Search results for: exponential smoothing methods

Authors: Jehad Al Dallal

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A class in an Object-Oriented (OO) system is the basic unit of design, and it encapsulates a set of attributes and methods. In OO systems, instead of redefining the attributes and methods that are included in other classes, a class can inherit these attributes and methods and only implement its unique attributes and methods, which results in reducing code redundancy and improving code testability and maintainability. Such mechanism is called Class Inheritance. However, some software engineering applications may require accounting for all the inherited class members (i.e., attributes and methods). This paper explains how to account for inherited class members and discusses the software engineering applications that require such consideration.

Keywords: class flattening, external quality attribute, inheritance, internal quality attribute, object-oriented design

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Authors: Hanan Hayat, Russell Lock

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The importance of usability in ensuring software quality has been well established in literature and widely accepted by software development practitioners. Consequently, numerous usability evaluation methods have been developed. However, the availability of large variety of evaluation methods alongside insufficient studies that critically analyse them resulted in an ambiguous process of selection amongst non-usability-expert practitioners. This study investigates the factors affecting the selection of usability evaluation methods within a project by interviewing a software development team. The results of the data gathered are then analysed and integrated in developing a framework. The framework developed poses a solution to the selection processes of usability evaluation methods by adjusting to individual projects resources and goals. It has the potential to be further evaluated to verify its applicability and usability within the domain of this study.

Keywords: usability evaluation, evaluating usability in non-user entered designs, usability evaluation methods (UEM), usability evaluation in projects

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Authors: Sulmaz Mozaffari, Zahra Mozaffari, Saman Mozaffari

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Training is a counting and orderly process which purpose is to grow all as peals of the students to get the human knowledge and have the social norms. Also to help them grow their talents. Social science as in educational and training science at the sometime is very important for schools and universities. Unfortunately the method which is mostly used for teaching and training at present is student- teacher method and because of its ease the other methods are ignored. This research is to consider the most efficient methods in social science and analyse them. The Results show that the best methods in which the students are present during the teaching procedure.

Keywords: social science, methodology, student base methodology, technology

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Authors: Ouazoul Abdelouahd, Jemjami Nadia

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The concept of well-being at work is one of today's major challenges in maintaining quality of life and managing psycho-social risks at work. Indeed, work in the sports sector has evolved over time, and this exponential evolution, marked by increasing demands and psychological, physical and/or social challenges, which sometimes exceed the resources of sports players, influences their sense of well-being at work. Well-being and burnout as antagonists provide information on the quality of working life in sports. The main objective of this literature review was to examine the scientific corpus dealing with the subject of psychological well-being at work in the sports sector and, more specifically, with sports coaches while exploring the link between sports burnout and well-being. The results reveal the richness of the conceptual approaches and the difficulties of putting them into practice. Prospects for future research were put forward.

Keywords: psychological well-being, burnout, quality of life, sports coaching

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Authors: Yunus Doğan, Ahmet Durap

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Coastal regions are the one of the most commonly used places by the natural balance and the growing population. In coastal engineering, the most valuable data is wave behaviors. The amount of this data becomes very big because of observations that take place for periods of hours, days and months. In this study, some statistical methods such as the wave spectrum analysis methods and the standard statistical methods have been used. The goal of this study is the discovery profiles of the different coast areas by using these statistical methods, and thus, obtaining an instance based data set from the big data to analysis by using data mining algorithms. In the experimental studies, the six sample data sets about the wave behaviors obtained by 20 minutes of observations from Mersin Bay in Turkey and converted to an instance based form, while different clustering techniques in data mining algorithms were used to discover similar coastal places. Moreover, this study discusses that this summarization approach can be used in other branches collecting big data such as medicine.

Keywords: clustering algorithms, coastal engineering, data mining, data summarization, statistical methods

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Authors: N. Samarinas, C. Evangelides, C. Vrekos

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The aim of this paper is the comparison of three different methods, in order to produce fuzzy tolerance relations for rainfall data classification. More specifically, the three methods are correlation coefficient, cosine amplitude and max-min method. The data were obtained from seven rainfall stations in the region of central Greece and refers to 20-year time series of monthly rainfall height average. Three methods were used to express these data as a fuzzy relation. This specific fuzzy tolerance relation is reformed into an equivalence relation with max-min composition for all three methods. From the equivalence relation, the rainfall stations were categorized and classified according to the degree of confidence. The classification shows the similarities among the rainfall stations. Stations with high similarity can be utilized in water resource management scenarios interchangeably or to augment data from one to another. Due to the complexity of calculations, it is important to find out which of the methods is computationally simpler and needs fewer compositions in order to give reliable results.

