This thesis is part of a joint thermochemical heat storage (TCS) research project named Neutrons for Heat Storage (NHS), involving three Nordic research institutes. The project isfunded by Nordforsk and KTH Royal Institute of Technology for the project partner KTH. KTH´s objective in the NHS project is to design, build and operate a bench-scale TCS system using strontium chloride (SrCl2) and ammonia (NH3) as a solid-gas reaction system for low temperature heat storage (40-100 ℃). Here, absorption of NH3 into SrCl2⋅NH3 (monoammine) to form SrCl2⋅8NH3 (octaammine) is used for heat release, and desorption (of NH3 from SrCl2⋅8NH3 to form SrCl2⋅NH3) for heat storage. This thesis initially aimed to conduct commissioning, operation and experimental data acquisition, and performance evaluation of the bench-scale TCS system. However, due to various delays in equipment delivery and shortcomings discovered during the project timeline, its objectives were then redefined to partially commission the system with NH3 and carry out the first absorption cycle in one of the reactors. This thesis project was partly a joint project, where Hjörtur Brynjarsson performed various tasks in the overarching NHS project as part of his thesis project, alongside the work described in this report. Brynjarsson’s work involved reviewing and adapting the design of this bench-scale TCS system. For further details about the shortcomings discovered and corresponding design adaptations, readers are referred to Brynjarsson’s report. In this thesis project, to understand the design of the TCS system, background research on the current project and the SrCl2-NH3 reaction pair was conducted. This includes comprehending the evolution of the project carried out by the previous students and project researchers to the current thesis project. Following this, the maximum theoretical volume of composites in the reactor-heat exchanger (R-HEX) was determined. This was found to be 5262 cm3, and the corresponding SrCl2 in the R-HEX is 1631 g for an average salt density in the composite of 0.31g/cm3. Thereupon, a literature review was conducted on the performance evaluation of Thermal energy storage (TES) systems. The final report of International Energy Agency (IEA) Annex 30 (on Applications of TES in the Energy Transition: Benchmarks and Developments) presents numerous Key Performance Indicators (KPIs) relevant to TES systems and are classified into technical, economic, and lifetime performance indicators. These KPIs are used as the basis for the current thesis work and are compared to examples from other metalhalide-NH3 TCS systems. Finally, for the current thesis project, it was decided to focus the KPIs on technical performance indicators, such as energy storage capacity [kJ] and reaction advancement [-]. As one of the main tasks within the project, the data acquisition system (for measuring temperature, pressure, and mass flow rate parameters), as well as the system components and many final connections, were commissioned herein. A data acquisition manual is thus provided for future use. It considers all the data measuring instruments and their respective locations in the system and the data logger. Also, explanations are provided for the calibration of these instruments. As the next main task, a thermal homogeneity test of the reactors (to compare the heat transfer similarity of reactors before the first reaction) was performed, to investigate the underlying assumption that the reactors were identical was valid. After conducting the test, it was found that reactor A had slightly better heat transfer than reactor B. However, this inhomogeneity is not significant enough to affect the system’s overall performance. As the final main task, partial commissioning of the system (i.e., for the first absorption reaction in reactor B) with N2 (as a mock-test to troubleshoot the procedure forNH3) and then with NH3 were carried out. During the partial commissioning of the system using NH3, the NH3 was added in short pressure pulses (between 5-8 bar(a)) with idling between each pulse due to some practical reasons. In addition to this, the absorption reaction was carried out under less than ideal (still not unfavourable) absorption conditions by deliberately setting