This thesis is focused on the analysis of fetal ECG records measured by indirect method from mother´s abdomen. The thesis consists of the theoretical part is focused on fetal, heart development and description of fetal ECG signal. This thesis also offers an overview of fECG signal processing methods used nowadays. The practical part of the thesis deals with the implementation of algorithms based on wavelet transformation and Least Mean Square LMS method in Matlab programming environment. The final part of the thesis consists of the analysis of achieved results.

Tato práce je psaná v angličtině a je zaměřená na problematiku ekvalizace v digitálních komunikačních systémech. Teoretická část zahrnuje stručné pozorování různých způsobů návrhu ekvalizérů. Praktická část se zabývá implementací nejčastěji používaných ekvalizérů a s jejich adaptačními algoritmy. Cílem praktické části je porovnat jejich charakteristiky a odhalit činitele, které ovlivňují kvalitu ekvalizace. V rámci problematiky ekvalizace jsou prozkoumány tři typy ekvalizérů. Lineární ekvalizér, ekvalizér se zpětnou vazbou a ML (Maximum likelihood) ekvalizér. Každý ekvalizér byl testován na modelu, který simuloval reálnou přenosovou soustavu s komplexním zkreslením, která je složena z útlumu, mezisymbolové interference a aditivního šumu. Na základě implenentace byli určeny charakteristiky ekvalizérů a stanoveno že optimální výkon má ML ekvalizér. Adaptační algoritmy hrají významnou roli ve výkonnosti všech zmíněných ekvalizérů. V práci je nastudována skupina stochastických algoritmů jako algoritmus nejmenších čtverců(LMS), Normalizovaný LMS, Variable step-size LMS a algoritmus RLS jako zástupce deterministického přístupu. Bylo zjištěno, že RLS konverguje mnohem rychleji, než algoritmy založené na LMS. Byly nastudovány činitele, které ovlivnili výkon popisovaných algoritmů. Jedním z důležitých činitelů, který ovlivňuje rychlost konvergence a stabilitu algoritmů LMS je parametr velikosti kroku. Dalším velmi důležitým faktorem je výběr trénovací sekvence. Bylo zjištěno, že velkou nevýhodou algoritmů založených na LMS v porovnání s RLS algoritmy je, že kvalita ekvalizace je velmi závislá na spektrální výkonové hustotě a a trénovací sekvenci.

This thesis examines the possibility to implement e­learning in the educational process at HOPE – E. S. , v.o.s. The thesis compared the competitive opportunities of LMS systems, and selected one particular solution. The chosen solution is further specified, including the possible implementation and description of the environment. The last part is a proposed structure of the courses and supplementary materials for ongoing full-time courses.

The thesis deals with a design of adaptive testing in educational systems, the aim of the designed adaptive test is to simulate an oral examination by a teacher. Tes-ted knowledge are represented in two new structures - study map and proposition map that also drive the test. The goal of the test is to create a connected graph depicting knowledge of the examinee that represents its non-scalar result. Methodology for creation the maps, design of a complex software solution and proposal for incorporation of the adaptive testing to existing LMS were created. The economic benefits of the solution are discussed in case of its utilisation at FBE MENDELU. The adaptive testing can be used on different levels of education, e.g. corporate education as is shown on a practical application. The main contribution of the thesis is complexity of the solution - the thesis deals all aspects of adaptive testing starting with creation of educational materials up final feedback after the test.

