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Dashboard KPI for OST
Get PDFMany companies today use Key Performance Indicators (KPIs) to monitor trends and to control their decision-making processes.
The OST has also implemented KPIs to get a comprehensive overview of various aspects of their organization.
Currently, these KPIs are manually tracked in a large Excel sheet.
However, as the datasets grow, this approach becomes increasingly challenging to manage.
The goal of this semester thesis was to develop a prototype for a web application that could eventually replace the current solution.
The application must support the creation and adjustment of KPIs and their formulas, include a user permission system to restrict access to certain data, and provide a method for entering new data.
Additionally, it should allow for filtering and visualizing data sets in graphs to facilitate informed decision-making.
The prototype developed in this project supports all previously mentioned functionalities and introduces several new features.
Users can add supplementary information to data entries, providing context for anomalies such as sudden spikes or drops in graphs.
A date filter has also been added, allowing users to select specific time periods when necessary.
Currently, the application supports importing large datasets directly from CSV files.
In the future, the application could be further improved by retrieving data automatically from surrounding systems, reducing maintenance efforts and minimizing errors caused by manual user input.
In conclusion, this project has successfully delivered a prototype that improves confidentiality, accessibility, and user experience.
Future enhancements will continue to refine the tool, ensuring it remains adaptable and meets evolving needs
Digital Forensics - Creation of a Crime Scene and Digital Evidences
No full textDigital forensics is a rapidly developing field that is critical to modern law enforcement, cybersecurity, and legal investigations.
It is crucial to have well-educated professionals to ensure that criminal activity in the digital realm can be correctly and securely identified.
The work presented in this paper serves to advance the field of digital forensics by combining a comprehensive theoretical foundation with the creation of a practical learning environment.
Thorough documentation of the creation of this investigation lab not only supports educational efforts by providing instructional materials, but also aims to serve as a stepping stone for future similar endeavours.
Creating digital evidence can be time-consuming, and it requires a high degree of attention to detail.
The methods evaluated in the presented work can support the creation of future labs to strengthen the forensic community.
The theoretical foundation examines fundamental concepts in digital forensics, focusing on the dynamic nature of cyber threats, evolving technologies, and the legal landscape.
Emphasis is placed on the significance of a proactive and adaptive approach to investigations, taking into account the challenges posed by encrypted communications, cloud storage, and emerging technologies.
By showing the development process of a forensic training scenario using a concrete example, readers are introduced to both challenges and opportunities faced when creating similar work
Der digitale Kostümfundus
Get PDFIm Fokus der vorliegenden Arbeit stehen die beiden Auftraggeber Bühnen Bern und das Luzerner Theater, sowie der Fundus von SRF (Schweizer Radio und Fernsehen) als zusätzlicher Praxispartner. Für Theater-Aufführungen werden Kostüme extra neu hergestellt – in Bern sind das pro Jahr ca. 1’000 Kostüme. Nach den Aufführungen werden diese in den Kostümfundus verschoben. Der Kostümfundus wächst so über die Jahre zu einer beträchtlichen Grösse an und beherbergt zum heutigen Zeitpunkt in Bern und Luzern je ca. 30’000 Kostüme. Das Wissen über die Kostüme und den Fundus befindet sich in den Köpfen von einzelnen Personen. Die ganzen Prozesse rund um den Bereich Kostüm und Kostümfundus sind hauptsächlich analog.
Das Projektteam legt den Schwerpunkt der Arbeit auf einen zentralen Kostüm-Finder, dem «Kostüm+». Dabei handelt es sich um ein Digitalisierungsprojekt eines analogen Prozesses. Innerhalb der Masterarbeit soll untersucht werden, wie eine für Theater und andere Institutionen übergreifende, zentrale Lösung die Kostümfundus Verantwortlichen unterstützen kann. Im Zentrum steht die Inventarisierung, Suche und Ausleihe von Kostümen. Nachhaltigkeit und Vernetzung der Institutionen stehen dabei als übergeordnete Leitgedanken über der Arbeit. Die Transparenz sowie die Zugänglichkeit zum Knowhow rund um die Kostüme im Fundus sollen erhöht werden.
