Search results for: mixed methods approach

Authors: M. Abou-Amouna, A. Radwan, L. Al-kuwari, A. Hammuda, K. Al-Khalifa

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There is growing concern over increasing incidences of road accidents and consequent loss of human life in Qatar. In light to the future planned event in Qatar, World Cup 2022; Qatar should put into consideration the future deaths caused by road accidents, and past trends should be considered to give a reasonable picture of what may happen in the future. Qatar roads should be arranged and paved in a way that accommodate high capacity of the population in that time, since then there will be a huge number of visitors from the world. Qatar should also consider the risk issues of road accidents raised in that period, and plan to maintain high level to safety strategies. According to the increase in the number of road accidents in Qatar from 1995 until 2012, an analysis of elements affecting and causing road accidents will be effectively studied. This paper aims to identify and criticize the factors that have high effect on causing road accidents in the state of Qatar, and predict the total number of road accidents in Qatar 2022. Alternative methods are discussed and the most applicable ones according to the previous researches are selected for further studies. The methods that satisfy the existing case in Qatar were the multiple linear regression model (MLR) and artificial neutral network (ANN). Those methods are analyzed and their findings are compared. We conclude that by using MLR the number of accidents in 2022 will become 355,226 accidents, and by using ANN 216,264 accidents. We conclude that MLR gave better results than ANN because the artificial neutral network doesn’t fit data with large range varieties.

Keywords: road safety, prediction, accident, model, Qatar

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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

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Authors: Ece Cigdem Mutlu, Burak Alakent

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Maintaining the quality of manufactured products at a desired level depends on the stability of process dispersion and location parameters and detection of perturbations in these parameters as promptly as possible. Shewhart control chart is the most widely used technique in statistical process monitoring to monitor the quality of products and control process mean and variability. In the application of Xbar control charts, sample standard deviation and sample mean are known to be the most efficient conventional estimators in determining process dispersion and location parameters, respectively, based on the assumption of independent and normally distributed datasets. On the other hand, there is no guarantee that the real-world data would be normally distributed. In the cases of estimated process parameters from Phase I data clouded with outliers, efficiency of traditional estimators is significantly reduced, and performance of Xbar charts are undesirably low, e.g. occasional outliers in the rational subgroups in Phase I data set may considerably affect the sample mean and standard deviation, resulting a serious delay in detection of inferior products in Phase II. For more efficient application of control charts, it is required to use robust estimators against contaminations, which may exist in Phase I. In the current study, we present a simple approach to construct robust Xbar control charts using average distance to the median, Qn-estimator of scale, M-estimator of scale with logistic psi-function in the estimation of process dispersion parameter, and Harrell-Davis qth quantile estimator, Hodge-Lehmann estimator and M-estimator of location with Huber psi-function and logistic psi-function in the estimation of process location parameter. Phase I efficiency of proposed estimators and Phase II performance of Xbar charts constructed from these estimators are compared with the conventional mean and standard deviation statistics both under normality and against diffuse-localized and symmetric-asymmetric contaminations using 50,000 Monte Carlo simulations on MATLAB. Consequently, it is found that robust estimators yield parameter estimates with higher efficiency against all types of contaminations, and Xbar charts constructed using robust estimators have higher power in detecting disturbances, compared to conventional methods. Additionally, utilizing individuals charts to screen outlier subgroups and employing different combination of dispersion and location estimators on subgroups and individual observations are found to improve the performance of Xbar charts.

Keywords: average run length, M-estimators, quality control, robust estimators

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Authors: M. Farhaoui, M. Derraz

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In the drinking water treatment processes, the optimization of the treatment is an issue of particular concern. In general, the process consists of many units as settling, coagulation, flocculation, sedimentation, filtration and disinfection. The optimization of the process consists of some measures to decrease the managing and monitoring expenses and improve the quality of the produced water. The objective of this study is to provide water treatment operators with methods and practices that enable to attain the most effective use of the facility and, in consequence, optimize the of the cubic meter price of the treated water. This paper proposes a review on optimization of drinking water treatment process by analyzing all of the water treatment units and gives some solutions in order to maximize the water treatment performances without compromising the water quality standards. Some solutions and methods are performed in the water treatment plant located in the middle of Morocco (Meknes).

