Search results for: classification method

Authors: Atieh Andakhshideh, S. Maleki, Sayed Sadegh Marashi

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In this paper, the interlaminar stresses of generally laminated piezoelectric plates are presented. The electromechanical coupling effect of the piezoelectric plate is considered and the governing equations and boundary conditions are derived using the principle of minimum total potential energy. The solution procedure is a three-dimensional multi-term extended Kantorovich method (3DMTEKM). The objective of this paper is to accurately study coupling influence on the edge effects of piezolaminated plates with finite dimensions, arbitrary lamination lay-ups and under uniform axial strain. These results can provide a benchmark for checking the accuracy of the other numerical method or two-dimensional laminate theories. To verify the accuracy of the 3DMTEKM, first examples are simplified to special cases such as cross-ply or symmetric laminations and are compared with other analytical solutions available in the literature. Excellent agreement is achieved in validation test and other numerical results are presented for general cases. Numerical examples indicate the singular behavior of interlaminar normal/shear stresses and electric field strength components near the edges of the piezolaminated plates. The coupling influence on the free edge effect with respect to lamination lay-ups of piezoelectric plate is studied in several examples.

Keywords: electromechanical coupling, generally laminated piezoelectric plates, Kantorovich method, edge effect, interlaminar stresses

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Authors: Kimberly McCabe

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The trafficking of women and children for abuse and exploitation is not a new problem under the umbrella of human trafficking; however, over the last decade, the problem has attracted increased attention from international governments and non-profits attempting to reduce victimization and provide services for survivors. Research on human trafficking suggests that the trafficking of human beings is, largely, a symptom of poverty. As the trafficking of human beings may be viewed as a response to the demand for people for various forms of exploitation, a product of poverty, and a consequence of the subordinate positions of women and children in society, it reaches beyond randomized victimization. Hence, human trafficking, and especially the trafficking of women and children, goes beyond the realm of poorness. Therefore, to begin to understand the reasons for the existence of human trafficking, one must identify and consider not only the immediate causes but also those underlying structural determinants that facilitate this form of victimization. Specifically, one must acknowledge the economic, social, and cultural factors that support human trafficking. This research attempts to study human trafficking at the country level by focusing on economic, social, and cultural characteristics. This study focuses on inequality and, in particular, gender inequality as related to legislative attempts to address human trafficking. Within the design of this project is the use of the US State Department’s tier classification system for Trafficking in Persons (TIP) and the USA CIA Fact Sheet of country characteristics for over 150 countries in an attempt to model legal outcomes as related to human trafficking. Results of this research demonstrate the significance of characteristics beyond poverty as related to country-level responses to human trafficking.

Keywords: child trafficking, gender inequality, human trafficking, inequality

Procedia PDF Downloads 212

Authors: Delara Kazempour, Mashallah Abasi Dezfuli, Reza Javidan

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Video compression used for channels with limited bandwidth and storage devices has limited storage capabilities. One of the most popular approaches in video compression is the usage of different transforms. Discrete cosine transform is one of the video compression methods that have some problems such as blocking, noising and high distortion inappropriate effect in compression ratio. wavelet transform is another approach is better than cosine transforms in balancing of compression and quality but the recognizing of curve curvature is so limit. Because of the importance of the compression and problems of the cosine and wavelet transforms, the contourlet transform is most popular in video compression. In the new proposed method, we used contourlet transform in video image compression. Contourlet transform can save details of the image better than the previous transforms because this transform is multi-scale and oriented. This transform can recognize discontinuity such as edges. In this approach we lost data less than previous approaches. Contourlet transform finds discrete space structure. This transform is useful for represented of two dimension smooth images. This transform, produces compressed images with high compression ratio along with texture and edge preservation. Finally, the results show that the majority of the images, the parameters of the mean square error and maximum signal-to-noise ratio of the new method based contourlet transform compared to wavelet transform are improved but in most of the images, the parameters of the mean square error and maximum signal-to-noise ratio in the cosine transform is better than the method based on contourlet transform.

