Search results for: brine method

Authors: Mahdi Bazarganigilani

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Aortic enlargement, also known as an aortic aneurysm, can occur when the walls of the aorta become weak. This disease can become deadly if overlooked and undiagnosed. In this paper, a computer-aided diagnosis (CAD) system was introduced to accurately diagnose aortic enlargement from chest x-ray images. An enhanced convolutional neural network (CNN) was employed and then trained by transfer learning by using three different main areas from the original images. The areas included the left lung, heart, and right lung. The accuracy of the system was then evaluated on 1001 samples by using 4-fold cross-validation. A promising accuracy of 90% was achieved in terms of the F-measure indicator. The results showed using different areas from the original image in the training phase of CNN could increase the accuracy of predictions. This encouraged the author to evaluate this method on a larger dataset and even on different CAD systems for further enhancement of this methodology.

Keywords: computer-aided diagnosis systems, aortic enlargement, chest X-ray, image processing, convolutional neural networks

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Authors: Abdelrahman Zkria, Tsuyoshi Yoshitake

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Diamond is one of the most interesting semiconducting carbon materials owing to its unique physical and chemical properties, yet its application in electronic devices is limited due to the difficulty of realizing n-type conduction by nitrogen doping. In contrast Ultrananocrystalline diamond with diamond grains of about 3–5 nm in diameter have attracted much attention for device-oriented applications because they may enable the realization of n-type doping with nitrogen. In this study, nitrogen-doped Ultra-Nanocrystalline diamond films were prepared by coaxial arc plasma deposition (CAPD) method, the nitrogen content was estimated by X-ray photoemission spectroscopy (XPS). The electrical conductivity increased with increasing nitrogen contents. Heterojunction diodes with p-type Si were fabricated and evaluated based on current–voltage (I–V) and capacitance–voltage (C–V) characteristics measured in dark at room temperature.

Keywords: heterojunction diodes, hopping conduction mechanism, nitrogen-doping, ultra-nanocrystalline diamond

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Authors: Huie-Wen Lin

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This study integrated various teaching factors -based on the idea of a flipped classroom- in a financial management course. The study’s aim was to establish an effective teaching implementation strategy and evaluation mechanism with respect to learning outcomes, which can serve as a reference for the future modification of teaching methods. This study implemented a teaching method in five stages and estimated the learning efficiencies of 22 students (in the teaching scenario and over two semesters). Subsequently, data envelopment analysis (DEA) was used to compare, for each student, between the learning efficiencies before and after participation in the flipped classroom -in the first and second semesters, respectively- to identify the crucial external factors influencing learning efficiency. According to the results, the average overall student learning efficiency increased from 0.901 in the first semester to 0.967 in the second semester, which demonstrate that the flipped classroom approach can improve teaching effectiveness and learning outcomes. The results also revealed a difference in learning efficiency between male and female students.

Keywords: data envelopment analysis, flipped classroom, learning outcome, teaching and learning

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Authors: Ferzat Anka

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Many types of problems can be solved using traditional analytical methods. However, these methods take a long time and cause inefficient use of resources. In particular, different approaches may be required in solving complex and global engineering problems that we frequently encounter in real life. The bigger and more complex a problem, the harder it is to solve. Such problems are called Nondeterministic Polynomial time (NP-hard) in the literature. The main reasons for recommending different metaheuristic algorithms for various problems are the use of simple concepts, the use of simple mathematical equations and structures, the use of non-derivative mechanisms, the avoidance of local optima, and their fast convergence. They are also flexible, as they can be applied to different problems without very specific modifications. Thanks to these features, it can be easily embedded even in many hardware devices. Accordingly, this approach can also be used in trend application areas such as IoT, big data, and parallel structures. Indeed, the metaheuristic approaches are algorithms that return near-optimal results for solving large-scale optimization problems. This study is focused on the new metaheuristic method that has been merged with the chaotic approach. It is based on the chaos theorem and helps relevant algorithms to improve the diversity of the population and fast convergence. This approach is based on Chimp Optimization Algorithm (ChOA), that is a recently introduced metaheuristic algorithm inspired by nature. This algorithm identified four types of chimpanzee groups: attacker, barrier, chaser, and driver, and proposed a suitable mathematical model for them based on the various intelligence and sexual motivations of chimpanzees. However, this algorithm is not more successful in the convergence rate and escaping of the local optimum trap in solving high-dimensional problems. Although it and some of its variants use some strategies to overcome these problems, it is observed that it is not sufficient. Therefore, in this study, a newly expanded variant is described. In the algorithm called Ex-ChOA, hybrid models are proposed for position updates of search agents, and a dynamic switching mechanism is provided for transition phases. This flexible structure solves the slow convergence problem of ChOA and improves its accuracy in multidimensional problems. Therefore, it tries to achieve success in solving global, complex, and constrained problems. The main contribution of this study is 1) It improves the accuracy and solves the slow convergence problem of the ChOA. 2) It proposes new hybrid movement strategy models for position updates of search agents. 3) It provides success in solving global, complex, and constrained problems. 4) It provides a dynamic switching mechanism between phases. The performance of the Ex-ChOA algorithm is analyzed on a total of 8 benchmark functions, as well as a total of 2 classical and constrained engineering problems. The proposed algorithm is compared with the ChoA, and several well-known variants (Weighted-ChoA, Enhanced-ChoA) are used. In addition, an Improved algorithm from the Grey Wolf Optimizer (I-GWO) method is chosen for comparison since the working model is similar. The obtained results depict that the proposed algorithm performs better or equivalently to the compared algorithms.