Keywords: coagulation process, optimization, turbidity removal, water treatment

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Authors: Cruz Queen Allysa Rose, Bautista Joymeeh Anne, Lantoria Kaye, Barretto Katya Louise

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The study presents the preferences of passengers on the quality of service provided by the two airline check-in methods currently present in airports-traditional counter check-in and common-use self-service kiosks. Since a study has shown that airlines perceive self-service kiosks alone are sufficient enough to ensure adequate services and customer satisfaction, and in contrast, agents and passengers stated that it alone is not enough and that human interaction is essential. In reference with former studies that established opposing ideas about the choice of the more favorable airline check-in method to employ, it is the purpose of this study to present a recommendation that shall somehow fill-in the gap between the conflicting ideas by means of comparing the perceived quality of service through the RATER model. Furthermore, this study discusses the major competencies present in each method which are supported by the theories–FIRO Theory of Needs upholding the importance of inclusion, control and affection, and the Queueing Theory which points out the discipline of passengers and the length of the queue line as important factors affecting quality service. The findings of the study were based on the data gathered by the researchers from selected Thomasian third year and fourth year college students currently enrolled in the first semester of the academic year 2014-2015, who have already experienced both airline check-in methods through the implication of a stratified probability sampling. The statistical treatments applied in order to interpret the data were mean, frequency, standard deviation, t-test, logistic regression and chi-square test. The final point of the study revealed that there is a greater effect in passenger preference concerning the satisfaction experienced in common-use self-service kiosks in comparison with the application of the traditional counter check-in.

Keywords: traditional counter check-in, common-use self-service Kiosks, airline check-in methods

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Authors: Charline David, Alexandre Blondin Massé, Arnaud Zinflou

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In 2016, Clements, Hurn, and Li proposed a multiple equation time series approach for the short-term load forecasting, reporting an average mean absolute percentage error (MAPE) of 1.36% on an 11-years dataset for the Queensland region in Australia. We present an adaptation of their model to the electrical power load consumption for the whole Quebec province in Canada. More precisely, we take into account two additional meteorological variables — cloudiness and wind speed — on top of temperature, as well as the use of multiple meteorological measurements taken at different locations on the territory. We also consider other minor improvements. Our final model shows an average MAPE score of 1:79% over an 8-years dataset.

Keywords: short-term load forecasting, special days, time series, multiple equations, parallelization, clustering

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Authors: Luís Felipe da Cunha Mendonça

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Normally, rural roads do not have any type of coating, and when they have any coating, they have a high maintenance cost due to the characteristics of natural materials. The Steel Aggregate has specific technical characteristics, which considerably reduce the maintenance costs of rural roads with the execution of the Primary Coating. For use as a primary coating, it must be mixed with clay due to the physical-chemical properties of the material. The application is mainly in the Primary Coating of rural roads due to the cementitious property in the presence of water, offering greater resistance to wear caused by traffic and consequently a longer useful life of the coating. The Steel Aggregate executed on rural roads has reduced particulate emissions and offers normal traffic in any weather condition, as well as creating sustainability. Contribute to the quality of life of communities through improvements in the conditions of rural and urban unpaved roads. Leading to substantial savings in maintenance. Because the durability, if applied correctly, is about 3 years, but if annual monitoring is carried out, it can be extended for more than 5 years.

Keywords: steel slag, co-product, primary coating, steel aggregate

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Authors: Ashish Dhamaniya, Satish Chandra

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Speed and traffic volume data are collected on different sections of four lane and six lane roads in three metropolitan cities in India. Speed data are analyzed to fit the statistical distribution to individual vehicle speed data and all vehicles speed data. It is noted that speed data of individual vehicle generally follows a normal distribution but speed data of all vehicle combined at a section of urban road may or may not follow the normal distribution depending upon the composition of traffic stream. A new term Speed Spread Ratio (SSR) is introduced in this paper which is the ratio of difference in 85^th and 50^th percentile speed to the difference in 50^th and 15^th percentile speed. If SSR is unity then speed data are truly normally distributed. It is noted that on six lane urban roads, speed data follow a normal distribution only when SSR is in the range of 0.86 – 1.11. The range of SSR is validated on four lane roads also.

Keywords: normal distribution, percentile speed, speed spread ratio, traffic volume

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Authors: S. Athiralakshmi, B.E. Bhojaraja, U. Pruthviraj

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In agriculture, remote sensing is applied for monitoring of plant development, evaluating of physiological processes and growth conditions. Especially valuable are the spatio-temporal aspects of the remotely sensed data in detecting crop state differences and stress situations. In this study, hyperion imagery is used for classifying arecanut crops based on their age so that these maps can be used in yield estimation of crops, irrigation purposes, applying fertilizers etc. Traditional hard classifiers assigns the mixed pixels to the dominant classes. The proposed method uses a sub pixel level classifier called linear spectral unmixing available in ENVI software. It provides the relative abundance of surface materials and the context within a pixel that may be a potential solution to effectively identifying the land-cover distribution. Validation is done referring to field spectra collected using spectroradiometer and the ground control points obtained from GPS.

Keywords: FLAASH, Hyperspectral remote sensing, Linear Spectral Unmixing, Spectral Angle Mapper Classifier.