Keywords: video compression, contourlet transform, discrete cosine transform, wavelet transform

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Authors: Kübra Yüzüncüyıl, Aytekin İşman, Berkay Buluş

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In the last quarter of the 20th century, Food Studies was emerged as an interdisciplinary program. It seeks to develop a critical perspective on sociocultural meanings of food. The notion of food has been related with certain social and cultural values throughout history. In today’s society, with the rise of new media technologies, cultural structure have been digitized. Food culture in this main, is also endowed with digital codes. In particular, social media has been integrated into foodways. This study attempts to examine the gratifications that individuals obtain from social media use on foodways. In the first part of study, the relationship between food culture and digital culture is examined. Secondly, theoretical framework and research method of the study are explained. In order to achieve the particular aim of study, Uses and Gratifications Theory is adopted as conceptual framework. Conventional gratification categories are redefined in new media terms. After that, the relation between redefined categories and foodways is uncovered. Due to its peculiar context, this study follows a quantitative research method. By conducting pre-interviews and factor analysis, a peculiar survey is developed. The sample of study is chosen among 405 undergraduate communication faculty students of Sakarya University by proportionate stratification sampling method. In the analysis of the collected data, statistical methods One-Way ANOVA, Independent Samples T-test, and Tuckey Honest Significant Difference Test, Post Hoc Test are used.

Keywords: food studies, food communication, new media, communication

Procedia PDF Downloads 182

Authors: Sandesh Achar

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Personalized advertising holds greater potential for higher conversion rates compared to generic advertisements. However, its widespread application in the retail industry faces challenges due to complex implementation processes. These complexities impede the swift adoption of personalized advertisement on a large scale. Personalized advertisement, being a data-driven approach, necessitates consumer-related data, adding to its complexity. This paper introduces an innovative data-driven decision-making framework, D3Advert, which personalizes advertisements by analyzing personalities using a BiLSTM network. The framework utilizes the Myers–Briggs Type Indicator (MBTI) dataset for development. The employed BiLSTM network, specifically designed and optimized for D3Advert, classifies user personalities into one of the sixteen MBTI categories based on their social media posts. The classification accuracy is 86.42%, with precision, recall, and F1-Score values of 85.11%, 84.14%, and 83.89%, respectively. The D3Advert framework personalizes advertisements based on these personality classifications. Experimental implementation and performance analysis of D3Advert demonstrate a 40% improvement in impressions. D3Advert’s innovative and straightforward approach has the potential to transform personalized advertising and foster widespread personalized advertisement adoption in marketing.

Keywords: personalized advertisement, deep Learning, MBTI dataset, BiLSTM network, NLP.

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Authors: Desta Brhanu Gebrehiwot

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The study aims to investigate the impact of land tenure arrangements on fertilizer use per hectare in Northern Ethiopia. Household and Plot level data are used for analysis. Land tenure contracts such as sharecropping and fixed rent arrangements have endogeneity. Different unobservable characteristics may affect renting-out decisions. Thus, the appropriate method of analysis was the instrumental variable estimation technic. Therefore, the family of instrumental variable estimation methods two-stage least-squares regression (2SLS, the generalized method of moments (GMM), Limited information maximum likelihood (LIML), and instrumental variable Tobit (IV-Tobit) was used. Besides, a method to handle a binary endogenous variable is applied, which uses a two-step estimation. In the first step probit model includes instruments, and in the second step, maximum likelihood estimation (MLE) (“etregress” command in Stata 14) was used. There was lower fertilizer use per hectare on sharecropped and fixed rented plots relative to owner-operated. The result supports the Marshallian inefficiency principle in sharecropping. The difference in fertilizer use per hectare could be explained by a lack of incentivized detailed contract forms, such as giving more proportion of the output to the tenant under sharecropping contracts, which motivates to use of more fertilizer in rented plots to maximize the production because most sharecropping arrangements share output equally between tenants and landlords.

Keywords: tenure-contracts, endogeneity, plot-level data, Ethiopia, fertilizer

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Authors: Shrikaant Kulkarni, Akshata Naik Nimbalkar

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In this worki a method protocol has been developed for the synthesis of innovative Co3O4 material by using a method of chemical synthesis followed by calcination. The effect of calcination temperature on the morphology, structure and catalytic performance on material in question is investigated by using characterization tools like scanning electron microscopy (SEM), X-ray diffraction (XRD) spectroscopy and electrochemical techniques. The SEM images reveal that the morphology of the Co3O4 material undergoes a change from the rod to a beadlike shape on calcination at temperature of 700 °C. The XRD image shows that although the morphology of synthesized Co3O4 material exhibits a cubic phase but it differs in crystallinity depending upon morphology. Similarly spherical beadlike Co3O4 material has exhibited better activity than its rodlike counterpart which is reflected from electrochemical findings. Further, its performance in terms of bifunctional nature and hlods a lot much of promise as a excellent electrode material in the next generation batteries and fuel cells.

