Search results for: iterative methods
15088 A Case Study on the Guidelines for Application of Project Management Methods in Infrastructure Projects
Authors: Fernanda Varella Borges, Silvio Burrattino Melhado
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Motivated by the importance of public infrastructure projects in the civil construction chain, this research shows the study of project management methods and the infrastructure projects’ characteristics. The research aims at the objective of improving management efficiency by proposing guidelines for the application of project management methods in infrastructure projects. Through literature review and case studies, the research analyses two major infrastructure projects underway in Brazil, identifying the critical points for achieving its success. As a result, the proposed guidelines indicate that special attention should be given to the management of stakeholders, focusing on their knowledge and experience, their different interests, the efficient management of their communication, and their behavior in the day-by-day project management process.Keywords: construction, infrastructure, project management, public projects
Procedia PDF Downloads 49415087 Microwave and Ultrasound Assisted Extraction of Pectin from Mandarin and Lemon Peel: Comparisons between Sources and Methods
Authors: Pınar Karbuz, A. Seyhun Kıpcak, Mehmet B. Piskin, Emek Derun, Nurcan Tugrul
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Pectin is a complex colloidal polysaccharide, found on the cell walls of all young plants such as fruit and vegetables. It acts as a thickening, stabilizing and gelling agent in foods. Pectin was extracted from mandarin and lemon peels using ultrasound and microwave assisted extraction methods to compare with these two different sources and methods of pectin production. In this work, the effect of microwave power (360, 600 W) and irradiation time (1, 2, 3 min) on the yield of extracted pectin from mandarin and lemon peels for microwave assisted extraction (MAE) were investigated. For ultrasound assisted extraction (UAE), parameters were determined as temperature (60, 75 °C) and sonication time (15, 30, 45 min) and hydrochloric acid (HCl) was used as an extracting agent for both extraction methods. The highest yields of extracted pectin from lemon peels were found to be 8.16 % (w/w) for 75 °C, 45 min by UAE and 8.58 % (w/w) for 360 W, 1 min by MAE. Additionally, the highest yields of extracted pectin from mandarin peels were found to be 11.29 % (w/w) for 75 °C, 45 min by UAE and 16.44 % (w/w) for 600 W, 1 min by MAE. The results showed that the use of microwave assisted extraction promoted a better yield when compared to the two extraction methods. On the other hand, according to the results of experiments, mandarin peels contain more pectin than lemon peels when the compared to the pectin product values of two sources. Therefore, these results suggested that MAE could be used as an efficient and rapid method for extraction of pectin and mandarin peels should be preferred as sources of pectin production compared to lemon peels.Keywords: mandarin peel, lemon peel, pectin, ultrasound, microwave, extraction
Procedia PDF Downloads 23415086 Estimation of Physico-Mechanical Properties of Tuffs (Turkey) from Indirect Methods
Authors: Mustafa Gok, Sair Kahraman, Mustafa Fener
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In rock engineering applications, determining uniaxial compressive strength (UCS), Brazilian tensile strength (BTS), and basic index properties such as density, porosity, and water absorption is crucial for the design of both underground and surface structures. However, obtaining reliable samples for direct testing, especially from rocks that weather quickly and have low strength, is often challenging. In such cases, indirect methods provide a practical alternative to estimate the physical and mechanical properties of these rocks. In this study, tuff samples collected from the Cappadocia region (Nevşehir) in Turkey were subjected to indirect testing methods. Over 100 tests were conducted, using needle penetrometer index (NPI), point load strength index (PLI), and disc shear index (BPI) to estimate the uniaxial compressive strength (UCS), Brazilian tensile strength (BTS), density, and water absorption index of the tuffs. The relationships between the results of these indirect tests and the target physical properties were evaluated using simple and multiple regression analyses. The findings of this research reveal strong correlations between the indirect methods and the mechanical properties of the tuffs. Both uniaxial compressive strength and Brazilian tensile strength could be accurately predicted using NPI, PLI, and BPI values. The regression models developed in this study allow for rapid, cost-effective assessments of tuff strength in cases where direct testing is impractical. These results are particularly valuable for geological engineering applications, where time and resource constraints exist. This study highlights the significance of using indirect methods as reliable predictors of the mechanical behavior of weak rocks like tuffs. Further research is recommended to explore the application of these methods to other rock types with similar characteristics. Further research is required to compare the results with those of established direct test methods.Keywords: brazilian tensile strength, disc shear strength, indirect methods, tuffs, uniaxial compressive strength
Procedia PDF Downloads 1515085 A Trend Based Forecasting Framework of the ATA Method and Its Performance on the M3-Competition Data
Authors: H. Taylan Selamlar, I. Yavuz, G. Yapar
