Search results for: statistics of sales of small wind turbines in the United States

Authors: A. Ashraff

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The increasing importance of the web as a medium for electronic and business transactions has served as a catalyst or rather a driving force for the introduction and implementation of recommender systems. Recommender Systems play a major role in processing and analyzing thousands of data rows or reviews and help humans make a purchase decision of a product or service. It also has the ability to predict whether a particular user would rate a product or service based on the user’s profile behavioral pattern. At present, Recommender Systems are being used extensively in every domain known to us. They are said to be ubiquitous. However, in the field of recruitment, it’s not being utilized exclusively. Recent statistics show an increase in staff turnover, which has negatively impacted the organization as well as the employee. The reasons being company culture, working flexibility (work from home opportunity), no learning advancements, and pay scale. Further investigations revealed that there are lacking guidance or support, which helps a job seeker find the company that will suit him best, and though there’s information available about companies, job seekers can’t read all the reviews by themselves and get an analytical decision. In this paper, we propose an approach to study the available review data on IT companies (score their reviews based on user review sentiments) and gather information on job seekers, which includes their Psychometric evaluations. Then presents the job seeker with useful information or rather outputs on which company is most suitable for the job seeker. The theoretical approach, Algorithmic approach and the importance of such a system will be discussed in this paper.

Keywords: psychometric tests, recommender systems, sentiment analysis, hybrid recommender systems

Procedia PDF Downloads 96

Authors: Mohamed M. Bumadian, D. James Gilmour

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Three bacterial species were isolated from the River Wye (Derbyshire, England) and identified using 16S rRNA gene sequencing as Serratia proteamaculans, Aeromonas hydrophila and Klebsiella pneumoniae. Respiration rates of the strains were measured in order to determine the metabolic activity under salt stress. The highest respiration rates of all three strains were found at 0.17 M and 0.5 M NaCl and then the respiration rate decreased with increasing concentrations of NaCl. In addition, the effect of increasing concentrations of NaCl on malate dehydrogenase activity was determined using cell-free extracts of the three strains. Malate dehydrogenase activity was stimulated at NaCl concentrations up to 0.5 M, and a small level of activity remained even at 3.5 M NaCl. The pH optimum of the malate dehydrogenase in cell-free extracts of all strains was higher than pH 7.5.

Keywords: fresh water, halotolerant pathogenic bacteria, 16S rRNA gene, cell-free extracts, respiration rates, malate dehydrogenase

Procedia PDF Downloads 450

Authors: I. Algul, G. Akgun, H. Kurtaran

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Dynamic analysis of composite doubly curved panels with variable thickness subjected to different pulse types using Generalized Differential Quadrature method (GDQ) is presented in this study. Panels with variable thickness are used in the construction of aerospace and marine industry. Giving variable thickness to panels can allow the designer to get optimum structural efficiency. For this reason, estimating the response of variable thickness panels is very important to design more reliable structures under dynamic loads. Dynamic equations for composite panels with variable thickness are obtained using virtual work principle. Partial derivatives in the equation of motion are expressed with GDQ and Newmark average acceleration scheme is used for temporal discretization. Several examples are used to highlight the effectiveness of the proposed method. Results are compared with finite element method. Effects of taper ratios, boundary conditions and loading type on the response of composite panel are investigated.

Keywords: differential quadrature method, doubly curved panels, laminated composite materials, small displacement

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Authors: Naduni Ranasinghe

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E-learning environments are getting more popular than any other due to the impact of COVID19. Even though e-learning is one of the best solutions for the teaching-learning process in the academic process, it’s not without major challenges. Nowadays, machine learning approaches are utilized in the analysis of how behavioral factors lead to better adoption and how they related to better performance of the students in eLearning environments. During the pandemic, we realized the academic process in the eLearning approach had a major issue, especially for the performance of the students. Therefore, an approach that investigates student behaviors in eLearning environments using a data-intensive machine learning approach is appreciated. A hybrid approach was used to understand how each previously told variables are related to the other. A more quantitative approach was used referred to literature to understand the weights of each factor for adoption and in terms of performance. The data set was collected from previously done research to help the training and testing process in ML. Special attention was made to incorporating different dimensionality of the data to understand the dependency levels of each. Five independent variables out of twelve variables were chosen based on their impact on the dependent variable, and by considering the descriptive statistics, out of three models developed (Random Forest classifier, SVM, and Decision tree classifier), random forest Classifier (Accuracy – 0.8542) gave the highest value for accuracy. Overall, this work met its goals of improving student performance by identifying students who are at-risk and dropout, emphasizing the necessity of using both static and dynamic data.

Keywords: academic performance prediction, e learning, learning analytics, machine learning, predictive model

Procedia PDF Downloads 139

Authors: Eric Asare, Jamie Evans, Mark Newton, Emiliano Bilotti

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Two types of filler shapes (sphere and flakes) and three different sizes are employed to study the size effect on PTC. The composite is prepared using a mini-extruder with high-density polyethylene (HDPE) as the matrix. A computer modelling is used to fit the experimental results. The percolation threshold decreases with decreasing filler size and this was observed for both the spherical particles as well as the flakes. This was caused by the decrease in interparticle distance with decreasing filler size. The 100 µm particles showed a larger PTC intensity compared to the 5 µm particles for the metal coated glass sphere and flake. The small particles have a large surface area and agglomeration and this makes it difficult for the conductive network to e disturbed. Increasing the filler content decreased the PTC intensity and this is due to an increase in the conductive network within the polymer matrix hence more energy is needed to disrupt the network.