Keywords: classification, fuzzy logic, tolerance relations, rainfall data

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Authors: Rafik Djemili, Hocine Bourouba, M. C. Amara Korba

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In this paper, we present a method in order to classify EEG signals for Brain-Computer Interfaces (BCI). EEG signals are first processed by means of spectral estimation methods to derive reliable features before classification step. Spectral estimation methods used are standard periodogram and the periodogram calculated by the Welch method; both methods are compared with Logarithm of Band Power (logBP) features. In the method proposed, we apply Linear Discriminant Analysis (LDA) followed by Support Vector Machine (SVM). Classification accuracy reached could be as high as 85%, which proves the effectiveness of classification of EEG signals based BCI using spectral methods.

Keywords: brain-computer interface, motor imagery, electroencephalogram, linear discriminant analysis, support vector machine

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Authors: Peter Schnell, Phillip Haag

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In the course of the structural transformation of the construction industry, the integration of industrialization and digitization has led to the development of construction methods with an increased degree of prefabrication, such as system or modular construction. Compared to conventional construction, these innovative construction methods are characterized by modified structural and procedural properties and expand the range of construction services. Faced with the supply side, it is possible to identify construction-specific customer types with different characteristics and certain preferences as far as the choice of construction method is concerned. The basis for this finding was qualitative expert interviews. By evaluating the stereotypical customer needs, a corresponding segmentation of the demand side can be made along with the basic orientation and decision behavior. This demarcation supports the target- and needs-oriented customer approach and contributes to cooperative and successful project management.

Keywords: differentiation of customer types, modular construction methods, conventional construction methods, stereotypical customer types

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Authors: Bilquis Ferdousi

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With the exponential growth of the online business, the threat to consumers’ privacy and data security has become a serious challenge. This literature review-based study focuses on a better understanding of those threats and what legislative measures have been taken to address those challenges. Research shows that people are increasingly involved in online business using different digital devices and platforms, although this practice varies based on age groups. The threat to consumers’ privacy and data security is a serious hindrance in developing trust among consumers in online businesses. There are some legislative measures taken at the federal and state level to protect consumers’ privacy and data security. The study was based on an extensive review of current literature on protecting consumers’ privacy and data security and legislative measures that have been taken.

Keywords: privacy, data security, legislation, online business

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Authors: Aicha Zohbie

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The purpose of this paper is to critically compare two teaching methods: the communicative method and the grammar-translation method. The paper presents the importance of language awareness as an approach to teaching and learning language and some challenges that language teachers face. In addition, the paper strives to determine whether the adoption of communicative teaching methods or the grammar teaching method would be more effective to teach a language. A variety of features are considered for comparing the two methods: the purpose of each method, techniques used, teachers’ and students’ roles, the use of L1, the skills that are emphasized, the correction of students’ errors, and the students’ assessments. Finally, the paper includes suggestions and recommendations for implementing an approach that best meets the students’ needs in a classroom.

Keywords: language teaching methods, language awareness, communicative method grammar translation method, advantages and disadvantages

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Authors: Seongsoo Lee

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IP reuse is an effective design methodology for modern SoC design to reduce effort and time. However, description and modeling methods of IP interfaces are different due to different IP designers. In this paper, standardized description and modeling methods of IP interfaces are proposed. It consists of 11 items such as IP information, model provision, data type, description level, interface information, port information, signal information, protocol information, modeling level, modeling information, and source file. The proposed description and modeling methods enables easy understanding, simulation, verification, and modification in IP reuse.

Keywords: interface, standardization, description, modeling, semiconductor IP

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Authors: M. Meenasaranya, S. Saravanan

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Nonlinear stability analysis is carried out to determine the effect of surface temperature modulation in an infinite horizontal porous layer heated from below. The layer is saturated by an electrically conducting, viscous, incompressible and Newtonian fluid. The Brinkman model is used for momentum equation, and the Boussinesq approximation is invoked. The system is assumed to be bounded by rigid boundaries. The energy theory is implemented to find the global exponential stability region of the considered system. The results are analysed for arbitrary values of modulation frequency and amplitude. The existence of subcritical instability region is confirmed by comparing the obtained result with the known linear result. The vertical magnetic field is found to stabilize the system.