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It is difficult to make predictions especially about the future and making accurate predictions is not always easy. However, better predictions remain the foundation of all science therefore the development of accurate, robust and reliable forecasting methods is very important. Numerous number of forecasting methods have been proposed and studied in the literature. There are still two dominant major forecasting methods: Box-Jenkins ARIMA and Exponential Smoothing (ES), and still new methods are derived or inspired from them. After more than 50 years of widespread use, exponential smoothing is still one of the most practically relevant forecasting methods available due to their simplicity, robustness and accuracy as automatic forecasting procedures especially in the famous M-Competitions. Despite its success and widespread use in many areas, ES models have some shortcomings that negatively affect the accuracy of forecasts. Therefore, a new forecasting method in this study will be proposed to cope with these shortcomings and it will be called ATA method. This new method is obtained from traditional ES models by modifying the smoothing parameters therefore both methods have similar structural forms and ATA can be easily adapted to all of the individual ES models however ATA has many advantages due to its innovative new weighting scheme. In this paper, the focus is on modeling the trend component and handling seasonality patterns by utilizing classical decomposition. Therefore, ATA method is expanded to higher order ES methods for additive, multiplicative, additive damped and multiplicative damped trend components. The proposed models are called ATA trended models and their predictive performances are compared to their counter ES models on the M3 competition data set since it is still the most recent and comprehensive time-series data collection available. It is shown that the models outperform their counters on almost all settings and when a model selection is carried out amongst these trended models ATA outperforms all of the competitors in the M3- competition for both short term and long term forecasting horizons when the models’ forecasting accuracies are compared based on popular error metrics.Keywords: accuracy, exponential smoothing, forecasting, initial value
Procedia PDF Downloads 17715084 Contrasting The Water Consumption Estimation Methods
Authors: Etienne Alain Feukeu, L. W. Snyman
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Water scarcity is becoming a real issue nowadays. Most countries in the world are facing it in their own way based on their own geographical coordinate and condition. Many countries are facing a challenge of a growing water demand as a result of not only an increased population, economic growth, but also as a pressure of the population dynamic and urbanization. In view to mitigate some of this related problem, an accurate method of water estimation and future prediction, forecast is essential to guarantee not only the sufficient quantity, but also a good water distribution and management system. Beside the fact that several works have been undertaken to address this concern, there is still a considerable disparity between different methods and standard used for water prediction and estimation. Hence this work contrast and compare two well-defined and established methods from two countries (USA and South Africa) to demonstrate the inconsistency when different method and standards are used interchangeably.Keywords: water scarcity, water estimation, water prediction, water forecast.
Procedia PDF Downloads 20115083 Comparison of Different Artificial Intelligence-Based Protein Secondary Structure Prediction Methods
Authors: Jamerson Felipe Pereira Lima, Jeane Cecília Bezerra de Melo
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The difficulty and cost related to obtaining of protein tertiary structure information through experimental methods, such as X-ray crystallography or NMR spectroscopy, helped raising the development of computational methods to do so. An approach used in these last is prediction of tridimensional structure based in the residue chain, however, this has been proved an NP-hard problem, due to the complexity of this process, explained by the Levinthal paradox. An alternative solution is the prediction of intermediary structures, such as the secondary structure of the protein. Artificial Intelligence methods, such as Bayesian statistics, artificial neural networks (ANN), support vector machines (SVM), among others, were used to predict protein secondary structure. Due to its good results, artificial neural networks have been used as a standard method to predict protein secondary structure. Recent published methods that use this technique, in general, achieved a Q3 accuracy between 75% and 83%, whereas the theoretical accuracy limit for protein prediction is 88%. Alternatively, to achieve better results, support vector machines prediction methods have been developed. The statistical evaluation of methods that use different AI techniques, such as ANNs and SVMs, for example, is not a trivial problem, since different training sets, validation techniques, as well as other variables can influence the behavior of a prediction method. In this study, we propose a prediction method based on artificial neural networks, which is then compared with a selected SVM method. The chosen SVM protein secondary structure prediction method is the one proposed by Huang in his work Extracting Physico chemical Features to Predict Protein Secondary Structure (2013). The developed ANN method has the same training and testing process that was used by Huang to validate his method, which comprises the use of the CB513 protein data set and three-fold cross-validation, so that the comparative analysis of the results can be made comparing directly the statistical results of each method.Keywords: artificial neural networks, protein secondary structure, protein structure prediction, support vector machines
