A knowledge based system for valuing variations in civil engineering works: a user centred approach

There has been much evidence that valuing variations in construction projects can lead to conflicts and disputes leading to loss of time, efficiency, and productivity. One of the reasons for these conflicts and disputes concerns the subjectivity of the project stakeholders involved in the process. One way to minimise this is to capture and collate the knowledge and perceptions of the different parties involved in order to develop a robust mechanism for valuing variations. Focusing on the development of such a mechanism, the development of a Knowledge Based System (KBS) for valuing variations in civil engineering work is described. Evaluation of the KBS involved demonstration to practitioners in the construction industry to support the contents of the knowledge base and perceived usability and acceptance of the system. Results support the novelty, contents, usability, and acceptance of the system, and also identify further potential developments of the KBS

Project:Filter - using applied games to engage secondary schoolchildren with public policy

Applied games present a twenty-first-century method of consuming information for a specific purpose beyond pure entertainment. Objectives such as awareness and engagement are often used as intended outcomes of applied games in alignment with strategic, organizational, or commercial purposes. Applied games were highlighted as an engagement-based outcome to explore noPILLS, a pan-European policy research project which presented policy pointers and suggested methods of interventions for reducing micropollution within the wastewater treatment process. This paper provides an assessment of a video game which was developed for the purpose of public engagement with policy-based research. The video game, Project:Filter, was developed as a means of communicating noPILLS to secondary school children in Scotland as part of a classroom-based activity. Knowledge development and engagement were identified using Interpretative Phenomenological Analysis to evidence topical awareness, depth of understanding, and suggested methods of intervention. Analysis of observations also provided insights into challenges surrounding logistics, pedagogy, social interactions, learning, and gender as contributing factors to the schoolchildren’s experiences of Project:Filter. The intention of this paper is two-fold: firstly, to provide an example of developing video games from policy-based research; and secondly, to suggest methods of phenomenological assessment for identifying play-based engagement

Learning and Interpreting Multi-Multi-Instance Learning Networks

We introduce an extension of the multi-instance learning problem where examples are organized as nested bags of instances (e.g., a document could be represented as a bag of sentences, which in turn are bags of words). This framework can be useful in various scenarios, such as text and image classification, but also supervised learning over graphs. As a further advantage, multi-multi instance learning enables a particular way of interpreting predictions and the decision function. Our approach is based on a special neural network layer, called bag-layer, whose units aggregate bags of inputs of arbitrary size. We prove theoretically that the associated class of functions contains all Boolean functions over sets of sets of instances and we provide empirical evidence that functions of this kind can be actually learned on semi-synthetic datasets. We finally present experiments on text classification, on citation graphs, and social graph data, which show that our model obtains competitive results with respect to accuracy when compared to other approaches such as convolutional networks on graphs, while at the same time it supports a general approach to interpret the learnt model, as well as explain individual predictions.Comment: JML

Learning dispositif and emotional attachment:a preliminary international investigation

This research investigated the significance of learning dispositif (LD) and emotional attachment (EA) on perceived learning success (LS) across a diaspora of Western, Russian, Asian, Middle Eastern and Chinese student cohorts. Foucault’s LD captures the disparate socio-cultural contexts, institutional milieus and more or less didactic teaching styles that moderate learning. EA is a multi-dimensional notion involving affective bonds that emerged in child psychology and spread to marketing and other fields. The sequential explanatory research reviewed the learning and EA literatures and generated an LD–EA framework to structure the quantitative phase of its mixed investigations. In 2017 and 2018, the research collected 150 responses and used a range of statistical techniques for quantitative analysis. It found that LS varied significantly across cohorts, intimating that dispositifs influence learning. Nonparametric analysis suggested that EA also influenced learning, but regressions were inconclusive. Exploratory techniques hint at a dynamic mix of emotional or cognitive motivations during the student learning journey, involving structural breaks in student/instructor relationships. Cluster analysis identified distinct student groupings, linked to years of learning. Separately, qualitative analysis of open-ended survey questions and expert interviews intimates that frequent teacher interactions can increase EA. The synthesis of quantitative with qualitative results and pedagogical reflection suggests that LD and EA both influence learning in a complex, dynamic system. The key constituents for EA are Affection, Connection, Social Presence (SP), Teaching Presence (TP) and Flow but student emotional engagement is conditioned by the socio-cultural milieu (LD) and associated factors like relationships and trust. Unlike in the Community of Learning framework, in the EA framework Cognitive Presence (CP) is an outcome of the interaction between these EA constituents, associated factors and the socio-cultural milieu. Finally, whilst awareness of culture and emotions is a useful pedagogical consideration, learning mainstays remain inclusive educational systems that identify student needs and support well-designed programmes. Within these, scaffolded modules should include a variety of engaging learning activities with non-threatening formative and trustworthy summative feedback. We acknowledge some statistical study limitations, but its tentative findings make a useful preliminary contribution

The internet: strategy and boundaries of the firm

Many advantages have been ascribed to the Internet. Although it lacks the necessary elements to be regarded as a strategic resource, the Internet seems to be a useful tool to provide support for business strategies.In this work we discuss how the Internet can be used to support the development of capabilities and define firm boundaries. Using a sample of Spanish firms, empirically analysed, we find positive relationships between the use of the Internet and product differentiation, as well as the introduction of organizational changes. In addition, we present evidence that the Internet reduces both internal coordination costs and transaction costs as a result of the positive relationships found between the use of the Internet, the degree of vertical integration and the establishment of technological agreements with suppliers and customers

The DEEP2 Galaxy Redshift Survey: Redshift Identification of Single-Line Emission Galaxies

We present two methods for determining spectroscopic redshifts of galaxies in the DEEP2 survey which display only one identifiable feature, an emission line, in the observed spectrum ("single-line galaxies"). First, we assume each single line is one of the four brightest lines accessible to DEEP2: Halpha, [OIII] 5007, Hbeta, or [OII] 3727. Then, we supplement spectral information with BRI photometry. The first method, parameter space proximity (PSP), calculates the distance of a single-line galaxy to galaxies of known redshift in (B-R), (R-I), R, observed wavelength parameter space. The second method is an artificial neural network (ANN). Prior information, such as allowable line widths and ratios, rules out one or more of the four lines for some galaxies in both methods. Based on analyses of evaluation sets, both methods are nearly perfect at identifying blended [OII] doublets. Of the lines identified as Halpha in the PSP and ANN methods, 91.4% and 94.2% respectively are accurate. Although the methods are not this accurate at discriminating between [OIII] and Hbeta, they can identify a single line as one of the two, and the ANN method in particular unambiguously identifies many [OIII] lines. From a sample of 640 single-line spectra, the methods determine the identities of 401 (62.7%) and 472 (73.8%) single lines, respectively, at accuracies similar to those found in the evaluation sets.Comment: 11 pages, 6 figures, accepted to Ap