Die vorliegende Arbeit orientiert sich an dem Vorgehensmodell Contextual Design von Beyer und Holtzblatt. Das Projektteam startet mit einem aufwendigen Research in die Arbeit. Aus den konsolidierten Ergebnissen werden Produktideen für den Bereich Inventarisierung, Suche und Ausleihe entwickelt. Die Produktkonzepte werden drei Testings unterzogen. Gestartet wird in die Testings mit Handskizzen und einem Hallway-Test, zumeist mit Laien. Die beiden weiteren Testings werden in den Institutionen mit Fachspezialisten durchgeführt. Zuerst mit einem Wireframe Prototypen und in der zweiten Testing Runde mit einem Design Prototypen.
Einen guten digitalen Kostüm-Finder zu entwickeln, reicht aber nicht aus, um Prozesse im Fundus des Theaters zu verändern. Es braucht hier Personen, die eine Veränderung anstossen wollen und diese Veränderungen auch tragen.
Die Digitalisierung des Kostümfundus kann in mehreren Etappen umgesetzt werden. Dabei soll mit der Inventarisierung gestartet werden, da alle anderen Prozesse von den digital erfassten Kostümen abhängig sind. Zusätzlich wird den Praxispartnern eine Checkliste für eine Umsetzung des Projekts an die Hand gegeben, um eine mögliche Hemmschwelle für den Umsetzungsprozess zu minimieren.
Das Projektteam startet ohne Vorwissen in das Thema «Digitalisierung des Kostümfundus» und überwindet die anfängliche Skepsis der Praxispartner. Im Verlauf gelingt es, Begeisterung zu wecken und die Vorteile der Digitalisierung aufzuzeigen. Die Zusammenarbeit im Viererteam ist stets positiv, zielorientiert und produktiv. Das Thema interessiert alle vier Teammitglieder, da mit dem Projekt in der Theaterlandschaft etwas bewegt werden kann, sei es in der Nachhaltigkeit oder auch in den Arbeitsprozessen. Das Projektteam kann seine zu Beginn definierten Lernziele erreichen und hat ein neues Vorgehensmodell kennengelernt. Dieses bietet eine gute Orientierung während des Projektes mit dem nötigen Freiraum für die Anwendung passender Methoden
Einkaufshelfer Android App
Get PDFDas Ziel dieser Bachelorarbeit ist die
Entwicklung einer Android-App, die Verbrauchern hilft, Ihre Einkaufserlebnisse durch effiziente
Preisvergleiche und die Verfolgung von Preisentwicklungen zu optimieren. Im Kontext der
steigenden Inflation und Preisvolatilität steht die Notwendigkeit für einkommensschwache
Bevölkerungsschichten, Preise von Produkten aus verschiedenen Geschäften zu vergleichen, im
Vordergrund. Dies wird durch die Erstellung einer App ermöglicht, die mittels Optical Character Recognition
(OCR) Technologie die Produktnamen und Preise aus Kassenbelegen extrahiert und vergleicht.
Wesentliche Aspekte dieser Arbeit umfassen die Evaluation geeigneter Technologien für die
automatische und manuelle Erkennung der relevanten Bereiche auf dem Kassenbeleg und die
Textzeichenerkennung mittels einer OCR-Bibliothek. Die App soll es den Nutzern ermöglichen, ohne
Vorkenntnisse Kassenbelege scannen zu können, damit die App automatisch Preisänderungen ermitteln
kann.