Procedia PDF Downloads 62115082 Current Medical and Natural Synchronization Methods in Small Ruminants
Authors: Mehmet Akoz, Mustafa Kul
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Ewes and goats are seasonally polyestrus animals. Their reproductive activities are associated with the reduction or extending of daylight. Melatonin releasing from pineal gland regulates the sexual activities depending on daylight. In recent years, number of ewes decreased in our country. This situation dispatched to developing of some methods to increase productivity. Small ruminants can be synchronized with the natural and medical methods. known methods from natural light set with ram and goat participation. The most important natural methods of male influence, daylight is regulated and feed. On the other hand, progestagens, PGF2α, melatonin, and gonadotropins are commonly used for the purpose of estrus synchranization. But it is not effective PGF2α anestrous season The short-term and long-term progesterone treatment was effective to synchronize estrus in small ruminats during both breeding and anestrus seasons. Alternative choices of progesterone/progestagen have been controlled internal drug release (CIDR) devices, supplying natural progesterone, norgestomet implants, and orally active melengestrol acetate Melatonin anestrous season and should be applied during the transition period, but the season can be synchronized. Estrus synchronisation shortens anestrus season, decreases labor for mating/insemination and estrus pursuit, and induces multiple pregnancies.Keywords: ewes, goat, synchronization, progestagen, PGF2α
Procedia PDF Downloads 34215081 Optimization of Spatial Light Modulator to Generate Aberration Free Optical Traps
Authors: Deepak K. Gupta, T. R. Ravindran
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Holographic Optical Tweezers (HOTs) in general use iterative algorithms such as weighted Gerchberg-Saxton (WGS) to generate multiple traps, which produce traps with 99% uniformity theoretically. But in experiments, it is the phase response of the spatial light modulator (SLM) which ultimately determines the efficiency, uniformity, and quality of the trap spots. In general, SLMs show a nonlinear phase response behavior, and they may even have asymmetric phase modulation depth before and after π. This affects the resolution with which the gray levels are addressed before and after π, leading to a degraded trap performance. We present a method to optimize the SLM for a linear phase response behavior along with a symmetric phase modulation depth around π. Further, we optimize the SLM for its varying phase response over different spatial regions by optimizing the brightness/contrast and gamma of the hologram in different subsections. We show the effect of the optimization on an array of trap spots resulting in improved efficiency and uniformity. We also calculate the spot sharpness metric and trap performance metric and show a tightly focused spot with reduced aberration. The trap performance is compared by calculating the trap stiffness of a trapped particle in a given trap spot before and after aberration correction. The trap stiffness is found to improve by 200% after the optimization.Keywords: spatial light modulator, optical trapping, aberration, phase modulation
Procedia PDF Downloads 18715080 Quartic Spline Method for Numerical Solution of Self-Adjoint Singularly Perturbed Boundary Value Problems
Authors: Reza Mohammadi
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Using quartic spline, we develop a method for numerical solution of singularly perturbed two-point boundary-value problems. The purposed method is fourth-order accurate and applicable to problems both in singular and non-singular cases. The convergence analysis of the method is given. The resulting linear system of equations has been solved by using a tri-diagonal solver. We applied the presented method to test problems which have been solved by other existing methods in references, for comparison of presented method with the existing methods. Numerical results are given to illustrate the efficiency of our methods.Keywords: second-order ordinary differential equation, singularly-perturbed, quartic spline, convergence analysis
Procedia PDF Downloads 36015079 The Role of Banks Funding and Promoting the Foreign Trade: Case of Turkey
Authors: Mikail Altan
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International trust takes first place in the development of foreign trade in the country. They see an important role in ensuring that trust. Various payment methods that are developed in the banking system provide fast and reliable way to execution and promote foreign trade by financing the foreign trade. In this study, we investigate the influence of bank on foreign trade in Turkey. 26 years of data for 1990-2015 period have been used in this study. After correlation analysis, a simple regression model was established. Payment methods that are developed in the banking system make a positive contribution in Turkey’s foreign trade volume. In addition, the export of Turkey was affected positively more than import’s by these payment methods.Keywords: banks, export, foreign trade, import
Procedia PDF Downloads 35815078 High-Efficiency Comparator for Low-Power Application
Authors: M. Yousefi, N. Nasirzadeh