the heat transfer fluid (HTF) at high temperatures (e.g., at 105, 90, and 65 °C) to avoid a drastic pressure drop in the reactor between each NH3 pulse. At the end of the NH3 commissioning (possible completion of absorption), it was found that 1541 g of NH3 passed through the mass flow meter. The most likely scenario is that 1521 g of NH3 reacted with the SrCl2 salt in the reactor (the rest, 20 g, is in the dead space, comprised of, e.g., the voids in composite, voids in the R-HEX, and the volume in the gas lines). The heat released from the absorption reaction, in this case, is 3774 kJ (or 1.05 kWh), considering all eight ammines. The heat released from the absorption reaction of SrCl2∙NH3 (monoammine) to SrCl2∙8NH3 (octaammine) is 3224 kJ (or 0.89 kWh). The discharge power calculation is excluded here due to the special approach used in this first absorption, with long idling steps, making that irrelevant. In addition, the sustainability aspects of this TCS technology (SrCl2-NH3) used in this project were analyzed. Based on the analysis, it was found that this technology is environmentally friendly, economically feasible, and can aid in social development. Hence, this technology is considered sustainable, and the designed TCS system has an overall positive impact on sustainable development. To conclude, within this project, the designed TCS system was successfully operated for the first absorption in one reactor and is found to meet the design storage capacity (0.89 kWh). As this TCS system was mainly operated for data acquisition, and since the first absorption was performed at less-than ideal conditions, better absorption conditions are recommended for the subsequent cycles, accommodating better temperature and pressure conditions for both absorption and desorption reactions. Finally, evaluation of the system's technical performance at different reaction conditions (pressure, temperature) and optimizing the system for energy and economics are some of the key follow-up tasks for future work that will benefit the system. / Detta exjobbsprojekt är en del av ett forskningsprojekt Neutrons for Heat Storage (NHS), som handlar om termokemisk energilagring (TCS) och genomfördes med hjälp av tre nordiska forskningsinstitut. Projektet finansieras av Nordforsk och KTH Kungliga Tekniska Högskolan för KTH. I NHS-projektet, KTH:s mål är att utforma, bygga och driva ett TCS-system i bänkskala med ett fast-gasreaktionssystem som använder reaktionsparet strontiumklorid (SrCl2) och ammoniak (NH3), för värmelagring vid låg temperatur (t.ex. 40-100 ℃). Här används specifikt absorption av NH3 i SrCl2⋅NH3 (monoammin) till SrCl2⋅8NH3 (oktaammin) för värmeavgivning och desorption av NH3 från SrCl2⋅8NH3 till SrCl2⋅NH3 för värmelagring. Detta projekt syftade inledningsvis till att genomföra driftsättning, drift och insamling av experimentella data samt utvärdering av prestanda för TCS-systemet i bänkskala. På grund av olika förseningar i leveransen av flertal utrustningar och brister som upptäcktes under projektets gång, omdefinierades målen till att ta en partiell driftsättning av systemet med NH3 och genomföra den första absorptionscykeln i en av reaktorerna. Detta exjobbsprojekt var delvis ett gemensamt projekt, där Hjörtur Brynjarsson utförde olika uppgifter i det övergripande NHS-projektet som en del av sitt exjobbsprojekt, parallelt med arbetet som beskrivs i denna rapport. Brynjarsson’s arbete bestod i att granska och anpassa utformningen av denna bänkskala i TCS-system. För ytterligare detaljer om de brister som upptäcktes och motsvarande anpassningar av utformningen hänvisas läsarna till Brynjarsson’s rapport. I detta exjobbsprojekt, för att förstå TCS-systemets utformning, genomfördes bakgrundsforskning om det aktuella NHS projektet och reaktionsparet SrCl2-NH3. Detta innefattar att förstå utvecklingen av NHS projektet från tidigare projekt utförda av studenter och projektforskare för att sammanställa detta exjobbsprojekt. Därefter fastställdes i detta projekt den maximala teoretiska volymen kompositer i reaktor-värmeväxlare enheten (RHEX). Den visade sig vara 5262 cm3 och att motsvarande SrCl2 i R-HEX är 1631 g för en genomsnittlig salttäthet i kompositen på 0,31 g/cm3. Därefter gjordes en litteraturstudie