Keywords: Brinkman model, energy method, magnetic field, surface temperature modulation

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Authors: Karim Matter, Heba Fayed, Ahmed Abd-Elaziz, Moustafa Hussein

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Due to the exponential growth of mobile devices and wireless services, a huge demand for radiofrequency has increased. The presence of several frequencies causes interference between cells, which must be minimized to get the lower Bit Error Rate (BER). For this reason, it is of great interest to use visible light communication (VLC). This paper suggests a VLC system that decreases the BER by applying a new LED distribution with a hexagonal shape using a Frequency Reuse (FR) concept to mitigate the interference between the reused frequencies inside the hexagonal shape. The BER is measured in two scenarios, Line of Sight (LoS) and Non-Line of Sight (Non-LoS), for each technique that we used. The recommended values of BER in the proposed model for Soft Frequency Reuse (SFR) in the case of Los at 4, 8, and 10 dB signal to noise ratio (SNR), are 3.6×10⁻⁶, 6.03×10⁻¹³, and 2.66×10⁻¹⁸, respectively.

Keywords: visible light communication (VLC), field of view (FoV), hexagonal array, frequency reuse

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Authors: Madhu Jain, Rakesh Kumar Meena

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This paper investigates a finite M/G/1 fault tolerant multi-component machining system. The system incorporates the features such as standby support, threshold recovery and imperfect coverage make the study closer to real time systems. The performance prediction of M/G/1 fault tolerant system is carried out using recursive approach by treating remaining service time as a supplementary variable. The numerical results are presented to illustrate the computational tractability of analytical results by taking three different service time distributions viz. exponential, 3-stage Erlang and deterministic. Moreover, the cost function is constructed to determine the optimal choice of system descriptors to upgrading the system.

Keywords: fault tolerant, machine repair, threshold recovery policy, imperfect coverage, supplementary variable technique

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Authors: Parshanth Maroju, Ramandeep Behl, Sandile S. Motsa

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In this study, we proposed a simple and interesting family of fourth-order multi-point methods without memory for obtaining simple roots. This family requires only three functional evaluations (viz. two of functions f(xn), f(yn) and third one of its first-order derivative f'(xn)) per iteration. Moreover, the accuracy and validity of new schemes is tested by a number of numerical examples are also proposed to illustrate their accuracy by comparing them with the new existing optimal fourth-order methods available in the literature. It is found that they are very useful in high precision computations. Further, the dynamic study of these methods also supports the theoretical aspect.

Keywords: basins of attraction, nonlinear equations, simple roots, Newton's method

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Authors: Ahmad Zahran, Ahmed Herzallah, Ahmad Ahmad, Mahran Quraan

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Generation of high DC voltages is necessary for testing the insulation material of high voltage AC transmission lines with long lengths. The harmonic and ripple contents of the output DC voltage supplied by high voltage DC circuits require the use of costly capacitors to smooth the output voltage after rectification. This paper proposes a new modular multiplier high voltage DC generator with embedded Cockcroft-Walton circuits that achieve a negligible harmonic and ripple contents of the output DC voltage without the need for costly filters to produce a nearly constant output voltage. In this new topology, Cockcroft-Walton modules are connected in series to produce a high DC output voltage. The modules are supplied by low input AC voltage sources that have the same magnitude and frequency and shifted from each other by a certain angle to eliminate the harmonics from the output voltage. The small ripple factor is provided by the smoothing column capacitors and the phase shifted input voltages of the cascaded modules. The constituent harmonics within each module are determined using Fourier analysis. The viability of the proposed DC generator for testing purposes and the effectiveness of the cascaded connection are confirmed by numerical simulations using MATLAB/Simulink.

Keywords: Cockcroft-Walton circuit, harmonics, ripple factor, HVDC generator

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Authors: Mohan Li

Abstract:

Nowadays, intelligent research technology is more and more important than traditional research methods in urban research work, and this proportion will greatly increase in the next few decades. Frequently such analyzing work cannot be carried without some software engineering knowledge. And here, domain models of urban research will be necessary when applying software engineering knowledge to urban work. In many urban plan practice projects, making rational models, feeding reliable data, and providing enough computation all make indispensable assistance in producing good urban planning. During the whole work process, domain models can optimize workflow design. At present, human beings have entered the era of big data. The amount of digital data generated by cities every day will increase at an exponential rate, and new data forms are constantly emerging. How to select a suitable data set from the massive amount of data, manage and process it has become an ability that more and more planners and urban researchers need to possess. This paper summarizes and makes predictions of the emergence of technologies and technological iterations that may affect urban research in the future, discover urban problems, and implement targeted sustainable urban strategies. They are summarized into seven major domain models. They are urban and rural regional domain model, urban ecological domain model, urban industry domain model, development dynamic domain model, urban social and cultural domain model, urban traffic domain model, and urban space domain model. These seven domain models can be used to guide the construction of systematic urban research topics and help researchers organize a series of intelligent analytical tools, such as Python, R, GIS, etc. These seven models make full use of quantitative spatial analysis, machine learning, and other technologies to achieve higher efficiency and accuracy in urban research, assisting people in making reasonable decisions.

