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Nowadays, the most employed devices for recoding videos or capturing images are undoubtedly the smartphones. Our work investigates the application of source camera identification on mobile phones. We present a dataset entirely collected by mobile phones. The dataset contains both still images and videos collected by 67 different smartphones. Part of the images consists in photos of uniform backgrounds, especially collected for the computation of the RSPN. Identifying the source camera given a video is particularly challenging due to the strong video compression. The experiments reported in this paper, show the large variation in performance when testing an highly accurate technique on still images and videos.
Recent analysis of scientific data from Cassini and earth-based observations gave evidence for a global ocean under a surrounding solid ice shell on Saturn's moon Enceladus. Images of Enceladus' South Pole showed several fissures in the ice shell with plumes constantly exhausting frozen water particles, building up the E-Ring, one of the outer rings of Saturn. In this southern region of Enceladus, the ice shell is considered to be as thin as 2 km, about an order of magnitude thinner than on the rest of the moon. Under the ice shell, there is a global ocean consisting of liquid water. Scientists are discussing different approaches the possibilities of taking samples of water, i.e. by melting through the ice using a melting probe. FH Aachen UAS developed a prototype of maneuverable melting probe which can navigate through the ice that has already been tested successfully in a terrestrial environment. This means no atmosphere and or ambient pressure, low ice temperatures of around 100 to 150K (near the South Pole) and a very low gravity of 0,114 m/s^2 or 1100 μg. Two of these influencing measures are about to be investigated at FH Aachen UAS in 2017, low ice temperature and low ambient pressure below the triple point of water. Low gravity cannot be easily simulated inside a large experiment chamber, though. Numerical simulations of the melting process at RWTH Aachen however are showing a gravity dependence of melting behavior. Considering this aspect, VIPER provides a link between large-scale experimental simulations at FH Aachen UAS and numerical simulations at RWTH Aachen. To analyze the melting process, about 90 seconds of experiment time in reduced gravity and low ambient pressure is provided by the REXUS rocket. In this time frame, the melting speed and contact force between ice and probes are measured, as well as heating power and a two-dimensional array of ice temperatures. Additionally, visual and infrared cameras are used to observe the melting process.
Hands-on-training in high technology areas is usually limited due to the high cost for lab infrastructure and equipment. One specific example is the field of MEMS, where investment and upkeep of clean rooms with microtechnology equipment is either financed by production or R&D projects greatly reducing the availability for education purposes. For efficient hands-on-courses a MEMS training foundry, currently used jointly by six higher education institutions, was established at FH Kaiserslautern. In a typical one week course, students manufacture a micromachined pressure sensor including all lithography, thin film and packaging steps. This compact and yet complete program is only possible because participants learn to use the different complex machines in advance via a Virtual Training Lab (VTL). In this paper we present the concept of the MEMS training foundry and the VTL preparation together with results from a scientific evaluation of the VTL over the last three years.
The management of knowledge in organizations considers both established long-term processes and cooperation in agile project teams. Since knowledge can be both tacit and explicit, its transfer from the individual to the organizational knowledge base poses a challenge in organizations. This challenge increases when the fluctuation of knowledge carriers is exceptionally high. Especially in large projects in which external consultants are involved, there is a risk that critical, company-relevant knowledge generated in the project will leave the company with the external knowledge carrier and thus be lost. In this paper, we show the advantages of an early warning system for knowledge management to avoid this loss. In particular, the potential of visual analytics in the context of knowledge management systems is presented and discussed. We present a project for the development of a business-critical software system and discuss the first implementations and results.
Proc. of the 2005 ASCE Intl. Conf. on Computing in Civil Engineering (ICCC 2005) eds. L. Soibelman und F. Pena-Mora, Seite 1-14, ASCE (CD-ROM), Cancun, Mexico, 2005 Current CAD tools are not able to support the fundamental conceptual design phase, and none of them provides consistency analyses of sketches produced by architects. To give architects a greater support at the conceptual design phase, we develop a CAD tool for conceptual design and a knowledge specification tool allowing the definition of conceptually relevant knowledge. The knowledge is specific to one class of buildings and can be reused. Based on a dynamic knowledge model, different types of design rules formalize the knowledge in a graph-based realization. An expressive visual language provides a user-friendly, human readable representation. Finally, consistency analyses enable conceptual designs to be checked against this defined knowledge. In this paper we concentrate on the knowledge specification part of our project.