Keywords: positive temperature coefficient (PTC) effect, conductive polymer composite (CPC), electrical conductivity

Procedia PDF Downloads 418

Authors: Neda Safari, Jacob Petersen-Perlman

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There are more than two million dams in the United States, and a considerable portion of them are either non-operational or approaching the end of their designed lifespan. However, this emerging trend is new, and the majority of dam sites have not undergone thorough research and assessments after their removal to determine the overall effectiveness of restoration initiatives, particularly in the case of large-scale dams that may significantly impact their surrounding areas. A crucial factor to consider is the lack of specific regulations pertaining to dam removal at the federal level. Consequently, other environmental regulations that were not originally designed with dam removal considerations are used to execute these projects. This can result in delays or challenges for dam removal initiatives. The process of removing dams is usually the most important first step to restore the ecological and biological health of the river, but often there is a lack of measurable indicators to assess if it has achieved its intended objectives. In addition, the majority of studies on dam removal are only short-term and focus on a particular measure of response. Therefore, it is essential to conduct extensive and continuous monitoring to analyze the river's response throughout every aspect. Our study is divided into two sections. The first section of my research will analyze the establishment and utilization of dam removal laws and regulations in the Condit Dam removal process. We will highlight the areas where the frameworks for policy and dam removal projects remain in need of improvement in order to facilitate successful dam removals in the future. In this part, We will review the policies and plans that affected the decision-making process to remove the Condit dam while also looking at how they impacted the physical changes to the river after the dam was removed. In the second section, we will look at the effects of the dam removal over a decade later and attempt to determine how the river's physical response has been impacted by this modification. Our study aims to investigate the Condit dam removal process and its impact on the ecological response of the river. We anticipate identifying areas for improvement in policies pertaining to dam removal projects and exploring ways to enhance them to ensure improved project outcomes in the future.

Keywords: dam removal, ecolocgical change, water related regulation, water resources

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Authors: Omar Ramzi Jasim, Jalal Sultan Ashour

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Production Planning or Master Production Schedule (MPS) is a key interface between marketing and manufacturing, since it links customer service directly to efficient use of production resources. Mismanagement of the MPS is considered as one of fundamental problems in operation and it can potentially lead to poor customer satisfaction. In this paper, a hybrid evolutionary algorithm (ICA-GA) is presented, which integrates the merits of both imperialist competitive algorithm (ICA) and genetic algorithm (GA) for solving multi-objective MPS problems. In the presented algorithm, the colonies in each empire has be represented a small population and communicate with each other using genetic operators. By testing on 5 production scenarios, the numerical results of ICA-GA algorithm show the efficiency and capabilities of the hybrid algorithm in finding the optimum solutions. The ICA-GA solutions yield the lower inventory level and keep customer satisfaction high and the required overtime is also lower, compared with results of GA and SA in all production scenarios.

Keywords: master production scheduling, genetic algorithm, imperialist competitive algorithm, hybrid algorithm

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Authors: Antonia Müller, Svend Reuse

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The Brexit referendum in June 2016 led to different publications analysing potential consequences for European and British insurance companies under the European Passport. This study addresses a research gap, regarding the measures taken by insurance companies based in the United Kingdom and thus on structural changes to the European insurance market by an innovative structured Solvency and Financial Condition Report content analysis. In scope are all insurance companies based in the United Kingdom, that fall under the Solvency II supervisory regime. The results show that the majority of British Solvency II insurance companies in scope, conducting cross-border business to the European Union, have applied and reported measures to be able to continue operating this cross-border business after Brexit. In addition, the study shows that 34 new insurance companies based in the European Union were established as a result of Brexit, indicating structural changes to the European insurance market.

Keywords: brexit, europe, insurance market, solvency and financial condition repot, structural changes

Procedia PDF Downloads 193

Authors: Hamid Reza Mahdipoor, Mehdi Bahrami, Mohammad Bodaghi, Seyed Ali Akbar Mansoori

