Hardness and Fracture Toughness of Solid Solutions of Mg2Si and Mg2Sn

Semiconductors - Thermoelectric material development typically aims at maximizing produced electrical power and efficiency of energy conversion, even though sometimes, this means adding expensive...     

Algorithm transformation methods to reduce the overhead of software-based fault tolerance techniques

This paper introduces a framework that tackles the costs in area and energy consumed by methodologies like spatial or temporal redundancy with a different approach: given an algorithm, we find a transformation in which part of the computation involved is transformed into memory accesses. The precomputed data stored in memory can be protected then by applying traditional and well established ECC algorithms to provide fault tolerant hardware designs. At the same time, the transformation increases the performance of the system by reducing its execution time, which is then used by customized software-based fault tolerant techniques to protect the system without any degradation when compared to its original form. Application of this technique to key algorithms in a MP3 player, combined with a fault injection campaign, show that this approach increases fault tolerance up to 92%, without any performance degradation.     

An application framework for developing collaborative handheld decision-making tools

This paper describes an application framework supporting collaborative handheld decision-making (CHDM). The main characteristics of the framework are: (1) extensive usage of visual elements and gestures; and (2) independence from specific decision-making methods, processes and tasks. The research departed from the analysis and systematisation of several CHDM scenarios, highlighting repeatable behaviour across multiple decision-making contexts. From these scenarios, we distilled a coherent set of common functional requirements organised in three main categories: process, macro- and micro-functionality. The proposed framework has been validated at length through the development of several CHDM tools. Six different tools are described in the paper. The main contribution of this work is a common foundation for developing CHDM tools.     

Scenario evaluation for the management of household solid waste in small Brazilian municipalities

As achieving Brazil’s National Policy on Solid Waste-based goals effectively is not simple, there are alternatives such as intermunicipal cooperation by consortium or privatization. Therefore, this study aimed to evaluate the Greenhouse Gas emissions and energy use of six scenarios in two landfills contexts (private and consortium) for small municipalities (less than 100,000 inhabitants as per Brazilian standards) located in São Paulo, Brazil. Through the technique of scenario building and method of Waste Reduction Model was possible to obtain the total energy, the amount of carbon dioxide equivalent (CO₂E) and carbon equivalent (CE) emissions. The best scenario integrates composting and recycling, reducing 72 % for CO₂E and CE emissions, and saving about 410 % in energy. The landfill consortium will only take advantage, if the location is the most ideal as far as possible. Small municipalities that do not dispose their waste in landfills compatible with regulatory standards may seek for intermunicipal cooperation and adopt integrated waste-management programmes to reduce their environmental impacts.     

Web-GIS models: accomplishing modularity with aspects

Spatial concerns of Web geographical information systems (Web-GIS) are inherently crosscutting and volatile: crosscutting because they affect multiple functionalities of Web-GIS systems, and volatile because their status may change often. If these concerns are not modularized properly, the quality of Web-GIS services, particularly with regard to adaptation and evolution, can be severely compromised. This paper uses aspect-orientation to model crosscutting and volatile spatial concerns. By modeling both types of concerns, crosscutting and volatile, as candidate aspects, one can use dynamic weaving to add or remove them from a system at runtime. The aspect-oriented approach proposed starts with the identification and specification of crosscutting concerns and follows by composing these using modeling aspects using a transformation approach, an aspect-oriented modeling technique. The conflicts that can emerge due to the composition order are also taken into consideration. Finally, this paper proposes a set of reusable GIS crosscutting concerns, documenting them in a concern catalogue.     

Performance of the most common non‐cryptographic hash functions

Non‐cryptographic hash functions (NCHFs) have an immense number of applications, ranging from compilers and databases to videogames and computer networks. Some of the most important NCHF have been used by major corporations in commercial products. This practical success demonstrates the ability of hashing systems to provide extremely efficient searches over unsorted sets. However, very little research has been devoted to the experimental evaluation of these functions. Therefore, we evaluated the most widely used NCHF using four criteria as follows: collision resistance, distribution of outputs, avalanche effect, and speed. We identified their strengths and weaknesses and found significant flaws in some cases. We also discuss our conclusions regarding general hashing considerations such as selection of the compression map. Our results should assist practitioners and engineers in making more informed choices regarding which function to use for a particular problem. Copyright © 2013 John Wiley & Sons, Ltd.     

