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The 0-1 multidimensional knapsack problem (MKP) is a well-known combinatorial optimization problem with several real-life applications, for example, in project selection. Genetic algorithms (GA) are effective heuristics for solving the 0-1 MKP. Multiple individual GAs with specific characteristics have been proposed in literature. However, so far, these approaches have only been partially compared in multiple studies with unequal conditions. Therefore, to identify the “best” genetic algorithm, this article reviews and compares 11 existing GAs. The authors' tests provide detailed information on the GAs themselves as well as their performance. The authors validated fitness values and required computation times in varying problem types and environments. Results demonstrate the superiority of one GA.
We compute the Fourier expansion of Hecke operators on vector-valued modular forms for the Weil representation associated to a lattice L. The Hecke operators considered in this paper include operators T(p^2l) where p is a prime dividing the level of the lattice L. Additionally, an explicit formula for a general type of Gauss sum associated to a lattice L drops out as a by-product.
Today, ubiquitous mobile devices have not only arrived but entered the safety critical domain. There, systems are about to be controlled where human health or even human life is put at risk. For example, in automation systems first ideas surface to control parts of the system via a COTS smartphone. Another example is the idea to control the autonomous parking function of a car via a COTS smartphone too. As beneficial and convenient these ideas are on the first thought, on the second thought, dangers of these approaches become obvious. Especially in case of failures the system’s safety has to be maintained. The open question is how to achieve this mandatory requirement with COTS components, e.g. smartphones that are not developed following the development process necessary for safetycritical systems. This paper presents a concept to reliably detect human interaction while activating safety critical functions via COTS mobile devices. Thus a means is provided to detect erroneous activation requests for the safetycritical function.
Fluctuations of hi-hat timing and dynamics in a virtuoso drum track of a popular music recording
(2015)
Long-range correlated temporal fluctuations in the beats of musical rhythms are an inevitable consequence of human action. According to recent studies, such fluctuations also lead to a favored listening experience. The scaling laws of amplitude variations in rhythms, however, are widely unknown. Here we use highly sensitive onset detection and time series analysis to study the amplitude and temporal fluctuations of Jeff Porcaro's one-handed hi-hat pattern in "I Keep Forgettin'"-one of the most renowned 16th note patterns in modern drumming. We show that fluctuations of hi-hat amplitudes and interbeat intervals (times between hits) have clear long-range correlations and short-range anticorrelations separated by a characteristic time scale. In addition, we detect subtle features in Porcaro's drumming such as small drifts in the 16th note pulse and non-trivial periodic two-bar patterns in both hi-hat amplitudes and intervals. Through this investigation we introduce a step towards statistical studies of the 20th and 21st century music recordings in the framework of complex systems. Our analysis has direct applications to the development of drum machines and to drumming pedagogy.
This article provides a unifying Bayesian view on various approaches for acoustic model adaptation, missing feature, and uncertainty decoding that are well-known in the literature of robust automatic speech recognition. The representatives of these classes can often be deduced from a Bayesian network that extends the conventional hidden Markov models used in speech recognition. These extensions, in turn, can in many cases be motivated from an underlying observation model that relates clean and distorted feature vectors. By identifying and converting the observation models into a Bayesian network representation, we formulate the corresponding compensation rules. We thus summarize the various approaches as approximations or modifications of the same Bayesian decoding rule leading to a unified view on known derivations as well as to new formulations for certain approaches.
The vehicular ad hoc network (VANET) technology based on the approved IEEE 802.11p standard and the appendant inter-vehicle communication (IVC) has the potential to dramatically change the way transportation systems work. The fundamental idea is to change the individual behavior of each vehicle by exchanging information among traffic participants to realize a cooperative and more efficient ransportation system. Certainly, the evaluation of such systems is a comprehensive and challenging task in a real world test bed, therefore, simulation frameworks are a key tool to analyze IVC. Several models are needed to emulate the real behavior of a VANET in all aspects as much realistically as necessary. The intention of this survey is to provide a comprehensive overview of publications concerning IVC simulations of the year 2013 and to see how IVC simulation has changed since 2009. Based on this analysis, we will answer the following questions: What simulation techniques are applied to IVC? Which aspects of IVS have been evaluated? What has changed within five years of IVC simulations? We also take a closer look at commonly used software tools and discuss their functionality and drawbacks. Finally, we present open questions concerning IVC simulations.
We have developed a novel, computer-assisted operation method for minimal-invasive total hip replacement (THR) following the concept of “femur first/combined anteversion,” which incorporates various aspects of performing a functional optimization of the prosthetic stem and cup position (CAS FF). The purpose of this study is to assess whether the hip joint reaction forces and patient’s gait parameters are being improved by CAS FF in relation to conventional THR (CON). We enrolled 60 patients (28 CAS FF/32 CON) and invited them for gait analysis at three time points (preoperatively, postop six months, and postop 12 months). Data retrieved from gait analysis was processed using patient-specific musculoskeletal models. The target parameters were hip reaction force magnitude (hrf), symmetries, and orientation with respect to the cup. Hrf in the CAS FF group were closer to a young healthy normal. Phase-shift symmetry showed an increase in the CAS FF group. Hrf orientation in the CAS FF group was closer to optimum, though no edge or rim-loading occurred in the CON group as well. The CAS FF group showed an improved hrf orientation in an early stage and a trend to an improved long-term outcome.
Companies use special designed flow shops, in order to satisfy specific demands. Products need to be transported (from one station to the next station) by a crane and the way of working of this crane excludes the intermediate storage (of a work piece). In addition, the way of working restricts the set of feasible schedules even more than the no-buffer restriction discussed in the literature in the case of limited storage. Since this scheduling problem is integrated in the usual hierarchical planning, the tardiness is minimised. A linear optimisation model is presented to provide a formal description of this NP-hard problem. It is also used to explain the performance of priority rule based heuristic solutions on small test problems. In detail, priority rules as well as a priority rule based branch and bound procedure are analysed; priority rules are regarded, because a priority rule is still the standard procedure for on-line scheduling in industrial practise. Out of successful priority rules in the literature the best one is identified by an extensive simulative investigation. An improved look-ahead is realised by a restricted search over all possible schedules.