This dissertation addresses the analysis of partially premixed flame configurations and the detection and characterization of their local flame regimes. First, the identification of flame regimes in experimental data is intensively discussed. Current methods for combustion regime characterization, such as the flame index, rely on 3D gradient information that is not accessible with available experimental techniques. Here, a method is proposed for reaction zone detection and characterization, which can be applied to instantaneous 1D Raman/Rayleigh line measurements of major species and temperature as well as to the results of laminar and turbulent flame simulations, without the need for 3D gradient information. Several derived flame markers, namely the mixture fraction, the heat release rate and the chemical explosive mode, are combined to detect and characterize premixed versus non-premixed reaction zones. The methodology is developed and evaluated using fully resolved simulation data from laminar flames. The fully resolved 1D simulation data are spatially filtered to account for the difference in spatial resolution between the experiment and the simulation, and experimental uncertainty is superimposed onto the filtered numerical results to produce Raman/Rayleigh equivalent data. Then, starting from just the temperature and major species, a constrained homogeneous batch reactor calculation gives an approximation of the full thermochemical state at each sample location. Finally, the chemical explosive mode and the heat release rate are calculated from this approximated state and compared to those calculated directly from the simulation data. After successful validation, the approach is applied to Raman/Rayleigh line measurements from laminar counterflow flames, a mildly turbulent lifted flame and turbulent benchmark cases. The results confirm that the reaction zones can be reliably detected and characterized using experimental data. In contrast to other approaches, the presented methodology circumvents uncertainties arising from the use of limited gradient information and offers an alternative to known reaction zone identification methods. Second, this work focuses on the flame structure of partially premixed dimethyl ether (DME) flames. DME flames form significant intermediate hydrocarbons in the reaction zone and are classified as the next more complex fuel candidate in research after methane. To simulate DME combustion processes, accurate predictions by computational combustion models are required. To evaluate such models and to identify appropriate flame regimes, numerical simulations are necessary. Therefore, fully resolved simulations of laminar dimethyl ether flames, defined by different levels of premixing, are performed. Further, the qualitative two-dimensional structures of the partially premixed DME flames are discussed and analyses are carried out at selected slices and compared to each other as well as to experimental data. Further, the flamelet/progress variable (FPV) approach is investigated to predict the partially premixed flame structures of the DME flames. In the context of the FPV approach, a rigorous analysis of the underlying manifold is carried out based on the newly developed regime identification approach and an a priori analysis. The most promising flamelet look-up table is chosen for the fully coupled tabulated chemistry simulations and the results are further compared to the fully resolved simulation data.

This dissertation addresses the analysis of partially premixed flame configurations and the detection and characterization of their local flame regimes. First, the identification of flame regimes in experimental data is intensively discussed. Current methods for combustion regime characterization, such as the flame index, rely on 3D gradient information that is not accessible with available experimental techniques. Here, a method is proposed for reaction zone detection and characterization, which can be applied to instantaneous 1D Raman/Rayleigh line measurements of major species and temperature as well as to the results of laminar and turbulent flame simulations, without the need for 3D gradient information. Several derived flame markers, namely the mixture fraction, the heat release rate and the chemical explosive mode, are combined to detect and characterize premixed versus non-premixed reaction zones. The methodology is developed and evaluated using fully resolved simulation data from laminar flames. The fully resolved 1D simulation data are spatially filtered to account for the difference in spatial resolution between the experiment and the simulation, and experimental uncertainty is superimposed onto the filtered numerical results to produce Raman/Rayleigh equivalent data. Then, starting from just the temperature and major species, a constrained homogeneous batch reactor calculation gives an approximation of the full thermochemical state at each sample location. Finally, the chemical explosive mode and the heat release rate are calculated from this approximated state and compared to those calculated directly from the simulation data. After successful validation, the approach is applied to Raman/Rayleigh line measurements from laminar counterflow flames, a mildly turbulent lifted flame and turbulent benchmark cases. The results confirm that the reaction zones can be reliably detected and characterized using experimental data. In contrast to other approaches, the presented methodology circumvents uncertainties arising from the use of limited gradient information and offers an alternative to known reaction zone identification methods. Second, this work focuses on the flame structure of partially premixed dimethyl ether (DME) flames. DME flames form significant intermediate hydrocarbons in the reaction zone and are classified as the next more complex fuel candidate in research after methane. To simulate DME combustion processes, accurate predictions by computational combustion models are required. To evaluate such models and to identify appropriate flame regimes, numerical simulations are necessary. Therefore, fully resolved simulations of laminar dimethyl ether flames, defined by different levels of premixing, are performed. Further, the qualitative two-dimensional structures of the partially premixed DME flames are discussed and analyses are carried out at selected slices and compared to each other as well as to experimental data. Further, the flamelet/progress variable (FPV) approach is investigated to predict the partially premixed flame structures of the DME flames. In the context of the FPV approach, a rigorous analysis of the underlying manifold is carried out based on the newly developed regime identification approach and an a priori analysis. The most promising flamelet look-up table is chosen for the fully coupled tabulated chemistry simulations and the results are further compared to the fully resolved simulation data.