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Nowadays, with stricter limitations to reduce emissions, considerable penalties are imposed if pollution limits are exceeded. Therefore, refineries, along with focusing on improving the quality of their products, are also focused on producing products with the least environmental impact. The duty of the sulfur recovery unit (SRU) is to convert H₂S gas coming from the upstream units to elemental sulfur and minimize the burning of sulfur compounds to SO₂. The Claus process is a common process for converting H₂S to sulfur, including a reaction furnace followed by catalytic reactors and sulfur condensers. In addition to a Claus section, SRUs usually consist of a tail gas treatment (TGT) section to decrease the concentration of SO₂ in the flue gas below the emission limits. To operate an SRU properly, the flow rate of combustion air to the reaction furnace must be adjusted so that the Claus reaction is performed according to stoichiometry. Accurate control of the air demand leads to an optimum recovery of sulfur during the flow and composition fluctuations in the acid gas feed. Therefore, the major control system in the SRU is the air demand control loop, which includes a feed-forward control system based on predetermined feed flow rates and a feed-back control system based on the signal from the tail gas online analyzer. The use of online analyzers requires compliance with the installation and operation instructions. Unfortunately, most of these analyzers in Iran are out of service for different reasons, like the low importance of environmental issues and a lack of access to after-sales services due to sanctions. In this paper, an SRU in Iran was simulated and calibrated using industrial experimental data. Afterward, the effect of the malfunction of the online analyzer on the performance of SRU was investigated using the calibrated simulation. The results showed that an increase in the SO₂ concentration in the tail gas led to an increase in the temperature of the reduction reactor in the TGT section. This increase in temperature caused the failure of TGT and increased the concentration of SO₂ from 750 ppm to 35,000 ppm. In addition, the lack of a control system for the adjustment of the combustion air caused further increases in SO₂ emissions. In some processes, the major variable cannot be controlled directly due to difficulty in measurement or a long delay in the sampling system. In these cases, a secondary variable, which can be measured more easily, is considered to be controlled. With the correct selection of this variable, the main variable is also controlled along with the secondary variable. This strategy for controlling a process system is referred to as inferential control" and is considered in this paper. Therefore, a sensitivity analysis was performed to investigate the sensitivity of other measurable parameters to input disturbances. The results revealed that the output temperature of the first Claus reactor could be used for inferential control of the combustion air. Applying this method to the operation led to maximizing the sulfur recovery in the Claus section.

Keywords: sulfur recovery, online analyzer, inferential control, SO₂ emission

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Authors: Kevin Worrall, Euan McGookin

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The use of optimization algorithms is common across a large number of diverse fields. This work presents the use of a hybrid optimization algorithm applied to a mobile robot tasked with carrying out a search of an unknown environment. The algorithm is then applied to the multiple robots case, which results in a reduction in the time taken to carry out the search. The hybrid algorithm is a Random Search Algorithm fused with a Tabu mechanism. The work shows that the algorithm locates the desired points in a quicker time than a brute force search. The Tabu Random algorithm is shown to work within a simulated environment using a validated mathematical model. The simulation was run using three different environments with varying numbers of targets. As an algorithm, the Tabu Random is small, clear and can be implemented with minimal resources. The power of the algorithm is the speed at which it locates points of interest and the robustness to the number of robots involved. The number of robots can vary with no changes to the algorithm resulting in a flexible algorithm.

Keywords: algorithms, control, multi-agent, search and rescue

Procedia PDF Downloads 227

Authors: Sergio Zabala-Vargas, Miguel Jiménez-Barrera, Luz VArgas-Sánchez

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In recent years, information related to project management in organizations has been increasing exponentially. Performance data, management statistics, indicator results have forced the collection, analysis, traceability, and dissemination of project managers to be essential. In this sense, there are current trends to facilitate efficient decision-making in emerging technology projects, such as: Machine Learning, Data Analytics, Data Mining, and Big Data. The latter is the most interesting in this project. This research is part of the thematic line Construction methods and project management. Many authors present the relevance that the use of emerging technologies, such as Big Data, has taken in recent years in project management in the construction sector. The main focus is the optimization of time, scope, budget, and in general mitigating risks. This research was developed in the northeastern region of Colombia-South America. The first phase was aimed at diagnosing the use of emerging technologies (Big-Data) in the construction sector. In Colombia, the construction sector represents more than 50% of the productive system, and more than 2 million people participate in this economic segment. The quantitative approach was used. A survey was applied to a sample of 91 companies in the construction sector. Preliminary results indicate that the use of Big Data and other emerging technologies is very low and also that there is interest in modernizing project management. There is evidence of a correlation between the interest in using new data management technologies and the incorporation of Building Information Modeling BIM. The next phase of the research will allow the generation of guidelines and strategies for the incorporation of technological tools in the construction sector in Colombia.

Keywords: big data, building information modeling, tecnology, project manamegent

Procedia PDF Downloads 119

Authors: Gizelle K. Vianna, Gustavo S. Oliveira, Gabriel V. Cunha

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The use of decision support systems in agriculture may help monitoring large fields of crops by automatically detecting the symptoms of foliage diseases. In our work, we designed and implemented a decision support system for small tomatoes producers. This work investigates ways to recognize the late blight disease from the analysis of digital images of tomatoes, using a pair of multilayer perceptron neural networks. The networks outputs are used to generate repainted tomato images in which the injuries on the plant are highlighted, and to calculate the damage level of each plant. Those levels are then used to construct a situation map of a farm where a cellular automata simulates the outbreak evolution over the fields. The simulator can test different pesticides actions, helping in the decision on when to start the spraying and in the analysis of losses and gains of each choice of action.