Keywords: optimization, metaheuristic, chimp optimization algorithm, engineering constrained problems

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Authors: Tomola Obamuyi

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The banking system in Nigeria adopted innovative banking, with the aim of enhancing financial inclusion, and making financial services readily and cheaply available to majority of the people, and to contribute to the efficiency of the financial system. Some of the innovative services include: Automatic Teller Machines (ATMs), National Electronic Fund Transfer (NEFT), Point of Sale (PoS), internet (Web) banking, Mobile Money payment (MMO), Real-Time Gross Settlement (RTGS), agent banking, among others. The introduction of these payment systems is expected to increase bank efficiency and customers' satisfaction, culminating in better performance for the commercial banks. However, opinions differ on the possible effects of the various innovative payment systems on the performance of commercial banks in the country. Thus, this study empirically determines how commercial banks use innovation to gain competitive advantage in the specific context of Nigeria's finance and business. The study also analyses the effects of financial innovation on the performance of commercial banks, when different periods of analysis are considered. The study employed secondary data from 2009 to 2018, the period that witnessed aggressive innovation in the financial sector of the country. The Vector Autoregression (VAR) estimation technique forecasts the relative variance of each random innovation to the variables in the VAR, examine the effect of standard deviation shock to one of the innovations on current and future values of the impulse response and determine the causal relationship between the variables (VAR granger causality test). The study also employed the Multi-Criteria Decision Making (MCDM) to rank the innovations and the performance criteria of Return on Assets (ROA) and Return on Equity (ROE). The entropy method of MCDM was used to determine which of the performance criteria better reflect the contributions of the various innovations in the banking sector. On the other hand, the Range of Values (ROV) method was used to rank the contributions of the seven innovations to performance. The analysis was done based on medium term (five years) and long run (ten years) of innovations in the sector. The impulse response function derived from the VAR system indicated that the response of ROA to the values of cheques transaction, values of NEFT transactions, values of POS transactions was positive and significant in the periods of analysis. The paper also confirmed with entropy and range of value that, in the long run, both the CHEQUE and MMO performed best while NEFT was next in performance. The paper concluded that commercial banks would enhance their performance by continuously improving on the services provided through Cheques, National Electronic Fund Transfer and Point of Sale since these instruments have long run effects on their performance. This will increase the confidence of the populace and encourage more usage/patronage of these services. The banking sector will in turn experience better performance which will improve the economy of the country. Keywords: Bank performance, financial innovation, multi-criteria decision making, vector autoregression,

Keywords: Bank performance, financial innovation, multi-criteria decision making, vector autoregression

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Authors: Marijana Pantić, Saša Milijić

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In Serbia as a continental country, the tourism industry relies on city-break, spa and mountain tourism, where ski resorts have primacy during the winter season. Even though the number of tourists has recently increased, the share of domestic tourists remained predominant. It is also noticed that tourists from Serbia eagerly travel abroad, which was so far researched in the context of summer holidays but not in the framework of ski resorts. Therefore, this paper examines the competitiveness of ski resorts in Serbia from the perspective of domestic tourists. A survey was used as a data collection method, covering various competitiveness dimensions. The aim is to recognize the main motives of consumers when choosing a ski resort in Serbia or abroad. The results showed that the choices of Serbian tourists are predominantly shaped by the cost of an offer – of accommodation above all others. They are attentive by estimating the value for money, which is the most common reason to choose a ski resort abroad over a domestic one. The crowd at ski resorts and ski runs appears to be a result of unbalanced accommodation capacities on the one hand and ski infrastructure on the other, which is currently the most notable competitiveness drawback of ski resorts in Serbia.

