A Study on the Factors Affecting Student Behavior Intention to Attend Robotics Courses at the Primary and Secondary School Levels

In order to explore the key factors affecting the robot program learning intention of school students, this study takes the technology acceptance model as the theoretical basis and invites 167 students from Jiading District of Shanghai as the research subjects. In the robot course, the model of school students on their learning behavior is constructed. By verifying the causal path relationship between variables, it is concluded that teachers can enhance students’ perceptual usefulness to robotics courses by enhancing subjective norms, entertainment perception, and reducing technical anxiety, such as focusing on the gradual progress of programming and analyzing learner characteristics. Students can improve perceived ease of use by enhancing self-efficacy. At the same time, robot hardware designers can optimize in terms of entertainment and interactivity, which will directly or indirectly increase the learning intention of the robot course. By changing these factors, the learning behavior of primary and secondary school students can be more sustainable.

Object Recognition Approach Based on Generalized Hough Transform and Color Distribution Serving in Generating Arabic Sentences

The recognition of the objects contained in images has always presented a challenge in the field of research because of several difficulties that the researcher can envisage because of the variability of shape, position, contrast of objects, etc. In this paper, we will be interested in the recognition of objects. The classical Hough Transform (HT) presented a tool for detecting straight line segments in images. The technique of HT has been generalized (GHT) for the detection of arbitrary forms. With GHT, the forms sought are not necessarily defined analytically but rather by a particular silhouette. For more precision, we proposed to combine the results from the GHT with the results from a calculation of similarity between the histograms and the spatiograms of the images. The main purpose of our work is to use the concepts from recognition to generate sentences in Arabic that summarize the content of the image.

‘Daily Speaking’: Designing an App for Construction of Language Learning Model Supporting ‘Seamless Flipped’ Environment

Seamless learning is becoming a research hotspot in recent years, and the emerging of micro-lectures, flipped classroom has strengthened the development of seamless learning. Based on the characteristics of the seamless learning across time and space and the course structure of the flipped classroom, and the theories of language learning, we put forward the language learning model which can support ‘seamless flipped’ environment (abbreviated as ‘S-F’). Meanwhile, the characteristics of the ‘S-F’ learning environment, the corresponding framework construction and the activity design of diversified corpora were introduced. Moreover, a language learning app named ‘Daily Speaking’ was developed to facilitate the practice of the language learning model in ‘S-F’ environment. In virtue of the learning case of Shanghai language, the rationality and feasibility of this framework were examined, expecting to provide a reference for the design of ‘S-F’ learning in different situations.

Vr-GIS and Ar-GIS In Education: A Case Study

ICT tools and platforms endorse more and more educational process. Many models and techniques for people to be educated and trained about specific topics and skills do exist, as classroom lectures with textbooks, computers, handheld devices and others. The choice to what extent ICT is applied within learning contexts is related to personal access to technologies as well as to the infrastructure surrounding environment. Among recent techniques, the adoption of Virtual Reality (VR) and Augmented Reality (AR) provides significant impulse in fully engaging users senses. In this paper, an application of AR/VR within Geographic Information Systems (GIS) context is presented. It aims to provide immersive environment experiences for educational and training purposes (e.g. for civil protection personnel), useful especially for situations where real scenarios are not easily accessible by humans. First acknowledgments are promising for building an effective tool that helps civil protection personnel training with risk reduction.

Analysis of the Influence of Reshoring on the Structural Behavior of Reinforced Concrete Beams

There is little published research about the influence of execution methods on structural behavior. Structural analysis is typically based on a constructed building, considering the actions of all forces under which it was designed. However, during construction, execution loads do not match those designed, and in some cases the loads begin to act when the concrete has not yet reached its maximum strength. Changes to structural element support conditions may occur, resulting in unforeseen alterations to the structure’s behavior. Shoring is an example of a construction process that, if executed improperly, will directly influence the structural performance, and may result in unpredicted cracks and displacements. The NBR 14931/2004 standard, which guides the execution of reinforced concrete structures, mentions that shoring must be executed in a way that avoids unpredicted loads and that it may be removed after previous analysis of the structure’s behavior by the professional responsible for the structure’s design. Differences in structural behavior are reduced for small spans. It is important to qualify and quantify how the incorrect placement of shores can compromise a structure’s safety. The results of this research allowed a more precise acknowledgment of the relationship between spans and loads, for which the influence of execution processes can be considerable, and reinforced that civil engineering practice must be performed with the presence of a qualified professional, respecting existing standards’ guidelines.

