Search results for: WEKA data mining tool

Authors: Pawel Twardowski, Tadeusz Chwalczuk, Szymon Wojciechowski

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Inconel 718 is a material characterized by the unique mechanical properties, high temperature strength, high thermal conductivity and the corrosion resistance. However, these features affect the low machinability of this material, which is usually manifested by the intense tool wear and low surface finish. Therefore, this paper is focused on the evaluation of surface roughness during hybrid machining of Inconel 718. The primary aim of the study was to determine the relations between the vibrations generated during hybrid turning and the formed surface roughness. Moreover, the comparison of tested machining techniques in terms of vibrations, tool wear and surface roughness has been made. The conducted tests included the face turning of Inconel 718 with laser assistance in the range of variable cutting speeds. The surface roughness was inspected with the application of stylus profile meter and accelerations of vibrations were measured with the use of three-component piezoelectric accelerometer. The carried out research shows that application of laser assisted machining can contribute to the reduction of surface roughness and cutting vibrations, in comparison to conventional turning. Moreover, the obtained results enable the selection of effective cutting speed allowing the improvement of surface finish and cutting dynamics.

Keywords: hybrid machining, nickel alloys, surface roughness, turning, vibrations

Procedia PDF Downloads 324

Authors: Ademuyiwa Agbonyin, Stamatis Zoras, Mohammad Zandi

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This paper investigates the extent to which building energy modelling can be informed based on preliminary information provided by infrared thermography using a thermal imaging camera in a walkthrough audit. The case-study building is the Sheffield Cathedral, built in the early 1400s. Based on an informative qualitative report generated from the thermal images taken at the site, the regions showing significant heat loss are input into a computer model of the cathedral within the integrated environmental solution (IES) virtual environment software which performs an energy simulation to determine quantitative heat losses through the building envelope. Building data such as material thermal properties and building plans are provided by the architects, Thomas Ford and Partners Ltd. The results of the modelling revealed the portions of the building with the highest heat loss and these aligned with those suggested by the thermal camera. Retrofit options for the building are also considered, however, may not see implementation due to a desire to conserve the architectural heritage of the building. Results show that thermal imaging in a walk-through audit serves as a useful guide for the energy modelling process. Hand calculations were also performed to serve as a 'control' to estimate losses, providing a second set of data points of comparison.

Keywords: historic buildings, energy retrofit, thermal comfort, software modelling, energy modelling

Procedia PDF Downloads 170

Authors: Babatunde Akeem Lawal

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In any organization, the primary aim is to maximize profit, but the major challenges facing them is the increase in cost of operation because of this there is increase in cost of production that could lead to inevitable cost control and cost reduction scheme which make it difficult for most organizations to operate at the cost efficient frontier. The study aims to critically examine and evaluate the application of cost control and cost reduction in organization performance and also to review budget as an effective tool of cost control and cost reduction. A descriptive survey research was adopted. A total number of 40 respondent retrieved were used for the study. The analysis of data collected was undertaken by applying appropriate statistical tools. Regression analysis was used to test the hypothesis with the use of SPSS. Based on the findings; it was evident that cost control has a positive impact on organizational performance and also the style of management has a positive impact on organizational performance.

Keywords: organization, cost reduction, cost control, performance, budget, profit

Procedia PDF Downloads 603

Authors: Luciana Marrone

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Natural dyes are a great resource for today's artists and designers providing endless possibilities for design and sustainability. This research and development project focuses on the idea of making these dyeing or painting methodologies reach the widest possible range of students. The main objective is to inform and train, free of charge, teachers and students from different academic institutions, at different levels, kindergarten, primary, secondary, tertiary and university. In this research and dissemination project, in the first instance, institutions from Argentina, Chile, Uruguay, Mexico, Spain, Italy, Colombia, Paraguay, Venezuela, Brazil and Australia joined the project, reaching the grassroots of education from the very beginning. Natural dyes will become part of everyday life for more people, achieving their own colors for art, textiles or any other application. The knowledge of the techniques and resources of the student a fundamental tool, sustainable and opens endless possibilities even in places or homes with few economic resources, thus achieving that natural dyes are not only part of the world of designers but also that they are incorporated from the basics and can thus become a resource applicable in different areas even in places with few economic or development possibilities.

Keywords: art, education, natural dyes, sustainability, textile design.

Procedia PDF Downloads 85

Authors: Dammar Bahadur Adhikari

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Mathematics teaching begins with human civilization. The rular used to choose mathematician as prime adviser in many tribes and country. Mathematics was powerful tool for understanding economial situation and strength of rular. In ancient Nepal teaching of mathematics starts with informal education provided by religious leaders there after in modern education system seems to follow the world’s educational system. The aim of this paper is to present a brief historical background of the Nepalese mathematicians up to nineteenth century and highlight the transformation in mathematical science in the line with modern world. Secondary data and formal papers and informal publications were studied to explore the present situation of education. The study concluded that there is remarcable change in quality of education and there are sufficient human powers in the mathematical sciences in Nepal.