Keywords: artificial neural networks, cellular automata, decision support system, pattern recognition

Procedia PDF Downloads 436

Authors: Tal Remez, Or Litany, Alex Bronstein

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The pursuit of smaller pixel sizes at ever increasing resolution in digital image sensors is mainly driven by the stringent price and form-factor requirements of sensors and optics in the cellular phone market. Recently, Eric Fossum proposed a novel concept of an image sensor with dense sub-diffraction limit one-bit pixels (jots), which can be considered a digital emulation of silver halide photographic film. This idea has been recently embodied as the EPFL Gigavision camera. A major bottleneck in the design of such sensors is the image reconstruction process, producing a continuous high dynamic range image from oversampled binary measurements. The extreme quantization of the Poisson statistics is incompatible with the assumptions of most standard image processing and enhancement frameworks. The recently proposed maximum-likelihood (ML) approach addresses this difficulty, but suffers from image artifacts and has impractically high computational complexity. In this work, we study a variant of a sensor with binary threshold pixels and propose a reconstruction algorithm combining an ML data fitting term with a sparse synthesis prior. We also show an efficient hardware-friendly real-time approximation of this inverse operator. Promising results are shown on synthetic data as well as on HDR data emulated using multiple exposures of a regular CMOS sensor.

Keywords: binary pixels, maximum likelihood, neural networks, sparse coding

Procedia PDF Downloads 187

Authors: Surajj Sarode, G. P. Vadnere, G. Vidya Sagar

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Compression coating is one of the strategies for delivering drug to the colon based on Gastrointestinal PH and transit time concept. The main aim of these formulations to develop rapidly disintegrating Zaltoprofen core tablets compression-coated with a mixture of time-dependent hydrophilic swellable polymer HPMC K 15 and PH responsive soluble polymer Chitosan and Guar gum in different ratios. The effect of the proportion of HPMC, Chitosan and Guar gum in the coat on premature drug release in upper part (Stomach and small intestine) of GIT and the amount of drug release in colon target area was studied. The formulations are carried out by using Direct Compression method. Sodium starch Glycolate used for rapid disintegration. FTIR used for Drug-Polymer Interaction studies. The prepared tablets were evaluated for hardness, thickness, friability, in-vitro disintegration, in-Vitro dissolution and in-vitro kinetic study.

Keywords: zaltoprofen, chitosan, formulation, drug delivery

Procedia PDF Downloads 437

Authors: Maryam Ziaee

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This research proposes a new approach and provides an opportunity for manufacturing companies to produce large amounts of products that meet their prospective customers’ tastes, needs, and expectations and simultaneously enable manufacturers to increase their profit. Mass customization is the production of products or services to meet each individual customer’s desires to the greatest possible extent in high quantities and at reasonable prices. This process takes place at different levels such as the customization of goods’ design, assembly, sale, and delivery status, and classifies in several categories. The main focus of this study is on one class of mass customization, called optional customization, in which companies try to provide their customers with as many options as possible to customize their products. These options could range from the design phase to the manufacturing phase, or even methods of delivery. Mass customization values customers’ tastes, but it is only one side of clients’ satisfaction; on the other side is companies’ fast responsiveness delivery. It brings the concept of agility, which is the ability of a company to respond rapidly to changes in volatile markets in terms of volume and variety. Indeed, mass customization is not effectively feasible without integrating the concept of agility. To gain the customers’ satisfaction, the companies need to be quick in responding to their customers’ demands, thus highlighting the significance of agility. This research offers a different method that successfully integrates mass customization and fast production in manufacturing industries. This research is built upon the hypothesis that the success key to being agile in mass customization is to forecast demand, cooperate with suppliers, and control inventory. Therefore, the significance of the supply chain (SC) is more pertinent when it comes to this stage. Since SC behavior is dynamic and its behavior changes constantly, companies have to apply one of the predicting techniques to identify the changes associated with SC behavior to be able to respond properly to any unwelcome events. System dynamics utilized in this research is a simulation approach to provide a mathematical model among different variables to understand, control, and forecast SC behavior. The final stage is delayed differentiation, the production strategy considered in this research. In this approach, the main platform of products is produced and stocked and when the company receives an order from a customer, a specific customized feature is assigned to this platform and the customized products will be created. The main research question is to what extent applying system dynamics for the prediction of SC behavior improves the agility of mass customization. This research is built upon a qualitative approach to bring about richer, deeper, and more revealing results. The data is collected through interviews and is analyzed through NVivo software. This proposed model offers numerous benefits such as reduction in the number of product inventories and their storage costs, improvement in the resilience of companies’ responses to their clients’ needs and tastes, the increase of profits, and the optimization of productivity with the minimum level of lost sales.

