Search results for: sequential confidence estimation

Authors: Suparman

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Piecewise polynomial regression model is very flexible model for modeling the data. If the piecewise polynomial regression model is matched against the data, its parameters are not generally known. This paper studies the parameter estimation problem of piecewise polynomial regression model. The method which is used to estimate the parameters of the piecewise polynomial regression model is Bayesian method. Unfortunately, the Bayes estimator cannot be found analytically. Reversible jump MCMC algorithm is proposed to solve this problem. Reversible jump MCMC algorithm generates the Markov chain that converges to the limit distribution of the posterior distribution of piecewise polynomial regression model parameter. The resulting Markov chain is used to calculate the Bayes estimator for the parameters of piecewise polynomial regression model.

Keywords: piecewise regression, bayesian, reversible jump MCMC, segmentation

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Authors: A. Giannakopoulos, S. B. Buckley

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Problem solving in any field is recognised as a prerequisite for any advancement in knowledge. For example in South Africa it is one of the seven critical outcomes of education together with critical thinking. As a systematic way to problem solving was initiated in mathematics by the great mathematician George Polya (the father of problem solving), more detailed and comprehensive ways in problem solving have been developed. This paper is based on the findings by the author and subsequent recommendations for further research in problem solving and critical thinking. Although the study was done in mathematics, there is no doubt by now in almost anyone’s mind that mathematics is involved to a greater or a lesser extent in all fields, from symbols, to variables, to equations, to logic, to critical thinking. Therefore it stands to reason that mathematical principles and learning cannot be divorced from any field. In management of knowledge situations, the types of problems are similar to mathematics problems varying from simple to analogical to complex; from well-structured to ill-structured problems. While simple problems could be solved by employees by adhering to prescribed sequential steps (the process), analogical and complex problems cannot be proceduralised and that diminishes the capacity of the organisation of knowledge creation and innovation. The low efficiency in some organisations and the low pass rates in mathematics prompted the author to view problem solving as a product. The authors argue that using mathematical approaches to knowledge management problem solving and treating problem solving as a product will empower the employee through further training to tackle analogical and complex problems. The question the authors asked was: If it is true that problem solving and critical thinking are indeed basic skills necessary for advancement of knowledge why is there so little literature of knowledge management (KM) about them and how they are connected and advance KM?This paper concludes with a conceptual model which is based on general accepted principles of knowledge acquisition (developing a learning organisation), knowledge creation, sharing, disseminating and storing thereof, the five pillars of knowledge management (KM). This model, also expands on Gray’s framework on KM practices and problem solving and opens the doors to a new approach to training employees in general and domain specific areas problems which can be adapted in any type of organisation.

Keywords: critical thinking, knowledge management, mathematics, problem solving

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Authors: Janusz Getta, Zhaoxi Pan

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Performance-based quality evaluation of database conceptual schemas is an important aspect of database design process. It is evident that different conceptual schemas provide different logical schemas and performance of user applications strongly depends on logical and physical database structures. This work presents the entire process of performance-based quality evaluation of conceptual schemas. First, we show format. Then, the paper proposes a new specification of object algebra for representation of conceptual level database applications. Transformation of conceptual schemas and expression of object algebra into implementation schema and implementation in a particular database system allows for precise estimation of the processing costs of database applications and as a consequence for precise evaluation of performance-based quality of conceptual schemas. Then we describe an experiment as a proof of concept for the evaluation procedure presented in the paper.

Keywords: conceptual schema, implementation schema, logical schema, object algebra, performance evaluation, query processing

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Authors: Louis Botha

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Since the presentation of South Africa’s inclusive education strategy in Education White Paper 6 in 2001, very little has been accomplished in terms of its implementation. The failure to achieve the goals set by this policy document is related to teachers lacking confidence and knowledge about how to enact inclusive education, as well as challenges of inflexible curricula, limited resources in overcrowded classrooms, and so forth. This paper presents a socio-cultural approach to addressing these challenges of implementing inclusive education in the South African context. It takes its departure from the view that inclusive education has been adequately theorized and conceptualized in terms of its philosophical and ethical principles, especially in South African policy and debates. What is missing, however, are carefully theorized, practically implementable research interventions which can address the concerns mentioned above. Drawing on socio-cultural principles of learning and development and on cultural-historical activity theory (CHAT) in particular, this paper argues for the use of formative interventions which introduce appropriately constructed mediational artifacts that have the potential to initiate inclusive practices and pedagogies within South African schools and classrooms. It makes use of Vygotsky’s concept of double stimulation to show how the proposed artifacts could instigate forms of transformative agency which promote the adoption of inclusive cultures of learning and teaching.