Keywords: human development, mathematics, Nepal, science, traditional

Procedia PDF Downloads 387

Authors: Jerry Q. Cheng

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Currently, in analyzing large-scale recurrent event data, there are many challenges such as memory limitations, unscalable computing time, etc. In this research, a divide-and-conquer method is proposed using parametric frailty models. Specifically, the data is randomly divided into many subsets, and the maximum likelihood estimator from each individual data set is obtained. Then a weighted method is proposed to combine these individual estimators as the final estimator. It is shown that this divide-and-conquer estimator is asymptotically equivalent to the estimator based on the full data. Simulation studies are conducted to demonstrate the performance of this proposed method. This approach is applied to a large real dataset of repeated heart failure hospitalizations.

Keywords: big data analytics, divide-and-conquer, recurrent event data, statistical computing

Procedia PDF Downloads 166

Authors: Tejaswi Agarwal, Amritansh Agarwal

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Forest ecosystem plays very important role in the global carbon cycle. It stores about 80% of all above ground and 40% of all below ground terrestrial organic carbon. There is much interest in the extent of tropical forests and their rates of deforestation for two reasons: greenhouse gas contributions and the impact of profoundly negative biodiversity. Deforestation has many ecological, social and economic consequences, one of which is the loss of biological diversity. The rapid deployment of remote sensing (RS) satellites and development of RS analysis techniques in the past three decades have provided a reliable, effective, and practical way to characterize terrestrial ecosystem properties. Global estimates of tropical deforestation vary widely and range from 50,000 to 170,000km2 /yr Recent FAO tropical deforestation estimates for 1990–1995 cite 116,756km2 / yr globally. Remote Sensing can prove to be a very useful tool in monitoring of forests and associated deforestation to a sufficient level of accuracy without the need of physically surveying the forest areas as many of them are physically inaccessible. The methodology for the assessment of forest cover using digital image processing (ERDAS) has been followed. The satellite data for the study was procured from Indian institute of remote Sensing (IIRS), Dehradoon in the digital format. While procuring the satellite data, care was taken to ensure that the data was cloud free and did not belong to dry and leafless season. The Normalized Difference Vegetation Index (NDVI) has been used as a numerical indicator of the reduction in ground biomass. NDVI = (near I.R - Red)/ (near I.R + Red). After calculating the NDVI variations and associated mean, we have analysed the change in ground biomass. Through this paper, we have tried to indicate the rate of deforestation over a given period of time by comparing the forest cover at different time intervals. With the help of remote sensing and GIS techniques, it is clearly shown that the total forest cover is continuously degrading and transforming into various land use/land cover category.

Keywords: remote sensing, deforestation, supervised classification, NDVI, change detection

Procedia PDF Downloads 1204

Authors: Weic-Ting Chen, Jo-Ming Tseng

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Ammonium nitrate (AN) has caused many accidents in the world, which have caused a large number of people’s life and serious economic losses. In this study, the safety of the AN production process was discussed deeply, and the influence of incompatible substances was estimated according to the change of their heat value by mixing them with incompatible substances by thermal analysis techniques, and their safety parameters were calculated according to their kinetic parameters. In this study, differential scanning calorimeters (DSC) were applied for the temperature rise test and adiabatic thermal analysis in combination with the Advanced Reactive System Screening Tool (ARSST). The research results could contribute to the safety of the ammonium nitrate production process. Manufacturers can better understand the possibility of chemical heat release and the operating conditions that will cause a chemical reaction to be out of control when storing or adding new substances, so safety parameters were researched for these complex reactions. The results of this study will benefit the process of AN and the relevant staff, which also have safety protection in the working environment.

Keywords: ammonium nitrate, incompatible substances, differential scanning calorimeters, advanced reactive system screening tool, safety parameters

Procedia PDF Downloads 94

Authors: Chen Wang, Gerard Rowe

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The number of undergraduate engineering students enrolled in university has been increasing rapidly recently, leading to challenges associated with increased student-instructor ratios and increased diversity in academic preparedness of the entrants. An increased student-instructor ratio makes the interaction between teachers and students more difficult, with the resulting student ‘anonymity’ known to be a risk to academic success. With increasing student numbers, there is also an increasing diversity in the academic preparedness of the students at entry to university. Conceptual understanding of the entrants has been quantified via diagnostic testing, with the results for the first-year course in electrical engineering showing significant conceptual misunderstandings amongst the entry cohort. The solution is clearly multi-faceted, but part of the solution likely involves greater demands being placed on students to be masters of their own learning. In consequence, it is highly desirable that instructors help students to develop better self-regulated learning skills. A self-regulated learner is one who is capable of setting up their own learning goals, monitoring their study processes, adopting and adjusting learning strategies, and reflecting on their own study achievements. The methods by which instructors might cultivate students’ self-regulated learning abilities is receiving increasing attention from instructors and researchers. The aim of this study was to help students understand fully their self-regulated learning skill levels and provide targeted instructions to help them improve particular learning abilities in order to meet the curriculum requirements. As a survey tool, this research applied the questionnaire ‘Motivated Strategies for Learning Questionnaire’ (MSLQ) to collect first year engineering student’s self-reported data of their cognitive abilities, motivational orientations and learning strategies. MSLQ is a widely-used questionnaire for assessment of university student’s self-regulated learning skills. The questionnaire was offered online as a part of the online-scaffolding-learning tools to develop student understanding of self-regulated learning theories and learning strategies. The online tools, which have been under development since 2015, are designed to help first-year students understand their self-regulated learning skill levels by providing prompt feedback after they complete the questionnaire. In addition, the online tool also supplies corresponding learning strategies to students if they want to improve specific learning skills. A total of 866 first year engineering students who enrolled in the first-year electrical engineering course were invited to participate in this research project. By the end of the course 857 students responded and 738 of their questionnaires were considered as valid questionnaires. Analysis of these surveys showed that 66% of the students thought the online-scaffolding-learning tools helped significantly to improve their self-regulated learning abilities. It was particularly pleasing that 16.4% of the respondents thought the online-scaffolding-learning tools were extremely effective. A current thrust of our research is to investigate the relationships between students’ self-regulated learning abilities and their academic performance. Our results are being used by the course instructors as they revise the curriculum and pedagogy for this fundamental first-year engineering course, but the general principles we have identified are applicable to most first-year STEM courses.