Real-time scalable hardware architecture for 3D-HEVC bipartition modes

This article presents a real-time scalable hardware architecture for the bipartition modes of 3D high-efficiency video coding (3D-HEVC) standard, which includes the depth modeling modes 1 (DMM-1) and 4 (DMM-4). A simplification of the DMM-1 algorithm was done, removing the refinement step. This simplification causes a small BD-rate increase (0.09 %) with the advantage of better using our hardware resources, reducing the necessary memory required for storing all DMM-1 wedgelet patterns by 30 %. The scalable architecture can be configured to support all the different block sizes supported by the 3D-HEVC and also to reach different throughputs, according to the application requirements. Then, the proposed solution can be efficiently used for several encoding scenarios and many different applications. Synthesis results considering a test case show that the designed architecture is capable of processing HD 1080p videos in real time, but with other configurations, higher resolutions are also possible to be processed.     

In vitro digestibility of phenolic compounds from edible fruits: could it be explained by chemometrics?

The health benefits of phenolic compounds depend on the ingested amount, molecular diversity and gastrointestinal digestibility. The phenolic profile of eight fruits (blackberry, blueberry, strawberry, raspberry, mulberry, pomegranate, green and red globe grapes) was chemometrically associated with their in vitro digestibility (oral, gastric, intestinal). Extractable phenols, flavonoids and anthocyanins strongly correlated with each other (r ≥ 0.84), proanthocyanidins with anthocyanins (r = 0.62) and hydrolysable phenols with both extractable phenols (r = 0.45) and proanthocyanidins (r = ?0.54). Two principal components explained 93% of the variance [61% (free‐phenols), 32% (bounded‐phenols)], and four clusters were confirmed by hierarchical analysis, based in their phenolic richness (CLT 1‐4: low to high) and molecular diversity. In vitro digestibility of extractable phenols and flavonoids was blackberry (CLT‐4)> raspberry (CLT‐2)> red grape (CLT‐1) related to their phenolic richness (r ≥ 0.96; P < 0.001), but anthocyanins’ digestibility was pH‐dependent. Chemometrics is useful to predict the in vitro digestibility of phenolic compounds in the assayed fruits.     

Determination of alcohols and volatile organic acids in anaerobic bioreactors for H2 production by near infrared spectroscopy

In recent years, near infrared (NIR) spectroscopy has been investigated as a tool for monitoring anaerobic digesters, but several adversities in its application have been reported. This study proposes the application of NIR for the determination of alcohols and volatile organic acids from H₂ production bioreactors and evaluates different approaches to optimize the prediction models. Partial least squad (PLS) models were developed using samples from anaerobic batch reactors fed with crude glycerol for wastewater treatment. The analytes predicted were: methanol, ethanol, 1-butanol, acetic, propanoic, butyric, isocaproic and total volatile organic acids (VFA). The optimization of the predictive capacity of the models was achieved through the orthogonal signal correction (OSC) preprocessing and the selection of variables performed by the genetic algorithm (GA). The application of the proposed models were based on the following figures of merit: accuracy, precision, linearity, limits of detection and quantitation, measurement interval, sensitivity, selectivity, signal-to-noise ratio and bias. Despite the low selectivity (maximum of 0.12%), the models presented high sensitivity [γ^?1 = 0.19 (mg L^?1)^?1], low LOQ (1 mg L^?1) and correlation between reference and predicted values (r) at least 0.93, except for propanoic acid (r_pred = 0.85). The F-test revealed that the selection of variables by GA significantly improved the accuracy and linearity of the prediction models for methanol, acetic acid, isocaproic acid and VFA. NIR spectroscopy has proved to be a powerful tool for monitoring H₂ production bioreactors since provides fast, low cost and multicomponent information.