om utvärdering av prestanda för system för termisk energilagring (TES). Slutrapporten om bilaga 30 från International Energy Agency (IEA) (om tillämpningar av TES i energiomställningen: Benchmarks och Utvecklingar) presenterar ett flertal nyckelindikatorer (KPI:er) för prestandaanalys som är relevanta för TES-system och som är klassificerade i tekniska, ekonomiska och livslängdsindikatorer. Dessa KPI:er används som grund för den aktuella exjobben och jämförs med exempel från andra metallhalogenid-NH3- TCS-system. För detta exjobbprojektet beslutades slutligen att fokusera KPI:erna på tekniska prestandaindikatorer, t.ex. energilagringskapacitet [kJ] och reaktionsframsteg [-]. Som en av huvuduppgifterna inom detta projekt togs datainsamlingssystemet (för mätning av temperatur, tryck och massflödesparametrar) samt systemkomponenterna och många slutliga anslutningar i drift här. En användarmanual för datainsamling tillhandahålls därför för framtida användning. Den gäller alla instrument för datamätning och deras respektive placering i systemet samt dataloggern. Dessutom ges här förklaringar till kalibreringen av dessa instrument. Som nästa huvuduppgift utfördes ett test av reaktorernas termiska homogenitet (för att jämföra reaktorernas likhet i värmeöverföring före den första reaktionen), för att undersöka om det underliggande antagandet att reaktorerna var identiska var giltigt. Efter att ha utfört testet konstaterades det att reaktor A hade en något bättre värmeöverföring än reaktor B. Denna inhomogenitet är dock inte tillräckligt betydande för att påverka systemets totala prestanda. Som sista huvuduppgift genomfördes en partielldriftsättning av systemet (dvs. för den första absorptionsreaktionen i reaktor B) med N2 (som ett simuleringstest för att felsöka förfarandet för NH3) och sedan med NH3. Under den partiella idrifttagningen av systemet med NH3 tillsattes NH3 i korta tryckpulser (mellan 5-8 bar(a)) med tomgång mellan varje puls av praktiska skäl. Dessutom utfördes absorptionsreaktionen under mindre än ideala (men ändå inte ogynnsamma) absorptionsförhållanden genom att värmeöverföringsvätskan medvetet ställdes in på höga temperaturer (t.ex. 105, 90 och 65 °C) för att undvika en drastisk tryckminskning i reaktorn mellan varje NH3-puls. I slutet av NH3-installationen (eventuellt avslutad absorption) konstaterades att 1541 g NH3 passerade genom massflödesmätaren. Det mest sannolika scenariot är att 1521 g NH3 reagerade med SrCl2-saltet i reaktorn (resten dvs., 20 g, finns i det döda utrymmet, som t.ex.består av hålrummen i kompositen, hålrummen i R-HEX och volymen i gasledningarna). Den värme som frigörs från absorptionsreaktionen är i detta fall 3774 kJ (eller 1,05 kWh), om man beaktar alla åtta aminer. Den värme som frigörs från absorptionsreaktionen av SrCl2∙NH3 (monoammin) till SrCl2∙8NH3 (oktaammin) är 3224 kJ (eller 0,89 kWh). Beräkningen av utmatningseffekten är utesluten här på grund av det speciella tillvägagångssätt som används vid denna första absorption, med långa tomgångssteg, vilket gör att den är irrelevant. Dessutom analyserades hållbarhetsaspekterna av denna TCS-teknik (SrCl2-NH3) som användes i detta projekt. På grundval av analysen konstaterades det att denna teknik är miljövänlig, ekonomiskt genomförbar och kan bidra till social utveckling. Tekniken anses därför vara hållbar och det konstruerade TCS-systemet har en övergripande positiv inverkan på hållbar utveckling. Sammanfattningsvis kan man konstatera att det konstruerade TCS-systemet inom ramen för detta projekt används på ett framgångsrikt sätt för den första absorptionen i en reaktor och att det uppfyller den avsedda lagringskapaciteten (0,89 kWh). Eftersom detta TCS-system huvudsakligen användes för datainsamling och eftersom den första absorptionen utfördes under mindre än ideala förhållanden, rekommenderas bättre absorptionsförhållanden för de efterföljande cyklerna, med bättre temperatur- och tryckförhållanden för både absorptions och desorptionsreaktioner. Slutligen är utvärdering av systemets tekniska prestanda vid olika reaktionsförhållanden (tryck, temperatur) och optimering av systemet med avseende på energi och ekonomi några av de viktigaste uppföljningsuppgifterna för framtida arbete som kommer att gynna systemet.