Keywords: academic preparedness, online-scaffolding-learning tool, self-regulated learning, STEM education

Procedia PDF Downloads 110

Authors: Amritansh Agarwal, Tejaswi Agarwal

Abstract:

Forest ecosystem plays very important role in the global carbon cycle. It stores about 80% of all above ground and 40% of all below ground terrestrial organic carbon. There is much interest in the extent of tropical forests and their rates of deforestation for two reasons: greenhouse gas contributions and the impact of profoundly negative biodiversity. Deforestation has many ecological, social and economic consequences, one of which is the loss of biological diversity. The rapid deployment of remote sensing (RS) satellites and development of RS analysis techniques in the past three decades have provided a reliable, effective, and practical way to characterize terrestrial ecosystem properties. Global estimates of tropical deforestation vary widely and range from 50,000 to 170,000 km2 /yr Recent FAO tropical deforestation estimates for 1990–1995 cite 116,756km2 / yr globally. Remote Sensing can prove to be a very useful tool in monitoring of forests and associated deforestation to a sufficient level of accuracy without the need of physically surveying the forest areas as many of them are physically inaccessible. The methodology for the assessment of forest cover using digital image processing (ERDAS) has been followed. The satellite data for the study was procured from USGS website in the digital format. While procuring the satellite data, care was taken to ensure that the data was cloud and aerosol free by making using of FLAASH atmospheric correction technique. The Normalized Difference Vegetation Index (NDVI) has been used as a numerical indicator of the reduction in ground biomass. NDVI = (near I.R - Red)/ (near I.R + Red). After calculating the NDVI variations and associated mean we have analysed the change in ground biomass. Through this paper we have tried to indicate the rate of deforestation over a given period of time by comparing the forest cover at different time intervals. With the help of remote sensing and GIS techniques it is clearly shows that the total forest cover is continuously degrading and transforming into various land use/land cover category.

Keywords: remote sensing, deforestation, supervised classification, NDVI change detection

Procedia PDF Downloads 402

Authors: Muhtasim Shafi Kader, Fizar Ahmed, Annesha Acharjee

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Machine learning and data mining are crucial in health care, as well as medical information and detection. Machine learning approaches are now being utilized to improve awareness of a variety of critical health issues, including diabetes detection, neuron cell tumor diagnosis, COVID 19 identification, and so on. Parkinson’s disease is basically a disease for our senior citizens in Bangladesh. Parkinson's Disease indications often seem progressive and get worst with time. People got affected trouble walking and communicating with the condition advances. Patients can also have psychological and social vagaries, nap problems, hopelessness, reminiscence loss, and weariness. Parkinson's disease can happen in both men and women. Though men are affected by the illness at a proportion that is around partial of them are women. In this research, we have to get out the accurate ML algorithm to find out the disease with a predictable dataset and the model of the following machine learning classifiers. Therefore, nine ML classifiers are secondhand to portion study to use machine learning approaches like as follows, Naive Bayes, Adaptive Boosting, Bagging Classifier, Decision Tree Classifier, Random Forest classifier, XBG Classifier, K Nearest Neighbor Classifier, Support Vector Machine Classifier, and Gradient Boosting Classifier are used.

Keywords: naive bayes, adaptive boosting, bagging classifier, decision tree classifier, random forest classifier, XBG classifier, k nearest neighbor classifier, support vector classifier, gradient boosting classifier

Procedia PDF Downloads 129

Authors: Mandlenkosi G. R. Mahlobo, Peter A. Olubambi

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Cathodic protection (CP) has been widely considered as a suitable technique for mitigating corrosion of steel structures buried in soil. Plenty of efforts have been made in developing techniques, in particular non-destructive techniques, for monitoring and quantifying the effectiveness of CP to ensure the sustainability and performance of buried steel structures. This study was aimed at using a specifically modified voltammetry approach as a non-destructive tool to monitor and quantify the effectiveness of CP of steel in simulated soil. Carbon steel was subjected to electrochemical tests with NS4 solution used as simulated soil conditions for four days before applying CP for further 11 days. A specifically modified voltammetry technique was applied at various time intervals of the experiment to monitor the corrosion behaviour and therefore reflect CP effectiveness. The voltammetry results revealed that the application of CP reduced the corrosion rate from the highest value of 410 µm/yr to 8 µm/yr between days 5 and 14 of the experiments. The microstructural analysis of the steel surface performed using x-ray diffraction identified calcareous deposit as the dominant phase protecting the surface from corrosion. It was deduced that the formation of calcareous deposits was linked with the effectiveness of CP of steel.

