Artificial intelligence for BIM content management and delivery: Case study of association rule mining for construction detailing

The proliferation of Building Information Modeling (BIM) applications, in tandem with the extensive variation of building products, pose new demands on design and engineering firms to efficiently manage and reuse BIM content (i.e., data-rich parametric model objects and assembly details). Tasks such as classifying BIM objects, indexing them with meta-data (e.g., category), and searching digital libraries to load objects into models still plague practice with inefficient manual workflows. This research aims to improve the productivity of BIM content management and retrieval by developing an AI-backed BIM content recommender system. Using data from a case-study firm, this research extracted content from over 30,000 technical BIM views (e.g., plans, sections, details) in historical projects to build an unsupervised machine-learning prototype with association rule mining. This prototype explicated the strength of relationships among co-occurring BIM objects. Using this prototype as the backbone AI-engine in live BIM sessions, this research developed a context-aware recommender system that dynamically provides BIM users with a set of objects associable with their modeling context (e.g., type of view, existing objects in the model) and human–computer interactions (e.g., objects selected by the user). By mining association data from hundreds of historical projects, this development marks a departure from the existing prototypes that rely on explicit coding, recurring user input, or subjective ratings to recommend BIM content to users. The simulation and experimental implementation of this recommender system yielded high efficacy in predicting content needs and achieved significant savings in the time spent on conventional BIM workflows.     

Satellite-Based Water Quality Mapping from Sequential Simulation with Parameter Outlier Removal

The satellite-based regression model provides the data model that identifies water quality for inland and coastal waters. However, the satellite regression usually depends on the selection of observation, satellite data, and model type. A resampling simulation technique, such as sequential simulation using geographically weighted regression (GWR simulation), can be applied in generating multiple realizations for water quality estimation to reduce the sampling effect and consider spatial heterogeneity. Traditional models often result in considerable underestimation in extreme observations. The GWR simulation provides the best goodness of fit and spatial varying relationship between observed water quality and remote sensing considering parameter outlier and noise removal for parameter stability. This simulation model can increase the sampling diversity from various observations and reduce the neighboring effects of observations using outlier and noise removal. The model that handles spatial uncertainty and heterogeneity is a novel tool for inferring the characteristics of water quality from a series of sample subsets.

     

Electrochemical investigation of La0.4Sr0.6TiO3 synthesized in air for SOFC application

Journal of Applied Electrochemistry - La-doped titanate materials have been widely investigated as alternative Ni-free anodes for solid oxide fuel cells (SOFCs). In this study, La0.4Sr0.6TiO3 (LST)...     

Model checking response times in Networked Automation Systems using jitter bounds

Response time (RT) of Networked Automation Systems (NAS) is affected by timing imperfections induced due to the network, computing and hardware components. Guaranteeing RT in the presence of such timing imperfections is essential for building dependable NAS, and to avoid costly upgrades after deployment in industries.This investigation proposes a methodology and work-flow that combines modelling, simulation, verification, experiments, and software tools to verify the RT of the NAS during the design, rather than after deployment. The RT evaluation work-flow has three phases: model building, modelling and verification. During the model building phase component reaction times are specified and their timing performance is measured by combining experiments with simulation. During the modelling phase, component based mathematical models that capture the network architecture and inter-connection are proposed. Composition of the component models gives the NAS model required for studying the RT performance on system level. Finally, in the verification step, the NAS formal models are abstracted as UPPAAL timed automata with their timing interfaces. To model timing interfaces, the action patterns, and their timing wrapper are proposed. The formal model of high level of abstraction is used to verify the total response time of the NAS where the reactions to be verified are specified using a subset of timed computation tree logic (TCTL) in UPPAAL model checker. The proposed approach is illustrated on an industrial steam boiler deployment.     

The impact of global dispersion on coordination,team performance and software quality – A systematic literature review

ContextGlobal software development (GSD) contains different context setting dimensions, which are essential for effective teamwork and success of projects. Although considerable research effort has been made in this area, as yet, no agreement has been reached about the impact of these dispersion dimensions on team coordination and project outcomes.ObjectiveThis paper summarizes empirical evidence on the impact of global dispersion dimensions on coordination, team performance and project outcomes.MethodWe performed a systematic literature review of 46 publications from 25 journals and 19 conference and workshop proceedings, which were published between 2001 and 2013. Thematic analysis was used to identify global dimensions and their measures. Vote counting was used to decide on the impact trends of dispersion dimensions on team performance and software quality.ResultsGlobal dispersion dimensions are consistently conceptualized, but quantified in many different ways. Different dispersion dimensions are associated with a distinct set of coordination challenges. Overall, geographical dispersion tends to have a negative impact on team performance and software quality. Temporal dispersion tends to have a negative impact on software quality, but its impact on team performance is inconsistent and can be explained by type of performance.ConclusionFor researchers, we reveal several opportunities for future research, such as coordination challenges in inter-organizational software projects, impact of processes and practices mismatches on project outcomes, evolution of coordination needs and mechanism over time and impact of dispersion dimensions on open source project outcomes. For practitioners, they should consider the tradeoff between cost and benefits while dispersing tasks, alignment impact of dispersion dimensions with individual and organizational objectives, coordination mechanisms as situational approaches and collocation of development activities of high quality demand components in GSD projects.     

