Search results for: gradient training method

Authors: Adeel Zulifqar, Hong Hu

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Auxetic fabrics are a special kind of textile materials which possess negative Poisson’s ratio. Opposite to most of the conventional fabrics, auxetic fabrics get bigger in the transversal direction when stretched or get smaller when compressed. Auxetic fabrics are superior to conventional fabrics because of their counterintuitive properties, such as enhanced porosity under the extension, excellent formability to a curved surface and high energy absorption ability. Up till today, auxetic fabrics have been produced based on two approaches. The first approach involves using auxetic fibre or yarn and weaving technology to fabricate auxetic fabrics. The other method to fabricate the auxetic fabrics is by using non-auxetic yarns. This method has gained extraordinary curiosity of researcher in recent years. This method is based on realizing auxetic geometries into the fabric structure. In the woven fabric structure auxetic geometries can be realized by creating a differential shrinkage phenomenon into the fabric structural unit cell. This phenomenon can be created by using loose and tight weave combinations within the unit cell of interlacement pattern along with elastic and non-elastic yarns. Upon relaxation, the unit cell of interlacement pattern acquires a non-uniform shrinkage profile due to different shrinkage properties of loose and tight weaves in designed pattern, and the auxetic geometry is realized. The development of uni-stretch auxetic woven fabrics and bi-stretch auxetic woven fabrics by using this method has already been reported. This study reports the development of another kind of bi-stretch auxetic woven fabric. The fabric is first designed by transforming the auxetic geometry into interlacement pattern and then fabricated, using the available conventional weaving technology and non-auxetic elastic and non-elastic yarns. The tensile tests confirmed that the developed bi-stretch auxetic woven fabrics exhibit negative Poisson’s ratio over a wide range of tensile strain. Therefore, it can be concluded that the auxetic geometry can be realized into the woven fabric structure by creating the phenomenon of differential shrinkage and bi-stretch woven fabrics made of non-auxetic yarns having auxetic behavior and stretchability are possible can be obtained. Acknowledgement: This work was supported by the Research Grants Council of Hong Kong Special Administrative Region Government (grant number 15205514).

Keywords: auxetic, differential shrinkage, negative Poisson's ratio, weaving, stretchable

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Authors: Aisha Noour, Nick Hubbard

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Learner motivation is considered an important premise for the Blended e-Learning (BL) method. BL is an effective learning method in multiple domains, which opens several opportunities for its participants to engage in the learning environment. This research explores the learners’ perspective of BL according to the Self-Determination Theory (SDT). It identifies the opportunities and challenges for using the BL in Logistics Education (LE) in Egyptian Higher Education (HE). SDT is approached from different perspectives within the relationship between Intrinsic Motivation (IM), Extrinsic Motivation (EM) and Amotivation (AM). A self-administered face-to-face questionnaire was used to collect data from learners who were geographically widely spread around three colleges of International Transport and Logistics (CILTs) at the Arab Academy for Science, Technology and Maritime Transport (AAST&MT) in Egypt. Six hundred and sixteen undergraduates responded to a questionnaire survey. Respondents were drawn from three branches in Greater Cairo, Alexandria, and Port Said. The data analysis used was SPSS 22 and AMOS 18.

Keywords: intrinsic motivation, extrinsic motivation, amotivation, blended e-learning, Self Determination Theory

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Authors: Sivia Amado Cordeiro, Bruna Rodrigues, Maria Do Ceu Taveira, Catia Marques, Iris Oliveira, Ana Daniela Silva, Cristina Costa-Lobo

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This work intends to analyse the teaching of Psychology in Portugal and, particularly, the teaching of Career Psychology, reflecting about the changes that have occurred to date. Were analysed the educational offerings of 31 Portuguese higher education institutions, 12 public and 19 private, who teach the course of Psychology. The three degrees of study were considered, namely, bachelors, masters and doctoral. The analysis of the data focused on the curricular plans of the different degrees of studies in Psychology made available online by higher education institutions. Through them, we identified the curricular units with themes related to the teaching of Career Psychology. The results show the existence of 89 higher psychology courses in Portugal, distributed throughout the three degrees of studies. Concerning to the teaching of Career Psychology there were registered 49 curricular units with themes dedicated to this area of knowledge. There were identified 16 curricular units in the bachelor’s degree, 31 in master’s degree, and two in doctoral degree. It was observed a reduction in the number of degrees in Psychology in the last nine years in Portugal. We discuss the current situation of Psychology teaching, particularly the teaching of Career Psychology. The aim is to stimulate reflection about future perspectives of Psychology teaching, and specifically, specialized training in Psychology of Career, in Portugal.