Keywords: carbon steel, cathodic protection, NS4 solution, voltammetry, XRD

Procedia PDF Downloads 68

Authors: Ashiff Khan, A. Seetharaman, Abhijit Dasgupta

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The new era of big data (BD) is influencing chemical industries tremendously, providing several opportunities to reshape the way they operate and help them shift towards intelligent manufacturing. Given the availability of free software and the large amount of real-time data generated and stored in process plants, chemical industries are still in the early stages of big data adoption. The industry is just starting to realize the importance of the large amount of data it owns to make the right decisions and support its strategies. This article explores the importance of professional competencies and data science that influence BD in chemical industries to help it move towards intelligent manufacturing fast and reliable. This article utilizes a literature review and identifies potential applications in the chemical industry to move from conventional methods to a data-driven approach. The scope of this document is limited to the adoption of BD in chemical industries and the variables identified in this article. To achieve this objective, government, academia, and industry must work together to overcome all present and future challenges.

Keywords: chemical engineering, big data analytics, industrial revolution, professional competence, data science

Procedia PDF Downloads 85

Authors: Hammadi Larbi, Bergane Cheikh

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Drilling for oil is done through many mechanisms. The goal is first to dig deep and then, after arriving at the oil source, to simply suck it up. And for this, it is important to know the role of oil-based drilling muds, which had many benefits for the drilling tool and for drilling generally, and also and essentially to know the rheological behavior of the emulsion system in particular water-in-oil inverse emulsions (Water/crude oil). This work contributes to the improvement of the stability and rheological properties of crude oil-based drilling mud by organophilic clay. Experimental data from steady-state flow measurements of crude oil-based drilling mud are classically analyzed by the Herschel-Bulkley model. The effects of organophilic clay type VG69 are studied. Microscopic observation showed that the addition of quantities of organophilic clay type VG69 less than or equal to 3 g leads to the stability of inverse Water/Oil emulsions; on the other hand, for quantities greater than 3g, the emulsions are destabilized.

Keywords: drilling, organophilic clay, crude oil, stability

Procedia PDF Downloads 125

Authors: B. Gültekin, T. Gültekin

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Peace diplomacy is the most important international tool to maintain peace all over the World. This study consists of three parts. In the first part, the leadership of Devlet Bahçeli, leader of the Nationalist Movement Party, will be introduced as a tool of peace communication and peace management. Also, in this part, peace communication will be explained by the peace leadership traits of Devlet Bahçeli, who is one of the efficient political leaders representing the concepts of compromise and agreement on different sides of politics. In the second part of study, it is aimed to analyze Devlet Bahçeli’s leadership within the frame of peace communication and the final part of this study is about creating an original public communication model for public diplomacy based on Devlet Bahçeli as an example. As a result, the main purpose of this study is to develop an original peace communication model including peace modules, peace management projects, original dialogue procedures and protocols exhibited in the policies of Devlet Bahçeli. The political leadership represented by Devlet Bahçeli inspires political leaders to provide peace communication. In this study, principles and policies of peace leadership of Devlet Bahçeli will be explained as an original model on a peace communication platform.

Keywords: public diplomacy, dialogue management, peace leadership, peace diplomacy

Procedia PDF Downloads 167

Authors: Rajkumar Kolangarakandy

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Feature extraction and selection is the primary part of any mammogram classification algorithms. The choice of feature, attribute or measurements have an important influence in any classification system. Discrete Wavelet Transformation (DWT) coefficients are one of the prominent features for representing images in frequency domain. The features obtained after the decomposition of the mammogram images using wavelet transformations have higher dimension. Even though the features are higher in dimension, they were highly correlated and redundant in nature. The dimensionality reduction techniques play an important role in selecting the optimum number of features from the higher dimension data, which are highly correlated. PCA is a mathematical tool that reduces the dimensionality of the data while retaining most of the variation in the dataset. In this paper, a multilevel classification of mammogram images using reduced discrete wavelet transformation coefficients and lazy classifiers is proposed. The classification is accomplished in two different levels. In the first level, mammogram ROIs extracted from the dataset is classified as normal and abnormal types. In the second level, all the abnormal mammogram ROIs is classified into benign and malignant too. A further classification is also accomplished based on the variation in structure and intensity distribution of the images in the dataset. The Lazy classifiers called Kstar, IBL and LWL are used for classification. The classification results obtained with the reduced feature set is highly promising and the result is also compared with the performance obtained without dimension reduction.

Keywords: PCA, wavelet transformation, lazy classifiers, Kstar, IBL, LWL

Procedia PDF Downloads 335

Authors: Phatthanan Chaiyabut

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This research paper investigates whether the development of environmentally friendly practices by luxury hotel resorts can be used as a strategy for gaining competitive advantage through differentiation, and suggests ways to do it. The focus is on luxury hotel resorts in Samut Songkram Province, Thailand. A questionnaire was utilized as a tool to collect data. Statistics utilized in this research included frequency, percentage, mean, standard deviation, and multiple regression analysis. Findings indicate that environmentally friendly development of hotel resorts in Samut Songkram Province has a very limited use as a corporate strategy. Only two luxury hotel resorts had it incorporated in their strategy, it is not much used in marketing indicating environmental issues are not seen as important. This was confirmed through the interviews with the managers that it is not seen as important issue to promote.