Keywords: big data, domain model, urban planning, urban quantitative analysis, machine learning, workflow design

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Authors: Pradeep Kulshrestha, Maulana Ayoub Ali

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The level of penetration of Islamic banking products and services has recorded a reasonable growth at an exponential rate in many parts of the world. There are many factors which have contributed to this growth including, but not limited to the rapid growth of number of Muslims who are uncomfortable with the conventional ways of banking, interest and higher interest rates scheduled by conventional banks and financial institutions as well as the financial inclusion campaign conducted in many countries. The system is facing legal challenges which open the research fdoor for practitioners and academicians for the sake of finding out solutions to those challenges. This paper tries to investigate the development of the Islamic banking system in the United Kingdom (UK), Saudi Arabia, Malaysia, Iran, Kenya, Nigeria and Uganda in order to understand the modalities which have been employed to run an Islamic banking system in the aforementioned countries. The methodology which has been employed in doing this research paper is Doctrinal, of which legislations, policies and other legal tools have been carefully studied and analysed. Again, papers from academic journals, books and financial reports have been deeply analysed for the purpose of enriching the paper and come up with a tangible results. The paper found that in Asia, Malaysia has created the smoothest legal platform for Islamic banking system to work properly in the country. The United Kingdom has tried harder to smooth the banking system without affecting the conventional banking methods and without favouring the operations of Islamic banks. It also tries harder to make UK as an Islamic banking and finance hub in Europe. The entire banking system in Iran is Islamic, while Nigeria has undergone several legal reforms to suit Islamic banking system in the country. Kenya and Uganda are at a different pace in making Islamic Banking system work alongside the conventional banking system.  

Keywords: shariah, Islamic banking, law, alternative banking

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Authors: Lubabatu Sada Sodangu

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Malaria is a major cause of death in tropical and subtropical nations. Malaria cases are continually rising as a result of a number of factors, despite the fact that the condition is now treatable using effective methods. In this situation, quick and effective diagnostic methods are essential for the management and control of malaria. Malaria diagnosis using conventional methods is still troublesome, hence new technologies have been created and implemented to get around the drawbacks. The review describes the currently known malaria diagnostic techniques, their strengths and shortcomings.

Keywords: malaria, technique, diagnosis, Africa

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Authors: Lubabatu Sada Sodangi

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Malaria is a major cause of death in tropical and subtropical nations. Malaria cases are continually rising as a result of a number of factors, despite the fact that the condition is now treatable using effective methods. In this situation, quick and effective diagnostic methods are essential for the management and control of malaria. Malaria diagnosis using conventional methods is still troublesome; hence, new technologies have been created and implemented to get around the drawbacks. The review describes the currently known malaria diagnostic techniques, their strengths, and shortcomings.

Keywords: malaria, technique, diagnosis, Africa

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Authors: Heri Suryoatmojo, Adi Kurniawan, Feby A. Pamuji, Nursalim, Syaffaruddin, Herbert Innah

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Photovoltaic (PV) system hybrid with diesel system is utilized widely for electrification in remote area. PV output power fluctuates due to uncertainty condition of temperature and sun irradiance. When the penetration of PV power is large, the reliability of the power utility will be disturbed and seriously impact the unstable frequency of system. Therefore, designing a robust frequency controller in PV-diesel hybrid power system is very important. This paper proposes new method of frequency control application in hybrid PV-diesel system based on artificial neural network (ANN). This method can minimize the frequency deviation without smoothing PV output power that controlled by maximum power point tracking (MPPT) method. The neural network algorithm controller considers average irradiance, change of irradiance and frequency deviation. In order the show the effectiveness of proposed algorithm, the addition of battery as energy storage system is also presented. To validate the proposed method, the results of proposed system are compared with the results of similar system using MPPT only. The simulation results show that the proposed method able to suppress frequency deviation smaller compared to the results of system using MPPT only.