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<p>  </p> <p>Cold chain logistics comprise a large portion of transported pharmaceutical medications and raw materials which must be preserved at specified temperatures to maintain consumer safety and efficacy. An immutable record of temperatures of transported pharmaceutical goods allows for mitigation of temperature-related issues of such drugs and their raw components. The recording of this information on a blockchain creates such an immutable record of this information which can be readily accessed by any relevant party. This can allow for any components which have not been kept at the appropriate temperatures to be removed from production. These data can also be used as inputs for smart contracts or for data analytic purposes. </p> <p>A theoretical framework for such a system, referred to as “TempEnsure” is described, which provides digital capture of the internal temperature of temperature-controlled shipping containers. The data are recorded in a blockchain system. Real world testing of this system was not possible due to monetary constraints, but the functional elements of the system, as well as potential improvements for the system, are discussed.</p>

<p dir="ltr">Achieving higher throughput is one of the most important requirements of a modern microcontroller. It is therefore not affordable for it to waste a considerable number of clock cycles in branch mispredictions. This paper proposes a hardware mechanism that makes microcontrollers forgo branch predictors, thereby removing branch mispredictions. The scope of this work is limited to low cost microcontroller cores that are applied in embedded systems. The proposed technique is implemented as five different modules which work together to forward required operands, resolve branches without prediction, and calculate the next instruction's address in the first stage of an in-order five stage pipelined micro-architecture. Since the address of successive instruction to a control transfer instruction is calculated in the first stage of pipeline, branch prediction is no longer necessary, thereby eliminating the clock cycle penalties occurred when using a branch predictor. The designed architecture was able to successfully calculate the address of next correct instruction and fetch it without any wastage of clock cycles except in cases where control transfer instructions are in true dependence with their immediate previous instructions. Further, we synthesized the proposed design with 7nm FinFET process and compared its latency with other designs to make sure that the microcontroller's operating frequency is not degraded by using this design. The critical path latency of instruction fetch stage integrated with the proposed architecture is 307 ps excluding the instruction cache access time.</p>

The telecommunications industry is rapidly advancing with the adoption of cloud-native technologies, aiming to enhance service delivery and network management. Kubernetes, an open-source platform for automating containerized applications, plays a significant role in this transformation. However, the use of Kubernetes in telecommunications presents unique challenges, particularly in effective network traffic separation. This thesis explores the feasibility and implications of exposing services on secondary network interfaces in Kubernetes to address traffic separation issues. The research investigates current trends and approaches for enabling service exposure on secondary interfaces, evaluates how these services support Kubernetes' resiliency features, and assesses the performance implications. A combination of literature review, empirical experiments, and interviews was used. Initially, a proof of concept (PoC) using Multus-service was attempted but faced setbacks due to the project's deactivation. Developer interviews revealed resistance within the Kubernetes SIG-Network group to modifying the established services API for secondary interfaces, and a lack of compelling use cases and community feedback led to the deprecation of Multus-service. Current trends indicate a shift towards more scalable, less disruptive solutions like the Gateway API. The focus then shifted to Meridio, another project claimed to have the capability of enabling service exposure through secondary interfaces. A successful PoC with Meridio in an OpenShift cluster served as the basis for further evaluations. The findings indicate that Meridio has the capability of providing service exposure through secondary network interfaces and aligns with Kubernetes' self-healing mechanisms. Performance evaluations showed that services on secondary interfaces could offer comparable overall performance to those on primary interfaces. Resource utilization metrics reveal additional CPU and memory overheads, but these are considered manageable. This research provides insights into the use of secondary network interfaces for service exposure in Kubernetes, contributing to ongoing discussions within Ericsson Cloud-RAN. The research underscores the need for further development and optimization, suggesting that with continued advancements, service exposure through secondary interfaces could enhance network management and service delivery in cloud-native environments.

