This thesis introduces "SNR," a Python library for programming robotic systems in the context of introductory robotics courses. Greater demand for roboticists has pressured educational institutions to expand robotics curricula. Students are now more likely to take robotics courses earlier and with less prior programming experience. Students may be attempting to simultaneously learn a systems programming language, a library API, and robotics concepts. SNR is written purely in Python to present familiar semantics, eliminating one of these learning curves. Industry standard robotics libraries such as ROS often require additional build tools and configuration languages. Students in introductory courses frequently lack skills needed for these tools. SNR does not use any additional build tools, so students are faced with fewer compounding learning curves. SNR presents students with concepts important to robotic systems programming such as modular and event driven architectures to bridge the gap between introductory programming courses and industry standard libraries.

This thesis deals with the design of a software library for PLC Siemens S7-1200 usable in programming of robotic cell. The theoretical part explains the principle of PLC programming and the configuration of an industrial robot. The practical part presents the design of the software library and then the individual blocks of the library are described. The library contains blocks for PLC and is also supplemented by blocks for HMI. Using the proposed library reduces the time required for programming. The software library allows the creation of a unified structure of control programs within the company. The result of the diploma thesis is a tested software library usable in the field.

With the ever-growing size of sequence data sets, data processing and analysis are an increasingly large portion of the time and money spent on nucleic acid sequencing projects. Correspondingly, the performance of the software and algorithms used to perform that analysis has a direct effect on the time and expense involved. Although the analytical methods are widely varied, certain types of software and algorithms are applicable to a number of areas. Targeting improvements to these common elements has the potential for wide reaching rewards. This dissertation research consisted of several projects to characterize and improve upon the efficiency of several common elements of sequence data analysis software and algorithms. The first project sought to improve the efficiency of the short read mapping process, as mapping is the most time consuming step in many data analysis pipelines. The result was a new short read mapping algorithm and software, demonstrated to be more computationally efficient than existing software and enabling more of the raw data to be utilized. While developing this software, it was discovered that a widely used bioinformatics software library introduced a great deal of inefficiency into the application. Given the potential impact of similar libraries to other applications, and because little research had been done to evaluate library efficiency, the second project evaluated the efficiency of seven of the most popular bioinformatics software libraries, written in C++, Java, Python, and Perl. This evaluation showed that two of libraries written in the most popular language, Java, were an order of magnitude slower and used more memory than expected based on the language in which they were implemented. The third and final project, therefore, was the development of a new general-purpose bioinformatics software library for Java. This library, known as BioMojo, incorporated a new design approach resulting in vastly improved efficiency. Assessing the performance of this new library using the benchmark methods developed for the second project showed that BioMojo outperformed all of the other libraries across all benchmark tasks, being up to 30 times more CPU efficient than existing Java libraries.

Over the past 10 years, smartwatches have become increasingly popular for commercial use. Their ever-increasing capabilities, accuracy, and sophistication of smartwatches is making them increasingly appealing to physical activity researchers as a valuable research tool. The non-invasive nature, prevalence, and versatility of smartwatches is being utilized to track heart rate, blood-oxygen levels, activity and movement, and sleep. However, the current state of the art lacks a uniform method to extract, organize, and analyze data collected from these devices. The objective of this research was to develop a Python software library that is widely available, highly capable, and easy to use with the data collected by the Apple Watch. The library was designed to offer data science, visualization, and mining features that help physical activity research find and communicate patterns in the Apple Health data. The custom-built caching system of the library provides near-instant runtime to parse and analyze large files without trading off on memory usage. The Wanjara Smartwatch Library has significantly better performance, proven reliability and robustness, and improved usability than the alternatives discovered in the review of the literature. / Master of Science / Over the past 10 years, smartwatches have become increasingly popular for commercial use. Their ever-increasing capabilities, accuracy, and sophistication of smartwatches is making them increasingly appealing to physical activity researchers as a valuable research tool. The non-invasive nature, prevalence, and versatility of smartwatches is being utilized to track heart rate, blood-oxygen levels, activity and movement, and sleep. However, the current state of the art lacks a uniform method to extract, organize, and analyze data collected from these devices. The objective of this research was to develop a Python software library that is widely available, highly capable, and easy to use with the data collected by the Apple Watch. The library was designed to offer data science, visualization, and mining features that help physical activity research find and communicate patterns in the Apple Health data. The custom-built caching system of the library provides near-instant runtime to parse and analyze large files without trading off on memory usage. The Wanjara Smartwatch Library has significantly better performance, proven reliability and robustness, and improved usability than the alternatives discovered in the review of the literature.

