Search results for: Background Noise Statistical Modeling

Authors: Salma Ainine, Colin Ritchie, Tracey McFee

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Background: The societal impact of antibiotic resistance is a major public health concern. The increase in incidence of resistant bacteria can ultimately be fatal. Objective: To analyse the appropriateness of antibiotic prescribing in Dundee Dental Hospital, ultimately improving the safety and quality of patient care. Methods: Two examiners independently crosschecked approximately fifty consecutive prescriptions, and corresponding patient case notes, for three data collection cycles between August 2014 – September 2015. The Scottish Dental Clinical Effectiveness Program (SDCEP) Drug Prescribing for Dentistry guidelines was the standard utilised. The criteria: clinical justification, regime justification and review arrangements was measured, and compared to the standard. Results: Cycle one revealed 42% of antibiotic prescriptions were appropriate. Interventions included: multiple staff meetings, introduction of a checklist attached to the prescription pack, and production of patient leaflets explaining indications for antibiotics. Cycle two and three revealed 44%, and 30% compliance, respectively. Conclusion: The results of the audit have yet to meet target standards set out in prescribing guidelines. However, steps are being taken and change has occurred on a cultural level.

Keywords: Antibiotic resistance, antibiotic stewardship, dental infection and hygiene standards.

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Authors: Mohammed Kamil, M. M. Rahman, Rosli A. Bakar

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Modeling of hydrogen fueled engine (H₂ICE) injection system is a very important tool that can be used for explaining or predicting the effect of advanced injection strategies on combustion and emissions. In this paper, a common rail injection system (CRIS) is proposed for 4-strokes 4-cylinders hydrogen fueled engine with port injection feeding system (PIH₂ICE). For this system, a numerical one-dimensional gas dynamic model is developed considering single injection event for each injector per a cycle. One-dimensional flow equations in conservation form are used to simulate wave propagation phenomenon throughout the CR (accumulator). Using this model, the effect of common rail on the injection system characteristics is clarified. These characteristics include: rail pressure, sound velocity, rail mass flow rate, injected mass flow rate and pressure drop across injectors. The interaction effects of operational conditions (engine speed and rail pressure) and geometrical features (injector hole diameter) are illustrated; and the required compromised solutions are highlighted. The CRIS is shown to be a promising enhancement for PIH₂ICE.

Keywords: Common rail, hydrogen engine, port injection, wave propagation.

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Authors: N. Neysani Samany, M.R. Delavar, N. Chrisman, M.R. Malek

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Location-aware computing is a type of pervasive computing that utilizes user-s location as a dominant factor for providing urban services and application-related usages. One of the important urban services is navigation instruction for wayfinders in a city especially when the user is a tourist. The services which are presented to the tourists should provide adapted location aware instructions. In order to achieve this goal, the main challenge is to find spatial relevant objects and location-dependent information. The aim of this paper is the development of a reusable location-aware model to handle spatial relevancy parameters in urban location-aware systems. In this way we utilized ontology as an approach which could manage spatial relevancy by defining a generic model. Our contribution is the introduction of an ontological model based on the directed interval algebra principles. Indeed, it is assumed that the basic elements of our ontology are the spatial intervals for the user and his/her related contexts. The relationships between them would model the spatial relevancy parameters. The implementation language for the model is OWLs, a web ontology language. The achieved results show that our proposed location-aware model and the application adaptation strategies provide appropriate services for the user.

Keywords: Spatial relevancy, Context-aware, Ontology, Modeling

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Authors: Shaukat Wasi, Zubair A. Shaikh, Sajid Qasmi, Hussain Sachwani, Rehman Lalani, Aamir Chagani

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Automatic Extraction of Event information from social text stream (emails, social network sites, blogs etc) is a vital requirement for many applications like Event Planning and Management systems and security applications. The key information components needed from Event related text are Event title, location, participants, date and time. Emails have very unique distinctions over other social text streams from the perspective of layout and format and conversation style and are the most commonly used communication channel for broadcasting and planning events. Therefore we have chosen emails as our dataset. In our work, we have employed two statistical NLP methods, named as Finite State Machines (FSM) and Hidden Markov Model (HMM) for the extraction of event related contextual information. An application has been developed providing a comparison among the two methods over the event extraction task. It comprises of two modules, one for each method, and works for both bulk as well as direct user input. The results are evaluated using Precision, Recall and F-Score. Experiments show that both methods produce high performance and accuracy, however HMM was good enough over Title extraction and FSM proved to be better for Venue, Date, and time.

Keywords: Emails, Event Extraction, Event Detection, Finite state machines, Hidden Markov Model.