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In this paper, dynamic comparator structure employing two methods for power consumption reduction with applications in low-power high-speed analog-to-digital converters have been presented. The proposed comparator has low consumption thanks to power reduction methods. They have the ability for offset adjustment. The comparator consumes 14.3 μW at 100 MHz which is equal to 11.8 fJ. The comparator has been designed and simulated in 180 nm CMOS. Layouts occupy 210 μm2.Keywords: efficiency, comparator, power, low
Procedia PDF Downloads 35815077 Coordinated Voltage Control in a Radial Distribution System
Authors: Shivarudraswamy, Anubhav Shrivastava, Lakshya Bhat
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Distributed generation has indeed become a major area of interest in recent years. Distributed Generation can address large number of loads in a power line and hence has better efficiency over the conventional methods. However there are certain drawbacks associated with it, increase in voltage being the major one. This paper addresses the voltage control at the buses for an IEEE 30 bus system by regulating reactive power. For carrying out the analysis, the suitable location for placing distributed generators (DG) is identified through load flow analysis and seeing where the voltage profile is dipping. MATLAB programming is used to regulate the voltage at all buses within +/-5% of the base value even after the introduction of DG’s. Three methods for regulation of voltage are discussed. A sensitivity based analysis is later carried out to determine the priority among the various methods listed in the paper.Keywords: distributed generators, distributed system, reactive power, voltage control
Procedia PDF Downloads 50015076 Effects of the Social Work Field Practicum on the Wellbeing of Non-Traditional and Underserved Students: A Mixed-Methods Study
Authors: Dana S. Smith, Angela Goins, Shahnaz Savani
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Using a mixed-methods approach, this study explored costs to student wellbeing generated by the social work field practicum requirement. The project was conducted by faculty at a medium-sized university in the United States. Social work educators and field practicum instructors participated in interviews. Students and former students completed surveys on the topic. The data analysis revealed emotional burdens as well as threats to student wellbeing in association with the fieldwork required for those in pursuit of a social work degree. The study includes recommendations for anti-oppressive approaches for academic programs and implications for further research.Keywords: emotional wellbeing, field practicum, mixed-methods, social justice
Procedia PDF Downloads 10115075 Effects of the Social Work Field Practicum on the Wellbeing of Non-traditional and Underserved Students: A Mixed-Methods Study
Authors: Dana S. Smith, Angela Goins, Shahnaz Savani
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Using a mixed-methods approach, this study explored costs to student wellbeing generated by the social work field practicum requirement. The project was conducted by faculty at a medium sized university in the United States. Social work educators and field practicum instructors participated in interviews. Students and former students completed surveys on the topic. The data analysis revealed emotional burdens as well as threats to student wellbeing in association with the fieldwork required for those in pursuit of a social work degree. The study includes recommendations of anti-oppressive approaches for academic programs and implications for further research.Keywords: emotional wellbeing, field practicum, mixed-methods, social justice
Procedia PDF Downloads 9015074 Make Up Flash: Web Application for the Improvement of Physical Appearance in Images Based on Recognition Methods
Authors: Stefania Arguelles Reyes, Octavio José Salcedo Parra, Alberto Acosta López
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This paper presents a web application for the improvement of images through recognition. The web application is based on the analysis of picture-based recognition methods that allow an improvement on the physical appearance of people posting in social networks. The basis relies on the study of tools that can correct or improve some features of the face, with the help of a wide collection of user images taken as reference to build a facial profile. Automatic facial profiling can be achieved with a deeper study of the Object Detection Library. It was possible to improve the initial images with the help of MATLAB and its filtering functions. The user can have a direct interaction with the program and manually adjust his preferences.Keywords: Matlab, make up, recognition methods, web application
Procedia PDF Downloads 14415073 Random Forest Classification for Population Segmentation
Authors: Regina Chua