Keywords: agility, manufacturing, resilience, supply chain

Procedia PDF Downloads 79

Authors: Yusuf Jundi Sado

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Changes in land use are mostly credited to human actions that result in negative impacts on biodiversity and ecosystem functions. This study aims to analyze the dynamics of land use and land cover changes for sustainable natural resources planning and management. Chilalo-Galama Mountain Range, Ethiopia. This study used Thematic Mapper 05 (TM) for 1986, 2001 and Landsat 8 (OLI) data 2017. Additionally, data from the Central Statistics Agency on human population growth were analyzed. Semi-Automatic classification plugin (SCP) in QGIS 3.2.3 software was used for image classification. Global positioning system, field observations and focus group discussions were used for ground verification. Land Use Land Cover (LU/LC) change analysis was using maximum likelihood supervised classification and changes were calculated for the 1986–2001 and the 2001–2017 and 1986-2017 periods. The results show that agricultural land increased from 27.85% (1986) to 44.43% and 51.32% in 2001 and 2017, respectively with the overall accuracies of 92% (1986), 90.36% (2001), and 88% (2017). On the other hand, forests decreased from 8.51% (1986) to 7.64 (2001) and 4.46% (2017), and grassland decreased from 37.47% (1986) to 15.22%, and 15.01% in 2001 and 2017, respectively. It indicates for the years 1986–2017 the largest area cover gain of agricultural land was obtained from grassland. The matrix also shows that shrubland gained land from agricultural land, afro-alpine, and forest land. Population dynamics is found to be one of the major driving forces for the LU/LU changes in the study area.

Keywords: Landsat, LU/LC change, Semi-Automatic classification plugin, population dynamics, Ethiopia

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Authors: Yan Ma

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Parents in China now are of great enthusiasm to outsource extracurricular lessons and activities to ensure their children’s English learning. This study draws on one year of ethnographic observations and interviews with parents and children in 6 families in Shaoxing, a small city in East China, to explore how parents in different social classes differ in their ideology and investment practice towards their children’s English education. Through comparative analysis, the study reveals though all the families acknowledge the importance of English and there are great similarities among families in the same social class, differences are distinct among those in different social classes with regard to how they perceived the importance and what measures they take. The results also reflect China’s sociocultural and socioeconomic factors that underlined the heated wave of English learning as well as the social, cultural and economic conditions of different families that exert a decisive influence on their children’s learning experience.

Keywords: family background, extracurricular English learning, language ideologies, language management

Procedia PDF Downloads 97

Authors: M. I. Abdelhamid, A. O. Ghallab, R. S. Ettouney, M. A. El-Rifai

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An optimization scheme based on COM server is suggested for communication between Genetic Algorithm (GA) toolbox of MATLAB and Aspen HYSYS. The structure and details of the proposed framework are discussed. The power of the developed scheme is illustrated by its application to the optimization of a recently developed natural gas liquefaction process in which Aspen HYSYS was used for minimization of the power consumption by optimizing the values of five operating variables. In this work, optimization by coupling between the GA in MATLAB and Aspen HYSYS model of the same process using the same five decision variables enabled improvements in power consumption by 3.3%, when 77% of the natural gas feed is liquefied. Also on inclusion of the flow rates of both nitrogen and carbon dioxide refrigerants as two additional decision variables, the power consumption decreased by 6.5% for a 78% liquefaction of the natural gas feed.

Keywords: stranded gas liquefaction, genetic algorithm, COM server, single nitrogen expansion, carbon dioxide pre-cooling

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Authors: Mohsen Negmeddin

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Throughout their history, ancient Egyptians had known several kinds and types of boats, which were made from two main kinds of materials, the local one, as the dried papyrus reeds and the local tree trunks, the imported one, as the boats which were made from Lebanon cedar tree trunks. A varied using of these boats, as the fish hunting small boats, the transportation and trade boats "Cargo Boats", as well as the ceremonial boats, and the warfare boats. The research is intending for the last one, the warfare boats and the river/maritime battles since the beginning of ancient Egyptian civilization at the pre-historic era up till the end of the second intermediate period, to reveal the kinds and types of those fighting ships before establishing the Egyptian navy at the beginning of the New Kingdome (1550-1770 B.C). Two methods will follow at this research, the mention of names and titles of these ships through the texts (ancient Egyptian language) resources, and the depiction of it at the scenes.

Keywords: the warfare boats, the maritime battles, the pre-historic era, the second intermediate period

Procedia PDF Downloads 265

Authors: Amirmozafar Benshams, Khatere Kashmari, Farzad Hatami, Mesbah Saybani

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Shape memory alloys with high capability of energy dissipation and large deformation bearing with return ability to their original shape without too much hysteresis strain have opened their place among the other damping systems as smart materials. Ninitol which is the most well-known and most used alloy material from the shape memory alloys family, has high resistance and fatigue and is coverage for large deformations. Shape memory effect and super-elasticity by shape alloys like Nitinol, are the reasons of the high power of these materials in energy depreciation. Thus, these materials are suitable for use in reciprocating dynamic loading conditions. The experiments results showed that Nitinol wires with small diameter have greater energy dissipation capability and by increase of diameter and thickness the damping capability and energy dissipation increase.

