Quantum modeling of semiconductor gain materials and vertical-external-cavity surface-emitting laser systems

This article gives an,overview of the microscopic theory,theory used to quantitatively model a wide range of semiconductor laser gain materials. As a snapshot of the current state of research, applications to a variety of actual quantum-well systems are presented. Detailed theory experiment comparisons are shown and it is analyze how the theory can be used to extract poorly known material parameters. The intrinsic laser loss processes due to radiative and nonradiative Auger recombination are evaluated microscopically. The results are used for realistic simulations of vertical-external-cavity surface-emitting laser systems. To account for nonequilibrium effects, a simplified model is presented using pre-computed microscopic scattering and dephasing rates. Prominent deviations from quasi-equilibrium carrier distributions are obtained under strong in-well pumping conditions

THE SMART CITY INFRASTRUCTURE DEVELOPMENT & MONITORING

The smart city infrastructure is the introductory step for establishing the overall smart city framework and architecture. Very few smart cities are recently established across the world. Some examples are: Dubai, Malta, Kochi (India), Singapore. The scope of these cities is mainly limited to construct a technology park converting the industrial real estate to state of the art information technology using the evolution in the telecom and IP networks including insignificant asset management automation system. The development background is to create an operational platform that would manage the power consumption and operational resources in order to reduce the overall running operational cost. This paper will debate the smart infrastructure development framework and the surveying positional accuracy of locating the assets as a base of the smart city development architecture integrated with all the facilities and systems related to the smart city framework. The paper will discuss also the main advantages of the proposed architecture including the quantifiable and non quantifiable benefits.Smart Infrastructure, GIS, Smart City, Geopsatial application, Infrastructure Development, Infrastructure Monitoring.

Development Of A Spatial Web-Based Graphical User Interface With Gis For Real Estate Users

Geographic information is a valuable source for applications and analysis, where location of objects and events, can enhance the decision making activities. Recently, the interoperability of geospatial data has been an ongoing research activity and goal of the geospatial information user community for decades. Focusing on data integration scenarios, the recent popularity and adoption of the internet and web services, has provided a new means of interoperability for geospatial information, differing from previous approaches to information exchange. Currently the interoperability approaches of geospatial information with real estate data are inadequate. This thesis argues that utilizing the interoperability real estate data, with geospatial data using web services, is the best method to achieve efficient data exchange than traditional approaches. The thesis demonstrates this by developing a spatial web service to facilitate transferring data, from real estate users, to Geographic Information System (GIS) data layers. The thesis also discusses how web services affect data preparation and data updating. Various scenarios of geocoding and transferring real estate data into geospatial data will be discussed. A web interface implementation is presented, to illustrate the validity of the interoperable spatial web service approach, with real estate for which this thesis argues. The interface has two ways communication. On one hand users will be able to use the spatial web service to integrate the property data, with GIS service provider. On the other hand, user will be able to receive a map report for the geocoded property

Mass or Only "Niche Customization"? Why We Should Interpret Configuration Toolkits as Learning Instruments

In order to configure individual products according to their own preferences, customers are required to know what they want. While most research simply assumes that consumers have sufficient preference insight to do so, a number of psychologically oriented scholars have recently voiced serious concerns about this assumption. They argue that decades of consumer behavior research have shown that most consumers in most product categories lack this knowledge. Not knowing what one wants means being unable to specify what one wants¿and therefore, they conclude, the majority of customers are unable to use configuration toolkits in a meaningful way. In essence, this would mean that mass customization should rather be termed "niche customization" as it will be doomed to remain a concept for a very small minority of customers only. This pessimism stands in sharp contrast to the optimism of those who herald the new possibilities enabled by advances in communication and production technologies as the dawn of a new era in new product development and business in general. Which position is right? In order to answer this question, this research investigates the role of the configuration toolkit. Implicitly, the skeptic position assumes that the individual customers' knowledge (or absence of knowledge) of what they want is an exogenous and constant term that does not change during the interaction with the toolkit. However, learning theories suggest that the customers' trial-and-error interaction with the configuration toolkit and the feedback information they receive should increase their preference insight. If this was true and the effect size strong, it would mean that low a priori preference insight does not impede customers to derive value from mass customization. Three experiments show that configuration toolkits should be interpreted as learning instruments that allow consumers to understand their preferences more clearly. Even short trial-and-error self-design processes with conventional toolkits bring about substantial and time-stable enhancements of preference insight. The value of this knowledge is remarkable. In the product category of self-designed watches, the 10-minute design process resulted in additional preference insight worth 43.13 euros on average or +66%, measured by incentive-compatible auctions. A moderator analysis in a representative sample shows that the learning effect is particularly strong among customers who initially exhibit low levels of preference insight. These findings entail three contributions. First, it becomes evident that the interaction with mass customization toolkits not only triggers affective reactions among customers but also has cognitive effects¿a response category not investigated before. Second, it suggests that the pessimism regarding the mass appeal of these toolkits is not justified¿mass customization has the potential to truly deserve its name. The prerequisite for this, and this normative conclusion is the final contribution, is that the toolkit should not be interpreted as a mere interface for conveying preexisting preferences to the producer. Rather, it should be treated as a learning instrument. Several suggestions are made for how firms employing this innovative business model could design their toolkits towards this end. (authors' abstract