Keywords: bifunctional, next generation material, Co3O4, XRD

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Authors: Taki Eddine Seghier, Mohd Hamdan Ahmad, Yaik-Wah Lim, Samuel Opeyemi Williams

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The assessment of building sustainability to achieve a specific green benchmark and the preparation of the required documents in order to receive a green building certification, both are considered as major challenging tasks for green building design team. However, this labor and time-consuming process can take advantage of the available Building Information Modeling (BIM) features such as material take-off and scheduling. Furthermore, the workflow can be automated in order to track potentially achievable credit points and provide rating feedback for several design options by using integrated Visual Programing (VP) to handle the stored parameters within the BIM model. Hence, this study proposes a BIM-based tool that uses Green Building Index (GBI) rating system requirements as a unique input case to evaluate the building sustainability in the design stage of the building project life cycle. The tool covers two key models for data extraction, firstly, a model for data extraction, calculation and the classification of achievable credit points in a green template, secondly, a model for the generation of the required documents for green building certification. The tool was validated on a BIM model of residential building and it serves as proof of concept that building sustainability assessment of GBI certification can be automatically evaluated and documented through BIM.

Keywords: green building rating system, GBRS, building information modeling, BIM, visual programming, VP, sustainability assessment

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Authors: Li Ji, Kaiwei Chu, Shibo Kuang, Aibing Yu

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Hydrocyclones are widely used to classify particles by size in industries such as mineral processing and chemical processing. The particles to be handled usually have a broad range of size distributions and sometimes density distributions, which has to be properly considered, causing challenges in the modelling of hydrocyclone. The combined approach of Computational Fluid Dynamics (CFD) and Discrete Element Method (DEM) offers convenience to model particle size/density distribution. However, its direct application to hydrocyclones is computationally prohibitive because there are billions of particles involved. In this work, a CFD-DEM model with the concept of the coarse-grained (CG) model is developed to model the solid-fluid flow in a hydrocyclone. The DEM is used to model the motion of discrete particles by applying Newton’s laws of motion. Here, a particle assembly containing a certain number of particles with same properties is treated as one CG particle. The CFD is used to model the liquid flow by numerically solving the local-averaged Navier-Stokes equations facilitated with the Volume of Fluid (VOF) model to capture air-core. The results are analyzed in terms of fluid and solid flow structures, and particle-fluid, particle-particle and particle-wall interaction forces. Furthermore, the calculated separation performance is compared with the measurements. The results obtained from the present study indicate that this approach can offer an alternative way to examine the flow and performance of hydrocyclones

Keywords: computational fluid dynamics, discrete element method, hydrocyclone, multiphase flow

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Authors: Yuliang Liu, Thomas Lavallee, Mary Weishaar, Gretchen Fricke, Huaibo Xin

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The longitudinal study was designed to investigate the impacts of the International Training Program in Pedagogy (ITPP) at a midwestern institution in the United States on the visiting scholars from China from 2012-18. The study used the survey research method and involved 48 visiting scholars from Northwest Normal University in China in those eight ITPP cohorts. The results of both quantitative and qualitative data were critically examined and indicated both types of data sources revealed similar findings. It was found that the ITPP has significantly affected all scholars' instruction in China. International implications resulted from the study.

Keywords: international training program in pedagogy, visiting scholars, survey research method, International implications

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Authors: Adisorn Banhan, Toansakul Santiboon, Prasong Saihong

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Using the Socio-Scientific Issues-Based Learning Method is to compare of the blended instruction of STEM education with a sample consisted of 84 students in 2 classes at the 11th grade level in Sarakham Pittayakhom School. The 2-instructional models were managed of five instructional lesson plans in the context of electronic wave issue. These research procedures were designed of each instructional method through two groups, the 40-experimental student group was designed for the instructional STEM education (STEMe) and 40-controlling student group was administered with the Socio-Scientific Issues-Based Learning (SSIBL) methods. Associations between students’ learning achievements of each instructional method and their science attitudes of their predictions to their exploring activities toward physics with the STEMe and SSIBL methods were compared. The Measuring Reasonable Ethics Test (MRET) was assessed students’ reasonable ethics with the STEMe and SSIBL instructional design methods on two each group. Using the pretest and posttest technique to monitor and evaluate students’ performances of their reasonable ethics on electromagnetic wave issue in the STEMe and SSIBL instructional classes were examined. Students were observed and gained experience with the phenomena being studied with the Socio-Scientific Issues-Based Learning method Model. To support with the STEM that it was not just teaching about Science, Technology, Engineering, and Mathematics; it is a culture that needs to be cultivated to help create a problem solving, creative, critical thinking workforce for tomorrow in physics. Students’ attitudes were assessed with the Test Of Physics-Related Attitude (TOPRA) modified from the original Test Of Science-Related Attitude (TOSRA). Comparisons between students’ learning achievements of their different instructional methods on the STEMe and SSIBL were analyzed. Associations between students’ performances the STEMe and SSIBL instructional design methods of their reasonable ethics and their science attitudes toward physics were associated. These findings have found that the efficiency of the SSIBL and the STEMe innovations were based on criteria of the IOC value higher than evidence as 80/80 standard level. Statistically significant of students’ learning achievements to their later outcomes on the controlling and experimental groups with the SSIBL and STEMe were differentiated between students’ learning achievements at the .05 level. To compare between students’ reasonable ethics with the SSIBL and STEMe of students’ responses to their instructional activities in the STEMe is higher than the SSIBL instructional methods. Associations between students’ later learning achievements with the SSIBL and STEMe, the predictive efficiency values of the R2 indicate that 67% and 75% for the SSIBL, and indicate that 74% and 81% for the STEMe of the variances were attributable to their developing reasonable ethics and science attitudes toward physics, consequently.

