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In this paper we discuss how group processes can be influenced by designing specific tools in computer supported collaborative leaning. We present the design of a shared workspace application for co-constructive tasks that is enriched by certain functions that are able to track, analyze and feed back parameters of collaboration to group members. Thereby our interdisciplinary approach is mainly based on an integrative methodology for analyzing collaboration behavior and patterns in an implicit manner combined with explicit surveyed data of group members’ attitudes and its immediate feedback to the groups. In an exploratory study we examined the influence of this feedback function. Although we could only analyze ad-hoc groups in this study, we detected some benefits of our methodology which might enrich real life Learning Communities’ collaboration processes. The data analysis in our study showed advantages of this feedback on processes of a group’s well-being as well as parameters of participation. These results provide a basis for further empirical work on problem solving groups that are supported by means of parallel interaction analysis as well as its re-use as information resource.
Artificial intelligence (AI) is one of the most auspicious yet controversial technologies with virtually unlimited potential to solve almost all of the existential problems humanity is facing today.1 Huge resources are poured into the development, testing and application of AI that is supposed to be utilized in almost all areas of everyday life.2 It may be used to combat genetically inherited diseases, to revolutionize the economy, to bring prosperity and equality to everyone and to counter the effects of climate change.3 With AI as the enabling technology humanity may experience a better future. Today, AI capabilities can already drastically improve analytic processing tasks and algorithmic systems and have beaten humans in games such as chess.4 Yet, AI and all of its applications bring about a myriad of ethical challenges. Revolutionary weapon systems that achieve autonomy via AI and genome-editing powered by AI are just some specific examples.5 An omnipotent AI will be either the greatest or the vilest thing that has happened to humanity in its brief existence.6 However, even today more and more computational devices are connected to each other, spurring a huge increase in global data streams that can be used to further train and enhance AI systems.
The prowess of AI for executing analytic tasks paves the way for the use of AI in more and more applications. One of these applications, that shows great promise, is the use of AI in surveillance applications.7 AI surveillance applications are proliferating at a fast rate, with a number of appli-cations already being in use today.8 These applications are aimed at accomplishing a number of policy objectives, some are in accordance with basic human laws, some are definitely not and some
1 Cf. Hawking (2018). P. 183ff
2 Cf. Hawking (2018). P. 183ff.
3 Cf. Hawking (2018). P. 183ff.
4 Cf. Burton (2015). P. 1ff.
5 Cf. Hawking (2018). P. 183ff.
6 Cf. Hawking (2018). P. 183ff.
7 Cf. Feldstein (2019). P. 1.
8 Cf. Feldstein (2019). P. 1.
2
belong in the nebulous area in between lawful and unlawful.9 But what are lawful and unlawful uses of AI surveillance systems and what are their ethical implications?
This thesis will examine the ethical implications of AI based mass surveillance systems and try to answer the first central question, if it is possible to use AI based mass surveillance applica-tions in an ethical way. Furthermore, the thesis will attempt to answer the second central ques-tion and find out how the ethical use of AI based mass surveillance systems, if this ethical use is possible, materialize. Governmental agencies will be in the focus of this discussion, as their use of the technology may have bigger ethical challenges. Yet private companies will play a part as well. In an attempt to accomplish these two aims, the thesis will inspect the basics of ethics and possible ethical theories that can be utilized to answer the questions. Normative ethics will be stud-ied first with a focus on consequentialism and utilitarianism. To gain a deeper understanding of utilitarianism, act and rule utilitarianism will be compared. Afterwards, deontological theories will be the focus of the discussion with a concentration on deontological pluralism. Next, the mentioned theories will be evaluated, discussing advantages and weak spots of the theories, to assess which theory may serve as the ethical framework of this thesis and the subsequent answer to the two main questions.
