Reliability Improvement On Feasibility Study For Selection Of Infrastructure Projects Using Data Mining And Machine Learning

With the progressive development of infrastructure construction, conventional analytical methods such as correlation index, quantifying factors, and peer review are no longer satisfactory in support for decision-making of implementing an infrastructure project in the age of big data. This study proposes using a mathematical model named Fuzzy-Neural Comprehensive Evaluation Model (FNCEM) to improve the reliability of the feasibility study of infrastructure projects by using data mining and machine learning. Specifically, the data collection on time-series data, including traffic videos (278 Gigabytes) and historical weather data, uses transportation cameras and online searching, respectively. Meanwhile, the researcher sent out a questionnaire for the collection of the public opinions upon the influencing factors that an infrastructure project may have. Then, this model implements the backpropagation Artificial Neural Network (BP-ANN) algorithm to simulate traffic flows and generate outputs as partial quantitative references for evaluation. The traffic simulation outputs used as partial inputs to the Analytic Hierarchy Process (AHP) based Fuzzy logic module of the system for the determination of the minimum traffic flows that a construction scheme in corresponding feasibility study should meet. This study bases on a real scenario of constructing a railway-crossing facility in a college town. The research results indicated that BP-ANN was well applied to simulate 15-minute small-scale pedestrian and vehicle flow with minimum overall logarithmic mean squared errors (Log-MSE) of 3.80 and 5.09, respectively. Also, AHP-based Fuzzy evaluation significantly decreased the evaluation subjectivity of selecting construction schemes by 62.5%. It concluded that the FNCEM model has strong potentials of enriching the methodology of conducting a feasibility study of the infrastructure project

Educational Technology Topic Guide

This guide aims to contribute to what we know about the relationship between educational technology (edtech) and educational outcomes by addressing the following overarching question: What is the evidence that the use of edtech, by teachers or students, impacts teaching and learning practices, or learning outcomes? It also offers recommendations to support advisors to strengthen the design, implementation and evaluation of programmes that use edtech. We define edtech as the use of digital or electronic technologies and materials to support teaching and learning. Recognising that technology alone does not enhance learning, evaluations must also consider how programmes are designed and implemented, how teachers are supported, how communities are developed and how outcomes are measured (see http://tel.ac.uk/about-3/, 2014). Effective edtech programmes are characterised by: a clear and specific curriculum focus the use of relevant curriculum materials a focus on teacher development and pedagogy evaluation mechanisms that go beyond outputs. These findings come from a wide range of technology use including: interactive radio instruction (IRI) classroom audio or video resources accessed via teachers’ mobile phones student tablets and eReaders computer-assisted learning (CAL) to supplement classroom teaching. However, there are also examples of large-scale investment in edtech – particularly computers for student use – that produce limited educational outcomes. We need to know more about: how to support teachers to develop appropriate, relevant practices using edtech how such practices are enacted in schools, and what factors contribute to or mitigate against successful outcomes. Recommendations: 1. Edtech programmes should focus on enabling educational change, not delivering technology. In doing so, programmes should provide adequate support for teachers and aim to capture changes in teaching practice and learning outcomes in evaluation. 2. Advisors should support proposals that further develop successful practices or that address gaps in evidence and understanding. 3. Advisors should discourage proposals that have an emphasis on technology over education, weak programmatic support or poor evaluation. 4. In design and evaluation, value-for-money metrics and cost-effectiveness analyses should be carried out

APPLICATION OF HYBRID DIBR-FUCOM-LMAW-BONFERRONI-GREY-EDAS MODEL IN MULTICRITERIA DECISION-MAKING

The selection of unmanned aerial vehicles for different purposes is a frequent topic of research. This paper presents a hybrid model of an unmanned aerial vehicle (UAV) selection using the Defining Interrelationships Between Ranked criteria (DIBR), Full Consistency Method (FUCOM), Logarithm Methodology of Additive Weights (LMAW) and grey - Evaluation based on Distance from Average Solution (G-EDAS) methods. The above-mentioned model is tested and confirmed in a case study. First of all, in the paper are defined the criteria conditioning the selection, and then with the help of experts and by applying the DIBR, FUCOM and LMAW methods, the weight coefficients of the criteria are determined. The final values of the weight coefficients are obtained by aggregating the values of the criteria weights from all the three methods using the Bonferroni aggregator. Ranking and selection of the optimal UAV from twenty-three defined alternatives is carried out using the G-EDAS method. Sensitivity analysis confirmed a high degree of consistency of the solutions obtained using other MCDM methods, as well as changing the criteria weight coefficients. The proposed model has proved to be stable; its application is also possible in other areas and it is a reliable tool for decision-makers during the selection process