Keywords: mountain tourism, Serbia, ski resorts, tourism competitiveness

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Authors: Salami Akeem Olanrewaju

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The transportation models or problems are primarily concerned with the optimal (best possible) way in which a product produced at different factories or plants (called supply origins) can be transported to a number of warehouses or customers (called demand destinations). The objective in a transportation problem is to fully satisfy the destination requirements within the operating production capacity constraints at the minimum possible cost. The objective of this study is to determine ways of minimizing transport cost in order to maximum profit. Data were gathered from the records of the Distribution Department of 7-Up Bottling Company Plc. Ilorin, Kwara State, Nigeria. The data were analyzed using SPSS (Statistical Package for Social Sciences) while applying the three methods of solving a transportation problem. The three methods produced the same results; therefore, any of the method can be adopted by the company in transporting its final products to the wholesale dealers in order to minimize total production cost.

Keywords: cost minimization, resources utilization, distribution system, allocation problem

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Authors: Fanqiang Kong, Chending Bian

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In this work, we exploit two assumed properties of the abundances of the observed signatures (endmembers) in order to reconstruct the abundances from hyperspectral data. Joint-sparsity is the first property of the abundances, which assumes the adjacent pixels can be expressed as different linear combinations of same materials. The second property is rank-deficiency where the number of endmembers participating in hyperspectral data is very small compared with the dimensionality of spectral library, which means that the abundances matrix of the endmembers is a low-rank matrix. These assumptions lead to an optimization problem for the sparse unmixing model that requires minimizing a combined l_2,p-norm and nuclear norm. We propose a variable splitting and augmented Lagrangian algorithm to solve the optimization problem. Experimental evaluation carried out on synthetic and real hyperspectral data shows that the proposed method outperforms the state-of-the-art algorithms with a better spectral unmixing accuracy.

Keywords: hyperspectral unmixing, joint-sparse, low-rank representation, abundance estimation

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Authors: Mohamed M. El Gendy, Ibrahim A. El Arabi, Rafeek W. Abdel-Missih, Omar A. Kandil

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Nonlinear analysis is one of the most important design and safety tools in structural engineering. Based on the finite-element method, a geometrical and material nonlinear analysis of large span reinforced concrete arches is carried out considering soil-structure interaction. The concrete section details and reinforcement distribution are taken into account. The behavior of soil is considered via Winkler's and continuum models. A computer program (NARC II) is specially developed in order to follow the structural behavior of large span reinforced concrete arches up to failure. The results obtained by the proposed model are compared with available literature for verification. This work confirmed that the geometrical and material nonlinearities, as well as soil structure interaction, have considerable influence on the structural response of reinforced concrete arches.

Keywords: nonlinear analysis, reinforced concrete arched structure, soil-structure interaction, geotechnical engineering

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Authors: B. Falah, N. E. Abakouy

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Due to its high computational cost, mutation testing has been neglected by researchers. Recently, many cost and mutants’ reduction techniques have been developed, improved, and experimented, but few of them has relied the possibility of reducing the cost of mutation testing on the program type of the application under test. This paper is a comparative study between four operators’ selection techniques (mutants sampling, class level operators, method level operators, and all operators’ selection) based on the program code type of each application under test. It aims at finding an alternative approach to reveal the effect of code type on mutation testing score. The result of our experiment shows that the program code type can affect the mutation score and that the programs using polymorphism are best suited to be tested with mutation testing.

Keywords: equivalent mutant, killed mutant, mutation score, mutation testing, program code type, software testing

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Authors: Arezou Javadi

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The use of algorithmic models dependent on software calculations and simulation of new government management assays with the help of specialized software had increased the productivity and efficiency of the government management system recently. This has caused the management approach to change from the old bitch & fix model, which has low efficiency and less usefulness, to the capable management model with higher efficiency called the partnership with resident model. By using Govpilot TM software, the relationship between people in a system and the government was examined. The method of two tailed interaction was the outsourcing of a goal in a system, which is formed in the order of goals, qualified executive people, optimal executive model, and finally, summarizing additional activities at the different statistical levels. The results showed that the participation of people in a financial implementation system with a statistical potential of P≥5% caused a significant increase in investment and initial capital in the government system with maximum implement project in a smart government.

