E-Testing Construction Support System with some Prediction Tools

Non

Software Verification and Graph Similarity for Automated Evaluation of Students' Assignments

In this paper we promote introducing software verification and control flow graph similarity measurement in automated evaluation of students' programs. We present a new grading framework that merges results obtained by combination of these two approaches with results obtained by automated testing, leading to improved quality and precision of automated grading. These two approaches are also useful in providing a comprehensible feedback that can help students to improve the quality of their programs We also present our corresponding tools that are publicly available and open source. The tools are based on LLVM low-level intermediate code representation, so they could be applied to a number of programming languages. Experimental evaluation of the proposed grading framework is performed on a corpus of university students' programs written in programming language C. Results of the experiments show that automatically generated grades are highly correlated with manually determined grades suggesting that the presented tools can find real-world applications in studying and grading

High-Tech Tools for Teaching Physics: the Physics Education Technology Project

This article appeared in the Journal of Online Teaching and Learning September 15, 2006.This paper introduces a new suite of computer simulations from the Physics Education Technology (PhET) project, identifies features of these educational tools, and demonstrates their utility. We compare the use of PhET simulations to the use of more traditional educational resources in lecture, laboratory, recitation and informal settings of introductory college physics. In each case we demonstrate that simulations are as productive, or more productive, for developing student conceptual understanding as real equipment, reading resources, or chalk-talk lectures. We further identify six key characteristic features of these simulations that begin to delineate why these are productive tools. The simulations: support an interactive approach, employ dynamic feedback, follow a constructivist approach, provide a creative workplace, make explicit otherwise inaccessible models or phenomena, and constrain students productively

CAN CHANGE PREDICTION HELP PRIORITISE REDESIGN WORK IN FUTURE ENGINEERING SYSTEMS?

Future design environments will necessitate improved management of the propagation and impacts of changes. To ascertain whether change prediction can assist in making better work prioritisation decisions, this paper develops a new simulation approach and applies it to a model of a complex aerospace product, which was elicited from industry. We use an accepted technique to generate potential change propagation trees and apply Monte Carlo methods to generate a sample space within which multiple scheduling policies could be evaluated and compared. The experiments reveal that poor coordination of change activity can result in significant process inefficiencies, that the potential for inefficiency increases for larger change networks, and that a modest ability to accurately predict change propagation in the specific case at hand could have a dramatic effect in reducing unnecessary rework. The experiments also suggest that the capability of predicting multiple steps of change propagation would provide only minimal additional improvement.International Design Conference - DESIGN 201

Evaluating the impact of an enhanced energy performance standard on load-bearing masonry domestic construction: Understanding the gap between designed and real performance: lessons from Stamford Brook.

This report is aimed at those with interests in the procurement, design and construction of new dwellings both now and in the coming years as the Government’s increasingly stringent targets for low and zero carbon housing approach. It conveys the results of a research project, carried out between 2001 and 2008, that was designed to evaluate the extent to which low carbon housing standards can be achieved in the context of a large commercial housing development. The research was led by Leeds Metropolitan University in collaboration with University College London and was based on the Stamford Brook development in Altrincham, Cheshire. The project partners were the National Trust, Redrow and Taylor Wimpey and some 60 percent of the planned 700 dwelling development has been completed up to June 2008. As the UK house building industry and its suppliers grapple with the challenges of achieving zero carbon housing by 2016, the lessons arising from this project are timely and of considerable value. Stamford Brook has demonstrated that designing masonry dwellings to achieve an enhanced energy standard is feasible and that a number of innovative approaches, particularly in the area of airtightness, can be successful. The dwellings, as built, exceed the Building Regulations requirements in force at the time but tests on the completed dwellings and longer term monitoring of performance has shown that, overall, energy consumption and carbon emissions, under standard occupancy, are around 20 to 25 percent higher than design predictions. In the case of heat loss, the discrepancy can be much higher. The report contains much evidence of considerable potential but points out that realising the design potential requires a fundamental reappraisal of processes within the industry from design and construction to the relationship with its supply chain and the development of the workforce. The researchers conclude that, even when builders try hard, current mainstream technical and organisational practices together with industry cultures present barriers to consistent delivery of low and zero carbon performance. They suggest that the underlying reasons for this are deeply embedded at all levels of the house building industry. They point out also that without fundamental change in processes and cultures, technological innovations, whether they be based on traditional construction or modern methods are unlikely to reach their full potential. The report sets out a series of wide ranging implications for new housing in the UK, which are given in Chapter 14 and concludes by firmly declaring that cooperation between government, developers, supply chains, educators and researchers will be crucial to improvement. The recommendations in this report are already being put into practice by the researchers at Leeds Metropolitan University and University College London in their teaching and in further research projects. The implications of the work have been discussed across the industry at a series of workshops undertaken in 2008 as part of the LowCarb4Real project (see http://www.leedsmet.ac.uk/as/cebe/projects/lowcarb4real/index.htm). In addition, the learning is having an impact on the work of the developers (Redrow and Taylor Wimpey) who, with remarkable foresight and enthusiasm, hosted the project. This report seeks to make the findings more widely available and is offered for consideration by everyone who has a part to play in making low and zero carbon housing a reality