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To reduce the costs of re-fielding a large survey, a Random Forest classifier was applied to measure the accuracy of classifying individuals into their assigned segments with the fewest possible questions. Given a long survey, one needed to determine the most predictive ten or fewer questions that would accurately assign new individuals to custom segments. Furthermore, the solution needed to be quick in its classification and usable in non-Python environments. In this paper, a supervised Random Forest classifier was modeled on a dataset with 7,000 individuals, 60 questions, and 254 features. The Random Forest consisted of an iterative collection of individual decision trees that result in a predicted segment with robust precision and recall scores compared to a single tree. A random 70-30 stratified sampling for training the algorithm was used, and accuracy trade-offs at different depths for each segment were identified. Ultimately, the Random Forest classifier performed at 87% accuracy at a depth of 10 with 20 instead of 254 features and 10 instead of 60 questions. With an acceptable accuracy in prioritizing feature selection, new tools were developed for non-Python environments: a worksheet with a formulaic version of the algorithm and an embedded function to predict the segment of an individual in real-time. Random Forest was determined to be an optimal classification model by its feature selection, performance, processing speed, and flexible application in other environments.Keywords: machine learning, supervised learning, data science, random forest, classification, prediction, predictive modeling
Procedia PDF Downloads 9415072 The Non-Linear Analysis of Brain Response to Visual Stimuli
Authors: H. Namazi, H. T. N. Kuan
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Brain activity can be measured by acquiring and analyzing EEG signals from an individual. In fact, the human brain response to external and internal stimuli is mapped in his EEG signals. During years some methods such as Fourier transform, wavelet transform, empirical mode decomposition, etc. have been used to analyze the EEG signals in order to find the effect of stimuli, especially external stimuli. But each of these methods has some weak points in analysis of EEG signals. For instance, Fourier transform and wavelet transform methods are linear signal analysis methods which are not good to be used for analysis of EEG signals as nonlinear signals. In this research we analyze the brain response to visual stimuli by extracting information in the form of various measures from EEG signals using a software developed by our research group. The used measures are Jeffrey’s measure, Fractal dimension and Hurst exponent. The results of these analyses are useful not only for fundamental understanding of brain response to visual stimuli but provide us with very good recommendations for clinical purposes.Keywords: visual stimuli, brain response, EEG signal, fractal dimension, hurst exponent, Jeffrey’s measure
Procedia PDF Downloads 56115071 Assessment of Treatment Methods to Remove Hazardous Dyes from Synthetic Wastewater
Authors: Abhiram Siva Prasad Pamula
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Access to clean drinking water becomes scarce due to the increase in extreme weather events because of the rise in the average global temperatures and climate change. By 2030, approximately 47% of the world’s population will face water shortages due to uncertainty in seasonal rainfall. Over 10000 varieties of synthetic dyes are commercially available in the market and used by textile and paper industries, negatively impacting human health when ingested. Besides humans, textile dyes have a negative impact on aquatic ecosystems by increasing biological oxygen demand and chemical oxygen demand. This study assesses different treatment methods that remove dyes from textile wastewater while focusing on energy, economic, and engineering aspects of the treatment processes.Keywords: textile wastewater, dye removal, treatment methods, hazardous pollutants
Procedia PDF Downloads 9315070 Comparative Pre-treatment Analysis of RNA-Extraction Methods and Efficient Detection of SARS-COV-2 and PMMoV in Influents and 1ˢᵗ Sedimentation from a Wastewater Treatment Plan
Authors: Jesmin Akter, Chang Hyuk Ahn, Ilho Kim, Fumitake Nishimura, Jaiyeop Lee
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This study aimed to compare two pre-treatment and two RNA extraction methods, namely PEG, and Nano bubble, Viral RNA Soil, and Mini Kit, in terms of their efficiency in detecting SARS-CoV-2 and PMMoV in influent and 1st sedimentation samples from a wastewater treatment plant. The extracted RNA samples were quantified and evaluated for purity, yield, and integrity. The results indicated that the nanobubble PEG method provided the highest yield of RNA, while the QIAamp Viral RNA Mini Kit produced the purest RNA samples. In terms of sensitivity and specificity, all these methods were able to detect SARS-CoV-2 and PMMoV in both influent and 1st sedimentation samples. However, the nanobubble PEG method showed slightly higher sensitivity compared to the other methods. These findings suggest that the choice of RNA extraction method should depend on the downstream application and the quality of the RNA required. The study also highlights the potential of wastewater-based epidemiology as an effective and non-invasive method for monitoring the spread of infectious diseases in a community.Keywords: influent, PMMoV, SARS-CoV-2, wastewater based epidemiology
Procedia PDF Downloads 9615069 A Fuzzy Kernel K-Medoids Algorithm for Clustering Uncertain Data Objects
Authors: Behnam Tavakkol
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Uncertain data mining algorithms use different ways to consider uncertainty in data such as by representing a data object as a sample of points or a probability distribution. Fuzzy methods have long been used for clustering traditional (certain) data objects. They are used to produce non-crisp cluster labels. For uncertain data, however, besides some uncertain fuzzy k-medoids algorithms, not many other fuzzy clustering methods have been developed. In this work, we develop a fuzzy kernel k-medoids algorithm for clustering uncertain data objects. The developed fuzzy kernel k-medoids algorithm is superior to existing fuzzy k-medoids algorithms in clustering data sets with non-linearly separable clusters.Keywords: clustering algorithm, fuzzy methods, kernel k-medoids, uncertain data
