Podcasting: A new technological tool to facilitate good practice in higher education

The literature has frequently highlighted the usefulness of podcasting in higher education; however, there is an important gap between the theory on good practice in higher education and empirical studies about podcasting. With this in mind, we carried out an empirical study on an undergraduate degree course in Information Systems Management. The study consisted of the creation and broadcast of 13 podcasts, distributed over four months in which ninety distance students took part. The analysis follows the suggestions proposed in previous literature about the evaluation of technologies in a university learning environment. The findings, discussed within the framework of principles for good practice in higher education, suggest some interesting issues in distance courses, such as: (1) podcasting is a powerful tool as a complement to the traditional resources on a course, but not a substitute for them; (2) the characteristics of podcasting increase the impression of permanent contact between students and teachers, increasing students’ motivation; (3) the use of podcasting allows for a diverse range of student skills and learning methods. Other secondary findings are discussed and some suggestions for future research are proposed at the end of this paper.     

Design,manufacture and geometric verification of rapid prototyped microfluidic encapsulations by computed tomography

This paper presents the dimensional verification of encapsulations used to package microfluidic devices manufactured using a 3D printer of photopolymerisable resin. This characterisation has been performed by computed tomography (CT) by comparing newly manufactured encapsulations and samples that have been subjected to test conditions. Thus, it has been possible to draw conclusions both on the deviations of the nominal geometry of the encapsulations and on how this might affect their performance. This paper presents a scheme of dimensional verification from the point clouds obtained by CT. Finally, a combined threshold and scale factor correction technique of the tomography images is shown. This method is based on the simultaneous measurement of objective and master parts with known geometry. The results reveal the improvements achievable in the accuracy, given a particular machine configuration. The conclusions facilitate the improvement of the geometric design of these devices regarding their behaviour under test conditions.     

A SIMD-efficient 14 instruction shader program for high-throughput microtriangle rasterization

This paper shows that breaking the barrier of 1 triangle/clock rasterization rate for microtriangles in modern GPU architectures in an efficient way is possible. The fixed throughput of the special purpose culling and triangle setup stages of the classic pipeline limits the GPU scalability to rasterize many triangles in parallel when these cover very few pixels. In contrast, the shader core counts and increasing GFLOPs in modern GPUs clearly suggests parallelizing this computation entirely across multiple shader threads, making use of the powerful wide-ALU instructions. In this paper, we present a very efficient SIMD-like rasterization code targeted at very small triangles that scales very well with the number of shader cores and has higher performance than traditional edge equation based algorithms. We have extended the ATTILA GPU shader ISA (del Barrioet al. in IEEE International Symposium on Performance Analysis of Systems and Software, pp. 231–241, 2006) with two fixed point instructions to meet the rasterization precision requirement. This paper also introduces a novel subpixel Bounding Box size optimization that adjusts the bounds much more finely, which is critical for small triangles, and doubles the 2×2-pixel stamp test efficiency. The proposed shader rasterization program can run on top of the original pixel shader program in such a way that selected fragments are rasterized, attribute interpolated and pixel shaded in the same pass. Our results show that our technique yields better performance than a classic rasterizer at 8 or more shader cores, with speedups as high as 4× for 16 shader cores.     

Application of security reference architecture to Big Data ecosystems in an industrial scenario

Big Data environments are typically very complex ecosystems; this means that implementing them is complicated. One possible technique with which to address this complexity is the use of abstraction. Reference architecture (RA) can be useful for an improved understanding of the main components of Big Data. Herein, we propose a security RA that includes the management of security concerns and provides the main elements of a Big Data ecosystem. Application of this architecture to real-world scenarios facilitates its refinement and improves its usefulness. In this article, we present a case study of a real-world Big Data ecosystem implemented in a banking environment. This ecosystem was developed by everis, an NTT company with which we collaborated for this study. To conduct this validation case study, a map was established between the elements of the Big Data ecosystem implemented and our proposal. Consequently, a series of valuable lessons that can improve both our architecture and the security of the Big Data environment were obtained. These include recommendations for a set of best practices such as the use of security patterns.     

