Metal Alloys for Fusion‐Based Additive Manufacturing

Metal additive manufacturing (AM) is an innovative manufacturing technique, which builds parts incrementally layer by layer. Thus, metal AM has inherent advantages in part complexity, time, and waste saving. However, due to its complex thermal cycle and rapid solidification during processing, the alloys well suit and commercially used for metal AM today are limited. Therefore, it is important to understand the alloying strategy and current progress with materials performance to consider alloy development for metal AM. This review presents the current range of alloys available for metal AM, including titanium, steel, nickel, aluminum, less common alloys (including Mg alloys, metal matrix composites alloys, and low melting point alloys), and compositionally complex alloys (including bulk metallic glasses and high entropy alloys) with a focus on the relationship between compositions, processing, microstructures, and properties of each alloy system. In addition, some promising alloy systems for metal AM are highlighted. Approaches for designing and optimizing new materials for metal AM have been summarized.

     

Shifting role for human factors in an ‘unmanned’ era

Human factors practitioners (HFPs) play many different roles in the design, creation, operation and maintenance of engineered systems. Less well known are the methods which are aimed at helping with the early stages of design, which are more systems-oriented and often involve questions of the concept of operation in which the engineered system will be fielded. Emerging from the field of cognitive engineering, these methods, including simulation, cognitive work analysis, cognitive task analyses and hierarchical task analysis, will be important as autonomous systems become increasingly capable. Even the most capable systems will continue to interact with humans, and it is at these interfaces between humans and engineered systems that HFP will continue to be needed. This paper describes recent work to leverage these methods to inform concepts of operation in aviation and space, machine learning algorithms and goal-oriented human–machine collaboration.     

Symbolic Intersect Detection: A Method for Improving Spatial Intersect Joins

Due to the increasing popularity of spatial databases, researchers have focused their efforts on improving the query processing performance of the most expensive spatial database operation: the spatial join. While most previous work focused on optimizing the filter step, it has been discovered recently that, for typical GIS data sets, the refinement step of spatial join processing actually requires a longer processing time than the filter step. Furthermore, two-thirds of the time in processing the refinement step is devoted to the computation of polygon intersections. To address this issue, we therefore introduce a novel approach to spatial join optimization that drastically reduces the time of the refinement step. We propose a new approach called Symbolic Intersect Detection (SID) for early detection of true hits. Our SID optimization eliminates most of the expensive polygon intersect computations required by a spatial join by exploiting the symbolic topological relationships between the two candidate polygons and their overlapping minimum bounding rectangle. One important feature of our SID optimization is that it is complementary to the state-of-the-art methods in spatial join processing and therefore can be utilized by these techniques to further optimize their performance. In this paper, we also develop an analytical cost model that characterizes SIDs effectiveness under various conditions. Based on real map data, we furthermore conduct an experimental evaluation comparing the performance of the spatial joins with SID against the state-of-the-art approach. Our experimental results show that SID can effectively identify more than 80% of the true hits with negligible overhead. Consequently, with SID, the time needed for resolving polygon intersect in the refinement step is improved by over 50% over known techniques, as predicted by our analytical model.     

Normalized Interactions between autonomous agents

The CEC Project GOAL (Esprit 6283) aims to develop generic software tools to support a new project management paradigm, in which projects are collaborative, decentralised and inter-organizational. To support inter-organizational interaction, communication and cooperation, we are developing a design framework for formalizing the flow of information between organizations, specifying access to and provision of project services, and defining project-wide standards and procedures. This framework is based on normalizing interactions between autonomous software agents by specifying messages and protocols for inter-agent communication and cooperation. This paper reviews the framework, and then focusses on the specification and implementation of a case study, the automation of a distributed document review procedure. This is both a successful proof of concept and a demonstration of how Artificial Intelligence technologies can support inter-organizational project management. It also points the way to agent brokering, an enhancement of object brokering in distributed open systems, where the satisfaction of service requests can be subject to negotiation.Supported by CEC Esprit Project GOAL (Esprit 6283) and CEC Esprit BRA Medlar II (Esprit 6471).Supported by CEC Esprit Project GOAL (Esprit 6283).     

Effect of reduced dietary sodium on blood pressure: a meta-analysis of randomized controlled trials

OBJECTIVE:- To ascertain whether restriction of dietary sodium lowers blood pressure in hypertensive and normotensive individuals. DATA SOURCES:- An English-language computerized literature search, restricted to human studies with Medical Subject Heading terms, "hypertension," "blood pressure," "vascular resistance," "sodium and dietary," "diet and sodium restricted," "sodium chloride," "clinical trial," "randomized controlled trial," and "prospective studies," was conducted. Bibliographies of review articles and personal files were also searched. TRIAL SELECTION:- Trials that had randomized allocation to control and dietary sodium intervention groups, monitored by timed sodium excretion, with outcome measures of both systolic and diastolic blood pressure were selected by blinded review of the methods section. DATA EXTRACTION:- Two observers extracted data independently, using purpose-designed forms, and discrepancies were resolved by discussion. DATA SYNTHESIS:- The 56 trials that met our inclusion criteria showed significant heterogeneity. Publication bias was also evident. The mean reduction (95% confidence interval) in daily urinary sodium excretion, a proxy measure of dietary sodium intake, was 95 mmol/d (71-119 mmol/d) in 28 trials with 1131 hypertensive subjects and 125 mmol/d (95-156 mmol/d) in 28 trials with 2374 normotensive subjects. After adjustment for measurement error of urinary sodium excretion, the decrease in blood pressure for a 100-mmol/d reduction in daily sodium excretion was 3.7 mm Hg (2.35-5.05 mm Hg) for systolic (P<.001) and 0.9 mm Hg (-0.13 to 1.85 mm Hg) for diastolic (P=.09) in the hypertensive trials, and 1.0 mm Hg (0.51-1.56 mm Hg) for systolic (P<.001) and 0.1 mm Hg (-0.32 to 0.51 mm Hg) for diastolic (P=.64) in the normotensive trials. Decreases in blood pressure were larger in trials of older hypertensive individuals and small and nonsignificant in trials of normotensive individuals whose meals were prepared and who lived outside the institutional setting. CONCLUSION:- Dietary sodium restriction for older hypertensive individuals might be considered, but the evidence in the normotensive population does not support current recommendations for universal dietary sodium restriction.     