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Authors: Kai-Chieh Lin, Chih-Fu Wu, Hsiang Ling Hsu, Yung-Hsiang Tu, Chia-Chen Wu

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With the rapid development of computer technology, the design of computers and keyboards moves towards a trend of slimness. The change of mobile input devices directly influences users’ behavior. Although multi-touch applications allow entering texts through a virtual keyboard, the performance, feedback, and comfortableness of the technology is inferior to traditional keyboard, and while manufacturers launch mobile touch keyboards and projection keyboards, the performance has not been satisfying. Therefore, this study discussed the design factors of slim pressure-sensitive keyboards. The factors were evaluated with an objective (accuracy and speed) and a subjective evaluation (operability, recognition, feedback, and difficulty) depending on the shape (circle, rectangle, and L-shaped), thickness (flat, 3mm, and 6mm), and force (35±10g, 60±10g, and 85±10g) of the keyboard. Moreover, MANOVA and Taguchi methods (regarding signal-to-noise ratios) were conducted to find the optimal level of each design factor. The research participants, by their typing speed (30 words/ minute), were divided in two groups. Considering the multitude of variables and levels, the experiments were implemented using the fractional factorial design. A representative model of the research samples were established for input task testing. The findings of this study showed that participants with low typing speed primarily relied on vision to recognize the keys, and those with high typing speed relied on tactile feedback that was affected by the thickness and force of the keys. In the objective and subjective evaluation, a combination of keyboard design factors that might result in higher performance and satisfaction was identified (L-shaped, 3mm, and 60±10g) as the optimal combination. The learning curve was analyzed to make a comparison with a traditional standard keyboard to investigate the influence of user experience on keyboard operation. The research results indicated the optimal combination provided input performance to inferior to a standard keyboard. The results could serve as a reference for the development of related products in industry and for applying comprehensively to touch devices and input interfaces which are interacted with people.

Keywords: Input performance, mobile device, slim keyboard, tactile feedback.

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Authors: W. Kultangwattana, K. Somkantha, P. Phuangsuwan

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This paper presents a technique for diagnosis of the abdominal aorta aneurysm in magnetic resonance imaging (MRI) images. First, our technique is designed to segment the aorta image in MRI images. This is a required step to determine the volume of aorta image which is the important step for diagnosis of the abdominal aorta aneurysm. Our proposed technique can detect the volume of aorta in MRI images using a new external energy for snakes model. The new external energy for snakes model is calculated from Law-s texture. The new external energy can increase the capture range of snakes model efficiently more than the old external energy of snakes models. Second, our technique is designed to diagnose the abdominal aorta aneurysm by Bayesian classifier which is classification models based on statistical theory. The feature for data classification of abdominal aorta aneurysm was derived from the contour of aorta images which was a result from segmenting of our snakes model, i.e., area, perimeter and compactness. We also compare the proposed technique with the traditional snakes model. In our experiment results, 30 images are trained, 20 images are tested and compared with expert opinion. The experimental results show that our technique is able to provide more accurate results than 95%.

Keywords: Adbominal Aorta Aneurysm, Bayesian Classifier, Snakes Model, Texture Feature.

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Authors: Yu Shi, Rong Liu, Jingyun Lv

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Compression textiles with ergonomic-fit and controllable pressure performance have demonstrated positive effect on prevention and treatment of chronic venous insufficiency (CVI). Well-designed compression textile products contribute to improving user compliance in their daily application. This study explored the effects of multiple knitting variables (yarn-machinery settings) on the physical-mechanical properties and the produced pressure magnitudes of tubular compression fabrics (TCFs) through experimental testing and multiple regression modeling. The results indicated that fabric physical (stitch densities and circumference) and mechanical (tensile) properties were affected by the linear density of inlay yarns, which, to some extent, influenced pressure magnitudes of the TCFs. Knitting variables (e.g., feeding velocity of inlay yarns and loop size settings) can alter circumferences and tensile properties of tubular fabrics, respectively, and significantly varied pressure values of the TCFs. This study enhanced the understanding of the effects of knitting factors on pressure controlling of TCFs, thus facilitating dimension and pressure design of compression textiles in future development.

Keywords: Laid-in knitted fabric, yarn-machinery settings, pressure magnitudes, quantitative analysis, compression textiles.

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Authors: Kaushik Sathupadi, Sandesh Achar

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Human action recognition (HAR) modeling is a critical task in machine learning. These systems require better techniques for recognizing body parts and selecting optimal features based on vision sensors to identify complex action patterns efficiently. Still, there is a considerable gap and challenges between images and videos, such as brightness, motion variation, and random clutters. This paper proposes a robust approach for classifying human actions over cloud-based image data. First, we apply pre-processing and detection, human and outer shape detection techniques. Next, we extract valuable information in terms of cues. We extract two distinct features: fuzzy local binary patterns and sequence representation. Then, we applied a greedy, randomized adaptive search procedure for data optimization and dimension reduction, and for classification, we used a random forest. We tested our model on two benchmark datasets, AAMAZ and the KTH Multi-view Football datasets. Our HAR framework significantly outperforms the other state-of-the-art approaches and achieves a better recognition rate of 91% and 89.6% over the AAMAZ and KTH Multi-view Football datasets, respectively.