Keywords: career psychology, higher education, psychology, Portugal

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Authors: Mahtab Baghaei, Seyed Mahmoud Tabatabaei

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Aim & Background: Electrical stimulation of transcranial direct current is considered one of the treatment methods for mental disorders. The aim of this study was to evaluate the effectiveness of transcranial electrical stimulation on the delta, theta, alpha, beta and systolic and diastolic blood pressure in patients with generalized anxiety disorder. Materials and Methods: The present study was a double-blind intervention with a pre-test and post-test design on people with generalized anxiety disorder in Tabriz in 1400. In this study, 30 patients with generalized anxiety disorder were selected by purposive sampling method based on the criteria specified in DSM-5 and randomly divided into an experimental group (n = 15) and a control group (n = 15). The experimental group received two sessions of 30 minutes of electrical stimulation of transcranial direct current with an intensity of 2 mA in the area of the lateral dorsal prefrontal cortex, and the control group also received artificial stimulation. Results: The results showed that transcranial electrical stimulation reduces delta and theta waves and increases beta and alpha brain waves in the experimental group. On the other hand, this method also showed a significant decrease in systolic and diastolic blood pressure in these patients (p <0.01). Conclusion: The results show that transcranial electrical stimulation has a statistically significant effect on brain waves and blood pressure, and this non-invasive method can be used as one of the treatment methods in people with generalized anxiety disorder.

Keywords: transcranial direct current electrical stimulation, brain waves, systolic blood pressure, diastolic blood pressure

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Authors: Davies Obaromi, Qin Yongsong, James Ndege

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To interpolate scattered or regularly distributed data, there are imprecise or exact methods. However, there are some of these methods that could be used for interpolating data in a regular grid and others in an irregular grid. In spatial epidemiology, it is important to examine how a disease prevalence rates are distributed in space, and how they relate with each other within a defined distance and direction. In this study, for the geographic and graphic representation of the disease prevalence, linear and biharmonic spline methods were implemented in MATLAB, and used to identify, localize and compare for smoothing in the distribution patterns of tuberculosis (TB) in Eastern Cape Province. The aim of this study is to produce a more “smooth” graphical disease map for TB prevalence patterns by a 3-D curve fitting techniques, especially the biharmonic splines that can suppress noise easily, by seeking a least-squares fit rather than exact interpolation. The datasets are represented generally as a 3D or XYZ triplets, where X and Y are the spatial coordinates and Z is the variable of interest and in this case, TB counts in the province. This smoothing spline is a method of fitting a smooth curve to a set of noisy observations using a spline function, and it has also become the conventional method for its high precision, simplicity and flexibility. Surface and contour plots are produced for the TB prevalence at the provincial level for 2012 – 2015. From the results, the general outlook of all the fittings showed a systematic pattern in the distribution of TB cases in the province and this is consistent with some spatial statistical analyses carried out in the province. This new method is rarely used in disease mapping applications, but it has a superior advantage to be assessed at subjective locations rather than only on a rectangular grid as seen in most traditional GIS methods of geospatial analyses.

Keywords: linear, biharmonic splines, tuberculosis, South Africa

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Authors: Monette S. De Castro, Veneranda A. Magpantay, Christine B. Adiova, Mark D. Arboleda

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One-hundred-layer chicken farmers were randomly selected and interviewed using structured questionnaires to assess the production system and management practices in layer chicken farms. The respondents belonged to the commercial scale operation. Results showed that the predominant rearing and housing systems were intensive/complete confinement and open-sided, while slatted was the common type of flooring used during the brood-grow period. Dekalb and Lohmann were the common chicken layer strains reared by farmers. The majority of commercial chicken layer farms preferred ready-to-lay (RTL) pullets as their replacement stocks. Selling was the easiest way for farmers to dispose of and utilize poultry manure, while veterinary waste and mortality were disposed of in pits. Biosecurity practices employed by the farmers conformed with the ASEAN Biosecurity Management Manual for Commercial Poultry Farming. Flies and odor were the major problems in most layer farms that are associated with their farm wastes. Therefore, the application of new technologies and husbandry practices through training and actual demonstrations could be implemented to further improve the layer chicken raising in the province.

Keywords: layer chicken farms, marketing, production system, waste management

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Authors: Maruf Farhan, Abdul Salih, Sikandar Ali Tahir

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Protecting patient information's confidentiality is paramount considering the widespread use of Internet of Things (IoT) gadgets in medical settings. This study's subjects are decentralized identifiers (DIDs) and verifiable credentials (VCs) in conjunction with an OAuth-based authorization framework, as they are the key to protecting IoT healthcare devices. DIDs enable autonomous authentication and trust formation between IoT devices and other entities. To authorize users and enforce access controls based on verified claims, VCs offer a secure and adaptable solution. Through the proposed method, medical facilities can improve the privacy and security of their IoT devices while streamlining access control administration. A Smart pill dispenser in a hospital setting is used to illustrate the advantages of this method. The findings demonstrate the value of DIDs, VCs, and OAuth-based delegation in protecting the IoT devices. Improved processes for authorizing and controlling access to IoT devices are possible thanks to the research findings, which also help ensure patient confidentiality in the healthcare sector.