This essay means to examine and present the reasons of Firman boys use of collective violence, if they have influence regarding the outcome of AIK-football’s supporter gatherings, and their long-term club objectives. Through semi-structured interviews made with avid fans and firm-members alike, we dissected the answers through our framework consisting of a presentation of the well-developed Swedish association life and its activities, collective violence and the effects on group dynamics, and lastly, how Firman boys organize themselves through what we define as partial organization. The analysis of our interviews proved that violence is a vital part of a firm’s existence but employed only as a means in itself to shape and strengthen its members, therefore the means lack political motivation or end goal. From our interviews we cannot present a complete picture of the firms long term goals. But the club’s existence should, according to the firm rather strive for long term fulfillment and the accomplishments it brings. Not comfort their members with temporary distractions or other short-lived sensations.

IFRS 15 trädde i kraft 1 januari 2018, och innebar en stor förändring för intäktsredovisningen. Det saknas studier genomförda i en svensk kontext som undersöker om IFRS 15 haft någon påverkan på redovisningskvaliteten. Studien visar att redovisningskvaliteten, som mäts genom graden av resultatmanipulering, har ökat sedan införandet av IFRS 15 med avseende på de intäktsrelaterade periodiseringarna. Sett till de totala periodiseringarna har ingen förbättring skett, vilket innebär att det fortfarande förekommer resultatmanipulering hos företagen noterade på Stockholmsbörsen. / IFRS 15 took effect January 1st 2018, and resulted in a major change in revenue recognition. There are no studies conducted in a Swedish setting that examine whether IFRS 15 has had any impact on the accounting quality. The study shows that the accounting quality, which is measured by the extent of earnings management, has increased since the introduction of IFRS 15 with respect to the revenue related accruals. In terms of the total accruals, no improvement has been made, which implies that there is still earnings management conducted by the companies listed at the Stockholm Stock Exchange.

The usage of programmable logic resources in Field Programmable Gate Arrays, also known as FPGAs, has increased a lot recently due to the complexity of the algorithms, especially for some computer vision algorithms. Due to this reason, sometimes the hardware resources in the FPGA are not sufficient. Partial reconfiguration provides us with the possibility to solve this problem. Partial reconfiguration is a technique that can be used to reconfigure specific parts of the FPGA during run-time. By using this technique, we can reduce the need for programmable logic resources. This master thesis project aims to design a software framework for partial reconfiguration that can load a set of processing components/algorithms (e.g. object detection, optical flow, Harris-Corner detection etc) in the FPGA area without affecting real-time static components such as camera capture, basic image filtering and colour conversion which are continuously running. Partial reconfiguration has been applied to two different video processing pipelines, a direct streaming architecture and a frame buffer streaming architecture respectively. The result shows that reconfiguration time is predictable which depends on the partial bitstream size, and that partial reconfiguration can be used in real-time applications taking the partial bitstream size and the frequency to switch the partial bitstreams into account. / Användningen av programmerbara logiska resurser i Field Programmable Gate Arrayer, även känd som FPGA:er, har ökat mycket nyligen på grund av komplexiteten hos algoritmerna, speciellt för vissa datorvisningsalgoritmer. På grund av detta är det ibland inte tillräckligt med hårdvaruresurser i FPGA:n. Partiell omkonfiguration ger oss möjlighet att lösa detta problem. Partiell omkonfigurering är en teknik som kan användas för att omkonfigurera specifika delar av FPGA:n under körtid. Genom att använda denna teknik kan vi minska behovet av programmerbara logiska resurser. Det här mastersprojektet syftar till att utforma ett programvaru-ramverk för partiell omkonfiguration som kan ladda en uppsättning processkomponenter / algoritmer (t.ex. objektdetektering, optiskt flöde, Harris-Corner detection etc) i FPGA- området utan att påverka statiska realtids-komponenter såsom kamerafångst, grundläggande bildfiltrering och färgkonvertering som körs kontinuerligt. Partiell omkonfiguration har tillämpats på två olika videoprocessnings-pipelines, en direkt-strömmande respektive en rambuffert-strömmande arkitektur. Resultatet visar att omkonfigurationstiden är förutsägbar och att partiell omkonfiguration kan användas i realtids-tillämpningar.