Keywords: Computer vision, human motion analysis, random forest, machine learning.

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Authors: John Kabuba, Antoine Mulaba-Bafubiandi, Kim Battle

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This paper presents a critical study about the application of Neural Networks to ion-exchange process. Ionexchange is a complex non-linear process involving many factors influencing the ions uptake mechanisms from the pregnant solution. The following step includes the elution. Published data presents empirical isotherm equations with definite shortcomings resulting in unreliable predictions. Although Neural Network simulation technique encounters a number of disadvantages including its “black box", and a limited ability to explicitly identify possible causal relationships, it has the advantage to implicitly handle complex nonlinear relationships between dependent and independent variables. In the present paper, the Neural Network model based on the back-propagation algorithm Levenberg-Marquardt was developed using a three layer approach with a tangent sigmoid transfer function (tansig) at hidden layer with 11 neurons and linear transfer function (purelin) at out layer. The above mentioned approach has been used to test the effectiveness in simulating ion exchange processes. The modeling results showed that there is an excellent agreement between the experimental data and the predicted values of copper ions removed from aqueous solutions.

Keywords: Copper, ion-exchange process, neural networks, simulation

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Authors: L. L. Ivy-Yap, H. A. Bekhet

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As the Malaysian residential electricity consumption continued to increase rapidly, effective energy policies, which address factors affecting residential electricity consumption, is urgently needed. This study attempts to investigate the relationship between residential electricity consumption (EC), real disposable income (Y), price of electricity (Pe) and population (Po) in Malaysia for 1978-2011 period. Unlike previous studies on Malaysia, the current study focuses on the residential sector, a sector that is important for the contemplation of energy policy. The Phillips-Perron (P-P) unit root test is employed to infer the stationarity of each variable while the bound test is executed to determine the existence of co-integration relationship among the variables, modelled in an Autoregressive Distributed Lag (ARDL) framework. The CUSUM and CUSUM of squares tests are applied to ensure the stability of the model. The results suggest the existence of long-run equilibrium relationship and bidirectional Granger causality between EC and the macroeconomic variables. The empirical findings will help policy makers of Malaysia in developing new monitoring standards of energy consumption. As it is the major contributing factor in economic growth and CO₂ emission, there is a need for more proper planning in Malaysia to attain future targets in order to cut emissions.

Keywords: Co-integration, Elasticity, Granger causality, Malaysia, Residential electricity consumption.

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Authors: K. Mushtaq, M. Umar

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The research aims to study the association between job satisfaction, motivation and the five factors of organizational citizenship behavior (i.e. Altruism, Conscientiousness, Sportsmanship, Courtesy and Civic virtue) among Public Sector Employees in Pakistan. In this research Structure Equation Modeling with confirmatory factor analysis was used to test the relationship between two independent and five dependent variables. Data was collected through questionnaire survey from 152 Public Servants Working in Gujrat District-Pakistan in different capacities. Stratified Random Sampling Technique was used to conduct this survey. The results of the study indicate that five factors of OCB have positive significant relation with both motivation and job satisfaction except the relationship of Civic Virtue with Motivation. The research findings implicate that factors other than motivation and job satisfaction may also affect OCB. Likewise, all the five factors of OCB may not be present in all populations. Thus, Managers must concentrate on increasing motivation and job satisfaction to increase OCB. Furthermore, the present research gives a direction to future researchers to use more independent variables (e.g. Culture, leadership, workplace environment, various job attitudes, types of motivation, etc.) on different types of populations with larger sample size in order to find the reasons behind insignificant relationship of civic virtue with Motivation in the research in hand and to generalize the tested model.

Keywords: Five Factors of Organizational Citizenship Behavior (OCB), Motivation, Job Satisfaction, Public Sector Employees in Pakistan.

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Authors: Vidhu Mitha Goutham, Ruma Mukherjee

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The low availability of well-trained, unlimited, dynamic-access models for specific languages makes it hard for corporate users to adopt quick translation techniques and incorporate them into product solutions. As translation tasks increasingly require a dynamic sequence learning curve; stable, cost-free opensource models are scarce. We survey and compare current translation techniques and propose a modified sequence to sequence model repurposed with attention techniques. Sequence learning using an encoder-decoder model is now paving the path for higher precision levels in translation. Using a Convolutional Neural Network (CNN) encoder and a Recurrent Neural Network (RNN) decoder background, we use Fairseq tools to produce an end-to-end bilingually trained Spanish-English machine translation model including source language detection. We acquire competitive results using a duo-lingo-corpus trained model to provide for prospective, ready-made plug-in use for compound sentences and document translations. Our model serves a decent system for large, organizational data translation needs. While acknowledging its shortcomings and future scope, it also identifies itself as a well-optimized deep neural network model and solution.