Keywords: socio-scientific issues-based learning method, STEM education, science attitudes, measurement, reasonable ethics, physics classes

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Authors: Debjani Chakraborty, Abhijit Chatterjee, Aishwaryaprajna

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Posynomials, a special type of polynomials, having singularities, pose difficulties while solving geometric programming problems. In this paper, a methodology has been proposed and used to obtain extreme values for geometric programming problems by nth degree polynomial interpolation technique. Here the main idea to optimise the posynomial is to fit a best polynomial which has continuous gradient values throughout the range of the function. The approximating polynomial is smoothened to remove the discontinuities present in the feasible region and the objective function. This spatial interpolation method is capable to optimise univariate and multivariate geometric programming problems. An example is solved to explain the robustness of the methodology by considering a bivariate nonlinear geometric programming problem. This method is also applicable for signomial programming problem.

Keywords: geometric programming problem, multivariate optimisation technique, posynomial, spatial interpolation

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Authors: Tomas Vincze, Michal Micjan, Milan Pavuk, Martin Weis

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In recent years, alternative materials are gaining attention to replace polycrystalline and amorphous silicon, which are a standard for low requirement devices, where silicon is unnecessarily and high cost. For that reason, metal oxides are envisioned as the new materials for these low-requirement applications such as sensors, solar cells, energy storage devices, or field-effect transistors. Their most common way of layer growth is sputtering; however, this is a high-cost fabrication method, and a more industry-suitable alternative is the sol-gel method. In this group of materials, many oxides exhibit a semiconductor-like behavior with sufficiently high mobility to be applied as transistors. The sol-gel method is a cost-effective deposition technique for semiconductor-based devices. Copper oxides, as p-type semiconductors with free charge mobility up to 1 cm2/Vs., are suitable replacements for poly-Si or a-Si:H devices. However, to reach the potential of silicon devices, a fine-tuning of material properties is needed. Here we focus on the optimization of the electrical parameters of copper oxide-based field-effect transistors by modification of precursor solvent (usually 2-methoxy ethanol). However, to achieve solubility and high-quality films, a better solvent is required. Since almost no solvents have both high dielectric constant and high boiling point, an alternative approach was proposed with blend solvents. By mixing isopropyl alcohol (IPA) and 2-methoxy ethanol (2ME) the precursor reached better solubility. The quality of the layers fabricated using mixed solutions was evaluated in accordance with the surface morphology and electrical properties. The IPA:2ME solution mixture reached optimum results for the weight ratio of 1:3. The cupric oxide layers for optimal mixture had the highest crystallinity and highest effective charge mobility.

Keywords: copper oxide, field-effect transistor, semiconductor, sol-gel method

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Authors: Kartik Thakore, Anna-Roza Tamas, Adam Cole

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The world health organization (WHO) reports that by 2030 more than 23.7 million deaths annually will be caused by Cardiovascular Diseases (CVDs); with a 2008 economic impact of $3.76 T. Metabolic syndrome is a disorder of multiple metabolic risk factors strongly indicated in the development of cardiovascular diseases. Guided lifestyle intervention driven by live coaching has been shown to have a positive impact on metabolic risk factors. Individuals’ path to improved (decreased) metabolic risk factors are driven by personal motivation and personalized messages delivered by coaches and augmented by technology. Using interactions captured between 400 individuals and 3 coaches over a program period of 500 days, a preliminary model was designed. A novel real time event tracking system was created to track and classify clients based on their genetic profile, baseline questionnaires and usage of a mobile application with live coaching sessions. Classification of clients and coaches was done using a support vector machines application build on Apache Spark, Stanford Natural Language Processing Library (SNLPL) and decision-modeling.