Keywords: Iot, DID, authorization, verifiable credentials

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Authors: F. U. Rahman, R. Q. Zhang

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This work aims to develop a systematic numerical technique which can be easily extended to many-body problem. The Lippmann Schwinger equation (integral form of the Schrodinger wave equation) is solved for the nonrelativistic radial wave of hydrogen atom using iterative integration scheme. As the unknown wave function appears on both sides of the Lippmann Schwinger equation, therefore an approximate wave function is used in order to solve the equation. The Green’s function is obtained by the method of Laplace transform for the radial wave equation with excluded potential term. Using the Lippmann Schwinger equation, the product of approximate wave function, the Green’s function and the potential term is integrated iteratively. Finally, the wave function is normalized and plotted against the standard radial wave for comparison. The outcome wave function converges to the standard wave function with the increasing number of iteration. Results are verified for the first fifteen states of hydrogen atom. The method is efficient and consistent and can be applied to complex systems in future.

Keywords: Green’s function, hydrogen atom, Lippmann Schwinger equation, radial wave

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Authors: Toby Gibbs, Suwaree Yordchim

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This research analyzes factors affecting the success of Litecoin Value within Thailand and develops a guideline for self-reliance for effective business implementation. Samples in this study included 119 people through surveys. The results revealed four main factors affecting the success as follows: 1) Future Career training should be pursued in applied Litecoin development. 2) Didn't grasp the concept of a digital currency or see the benefit of a digital currency. 3) There is a great need to educate the next generation of learners on the benefits of Litecoin within the community. 4) A great majority didn't know what Litecoin was. The guideline for self-reliance planning consisted of 4 aspects: 1) Development planning: by arranging meet up groups to conduct further education on Litecoin and share solutions on adoption into every day usage. Local communities need to develop awareness of the usefulness of Litecoin and share the value of Litecoin among friends and family. 2) Computer Science and Business Management staff should develop skills to expand on the benefits of Litecoin within their departments. 3) Further research should be pursued on how Litecoin Value can improve business and tourism within Thailand. 4) Local communities should focus on developing Litecoin awareness by encouraging street vendors to accept Litecoin as another form of payment for services rendered.

Keywords: bitcoin, cryptocurrency, decentralized, business implementation

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Authors: Jung-Hwan Oh, Rajesh Kumar, Il-Kwon Oh

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Porous graphene has extensive potential applications in variety of fields such as hydrogen storage, CO oxidation, gas separation, supercapacitors, fuel cells, nanoelectronics, oil adsorption, and so on. However, the generation of some carbon atoms vacancies for precise small holes have been not extensively studied to prevent the agglomerates of graphene sheets and to obtain porous graphene with high surface area. Recently, many research efforts have been presented to develop physical and chemical synthetic approaches for porous graphene. But physical method has very high cost of manufacture and chemical method consumes so many hours for porous graphene. Herein, we propose a porous graphene contained holes with atomic scale precision by embedding metal nano-particles through microwave irradiation for hydrogen storage and CO oxidation multi- functionalities. This proposed synthetic method is appropriate for fast and convenient production of three dimensional nanostructures, which have nanoholes on the graphene surface in consequence of microwave irradiation. The metal nanoparticles are dispersed quickly on the graphene surface and generated uniform nanoholes on the graphene nanosheets. The morphological and structural characterization of the porous graphene were examined by scanning electron microscopy (SEM), transmission scanning electron microscopy (TEM) and RAMAN spectroscopy, respectively. The metal nanoparticle-embedded porous graphene exhibits a microporous volume of 2.586cm3g-1 with an average pore radius of 0.75 nm. HR-TEM analysis was carried out to further characterize the microstructures. By investigating the RAMAN spectra, we can understand the structural changes of graphene. The results of this work demonstrate a possibility to produce a new class of porous graphene. Furthermore, the newly acquired knowledge for the diffusion into graphene can provide useful guidance for the development of the growth of nanostructure.

