Search results for: software cumulative failure prediction

Authors: Engku Haliza Engku Ibrahim, Isarji Sarudin, Ainon Jariah Muhamad

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It is generally agreed that many factors contribute to one’s reading comprehension and there is consensus that vocabulary size one of the main factors. This study explores the relationship between second language learners’ vocabulary size and their reading comprehension scores. 130 Malay pre-university students of a public university participated in this study. They were students of an intensive English language programme doing preparatory English courses to pursue bachelors degree in English. A quantitative research method was employed based on the Vocabulary Levels Test by Nation (1990) and the reading comprehension score of the in-house English Proficiency Test. A review of the literature indicates that a somewhat positive correlation is to be expected though findings of this study can only be explicated once the final analysis has been carried out. This is an ongoing study and it is anticipated that results of this research will be finalized in the near future. The findings will help provide beneficial implications for the prediction of reading comprehension performance. It also has implications for the teaching of vocabulary in the ESL context. A better understanding of the relationship between vocabulary size and reading comprehension scores will enhance teachers’ and students’ awareness of the importance of vocabulary acquisition in the L2 classroom.

Keywords: vocabulary size, vocabulary learning, reading comprehension, ESL

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Authors: S. Shujan, A. T. Rupasinghe, N. L. Gunawardena

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Numerous studies have determined that there is a direct correlation between the successful interviewee and the nonverbal behavioral patterns of that person during the interview. In this study, we focus on formations of interview questions in such a way that, it gets an opportunity for assessing interviewee through the answers using the nonverbal behavioral cues. From all the nonverbal behavioral factors we have identified, in this study priority is given to the ‘facial expression variations’ with the assistance of facial expression analytics tool; this research proposes a novel approach in question formation for the assessment of interviewees in ‘Software Industry’.

Keywords: assessments, hirability, interviews, non-verbal behaviour patterns, question formation

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Authors: Mohammed Zaki, Hayder Rasheed

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This paper evaluates the flexural response of sand-lightweight Perlite concrete using full-scale reinforced concrete T beams strengthened and anchored with carbon fiber reinforced polymer (CFRP) materials. Four specimens were prepared with the same geometry, steel reinforcements, concrete properties, and span lengths. The anchored beams had a similar number of CFRP sheets but were secured utilizing different arrangements of CFRP fiber anchors. That will allow for effective and easily making comparisons to examine the flexural strengthening behavior of sand-lightweight Perlite concrete beams with anchors. The experimental outcomes were also compared with the numerical study and the comparisons were discussed. The test results showed an improvement in flexural behavior due to the use of CFRP sheets and anchors. Interestingly, the anchored beams recorded similar ultimate strength regardless of the number of CFRP fiber anchors used due to the failure by excessive wide cracks in the concrete.

Keywords: perlite concrete, CFRP fiber anchors, lightweight concrete, full-scale T-beams

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Authors: Oualid Benyamina Douma

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Repair is always the result of the appearance of apparent disorder or aggravation of a mass. Which had hitherto been considered minor if not negligible: The work was not done according to plan. So; the examination of causes can lead to thinking about repair. While the application of the epoxy resin has become a hot topic. In this context, we conducted an experimental campaign (48 specimens are tested beakout) whose objective is based on three points: 1- Highlight the importance and influence of important parameters (compressive strength of concrete anchorage length and diameter of the steel bar) on routes (steel-concrete and steel–concrete epoxy resin) 2- Understanding the influence of the parameters mentioned above on the relationship that may exist between the peel strength and slippage. 3- Faces of cracks and failure modes. This study shows that passage of a compressive strength of 40 MPa to 62 MPa increases the adhesion between the steel bar and concrete and for specimens with or without epoxy resin. The loading force was increased form 40 to 81 kM kN, a rate if increase in loading over 100% In addition, for specimens with and without epoxy resin. increased breakout force through a specimen without a specimen with resin ranging from 20% to 32%.