Folgende Probleme wurden gelöst: die Erkennung von Textzeichen, relevanten
Textbereichen auf Kassenbelegen und Preisdifferenzen gleichnamiger Produkte aus dem
gleichen Laden. Der entwickelte Prototyp ermöglicht es Nutzern, Belege in der App zu erfassen und
Preisschwankungen seit dem letzten Einkauf zu sehen. Dabei werden nur selbst erfasste Daten
genutzt, ohne Berücksichtigung von Rabattaktionen. Anfangs wurde für die Texterkennung die OCRLibrary des Google ML Kits verwendet, wobei der
Benutzer den relevanten Textbereich zuschneiden musste. Mit einer Regex wurden die Informationen
strukturiert ausgelesen. Um die Texterkennung zu verbessern, wurde experimentell festgestellt, dass
homogene Beleuchtung wichtig ist, um einen effizienten Binarisierungsalgorithmus anzuwenden,
der den Text vom Rest des Bildes löst. Da der Ansatz mit OCR und Regex ein bestimmtes Format der
Kassenbelege erfordert, wurde später die Google Gemini API verwendet. Gemini führt Texterkennung
und automatische Bereichserkennung durch, sodass verschiedene Belegstrukturen besser ausgelesen
werden können. Der Benutzer muss den relevanten Bereich nicht mehr manuell zuschneiden.
Experimentell wurde festgestellt, dass Gemini besser mit Bildern bei schlechter Beleuchtung umgehen
kann, wahrscheinlich durch eigene Bildverarbeitungsschritte wie Binarisierung. Der
Nachteil von Gemini ist die erforderliche Internetverbindung und die längere Verarbeitungszeit.
In einer Weiterentwicklung könnten die erfassten Daten anonymisiert gesammelt und an alle Benutzer
zur Verfügung gestellt werden, um aktuellere Preisänderungen anzuzeigen. Dies eröffnet
Möglichkeiten für ein Empfehlungssystem, z.B. ob ein Produkt an einem anderen Standort günstiger ist oder
ob ein Rabatt wirklich ein Rabatt ist, oder ob zuvor der Preis erhöht wurde.
Die Entwicklung einer App, die Kassenbelege scannen und relevante Informationen daraus
extrahieren kann, ist eine grosse Herausforderung, da Kassenbelege sehr unterschiedliche Formate haben
und die Daten beliebig strukturiert sein können. Modelle, die maschinelles Lernen verwenden, sind
besonders vielversprechend, um mit den verschiedenen Kassenbeleg Formaten umgehen zu
können. In der Arbeit wurde eine Grundlage erarbeitet, auf der ein schnelles und robustes System
zur Lösung der genannten Probleme entwickelt werden kann
upsi - a decentralized STI tracing approach
Get PDFIntroduction
Sexually Transmitted Infections (STIs) are a significant global public health challenge. While in Switzerland the incidence of Human Immunodeficiency Virus (HIV) has been declining since the 1980s pandemic, other STIs such as Chlamydia, Gonorrhea, and Syphilis exhibit an upward trend. Effective partner notification is essential to mitigate the spread of STIs. However, it is not practiced sufficiently, and no dedicated technical solution currently addresses this challenge.
During the COVID19 pandemic, proximity tracing mobile apps were successfully deployed to combat the spread of SARSCoV2. Various system architectures were employed, utilizing different approaches concerning privacy and data sovereignty.
Objective
The primary objective of this thesis is to design and develop upsi, a mobile application for STI partner notification. Inspired by the COVID19 proximity tracing apps, upsi aims to enhance partner notification, thereby mitigating the spread of STIs. Experts in the field of STIs will be consulted to evaluate the feasibility and importance of upsi.
Approach
Research was conducted to understand the current STI situation and existing solutions for STI partner notification and COVID19 proximity contact tracing. A concept for upsi was developed based on insights gained from the research and presented to leading STI experts. The expert feedback was integrated into the solution design. A minimum viable product (MVP) was developed using the most feasible technologies evaluated.
Results
upsi, a partner notification application for STI rapid tests, was developed with a focus on privacy and decentralization. The solution consists of a Flutter mobile app for users, which provides contact exchange and partner notification, and a second mobile app for test center employees to ensure trustworthy notifications. A .NET Core server application deployed to Azure handles the publication of positive test results onto the Optimism blockchain and simplifies wallet handling for the test center employees.
STI experts responded positively to the proposed concept and provided helpful inputs and insights that were integrated into upsi. While technical solutions for partner notification are discussed among experts, integration into existing IT systems remains challenging due to the large number of test centers, each using its own IT solution.
