactic information to the verbal content. In the ongoing instance of VIAN-DH, we focus on gesture extraction (pointing gestures, in particular), making use of existing models created for sign language and adapting them for this specific purpose. In order to view and search the data, VIAN-DH will provide a unified format and enable the import of the main existing formats of annotated video data and the export to other formats used in the field, while integrating different data source formats in a way that they can be combined in research. VIAN-DH will adapt querying methods from corpus linguistics to enable parallel search of many annotation levels, combining token-level and chronological search for various types of data. VIAN-DH strives to bring crucial and potentially revolutionary innovation to the field of IL, (that can also extend to other fields using video materials). It will allow the processing of large amounts of data automatically and, the implementation of quantitative analyses, combining it with the qualitative approach. It will facilitate the investigation of correlations between linguistic patterns (lexical or grammatical) with conversational aspects (turn-taking or gestures). Users will be able to automatically transcribe and annotate visual, spoken and grammatical information from videos, and to correlate those different levels and perform queries and analyses.

Keywords: multimodal analysis, corpus linguistics, computational linguistics, image recognition, speech recognition

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Authors: Meena Agrawal, Chaitanya P. Agrawal

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The power systems are transforming and becoming smarter with innovations in technologies to enable embark simultaneously upon the sustainable energy needs, rising environmental concerns, economic benefits and quality requirements. The advantages provided by inter-connection of renewable energy resources are becoming more viable and dependable with the smart controlling technologies. The limitation of most renewable resources have their diversity and intermittency causing problems in power quality, grid stability, reliability, security etc. is being cured by these efforts. A necessitate of optimal energy management by intelligent Micro-Grids at the distribution end of the power system has been accredited to accommodate sustainable renewable Distributed Energy Resources on large scale across the power grid. All over the world Smart Grids are emerging now as foremost concern infrastructure upgrade programs. The hardware setup includes NI cRIO 9022, Compact Reconfigurable Input Output microcontroller board connected to the PC on a LAN router with three hardware modules. The Real-Time Embedded Controller is reconfigurable controller device consisting of an embedded real-time processor controller for communication and processing, a reconfigurable chassis housing the user-programmable FPGA, Eight hot-swappable I/O modules, and graphical LabVIEW system design software. It has been employed for signal analysis, controls and acquisition and logging of the renewable sources with the LabVIEW Real-Time applications. The employed cRIO chassis controls the timing for the module and handles communication with the PC over the USB, Ethernet, or 802.11 Wi-Fi buses. It combines modular I/O, real-time processing, and NI LabVIEW programmable. In the presented setup, the Analog Input Module NI 9205 five channels have been used for input analog voltage signals from renewable energy sources and NI 9227 four channels have been used for input analog current signals of the renewable sources. For switching actions based on the programming logic developed in software, a module having Electromechanical Relays (single-pole single throw) with 4-Channels, electrically isolated and LED indicating the state of that channel have been used for isolating the renewable Sources on fault occurrence, which is decided by the logic in the program. The module for Ethernet based Data Acquisition Interface ENET 9163 Ethernet Carrier, which is connected on the LAN Router for data acquisition from a remote source over Ethernet also has the module NI 9229 installed. The LabVIEW platform has been employed for efficient data acquisition, monitoring and control. Control logic utilized in program for operation of the hardware switching Related to Fault Relays has been portrayed as a flowchart. A communication system has been successfully developed amongst the sources and loads connected on different computers using Hypertext transfer protocol, HTTP or Ethernet Local Stacked area Network TCP/IP protocol. There are two main I/O interfacing clients controlling the operation of the switching control of the renewable energy sources over internet or intranet. The paper presents experimental results of the briefed setup for intelligent control of the micro-grid for renewable energy sources, besides the control of Micro-Grid with data acquisition and control hardware based on a microcontroller with visual program developed in LabVIEW.

Keywords: data acquisition and control, LabVIEW, microcontroller cRIO, Smart Micro-Grid

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Authors: Hamda Ajmal, Karen Young, Ruth Melia, John Bogue, Mary O'Sullivan, Jim Duggan, Hannah Wood

