Influences on aircraft target off-block time prediction accuracy

With Airport Collaborative Decision Making (A-CDM) as a generic concept of working together of all airport partners, the main aim of this research project was to increase the understanding of the Influences on the Target Off-Block Time (TOBT) Prediction Accuracy during A-CDM. Predicting the TOBT accurately is important, because all airport partners use it as a reference time for the departure of the flights after the aircraft turn-round. Understanding such influencing factors is therefore not only required for finding measures to counteract inaccurate TOBT predictions, but also for establishing a more efficient A-CDM turn-round process. The research method chosen comprises a number of steps. Firstly, within the framework of a Cognitive Work Analysis, the sub-processes as well as the information requirements during turn-round were analysed. Secondly, a survey approach aimed at finding and describing situations during turn-round that are critical for TOBT adherence was pursued. The problems identified here were then investigated in field observations at different airlines’ operation control rooms. Based on the findings from these previous steps, small-scale human-in-the-loop experiments were designed aimed at testing hypotheses about data/information availability that influence TOBT predictability. A turn-round monitoring tool was developed for the experiments. As a result of this project, the critical chain of turn-round events and the decisions necessary during all stages of the turn-round were identified. It was concluded that information required but not shared among participants can result in TOBT inaccuracy swings. In addition, TOBT predictability was shown to depend on the location of the TOBT turn-round controller who assigns the TOBT: More reliable TOBT predictions were observed when the turn-round controller was physically present at the aircraft. During the experiments, TOBT prediction could be improved by eight minutes, if available information was cooperatively shared ten minutes prior turn-round start between air crews and turn-round controller; TOBT prediction could be improved by 15 minutes, if additional information was provided by ramp agents five minutes after turnround start

Editorial of the 2019 Workshop on Very Large Internet of Things (VLIoT)

We are proud of presenting the outcome of this third edition of the "Very Large Internet of Things" (VLIoT) workshop, which was held in Los Angeles (USA) in August 2019, in conjunction with the 45th International Conference on Very Large Data Bases (VLDB). Following the success path of the two previous workshop editions - in Munich (2017) and in Rio de Janeiro (2018) - VLIoT 2019 kept its tradition to be a vivid and high-quality technical forum for researchers and practitioners working with Internet of Things to share their experiences, visions and latest findings, most of them regarding the design, implementation, deployment and management of IoT systems at very large and scale. This editorial of the special issue introduces and introduces all papers presented at the workshop

Advances in Cloud and Ubiquitous Computing

Cloud computing provides on-demand access to a shared pool of configurable and dynamically reallocated computing resources typically located in third-party data centers. Ubiquitous computing aims at providing computing resources anytime and everywhere by using any device, in any location, and in any format. This special issue, Advances in Cloud and Ubiquitous Computing (ACUC), aims at addressing the challenges and reporting the latest research findings in the fields of Cloud computing and Ubiquitous Computing respectively, and how new technologies of Cloud Computing and Ubiquitous Computing complete each other

Lower Complexity Adaptation for Empirical Entropic Optimal Transport

Entropic optimal transport (EOT) presents an effective and computationally viable alternative to unregularized optimal transport (OT), offering diverse applications for large-scale data analysis. In this work, we derive novel statistical bounds for empirical plug-in estimators of the EOT cost and show that their statistical performance in the entropy regularization parameter $\epsilon$ and the sample size $n$ only depends on the simpler of the two probability measures. For instance, under sufficiently smooth costs this yields the parametric rate $n^{-1/2}$ with factor $\epsilon^{-d/2}$, where $d$ is the minimum dimension of the two population measures. This confirms that empirical EOT also adheres to the lower complexity adaptation principle, a hallmark feature only recently identified for unregularized OT. As a consequence of our theory, we show that the empirical entropic Gromov-Wasserstein distance and its unregularized version for measures on Euclidean spaces also obey this principle. Additionally, we comment on computational aspects and complement our findings with Monte Carlo simulations. Our techniques employ empirical process theory and rely on a dual formulation of EOT over a single function class. Crucial to our analysis is the observation that the entropic cost-transformation of a function class does not increase its uniform metric entropy by much.Comment: 46 pages, 5 figure

Webpage Ranking Analysis of Various Search Engines with Special Focus on Country-Specific Search

In order to attract many visitors to their own website, it is extremely important for website developers that their webpage is one of the best ranked webpages of search engines. As a rule, search engine operators do not disclose their exact ranking algorithm, so that website developers usually have only vague ideas about which measures have particularly positive influences on the webpage ranking. Conversely, we ask the question: "What are the properties of the best ranked webpages?" For this purpose, we perform a detailed analysis, in which we compare the properties of the best ranked webpages with the worse ranked webpages. Furthermore, we compare countryspecific differences

Getting Indexed by Bibliographic Databases in the Area of Computer Science

Every author and publisher is interested in adding their publications to the widely used bibliographic databases freely accessible in the world wide web: This ensures the visibility of their publications and hence of the published research. However, the inclusion requirements of publications in the bibliographic databases are heterogeneous even on the technical side. This survey paper aims in shedding light on the various data formats, protocols and technical requirements of getting indexed by widely used bibliographic databases in the area of computer science and provides hints for maximal database inclusion. Furthermore, we point out the possibilities to utilize the data of bibliographic databases, and describes some personal and institutional research repository systems with special regard to the support of inclusion in bibliographic databases

Multi-Game Code-Duel for Learning Programming Languages

Software developers compose computer instructions following the rules defined in programming languages for the purpose of automatic information processing. However, different programming languages have different syntax and semantic rules, and support different programming paradigms and design patterns. Learning a programming language needs many efforts and much practicing in order to master the rules and apply the patterns. Leaning multiple programming languages at the same time, of course, needs more efforts. In this work we develop the concept of multi-game and an e-learning platform called "Multi-Game Platform for Code-Duels" for learning multiple programming languages easily and efficiently. A multi-game is a video game, which consists of several mini-games. Dividing a big game into mini-games reduces the development efforts and implementation complexity. "Builders" is a multi-game developed in our platform consisting of three mini-games. Each mini-game can be solved by implementing a program by learners using different languages. Using our multi-game platform, each mini-game of Builders can be developed easily and played independently of the other mini-games. Finally, a user evaluation over our multi-game platform is performed, where users rate our multi-game approach and platform for learning programming languages very positively

The mf-index: A Citation-Based Multiple Factor Index to Evaluate and Compare the Output of Scientists

Comparing the output of scientists as objective as possible is an important factor for, e.g., the approval of research funds or the filling of open positions at universities. Numeric indices, which express the scientific output in the form of a concrete value, may not completely supersede an overall view of a researcher, but provide helpful indications for the assessment. This work introduces the most important citation-based indices, analyzes their advantages and disadvantages and provides an overview of the aspects considered by them. On this basis, we identify the criteria that an advanced index should fulfill, and develop a new index, the mf-index. The objective of the mf-index is to combine the benefits of the existing indices, while avoiding as far as possible their drawbacks and to consider additional aspects. Finally, an evaluation based on data of real publications and citations compares the mf-index with existing indices and verifies that its advantages in theory can also be determined in practice