A Review of Multi-Criteria Assessment of the Social Sustainability of Infrastructures

[EN] Nowadays multi-criteria methods enable non-monetary aspects to be incorporated into the assessment of infrastructure sustainability. Yet evaluation of the social aspects is still neglected and the multi-criteria assessment of these social aspects is still an emerging topic. Therefore, the aim of this article is to review the current state of multi-criteria infrastructure assessment studies that include social aspects. The review includes an analysis of the social criteria, participation and assessment methods. The results identify mobility and access, safety and local development among the most frequent criteria. The Analytic Hierarchy Process and Simple Additive Weighting methods are the most frequently used. Treatments of equity, uncertainty, learning and consideration of the context, however, are not properly analyzed yet. Anyway, the methods for implementing the evaluation must guarantee the social effect on the result, improvement of the representation of the social context and techniques to facilitate the evaluation in the absence of information.This research was funded by the Government of Chile under the Doctoral Fellowship Program Abroad (grant CONICYT-2015/72160059), the project DIUFRO DI14-0096 and the Spanish Ministry of Economy and Competitiveness along with FEDER funding (Projects BIA2014-56574-R and BIA2017-85098-R).Sierra-Varela, LA.; Yepes, V.; Pellicer, E. (2018). A Review of Multi-Criteria Assessment of the Social Sustainability of Infrastructures. Journal of Cleaner Production. 187:496-513. https://doi.org/10.1016/j.jclepro.2018.03.022S49651318

Design of a Problem-Based Learning Pain and Palliative Care Elective Course

Objective To implement and evaluate a problem-based learning (PBL) pain and palliative care elective course to develop studentsʼ pain and symptom management pharmacotherapy knowledge, clinical reasoning process, and self-directed learning skills. Methods Each week students received a patient case to independently develop an assessment and plan for each pain and symptom management problem. During class the students discussed their findings within small groups in preparation for a large-group discussion with the instructor. Studentsʼ course grades were based on weekly pre-class case preparation, individual case studies, and self-reflection questions. To assess knowledge gained over the semester a free-response pre- and post-course test was given. Results Twenty-five students enrolled in this course. A t-test comparison of the pre- and post-tests yielded a significant difference between the pre- and post-test scores (p \u3c 0.001), with the mean score for the tests increasing from 9.6 (out of 20 points) on the pre-test to 14.1 on the post-test. Pearsonʼs correlation coefficient between the pre- and post-test was 0.45, indicating increased scores were not a result of improvement only among the strong students. The normalized gain \u3cg\u3e was 0.43. The average score for each individual case study was slightly more than 80%. Four themes were noted in the studentsʼ self-reflections including patient/family goals of care, individualization of patient care and contrast to curative treatment, improved comfort with “gray therapeutic areas,” and advantages and disadvantages of problem-based learning. Conclusions Students demonstrated improved pain and symptom management pharmacotherapy knowledge, clinical reasoning process, and self-directed learning skills after course completion. The skills developed by students will benefit them in future clinical practice. Additional studies are needed to assess the long-term impact of the skills developed in this course

Competitive Intelligence and Academic Entrepreneurship as Innovative Vectors of a Resilient, Business-Oriented Education

Purpose – The present paper substantiates that the concepts of competitive intelligence and academic entrepreneurship are genuinely connected to the modern society and, through their perpetual and versatile evolution, have an important role in moving the development on the right way. Design/methodology/approach – Their evolutive is completed by a comparative analysis as appropriate method to point out similarities and differences and identify the way their application may serve innovation as a tool for those activating in the related domains of education, within our highly dynamic world. Findings – The development of the concepts is meant to link and accelerate the technological and operational innovation to a highly competitive academic environment, business-oriented, as a contribution to its wide potential for profit. Originality/value – The correlation between the two concepts provides an innovative tool able to serve as a platform helping the competitive intelligence, as design and functions, for any academic entrepreneurship business-oriented