The optimal level of CRM IT investments

In light of the growing relevance of customer-oriented business strategies IT investments in the field of Customer Relationship Management have increased considerably. However, firms often could not realize sufficient returns on these IT investments. One major reason for this failure seems to be the lack of appropriate approaches to determine the economic impact of such investments ex ante. Therefore, we develop an economic model to determine the optimal level of Customer Relationship Management IT investments. Using this approach, firms can evaluate, to what extent investments in Customer Relationship Management IT are reasonable. One major result is that in most cases the “all or nothing strategy” pursued by many firms does not lead to the optimal level of investments. To illustrate the practical utility and applicability of the approach, we provide a real world example of a German financial services provider.     

Performance and reliability prediction for evolving service-oriented software systems

During software system evolution, software architects intuitively trade off the different architecture alternatives for their extra-functional properties, such as performance, maintainability, reliability, security, and usability. Researchers have proposed numerous model-driven prediction methods based on queuing networks or Petri nets, which claim to be more cost-effective and less error-prone than current practice. Practitioners are reluctant to apply these methods because of the unknown prediction accuracy and work effort. We have applied a novel model-driven prediction method called Q-ImPrESS on a large-scale process control system from ABB consisting of several million lines of code. This paper reports on the achieved performance prediction accuracy and reliability prediction sensitivity analyses as well as the effort in person hours for achieving these results.     

Comparison of satellite-derived and in-situ observations of ice and snow surface temperatures over Greenland

The most practical way to get spatially broad and continuous measurements of the surface temperature in the data-sparse cryosphere is by satellite remote sensing. The uncertainties in satellite-derived LSTs must be understood to develop internally-consistent decade-scale land surface temperature (LST) records needed for climate studies. In this work we assess satellite-derived “clear-sky” LST products from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), and LSTs derived from the Enhanced Thematic Mapper Plus (ETM+) over snow and ice on Greenland. When possible, we compare satellite-derived LSTs with in-situ air temperature observations from Greenland Climate Network (GC-Net) automatic weather stations (AWS). We find that MODIS, ASTER and ETM+ provide reliable and consistent LSTs under clear-sky conditions and relatively-flat terrain over snow and ice targets over a range of temperatures from ? 40 to 0 °C. The satellite-derived LSTs agree within a relative RMS uncertainty of ~ 0.5 °C. The good agreement among the LSTs derived from the various satellite instruments is especially notable since different spectral channels and different retrieval algorithms are used to calculate LST from the raw satellite data. The AWS record in-situ data at a “point” while the satellite instruments record data over an area varying in size from: 57 × 57 m (ETM+), 90 × 90 m (ASTER), or to 1 × 1 km (MODIS). Surface topography and other factors contribute to variability of LST within a pixel, thus the AWS measurements may not be representative of the LST of the pixel. Without more information on the local spatial patterns of LST, the AWS LST cannot be considered valid ground truth for the satellite measurements, with RMS uncertainty ~ 2 °C. Despite the relatively large AWS-derived uncertainty, we find LST data are characterized by high accuracy but have uncertain absolute precision.     

Tool-supported enhancement of diagnosis in model-driven verification

We show on a case study from an autonomous aerospace context how to apply a game-based model-checking approach as a powerful technique for the verification, diagnosis, and adaptation of system behaviors based on temporal properties. This work is part of our contribution within the SHADOWS project, where we provide a number of enabling technologies for model-driven self-healing. We propose here to use GEAR, a game-based model checker, as a user-friendly tool that can offer automatic proofs of critical properties of such systems. Although it is a model checker for the full modal μ-calculus, it also supports derived, more user-oriented logics. With GEAR, designers and engineers can interactively investigate automatically generated winning strategies for the games, by this way exploring the connection between the property, the system, and the proof. This work has been partially supported by the European Union Specific Targeted Research Project SHADOWS (IST-2006-35157), exploring a Self-Healing Approach to Designing cOmplex softWare Systems. The project’s web page is at . This article is an extended version of Renner et al. [18] presented at ISoLA 2007, Poitiers, December 2007.     

Spray-Coating of Superhydrophobic Coatings for Advanced Applications

Superhydrophobic coatings are widely applicable, e.g., as self-cleaning surfaces or water–oil separation membranes, yet their wider usage is impeded due to costs of fabrication, size, or substrate limitation. Spray-coating is a versatile coating procedures and might offer a good solution for the fabrication of these superhydrophobic coatings, due to the fact that coatings can be fabricated on various materials in a simple, fast, and inexpensive manner. Most procedures rely on hybrid coatings of hydrophobized nanoparticles and a polymeric matrix, which have several drawbacks including the easy loss of nanoparticles and difficult waste handling. Here, the fabrication of the superhydrophobic material, called Fluoropor, for the first time, by spray-coating on various substrates including metals, tissues, concrete, and glass is presented. It is fabricated by spray-coating a mixture of a highly fluorinated monomer blended with porogens followed by photopolymerization. The superhydrophobicity of the material relies on the porous structure on the micro-/nanoscale across the bulk material and does not require any nanoparticles. Excellent self-cleaning ability of these coatings, resistance against thermal and abrasive impact, and their application as oil–water separation membranes are shown. This versatile applicability is highly promising for real-world application as self-cleaning coatings or oil–water separating membranes.     

