Search results for: linear regression estimation

Authors: Aleksey Fedorov

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Building a scalable platform for quantum computing remains one of the most challenging tasks in quantum science and technologies. However, the implementation of most important quantum operations with qubits (quantum analogues of classical bits), such as multiqubit Toffoli gate, requires either a polynomial number of operation or a linear number of operations with the use of ancilla qubits. Therefore, the reduction of the number of operations in the presence of scalability is a crucial goal in quantum information processing. One of the most elegant ideas in this direction is to use qudits (multilevel systems) instead of qubits and rely on additional levels of qudits instead of ancillas. Although some of the already obtained results demonstrate a reduction of the number of operation, they suffer from high complexity and/or of the absence of scalability. We show a strong reduction of the number of operations for the realization of the Toffoli gate by using qudits for a scalable multi-qudit processor. This is done on the basis of a general relation between the dimensionality of qudits and their topology of connections, that we derived.

Keywords: quantum computing, qudits, Toffoli gates, gate decomposition

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Authors: Iqra Ali

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This study uses panel Vector Auto Regression (VAR) to analyses the dynamic link between banking and insurance activities based on the asset size of the insurance industry for 73 countries between 1980 and 2014. Assets in the insurance industry and banking activities usually have a Granger causal link, according to panel Granger-causality tests. Impulse response analyses for the entire sample show that the size of insurance assets responds favorably to a shock to the liquid liabilities and deposits of the financial system but negatively to a shock to deposit money bank assets and private credit offered by commercial banks, other financial institutions, and deposit banks. While the findings for middle- and low-income nations varied significantly, the observations for high-income countries are essentially the same. Furthermore, we find that there is a substantial interplay between banking and insurance activity in civil law nations as opposed to common law ones.

Keywords: vector autoregression, banking, insurance, Granger-causality

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Authors: Supattra Kanchanopast

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The purpose of this research was to identify factors that influenced the trust of e-commerce within retail businesses. In order to achieve the objectives of this research, the researcher collected data from random e-commerce users in Bangkok. The data was comprised of the results of 382 questionnaires. The data was analyzed by using descriptive statistics, which included frequency, percentages, and the standard deviation of pertinent factors. Multiple regression analysis was also used. The findings of this research revealed that the majority of the respondents were female, 25-40 years old, and graduated a bachelor degree. The respondents mostly worked in private sectors and had monthly income between 15,000-25,000 baht. The findings also indicate that information quality factors, website design factors, service quality factor, security factor and advertising factors as significant factors effecting customer trust of e-commerce in online retail. The hypotheses testing revealed that these factors in e-commerce had an effect on customer’s trust in the same direction with high level.

Keywords: e-commerce, online retail, Retail business, trust, website

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Authors: Shirin Jalili, Hadi Shirzad, Samaneh Nabavi, Somayeh Khanjani

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Forensic entomology is the science of study and analysis of insects evidences to aid in criminal investigation. Being aware of the distribution, biology, ecology and behavior of insects, which are founded at crime scene can provide information about when, where and how the crime has been committed. It has many application in criminal investigations. Its main use is estimation of the minimum time after death in suspicious death. The close association between insects and corpses and the use of insects in criminal investigations is the subject of forensic entomology. Because insects attack to the decomposing corpse and spawning on it from the initial stages. Forensic scientists can estimate the postmortem index by studying the insects population and the developing larval stages.In addition, toxicological and molecular studies of these insects can reveal the cause of death or even the identity of a victim. It also be used to detect drugs and poisons, and determination of incident location. Gathering robust entomological evidences is made possible for experts by recent Techniques. They can provide vital information about death, corpse movement or burial, submersion interval, time of decapitation, identification of specific sites of trauma, post-mortem artefacts on the body, use of drugs, linking a suspect to the scene of a crime, sexual molestations and the identification of suspects.

