The European Union’s ambitious climate targets necessitate substantial reductions in greenhouse gas emissions, particularly within the heating and cooling sector, which accounts for a significant portion of energy consumption. District Heating and Cooling (DHC) systems emerge as a key solution for decarbonizing this sector by enabling high efficiency heat production and the integration of renewable and carbon-neutral energy sources. Despite the potential inherent in DHC systems, their utilization is limited, partly due to challenges associated with network topology selection. This master’s thesis addresses the optimization of District Heating Network layout expansion while tackling these challenges. Situated within the framework of an European funded project coordinated by EIFER, the research aims to develop an algorithm for modeling and planning the expansion of DHN networks, considering geographical location of pipes and heat production and consumption nodes. Building upon the Automatic Network Drawing Algorithm (ANDA) tool provided by EIFER, the project seeks to enhance it to generate expansion scenarios incorporating loops, a feature critical for network robustness absent in the current output. The tool pandapipes is used for fluid system modeling, effectively modelinghydraulics and heat through network elements such as heat producer, substationsand pipes. The algorithm’s core feature is to strategically determine optimallocations along initial tree-like network expansions to incorporate loops. Variousheuristic approaches are tested to identify the most efficient expansion strategies,subsequently adding new lines to minimize total costs, encompassing both capitaland operational expenses. Real-world data from a District Heating Network inMilan validate the algorithm’s capabilities. / Europeiska unionens ambitiösa klimatmål kräver avsevärda minskningar av utsläppen av växthusgaser, särskilt inom värme- och kylsektorn, som står för en betydande del av energiförbrukningen. Fjärrvärme- och fjärrkylasystem (DHC) framstår som en nyckellösning för att minska koldioxidutsläppen i denna sektor genom att möjliggöra högeffektiv värmeproduktion och integrering av förnybara och koldioxidneutrala energikällor. Trots potentialen som finns i DHC-system är deras användning begränsad, delvis på grund av utmaningar i samband med val av nätverkstopologi. Denna masteruppsats behandlar optimering av utbyggnaden av fjärrvärmenätets layout samtidigt som man tacklar dessa utmaningar. Beläget inom ramen för ett europeiskt finansierat projekt koordinerat av EIFER, syftar forskningen till att utveckla en algoritm för modellering och planering av utbyggnaden av DHN-nät, med hänsyn till den geografiska placeringen av rör och värmeproduktions- och förbrukningsnoder. Med utgångspunkt i verktyget Automatic Network Drawing Algorithm (ANDA) från EIFER, försöker projektet förbättra det för att generera expansionsscenarier med slingor, en funktion som är avgörande för nätverkets robusthet som saknas i den aktuella utgången. Verktyget pandapipes används för modellering av vätskesystem, effektiv modellering av hydraulik och värme genom nätverkselement som värmeproducent, transformatorstationer och rör. Algoritmens kärnfunktion är att strategiskt bestämma optimala platser längs initiala trädliknande nätverksutbyggnader för att införliva slingor. Olika heuristiska tillvägagångssätt testas för att identifiera de mest effektiva expansionsstrategierna, och sedan läggas till nya linjer för att minimera de totala kostnaderna, som omfattar både kapital- och driftskostnader. Verkliga data från ett fjärrvärmenätverk i Milano validerar algoritmens kapacitet.

Актуальность темы обусловлена тем, что на металлургическом предприятии вручную ведётся подсчёт и сверка количества трубной продукции, что предполагает большие трудозатраты и допущение ошибок в подсчётах. Научная новизна состоит в том, что было проанализировано большое количество исследований по теме применения методов компьютерного зрения для автоматизации бизнес-процессов на металлургическом предприятии, а также разработана уникальная программа, распознающая геометрические фигуры на снимке и подсчитывающая их количество. Практическая значимость работы заключается в том, что разработанная программа будет ежедневно использоваться в процессе отгрузки трубной продукции, упрощая процесс подсчёта количества труб в пачке и снижая время обработки заказа на отгрузку. / The relevance of the topic is due to the fact that the metallurgical enterprise manually counts and reconciles the number of pipe products, which involves large labor costs and the assumption of errors in calculations. The scientific novelty lies in the fact that a large number of studies on the use of computer vision methods for automating business processes at a metallurgical enterprise have been analyzed, and a unique program has been developed that recognizes geometric shapes in the image and counts their number. The practical significance of the work lies in the fact that the developed program will be used daily in the process of shipping pipe products, simplifying the process of counting the number of pipes in a bundle and reducing the processing time of the shipment order.