Centralized Radio Access Networks or C-RAN for short is a type of network that aims to centralize perform some of it's computation at centralized locations. Since a lot of functionality is centralized we can show from multiplexing that the centralization leads to lower operating costs. The drawback with C-RAN are the huge bandwidth requirements over the fronthaul. We know that scenarios where all cells experience high load is a very low probability scenario. Since functions are centralized this also allows more adaptability, we can choose to change the communication standard for each cell depending on the load scenario. In this thesis we set out to create such a controller with the use of Deep Reinforcement Learning. The problem overall is difficult due to the complexity of modelling the problem, but also since C-RAN is a relatively new concept in the telecom world. We solved this problem with two traditional reinforcement learning algorithms, DQN and SAC. We define a constraint optimization problem and phrase it in such a way that the problem can be solved with a deep reinforcement learning algorithm. We found that the learning worked pretty well and we can show that our trained policies satisfy the constraint. With these results one could show that resource allocations problems can be solved pretty well by a deep reinforcement learning controller. / Centralized Radio Access Networks eller C-RAN som förkortning är en kommunications nätverk som siktar på att centralisera vissa funktioner i centrala platser. Eftersom mmånga funktioner är centraliserade så kan vi visa från statistisk multiplexing att hög trafik scenarion över många celler är av låg sannolikhet vilket leder till lägre service kostnader. Nackdelen med C-RAN är den höga bandbredds kravet över fronthaulen. Trafik scenarion där alla celler utsäts för hög last är väldigt låg sannolikhet så kan vi dimensionera fronthaulen för att klara mindre än det värsta trafik scenariot. Eftersom funktioner är centralizerade så tillåter det även att vi kan adaptivt anpassa resurser för trafiken. I denna uppsats så kommer vi att skapa en sådan kontroller med djup reinforcement learning. Problemet är komplext att modellera och C-RAN är ett relativt nytt concept i telecom världen. Vi löser detta problem med två traditionella algoritmer, deep Q networks(DQN) och soft actor critic(SAC). Vi definierar ett vilkorligt optimerings problem och visar hur det kan formuleras som ett inlärnings problem. Vi visar att denna metod funkar rätt bra som en lösning till problemet och att den uppfyller bivilkoren. Våra resultat visar att resurs allokerings problem kan lösas nära optimalitet med reinforcement learning.

Facial recognition technology has become a ubiquitous tool in security and personal identification. However, the rise of this technology has been accompanied by concerns over inherent biases, particularly regarding ethnic and gender. This thesis examines the extent of these biases by focusing on the influence of dataset imbalances in facial recognition algorithms. We employ a structured methodological approach that integrates AI-generated images to enhance dataset diversity, with the intent to balance representation across ethnics and genders. Using the ResNet and Vgg model, we conducted a series of controlled experiments that compare the performance impacts of balanced versus imbalanced datasets. Our analysis includes the use of confusion matrices and accuracy, precision, recall and F1-score metrics to critically assess the model’s performance. The results demonstrate how tailored augmentation of training datasets can mitigate bias, leading to more equitable outcomes in facial recognition technology. We present our findings with the aim of contributing to the ongoing dialogue regarding AI fairness and propose a framework for future research in the field.