Factors Influencing Intention to Engage in Long-term Care Services among Nursing Aide Trainees and the General Public

Rapid aging and depopulation could lead to serious problems, including workforce shortages and health expenditure costs. The current and predicted future LTC workforce shortages could be a real threat to Taiwan’s society. By means of comparison of data from 144 nursing aide trainees and 727 general public, the main purpose of the present study was to determine whether there were any notable differences between the two groups toward engaging in LTC services. Moreover, this study focused on recognizing the attributes of the general public who had the willingness to take LTC jobs but continue to ride the fence. A self-developed questionnaire was designed based on Ajzen’s Theory of Planned Behavior model. After conducting exploratory factor analysis (EFA) and reliability analysis, the questionnaire was a reliable and valid instrument for both nursing aide trainees and the general public. The main results were as follows: Firstly, nearly 70% of nursing aide trainees showed interest in LTC jobs. Most of them were middle-aged female (M = 46.85, SD = 9.31), had a high school diploma or lower, had unrelated work experience in healthcare, and were mostly unemployed. The most common reason for attending the LTC training program was to gain skills in a particular field. The second most common reason was to obtain the license. The third and fourth reasons were to be interested in caring for people and to increase income. The three major reasons that might push them to leave LTC jobs were physical exhaustion, payment is bad, and being looked down on. Secondly, the variables that best-predicted nursing aide trainees’ intention to engage in LTC services were having personal willingness, perceived behavior control, with high school diploma or lower, and supported from family and friends. Finally, only 11.80% of the general public reported having interest in LTC jobs (the disapproval rating was 50% for the general public). In comparison to nursing aide trainees who showed interest in LTC settings, 64.8% of the new workforce for LTC among the general public was male and had an associate degree, 54.8% had relevant healthcare experience, 67.1% was currently employed, and they were younger (M = 32.19, SD = 13.19) and unmarried (66.3%). Furthermore, the most commonly reason for the new workforce to engage in LTC jobs were to gain skills in a particular field. The second priority was to be interested in caring for people. The third and fourth most reasons were to give back to society and to increase income, respectively. The top five most commonly reasons for the new workforce to quitting LTC jobs were listed as follows: physical exhaustion, being looked down on, excessive working hours, payment is bad, and excessive job stress.

Masquerade and “What Comes Behind Six Is More Than Seven”: Thoughts on Art History and Visual Culture Research Methods

In the 21st century, the disciplinary boundaries of past centuries that we often create through mainstream art historical classification, techniques and sources may have been eroded by visual culture, which seems to provide a more inclusive umbrella for the new ways artists go about the creative process and its resultant commodities. Over the past four decades, artists in Africa have resorted to new materials, techniques and themes which have affected our ways of research on these artists and their art. Frontline artists such as El Anatsui, Yinka Shonibare, Erasmus Onyishi are demonstrating that any material is just suitable for artistic expression. Most of times, these materials come with their own techniques/effects and visual syntax: a combination of materials compounds techniques, formal aesthetic indexes, halo effects, and iconography. This tends to challenge the categories and we lean on to view, think and talk about them. This renders our main stream art historical research methods inadequate, thus suggesting new discursive concepts, terms and theories. This paper proposed the Africanist eclectic methods derived from the dual framework of Masquerade Theory and What Comes Behind Six is More Than Seven. This paper shares thoughts/research on art historical methods, terminological re-alignments on classification/source data, presentational format and interpretation arising from the emergent trends in our subject. The outcome provides useful tools to mediate new thoughts and experiences in recent African art and visual culture.