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Authors: Lamphong Volady

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The primary purpose of this study was to explore the traditional cuisine (local food) of Luangprabang Province in line with the Lao PDR’s One District One Product Policy. Another purpose of the study was to examine channels used to present local food, reasons to preserve and promote local food, as well as local food preservation and promotion strategies. It also aimed at testing correlation hypotheses whether there is a statistically significant relationship between enjoyment of having local food and willingness to promote local cuisines becoming international cuisines, attractiveness to consume local food, preservation and promotion of local food problems, and local people’s occupations. The Convergent Parallel Mixed Methods were employed in this study. The results of the study showed that several local cuisines were found to be local food of Luangprabang Province, namely Jeow Bon (Chilli dipping suace), Or Lam or aw lahm (stew buffalo skin, herbs, Mai sakaan), Kai Pan (River Weed Dry), Tam Mak Houng Luangprabang (Papaya Salad), Nang (Yam Buffalo Skin Dry), Sai Oor (Sausage), Laap Sin Koay Sai Mar-Keua Pao (Beef Salad with Roasted Eggplants), Orm Born (Taro leaves Stew), Oor Nor Mai (Bamboo Shoot Sausage), Jeow Nam Poo (Pickled Crab Chillies), Mok Dok Kae (steaming or roasting a Dok Kae Wrapp), Nor Sa Wan, Kao Noom Kee Noo, Kao Noom Ba Bin. It also depicted that YouTube, Facebook, and TikTok were multiple social channels or platforms which were found to be used to introduce traditional food as well as television, smartphone, word of mouth, Lao food fairs and other provincial events. The study also found that local food should be preserved and promoted since traditional food is not only ancestral, ancient, traditional, and local cuisines, but it is also wisdom, unique, and national cuisine. The study also found that people feel attracted to consuming local food because local food is delicious, unique, clean, nutritious, non-contaminated and natural. The study showed that lack of funds to produce local food, inadequate draw materials, lack material to store products, insufficient place to produce and lack of related organizations engagement were found to be problems for preserving and promoting traditional food. Finally, the result of the study revealed that there is a statistically significant weak relationship between enjoyment of having local food and willingness to promote local cuisines becoming international cuisines (R²= 4.5%), (p-value <0.001). There is a statistically significant moderate relationship between enjoyment of having local food and attractiveness to consume local food (R²= 7.8%), (p-value <0.001). However, there is a statistically insignificant relationship between enjoyment of having local food and preservation and promotion of local food problems (R²= 1.8%), (p-value = 0.086). It was found that there is a statistically insignificant relationship between enjoyment of having local food and local people’s occupations (R²= 0.0%), (p-value = 0.929).

Keywords: local food, preservation, promotion, traditional food, cuisines

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Authors: E Tolufase

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The demand, high costs and health implications of using energy derived from hydrocarbon compound have necessitated the continuous search for alternative source of energy. The World energy market is facing some challenges viz: depletion of fossil fuel reserves, population explosion, lack of energy security, economic and urbanization growth and also, in Nigeria some rural areas still depend largely on wood, charcoal, kerosene, petrol among others, as the sources of their energy. To overcome these short falls in energy supply and demand, as well as taking into consideration the risks from global climate change due to effect of greenhouse gas emissions and other pollutants from fossil fuels’ combustion, brought a lot of attention on efficiently harnessing the renewable energy sources. A very promising among the renewable energy resources for a clean energy technology for power production, vehicle and domestic usage is biogas. Therefore, optimization of biogas yield and quality is imperative. Hence, this study investigated yield and quality of biogas using low cost bio-digester and combination of various feed stocks referred to as co-digestion. Batch/Discontinuous Bio-digester type was used because it was cheap, easy, plausible and appropriate for different substrates used to get the desired results. Three substrates were used; cow dung, chicken droppings and lemon grass digested in five separate 21 litre digesters, A, B, C, D, and E and the gas collection system was designed using locally available materials. For single digestion we had; cow dung, chicken droppings, lemon grass, in Bio-digesters A, B, and C respectively, the co-digested three substrates in different mixed ratio 7:1:2 in digester D and E in ratio 5:3:2. The respective feed-stocks materials were collected locally, digested and analyzed in accordance with standard procedures. They were pre-fermented for a period of 10 days before being introduced into the digesters. They were digested for a retention period of 28 days, the physiochemical parameters namely; pressure, temperature, pH, volume of the gas collector system and volume of biogas produced were all closely monitored and recorded daily. The values of pH and temperature ranged 6.0 - 8.0, and 220C- 350C respectively. For the single substrate, bio-digester A(Cow dung only) produced biogas of total volume 0.1607m3(average volume of 0.0054m3 daily),while B (Chicken droppings ) produced 0.1722m3 (average of 0.0057m3 daily) and C (lemon grass) produced 0.1035m3 (average of 0.0035m3 daily). For the co-digested substrates in bio-digester D the total biogas produced was 0.2007m³ (average volume of 0.0067m³ daily) and bio-digester E produced 0.1991m³ (average volume of 0.0066m³ daily) It’s obvious from the results, that combining different substrates gave higher yields than when a singular feed stock was used and also mixing ratio played some roles in the yield improvement. Bio-digesters D and E contained the same substrates but mixed with different ratios, but higher yield was noticed in D with mixing ratio of 7:1:2 than in E with ratio 5:3:2.Therefore, co-digestion of substrates and mixing proportions are important factors for biogas production optimization.

