This diploma thesis deals with the design and implementation of an electronic module for acoustic detection. The module has the task of detecting a predetermined acoustic signals through them learned classification model. The module is used mainly for security purposes. To identify and classify the proposed model using machine learning techniques. Given the possibility of retraining for a different set of sounds, the module becomes a universal sound detector. With acoustic sound using the digital MEMS microphone, for which it is designed and implemented conversion filter. The resulting system is implemented into firmware microcontroller with real time operating system. The various functions of the system are realized with regard to the possible optimization (less powerful MCU or battery power). The module transmits the detection results of the master station via Ethernet network. In the case of multiple modules connected to the network to create a distributed system, which is designed for precise time synchronization using PTP protocol defined by the IEEE-1588 standard.

Time synchronization is a process of ensuring all the time difference between the clocks of network components(like base stations, boundary clocks, grandmasters, etc.) in the mobile network is zero or negligible. It is one of the important factors responsible for ensuring effective communication between two user-equipments in a mobile network. Nevertheless, the presence of asymmetries can lead to faults, making the detection of these errors indispensable, especially in technologies demanding ultra-low latency, such as 5G technology. Developing methods to ensure time-synchronized mobile networks, would not only improve the network performance, and contribute towards cost-effective telecommunication infrastructure. A rulebased simulator to simulate the mobile network was built, using the rules provided by the domain experts, in order to generate more data for further studies. The possibility of using Reinforcement Learning to perform fault detection in the mobile network was explored. In addition to the simulator dataset, an unlabelled customer dataset, which consists of time error differences between the base stations, and additional features for each of its network components was provided. Classification algorithms to label the customer dataset were designed, and a comparative analysis of each of them has been presented. Mathematical algorithm and Graph Neural Network models were built to detect error, for both the simulator and customer dataset, for the faulty node detection task. The approach of using a Mathematical algorithm and Graph Neural Network architectures provided an accuracy of 95% for potential fault node detection. The feature importance of the additional features of the network components was analyzed using the best Graph Neural Network model which was used to train for the node classification task (to classify the base stations as faulty and non-faulty). Additionally, an attempt was made to predict the individual time error value for each of the links using Graph Neural Network, however, it failed potentially due to the presence of fewer features to train from. / Tidssynkronisering är en process för att säkerställa att all tidsskillnad mellan klockorna för nätverkskomponenter (som basstationer, gränsklockor, stormästare, etc.) i mobilnätet är noll eller försumbar. Det är en av de viktiga faktorerna som är ansvariga för att säkerställa effektiv kommunikation mellan två användarutrustningar i ett mobilnät. Icke desto mindre kan närvaron av asymmetrier leda till fel, vilket gör upptäckten av dessa fel oumbärlig, särskilt i tekniker som kräver ultralåg latens, som 5G-teknik. En regelbaserad simulator för att simulera mobilnätet byggdes, med hjälp av reglerna från domänexperterna, för att generera mer data för vidare studier. Möjligheten att använda RL för att utföra feldetektering i mobilnätet undersöktes. Utöver simulatordataset tillhandahölls en omärkt kunddatauppsättning, som består av tidsfelsskillnader mellan basstationerna och ytterligare funktioner för var och en av dess nätverkskomponenter. Klassificeringsalgoritmer för att märka kunddataset utformades, och en jämförande analys av var och en av dem har presenterats. Matematisk algoritm och GNN-modeller byggdes för att upptäcka fel, för både simulatorn och kunddatauppsättningen, för uppgiften att detektera felaktig nod. Metoden att använda en matematisk algoritm och GNN-arkitekturer gav en noggrannhet på 95% för potentiell felnoddetektering. Funktionens betydelse för de ytterligare funktionerna hos nätverkskomponenterna analyserades med den bästa GNN-modellen som användes för att träna för nodklassificeringsuppgiften (för att klassificera basstationerna som felaktiga och icke-felaktiga). Dessutom gjordes ett försök att förutsäga det individuella tidsfelsvärdet för var och en av länkarna med GNN, men det misslyckades potentiellt på grund av närvaron av färre funktioner att träna från.

