Search results for: adaptive filter and average filter

Authors: Maryna Barushka, Aleh Meshyk

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The research analyzes absolute maximum soil temperatures registered at 36 gauge stations in Belarus from 1950 to 2013. The main method applied in the research is cartographic, in particular, trend surface analysis. Warming that had never been so long and intensive before started in 1988. The average temperature in January and February of that year exceeded the norm by 7-7.5 С, in March and April by 3-5С. In general, that year, as well as the year of 2008, happened to be the hottest ones in the whole period of instrumental observation. Yearly average air temperature in Belarus in those years was +8.0-8.2 С, which exceeded the norm by 2.0 – 2.2 С. The warming has been observed so far. The only exception was in 1996 when the yearly average air temperature in Belarus was below normal by 0.5 С. In Belarus the value of trend line of standard temperature deviation in the warmest months (July-August) has been positive for the past 25 years. In 2010 absolute maximum air and soil temperature exceeded the norm at 15 gauge stations in Belarus. The structure of natural processes includes global, regional, and local constituents. Trend surface analysis of the investigated characteristics makes it possible to determine global, regional, and local components. Linear trend surface shows the occurrence of weather deviations on a global scale, outside Belarus. Maximum soil temperature appears to be growing in the south-west direction with the gradient of 5.0 С. It is explained by the latitude factor. Polynomial trend surfaces show regional peculiarities of Belarus. Extreme temperature regime is formed due to some factors. The prevailing one is advection of turbulent flow of the ground layer of the atmosphere. In summer influence of the Azores High producing anticyclones is great. The Gulf Stream current forms the values of temperature trends in a year period. The most intensive flow of the Gulf Stream in the second half of winter and the second half of summer coincides with the periods of maximum temperature trends in Belarus. It is possible to estimate a local component of weather deviations in the analysis of the difference in values of the investigated characteristics and their trend surfaces. Maximum positive deviation (up to +4 С) of averaged soil temperature corresponds to the flat terrain in Pripyat Polesie, Brest Polesie, and Belarusian Poozerie Area. Negative differences correspond to the higher relief which partially compensates extreme heat regime of soils. Another important factor for maximum soil temperature in these areas is peat-bog soils with the least albedo of 8-15%. As yearly maximum soil temperature reaches 40-60 С, this could be both negative and positive factors for Belarus’s environment and economy. High temperature causes droughts resulting in crops dying and soil blowing. On the other hand, vegetation period has lengthened thanks to bigger heat resources, which allows planting such heat-loving crops as melons and grapes with appropriate irrigation. Thus, trend surface analysis allows determining global, regional, and local factors in accumulating heat in the soils of Belarus.

Keywords: soil, temperature, trend surface analysis, warming

Procedia PDF Downloads 114

Authors: Xue Xiao, Sun Hao, Liu Donghua

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E-commerce is experiencing rapid development and evolution, but traditional research methods are difficult to fully demonstrate the relationship between micro factors and macro evolution in the development process of e-commerce, which cannot provide accurate assessment for the existing strategies and predict the future evolution trends. To solve these problems, this paper presents the concept of e-commerce service ecosystem based on the characteristics of e-commerce and business ecosystem theory, describes e-commerce environment as a complex adaptive system from the perspective of ecology, constructs a e-commerce service ecosystem model by using Agent-based modeling method and Java language in RePast simulation platform and conduct experiment through the way of computational experiment, attempt to provide a suitable and effective researching method for the research on e-commerce evolution. By two experiments, it can be found that system model built in this paper is able to show the evolution process of e-commerce service ecosystem and the relationship between micro factors and macro emergence. Therefore, the system model constructed by Agent-based method and computational experiment provides proper means to study the evolution of e-commerce ecosystem.

Keywords: e-commerce service ecosystem, complex system, agent-based modeling, computational experiment

Procedia PDF Downloads 331

Authors: Ouafa Benaida, Abdelhamid Loukil, Adda Ali Pacha

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In recent years, the growing interest of scientists in the field of image processing and analysis of underwater images and videos has been strengthened following the emergence of new underwater exploration techniques, such as the emergence of autonomous underwater vehicles and the use of underwater image sensors facilitating the exploration of underwater mineral resources as well as the search for new species of aquatic life by biologists. Indeed, underwater images and videos have several defects and must be preprocessed before their analysis. Underwater landscapes are usually darkened due to the interaction of light with the marine environment: light is absorbed as it travels through deep waters depending on its wavelength. Additionally, light does not follow a linear direction but is scattered due to its interaction with microparticles in water, resulting in low contrast, low brightness, color distortion, and restricted visibility. The improvement of the underwater image is, therefore, more than necessary in order to facilitate its analysis. The research presented in this paper aims to implement and evaluate a set of classical techniques used in the field of improving the quality of underwater images in several color representation spaces. These methods have the particularity of being simple to implement and do not require prior knowledge of the physical model at the origin of the degradation.

Keywords: underwater image enhancement, histogram normalization, histogram equalization, contrast limited adaptive histogram equalization, single-scale retinex

Procedia PDF Downloads 69

Authors: Khashayar Nasrifar

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Ionic liquids (ILs) exhibit particular properties exemplified by extremely low vapor pressure and high thermal stability. The properties of ILs can be tailored by proper selection of cations and anions. As such, ILs are appealing as potential solvents to substitute traditional solvents with high vapor pressure. One of the IL properties required in chemical and process design is density. In developing corresponding state liquid density correlations, scaling hypothesis is often used. The hypothesis expresses the temperature dependence of saturated liquid densities near the vapor-liquid critical point as a function of reduced temperature. Extending the temperature dependence, several successful correlations were developed to accurately correlate the densities of normal liquids from the triple point to a critical point. Applying mixing rules, the liquid density correlations are extended to liquid mixtures as well. ILs are not molecular liquids, and they are not classified among normal liquids either. Also, ILs are often used where the condition is far from equilibrium. Nevertheless, in calculating the properties of ILs, the use of corresponding state correlations would be useful if no experimental data were available. With well-known generalized saturated liquid density correlations, the accuracy in predicting the density of ILs is not that good. An average error of 4-5% should be expected. In this work, a data bank was compiled. A simplified and concise corresponding state saturated liquid density correlation is proposed by phenomena-logically modifying reduced temperature using the temperature-dependence for an interacting parameter of the Soave-Redlich-Kwong equation of state. This modification improves the temperature dependence of the developed correlation. Parametrization was next performed to optimize the three global parameters of the correlation. The correlation was then applied to the ILs in our data bank with satisfactory predictions. The correlation of IL density applied at 0.1 MPa and was tested with an average uncertainty of around 2%. No adjustable parameter was used. The critical temperature, critical volume, and acentric factor were all required. Methods to extend the predictions to higher pressures (200 MPa) were also devised. Compared to other methods, this correlation was found more accurate. This work also presents the chronological order of developing such correlations dealing with ILs. The pros and cons are also expressed.

