Dienstleistungsqualität als Erfolgsfaktor im Messewesen

Im Rahmen dieser Arbeit soll die Gestaltung der Dienstleistungsqualität der Messegesellschaft dargestellt bzw. konkretisiert werden. Die Probleme und Herausforderungen von deutschen Messegesellschaften werden anhand einer ausführlichen Dienstleistungsanalyse aufgezeigt und allgemeine politische, strategische Ansätze zu ihrer Bewältigung dargestellt. Nach Analyse der Dienstleistungsqualität des deutschen Messewesens sollen Schlussfolgerungen für ein Entwicklungskonzept zur Verbesserung der Dienstleistungsqualität im südkoreanischen Messewesen gezogen werden. Messeveranstaltungen werden zukünftig vermehrt an der Dienstleistungsqualität der Veranstalter gegenüber Ausstellern und Besuchern gemessen werden. Hierfür kann bei Umsetzung des im Rahmen dieser Arbeit vorgestellten Management-Konzepts auf das Ergebnis einer Synthese wissenschaftlicher Erkenntnisse und Praxiserfahrungen zum Thema Dienstleistungsqualität zurückgegriffen werden. Dies sind wichtige Vorschläge, die besonders von sich entwickelnden Messeländern wie KOREA betrachtet werden sollen. Qualität der Aussteller- und Fachbesucherstruktur Qualität des Messestandortes Qualität des Organisationssystems Hochwertige Messedienstleistungen für Aussteller und Besucher Leistungsfähigkeit für neue Kundenbindung Quantität und Qualität der Hotelkapazitäten in für die Nachfrager akzeptablen Kategorien Touristische, kulturelle und kommunikativ-gesellige Vorzüge des Messeplatzes, Anziehungskraft der Messemetropole Transparenz der Auswertung der Veranstaltung Die Dienstleistungsqualität des Messeortes mit touristisch relevanten Einrichtungen und Attraktionen hat unmittelbaren und konkreten Einfluss auf die potentiellen Messe-Touristen mit ihren gruppenspezifischen wie auch individuellen Ansprüchen. Messeveranstaltung und Umfeld sollen in den Augen der Aussteller und Besucher eine komplette und professionelle Dienstleistung darstellen, so dass sich aus dem Zusammenspiel einzelner Faktoren das Gesamtangebot ergibt

Quantification of The Performance of CMIP6 Models for Dynamic Downscaling in The North Pacific and Northwest Pacific Oceans

Selecting a reliable global climate model as the driving forcing in simulations with dynamic downscaling is critical for obtaining a reliable regional ocean climate. With respect to their accuracy in providing physical quantities and long-term trends, we quantify the performances of 17 models from the Coupled Model Inter-comparison Project Phase 6 (CMIP6) over the North Pacific (NP) and Northwest Pacific (NWP) oceans for 1979–2014. Based on normalized evaluation measures, each model’s performance for a physical quantity is mainly quantified by the performance score (PS), which ranges from 0 to 100. Overall, the CMIP6 models reasonably reproduce the physical quantities of the driving variables and the warming ocean heat content and temperature trends. However, their performances significantly depend on the variables and region analyzed. The EC-Earth-Veg and CNRM-CM6-1 models show the best performances for the NP and NWP oceans, respectively, with the highest PS values of 85.89 and 76.97, respectively. The EC-Earth3 model series are less sensitive to the driving variables in the NP ocean, as reflected in their PS. The model performance is significantly dependent on the driving variables in the NWP ocean. Nevertheless, providing a better physical quantity does not correlate with a better performance for trend. However, MRI-ESM2-0 model shows a high performance for the physical quantity in the NWP ocean with warming trends similar to references, and it could thus be used as an appropriate driving forcing in dynamic downscaling of this ocean. This study provides objective information for studies involving dynamic downscaling of the NP and NWP oceans

Improving Prediction Quality in Collaborative Filtering Based on Clustering

In this paper we present the recommender systems that use the k-means clustering method in order to solve the problems associated with neighbor selection. The first method is to solve the problem in which customers belong to different clusters due to the distance-based characteristics despite the fact that they are similar customers, by properly converting data before performing clustering. The second method explains the k-prototype algorithm performing clus-tering by expanding not only the numeric data but also the categorical data. The experimental results show that better prediction quality can be obtained when both methods are used together. 1

Iterative detection for frequency-asynchronous distributed Alamouti-coded (FADAC) OFDM

We propose a near intercarrier interference (ICI)-free and very low complexity iterative detector for frequency-asynchronous distributed Alamouti-coded (FADAC) orthogonal frequency division multiplexing (OFDM). In the previous cancelation schemes, the entire subcarrier signals from one transmit (TX) antenna are estimated and canceled in the received signal from the other TX antenna and vice versa. However, the reliability of the estimated symbols are revealed to significantly vary across the subcarriers and thus, the poorly estimated symbols lead to the incorrect cancelation. Motivated from this, we first propose a scheme which does not cancel the interfering subcarrier(s) at the half band edges which undergo very high interference in FADAC-OFDM. For further improvement, we propose a so-called selective scheme which instantly measures the reliability of the detected symbols at each iteration and then exclude the unreliable symbols in the estimated interference generation. Moreover, the proposed scheme has a drastically reduced complexity by converting the cancelation process from the subcarrier domain to the time domain. In accordance with the analysis on the considered reliability measures, the numerical results show that the proposed scheme achieves the near ICI-free level only within three or four iterations for wide ranges of SNR, frequency offset, and delay spread.1