Keywords: guided lifestyle intervention, metabolic risk factors, personal coaching, support vector machines application, Apache Spark, natural language processing

Procedia PDF Downloads 417

Authors: Raj Banerjee, Y. M. Parulekar, Aniruddha Sengupta, J. Chattopadhyay

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This study proposes a Discrete Element Method (DEM) simulation using a commercial software PFC 2D (2019) for quantitatively simulating the monotonic and cyclic behaviour of sand using irregular shapes of sand grains. A preliminary analysis of the number of particles for optimal Representative Element Volume (REV) simulation of dimension 35mm x 35mm x 70mm using the scaled Grain Size Distribution (GSD) of sand is carried out. Subsequently, the effect of particle shape on the performance of sand during monotonic and cyclic bi-axial tests is assessed using numerical simulation. The validation of the numerical simulation for one case is carried out using the test results from the literature. Further numerical studies are performed in which the particles in REV are simulated by mixing round discs with irregular clumps (100% round disc, 75% round disc 25% irregular clump, 50% round disc 50% irregular clump, 25% round disc 75% irregular clump, 100% irregular clump) in different proportions using Dry Deposition (DD) method. The macro response for monotonic loading shows that irregular sand has a higher strength than round particles and that the Mohr-Coulomb failure envelope depends on the shape of the grains. During cyclic loading, it is observed that the liquefaction resistance curve (Cyclic Stress Ratio (CSR)-Number of cycles (N)) of sand is dependent on the combination of particle shapes with different proportions.

Keywords: biaxial test, particle shape, monotonic, cyclic

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Authors: Amah Nnachi Lofty, Oyefeso Olufemi, Ibiam Udu Ama

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New and more powerful communications technologies continue to emerge at a rapid pace and their uses in education are widespread and the impact remarkable in the developing societies. This study investigates Mobile Collaboration Learning Technique (MCLT) on learners’ outcome among students in tertiary institutions of developing nations (a case of Nigeria students). It examines the significance of retention achievement scores of students taught using mobile collaboration and conventional method. The sample consisted of 120 students using Stratified random sampling method. Three research questions and hypotheses were formulated, and tested at a 0.05 level of significance. A student achievement test (SAT) was made of 40 items of multiple-choice objective type, developed and validated for data collection by professionals. The SAT was administered to students as pre-test and post-test. The data were analyzed using t-test statistic to test the hypotheses. The result indicated that students taught using MCLT performed significantly better than their counterparts using the conventional method of instruction. Also, there was no significant difference in the post-test performance scores of male and female students taught using MCLT. Based on the findings, the following recommendations was made that: Mobile collaboration system be encouraged in the institutions to boost knowledge sharing among learners, workshop and trainings should be organized to train teachers on the use of this technique and that schools and government should formulate policies and procedures towards responsible use of MCLT.

Keywords: education, communication, learning, mobile collaboration, technology

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Authors: Majid Forghani, Michael Khachay

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In genetics, the impact of neighboring amino acids on a target site is referred as the nearest-neighbor effect or simply neighbor effect. In this paper, a new method called wavelet particle decomposition representing the one-dimensional neighbor effect using wavelet packet decomposition is proposed. The main idea lies in known dependence of wavelet packet sub-bands on location and order of neighboring samples. The method decomposes the value of a signal sample into small values called particles that represent a part of the neighbor effect information. The results have shown that the information obtained from the particle decomposition can be used to create better model variables or features. As an example, the approach has been applied to improve the correlation of test and reference sequence distance with titer in the hemagglutination inhibition assay.

Keywords: antigenic variants, neighbor effect, wavelet packet, wavelet particle decomposition

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Authors: Jie Liu, Wei Wei, Chun-Ping Chang

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Using a sample of 110 countries over the period 1984-2013, this paper examines the impacts of country risks on choosing a specific exchange rate regime (first by utilizing the Levy-Yeyati and Sturzenegger de facto classification and then robusting it by the IMF de jure measurement) relative to other regimes via the panel multinomial logit approach. Empirical findings are as follows. First, in the full samples case we provide evidence that government is more likely to implement a flexible regime, but less likely to adopt a fixed regime, under a low level of composite and financial risk. Second, we find that Eurozone countries are more likely to choose a fixed exchange rate regime with a decrease in the level of country risk and favor a flexible regime in response to a shock from an increase of risk, which is opposite to non-Eurozone countries. Third, we note that high-risk countries are more likely to choose a fixed regime with a low level of composite and political risk in the government, but do not adjust the exchange rate regime as a shock absorber when facing economic and financial risks. It is interesting to see that those countries with relatively low risk display almost opposite results versus high-risk economies. Overall, we believe that it is critically important to account for political economy variables in a government’s exchange rate policy decisions, especially for country risks. All results are robust to the panel ordered probit model.