Keywords: correlation, corresponding state principle, ionic liquid, density

Procedia PDF Downloads 109

Authors: Ajda Osifo, Fatma Elshafie

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Mobile-assisted language learning favors social-constructivist and connectivist theories to learning and adaptive approaches to teaching. It offers many opportunities to differentiated instruction in meaningful ways as it enables learners to become more collaborative, engaged and independent through additional dimensions such as web-based media, virtual learning environments, online publishing to an imagined audience and digitally mediated communication. MALL applications can be a tool for the teacher to personalize and adjust instruction according to the learners’ needs and give continuous feedback to improve learning and performance in the process, which support differentiated instruction practices. This paper explores the utilization of Mobile Assisted Language Learning applications as a supporting tool for effective differentiation in the language classroom. It reports overall experience in terms of implementing MALL to shape and apply differentiated instruction and expand learning options. This session is structured in three main parts: first, a review of literature and effective practice of academically responsive instruction will be discussed. Second, samples of differentiated tasks, activities, projects and learner work will be demonstrated with relevant learning outcomes and learners’ survey results. Finally, project findings and conclusions will be given.

Keywords: academically responsive instruction, differentiation, mobile learning, mobile-assisted language learning

Procedia PDF Downloads 400

Authors: Tuba Tekin, Nurcan Baglam, Emine Dincer

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This study aimed to examine the effects of nutrition education received by university students on sustainable healthy eating behaviors and adherence to the Mediterranean diet. The 2nd, 3rd, and 4th-grade university students studying at the Faculty of Health Sciences, Nutrition and Dietetics, Midwifery, Nursing, Physical Therapy, and Rehabilitation departments of universities in Turkey were included in the study. Students' adherence to the Mediterranean diet was evaluated using the Mediterranean Diet Adherence Scale, and their sustainable and healthy eating behaviors were evaluated using the Sustainable and Healthy Eating Behaviors Scale. In addition, the body weight and height of the students were measured by the researchers, and the Body Mass Index (BMI) value was calculated. A total of 181 students, 85 of whom were studying in the Department of Nutrition and Dietetics and 96 of whom were educated in other departments, were included in the study. 75.7% of the students in the sample are female, while 24.3% are male. The average body weight of the students was 61.17±10.87 kg, and the average BMI was 22.04±3.40 kg/m2. While the mean score of the Mediterranean Diet Adherence Scale was 6.72±1.84, in the evaluation of adherence to the Mediterranean diet, it was determined that 25.4% of the students had poor adherence and 66.9% needed improvement. When the adherence scores of students who received and did not receive nutrition education were compared, it was discovered that the students who received nutrition education had a higher score (p<0.05). Students who received nutrition education had a higher total score on the Sustainable and Healthy Eating Behaviors scale (p<0.05). A moderately positive correlation was found between the Sustainable and Healthy Eating Behaviors scale total score and the Mediterranean Diet Adherence scores (p<0.05). As a result of the linear regression analysis, it was revealed that a 1-unit increase in the Mediterranean diet adherence score would result in a 1.3-point increase in the total score of the Sustainable and Healthy Eating Behaviors scale. Sustainable and healthy diets are important for improving and developing health and the prevention of diseases. The Mediterranean diet is defined as a sustainable diet model. The findings revealed the relationship between the Mediterranean diet and sustainable nutrition and showed that nutrition education increased knowledge and awareness about sustainable nutrition and increased adherence to the Mediterranean diet. For this reason, courses or seminars on sustainable nutrition can be organized during educational periods.

Keywords: healthy eating, Mediterranean diet, nutrition education, sustainable nutrition

Procedia PDF Downloads 59

Authors: Amal A. Hassan, Faten H. Fahmy, Abd El-Shafy A. Nafeh, Hosam K. M. Youssef

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Due to the growing penetration of wind energy into the power grid, it is very important to study its interactions with the power system and to provide good control technique in order to deliver high quality power. In this paper, an intelligent control methodology is proposed for optimizing the controllers’ parameters of doubly fed induction generator (DFIG) based wind turbine generation system (WTGS). The genetic algorithm (GA) and particle swarm optimization (PSO) are employed and compared for the parameters adaptive tuning of the proposed proportional integral (PI) multiple controllers of the back to back converters of the DFIG based WTGS. For this purpose, the dynamic model of WTGS with DFIG and its associated controllers is presented. Furthermore, the simulation of the system is performed using MATLAB/SIMULINK and SIMPOWERSYSTEM toolbox to illustrate the performance of the optimized controllers. Finally, this work is validated to 33-bus test radial system to show the interaction between wind distributed generation (DG) systems and the distribution network.

Keywords: DFIG wind turine, intelligent control, distributed generation, particle swarm optimization, genetic algorithm