Seismic Investigation on the Effect of Surface Structures and Twin Tunnel on the Site Response in Urban Areas

Site response has a profound effect on earthquake damages. Seismic interaction of urban tunnels with surface structures could also affect seismic site response. Here, we use FLAC 2D to investigate the interaction of a single tunnel and twin tunnels-surface structures on the site response. Soil stratification and properties are selected based on Line. No 7 of the Tehran subway. The effect of surface structure is considered in two ways: Equivalent surcharge and geometrical modeling of the structure. Comparison of the results shows that consideration of the structure geometry is vital in dynamic analysis and leads to the changes in the magnitude of displacements, accelerations and response spectrum. Therefore it is necessary for the surface structures to be wholly modeled and not just considered as a surcharge in dynamic analysis. The use of twin tunnel also leads to the reduction of dynamic residual settlement.

Classification of Health Risk Factors to Predict the Risk of Falling in Older Adults

Cognitive decline and frailty is apparent in older adults leading to an increased likelihood of the risk of falling. Currently health care professionals have to make professional decisions regarding such risks, and hence make difficult decisions regarding the future welfare of the ageing population. This study uses health data from The Irish Longitudinal Study on Ageing (TILDA), focusing on adults over the age of 50 years, in order to analyse health risk factors and predict the likelihood of falls. This prediction is based on the use of machine learning algorithms whereby health risk factors are used as inputs to predict the likelihood of falling. Initial results show that health risk factors such as long-term health issues contribute to the number of falls. The identification of such health risk factors has the potential to inform health and social care professionals, older people and their family members in order to mitigate daily living risks.

Evaluating of Bearing Capacity of Two Adjacent Strip Foundations Located around a Soil Slip

Selection of soil bearing capacity is an important issue that should be investigated under different conditions. The bearing capacity of foundation around of soil slope is based on the active and passive forces. On the other hand, due to extension of urban structures, it is inevitable to put the foundations together. Concerning the two cases mentioned above, investigating the behavior of adjacent foundations which are constructed besides soil slope is essential. It should be noted that, according to the conditions, the bearing capacity of adjacent foundations can be less or more than mat foundations. Also, soil reinforcement increases the bearing capacity of adjacent foundations, and the amount of its increase depends on the distance between foundations. In this research, based on numerical studies, a method is presented for evaluating ultimate bearing capacity of adjacent foundations at different intervals. In the present study, the effect of foundation width, the center to center distance of adjacent foundations and reinforced soil has been investigated on the bearing capacity of adjacent foundations beside soil slope. The results indicate that, due to interference of failure surfaces created under foundation, it depends on their intervals and the ultimate bearing capacity of foundation varies.

Bank Loans and the Business Cycle: The Case of the Czech Republic

This article aims to evaluate the impact of loans provided within the Czech banking sector on the growth of the Czech economy. The article is based on research of current scientific findings in respect to bank loans and economic development. The paper is based on data taken from the Czech Statistical Office on the development of the gross domestic product and data from the Czech National Bank on the development of loans from the period 2004-2015. Links between selected variables are tested using Granger causality tests. The results calculated confirm the hypothesis of the impact of the loans on economic growth, with a six-month delay. The results thus correspond to the standard economic findings and results of most previous studies.

Microclimate Variations in Rio de Janeiro Related to Massive Public Transportation

Urban public transportation in Rio de Janeiro is based on bus lines, powered by diesel, and four limited metro lines that support only some neighborhoods. This work presents an infrastructure built to better understand microclimate variations related to massive urban transportation in some specific areas of the city. The use of sensor nodes with small analytics capacity provides environmental information to population or public services. The analyses of data collected from a few small sensors positioned near some heavy traffic streets show the harmful impact due to poor bus route plan.

Improvement of Central Composite Design in Modeling and Optimization of Simulation Experiments

Simulation modeling can be used to solve real world problems. It provides an understanding of a complex system. To develop a simplified model of process simulation, a suitable experimental design is required to be able to capture surface characteristics. This paper presents the experimental design and algorithm used to model the process simulation for optimization problem. The CO2 liquefaction based on external refrigeration with two refrigeration circuits was used as a simulation case study. Latin Hypercube Sampling (LHS) was purposed to combine with existing Central Composite Design (CCD) samples to improve the performance of CCD in generating the second order model of the system. The second order model was then used as the objective function of the optimization problem. The results showed that adding LHS samples to CCD samples can help capture surface curvature characteristics. Suitable number of LHS sample points should be considered in order to get an accurate nonlinear model with minimum number of simulation experiments.