Keywords: machine learning, financial income, statistical potential, govpilot

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Authors: Arezou Javadi

Abstract:

The use of algorithmic models dependent on software calculations and simulation of new government management assays with the help of specialized software had increased the productivity and efficiency of the government management system recently. This has caused the management approach to change from the old bitch & fix model, which has low efficiency and less usefulness, to the capable management model with higher efficiency called the partnership with resident model. By using Govpilot TM software, the relationship between people in a system and the government was examined. The method of two tailed interaction was the outsourcing of a goal in a system, which is formed in the order of goals, qualified executive people, optimal executive model, and finally, summarizing additional activities at the different statistical levels. The results showed that the participation of people in a financial implementation system with a statistical potential of P≥5% caused a significant increase in investment and initial capital in the government system with maximum implement project in a smart government.

Keywords: machine learning, financial income, statistical potential, govpilot

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Authors: Amanda Cristina de Oliveira, Elias de Souza Monteiro Filho, Roberta Ceriani

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Liquid-liquid extraction in aqueous two-phase systems (ATPSs) constitutes a powerful tool for purifying bio-materials, such as cells, organelles, proteins, among others. In this work, the extraction of the bovine serum albumin (BSA) has been studied in systems formed by polyethylene glycol (PEG) (1500, 4000, and 6000 g.mol⁻¹) + potassium sodium tartrate + water at 303.15°K. Phase diagrams were obtained by turbidimetry and Merchuk’s method (1998). The experimental tie-lines were described using the Othmer-Tobias and Bancroft correlations. ATPSs were correlated with the nonrandom two-liquid (NRTL) model. The results were considered excellent according to global root-mean-square deviations found which were between 0,72 and 1,13%. The concentrations of the proteins in each phase were determined by spectrophotometry at 280 nm, finding partition efficiencies greater than 71%.

Keywords: aqueous two phases systems, bovine serum albumin , liquid-liquid extraction, polyethylene glycol

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Authors: Changqiao Wu, Guoqing Ding, Xin Chen

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In this paper, ways of modeling dynamic measurement systems are discussed. Specially, for linear system with single-input single-output, it could be modeled with shallow neural network. Then, gradient based optimization algorithms are used for searching the proper coefficients. Besides, method with normal equation and second order gradient descent are proposed to accelerate the modeling process, and ways of better gradient estimation are discussed. It shows that the mathematical essence of the learning objective is maximum likelihood with noises under Gaussian distribution. For conventional gradient descent, the mini-batch learning and gradient with momentum contribute to faster convergence and enhance model ability. Lastly, experimental results proved the effectiveness of second order gradient descent algorithm, and indicated that optimization with normal equation was the most suitable for linear dynamic models.

Keywords: dynamic system modeling, neural network, normal equation, second order gradient descent

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Authors: Khelfaoui Rachid, Chekifi Tawfiq, Dennai Brahim, Maazouzi A. Hak

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A numerical and experimental studies of passive micro drops production have been presented. This paper focuses on the modeling of micro-oscillators systems which are composed by passive amplifier without moving part. The micro-system modeling is based on geometrical oscillators form. An asymmetric micro-oscillator design that is based on a bistable fluidic amplifier is proposed. The characteristic size of the channels is generally about 35 microns of depth. The numerical results indicate that the production and manipulation of microdrops are possible with passive device within a typical oscillators chamber of 2.25 mm diameter and 0.20 mm length when the Reynolds number is Re = 490. The novel micro drops method that is presented in this study provides a simple solution about the production of microdrops problems in micro system. We undertake an experimental step. The first part is based on the realisation of sample oscillator; the second part is consisted of visualization, production and manipulation of microdrops.

