Clusteranalyse von Smart-Meter-Daten

The introduction of smart meter technology is a great challenge for the German energy industry. It requires not only large investments in the communication and metering infrastructure, but also a redesign of traditional business processes. The newly incurring costs cannot be fully passed on to the end customers. One option to counterbalance these expenses is to exploit the newly generated smart metering data for the creation of new services and improved processes. For instance, performing a cluster analysis of smart metering data focused on the customers?? time-based consumption behavior allows for a detailed customer segmentation. In the article we present a cluster analysis performed on real-world consumption data from a smart meter project conducted by a German regional utilities company. We show how to integrate a cluster analysis approach into a business intelligence environment and evaluate this artifact as defined by design science. We discuss the results of the cluster analysis and highlight options to apply them to segment-specific tariff design.     

A knowledge-based system for improving the consistency between object models and use case narratives

In today’s systems development environments, object models are playing an increasingly important role in contributing to the agility and flexibility expected of the information systems being built. While current computer-aided software engineering tools can aid in creating object models, they do not provide much support in ensuring that the object models created are consistent with the specifications in use case narratives. This paper presents a methodology and a knowledge-based system to facilitate the verification of consistency of a given object model against a set of use case narratives. The methodology is implemented as a prototype knowledge-based extension to an open source CASE tool. The prototype’s ability to reliably extract relevant information from use case narratives and its role in verifying the consistency of object models have been evaluated using a laboratory experiment. By analyzing use case narratives utilizing natural language processing techniques and applying collaboration patterns and heuristics, this methodology can determine missing and invalid model elements to guide the analyst in creating object models that are consistent with the requirements specified in a set of use case narratives. The results from this design science research indicate that the prototype system can be a useful tool to assist in this process.     

Online scheduling of bounded length jobs to maximize throughput

We consider an online scheduling problem, motivated by the issues present at the joints of networks using ATM and TCP/IP. Namely, IP packets have to be broken down into small ATM cells and sent out before their deadlines, but cells corresponding to different packets can be interwoven. More formally, we consider the online scheduling problem with preemptions, where each job j is revealed at release time r _j , and has processing time p _j , deadline?d _j , and weight w _j . A?preempted job can be resumed at any time. The goal is to maximize the total weight of all jobs completed on time. Our main results are as follows. Firstly, we prove that when the processing times of all jobs are at most k, the optimum deterministic competitive ratio is ??(k/log?k). Secondly, we give a deterministic algorithm with competitive ratio depending on the ratio between the smallest and the largest processing time of all jobs. In particular, it attains competitive ratio 5 in the case when all jobs have identical processing times, for which we give a lower bound of 2.598. The latter upper bound also yields an O(log?k)-competitive randomized algorithm for the variant with processing times bounded by k.     

Viscose‐based porous carbon fibers: improving yield and porosity through optimization of the carbonization process by design of experiment

Journal of Porous Materials - In this study, the production of porous carbon fibers from viscose fibers was investigated. The effects of final carbonization temperature...     

Decellularized Cartilage Extracellular Matrix Incorporated Silk Fibroin Hybrid Scaffolds for Endochondral Ossification Mediated Bone Regeneration

Tissue engineering strategies promote bone regeneration for large bone defects by stimulating the osteogenesis route via intramembranous ossification in engineered grafts, which upon implantation are frequently constrained by insufficient integration and functional anastomosis of vasculature from the host tissue. In this study, we developed a hybrid biomaterial incorporating decellularized cartilage extracellular matrix (CD-ECM) as a template and silk fibroin (SF) as a carrier to assess the bone regeneration capacity of bone marrow-derived mesenchymal stem cells (hBMSC’s) via the endochondral ossification (ECO) route. hBMSC’s were primed two weeks for chondrogenesis, followed by six weeks for hypertrophy onto hybrid CD-ECM/SF or SF alone scaffolds and evaluated for the mineralized matrix formation in vitro. Calcium deposition biochemically determined increased significantly from 4-8 weeks in both SF and CD-ECM/SF constructs, and retention of sGAG’s were observed only in CD-ECM/SF constructs. SEM/EDX revealed calcium and phosphate crystal localization by hBMSC’s under all conditions. Compressive modulus reached a maximum of 40 KPa after eight weeks of hypertrophic induction. μCT scanning at eight weeks indicated a cloud of denser minerals in groups after hypertrophic induction in CD-ECM/SF constructs than SF constructs. Gene expression by RT-qPCR revealed that hBMSC’s expressed hypertrophic markers VEGF, COL10, RUNX2, but the absence of early hypertrophic marker ChM1 and later hypertrophic marker TSBS1 and the presence of osteogenic markers ALPL, IBSP, OSX under all conditions. Our data indicate a new method to prime hBMSC’S into the late hypertrophic stage in vitro in mechanically stable constructs for ECO-mediated bone tissue regeneration.     

