Cost accounting for shared IT infrastructures

IT infrastructure, such as servers and networking equipment, accounts for a large proportion of the IT costs in modern organizations. Typically, this IT infrastructure is shared among multiple applications and customers. Cost allocation of shared IT infrastructure is difficult and regularly based on biased cost allocation keys, which often causes free-rider problems. Measuring usage is technically difficult and incurs high costs. In this paper we propose a method to derive adequate estimators for the resource consumption of a customer-oriented service. These so-called resource profiles can then provide a basis for cost allocation keys. The estimators are derived from a series of load tests, as they are typically done before an application is launched in larger organizations. Such profiles need to be unbiased and precise even in cases of varying workloads and in rather heterogeneous environments. We describe the results of a set of experiments in an infrastructure provided by the BMW Group, and illustrate how the estimation can be integrated into existing IT service management processes. In our experiments we use Queuing Networks to validate the estimated resource profiles under different workloads.     

Tiny Signals from the Human Brain: Acquisition and Processing of Biomagnetic Fields in Magnetoencephalography

Low-temperature superconductivity plays an important role in some specific biomedical applications, and, in particular, in non-invasive imaging methods of human brain activity. Superconducting magnets are indispensable for functional magnetic resonance imaging (fMRI) which allows functional imaging of the brain with high spatial but poor temporal resolution. Superconducting quantum interference devices (SQUIDs) are the most sensitive magnetic field detectors. Up to a few hundreds of SQUIDs are nowdays used in modern whole-head magnetoencephalography (MEG) systems. They allow tracking brain activation with a superior temporal resolution of milliseconds, which is a quintessential condition for the monitoring of brain dynamics and the understanding of information processing in the human brain. We introduce the prerequisites of MEG data acquisition and briefly review two established methods of biomagnetic signal processing: The concept of signal averaging, and the subsequent source identification as a solution of the biomagnetic inverse problem. Beside these standard techniques, we discuss advanced methods for signal processing in MEG, which take into account the frequency content of the recorded signal. We briefly refer to the prospects of Fourier analysis and wavelet transform in MEG data analysis, and suggest matching pursuit as a promising tool for signal decomposition and reconstruction with high resolution in time-frequency plane.     

Magnetometry of Individual Polycrystalline Ferromagnetic Nanowires

Ferromagnetic nanowires are finding use as untethered sensors and actuators for probing micro‐ and nanoscale biophysical phenomena, such as for localized sensing and application of forces and torques on biological samples, for tissue heating through magnetic hyperthermia, and for microrheology. Quantifying the magnetic properties of individual isolated nanowires is crucial for such applications. Dynamic cantilever magnetometry is used to measure the magnetic properties of individual sub‐500 nm diameter polycrystalline nanowires of Ni and Ni₈₀Co₂₀ fabricated by template‐assisted electrochemical deposition. The values are compared with bulk, ensemble measurements when the nanowires are still embedded within their growth matrix. It is found that single‐particle and ensemble measurements of nanowires yield significantly different results that reflect inter‐nanowire interactions and chemical modifications of the sample during the release process from the growth matrix. The results highlight the importance of performing single‐particle characterization for objects that will be used as individual magnetic nanoactuators or nanosensors in biomedical applications.     

Level‐of‐Detail Streaming and Rendering using Bidirectional Sparse Virtual Texture Functions

Bidirectional Texture Functions (BTFs) are among the highest quality material representations available today and thus well suited whenever an exact reproduction of the appearance of a material or complete object is required. In recent years, BTFs have started to find application in various industrial settings and there is also a growing interest in the cultural heritage domain. BTFs are usually measured from real‐world samples and easily consist of tens or hundreds of gigabytes. By using data‐driven compression schemes, such as matrix or tensor factorization, a more compact but still faithful representation can be derived. This way, BTFs can be employed for real‐time rendering of photo‐realistic materials on the GPU. However, scenes containing multiple BTFs or even single objects with high‐resolution BTFs easily exceed available GPU memory on today's consumer graphics cards unless quality is drastically reduced by the compression. In this paper, we propose the Bidirectional Sparse Virtual Texture Function, a hierarchical level‐of‐detail approach for the real‐time rendering of large BTFs that requires only a small amount of GPU memory. More importantly, for larger numbers or higher resolutions, the GPU and CPU memory demand grows only marginally and the GPU workload remains constant. For this, we extend the concept of sparse virtual textures by choosing an appropriate prioritization, finding a trade off between factorization components and spatial resolution. Besides GPU memory, the high demand on bandwidth poses a serious limitation for the deployment of conventional BTFs. We show that our proposed representation can be combined with an additional transmission compression and then be employed for streaming the BTF data to the GPU from from local storage media or over the Internet. In combination with the introduced prioritization this allows for the fast visualization of relevant content in the users field of view and a consecutive progressive refinement.     