Keywords: modelling, miscible, micro drops, production, oscillator sample, capillary

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Authors: Justyna P. Majewska, Szymon M. Truskolaski

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The growing importance of digitalized services in the so-called new economy, including the e-sports industry, can be observed recently. Various demographic or technological changes lead consumers to modify their needs, not regarding the services themselves but the method of their application (attracting customers, forms of payment, new content, etc.). In the case of leisure-related to competitive spectating activities, there is a growing need to participate in events whose content is not sports competitions but computer games challenge – e-sport. The literature in this area so far focuses on determining the number of e-sport fans with elements of a simple statistical description (mainly concerning demographic characteristics such as age, gender, place of residence). Meanwhile, the development of the industry is influenced by a combination of many different, intertwined demographic, personality and psychosocial characteristics of customers, as well as the characteristics of their environment. Therefore, there is a need for a deeper recognition of the determinants of the behavioral patterns upon selecting digitalized services by customers, which, in the absence of available large data sets, can be achieved by using econometric simulations – multi-agent modeling. The cognitive aim of the study is to reveal internal and external determinants of behavioral patterns of customers taking into account various variants of economic development (the pace of digitization and technological development, socio-demographic changes, etc.). In the paper, an agent-based model with heterogeneous agents (characteristics of customers themselves and their environment) was developed, which allowed identifying a three-stage development scenario: i) initial interest, ii) standardization, and iii) full professionalization. The probabilities regarding the transition process were estimated using the Method of Simulated Moments. The estimation of the agent-based model parameters and sensitivity analysis reveals crucial factors that have driven a rising trend in e-sport spectating and, in a wider perspective, the development of digitalized services. Among the psychosocial characteristics of customers, they are the level of familiarization with the rules of games as well as sports disciplines, active and passive participation history and individual perception of challenging activities. Environmental factors include general reception of games, number and level of recognition of community builders and the level of technological development of streaming as well as community building platforms. However, the crucial factor underlying the good predictive power of the model is the level of professionalization. While in the initial interest phase, the entry barriers for new customers are high. They decrease during the phase of standardization and increase again in the phase of full professionalization when new customers perceive participation history inaccessible. In this case, they are prone to switch to new methods of service application – in the case of e-sport vs. sports to new content and more modern methods of its delivery. In a wider context, the findings in the paper support the idea of a life cycle of services regarding methods of their application from “traditional” to digitalized.

Keywords: agent-based modeling, digitalized services, e-sport, spectators motives

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Authors: Ufuk Aydın

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The Coda attenuation and frequency dependency of seismic wave are strongly dependent on the effective stresses structures within the upper crust. In this study, the data of three different stations were used to examine the lateral variation of stress. The tectonic structures of these three areas have been examined comparatively using lateral coda tomography. In the study using the single scatter method, the window length selected to be 20 second. Coda values 80 with 94 and frequency dependency values obtained between 0.69 and 1.21. The 1/QC values for the three regions ranged from 0.0012 to 0.017, highlighting the regional differences in the seismotectonic activity of the crust. The lowest absorption values obtained from Erzurum station when the highest absorption values obtained at the Kemaliye station. The low Qc and high frequency dependency values obtained Kemaliye, which indicates that it has highest tectonic activity than other two regions. The seismo-dynamics data obtained from the study found to be in agreement with the tectonic structure of the region.

Keywords: regional coda attenuation, tectonic stress, crustal deformation

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Authors: Haydar Teymourlouei

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It is important to take security measures to protect your computer information, reduce identify theft, and prevent from malicious cyber-attacks. With cyber-attacks on the continuous rise, people need to understand and learn ways to prevent from these attacks. Cyber-attack is an important factor to be considered if one is to be able to protect oneself from malicious attacks. Without proper security measures, most computer technology would hinder home users more than such technologies would help. Knowledge of how cyber-attacks operate and protective steps that can be taken to reduce chances of its occurrence are key to increasing these security measures. The purpose of this paper is to inform home users on the importance of identifying and taking preventive steps to avoid cyberattacks. Throughout this paper, many aspects of cyber-attacks will be discuss: what a cyber-attack is, the affects of cyber-attack for home users, different types of cyber-attacks, methodology to prevent such attacks; home users can take to fortify security of their computer.