Keywords: energy storage system, frequency deviation, hybrid power generation, neural network algorithm

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Authors: Kanit Manatura

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The combustion and pyrolysis behavior of Palm Kernel Shell (PKS) were investigated in a thermogravimetric analyzer. A 10 mg sample of each biomass was heated from 30 °C to 800 °C at four heating rates (within 5, 10, 15 and 30 °C/min) in nitrogen and dry air flow of 20 ml/min instead of pyrolysis and combustion process respectively. During pyrolysis, thermal decomposition occurred on three different stages include dehydration, hemicellulose-cellulose and lignin decomposition on each temperature range. The TG/DTG curves showed the degradation behavior and the pyrolysis/combustion characteristics of the PKS samples which led to apply in thermogravimetric analysis. The kinetic factors including activation energy and pre-exponential factor were determined by the Coats-Redfern method. The obtained kinetic factors are used to simulate the thermal decomposition and compare with experimental data. Rising heating rate leads to shift the mass loss towards higher temperature.

Keywords: combustion, palm kernel shell, pyrolysis, thermogravimetric analyzer

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Authors: Justice Dadzie, Stacy H. Surman, Ruth K. Annan-Brew, Ifesinachi J. Ezugwu, Evans Addison

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This study aimed to explore the correlation between students' performance in educational statistics and research methods in education, as well as investigate potential differences in performance based on their undergraduate programs. A cross-sectional design was employed, and data was collected from 170 students enrolled in master of philosophy programs in the department of education and psychology. The correlation analysis revealed a strong positive correlation between students' performance in intermediate statistics in education and research methods in education. This indicates a close relationship between the two domains. The MANOVA analysis showed no significant differences in the linear combination of intermediate statistics in education and research methods in education scores across the different undergraduate programs. The tests of between-subjects effects further confirmed that the student's performance in intermediate statistics in education and research methods in education did not differ significantly across the different undergraduate programs. These findings contribute to the existing literature by providing insights into the correlation between educational statistics and research methods, and the influence of undergraduate program backgrounds on students' performance in these domains. The strong positive correlation between intermediate statistics and research methods highlights the importance of a solid foundation in statistics for understanding and applying research methods. Moreover, the consistent relationship across different academic backgrounds emphasizes the need for targeted interventions and support systems to enhance graduate students' competencies in these critical areas.

Keywords: educational statistics, research methods, undergraduate programs, students performance

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Authors: Belloufi Mohammed, Sellami Badreddine

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Conjugate gradient methods have played a special role for solving large scale optimization problems due to the simplicity of their iteration, convergence properties and their low memory requirements. In this work, we propose a new class of conjugate gradient methods which ensures sufficient descent. Moreover, we propose a new search direction with the Wolfe line search technique for solving unconstrained optimization problems, a global convergence result for general functions is established provided that the line search satisfies the Wolfe conditions. Our numerical experiments indicate that our proposed methods are preferable and in general superior to the classical conjugate gradient methods in terms of efficiency and robustness.

Keywords: unconstrained optimization, conjugate gradient method, sufficient descent property, numerical comparisons

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Authors: Aidan J. Bowes, Reaz Hasan

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The automotive industry is continually aiming to develop the aerodynamics of car body design. This may be for a variety of beneficial reasons such as to increase speed or fuel efficiency by reducing drag. However recently there has been a greater amount of focus on wind noise produced while driving. Designers in this industry seek a combination of both simplicity of approach and overall effectiveness. This combined with the growing availability of commercial CFD (Computational Fluid Dynamics) packages is likely to lead to an increase in the use of RANS (Reynolds Averaged Navier-Stokes) based CFD methods. This is due to these methods often being simpler than other CFD methods, having a lower demand on time and computing power. In this investigation the effectiveness of turbulent flow and acoustic noise prediction using RANS based methods has been assessed for different wing mirror geometries. Three different RANS based models were used, standard k-ε, realizable k-ε and k-ω SST. The merits and limitations of these methods are then discussed, by comparing with both experimental and numerical results found in literature. In general, flow prediction is fairly comparable to more complex LES (Large Eddy Simulation) based methods; in particular for the k-ω SST model. However acoustic noise prediction still leaves opportunities for more improvement using RANS based methods.