The next step will be the establishment of the AI framework. This contains the definition of AI and a distinction of terms that are commonly used in the its environment such as automation and au-tonomy. The importance of data for AI will be discussed. Afterwards, the technological basis of AI will be outlined, discussing key concepts such as machine learning and deep learning. Addi-tionally, it will be examined how an AI learns. The possible uses of AI in general will be outlined in a brief fashion, blazing the trail to discussing the moral challenges of AI. Afterwards, the current pace of AI development will be studied.
In the chapter that follows, the use of AI in surveillance technology is going to be highlighted. The possible ways of how AI can be used for surveillance purposes are reviewed here, discussing facial
9 Cf. Feldstein (2019). P. 1.
3
and behavioral recognition systems, smart cities, smart policing, communications/data driven sur-veillance and their enabling technologies. Then, the global proliferation of AI surveillance systems is going to be outlined.
Subsequently, the accordance of AI surveillance with basic human laws and rights, such as the right to privacy, will be checked to find out if the law and the international framework of human rights allow for AI surveillance or at least have restrictions that would greenlight the use of AI surveillance technology. All the aspects of the thesis, especially including the selected ethical framework, will be combined in this last section in order to enable the adaptation of a framework that allows to find out, if AI surveillance systems can be ethically permissible while also creating insights how this ethical AI surveillance system must be engineered. To finish, the thesis will end with a conclusion.
A simple copper coil without a voluminous stationary magnet can be utilized as a non-contacting transmitter and as a detector for ultrasonic vibrations in metals. Advantages of such compact EMATs without (electro-)magnet might be: applications in critical environments (hot, narrow, presence of iron filings…), potentially superior fields (then improved ultrasound transmission and more sensitive ultrasound detection).
The induction field of an EMAT strongly influences ultrasound transduction in the nearby metal. Herein, a simplified analytical method for field description at high liftoff is presented. Within certain limitations this method reasonably describes magnetic fields (and resulting eddy currents, inductances, Lorentz forces, acoustic pressures) of even complex coil arrangements. The methods can be adapted to conventional EMATS with a separate stationary magnet.
Increased distances (liftoff) are challenging and technically relevant, and this practical question is addressed: with limited electrical power and given free space between transducer and target metal, what would be the most efficient geometry of a circular coil? Furthermore, more complex coil geometries (“butterfly coil”) with a concentrated field and relatively higher reach are briefly investigated.
This experimental study demonstrates for the first time a solid-state circuitry and design for a simple compact copper coil (without an additional bulky permanent magnet or bulky electromagnet) as a contactless electromagnetic acoustic transducer (EMAT) for pulse echo operation at MHz frequencies. A pulsed ultrasound emission into a metallic test object is electromagnetically excited by
an intense MHz burst at up to 500 A through the 0.15 mm filaments of the transducer. Immediately thereafter, a smoother and quasi “DC-like” current of 100 A is applied for about 1 ms and allows an
echo detection. The ultrasonic pulse echo operation for a simple, compact, non-contacting copper coil is new. Application scenarios for compact transducer techniques include very narrow and
hostile environments, in which, e.g., quickly moving metal parts must be tested with only one, non-contacting ultrasound shot. The small transducer coil can be operated remotely with a cable
connection, separate from the much bulkier supply circuitry. Several options for more technical and fundamental progress are discussed.
Background:
Detection of influential actors in social media such as Twitter or Facebook plays an important role for improving the quality and efficiency of work and services in many fields such as education and marketing.
Methods:
The work described here aims to introduce a new approach that characterizes the influence of actors by the strength of attracting new active members into a networked community. We present a model of influence of an actor that is based on the attractiveness of the actor in terms of the number of other new actors with which he or she has established relations over time.
Results:
We have used this concept and measure of influence to determine optimal seeds in a simulation of influence maximization using two empirically collected social networks for the underlying graphs.
Conclusions:
Our empirical results on the datasets demonstrate that our measure stands out as a useful measure to define the attractors comparing to the other influence measures.
Background:
Influential actors detection in social media such as twitter or Facebook can play a major role in gathering opinions on particular topics, improving the market
-
ing efficiency, predicting the trends, etc.