Magister Educationis - MEd / In this dissertation I set out to reflect on and examine a case study of a Namibian nongovernmental educational organisation (NGEO),the Primary Teachers Project (PTP),from 1989to 1992 focusing on issuesof educational change and the role of NGEO'sin this process. My aim is to highlight some of the factors which helped and hindered the Primary Teachers Project playing a role in educational change. The study focuses on the following four aspects: The Primary Teachers Project'sin-service education and training (INSET)model. The relationship between the Namibian Ministry of Education and the PTP. Funding relationships and their influence on the project's development. Internal dynamics within the Primary Teachers Project The dissertation begins by locating the Primary Teachers Project within the broader geographical, political and educational context of Namibia. The PTP's development between 1989 and 1992is then described. The four focus areas above are highlighted within the case study. Topical reflections on each of these areas are integrated with relevant national and international literature on INSET, educational change and the role of NGEO's. Central learnings with regard to the PTP and its role in educational change in Namibia are raised. Some of the key factors which worked for and against this NGEO's influence on educational change are highlighted. Finally, I make a number of general recommendations with regard to the role of NGEO's in the Southern African context. This study raises key factors relating to the influence of NGEO's on educational change. These are: NGEO's need to develop their understanding of the complexity of educational change processes, in order to inform INSET strategies. School-focused INSET models need to strengthen strategies for follow-up support to assist teachers to implement new ideas and practices. A combination of curriculum-based INSET and organisation development support needs to be provided at the school level to assist educational change. Organisation development processes within NGEO's can strengthen their internal capacity and critically inform their INSET strategies. NGEO's need to research and reflect on their practice and disseminate their findings, in order to improve their own practice and influence educational change at other levels of the educational system, Collaboration between different INSET providers builds the capacity for sustainability of educational change processes at school level and supports NGEO's in disseminating their knowledge and expertise throughout the formal educational system. An enabling INSET policy framework is required at national and local level to support INSET work in schools and assist the work of NGEO's and donors.

The master's thesis provides a comprehensive overview of resampling methods for testing the correctness topology of the phylogenetic trees which estimate the process of phylogeny on the bases of biological sequences similarity. We focused on the possibility of errors creation in this estimate and the possibility of their removal and detection. These methods were implemented in Matlab for Bootstrapping, jackknifing, OTU jackknifing and PTP test (Permutation tail probability). The work aims to test their applicability to various biological sequences and also to assess the impact of the choice of input analysis parameters on the results of these statistical tests.

Indiana University-Purdue University Indianapolis (IUPUI) / Ninety-eight empirical effects examining the impact of pretrial publicity (PTP) on perceptions of guilt were meta-analytically analyzed. As hypothesized, results suggested that anti-defendant PTP was associated with increased perceptions of defendant guilt, whereas pro-defendant PTP was associated with decreased perceptions of defendant guilt. Additionally, several moderator variables were examined. The results suggested that the size of the effect of PTP is dependent upon several variables, including the level of the analysis (jury-level vs. juror level), the type of crime involved in the case, the nature of the information provided to the participants in the control condition, the reality of the case used in the study, the delay between PTP exposure and the collection of the verdict preference, the medium of the PTP presentation, the publication status of the data source, and the outcome measure utilized.

When recently graduated psychologists leave the profession, it can have a negative impact on the quality and continuity of care as well as resulting in socioeconomic costs. This study set out to investigate what personal and contextual factors affect newly graduated psychologists' intention to leave the profession (ITLP) over time. Longitudinal data was collected using a survey over three waves: 2017, 2018 and 2019. The participants were newly graduated psychologists in Sweden (n=346) who had answered two consecutive surveys. Logistic regressions were made, with the dependent variable ITLP. The independent variables were: sector (public or private), occupational self-efficacy, work related psychological flexibility, role stress. emotional demands, job satisfaction, social support (from colleagues, supervisor and family), transition between studies and internship, transition between internship and employment and sickness absence. Results showed that job satisfaction, social support from supervisors and the transition between internship and employment had a significant effect on the newly graduated psychologists’ ITLP over time. Due to data limitations some hypothesized relationships might not have been detected. Further research is needed to clarify what affects psychologists’ ITLP over time. / Att psykologer väljer att lämna yrket kan påverka vårdkvalitet och kontinuitet, dessutom innebär det samhällsekonomiska kostnader. Denna studie undersöker vilka faktorer det är som påverkar huruvida psykologer har en intention att lämna yrket (ITLP) eller inte. Longitudinell data samlades in i tre omgångar: 2017, 2018 och 2019. Deltagare var nyligen examinerade psykologer i Sverige (n=346) som hade svarat på två efterföljande enkäter. Logistiska regressioner genomfördes med den beroende variabeln ITLP. De oberoende variabler var: sektor (offentlig eller privat), arbetsrelaterad self-efficacy, arbetsrelaterad psykologisk flexibilitet, rollstress, emotionella krav, arbetstillfredsställelse, socialt stöd (från kollegor, överordnad och familj), övergång mellan studier och praktisk tjänstgöring, övergång mellan praktisk tjänstgöring och arbete samt sjukfrånvaro. Resultatet visade att arbetstillfredsställelse, socialt stöd från överordnad och transitionen mellan praktisk tjänstgöring och arbete hade en signifikant effekt på ITLP över tid. Begränsningar i data kan ha gjort så att vissa av de samband som hypotiserats inte kunde identifieras. Mer framtida forskning behövs för att klargöra vilka faktorer som påverkar psykologers ITLP över tid.