Procedia PDF Downloads 248

Authors: Hatem K. Hamed, Mohamed S. Hrouda

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The Middle Paleocene Lower Beda Formation was deposited in a ramp system with local shoaling. The main constituent is limestone, with subordinate dolomites and Shales. Reservoir quality is largely influenced by depositional environments and diagenesis processes. Generally the reservoir quality of Lower Beda Formation is low risk on the Inferred Horst and in the Southern Shelf where the Lower Beda formation comprises mainly of calcarenties. In the vicinity of the well GG1 the Lower Beda comprise mainly of argillaceous calcilutites and shale. The reservoir quality gradually improves from high risk to moderate risk towards KK1, LL1 and NN1 wells. The average gross thickness of Lower Beda Formation is about 300 ft. The net thickness varies from about 270 ft. in the E1-71 well to about 30 ft. in the vicinity of GG1-71 well. The net thickest of Lower Beda form a NNW-SSW trend with an average of 250 ft. the change in facies is due to change in the depositional environment, from lagoonal to shoal barrier to open marine affected the reservoir quality. The Upper Cretaceous Sirte Shale is the main source rock. It is developed within the three troughs surrounding the study area. S-Marada Trough to the N- E, Gerad Trough to the N N-W, and Abu Tummym Sub-basin to the S-W of the Inferred Horst. Sirte shale reaches 1000ft, of organically rich section. It has good organic contents over large area 2% to 3%. Hydrocarbon shows were encountered in several wells in Beda Formation this is an indication of vertical and lateral migration of hydrocarbon. The overlying Upper Paleocene Khalifa Formation is a transgressive shale, it is an effective regional top seal. Lithofacies variations in Khalifa Shale, from shales to limestones in the southern shelf in R1-71 well approximately 50-75% of the secession is limestone. About 47 million barrel of hydrocarbon recoverable reserves is expected to be trapped in structural and stratigraphic traps in Beda Formation in the study area.

Keywords: Sirte basin, Beda formation, concession 71, petroleum play fairway analysis

Procedia PDF Downloads 71

Authors: Michal Bialy, Marcin Szlachetka, Mateusz Paszko

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This paper discusses the CFD results of heat transfer in water channels in the engine body. The research engine was a newly designed Diesel combustion engine. The engine has three cylinders with three pairs of opposed pistons inside. The engine will be able to generate 100 kW mechanical power at a crankshaft speed of 3,800-4,000 rpm. The water channels are in the engine body along the axis of the three cylinders. These channels are around the three combustion chambers. The water channels transfer combustion heat that occurs the cylinders to the external radiator. This CFD research was based on the ANSYS Fluent software and aimed to optimize the geometry of the water channels. These channels should have a maximum flow of heat from the combustion chamber or the external radiator. Based on the parallel simulation research, the boundary and initial conditions enabled us to specify average values of key parameters for our numerical analysis. Our simulation used the average momentum equations and turbulence model k-epsilon double equation. There was also used a real k-epsilon model with a function of a standard wall. The turbulence intensity factor was 10%. The working fluid mass flow rate was calculated for a single typical value, specified in line with the research into the flow rate of automotive engine cooling pumps used in engines of similar power. The research uses a series of geometric models which differ, for instance, in the shape of the cross-section of the channel along the axis of the cylinder. The results are presented as colourful distribution maps of temperature, speed fields and heat flow through the cylinder walls. Due to limitations of space, our paper presents the results on the most representative geometric model only. Acknowledgement: This work has been realized in the cooperation with The Construction Office of WSK ‘PZL-KALISZ’ S.A. and is part of Grant Agreement No. POIR.01.02.00-00-0002/15 financed by the Polish National Centre for Research and Development.

Keywords: Ansys fluent, combustion engine, computational fluid dynamics CFD, cooling system

Procedia PDF Downloads 202

Authors: Gaye Demi̇rtaş Adli

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Research: It was conducted to determine the factors affecting the fear of self-injection and self-pricking of fingers of diabetic individuals.The study was conducted as a cross-sectional, relation-seeking, and descriptive study. The study was conducted on 122 patients who had just started insulin therapy. Data were obtained through The Descriptive Patient Form, The Diabetic Self-Injection, and the Fear of Testing Questionnaire Form (D-FISQ). Descriptive statistical methods used in the evaluation of data are the Mann-Whitney U test, Kruskal-Wallis H test, and the Spearman correlation. The factors affecting the scale scores were evaluated with multiple linear regression analysis. The value of P<0.05 was considered statistically significant. Study group: 56.6% of the patients are male patients. Fear of self-injection (injection), fear of self-testing (test), and total fear (total) scores of women were found to be statistically higher than men (p<0.001). Age, gender, and pain experience were important variables that affected patients' fear of injections. With a one-unit increase in age, the injection fear score decreased by 0.13 points, and the mean injection fear score of women was 2.11 points higher than that of men. It was determined that the patient's age, gender, living with whom, and blood donation history were important variables affecting the fear of self-testing. It is seen that the fear test score decreases by 0.18 points with an increase in age by one unit, and the fear test scores of women compared to men are on average 3,358 points, the fear test scores of those living alone are 4,711 points compared to those living with family members, and the fear test scores of those who do not donate blood are 2,572 compared to those who donate blood score, it was determined that those with more pain experience were 3,156 points higher on average than those with less fear of injection. As a result, it was seen that the most important factors affecting the fear of insulin injection and finger punching in individuals with diabetes were age, gender, pain experience, living with whom, and blood donation history.

Keywords: diabetes, needle phobia, fear of injection, insulin injection

Procedia PDF Downloads 47

Authors: Pankaj Kumar

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Rapid global changes resulted in unfavorable hydrological, ecological, and environmental changes and cumulatively affected natural resources. As a result, the local communities become vulnerable to water stress, poor hygiene, the spread of diseases, food security, etc.. However, the central point for this vulnerability revolves around water resources and the way people interrelate with the hydrological system. Also, most of the efforts to minimize the adverse effect of global changes are centered on the mitigation side. Hence, countries with poor adaptive capacities and poor governance suffer most in case of disasters. However, several transdisciplinary numerical tools are well designed and are capable of answering “what-if questions” through scenario analysis using a system approach. This study has predicted the future water environment in Marikina River in the National Capital Region, Metro Manila of Philippines, using Water Evaluation and Planning (WEAP), an integrated water resource management tool. Obtained results can answer possible adaptation measures along with their associated uncertainties. It also highlighted various challenges for the policy planners to design adaptation countermeasures as well as to track the progress of achieving SDG 6.0.