Ultralow Expansion Glass as Material for Advanced Micromechanical Systems

Ultralow expansion (ULE) glasses are of special interest for temperature stabilized systems for example in precision metrology. Nowadays, ULE materials are mainly used in macroscopic and less in micromechanical systems. Reasons for this are a lack of technologies for parallel fabricating high-quality released microstructures with a high accuracy. As a result, there is a high demand in transferring these materials into miniaturized application examples, realistic system modeling, and the investigation of microscopic material properties. Herein, a technological base for fabricating released micromechanical structures and systems with a structure height above 100 μm in ULE 7972 glass is established. Herein, the main fabrication parameters that are important for the system design and contribute thus to the introduction of titanium silicate as material for glass-based micromechanical systems are discussed. To study the mechanical properties in combination with respective simulation models, microcantilevers are used as basic mechanical elements to evaluate technological parameters and other impact factors. The implemented models allow to predict the micromechanical system properties with a deviation of only ±5% and can thus effectively support the micromechanical system design in an early stage of development.     

Using Selective Electron Beam Melting to Enhance the High-Temperature Strength and Creep Resistance of NiAl–28Cr–6Mo In Situ Composites

By increasing the density of interfaces in NiAl–CrMo in situ composites, the mechanical properties can be significantly improved compared to conventionally cast material. The refined microstructure is achieved by manufacturing through electron beam powder bed fusion (PBF-EB). By varying the process parameters, an equiaxed or columnar cell morphology can be obtained, exhibiting a plate-like or an interconnected network of the (Cr,Mo) reinforcement phase which is embedded in a NiAl matrix. The microstructure of the different cell morphologies is investigated in detail using scanning electron microscope, transmission electron microscopy, and atom probe tomography. For both morphologies, the mechanical properties at elevated temperatures are analyzed by compression and creep experiments parallel and perpendicular to the building direction. In comparison to cast NiAl and NiAl–(Cr, Mo), the yield strength of the PBF-EB fabricated specimens is significantly improved at temperatures up to 1,027 °C. While the columnar morphology exhibits the best improved mechanical properties at high temperatures, the equiaxial morphology shows nearly ideal isotropic mechanical behavior, which is a substantial advantage over directionally solidified material.     

The smart car seat: personalized monitoring of vital signs in automotive applications

Embedded wireless sensors are important components of mobile distributed computing networks, and one of the target applications areas is health care. The preservation of mobility for senior citizens is one of the key issues in maintaining an independent lifestyle. Thus health technologies inside a car can contribute both to safety issues (supervision of driver fitness) as well as healthcare issues by monitoring vitals signs imperceptibly. In this paper, three embedded measurement techniques for non-contact monitoring of vital signals have been investigated. Specifically, capacitive electrocardiogram (cECG) monitoring, mechanical movement analysis (ballistocardiogram, BCG) using piezo-foils and inductive impedance monitoring were examined regarding their potential for integration into car seats. All three sensing techniques omit the need for electroconductive contact to the human body, but require defined mechanical boundary conditions (stable distances or, in the case of BCG, frictional connection). The physical principles of operation, the specific boundary conditions regarding automotive integration and the results during wireless operation in a running car are presented. All three sensors were equipped with local intelligence by incorporating a microcontroller. To eliminate the need for additional cabling, a wireless Bluetooth communication module was added and used to transmit data to a measurement PC. Finally, preliminary results obtained during test drives on German city roads and highways are discussed.     

A fully integrated 1‐in. AMOLED display using current feedback based on a five‐mask LTPS CMOS process

Abstract— In the past, a five‐mask LTPS CMOS process requiring only one single ion‐doping step was used. Based on that process, all necessary components for the realization of a fully integrated AMOLED display using a 3T1C current‐feedback pixel circuit has recently been developed. The integrated data driver is based on a newly developed LTPS operational amplifier, which does not require any compensation for Vth or mobility variations. Only one operational amplifier per column is used to perform digital‐to‐analog conversion as well as current control. In order to achieve high‐precision analog behavior, the operational amplifier is embedded in a switched capacitor network. In addition to circuit verification by simulation and analytic analysis, a 1‐in. fully integrated AMOLED demonstrator was successfully built. To the best of the authors' knowledge, this is the first implementation of a fully integrated AMOLED display with current feedback.     

In situ exploration of large dynamic networks

The analysis of large dynamic networks poses a challenge in many fields, ranging from large bot-nets to social networks. As dynamic networks exhibit different characteristics, e.g., being of sparse or dense structure, or having a continuous or discrete time line, a variety of visualization techniques have been specifically designed to handle these different aspects of network structure and time. This wide range of existing techniques is well justified, as rarely a single visualization is suitable to cover the entire visual analysis. Instead, visual representations are often switched in the course of the exploration of dynamic graphs as the focus of analysis shifts between the temporal and the structural aspects of the data. To support such a switching in a seamless and intuitive manner, we introduce the concept of in situ visualization--a novel strategy that tightly integrates existing visualization techniques for dynamic networks. It does so by allowing the user to interactively select in a base visualization a region for which a different visualization technique is then applied and embedded in the selection made. This permits to change the way a locally selected group of data items, such as nodes or time points, are shown--right in the place where they are positioned, thus supporting the user's overall mental map. Using this approach, a user can switch seamlessly between different visual representations to adapt a region of a base visualization to the specifics of the data within it or to the current analysis focus. This paper presents and discusses the in situ visualization strategy and its implications for dynamic graph visualization. Furthermore, it illustrates its usefulness by employing it for the visual exploration of dynamic networks from two different fields: model versioning and wireless mesh networks.