Les logiciels dépendent de bibliothèques tierces pour réduire les coûts liés à leur développement et à leur maintenance. Elles proposent un ensemble de fonctionnalités robustes dont les développeurs peuvent tirer parti depuis une interface de programmation. Cependant, cette forte dépendance entre un logiciel et ses bibliothèques oblige les développeurs à reconsidérer leur rôle lorsque le logiciel évolue. Dans cette thèse, nous identifions plusieurs problématiques impliquant les bibliothèques tierces dans un contexte de maintenance logicielle. Plus particulièrement, une bibliothèque peut ne plus répondre aux besoins d’un logiciel et doit être remplacée par une nouvelle.Nous nommons cette opération une migration de bibliothèque.Nous soulevons dans ce contexte trois points qui caractérisent les difficultés rencontrées par les développeurs. Vers quelle bibliothèque migrer ? Comment appliquer la migration ? Avec l’aide de quels développeurs ? Cette thèse discute de solutions et apporte des contributions autour de ces problèmes. Nous présentons plusieurs approches et les évaluons lors de différents cas d’étude. L’analyse de l’évolution logicielle sera notre support de travail, dont la méthodologie est basée sur l’observation des changements de logiciels. Nous décrivons les limites actuelles de nos contribu-tions et ouvrons des perspectives futures pour enrichir l’état de l’art dans ce domaine / Software depend on third-party libraries to reduce development and maintenance costs. Developers have access to robust functionalities through an application programming interface designed by these libraries. However, due to the strong relationship with these libraries, developers have to reconsider their position when the software evolves. In this thesis, we identify several re-search problems involving these third-party libraries in a context of software maintenance. More specifically, a library may not satisfy the software new requirements and has to be replaced by anew one. We call this operation a library migration.We leverage three points that characterize the impediments met by developers in this situation.To which library should they migrate ? How to migrate their software ? Who can help them in this case ? This thesis suggests answers and exposes several contributions to these problems. We define three approaches that are evaluated through several case studies. To achieve this work, weuse a methodology based on software evolution analysis to observe and understand how software change. We describe numerous perspectives to overcome the current limitations of our solutions.

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In this diploma thesis, the reader is introduced to artificial neural networks and convolutional neural networks. Based on that, the design and implementation of a new library for convolutional neural networks is described. The library is then evaluated on widely used datasets and compared to other publicly available libraries. The added benefit of the library, that makes it unique, is its independence on data types. Each layer may contain up to three independent data types - for weights, for inference and for training. For the purpose of evaluating this feature, a data type with fixed point representation is also part of the library. The effects of this representation on trained net accuracy are put to a test.

The dissertation focuses on library automation. It examines relationships between the field of library automation and library management systems and the needs of libraries in relation to the process of library software selection. The main goal of the dissertation has been to create a library automation domain ontology and to develop tools to support a decision-making process of library software selection. The domain ontology has been created; it describes the field of library automation in relation to library systems, which are set in the broader context of the field of library automation and are regarded in terms of needs of libraries in connection to library software change. To obtain terms for ontology entity names both quantitative and mixed research methods were used, namely the analysis of scholarly texts on library automation and library systems; text analyses were performed using Voyant Tools software. Object properties and relationships among entities in ontology are based on the results of a qualitative survey of the needs of libraries in relation to the library management software. Based on the domain ontology, flowcharts have been created that illustrate the library's decision-making process when selecting a library management system. During the work on the dissertation, a methodological...

Chatbots are becoming increasingly popular in various industries, and thereare many options available for businesses and organisations. Several studieshave investigated open-source chatbots and identified their core strengths,implementation, and integration capabilities however few have investigatedopen-source chatbot frameworks and libraries in a specific use case such asmedicine. The project's objective was to evaluate a selection of chatbots ormore specifically two frameworks: Botkit and Rasa, and two libraries:ChatterBot, and Natural which was utilised together with Botkit and alanguage model which is DialoGPT. The evaluation focuses specifically onaccuracy, consistency, and response time. Frequently asked questions fromthe World Health Organization and COVID-19 related Dialogue Datasetfrom GitHub were utilised to test the chatbots' abilities in handling differentqueries and accuracy was measured through metrics like Jaccard similarity,bilingual evaluation understudy (BLEU), and recall oriented gistingevaluation (ROUGE) scores, consistency through Jaccard similarity betweenthe generated responses and response time was taken to be the average timefor a response in seconds. The analysis revealed unique strengths andlimitations for each chatbot model. Rasa displayed robust performance inaccuracy, consistency, and customisation capabilities if the chatbot works ina particular topic with acceptable response times. DialoGPT demonstratedstrong conversational abilities and contextually relevant responses withtrade-offs in consistency. ChatterBot showed consistency, though sometimesstruggled with advanced queries, and Botkit with Natural stood out for itsquick response times, albeit with limitations in accuracy and scalability.Despite implementation challenges, these open-source frameworks, libraries,and models offer promising solutions for organisations intending to harnessconversational agents' technology. The study suggests encouraging furtherexploration and refinement in this rapidly evolving field.