<p> </p><p>The today quarry planning at Klinthagen is rough, which provides an opportunity to introduce new exciting methods to improve the quarry gain and efficiency. Nordkalk AB, active at Klinthagen, wishes to start a new quarry at a nearby location. To exploit future quarries in an efficient manner and ensure production quality, multivariate statistics may help gather important information.</p><p>In this thesis the possibilities of the multivariate statistical approaches of Principal Component Analysis (PCA) and Partial Least Squares (PLS) regression were evaluated on the Klinthagen bore data. PCA data were spatially interpolated by Kriging, which also was evaluated and compared to IDW interpolation.</p><p>Principal component analysis supplied an overview of the variables relations, but also visualised the problems involved when linking geophysical data to geochemical data and the inaccuracy introduced by lacking data quality.</p><p>The PLS regression further emphasised the geochemical-geophysical problems, but also showed good precision when applied to strictly geochemical data.</p><p>Spatial interpolation by Kriging did not result in significantly better approximations than the less complex control interpolation by IDW.</p><p>In order to improve the information content of the data when modelled by PCA, a more discrete sampling method would be advisable. The data quality may cause trouble, though with sample technique of today it was considered to be of less consequence.</p><p>Faced with a single geophysical component to be predicted from chemical variables further geophysical data need to complement existing data to achieve satisfying PLS models.</p><p>The stratified rock composure caused trouble when spatially interpolated. Further investigations should be performed to develop more suitable interpolation techniques.</p>

The today quarry planning at Klinthagen is rough, which provides an opportunity to introduce new exciting methods to improve the quarry gain and efficiency. Nordkalk AB, active at Klinthagen, wishes to start a new quarry at a nearby location. To exploit future quarries in an efficient manner and ensure production quality, multivariate statistics may help gather important information. In this thesis the possibilities of the multivariate statistical approaches of Principal Component Analysis (PCA) and Partial Least Squares (PLS) regression were evaluated on the Klinthagen bore data. PCA data were spatially interpolated by Kriging, which also was evaluated and compared to IDW interpolation. Principal component analysis supplied an overview of the variables relations, but also visualised the problems involved when linking geophysical data to geochemical data and the inaccuracy introduced by lacking data quality. The PLS regression further emphasised the geochemical-geophysical problems, but also showed good precision when applied to strictly geochemical data. Spatial interpolation by Kriging did not result in significantly better approximations than the less complex control interpolation by IDW. In order to improve the information content of the data when modelled by PCA, a more discrete sampling method would be advisable. The data quality may cause trouble, though with sample technique of today it was considered to be of less consequence. Faced with a single geophysical component to be predicted from chemical variables further geophysical data need to complement existing data to achieve satisfying PLS models. The stratified rock composure caused trouble when spatially interpolated. Further investigations should be performed to develop more suitable interpolation techniques.