Avsikten med detta examensarbete har varit att undersöka om lärare på gymnasienivå ägnar enligt dem själva mycket tid åt att administrera anteckningar om elevbedömningar och om de anser detta vara tidsödande. En enkätundersökning har gjorts på detta område. Slutsatsen är att lärare ofta behandlar samma elevbedömning mer än en gång. Detta kan visa sig genom att en anteckning om en elevbedömning först skrivs ned i en lärarkalender för att sedan föras in på datorn och för att slutligen tas fram för en sammanställning vid till exempel ett utvecklingssamtal. Ett fåtal pedagoger i undersökningen använder sig av ett datoriserat system för att föra in bedömningar direkt, ett system där elever kan logga in och se sina bedömningar vilket gör att antalet behandlingar av bedömningar för läraren minskar.Vidare tar uppsatsen upp hur ett datoriserat system för att spara och administrera elevbedömningar enligt teori bör se ut. Här gås begrepp igenom för att allmänt skapa ett bra grafiskt gränssnitt och olika tekniker för att visa mycket information på liten yta behandlas. En sådan programvara har också utvecklats och redovisas. / The purpose of this essay has been to investigate if teachers spend much time to administrate assessment from students and if they consider this a time-consuming task. The conclusion is that teachers often handle these results more than one time. Sometimes teachers first manually write down the students result in paper and after that write it to the computer and then finally handle the result a third time when putting together a compilation of the results when for example it’s time for students to have performance appraisal with their mentor. Some teacher saves the result directly into a computer system where the student immediately can see the result and therefore the teacher saves time since the results only have been handled a single time. Further on this paper deals with how a system that administrates student results should look like according to theory and behave and finally software for this purpose has been developed.

No description available.

Passive radar is a technology for detection of targets using echoes of existing radio transmitter, such as FM-radio. Since only receivers are needed for operation, a passive radar system has the possibility of being implemented using low-cost hardware. Using lower cost implementations to cover blind-spots of other, more sophisticated systems, could be a viable solution for full radar coverage. To achieve this, an understanding of the effects such low-cost systems have on the performance of a radar is needed.  A prominent problem for passive radar is that the interference caused by the direct signal from the transmitter used and reflections from uninteresting terrain, called clutter, can drown out the echoes from targets. This thesis compares the direct signal interference (DSI) suppression algorithms: ECA, ECA-S, ECA-B, NLMS and FBNLMS when run on data from a low-cost receiver called KerberosSDR. It is found that the low ADC resolution of 8 bits is a limiting factor for KerberosSDR. Random noise in the receiver can also limit the performance. None of the tested algorithms are any more or less affected by the ADC resolution or the noise. The first difference appears when comparing the execution times, where FBNLMS is 10–20 times faster than the other algorithms. However, the slower rate of convergence for FBNLMS and NLMS causes them to lose performance in environments where the DSI and clutter are considerably stronger than the target echoes. The algorithms FBNLMS and NLMS also lose performance due to their inability to model frequency shifted echoes as unwanted. The main disadvantages of ECA, ECA-B and ECA-S are their long execution time. It is concluded that FBNLMS would be the best candidate in most cases for low-cost hardware, as it allows execution on slower hardware and the main disadvantages not being too prominent in the use case of covering blind-spots of other systems.

Adaptive LMS equalizers are widely used in digital communication systems for their simplicity in implementation. Conventional adaptive filtering theory suggests the upper bound of the performance of such equalizer is determined by the performance of a Wiener filter of the same structure. However, in the presence of a narrowband interferer the performance of the LMS equalizer is better than that of its Wiener counterpart. This phenomenon, termed a non-Wiener effect, has been observed before and substantial work has been done in explaining the underlying reasons. In this work, we focus on the Bit Error Rate (BER) performance of LMS equalizers. At first a model “the Gaussian Mixture (GM) model“ is presented to estimate the BER performance of a Wiener filter operating in an environment dominated by a narrowband interferer. Simulation results show that the model predicts BER accurately for a wide range of SNR, ISR, and equalizer length. Next, a model similar to GM termed the Gaussian Mixture using Steady State Weights (GMSSW) model is proposed to model the BER behavior of the adaptive NLMS equalizer. Simulation results show unsatisfactory performance of the model. A detailed discussion is presented that points out the limitations of the GMSSW model, thereby providing some insight into the non-Wiener behavior of (N)LMS equalizers. An improved model, the Gaussian with Mean Square Error (GMSE), is then proposed. Simulation results show that the GMSE model is able to model the non-Wiener characteristics of the NLMS equalizer when the normalized step size is between 0 and 0.4. A brief discussion is provided on why the model is inaccurate for larger step sizes. / Master of Science