Keywords: Forensic entomology, post mortem interval, insects, larvae

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Authors: Victor A. Okenyi, Kehinde A. Alawode

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Corrosion of reinforcement in concrete structures remains a durability issue in structural engineering with the increasing cost of repair and maintenance. The mechanism and factors influencing reinforcement corrosion in concrete with various electrochemical monitoring techniques including non-destructive, destructive techniques and the roles of sensors have been reviewed with the aim of determining the monitoring technique that proved most effective in determining corrosion parameters and more practicable for the assessment of concrete durability. Electrochemical impedance spectroscopy (EIS) and linear polarization resistance (LPR) techniques showed great performance in evaluating corrosion kinetics and corrosion rate, respectively, while the gravimetric weight loss (GWL) technique provided accurate measurements. However, no single monitoring technique showed to be the ultimate technique, and this calls for more research work in the development of more dynamic monitoring tools capable of considering all possible corrosion factors in the corrosion monitoring process.

Keywords: corrosion, concrete structures, durability, non-destructive technique, sensor

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Authors: Ng'etich K. Stephen

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Abstract—Globally analytics in basketball has advanced tremendously in the last decade. Organizations are leveraging the insights to improve team and player performance and, in the long run, generate revenue out of it. Due to limited basketball game-related statistics in African competitions, teams are unaware of how they compete with other continental basketball teams. The purpose of this study is to evaluate the regional difference in basketball game-related statistics between African teams that played in the newly formed league, the basketball African league and the European league. The basketball African league, a competition created through the partnership between NBA and FIBA, offers a good starting point since it has valuable basketball metrics to analyze. This study sought to use multivariate linear discriminant analysis to identify the game-related statistics that discriminate the teams in Euro league and the basketball African league.

Keywords: basketball africa league, basketball, euroleague, fiba, africa

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Authors: Sergo Tsiramua, Sulkhan Sulkhanishvili, Elisabed Asabashvili, Lazare Kvirtia

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The paper presents logical-probabilistic methods, models and algorithms for reliability assessment of complex systems, based on which a web application for structural analysis and reliability assessment of systems was created. The reliability assessment process included the following stages, which were reflected in the application: 1) Construction of a graphical scheme of the structural reliability of the system; 2) Transformation of the graphic scheme into a logical representation and modeling of the shortest ways of successful functioning of the system; 3) Description of system operability condition with logical function in the form of disjunctive normal form (DNF); 4) Transformation of DNF into orthogonal disjunction normal form (ODNF) using the orthogonalization algorithm; 5) Replacing logical elements with probabilistic elements in ODNF, obtaining a reliability estimation polynomial and quantifying reliability; 6) Calculation of weights of elements. Using the logical-probabilistic methods, models and algorithms discussed in the paper, a special software was created, by means of which a quantitative assessment of the reliability of systems of a complex structure is produced. As a result, structural analysis of systems, research and designing of optimal structure systems are carried out.

Keywords: Complex systems, logical-probabilistic methods, orthogonalization algorithm, reliability, weight of element

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Authors: Somdech Rungsrisawas

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The objectives of this study are to examine the relationship between the competitive advantage of small and medium enterprises (SMEs) and their overall performance. A mixed method has been applied to identify the effect of determinants toward competitive advantage. The sample is composed of SMEs in product and service businesses. The study has been tested at an organizational level with samples of SME entrepreneurs, business successors, and board of directors or management team. Quantitative analysis has been conducted through multiple regression analysis with 400 samples. The findings illustrate that each aspect of competitive advantage needs a different set of driving factors to explain either the direct or the indirect effect on firm performance. Interestingly, technological capability is a perfect mediator and interorganizational cooperation toward competitive advantage. In addition, differentiation is difficult to be perceived by customers, as well as difficult to manage; however, it is considered important to develop an SMEs product or service for firm sustainably.

