Agency: Cordis | Branch: FP7 | Program: CSA | Phase: ICT-2013.3.2 | Award Amount: 4.65M | Year: 2013
The aim of SSL-erate is to accelerate the uptake of high-quality SSL technology in Europe by means of open innovation with and by bringing validated information to all relevant stakeholders. A coordinated European effort is required to address the European societal challenges (in particular health & quality of life in an ageing society, energy consumption and resource efficiency), to resolve the specific challenges of the Lighting industry as noted in the results of the Green Paper Lighting the Future consultation (notably: poor SSL quality, lack of information and awareness among citizens) and to enable lighting solutions with a societal and environmental sustainability perspective, leading to a future in which Europe evolves to the global leadership in SSL systems and solutions. The lighting industry is highly fragmented. As a consequence of this the innovation speed and success rate have been too low and the benefits that we all expect from better lighting solutions, do not sufficiently materialize. To overcome this fragmentation, a collaborative way-of-working, using open-innovation and smart specialization principles, will be taken as the guiding approach. The active involvement of various stakeholders will be realized through workshops, but also through the creation of a web-based SSL-erate Innovation platform, which is planned to continue beyond the duration of this project. Relevant (lighting and non-lighting) companies, but also other stakeholders (like e.g. public authorities, property owners, research institutes, (lead) users/citizens, entrepreneurs, architects, installers) will become active contributors to this accelerated innovation process by applying validated insights on green business development and lighting effects on health & well-being in SSL business experiments.
Peters G.,Munich University of Applied Sciences
IEEE Transactions on Fuzzy Systems | Year: 2011
Granular computing (GrC) has gained increasing attention in the past decade. Although not uniquely defined, its basic idea is to approximate detailed machine-like information by a coarser presentation on a human-like level. Within granular computing, the mapping of continuous variables into intervals plays an important role. These intervals are often prerequisites for the formulation of linguistic variables. In this paper, we suggest a piecewise interval approximation and propose granular box regression. Its objective is to establish relationships between independent and dependent variables by multidimensional boxes. We interpret granular box regression as interval regression and show its potential for the extraction of fuzzy rules from data. In two experiments, we apply granular box regression to an artificial as well as to a real dataset in the field of finance and evaluate its properties. © 2011 IEEE.
Lachenmaier S.,Ludwig Maximilians University of Munich |
Rottmann H.,Munich University of Applied Sciences
International Journal of Industrial Organization | Year: 2011
This paper estimates the effect of innovation on employment at the firm level. Our uniquely long innovation panel data set of German manufacturing firms covers more than 20 years and allows us to use various innovation measures. We can distinguish between product and process innovations as well as between innovation input and innovation output measures. Using dynamic panel GMM system estimation we find positive effects of innovation on employment. This is true for innovation input as well as for innovation output variables. Innovations show their positive effect on employment with a time lag and process innovations have higher effects than product innovations. © 2010 Elsevier B.V. All rights reserved.
Schmidbauer H.,Istanbul Bilgi University |
Rosch A.,Munich University of Applied Sciences
Energy Economics | Year: 2012
Several times a year, OPEC hosts conferences among its members to agree on further oil production policies. Prior to OPEC conferences, there is usually rampant speculation about which decision concerning world oil production levels (no change, increase, or cut) will be announced. The purpose of our investigation is to assess the impact of OPEC announcements on expectation and volatility of daily oil price changes (returns).We modify dummy variables indicating the day of an OPEC announcement to reflect a certain pattern of impact on return expectation and volatility. A combination of regression and GARCH models can then differentiate between pre- and post-announcement effects, and distinguish between the three kinds of OPEC decisions. We find evidence for a post-announcement effect on expectation, which is negative in the case of a cut decision and positive in case of an increase or maintain decision, while there is a positive pre-announcement effect on volatility, which is strongest in the case of a cut decision. © 2012 Elsevier B.V.
Seitz M.J.,Munich University of Applied Sciences |
Koster G.,Munich University of Applied Sciences
Physical Review E - Statistical, Nonlinear, and Soft Matter Physics | Year: 2012
Is there a way to describe pedestrian movement with simple rules, as in a cellular automaton, but without being restricted to a cellular grid? Inspired by the natural stepwise movement of humans, we develop a model that uses local discretization on a circle around virtual pedestrians. This allows for movement in arbitrary directions, only limited by the chosen optimization algorithm and numerical resolution. The radii of the circles correspond to the step lengths of pedestrians and thus are model parameters, which must be derived from empirical observation. Therefore, we conducted a controlled experiment, collected empirical data for step lengths in relation with different speeds, and used the findings in our model. We complement the model with a simple calibration algorithm that allows reproducing known density-velocity relations, which constitutes a proof of concept. Further validation of the model is achieved by reenacting an evacuation scenario from experimental research. The simulated egress times match the values reported for the experiment very well. A new normalized measure for space occupancy serves to visualize the results. © 2012 American Physical Society.
