Blue-green ZnSe lasers with a new type of active region

We report the results of an experimental study of molecular-beam epitaxy of ZnSe-based laser heterostructures with a new structure of the active region, which contains a fractional-monolayer CdSe recombination region in an expanded ZnSe quantum well and a waveguide based on a variably-strained, short-period superlattice are reported. Growth of a fractional-monolayer CdSe region with a nominal thickness of 2–3 ML, i.e., less than the critical thickness, on a ZnSe surface (Δa/a∼7%) leads to the formation of self-organized, pseudomorphic, CdSe-enriched islands with lateral dimensions ∼10–30 nm and density ∼2×10¹⁰ cm⁻², which serve as efficient centers of carrier localization, giving rise to effective spatial separation of defective regions and regions of radiative recombination and, as a result, a higher quantum efficiency. Laser structures for optical pumping in the (Zn, Mg) (S, Se) system with a record-low threshold power density (less than 4 kW/cm² at 300 K) and continuous-wave laser diodes in the system (Be, Mg, Zn) Se with a 2.5 to 2.8-ML-thick, fractional-monolayer CdSe active region have been obtained. The laser structures and diodes have an improved degradation resistance. Fiz. Tekh. Poluprovodn. 33, 1115–1119 (September 1999)     

Design and experimental implementation of an electromagnetic engine valve drive

In conventional internal combustion engines, engine valve displacements are fixed relative to crankshaft position. If these valves were actuated as a variable function of crankshaft angle, significant improvements in fuel economy could be achieved. To this end, a new type of electromagnetic valve drive system (EMVD) for internal combustion engines was more recently proposed. This EMVD incorporates a disk cam with a very desirable nonlinear profile which that functions as a nonlinear mechanical transformer. Modeling and simulation results showed significant advantages of this EMVD over previously designed electromagnetic engine valve drives. In this articles, we describe an experimental implementation of the proposed EMVD, which was developed to confirm these benefits. The EMVD apparatus was designed, constructed, and integrated into a computer-controlled experimental test stand. The experimental results confirm the benefits of using a nonlinear mechanical transformer in a motordriven engine-valve spring system, as seen in the small average power consumption and low valve seating velocity. In addition, a valve transition time sufficient for 6000-rpm engine operation was achieved. The results also suggest ways to improve the EMVD apparatus in the future.     

Petrochemicals: Raw material change from fossil to biomass?

The petrochemical industry, which is based on crude oil and natural gas, competes with the energy providing industry for the same fossil raw material, but uses only 10% of it. This leaves the energy providers in the driver seat and makes the petrochemical industry dependent on them. Dwindling oil and gas reserves, concern regarding the greenhouse effect (carbon dioxide emissions) and worldwide rising energy demand raise the question of the future availability of fossil raw materials. Biomass as a renewable resource appears as an alternative to substitute oil and gas. Current use of biomass for organic chemicals amounts to 10% and is mainly based on sugar, starch, fats and oils (first generation of biomass). The use of these raw materials brings the chemical industry also in competition with nutrition for man and animal. Great interest centers around the use of “non-food-biomass” (lignocellulose), which is available in nearly abundant amounts, but routes for chemical utilizations are lacking. Biotechnological, chemical and engineering solutions are needed for utilization of this second generation bio-renewable based supply chain. One approach consists of the concept of a bio-refinery. Also gasification followed by liquefaction is a promising pathway. Short and medium term a feedstock mix with crude oil and natural gas dominating can most likely be expected. Very long term, due to the final limited availability of oil and gas, biomass will prevail. Prior to this change to occur great research and developments efforts must be carried out to have the necessary technology available when needed.     