语义信息与CRF结合的汉语功能块自动识别

为了构建汉语功能块自动识别系统,该文利用条件随机域模型对经过正确词语切分和词性标注处理的汉语句子进行功能块边界识别和功能信息标注处理,通过在特征提取阶段优化组合丰富的上下文特征,得到功能块识别的精确率、召回率和F1-measure值分别为85.84%、85.07%和85.45%。在此基础上,该文引入由词义聚合关系将汉语单词组织起来的《同义词词林》作为语义资源,把其中的语义信息作为特征加入到功能块的识别过程,缓解了数据稀疏以及歧义问题对识别结果造成的影响,使得上述三个性能指标分别提高到86.21%、85.31%和85.76%。     

Formalizing non-termination of recursive programs

In applicative theories the recursion theorem provides a term which solves recursive equations. However, it is not provable that a solution obtained by is minimal. In the present paper we introduce an applicative theory in which it is possible to define a least fixed point operator. Still, our theory has a standard recursion theoretic interpretation.     

Clinorotation Increases the Growth of Utricular Otoliths of Developing Cichlid Fish

It has been shown earlier that hypergravity slows down inner ear otolith growth in developing fish as an adaptation towards increased environmental gravity. Suggesting that otolith growth is regulated by the central nervous system, thus adjusting otolithic weight to produce a test mass, applying functional weightlessness should yield an opposite effect, i.e. larger than normal otoliths. Therefore, larval siblings of cichlid fish (Oreochromis mossambicus) were housed for 7 days in a submersed, two-dimensional clinostat, which provided a residual gravity of approximately 0.007g. After the experiment, otoliths were dissected and their size (area grown during the experiment) was determined. Maintenance in the clinostat resulted in significantly larger utricular otoliths (lapilli, involved in graviperception). There were no statistical significant differences regarding saccular otoliths obtained (sagittae, involved in transmitting linear acceleration and, especially, in the hearing process). These results indicated, that the animals had in fact received functional weightlessness. In line and contrasting results on the otoliths of other teleost species kept at actual microgravity (spaceflight) or within rotating wall vessels are discussed.     

Pathways and pitfalls of implementing the use of woodfuels in Germany's bioenergy sector

The paper presents an empirical study on the use of woody biomass for energy supply in Germany and the federal state of Brandenburg. It aims to explain the role forestry enterprises have for bioenergy provision in this area. The ‘Institutions of Sustainability’ framework is used as an analytical tool to investigate the role of private and public actors in these transactions, respectively, in the governance structures they are subject to. Empirical evidence was gathered by in-depth interviews with actors from forestry and bioenergy practice. Triggered by favorable governance structures, i.e. strong support by national and regional policies, rising prices for fossil energy sources, and co-operation of committed individuals and groups, a new bioenergy industry has been successfully established. However, the forestry sector has so far been just a marginal fuel supplier for this industry. The study identifies pitfalls impeding a broad implementation of wood-energy supply in forestry: not cost-covering prices offered by the bioenergy sector, lacking market transparency and security of supply, lacking mobilization of forest wood, and a preference among forest managers to sell products to the wood-processing industry. In terms of the Institutions of Sustainability the properties of transactions (asset specificities, uncertainties, separability), characteristics of actors (values, rationality) and governance structures (long-term contractual obligations elsewhere) are decisive in explaining the current form of transaction.     

Consideration of the mechanical behaviour of small fatigue cracks

The mechanical behaviour of small fatigue cracks is investigated for a low, medium and high strength material. At first an elastic consideration is performed which give a good impression how the stress fields change with crack size. In part 2 a full elastic-plastic analysis of short cracks is performed using a new numerical scheme to simulate the growth of shear bands emanating from the crack tip. The influence of material and loading paramters as well as of the crack size on the plastic crack tip opening displacement is discussed. It is also investigated how it is possible to get a conservative estimate of the crack tip deformation at small cracks.