This paper serves as an introduction to the ECTS monitoring system and its potential applications in higher education. It also emphasizes the potential for ECTS monitoring to become a proactive system, supporting students by predicting academic success and identifying groups of potential dropouts for tailored support services. The use of the nearest neighbor analysis is suggested for improving data analysis and prediction accuracy.
In many instances, freight vehicles exchange load or information with plants that are or will soon be Industry4.0 plants. The Wagon4.0 concept, as developed in close cooperation with e.g. port or mine operations, offers a maximum in railway operational efficiency while providing strong business cases already in the respective plant interaction. The Wagon4.0 consists of main components, a power supply, data network, sensors, actuators and an operating system, the so called WagonOS. The Wagon OS is implemented in a granular, self-sufficient manner, to allow basic features such as WiFi-Mesh and train christening in remote areas without network connection. Furthermore, the granularity of the operating system allows to extend the familiar app concept to freight rail rolling stock, making it possible to use specialised actuators for certain applications, e.g. an electrical parking brake or an auxiliary drive. In order to facilitate migration to the Wagon4.0 for existing fleets, a migration concept featuring five levels of technical adaptation was developed. The present paper investigates the benefits of Wagon4.0-implementations for the particular challenges of heavy haul operations by focusing on train christening, ep-assisted braking, autonomous last mile and traction boost operation as well as improved maintenance schedules
One of interesting but not well known water properties is related to appearance of highly ordered structures in response to strong electrical field. In 1893 Sir William Armstrong placed a cotton thread between two wine glasses filled with chemically pure water. When high DC voltage was applied between the glasses, a connection consisting of water formed, producing a "water bridge"
Digital twins enable the modeling and simulation of real-world entities (objects, processes or systems), resulting in improvements in the associated value chains. The emerging field of quantum computing holds tremendous promise forevolving this virtualization towards Quantum (Digital) Twins (QDT) and ultimately Quantum Twins (QT). The quantum (digital) twin concept is not a contradiction in terms - but instead describes a hybrid approach that can be implemented using the technologies available today by combining classicalcomputing and digital twin concepts with quantum processing. This paperpresents the status quo of research and practice on quantum (digital) twins. It alsodiscuses their potential to create competitive advantage through real-timesimulation of highly complex, interconnected entities that helps companies better
address changes in their environment and differentiate their products andservices.
In recent years, more and more digital startups have been founded and many of them work remotely by applying enterprise collaboration systems (ECS). The study investigates the functional affordances of ECS, particularly Slack, and examines its potential as a virtual office environment for cultural development in digital startups. Through a case study and based on affordance theoretical considerations, the paper explores how ECS facilitates remote collaboration, communication, and socialization within digital startups. The findings comprise material properties of ECS (synchrony and asynchrony communication), functional affordances (virtual office and culture development affordances) as well as its realization (through communication practices, openness, and inter-company accessibility) and are conceptualized as a model for ECS affordances in digital startups.
The popularity of social media and particularly Instagram grows steadily. People use the different platforms to share pictures as well as videos and to communicate with friends. The potential of social media platforms is also being used for marketing purposes and for selling products. While for Facebook and other online social media platforms the purchase decision factors are investigated several times, Instagram stores remain mainly unattended so far. The present research work closes this gap and sheds light into decisive factors for purchasing products offered in Instagram stores. A theoretical research model, which contains selected constructs that are assumed to have a significant influence on Instagram user´s purchase intention, is developed. The hypotheses are evaluated by applying structural equation modelling on survey data containing 127 relevant participants. The results of the study reveal that ‘trust’, ‘personal recommendation’, and ‘usability’ significantly influences user’s buying intention in Instagram stores.