Keywords: competitive advantage, firm performance, technological capability, Small and Medium Enterprise (SMEs)

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Authors: Koray U. Erbas

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Neural networks are appealing for many applications since they are able to learn complex non-linear relationships between input and output data. As the number of neurons and layers in a neural network increase, it is possible to represent more complex relationships with automatically extracted features. Nowadays Deep Neural Networks (DNNs) are widely used in Computer Vision problems such as; classification, object detection, segmentation image editing etc. In this work, Facial Emotion Recognition task is performed by proposed Convolutional Neural Network (CNN)-based DNN architecture using FER2013 Dataset. Moreover, the effects of different hyperparameters (activation function, kernel size, initializer, batch size and network size) are investigated and ablation study results for Pooling Layer, Dropout and Batch Normalization are presented.

Keywords: convolutional neural network, deep learning, deep learning based FER, facial emotion recognition

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Authors: I. L. Ibrahim, A. Mann, A. Ndanaimi

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The research involved phytochemical screening, antibacterial activities and mineral determination by flame photometry of the crude extract of Brysocarpus coccineus schum indeed were carried out. The result of Phytochemical screening reveal tha saponins, alkaloids, cardiac glycosides, and anthraquinones were present. This suggests that the plant extract could be used as anti-inflammatory and anti-bleeding agents. Estimation of mineral content shows that the crude extract of B. coccineus contains 0.73 (Na+), 1.06 (K+) and 1.98 (Ca+) which justifies its use to be safe for hypertensive patients and could be used to lower blood pressure. The antibacterial properties of aqueous and ethanol extract were studied against some bacteria; pseudomonas aeruginosa, Escherichia coli, Bacilus subtilis, Klebsilla penmuoniae by disc diffusion method. The aqueous extract showed significant activity against the organisms while the ethanol at concentrations 5-10mg/ml ethanol extract showed significant zone of inhibition against the organisms, E. coli, (19 mm), B. cereus (12 mm), P. aeruginosa (11 mm), K. pnemuoniae (11 mm). Minimum inhibitory concentration (MIC) was carried with considerable effect of inhibition on the organisms. The MIC values observed were 1, 24, 16 and 19 mm against E. coli, B. cereus, P. aeruginosa and K. pnemuoniae respectively. Therefore, the plant could be a potential source of antibacterial agent although more pharmacological and clinical study may be recommended.

Keywords: phytochemicals, microorganisms, screenings, mineral ions

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Authors: Vithaya Intaraphimol

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This research investigates the effect of financial accounting information and non-financial accounting reports on corporate credibility via strength of board of directors and market environment volatility as moderating effect. Data in this research is collected by questionnaire form non-financial companies listed on the Stock Exchange of Thailand. Multiple regression statistic technique is chosen for analyzing the data. The empirical results find that firms with greater financial accounting information reports and non-financial accounting information reports will gain greater corporate credibility. Therefore, the corporate reporting has the value for the firms. Moreover, the strength of board of directors will positively moderate the financial and non-financial accounting information reports and corporate credibility relationship. Whereas, market environment volatility will negatively moderate the financial and nonfinancial accounting information reports and corporate credibility relationship.

Keywords: corporate credibility, financial and non-financial reports, firms performance, economics

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Authors: Selen Demirtas-Zorbaz

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This study aimed to determine if there is any relation between child–parent relationships and parental self-efficacy. The participants of this study are 208 parents, and 82,5% of them are mothers. The children’s age range are differed from 4 to 13 (x̄=7,8). The results showed that there is a significant positive correlation between positive relationship with parents and parental self-efficacy (r=0.52, p < .01); and significant negative correlation between conflict with parents and parental self-efficacy (r=-0.28, p < .01). Also, findings reveal that there was no significant correlation between the time spent with the child and conflict with parents (r=-0.08, p>.05). It was also found that there was no significant correlation between the time spends with the child and positive relationship with parents (r=0.08, p > 0.5). In addition to this; regression analysis’ results indicated that parental self-efficacy is significant predictors of conflict (β=-.268, t=-4.002, p < .001) and positive relationship with parents (β =.519, t= 8.733, p < .001) whereas time spent with children is not (β =-.070, t=-1,045, p > .05 for conflict; β =.061, t=1.023, p > .05 for positive relationship with parents).

