scholarly journals Konzeption und Entwicklung eines datengetriebenen Unterstützungssystems für Etatplanung und Mittelallokation einer hybriden Spezialbibliothek

2021 ◽  
Author(s):  
◽  
Peter Breternitz

Due to economic developments, libraries must use their budgets efficiently and in line with demand. In addition, budget negotiations in libraries are becoming more and more important. The goal of this master thesis was to develop a proof-of-concept of a data-driven support system for budget planning and resource allocation for the library of the Max Planck Institute for Empirical Aesthetics. For this purpose, data from different library areas were analyzed and evaluated. The data-driven support system displays key performance indicators such as budget, expenditures, circulation, collection development, and reading room usage in a dashboard. This allows the library to plan its budget and allocate funds more efficiently and in line with its needs as well as conduct budget negotiations with confidence.

Author(s):  
Mariana Alves Rios ◽  
Paula Aboud Barbugli ◽  
Mônica Rosas Costa Iemma ◽  
Rafael Grande ◽  
Antônio José Felix Carvalho ◽  
...  

Author(s):  
Jessica Williams ◽  
Rhyse Bendell ◽  
Stephen M. Fiore ◽  
Florian Jentsch

Current approaches to player profiling are limited in that they typically employ only a single one of numerous of available techniques shown to have utility for categorizing and explaining player behavior. We propose a more comprehensive Video Game Player Profile Framework that considers the demographic, psychographic, mental model, and behavioral modeling approaches shown to be effective for describing gamer populations. We suggest that our proposed approach can improve the efficacy of video game player profiles by grounding data-driven techniques in game analytics with the theoretical backing of demographic, psychometric, and psychographic measurements. We provide an overview of our proposed framework, discuss the usage and relevance of each component technique, and provide a proof-of-concept demonstration with archived data.


2009 ◽  
Vol 48 (8) ◽  
pp. 2219-2231 ◽  
Author(s):  
Claudia Barreto Cabrera ◽  
Joaquín B. Ordieres Meré ◽  
Manuel Castejon Limas ◽  
Juan José del Coz Díaz
Keyword(s):  

Author(s):  
Svetlana E. Vecherskaya

A prototype of an automated decision support system for creative universities has been developed, which will allow assessing the achievements particularly talented students and identifying the needs in the learning process in order to help organize the educational process in accordance with identified capabilities. Use of a decision support system based on the Bayesian classifier is suggested which will allow to evaluate factors contributing to the progress in teaching students particular techniques, and in perspective to assess the possible resources that will be required to make changes to the learning. The list of specific performance indicators is given. The system should contribute to the formation of the learning plan, taking into account the capabilities of both a group art workshop as a whole, and special needs of an individual to develop, if necessary an individual approach.


2020 ◽  
Author(s):  
Raul Sanchez-Lopez ◽  
Michal Fereczkowski ◽  
Sébastien Santurette ◽  
Torsten Dau ◽  
Tobias Neher

AbstractObjectiveThe clinical characterization of hearing deficits for hearing-aid fitting purposes is typically based on the pure-tone audiogram only. In a previous study, a group of hearing-impaired listeners were tested using a comprehensive test battery designed to tap into different aspects of hearing. A data-driven analysis of the data yielded four clinically relevant patient subpopulations or “auditory profiles”. In the current study, profile-based hearing-aid settings were proposed and evaluated to explore their potential for providing more targeted hearing-aid treatment.DesignFour candidate hearing-aid settings were implemented and evaluated by a subset of the participants tested previously. The evaluation consisted of multi-comparison preference ratings carried out in realistic sound scenarios.ResultsListeners belonging to the different auditory profiles showed different patterns of preference for the tested hearing-aid settings that were largely consistent with the expectations.ConclusionThe results of this proof-of-concept study support further investigations into stratified, profile-based hearing-aid fitting with wearable hearing aids.