EEG-Based Screening Tool for School Student’s Brain Disorders Using Machine Learning Algorithms

Attention-Deficit/Hyperactivity Disorder (ADHD), epilepsy, and autism affect millions of children worldwide, many of which are undiagnosed despite the fact that all of these disorders are detectable in early childhood. Late diagnosis can cause severe problems due to the late treatment and to the misconceptions and lack of awareness as a whole towards these disorders. Moreover, electroencephalography (EEG) has played a vital role in the assessment of neural function in children. Therefore, quantitative EEG measurement will be utilized as a tool for use in the evaluation of patients who may have ADHD, epilepsy, and autism. We propose a screening tool that uses EEG signals and machine learning algorithms to detect these disorders at an early age in an automated manner. The proposed classifiers used with epilepsy as a step taken for the work done so far, provided an accuracy of approximately 97% using SVM, Naïve Bayes and Decision tree, while 98% using KNN, which gives hope for the work yet to be conducted.

Behavioral Response of Dogs to Interior Environment: An Exploratory Study on Design Parameters for Designing Dog Boarding Centers in Indian Context

Pet population in India is increasing phenomenally owing to the changes in urban lifestyle with increasing number of single professionals, single parents, delayed parenthood etc. The animal companionship as a means of reducing stress levels, deriving emotional support, and unconditional love provided by dogs are a few reasons attributed for increasing pet ownership. The consequence is the booming of the pet care products and dog care centers catering to the different requirements of rearing the pets. Dog care centers quite popular in tier 1 metros of India cater to the requirement of the dog owners providing space for the dogs in absence of the owner. However, it is often reported that the absence of the owner leads to destructive and exploratory behavior issues; the main being the anxiety disorders. In the above context, it becomes imperative for a designer to design dog boarding centers that help in reducing the separation anxiety in dogs keeping in mind the different interior design parameters. An exploratory research with focus group discussion is employed involving a group of dog owners, behaviorists, proprietors of day care as well as boarding centers, and veterinarians to understand their perception on the significance of different interior parameters of color, texture, ventilation, aroma therapy and acoustics as a means of reducing the stress levels in dogs sent to the boarding centers. The data collected is organized as thematic networks thus enabling the listing of the interior design parameters that needs to be considered in designing dog boarding centers. 

Scope, Relevance and Sustainability of Decentralized Renewable Energy Systems in Developing Economies: Imperatives from Indian Case Studies

‘Energy for all’, is a global issue of concern for the past many years. Despite the number of technological advancements and innovations, significant numbers of people are living without access to electricity around the world. India, an emerging economy, tops the list of nations having the maximum number of residents living off the grid, thus raising global attention in past few years to provide clean and sustainable energy access solutions to all of its residents. It is evident from developed economies that centralized planning and electrification alone is not sufficient for meeting energy security. Implementation of off-grid and consumer-driven energy models like Decentralized Renewable Energy (DRE) systems have played a significant role in meeting the national energy demand in developed nations. Cases of DRE systems have been reported in developing countries like India for the past few years. This paper attempts to profile the status of DRE projects in the Indian context with their scope and relevance to ensure universal electrification. Diversified cases of DRE projects, particularly solar, biomass and micro hydro are identified in different Indian states. Critical factors affecting the sustainability of DRE projects are extracted with their interlinkages in the context of developers, beneficiaries and promoters involved in such projects. Socio-techno-economic indicators are identified through similar cases in the context of DRE projects. Exploratory factor analysis is performed to evaluate the critical sustainability factors followed by regression analysis to establish the relationship between the dependent and independent factors. The generated EFA-Regression model provides a basis to develop the sustainability and replicability framework for broader coverage of DRE projects in developing nations in order to attain the goal of universal electrification with least carbon emissions.

