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Schriften zur Kultur- und Mediensemiotik | Online. Ausgabe 5
No full textSchriften zur Kultur- und Mediensemiotik | Online ist ein Open Access Journal des Virtuellen Zentrums für kultursemiotische Forschung / Virtual Centre for Cultural Semiotics (www.kultursemiotik.com). Die Ausgabe 5 wurde von Peter Klimczak herausgegeben.
Inhalt der fünften Ausgabe der Schriften zur Kultur- und Mediensemiotik | Online
Peter Klimczak (Hrsg.)
Vorwort
Thomas Wegener
Sinnvoll oder sinnfrei? Zur Darstellung von Geschichte im historischen Spielfilm
Samuel Schilling
Die selbstreferentielle Stadt: Kommunikation und die Orte urbaner Öffentlichkeit
Christian Ostwald
Filmischer Raum als Ort der Kontemplation in Andrej Tarkovskijs STALKER
Denis Newiak
Nicht-Ort Bates Motel:
Vorüberlegungen zu einer Ikonografie der Einsamkeit in der amerikanischen Moderne
Andreas Neumann
Sexualität und Rollenzuweisung der Frau im späten DDR-Fernsehen: Ein beispielhafter Einblick in ein vernachlässigtes Forschungsfeld
Peter Klimczak
Mono- und polyisotopische Lesarten von Walther von der Vogelweides Ir reiniu wîp, ir werden man (L. 66,21)
Anke Donnerstag
Die Deutschen und die Nazis: Figurendarstellungen in zeithistorischen Spielfilmen des öffentlich-rechtlichen Fernsehens
Impressum / Neuerscheinunge
Sinnvoll oder sinnfrei? Zur Darstellung von Geschichte im historischen Spielfilm
No full textAusgehend von den gattungsspezifischen Besonderheiten des Historienfilms zeigt Thomas Wegener anhand zahlreicher Beispiele, dass der historische Spielfilm höchst eklektizistische Geschichtsbilder (nach)zeichnet. Diese Geschichtsbilder basieren einerseits überwiegend auf Vorstellungen des 19. Jahrhunderts, andererseits auf einer aus dem Faschismus bekannten Bildsprache. Keiner der Filme berücksichtigt den aktuellen historischen Forschungsstand. Vielmehr kommentieren die dargestellten, vergangenen, Welten aktuelle Ereignisse und Konflikte und spiegeln rezente Werte und Normen wider. Daher scheint es, so Thomas Wegener, für die historiographische Forschung sinnvoller zu sein, weniger nach dem „richtig“ oder „falsch“ zu fragen, sondern angesichts der enormen Breitenwirkung des Medium Films zu erörtern, wie genau Geschichte im Spielfilm gedacht und inszeniert wird
Sexualität und Rollenzuweisung der Frau im späten DDR-Fernsehen: Ein beispielhafter Einblick in ein vernachlässigtes Forschungsfeld
No full textAndreas Neumann macht in seinem Beitrag auf einen bisher von der Medien- aber auch Geschichtswissenschaft nur unzureichend beachteten Bereich der DDR-Fernsehforschung aufmerksam: Die Rolle der Frau in Partnerschaft und ihre Sexualität, sowie der Wandel der dementsprechenden Diskurse im Laufe der Zeit. Dabei wird der Grundannahme Michel Foucaults gefolgt, wonach es sich bei der Sexualität um einen besonders dichten Durchgangspunkt für Machtbeziehungen, nicht zuletzt zwischen Mann und Frau sowie Verwaltung und Bevölkerung, handelt. Anhand von drei, durchaus für die ganze Familie konzipierten, Fernsehserien - ABER VATI! (DDR 1974/1979), MÄRKISCHE CHRONIK (DDR 1983) und JOHANNA (DDR 1989) - analysiert Andreas Neumann die Darstellung von weiblichen Rollenbildern und der dazugehörigen Sexualität. Abschließend widmet sich der Beitrag auch den gesellschaftspolitischen Implikationen der aufgezeigten Darstellungen
RAPID: Resource and API-Based Detection Against In-Browser Miners
No full textDirect access to the system's resources such as the GPU, persistent storage and networking has enabled in-browser crypto-mining. Thus, there has been a massive response by rogue actors who abuse browsers for mining without the user's consent. This trend has grown steadily for the last months until this practice, i.e., CryptoJacking, has been acknowledged as the number one security threat by several antivirus companies.