Keywords: Attention, encoder-decoder, Fairseq, Seq2Seq, Spanish, translation.

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Authors: Jinliang Yuan, Jong-Sung Yu, Bengt Sundén

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A computational fluid dynamics (CFD) model is developed for rechargeable non-aqueous electrolyte lithium-air batteries with a partial opening for oxygen supply to the cathode. Multi-phase transport phenomena occurred in the battery are considered, including dissolved lithium ions and oxygen gas in the liquid electrolyte, solid-phase electron transfer in the porous functional materials and liquid-phase charge transport in the electrolyte. These transport processes are coupled with the electrochemical reactions at the active surfaces, and effects of discharge reaction-generated solid Li2O2 on the transport properties and the electrochemical reaction rate are evaluated and implemented in the model. The predicted results are discussed and analyzed in terms of the spatial and transient distribution of various parameters, such as local oxygen concentration, reaction rate, variable solid Li2O2 volume fraction and porosity, as well as the effective diffusion coefficients. It is found that the effect of the solid Li2O2 product deposited at the solid active surfaces is significant on the transport phenomena and the overall battery performance.

Keywords: Computational Fluid Dynamics (CFD), Modeling, Multi-phase, Transport Phenomena, Lithium-air battery.

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Authors: Ahmed M. Hemeida, Wael A. Farag, Osama A. Mahgoub

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This paper focuses on developing an integrated reliable and sophisticated model for ultra large wind turbines And to study the performance and analysis of vector control on large wind turbines. With the advance of power electronics technology, direct driven multi-pole radial flux PMSG (Permanent Magnet Synchronous Generator) has proven to be a good choice for wind turbines manufacturers. To study the wind energy conversion systems, it is important to develop a wind turbine simulator that is able to produce realistic and validated conditions that occur in real ultra MW wind turbines. Three different packages are used to simulate this model, namely, Turbsim, FAST and Simulink. Turbsim is a Full field wind simulator developed by National Renewable Energy Laboratory (NREL). The wind turbine mechanical parts are modeled by FAST (Fatigue, Aerodynamics, Structures and Turbulence) code which is also developed by NREL. Simulink is used to model the PMSG, full scale back to back IGBT converters, and the grid.

Keywords: FAST, Permanent Magnet Synchronous Generator(PMSG), TurbSim, Vector Control and Pitch Control

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Authors: S. Deswal, M. Pal

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The paper aims to compare the performance of vertical and inclined multiple plunging jets and to model and predict their mass transfer capacity by multi-linear regression based approach. The multiple vertical plunging jets have jet impact angle of θ = 90^O; whereas, multiple inclined plunging jets have jet impact angle of θ = 60^O. The results of the study suggests that mass transfer is higher for multiple jets, and inclined multiple plunging jets have up to 1.6 times higher mass transfer than vertical multiple plunging jets under similar conditions. The derived relationship, based on multi-linear regression approach, has successfully predicted the volumetric mass transfer coefficient (K_La) from operational parameters of multiple plunging jets with a correlation coefficient of 0.973, root mean square error of 0.002 and coefficient of determination of 0.946. The results suggests that predicted overall mass transfer coefficient is in good agreement with actual experimental values; thereby, suggesting the utility of derived relationship based on multi-linear regression based approach and can be successfully employed in modeling mass transfer by multiple plunging jets.

Keywords: Mass transfer, multiple plunging jets, multi-linear regression.

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Authors: Melodi Mbuyi Mata, Blessing Olamide Taiwo, Afolabi Ayodele David

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The purpose of this research is to create empirical models for assessing the profitability of granite aggregate production in Akure, Ondo state aggregate quarries. In addition, an Artificial Neural Network (ANN) model and multivariate predicting models for granite profitability were developed in the study. A formal survey questionnaire was used to collect data for the study. The data extracted from the case study mine for this study include granite marketing operations, royalty, production costs, and mine production information. The following methods were used to achieve the goal of this study: descriptive statistics, MATLAB 2017, and SPSS16.0 software in analyzing and modeling the data collected from granite traders in the study areas. The ANN and Multi Variant Regression models' prediction accuracy was compared using a coefficient of determination (R2), Root Mean Square Error (RMSE), and mean square error (MSE). Due to the high prediction error, the model evaluation indices revealed that the ANN model was suitable for predicting generated profit in a typical quarry. More quarries in Nigeria's southwest region and other geopolitical zones should be considered to improve ANN prediction accuracy.

Keywords: National development, granite, profitability assessment, ANN models.