Keywords: competitive advantage, competitive strategy, Samut Songkram Province, hotel and resort

Procedia PDF Downloads 278

Authors: Junior Nomani

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This paper presents a novel approach to modelling the metal cutting of duplex stainless steels, a two-phase alloy regarded as a difficult-to-machine material. Calculation and control of shear strain and stresses during cutting are essential to achievement of ideal cutting conditions. Too low or too high leads to higher required cutting force or excessive heat generation causing premature tool wear failure. A 2D finite element cutting model was created based on electron backscatter diffraction (EBSD) data imagery of duplex microstructure. A mesh was generated using ‘object-oriented’ software OOF2 version V2.1.11, converting microstructural images to quadrilateral elements. A virtual workpiece was created on ABAQUS modelling software where a rigid body toolpiece advanced towards workpiece simulating chip formation, generating serrated edge chip formation cutting. Model results found calculated stress strain contour plots correlated well with similar finite element models tied with austenite stainless steel alloys. Virtual chip form profile is also similar compared experimental frozen machining chip samples. The output model data provides new insight description of strain behavior of two phase material on how it transitions from workpiece into the chip.

Keywords: Duplex stainless steel, ABAQUS, OOF2, Chip formation

Procedia PDF Downloads 100

Authors: Chansheng He, Zhongfu Wang, Xiao Bai, Jie Tian, Xin Jin

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Heterogeneity of soil hydraulic properties directly affects hydrological processes at different scales. Understanding heterogeneity of soil hydraulic properties such as soil moisture is therefore essential for modeling watershed ecohydrological processes, particularly in hard to access, topographically complex mountainous watersheds. This study maps spatial variations of soil moisture by in situ observation network that consists of sampling points, zones, and tributaries, and monitors corresponding hydrological variables of air and soil temperatures, evapotranspiration, infiltration, and runoff in the Upper Reach of the Heihe River Watershed, a second largest inland river (terminal lake) with a drainage area of over 128,000 km² in Northwest China. Subsequently, the study uses a hydrological model, SWAT (Soil and Water Assessment Tool) to simulate the effects of heterogeneity of soil moisture on watershed hydrological processes. The spatial clustering method, Full-Order-CLK was employed to derive five soil heterogeneous zones (Configuration 97, 80, 65, 40, and 20) for soil input to SWAT. Results show the simulations by the SWAT model with the spatially clustered soil hydraulic information from the field sampling data had much better representation of the soil heterogeneity and more accurate performance than the model using the average soil property values for each soil type derived from the coarse soil datasets. Thus, incorporating detailed field sampling soil heterogeneity data greatly improves performance in hydrologic modeling.

Keywords: heterogeneity, soil moisture, SWAT, up-scaling

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Authors: Krzysztof Pomorski

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In the given work we present universal mathematical framework for modeling of cattle farm system that can set and validate various hypothesis that can be tested against experimental data. The presented work is preliminary but it is expected to be valid tool for future deeper analysis that can result in new class of prediction methods allowing early detection of cow dieseaes as well as cow performance. Therefore the presented work shall have its meaning in agriculture models and in machine learning as well. It also opens the possibilities for incorporation of certain class of biological models necessary in modeling of cow behavior and farm performance that might include the impact of environment on the farm system. Particular attention is paid to the model of coupled oscillators that it the basic building hypothesis that can construct the model showing certain periodic or quasiperiodic behavior.

Keywords: coupled ordinary differential equations, cattle farm system, numerical methods, stochastic differential equations

Procedia PDF Downloads 145

Authors: Guilherme Giacomini, Ana Luiza Menegatti Pavan, Allan Felipe Fattori Alves, Marcela de Oliveira, Fernando Antonio Bacchim Neto, José Ricardo de Arruda Miranda, Seizo Yamashita, Diana Rodrigues de Pina