Procedia PDF Downloads 21515068 A Heuristic Based Decomposition Approach for a Hierarchical Production Planning Problem
Authors: Nusrat T. Chowdhury, M. F. Baki, A. Azab
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The production planning problem is concerned with specifying the optimal quantities to produce in order to meet the demand for a prespecified planning horizon with the least possible expenditure. Making the right decisions in production planning will affect directly the performance and productivity of a manufacturing firm, which is important for its ability to compete in the market. Therefore, developing and improving solution procedures for production planning problems is very significant. In this paper, we develop a Dantzig-Wolfe decomposition of a multi-item hierarchical production planning problem with capacity constraint and present a column generation approach to solve the problem. The original Mixed Integer Linear Programming model of the problem is decomposed item by item into a master problem and a number of subproblems. The capacity constraint is considered as the linking constraint between the master problem and the subproblems. The subproblems are solved using the dynamic programming approach. We also propose a multi-step iterative capacity allocation heuristic procedure to handle any kind of infeasibility that arises while solving the problem. We compare the computational performance of the developed solution approach against the state-of-the-art heuristic procedure available in the literature. The results show that the proposed heuristic-based decomposition approach improves the solution quality by 20% as compared to the literature.Keywords: inventory, multi-level capacitated lot-sizing, emission control, setup carryover
Procedia PDF Downloads 13815067 A Comparison between Fuzzy Analytic Hierarchy Process and Fuzzy Analytic Network Process for Rationality Evaluation of Land Use Planning Locations in Vietnam
Authors: X. L. Nguyen, T. Y. Chou, F. Y. Min, F. C. Lin, T. V. Hoang, Y. M. Huang
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In Vietnam, land use planning is utilized as an efficient tool for the local government to adjust land use. However, planned locations are facing disapproval from people who live near these planned sites because of environmental problems. The selection of these locations is normally based on the subjective opinion of decision-makers and is not supported by any scientific methods. Many researchers have applied Multi-Criteria Analysis (MCA) methods in which Analytic Hierarchy Process (AHP) is the most popular techniques in combination with Fuzzy set theory for the subject of rationality assessment of land use planning locations. In this research, the Fuzzy set theory and Analytic Network Process (ANP) multi-criteria-based technique were used for the assessment process. The Fuzzy Analytic Hierarchy Process was also utilized, and the output results from two methods were compared to extract the differences. The 20 planned landfills in Hung Ha district, Thai Binh province, Vietnam was selected as a case study. The comparison results indicate that there are different between weights computed by AHP and ANP methods and the assessment outputs produced from these two methods also slight differences. After evaluation of existing planned sites, some potential locations were suggested to the local government for possibility of land use planning adjusts.Keywords: Analytic Hierarchy Process, Analytic Network Process, Fuzzy set theory, land use planning
Procedia PDF Downloads 42115066 A Study on the Solutions of the 2-Dimensional and Forth-Order Partial Differential Equations
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In this study, we will carry out a comparative study between the reduced differential transform method, the adomian decomposition method, the variational iteration method and the homotopy analysis method. These methods are used in many fields of engineering. This is been achieved by handling a kind of 2-Dimensional and forth-order partial differential equations called the Kuramoto–Sivashinsky equations. Three numerical examples have also been carried out to validate and demonstrate efficiency of the four methods. Furthermost, it is shown that the reduced differential transform method has advantage over other methods. This method is very effective and simple and could be applied for nonlinear problems which used in engineering.Keywords: reduced differential transform method, adomian decomposition method, variational iteration method, homotopy analysis method
Procedia PDF Downloads 43315065 Economic Forecasting Analysis for Solar Photovoltaic Application
Authors: Enas R. Shouman
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Economic development with population growth is leading to a continuous increase in energy demand. At the same time, growing global concern for the environment is driving to decrease the use of conventional energy sources and to increase the use of renewable energy sources. The objective of this study is to present the market trends of solar energy photovoltaic technology over the world and to represent economics methods for PV financial analyzes on the basis of expectations for the expansion of PV in many applications. In the course of this study, detailed information about the current PV market was gathered and analyzed to find factors influencing the penetration of PV energy. The paper methodology depended on five relevant economic financial analysis methods that are often used for investment decisions maker. These methods are payback analysis, net benefit analysis, saving-to-investment ratio, adjusted internal rate of return, and life-cycle cost. The results of this study may be considered as a marketing guide that helps diffusion of using PV Energy. The study showed that PV cost is economically reliable. The consumers will pay higher purchase prices for PV system installation but will get lower electricity bill.Keywords: photovoltaic, financial methods, solar energy, economics, PV panel