Automatic Root Cause Analysis (RCA) systems aim to streamline the process of identifying the underlying cause of software failures in complex cloud-native environments. These systems employ graph-like structures to represent causal relationships between different components of a software application. These relationships are typically learned through performance and resource utilization metrics of the microservices in the system. To accomplish this objective, numerous RCA systems utilize statistical algorithms, specifically those falling under the category of causal discovery. These algorithms have demonstrated their utility not only in RCA systems but also in a wide range of other domains and applications. Nonetheless, there exists a research gap in the exploration of the feasibility and efficacy of multivariate time series causal discovery algorithms for deriving causal graphs within a microservice framework. By harnessing metric time series data from Prometheus and applying these algorithms, we aim to shed light on their performance in a cloudnative environment. Furthermore, we have introduced an adaptation in the form of an ensemble causal discovery algorithm. Our experimentation with this ensemble approach, conducted on datasets with known causal relationships, unequivocally demonstrates its potential in enhancing the precision of detected causal connections. Notably, our ultimate objective was to ascertain reliable causal relationships within Ericsson’s cloud-native system ’X,’ where the ground truth is unavailable. The ensemble causal discovery approach triumphs over the limitations of employing individual causal discovery algorithms, significantly augmenting confidence in the unveiled causal relationships. As a practical illustration of the utility of the ensemble causal discovery techniques, we have delved into the domain of anomaly detection. By leveraging causal graphs within our study, we have successfully applied this technique to anomaly detection within the Ericsson system. / System för automatisk rotorsaksanalys (RCA) syftar till att effektivisera process för att identifiera den underliggande orsaken till programvarufel i komplexa molnbaserade miljöer. Dessa system använder grafliknande strukturer att representera orsakssamband mellan olika komponenter i en mjukvaruapplikation. Dessa relationer lär man sig vanligtvis genom prestanda och resursutnyttjande mätvärden för mikrotjänsterna i systemet. För att uppnå detta mål använder många RCAsystem statistiska algoritmer, särskilt de som faller under kategorin orsaksupptäckt. Dessa algoritmer har visat att de inte är användbara endast i RCA-system men även inom en lång rad andra domäner och applikationer. Icke desto mindre finns det en forskningslucka i utforskningen av genomförbarhet och effektivitet av orsaksupptäckt av multivariat tidsserie algoritmer för att härleda kausala grafer inom ett mikrotjänstramverk. Genom att utnyttja metriska tidsseriedata från Prometheus och tillämpa Dessa algoritmer strävar vi efter att belysa deras prestanda i ett moln- inhemsk miljö. Dessutom har vi infört en anpassning i formen av en ensemble kausal upptäcktsalgoritm. Vårt experiment med denna ensemblemetod, utförd på datauppsättningar med kända orsakssamband relationer, visar otvetydigt sin potential för att förbättra precisionen hos upptäckta orsakssamband. Särskilt vår ultimata Målet var att fastställa tillförlitliga orsakssamband inom Ericssons molnbaserade systemet ’X’, där grundsanningen inte är tillgänglig. De ensemble kausal discovery approach segrar över begränsningarna av att använda individuella kausala upptäcktsalgoritmer, avsevärt öka förtroendet för de avslöjade orsakssambanden. Som en praktisk illustration av nyttan av ensemblens kausal upptäcktstekniker har vi fördjupat oss i anomalidomänen upptäckt. Genom att utnyttja kausala grafer inom vår studie har vi framgångsrikt tillämpat denna teknik för att detektera anomali inom Ericsson system