Keywords: child-parent relationship, conflict with parents, positive relationship with parents, parental efficacy

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Authors: Mahacine Amrani

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This paper aims at reviewing some Moroccan industrial applications of wavelet especially in the dynamic identification of a process model using Haar wavelet mother response. Two recent Moroccan study cases are described using dynamic data originated by a distillation column and an industrial polyethylene process plant. The purpose of the wavelet scheme is to build on-line dynamic models. In both case studies, a comparison is carried out between the Haar wavelet mother response model and a linear difference equation model. Finally it concludes, on the base of the comparison of the process performances and the best responses, which may be useful to create an estimated on-line internal model control and its application towards model-predictive controllers (MPC). All calculations were implemented using AutoSignal Software.

Keywords: process performance, model, wavelets, Haar, Moroccan

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Authors: Nan Tang, Bin Wu, Cunfu He

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The trapezoid rods are widely used in civil engineering as load –carrying members. Ultrasonic guided wave is one of the most popular techniques in analyzing the propagation of elastic guided wave. The goal of this paper is to investigate the propagation of elastic waves in the isotropic bar with trapezoid cross-section. Dispersion curves that describe the relationship between the frequency and velocity provide the fundamental information to describe the propagation of elastic waves through a structure. Based on the SAFE (semi-analytical finite element) a linear algebraic system of equations is obtained. By using numerical methods, dispersion curves solved for the rods with the trapezoid cross-section. These fundamental information plays an important role in applying ultrasonic guided waves to NTD for structures with trapezoid cross section.

Keywords: guided wave, dispersion, finite element method, trapezoid rod

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Authors: Fasanmi Samuel Sunday

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This study investigated the influence of gender and personality traits on emotional distress among awaiting trial inmates in Nigeria. Participants were three hundred and twenty (320) awaiting trial inmates, drawn from three main correctional centres in Northeast Nigeria, namely: Gashua Correctional Centre, Postiskum Correctional Centre, and Bauchi Correctional Centre. Expo facto research design was adopted. Questionnaires such as the Big Five Inventory and the Perceived Emotional Distress Inventory (PEDI) were used to measure the variables of the study. Three hypotheses were tested. Logistic regression was used for data analysis. Results of the analysis indicated that conscientiousness significantly predicted emotional distress among awaiting trial inmates. However, most of the identified personality traits did not significantly predict emotional distress among awaiting trial inmates. There was no significant gender difference in emotional distress among awaiting-trial inmates. The implications of the study were discussed.

Keywords: personality traits, emotional distress, awaiting-trial inmates, gender

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Authors: Raghad A. Altowairgi

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With the wide spread of social media platforms, young people tend to use them extensively as the first means of communication due to their ease and modernity. But these platforms often create a fertile ground for bullies to practice their aggressive behavior against their victims. Platform usage cannot be reduced, but intelligent mechanisms can be implemented to reduce the abuse. This is where machine learning comes in. Understanding and classifying text can be helpful in order to minimize the act of cyberbullying. Artificial intelligence techniques have expanded to formulate an applied tool to address the phenomenon of cyberbullying. In this research, machine learning models are built to classify text into two classes; cyberbullying and non-cyberbullying. After preprocessing the data in 4 stages; removing characters that do not provide meaningful information to the models, tokenization, removing stop words, and lowering text. BoW and TF-IDF are used as the main features for the five classifiers, which are; logistic regression, Naïve Bayes, Random Forest, XGboost, and Catboost classifiers. Each of them scores 92%, 90%, 92%, 91%, 86% respectively.