Active suspension technologies are well known for improving ride comfort and handling of ground vehicles relative to passive suspensions. They are ideally suited for mitigating single-event road obstacles. The work presented in this thesis aims to develop a structured approach for finding the peak force and bandwidth requirements of actuators for active suspensions, to mitigate single-event road obstacles. The approach is kept general to allow for application to different vehicle models, ride conditions and performance objectives. The current state-of-art in active suspensions was first evaluated. Based on these findings, the objectives of the simulation models and approach was defined. A quarter-car model was developed in Matlab to simulate the behavior of active suspensions over unilateral boundary conditions due to different road obstacle profiles. The obstacle profiles were obtained from existing standards and literature and then processed to replicate the interaction of tires on road. A least-mean-squares (LMS) algorithm for adaptive filtering, with the help of look-ahead preview was used to determine the ideal control force profile to achieve the performance objective of the active suspension. A case study was conducted to determine the requirements of the actuator in terms of bandwidth and peak force for different single-event road obstacle profiles, vehicle speeds and look-ahead preview distances. The results of the study show that the vehicle velocity and type of road obstacle have a strong influence on the required peak force and bandwidth of the actuator, while look-ahead preview will be much more important for real time controller implementation. / Master of Science

As more students interact with online learning platforms and eTextbooks, they generate massive amounts of data. For example, the OpenDSA eTextbook system collects clickstream data as users interact with prose, visualizations, and interactive auto-graded exercises. Ideally, instructors and system developers can harness this information to create better instructional experiences. But in its raw event-level form, it is difficult for developers or instructors to understand student behaviors, or to make testable hypotheses about relationships between behavior and performance. In this study, we describe our efforts to break raw event-level data first into sessions (a continuous series of work by a student) and then to meaningfully abstract the events into higher-level descriptions of that session. The goal of this abstraction is to help instructors and researchers gain insights into the students' learning behaviors. For example, we can distinguish when students read material and then attempt the associated exercise, versus going straight to the exercise and then hunting for the answers in the associated material. We first bundle events into related activities, such as the events associated with stepping through a given visualization, or with working a given exercise. Each such group of events defines a state. A state is a basic unit that characterizes the interaction log data, and there are multiple state types including reading prose, interacting with visual contents, and solving exercises. We harnessed the abstracted data to analyze studying behavior and compared it with course performance based on GPA. We analyzed data from the Fall 2020 and Spring 2021 sections of a senior-level Formal Languages course, and also from the Fall 2020 and Spring 2021 sections of a data structures course. / Master of Science / OpenDSA is an online learning platform used in multiple academic institutions including Virginia Tech's Computer Science courses. They use OpenDSA as the main instructional method and students in these courses generate massive amounts of clickstream data while interacting with the OpenDSA content. The system collects various events logs such as when students opened/closed a certain page, how long they stayed on the page, and how many times they clicked an interface element for visualizations and exercises. However, in its raw event-level form, it is difficult for instructors or developers to understand student behaviors, or to make testable hypotheses about relationships between behavior and performance. We describe our efforts to break raw event-level clickstreams into a session (continuous series of work by a student) and then to abstract the events into meaningful higher-level descriptions of students' behavior. We grouped raw events into related activities, such as the events associated with stepping through a given visualization, or working with a given exercise. We defined such a group of activities as a state, which is a basic unit that can characterize the interaction log data such as reading, slideshows, and exercises state. We harnessed the abstracted data to analyze students' studying behavior and compared it with their course performance based on their GPA. We analyzed data from two offerings of two CS courses at Virginia Tech to gain insights into students' learning behaviors.