Electricity from photovoltaic solar cells: Flat-Plate Solar Array Project final report. Volume VI: Engineering sciences and reliability

The Flat-Plate Solar Array (FSA) Project, funded by the U.S. Government and managed by the Jet Propulsion Laboratory, was formed in 1975 to develop the module/array technology needed to attain widespread terrestrial use of photovoltaics by 1985. To accomplish this, the FSA Project established and managed an Industry, University, and Federal Government Team to perform the needed research and development. This volume of the series of final reports documenting the FSA Project deals with the Project's activities directed at developing the engineering technology base required to achieve modules that meet the functional, safety and reliability requirements of large-scale terrestrial photovoltaic systems applications. These activities included: (1) development of functional, safety, and reliability requirements for such applications; (2) development of the engineering analytical approaches, test techniques, and design solutions required to meet the requirements; (3) synthesis and procurement of candidate designs for test and evaluation; and (4) performance of extensive testing, evaluation, and failure analysis to define design shortfalls and, thus, areas requiring additional research and development. During the life of the FSA Project, these activities were known by and included a variety of evolving organizational titles: Design and Test, Large-Scale Procurements, Engineering, Engineering Sciences, Operations, Module Performance and Failure Analysis, and at the end of the Project, Reliability and Engineering Sciences. This volume provides both a summary of the approach and technical outcome of these activities and provides a complete Bibliography (Appendix A) of the published documentation covering the detailed accomplishments and technologies developed

A novel improved model for building energy consumption prediction based on model integration

Building energy consumption prediction plays an irreplaceable role in energy planning, management, and conservation. Constantly improving the performance of prediction models is the key to ensuring the efficient operation of energy systems. Moreover, accuracy is no longer the only factor in revealing model performance, it is more important to evaluate the model from multiple perspectives, considering the characteristics of engineering applications. Based on the idea of model integration, this paper proposes a novel improved integration model (stacking model) that can be used to forecast building energy consumption. The stacking model combines advantages of various base prediction algorithms and forms them into “meta-features” to ensure that the final model can observe datasets from different spatial and structural angles. Two cases are used to demonstrate practical engineering applications of the stacking model. A comparative analysis is performed to evaluate the prediction performance of the stacking model in contrast with existing well-known prediction models including Random Forest, Gradient Boosted Decision Tree, Extreme Gradient Boosting, Support Vector Machine, and K-Nearest Neighbor. The results indicate that the stacking method achieves better performance than other models, regarding accuracy (improvement of 9.5%–31.6% for Case A and 16.2%–49.4% for Case B), generalization (improvement of 6.7%–29.5% for Case A and 7.1%-34.6% for Case B), and robustness (improvement of 1.5%–34.1% for Case A and 1.8%–19.3% for Case B). The proposed model enriches the diversity of algorithm libraries of empirical models