Keywords: cyberbullying, machine learning, Bag-of-Words, term frequency-inverse document frequency, natural language processing, Catboost

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Authors: Walid S. Alfuhaid, Saud A. Alghamdi, John M. Watkins, M. Edwin Sawan

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Designing a controller for stochastic decentralized interconnected large scale systems usually involves a high degree of complexity and computation ability. Noise, observability, and controllability of all system states, connectivity, and channel bandwidth are other constraints to design procedures for distributed large scale systems. The quasi-steady state model investigated in this paper is a reduced order model of the original system using singular perturbation techniques. This paper results in an optimal control synthesis to design an observer based feedback controller by standard stochastic control theory techniques using Linear Quadratic Gaussian (LQG) approach and Kalman filter design with less complexity and computation requirements. Numerical example is given at the end to demonstrate the efficiency of the proposed method.

Keywords: decentralized, optimal control, output, singular perturb

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Authors: Anupam Deka

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Gender discrimination has been considered as a major obstacle in granting equal opportunity for woman in Higher education as education plays a pivotal role in a country’s socio-economic development. To examine the empowerment of women in the higher education field of Assam, a case study has been carried out. In the first stage, an overview of enrolment of students in different courses has been made by considering the whole state. In the second stage a study has been conducted regarding the enrolment of students in various degree and P-G courses for the period 2000-2007 under Gauhati University (which is one of the four universities of Assam) and the relevant data has been collected. It has been found that though the enrolment of students in the degree levels has been constantly increasing, but the enrolment of girls are not proportionately increasing, specially in commerce and law. On the other hand, in the post-graduate level, these proportions are higher in almost all the subjects (except some subjects like M. COM., L.L.M, M. C. A., Mathematics, etc.), indicating that more number of girls than boys are taking admission in the P-G courses.

Keywords: field study, enrolment of girls in degree and P G levels, regression lines, Chi Square test, diagrams and statistical tables

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Authors: Sri Rejeki Dwi Astuti, Suyanta

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The demanding of the asessment in learning process was impact by policy changes. Nowadays, the assessment not only emphasizes knowledge, but also skills and attitude. However, in reality there are many obstacles in measuring them. This paper aimed to describe how to develop instrument of integrated assessment as alternative assessment to measure critical thinking skills and science process skills in electrolyte solution and to describe instrument’s characteristic such as logic validity and construct validity. This instrument development used test development model by McIntire. Development process data was acquired based on development test step and was analyzed by qualitative analysis. Initial product was observed by three peer reviewer and six expert judgment (two subject matter expert, two evaluation expert and two chemistry teacher) to acquire logic validity test. Logic validity test was analyzed using Aiken’s formula. The estimation of construct validity was analyzed by exploratory factor analysis. Result showed that integrated assessment instrument has 0,90 of Aiken’s Value and all item in integrated assessment asserted valid according to construct validity.

Keywords: construct validity, critical thinking skills, integrated assessment instrument, logic validity, science process skills

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Authors: Sirus Sharifi, Arunima Haldar, S. V. D. Nageswara Rao

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This research analyzes the effect of credit risk management practices of commercial banks in India and the relationship with their non-performing assets (NPAs). Required data on credit risk performance was collected through a survey questionnaire from top risk officers of 38 Indian banks. NPA data (period from 2012 to 2016) was collected from Prowess database compiled by the Centre for Monitoring Indian Economy (CMIE). The model was assessed utilizing cross sectional regression method. As expected, the results indicate a negative significant relationship between credit risk management in India banks and their NPA growth. The research has implications for banks given the high level of losses in India and other economies as well, and the implementation of Basel III standards by the central banks. This research would be an evidence on credit risk performance and its relationship with the level of non-performing assets (NPAs) in Indian banks.

Keywords: risk management, risk identification, banks, Non-Performing Assets (NPAs)

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Authors: Anton Serov, Alan Maslani, Michal Hlina, Vladimir Kopecky, Milan Hrabovsky