Изучение языка – это замечательное занятие, которое расширяет наш кругозор и позволяет нам общаться с представителями различных культур и людей по всему миру. Традиционно языковое образование основывалось на традиционных методах, таких как учебники, словарный запас и языковой обмен. Однако с появлением машинного обучения наступила новая эра в обучении языку, предлагающая инновационные и эффективные способы ускорения овладения языком. Одним из интригующих применений машинного обучения в изучении языков является использование родственных слов, слов, которые имеют схожее значение и написание в разных языках. Для решения этой темы в данной исследовательской работе предлагается облегчить процесс изучения второго языка с помощью искусственного интеллекта, в частности нейронных сетей, которые могут идентифицировать и использовать слова, похожие или идентичные как на первом языке учащегося, так и на целевом языке. Эти слова, известные как лексические родственные слова, могут облегчить изучение языка, предоставляя учащимся знакомый ориентир и позволяя им связывать новый словарный запас со словами, которые они уже знают. Используя возможности нейронных сетей для обнаружения и использования этих родственных слов, учащиеся смогут ускорить свой прогресс в освоении второго языка. Хотя исследование семантического сходства в разных языках не является новой темой, наша цель состоит в том, чтобы применить другой подход для выявления русско-английских лексических родственных слов и представить полученные результаты в качестве инструмента изучения языка, используя выборку данных о лексическом и семантическом сходстве. между языками, чтобы построить модель обнаружения лексических родственных слов и ассоциаций слов. Впоследствии, в зависимости от нашего анализа и результатов, мы представим приложение для определения словесных ассоциаций, которое смогут использовать конечные пользователи. Учитывая, что русский и английский являются одними из наиболее распространенных языков в мире, а Россия является популярным местом для иностранных студентов со всего мира, это послужило значительной мотивацией для разработки инструмента искусственного интеллекта, который поможет людям, изучающим русский язык как англоговорящие, или изучающим английский язык. как русскоязычные. / Language learning is a remarkable endeavor that expands our horizons and allows us to connect with diverse cultures and people around the world. Traditionally, language education has relied on conventional methods such as textbooks, vocabulary drills, and language exchanges. However, with the advent of machine learning, a new era has dawned upon language instruction, offering innovative and efficient ways to accelerate language acquisition. One intriguing application of machine learning in language learning is the utilization of cognates, words that share similar meanings and spellings across different languages. To address this subject, this research paper proposes to facilitate the process of acquiring a second language with the help of artificial intelligence, particularly neural networks, which can identify and use words that are similar or identical in both the learner's first language and the target language. These words, known as lexical cognates which can facilitate language learning by providing a familiar point of reference for the learner and enabling them to associate new vocabulary with words they already know. By leveraging the power of neural networks to detect and utilize these cognates, learners will be able to accelerate their progress in acquiring a second language. Although the study of semantic similarity across different languages is not a new topic, our objective is to adopt a different approach for identifying Russian-English Lexical cognates and present the obtained results as a language learning tool, by using the lexical and semantic similarity data sample across languages to build a lexical cognates detection and words association model. Subsequently, depend on our analysis and results, will present a word association application that can be utilized by end users. Given that Russian and English are among the most widely spoken languages globally and that Russia is a popular destination for international students from around the world, it served as a significant motivation to develop an AI tool to assist individuals learning Russian as English speakers or learning English as Russian speakers.

Maintenance work on the railway system is crucial to its high efficiency where designing maintenance areas to carry out such work is the foundation. Much work has been done regarding designing maintenance areas on mainline tracks, but there is still a blank spot for a systematic method to design such areas within a train station. This project aims to develop a prototype digital decision-supporting program, using RailML 2.4 and Python, for designing maintenance areas in the train station. The program includes parsing RailML data, generating routes using a depth-first search method, matching traffic flows, and generating and visualizing maintenance areas. This project also proposes two new data structures for train routes and traffic flow, where the traffic flow data structure introduces a flow-based structure which ensures that the program can work without an accurate train timetable. The program is tested on two different infrastructure layouts, one is based on Katrineholm Central Station, with several different traffic flow profiles. The result shows the program is functioning and can produce reasonable maintenance areas. Some modifications are also being done to the Katrineholm Central Station test case to simulate the different but similar infrastructures and compare the generated maintenance areas. This report also discussed the limitations of the program and the assumptions and simplifications that were made for this prototype program. This report also suggests possible directions for further work. / Underhållsarbete på järnvägssystemet är avgörande för dess höga effektivitet där utformandet av dess underhållsområden är grunden. Mycket arbete har gjorts när det gäller att utforma underhållsområden på huvudspår, men det återstår fortfarande som ett vakuum rörande den systematiska metoden för att skapa sådana ytor inom tågstationer. Detta projekt syftar till att utveckla en prototyp av ett digitalt besluts-stödsprogram för att utforma underhållsområden på tågstationer med hjälp av RailML 2.4 och Python. Programmet omfattar parsning av RailML-data, generering av rutter med hjälp av en Deep First Search-metod, matchning av trafikflöden samt generering och visualisering av underhållsområden. I projektet föreslås också två nya datastrukturer för tågvägar och trafikflöden, där datastrukturen för trafikflöden introducerar en flödesbaserad struktur som säkerställer att programmet kan fungera utan en exakt tågtidtabell. Programmet testas på två olika infrastrukturlayouter, varav den ena är baserad på Katrineholms Centralstation, med flera olika trafikflödesprofiler. Resultatet visar att programmet fungerar och kan producera rimliga underhållsområden. Vissa modifieringar görs också av testfallet för Katrineholms centralstation för att simulera olika men liknande infrastrukturer och jämföra de genererade underhållsområdena. I denna rapport diskuteras också programmets begränsningar och de antaganden och förenklingar som gjorts för detta prototypprogram. Denna rapport föreslår också möjliga riktningar för fortsatt arbete.