Proposed methods:
This work aims to extend our formally defined
T
measure to
present a new measure aiming to recognize the actor’s influence by the strength of
attracting new important actors into a networked community. Therefore, we propose a
model of the actor’s influence based on the attractiveness of the actor in relation to the
number of other attractors with whom he/she has established connections over time.
Results and conclusions:
Using an empirically collected social network for the
underlying graph, we have applied the above-mentioned measure of influence in
order to determine optimal seeds in a simulation of influence maximization. We study
our extended measure in the context of information diffusion because this measure is
based on a model of actors who attract others to be active members in a community.
This corresponds to the idea of the IC simulation model which is used to identify the
most important spreaders in a set of actors.
Keywords: Actor influence, Social media networks, Twitter, IC model, Information
diffusion, Independent cascade model, T measure
In this work we report the first quasi-continuous in-situ photoluminescence study of growing InGaN LED structures inside an industrial-grade metal-organic vapor phase epitaxy (MOVPE) reactor at growth temperature. The photoluminescence spectra contain information about temperature, thickness and composition of the epitaxial layers. Furthermore, the in-situ spectra – even at an early stage of the growth of the active region – can be used to predict the photoluminescence emission wavelength of the structure at room temperature. In this study an accuracy of this predicted wavelength in the range of ± 1.3 nm (2σ) is demonstrated. This technique thus appears suitable for closed-loop control of the emission wavelength of InGaN LEDs already during growth.
Photoluminescence (PL) in GaN or InGaN layers monitored during epitaxial growth at high temperatures permits a quasi-continuous in situ characterization of opto-electronic properties. Therefore, epitaxial parameters can now be optimized at the earliest possible stage. A pulsed and high-power UV laser was required for PL excitation at high temperatures. Herein, the underlying nonlinear mechanism was studied via time-resolved PL experiments and rate equation-based modeling. A temperature-activated and saturable path for quenching over defects was identified. Beyond the saturation threshold, reasonably-intensive PL sets in. At high temperatures not only is the near band gap-PL present, but also—as a new observation—a defect-assisted PL emerges. Apart from these specific electronic transitions in high-temperature PL of GaN, a simple, but reasonably predictive model of the luminescent thin film has been set up to track down interference fringes in the PL spectra. It is worth mentioning that the spectral PL modulation (aiming at the Purcell effect) is often mixed up with ordinary Fabry–Pérot interference. A distinction has become key to properly analyze the spectral signatures of high-temperature PL in order to provide a reliable in situ characterization of GaN layers during epitaxial growth
Digital transformation is a process of digitizing the working and living environment in which people are at the center of digitization. In this paper, we present a personas-based guideline for system developers on how the humanization of digital transformation integrates into the design process. The proposed guideline uses the positive personas from the beginning as a basis for the transformation of the working environment into the digital form. We used the literature research as a preliminary study for the process of wellbeing-driven digital transformation design, consisting of questions for structuring the required information in the positive personas as well as a potential method that could be integrated into the wellbeing-based design process.
This study aims to determine the competing concerns of people interested in startup development and entrepreneurship by using topic modeling and sentiment analysis on a social question-and-answer (SQA) website. Understanding the underlying concerns of startup entrepreneurs is critical to society and economic growth. Therefore, greater scientific support for entrepreneurship remains necessary, including data mining from virtual social communities. In this study, an SQA platform was used to identify the sentiment of thirty concerns of people interested in startup entrepreneurship. Based on topic modeling and sentiment analysis of 18819 inquiries in various forums on an SQA, we identified additional questions about founder figures, keys to success, and the location of a startup. In addition, we found that general questions were rated more positively, especially when it came to pitching, finding good sources, disruptive innovation, idea generation, and marketing advice. On average, the identified concerns were considered 48.9 percent positive, 41 percent neutral, and 10.1 percent negative. This research establishes a critical foundation for future research and development of digital startups by outlining a variety of different concerns associated with startup development in the digital age.