Procedia PDF Downloads 10915064 Convex Restrictions for Outage Constrained MU-MISO Downlink under Imperfect Channel State Information
Authors: A. Preetha Priyadharshini, S. B. M. Priya
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In this paper, we consider the MU-MISO downlink scenario, under imperfect channel state information (CSI). The main issue in imperfect CSI is to keep the probability of each user achievable outage rate below the given threshold level. Such a rate outage constraints present significant and analytical challenges. There are many probabilistic methods are used to minimize the transmit optimization problem under imperfect CSI. Here, decomposition based large deviation inequality and Bernstein type inequality convex restriction methods are used to perform the optimization problem under imperfect CSI. These methods are used for achieving improved output quality and lower complexity. They provide a safe tractable approximation of the original rate outage constraints. Based on these method implementations, performance has been evaluated in the terms of feasible rate and average transmission power. The simulation results are shown that all the two methods offer significantly improved outage quality and lower computational complexity.Keywords: imperfect channel state information, outage probability, multiuser- multi input single output, channel state information
Procedia PDF Downloads 81315063 The Analysis of Brain Response to Auditory Stimuli through EEG Signals’ Non-Linear Analysis
Authors: H. Namazi, H. T. N. Kuan
Abstract:
Brain activity can be measured by acquiring and analyzing EEG signals from an individual. In fact, the human brain response to external and internal stimuli is mapped in his EEG signals. During years some methods such as Fourier transform, wavelet transform, empirical mode decomposition, etc. have been used to analyze the EEG signals in order to find the effect of stimuli, especially external stimuli. But each of these methods has some weak points in analysis of EEG signals. For instance, Fourier transform and wavelet transform methods are linear signal analysis methods which are not good to be used for analysis of EEG signals as nonlinear signals. In this research we analyze the brain response to auditory stimuli by extracting information in the form of various measures from EEG signals using a software developed by our research group. The used measures are Jeffrey’s measure, Fractal dimension and Hurst exponent. The results of these analyses are useful not only for fundamental understanding of brain response to auditory stimuli but provide us with very good recommendations for clinical purposes.Keywords: auditory stimuli, brain response, EEG signal, fractal dimension, hurst exponent, Jeffrey’s measure
Procedia PDF Downloads 53415062 Standalone Docking Station with Combined Charging Methods for Agricultural Mobile Robots
Authors: Leonor Varandas, Pedro D. Gaspar, Martim L. Aguiar
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One of the biggest concerns in the field of agriculture is around the energy efficiency of robots that will perform agriculture’s activity and their charging methods. In this paper, two different charging methods for agricultural standalone docking stations are shown that will take into account various variants as field size and its irregularities, work’s nature to which the robot will perform, deadlines that have to be respected, among others. Its features also are dependent on the orchard, season, battery type and its technical specifications and cost. First charging base method focuses on wireless charging, presenting more benefits for small field. The second charging base method relies on battery replacement being more suitable for large fields, thus avoiding the robot stop for recharge. Existing many methods to charge a battery, the CC CV was considered the most appropriate for either simplicity or effectiveness. The choice of the battery for agricultural purposes is if most importance. While the most common battery used is Li-ion battery, this study also discusses the use of graphene-based new type of batteries with 45% over capacity to the Li-ion one. A Battery Management Systems (BMS) is applied for battery balancing. All these approaches combined showed to be a promising method to improve a lot of technical agricultural work, not just in terms of plantation and harvesting but also about every technique to prevent harmful events like plagues and weeds or even to reduce crop time and cost.Keywords: agricultural mobile robot, charging methods, battery replacement method, wireless charging method
Procedia PDF Downloads 14815061 Requirements Management in Agile
Authors: Ravneet Kaur
