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Auflistung S17 - SKILL 2021 - Studierendenkonferenz Informatik nach Erscheinungsdatum
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- TextdokumentDistance Decay Effect and Spatial Interaction during the COVID-19 Pandemic(SKILL 2021, 2021) Wolz, Nicolas; Xu, Manning; Wang, TiantianIn computational communication science, social network data can be used to analyze trends in the communication behavior of people. For this work, a data set containing english Tweets was provided by the University of Technology Ilmenau, which was collected during the begining of the COVID-19 pandemic. The goal was to find hidden patterns within the data to show if and how the pandemic influenced our communication. This paper looks at the Distance Decay Effect, which says that near things are more related to each other than distant things, and therefore communication should get more sparse the greater the distance between users. Modeling the data with a Gravity Model shows that this relationship is true for the data provided, therefore reproducing earlier research on this topic. We were not successful in finding any clear trend showing that the strengh of the Distance Decay Effect changed over the course of the first weeks of the pandamic.
- TextdokumentIT-Qualitätsmanagement im Rahmen des Informationsmanagements(SKILL 2021, 2021) Zenth, Benjamin; Malik, MajeedDie Anzahl an zu verarbeitenden Unternehmensdaten steigt stetig an, in diesem Kontext stellt das Informationsmanagement eine zentrale Disziplin dar. Dem IT-Qualitätsmanagement kommt hierbei eine wichtige strategische Rolle zu, da es die Qualitätssicherung der einzelnen Teilbereiche des Informationsmanagements zum Ziel hat. Obwohl dieses folglich eine zentrale Managementaufgabe darstellt, fehlt es einer aktuellen Betrachtung zum Stand der Wissenschaft. Mit dem vorliegenden Beitrag schließen wir diese Forschungslücke und zeigen den aktuellen Stand der Wissenschaft zum IT-Qualitätsmanagement im Rahmen des Informationsmanagements und decken möglichen Forschungsbedarf auf. Hierfür wurden 38 Teilthemen zum IT-Qualitätsmanagement im Rahmen des Informationsmanagements definiert und je Teilthema eine Literaturanalyse im Zeitraum 2016 bis 2021 durchgeführt. Dabei wurde je Teilthema der aktuelle Stand der Wissenschaft aufgezeigt und eine Einordnung hinsichtlich des zukünftigen Forschungsbedarfs vorgenommen. Hierbei konnte in einem Teilthema ein hoher, in 20 ein mittlerer und in 16 ein niedriger Forschungsbedarf identifiziert werden.
- TextdokumentDie BYTE Challenge(SKILL 2021, 2021) Hildebrand, Stefan; Neumann, CarolinDie BYTE Challenge ist ein digitaler Wettbewerb für Schüler*innen aus ganz Deutschland, der Informatik, Informationstechnische Grundlagen sowie deren gesellschaftliche Bedeutung vermittelt und auf die Reduzierung bestehender Ungerechtigkeiten im MINT-Bereich hinwirken soll. Dazu soll die Teilnahme in jeder Hinsicht niedrigschwellig möglich sein; die Teilnahme ist kostenlos.
- TextdokumentKünstliche Intelligenz im Requirements Engineering(SKILL 2021, 2021) Breuninger, Judith; Kücher, Franziska; Misic, NataliDem Einsatz von Künstlicher Intelligenz (KI) im Requirements Engineering (RE) wird ein hohes Potenzial zugeschrieben. Der Stand der Forschung gestaltet sich jedoch unübersichtlich. Im Rahmen einer Systematischen Literaturrecherche werden 27 wissenschaftliche Publikationen aus drei Datenbanken identifiziert und analysiert. Anschließend werden diese in die RE-Phasen der Anforderungserhebung, -analyse, -spezifikation und -validierung eingeordnet und zusammengefasst. Die Ergebnisse zeigen, dass KI in den vier Phasen eingesetzt wird, allerdings ist die Anwendung unterschiedlich stark ausgeprägt. Weitere tiefgehende Forschungsarbeit, insbesondere zum Einsatz von KI in der Anforderungsvalidierung, ist notwendig. Die vorliegende Arbeit stellt dafür einen wesentlichen Ausgangspunkt dar, indem sie einen strukturierten Überblick der verschiedenen KI-Methoden zum Einsatz im RE aufzeigt und diskutiert.
- TextdokumentAnomaly Detection in Motion Timeseries using the Bosch XDK and Dynamic Time Warping(SKILL 2021, 2021) Mejía, Julián Rico; Isaías, Oscar Aguilar Aguila; Paschapur, PriyankaThis paper presents the development of an anomaly detector for robotic movements using the dynamic time warping (DTW) algorithm and its implementation in Matlab. Data was collected by mounting the Bosch Cross-Domain Development Kit (XDK) sensor on a collaborative robot arm (Cobot), aiming at industrial applications in need for motion anomaly detection during repetitive tasks. The paper discusses practical issues like parameter tuning as well as algorithmic variants such as decoupling accelerometer and gyroscope data.