Keywords: anaerobic, batch, biogas, biodigester, digestion, fermentation, optimization

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Authors: Thomas Odaker, Dieter Kranzlmueller, Jens Volkert

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We present an approach to triangle mesh simplification designed to be executed on the GPU. We use a quadric error metric to calculate an error value for each vertex of the mesh and order all vertices based on this value. This step is followed by the parallel removal of a number of vertices with the lowest calculated error values. To allow for the parallel removal of multiple vertices we use a set of per-vertex boundaries that prevent mesh foldovers even when simplification operations are performed on neighbouring vertices. We execute multiple iterations of the calculation of the vertex errors, ordering of the error values and removal of vertices until either a desired number of vertices remains in the mesh or a minimum error value is reached. This parallel approach is used to speed up the simplification process while maintaining mesh topology and avoiding foldovers at every step of the simplification.

Keywords: computer graphics, half edge collapse, mesh simplification, precomputed simplification, topology preserving

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Authors: Ebtesam. E. Ateia, L. M. Salah, A. H. El-Bassuony

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The aim of the presented study was the possibility of developing a nanosized material with enhanced structural properties that was suitable for many applications. Nanostructure ferrite of composition Ni0.5 Zn0.5 Cr0.1 Fe1.9 O4 were prepared by sol–gel, co-precipitation, citrate-gel, flash and oxalate precursor methods. The Structural and micro structural analysis of the investigated samples were carried out. It was observed that the lattice parameter of cubic spinel was constant, and the positions of both tetrahedral and the octahedral bands had a fixed position. The values of the lattice parameter had a significant role in determining the stoichiometric cation distribution of the composition.The average crystalline sizes of the investigated samples were from 16.4 to 69 nm. Discussion was made on the basis of a comparison of average crystallite size of the investigated samples, indicating that the co-precipitation method was the the effective one in producing small crystallite sized samples.

Keywords: chemical preparation, ferrite, grain size, nanocomposites, sol-gel

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Authors: Yongqi Dong, Zuo Zhang, Rui Fu, Li Li

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The records generated by taxicabs which are equipped with GPS devices is of vital importance for studying human mobility behavior, however, here we are focusing on taxi drivers' operation strategies between workdays and weekends temporally and spatially. We identify a group of valuable characteristics through large scale drivers' behavior in a complex metropolis environment. Based on the daily operations of 31,000 taxi drivers in New York City, we classify drivers into top, ordinary and low-income groups according to their monthly working load, daily income, daily ranking and the variance of the daily rank. Then, we apply big data analysis and visualization methods to compare the different characteristics among top, ordinary and low income drivers in selecting of working time, working area as well as strategies between workdays and weekends. The results verify that top drivers do have special operation tactics to help themselves serve more passengers, travel faster thus make more money per unit time. This research provides new possibilities for fully utilizing the information obtained from urban taxicab data for estimating human behavior, which is not only very useful for individual taxicab driver but also to those policy-makers in city authorities.

Keywords: big data, operation strategies, comparison, revenue, temporal, spatial

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Authors: Snezana Mugosa, Zoran Todorovic, Zoran Bukumiric, Ivan Radosavljevic, Natasa Djordjevic

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Introduction: Various studies have shown that the frequency of clopidogrel resistance ranges from 4-40%. The aim of this study was to provide in depth analysis of genetic and non-genetic factors that influence clopidogrel resistance in cardiology patients. Methods: We have conducted a prospective study in 200 hospitalized patients hospitalized at Cardiology Centre of the Clinical Centre of Montenegro. CYP2C19 genetic testing was conducted, and the PREDICT score was calculated in 102 out of 200 patients treated with clopidogrel in order to determine the influence of genetic and non-genetic factors on outcomes of interest. Adverse cardiovascular events and adverse reactions to clopidogrel were assessed during 12 months follow up period. Results: PREDICT score and CYP2C19 enzymatic activity were found to be statistically significant predictors of expressing lack of therapeutic efficacy of clopidogrel by multivariate logistic regression, without multicollinearity or interaction between the predictors (p = 0.002 and 0.009, respectively). Conclusions: Pharmacogenetics analyses that were done in the Montenegrin population of patients for the first time suggest that these analyses can predict patient response to the certain therapy. Stepwise approach could be used in assessing the clopidogrel resistance in cardiology patients, combining the PREDICT score, platelet aggregation test, and genetic testing for CYP2C19 polymorphism.