Investigating the Pedestrian Willingness to Pay to Choose Appropriate Policies for Improving the Safety of Pedestrian Facilities

Road traffic accidents lead to a higher rate of death and injury, especially in vulnerable road users such as pedestrians. Improving the safety of facilities for pedestrians is a major concern for policymakers because of the high number of pedestrian fatalities and direct and indirect costs which are imposed to the society. This study focuses on the idea of determining the willingness to pay of pedestrians for increasing their safety while crossing the street. In this study, three different scenarios including crossing the street with zebra crossing facilities, crossing the street with zebra crossing facilities and installing a pedestrian traffic light and constructing a pedestrian bridge with escalator are presented. The research was conducted based on stated preferences method. The required data were collected from a questionnaire that consisted of three parts: pedestrian’s demographic characteristics, travel characteristics and scenarios. Four different payment amounts are presented for each scenario and a logit model has been built for each proposed payment. The results show that sex, age, education, average household income and individual salary have significant effect on choosing a scenario. Among the policies that have been mentioned through the questionnaire scenarios, the scenario of crossing the street with zebra crossing facilities and installing a traffic lights is the most frequent, with willingness to pay 10,000 Rials and the scenario of crossing the street with a zebra crossing with a willingness to pay 100,000 Rials having the least frequency. For all scenarios, as the payment is increasing, the willingness to pay decreases.

Effect of Silt Presence on Shear Strength Parameters of Unsaturated Sandy Soils

Direct shear test is widely used in soil mechanics experiment to determine the shear strength parameters of granular soils. For analysis of soil stability problems such as bearing capacity, slope stability and lateral pressure on soil retaining structures, the shear strength parameters must be known well. In the present study, shear strength parameters are determined in silty-sand mixtures. Direct shear tests are performed on 161 Firoozkooh sand with different silt content at a relative density of 70% in three vertical stress of 100, 150, and 200 kPa. Wet tamping method is used for soil sample preparation, and the results include diagrams of shear stress versus shear deformation and sample height changes against shear deformation. Accordingly, in different silt percent, the shear strength parameters of the soil such as internal friction angle and dilation angle are calculated and compared. According to the results, when the sample contains up to 10% silt, peak shear strength and internal friction angle have an upward trend. However, if the sample contains 10% to 50% of silt a downward trend is seen in peak shear strength and internal friction angle.

Simplified 3R2C Building Thermal Network Model: A Case Study

Whole building energy simulation models are widely used for predicting future energy consumption, performance diagnosis and optimum control.  Black box building energy modeling approach has been heavily studied in the past decade. The thermal response of a building can also be modeled using a network of interconnected resistors (R) and capacitors (C) at each node called R-C network. In this study, a model building, Case 600, as described in the “Standard Method of Test for the Evaluation of Building Energy Analysis Computer Program”, ASHRAE standard 140, is studied along with a 3R2C thermal network model and the ASHRAE clear sky solar radiation model. Although building an energy model involves two important parts of building component i.e., the envelope and internal mass, the effect of building internal mass is not considered in this study. All the characteristic parameters of the building envelope are evaluated as on Case 600. Finally, monthly building energy consumption from the thermal network model is compared with a simple-box energy model within reasonable accuracy. From the results, 0.6-9.4% variation of monthly energy consumption is observed because of the south-facing windows.

A Mixing Matrix Estimation Algorithm for Speech Signals under the Under-Determined Blind Source Separation Model

The separation of speech signals has become a research hotspot in the field of signal processing in recent years. It has many applications and influences in teleconferencing, hearing aids, speech recognition of machines and so on. The sounds received are usually noisy. The issue of identifying the sounds of interest and obtaining clear sounds in such an environment becomes a problem worth exploring, that is, the problem of blind source separation. This paper focuses on the under-determined blind source separation (UBSS). Sparse component analysis is generally used for the problem of under-determined blind source separation. The method is mainly divided into two parts. Firstly, the clustering algorithm is used to estimate the mixing matrix according to the observed signals. Then the signal is separated based on the known mixing matrix. In this paper, the problem of mixing matrix estimation is studied. This paper proposes an improved algorithm to estimate the mixing matrix for speech signals in the UBSS model. The traditional potential algorithm is not accurate for the mixing matrix estimation, especially for low signal-to noise ratio (SNR).In response to this problem, this paper considers the idea of an improved potential function method to estimate the mixing matrix. The algorithm not only avoids the inuence of insufficient prior information in traditional clustering algorithm, but also improves the estimation accuracy of mixing matrix. This paper takes the mixing of four speech signals into two channels as an example. The results of simulations show that the approach in this paper not only improves the accuracy of estimation, but also applies to any mixing matrix.