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Authors: Raif Parlakkaya, Huseyin Cetin, Duygu Irdiren

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By the development of World Wide Web, the usage rate of Internet has rapidly grown globally; and provided a basis for the emergence of electronic business. As well as other sectors, the banking sector has adopted the use of internet with the developments in information and communication technologies. Due to the public disclosure and transparency principle of Corporate Governance, the importance of information disclosure of banks on their web sites has increased significantly. For the purpose of this study, a Bank Disclosure Attribute Index (BDAI) in Turkey has been constructed through classifying the information disclosure on banks’ web sites into general, financial, investors and corporate governance attributes. All 47 banks in Turkish Banking System have been evaluated according to the index with the aim of providing a comparison between banks. By Chi Square Test, Pearson Correlation, T-Test, and ANOVA statistical tools, it has been concluded that the majority of banks in Turkey have shared information on their web sites adequately with respect to their total index score. Although there is a positive correlation between various types of information on banks’ web sites, there is no uniformity among them. Also, no significant difference between various types of information disclosure and bank types has been observed. Compared with the total index score averages of the five largest banks in Turkey, there are some banks that need to improve the content of their web sites.

Keywords: Banking sector, public disclosure, Turkey, web site evaluation.

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Authors: Mutuku Muvengei, John Kihiu

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In this paper, a bond graph dynamic model for a valvecontrolled hydraulic cylinder has been developed. A simplified bond graph model of the inter-actuator interactions in a multi-cylinder hydraulic system has also been presented. The overall bond graph model of a valve-controlled hydraulic cylinder was developed by combining the bond graph sub-models of the pump, spool valve and the actuator using junction structures. Causality was then assigned in order to obtain a computational model which could be simulated. The causal bond graph model of the hydraulic cylinder was verified by comparing the open loop state responses to those of an ODE model which had been developed in literature based on the same assumptions. The results were found to correlate very well both in the shape of the curves, magnitude and the response times, thus indicating that the developed model represents the hydraulic dynamics of a valve-controlled cylinder. A simplified model for interactuator interaction was presented by connecting an effort source with constant pump pressure to the zero-junction from which the cylinders in a multi-cylinder system are supplied with a constant pressure from the pump. On simulating the state responses of the developed model under different situations of cylinder operations, indicated that such a simple model can be used to predict the inter-actuator interactions.

Keywords: Bond graphs, Inter-actuator interactions, Valvecontrolledhydraulic cylinder.

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Authors: Jamal S. Yassin

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This paper is to formulate a mathematical model to predict the amounts of the emissions produced from the combustion process of the gas turbine unit of the jet engine. These emissions have bad impacts on the environment if they are out of standards, which cause real threats to all type of life on the earth. The amounts of the emissions from the gas turbine engine are functions to many operational and design factors. In landing-takeoff (LTO) these amounts are not the same as in taxi or cruise of the plane using jet engines, because of the difference in the activity period during these operating modes. These emissions can be affected by several physical and chemical variables, such as fuel type, fuel to air ratio or equivalence ratio, flame temperature, combustion pressure, in addition to some inlet conditions such as ambient temperature and air humidity. To study the influence of these variables on the amounts of these emissions during the combustion process in the gas turbine unit, a computer program has been developed by using the visual basic 6 software. Here, the analysis of the combustion process is carried out by considering it as a chemical reaction with shifting equilibrium to find the products of the combustion of the octane fuel, at different equivalence ratios, compressor pressure ratios (CPR) and combustion temperatures. The results obtained have shown that there is noticeable influence of the equivalence ratio, CPR, and the combustion temperature on the amounts of the main emissions which are considered pollutants, such as CO, CO₂ and NO.

Keywords: Mathematical model, gas turbine unit, equivalence ratio, emissions, shifting equilibrium.

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Authors: Abbas Siefi, Mohammad Javad Karimifar

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We study the spatial design of experiment and we want to select a most informative subset, having prespecified size, from a set of correlated random variables. The problem arises in many applied domains, such as meteorology, environmental statistics, and statistical geology. In these applications, observations can be collected at different locations and possibly at different times. In spatial design, when the design region and the set of interest are discrete then the covariance matrix completely describe any objective function and our goal is to choose a feasible design that minimizes the resulting uncertainty. The problem is recast as that of maximizing the determinant of the covariance matrix of the chosen subset. This problem is NP-hard. For using these designs in computer experiments, in many cases, the design space is very large and it's not possible to calculate the exact optimal solution. Heuristic optimization methods can discover efficient experiment designs in situations where traditional designs cannot be applied, exchange methods are ineffective and exact solution not possible. We developed a GA algorithm to take advantage of the exploratory power of this algorithm. The successful application of this method is demonstrated in large design space. We consider a real case of design of experiment. In our problem, design space is very large and for solving the problem, we used proposed GA algorithm.

Keywords: Spatial design of experiments, maximum entropy sampling, computer experiments, genetic algorithm.