Keywords: shape memory alloys, shape memory effect, super elastic effect, nitinol, energy dissipation

Procedia PDF Downloads 496

Authors: Mulugeta Fola, Mengistu Ketema, Kumilachew Alamerie

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Watershed provides vast economic benefits within and beyond the management area of interest. But most watersheds in Ethiopia are increasingly facing the threats of degradation due to both natural and man-made causes. To reverse these problems, communities’ participation in sustainable management programs is among the necessary measures. Hence, this study assessed the households’ willingness to pay for watershed management practices through a contingent valuation study approach. Double bounded dichotomous choice with open-ended follow-up format was used to elicit the households’ willingness to pay. Based on data collected from 275 randomly selected households, descriptive statistics results indicated that most households (79.64%) were willing to pay for watershed management practices. A bivariate Probit model was employed to identify determinants of households’ willingness to pay and estimate mean willingness to pay. Its result shows that age, gender, income, livestock size, perception of watershed degradation, social position, and offered bids were important variables affecting willingness to pay for watershed management practices. The study also revealed that the mean willingness to pay for watershed management practices was calculated to be 58.41 Birr and 47.27 Birr per year from the double bounded and open-ended format, respectively. The study revealed that the aggregate welfare gains from watershed management practices were calculated to be 931581.09 Birr and 753909.23 Birr per year from double bounded dichotomous choice and open-ended format, respectively. Therefore, the policymakers should make households to pay for the services of watershed management practices in the study area.

Keywords: bivariate probit model, contingent valuation, watershed management practices, willingness to pay

Procedia PDF Downloads 207

Authors: Navneet Dabra, Baljinder Kaur, Lakhbir Singh, V. Annapu Reddy, R. Nath, Dae-Yong Jeong, Jasbir S. Hundal

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Nano-composite films of sodium nitrite (NaNO2): Starch with different proportions of NaNO2 and Starch have been prepared by drop cast technique. The ferroelectric hysteresis loops (P-V) have been traced using modified Sawyar-Tower circuit. The films containing equal proportions of NaNO2 and Starch exhibit optimized ferroelectric properties. The stability of the remanent polarization, Pr in the optimized nano-composite films exhibit improved stability over the pure NaNO2 films. The Atomic Force Microscopy (AFM) has been employed to investigate the surface morphology. AFM images clearly reveal the nano sized particles of NaNO2 dispersed in starch with small value of surface roughness.

Keywords: ferroelectricity, nano-composite films, Atomic Force Microscopy (AFM), nano composite film

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Authors: Karen Koellner, Nanette Seago, Jennifer Jacobs, Helen Garnier

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Although studies of teacher professional development (PD) are prevalent, surprisingly most have only produced incremental shifts in teachers’ learning and their impact on students. There is a critical need to understand what teachers take up and use in their classroom practice after attending PD and why we often do not see greater changes in learning and practice. This paper is based on a mixed methods efficacy study of the Learning and Teaching Geometry (LTG) video-based mathematics professional development materials. The extent to which the materials produce a beneficial impact on teachers’ mathematics knowledge, classroom practices, and their students’ knowledge in the domain of geometry through a group-randomized experimental design are considered. Included is a close-up examination of a small group of teachers to better understand their interpretations of the workshops and their classroom uptake. The participants included 103 secondary mathematics teachers serving grades 6-12 from two US states in different regions. Randomization was conducted at the school level, with 23 schools and 49 teachers assigned to the treatment group and 18 schools and 54 teachers assigned to the comparison group. The case study examination included twelve treatment teachers. PD workshops for treatment teachers began in Summer 2016. Nine full days of professional development were offered to teachers, beginning with the one-week institute (Summer 2016) and four days of PD throughout the academic year. The same facilitator-led all of the workshops, after completing a facilitator preparation process that included a multi-faceted assessment of fidelity. The overall impact of the LTG PD program was assessed from multiple sources: two teacher content assessments, two PD embedded assessments, pre-post-post videotaped classroom observations, and student assessments. Additional data were collected from the case study teachers including additional videotaped classroom observations and interviews. Repeated measures ANOVA analyses were used to detect patterns of change in the treatment teachers’ content knowledge before and after completion of the LTG PD, relative to the comparison group. No significant effects were found across the two groups of teachers on the two teacher content assessments. Teachers were rated on the quality of their mathematics instruction captured in videotaped classroom observations using the Math in Common Observation Protocol. On average, teachers who attended the LTG PD intervention improved their ability to engage students in mathematical reasoning and to provide accurate, coherent, and well-justified mathematical content. In addition, the LTG PD intervention and instruction that engaged students in mathematical practices both positively and significantly predicted greater student knowledge gains. Teacher knowledge was not a significant predictor. Twelve treatment teachers self-selected to serve as case study teachers to provide additional videotapes in which they felt they were using something from the PD they learned and experienced. Project staff analyzed the videos, compared them to previous videos and interviewed the teachers regarding their uptake of the PD related to content knowledge, pedagogical knowledge and resources used. The full paper will include the case study of Ana to illustrate the factors involved in what teachers take up and use from participating in the LTG PD.

Keywords: geometry, mathematics professional development, pedagogical content knowledge, teacher learning

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Authors: Benabdelaziz Soufyane

Abstract:

The process of developing the activity of small and medium-sized enterprises(SME), and increasing the entrepreneurial sense, is becoming at the current period as one of the main bets, where many countries around the world try to give it the great importance because of their positive role in improving the economic development indicators in these countries. As a result of the sequential changes that international economic environment lives, the biggest global economic entities has become threatened because of different secretions financial crises and economic disorders. For this lots of countries tended to search for a mechanism to help it for creating new jobs and to spur the economy in order to face the foreign competition, fot this, we find the process of creating innovative entrepreneurial activity comes at the forefront of solutions for the purpose of achieving that. For the purpose of highlighting the role of this process and its future in the economy, this study seeks to consolidate the innovation’s concept and innovative entrepreneurship, then the success’s conditions of these entrepreneurships, to conclude with recommendations , solutions and important results.