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Recycling of organic waste is an increasingly hot topic in recent years. This issue becomes even more interesting if the raw material for the fuel production can be obtained as the result of that recycling. A process of high-temperature decomposition of a lignite (a non-hydrolysable complex organic compound) was studied on the plasma gasification reactor PLASGAS, where water-stabilized plasma torch was used as a source of high enthalpy plasma. The plasma torch power was 120 kW and allowed heating of the reactor to more than 1000 °C. The material feeding rate in the gasification reactor was selected 30 and 60 kg per hour that could be compared with small industrial production. An efficiency estimation of the thermal decomposition process was done. A balance of the torch energy distribution was studied as well as an influence of the lignite particle size and an addition of methane (CH4) in a reaction volume on the syngas composition (H2+CO). It was found that the ratio H2:CO had values in the range of 1,5 to 2,5 depending on the experimental conditions. The recycling process occurred at atmospheric pressure that was one of the important benefits because of the lack of expensive vacuum pump systems. The work was supported by the Grant Agency of the Czech Republic under the project GA15-19444S.

Keywords: atmospheric pressure, lignite, plasma treatment, water-stabilized plasma torch

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Authors: Mohamed Abdel Sabour, Mohamed Nouh, Ian Stevans, Essam Elkholy

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We study the period change of six Cepheids using 19376 accurate flux observations of the Solar Mass Ejection Imager (SMEI) onboard the Coriolis spacecraft. All observations for the six Cepheids have been derived as templates for each star, independent of the specific sites utilized to establish and update the O-C values. Sometimes, sinusoidal patterns are superimposed on the star's O-C changes, which cannot be regarded as random fluctuations in the pulsation period. Random period changes were detected and computed using Eddington's and Plakidis's approaches. A comparison of the observed and predicted period change reveals a good agreement with some published models and a very substantial divergence with others. Between the reported period change and that estimated by the current technique, a linear fit with a correlation coefficient of 90.08 percent was obtained. The temporal rate of period change in Cepheid stars might be connected to how well these stars' mass losses are known today.

Keywords: cepheids, period change, mass loss, O-C changes, period change, mass loss, O-C

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Authors: The Danh Phan

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House price forecasting is a main topic in the real estate market research. Effective house price prediction models could not only allow home buyers and real estate agents to make better data-driven decisions but may also be beneficial for the property policymaking process. This study investigates the housing market by using machine learning techniques to analyze real historical house sale transactions in Australia. It seeks useful models which could be deployed as an application for house buyers and sellers. Data analytics show a high discrepancy between the house price in the most expensive suburbs and the most affordable suburbs in the city of Melbourne. In addition, experiments demonstrate that the combination of Stepwise and Support Vector Machine (SVM), based on the Mean Squared Error (MSE) measurement, consistently outperforms other models in terms of prediction accuracy.

Keywords: house price prediction, regression trees, neural network, support vector machine, stepwise

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Authors: Amir Ahmad Dehghani, Morteza Nabizadeh

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This paper presents the application of an Adaptive Neuro-Fuzzy Inference System (ANFIS) to flood hydrograph modeling of Shahid Rajaee reservoir dam located in Iran. This was carried out using 11 flood hydrographs recorded in Tajan river gauging station. From this dataset, 9 flood hydrographs were chosen to train the model and 2 flood hydrographs to test the model. The different architectures of neuro-fuzzy model according to the membership function and learning algorithm were designed and trained with different epochs. The results were evaluated in comparison with the observed hydrographs and the best structure of model was chosen according the least RMSE in each performance. To evaluate the efficiency of neuro-fuzzy model, various statistical indices such as Nash-Sutcliff and flood peak discharge error criteria were calculated. In this simulation, the coordinates of a flood hydrograph including peak discharge were estimated using the discharge values occurred in the earlier time steps as input values to the neuro-fuzzy model. These results indicate the satisfactory efficiency of neuro-fuzzy model for flood simulating. This performance of the model demonstrates the suitability of the implemented approach to flood management projects.