Keywords: epoxy resin, peel strength, anchors, slip diameter steel rod, anchor plain concrete and concrete with moderate resistance

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Authors: Abdolreza Memari

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In this article in order to estimate the viscosity of crude oil,a numerical method has been used. We use this method to measure the crude oil's viscosity for 3 states: Saturated oil's viscosity, viscosity above the bubble point and viscosity under the saturation pressure. Then the crude oil's viscosity is estimated by using KHAN model and roller ball method. After that using these data that include efficient conditions in measuring viscosity, the estimated viscosity by the presented method, a radial based neural method, is taught. This network is a kind of two layered artificial neural network that its stimulation function of hidden layer is Gaussian function and teaching algorithms are used to teach them. After teaching radial based neural network, results of experimental method and artificial intelligence are compared all together. Teaching this network, we are able to estimate crude oil's viscosity without using KHAN model and experimental conditions and under any other condition with acceptable accuracy. Results show that radial neural network has high capability of estimating crude oil saving in time and cost is another advantage of this investigation.

Keywords: viscosity, Iranian crude oil, radial based, neural network, roller ball method, KHAN model

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Authors: Ather Saeed, Arif Khan, Jeffrey Gosper

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Sensor devices are prone to errors and sudden node failures, which are difficult to detect in a timely manner when deployed in real-time, hazardous, large-scale harsh environments and in medical emergencies. Therefore, the loss of data can be life-threatening when the sensed phenomenon is not disseminated due to sudden node failure, battery depletion or temporary malfunctioning. We introduce a set of partial differential equations for localizing faults, similar to Green’s and Maxwell’s equations used in Electrostatics and Electromagnetism. We introduce a node organization and clustering scheme for self-stabilizing sensor networks. Green’s theorem is applied to regions where the curve is closed and continuously differentiable to ensure network connectivity. Experimental results show that the proposed GTFD (Green’s Theorem fault-detection and Self-stabilization) protocol not only detects faulty nodes but also accurately generates network stability graphs where urgent intervention is required for dynamically self-stabilizing the network.

Keywords: Green’s Theorem, self-stabilization, fault-localization, RSSI, WSN, clustering

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Authors: Hallan Moura Ladeira, Carla Tatiana Mota Anflor

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The drilling process for bolted or riveted joints of components is very common in the naval, aeronautical, mechanical, and civil industries. In this context, the present work aims to study, through computer simulation, the influence of hole geometry (through, chamfered, and rounded) on crack propagation when submitted to static and dynamic loads. For the static crack evaluation, failure was considered when the stress intensity factor (FIT) exceeds the fracture toughness of the material (KIc). In the case of fatigue, the condition of the small crack tip plastification zone and the Paris Law were considered for determining region II of the dadN x ΔK curve. Initially, a parametric analysis of the hole geometry was performed to obtain a topology that would result in less discontinuity of the stress field and, consequently, less influence on static crack growth. The best performing topology was then used to study the fatigue crack growth rate considering the Paris Law. The numerical tests were performed on a 7075-T6 aluminum specimen resulting in dadN x ΔK curves in good agreement with the literature.

Keywords: holes, cracks, loading, fracture toughness

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Authors: Uduak Umoh, Imo Eyoh, Emmauel Nyoho

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This paper compares fuzzy-machine learning algorithms such as Support Vector Machine (SVM), and K-Nearest Neighbor (KNN) for the predicting cases of fire outbreak. The paper uses the fire outbreak dataset with three features (Temperature, Smoke, and Flame). The data is pre-processed using Interval Type-2 Fuzzy Logic (IT2FL) algorithm. Min-Max Normalization and Principal Component Analysis (PCA) are used to predict feature labels in the dataset, normalize the dataset, and select relevant features respectively. The output of the pre-processing is a dataset with two principal components (PC1 and PC2). The pre-processed dataset is then used in the training of the aforementioned machine learning models. K-fold (with K=10) cross-validation method is used to evaluate the performance of the models using the matrices – ROC (Receiver Operating Curve), Specificity, and Sensitivity. The model is also tested with 20% of the dataset. The validation result shows KNN is the better model for fire outbreak detection with an ROC value of 0.99878, followed by SVM with an ROC value of 0.99753.

