Designing robustly stabilising controllers for LTI spatially distributed systems using coprime factor synthesis

This paper considers the design of feedback controllers for linear, time-invariant, spatially distributed systems in an approach which generalises the H^∞-framework and in particular the H^∞ loop-shaping method. To this end, we introduce a class of spatially distributed system models called finite dimensional, distributed, linear, time-invariant systems. Sensors and actuators are considered to be part of the controller, rather than part of the plant, and thus the controller we wish to design is itself a spatially distributed system. Optimising over placements and shapes of the sensor and actuator spatial distribution functions is an integrated part of the controller design procedure. As an illustrative design example, we present the feedback stabilisation of an electrostatically destabilised, electrically conducting membrane.     

Physiological cost of energy-equivalent noise exposures with a rating level of 85 dB(A):: Hearing threshold shifts associated with energetically negligible continuous and impulse noise

In industry continuous or impulse noise does not occur exclusively; rather it is a combination of both. If low-level continuous noise or impulse noise (below 120 dB) is added to an already existing high-level continuous noise this often numerically causes no essential increase in the rating level. Yet, it cannot be expected that also aural strain of these exposures is always negligible. Therefore, in a cross-over test series, ten male subjects (Ss) were exposed to white noise of 94 dB(A) for 1 h (TS I), energy-equivalent to an 8 h-rating level L_Ard of 85 dB(A). In a second test series (TS II) the same exposure was combined with 900 energetically negligible 5-ms impulses with a noise level of 113 dB(A) which increased the rating level by only 0.4 dB. The noise exposure of TS I and TS II was followed by an idealized resting phase in a soundproof cabin. In a third test series (TS III) the continuous noise of 94 dB(A) / 1 h was followed by 3 h of white noise at 70 dB(A). Such an additional load increases the L_Ard by merely 0.1 dB to 85.1 dB(A). In all three test series, the noise-induced temporary threshold shift (TTS₂) and its restitution were measured. The continuous noise exposure of 94 dB(A) for 1 h was associated with a TTS₂ of around 20 dB which disappeared completely after about 2 h. The additional impulse noise caused a small increase in the TTS₂ and a prolongation of the restitution time. The maximum mean temporary threshold shift for the group increased only slightly (from 22.5 to 25.9 dB, which nevertheless can be statistically proven at a significance level of p 0.99). Yet, more importantly, the restitution time increased from 126 to 175 min, i. e. 3 h, which can be statistically proven at a significance level of p0.95. The TTS₂-values of TS III did not differ significantly from those resulting from TS I. That was expected as the conditions up to that point in time were identical. But due to the additional subsequent exposure, the mean restitution time increased considerably from 126 min up to 240 min (4 h). The mean total physiological cost represented by the integrated restitution temporary threshold shift (IRTTS) increased in TS II by approximately 40% and in TS III even by 140%.

Relevance to industry

The results of the study show that levels of noise which have no influence on the rating level which traditionally is calculated according to the energy-equivalence principle are often of great importance, as they can lead to considerably prolonged restitution times. Therefore, the purely energy-equivalent determination of the rating level of both impulse noise and low sound levels can lead to an underestimation of latent problems so that over time a reversible TTS can evolve into a permanent threshold shift. The results are also of importance for the acoustic design of break rooms for noise-exposed workers. There should be conditions that allow an undisturbed restitution of hearing.     

Model-based cloud resource management with TOSCA and OCCI

Software and Systems Modeling - With the advent of cloud computing, different cloud providers with heterogeneous cloud services (compute, storage, network, applications, etc.) and their related...     

Simulating the spread of opinions in online social networks when targeting opinion leaders

An increasing number of people are joining online social networks. By interacting with each other, network members influence one another’s opinion. These influencing effects can be utilized by marketing. A wave of influence can be triggered by addressing only a few opinion leaders in the network. Targeting the right opinion leaders is a big challenge. This paper presents a new approach which simulates the spread of opinions when influencing certain opinion leaders. In contrast to other approaches, the influencing effects are not assumed but revealed by real data. The principles of opinion formation are detected by ant mining algorithms before they are applied to simulate the spread of opinions. The approach is applied to an online gaming community and provides valuable insights for marketing.     

Relative deprivation and energy poverty: when does unequal access to electricity cause dissatisfaction?

In the least developed countries, unequal access to infrastructure is a major form of inequality. We examine the conditions under which unequal electricity access causes dissatisfaction. The question is important because grievances could prompt demands for policy change. We argue that feelings of relative deprivation both cause dissatisfaction and create hope for improvement. Empirically, we analyze household survey data from five East African countries. All else constant, households living close to a power line are less satisfied with their lighting solution but also have more hope for improvement. Because household lighting is the most important use for electricity in a poor household, this supports the relative deprivation hypothesis. Households that are reminded of their deprivation by the power line are both less satisfied and believe something can be done to solve the problem. To inform policy, we also show that the proximity of a power line decreases the household's interest in solar home systems as an alternative to grid electrification, whereas valuation for solar lanterns seems to be increasing. Copyright © 2014 John Wiley & Sons, Ltd.     

Current Status of Long Non-Coding RNAs in Human Cancer with Specific Focus on Colorectal Cancer

The latest investigations of long non-coding RNAs (lncRNAs) have revealed their important role in human cancers. LncRNAs are larger than 200 nucleotides in length and fulfill their cellular purpose without being translated into proteins. Though the molecular functions of some lncRNAs have been elucidated, there is still a high number of lncRNAs with unknown or controversial functions. In this review, we provide an overview of different lncRNAs and their role in human cancers. In particular, we emphasize their importance in tumorigenesis of colorectal cancer, the third most common cancer worldwide.     

Data-driven parameterization of polymer electrolyte membrane fuel cell models via simultaneous local linear structured state space identification

In order to mitigate the degradation and prolong the lifetime of polymer electrolyte membrane fuel cells, advanced, model-based control strategies are becoming indispensable. Thereby, the availability of accurate yet computationally efficient fuel cell models is of crucial importance. Associated with this is the need to efficiently parameterize a given model to a concise and cost-effective experimental data set. A challenging task due to the large number of unknown parameters and the resulting complex optimization problem. In this work, a parameterization scheme based on the simultaneous estimation of multiple structured state space models, obtained by analytic linearization of a candidate fuel cell stack model, is proposed. These local linear models have the advantage of high computational efficiency, regaining the desired flexibility required for the typically iterative task of model parameterization. Due to the analytic derivation of the local linear models, the relation to the original parameters of the non-linear model is retained. Furthermore, the local linear models enable a straight-forward parameter significance and identifiability analysis with respect to experimental data. The proposed method is demonstrated using experimental data from a 30 kW commercial polymer electrolyte membrane fuel cell stack.