FPGA based systems have been heavily used to prototype and test Application Specic Integrated Circuit (ASIC) designs with much lower costs and development time compared to hardwired prototypes. In recentyears, thanks to both the latest technology nodes and a change in the architecture of reconfigurable integrated circuits (from traditional Complex Programmable Logic Device (CPLD) to full-CMOS FPGA), FPGAs have become more popular in embedded systems, both as main computation resources and as hardware accelerators. A new era is beginning for FPGA based systems: the partial run-time reconguration of a FPGA is a feature now available in products already on the market and hardware designers and software developers have to exploit this capability. Previous works show that, when designed properly, a system can improve both its power efficiency and its performance taking advantage of a partial run-time reconfigurable architecture. Unfortunately, taking advantage of run-time reconfigurable hardware is very challenging and there are several problems to face: the reconfiguration overhead is not negligible compared to nowadays CPUs performance,the reconfiguration time is not easily predictable, and the software has to be re-though to work with a time-evolving platform. This thesis project aims to investigate the performance of a modern run-time reconfigurable SoC (a Xilinx Zynq 7020), focusing on the reconfiguration overhead and its predictability, on the achievable speedup, and the trade-off and limits of this kind of platform. Since it is not always obvious when an application (especially a real-time one) is really able to use at its own advantage a partial run-time reconfigurable platform, the data collected during this project could be a valid help for hardware designers that use reconfigurable computing. / FPGA-baserade system har tidigare främst använts för snabb och kostnadseffektiv konstruktion av prototyper vid framtagandet av applikationsspecika integrerade kretsar (ASIC). På senare år har användandet av FPGA:er i inbyggda system för implementation av hårdvaruacceleratorers såväl som huvudsaklig beräkningsenhet ökat. Denna ökning har möjliggjorts mycket tack vare den utveckling som har skett av rekonfigurerbara integrerade kretsar: från de mer traditionella Complex Programmable Logic Devices (CPLD) till helt CMOS-baserade FPGA:er. Nu inleds en ny era för FPGA-baserade system tack vare möjligheten att under körning rekonfigurera delar av FPGA:n genom så kallad partial run-time reconguration(RTR) - en teknik som redan idag finns tillgänglig i produkter på marknaden. Tidigare forskning visar att användandet av en RTR-baserad hårdvaruarkitektur kan ha en positiv effekt med avseende på prestanda såväl som strömförbrukning. Att använda RTR-baserad hårdvara innebär dock flera utmaningar: En ej försumbar rekonfigurationstid måste tas i beaktning, så även den icke-deterministiska exekveringstiden som en rekonfiguration kan innebära. Vidare måste anpassningar av mjukvaran göras för att fungera med en hårdvaruplattform som förändras över tid. Denna uppsats syftar till att undersöka prestandan hos ett modernt RTRbaserat SoC (Xilinx Zynq 7020) med fokus på rekonfigurationstider och dess förutsägbarhet, prestanda ökning, begränsningar samt nödvändiga kompromisser som denna arkitektur innebär. Huruvida en applikation kan dra nytta av en RTR-baserad arkitektur eller inte kan vara svårt att avgöra. Den insamlade datan som presenteras i denna rapport kan dock fungera som stöd för hårdvarukonstruktörer som önskar använda en RTR-baserad plattform.

There are different transportations in the city logistics (e.g., passengers, freights, and wastes), which are handled respectively by single-purpose vehicles (SVs) of the corresponding type. The multi-purpose vehicle (MV) is a future concept whose load modules can be changed for different urban transportations. MVs enable the sequential sharing of different mobilities, thus theoretically improving the efficacy of the city logistics by higher utilization of vehicles. A variant model of the Pick-up and Delivery Problem with Time Windows is established to describe the sequential sharing problem considering both MVs and SVs with the features of multiple depots, partial recharging strategies, and fleet sizing. In the problem, MVs can change their load modules for all types of objects carried by SVs. An adaptive large neighborhood algorithm (ALNS) is developed with new mechanisms for MVs. The proposed ALNS is tested by 15 artificial data cases and compared with the MIP solver. The results show the proposed ALNS is time-effective and validated to find good solutions. / Det finns olika transporter i stadslogistiken (t.ex. passagerare, gods och avfall), som hanteras av enskilda fordon (SV) av motsvarande typ. Multifunktionsfordonet (MV) är ett framtida koncept vars lastmoduler kan ändras för olika stadstransporter. MV möjliggör sekventiell delning av olika mobiliteter, vilket på ett teoretiskt sätt förbättrar stadslogistikens effektivitet genom högre användning av fordon. En variantmodell av Pick-up and Delivery Problem with Time Windows är etablerad för att beskriva det sekventiella delningsproblemet med beaktande av både MV och SV med funktionerna i flera depåer, partiella laddningsstrategier och flottans storlek. I problemet kan MV: er ändra sina belastningsmoduler för alla typer av objekt som bärs av SV: er. En adaptiv stor stadsdelalgoritm (ALNS) har utvecklats med nya mekanismer för MV. Den föreslagna ALNS testas av 15 artificiella datafall och jämförs med MIP-lösaren. Resultaten visar att det föreslagna ALNS är tidseffektivt och validerat för att hitta bra lösningar.