A Versatile Toolkit for Semi-Automated Production of Fluorescent Chemokines to Study CCR7 Expression and Functions

Chemokines guide leukocyte migration in different contexts, including homeostasis, immune surveillance and immunity. The chemokines CCL19 and CCL21 control lymphocyte and dendritic cell migration and homing to lymphoid organs. Thereby they orchestrate adaptive immunity in a chemokine receptor CCR7-dependent manner. Likewise, cancer cells that upregulate CCR7 expression are attracted by these chemokines and metastasize to lymphoid organs. In-depth investigation of CCR7 expression and chemokine-mediated signaling is pivotal to understand their role in health and disease. Appropriate fluorescent probes to track these events are increasingly in demand. Here, we present an approach to cost-effectively produce and fluorescently label CCL19 and CCL21 in a semi-automated process. We established a versatile protocol for the production of recombinant chemokines harboring a small C-terminal S6-tag for efficient and site-specific enzymatic labelling with an inorganic fluorescent dye of choice. We demonstrate that the fluorescently labeled chemokines CCL19-S6^Dy649P1 and CCL21-S6^Dy649P1 retain their full biological function as assessed by their abilities to mobilize intracellular calcium, to recruit β-arrestin to engaged receptors and to attract CCR7-expressing leukocytes. Moreover, we show that CCL19-S6^Dy649P1 serves as powerful reagent to monitor CCR7 internalization by time-lapse confocal video microscopy and to stain CCR7-positive primary human and mouse T cell sub-populations.     

Material Flow Control and Optimization in High‐Pressure Sheet Metal Forming by Active‐Elastic Tools

High‐pressure forming of metal sheets is an innovative forming technology for the production of complex components and offers high potentials to improve the properties and qualities of sheet metal parts. This report describes investigations of a newly developed active‐elastic tool system referred to as ACTEC system. Unlike the use of a comparable semi‐rigid tool system, the ACTEC system shows improvements with respect to the material flow in the flange area and reduced sheet thinning in critical corner regions of the workpiece. In addition, the clamping forces respectively sealing forces necessary to avoid leakage in the tool system during the forming process can be reduced. Moreover, the specific design of the ACTEC‐system as well as current experimental examinations are presented and discussed.     

Models of non‐smooth switches in electrical systems

Idealized modelling of diodes, relays and switches in the framework of linear complementarity is introduced. Within the charge approach, the classical electromechanical analogy is extended to passively and actively switching components in electrical circuits. The associated branch relations are expressed in terms of set‐valued functions, which allow to formulate the circuit's dynamic behaviour as a differential inclusion. This approach is demonstrated by the example of the DC–DC buck converter. A difference scheme, known in mechanics as time stepping, is applied for numerical approximation of the evolution problem. The discretized inclusions are formulated as a linear complementarity problem in standard form, which implicitly takes care of all switching events by its solution. State reduction, which requires manipulation of the set‐valued branch relations in order to obtain a minimal model, is performed on the example of the buck converter. Copyright © 2005 John Wiley & Sons, Ltd.     

Level-of-detail for cognitive real-time characters

We present a solution for the real-time simulation of artificial environments containing cognitive and hierarchically organized agents at constant rendering framerates. We introduce a level-of-detail concept to behavioral modeling, where agents populating the world can be both reactive and proactive. The disposable time per rendered frame for behavioral simulation is variable and determines the complexity of the presented behavior. A special scheduling algorithm distributes this time to the agents depending on their level-of-detail such that visible and nearby agents get more time than invisible or distant agents. This allows for smooth transitions between reactive and proactive behavior. The time available per agent influences the proactive behavior, which becomes more sophisticated because it can spend time anticipating future situations. Additionally, we exploit the use of hierarchies within groups of agents that allow for different levels of control. We show that our approach is well-suited for simulating environments with up to several hundred agents with reasonable response times and the behavior adapts to the current viewpoint.     

Semantic social overlay networks

Peer selection for query routing is a core task in peer-to-peer networks. Unstructured peer-to-peer systems (like Gnutella) ignore this problem, leading to an abundance of network traffic. Structured peer-to-peer systems (like Chord) enforce a particular, global way of distributing data among the peers in order to solve this problem, but then encounter problems of network volatility and conflicts with the autonomy of the peer data management. In this paper, we propose a new mechanism, INGA, which is based on the observation that query routing in social networks is made possible by locally available knowledge about the expertise of neighbors and a semantics-based peer selection function. We validate INGA by simulation experiments with different data sets. We compare INGA with competing peer selection mechanisms on resulting parameters like recall, message gain or number of messages produced