Keywords: Machine Learning Algorithms , Interval Type-2 Fuzzy Logic, Fire Outbreak, Support Vector Machine, K-Nearest Neighbour, Principal Component Analysis

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Authors: Khaja Moiduddin, Tamer Khalaf, Muthuramalingam Thangaraj

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Due to the variety of benefits over traditional cutting techniques, the usage of laser cutting technology has risen substantially in recent years. Hot wire machining can cut the leather in the required shape by controlling the wire by generating thermal energy. In the present study, an attempt has been made to investigate the effects of performance measures in the hot wire machining process on cutting leather specimens. Carbonization and material removal rates were considered as quality indicators. Burning leather during machining might cause carbon particles, reducing product quality. Minimizing the effect of carbon particles is crucial for assuring operator and environmental safety, health, and product quality. Hot wire machining can efficiently cut the specimens by controlling the current through it. Taguchi- DEAR-based optimization was also performed in the process, which resulted in a required Carbonization and material removal rate. Using the DEAR approach, the optimal parameters of the present study were found with 3.7% prediction error accuracy.

Keywords: cabronization, leather, MRR, current

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Authors: Leila Jafari, Viliam Makis, G. B. Akram Khaleghei

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In this paper, we present a maintenance model of a two-unit series system with economic dependence. Unit#1, which is considered to be more expensive and more important, is subject to condition monitoring (CM) at equidistant, discrete time epochs and unit#2, which is not subject to CM, has a general lifetime distribution. The multivariate observation vectors obtained through condition monitoring carry partial information about the hidden state of unit#1, which can be in a healthy or a warning state while operating. Only the failure state is assumed to be observable for both units. The objective is to find an optimal opportunistic maintenance policy minimizing the long-run expected average cost per unit time. The problem is formulated and solved in the partially observable semi-Markov decision process framework. An effective computational algorithm for finding the optimal policy and the minimum average cost is developed and illustrated by a numerical example.

Keywords: condition-based maintenance, semi-Markov decision process, multivariate Bayesian control chart, partially observable system, two-unit system

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Authors: Samaniego Campoverde José Enrique, Rosero Muñoz Jorge Enrique, Luzcando Narea Lorena Elizabeth

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This paper presents a practical and theoretical model for the operation of the Tesla coil using digital signal processing. The research is based on the analysis of ten scientific papers exploring the development and operation of the Tesla coil. Starting from the Testa coil, several modifications were carried out on the Tesla coil, with the aim of amplifying the digital signal by making use of digital signal processing. To achieve this, an amplifier with a transistor and digital filters provided by MATLAB software were used, which were chosen according to the characteristics of the signals in question.

Keywords: tesla coil, digital signal process, equalizer, graphical environment

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Authors: Quan Gu, Daniel Dimitrov

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BingleSeq was developed as a shiny-based, intuitive, and comprehensive application that enables the analysis of single-Cell RNA-Sequencing count data. This was achieved via incorporating three state-of-the-art software packages for each type of RNA sequencing analysis, alongside functional annotation analysis and a way to assess the overlap of differential expression method results. At its current state, the functionality implemented within BingleSeq is comparable to that of other applications, also developed with the purpose of lowering the entry requirements to RNA Sequencing analyses. BingleSeq is available on GitHub and will be submitted to R/Bioconductor.