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The Covid-19 pandemic led to a range of public health mitigation strategies in order to suppress the SARS-CoV-2 virus. The drastic changes in everyday life due to lockdowns had the potential for a significant negative impact on public mental health, and a key public health goal is to now assess the evidence from available Irish datasets to provide useful insights on this issue. Text-50808 is an online text-based mental health support service, established in Ireland in 2020, and can provide a measure of revealed distress and mental health concerns across the population. The aim of this study is to explore statistical associations between public mental health in Ireland and the Covid-19 pandemic. Uniquely, this study combines two measures of emotional wellbeing in Ireland: (1) weekly text volume at Text-50808, and (2) emotional wellbeing indicators reported by respondents of the Amárach public opinion survey, carried out on behalf of the Department of Health, Ireland. For this analysis, a multivariate graphical exploratory data analysis (EDA) was performed on the Text-50808 dataset dated from 15th June 2020 to 30th June 2021. This was followed by time-series analysis of key mental health indicators including: (1) the percentage of daily/weekly texts at Text-50808 that mention Covid-19 related issues; (2) the weekly percentage of people experiencing anxiety, boredom, enjoyment, happiness, worry, fear and stress in Amárach survey; and Covid-19 related factors: (3) daily new Covid-19 case numbers; (4) daily stringency index capturing the effect of government non-pharmaceutical interventions (NPIs) in Ireland. The cross-correlation function was applied to measure the relationship between the different time series. EDA of the Text-50808 dataset reveals significant peaks in the volume of texts on days prior to level 3 lockdown and level 5 lockdown in October 2020, and full level 5 lockdown in December 2020. A significantly high positive correlation was observed between the percentage of texts at Text-50808 that reported Covid-19 related issues and the percentage of respondents experiencing anxiety, worry and boredom (at a lag of 1 week) in Amárach survey data. There is a significant negative correlation between percentage of texts with Covid-19 related issues and percentage of respondents experiencing happiness in Amárach survey. Daily percentage of texts at Text-50808 that reported Covid-19 related issues to have a weak positive correlation with daily new Covid-19 cases in Ireland at a lag of 10 days and with daily stringency index of NPIs in Ireland at a lag of 2 days. The sudden peaks in text volume at Text-50808 immediately prior to new restrictions in Ireland indicate an association between a rise in mental health concerns following the announcement of new restrictions. There is also a high correlation between emotional wellbeing variables in the Amárach dataset and the number of weekly texts at Text-50808, and this confirms that Text-50808 reflects overall public sentiment. This analysis confirms the benefits of the texting service as a community surveillance tool for mental health in the population. This initial EDA will be extended to use multivariate modeling to predict the effect of additional Covid-19 related factors on public mental health in Ireland.

Keywords: COVID-19 pandemic, data analysis, digital health, mental health, public health, digital health

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Authors: David A. Olasehinde, Peter I. Olasehinde, Segun M. A. Adelana, Dapo O. Olasehinde

Abstract:

An investigation was carried out on underground water system dynamics within Ilorin metropolis to monitor the subsurface flow and its corresponding pollution. Africa population growth rate is the highest among the regions of the world, especially in urban areas. A corresponding increase in waste generation and a change in waste composition from predominantly organic to non-organic waste has also been observed. Percolation of leachate from non-engineered landfills, the chief means of waste disposal in many of its cities, constitutes a threat to the underground water bodies. Ilorin city, a transboundary town in southwestern Nigeria, is a ready microcosm of Africa’s unique challenge. In spite of the fact that groundwater is naturally protected from common contaminants such as bacteria as the subsurface provides natural attenuation process, groundwater samples have been noted to however possesses relatively higher dissolved chemical contaminants such as bicarbonate, sodium, and chloride which poses a great threat to environmental receptors and human consumption. The Geographic Information System (GIS) was used as a tool to illustrate, subsurface dynamics and the corresponding pollutant indicators. Forty-four sampling points were selected around known groundwater pollutant, major old dumpsites without landfill liners. The results of the groundwater flow directions and the corresponding contaminant transport were presented using expert geospatial software. The experimental results were subjected to four descriptive statistical analyses, namely: principal component analysis, Pearson correlation analysis, scree plot analysis, and Ward cluster analysis. Regression model was also developed aimed at finding functional relationships that can adequately relate or describe the behaviour of water qualities and the hypothetical factors landfill characteristics that may influence them namely; distance of source of water body from dumpsites, static water level of groundwater, subsurface permeability (inferred from hydraulic gradient), and soil infiltration. The regression equations developed were validated using the graphical approach. Underground water seems to flow from the northern portion of Ilorin metropolis down southwards transporting contaminants. Pollution pattern in the study area generally assumed a bimodal pattern with the major concentration of the chemical pollutants in the underground watershed and the recharge. The correlation between contaminant concentrations and the spread of pollution indicates that areas of lower subsurface permeability display a higher concentration of dissolved chemical content. The principal component analysis showed that conductivity, suspended solids, calcium hardness, total dissolved solids, total coliforms, and coliforms were the chief contaminant indicators in the underground water system in the study area. Pearson correlation revealed a high correlation of electrical conductivity for many parameters analyzed. In the same vein, the regression models suggest that the heavier the molecular weight of a chemical contaminant of a pollutant from a point source, the greater the pollution of the underground water system at a short distance. The study concludes that the associative properties of landfill have a significant effect on groundwater quality in the study area.

Keywords: dumpsite, leachate, groundwater pollution, linear regression, principal component

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