Keywords: cultural-historical activity theory, double stimulation, formative interventions, transformative agency

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Authors: Abul Hassan

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Present socio-economic context and women wellbeing in Bangladesh imposes lots of constraints on women’s involvement in income generating activities. Different studies showed that the implementation of World Bank structural adjustment policies have had mixed impacts on women and their wellbeing. By involving poor people specially women in Islamic microfinance programmes in Bangladesh are used as a tool to combat poverty. Women are specifically targeted by Islamic microfinance under the rural development scheme of Islami Bank Bangladesh that provide interest free loan to the women groups. The programme has a multiplier effect since women invest largely in their households. The aim of this research is twofold: firstly, it wanted to confirm or refute a positive link between Islamic microfinance and the socio-economic wellbeing of women in Bangladesh and secondly, to explore the context in which Islamic microfinance programs function in Bangladesh and the way their performance can be improved. Based on structured questionnaires’ survey, this study addressed two research questions: (1) What can be expected from the offer of Islamic microfinance on the welfare of recipients and (2) Under what conditions would such an offer be more beneficial. The main result of this study shows that increase in women’s income and assets played a very important role in enhancing women’s economic independence and sense of self-confidence. An important policy recommendation is that it is necessary to redirect Islamic microfinance towards diversified developmental activities that will contribute to the improvement, in the long run, of the wellbeing of the recipients.

Keywords: business model, Islamic microfinance, women’s wellbeing

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Authors: Amro Issam Hamed Attia Ramadan, Marco Zappatore, Pasquale Balena, Antonella Longo

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Considering the energetic crisis that is hitting Europe, it becomes more and more necessary to change the energy policies to depend less on fossil fuels and replace them with energy from renewable sources. This has triggered the urge to use clean energy not only to satisfy energy needs and fulfill the required consumption but also to decrease the danger of climatic changes due to harmful emissions. Many countries have already started creating energetic communities based on renewable energy sources. The first step to understanding energy needs in any place is to perfectly know the consumption. In this work, we aim to estimate electricity consumption for a municipality that makes up part of a rural area located in southern Italy using forecast models that allow for the estimation of electricity consumption for the next ten years, and we then apply the same model to the province where the municipality is located and estimate the future consumption for the same period to examine whether it is possible to start from the municipality level to reach the province level when creating energy communities.

Keywords: ARIMA, electricity consumption, forecasting models, time series

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Authors: Wu Yufeng, Gu Yifan, Wang Hengguang, Gongyu, Zuo Tieyong

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Indium is one the scarce resources which can be only used less than 30 years, and more than 70% of the indium is used for the production of the LCD. The benefit of recycling Indium from waste LCD is large. Take the LCD-TV for example, the yield of which was close to 90 million units in 2010. If it was available to recycle the indium effectively, the yield of the secondary-indium could reach up to 110 metric ton, which accounted for one third of the primary indium production in China. And compared with the dispersion and long process extraction of the primary indium resources, secondary indium concentrates in the waste LCD, the exploitation has great economic and environmental benefits. However, the potential benefits were indefinite, resulting in China’s government did not pay enough attention to the indium recycling industry. In our study, an estimation model was constructed to analyze the potential of the indium in the waste LCD. The different types of LCD were detected to find out the content of indium. Then, the potential of the indium in the waste LCD was estimated in China. Furthermore, the pollution emissions of the product process of the primary and secondary indium was analyzed respectively to calculate the economic and environmental benefits of the indium recycling from the waste LCD in China.