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The maxillary sinus (MS), part of the paranasal sinus complex, is one of the most enigmatic structures in modern humans. The literature has suggested that MSs function as olfaction accessories, to heat or humidify inspired air, for thermoregulation, to impart resonance to the voice and others. Thus, the real function of the MS is still uncertain. Furthermore, the MS anatomy is complex and varies from person to person. Many diseases may affect the development process of sinuses. The incidence of rhinosinusitis and other pathoses in the MS is comparatively high, so, volume analysis has clinical value. Providing volume values for MS could be helpful in evaluating the presence of any abnormality and could be used for treatment planning and evaluation of the outcome. The computed tomography (CT) has allowed a more exact assessment of this structure, which enables a quantitative analysis. However, this is not always possible in the clinical routine, and if possible, it involves much effort and/or time. Therefore, it is necessary to have a convenient, robust, and practical tool correlated with the MS volume, allowing clinical applicability. Nowadays, the available methods for MS segmentation are manual or semi-automatic. Additionally, manual methods present inter and intraindividual variability. Thus, the aim of this study was to develop an automatic tool to quantity the MS volume in CT scans of paranasal sinuses. This study was developed with ethical approval from the authors’ institutions and national review panels. The research involved 30 retrospective exams of University Hospital, Botucatu Medical School, São Paulo State University, Brazil. The tool for automatic MS quantification, developed in Matlab®, uses a hybrid method, combining different image processing techniques. For MS detection, the algorithm uses a Support Vector Machine (SVM), by features such as pixel value, spatial distribution, shape and others. The detected pixels are used as seed point for a region growing (RG) segmentation. Then, morphological operators are applied to reduce false-positive pixels, improving the segmentation accuracy. These steps are applied in all slices of CT exam, obtaining the MS volume. To evaluate the accuracy of the developed tool, the automatic method was compared with manual segmentation realized by an experienced radiologist. For comparison, we used Bland-Altman statistics, linear regression, and Jaccard similarity coefficient. From the statistical analyses for the comparison between both methods, the linear regression showed a strong association and low dispersion between variables. The Bland–Altman analyses showed no significant differences between the analyzed methods. The Jaccard similarity coefficient was > 0.90 in all exams. In conclusion, the developed tool to quantify MS volume proved to be robust, fast, and efficient, when compared with manual segmentation. Furthermore, it avoids the intra and inter-observer variations caused by manual and semi-automatic methods. As future work, the tool will be applied in clinical practice. Thus, it may be useful in the diagnosis and treatment determination of MS diseases. Providing volume values for MS could be helpful in evaluating the presence of any abnormality and could be used for treatment planning and evaluation of the outcome. The computed tomography (CT) has allowed a more exact assessment of this structure which enables a quantitative analysis. However, this is not always possible in the clinical routine, and if possible, it involves much effort and/or time. Therefore, it is necessary to have a convenient, robust and practical tool correlated with the MS volume, allowing clinical applicability. Nowadays, the available methods for MS segmentation are manual or semi-automatic. Additionally, manual methods present inter and intraindividual variability. Thus, the aim of this study was to develop an automatic tool to quantity the MS volume in CT scans of paranasal sinuses. This study was developed with ethical approval from the authors’ institutions and national review panels. The research involved 30 retrospective exams of University Hospital, Botucatu Medical School, São Paulo State University, Brazil. The tool for automatic MS quantification, developed in Matlab®, uses a hybrid method, combining different image processing techniques. For MS detection, the algorithm uses a Support Vector Machine (SVM), by features such as pixel value, spatial distribution, shape and others. The detected pixels are used as seed point for a region growing (RG) segmentation. Then, morphological operators are applied to reduce false-positive pixels, improving the segmentation accuracy. These steps are applied in all slices of CT exam, obtaining the MS volume. To evaluate the accuracy of the developed tool, the automatic method was compared with manual segmentation realized by an experienced radiologist. For comparison, we used Bland-Altman statistics, linear regression and Jaccard similarity coefficient. From the statistical analyses for the comparison between both methods, the linear regression showed a strong association and low dispersion between variables. The Bland–Altman analyses showed no significant differences between the analyzed methods. The Jaccard similarity coefficient was > 0.90 in all exams. In conclusion, the developed tool to automatically quantify MS volume proved to be robust, fast and efficient, when compared with manual segmentation. Furthermore, it avoids the intra and inter-observer variations caused by manual and semi-automatic methods. As future work, the tool will be applied in clinical practice. Thus, it may be useful in the diagnosis and treatment determination of MS diseases.

Keywords: maxillary sinus, support vector machine, region growing, volume quantification

Procedia PDF Downloads 504

Authors: Tuba Senel Zor, Oktay Aslan

Abstract:

With current trends in nanoscience and nanotechnology (NST), scientists have paid much attention to education and nanoliteracy in parallel with the developments on these fields. To understand the advances in NST research requires a population with a high degree of science literacy. All citizens should soon need nanoliteracy in order to navigate some of the important science-based issues faced to their everyday lives. While the fields of NST are advancing rapidly and raising their societal significance, general public’s awareness of these fields has remained at a low level. Moreover, students enrolled different education levels and teachers don’t have awareness at expected level. This problem may be stemmed from inadequate education and training. To remove the inadequacy, teachers have greatest duties and responsibilities. Especially science teachers at all levels need to be made aware of these developments and adequately prepared so that they are able to teach about these advances in a developmentally appropriate manner. If the teachers develop understanding and awareness of NST, they can also discuss the topic with their students. Therefore, the awareness and conceptual understandings of both the teachers who will teach science to students and the students who will be introduced about NST should be increased, and the necessary training should be provided. The aim of this study was to examine the effect of NST education on preservice science teachers’ awareness of NST. The study was designed in one group pre-test post-test quasi-experimental pattern. The study was conducted with 32 preservice science teachers attending the Elementary Science Education Program at a large Turkish university in central Anatolia. NST education was given during five weeks as two hours per week. Nanoscience and Nanotechnology Awareness Questionnaire was used as data collected tool and was implemented for pre-test and post-test. The collected data were analyzed using Statistical package for the Social Science (SPSS). The results of data analysis showed that there was a significant difference (z=6.25, p< .05) on NST awareness of preservice science teachers after implemented NST education. The results of the study indicate that NST education has an important effect for improving awareness of preservice science teachers on NST.