Keywords: clopidogrel, pharmacogenetics, pharmacotherapy, PREDICT score

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Authors: Mohammadreza Akbari, Pooya Soleimani Besheli, Reza Khalili, Davood Domiri Danji

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In this conference, our aims are accuracy, capabilities and power at solving of the complicated non-linear partial differential. Our purpose is to enhance the ability to solve the mentioned nonlinear differential equations at basic science and engineering field and similar issues with a simple and innovative approach. As we know most of engineering system behavior in practical are nonlinear process (especially basic science and engineering field, etc.) and analytical solving (no numeric) these problems are difficult, complex, and sometimes impossible like (Fluids and Gas wave, these problems can't solve with numeric method, because of no have boundary condition) accordingly in this symposium we are going to exposure an innovative approach which we have named it Akbari-Ganji's Method or AGM in engineering, that can solve sets of coupled nonlinear differential equations (ODE, PDE) with high accuracy and simple solution and so this issue will emerge after comparing the achieved solutions by Numerical method (Runge-Kutta 4th). Eventually, AGM method will be proved that could be created huge evolution for researchers, professors and students in whole over the world, because of AGM coding system, so by using this software we can analytically solve all complicated linear and nonlinear partial differential equations, with help of that there is no difficulty for solving all nonlinear differential equations. Advantages and ability of this method (AGM) as follow: (a) Non-linear Differential equations (ODE, PDE) are directly solvable by this method. (b) In this method (AGM), most of the time, without any dimensionless procedure, we can solve equation(s) by any boundary or initial condition number. (c) AGM method always is convergent in boundary or initial condition. (d) Parameters of exponential, Trigonometric and Logarithmic of the existent in the non-linear differential equation with AGM method no needs Taylor expand which are caused high solve precision. (e) AGM method is very flexible in the coding system, and can solve easily varieties of the non-linear differential equation at high acceptable accuracy. (f) One of the important advantages of this method is analytical solving with high accuracy such as partial differential equation in vibration in solids, waves in water and gas, with minimum initial and boundary condition capable to solve problem. (g) It is very important to present a general and simple approach for solving most problems of the differential equations with high non-linearity in engineering sciences especially at civil engineering, and compare output with numerical method (Runge-Kutta 4th) and Exact solutions.

Keywords: new approach, AGM, sets of coupled nonlinear differential equation, exact solutions, numerical

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Authors: Po-Fang Hsu, Chiching Wei

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In this paper, we present a novel neural graph matching approach applied to document comparison. Document comparison is a common task in the legal and financial industries. In some cases, the most important differences may be the addition or omission of words, sentences, clauses, or paragraphs. However, it is a challenging task without recording or tracing the whole edited process. Under many temporal uncertainties, we explore the potentiality of our approach to proximate the accurate comparison to make sure which element blocks have a relation of edition with others. In the beginning, we apply a document layout analysis that combines traditional and modern technics to segment layouts in blocks of various types appropriately. Then we transform this issue into a problem of layout graph matching with textual awareness. Regarding graph matching, it is a long-studied problem with a broad range of applications. However, different from previous works focusing on visual images or structural layout, we also bring textual features into our model for adapting this domain. Specifically, based on the electronic document, we introduce an encoder to deal with the visual presentation decoding from PDF. Additionally, because the modifications can cause the inconsistency of document layout analysis between modified documents and the blocks can be merged and split, Sinkhorn divergence is adopted in our neural graph approach, which tries to overcome both these issues with many-to-many block matching. We demonstrate this on two categories of layouts, as follows., legal agreement and scientific articles, collected from our real-case datasets.

Keywords: document comparison, graph matching, graph neural network, modification similarity, multi-modal

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Authors: A. M. Byrne, E. Bonfiglio, C. Rigby, N. Edelstyn

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Introduction: Neuromarketing employs numerous methodologies when investigating products and advertisement effectiveness. Electroencephalography (EEG), a non-invasive measure of electrical activity from the brain, is commonly used in neuromarketing. EEG data can be considered using time-frequency (TF) analysis, where changes in the frequency of brainwaves are calculated to infer participant’s mental states, or event-related potential (ERP) analysis, where changes in amplitude are observed in direct response to a stimulus. This presentation discusses the findings of a systematic review of EEG measures in neuromarketing. A systematic review summarises evidence on a research question, using explicit measures to identify, select, and critically appraise relevant research papers. Thissystematic review identifies which EEG measures are the most robust predictor of customer preference and purchase intention. Methods: Search terms identified174 papers that used EEG in combination with marketing-related stimuli. Publications were excluded if they were written in a language other than English or were not published as journal articles (e.g., book chapters). The review investigated which TF effect (e.g., theta-band power) and ERP component (e.g., N400) most consistently reflected preference and purchase intention. Machine-learning prediction was also investigated, along with the use of EEG combined with physiological measures such as eye-tracking. Results: Frontal alpha asymmetry was the most reliable TF signal, where an increase in activity over the left side of the frontal lobe indexed a positive response to marketing stimuli, while an increase in activity over the right side indexed a negative response. The late positive potential, a positive amplitude increase around 600 ms after stimulus presentation, was the most reliable ERP component, reflecting the conscious emotional evaluation of marketing stimuli. However, each measure showed mixed results when related to preference and purchase behaviour. Predictive accuracy was greatly improved through machine-learning algorithms such as deep neural networks, especially when combined with eye-tracking or facial expression analyses. Discussion: This systematic review provides a novel catalogue of the most effective use of each EEG measure commonly used in neuromarketing. Exciting findings to emerge are the identification of the frontal alpha asymmetry and late positive potential as markers of preferential responses to marketing stimuli. Predictive accuracy using machine-learning algorithms achieved predictive accuracies as high as 97%, and future research should therefore focus on machine-learning prediction when using EEG measures in neuromarketing.