Keywords: adaptive neuro-fuzzy inference system, flood hydrograph, hybrid learning algorithm, Shahid Rajaee reservoir dam

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Authors: Lamia L. G. Al-Mahamad, Benjamin R. Horrocks, Andrew Houlton

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Hydrogels based on metal coordination polymers of nucleosides and a range of metal ions (Au, Ag, Cu) have been prepared and characterized by atomic force microscopy (AFM), transmission electron microscopy (TEM), X-ray photoelectron spectroscopy, Fourier transform infrared spectroscopy, ultraviolet-visible absorption spectroscopy, and powder X-ray diffraction. AFM images of the xerogels revealed the formation of extremely long polymer molecules (> 10 micrometers, the maximum scan range). This result is also consistent with TEM images which show a fibrous morphology. Oxidative doping of the Au-nucleoside fibres produces an electrically conductive nanowire. No sharp Bragg peaks were found at the at the X-ray diffraction pattern for metal ions hydrogels indicating that the samples were amorphous, but instead the data showed broad peaks in the range 20 < Q < 40 and correspond to distances d=2μ/Q. The data was analysed using a simplified Rietveld method by fitting a regression model to obtain the distance between atoms.

Keywords: hydrogel, metal ions, nanowire, nucleoside

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Authors: Luqman Afolabi

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This paper measures the impacts of trade and institutions on environmental quality in Sub-Saharan Africa (SSA). To examine the direction and the magnitude of the effects, the study employs the pooled mean group (PMG) estimation technique on the panel data obtained from the World Bank’s World Development and Governance Indicators, between 1996 and 2018. The empirical estimates validate the environmental Kuznets curve hypothesis (EKC) for the region, even though there have been inconclusive results on the environment – growth nexus. Similarly, a positive coefficient is obtained on the impact of trade on the environment, while the impact of the institutional indicators produce mixed results. A significant policy implication is that the governments of the SSA countries pursue policies that tend to increase economic growth, so that pollutants may be reduced. Such policies may include the provision of incentives for sustainable growth-driven industries in the region. In addition, the governance infrastructures should be improved in such a way that appropriate penalties are imposed on the pollutants, while advanced technologies that have the potentials to reduce environmental degradation should be encouraged. Finally, it is imperative from these findings that the governments of the region should promote their trade relations and the competitiveness of their local industries in order to keep pace with the global markets.

Keywords: environmental quality, institutional quality sustainable development goals, trade

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Authors: I. M. L. Nadeesha Jayaweera, Adao Alex Trindade

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In choosing a candidate model in likelihood-based modeling via an information criterion, the practitioner is often faced with the difficult task of deciding just how far up the ranked list to look. Motivated by this pragmatic necessity, we construct an uncertainty band for a generalized (model selection) information criterion (GIC), defined as a criterion for which the limit in probability is identical to that of the normalized log-likelihood. This includes common special cases such as AIC & BIC. The method starts from the asymptotic normality of the GIC for the joint distribution of the candidate models in an independent and identically distributed (IID) data framework and proceeds by deriving the (asymptotically) exact distribution of the minimum. The calculation of an upper quantile for its distribution then involves the computation of multivariate Gaussian integrals, which is amenable to efficient implementation via the R package "mvtnorm". The performance of the methodology is tested on simulated data by checking the coverage probability of nominal upper quantiles and compared to the bootstrap. Both methods give coverages close to nominal for large samples, but the bootstrap is two orders of magnitude slower. The methodology is subsequently extended to two other commonly used model structures: regression and time series. In the regression case, we derive the corresponding asymptotically exact distribution of the minimum GIC invoking Lindeberg-Feller type conditions for triangular arrays and are thus able to similarly calculate upper quantiles for its distribution via multivariate Gaussian integration. The bootstrap once again provides a default competing procedure, and we find that similar comparison performance metrics hold as for the IID case. The time series case is complicated by far more intricate asymptotic regime for the joint distribution of the model GIC statistics. Under a Gaussian likelihood, the default in most packages, one needs to derive the limiting distribution of a normalized quadratic form for a realization from a stationary series. Under conditions on the process satisfied by ARMA models, a multivariate normal limit is once again achieved. The bootstrap can, however, be employed for its computation, whence we are once again in the multivariate Gaussian integration paradigm for upper quantile evaluation. Comparisons of this bootstrap-aided semi-exact method with the full-blown bootstrap once again reveal a similar performance but faster computation speeds. One of the most difficult problems in contemporary statistical methodological research is to be able to account for the extra variability introduced by model selection uncertainty, the so-called post-model selection inference (PMSI). We explore ways in which the GIC uncertainty band can be inverted to make inferences on the parameters. This is being attempted in the IID case by pivoting the CDF of the asymptotically exact distribution of the minimum GIC. For inference one parameter at a time and a small number of candidate models, this works well, whence the attained PMSI confidence intervals are wider than the MLE-based Wald, as expected.