Keywords: indium recycling, waste liquid crystal displays, benefits, China

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Authors: Sunit Kumar Sahoo, Prakash Chandra Senapati

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The main drawback to design drug delivery systems with BCS class II drugs is their low bioavailabilty due to their inherent low permeability characteristics. So the present investigation aspire to develop a self-nanoemulsifying drug delivery system (SNEDDS) of BCS class II anti HIV drug efavirenz (EFZ) using mixtures of non-ionic surfactant mixtures with the main objective to improve the oral bioavailability of said drug. Results obtained from solubility studies of EFZ in various expients utilized for construction of the pseudo ternary phase diagram containing surfactant mixtures. Surfactants in 1:1 combination are used with different co-surfactants in different ratio to delineate the area of monophasic region of the pseudo ternary phase diagram. The formulations which offered positive results in different thermodynamic stability studies were considered for percentage transmittance and turbidity analysis. The various characterization studies like the TEM analysis of post diluted SNEDDS formulations r confirmed the size in nanometric range (below 50 nm) and FT-IR studies confirmed the intactness of the drug the in the preconcentrate. The in vitro dissolution profile of SNEDDS showed that 80% drug was released within 30 min in case of optimized SNEDDS while it was approximately 18.3 % in the case of plain drug powder.. The Pharmacokinetic study using rat model revealed a 2.63 fold increase in AUC (0-∞) in comparison to plain EFZ suspension. The designed delivery system illustrated the confidence in creating a formulation of EFZ with enhanced bioavailability for better HIV treatment.

Keywords: efavirenz, self-nanoemulsifying, surfactant mixture, bioavailability

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Authors: Samina Yasmin, Anzar Khaliq, Zareen Tabassum

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Acute power shortage in Pakistan requires an urgent attention to take preliminary steps to spread energy awareness at all levels. One such initiative is taken at Habib University (HU), Pakistan, through renewable energy course, one of the core offerings, where students are trained to investigate various aspects of renewable energy concepts. The course is offered to all freshmen enrolled at HU regardless of their academic backgrounds and degree programs. A four-credit modular course includes both theory and laboratory elements. Hands-on laboratories play an important role in science classes, particularly to enhance the motivation and deep understanding of energy science. A set of selected hands-on activities included in course introduced students to explore the latest developments in the field of renewable energy such as dye-sensitized solar cells, gas chromatography, global warming, climate change, fuel cell energy and power of biomass etc. These projects not only helped HU freshmen to build on energy fundamentals but also provided them greater confidence in investigating, questioning and experimenting with renewable energy related conceptions. A feedback survey arranged during and end of term revealed the effectiveness of the hands-on laboratory to enhance the common understanding of real world problems related to energy such as awareness of energy saving, the level of concern about global climate change, environmental pollution and science of energy behind the energy usage.

Keywords: biochemical approaches, energy curriculum, hands-on laboratory, renewable energy

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Authors: Azadeh Davachi

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Although there is a growing interest in Iranian female migration and gender roles, little attention has been paid to how Iranian migrant women in Australia access and sustain social networks, both locally and spatially dispersed over time. Social network theories have much to offer an analysis of migrant’s social ties and interpersonal relationships. Thus, it is important to note that social media are not only new communication channels in a migration network but also that they actively transform the nature of these networks and thereby facilitate migration for migrants. Drawing on that, this article will focus on Iranian women migrants and the use of social media in migration in Australia. Based on the case of main social networks such as Facebook and Instagram; this paper will investigate that how women migrants use these networks to facilitate the process of migration and integration. In addition, with the use of social networks, they could promote their home business and as a result become more engaged economically in Australian society. This paper will focus on three main Iranian pages in Instagram and Facebook, they will contend that compared to men, women are more active in these social networks. Consequently, as this article will discuss with the use of these social media Iranian migrant women can become more engaged and overcome post migration hardships, thus, gender plays a key role in using social media in migrant communities. Based on these findings from these social media pages, this paper will conclude that social media are transforming migration networks and thereby lowering the threshold for migration. It also will be demonstrated that these networks boost Iranian women’s confidence and lead them to become more visible in Iranian migrant communities comparing to men.

Keywords: integration, gender, migration, women migrants

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Authors: M. Akhlaque Ahmed, Maliha Afshan, Adeel Tahir

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Global and diffuse solar radiation studies have been carried out for the Capital city of Pakistan, Islamabad ( latitude 330 43’N and Longitude 370 71’E) to assess the solar potential of the area. The global and diffuse solar radiation were carried out using sunshine hour data for the above-mentioned area. Monthly total solar radiation is calculated through regression constants a and b through declination angle of the sun and sunshine hours and KT that is cloudiness index are used to calculate the diffuse solar radiation. Result obtained shows variation in the direct and diffuse component of solar radiation in summer and winter months for Islamabad. Diffuse solar radiation was found maximum in July, i.e., 32% whereas direct or beam radiation was found to be high in April to June, i.e., 73%. During July, August, and December, the sky was found cloudy. From the result, it appears that with the exception of monsoon month July and August the solar energy can be utilized very efficiently throughout the year in Islamabad.