Identifying facemasks is an important duty that affects public health and safety, especially during epidemics of communicable diseases. Many architectures of deep learning models are being investigated for their effectiveness, as they have demonstrated great potential in automating this process. The performance of four well-known deep learning architectures—VGG19, VGG16, GRU, and Fully Convolutional Neural Networks (FCNN)—for facemask identification is thoroughly compared in this thesis. The goal of the study is to assess these architectures in terms of accuracy, efficiency, and robustness in order to offer important information for the creation of efficient facemask detection systems. This study examines the advantages and disadvantages of each model in relation to facemask detection through thorough testing and analysis. The models are statistically evaluated for their ability to detect facemasks in pictures or video streams using performance metrics including precision, recall, and F1-score. Furthermore, the actual feasibility of using these models in real-world applications is assessed by analyzing computational efficiency measures like inference time and model size. Moreover, the models' resilience is assessed in a range of demanding scenarios, such as changes in illumination, facial expressions, and occlusions. The consequences of these results are discussed in the thesis along with suggestions for improving each architecture for facemask detection tasks. This study's methodology focuses on developing and evaluating deep learning models for facemask recognition that are especially suited for usage in mobile health care units. This method seeks to guarantee high accuracy, robustness, and efficiency in real-world healthcare environments, where prompt and accurate facemask detection is essential. Four well-known deep learning architectures VGG19, VGG16, Gated Recurrent Unit (GRU), and Fully Convolutional Neural Networks (FCNN) were chosen for the models' selection and development. Due to their shown effectiveness in a range of image recognition tasks and possible flexibility to facemask detection, these models were selected. / Идентификация лицевых масок является важной задачей, которая влияет на здоровье и безопасность населения, особенно во время эпидемий инфекционных заболеваний. Многие архитектуры моделей глубокого обучения исследуются на предмет их эффективности, поскольку они продемонстрировали большой потенциал в автоматизации этого процесса. В этой работе проводится тщательное сравнение производительности четырех хорошо известных архитектур глубокого обучения —VGG19, VGG16, GRU и полностью сверточных нейронных сетей (FCNN)— для идентификации лицевых масок. Цель исследования - оценить эти архитектуры с точки зрения точности, эффективности и надежности, чтобы предоставить важную информацию для создания эффективных систем обнаружения лицевых масок. В этом исследовании рассматриваются преимущества и недостатки каждой модели в отношении распознавания лицевых масок путем тщательного тестирования и анализа. Модели подвергаются статистической оценке на предмет их способности обнаруживать лицевые маски на изображениях или в видеопотоках с использованием показателей производительности, включая точность, запоминаемость и показатель F1. Кроме того, фактическая возможность использования этих моделей в реальных приложениях оценивается путем анализа показателей вычислительной эффективности, таких как время вывода и размер модели. Более того, устойчивость моделей оценивается в ряде сложных сценариев, таких как изменение освещения, выражения лица и прикуса. В диссертации обсуждаются последствия этих результатов, а также предложения по улучшению каждой архитектуры для задач обнаружения лицевых масок. Методология этого исследования направлена на разработку и оценку моделей глубокого обучения для распознавания лицевых масок, которые особенно подходят для использования в мобильных медицинских учреждениях. Этот метод призван гарантировать высокую точность, надежность и эффективность в реальных условиях здравоохранения, где важно быстрое и точное распознавание лицевых масок. Для выбора и разработки моделей были выбраны четыре хорошо известные архитектуры глубокого обучения VGG19, VGG16, Gated Recurrent Unit (GRU) и полностью сверточные нейронные сети (FCNN). Эти модели были выбраны из-за их доказанной эффективности в решении целого ряда задач распознавания изображений и возможной гибкости в обнаружении лицевых масок. Ключевые слова: Распознавание лицевых масок, глубокое обучение, VGG19, VGG16, GRU, Полностью сверточные нейронные сети, Оценка эффективности, Мобильные медицинские учреждения.