Further Work
Further development of the app is suggested, including the extension to iOS mobile devices and additional features to enhance user experience and functionality. Integration into existing STI test center IT systems should be carried out to also handle laboratory tests. Additionally, a study to evaluate the effectiveness and acceptance of upsi among users should be conducted
Entwicklung einer gamifizierbaren Anwendung für die Programmierausbildung
Get PDFThis Bachelor's thesis documents the implementation and design of Codable. Codable is a user-centered application for creating, managing and solving exercises in an academic environment. Its main goal is to improve the organizational and qualitative problems of exercises in the Department of Computer Science, which were identified in the preceding semester thesis written by Lukas Messmer and Mathias Fischler. The paper focuses on the architectural design of Codable and documents aspects such as the implemented plugin system, the automation process for exercise submissions and evaluations, as well as the architectural decomposition of the system
API Security Lab
Get PDFAPIs (Application Programming Interfaces) are integral to modern software development and digital transactions, facilitating communication and data exchange between diverse systems. However, their widespread use has made them prime targets for cyberattacks. Many APIs are developed rapidly without sufficient security measures, leading to vulnerabilities such as weak authentication, data exposure, inadequate logging, and poor error handling.The bachelor thesis aims to develop labs in API security for future OST Hacking-Lab students to raise awareness of risks.
The research phase extensively examined API history, styles, and security fundamentals. Key areas such as threat identification, authentication methods and the OWASP Top 10 API Security Risks 2023 were explored. This foundational research informed the collection and categorization of lab ideas, which were then evaluated using a decision matrix based on feasibility, educational value, and expandability criteria.
A proof of concept (PoC) phase validated the feasibility of each lab, followed by iterative improvements based on detailed feedback from usability testing. Participants evaluated the labs on setup difficulty, usability, design, and realism, leading to enhancements that ensured an effective learning experience.
The project successfully developed six labs covering most OWASP Top 10 API Security risks. Each lab provided hands-on experience identifying and mitigating these vulnerabilities through practical exercises using tools in a containerized environment.
To enhance the educational value, future expansions could include additional labs to cover remaining OWASP risks and specialized areas like cloud provider APIs and advanced OAuth2 authentication flows
AI-based Review Analysis
No full textThe rapid expansion of e-commerce in Switzerland, especially during the COVID-19 pandemic, has led to a significant increase in product reviews.
This term paper addresses the challenge of efficiently summarizing key aspects of a product from its reviews into keywords to help customers make decisions.
The goal was to develop an AI solution capable of extracting and condensing product review insights into concise positive and negative keywords, following an approach similar to the AI-driven keyword generation used by Digitec Galaxus AG.
The final solution uses a single large language model (LLM) to provide both flexibility and robust performance while requiring no training.
OpenAI's gpt-4o mini model was chosen for its cost-effectiveness and large context size.
The workflow, implemented in Python using Jupyter notebooks, systematically extracts review aspects and aggregates them into three positive and three negative keywords per product.
The process follows a four-stage pipeline:
(0) Review Data Composition, where raw review data is organized for analysis;
(1) Aspect Extraction, where positive and negative aspects are isolated for easier reprocessing;
(2) Chunk Summarization, where similar aspects are consolidated over multiple reviews to reduce complexity and fit context boundaries of the LLM; and (3) Aspect Unification, where aspects are aggregated across all the chunks to produce final keywords.
Additional stages to extend functionality, such as generating summaries or incorporating user-defined criteria, are described in this term paper.
The verification showed the ability to effectively summarize large amounts of product reviews into positive and negative keywords, capturing many key aspects mentioned in the reviews.
However, some problems were observed during the verification phase.
The keywords generated were often overly broad or generic, making it difficult to identify specific product features.
In addition, the system sometimes combined multiple features into a single keyword, resulting in some lost features.
Despite these challenges, the approach demonstrated promising results and strong potential as a proof of concept.
However, further development is needed to improve the precision of keyword generation for productive use
Wish an instant map!