Keywords: global radiation, Islamabad, diffuse radiation, sky condition, sunshine hour

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Authors: Seon Soon Choi

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The fatigue crack growth is stochastic because of the fatigue behavior having an uncertainty and a randomness. Therefore, it is necessary to determine the probability distribution of a grown crack size at a specific fatigue crack propagation life for maintenance of structure as well as reliability estimation. The essential purpose of this study is to present the good probability distribution fit for the grown crack size at a specified fatigue life in a rolled magnesium alloy under different specimen thickness conditions. Fatigue crack propagation experiments are carried out in laboratory air under three conditions of specimen thickness using AZ31 to investigate a stochastic crack growth behavior. The goodness-of-fit test for probability distribution of a grown crack size under different specimen thickness conditions is performed by Anderson-Darling test. The effect of a specimen thickness on variability of a grown crack size is also investigated.

Keywords: crack size, fatigue crack propagation, magnesium alloys, probability distribution, specimen thickness

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Authors: D.Mendes, J. Henriques, P. Carvalho, T. Rocha, S. Paredes, R. Cabiddu, R. Trimer, R. Mendes, A. Borghi-Silva, L. Kaminsky, E. Ashley, R. Arena, J. Myers

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The continued exploration of clinically relevant predictive models continues to be an important pursuit. Cardiorespiratory fitness (CRF) portends clinical vital information and as such its accurate prediction is of high importance. Therefore, the aim of the current study was to develop a data-driven model, based on computational intelligence techniques and, in particular, clustering approaches, to predict CRF. Two prediction models were implemented and compared: 1) the traditional Wasserman/Hansen Equations; and 2) an interpretable clustering approach. Data used for this analysis were from the 'FRIEND - Fitness Registry and the Importance of Exercise: The National Data Base'; in the present study a subset of 10690 apparently healthy individuals were utilized. The accuracy of the models was performed through the computation of sensitivity, specificity, and geometric mean values. The results show the superiority of the clustering approach in the accurate estimation of CRF (i.e., maximal oxygen consumption).

Keywords: cardiorespiratory fitness, data-driven models, knowledge extraction, machine learning

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Authors: Irfan Abdulrahman Sheth, Sohil Pothiawala

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Dermatomyositis is an idiopathic inflammatory myopathy, traditionally characterized by a progressive, symmetrical proximal muscle weakness and pathognomonic or characteristic cutaneous manifestations. We report a case of a 60-year old Chinese female who was referred from polyclinic for allergic rash over the body after applying hair dye 3 weeks ago. It was associated with puffiness of face, shortness of breath and hoarse voice since last 2 weeks with decrease effort tolerance. She also complained of dysphagia/ myalgia with progressive weakness of proximal muscles and palpitations. She denied chest pain, loss of appetite, weight loss, orthopnea or fever. She had stable vital signs and appeared cushingoid. She was noted to have rash over the scalp/ face and ecchymosis over the right arm with puffiness of face and periorbital oedema. There was symmetrical muscle weakness and other neurological examination was normal. Initial impression was of allergic reaction and underlying nephrotic syndrome and Cushing’s syndrome from TCM use. Diagnostic tests showed high Creatinine kinase (CK) of 1463 u/l, CK–MB of 18.7 ug/l and Troponin –T of 0.09 ug/l. The Full blood count and renal panel was normal. EMG showed inflammatory myositis. Patient was managed by rheumatologist and discharged on oral prednisolone with methotrexate/ ergocalciferol capsule and calcium carb, vitamin D tablets and outpatient follow up. In some patients, cutaneous disease exists in the absence of objective evidence of muscle inflammation. Management of dermatomyositis begins with careful investigation for the presence of muscle disease or of additional systemic involvement, particularly of the pulmonary, cardiac or gastrointestinal systems, and for the possibility of an accompanying malignancy. Muscle disease and systemic involvement can be refractory and may require multiple sequential therapeutic interventions or, at times, combinations of therapies. Thus, we want to highlight to the physicians that the cutaneous disease of dermatomyositis should not be confused with allergic reaction. It can be particularly challenging to diagnose. Early recognition aids appropriate management of this group of patients.