Field‐based robotic phenotyping of sorghum plant architecture using stereo vision

Sorghum (Sorghum bicolor) is known as a major feedstock for biofuel production. To improve its biomass yield through genetic research, manually measuring yield component traits (e.g. plant height, stem diameter, leaf angle, leaf area, leaf number, and panicle size) in the field is the current best practice. However, such laborious and time‐consuming tasks have become a bottleneck limiting experiment scale and data acquisition frequency. This paper presents a high‐throughput field‐based robotic phenotyping system which performed side‐view stereo imaging for dense sorghum plants with a wide range of plant heights throughout the growing season. Our study demonstrated the suitability of stereo vision for field‐based three‐dimensional plant phenotyping when recent advances in stereo matching algorithms were incorporated. A robust data processing pipeline was developed to quantify the variations or morphological traits in plant architecture, which included plot‐based plant height, plot‐based plant width, convex hull volume, plant surface area, and stem diameter (semiautomated). These image‐derived measurements were highly repeatable and showed high correlations with the in‐field manual measurements. Meanwhile, manually collecting the same traits required a large amount of manpower and time compared to the robotic system. The results demonstrated that the proposed system could be a promising tool for large‐scale field‐based high‐throughput plant phenotyping of bioenergy crops.     

Mobile digcovery: discovering and interacting with the world through the Internet of things

The application of Internet-enabled devices in the real world for the development of Smart Cities, environmental monitoring, bus tracking, and parking requires scalability, extensibility, and integration of emerging resources to reach a suitable ecosystem for data acquisition and interaction with citizens. Internet of things needs to offer efficient support for global communications and access to services and information. It needs to enable homogeneous and seamless machine-to-machine communication for different solutions and applications. This work presents an homogeneous and suitable mechanism for global resource discovery, device access for deployed smart objects in different scenarios, and sensors and devices from end users (participative sensing). The integration of legacy and sensors already available from smart buildings and smart objects is presented. For this purpose, a resolution infrastructure called “digcovery” is defined for maximizing efficiency and sustainability of deployments. Digcovery architecture offers the framework to allow users to register/include their own sensors into a common infrastructure and access/discover the available resources through mobile digcovery. Mobile digcovery exploits the context-awareness, geo-location, and identification technologies available in mobile platforms such as smartphones to discover, interact, and access the resources through its ElasticSearch engine.     

Extending the Similarity‐Attraction Effect: The Effects of When‐Similarity in Computer‐Mediated Communication

The feeling of connectedness experienced in computer‐mediated relationships can be explained by the similarity‐attraction effect (SAE). Though SAE is well established in psychology, the effects of some types of similarity have not yet been explored. In 2 studies, we demonstrate similarity‐attraction based on the timing of activities—“when‐similarity.” We describe a novel experimental paradigm for manifesting when‐similarity while controlling for the activities being performed (what‐similarity). Study 1 (N = 24) shows when‐similarity attraction in the evaluation of connectedness with others. Study 2 (N = 42) identifies an interaction between who‐similarity—similarity in personal backgrounds—and when‐similarity. Both studies show that real‐time computer‐mediated interaction can lead to greater feelings of connectedness between people when there is an opportunity to discover when‐similarity.     

Janus II: A new generation application-driven computer for spin-system simulations

This paper describes the architecture, the development and the implementation of Janus II, a new generation application-driven number cruncher optimized for Monte Carlo simulations of spin systems (mainly spin glasses). This domain of computational physics is a recognized grand challenge of high-performance computing: the resources necessary to study in detail theoretical models that can make contact with experimental data are by far beyond those available using commodity computer systems. On the other hand, several specific features of the associated algorithms suggest that unconventional computer architectures–that can be implemented with available electronics technologies–may lead to order of magnitude increases in performance, reducing to acceptable values on human scales the time needed to carry out simulation campaigns that would take centuries on commercially available machines. Janus II is one such machine, recently developed and commissioned, that builds upon and improves on the successful JANUS machine, which has been used for physics since 2008 and is still in operation today. This paper describes in detail the motivations behind the project, the computational requirements, the architecture and the implementation of this new machine and compares its expected performances with those of currently available commercial systems.     

Thermodynamic and ab initio investigation of the Al–H–Mg system

A coupled ab initio and thermodynamic study of the Al–H–Mg system has been carried out and a self-consistent thermodynamic database has been obtained. Magnesium alanate Mg(AlH₄)₂, a candidate material for hydrogen storage, has been included into the database. According to Density Functional first principles calculations, the alanate is an insulator and its thermodynamic properties have been obtained at room temperature. This compound has been found metastable at 298.15 K and 1 bar. The alanate has been found thermodynamically stable only at high pressure when the formation of the binary β-MgH₂ phase is neglected. A reassessment of thermodynamic parameters of the liquid phase in the binary Mg–H system has also been carried out in order to be consistent with the Al–H system. The present results can reproduce reasonably well the available experimental data.