Keywords: EEG, ERP, neuromarketing, machine-learning, systematic review, time-frequency

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Authors: Louiza C. Duncker, Duarte Gonçalves

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Wildlife crime is a complex problem with many interconnected facets, which are generally responded to in parts or fragments in efforts to “break down” the complexity into manageable components. However, fragmentation increases complexity as coherence and cooperation become diluted. A whole-of-society approach has been developed towards finding a common goal and integrated approach to preventing wildlife crime. As part of this development, research was conducted in rural communities adjacent to conservation areas in South Africa to define and comprehend the challenges faced by them, and to understand their perceptions of wildlife crime. The results of the research showed that the perceptions of community members varied - most were in favor of conservation and of protecting rhinos, only if they derive adequate benefit from it. Regardless of gender, income level, education level, or access to services, conservation was perceived to be good and bad by the same people. Even though people in the communities are poor, a willingness to stop rhino poaching does exist amongst them, but their perception of parks not caring about people triggered an attitude of not being willing to stop, prevent or report poaching. Understanding the nuances, the history, the interests and values of community members, and the drivers behind poaching mind-sets (intrinsic or driven by transnational organized crime) is imperative to create sustainable and resilient communities on multiple levels that make a substantial positive impact on people’s lives, but also conserve wildlife for posterity.

Keywords: community perceptions, conservation, rhino poaching, whole-of-society approach, wildlife crime

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Authors: Christine K. Fulmer

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Social work education is competency based in nature. There is an expectation that graduates of social work programs throughout the world are to be prepared to practice at a level of competence, which is beneficial to both the well-being of individuals and community. Experiential learning is one way to prepare students for competent practice. The use of Problem-Based Learning (PBL) is a form experiential education that has been successful in a number of disciplines to bridge the gap between the theoretical concepts in the classroom to the real world. PBL aligns with the constructivist theoretical approach to learning, which emphasizes the integration of new knowledge with the beliefs students already hold. In addition, the basic tenants of PBL correspond well with the practice behaviors associated with social work practice including multi-disciplinary collaboration and critical thinking. This paper makes an argument for utilizing PBL in social work education.

Keywords: social work education, problem-based learning, pedagogy, experiential learning, constructivist theoretical approach

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Authors: Bastien Batardière, Joon Kwon

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For finite-sum optimization, variance-reduced gradient methods (VR) compute at each iteration the gradient of a single function (or of a mini-batch), and yet achieve faster convergence than SGD thanks to a carefully crafted lower-variance stochastic gradient estimator that reuses past gradients. Another important line of research of the past decade in continuous optimization is the adaptive algorithms such as AdaGrad, that dynamically adjust the (possibly coordinate-wise) learning rate to past gradients and thereby adapt to the geometry of the objective function. Variants such as RMSprop and Adam demonstrate outstanding practical performance that have contributed to the success of deep learning. In this work, we present AdaLVR, which combines the AdaGrad algorithm with loopless variance-reduced gradient estimators such as SAGA or L-SVRG that benefits from a straightforward construction and a streamlined analysis. We assess that AdaLVR inherits both good convergence properties from VR methods and the adaptive nature of AdaGrad: in the case of L-smooth convex functions we establish a gradient complexity of O(n + (L + √ nL)/ε) without prior knowledge of L. Numerical experiments demonstrate the superiority of AdaLVR over state-of-the-art methods. Moreover, we empirically show that the RMSprop and Adam algorithm combined with variance-reduced gradients estimators achieve even faster convergence.

Keywords: convex optimization, variance reduction, adaptive algorithms, loopless

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Authors: Hong Seung Kim, Chang Hoi Kim, Lili Yue

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Single-phase, high band gap energy Zn0.5Mg0.5O films were grown under oxygen pressure, using pulse laser deposition with a Zn0.5Mg0.5O target. Structural characterization studies revealed that the crystal structures of the ZnX-1MgXO films could be controlled via changes in the oxygen pressure. TEM analysis showed that the thickness of the deposited Zn1-xMgxO thin films was 50–75 nm. As the oxygen pressure increased, we found that one axis of the crystals did not show a very significant increase in the crystallization compared with that observed at low oxygen pressure. The X-ray diffraction peak intensity for the hexagonal-ZnMgO (002) plane increased relative to that for the cubic-ZnMgO (111) plane. The corresponding c-axis of the h-ZnMgO lattice constant increased from 5.141 to 5.148 Å, and the a-axis of the c-ZnMgO lattice constant decreased from 4.255 to 4.250 Å. EDX analysis showed that the Mg content in the mixed-phase ZnMgO films decreased significantly, from 54.25 to 46.96 at.%. As the oxygen pressure was increased from 100 to 150 mTorr, the absorption edge red-shifted from 3.96 to 3.81 eV; however, a film grown at the highest oxygen pressure tested here (200 mTorr).