Keywords: dermatomyositis, myopathy, allergy, cutaneous disease

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Authors: Hyon I. Paek, Sang Rim Kim, Hyon A. Ryu

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In functional linear regression, one typical problem is to reduce dimension. Compared with multivariate linear regression, functional linear regression is regarded as an infinite-dimensional case, and the main task is to reduce dimensions of functional response and functional predictors. One common approach is to adapt functional principal component analysis (FPCA) on functional predictors and then use a few leading functional principal components (FPC) to predict the functional model. The leading FPCs estimated by the typical FPCA explain a major variation of the functional predictor, but these leading FPCs may not be mostly correlated with the functional response, so they may not be significant in the prediction for response. In this paper, we propose a supervised functional principal component analysis method for a functional response model with FPCs obtained by considering the correlation of the functional response. Our method would have a better prediction accuracy than the typical FPCA method.

Keywords: supervised, functional principal component analysis, functional response, functional linear regression

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Authors: Thuy Phan, Stephanie Luallin

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Inclusive education policies have demonstrated benefits for students with and without disabilities in the US. There are several laws that relate to inclusive education, such as 'No Child Left Behind', 'The Individuals with Disabilities Education Act'. However, the application of these inclusive education laws and policies vary per state and school district. Classroom teachers in an inclusive classroom often experience confusion as to how to apply these policies in order to create appropriate inclusive learning environments that meet the abilities and needs of their diverse student population. The study aims to investigate teachers’ perspective of their capacities to create an appropriate learning environment for their diverse student population including students with disabilities. Qualitative method is implemented in this study, using open-end interview questions to investigate teachers’ perspective of their capacities to create an appropriate inclusive learning environment for all students based on current inclusive education laws and district policies in the state of Colorado, USA. These findings may indicate a lack of confidence in teachers’ capacity to create appropriate inclusive learning environments based on laws and district policies; including challenges that classroom teachers may experience in creating inclusive learning environments. The purpose of this study is to examine the adequate preparation of classroom teachers in creating inclusive classrooms with the intent of determining implications for developing policies in inclusive education.

Keywords: educator’s capacity, inclusive education, inclusive learning environment, policy

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Authors: Saleh Alagla, Murya Habbash

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The paper investigates whether the board of directors plays a monitoring role or not in CEO compensation for the UK firms during the eve of the recent financial crisis, 2004-2008. The use of heteroscedastic and autocorrelated error consistent estimation of the panel data shows, surprisingly, that four board characteristics variables are found to play a significant role in increasing the level of CEO compensation. This insightful result would suggest evidence of the managerial power theory in general and the cronyism hypothesis in particular. Moreover, the interesting evidence supporting managerial power perspective is that CEO-Chair duality reduces long-term compensation while increasing short-term compensation, thus suggesting that CEOs are risk averse who prefer short-term compensation to long-term compensation. Finally, consistent with the agency perspective board size is found to increase all compensation variables as expected.

Keywords: corporate governance, CEO compensation, board of directors, internal governance mechanisms, agency theory, managerial power theory, cronyism hypothesis

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Authors: Nikita Katyal, Shaurya Uppal

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

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

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Authors: Lucija Pustahija, Christine Bandl, Wolfgang Kern, Christian Mitterer

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Concerning today´s ecological demands, producing reliable materials from sustainable resources is a continuously developing topic. Such an example is the production of carbon materials via pyrolysis of natural gases or biomass. The amazing properties of pyrolytic carbon are utilized in various fields, where in particular the application in building industry is a promising way towards the utilization of pyrolytic carbon and composites based on pyrolytic carbon. For many applications, surface modification of carbon is an important step in tailoring its properties. Therefore, in this paper, an investigation of different oxidation methods was performed to prepare the carbon surface before functionalizing it with organosilanes, which act as coupling agents for epoxy and polyurethane resins. Made in such a way, a building material based on carbon composites could be used as a lightweight, durable material that can be applied where water or air filtration / purification is needed. In this work, both wet and dry oxidation were investigated. Wet oxidation was first performed in solutions of nitric acid (at 120 °C and 150 °C) followed by oxidation in hydrogen peroxide (80 °C) for 3 and 6 h. Moreover, a hydrothermal method (under oxygen gas) in autoclaves was investigated. Dry oxidation was performed under plasma and corona discharges, using different power values to elaborate optimum conditions. Selected samples were then (in preliminary experiments) subjected to a silanization of the surface with amino and glycidoxy organosilanes. The functionalized surfaces were examined by X-ray photon spectroscopy and Fourier transform infrared spectroscopy spectroscopy, and by scanning electron microscopy. The results of wet and dry oxidation methods indicated that the creation of functionalities was influenced by temperature, the concentration of the reagents (and gases) and the duration of the treatment. Sequential oxidation in aq. HNO₃ and H₂O₂ results in a higher content of oxygen functionalities at lower concentrations of oxidizing agents, when compared to oxidizing the carbon with concentrated nitric acid. Plasma oxidation results in non-permanent functionalization on the carbon surface, by which it´s necessary to find adequate parameters of oxidation treatments that could enable longer stability of functionalities. Results of the functionalization of the carbon surfaces with organosilanes will be presented as well.