Keywords: CO oxidation, hydrogen storage, nanocomposites, porous graphene

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Authors: Jae-Kyung Choi, Soon-Yong Kwon, Hyung Duk Yun, Hyun-Sang Chung, Seongho Seo, Kukjin Bae

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Recently, there were several attempts to utilize a graphene layer as a water desalination membrane. In order to use a graphene layer as a water desalination membrane, fabrication of crack-free suspension of graphene on a porous membrane, having hydrophobic surface, and generation of a uniform holes on a graphene are very important. In here, we showed a simple chemical vapor deposition (CVD) method to create a patterned graphene membrane on a patterned platinum film. After CVD growth process of patterned graphene layer/patterned Pt on SiO2 substrates, the patterned graphene layer can be successfully transferred onto arbitrary substrates via thermal-assisted transfer method. In this result, the transferred patterned graphene membrane has so hydrophobic surface which will certainly impact on the naturally and speed pass way for fresh water. In addition to this, we observed that overlapping of patterned graphene membranes reported previously by our group may generate different size of holes.

Keywords: chemical vapor deposition (CVD), hydrophobic surface, membrane desalination, porous graphene

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Authors: Mário Ernesto Sitoe, Orlando Zacarias

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University education is influenced by several factors that range from the adoption of strategies to strengthen the whole process to the academic performance improvement of the students themselves. This work uses data mining techniques to develop a predictive model to identify students with a tendency to evasion and retention. To this end, a database of real students’ data from the Department of University Admission (DAU) and the Department of Mathematics and Informatics (DMI) was used. The data comprised 388 undergraduate students admitted in the years 2009 to 2014. The Weka tool was used for model building, using three different techniques, namely: K-nearest neighbor, random forest, and logistic regression. To allow for training on multiple train-test splits, a cross-validation approach was employed with a varying number of folds. To reduce bias variance and improve the performance of the models, ensemble methods of Bagging and Stacking were used. After comparing the results obtained by the three classifiers, Logistic Regression using Bagging with seven folds obtained the best performance, showing results above 90% in all evaluated metrics: accuracy, rate of true positives, and precision. Retention is the most common tendency.

Keywords: evasion and retention, cross-validation, bagging, stacking

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Authors: Messis A., Adjebli A., Ayeche R., Talbi M., Tighilet K., Louardiane M.

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Cancers are the second cause of death worldwide. Prevalence and incidence of cancers is getting increased by aging and population growth. This study aims to predict and modeling the evolution of breast, Colorectal, Lung, Bladder and Prostate cancers over the period of 2014-2019. In this study, data were analyzed using time series analysis with double exponential smoothing method to forecast the future pattern. To describe and fit the appropriate models, Minitab statistical software version 17 was used. Between 2014 and 2019, the overall trend in the raw number of new cancer cases registered has been increasing over time; the change in observations over time has been increasing. Our forecast model is validated since we have good prediction for the period 2020 and data not available for 2021 and 2022. Time series analysis showed that the double exponential smoothing is an efficient tool to model the future data on the raw number of new cancer cases.

Keywords: cancer, time series, prediction, double exponential smoothing

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Authors: Nattawipa Pakasri

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58S (60SiO2-36CaO-4P2O5), three-dimensionally ordered macroporous bioactive glasses (3DOM-BGs) were synthesized by the sol-gel method using dual templating methods. non-ionic surfactant Brij56 used as templates component produced mesoporous and the spherical PMMA colloidal crystals as one template component yielded either three-dimensionally ordered microporous products or shaped bioactive glass nanoparticles. The bioactive glass with aging step for 12 h at room temperature, no structure transformation occurred and the 3DOM structure was produced (Figure a) due to no shrinkage process between the aging step. After 48 h time of o 3DOM structure remained and, nanocube with ∼120 nm edge lengths and nanosphere particle with ∼50 nm was obtained (Figure c, d). PMMA packing templates have octahedral and tetrahedral holes to make 2 final shapes of 3DOM-BGs which is rounded and cubic, respectively. The ageing time change from 12h, 24h and 48h affected to the thickness of interconnecting macropores network. The wall thickness was gradually decrease after increase aging time.

Keywords: three-dimensionally ordered macroporous bioactive glasses, sol-gel method, PMMA, bioactive glass

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Authors: Abu Afree Andalib, Rafiur Rahman, Md Mezbah Uddin

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The main objective of this work is to anatomize on the various parameters of AGM 88 missile anatomized using FSI module in Ansys. Computational fluid dynamics is used for the study of fluid flow pattern and fluidic phenomenon such as drag, pressure force, energy dissipation and shockwave distribution in water. Using finite element analysis module of Ansys, structural parameters such as stress and stress density, localization point, deflection, force propagation is determined. Separate analysis on structural parameters is done on Abacus. State of the art coupling module is used for FSI analysis. Fine mesh is considered in every case for better result during simulation according to computational machine power. The result of the above-mentioned parameters is analyzed and compared for two phases using graphical representation. The result of Ansys and Abaqus are also showed. Computational Fluid Dynamics and Finite Element analyses and subsequently the Fluid-Structure Interaction (FSI) technique is being considered. Finite volume method and finite element method are being considered for modelling fluid flow and structural parameters analysis. Feasible boundary conditions are also utilized in the research. Significant change in the interaction and interference pattern while the impact was found. Theoretically as well as according to simulation angled condition was found with higher impact.