Keywords: country risk, political economy, exchange rate regimes, shock absorber

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Authors: Mohammad Ghavami, Reza S. Dilmaghani

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This paper presents an adaptive framework for modelling financial markets using equity risk premiums, risk free rates and volatilities. The recorded economic factors are initially used to train four adaptive filters for a certain limited period of time in the past. Once the systems are trained, the adjusted coefficients are used for modelling and prediction of an important financial market index. Two different approaches based on least mean squares (LMS) and recursive least squares (RLS) algorithms are investigated. Performance analysis of each method in terms of the mean squared error (MSE) is presented and the results are discussed. Computer simulations carried out using recorded data show MSEs of 4% and 3.4% for the next month prediction using LMS and RLS adaptive algorithms, respectively. In terms of twelve months prediction, RLS method shows a better tendency estimation compared to the LMS algorithm.

Keywords: adaptive methods, LSE, MSE, prediction of financial Markets

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Authors: M. Kubilay Önal

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The objective of this study was to determine the adaptabilities of native apricot materials collected from Southeast Anatolia region of Turkey to Aegean Region conditions. Different phenological and pomological characteristics of the cultivars were observed during study. Determination of promising types for adaptation trials were performed employing the 'weighed-ranking' method. To determine them the relative points were given to the characteristics such as yield, average fruit weight, attractiveness, soluble solid, seed ratio by weight and aroma. As a result of two-year evaluation studies on the phenological and pomological characteristics of 22 types, 9 out of them, viz., nos. 2235, 2236, 2237, 2239, 2242, 2244, 2246, 2249, 2257 were selected as promising ones.

Keywords: apricot, phenological characters, pomological characters, weight-ranking method

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Authors: E. Tandis, E. Assareh

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Designing the optimal shape of MW wind turbine blades is provided in a number of cases through evolutionary algorithms associated with mathematical modeling (Blade Element Momentum Theory). Evolutionary algorithms, among the optimization methods, enjoy many advantages, particularly in stability. However, they usually need a large number of function evaluations. Since there are a large number of local extremes, the optimization method has to find the global extreme accurately. The present paper introduces a new population-based hybrid algorithm called Genetic-Based Bees Algorithm (GBBA). This algorithm is meant to design the optimal shape for MW wind turbine blades. The current method employs crossover and neighborhood searching operators taken from the respective Genetic Algorithm (GA) and Bees Algorithm (BA) to provide a method with good performance in accuracy and speed convergence. Different blade designs, twenty-one to be exact, were considered based on the chord length, twist angle and tip speed ratio using GA results. They were compared with BA and GBBA optimum design results targeting the power coefficient and solidity. The results suggest that the final shape, obtained by the proposed hybrid algorithm, performs better compared to either BA or GA. Furthermore, the accuracy and speed convergence increases when the GBBA is employed

Keywords: Blade Design, Optimization, Genetic Algorithm, Bees Algorithm, Genetic-Based Bees Algorithm, Large Wind Turbine

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Authors: Nevena Jakovčević Stor, Ivan Slapničar

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Any polynomial can be expressed as a characteristic polynomial of a complex symmetric arrowhead matrix. This expression is not unique. If the polynomial is real with only real distinct roots, the matrix can be chosen as real. By using accurate forward stable algorithm for computing eigen values of real symmetric arrowhead matrices we derive a forward stable algorithm for computation of roots of such polynomials in O(n^2 ) operations. The algorithm computes each root to almost full accuracy. In some cases, the algorithm invokes extended precision routines, but only in the non-iterative part. Our examples include numerically difficult problems, like the well-known Wilkinson’s polynomials. Our algorithm compares favorably to other method for polynomial root-finding, like MPSolve or Newton’s method.

Keywords: roots of polynomials, eigenvalue decomposition, arrowhead matrix, high relative accuracy

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Authors: Kishore Kumar R., Kaustav Sengupta, Shalini Sood Sehgal, Poornima Santhanam

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Fashion is a human expression that is constantly changing. One of the prime factors that consistently influences fashion is the change in colour preferences. The role of colour in our everyday lives is very significant. It subconsciously explains a lot about one’s mindset and mood. Analyzing the colours by extracting them from the outfit images is a critical study to examine the individual’s/consumer behaviour. Several research works have been carried out on extracting colours from images, but to the best of our knowledge, there were no studies that extract colours to specific apparel and identify colour patterns geographically. This paper proposes a framework for accurately extracting colours from T-shirt images and predicting dominant colours geographically. The proposed method consists of two stages: first, a U-Net deep learning model is adopted to segment the T-shirts from the images. Second, the colours are extracted only from the T-shirt segments. The proposed method employs the iMaterialist (Fashion) 2019 dataset for the semantic segmentation task. The proposed framework also includes a mechanism for gathering data and analyzing India’s general colour preferences. From this research, it was observed that black and grey are the dominant colour in different regions of India. The proposed method can be adapted to study fashion’s evolving colour preferences.