Keywords: building materials, dry oxidation, organosilanes, pyrolytic carbon, resins, surface functionalization, wet oxidation

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Authors: Rajvir Kaur, Jeewani Anupama Ginige

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

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

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Authors: K. Assis, K. P. Chong, A. S. Idris, C. M. Ho

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Oil palm or Elaeis guineensis is considered as the golden crop in Malaysia. But oil palm industry in this country is now facing with the most devastating disease called as Ganoderma Basal Stem Rot disease. The objective of this paper is to analyze the economic loss due to this disease. There were three commercial oil palm sites selected for collecting the required data for economic analysis. Yield parameter used to measure the loss was the total weight of fresh fruit bunch in six months. The predictors include disease severity, change in disease severity, number of infected neighbor palms, age of palm, planting generation, topography, and first order interaction variables. The estimation model of yield loss was identified by using backward elimination based regression method. Diagnostic checking was conducted on the residual of the best yield loss model. The value of mean absolute percentage error (MAPE) was used to measure the forecast performance of the model. The best yield loss model was then used to estimate the economic loss by using the current monthly price of fresh fruit bunch at mill gate.

Keywords: ganoderma, oil palm, regression model, yield loss, economic loss

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Authors: Yiyang Su, Jörg Neumann, Jan Wetzlich, Florian Thiel

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Smart grid is a term used to describe the next generation power grid. New challenges such as integration of renewable and decentralized energy sources, the requirement for continuous grid estimation and optimization, as well as the use of two-way flows of energy have been brought to the power gird. In order to achieve efficient, reliable, sustainable, as well as secure delivery of electric power more and more information and communication technologies are used for the monitoring and the control of power grids. Consequently, the need for cybersecurity is dramatically increased and has converged into several standards which will be presented here. These standards for the smart grid must be designed to satisfy both performance and reliability requirements. An in depth investigation of the effect of retrospectively embedded security in existing grids on it’s dynamic behavior is required. Therefore, a retrofitting plan for existing meters is offered, and it’s performance in a test low voltage microgrid is investigated. As a result of this, integration of security measures into measurement architectures of smart grids at the design phase is strongly recommended.

Keywords: cyber security, performance, protocols, security standards, smart grid

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Authors: M. Gangadharappa, M. Ravi Kumar, H. N. Reddappa

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The mechanical properties and morphological analysis of Al6061-Red mud particulate composites were investigated. The compositions of the composite include a matrix of Al6061 and the red mud particles of 53-75 micron size as reinforcement ranging from 0% to 12% at an interval of 2%. Stir casting technique was used to fabricate Al6061-Red mud composites. Density measurement, estimation of percentage porosity, tensile properties, fracture toughness, hardness value, impact energy, percentage elongation and percentage reduction in area. Further, the microstructures and SEM examinations were investigated to characterize the composites produced. The result shows that a uniform dispersion of the red mud particles along the grain boundaries of the Al6061 alloy. The tensile strength and hardness values increases with the addition of Red mud particles, but there is a slight decrease in the impact energy values, values of percentage elongation and percentage reduction in area as the reinforcement increases. From these results of investigation, we concluded that the red mud, an industrial waste can be used to enhance the properties of Al6061 alloy for engineering applications.