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Authors: Mustafa Bayram Gücen, Coşkun Yakar

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In this study, we have investigated the strict stability of fuzzy differential systems and we compare the classical notion of strict stability criteria of ordinary differential equations and the notion of strict stability of fuzzy differential systems. In addition that, we present definitions of stability and strict stability of fuzzy differential equations and also we have some theorems and comparison results. Strict Stability is a different stability definition and this stability type can give us an information about the rate of decay of the solutions. Lyapunov’s second method is a standard technique used in the study of the qualitative behavior of fuzzy differential systems along with a comparison result that allows the prediction of behavior of a fuzzy differential system when the behavior of the null solution of a fuzzy comparison system is known. This method is a usefull for investigating strict stability of fuzzy systems. First of all, we present definitions and necessary background material. Secondly, we discuss and compare the differences between the classical notion of stability and the recent notion of strict stability. And then, we have a comparison result in which the stability properties of the null solution of the comparison system imply the corresponding stability properties of the fuzzy differential system. Consequently, we give the strict stability results and a comparison theorem. We have used Lyapunov second method and we have proved a comparison result with scalar differential equations.

Keywords: Fuzzy systems, fuzzy differential equations, fuzzy stability, strict stability.

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Authors: Natalia Podkhodova, Olga Sheremeteva, Mariia Soldaeva

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Creating favourable conditions for students’ comprehension of mathematical content is one of the primary problems in teaching mathematics in secondary school. The fact of comprehension includes the ability to build a working situational model and thus becomes an important means of solving mathematical problems. This paper describes a holistic approach to teaching mathematics designed to address the primary challenges of such teaching; specifically, the challenge of students’ comprehension. Essentially, this approach consists of (1) establishing links between the attributes of the notion: the sense, the meaning, and the term; (2) taking into account the components of student’s subjective experience—value-based emotions, contextual, procedural and communicative—during the educational process; (3) linking together different ways to present mathematical information; (4) identifying and leveraging the relationships between real, perceptual and conceptual (scientific) mathematical spaces by applying real-life situational modelling. The article describes approaches to the practical use of these foundational concepts. Identifying how proposed methods and techniques influence understanding of material used in teaching mathematics was the primary goal. The study included an experiment in which 256 secondary school students took part: 142 in the study group and 114 in the control group. All students in these groups had similar levels of achievement in math and studied math under the same curriculum. In the course of the experiment, comprehension of two topics — “Derivative” and “Trigonometric functions”—was evaluated. Control group participants were taught using traditional methods. Students in the study group were taught using the holistic method: under teacher’s guidance, they carried out assignments designed to establish linkages between notion’s characteristics, to convert information from one mode of presentation to another, as well as assignments that required the ability to operate with all modes of presentation. Identification, accounting for and transformation of subjective experience were associated with methods of stimulating the emotional value component of the studied mathematical content (discussions of lesson titles, assignments aimed to create study dominants, performing theme-related physical exercise ...) The use of techniques that forms inter-subject notions based on linkages between, perceptual real and mathematical conceptual spaces proved to be of special interest to the students. Results of the experiment were analysed by presenting students in each of the groups with a final test in each of the studied topics. The test included assignments that required building real situational models. Statistical analysis was used to aggregate test results. Pierson criterion x2 was used to reveal statistics significance of results (pass-fail the modelling test). Significant difference of results was revealed (p < 0.001), which allowed to conclude that students in the study group showed better comprehension of mathematical information than those in the control group. The total number of completed assignments of each student was analysed as well, with average results calculated for each group. Statistical significance of result differences against the quantitative criterion (number of completed assignments) was determined using Student’s t-test, which showed that students in the study group completed significantly more assignments than those in the control group (p = 0.0001). Authors thus come to the conclusion that suggested increase in the level of comprehension of study material took place as a result of applying implemented methods and techniques.

Keywords: Comprehension of mathematical content, holistic approach to teaching mathematics in secondary school, subjective experience, technology of the formation of inter-subject notions.

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Authors: Marcia T. Mitchell

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This research uses computational linguistics, an area of study that employs a computer to process natural language, and aims at discerning the patterns that exist in declarative sentences used in technical texts. The approach is mathematical, and the focus is on instructional texts found on web pages. The technique developed by the author and named the MAYA Semantic Technique is used here and organized into four stages. In the first stage, the parts of speech in each sentence are identified. In the second stage, the subject of the sentence is determined. In the third stage, MAYA performs a frequency analysis on the remaining words to determine the verb and its object. In the fourth stage, MAYA does statistical analysis to determine the content of the web page. The advantage of the MAYA Semantic Technique lies in its use of mathematical principles to represent grammatical operations which assist processing and accuracy if performed on unambiguous text. The MAYA Semantic Technique is part of a proposed architecture for an entire web-based intelligent tutoring system. On a sample set of sentences, partial semantics derived using the MAYA Semantic Technique were approximately 80% accurate. The system currently processes technical text in one domain, namely Cµ programming. In this domain all the keywords and programming concepts are known and understood.