Radar system development is generally costly, complicated and time consuming. This has kept its presence mostly inside industries and research centers with the necessary equipment to produce and operate such a system. Until recent years, realization of a fully integrated radar system on a chip was not feasible, however this is no longer the case and there are several types of sensors available from different manufacturers. Radar sensors offer some advantages that are unmatched by other sensing and imaging technologies such as operation in fog, dust and over long distances. This makes them suitable for use in Navigation, Automation, Robotics, and Security systems applications. The purpose of this thesis is to demonstrate the feasibility of a simplified radar system’s user interface via integration with the most common portable computer, a Smartphone, to make it possible for users with minimal knowledge of radar systems design and operation to use it in different applications. Smartphones are very powerful portable computers equipped with a suite of sensors with the potential to be used in a wide variety of applications. It seems logical to take advantage of their computing power and portability. The combination of a radar sensor and a smartphone can act as a demonstrator in an effort to bring radar sensors one step closer to the hands of the developers and consumers. In this study the following areas are explored and proper solutions are implemented; Design of a control board with capability to drive a radar sensor, capture the signal and transfer it to a secondary device (PC or Smartphone) both wired and wirelessly e.g. Bluetooth. A firmware that is capable of driving the control board and can receive, interpret and execute messages from a PC and or a Smartphone A cross compatible master software that can run on Linux, Windows, Mac and Android OSs and is capable of communication with the firmware/control board Proper analysis methods for signal capture and process purposes Automation of some parameter adjustment for different modes of operation of the Radar System in order to make the user interface as simple as possible A user friendly user-interface and API that can run on both PC and Smartphone

The key of presented diploma thesis is to find a way to take shape of roads into account when performing network analysis. Methods of mathematical representation of shape of lines are discussed; the curvature is chose for later use. Then the relation between road's curvature and speed is discussed - the model for setting the speed is suggested. Important part of the thesis is focused on implementation in GIS. Designed model is implemented by Python in the ArcGIS for Desktop. Due to testing on specific examples, it was confirmed, that the taking the shape characteristics into account provides high précising of network analysis.

<p>It takes time to model buildings in a 3D city environment, for example in a game. Time is usually something very constricted in a production stage of anything, whether it is a personal project at home, at school or more occurring; in the 3D industry. This report will bring forth a method to quickly generate detailed buildings with the help of Python scripting, integrated in Maya 2009. The script will be working with modules that will be assembled together to create a modern city type of building. A comparison will be made between this script and a couple other scripts that offer the same solution but in different ways.</p>

It takes time to model buildings in a 3D city environment, for example in a game. Time is usually something very constricted in a production stage of anything, whether it is a personal project at home, at school or more occurring; in the 3D industry. This report will bring forth a method to quickly generate detailed buildings with the help of Python scripting, integrated in Maya 2009. The script will be working with modules that will be assembled together to create a modern city type of building. A comparison will be made between this script and a couple other scripts that offer the same solution but in different ways.

Control design for flexible robots is a challenging problem. Part of the difficulty comes from a lack of controls-focused modeling tools. Practical flexible robots have several aspects that make them difficult to model: continuous elements, complicated actuators, multiple feedback loops, non-collocated sensors and actuators, and the ability to take on arbitrary three-dimensional poses. Even if existing techniques for modeling flexible structures could model the closed-loop response of a hydraulically-actuated flexible robot with a vibration suppression controller, how would such a model be used for control design? This work presents the development of a modeling approach that meets the needs of a controls engineer. The approach is based on the transfer matrix method (TMM). The TMM has been expanded in several ways to enable it to accurately model practical flexible robots. Quantitative agreement is shown between model and experiment for the interaction of a hydraulic actuator and a flexible structure as well as for the closed-loop response of a system with vibration suppression. Once the ability to model the closed-loop response of the system has been demonstrated, this work focuses on using the model for control design. Control design is facilitated by symbolic implementation of the TMM, which allows closed-form expressions for the closed-loop response of the system to be found without discretization. These closed-form expressions will be transcendental transfer functions for systems with continuous elements. These transfer functions can then be used in various optimization approaches for designing the closed-loop system response.

Proposes a new method to model the geometric form of articulated mechanical parts while simultaneously testing their range of motion in relation to other nearby parts. Utilizing a database of mechanical parts in virtual three-dimensional form, a software tool assists users in quickly building a complex high-level mechanical object which can be placed directly into a visual effects production pipeline. The tool creates a workflow that allows modeling and rigging problems to be solved concurrently within the same interface. Optimized animation controls are generated automatically to expedite the rigging process. A system of standardization provides a framework for each part?s functionality within the hierarchy of each new assembly, while also guaranteeing reusability and backwards compatibility with all other assemblies created with this tool. A prototype has been developed as a plug-in to existing commercial software to showcase the described methodology. This prototype provides a unique solution to common modeling and rigging problems in the field of visual effects and animation.