Keywords: Al6061, red mud, tensile strength, hardness and microstructures

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Authors: Friday Godwin Okibe, Elaoyi David Paul, Oladayo Thomas Ojekunle

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In this study, Nitrogen and Phosphorous co-doped Zinc Oxide (NPZ) was prepared through a solvent-free reaction. The NPZ was characterized by Scanning Electron Microscopy (SEM) and Fourier Transform Infrared (FTIR) spectroscopy. The photocatalytic activity of the catalyst was investigated by monitoring the degradation of para-nitrophenol (PNP) under visible light irradiation and the process was optimized using factorial design of experiment. The factors investigated were initial concentration of para-nitrophenol, catalyst loading, pH and irradiation time. The characterization results revealed a successful doping of ZnO by nitrogen and phosphorus and an improvement in the surface morphology of the catalyst. The photo-catalyst exhibited improved photocatalytic activity under visible light by 73.8%. The statistical analysis of the optimization result showed that the model terms were significant at 95% confidence level. Interactions plots revealed that irradiation time was the most significant factor affecting the degradation process. The cube plots of the interactions of the variables showed that an optimum degradation efficiency of 66.9% was achieved at 10mg/L initial PNP concentration, 0.5g catalyst loading, pH 7 and 150 minutes irradiation time.

Keywords: nitrogen and phosphorous co-doped Zno, p-nitrophenol, photocatalytic degradation, optimization, factorial design of experimental

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Authors: Shavindrie Cooray

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It is vital that students are supported in having balanced conversations about topics that might be controversial. This process is crucial to the development of critical thinking skills. This can be difficult to attain in e-learning environments, with some research finding students report a perceived loss in the quality of knowledge exchange and performance. This research investigated if Systems Theory could be applied to structure the discussion, improve information sharing, and reduce conflicts when students are working in online environments. This research involved 160 participants across four categories of student groups at a college in the Northeastern US. Each group was provided with a shared problem, and each group was expected to make a proposal for a solution. Two groups worked face-to-face; the first face to face group engaged with the problem and each other with no intervention from a facilitator; a second face to face group worked on the problem using Systems tools to facilitate problem structuring, group discussion, and decision-making. There were two types of virtual teams. The first virtual group also used Systems tools to facilitate problem structuring and group discussion. However, all interactions were conducted in a synchronous virtual environment. The second type of virtual team also met in real time but worked with no intervention. Findings from the study demonstrated that the teams (both virtual and face-to-face) using Systems tools shared more information with each other than the other teams; additionally, these teams reported an increased level of disagreement amongst their members, but also expressed more confidence and satisfaction with the experience and resulting decision compared to the other groups.

Keywords: e-learning, virtual teams, systems approach, conflicts

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Authors: Fabio Oettl, Sebastian Hoerbrand, Tobias Wittmeir, Johannes Schilp

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By combining the additive manufacturing (AM)- process with digital concepts, like the digital twin (DT) or the downsized and basing concept of the digital part file (DPF), the competitiveness of additive manufacturing is enhanced and new use cases like decentral production are enabled. But in literature, one can´t find any quantitative approach for valuing the usage of a DT or DPF in AM. Out of this fact, such an approach will be developed within this paper in order to further promote or dissuade the usage of these concepts. The focus is set on the production as an early lifecycle phase, which means that the AM-production process gets analyzed regarding the potential advantages of using DPF in AM. These advantages are transferred to a monetary value with this approach. By calculating the costs of the DPF, an overall monetary value is a result. Thereon a tool, based on a simulation environment is constructed, where the algorithms are transformed into a program. The results of applying this tool show that an overall value of 20,81 € for the DPF can be realized for one special use case. For the future application of the DPF there is the recommendation to integrate especially sustainable information because out of this, a higher value of the DPF can be expected.

Keywords: additive manufacturing, digital concept costs, digital part file, digital twin, monetary value estimation

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Authors: Lin Li, Farshad Amini

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The flipped classroom has been introduced to promote collaborative learning and higher-order learning objectives. In contrast to the traditional classroom, the flipped classroom has students watch prerecorded lecture videos before coming to class and then “class becomes the place to work through problems, advance concepts, and engage in collaborative learning”. In this paper, the active flipped learning combines flipped classroom with active learning that is to establish an active flipped learning (AFL) model, aiming to promote active learning, stress deep learning, encourage student engagement and highlight data-driven personalized learning. Because students have watched the lecture prior to class, contact hours can be devoted to problem-solving and gain a deeper understanding of the subject matter. The instructor is able to provide students with a wide range of learner-centered opportunities in class for greater mentoring and collaboration, increasing the possibility to engage students. Currently, little is known about the extent to which AFL improves engineering students’ performance. This paper presents the preliminary study on the core course of sophomore students in Engineering Mechanics. A series of survey and interviews have been conducted to compare students’ learning engagement, empowerment, self-efficacy, and satisfaction with the AFL. It was found that the AFL model taking advantage of advanced technology is a convenient and professional avenue for engineering students to strengthen their academic confidence and self-efficacy in the Engineering Mechanics by actively participating in learning and fostering their deep understanding of engineering statics and dynamics