Keywords: bioinformatics, functional annotation analysis, single-cell RNA-sequencing, transcriptomics

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Authors: Timothy Onyenobi

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Accidental fires and its dynamic as it relates to building compartmentation and the impact of the compartment morphology, is still an on-going area of study; especially with the use of computational fluid dynamics (CFD) modeling methods. With better knowledge on this subject come better solution recommendations by fire engineers. Interviews were carried out for this study where it was identified that the response perspectives to accidental fire were different with the fire engineer providing qualitative data which is based on “what is expected in real fires” and the fire fighters provided information on “what actually obtains in real fires”. This further led to a study and analysis of two real and comprehensively instrumented fire experiments: the Open Plan Office Project by National Institute of Standard and Technology (NIST) USA (to study time to flashover) and the TF2000 project by the Building Research Establishment (BRE) UK (to test for conformity with Building Regulation requirements). The findings from the analysis of the experiments revealed the relative yet critical weakness of fire prediction using a CFD model (usually used by fire engineers) as well as explained the differences in response perspectives of the fire engineers and firefighters from the interview analysis.

Keywords: CFD, compartment fire, experiment, fire fighters, fire engineers

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Authors: Yenni Anggrayni

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The lack of awareness of the significant prevalence of school absenteeism in Indonesia, which ultimately results in high rates of school dropouts, is an unresolved issue. Therefore, this study aims to investigate the root causes of chronic absenteeism qualitatively and quantitatively using the bioecological systems paradigm in secondary schools for any reason. This study used an open-ended questionnaire to collect data from 1,148 students in six West Java Province districts/cities. Univariate and stepwise multiple logistic regression analyses produced a prediction model for the components. Analysis results show that poor teacher-student relationships, bullying by peers or teachers, negative perception of education, and lack of parental involvement in learning activities are the leading causes of chronic absenteeism. Another finding is to promote home-school partnerships to improve school climate and parental involvement in learning to address chronic absenteeism.

Keywords: bullying, chronic absenteeism, dropout of school, home-school partnerships, parental involvement

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Authors: Abongile Zweni

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As a post-apartheid strategy to redress the social imbalances of the past, local governments are tasked with the role of delivering crucial services to their constituents. Apart from political instability, evidence shows that managers in South African municipalities lack effective financial management skills and competencies. This resulted in a failure to fulfill its administrative obligations, particularly municipal financial management. Most municipalities have, however, failed in this role, which has led them to be placed under administration by the provincial government in terms of Section 139 of the constitution of the Republic of South Africa. Thus, this study proposed a leadership conceptual framework for effectively managing ever-eroding municipal finances in South Africa. The study adopted a desktop research approach to explore the key components of leadership and municipal financial management toward the development of the conceptual framework. The study fostered a better understanding of the need for transformation in relation to the current financial management practices and sustainability of a municipality. Moreover, the conceptual framework applies not only to municipalities but also to other government departments and public authorities in the country for financial management.

Keywords: leadership, municipal finance, financial performance, management skills, municipality

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Authors: Farid Arya, Trevor Hyde

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The development of vacuum glazing represents a significant advancement in the area of low heat loss glazing systems with the potential to substantially reduce building heating and cooling loads. Vacuum glazing consists of two or more glass panes hermetically sealed together around the edge with a vacuum gap between the panes. To avoid the glass panes from collapsing and touching each other under the influence of atmospheric pressure an array of support pillars is provided between the glass panes. A high level of thermal insulation is achieved by evacuating the spaces between the glass panes to a very low pressure which greatly reduces conduction and convection within the space; therefore heat transfer through this kind of glazing is significantly lower when compared with conventional insulating glazing. However, vacuum glazing is subject to inherent stresses due to atmospheric pressure and temperature differentials which can lead to fracture of the glass panes and failure of the edge seal. A flexible edge seal has been proposed to minimise the impact of these issues. In this paper, vacuum glazing system with rigid and flexible edge seals is theoretically studied and their advantages and disadvantages are discussed.

