A generic framework for the development of standardised learning objects within the discipline of construction management

E-learning has occurred in the academic world in different forms since the early 1990s. Its use varies from interactive multimedia tools and simulation environments to static resources within learning management systems. E-learning tools and environments are no longer criticised for their lack of use in higher education in general and within the construction domain in particular. The main criticism, however, is that of reinventing the wheel in order to create new learning environments that cater for different educational needs. Therefore, sharing educational content has become the focus of current research, taking e-learning into a whole new era of developments. This era is enabled by the emergence of new technologies (online and wireless) and the development of educational standards, such as SCORM (Sharable Content Object Reference Model) and LOM (Learning Object Metadata) for example. Accordingly, the broad definition of the construction domain and the interlocking nature of subjects taught within this domain, makes the concept of sharing content most appealing. This paper proposes a framework developed to describe the various steps required in order to enable the application of e-learning metadata standards and ontology for sharable learning objects to serve the construction discipline. The paper further describes the application of the proposed framework to a case study for developing an online environment for learning objects that are standardised, sharable, transparent and that cater for the needs of learners, educators and curricula developers in Construction Management. Based on the framework, a learning objects repository is developed incorporating educational and web standards. The repository manages objects as well as metadata using ontology and offers a set of services such as storing, retrieving and searching of learning objects using Semantic Web technologies. Thus, it increases the reusability, sharability and interoperability of learning objects

A mosaic of eyes

Autonomous navigation is a traditional research topic in intelligent robotics and vehicles, which requires a robot to perceive its environment through onboard sensors such as cameras or laser scanners, to enable it to drive to its goal. Most research to date has focused on the development of a large and smart brain to gain autonomous capability for robots. There are three fundamental questions to be answered by an autonomous mobile robot: 1) Where am I going? 2) Where am I? and 3) How do I get there? To answer these basic questions, a robot requires a massive spatial memory and considerable computational resources to accomplish perception, localization, path planning, and control. It is not yet possible to deliver the centralized intelligence required for our real-life applications, such as autonomous ground vehicles and wheelchairs in care centers. In fact, most autonomous robots try to mimic how humans navigate, interpreting images taken by cameras and then taking decisions accordingly. They may encounter the following difficulties

Harnessing the Power of Many: Extensible Toolkit for Scalable Ensemble Applications

Many scientific problems require multiple distinct computational tasks to be executed in order to achieve a desired solution. We introduce the Ensemble Toolkit (EnTK) to address the challenges of scale, diversity and reliability they pose. We describe the design and implementation of EnTK, characterize its performance and integrate it with two distinct exemplar use cases: seismic inversion and adaptive analog ensembles. We perform nine experiments, characterizing EnTK overheads, strong and weak scalability, and the performance of two use case implementations, at scale and on production infrastructures. We show how EnTK meets the following general requirements: (i) implementing dedicated abstractions to support the description and execution of ensemble applications; (ii) support for execution on heterogeneous computing infrastructures; (iii) efficient scalability up to O(10^4) tasks; and (iv) fault tolerance. We discuss novel computational capabilities that EnTK enables and the scientific advantages arising thereof. We propose EnTK as an important addition to the suite of tools in support of production scientific computing

Lurking and learning: Making learning visible in a Virtual Design Studio

This paper explores certain types of student behaviour in design courses presented through an online distance learning environment and using a virtual design studio. It demonstrates that types of behaviour often considered to be passive, and therefore negative or less valuable than obviously active behaviours, can be significant evidence of student learning. Specifically, viewing other students’ work is demonstrated to be a stronger (or equal) correlation of student success compared to any other behaviour measured in the virtual design studios studied. It is hypothesised that this activity is part of a larger set of social learning behaviours that contribute to a general social press or ‘ecology’ of studio learning. This finding has important implications for the design and implementation of virtual studios (technically and in learning design) and these are reported specifically for the interest and use of learning designers

Investigating the flow dynamics in the obstructed and stented ureter by means of a biomimetic artificial model.