Keywords: cyber-attacks, home user, prevention, security, technology

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Authors: Chia-Feng Lu, Yuh-Jen Wang, Yu-Te Wu, Sui-Hing Yan

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This study aimed at investigating whether the functional brain networks constructed using the initial EEG (obtained when patients first visited hospital) can be correlated with the progression of cognitive decline calculated as the changes of mini-mental state examination (MMSE) scores between the latest and initial examinations. We integrated the time–frequency cross mutual information (TFCMI) method to estimate the EEG functional connectivity between cortical regions, and the network analysis based on graph theory to investigate the organization of functional networks in aMCI. Our finding suggested that higher integrated functional network with sufficient connection strengths, dense connection between local regions, and high network efficiency in processing information at the initial stage may result in a better prognosis of the subsequent cognitive functions for aMCI. In conclusion, the functional connectivity can be a useful biomarker to assist in prediction of cognitive declines in aMCI.

Keywords: cognitive decline, functional connectivity, MCI, MMSE

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Authors: Samiah Alammari, Nassim Ammour

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When providing a massive number of tasks successively to a deep learning process, a good performance of the model requires preserving the previous tasks data to retrain the model for each upcoming classification. Otherwise, the model performs poorly due to the catastrophic forgetting phenomenon. To overcome this shortcoming, we developed a successful continual learning deep model for remote sensing hyperspectral image regions classification. The proposed neural network architecture encapsulates two trainable subnetworks. The first module adapts its weights by minimizing the discrimination error between the land-cover classes during the new task learning, and the second module tries to learn how to replicate the data of the previous tasks by discovering the latent data structure of the new task dataset. We conduct experiments on HSI dataset Indian Pines. The results confirm the capability of the proposed method.

Keywords: continual learning, data reconstruction, remote sensing, hyperspectral image segmentation

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Authors: Kamel Al-Khaled

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A comparative study of the Sinc-Galerkin and Sinc-Collocation methods for solving the Kuramoto-Sivashinsky equation is given. Both approaches depend on using Sinc basis functions. Firstly, a numerical scheme using Sinc-Galerkin method is developed to approximate the solution of Kuramoto-Sivashinsky equation. Sinc approximations to both derivatives and indefinite integrals reduces the solution to an explicit system of algebraic equations. The error in the solution is shown to converge to the exact solution at an exponential. The convergence proof of the solution for the discrete system is given using fixed-point iteration. Secondly, a combination of a Crank-Nicolson formula in the time direction, with the Sinc-collocation in the space direction is presented, where the derivatives in the space variable are replaced by the necessary matrices to produce a system of algebraic equations. The methods are tested on two examples. The demonstrated results show that both of the presented methods more or less have the same accuracy.

Keywords: Sinc-Collocation, nonlinear PDEs, numerical methods, fixed-point

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Authors: Albert Mufundirwa, Satoru Yoshioka, K. Ogi, Takeharu Sugiyama, George F. Harrington, Bretislav Smid, Benjamin Cunning, Kazunari Sasaki, Akari Hayashi, Stephen M. Lyth

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Polymer electrolyte membrane fuel cells (PEMFCs) are electrochemical energy conversion devices used for portable, residential and vehicular applications due to their low emissions, high efficiency, and quick start-up characteristics. However, PEMFCs generally use expensive, Pt-based electrocatalysts as electrode catalysts. Due to the high cost and limited availability of platinum, research and development to either drastically reduce platinum loading, or replace platinum with alternative catalysts is of paramount importance. A combination of high surface area supports and nano-structured active sites is essential for effective operation of catalysts. We synthesize carbon foam supports by thermal decomposition of sodium ethoxide, using a template-free, gram scale, cheap, and scalable pyrolysis method. This carbon foam has a high surface area, highly porous, three-dimensional framework which is ideal for electrochemical applications. These carbon foams can have surface area larger than 2500 m²/g, and electron microscopy reveals that they have micron-scale cells, separated by few-layer graphene-like carbon walls. We applied this carbon foam as a platinum catalyst support, resulting in the improved electrochemical surface area and mass activity for the oxygen reduction reaction (ORR), compared to carbon black. Similarly, silver-decorated carbon foams showed higher activity and efficiency for electrochemical carbon dioxide conversion than silver-decorated carbon black. A promising alternative to Pt-catalysts for the ORR is iron-impregnated nitrogen-doped carbon catalysts (Fe-N-C). Doping carbon with nitrogen alters the chemical structure and modulates the electronic properties, allowing a degree of control over the catalytic properties. We have adapted our synthesis method to produce nitrogen-doped carbon foams with large surface area, using triethanolamine as a nitrogen feedstock, in a novel bottom-up protocol. These foams are then infiltrated with iron acetate (FeAc) and pyrolysed to form Fe-N-C foams. The resulting Fe-N-C foam catalysts have high initial activity (half-wave potential of 0.68 VRHE), comparable to that of commercially available Pt-free catalysts (e.g., NPC-2000, Pajarito Powder) in acid solution. In alkaline solution, the Fe-N-C carbon foam catalysts have a half-wave potential of 0.89 VRHE, which is higher than that of NPC-2000 by almost 10 mVRHE, and far out-performing platinum. However, the durability is still a problem at present. The lessons learned from X-ray absorption spectroscopy (XAS), transmission electron microscopy (TEM), X-ray photoelectron spectroscopy (XPS), and electrochemical measurements will be used to carefully design Fe-N-C catalysts for higher performance PEMFCs.