Keywords: acoustics, aerodynamics, RANS models, turbulent flow

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Authors: John Paul Q. Tomas, Mark Wilson L. de los Reyes, Kirsten Joyce P. Vasquez

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The most frequent type of fracture is a wrist fracture, which often makes it difficult for medical professionals to find and locate. In this study, fractures in wrist x-ray pictures were located and identified using deep learning and computer vision. The researchers used image filtering, masking, morphological operations, and data augmentation for the image preprocessing and trained the RetinaNet and Faster R-CNN models with ResNet50 backbones and Adam optimizers separately for each image filtering technique and projection. The RetinaNet model with Anisotropic Diffusion Smoothing filter trained with 50 epochs has obtained the greatest accuracy of 99.14%, precision of 100%, sensitivity/recall of 98.41%, specificity of 100%, and an IoU score of 56.44% for the Posteroanterior projection utilizing augmented data. For the Lateral projection using augmented data, the RetinaNet model with an Anisotropic Diffusion filter trained with 50 epochs has produced the highest accuracy of 98.40%, precision of 98.36%, sensitivity/recall of 98.36%, specificity of 98.43%, and an IoU score of 58.69%. When comparing the test results of the different individual projections, models, and image filtering techniques, the Anisotropic Diffusion filter trained with 50 epochs has produced the best classification and regression scores for both projections.

Keywords: Artificial Intelligence, Computer Vision, Wrist Fracture, Deep Learning

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Authors: Pejman Daryabor, Kamal Mohammadi

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In the present work, the study of vibration characteristics of a functionally graded thick hollow cylinder is investigated. The cylinder natural frequencies are obtained using Galerkin finite element method. The functionally graded cylinder is assumed to be made from many subcylinders. Each subcylinder is considered as an isotropic layer. Material’s properties in each layer are constant and functionally graded properties result by exponential function of layer radius in multilayer cylinder. To validate the FE results code, plane strain model of functionally graded cylinder are also modeled in ABAQUS. Analytical results are validated for both models. Also, a good agreement is found between the present results and those reported in the literature.

Keywords: natural frequency, functionally graded material, finite element method, thick cylinder

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Authors: Colm Barcoe, Garvan Whelan

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In tourism, engagement has been found to boost awareness of a destination and subsequently increase visits. Customer engagement in this industry is now facilitated by social media. This phenomenon is not very well researched in relation to Ireland and the North American tourism market. The objective of this paper is to present research findings on two related topics; the first is an investigation into the effectiveness of social media channels as components of a digital marketing campaign when promoting Ireland as a brand in North America. Secondly, this study reveals how Irish marketers have embraced social media platforms and channels with an innovative strategy that has successfully attracted growing numbers of US and Canadian holidaymakers to Ireland. A range of methodological approaches was applied in order to achieve the study’s objective. The methods used were both quantitative and qualitative, and the data was obtained from both Irish marketers and North American holidaymakers. Surveys of these holidaymakers in the pre, during and post-trip phases revealed their attitudes towards social media and Ireland as a destination. Semi-structured interviews with those responsible for implementing relationship marketing strategies for this segment provide insight into the effectiveness of social media when used to capitalise on the cultural link between Ireland and North America. Further analysis involved using Nvivo 11+ software to investigate the activities of the Irish destination marketer (DMO) and the engagement of the US and Canadian audiences through a detailed study of social media platform content. The findings from this investigation will extend an under-researched body of literature pertaining to Ireland as a destination and the successful digital marketing campaigns that have achieved exponential growth in this sector over the past five years. The empirical evidence presented also illustrates how the innovative use of social media has assisted the DMO to engage with the North American holidaymaker as part of an effective digital marketing strategy.

Keywords: channels, digital, engagement, marketing, strategies

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Authors: Parastou Kharazmi

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In this paper, rehabilitation methods for pipeline by advanced polymeric coating such as relining are reviewed. A number of diverse methods which are globally used are described and a brief summary of advances in technology, methods and materials is provided. The paper explains why it is claimed that sewerage rehabilitation with relining in residential buildings is environmentally friendly and economical, the importance of the quality control procedure is discussed and several quality tests are proposed.

Keywords: buildings, composite, material, renovation

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Authors: Jie Liu, Xudong Luo, Pingping Lin, Yifan Fan

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Facebook, Twitter, Weibo, and other social media and significant e-commerce sites generate a massive amount of online texts, which can be used to analyse people’s opinions or sentiments for better decision-making. So, sentiment analysis, especially fine-grained sentiment analysis, is a very active research topic. In this paper, we survey various methods for fine-grained sentiment analysis, including traditional sentiment lexicon-based methods, machine learning-based methods, and deep learning-based methods in aspect/target/attribute-based sentiment analysis tasks. Besides, we discuss their advantages and problems worthy of careful studies in the future.

Keywords: sentiment analysis, fine-grained, machine learning, deep learning

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