Keywords: FSI (Fluid Surface Interaction), impact, missile, high viscous fluid, CFD (Computational Fluid Dynamics), FEM (Finite Element Analysis), FVM (Finite Volume Method), fluid flow, fluid pattern, structural analysis, AGM-88, Ansys, Abaqus, meshing, k-omega, turbulence model

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Authors: Xulu Yao, Moi Hoon Yap, Yanlong Zhang

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As a branch of artificial neural network, deep learning is widely used in the field of image recognition, but the lack of its dataset leads to imperfect model learning. By analysing the data scale requirements of deep learning and aiming at the application in GUI generation, it is found that the collection of GUI dataset is a time-consuming and labor-consuming project, which is difficult to meet the needs of current deep learning network. To solve this problem, this paper proposes a semi-supervised deep learning model that relies on the original small-scale datasets to produce a large number of reliable data sets. By combining the cyclic neural network with the generated countermeasure network, the cyclic neural network can learn the sequence relationship and characteristics of data, make the generated countermeasure network generate reasonable data, and then expand the Rico dataset. Relying on the network structure, the characteristics of collected data can be well analysed, and a large number of reasonable data can be generated according to these characteristics. After data processing, a reliable dataset for model training can be formed, which alleviates the problem of dataset shortage in deep learning.

Keywords: GUI, deep learning, GAN, data augmentation

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Authors: Abdelhacine Gouasmia, Abdelhamid Belkhiri, Allaeddine Athmani

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The objective of this paper is to evaluate the effects of soil-structure interaction (SSI) on the modal characteristics and on the dynamic response of current structures. The objective is on the overall behaviour of a real structure of five storeys reinforced concrete (R/C) building typically encountered in Algeria. Sensitivity studies are undertaken in order to study the effects of frequency content of the input motion, frequency of the soil-structure system, rigidity and depth of the soil layer on the dynamic response of such structures. This investigation indicated that the rigidity of the soil layer is the predominant factor in soil-structure interaction and its increases would definitely reduce the deformation in the R/C structure. On the other hand, increasing the period of the underlying soil will cause an increase in the lateral displacements at story levels and create irregularity in the distribution of story shears. Possible resonance between the frequency content of the input motion and soil could also play an important role in increasing the structural response.

Keywords: direct method, finite element method, foundation, R/C Frame, soil-structure interaction

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Authors: Paula Salazar, Rodrigo Henríquez, Pablo Zerega

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The textile, food and pharmaceutical industries are expanding daily worldwide, and they are located within the most polluting industries due to the fact that wastewater is discharged into watercourses with high concentrations of dyes and traces of drugs. Many of these compounds are stable to light and biodegradation, being considered as emerging organic contaminants. Advanced oxidation processes (AOPs) emerge as an effective alternative for the removal and elimination of this type of contaminants. Heterogeneous photocatalysis has been extensively studied as it is an efficient, low-cost and durable method. As the main photocatalyst, TiO₂ has been used for the degradation of a large number of dyes and drugs. The disadvantage of TiO₂ is its absorption in the UV region of the solar spectrum. On the other hand, quaternary chalcogenides based on Cu₂SnZnX₄ (X = S, Se) are a possible alternative due to their narrow bandgap (ca. between 0.8 to 1.5 eV depending on the phase considered), low cost, an abundance of its constituent elements in the earth's crust and its low toxicity. The objective of this research was to synthesize Cu₂SnZnS₄ (CZTS) through of a low-cost hydrothermal method and evaluate it as a potential photo-catalyst in the photo-degradation process of Congo Red. The synthesis of the nanoparticle in suspension and film onto fluorine-doped tin oxide coated glass (FTO) was carried out using a mixture of: 2 mmol CuCl₂, 1 mmol ZnCl₂, 1 mmol SnCl₂ and 4 mmol CH4N₂S in a Teflon reactor at 180⁰C for 72 h. Characterization was performed through scanning electron microscopy (SEM), X-ray diffraction (XRD) and UV VIS spectroscopy. Photo-degradation monitoring was carried out employing a UV VIS spectrophotometer. The results show that photodegradation of 55% of the dye can be obtained after 4h of exposure to polychromatic light, it should be noted that the Congo Red dye is being studied for the first time.