Keywords: awareness level, nanoliteracy, nanoscience and nanotechnology education, preservice science teachers

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Authors: Sousan Arafeh

Abstract:

Educational systems and schools worldwide are increasingly reliant on information and communication technology (ICT). Unfortunately, most educational leadership development programs do not offer formal curricular and/or field experiences that prepare students for managing ICT resources, personnel, and processes. The result is a steep learning curve for the leader and his/her staff and dissipated organizational energy that compromises desired outcomes. To address this gap in education leaders’ development, Arafeh’s Integrated Technology Leadership Model (AITLM) was created. It is a conceptual model and tool that educational leadership students can use to better understand the ICT ecology that exists within their schools. The AITL Model consists of six 'infrastructure types' where ICT activity takes place: technical infrastructure, communications infrastructure, core business infrastructure, context infrastructure, resources infrastructure, and human infrastructure. These six infrastructures are further divided into 16 key areas that need management attention. The AITL Model was created by critically analyzing existing technology/ICT leadership models and working to make something more authentic and comprehensive regarding school leaders’ purview and experience. The AITL Model then served as a tool when it was distributed to over 150 educational leadership students who were asked to review it and qualitatively share their reactions. Students said the model presented crucial areas of consideration that they had not been exposed to before and that the exercise of reviewing and discussing the AITL Model as a group was useful for identifying areas of growth that they could pursue in the leadership development program and in their professional settings. While development in all infrastructures and key areas was important for students’ understanding of ICT, they noted that they were least aware of the importance of the intangible area of the resources infrastructure. The AITL Model will be presented and session participants will have an opportunity to review and reflect on its impact and utility. Ultimately, the AITL Model is one that could have significant policy and practice implications. At the very least, it might help shape ICT content in educational leadership development programs through curricular and pedagogical updates.

Keywords: education leadership, information and communications technology, ICT, leadership capacity building, leadership development

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Authors: Nahlah Abbas, Saleh A. Wasimi, Nadhir Al-Ansari

Abstract:

The Greater Zab and Lesser Zab are the major tributaries of Tigris River contributing the largest flow volumes into the river. The impacts of climate change on water resources in these basins have not been well addressed. To gain a better understanding of the effects of climate change on water resources of the study area in near future (2049-2069) as well as in distant future (2080-2099), Soil and Water Assessment Tool (SWAT) was applied. The model was first calibrated for the period from 1979 to 2004 to test its suitability in describing the hydrological processes in the basins. The SWAT model showed a good performance in simulating streamflow. The calibrated model was then used to evaluate the impacts of climate change on water resources. Six general circulation models (GCMs) from phase five of the Coupled Model Intercomparison Project (CMIP5) under three Representative Concentration Pathways (RCPs) RCP 2.6, RCP 4.5, and RCP 8.5 for periods of 2049-2069 and 2080-2099 were used to project the climate change impacts on these basins. The results demonstrated a significant decline in water resources availability in the future.

Keywords: Tigris River, climate change, water resources, SWAT

Procedia PDF Downloads 204

Authors: Varsha V. Rohini, P. R. Shreya, B. Renukadevi

Abstract:

In the web analytics the information delivery and the web usage is optimized and the analysis of data is done. The analytics is the measurement, collection and analysis of webpage data. Page statistics and user metrics are the important factor in most of the web analytics tool. This is the limitation of the existing tools. It does not provide design inputs for the optimization of information. This paper aims at providing an extension for the scope of web analytics to provide analysis and statistics of each segment of a webpage. The number of click count is calculated and the concentration of links in a web page is obtained. Its user metrics are used to help in proper design of the displayed content in a webpage by Vision Based Page Segmentation (VIPS) algorithm. When the algorithm is applied on the web page it divides the entire web page into the visual block tree. The visual block tree generated will further divide the web page into visual blocks or segments which help us to understand the usage of each segment in a page and its content. The dynamic web pages and deep web pages are used to extend the scope of web page segment analytics. Space optimization concept is used with the help of the output obtained from the Vision Based Page Segmentation (VIPS) algorithm. This technique provides us the visibility of the user interaction with the WebPages and helps us to place the important links in the appropriate segments of the webpage and effectively manage space in a page and the concentration of links.

Keywords: analytics, design optimization, visual block trees, vision based technology

Procedia PDF Downloads 266

Authors: Annette Joseph

Abstract:

Background: The construction industry is dynamic in nature owing to the increasing uncertainties in technology, budgets, and development processes making projects more complex. Thus, predicting project performance and chances of its likely success has become difficult. The goal of all parties involved in construction projects is to successfully complete it on schedule, within planned budget and with the highest quality and in the safest manner. However, the concept of project success has remained ambiguously defined in the mind of the construction professionals. Purpose: This paper aims to study the analysis of a project in terms of its performance and measure the success. Methodology: The parameters for evaluating project success and the indices to measure success/performance of a project are identified through literature study. Through questionnaire surveys aimed at the stakeholders in the projects, data is collected from two live case studies (an ongoing and completed project) on the overall performance in terms of its success/failure. Finally, with the help of SPSS tool, the data collected from the surveys are analyzed and applied on the selected performance indices. Findings: The score calculated by using the indices and models helps in assessing the overall performance of the project and interpreting it to find out whether the project will be a success or failure. This study acts as a reference for firms to carry out performance evaluation and success measurement on a regular basis helping projects to identify the areas which are performing well and those that require improvement. Originality & Value: The study signifies that by measuring project performance; a project’s deviation towards success/failure can be assessed thus helping in suggesting early remedial measures to bring it on track ensuring that a project will be completed successfully.