Keywords: Natural language understanding, computational linguistics, knowledge representation, linguistic theories.

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Authors: D. Y. Bawa, M. I. Ribah, I. S. Jega, V. O. Oyedepo

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This study was conducted to determine the physicochemical characteristics and heavy metal concentration (Cadmium (Cd), Copper (Cu), Iron (Fe), Lead (Pb) and Zinc (Zn)) in freshwater from Jega river. 30 water samples were collected in two 1-liter sterile plastic containers from three designated sampling points, namely; Station A (before the bridge; upstream), Station B (at the bridge where human activities such as washing of cars, motorbike, clothes, bathing and other household materials are concentrated), Station C (after the bridge; downstream) fortnightly, between March and July 2014. Results indicated that the highest pH mean value of 7.08 ± 1.12 was observed in station C, the highest conductivity with the mean 58.75 ± 7.87 µs/cm was observed at station A, the highest mean value of the water total hardness was observed at station A (54 ± 16.11 mg/L), the highest mean value of nitrate deposit was observed in station A (1.66 ± 1.33 mg/L), the highest mean value of alkalinity was observed at station B (51.33 ± 6.66 mg/L) and the highest mean (39.56 ± 3.24 mg/L) of total dissolved solids was observed at station A. The highest concentration mean value of Fe was observed in station C (65.33 ± 4.50 mg/L), the highest concentrations of Cd was observed in station C (0.99 ± 0.36 mg/L), the mean value of 2.13 ± 1.99 mg/L was the highest concentration of Zn observed in station B, the concentration of Pb was not detected (ND) and the highest concentration of Cu with the mean value of 0.43 ± 0.16 mg/L was observed in station B, while the lowest concentration was observed at station C (0.27 ± 0.26 mg/L). Statistical analysis shows no significant difference (P > 0.05) among the sampling stations for both the physicochemical characteristics and heavy metal concentrations. The results were found to be within the internationally acceptable standard limits.

Keywords: Assessment, freshwater, heavy metal concentration, physicochemical.

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Authors: Niall J. English, Sylvia Leatham, Maria Isabel Meza Silva, Denis P. Dowling

Abstract:

The training and education of under- and post-graduate students can be promoted by more active learning especially in engineering, overcoming more passive and vicarious experiences and approaches in their documented effectiveness. However, the possibility of outreach to young pupils and school-children in primary and secondary schools is a lesser explored area in terms of Education and Public Engagement (EPE) efforts – as relates to feedback and influence on shaping 3rd-level engineering training and education. Therefore, the outreach and school-visit agenda constitutes an interesting avenue to observe how active learning, careers stimulus and EPE efforts for young children and teenagers can teach the university sector, to improve future engineering-teaching standards and enhance both quality and capabilities of practice. This intervention involved careers-outreach efforts to lead to statistical determinations of motivations towards engineering, manufacturing and training. The aim was to gauge to what extent this intervention would lead to an increased careers awareness in engineering, using the method of the schools-visits programme as the means for so doing. It was found that this led to an increase in engagement by school pupils with engineering as a career option and a greater awareness of the importance of manufacturing. 

Keywords: outreach, education and public engagement, careers, peer interactions

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Authors: Guenther Schuh, Christina Koenig, Nico Schoen, Markus Wellensiek

Abstract:

Identification and selection of appropriate product and manufacturing technologies are key factors for competitiveness and market success of technology-based companies. Therefore, many companies perform technology intelligence (TI) activities to ensure the identification of evolving technologies at the right time. Technology monitoring is one of the three base activities of TI, besides scanning and scouting. As the technological progress is accelerating, more and more technologies are being developed. Against the background of limited resources it is therefore necessary to focus TI activities. In this paper we propose a concept for defining appropriate search fields for technology monitoring. This limitation of search space leads to more concentrated monitoring activities. The concept will be introduced and demonstrated through an anonymized case study conducted within an industry project at the Fraunhofer Institute for Production Technology IPT. The described concept provides a customized monitoring approach, which is suitable for use in technology-oriented companies. It is shown in this paper that the definition of search fields and search tasks are suitable methods to define topics of interest and thus to align monitoring activities. Current as well as planned product, production and material technologies and existing skills, capabilities and resources form the basis for derivation of relevant search areas. To further improve the concept of technology monitoring the proposed concept should be extended during future research e.g. by the definition of relevant monitoring parameters.

Keywords: Monitoring radar, search field, technology intelligence, technology monitoring.