Keywords: carbon-foam, polymer electrolyte membrane fuel cells, platinum, Pt-free, Fe-N-C, ORR

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Authors: M. Brahim, I. Bahri, Y. Bernard

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Traveling Wave Ultrasonic Motor (TWUM) is a compact, precise, and silent actuator generating high torque at low speed without gears. Moreover, the TWUM has a high holding torque without supply, which makes this motor as an attractive solution for holding position of robotic arms. However, their nonlinear dynamics, and the presence of load-dependent dead zones often limit their use. Those issues can be overcome in closed loop with effective and precise controllers. In this paper, robust H-infinity (H∞) and discrete time RST position controllers are presented. The H∞ controller is designed in continuous time with additional weighting filters to ensure the robustness in the case of uncertain motor model and external disturbances. Robust RST controller based on the pole placement method is also designed and compared to the H∞. Simulink model of TWUM is used to validate the stability and the robustness of the two proposed controllers.

Keywords: piezoelectric motors, position control, H∞, RST, stability criteria, robustness

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Authors: Muneerah Jeludin, V. Sivakumar

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Numerous laboratory-based research studies on the behavior of ground improved with granular columns with respect to bearing capacity have been well-documented. However, information on its settlement performance is still scarce. Laboratory model study on the settlement behavior of soft clay reinforced with granular columns was conducted and results are presented. The investigation uses a soft kaolin clay sample of 300 mm in diameter and 400 mm in length. The clay samples were reinforced with single and multiple granular columns of various lengths using the displacement and replacement installation method. The results indicated that that no settlement reduction was achieved for a short single floating column. The settlement reduction factors reported for L/d ratios of 5.0, 7.5 and 10.0 are in the range of 1 to 2. The findings obtained in this research showed that the reduction factors are considerably less and that load-sharing mechanism between columns and surrounding clay is complex, particularly for column groups and is affected by other factors such as negative skin friction.

Keywords: ground improvement, model test, reinforced soil, settlement

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Authors: Sergio Pérez-López, Daniel Tarrazó-Serrano, José M. Fuster, Pilar Candelas, Constanza Rubio

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Fresnel Zone Plates (FZPs) are widely used in many areas, such as optics, microwaves or acoustics. On the design of FZPs, plane wave incidence is typically considered, but that is not usually the case in ultrasounds, especially in applications where a piston emitter is placed at a certain distance from the lens. In these cases, having control of the focal distance is very important, and with the usual Fresnel equation a focal displacement from the theoretical distance is observed due to the plane wave supposition. In this work, a comparison between FZP with plane wave incidence design and FZP with point source design in the case of piston emitter is presented. Influence of the main parameters of the piston in the final focalization profile has been studied. Numerical models and experimental results are shown, and they prove that when spherical wave incidence is considered for the piston case, it is possible to have a fine control of the focal distance in comparison with the classical design method.

Keywords: focusing, Fresnel zone plates, FZP, ultrasound

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Authors: Aritras Roy, Rinku Mukherjee

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The current study couples a quasi-steady Vortex Lattice Method and a camber correcting technique, ‘Decambering’ for unsteady post-stall flow prediction. The wake is force-free and discrete such that the wake lattices move with the free-stream once shed from the wing. It is observed that the time-averaged unsteady coefficient of lift sees a relative drop at post-stall angles of attack in comparison to its steady counterpart for some angles of attack. Multiple solutions occur at post-stall and three different algorithms to choose solutions in these regimes show both unsteadiness and non-convergence of the iterations. The distribution of coefficient of lift on the wing span also shows sawtooth. Distribution of vorticity changes both along span and in the direction of the free-stream as the wake develops over time with distinct roll-up, which increases with time.