Keywords: project, performance, indices, success

Procedia PDF Downloads 191

Authors: Elias K. Maragos, Petros E. Maravelakis, Apostolos I. Linardis

Abstract:

Health2020 is a promising framework of policies provided by the World Health Organization (WHO) and aiming to diminish the health and well-being inequalities among the citizens of the European Union (EU) countries. The major demographic, social and environmental changes, in addition to the resent economic crisis prevent the unobstructed and successful implementation of this framework. The unemployment rates and the percentage of people at risk of poverty have increased among the citizens of EU countries. At the same time, the adopted fiscal, economic policies do not help governments to serve their social role and mitigate social and health inequalities. In those circumstances, there is a strong pressure to organize all health system resources efficiently and wisely. In order to provide a unified and value-based framework of valuation, we propose a valuation framework using data envelopment analysis (DEA) and dynamic DEA. We believe that the adopted methodology could provide a robust tool which can capture the degree of success with which policies have been implemented and is capable to determine which of the countries developed the requested policies efficiently and which of the countries have been lagged. Using the proposed methodology, we evaluated the performance of 28 EU member-countries in relation to the Health2020 peripheral targets. We adopted several versions of evaluation, measuring the effectiveness and the efficiency of EU countries from 2011 to 2016. Our results showed stability in technological changes and revealed a group of countries which were benchmarks in most of the years for the inefficient countries.

Keywords: DEA, Health2020, health inequalities, malmquist index, policies evaluation, well-being

Procedia PDF Downloads 143

Authors: Pradeep Singh, Shrish Verma

Abstract:

Software fault prediction models are created by using the source code, processed metrics from the same or previous version of code and related fault data. Some company do not store and keep track of all artifacts which are required for software fault prediction. To construct fault prediction model for such company, the training data from the other projects can be one potential solution. The earlier we predict the fault the less cost it requires to correct. The training data consists of metrics data and related fault data at function/module level. This paper investigates fault predictions at early stage using the cross-project data focusing on the design metrics. In this study, empirical analysis is carried out to validate design metrics for cross project fault prediction. The machine learning techniques used for evaluation is Naïve Bayes. The design phase metrics of other projects can be used as initial guideline for the projects where no previous fault data is available. We analyze seven data sets from NASA Metrics Data Program which offer design as well as code metrics. Overall, the results of cross project is comparable to the within company data learning.

Keywords: software metrics, fault prediction, cross project, within project.

Procedia PDF Downloads 344

Authors: A. Dionísio, L. Roseiro, J. Fonseca, P. Nicolau

Abstract:

Thermography is a non-radiating and contact-free technology which can be used to monitor skin temperature. The efficiency and safety of thermography technology make it a useful tool for detecting and locating thermal changes in skin surface, characterized by increases or decreases in temperature. This work intends to be a contribution for the use of thermography as a methodology for evaluation of skin temperature in the context of orofacial biomechanics. The study aims to identify the oscillations of skin temperature in the left and right hemiface regions of the masseter muscle, during and after thermal stimulus, and estimate the time required to restore the initial temperature after the application of the stimulus. Using a FLIR T430sc camera, a data acquisition protocol was followed with a group of eight volunteers, aged between 22 and 27 years. The tests were performed in a controlled environment with the volunteers in a comfortably static position. The thermal stimulus involves the use of an ice volume with controlled size and contact surface. The skin surface temperature was recorded in two distinct situations, namely without further stimulus and with the additions of a stimulus obtained by a chewing gum. The data obtained were treated using FLIR Research IR Max software. The time required to recover the initial temperature ranged from 20 to 52 minutes when no stimulus was added and varied between 8 and 26 minutes with the chewing gum stimulus. These results show that recovery is faster with the addition of the stimulus and may guide clinicians regarding the pre and post-operative times with ice therapy, in the presence or absence of mechanical stimulus that increases muscle functions (e.g. phonetics or mastication).

Keywords: thermography, orofacial biomechanics, skin temperature, ice therapy

Procedia PDF Downloads 255

Authors: Christoph Ramsauer, Jaydeep Karandikar, Tony Schmitz, Friedrich Bleicher

Abstract:

Machining stability is an important limitation to discrete part machining. In this work, a networked implementation of milling stability optimization with Bayesian learning is presented. The milling process was monitored with a wireless sensory tool holder instrumented with an accelerometer at the Vienna University of Technology, Vienna, Austria. The recorded data from a milling test cut is used to classify the cut as stable or unstable based on the frequency analysis. The test cut result is fed to a Bayesian stability learning algorithm at the University of Tennessee, Knoxville, Tennessee, USA. The algorithm calculates the probability of stability as a function of axial depth of cut and spindle speed and recommends the parameters for the next test cut. The iterative process between two transatlantic locations repeats until convergence to a stable optimal process parameter set is achieved.

Keywords: machining stability, machine learning, sensor, optimization

Procedia PDF Downloads 206