Influence of groove type on welding-induced residual stress,deformation and width of sensitization region in a SUS304 steel butt welded joint

To join a medium or thick plate weldment with a full penetration, a groove is usually prepared in the space between two sections of metal. Because weld metal needs to be deposited within the groove to form the joint, it is expected that different groove type will require different heat input, which may consequently have influence on welding residual stress and deformation. Generally, different groove corresponds to different bead layout, so it can be foreseen that the groove type has a significant effect on temperature history, shape and size of heat affected zone, and region of sensitization in certain alloys such as austenitic stainless steel. The influences of groove type on residual stress, angular distortion and width of sensitization region in a SUS304 butt-welded joint were investigated by means of numerical simulation and experiment. Based on ABAQUS code, a computational approach with considering thermo-mechanical coupling behaviors, moving heat source, strain hardening and annealing effect was developed to simulate temperature profile, stress field and deformation in multi-pass joint. Welding temperature cycles, residual stress distributions and deformations in V, K and X groove joints were calculated through using the proposed computational procedure. Meanwhile, experiments were carried out to obtain residual stress distributions and angular distortions. Through comparing the numerical results and the measured data, the effectiveness and accuracy of the developed computational approach were verified. The simulation results show that groove type has a significant influence on welding residual stress distribution, angular distortion and width of sensitization region.     

Categorization of risk factors for distributed agile projects

ContextOrganizations combine agile approach and Distributed Software Development (DSD) in order to develop better quality software solutions in lesser time and cost. It helps to reap the benefits of both agile and distributed development but pose significant challenges and risks. Relatively scanty evidence of research on the risks prevailing in distributed agile development (DAD) has motivated this study.ObjectiveThis paper aims at creating a comprehensive set of risk factors that affect the performance of distributed agile development projects and identifies the risk management methods which are frequently used in practice for controlling those risks.MethodThe study is an exploration of practitioners’ experience using constant comparison method for analyzing in-depth interviews of thirteen practitioners and work documents of twenty-eight projects from thirteen different information technology (IT) organizations. The field experience was supported by extensive research literature on risk management in traditional, agile and distributed development.ResultsAnalysis of qualitative data from interviews and project work documents resulted into categorization of forty-five DAD risk factors grouped under five core risk categories. The risk categories were mapped to Leavitt’s model of organizational change for facilitating the implementation of results in real world. The risk factors could be attributed to the conflicting properties of DSD and agile development. Besides that, some new risk factors have been experienced by practitioners and need further exploration as their understanding will help the practitioners to act on time.ConclusionOrganizations are adopting DAD for developing solutions that caters to the changing business needs, while utilizing the global talent. Conflicting properties of DSD and agile approach pose several risks for DAD. This study gives a comprehensive categorization of the risks faced by the practitioners in managing DAD projects and presents frequently used methods to reduce their impact. The work fills the yawning research void in this field.     

Virtual screening of eighteen million compounds against dengue virus: Combined molecular docking and molecular dynamics simulations study

Dengue virus is a major issue of tropical and sub-tropical regions. Dengue virus has been the cause behind the major alarming epidemics in the history with mass causalities from the decades. Unavailability of on-shelf drugs for the prevention of further proliferation of virus inside the human body results in immense number of deaths each year. This issue necessitates the design of novel anti-dengue drug. The protease enzyme pathway is the critical target for drug design due to its significance in the replication, survival and other cellular activities of dengue virus. Therefore, approximately eighteen million compounds from the ZINC database have been virtually screened against nonstructural protein 3 (NS3). The incremental construction algorithm of Glide docking program has been used with its features high throughput virtual screening (HTVS), standard precision (SP), extra precision (XP) and in combination of Prime module, induced fit docking (IFD) approach has also been applied. Five top-ranked compounds were then selected from the IFD results with better predicted binding energies with the catalytic triad residues (His51, Asp75, and Ser135) that may act as potential inhibitors for the underlying target protease enzyme. The top-ranked compounds ZINC95518765, ZINC44921800, ZINC71917414, ZINC39500661, ZINC36681949 have shown the predicted binding energies of −7.55, −7.36, −8.04, −8.41, −9.18 kcal/mol, respectively, forming binding interactions with three catalytically important amino acids. Top-docking poses of compounds are then used in molecular dynamics (MD) simulations. In computational studies, our proposed compounds confirm promising results against all the four serotypes of dengue virus, strengthening the opportunity of these compounds to work as potential on-shelf drugs against dengue virus. Further experimentation on the proposed compounds can result in development of strong inhibitors.