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Smartphone Forensik
(2012)
Auswahl der Herniennetze nach der “effektiven Porosität” - warum das Gewicht weniger wichtig ist
(2012)
If we think about applications for modern Power MOSFETs using trench technology, running them in linear mode may not be top of the priority list. Yet there are multiple uses for Trench Power MOSFETs in linear mode. In fact, even turning the device on and off in switching applications is a form of linear operation. Also, these components can be run in linear mode to protect the device against voltage surges. This article will illustrate the factors that need to be considered for linear operation and show how Trench Power MOSFETs are suited to it.
Many tasks for autonomous agents or robots are best described by a specification of the environment and a specification of the available actions the agent or robot can perform. Combining such a specification with the possibility to imperatively program a robot or agent is what we call the actionbased imperative programming. One of the most successful such approaches is Golog. In this paper, we draft a proposal for a new robot programming language YAGI, which is based on the action-based imperative programming paradigm. Our goal is to design a small, portable stand-alone YAGI interpreter. We combine the benefits of a principled domain specification with a clean, small and simple programming language, which does not exploit any side-effects from the implementation language. We discuss general requirements of action-based programming languages and outline YAGI, our action-based language approach which particularly aims at embeddability.
As the potential of a next generation network (NGN) is recognised, telecommunication companies consider switching to it. Although the implementation of an NGN seems to be merely a modification of the network infrastructure, it may trigger or require changes in the whole company, because it builds upon the separation between service and transport, a flexible bundling of services to products and the streamlining of the IT infrastructure. We propose a holistic framework, structured into the layers ‘strategy’, ‘processes’ and ‘information systems’ and incorporate into each layer all concepts necessary for the implementation of an NGN, as well as the alignment of these concepts. As a first proof-of-concept for our framework we have performed a case study on the introduction of NGN in a large telecommunication company; we show that our framework captures all topics that are affected by an NGN implementation.
s the magnetic field strength and therefore the operational frequency in MRI are increased, the radiofrequency wavelength approaches the size of the human head/body, resulting in wave effects which cause signal decreases and dropouts. Especially, whole-body imaging at 7 T and higher is therefore challenging. Recently, an acquisition scheme called time-interleaved acquisition of modes has been proposed to tackle the inhomogeneity problems in high-field MRI. The basic premise is to excite two (or more) different Burn:x-wiley:07403194:media:MRM23081:tex2gif-stack-1 modes using static radiofrequency shimming in an interleaved acquisition, where the complementary radiofrequency patterns of the two modes can be exploited to improve overall signal homogeneity. In this work, the impact of time-interleaved acquisition of mode on image contrast as well as on time-averaged specific absorption rate is addressed in detail. Time-interleaved acquisition of mode is superior in Burn:x-wiley:07403194:media:MRM23081:tex2gif-stack-2 homogeneity compared with conventional radiofrequency shimming while being highly specific absorption rate efficient. Time-interleaved acquisition of modes can enable almost homogeneous high-field imaging throughout the entire field of view in PD, T2, and T2*-weighted imaging and, if a specified homogeneity criterion is met, in T1-weighted imaging as well.
31P MR spectroscopic imaging of the human prostate provides information about phosphorylated metabolites that could be used for prostate cancer characterization. The sensitivity of a magnetic field strength of 7 T might enable 3D 31P MR spectroscopic imaging with relevant spatial resolution in a clinically acceptable measurement time. To this end, a 31P endorectal coil was developed and combined with an eight-channel 1H body-array coil to relate metabolic information to anatomical location. An extensive safety validation was performed to evaluate the specific absorption rate, the radiofrequency field distribution, and the temperature distribution of both coils. This validation consisted of detailed Finite Integration Technique simulations, confirmed by MR thermometry and Burn:x-wiley:07403194:media:MRM24175:tex2gif-stack-1 measurements in a phantom and in vivo temperature measurements. The safety studies demonstrated that the presence of the 31P endorectal coil had no influence on the specific absorption rate levels and temperature distribution of the external eight-channel 1H array coil. To stay within a 10 g averaged local specific absorption rate of 10 W/kg, a maximum time-averaged input power of 33 W for the 1H array coil was allowed. For transmitting with the 31P endorectal coil, our safety limit of less than 1°C temperature increase in vivo during a 15-min MR spectroscopic imaging experiment was reached at a time-averaged input power of 1.9 W. With this power setting, a second in vivo measurement was performed on a healthy volunteer. Using adiabatic excitation, 3D 31P MR spectroscopic imaging produced spectra from the entire prostate in 18 min with a spatial resolution of 4 cm3. The spectral resolution enabled the separate detection of phosphocholine, phosphoethanolamine, inorganic phosphate, and other metabolites that could play an important role in the characterization of prostate cancer.
This contribution discusses the utilization of RF power in an MRI system with RF mode shimming which enables the superposition of circularly polarized modes of a transmit RF coil array driven by a Butler matrix. Since the required power for the individual modes can vary widely, mode-shimming can result in a significant underutilization of the total available RF power. A variable power combiner (VPC) is proposed to improve the power utilization: it can be realized as a reconfiguration of the MRI transmit system by the inclusion of one additional matrix network which receives the power from all transmit amplifiers at its input ports and provides any desired (combined) power distribution at its output ports by controlling the phase and amplitude of the amplifiers’ input signals. The power distribution at the output ports of the VPC is then fed into the “mode” ports of the coil array Butler matrix in order to superimpose the spatial modes at the highest achievable power utilization. The VPC configuration is compared to the standard configuration of the transmit chain of our MRI system with 8 transmit channels and 16 coils. In realistic scenarios, improved power utilization was achieved from 17% to 60% and from 14% to 55% for an elliptical phantom and a region of interest in the abdomen, respectively, and an increase of the power utilization of 1 dB for a region of interest in the upper leg. In general, it is found that the VPC allows significant improvement in power utilization when the shimming solution demands only a few modes to be energized, while the technique can yield loss in power utilization in cases with many modes required at high power level.
In this paper we present CAESAR, an intelligent domestic service robot. In domestic settings for service robots complex tasks have to be accomplished. Those tasks benefit from deliberation, from robust action execution and from flexible methods for human–robot interaction that account for qualitative notions used in natural language as well as human fallibility. Our robot CAESAR deploys AI techniques on several levels of its system architecture. On the low-level side, system modules for localization or navigation make, for instance, use of path-planning methods, heuristic search, and Bayesian filters. For face recognition and human–machine interaction, random trees and well-known methods from natural language processing are deployed. For deliberation, we use the robot programming and plan language READYLOG, which was developed for the high-level control of agents and robots; it allows combining programming the behaviour using planning to find a course of action. READYLOG is a variant of the robot programming language Golog. We extended READYLOG to be able to cope with qualitative notions of space frequently used by humans, such as “near” and “far”. This facilitates human–robot interaction by bridging the gap between human natural language and the numerical values needed by the robot. Further, we use READYLOG to increase the flexible interpretation of human commands with decision-theoretic planning. We give an overview of the different methods deployed in CAESAR and show the applicability of a system equipped with these AI techniques in domestic service robotics