Considering this, and the fact that these attacks do not behave as JavaScript malware or other Web attacks, we propose and evaluate several approaches to detect in-browser mining. To this end, we collect information from the top 330.500 Alexa sites. Mainly, we used real-life browsers to visit sites while monitoring resource-related API calls and the browser's resource consumption, e.g., CPU.
Our detection mechanisms are based on dynamic monitoring, so they are resistant to JavaScript obfuscation. Furthermore, our detection techniques can generalize well and classify previously unseen samples with up to 99.99\% precision and recall for the benign class and up to 96\% precision and recall for the mining class. These results demonstrate the applicability of detection mechanisms as a server-side approach, e.g., to support the enhancement of existing blacklists.
Last but not least, we evaluated the feasibility of deploying prototypical implementations of some detection mechanisms directly on the browser. Specifically, we measured the impact of in-browser API monitoring on page-loading time and performed micro-benchmarks for the execution of some classifiers directly within the browser. In this regard, we ascertain that, even though there are engineering challenges to overcome, it is feasible and beneficial for users to bring the mining detection to the browser
CSP & Co. Can Save Us from a Rogue Cross-Origin Storage Browser Network! But for How Long?
No full textWe introduce a new browser abuse scenario where an attacker uses local storage capabilities without the website's visitor knowledge to create a network of browsers for persistent storage and distribution of arbitrary data. We describe how security-aware users can use mechanisms such as the Content Security Policy (CSP), sandboxing, and third-party tracking protection, i.e., CSP & Company, to limit the network's effectiveness. From another point of view, we also show that the upcoming Suborigin standard can inadvertently thwart existing countermeasures, if it is adopted
Evaluation and Adaption of the Trier Inventory for Chronic Stress (TICS) for Assessment in Competitive Sports
No full textThe demands of a career in competitive sports can lead to chronic stress perception among athletes if there is a non-conformity of requirements and available coping resources. The Trier Inventory for Chronic Stress (TICS) (Schulz et al., 2004) is said to be thoroughly validated. Nevertheless, it has not yet been subjected to a confirmatory factor analysis. The present study aims (1) to evaluate the factorial validity of the TICS within the context of competitive sports and (2) to adapt a short version (TICS-36). The total sample consisted of 564 athletes (age in years: M = 19.1, SD = 3.70). The factor structure of the original TICS did not adequately fit the present data, whereas the short version presented a satisfactory fit. The results indicate that the TICS-36 is an economical instrument for gathering interpretable information about chronic stress. For assessment in competitive sports with TICS-36, we generated overall and gender-specific norm values
Cooperative Relative Positioning for Vehicular Environments
Get PDFFahrerassistenzsysteme sind ein wesentlicher Baustein zur Steigerung der Sicherheit im Straßenverkehr. Vor allem sicherheitsrelevante Applikationen benötigen eine genaue Information über den Ort und der Geschwindigkeit der Fahrzeuge in der unmittelbaren Umgebung, um mögliche Gefahrensituationen vorherzusehen, den Fahrer zu warnen oder eigenständig einzugreifen. Repräsentative Beispiele für Assistenzsysteme, die auf eine genaue, kontinuierliche und zuverlässige Relativpositionierung anderer Verkehrsteilnehmer angewiesen sind, sind Notbremsassitenten, Spurwechselassitenten und Abstandsregeltempomate.
Moderne Lösungsansätze benutzen Umfeldsensorik wie zum Beispiel Radar, Laser Scanner oder Kameras, um die Position benachbarter Fahrzeuge zu schätzen. Dieser Sensorsysteme gemeinsame Nachteile sind deren limitierte Erfassungsreichweite und die Notwendigkeit einer direkten und nicht blockierten Sichtlinie zum Nachbarfahrzeug. Kooperative Lösungen basierend auf einer Fahrzeug-zu-Fahrzeug Kommunikation können die eigene Wahrnehmungsreichweite erhöhen, in dem Positionsinformationen zwischen den Verkehrsteilnehmern ausgetauscht werden.