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Authors: M. R. Ghasemi, R. Ghiasi, H. Varaee

Abstract:

Surrogate model has received increasing attention for use in detecting damage of structures based on vibration modal parameters. However, uncertainties existing in the measured vibration data may lead to false or unreliable output result from such model. In this study, an efficient approach based on Monte Carlo simulation is proposed to take into account the effect of uncertainties in developing a surrogate model. The probability of damage existence (PDE) is calculated based on the probability density function of the existence of undamaged and damaged states. The kriging technique allows one to genuinely quantify the surrogate error, therefore it is chosen as metamodeling technique. Enhanced version of ideal gas molecular movement (EIGMM) algorithm is used as main algorithm for model updating. The developed approach is applied to detect simulated damage in numerical models of 72-bar space truss and 120-bar dome truss. The simulation results show the proposed method can perform well in probability-based damage detection of structures with less computational effort compared to direct finite element model.

Keywords: Enhanced ideal gas molecular movement, Kriging, probability-based damage detection, probability of damage existence, surrogate modeling, uncertainty quantification.

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Authors: Laila Seada, Hanan Oreiby, Fawaz Al Rashid, Ashraf Negm

Abstract:

Background and Objective: In most areas of the world, the incidence of thyroid cancer has been increasing over the last decade, mostly due to a combination of early detection of the neoplasm resulting from sensitive procedures and increased population exposure to radiation and unrecognized carcinogens. Methods: Cases of thyroid cancer have been retrieved from the cancer registry at King Khalid Hospital during the period from August 2012 to April 2016. Age, gender and histopathologic types have been recorded. Results: Thyroid carcinoma ranked as the second most common malignancy in females (25%) after breast cancer (31%). It constituted 20.8% of all newly diagnosed cancer cases. As for males, it ranked the 4^th type of malignancy after gastrointestinal cancer, lymphomas and soft tissue sarcomas. Mean age for females and males was 38.7 +/- 13.2 and 60.25 +/- 11.5 years, respectively, and the difference between the two groups was statistically significant (p value = 0.0001). Fifty-five (82%) were papillary carcinomas including 10 follicular variant of papillary (FVPC), and eight papillary micro carcinomas (PMC) and two tall cell/oncocytic variants. Follicular carcinomas constituted two (3.1%), while two (3.1%) were anaplastic, and two (3.1%) were medullary. Conclusion: Thyroid cancer incidence in Hail is ranking as the 2^nd most common female malignancy similar to other regions in the Kingdom. However, this high incidence contrasts with much lower rates worldwide.

Keywords: Thyroid, Hail, papillary, micro carcinoma.

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Authors: T. C. Manjunath, B. Bandyopadhyay

Abstract:

This paper deals with the design of a periodic output feedback controller for a flexible beam structure modeled with Timoshenko beam theory, Finite Element Method, State space methods and embedded piezoelectrics concept. The first 3 modes are considered in modeling the beam. The main objective of this work is to control the vibrations of the beam when subjected to an external force. Shear piezoelectric sensors and actuators are embedded into the top and bottom layers of a flexible aluminum beam structure, thus making it intelligent and self-adaptive. The composite beam is divided into 5 finite elements and the control actuator is placed at finite element position 1, whereas the sensor is varied from position 2 to 5, i.e., from the nearby fixed end to the free end. 4 state space SISO models are thus developed. Periodic Output Feedback (POF) Controllers are designed for the 4 SISO models of the same plant to control the flexural vibrations. The effect of placing the sensor at different locations on the beam is observed and the performance of the controller is evaluated for vibration control. Conclusions are finally drawn.

Keywords: Smart structure, Timoshenko beam theory, Periodic output feedback control, Finite Element Method, State space model, SISO, Embedded sensors and actuators, Vibration control.

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Authors: M. H. Mehrabi, S. S. Ghodsi, Zainah Ibrahim, Meldi Suhatril

Abstract:

Standard routes for upgrading existing buildings to improve their seismic response can be expensive in terms of both time and cost due to the modifications required to the foundations. As a result, interest has grown in the installation of viscoelastic dampers (VEDs) in mid and high-rise buildings. Details of a low-cost viscoelastic passive control device, the rotary rubber braced damper (RRBD), are presented in this paper. This design has the added benefits of being lightweight and simple to install. Experimental methods and finite element modeling were used to assess the performance of the proposed VED design and its effect on building response during earthquakes. The analyses took into account the behaviors of non-linear materials and large deformations. The results indicate that the proposed RRBD provides high levels of energy absorption, ensuring the stable cyclical response of buildings in all scenarios considered. In addition, time history analysis was employed in this study to evaluate the RRBD’s ability to control the displacements and accelerations experienced by steel frame structures. It was demonstrated that the device responds well even at low displacements, highlighting its suitability for use in seismic events of varying severity.

Keywords: Dynamic response, passive control, performance test, seismic protection.

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