Keywords: entrepreneurship, innovation, performance, vigilance, modernity, technology, business incubators

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Authors: Md Y. Reja, Samuel D. Brody, Wesley E. Highfield, Galen D. Newman

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Historically, wetlands in the United States have been lost due to agriculture, anthropogenic activities, and rapid urbanization along the coast. Such losses of wetlands have resulted in high flooding risk for coastal communities over the period of time. In addition, alteration of wetlands via the Section 404 Clean Water Act permits can increase the flooding risk to future hurricane events, as the cumulative impact of this program is poorly understood and under-accounted. Further, recovery after hurricane events is acting as an encouragement for new development and reconstruction activities by converting wetlands under the wetland alteration permitting program. This study investigates the degree to which hurricane recovery activities in coastal communities are undermining the ability of these places to absorb the impacts of future storm events. Specifically, this work explores how and to what extent wetlands are being affected by the federal permitting program post-Hurricane Ike in 2008. Wetland alteration patterns are examined across three counties (Harris, Galveston, and Chambers County) along the Texas Gulf Coast over a 10-year time period, from 2004-2013 (five years before and after Hurricane Ike) by conducting descriptive spatial analyses. Results indicate that after Hurricane Ike, the number of permits substantially increased in Harris and Chambers County. The vast majority of individual and nationwide type permits were issued within the 100-year floodplain, storm surge zones, and areas damaged by Ike flooding, suggesting that recovery after the hurricane is compromising the ecological resiliency on which coastal communities depend. The authors expect that the findings of this study can increase awareness to policy makers and hazard mitigation planners regarding how to manage wetlands during a long-term recovery process to maintain their natural functions for future flood mitigation.

Keywords: ecological resiliency, Hurricane Ike, recovery, Section 404 Permitting, wetland alteration

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Authors: Ruedee Niyomrath, Somboon Sarasit, Chaisri Tharaswatpipat

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This research aims to study the potential of local waste material in quantity and quality. The potential for such local forms of waste material used as renewable energy for the production of processed agricultural products. The results of this study are useful to producers of agricultural products to use fuel that in local, reduce production costs, and conservation. The results showed that Samut Songkhram is a small province located in the central Thailand, sea area, and subdivided into 3 districts. This province has a population of 80 percent of farmers and agriculture with 50 percent of the area planted to coconut growing. Productivity of coconut help create value for the primacy of the province. Waste materials from coconut have quantity and quality potentials for processing biomass into charcoal as the renewable energy for the production of processed agricultural products.

Keywords: waste, renewable energy, producing of product, processed agricultural products

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Authors: Abhijit Trailokya, Kamlesh Patel

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Background: Hypertension is a common disease seen in clinical practice and is associated with high morbidity and mortality. Many patients require combination therapy for the management of hypertension. Objective: To evaluate co-morbidities, risk factors and management practices of hypertension in Indian population. Material and methods: A total of 1596 hypertensive adult patients received anti-hypertensive medications were studied in a cross-sectional, multi-centric, non-interventional, observational registry. Statistical analysis: Categories or nominal data was expressed as numbers with percentages. Continuous variables were analyzed by descriptive statistics using mean, SD, and range Chi square test was used for in between group comparison. Results: The study included 73.50% males and 26.50% females. Overweight (50.50%) and obesity (30.01%) was common in the hypertensive patients (n=903). A total of 54.76% patients had history of smoking. Alcohol use (33.08%), sedentary life style (32.96%) and history of tobacco chewing (17.92%) were the other lifestyle habits of hypertensive patients. Diabetes (36.03%) and dyslipidemia (39.79%) history was common in these patients. Family history of hypertension and diabetes was seen in 82.21% and 45.99% patients respectively. Most (89.16%) patients were treated with combination of antihypertensive agents. ARBs were the by far most commonly used agents (91.98%) followed by calcium channel blockers (68.23%) and diuretics (60.21%). ARB was the most (80.35%) preferred agent as monotherapy. ARB was also the most common agent as a component of dual therapy, four drug and five drug combinations. Conclusion: Most of the hypertensive patients need combination treatment with antihypertensive agents. ARBs are the most preferred agents as monotherapy for the management of hypertension. ARBs are also very commonly used as a component of combination therapy during hypertension management.