Keywords: water quality, Philippines, climate change adaptation, hydrological simulation, wastewater management, weap

Procedia PDF Downloads 79

Authors: Soumaya Mrabet, Taieb Ach, Imen Akkari, Amira Atig, Neirouz Ghannouchi, Koussay Ach, Elhem Ben Jazia

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Introduction: Celiac disease (CD) and type 1 diabetes mellitus (T1D) are complex disorders with shared genetic components. The association between CD and T1D has been reported in many pediatric series. The aim of our study is to describe the epidemiological, clinical and evolutive characteristics of adult patients presenting this association. Material and Methods: This is a retrospective study including patients diagnosed with CD and T1D, explored in Internal Medicine, Gastroenterology and Endocrinology and Diabetology Departments of the Farhat Hached University Hospital, between January 2005 and June 2016. Results: Among 57 patients with CD, 15 patients had also T1D (26.3%). There are 11 women and 4 men with a median age of 27 years (16-48). All patients developed T1D prior to the diagnosis of CD with an average duration of 47 months between the two diagnosis (6 months-5 years). CD was revealed by recurrent abdominal pain in 11 cases, diarrhea in 10 cases, bloating in 8 cases, constipation in 6 cases and vomiting in 2 cases. Three patients presented cycle disorders with secondary amenorrhea in 2 patients. Anti-Endomysium, anti-transglutaminase and Anti-gliadin antibodies were positive respectively in 57, 54 and 11 cases. The biological tests revealed anemia in 10 cases, secondary to iron deficiency in 6 cases and folate and vitamin B12 deficiency in 4 cases, hypoalbuminaemia in 4 cases, hypocalcemia in 3 cases and hypocholesterolemia in 1 patient. Upper gastrointestinal endoscopy showed an effacement of the folds of the duodenal mucosa in 6 cases and a congestive duodenal mucosa in 3 cases. The macroscopic appearance was normal in the others cases. Microscopic examination showed an aspect of villous atrophy in 57 cases, which was partial in 10 cases and total in 47 cases. After an average follow-up of 3 years 2 months, the evolution was favorable in all patients under gluten-free diet with the necessity of less important doses of insulin in 10 patients. Conclusion: In our study, the prevalence of T1D in adult patients with CD was 26.3%. This association can be attributed to overlapping genetic HLA risk loci. In recent studies, the role of gluten as an important player in the pathogenesis of CD and T1D has been also suggested.

Keywords: celiac disease, gluten, prevalence, type 1 diabetes

Procedia PDF Downloads 235

Authors: Ali Razmi, Saeed Golian

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Climate change is known to have the potential to impact adversely hydrologic patterns for variables such as rainfall, maximum and minimum temperature and sea level rise. Long-term average of these climate variables could possibly change over time due to climate change impacts. In this study, trend analysis was performed on rainfall, maximum and minimum temperature and water level data of a coastal area in Manhattan, New York City, Central Park and Battery Park stations to investigate if there is a significant change in the data mean. Partial Man-Kendall test was used for trend analysis. Frequency analysis was then performed on data using common probability distribution functions such as Generalized Extreme Value (GEV), normal, log-normal and log-Pearson. Goodness of fit tests such as Kolmogorov-Smirnov are used to determine the most appropriate distributions. In flood frequency analysis, rainfall and water level data are often separately investigated. However, in determining flood zones, simultaneous consideration of rainfall and water level in frequency analysis could have considerable effect on floodplain delineation (flood extent and depth). The present study aims to perform flood frequency analysis considering joint probability distribution for rainfall and storm surge. First, correlation between the considered variables was investigated. Joint probability distribution of extreme water level and temperature was also investigated to examine how global warming could affect sea level flooding impacts. Copula functions were fitted to data and joint probability of water level with rainfall and temperature for different recurrence intervals of 2, 5, 25, 50, 100, 200, 500, 600 and 1000 was determined and compared with the severity of individual events. Results for trend analysis showed increase in long-term average of data that could be attributed to climate change impacts. GEV distribution was found as the most appropriate function to be fitted to the extreme climate variables. The results for joint probability distribution analysis confirmed the necessity for incorporation of both rainfall and water level data in flood frequency analysis.

Keywords: climate change, climate variables, copula, joint probability

Procedia PDF Downloads 339

Authors: Mateusz Jeżowski, Jadwiga Fila, Paweł Poszytek

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This abstract summarizes the combined findings of several analyses carried out by the authors on the barriers to accessing international education mobility programs by people with fewer opportunities, especially those with a low level of cultural and social capital. Two flagship educational mobility initiatives of the European Union – the Erasmus+ Program and the European Solidarity Corps are aimed at equipping young people and participants of all ages with the qualifications and skills needed for their meaningful participation in a democratic society intercultural understanding and successful transition in the labour market. The heart of these programs is to come closer to people with fewer opportunities, including people with disabilities, migrants, as well as those facing socio-economic difficulties and displaying a low level of social and cultural capital. Still, people who participate in such initiatives usually demonstrate higher than average cultural and social capital, as understood by Pierre Bourdieu. First of all, the educational attainment of their parents is higher than the average. Secondly, they mostly live in large agglomerations, with good access to education and culture, which affects their foreign language skills as well as social and cultural competencies. Finally, participation in Erasmus+ Program or European Solidarity Corps is not their first educational mobility experience. It is therefore justified to state that their social and cultural capital, already high before taking part in Erasmus+ and European Solidarity Corps, becomes even higher once their international mobility activities have been over, at the expense of those people with fewer opportunities, who, in theory, could participate in those initiatives, nonetheless did not, for the following reasons: lack of sufficient information on such programs, financial obstacles or unappreciation of the value of international mobility. In their work, the authors will discuss what are, in the light of Bourdieu’s perception of social and cultural capital, the main obstacles for young people to participate in international mobility programs of the European Union and will offer comprehensive solutions rooted in their vast experience in management and implementation of Erasmus+ Program and European Solidarity Corps.

Keywords: cultural capital, educational mobility, Erasmus+, European solidarity corps, inclusion, social capital

Procedia PDF Downloads 101

Authors: Maria Ezziani, Rabie Zine, Amine Amar, Ilhame Kissani

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This paper introduces a predictive model for urban transportation engineering, which is vital for efficient traffic management. Utilizing comprehensive datasets and advanced statistical techniques, the model accurately forecasts travel times by considering temporal variations and traffic dynamics. Machine learning algorithms, including regression trees and neural networks, are employed to capture sequential dependencies. Results indicate significant improvements in predictive accuracy, particularly during peak hours and holidays, with the incorporation of traffic flow and speed variables. Future enhancements may integrate weather conditions and traffic incidents. The model's applications range from adaptive traffic management systems to route optimization algorithms, facilitating congestion reduction and enhancing journey reliability. Overall, this research extends beyond travel time estimation, offering insights into broader transportation planning and policy-making realms, empowering stakeholders to optimize infrastructure utilization and improve network efficiency.