2019 ◽  
Vol 887 ◽  
pp. 164-171
Author(s):  
Marija Marković ◽  
Ulrich Pont ◽  
Ardeshir Mahdavi

Energy performance calculations are stipulated by law in most European countries. Thereby, different calculation schemes have been developed in the past years in different countries. The physical processes in buildings were simplified in terms of normative calculation routines in most of these schemes. A major idea behind these simplifications was to enable different stakeholders (practitioners, engineers, and architects) to issue energy certificates without being simulation experts. Moreover, the simplifications needed to be described thoroughly in corresponding guidelines to ensure and facilitate the comparability of the energy performance of different buildings. However, neither of these objectives can be considered to be fully met. Regarding the former, the normative calculation procedures increased in complexity in the past years, so that the issuing of energy certificates requires not only the stakeholder’s expertise but also a comprehensive knowledge of the standards that form the calculation method. Regarding the latter, recent research efforts revealed that many guidelines do not fully cover every aspect of the calculation procedures and the assumptions regarding required input data. Thus, the comparability of energy certificates has to be strongly questioned, as a number of relevant calculation parameters are dependent on the interpretation of the corresponding issuer.Given this background, alternative approaches to building performance evaluation would be of interest. Previous approaches by different researchers suggested so called prescriptive indicators, which can be derived by basic building data (for instance, geometry and thermal quality of the building envelope components). This contribution is based on this concept. In the framework of a master thesis, a number of prescriptive indicators were considered. These indicators were derived for a set of sample buildings. In a parallel effort, energy certificates (encompassing Key Performance Indicators KPIs) were calculated for the sample buildings. It is clear that the prescriptive indicators cannot act as a 1:1 replacement for KPIs in terms of a numeric value. However, their usefulness can be expressed by the relation of the prescriptive indicator and the corresponding KPIs of a building. Thus, the results of the described calculation efforts were ranked. Subsequently, the lists of buildings ranked by the different indicators were compared in order to identify prescriptive indicators, which result in the same or at least similar ranking as the normative key performance indicators. Within this contribution, the suggested prescriptive indicators, the sample buildings, and the results of the analysis are presented and discussed.


2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
He Ma ◽  
Yi Zuo ◽  
Tieshan Li ◽  
C. L. Philip Chen

Recently, biometric authorizations using fingerprint, voiceprint, and facial features have garnered considerable attention from the public with the development of recognition techniques and popularization of the smartphone. Among such biometrics, voiceprint has a personal identity as high as that of fingerprint and also uses a noncontact mode to recognize similar faces. Speech signal-processing is one of the keys to accuracy in voice recognition. Most voice-identification systems still employ the mel-scale frequency cepstrum coefficient (MFCC) as the key vocal feature. The quality and accuracy of the MFCC are dependent on the prepared phrase, which belongs to text-dependent speaker identification. In contrast, several new features, such as d-vector, provide a black-box process in vocal feature learning. To address these aspects, a novel data-driven approach for vocal feature extraction based on a decision-support system (DSS) is proposed in this study. Each speech signal can be transformed into a vector representing the vocal features using this DSS. The establishment of this DSS involves three steps: (i) voice data preprocessing, (ii) hierarchical cluster analysis for the inverse discrete cosine transform cepstrum coefficient, and (iii) learning the E-vector through minimization of the Euclidean metric. We compare experiments to verify the E-vectors extracted by this DSS with other vocal features measures and apply them to both text-dependent and text-independent datasets. In the experiments containing one utterance of each speaker, the average accuracy of the E-vector is improved by approximately 1.5% over the MFCC. In the experiments containing multiple utterances of each speaker, the average micro-F1 score of the E-vector is also improved by approximately 2.1% over the MFCC. The results of the E-vector show remarkable advantages when applied to both the Texas Instruments/Massachusetts Institute of Technology corpus and LibriSpeech corpus. These improvements of the E-vector contribute to the capabilities of speaker identification and also enhance its usability for more real-world identification tasks.


2013 ◽  
Vol 44 (2-3) ◽  
pp. 204-221 ◽  
Author(s):  
Krzysztof Brzostowski ◽  
Jarosław Drapała ◽  
Adam Grzech ◽  
Paweł Świątek

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