Keywords: antihypertensive, hypertension, management, ARB

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Authors: Ross Calvert, Colin Whittaker, Alison Raby, Alistair G. L. Borthwick, Ton S. van den Bremer

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Large concentrations of plastic have polluted the seas in the last half century, with harmful effects on marine wildlife and potentially to human health. Plastic pollution will have lasting effects because it is expected to take hundreds or thousands of years for plastic to decay in the ocean. The question arises how waves transport plastic in the ocean. The predominant motion induced by waves creates ellipsoid orbits. However, these orbits do not close, resulting in a drift. This is defined as Stokes drift. If a particle is infinitesimally small and the same density as water, it will behave exactly as the water does, i.e., as a purely Lagrangian tracer. However, as the particle grows in size or changes density, it will behave differently. The particle will then have its own inertia, the fluid will exert drag on the particle, because there is relative velocity, and it will rise or sink depending on the density and whether it is on the free surface. Previously, plastic pollution has all been considered to be purely Lagrangian. However, the steepness of waves in the ocean is small, normally about α = k₀a = 0.1 (where k₀ is the wavenumber and a is the wave amplitude), this means that the mean drift flows are of the order of ten times smaller than the oscillatory velocities (Stokes drift is proportional to steepness squared, whilst the oscillatory velocities are proportional to the steepness). Thus, the particle motion must have the forces of the full motion, oscillatory and mean flow, as well as a dynamic buoyancy term to account for the free surface, to determine whether inertia is important. To track the motion of a floating inertial particle under wave action requires the fluid velocities, which form the forcing, and the full equations of motion of a particle to be solved. Starting with the equation of motion of a sphere in unsteady flow with viscous drag. Terms can added then be added to the equation of motion to better model floating plastic: a dynamic buoyancy to model a particle floating on the free surface, quadratic drag for larger particles and a slope sliding term. Using perturbation methods to order the equation of motion into sequentially solvable parts allows a parametric equation for the transport of inertial finite-sized floating particles to be derived. This parametric equation can then be validated using numerical simulations of the equation of motion and flume experiments. This paper presents a parametric equation for the transport of inertial floating finite-size particles by ocean waves. The equation shows an increase in Stokes drift for larger, less dense particles. The equation has been validated using numerical solutions of the equation of motion and laboratory flume experiments. The difference in the particle transport equation and a purely Lagrangian tracer is illustrated using worlds maps of the induced transport. This parametric transport equation would allow ocean-scale numerical models to include inertial effects of floating plastic when predicting or tracing the transport of pollutants.

Keywords: perturbation methods, plastic pollution transport, Stokes drift, wave flume experiments, wave-induced mean flow

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Authors: Parvin Ghafarian, Mohammadreza Mohammadpur Panchah, Mehri Fallahi

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Synoptic patterns from surface up to tropopause are very important for forecasting the weather and atmospheric conditions. There are many tools to prepare and analyze these maps. Reanalysis data and the outputs of numerical weather prediction models, satellite images, meteorological radar, and weather station data are used in world forecasting centers to predict the weather. The forecasting extreme precipitating on the southern coast of the Caspian Sea (CS) is the main issue due to complex topography. Also, there are different types of climate in these areas. In this research, we used two reanalysis data such as ECMWF Reanalysis 5th Generation Description (ERA5) and National Centers for Environmental Prediction /National Center for Atmospheric Research (NCEP/NCAR) for verification of the numerical model. ERA5 is the latest version of ECMWF. The temporal resolution of ERA5 is hourly, and the NCEP/NCAR is every six hours. Some atmospheric parameters such as mean sea level pressure, geopotential height, relative humidity, wind speed and direction, sea surface temperature, etc. were selected and analyzed. Some different type of precipitation (rain and snow) was selected. The results showed that the NCEP/NCAR has more ability to demonstrate the intensity of the atmospheric system. The ERA5 is suitable for extract the value of parameters for specific point. Also, ERA5 is appropriate to analyze the snowfall events over CS (snow cover and snow depth). Sea surface temperature has the main role to generate instability over CS, especially when the cold air pass from the CS. Sea surface temperature of NCEP/NCAR product has low resolution near coast. However, both data were able to detect meteorological synoptic patterns that led to heavy rainfall over CS. However, due to the time lag, they are not suitable for forecast centers. The application of these two data is for research and verification of meteorological models. Finally, ERA5 has a better resolution, respect to NCEP/NCAR reanalysis data, but NCEP/NCAR data is available from 1948 and appropriate for long term research.

Keywords: synoptic patterns, heavy precipitation, reanalysis data, snow

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Authors: Yupaporn Areepong

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The main goal of this paper is to study Statistical Process Control (SPC) with Exponentially Weighted Moving Average (EWMA) control chart when observations are serially-correlated. The characteristic of control chart is Average Run Length (ARL) which is the average number of samples taken before an action signal is given. Ideally, an acceptable ARL of in-control process should be enough large, so-called (ARL0). Otherwise it should be small when the process is out-of-control, so-called Average of Delay Time (ARL1) or a mean of true alarm. We find explicit formulas of ARL for EWMA control chart for Seasonal Autoregressive and Moving Average processes (SARMA) with Exponential white noise. The results of ARL obtained from explicit formula and Integral equation are in good agreement. In particular, this formulas for evaluating (ARL0) and (ARL1) be able to get a set of optimal parameters which depend on smoothing parameter (λ) and width of control limit (H) for designing EWMA chart with minimum of (ARL1).

Keywords: average run length, optimal parameters, exponentially weighted moving average (EWMA), control chart

Procedia PDF Downloads 549