- TextdokumentData-based Transparency and Leadership in Small and Medium-sized Enterprises(SKILL 2021, 2021) Mayer, CarmenBased on the increasing usage of Information Systems (IS), the amount of employee-specific data in companies is rising. As this data is more often used for leadership, referred to as data-based leadership, the question about complete transparency and its consequences in companies needs consideration. This work therefore, aims to analyze the amount of gathered employee-specific data, the resulting data-based leadership, and the exercised control and transparency in small and medium enterprises (SME) which have limited experience in using digital leadership approaches. The applied case study provides qualitative insights into these aspects. This case study is based on five selected SMEs from different industries. With my study, I enhance control theory and derive practical recommendations for a sustainable handling of employee-data for leadership.
- TextdokumentDesigning an ethical technology project with the help of Data Feminism(SKILL 2021, 2021) Gleißner, Lea-Kathrin; Bui, Magdalena; Kühn, Fey; Nenninger, AmelieAlgorithms and new technologies help people in several life situations, but society pays a high price for their advantages. Several scandals occurred recently, showing that algorithms are neither neutral nor fair – quite the contrary: They discriminate people as humans do. One approach to create less biased data science projects is the “Data Feminism” method, presented by Catherine D’Ignazio and Lauren F. Klein in their book of the same title. This paper evaluates how feasible the method can be implemented in student projects based on the experiences four Leipzig students made by trying to implement the method into their project ‘Questioning Street Names Leipzig’. The paper focusses on three main concepts: subjective viewpoints and context, crediting all forms of labour, and building and linking communities through public tagging events, thus opening the academic question for some citizen science help. The project utilizes open data and open data sources such as Wikidata and OpenStreetMap. The authors of “Data Feminism” want to encourage students, as well as academic professionals, to think about their bias in their data and to use the data feminism approach to reduce the impact of them and create more ethical computer science projects.
- TextdokumentMultiple Sequence Alignment using Deep Reinforcement Learning(SKILL 2021, 2021) Joeres, RomanMultiple sequence alignment (MSA) is one of the primal problems in biology and bioinformatics. The question of how to align multiple sequences correctly is crucial for many other fields of research, e.g., gaining information about the evolutionary distance of two or more sequences and therefore about their corresponding species, finding protein targets for drugs, or finding a drug for a certain target protein. Reinforcement learning (RL), and especially deep reinforcement learning (DRL), has become popular in recent years. To name just a few, DRL has shown major success in complex games such as Atari Games, Chess, and Go. We model the problem of aligning multiple sequences as a Markov decision process (MDP) and examine the performance of different (D)RL algorithms compared to state-of-the-art tools.
- TextdokumentBicycle Detection from Top View Perspective in Surveillance System using Convolutional Neural Network(SKILL 2021, 2021) Ramkumar, Sanal DarshidBicycle detection and tracking from top view perspective using deep learning is a highly active research area for video surveillance and automatic ticket generation in Advanced Public Transportation System (APTS). People detection using conventional cameras has received massive attention for video surveillance inside public transportation systems but inattentive towards bicycle detection. Experimentation is performed on You Only Look Once (YOLO), Faster Regional-Convolutional Neural Network (Faster R-CNN) and Single Shot Multibox Detector (SSD). Due to the sparse availability of dataset for this work, a customized dataset was recorded in the Media Computing lab, Junior Professorship of Media Computing, TU Chemnitz, Germany. The customized dataset was recorded using a wide-angle smart stereo sensor (S2000, Intenta GmbH) mounted in bird’s eye perspective. Furthermore, two additional datasets were recorded using a mobile camera representing indoor and outdoor bicycle parking area. This paper provides best case solution for bicycle detection from a top view perspective.
- TextdokumentThe Impact of Domain Knowledge on Applying Machine Learning Methods to Exoplanet Detection(SKILL 2021, 2021) Nguyen, The-Gia LeoExoplanets do not emit electromagnetic waves which makes it challenging to detect them. Based on transit photometry, we trained a neural network on NASA Kepler space telescope data to detect exoplanets based on light intensity curves. We showcase, that with a well designed data pipeline, a small neural network is sufficient to achieve state-of-the-art performance, saving both computation time and hardware cost. The strongest improvement in performance could only be achieved by adding domain specific processing steps to the data pipeline. Domain knowledge was essential in selecting the appropriate machine learning concepts that are beneficial to solving the problem and have a higher impact on the performance than the actual classification method itself. We encourage to consider the data pipeline as an additional component, besides the classification model, that can potentially improve the overall performance.