In dieser Dissertation soll die Möglichkeit der kooperativen Relativpositionierung von Straßenfahrzeugen mittels Fahrzeug-zu-Fahrzeug Kommunikation auf ihre Genauigkeit, Kontinuität und Robustheit untersucht werden. Anstatt die in jedem Fahrzeug unabhängig ermittelte Position zu übertragen, werden in einem neuartigem Ansatz GNSS-Rohdaten, wie Pseudoranges und Doppler-Messungen, ausgetauscht. Dies hat den Vorteil, dass sich korrelierte Fehler in beiden Fahrzeugen potentiell herauskürzen. Dies wird in dieser Dissertation mathematisch untersucht, simulativ modelliert und experimentell verifiziert. Um die Zuverlässigkeit und Kontinuität auch in "gestörten" Umgebungen zu erhöhen, werden in einem Bayesischen Filter die GNSS-Rohdaten mit Inertialsensormessungen aus zwei Fahrzeugen fusioniert. Die Validierung des Sensorfusionsansatzes wurde im Rahmen dieser Dissertation in einem Verkehrs- sowie in einem GNSS-Simulator durchgeführt. Zur experimentellen Untersuchung wurden zwei Testfahrzeuge mit den verschiedenen Sensoren ausgestattet und Messungen in diversen Umgebungen gefahren.
In dieser Arbeit wird gezeigt, dass auf Autobahnen, die Relativposition eines anderen Fahrzeugs mit einer Genauigkeit von unter einem Meter kontinuierlich geschätzt werden kann. Eine hohe Zuverlässigkeit in der longitudinalen und lateralen Richtung können erzielt werden und das System erweist 90% der Zeit eine Unsicherheit unter 2.5m. In ländlichen Umgebungen wächst die Unsicherheit in der relativen Position. Mit Hilfe der on-board Sensoren können Fehler bei der Fahrt durch Wälder und Dörfer korrekt gestützt werden. In städtischen Umgebungen werden die Limitierungen des Systems deutlich. Durch die erschwerte Schätzung der Fahrtrichtung des Ego-Fahrzeugs ist vor Allem die longitudinale Komponente der Relativen Position in städtischen Umgebungen stark verfälscht.Advanced driver assistance systems play an important role in increasing the safety on today's roads. The knowledge about the other vehicles' positions is a fundamental prerequisite for numerous safety critical applications, making it possible to foresee critical situations, warn the driver or autonomously intervene. Forward collision avoidance systems, lane change assistants or adaptive cruise control are examples of safety relevant applications that require an accurate, continuous and reliable relative position of surrounding vehicles.
Currently, the positions of surrounding vehicles is estimated by measuring the distance with e.g. radar, laser scanners or camera systems. However, all these techniques have limitations in their perception range, as all of them can only detect objects in their line-of-sight. The limited perception range of today's vehicles can be extended in future by using cooperative approaches based on Vehicle-to-Vehicle (V2V) communication.
In this thesis, the capabilities of cooperative relative positioning for vehicles will be assessed in terms of its accuracy, continuity and reliability. A novel approach where Global Navigation Satellite System (GNSS) raw data is exchanged between the vehicles is presented. Vehicles use GNSS pseudorange and Doppler measurements from surrounding vehicles to estimate the relative positioning vector in a cooperative way. In this thesis, this approach is shown to outperform the absolute position subtraction as it is able to effectively cancel out common errors to both GNSS receivers. This is modeled theoretically and demonstrated empirically using simulated signals from a GNSS constellation simulator.
In order to cope with GNSS outages and to have a sufficiently good relative position estimate even in strong multipath environments, a sensor fusion approach is proposed. In addition to the GNSS raw data, inertial measurements from speedometers, accelerometers and turn rate sensors from each vehicle are exchanged over V2V communication links. A Bayesian approach is applied to consider the uncertainties inherently to each of the information sources. In a dynamic Bayesian network, the temporal relationship of the relative position estimate is predicted by using relative vehicle movement models.