Keywords: flexible edge seal, stress, support pillar, vacuum glazing

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Authors: Shuja Alharbi

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Oil and Gas industry has many applications considered as toxic or hazardous, where process fluid leakage is not permitted and leads to health, safety, and environmental impacts. Caustic/Acidic applications, High Benzene Concentrations, Hydrogen sulfide rich oil/gas as well as liquids operating above their auto-ignition temperatures are examples of such liquids that pose as a risk to the industry operation, and for those, special arrangements are in place to allow for the safe operation environment. Pumps in the industry requires special attention, specifically in the interface between the fluid and the environment, where the potential of leakages are foreseen. Mechanical Seals are used to contain the fluid within the equipment, but the prices are ever increasing for such seals, along with maintenance, design, and operating requirements. Several alternatives to seals are being employed nowadays, such as Sealless systems, which is hermitically sealed from the atmosphere and does not require sealing. This technology is considered relatively new and requires more studies to understand the limitations and factors associated from an owner and design perspective. Things like financial factors, maintenance factors, and design limitation should be studies further in order to have a mature and reliable technical solution available to end users.

Keywords: pump, sealless, selection, failure

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Authors: Usha Sivasankaran, Seetha Raman

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Experimental work on Double skin Concrete Filled tubes (DSCFT) are a variation of CFT (Concrete- filled steel tubular) with a hollow core formed by two concentric steel tubes in – filled with concrete. Six Specimens with three different volume fractions of steel fibres are cast and tested. Experiments on circular steel tubes in – filled with steel fibre reinforced concrete (SFRC) and normal concrete have been performed to investigate the contribution of steel fibres to the load bearing capacity of Short Composite Columns. The main Variable considered in the test study is the percentage of steel fibres added to the in –filled concrete. All the specimens were tested under axial compression until failure state realisation. This project presents the percentage Variation in the compression strengths of the 3 types of Composite members taken under Study. The results show that 1.5% SFRC in filled steel columns exhibit enhanced ultimate load carrying capacity.

Keywords: composite columns, optimization of steel, double skin, DSCFT

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Authors: Zachary Blanks, Solomon Sonya

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Poaching presents a serious threat to endangered animal species, environment conservations, and human life. Additionally, some poaching activity has even been linked to supplying funds to support terrorist networks elsewhere around the world. Consequently, agencies dedicated to protecting wildlife habitats have a near intractable task of adequately patrolling an entire area (spanning several thousand kilometers) given limited resources, funds, and personnel at their disposal. Thus, agencies need predictive tools that are both high-performing and easily implementable by the user to help in learning how the significant features (e.g. animal population densities, topography, behavior patterns of the criminals within the area, etc) interact with each other in hopes of abating poaching. This research develops a classification model using machine learning algorithms to aid in forecasting future attacks that is both easy to train and performs well when compared to other models. In this research, we demonstrate how data imputation methods (specifically predictive mean matching, gradient boosting, and random forest multiple imputation) can be applied to analyze data and create significant predictions across a varied data set. Specifically, we apply these methods to improve the accuracy of adopted prediction models (Logistic Regression, Support Vector Machine, etc). Finally, we assess the performance of the model and the accuracy of our data imputation methods by learning on a real-world data set constituting four years of imputed data and testing on one year of non-imputed data. This paper provides three main contributions. First, we extend work done by the Teamcore and CREATE (Center for Risk and Economic Analysis of Terrorism Events) research group at the University of Southern California (USC) working in conjunction with the Department of Homeland Security to apply game theory and machine learning algorithms to develop more efficient ways of reducing poaching. This research introduces ensemble methods (Random Forests and Stochastic Gradient Boosting) and applies it to real-world poaching data gathered from the Ugandan rain forest park rangers. Next, we consider the effect of data imputation on both the performance of various algorithms and the general accuracy of the method itself when applied to a dependent variable where a large number of observations are missing. Third, we provide an alternate approach to predict the probability of observing poaching both by season and by month. The results from this research are very promising. We conclude that by using Stochastic Gradient Boosting to predict observations for non-commercial poaching by season, we are able to produce statistically equivalent results while being orders of magnitude faster in computation time and complexity. Additionally, when predicting potential poaching incidents by individual month vice entire seasons, boosting techniques produce a mean area under the curve increase of approximately 3% relative to previous prediction schedules by entire seasons.