Get PDFThe aim of this work is to develop a proof-of-concept (POC) for an open-source QGIS plugin capable of translating natural language queries into Overpass-QL to perform spatial, temporal and attributive filtering of OpenStreetMap (OSM) data. The plugin visualises query results directly in QGIS. For example, a query like "All cafés within 50 metres of a fountain in St. Gallen" is processed and rendered as a map. Unlike existing solutions that either require knowledge of Overpass-QL (e.g. QuickOSM) or are proprietary, this plugin aims to make such functionality accessible to non-experts.
The query processing consists of three main steps: (1) geoname recognition and geocoding (e.g. resolving "St. Gallen"), (2) recognition and semantic alignment of spatial entity sets (SES) with OSM attributes (e.g. mapping "café" to `amenity=cafe`), and (3) generation of Overpass-QL queries. Early attempts to implement the plugin using open source models such as LLaMA yielded suboptimal results. Consequently, a fine-tuned OpenAI GPT-4o model was used, resulting in significant improvements in query generation. Geonames were resolved using Photon, an OSM-based geocoder, in addition to OpenAI's assistant, and SES were mapped using semantic similarity analysis with pre-embedded OSM tags.
The finetuned LLMs were evaluated using 100 natural language queries, with the best fine-tuned GPT-4o model achieving a BLEU score of 0.67, significantly outperforming base models and open source alternatives. The exact match rate was 0.09, indicating room for improvement in the generation of perfectly accurate queries. Most of the generated Overpass-QL queries were functional within QGIS, with a high validity rate, although still lacking in semantic precision.
The resulting QGIS plugin, called Wish an Instant Map! (WAIM), was implemented in Python using the two preprocessing steps, together with the finetuned OpenAI LLM. The graphical user interface includes text input for queries, support for current map extents, and an expert mode for editing OverpassQL. While the system has demonstrated feasibility through black-box testing with English language queries, challenges remain, including reliability of generated queries and reliance on proprietary LLMs.
Future improvements can include the development of an OSM thesaurus to improve semantic matching, the integration of structured output for query validation, and the use of larger datasets or larger LLMs to fine-tune open-source models. Despite its limitations, WAIM illustrates the potential for combining AI with geospatial systems
Mondriλn: A Visual Programming Language Based on the Lambda Calculus
Get PDFThe lambda calculus is a core part of every functional programming class. However, students often find it difficult to grasp, especially the process of beta reduction. Hence, representing lambda terms and the beta reduction process visually could improve its comprehensibility to students and motivate them to learn more about the subject. The goal was to design a visual language for the representation of lambda terms which can aid students’ understanding of lambda calculus. In addition, the language aims to be visually pleasing, simple to draw and reason about on paper, and straightforward to read for humans. A proof of concept application should be created to ensure that the implementation of this language is feasible.
The team conducted research about existing visual esoteric programming languages and visual lambda calculus representations. The results of this research influenced the design of the language. Additionally, the SVG format was chosen for storing the visual representations. Mondriλn uses coloured rectangles and their relative positions to represent lambda terms. This design was inspired by the Dutch painter Piet Mondrian. The language allows for artistic freedom without sacrificing its understandability. Furthermore, it is able to represent all lambda terms, only limited by the number of colours displayable on screens. The proof of concept application is implemented as a command line tool and supports generating images from lambda terms, parsing a lambda term from an image and performing beta reduction on them. This proves that it is possible to implement the language we envisioned. Mondriλn appears to make lambda terms simpler to understand, particularly when it comes to the beta reduction process.
While the language shows promise, its potential usefulness to students remains an open question. Further evaluation is needed to determine how effectively it can aid students’ understanding of lambda calculus, with a particular focus on the beta reduction process. Some unresolved issues remain in the proof of concept application, for example, when handling large lambda terms. A next step to improve the usability of the system could be to develop a web-based interface, which could also offer additional features. Overall, this project provides a good starting point for further development. By addressing the aforementioned limitations and opportunities for enhancement, the system can become even more usable and effective