Also real world measurements in highway, rural and urban scenarios are performed in the scope of this work to demonstrate the performance of the cooperative relative positioning approach based on sensor fusion. The results show that the relative position of another vehicle towards the ego vehicle can be estimated with sub-meter accuracy in highway scenarios. Here, good reliability and 90% availability with an uncertainty of less than 2.5m is achieved. In rural environments, drives through forests and towns are correctly bridged with the support of on-board sensors. In an urban environment, the difficult estimation of the ego vehicle heading has a mayor impact in the relative position estimate, yielding large errors in its longitudinal component
Three essays on the welfare and social impacts of external shocks and public policies in Mexico
Get PDFIn this thesis I examine the welfare and social consequences associated with one economic shock and two policy interventions in Mexico. I use non-experimental approaches that exploit increased data availability as well as in-depth knowledge of the institutional background and show how germane extensions in the methodology shed light on previously unaccounted consequences and help better identify affected households. In particular, I quantify the role of quantity substitution effects in the alleviation of welfare, I estimate the effect of quality substitution on the efficiency of a taxation policy, and I document the possible consequences of an aggressive policy intervention on organized and property crime
Test of different structural equation models describing the relationship between nationalism, patriotism, and anti-immigration attitudes: documentation of an empirical study
Get PDFThis paper aims at the documentation of the results of a study dealing with the relationship between in-group and out-group attitudes. The research enquires into the question whether nationalistic, patriotic, and anti-immigration attitudes are only correlated with each other or whether there is a causal relationship. The presentation of the Mplus output together with the correlation and covariance matrices will allow the readers to control the results and, if they want to do it, to test alternative models
Mining Functional and Structural Relationships of Context Variables in Smart-Buildings
No full textThe Internet of Things (IoT) is a network of computational services, devices, and people, which share information with each other. In IoT, inter-system communication is possible and human interaction is not required. IoT devices are penetrating the home and office building environments. According to current estimates, about 35 billion IoT devices will be connected by the year 20212. In the IoT business model, value comes from integrating devices into applications, e.g., home and office automation. In general, an IoT application associates different information sources with actions which can modify the environment, e.g., change the room’s temperature, inform a person, e.g., send an e-mail, or activate other services, e.g., buy milk on-line.
In this thesis, we focus on the commissioning and verification processes of IoT devices used in building automation applications. Within a building’s lifespan, new devices are added, interior spaces are refurbished, and faulty devices are replaced. All of these changes are currently made manually. Furthermore, consider that a context-aware Building Management System (BMS) is an IoT application, which measures direct-context from the building’s sensors to characterize environmental conditions, user locations, and state. Additionally, a BMS combines sensor information to derive inferred-context, such as user activity. Similar to IoT devices, inferred-context instances have to be created manually. As the number of devices and inferred-context instances increases, keeping track of all associations becomes a time-consuming and error-prone task.
The hypothesis of the thesis is that users who interact with the building create use-patterns in the data, which describe functional relations between devices and inferred-context instances, e.g., which desk-movement sensor is used to infer desk-presence and controls which overhead light; additionally, use-patterns can also provide structural relations, e.g., the relative position of spatial sensors. To test the hypothesis, this thesis presents an extension to the new IoT class rule programming paradigm, which simplifies rule creation based on classes. The proposed extension uses a semantic compiler to simplify the device and inferred-context associations. Using direct-context information and template classes, the compiler creates all possible inferredcontext instances. Buildings using context-aware BMSs will have a dynamic response to user behaviour, e.g., required illumination for computer-work is provided by adjusting blinds or increasing the dim setting of overhead ceiling lamps. We propose a rule mining framework to extract use-patterns and find the functional and structural relationships between devices. The rule mining framework uses three stages: (1) event extraction, (2) rule mining, (3) structure creation. The event extraction combines the building’s data into a time-series of device events. Then, in the rule mining stage, rules are mined from the time series, where we use the established algorithm temporal interval tree association rule learner. Additionally, we proposed a rule extraction algorithm for spatial sensor’s data. The algorithm is based on statistical analysis of user transition times between adjacent sensors. We also introduce a new rule extraction algorithm based on increasing belief. In the last stage, structure creation uses the extracted rules to produce device association groups, hierarchical representation of the building, or the relative location of spatial sensors. The proposed algorithms were tested using a year-long installation in a living-lab consisting of a four-person office, a 12-person open office, and a meeting room. For the spatial sensors, four locations within public buildings were used: a meeting room, a hallway, T-crossing, and a foyer. The recording times range from two weeks to two months depending on scenario complexity.
We found that user-generated patterns appear in building data. The rule mining framework produced structures that represent functional and spatial relationships of building’s devices and provide sufficient information to automate maintenance tasks, e.g., automatic device naming. Furthermore, we found that environmental changes are also a source of device data patterns, which provide additional associations. For example, using the framework we found the façade group for exterior light sensors. The façade group can be used to automatically find an alternative signal source to replace broken outdoor light sensors. Finally, the rule mining framework successfully retrieved the relative location of spatial sensors in all locations but the foyer