Keywords: predictive analytics, traffic flow, travel time estimation, urban transportation, machine learning, traffic management

Procedia PDF Downloads 56

Authors: M. Pawlaczyk-Łuszczyńska, T. Wszołek, A. Dudarewicz, P. Małecki, M. Kłaczyński, A. Bortkiewicz

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Human tolerance to infrasound is defined by the hearing threshold. Infrasound that cannot be heard (or felt) is not annoying and is not thought to have any other adverse or health effects. Recent research has largely confirmed earlier findings. ISO 7196:1995 recommends the use of G-weighted characteristics for the assessment of infrasound. There is a strong correlation between G-weighted SPL and annoyance perception. The aim of this study was to propose exposure limits for infrasound from wind turbines. However, only a few countries have set limits for infrasound. These limits are usually no higher than 85-92 dBG, and none of them are specific to wind turbines. Over the years, a number of studies have been carried out to determine hearing thresholds below 20 Hz. It has been recognized that 10% of young people would be able to perceive 10 Hz at around 90 dB, and it has also been found that the difference in median hearing thresholds between young adults aged around 20 years and older adults aged over 60 years is around 10 dB, irrespective of frequency. This shows that older people (up to about 60 years of age) retain good hearing in the low frequency range, while their sensitivity to higher frequencies is often significantly reduced. In terms of exposure limits for infrasound, the average hearing threshold corresponds to a tone with a G-weighted SPL of about 96 dBG. In contrast, infrasound at Lp,G levels below 85-90 dBG is usually inaudible. The individual hearing threshold can, therefore be 10-15 dB lower than the average threshold, so the recommended limits for environmental infrasound could be 75 dBG or 80 dBG. It is worth noting that the G86 curve has been taken as the threshold of auditory perception of infrasound reached by 90-95% of the population, so the G75 and G80 curves can be taken as the criterion curve for wind turbine infrasound. Finally, two assessment methods and corresponding exposure limit values have been proposed for wind turbine infrasound, i.e. method I - based on G-weighted sound pressure level measurements and method II - based on frequency analysis in 1/3-octave bands in the frequency range 4-20 Hz. Separate limit values have been set for outdoor living areas in the open countryside (Area A) and for noise sensitive areas (Area B). In the case of Method I, infrasound limit values of 80 dBG (for areas A) and 75 dBG (for areas B) have been proposed, while in the case of Method II - criterion curves G80 and G75 have been chosen (for areas A and B, respectively).

Keywords: infrasound, exposure limit, hearing thresholds, wind turbines

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Authors: Li-Jun Ren, Wei Pan, Li-Li Xu, Shu-Qing An

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This study evaluated whether different matrix composition volume ratio can improve water quality in the experiment. The mechanism and adsorption capability of wetland matrixes (oyster shell, coarse slag, and volcanic rock) and their different volume ratio in group configuration during pollutants removal processes were tested. When conditions unchanged, the residence time affects the reaction effect. The average removal efficiencies of four kinds of matrix volume ratio on the TN were 62.76%, 61.54%, 64.13%, and 55.89%, respectively.

Keywords: hydraulic residence time, matrix composition, removal efficiency, volume ratio

Procedia PDF Downloads 307

Authors: Bilgen Ozluk, Ayfer Karaaslan

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Introduction: Adaptation to university life is a difficult process for students. In peer support, students are expected to help other students or sometimes adults using their helping skills. Therefore, it is expected that peer support will have significant effect on students’ adaptation to university life. Aim: This study was conducted with the aim of determining the effect of peer support on adaptation to university life in the first year students of the faculty of health sciences. Methods: The population consists of 340 first year university students receiving education in the departments of nursing, health management, social services, nutrition and dietetics, physiotherapy and rehabilitation at an university located in the province of Konya. The sample of the study consisted of 274 students who voluntarily participated in the study. The data were collected between the dates 23 May 2016 and 3 June 2016. The data were collected using the socio-demographic information, the peer support scale and the university life adaptation scale. Ethical approvals for the study and permission from the university were taken. Numbers, percentages, averages, one-Way ANOVA, pearson correlation analysis and regression analysis have been used in assessing the data. Findings: When the problems most frequently encountered by students just starting the university were ordered, problems regarding their classes took the first place by 41.6%, socio-cultural problems took the second place by 38.7%, and economic problems took the third place by 37.6%. The mean total score of the Adaptation to University Life Scale was found to be 216.78±32.15. Considering that the lowest and highest scores that can be gained from the scale are 132 and 289 respectively, it was found that the adaptation to university life levels of the students were higher than the average. The mean adaptation to university life score of the nursing students was higher than those of the students of other departments. The mean score of ‘the Peer Support Scale’ was found to be 47.24±10.27. Considering that the lowest and highest scores that can be gained from the scale are 17 and 68 respectively, it was found that the peer support levels of the students were higher than the average. As a result of the regression analysis, it was found that 20% of the total variance regarding adaptation to university life was explained by peer support. Conclution: Receiving the support peer groups becomes highly important in the university adaptation process of first-year students. Peer support will create the means for easier completion of this difficult transition process.

Keywords: adaptation to university life, first years, peer support, university student

Procedia PDF Downloads 192

Authors: Arthur D. Wiedemann, Christopher Fuller, Kyle A. Pascioni

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With the introduction of electric motors, small unmanned aerial vehicle designers have to consider trade-offs between acoustic noise and thrust generated. Currently, there are few low-computational tools available for predicting acoustic noise emitted by a propeller into the far-field. Artificial neural networks offer a highly non-linear and adaptive model for predicting isolated and interactive tonal noise. But neural networks require large data sets, exceeding practical considerations in modeling experimental results. A methodology known as physics guided machine learning has been applied in this study to reduce the required data set to train the network. After building and evaluating several neural networks, the best model is investigated to determine how the network successfully predicts the acoustic waveform. Lastly, a post-network transfer function is developed to remove discontinuity from the predicted waveform. Overall, methodologies from physics guided machine learning show a notable improvement in prediction performance, but additional loss functions are necessary for constructing predictive networks on small datasets.

