Energieinformatik

Due to the increasing importance of producing and consuming energy more sustainably, Energy Informatics (EI) has evolved into a thriving research area within the CS/IS community. The article attempts to characterize this young and highly dynamic field of research by describing current EI research topics and methods and provides an outlook of how the field might evolve in the future. It is shown that two general research questions have received the most attention so far and are likely to dominate the EI research agenda in the coming years: How to leverage information and communication technology (ICT) to (1) improve energy efficiency, and (2) to integrate decentralized renewable energy sources into the power grid. Selected EI streams are reviewed, highlighting how the respective research questions are broken down into specific research projects and how EI researchers have made contributions based on their individual academic background.     

Nanostructure array of coupled RTDs as cellular neural networks

The processing capabilities of a proposed nanoelectronic device are investigated. The device is considered as a global dynamical system with local circuit model components. The system equations and the corresponding network model are presented. The characteristics of this network model are compared with the cellular neural networks. Certain characteristics of the network are analysed theoretically and demonstrated with circuit‐system level simulations. As a novel property, it is shown that the single layer nanodevice network structure is a basic reaction–diffusion system and it is capable of autowave propagation. Furthermore, the same network structure exhibits several image processing capabilities like image smoothing, edge enhancement, and horizontal or vertical line detection using simple arrangements of the device parameters. Copyright ©2003 John Wiley & Sons, Ltd.     

Combating discrimination using Bayesian networks

Discrimination in decision making is prohibited on many attributes (religion, gender, etc…), but often present in historical decisions. Use of such discriminatory historical decision making as training data can perpetuate discrimination, even if the protected attributes are not directly present in the data. This work focuses on discovering discrimination in instances and preventing discrimination in classification. First, we propose a discrimination discovery method based on modeling the probability distribution of a class using Bayesian networks. This measures the effect of a protected attribute (e.g., gender) in a subset of the dataset using the estimated probability distribution (via a Bayesian network). Second, we propose a classification method that corrects for the discovered discrimination without using protected attributes in the decision process. We evaluate the discrimination discovery and discrimination prevention approaches on two different datasets. The empirical results show that a substantial amount of discrimination identified in instances is prevented in future decisions.     

UV curable lens production using molecular weight controlled PEEK based acrylic oligomer (Ac-PEEK)

We produced UV curable lenses with properties blocking short wave UV light. In the UV-curable formulations, we used an oligomer (Ac-PEEK) with another urethan oligomer (Mw = 2000). Radically active, molecular weight controlled Ac-PEEK was obtained by reacting 2-hydroxyl ethyl methacrylate with molecular- weight- controlled and isocyanate terminated PEEK (Mn = 4500). We characterized all synthesized monomer, oligomer and optical materials with UV/Vis spectrophotometer with interferogram, elemental analyser, mass spectrophotometer, proton nuclear magnetic resonance, Fourier transform infrared spectroscopy, thermal gravimetric analyzer, differential scanning calorimeter, scanning electron microscopy and gas chromatography. Results suggested that newly synthesized oligomer with the structure of PEEK absorbs short wave UV-light. Ageing tests [ISO 11979-5, Ophthalmic implants—intraocular lenses (IOL)—Part 5: Biocompatibility] performed on the IOL materials were successful. High contact angle of the obtained lenses suggests that all lenses were hydrophobic and SEM results revealed that lenses are morphologically homogeneous. Based on all positive properties just mentioned, we safely conclude that the lenses produced in this study are very promising for IOL production.     

Development of a framework for customer co-creation in NPD through multi-issue negotiation with issue trade-offs

In complex product design environments, new product development (NPD) becomes all about trade-offs and therefore trade-off management gets an important responsibility for designers. Correspondingly, in these environments, customer co-creation in NPD requires multi-issue negotiation with issue trade-offs. However, there is no study researching customer co-creation in NPD through multi-issue negotiation with issue trade-offs according to our best knowledge. This study presents a framework for customer co-creation in NPD through a multi-issue negotiation mechanism, namely; Modified Even-Swaps, to fill this gap. This mechanism uses a modified version of Even-Swaps method, that finds differences among alternatives and utilizes the differences for assessing the value of multi-issue offers, and that includes a fuzzy-inference-system for bargaining on several issues simultaneously. In the proposed framework, customers are represented by “lead-user”. Thus, negotiation is performed between lead-user and designer. In order to show how the framework works, an illustrative example is also presented.     

Technology evaluation through the use of interval type-2 fuzzy sets and systems

Even though fuzzy logic is one of the most common methodologies for matching different kind of data sources, there is no study which uses this methodology for matching publication and patent data within a technology evaluation framework according to the authors’ best knowledge. In order to fill this gap and to demonstrate the usefulness of fuzzy logic in technology evaluation, this study proposes a novel technology evaluation framework based on an advanced/improved version of fuzzy logic, namely; interval type-2 fuzzy sets and systems (IT2FSSs). This framework uses patent data obtained from the European Patent Office (EPO) and publication data obtained from Web of Science/Knowledge (WoS/K) to evaluate technology groups with respect to their trendiness. Since it has been decided to target technology groups, patent and publication data sources are matched through the use IT2FSSs. The proposed framework enables us to make a strategic evaluation which directs considerations to use-inspired basic researches, hence achieving science-based technological improvements which are more beneficial for society. A European Classification System (ECLA) class – H01-Basic Electric Elements – is evaluated by means of the proposed framework in order to demonstrate how it works. The influence of the use of IT2FSSs is investigated by comparison with the results of its type-1 counterpart. This method shows that the use of type-2 fuzzy sets, i.e. handling more uncertainty, improves technology evaluation outcomes.     

Modeling and simulation of an artificial muscle and its application to biomimetic robot posture control

The shape memory effect exhibited by Nitinol wire can be utilized to construct an artificial muscle. The muscle is activated by an electric current, which produces heat and initiates a phase transformation. The Nitinol artificial muscle stress–strain–power relationship was determined by experiments, and a mathematical model was developed. The artificial muscle model was utilized for the posture control of a biomimetic underwater robot. The optimal activation patterns for height, pitch, and roll postures were determined. Simulation results for the height postures are in agreement with the experiments. The separation between the center of gravity and the centroid of the robot has a stabilizing effect on pitch and roll postures.