Keywords: colour analysis in t-shirts, convolutional neural network, encoder-decoder, k-means clustering, semantic segmentation, U-Net model

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Authors: Chih-Jer Lin, Jian-Hong Hou

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Industry 4.0 is a vision of integrated industry implemented by artificial intelligent computing, software, and Internet technologies. The main goal of industry 4.0 is to deal with the difficulty owing to competitive pressures in the marketplace. For today’s manufacturing factories, the type of production is changed from mass production (high quantity production with low product variety) to medium quantity-high variety production. To offer flexibility, better quality control, and improved productivity, robot manipulators are used to combine material processing, material handling, and part positioning systems into an integrated manufacturing system. To implement the automated system for sheet metal bending operations, motion planning of a 7-degrees of freedom (DOF) robot is studied in this paper. A virtual reality (VR) environment of a bending cell, which consists of the robot and a bending machine, is established using the virtual robot experimentation platform (V-REP) simulator. For sheet metal bending operations, the robot only needs six DOFs for the pick-and-place or tracking tasks. Therefore, this 7 DOF robot has more DOFs than the required to execute a specified task; it can be called a redundant robot. Therefore, this robot has kinematic redundancies to deal with the task-priority problems. For redundant robots, Pseudo-inverse of the Jacobian is the most popular motion planning method, but the pseudo-inverse methods usually lead to a kind of chaotic motion with unpredictable arm configurations as the Jacobian matrix lose ranks. To overcome the above problem, we proposed a method to formulate the motion planning problems as optimization problem. Moreover, a genetic algorithm (GA) based method is proposed to deal with motion planning of the redundant robot. Simulation results validate the proposed method feasible for motion planning of the redundant robot in an automated sheet-metal bending operations.

Keywords: redundant robot, motion planning, genetic algorithm, obstacle avoidance

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Authors: Zulfikar Dinar Wahidayat Putra

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Water scarcity become a major challenge in an arid area. One of the arid areas is La Serena city in the Northern Chile which become a case study of this paper. Based on that, this paper tries to identify a sustainable water system by using urban harvest approach as a method to achieve water self-sufficiency for a neighborhood area in the La Serena city. By using the method, it is possible to create sustainable water system in the neighborhood area by reducing up to 38% of water demand and 94% of wastewater production even though water self-sufficient cannot be fully achieved, because of its dependency to the drinking water supply from water treatment plant of La Serena city.

Keywords: arid area, sustainable water system, urban harvest approach, self-sufficiency

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Authors: Le Hieu Giang, Truong Nguyen Luan Vu, Le Linh

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In this paper, the analytical tuning rules of IMC-PID controller are presented for the multivariable Smith predictor that involved the ideal decoupling. Accordingly, the decoupler is first introduced into the multivariable Smith predictor control system by a well-known approach of ideal decoupling, which is compactly extended for general nxn multivariable processes and the multivariable Smith predictor controller is then obtained in terms of the multiple single-loop Smith predictor controllers. The tuning rules of PID controller in series with filter are found by using Maclaurin approximation. Many multivariable industrial processes are employed to demonstrate the simplicity and effectiveness of the presented method. The simulation results show the superior performances of presented method in compared with the other methods.

Keywords: ideal decoupler, IMC-PID controller, multivariable smith predictor, Padé approximation

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Authors: C. B. Le, V. N. Pham

Abstract:

In modern data analysis, multi-source data appears more and more in real applications. Multi-source data clustering has emerged as a important issue in the data mining and machine learning community. Different data sources provide information about different data. Therefore, multi-source data linking is essential to improve clustering performance. However, in practice multi-source data is often heterogeneous, uncertain, and large. This issue is considered a major challenge from multi-source data. Ensemble is a versatile machine learning model in which learning techniques can work in parallel, with big data. Clustering ensemble has been shown to outperform any standard clustering algorithm in terms of accuracy and robustness. However, most of the traditional clustering ensemble approaches are based on single-objective function and single-source data. This paper proposes a new clustering ensemble method for multi-source data analysis. The fuzzy optimized multi-objective clustering ensemble method is called FOMOCE. Firstly, a clustering ensemble mathematical model based on the structure of multi-objective clustering function, multi-source data, and dark knowledge is introduced. Then, rules for extracting dark knowledge from the input data, clustering algorithms, and base clusterings are designed and applied. Finally, a clustering ensemble algorithm is proposed for multi-source data analysis. The experiments were performed on the standard sample data set. The experimental results demonstrate the superior performance of the FOMOCE method compared to the existing clustering ensemble methods and multi-source clustering methods.