Keywords: ensemble methods, imputation, machine learning, random forests, statistical analysis, stochastic gradient boosting, wildlife protection

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Authors: Hossein Agheshlui, Stephan Matthai

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In fractured rock masses open fractures tend to act as the main pathways of fluid flow. The permeability of a rock fracture depends on its aperture. The change of aperture with stress can cause a many-orders-of-magnitude change in the hydraulic conductivity at moderate compressive stress levels. In this study, the change of aperture in fragmented rocks is investigated using finite element analysis. A full 3D mechanical model of a simplified version of an outcrop analog is created and studied. A constant initial aperture value is applied to all fractures. Different far field stresses are applied and the change of aperture is monitored considering the block to block interaction. The fragmented rock layer is assumed to be sandwiched between softer layers. Frictional contact forces are defined at the layer boundaries as well as among contacting rock blocks. For a given in situ stress, the blocks slide and contact each other, resulting in new aperture distributions. A map of changed aperture is produced after applying the in situ stress and compared to the initial apertures. Subsequently, the permeability of the system before and after the stress application is compared.

Keywords: fractured rocks, mechanical model, aperture change due to stress, frictional interface

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Authors: Youngji Yoo, Seung Hwan Park, Daewoong An, Sung-Shick Kim, Jun-Geol Baek

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The yield management system is very important to produce high-quality semiconductor chips in the semiconductor manufacturing process. In order to improve quality of semiconductors, various tests are conducted in the post fabrication (FAB) process. During the test process, large amount of data are collected and the data includes a lot of information about defect. In general, the defect on the wafer is the main causes of yield loss. Therefore, analyzing the defect data is necessary to improve performance of yield prediction. The wafer bin map (WBM) is one of the data collected in the test process and includes defect information such as the fail bit patterns. The fail bit has characteristics of spatial point patterns. Therefore, this paper proposes the feature extraction method using the spatial point pattern analysis. Actual data obtained from the semiconductor process is used for experiments and the experimental result shows that the proposed method is more accurately recognize the fail bit patterns.

Keywords: semiconductor, wafer bin map, feature extraction, spatial point patterns, contour map

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Authors: Ghada M. AlSwayied, Anas N. AlHumaid

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Smoking has been linked to thousands of deaths worldwide. Around three million adults continue to use tobacco each day in Saudi Arabia; a sign that smoking is prevalent among Saudi population and obviously considered as a public health threat. Although the awareness against smoking is continuously running, it can be observed that smoking behavior increases noticeably as common practice especially among young adults across the world. Therefore, it was an essential step to guess what does motivate smokers to think about quit smoking. Can a graphic and emotional ad that is focusing on health consequences do really make a difference? A case study has been conducted on the Annual Anti-Smoking National Campaign, which was provided by Saudi Ministry of Health in the period of May 2017. To assess campaign’s effects on the number of calls, the number of visits and online access to health messages during and after the campaign period from May to August compared with the previous campaign in 2016. The educational video was selected as a primary tool to deliver the smoking health message. The Minister of Health who is acting as a role model for young adults was used to deliver a direct message to smokers with an avoidance of smoking cues usage. Due to serious consequences of smoking, the Minister of Health delivered the news of canceling the media campaign and directing the budget to smoking cessation clinics. It was shown that the positive responses and interactions on the campaign were obviously remarkable; achieving a high rate of recall and recognition. During the campaign, the number of calls to book for a visit reached 45880 phone calls, and the total online views ran to 1,253,879. Whereas, clinic visit raised up to 213 cumulative percent. Interestingly, a total number of 15,192 patients visited the clinics along three months compared with the last year campaign’s period, which was merely 4850 patients. Furthermore, around half of patients who visited the clinics were in the age from 26 to 40-year-old. There was a great progress in enhancing public awareness on: 'where to go' to assist smokers in making a quit attempt. With regard to the stages of change theory, it was predicted that by following direct-message technique; the proportion of patients in the contemplation and preparation stages would be increased. There was no process evaluation obtained to assess implementation of the campaigns’ activities.