Keywords: MgO, UV LED, ZnMgO, ZnO

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Authors: Hanaa Farouk Saleh

Abstract:

The main purposes of this study are to develop a scale that reflects emerging theoretical understandings of new media credibility, based on the evolution of credibility studies in western researches, identification of the determinants of credibility in the media and its components by comparing traditional and new media credibility scales and building accumulative scale to test new media credibility. This approach was built on western researches using conceptualizations of media credibility, which focuses on four principal components: Source (journalist), message (article), medium (newspaper, radio, TV, web, etc.), and organization (owner of the medium), and adding user and cultural context as key components to assess new media credibility in particular. This study’s value lies in its contribution to the conceptualization and development of new media credibility through the creation of a theoretical measurement tool. Future studies should explore this scale to test new media credibility, which represents a promising new approach in the efforts to define and measure credibility of all media types.

Keywords: credibility scale, media credibility components, new media credibility scale, scale development

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Authors: Cheryl Leggon

Abstract:

Although women in the aggregate are earning more doctorates in science and engineering from U.S. institutions, they continue to concentrate in some fields--e.g., biology--and underrepresented in others--e.g., engineering. Traditionally, most studies of women doctorate recipients in the sciences (including the social, behavioral and economic sciences) or engineering do not report their findings by demographic subgroups. This study extends the literature on these topics by using an intersectional approach to examine decadal trends. Intersectionality suggests that race, gender, and nation are not separate mutually exclusive entities whose impacts are summative, but rather as a confluence of synergistic factors that shape complex social inequities. Drawing on critical aspects of the intersectionality approach is particularly well suited for a more fine-grained analysis of the representation of women doctorate recipients in science and engineering. The implications of the findings are discussed in terms of policies and evidence-based programmatic strategies for enhancing women’s participation in fields in which they are especially underrepresented.

Keywords: doctorates, engineering, science, women

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Authors: Asnawi Mohd Busrah, Au Mau Teng, Tan Chin Hooi, Lau Chee Chong

Abstract:

This paper describes value based planning (VBP) methodology incorporating risk assessment as an enhanced and more practical approach to evaluate distribution network projects in Peninsular Malaysia. Assessment indicators associated with economics, performance and risks are formulated to evaluate distribution projects to quantify their benefits against investment. The developed methodology is implemented in a web-based software customized to capture investment and network data, compute assessment indicators and rank the proposed projects according to their benefits. Value based planning approach addresses economic factors in the power distribution planning assessment, so as to minimize cost solution to the power utility while at the same time provide maximum benefits to customers.

Keywords: value based planning, distribution network, value of loss load (VoLL), energy not served (ENS)

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Authors: Jaroslav Masek, Juraj Camaj, Eva Nedeliakova

Abstract:

The aim of optimization of store management is not only designing the situation of store management itself including its equipment, technology and operation. In optimization of store management we need to consider also synchronizing of technological, transport, store and service operations throughout the whole process of logistic chain in such a way that a natural flow of material from provider to consumer will be achieved the shortest possible way, in the shortest possible time in requested quality and quantity and with minimum costs. The paper deals with the application of the queuing theory for optimization of warehouse processes. The first part refers to common information about the problematic of warehousing and using mathematical methods for logistics chains optimization. The second part refers to preparing a model of a warehouse within queuing theory. The conclusion of the paper includes two examples of using queuing theory in praxis.

Keywords: queuing theory, logistics system, mathematical methods, warehouse optimization

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Authors: Abder-Rahman Ali, Adélaïde Albouy-Kissi, Manuel Grand-Brochier, Viviane Ladan-Marcus, Christine Hoeffl, Claude Marcus, Antoine Vacavant, Jean-Yves Boire

Abstract:

In this paper, we present a new segmentation approach for focal liver lesions in contrast enhanced ultrasound imaging. This approach, based on a two-cluster Fuzzy C-Means methodology, considers type-II fuzzy sets to handle uncertainty due to the image modality (presence of speckle noise, low contrast, etc.), and to calculate the optimum inter-cluster threshold. Fine boundaries are detected by a local recursive merging of ambiguous pixels. The method has been tested on a representative database. Compared to both Otsu and type-I Fuzzy C-Means techniques, the proposed method significantly reduces the segmentation errors.