Low-complexity joint range and Doppler FMCW radar algorithm based on number of targets

A low-complexity joint range and Doppler frequency-modulated continuous wave (FMCW) radar algorithm based on the number of targets is proposed in this paper. This paper introduces two low-complexity FMCW radar algorithms, that is, region of interest (ROI)-based and partial discrete Fourier transform (DFT)-based algorithms. We find the low-complexity condition of each algorithm by analyzing the complexity of these algorithms. From this analysis, it is found that the number of targets is an important factor in determining complexity. Based on this result, the proposed algorithm selects a low-complexity algorithm between two algorithms depending the estimated number of targets and thus achieves lower complexity compared two low-complexity algorithms introduced. The experimental results using real FMCW radar systems show that the proposed algorithm works well in a real environment. Moreover, central process unit time and count of float pointing are shown as a measure of complexity. © 2020 by the authors. Licensee MDPI, Basel, Switzerland.1

Highly efficient active optical interconnect incorporating a partially chlorinated ribbon POF in conjunction with a visible VCSEL

A low-loss 4-ch active optical interconnect (AOI) enabling passive alignment was proposed and built resorting to a transmitter (Tx) incorporating a red 680-nm VCSEL, which is linked to a receiver (Rx) module via a partially chlorinated ribbon POF. The POF was observed to exhibit an extremely low loss of similar to 0.24 dB/m at lambda = 680 nm, in comparison to similar to 1.29 dB/m at lambda = 850 nm, and a large numerical aperture of similar to 0.42. Both the Tx and Rx, which taps into a beam router based on collimated beam optics involving a pair of spherical lenses, were meant to be substantially alignment tolerant and compact. The achieved tolerance for the constructed modules was beyond 40 m in terms of the positioning of VCSEL and photodetector. The proposed AOI was completed by linking the Tx with the Rx via a 3-m long ribbon POF, incurring a transmission loss of as small as 3.2 dB. The AOI was practically assessed in terms of a high-speed data transmission over a wide range of temperatures and then exploited to convey full HD video signals. (C) 2014 Optical Society of Americ

Low-Complexity MUSIC-Based Direction-of-Arrival Detection Algorithm for Frequency-Modulated Continuous-Wave Vital Radar

This paper proposes a low complexity multiple-signal-classifier (MUSIC)-based direction-of-arrival (DOA) detection algorithm for frequency-modulated continuous-wave (FMCW) vital radars. In order to reduce redundant complexity, the proposed algorithm employs characteristics of distance between adjacent arrays having trade-offs between field of view (FOV) and resolution performance. First, the proposed algorithm performs coarse DOA estimation using fast Fourier transform. On the basis of the coarse DOA estimation, the number of channels as input of the MUSIC algorithm are selected. If the estimated DOA is smaller than 30◦, it implies that there is an FOV margin. Therefore, the proposed algorithm employs only half of the channels, that is, it is the same as doubling the spacing between arrays. By doing so, the proposed algorithm achieves more than 40% complexity reduction compared to the conventional MUSIC algorithm while achieving similar performance. By experiments, it is shown that the proposed algorithm despite the low complexity is enable to distinguish the adjacent DOA in a practical environment. © 2020 by the authors. Licensee MDPI, Basel, Switzerland.1

Extrapolation-RELAX Estimator Based on Spectrum Partitioning for DOA Estimation of FMCW Radar

This paper proposes an extrapolation-RELAX estimator based on spectrum partitioning (SP) for the direction of arrival (DOA) estimation of frequency-modulated continuous-wave (FMCW) radar. The FMCW radar employs fast Fourier transform (FFT)-based digital beamforming (DBF) for the DOA estimation owing to its low complexity and easy implementation. However, the DBF algorithm has a disadvantage of low angle resolution. To improve the angle resolution, super-resolution algorithms such as multiple signal classification (MUSIC) and estimation of signal parameters via rotational invariance techniques (ESPRIT) are proposed. However, these algorithms require the high signal-to-noise ratio (SNR) to meet the required performance. To overcome this drawback of super-resolution algorithms, the SP-based extrapolation method has been proposed. However, this algorithm still has the problem that the resolution performance degrades owing to the insufficient number of actual antenna arrays. To solve this problem, we propose the SP-based extrapolation-RELAX algorithm for DOA estimation of FMCW radar. Through extrapolation, the proposed structure solves the problem of insufficient number of arrays, resulting in high reliability of SP results. When the extrapolation algorithm is used to generate the input signal of the RELAX algorithm, the RELAX method improves the performance of the DOA estimation. To confirm the effectiveness of the proposed estimation, we compare the Monte Carlo simulation and root-mean-square error results of the proposed and conventional algorithms. To verify the performance of the proposed algorithm in practical conditions, experiments were performed using the FMCW radar module within a chamber and in an indoor environment.1