Keywords: smoking, health promotion, role model, educational material, intervention, community health

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Authors: Raghabendra Yadav, Baochun Chen, Huihui Yuan, Zhibin Lian

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Concrete Filled Steel Tube (CFST) columns are widely used in Civil Engineering Structures due to their abundant properties. CFST-RC column is a built up column in which CFST members are connected with RC web. The CFST-RC column has excellent static and earthquake resistant properties, such as high strength, high ductility and large energy absorption capacity. CFST-RC columns have been adopted as piers in Ganhaizi Bridge in high seismic risk zone with a highest pier of 107m. The experimental investigation on scaled models of similar type of the CFST-RC pier are carried out. The experimental investigation on scaled models of similar type of the CFST-RC pier are carried out. Under cyclic loading, the hysteretic performance of CFST-RC columns, such as failure modes, ductility, load displacement hysteretic curves, energy absorption capacity, strength and stiffness degradation are studied in this paper.

Keywords: CFST, cyclic load, Ganhaizi bridge, seismic performance

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Authors: André Furtado, Hugo Rodrigues, António Arêde, Humberto Varum

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Besides characterized as non-structural elements, infill masonry (IM) walls have an important contribute in the structural response of reinforced concrete structures as proved by the damages observed recent earthquakes. In particular, the out-of-plane (OOP) collapse has been one of the most observed failure mechanism. The aim of this research is to contribute to the increase of understanding regarding the OOP behaviour of full-scale infill panels considering different variables such as panel support width and axial load on the top of columns. For this, it was carried out in the Laboratory of Earthquake and Structural Engineering (LESE) an experimental campaign of five full-scale IM walls subjected to OOP distributed cyclic loadings. Specimens with different variables such as previous in-plane damage, support conditions, axial load on the top of the columns were studied. The results will be presented and discussed along the manuscript in terms of force-displacement hysteretic curves, cracking pattern, initial stiffness, stiffness degradation and accumulative energy dissipation.

Keywords: infill masonry walls, experimental testing, out-of-plane, full-scale

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Authors: Dagmar Monett, Sven-Erik Kujat, Marvin Hartmann

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This paper discusses the use of a template-based approach for documenting high-quality requirements as part of course projects in an undergraduate Software Engineering course. In order to ease some of the Requirements Engineering activities that are performed when defining requirements by using the template, a new CASE tool, RED:WIRE, was first developed and later tested by students attending the course. Two questionnaires were conceived around a study that aims to analyze the new tool’s learnability as well as other obtained results concerning its usability in particular and the Requirements Engineering skills developed by the students in general.

Keywords: CASE tool, requirements engineering, SOPHIST template, undergraduate course

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Authors: Mustafa Albayrak, Mete Onur Kaman, Ilyas Bozkurt

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In this study, the necessary material parameters were determined to be able to conduct progressive damage analysis of layered composites under low velocity impact by using the MAT162 material module in the LS-DYNA program. The material module MAT162 based on Hashin failure criterion requires 34 parameters in total. Some of these parameters were obtained directly as a result of dynamic and quasi-static mechanical tests, and the remaining part was calibrated and determined by comparing numerical and experimental results. Woven glass/epoxy was used as the composite material and it was produced by vacuum infusion method. In the numerical model, composites are modeled as three-dimensional and layered. As a result, the acquisition of MAT162 material module parameters, which will enable progressive damage analysis, is given in detail and step by step, and the selection methods of the parameters are explained. Numerical data consistent with the experimental results are given in graphics.