Double-J stenting is the most common clinical method employed to restore the upper urinary tract drainage, in the presence of a ureteric obstruction. After implant, stents provide an immediate pain relief by decreasing the pressure in the renal pelvis (P). However, their long-term usage can cause infections and encrustations, due to bacterial colonization and crystal deposition on the stent surface, respectively. The performance of double-J stents - and in general of all ureteric stents - is thought to depend significantly on urine flow field within the stented ureter. However very little fundamental research about the role played by fluid dynamic parameters on stent functionality has been conducted so far. These parameters are often difficult to assess in-vivo, requiring the implementation of laborious and expensive experimental protocols. The aim of the present work was therefore to develop an artificial model of the ureter (i.e. ureter model, UM) to mimic the fluid dynamic environment in a stented ureter. The UM was designed to reflect the geometry of pig ureters, and to investigate the values of fluid dynamic viscosity (?), volumetric flow rate (Q) and severity of ureteric obstruction (OB%) which may cause critical pressures in the renal pelvis. The distributed obstruction derived by the sole stent insertion was also quantified. In addition, flow visualisation experiments and computational simulations were performed in order to further characterise the flow field in the UM. Unique characteristics of the flow dynamics in the obstructed and stented ureter have been revealed with using the developed UM

A Data Distribution Service in a hierarchical SDN architecture: implementation and evaluation

© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Software-defined networks (SDNs) have caused a paradigm shift in communication networks as they enable network programmability using either centralized or distributed controllers. With the development of the industry and society, new verticals have emerged, such as Industry 4.0, cooperative sensing and augmented reality. These verticals require network robustness and availability, which forces the use of distributed domains to improve network scalability and resilience. To this aim, this paper proposes a new solution to distribute SDN domains by using Data Distribution Services (DDS). The DDS allows the exchange of network information, synchronization among controllers and auto-discovery. Moreover, it increases the control plane robustness, an important characteristic in 5G networks (e.g., if a controller fails, its resources and devices can be managed by other controllers in a short amount of time as they already know this information). To verify the effectiveness of the DDS, we design a testbed by integrating the DDS in SDN controllers and deploying these controllers in different regions of Spain. The communication among the controllers was evaluated in terms of latency and overhead.Postprint (author's final draft

Towards homeostatic architecture: simulation of the generative process of a termite mound construction

This report sets out to the theme of the generation of a ‘living’, homeostatic and self-organizing architectural structure. The main research question this project addresses is what innovative techniques of design, construction and materials could prospectively be developed and eventually applied to create and sustain human-made buildings which are mostly adaptive, self-controlled and self-functioning, without option to a vast supply of materials and peripheral services. The hypothesis is that through the implementation of the biological building behaviour of termites, in terms of collective construction mechanisms that are based on environmental stimuli, we could achieve a simulation of the generative process of their adaptive structures, capable to inform in many ways human construction. The essay explicates the development of the 3-dimensional, agent-based simulation of the termite collective construction and analyzes the results, which involve besides physical modelling of the evolved structures. It finally elucidates the potential of this emerging and adaptive architectural performance to be translated to human practice and thus enlighten new ecological engineering and design methodologies

Autonomy Infused Teleoperation with Application to BCI Manipulation

Robot teleoperation systems face a common set of challenges including latency, low-dimensional user commands, and asymmetric control inputs. User control with Brain-Computer Interfaces (BCIs) exacerbates these problems through especially noisy and erratic low-dimensional motion commands due to the difficulty in decoding neural activity. We introduce a general framework to address these challenges through a combination of computer vision, user intent inference, and arbitration between the human input and autonomous control schemes. Adjustable levels of assistance allow the system to balance the operator's capabilities and feelings of comfort and control while compensating for a task's difficulty. We present experimental results demonstrating significant performance improvement using the shared-control assistance framework on adapted rehabilitation benchmarks with two subjects implanted with intracortical brain-computer interfaces controlling a seven degree-of-freedom robotic manipulator as a prosthetic. Our results further indicate that shared assistance mitigates perceived user difficulty and even enables successful performance on previously infeasible tasks. We showcase the extensibility of our architecture with applications to quality-of-life tasks such as opening a door, pouring liquids from containers, and manipulation with novel objects in densely cluttered environments