Keywords: CZTS, hydrothermal, photocatalysis, dye

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Authors: Mahmoud Nassar

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This paper was designed for interviews with companies that had implemented Management Accounting Innovations (MAIs) within Jordanian Industrial Sector in full. Each company in this paper was examined as an entity to obtain an understanding of the process of MAIs adoption and implementation as well as the respondents’ opinions and perspectives of each individual company as to what are considered to be the important factors in the company. By firstly using within-case analysis has the potential to aid in-depth views of the issues and their impact on each particular company. Then, cross-case analysis was used to analyse the similarities and differences of the six companies. The study concludes that, the six companies interviewed gradually moved to using MAIs over the last ten years. The length of time required to implement the MAIs varied across the companies. Interviewees revealed several factors from both the demand and supply side that influence implementation of MAIs within the Jordanian industrial companies. Respondents mentioned and emphasised the important effect of the following factors: top management support, education about ABC concept and benefits, training programmes, shortcoming of existing cost system, competition, size of company, professional accounting bodies, management accounting journals, management accounting research and PhD degrees, and cooperation between universities and companies.

Keywords: industrial sector, innovations, Jordan, management accounting

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Authors: Ge Zheng, Jun Peng

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Unbalanced power output from individual cells of Proton Exchange Membrane Fuel Cell (PEMFC) has direct effects on PEMFC stack performance, in particular under transient operation. In the paper, a multi-layer ANN (Artificial Neural Network) model Radial Basis Functions (RBF) has been developed for predicting cells' output profiles by applying gas supply parameters, cooling conditions, temperature measurement of individual cells, etc. The feed-forward ANN model was validated with experimental data. Influence of relevant parameters of RBF on the network accuracy was investigated. After adequate model training, the modelling results show good correspondence between actual measurements and reconstructed output profiles. Finally, after the model was used to optimize the stack output performance under steady-state and transient operating conditions, it suggested that the developed ANN control model can help PEMFC stack to have obvious improvement on power output under fast acceleration process.

Keywords: proton exchange membrane fuel cell, PEMFC, artificial neural network, ANN, cell output profile, transient

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Authors: Revoti Prasad Bora, Nikita Katyal, Saurabh Yadav

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Pre-processing plays an important role in various image processing applications. Most of the time due to the similar nature of images, a particular pre-processing or a set of pre-processing steps are sufficient to produce the desired results. However, in the education domain, there is a wide variety of images in various aspects like images with line-based diagrams, chemical formulas, mathematical equations, etc. Hence a single pre-processing or a set of pre-processing steps may not yield good results. Therefore, a Deep Learning based approach for dynamically selecting a relevant pre-processing technique for each image is proposed. The proposed method works as a classifier to detect hidden patterns in the images and predicts the relevant pre-processing technique needed for the image. This approach experimented for an image similarity matching problem but it can be adapted to other use cases too. Experimental results showed significant improvement in average similarity ranking with the proposed method as opposed to static pre-processing techniques.

Keywords: deep-learning, classification, pre-processing, computer vision, image processing, educational data mining

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Authors: Z. Olczykowski

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The paper presents the impact of work on the electric arc furnace. Arc equipment is one of the largest receivers powered by the power system. Electric arc disturbances arising during melting process occurring in these furnaces are the cause of an abrupt change of the passive power of furnaces. Currents drawn by these devices undergo an abrupt change, which in turn cause voltage fluctuations and light flicker. The quantitative evaluation of the voltage fluctuations is now the basic criterion of assessment of an influence of unquiet receiver on the supplying net. The paper presents the method of determination of range of voltage fluctuations and light flicker at parallel operation of arc devices. The results of measurements of voltage fluctuations and light flicker indicators recorded in power supply networks of steelworks were presented, with different number of parallel arc devices. Measurements of energy quality parameters were aimed at verifying the proposed method in practice. It was also analyzed changes in other parameters of electricity: the content of higher harmonics, asymmetry, voltage dips.

Keywords: power quality, arc furnaces, propagation of voltage fluctuations, disturbances

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Authors: Sarah Beaver, Renee Bryce

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Audiograms detect hearing impairment, but missing values pose problems. This work explores imputations in an attempt to improve accuracy. This work implements Linear Regression, Lasso, Linear Support Vector Regression, Bayesian Ridge, K Nearest Neighbors (KNN), and Random Forest machine learning techniques to impute audiogram frequencies ranging from 125Hz to 8000Hz. The data contains patients who had or were candidates for cochlear implants. Accuracy is compared across two different Nested Cross-Validation k values. Over 4000 audiograms were used from 800 unique patients. Additionally, training on data combines and compares left and right ear audiograms versus single ear side audiograms. The accuracy achieved using Root Mean Square Error (RMSE) values for the best models for Random Forest ranges from 4.74 to 6.37. The R\textsuperscript{2} values for the best models for Random Forest ranges from .91 to .96. The accuracy achieved using RMSE values for the best models for KNN ranges from 5.00 to 7.72. The R\textsuperscript{2} values for the best models for KNN ranges from .89 to .95. The best imputation models received R\textsuperscript{2} between .89 to .96 and RMSE values less than 8dB. We also show that the accuracy of classification predictive models performed better with our best imputation models versus constant imputations by a two percent increase.