Keywords: defuzzification, fuzzy clustering, image segmentation, type-II fuzzy sets

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Authors: K. E. Ch. Vidyasagar, M. Moghavvemi, T. S. S. T. Prabhat

Abstract:

Epilepsy is a global problem, and with seizures eluding even the smartest of diagnoses a requirement for automatic detection of the same using electroencephalogram (EEG) would have a huge impact in diagnosis of the disorder. Among a multitude of methods for automatic epilepsy detection, one should find the best method out, based on accuracy, for classification. This paper reasons out, and rationalizes, the best methods for classification. Accuracy is based on the classifier, and thus this paper discusses classifiers like quadratic discriminant analysis (QDA), classification and regression tree (CART), support vector machine (SVM), naive Bayes classifier (NBC), linear discriminant analysis (LDA), K-nearest neighbor (KNN) and artificial neural networks (ANN). Results show that ANN is the most accurate of all the above stated classifiers with 97.7% accuracy, 97.25% specificity and 98.28% sensitivity in its merit. This is followed closely by SVM with 1% variation in result. These results would certainly help researchers choose the best classifier for detection of epilepsy.

Keywords: classification, seizure, KNN, SVM, LDA, ANN, epilepsy

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Authors: Ganesh Dattatraya Saratale, Min Kyu Oh

Abstract:

Rice straw is one of the most abundant lignocellulosic waste materials and its annual production is about 731 Mt in the world. This study treats the subject of effective utilization of this waste biomass for biofuels production. We have showed a comparative assessment of numerous pretreatment strategies for rice straw, comprising of major physical, chemical and physicochemical methods. Among the different methods employed for pretreatment alkaline pretreatment in combination with sodium chlorite/acetic acid delignification found efficient pretreatment with significant improvement in the enzymatic digestibility of rice straw. A cellulase dose of 20 filter paper units (FPU) released a maximum 63.21 g/L of reducing sugar with 94.45% hydrolysis yield and 64.64% glucose yield from rice straw, respectively. The effects of different pretreatment methods on biomass structure and complexity were investigated by FTIR, XRD and SEM analytical techniques. Finally the enzymatic hydrolysate of rice straw was used for ethanol production using developed Saccharomyces cerevisiae SR8. The developed yeast strain enabled efficient fermentation of xylose and glucose and produced higher ethanol production. Thus development of bioethanol production from lignocellulosic waste biomass is generic, applicable methodology and have great implication for using ‘green raw materials’ and producing ‘green products’ much needed today.

Keywords: rice straw, pretreatment, enzymatic hydrolysis, FPU, Saccharomyces cerevisiae SR8, ethanol fermentation

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Authors: Komal Rathore, Kiesha Pierre, Kyle Cogswell, Aaron Driscoll, Andres Tejada Martinez, Gita Iranipour, Luke Mulford, Aydin Sunol

Abstract:

Modeling of Biological Wastewater Treatment Plants requires several parameters for kinetic rate expressions, thermo-physical properties, and hydrodynamic behavior. The kinetics and associated mechanisms become complex due to several biological processes taking place in wastewater treatment plants at varying times and spatial scales. A dynamic process model that incorporated the complex model for activated sludge kinetics was developed using the BioWin software platform for an Advanced Wastewater Treatment Plant in Valrico, Florida. Due to the extensive number of tunable parameters, an experimental design was employed for judicious selection of the most influential parameter sets and their bounds. The model was tuned using both the influent and effluent plant data to reconcile and rectify the forecasted results from the BioWin Model. Amount of mixed liquor suspended solids in the oxidation ditch, aeration rates and recycle rates were adjusted accordingly. The experimental analysis and plant SCADA data were used to predict influent wastewater rates and composition profiles as a function of time for extended periods. The lumped dynamic model development process was coupled with Computational Fluid Dynamics (CFD) modeling of the key units such as oxidation ditches in the plant. Several CFD models that incorporate the nitrification-denitrification kinetics, as well as, hydrodynamics was developed and being tested using ANSYS Fluent software platform. These realistic and verified models developed using BioWin and ANSYS were used to plan beforehand the operating policies and control strategies for the biological wastewater plant accordingly that further allows regulatory compliance at minimum operational cost. These models, with a little bit of tuning, can be used for other biological wastewater treatment plants as well. The BioWin model mimics the existing performance of the Valrico Plant which allowed the operators and engineers to predict effluent behavior and take control actions to meet the discharge limits of the plant. Also, with the help of this model, we were able to find out the key kinetic and stoichiometric parameters which are significantly more important for modeling of biological wastewater treatment plants. One of the other important findings from this model were the effects of mixed liquor suspended solids and recycle ratios on the effluent concentration of various parameters such as total nitrogen, ammonia, nitrate, nitrite, etc. The ANSYS model allowed the abstraction of information such as the formation of dead zones increases through the length of the oxidation ditches as compared to near the aerators. These profiles were also very useful in studying the behavior of mixing patterns, effect of aerator speed, and use of baffles which in turn helps in optimizing the plant performance.

Keywords: computational fluid dynamics, flow-sheet simulation, kinetic modeling, process dynamics

Procedia PDF Downloads 210