Keywords: aeroacoustics, machine learning, propeller, rotor, neural network, physics guided machine learning

Procedia PDF Downloads 198

Authors: Chen-Ya Juan

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Problem-Based Learning uses vague questions to guide student thinking and enhance their self-learning and collaboration. Most teachers implement PBL in a physical classroom, where teachers can monitor and evaluate students’ learning progress and guide them to search resources for answers. However, the prevalence of the Covid-19 in the world had changed from physical teaching to distance teaching. This instruction used many cases and applied Problem-Based Learning combined on the distance teaching via the internet for college students. This study involved an experimental group with PBL and a control group without PBL. The teacher divided all students in PBL class into eight groups, and 7~8 students in each group. The teacher assigned different cases for each group of the PBL class. Three stages of instruction were developed, including background knowledge of Learning, case analysis, and solving problems for each case. This study used a quantitative research method, a two-sample t-test, to find a significant difference in groups with PBL and without PBL. Findings indicated that PBL incased the average score of special education knowledge. The average score was improved by 20.46% in the PBL group and 15.4% without PBL. Results didn’t show significant differences (0.589>0.05) in special education professional knowledge. However, the feedback of the PBL students implied learning more about the application, problem-solving skills, and critical thinking. PBL students were more likely to apply professional knowledge on the actual case, find questions, resources, and answers. Most of them understood the importance of collaboration, working as a team, and communicating with other team members. The suggestions of this study included that (a) different web-based teaching instruments influenced student’s Learning; (b) it is difficult to monitor online PBL progress; (c) online PBL should be implemented flexible and multi-oriented; (d) although PBL did not show a significant difference on the group with PBL and without PBL, it did increase student’s problem-solving skills and critical thinking.

Keywords: problem-based learning, college students, distance learning, case analysis, problem-solving

Procedia PDF Downloads 113

Authors: Ritu Chaturvedi, Manoj Paul

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A pot experiment was conducted to investigate the effect of Arbuscular mycorrhizal fungus (AMF) on metal(loid) uptake and accumulation efficiency of Pisum sativum along with physiological and biochemical response. Plants were grown in soil spiked with 50 and 100 mg kg-1 Pb, 25 and 50 mg kg-1 Cd, 50 and 100 mg kg-1 As and a combination of all three metal(loid)s. A parallel set was maintained and inoculated with arbuscular mycorrhizal fungus for comparison. After 60 days, plants were harvested and analysed for metal(loid) content. A steady increase in metal(loid) accumulation was observed on increment of metal(loid) dose and also on AMF inoculation. Plant height, biomass, chlorophyll, carotenoid and carbohydrate content reduced upon metal(loid) exposure. Increase in enzymatic (CAT, SOD and APX) and nonenzymatic (Proline) defence proteins was observed on metal(loid) exposure. AMF inoculation leads to an increase in plant height, biomass, chlorophyll, carotenoids, carbohydrate and enzymatic defence proteins (p≤0.001) under study; whereas proline content was reduced. Considering the accumulation efficiency and adaptive response of plants and alleviation of stress by AMF, this symbiosis can be applied for on-site remediation of Pb and Cd contaminated soil.

Keywords: heavy metal, mycorrhiza, pea, phyroremediation

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Authors: F. Hiouani, M. Henouda, A. Masmoudi, M. Rechachi

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The objective of this study was to evaluate the quality of irrigation water of some underground water resources in the region of Lioua (Biskra, Algéria). Analysis of cations (Ca++, Mg++, Na+, K+), anions (Cl-, SO4--, CO3--, HCO3-, NO3-), pH and electrical conductivity (EC) of ten water samples taken during March 2015. The resulted showed that water samples are designated salty and very salty. On the other hand, average SAR values show that there is no alkalinity risk of soil. According to Riverside diagram water samples are grouped into five classes (C3-S1, C4-S1, C4-S3, C5-S2 and C5-S3).

Keywords: groundwater, irrigation, quality, lioua biskra

Procedia PDF Downloads 291

Authors: Julius M. Ndambuki, Gislar E. Kifanyi, Samuel N. Odai, Charles Gyamfi

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Conjunctive management of surface and groundwater resources is a challenging task due to the spatial and temporal variability nature of hydrology as well as hydrogeology of the water storage systems. Surface water-groundwater hydrogeology is highly uncertain; thus it is imperative that this uncertainty is explicitly accounted for, when managing water resources. Various methodologies have been developed and applied by researchers in an attempt to account for the uncertainty. For example, simulation-optimization models are often used for conjunctive water resources management. However, direct application of such an approach in which all realizations are considered at each iteration of the optimization process leads to a very expensive optimization in terms of computational time, particularly when the number of realizations is large. The aim of this paper, therefore, is to introduce and apply an efficient approach referred to as Retrospective Optimization Approximation (ROA) that can be used for optimizing conjunctive use of surface water and groundwater over a multiple hydrogeological model simulations. This work is based on stochastic simulation-optimization framework using a recently emerged technique of sample average approximation (SAA) which is a sampling based method implemented within the Retrospective Optimization Approximation (ROA) approach. The ROA approach solves and evaluates a sequence of generated optimization sub-problems in an increasing number of realizations (sample size). Response matrix technique was used for linking simulation model with optimization procedure. The k-means clustering sampling technique was used to map the realizations. The methodology is demonstrated through the application to a hypothetical example. In the example, the optimization sub-problems generated were solved and analysed using “Active-Set” core optimizer implemented under MATLAB 2014a environment. Through k-means clustering sampling technique, the ROA – Active Set procedure was able to arrive at a (nearly) converged maximum expected total optimal conjunctive water use withdrawal rate within a relatively few number of iterations (6 to 7 iterations). Results indicate that the ROA approach is a promising technique for optimizing conjunctive water use of surface water and groundwater withdrawal rates under hydrogeological uncertainty.