Keywords: post-stall, unsteady, wing, aerodynamics

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Authors: Amir Masoud Dabagh, Mahsa Khaleghi

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The world has entered a new phase of cultural, social, economic, and so on in the last two centuries. Apart from its positive benefits and achievements to the world, it has also incurred many costs, most of which can be mentioned as destroying or at least diminishing the role of the costumes, traditions and authentic culture of the past communities. Understanding what lasts in traditional arts is vital and worthy of study because receiving it and embracing art and forms of art using that last the artistic creation removes the age-old color and smell of its face, making it immortal and persistent in all ages. This paper attempts to present traditional art concepts and solutions for interior design with the approach of handicrafts recreation as a symbol and manifestation of national identity and proof of ancient civilizations, which is at the center of tourists' attention today. The research method is a descriptive-analytical one that first explores the theoretical foundations of research, which are the concepts of recreation and traditional arts, and analyzes the process of recreation that conceals the recollection of past experiences as well as the dynamics and creativity.

Keywords: recreation, handicrafts, interior design, concept, traditional arts

Procedia PDF Downloads 111

Authors: C. D. Papanikolaou, V. A. Giouvanis, E. A. Karatasiou, D. S. Dimakas, M. A. Sakellariou-Makrantonaki

Abstract:

Irrigation is one of the most important cultivation practices for each crop, especially in areas where rainfall is enough to cover the crop water needs. In such areas, the farmers must irrigate in order to achieve high economical results. The precise irrigation scheduling contributes to irrigation water saving and thus a valuable natural resource is protected. Under this point of view, in the experimental field of the Laboratory of Agricultural Hydraulics of the University of Thessaly, a research was conducted during the growing season of 2012 in order to evaluate the growth, seed and oil production of sunflower as well as the water saving, by applying different methods of irrigation scheduling. Three treatments in four replications were organized. These were: a) surface drip irrigation where the irrigation scheduling based on the Penman-Monteith (PM) method (control); b) surface drip irrigation where the irrigation scheduling based on a soil moisture sensor (SMS); and c) surface drip irrigation, where the irrigation scheduling based on a soil potential sensor (WM).

Keywords: irrigation, energy production, soil moisture sensor, sunflower, water saving

Procedia PDF Downloads 180

Authors: Alberto Alcalá-Alvarez, Pablo Padilla-Longoria

Abstract:

The present paper describes a framework for constructing mathematical networks encoding relevant musical information from a music score for structural analysis. These graphs englobe statistical information about music elements such as notes, chords, rhythms, intervals, etc., and the relations among them, and so become helpful in visualizing and understanding important stylistic features of a music fragment. In order to build such networks, musical data is parsed out of a digital symbolic music file. This data undergoes different analytical procedures from Graph Theory, such as measuring the centrality of nodes, community detection, and entropy calculation. The resulting networks reflect important structural characteristics of the fragment in question: predominant elements, connectivity between them, and complexity of the information contained in it. Music pieces in different styles are analyzed, and the results are contrasted with the traditional analysis outcome in order to show the consistency and potential utility of this method for music analysis.

Keywords: computational musicology, mathematical music modelling, music analysis, style classification

Procedia PDF Downloads 102

Authors: Ashley Wei-Ting Wang, Wen-Yau Hsu

Abstract:

Objectives: The current study applies and expands the Tripartite Model to elaborate the link between non-suicidal self-injury (NSSI) and suicidal behavior. We propose a structural model of NSSI and suicidal risk, in which negative affect (NA) predicts both anxiety and depression, positive affect (PA) predicts depression only, anxiety is linked to NSSI, and depression is linked to suicidal risk. Method: Four hundreds and eighty seven undergraduates participated. Data were collected by administering self-report questionnaires. We performed hierarchical regression and structural equation modeling to test the proposed structural model. Results: The results largely support the proposed structural model, with one exception: anxiety was strongly associated with NSSI and to a lesser extent with suicidal risk. Conclusions: We conclude that the co-occurrence of NSSI and suicidal risk is due to NA and anxiety, and suicidal risk can be differentiated by depression. Further theoretical and practical implications are discussed.

Keywords: non-suicidal self-injury, suicidal risk, anxiety, depression, the tripartite model, hierarchical relationship

Procedia PDF Downloads 470