Quality metrics in high-dimensional data visualization: an overview and systematization

In this paper, we present a systematization of techniques that use quality metrics to help in the visual exploration of meaningful patterns in high-dimensional data. In a number of recent papers, different quality metrics are proposed to automate the demanding search through large spaces of alternative visualizations (e.g., alternative projections or ordering), allowing the user to concentrate on the most promising visualizations suggested by the quality metrics. Over the last decade, this approach has witnessed a remarkable development but few reflections exist on how these methods are related to each other and how the approach can be developed further. For this purpose, we provide an overview of approaches that use quality metrics in high-dimensional data visualization and propose a systematization based on a thorough literature review. We carefully analyze the papers and derive a set of factors for discriminating the quality metrics, visualization techniques, and the process itself. The process is described through a reworked version of the well-known information visualization pipeline. We demonstrate the usefulness of our model by applying it to several existing approaches that use quality metrics, and we provide reflections on implications of our model for future research.     

SurgeryCuts: Embedding Additional Information in Maps without Occluding Features

Visualizing contextual information to a map often comes at the expense of overplotting issues. Especially for use cases with relevant map features in the immediate vicinity of an information to add, occlusion of the relevant map context should be avoided. We present SurgeryCuts, a map manipulation technique for the creation of additional canvas area for contextual visualizations on maps. SurgeryCuts is occlusion‐free and does not shift, zoom or alter the map viewport. Instead, relevant parts of the map can be cut apart. The affected area is controlledly distorted using a parameterizable warping function fading out the map distortion depending on the distance to the cut. We define extended metrics for our approach and compare to related approaches. As well, we demonstrate the applicability of our approach at the example of tangible use cases and a comparative user study.     

Visual Analytics for Exploring Local Impact of Air Traffic

The environmental and noise impact of airports often causes extensive political discussion which in some cases even lead to transnational tensions. Analyzing local approach and departure patterns around an airport is difficult since it depends on a variety of complex variables like weather, local and general regulations and many more. Yet, understanding these movements and the expected amount of flights during arrival and departure is of great interest to both casual and expert users, as planes have a higher impact on the areas beneath during these phases. We present a Visual Analytics framework that enables users to develop an understanding of local flight behavior through visual exploration of historical data and interactive manipulation of prediction models with direct feedback, as well as a classification quality visualization using a random noise metaphor. We showcase our approach using real world data from the Zurich International Airport region, where aircraft noise has led to an ongoing conflict between Germany and Switzerland. The use cases, findings and expert feedback demonstrate how our approach helps in understanding the situation and to substantiate the otherwise often subjective discourse on the topic.     

Density Displays for Data Stream Monitoring

In many business applications, large data workloads such as sales figures or process performance measures need to be monitored in real‐time. The data analysts want to catch problems in flight to reveal the root cause of anomalies. Immediate actions need to be taken before the problems become too expensive or consume too many resources. In the meantime, analysts need to have the “big picture” of what the information is about. In this paper, we derive and analyze two real‐time visualization techniques for managing density displays: (1) circular overlay d isplays which visualize large volumes of data without data shift movements after the display is full, thus freeing the analyst from adjusting the mental picture of the data after each data shift; and (2) variable resolution density displays which allow users to get the entire view without cluttering. We evaluate these techniques with respect to a number of evaluation measures, such as constancy of the display and usage of display space, and compare them to conventional d isplays with periodic shifts. Our real time data monitoring system also provides advanced interactions such as a local root cause analysis for further exploration. The applications using a number of real‐world data sets show the wide applicability and usefulness of our ideas.     

Visual data mining in large geospatial point sets

Visual data-mining techniques have proven valuable in exploratory data analysis, and they have strong potential in the exploration of large databases. Detecting interesting local patterns in large data sets is a key research challenge. Particularly challenging today is finding and deploying efficient and scalable visualization strategies for exploring large geospatial data sets. One way is to share ideas from the statistics and machine-learning disciplines with ideas and methods from the information and geo-visualization disciplines. PixelMaps in the Waldo system demonstrates how data mining can be successfully integrated with interactive visualization. The increasing scale and complexity of data analysis problems require tighter integration of interactive geospatial data visualization with statistical data-mining algorithms.