Keywords: active learning, engineering mechanics, flipped classroom, performance

Procedia PDF Downloads 293

Authors: Ishapathik Das, Sumen Sen, N. Rao Chaganty, Pooja Sengupta

Abstract:

Dependent multivariate count data occur in several research studies. These data can be modeled by a multivariate Poisson or Negative binomial distribution constructed using copulas. However, when some of the counts are inflated, that is, the number of observations in some cells are much larger than other cells, then the copula based multivariate Poisson (or Negative binomial) distribution may not fit well and it is not an appropriate statistical model for the data. There is a need to modify or adjust the multivariate distribution to account for the inflated frequencies. In this article, we consider the situation where the frequencies of two cells are higher compared to the other cells, and develop a doubly inflated multivariate Poisson distribution function using multivariate Gaussian copula. We also discuss procedures for regression on covariates for the doubly inflated multivariate count data. For illustrating the proposed methodologies, we present a real data containing bivariate count observations with inflations in two cells. Several models and linear predictors with log link functions are considered, and we discuss maximum likelihood estimation to estimate unknown parameters of the models.

Keywords: copula, Gaussian copula, multivariate distributions, inflated distributios

Procedia PDF Downloads 156

Authors: Maaly Jarrah

Abstract:

In a study abroad context, students have the advantage of immersing themselves in the environment of the target language and being exposed to it. However, in and a stay home context, where English is not the mother tongue, students’ exposure to the second language is often times restricted to the classroom. Although language teachers are keen to develop inside class room activities and practices that increase the suitability of students to acquire a second language (Cook & Singleton, 2014), many would agree that class time is too limited to enhance students’ oral fluency skills. Consequently, creating opportunities outside the classroom for students to speak English is an effective strategy in compensating for students’ limited use of the L2. In an argument by Ortega (2012) external classroom activities have equal significance in enabling students learn English as a second language. The author further asserts that the activities provide a non-educational environment from which a student may feel free and comfortable to acquire new language skills. This study investigates the significance of outside classroom activities in promoting students’ oral proficiency. In addition, it reports on students’ perceptions of such activities. 15 participants from the American University of Kuwait took part in this study. Open-ended interviews were done to find out what the participants thought of these activities, and what they gained from them. Interview results show that students found outside classroom activities very effective in improving not only their oral fluency skills, but their confidence and critical thinking skills as well. The implications of this research study are for language practitioners and language programs in the EFL context to be aware of the benefits of incorporating outside classroom activities in language teaching.

Keywords: language teaching, oral fluency, outside classroom activities

Procedia PDF Downloads 459

Authors: Sakul Jariyachansit

Abstract:

The purposes of this research were to investigate and to compare the factors affecting the decision for Tourism in Thailand by ASEAN Tourists and among ASEAN community tourists. Samples in this research were 400 ASEAN Community Tourists who travel in Thailand at Suvarnabhumi Airport during November 2016 - February 2016. The researchers determined the sample size by using the formula Taro Yamane at 95% confidence level tolerances 0.05. The English questionnaire, research instrument, was distributed by convenience sampling, for gathering data. Descriptive statistics was applied to analyze percentages, mean and standard deviation and used for hypothesis testing. The statistical analysis by multiple regression analysis (Multiple Regression) was employed to prove the relationship hypotheses at the significant level of 0.01. The results showed that majority of the respondents indicated the factors affecting the decision for Tourism in Thailand by ASEAN Tourists, in general there were a moderate effects and the mean of each side is moderate. Transportation was the most influential factor for tourism in Thailand. Therefore, the mode of transport, information, infrastructure and personnel are very important to factor affecting decision making for tourism in Thailand by ASEAN tourists. From the hypothesis testing, it can be predicted that the decision for choosing Tourism in Thailand is at R2 = 0.449. The predictive equation is decision for choosing Tourism in Thailand = 1.195 (constant value) + 0.425 (tourist attraction) +0.217 (information received) and transportation factors, tourist attraction, information, human resource and infrastructure at the significant level of 0.01.

Keywords: factor, decision making, ASEAN tourists, tourism in Thailand

Procedia PDF Downloads 206