Keywords: conjunctive water management, retrospective optimization approximation approach, sample average approximation, uncertainty

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Authors: Michal Krecichwost, Zauzanna Miodonska, Pawel Badura

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The diagnosis of sigmatism is mostly based on the observation of articulatory organs. It is, however, not always possible to precisely observe the vocal apparatus, in particular in the oral cavity of the patient. Speech processing can allow to objectify the therapy and simplify the verification of its progress. In the described study the methodology for classification of incorrectly pronounced phoneme [s] is proposed. The recordings come from adults. They were registered with the speech recorder at the sampling rate of 44.1 kHz and the resolution of 16 bit. The database of pathological and normative speech has been collected for the study including reference assessments provided by the speech therapy experts. Ten adult subjects were asked to simulate a certain type of stigmatism under the speech therapy expert supervision. In the recordings, the analyzed phone [s] was surrounded by vowels, viz: ASA, ESE, ISI, SPA, USU, YSY. Thirteen MFCC (mel-frequency cepstral coefficients) and RMS (root mean square) values are calculated within each frame being a part of the analyzed phoneme. Additionally, 3 fricative formants along with corresponding amplitudes are determined for the entire segment. In order to aggregate the information within the segment, the average value of each MFCC coefficient is calculated. All features of other types are aggregated by means of their 75th percentile. The proposed method of features aggregation reduces the size of the feature vector used in the classification. Binary SVM (support vector machine) classifier is employed at the phoneme recognition stage. The first group consists of pathological phones, while the other of the normative ones. The proposed feature vector yields classification sensitivity and specificity measures above 90% level in case of individual logo phones. The employment of a fricative formants-based information improves the sole-MFCC classification results average of 5 percentage points. The study shows that the employment of specific parameters for the selected phones improves the efficiency of pathology detection referred to the traditional methods of speech signal parameterization.

Keywords: computer-aided pronunciation evaluation, sibilants, sigmatism diagnosis, speech processing

Procedia PDF Downloads 262

Authors: Christina Adly, Meena Abdelmeseeh, Tamer Basha

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This paper proposes a system for hand movement recognition using multichannel surface EMG(sEMG) signals obtained from 40 subjects using 40 different exercises, which are available on the Ninapro(Non-Invasive Adaptive Prosthetics) database. First, we applied processing methods to the raw sEMG signals to convert them to their amplitudes. Second, we used deep learning methods to solve our problem by passing the preprocessed signals to Fully connected neural networks(FCNN) and recurrent neural networks(RNN) with Long Short Term Memory(LSTM). Using intrasubject evaluation, The accuracy using the FCNN is 72%, with a processing time for training around 76 minutes, and for RNN's accuracy is 79.9%, with 8 minutes and 22 seconds processing time. Third, we applied some postprocessing methods to improve the accuracy, like majority voting(MV) and Movement Error Rate(MER). The accuracy after applying MV is 75% and 86% for FCNN and RNN, respectively. The MER value has an inverse relationship with the prediction delay while varying the window length for measuring the MV. The different part uses the RNN with the intersubject evaluation. The experimental results showed that to get a good accuracy for testing with reasonable processing time, we should use around 20 subjects.

Keywords: hand movement recognition, recurrent neural network, movement error rate, intrasubject evaluation, intersubject evaluation

Procedia PDF Downloads 118

Authors: Bharat Sapkota

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Nepal is the one of the victim country of climate change. Decreasing snow line, sometimes higher and sometime non-rain fall are common phenomena in hill area. Natural flood disaster and drought is also common every year in certain place of the country. So this paper analyze the effect of climate and natural water sources for sustainability of water sanitation and hygiene of Tanahun district. It is one of the Rural Water Supply and Sanitation Project Western Nepal Phase-II (RWSSP-WN Phase-II) project district out of 14 project districts of western and mid-western Nepal. RWSSP-WN II is a bilateral development cooperation of governments of Nepal and Finland. Big investment is still going on in water sanitation and hygiene sector but sustainability is still a challenge throughout the country. So RWSSP-WN has started the strengthen of the capacity of local Governments to deliver services in water supply, sanitation and hygiene and its sustainability through the implementation of cross cutting approach of climate change and disaster risk reduction. The study shows that the average yield in 685 natural point sources were around 0.045 l/s in 2014 but it was twice as high in 2004 i.e. 0.09 l/s. The maximum measured yield in 2014 was 1.87 l/s, whereas, the maximum yield was 3 l/s in 2004. Likewise, spring source mean and maximum yield measured in 2014 were 0.16 l/s and 3.33 l/s respectively, whereas, mean and maximum yields in 2004 were 0.204 l/s and 3 l/s respectively. Small streams average yield measured in 2014 was 0.32 l/s with the maximum of around 4.99 l/s. In 2004, mean and maximum yields of streams were 0.485 l/s and 5 l/s respectively. The overall climate between years 2002 to 2013 and measured yield data between 2004 and 2014 shows climate as one of the causes of water source decline. The temperature is rising with pace of 0.041°C per year and rainfall is decreased by 16.8 mm/year. The Khosla’s empirical formula shows decrease of 1.7 cm/year in runoff. At present sustainability of water, sanitation and hygiene is more challenge due to sources decreasing in the district. Sanitation and hygiene total behavior change and watershed conservation as well as design and implementation of recharge pound construction are the way forward of sustainability of water, sanitation and hygiene.

Keywords: water sanitation, hygiene, sustainability, climate change

Procedia PDF Downloads 316

Authors: Muhammad Bilal Shaikh

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Mineral processing plants play a pivotal role in extracting valuable minerals from raw ores, contributing significantly to various industries. However, the optimization of plant throughput remains a complex challenge, necessitating innovative approaches for increased efficiency and productivity. This research paper investigates the application of Multimodal Artificial Intelligence (MAI) techniques to address this challenge, aiming to improve overall plant throughput in mineral processing operations. The integration of multimodal AI leverages a combination of diverse data sources, including sensor data, images, and textual information, to provide a holistic understanding of the complex processes involved in mineral extraction. The paper explores the synergies between various AI modalities, such as machine learning, computer vision, and natural language processing, to create a comprehensive and adaptive system for optimizing mineral processing plants. The primary focus of the research is on developing advanced predictive models that can accurately forecast various parameters affecting plant throughput. Utilizing historical process data, machine learning algorithms are trained to identify patterns, correlations, and dependencies within the intricate network of mineral processing operations. This enables real-time decision-making and process optimization, ultimately leading to enhanced plant throughput. Incorporating computer vision into the multimodal AI framework allows for the analysis of visual data from sensors and cameras positioned throughout the plant. This visual input aids in monitoring equipment conditions, identifying anomalies, and optimizing the flow of raw materials. The combination of machine learning and computer vision enables the creation of predictive maintenance strategies, reducing downtime and improving the overall reliability of mineral processing plants. Furthermore, the integration of natural language processing facilitates the extraction of valuable insights from unstructured textual data, such as maintenance logs, research papers, and operator reports. By understanding and analyzing this textual information, the multimodal AI system can identify trends, potential bottlenecks, and areas for improvement in plant operations. This comprehensive approach enables a more nuanced understanding of the factors influencing throughput and allows for targeted interventions. The research also explores the challenges associated with implementing multimodal AI in mineral processing plants, including data integration, model interpretability, and scalability. Addressing these challenges is crucial for the successful deployment of AI solutions in real-world industrial settings. To validate the effectiveness of the proposed multimodal AI framework, the research conducts case studies in collaboration with mineral processing plants. The results demonstrate tangible improvements in plant throughput, efficiency, and cost-effectiveness. The paper concludes with insights into the broader implications of implementing multimodal AI in mineral processing and its potential to revolutionize the industry by providing a robust, adaptive, and data-driven approach to optimizing plant operations. In summary, this research contributes to the evolving field of mineral processing by showcasing the transformative potential of multimodal artificial intelligence in enhancing plant throughput. The proposed framework offers a holistic solution that integrates machine learning, computer vision, and natural language processing to address the intricacies of mineral extraction processes, paving the way for a more efficient and sustainable future in the mineral processing industry.