Keywords: clustering ensemble, multi-source, multi-objective, fuzzy clustering

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Authors: R. Devicharan

Abstract:

In a short span 3D Printing is expected to play a vital role in our life. The possibility of creativity and speed in manufacturing through various 3D printing processes is infinite. This study is performed on the FDM (Fused Deposition Modelling) method of 3D printing, which is one of the pre-dominant methods of 3D printing technologies. This study focuses on physical properties of the objects produced by 3D printing which determine the applications of the 3D printed objects. This paper specifically aims at the study of the tensile strength and the folding endurance of the 3D printed objects through the FDM (Fused Deposition Modelling) method using the ABS (Acronitirile Butadiene Styrene) and PLA (Poly Lactic Acid) plastic materials. The study is performed on a controlled environment and the specific machine settings. Appropriate tables, graphs are plotted and research analysis techniques will be utilized to analyse, verify and validate the experiment results.

Keywords: FDM process, 3D printing, ABS for 3D printing, PLA for 3D printing, rapid prototyping

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Authors: Raghvendra Singh Yadav, Ivo Kuřitka, Jaromir Havlica, Zuzana Kozakova, Jiri Masilko, Lukas Kalina, Miroslava Hajdúchová, Vojtěch Enev, Jaromir Wasserbauer

Abstract:

In this work, we investigated the structural and magnetic properties of CoFe2O4:Nd3+/Dy3+/Pr3+/Gd3+ nanoparticles synthesized by starch-assisted sol-gel combustion method. X-ray diffraction pattern confirmed the formation of cubic spinel structure of rare-earth ions (Nd3+, Dy3+, Pr3+, Gd3+) doped CoFe2O4 spinel ferrite nanoparticles. Raman and Fourier Transform Infrared spectroscopy study also confirmed cubic spinel structure of rare-earth ions (Nd3+, Dy3+, Pr3+, Gd3+) substituted CoFe2O4 nanoparticles. The field emission scanning electron microscopy study revealed the effect of annealing temperature on size of rare-earth ions (Nd3+, Dy3+, Pr3+, Gd3+) substituted CoFe2O4 nanoparticles and particles were in the range of 10-100 nm. The magnetic properties of rare-earth ions (Nd3+, Dy3+, Pr3+, Gd3+) substituted CoFe2O4 nanoparticles were investigated by using vibrating sample magnetometer. The variation in saturation magnetization, coercivity and remanent magnetization with annealing temperature/ particle size of rare-earth ions (Nd3+, Dy3+, Pr3+, Gd3+) substituted CoFe2O4 nanoparticles was observed. Acknowledgment: This work was supported by the Ministry of Education, Youth and Sports of the Czech Republic – Program NPU I (LO1504).

Keywords: starch, sol-gel combustion method, rare-earth ions, spinel ferrite nanoparticles, magnetic properties

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Authors: N. K. Chougule, G. V. Parishwad

Abstract:

The pin fin heat sink is a novel heat transfer device to transfer large amount of heat through with very small temperature differences and it also possesses large uniform cooling characteristics. Pin fins are widely used as elements that provide increased cooling for electronic devices. Increasing demands regarding the performance of such devices can be observed due to the increasing heat production density of electronic components. For this reason, extensive work is being carried out to select and optimize pin fin elements for increased heat transfer. In this paper, the effects of design parameters and the optimum design parameters for a Pin-Fin heat sink (PFHS) under multi-jet impingement case with thermal performance characteristics have been investigated by using Taguchi methodology based on the L9 orthogonal arrays. Various design parameters, such as pin-fin array size, gap between nozzle exit to impingement target surface (Z/d) and air velocity are explored by numerical experiment. The average convective heat transfer coefficient is considered as the thermal performance characteristics. The analysis of variance (ANOVA) is applied to find the effect of each design parameter on the thermal performance characteristics. Then the results of confirmation test with the optimal level constitution of design parameters have obviously shown that this logic approach can effective in optimizing the PFHS with the thermal performance characteristics. The analysis of the Taguchi method reveals that, all the parameters mentioned above have equal contributions in the performance of heat sink efficiency. Experimental results are provided to validate the suitability of the proposed approach.

Keywords: Pin Fin Heat Sink (PFHS), Taguchi method, CFD, thermal performance

Procedia PDF Downloads 236