Keywords: machine learning, audiograms, data imputations, single imputations

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Authors: Benghenia Hadj Abd El Kader

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Sleep apnea events as obstructive, central, mixed or hypopnea are characterized by frequent breathing cessations or reduction in upper airflow during sleep. An advanced method for analyzing the patterning of biomedical signals to recognize obstructive sleep apnea and hypopnea is presented. In the aim to extract characteristic parameters, which will be used for classifying the above stated (obstructive, central, mixed) sleep apnea and hypopnea, the proposed method is based first on the analysis of polysomnography signals such as electrocardiogram signal (ECG) and electromyogram (EMG), then classification of the (obstructive, central, mixed) sleep apnea and hypopnea. The analysis is carried out using the wavelet transform technique in order to extract characteristic parameters whereas classification is carried out by applying the SVM (support vector machine) technique. The obtained results show good recognition rates using characteristic parameters.

Keywords: obstructive, central, mixed, sleep apnea, hypopnea, ECG, EMG, wavelet transform, SVM classifier

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Authors: Sarah K. Taylor, Miratun M. Saharuddin, Zabri A. Talib

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Cybercrime is on the rise, and yet many Law Enforcement Agencies (LEAs) in Malaysia have no Digital Forensics Laboratory (DFL) to assist them in the attrition and analysis of digital evidence. From the estimated number of 30 LEAs in Malaysia, sadly, only eight of them owned a DFL. All of the DFLs are concentrated in the capital of Malaysia and none at the state level. LEAs are still depending on the national DFL (CyberSecurity Malaysia) even for simple and straightforward cases. A survey was conducted among LEAs in Malaysia owning a DFL to understand their history of establishing the DFL, the challenges that they faced and the significance of the DFL to their case investigation. The results showed that the while some LEAs faced no challenge in establishing a DFL, some of them took seven to 10 years to do so. The reason was due to the difficulty in convincing their management because of the high costs involved. The results also revealed that with the establishment of a DFL, LEAs were better able to get faster forensic result and to meet agency’s timeline expectation. It is also found that LEAs were also able to get more meaningful forensic results on cases that require niche expertise, compared to sending off cases to the national DFL. Other than that, cases are getting more complex, and hence, a continuous stream of budget for equipment and training is inevitable. The result derived from the study is hoped to be used by other LEAs in justifying to their management the benefits of establishing an in-house DFL.

Keywords: digital evidence, digital forensics, digital forensics laboratory, law enforcement agency

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Authors: Konstantinos Perifanos, Eirini Florou, Dionysis Goutsos

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This paper presents and benchmarks a number of end-to-end Deep Learning based models for metaphor detection in Greek. We combine Convolutional Neural Networks and Recurrent Neural Networks with representation learning to bear on the metaphor detection problem for the Greek language. The models presented achieve exceptional accuracy scores, significantly improving the previous state-of-the-art results, which had already achieved accuracy 0.82. Furthermore, no special preprocessing, feature engineering or linguistic knowledge is used in this work. The methods presented achieve accuracy of 0.92 and F-score 0.92 with Convolutional Neural Networks (CNNs) and bidirectional Long Short Term Memory networks (LSTMs). Comparable results of 0.91 accuracy and 0.91 F-score are also achieved with bidirectional Gated Recurrent Units (GRUs) and Convolutional Recurrent Neural Nets (CRNNs). The models are trained and evaluated only on the basis of training tuples, the related sentences and their labels. The outcome is a state-of-the-art collection of metaphor detection models, trained on limited labelled resources, which can be extended to other languages and similar tasks.

Keywords: metaphor detection, deep learning, representation learning, embeddings

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Authors: Shima Nikanjam, Badiossadat Hassanpour, Adi Irfan Che Ani

Abstract:

The design process in architecture education is based upon the Learning-by-Doing method, which leads students to understand how to design by practicing rather than studying. First-year design studios, as starting educational stage, provide integrated knowledge and skills of design for newly jointed architecture students. Within the basic design studio environment, students are guided to transfer their abstract thoughts into visual concrete decisions under the supervision of design educators for the first time. Therefore, introductory design studios have predominant impacts on students’ operational thinking and designing. Architectural design thinking is quite different from students’ educational backgrounds and learning habits. This educational challenge at basic design studios creates a severe need to study the reality of design education at foundation year and define appropriate educational methods with convenient project types with the intention of enhancing architecture education quality. Material for this study has been gathered through long-term direct observation at a first year second semester design studio at the faculty of architecture at EMU (known as FARC 102), fall and spring academic semester 2014-15. Distribution of a questionnaire among case study students and interviews with third and fourth design studio students who passed through the same methods of education in the past 2 years and conducting interviews with instructors are other methodologies used in this research. The results of this study reveal a risk of a mismatch between the implemented teaching method, project type and scale in this particular level and students’ learning styles. Although the existence of such risk due to varieties in students’ profiles could be expected to some extent, recommendations can support educators to reach maximum compatibility.