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The concept of Agile Requirements Engineering and Management is not new. However, the struggle to figure out how traditional Requirements Management Process fits within an Agile framework remains complex. This paper talks about a process that can merge the organization’s traditional Requirements Management Process nicely into the Agile Software Development Process. This process provides Traceability of the Product Backlog to the external documents on one hand and User Stories on the other hand. It also gives sufficient evidence that the system will deliver the right functionality with good quality in the form of various statistics and reports. In the nutshell, by overlaying a process on top of Agile, without disturbing the Agility, we are able to get synergic benefits in terms of productivity, profitability, its reporting, and end to end visibility to all Stakeholders. The framework can be used for just-in-time requirements definition or to build a repository of requirements for future use. The goal is to make sure that the business (specifically, the product owner) can clearly articulate what needs to be built and define what is of high quality. To accomplish this, the requirements cycle follows a Scrum-like process that mirrors the development cycle but stays two to three steps ahead. The goal is to create a process by which requirements can be thoroughly vetted, organized, and communicated in a manner that is iterative, timely, and quality-focused. Agile is quickly becoming the most popular way of developing software because it fosters continuous improvement, time-boxed development cycles, and more quickly delivering value to the end users. That value will be driven to a large extent by the quality and clarity of requirements that feed the software development process. An agile, lean, and timely approach to requirements as the starting point will help to ensure that the process is optimized.Keywords: requirements management, Agile
Procedia PDF Downloads 37015060 Resilient Analysis as an Alternative to Conventional Seismic Analysis Methods for the Maintenance of a Socioeconomical Functionality of Structures
Authors: Sara Muhammad Elqudah, Vigh László Gergely
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Catastrophic events, such as earthquakes, are sudden, short, and devastating, threatening lives, demolishing futures, and causing huge economic losses. Current seismic analyses and design standards are based on life safety levels where only some residual strength and stiffness are left in the structure leaving it beyond economical repair. Consequently, it has become necessary to introduce and implement the concept of resilient design. Resilient design is about designing for ductility over time by resisting, absorbing, and recovering from the effects of a hazard in an appropriate and efficient time manner while maintaining the functionality of the structure in the aftermath of the incident. Resilient analysis is mainly based on the fragility, vulnerability, and functionality curves where eventually a resilience index is generated from these curves, and the higher this index is, the better is the performance of the structure. In this paper, seismic performances of a simple two story reinforced concrete building, located in a moderate seismic region, has been evaluated using the conventional seismic analyses methods, which are the linear static analysis, the response spectrum analysis, and the pushover analysis, and the generated results of these analyses methods are compared to those of the resilient analysis. Results highlight that the resilience analysis was the most convenient method in generating a more ductile and functional structure from a socio-economic perspective, in comparison to the standard seismic analysis methods.Keywords: conventional analysis methods, functionality, resilient analysis, seismic performance
Procedia PDF Downloads 11615059 Teaching Research Methods at the Graduate Level Utilizing Flipped Classroom Approach; An Action Research Study
Authors: Munirah Alaboudi
Abstract:
This paper discusses a research project carried out with 12 first-year graduate students enrolled in research methods course prior to undertaking a graduate thesis during the academic year 2019. The research was designed for the objective of creating research methods course structure that embraces an individualized and activity-based approach to learning in a highly engaging group environment. This approach targeted innovating the traditional research methods lecture-based, theoretical format where students reported less engagement and limited learning. This study utilized action research methodology in developing a different approach to research methods course instruction where student performance indicators and feedback were periodically collected to assess the new teaching method. Student learning was achieved through utilizing the flipped classroom approach where students learned the material at home and classroom activities were designed to implement and experiment with the newly acquired information, with the guidance of the course instructor. Student learning in class was practiced through a series of activities based on different research methods. With the goal of encouraging student engagement, a wide range of activities was utilized including workshops, role play, mind-mapping, presentations, peer evaluations. Data was collected through an open-ended qualitative questionnaire to establish whether students were engaged in the material they were learning, and to what degree were they engaged, and to test their mastery level of the concepts discussed. Analysis of the data presented positive results as around 91% of the students reported feeling more engaged with the active learning experience and learning research by “actually doing research, not just reading about it”. The students expressed feeling invested in the process of their learning as they saw their research “gradually come to life” through peer learning and practice during workshops. Based on the results of this study, the research methods course structure was successfully remodeled and continues to be delivered.Keywords: research methods, higher education instruction, flipped classroom, graduate education
Procedia PDF Downloads 103