Keywords: multimodal AI, computer vision, NLP, mineral processing, mining

Procedia PDF Downloads 53

Authors: Rachida Gherbi-Salmi, Abdelkarim Si Bachir, Salah Eddine Doumandji

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The Cattle Egret is a predatory bird with an insectivorous diet. It feeds in open environments (wetlands, meadows, farmland and cultivated land). Few studies have determined the status of its prey (useful or harmful species for agriculture). Hence, our study was carried out in the Bejaia region (Algeria). It consisted of examining adult rejection pellets collected in a heronry located in the lower Soummam Valley (El-Kseur), which has been a permanent habitat for over 30 years. Field sampling was carried out during the juvenile rearing period in 1998 (wet spring) and 2020 (almost dry spring). Examination of 50 pellets at a rate of 10 per month (May - September) in 1998 revealed the presence of 2,661 prey belonging to 170 species, i.e., an average of 53.36 prey per pellet. The results reveal that the diet of this Ardeidae consists mainly of Insecta (95.09%). Arachnida was a distant second (4.05%). Vertebrates (Reptilia and Rodentia) (0.82%) and myriapods (0.04%) are rare prey. We counted 2,154 plant pests (80.27%), of which 2,138 were insects (99.27%) and 0.73% rodents (Mus spretus). Of the plant-pest insects identified, 1385 were Orthoptera (64.78%). Fourmicidae came second (13.05%), and Coleoptera third (12.82%). Dermaptera, on the other hand, accounted for only 7.86%. Analysis of 30 rejection pellets, 10 per month (May - July) in 2020, identified 1,330 prey belonging to 80 species, an average of 44.33 prey per pellet. The results reveal that its diet is essentially made up of Insecta (94.81%). These are followed by Vertebrata (3.01%) and Arachnida (2.18%). We counted 1156 plant pests (86.82%), of which 86.02% are Insecta. Orthoptera are the most frequent (45.72%). They are followed by Dermaptera (33.74%) and Coleoptera (18.44%). The present study highlighted the importance of plant pests consumed by the Cattle Egret (80.27% in 1998 and 86.82% in 2020), which are far more numerous and diverse than auxiliary prey and pollinators. This confirms the bird's status as a biological control agent in the lower Soummam valley. It is, therefore, worth pointing out that this species deserves to be protected.

Keywords: bubulcus ibis, diet, lower soummam valley, insect crop pests

Procedia PDF Downloads 23

Authors: Ariful Islam, Showkat Ahmad Lone

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Statistical distributions have long been employed in the assessment of semiconductor devices and product reliability. The power function-distribution is one of the most important distributions in the modern reliability practice and can be frequently preferred over mathematically more complex distributions, such as the Weibull and the lognormal, because of its simplicity. Moreover, it may exhibit a better fit for failure data and provide more appropriate information about reliability and hazard rates in some circumstances. This study deals with estimating information about failure times of items under step-stress partially accelerated life tests for competing risk based on adoptive type-I progressive hybrid censoring criteria. The life data of the units under test is assumed to follow Mukherjee-Islam distribution. The point and interval maximum-likelihood estimations are obtained for distribution parameters and tampering coefficient. The performances of the resulting estimators of the developed model parameters are evaluated and investigated by using a simulation algorithm.

Keywords: adoptive progressive hybrid censoring, competing risk, mukherjee-islam distribution, partially accelerated life testing, simulation study

Procedia PDF Downloads 330

Authors: Dharmendra Jariwala, Robin Christian

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Thermal exposure is a common problem in every manufacturing industry where heat is used in the manufacturing process. In developing countries like India, a lack of awareness regarding the proper work environmental condition is observed among workers. Improper planning of factory building, arrangement of machineries, ventilation system, etc. play a vital role in the rise of temperature within the manufacturing areas. Due to the uncontrolled thermal stress, workers may be subjected to various heat illnesses from mild disorder to heat stroke. Heat stress is responsible for the health risk and reduction in production. Wet Bulb Globe Temperature (WBGT) index and relative humidity are used to evaluate heat stress conditions. WBGT index is a weighted average of natural wet bulb temperature, globe temperature, dry bulb temperature, which are measured with standard instrument QuestTemp 36 area stress monitor. In this study textile processing units have been selected in the industrial estate in the Surat city. Based on the manufacturing process six locations were identified within the plant at which process was undertaken at 120°C to 180°C. These locations were jet dying machine area, stenter machine area, printing machine, looping machine area, washing area which generate process heat. Office area was also selected for comparision purpose as a sixth location. Present Study was conducted in the winter season and summer season for day and night shift. The results shows that average WBGT index was found above Threshold Limiting Value (TLV) during summer season for day and night shift in all three industries except office area. During summer season highest WBGT index of 32.8°C was found during day shift and 31.5°C was found during night shift at printing machine area. Also during winter season highest WBGT index of 30°C and 29.5°C was found at printing machine area during day shift and night shift respectively.

Keywords: relative humidity, textile industry, thermal stress, WBGT

Procedia PDF Downloads 157