Keywords: architecture education, basic design studio, educational method, forms creation skill

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Authors: Hayal Akyildirim Beğen, Özgür Emi̇nağaoğlu

Abstract:

DNA barcoding is the method of description of species based on gene diversity. In current studies, registration, genetic identification and protection of especially endemic plants pecies are carried out by DNA barcoding techniques. Molecular studies are based on the amplification and sequencing of the barcode gene region by the PCR method. Endemic Campanula choruhensis Kit Tan & Sorger, Campanula troegera Damboldt and Campanula betulifolia K.Koch is widespread in Artvin, Erzurum and around Çoruh valley passing through it. Intense road and dam constructions are carried out in and around the distribution area of this species. This situation harms the habitat of the species and puts its extinction. In this study, the plastid matK barcode gene regions (650 bp) of three Campanula species were created. To make the identification of this species quickly and accurately, gene sequence compared with sequences of other Campanula L. species. As a result of phylogenetic analysis, C. choruhensis is close relative to C. betulifolia. Morphologically, these species were determined to be more similar to each other with flower and leaf characters. C. troegera formed a separate branch.

Keywords: campanula, DNA barcoding, endemic, türkiye, artvin

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Authors: Si-yang Zhang, Chi Zhao

Abstract:

Comprehensive transportation hubs are important nodes of the transportation network, and their internal signage the functions as guidance and distribution assistance, which directly affects the operational efficiency of traffic in and around the hubs. Reasonably installed signage effectively attracts the visual focus of travelers and improves wayfinding efficiency. Among the elements of signage, the visual guidance effect is the key factor affecting the information conveyance, whom should be evaluated during design and optimization process. However, existing evaluation methods mostly focus on the layout, and are not able to fully understand if signage caters travelers’ need. This study conducted field investigations and developed panoramic videos for multiple transportation hubs in China, and designed survey accordingly. Human subjects are recruited to watch panoramic videos via virtual reality (VR) and respond to the surveys. In this paper, Pudong Airport and Xi'an North Railway Station were studied and compared as examples due to their high traveler volume and relatively well-developed traveler service systems. Visual attention was captured by eye tracker and subjective satisfaction ratings were collected through surveys. Entropy Weight Method (EWM) was utilized to evaluate the effectiveness of signage elements and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) was used to further rank the importance of the elements. The results show that the degree of visual attention of travelers significantly affects the evaluation results of guidance signage. Key factors affecting visual attention include accurate legibility, obstruction and defacement rates, informativeness, and whether signage is set up in a hierarchical manner.

Keywords: traveler guidance signage, panoramic video, visual attention, entropy weight method, TOPSIS

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Authors: Seyed Ali Mahdipour, Maryam Shafeei Sarvestani

Abstract:

Radiation pressure acceleration (RPA) and target normal sheath acceleration (TNSA) are the most important methods of Laser-accelerated proton beams (LAP) planning systems.LAP has inspired novel applications that can benefit from proton bunch properties different from conventionally accelerated proton beams. The secondary neutron and photon produced in the collision of protons with beamline components are of the important concern in proton therapy. Various published Monte Carlo researches evaluated the beamline and shielding considerations for TNSA method, but there is no studies directly address secondary neutron and photon production from RPA method in LAP. The purpose of this study is to calculate the flux distribution of neutron and photon secondary radiations on the first area ofLAP and to determine the optimize thickness and radius of the energyselector in a LAP planning system based on RPA method. Also, we present the Monte Carlo calculations to determine the appropriate beam pipe for shielding a LAP planning system. The GEANT4 Monte Carlo toolkit has been used to simulate a secondary radiation production in LAP. A section of new multifunctional LAP beamlinehas been proposed, based on the pulsed power solenoid scheme as a GEANT4 toolkit. The results show that the energy selector is the most important source of neutron and photon secondary particles in LAP beamline. According to the calculations, the pure Tungsten energy selector not be the proper case, and using of Tungsten+Polyethylene or Tungsten+Graphitecomposite selectors will reduce the production of neutron and photon intensities by approximately ~10% and ~25%, respectively. Also the optimal radiuses of energy selectors were found to be ~4 cm and ~6 cm for a 3 degree and 5 degree proton deviation angles, respectively.

Keywords: neutron, photon, flux distribution, energy selector, GEANT4 toolkit

Procedia PDF Downloads 88