A scalable approach to mapping annual land cover at 250 m using MODIS time series data: A case study in the Dry Chaco ecoregion of South America

Land use and land cover (LULC) maps from remote sensing are vital for monitoring, understanding and predicting the effects of complex human-nature interactions that span local, regional and global scales. We present a method to map annual LULC at a regional spatial scale with source data and processing techniques that permit scaling to broader spatial and temporal scales, while maintaining a consistent classification scheme and accuracy. Using the Dry Chaco ecoregion in Argentina, Bolivia and Paraguay as a test site, we derived a suite of predictor variables from 2001 to 2007 from the MODIS 250 m vegetation index product (MOD13Q1). These variables included: annual statistics of red, near infrared, and enhanced vegetation index (EVI), phenological metrics derived from EVI time series data, and slope and elevation. For reference data, we visually interpreted percent cover of eight classes at locations with high-resolution QuickBird imagery in Google Earth. An adjustable majority cover threshold was used to assign samples to a dominant class. When compared to field data, we found this imagery to have georeferencing error < 5% the length of a MODIS pixel, while most class interpretation error was related to confusion between agriculture and herbaceous vegetation. We used the Random Forests classifier to identify the best sets of predictor variables and percent cover thresholds for discriminating our LULC classes. The best variable set included all predictor variables and a cover threshold of 80%. This optimal Random Forests was used to map LULC for each year between 2001 and 2007, followed by a per-pixel, 3-year temporal filter to remove disallowed LULC transitions. Our sequence of maps had an overall accuracy of 79.3%, producer accuracy from 51.4% (plantation) to 95.8% (woody vegetation), and user accuracy from 58.9% (herbaceous vegetation) to 100.0% (water). We attributed map class confusion to limited spectral information, sub-pixel spectral mixing, georeferencing error and human error in interpreting reference samples. We used our maps to assess woody vegetation change in the Dry Chaco from 2002 to 2006, which was characterized by rapid deforestation related to soybean and planted pasture expansion. This method can be easily applied to other regions or continents to produce spatially and temporally consistent information on annual LULC.     

Evaluating improvements to a meta-heuristic search for constrained interaction testing

Combinatorial interaction testing (CIT) is a cost-effective sampling technique for discovering interaction faults in highly-configurable systems. Constrained CIT extends the technique to situations where some features cannot coexist in a configuration, and is therefore more applicable to real-world software. Recent work on greedy algorithms to build CIT samples now efficiently supports these feature constraints. But when testing a single system configuration is expensive, greedy techniques perform worse than meta-heuristic algorithms, because greedy algorithms generally need larger samples to exercise the same set of interactions. On the other hand, current meta-heuristic algorithms have long run times when feature constraints are present. Neither class of algorithm is suitable when both constraints and the cost of testing configurations are important factors. Therefore, we reformulate one meta-heuristic search algorithm for constructing CIT samples, simulated annealing, to more efficiently incorporate constraints. We identify a set of algorithmic changes and experiment with our modifications on 35 realistic constrained problems and on a set of unconstrained problems from the literature to isolate the factors that improve performance. Our evaluation determines that the optimizations reduce run time by a factor of 90 and accomplish the same coverage objectives with even fewer system configurations. Furthermore, the new version compares favorably with greedy algorithms on real-world problems, and, though our modifications were aimed at constrained problems, it shows similar advantages when feature constraints are absent.     

Polygon subdivision for pocket machining process planning

This paper presents a new approach to improve tool selection for arbitrary shaped pockets based on an approximate polygon subdivision technique. The pocket is subdivided into smaller sub-polygons and tools are selected separately for each sub-polygon. A set of tools for the entire pocket is obtained based on both machining time and the number of tools used. In addition, the sub-polygons are sequenced to eliminate the requirement of multiple plunging operations. In process planning for pocket machining, selection of tool sizes and minimizing the number of plunging operations can be very important factors. The approach presented in this paper is an improvement over previous work in its use of a polygon subdivision strategy to improve the machining time as well as reducing the number of plunges. The implementation of this technique suggests that using a subdivision approach can reduce machining time when compared to solving for the entire polygonal region.     

An ontological modelling of user requirements for personalised information provision

The knowledge economy offers opportunity to a broad and diverse community of information systems users to efficiently gain information and know-how for improving qualifications and enhancing productivity in the work place. Such demand will continue and users will frequently require optimised and personalised information content. The advancement of information technology and the wide dissemination of information endorse individual users when constructing new knowledge from their experience in the real-world context. However, a design of personalised information provision is challenging because users’ requirements and information provision specifications are complex in their representation. The existing methods are not able to effectively support this analysis process. This paper presents a mechanism which can holistically facilitate customisation of information provision based on individual users’ goals, level of knowledge and cognitive styles preferences. An ontology model with embedded norms represents the domain knowledge of information provision in a specific context where users’ needs can be articulated and represented in a user profile. These formal requirements can then be transformed onto information provision specifications which are used to discover suitable information content from repositories and pedagogically organise the selected content to meet the users’ needs. The method is provided with adaptability which enables an appropriate response to changes in users’ requirements during the process of acquiring knowledge and skills.