Peters G.,Munich University of Applied Sciences |
Peters G.,Australian Catholic University
Information Sciences | Year: 2014
Clustering is one of the most widely used method in data mining with applications in virtually any domain. Its main objective is to group similar objects into the same cluster, while dissimilar objects should belong to different clusters. In particular k-means clustering, as member of the partitioning clustering family, has obtained great popularity. The classic (hard) k-means assigns an object unambiguously to one and only one cluster. To address uncertainty soft clustering has been introduced using concepts like fuzziness, possibility or roughness. A decade ago Lingras and West introduced a k-means approach based on the interval interpretation of rough sets theory. In the past years their rough k-means has gained increasing attention. In our paper, we propose a refined rough k-means algorithm that utilizes Laplace's principle of indifference to calculate the means. As we will discuss this provides a sounder justification for the impacts of the objects in the approximations in comparison to established rough k-means algorithms. Furthermore, the weighting in the mean function is based on individual objects rather than on aggregated sub-means. In experiments, we compare the refined algorithm to related approaches. © 2014 Elsevier Inc. All rights reserved.
Yao W.,Munich University of Applied Sciences |
Krzystek P.,Munich University of Applied Sciences |
Heurich M.,Bavarian Forest National Park
Remote Sensing of Environment | Year: 2012
The paper highlights recent results of forest structure analysis at single tree level based on analyzing airborne full waveform LiDAR data. Single trees are automatically detected by a 3D segmentation technique applied directly to laser point clouds, which uses the normalized cut segmentation combined with a stem detection method. A subsequent classification identifies tree species using salient features that are defined on single 3D tree segments and utilize the additional information extracted from the reflected laser signal by the waveform decomposition. The stem volume and diameter at breast height (DBH) are estimated by a multiple linear regression analysis which uses tree shape parameters derived from the 3D model of the trees. Experiments were conducted in the Bavarian Forest National Park with full waveform LiDAR data. The data were captured with the Riegl LMS Q-560 system at a point density of 25points/m 2 under leaf-off and leaf-on conditions. The analysis of waveform data in the tree structure shows that the intensity and pulse width discriminate stem points, crown points and ground points significantly. The unsupervised classification of deciduous and coniferous trees is in the best case 93%. If a supervised classification is applied the accuracy is slightly increased to 95%. Concerning stem volume estimation, in the case of coniferous trees the study shows a low RMSE of about 0.46m 3 to 0.43m 3 both for the watershed segmentation and the new normalized cut segmentation. In the case of deciduous trees RMSE has increased by 14% in leaf off condition and by 4% in leaf on condition for the normalized cut segmentation. A similar trend can be confirmed for DBH estimation as well, even demonstrating a larger benefit from 3D segmentation. The study results proved that the 3D segmentation approach is not only capable of detecting more small trees in the lower forest layer but also can allow to derive more promising features of single trees used for yielding better performance in species classification and estimation of forest structural parameters, especially for deciduous trees. © 2012 Elsevier Inc.
Klug F.,Munich University of Applied Sciences
International Journal of Production Research | Year: 2013
The paper describes variance amplification of orders in a car manufacturing context. Demand fluctuation in inter-company supply chains has been well described in literature over many years. The specific contribution of this paper is to examine the cyclical boom-and-bust behaviour, commonly known as the bullwhip effect, inside the plant boundaries of a single company with the help of system dynamics modelling. To gain insight into this phenomenon we will first perform an extensive literature review on the subject of factory relevant internal bullwhip. Based on these results we illustrate through a real-life car assembly operation the existence of internal bullwhip. Finally we conclude with a discussion of our results and future research opportunities. © 2013 Copyright Taylor and Francis Group, LLC.
Munich University of Applied Sciences | Date: 2013-05-03
The amplifier according to the present invention serves to amplify an input signal to an output signal and includes a signal path and a negative feedback connection. The signal path includes a modulator which is suitable for receiving the input signal and for generating a switching signal in response to the received input signal. The signal path further includes a switched output stage, which is connected to a supply voltage, wherein the switched output stage contains a switch that is switched according to the switching signal generated by the modulator, wherein the switched output stage generates an output signal the amplitude of which depends on the supply voltage.
Munich University of Applied Sciences | Date: 2011-08-12
The invention provides a device and method for wireless transmission of energy. An electromagnetic field used for transmitting energy is generated using a resonator system comprising a plurality of weakly coupled resonators, the resonator system having a plurality of eigenmodes with different eigenfrequencies. At least one generator is coupled to one of the resonators. The resonator is configured to operate the resonator system at one of the plurality of eigenmodes, thereby generating a spatially coherent magnetic field adapted for transmitting energy to an appliance.