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Millimeter-wave (mmWave) frequencies are set to play an important role in fifth-generation (5G) wireless systems. A pre-requisite for the design and performance assessment of 5G wireless is the understanding of the involved propagation processes and derivation of insightful channel models. Unlike bands below 6 GHz, several additional modelling features need to be catered for at mmWaves. For dynami

We consider the over-fitting problem for multinomial probabilistic Latent Semantic Analysis (pLSA) in collaborative filtering, using a regularization approach. For big data applications, the computational complexity is at a premium and we, therefore, consider a maximum a posteriori approach based on conjugate priors that ensure that complexity of each step remains the same as compared to the un-re

Detecting fires at an early stage is crucial for mitigating and extinguishing fires. The increased use of biofuels in Northern Europe has led to an increased number of fires in storage facilities. These fires are often caused by self-heating in the interior of the stored materials and slowly develop to smouldering fires. Consequently, these smouldering fires are usually detected several days or we

Using NMR and Monte Carlo (MC) methods, we investigate the stability and dynamics of superoxide dismutase 1 (SOD1) in homogeneous crowding environments, where either bovine pancreatic trypsin inhibitor (BPTI) or the B1 domain of streptococcal protein G (PGB1) serves as a crowding agent. By NMR, we show that both crowders, and especially BPTI, cause a drastic loss in the overall stability of SOD1 i

Advanced combustion such as the partially premixed combustion (PPC) is characterized by high energy efficiency. However, they are sensitive to the inlet condition and injection of a combustion engine. Therefore, it is essential to use combustion feedback. The accuracy of the feedback variables, derived from the cylinder pressure signal, is crucial for effective combustion feedback control. This pa

The focus of this work is detecting pedestrians, captured in a surveillance setting, and locating them in world coordinates. Commonly adopted search strategies operate in the image plane to address the object detection problem with machine learning, for example using scale-space pyramid with the sliding windows methodology or object proposals. In contrast, here a new search space is presented, whi

Partially Premixed Combustion (PPC) is a promising combustion concept with high thermodynamic efficiency and low emission level, and also with minimal modification of standard engine hardware. To use PPC in a production oriented engine, the optimal intake charge conditions for PPC should be included in the analysis. The experiments in this paper investigated and confirmed that the optimal intake c

The ignition delay is an important quantity in low temperature combustion concepts where a prolonged ignition delay gives an enhanced fuel-air mixing process, favorable for decreased particulate and NOx emission levels. This article investigates three different low-order physics-based correlation models and their ability to predict the ignition delay for the purpose of model-based controller desig

The computation power we expect from the various smart devices we use keeps increasing. Not only do we want faster devices but also less power hungry and energy efficient devices, both for the environment and our personal convenience (remember that "mobile phone" attached to a power plug at all times?).One way of addressing this demand is to build custom processor architectures that focus on a spe

Partially premixed combustion (PPC) is a low temperature, direct-injection combustion concept that has shown to give promising emission levels and efficiencies over a wide operating range. In this concept, high EGR ratios, high octane-number fuels and early injection timings are used to slow down the auto-ignition reactions and to enhance the fuel and are mixing before the start of combustion. A d

This contribution presents a novel model-based methodology for open-loop optimal control of batch high-pressure liquid chromatographic (HPLC) separation processes. The framework allows for simultaneous optimization of target component recovery yield and production rate with respect to a parameterization of the input elution trajectory and fractionating interval endpoints. The proposed methodology

This paper presents an approach to the synthesis of low-power fault-tolerant hard real-time applications mapped on distributed heterogeneous embedded systems. Our synthesis approach decides the mapping of tasks to processing elements, as well as the voltage and frequency levels for executing each task, such that transient faults are tolerated, the timing constraints of the application are satisfie

Changes in vehicle emission reduction technologies significantly affect traffic-related emissions in urban areas. In many densely populated areas the amount of traffic is increasing, keeping the emission level high or even increasing. To understand the health effects of traffic-related emissions, both primary (direct) particulate emission and secondary particle formation (from gaseous precursors i

A three bit second order delta sigma modulator for audio applications implemented in 130nm CMOS technology is presented. The modulator features two integrators, a flash quantizer and two current steering DACs. In order to minimize the effect of delays in the DACs, excessive loop delay (ELD) compensation is utilized. Using an oversampling ratio (OSR) of 80, the design consumes 2.8mW and achieves a

In this paper we present an audio synthesizer that creates audio signals, intended to be reproduced as sound by a loudspeaker. This paper details the design, implementation and verification of an analog, subtractive audio synthesizer. The synthesizer produces a variety of waveforms spanning approximately 3 octaves. The frequency is controlled by an external voltage and the harmonic content is regu

The analysis of the trace graphs generated by dataflow program executions has been shown to be an effective tool for exploring and optimizing the design space of application programs on manycore/multicore platforms. In this work a new approach aiming at finding bounded buffer size configurations for implementations generated by dataflow programs is presented. The introduced method is based on an o

Collaborative filtering for recommender systems seeks to learn and predict user preferences for a collection of items by identifying similarities between users on the basis of their past interest or interaction with the items in question. In this work, we present a conjugate prior regularized extension of Hofmann's Gaussian emission probabilistic latent semantic analysis model, able to overcome th

Splatting photons onto primary view samples, rather than gathering from a photon acceleration structure, can be a more efficient approach to evaluating the photon-density estimate in interactive applications, where the number of photons is often low compared to the number of view samples. Most photon splatting approaches struggle with large photon radii or high resolutions due to overdraw and insu