Keywords: Composite Impact, Finite Element Simulation, Progressive Damage Analyze, LS-DYNA, MAT162

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Authors: Chejarla Raghunathababu, E. Logashanmugam

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An antenna is an assortment of linked devices that function together to transmit and receive radio waves as a single antenna. Antennas occur in a variety of sizes and forms, but the microstrip patch antenna outperforms other types in terms of effectiveness and prediction. These antennas are easy to generate with discreet benefits. Nevertheless, the antenna's effectiveness will be affected because of the patch's shape above a thick dielectric substrate. As a result, a double-pole rectangular microstrip antenna with nanofillers was suggested in this study. By employing nano-composite substances (Fumed Silica and Aluminum Oxide), which are composites of graphene with nanofillers, the physical characteristics of the microstrip antenna, that is, the elevation of the microstrip antenna substrate and the width of the patch microstrip antenna have been improved in this research. The surface conductivity of graphene may be modified to function at specific frequencies. In order to prepare for future wireless communication technologies, a microstrip patch antenna operating at 93 GHz resonant frequency is constructed and investigated. The goal of this study was to reduce VSWR and increase gain. The simulation yielded results for the gain and VSWR, which were 8.26 dBi and 1.01, respectively.

Keywords: graphene, microstrip patch antenna, substrate material, wireless communication, nanocomposite material

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Authors: O. P. Rahi, Manoj Kumar

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Power transformers are essential and expensive equipments in electrical power system. Dissolved gas analysis (DGA) is one of the most useful techniques to detect incipient faults in power transformers. However, the identification of the faulted location by conventional method is not always an easy task due to variability of gas data and operational variables. In this paper, an extension theory based power transformer fault diagnosis method is presented. Extension theory tries to solve contradictions and incompatibility problems. This paper first briefly introduces the basic concept of matter element theory, establishes the matter element models for three-ratio method, and then briefly discusses extension set theory. Detailed analysis is carried out on the extended relation function (ERF) adopted in this paper for transformer fault diagnosis. The detailed diagnosing steps are offered. Simulation proves that the proposed method can overcome the drawbacks of the conventional three-ratio method, such as no matching and failure to diagnose multi-fault. It enhances diagnosing accuracy.

Keywords: DGA, extension theory, ERF, fault diagnosis power transformers, fault diagnosis, fuzzy logic

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Authors: Ferdi Sönmez, Başak Buluz

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Agility in Knowledge Management (AKM) tries to capture agility requirements and their respective answers within the framework of knowledge and learning for organizations. Since it is rather a new construct, it is difficult to claim that it has been sufficiently discussed and analyzed in practical and theoretical realms. Like the term ‘agile learning’, it is also commonly addressed in the software development and information technology fields and across the related areas where those technologies can be applied. The organizational perspective towards AKM, seems to need some more time to become scholarly mature. Nevertheless, in the literature one can come across some implicit usages of this term occasionally. This research is aimed to explore the conceptual background of agility in KM, re-conceptualize it and extend it to business applications with a special focus on e-business.

Keywords: knowledge management, agility requirements, agility, knowledge

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Authors: Ninlawat Phuangchoke, Waraporn Viyanon, Setta Sasananan

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The most important process of the water treatment plant process is the coagulation using alum and poly aluminum chloride (PACL), and the value of usage per day is a hundred thousand baht. Therefore, determining the dosage of alum and PACL are the most important factors to be prescribed. Water production is economical and valuable. This research applies an artificial neural network (ANN), which uses the Levenberg–Marquardt algorithm to create a mathematical model (Soft Jar Test) for prediction chemical dose used to coagulation such as alum and PACL, which input data consists of turbidity, pH, alkalinity, conductivity, and, oxygen consumption (OC) of Bangkhen water treatment plant (BKWTP) Metropolitan Waterworks Authority. The data collected from 1 January 2019 to 31 December 2019 cover changing seasons of Thailand. The input data of ANN is divided into three groups training set, test set, and validation set, which the best model performance with a coefficient of determination and mean absolute error of alum are 0.73, 3.18, and PACL is 0.59, 3.21 respectively.

Keywords: soft jar test, jar test, water treatment plant process, artificial neural network

Procedia PDF Downloads 151