Keywords: model selection inference, generalized information criteria, post model selection, Asymptotic Theory

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Authors: V. Antevska, B. Dejanova, L. Todorovska, J. Pluncevic, E. Sivevska, S. Petrovska, S. Mancevska, I. Karagjozova

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Introduction: The aim of this study was to optimise the laboratory oxidative stress (OS) markers in soccer players. Material and methods: In a number of 37 soccer players (21±3 years old) and 25 control subjects (sedenters), plasma samples were taken for d-ROMs (reactive oxygen metabolites) and NO (nitric oxide) determination. The d-ROMs test was performed by measurement of hydroperoxide levels (Diacron, Italy). For NO determination the method of nitrate enzyme reduction with the Greiss reagent was used (OXIS, USA). The parameters were taken after the training of the soccer players and were compared with the control group. Training was considered as maximal exercise treadmill test. The criteria of maximum loading for each subject was established as >95% maximal heart rate. Results: The level of d-ROMs was found to be increased in the soccer players vs. control group but no significant difference was noticed. After the training d-ROMs in soccer players showed increased value of 299±44 UCarr (p<0.05). NO showed increased level in all soccer players vs. controls but significant difference was found after the training 102±29 μmol (p<0.05). Conclusion: Due to these results we may suggest that the measuring these OS markers in sport medicine may be useful for better estimation and evaluation of the training program. More oxidative stress should be used to clarify optimization of the training intensity program.

Keywords: oxidative stress markers, soccer players, training, sport

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Authors: Sabina Akter, Osiris Valdez Banda, Pentti Kujala, Jani Romanoff

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This paper examines the relationship between on-board environmental factors and customer overall satisfaction in the context of the cruise on-board experience. The on-board environmental factors considered are ambient, layout/design, social, product/service and on-board enjoyment factors. The study presents a data-driven framework and model for the on-board cruise experience. The data are collected from 893 respondents in an application of a self-administered online questionnaire of their cruise experience. This study reveals the cruise passengers’ on-board experience through the customer decision journey based on the publicly available data. Pearson correlation and regression analysis have been applied, and the results show a positive and a significant relationship between the environmental factors and on-board experience. These data help understand the cruise passengers’ on-board experience, which will be used for the ultimate decision-making process in cruise ship design.

Keywords: cruise behavior, customer activities, on-board environmental factors, on-board experience, user or customer satisfaction

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Authors: Shweta K. Vyas, Rakesh Musale, Sanjeev R. Shukla

Abstract:

Eri silk is a non mulberry silk which is obtained without killing the silkworms and hence it is also known as Ahmisa silk. In the present study, the results on degumming of eri silk with alkaline peroxide have been compared with those obtained by using ionic liquid (IL) 1-Butyl-3-methylimidazolium chloride [BMIM]Cl. Experiments were designed to find out the optimum processing parameters for degumming of eri silk by response surface methodology. The statistical software, Design-Expert 6.0 was used for regression analysis and graphical analysis of the responses obtained by running the set of designed experiments. Analysis of variance (ANOVA) was used to estimate the statistical parameters. The polynomial equation of quadratic order was employed to fit the experimental data. The quality and model terms were evaluated by F-test. Three dimensional surface plots were prepared to study the effect of variables on different responses. The optimum conditions for IL treatment were selected from predicted combinations and the experiments were repeated under these conditions to determine the reproducibility.

Keywords: silk degumming, ionic liquid, response surface methodology, ANOVA

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