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In this TDP we describe a new tool created for testing the strategy layer of our soccer playing agents. It is a complete 2D simulator that simulates the games based on the decisions of 22 agents. With this tool, debugging the decision and strategy layer of our agents is much more efficient than before due to various interaction methods and complete control over the simulation.
In the future, the tool could also serve as a measure to run simulations of game series much faster than with the 3D simulator. This way, the impact of different play strategies could be evaluated much faster than before.
Objectives: Speech recognition on the telephone poses a challenge for patients with cochlear implants (CIs) due to a reduced bandwidth of transmission. This trial evaluates a home-based auditory training with telephone-specific filtered speech material to improve sentence recognition. Design: Randomised controlled parallel double-blind. Setting: One tertiary referral centre. Participants: A total of 20 postlingually deafened patients with CIs. Main outcome measures: Primary outcome measure was sentence recognition assessed by a modified version of the Oldenburg Sentence Test filtered to the telephone bandwidth of 0.3-3.4 kHz. Additionally, pure tone thresholds, recognition of monosyllables and subjective hearing benefit were acquired at two separate visits before and after a home-based training period of 10-14 weeks. For training, patients received a CD with speech material, either unmodified for the unfiltered training group or filtered to the telephone bandwidth in the filtered group. Results: Patients in the unfiltered training group achieved an average sentence recognition score of 70.0%±13.6% (mean±SD) before and 73.6%±16.5% after training. Patients in the filtered training group achieved 70.7%±13.8% and 78.9%±7.0%, a statistically significant difference (P=.034, t10 =2.292; two-way RM ANOVA/Bonferroni). An increase in the recognition of monosyllabic words was noted in both groups. The subjective benefit was positive for filtered and negative for unfiltered training. Conclusions: Auditory training with specifically filtered speech material provided an improvement in sentence recognition on the telephone compared to training with unfiltered material.
The electrical field (E-field) of the biventricular (BV) stimulation is important for the success of cardiac resynchronization therapy (CRT) in patients with cardiac insufficiency and widened QRS complex.
The aim of the study was to model different pacing and ablation electrodes and to integrate them into a heart model for the static and dynamic simulation of BV stimulation and HF ablation in atrial fibrillation (AF).
The modeling and simulation was carried out using the electromagnetic simulation software CST. Five multipolar left ventricular (LV) electrodes, four bipolar right atrial (RA) electrodes, two right ventricular (RV) electrodes and one HF ablation catheter were modelled. A selection were integrated into the heart rhythm model (Schalk, Offenburg) for the electrical field simulation. The simulation of an AV node ablation at CRT was performed with RA, RV and LV electrodes and integrated ablation catheter with an 8 mm gold tip.
The BV stimulation were performed simultaneously at amplitude of 3 V at the LV electrode and 1 V at the RV electrode with a pulse width of 0.5 ms each. The far-field potential at the RA electrode tip was 32.86 mV and 185.97 mV at a distance of 1 mm from the RA electrode tip. AV node ablation was simulated with an applied power of 5 W at 420 kHz at the distal ablation electrode. The temperature at the catheter tip was 103.87 °C after 5 s ablation time and 37.61 °C at a distance of 2 mm inside the myocardium. After 15 s, the temperature was 118.42 °C and 42.13 °C.
Virtual heart and electrode models as well as the simulations of electrical fields and temperature profiles allow the static and dynamic simulation of atrial synchronous BV stimulation and HF ablation at AF and could be used to optimize the CRT and AF ablation.
The ability to detect a target signal masked by noise is improved in normal-hearing listeners when interaural phase differences (IPDs) between the ear signals exist either in the masker or in the signal. To improve binaural hearing in bilaterally implanted cochlear implant (BiCI) users, a coding strategy providing the best possible access to IPDs is highly desirable. Outcomes of a previous study (Zirn, Arndt et al. 2016) revealed that a subset of BiCI users showed improved IPD detection thresholds with the fine structure processing strategy FS4 compared to the constant rate strategy HDCIS using narrowband stimuli. In contrast, little differences between the coding strategies were found for broadband stimuli with regard to binaural speech intelligibility level differences (BILD) as an estimate of binaural unmasking. Compared to normalhearing listeners (7.5 ± 1.2 dB) BILD were small in BiCI users (around 0.5 dB with both coding strategies).
In the present work, we investigated the influence of binaural fitting parameters on BILD. In our cohort of BiCI users many were implanted with electrode arrays differing in length left versus right. Because this length difference typically corresponded to the distance of two electrode contacts the first modification of bilateral fitting was a tonotopic adjustment by deactivation of the most apical electrode contact on the side with the deeper inserted array (tonotopic approach).
The second modification was the isolation of the residual, most apical electrode contacts by deactivation of the basally adjacent electrode contact on each side (tonotopic sparse approach). Applying these modifications, BILD improved by up to 1.5 dB.
Since their dawning, space communications have been among the strongest driving applications for the development of error correcting codes. Indeed, space-to-Earth telemetry (TM) links have extensively exploited advanced coding schemes, from convolutional codes to Reed-Solomon codes (also in concatenated form) and, more recently, from turbo codes to low-density parity-check (LDPC) codes. The efficiency of these schemes has been extensively proved in several papers and reports. The situation is a bit different for Earth-to-space telecommand (TC) links. Space TCs must reliably convey control information as well as software patches from Earth control centers to scientific payload instruments and engineering equipment onboard (O/B) spacecraft. The success of a mission may be compromised because of an error corrupting a TC message: a detected error causing no execution or, even worse, an undetected error causing a wrong execution. This imposes strict constraints on the maximum acceptable detected and undetected error rates.
Finding clusters in high dimensional data is a challenging research problem. Subspace clustering algorithms aim to find clusters in all possible subspaces of the dataset where, a subspace is the subset of dimensions of the data. But exponential increase in the number of subspaces with the dimensionality of data renders most of the algorithms inefficient as well as ineffective. Moreover, these algorithms have ingrained data dependency in the clustering process, thus, parallelization becomes difficult and inefficient. SUBSCALE is a recent subspace clustering algorithm which is scalable with the dimensions and contains independent processing steps which can be exploited through parallelism. In this paper, we aim to leverage, firstly, the computational power of widely available multi-core processors to improve the runtime performance of the SUBSCALE algorithm. The experimental evaluation has shown linear speedup. Secondly, we are developing an approach using graphics processing units (GPUs) for fine-grained data parallelism to accelerate the computation further. First tests of the GPU implementation show very promising results.