Stage IV cancer is characterized by a cancer’s ability to metastasize, or spread throughout the body. Metastatic disease in bone is a devastating condition affecting hundreds of thousands of people each year. Stage IV cancer patients suffering from metastatic disease in the proximal femur are at high risk of catastrophic pathologic fracture, an event which severely impacts patient health. Although metrics have been created to assess the risk of impending fracture, they lack specificity in the proximal femoral region. Shortcomings of these metrics further complicate clinical decision making related to prophylactic fixation in these medically compromised individuals. Fortunately, by using computational modeling to study this at-risk patient population, the likelihood of fracture due to metastatic lesions in the proximal femur can be more accurately assessed to improve clinical decision making. Finite element analysis (FEA) is a computational modeling technique that can non-invasively provide mechanics information to better assess true fracture risk of a given metastatic lesion. Although FEA has previously been utilized to study metastatic disease, lesions were always modeled as spheres or ellipsoids, while true lesion shapes are far more amorphous. It was the focus of this study to validate FEA’s ability to predict fracture location in cadaveric femora with realistically shaped experimental metastatic lesions. Off-set torsion, or load applied off-set from the fixed long bone axis, was applied to cadaveric specimens with mechanically induced metastatic lesions, and the resultant fracture location was compared to specimen-specific FEA models replicating the mechanical test. FEA was able to correctly predict fracture locations in five models. Determining fracture risk based on objective mechanical data may more accurate and effective in this patient population.

Infertility is a widespread problem around the world, although the available treatment options constantly improve through research and methodological development. A common treatment option mainly for biologically caused infertility is in-vitro fertilization, where in a menstrual cycle multiple oocytes are stimulated to mature and are then fertilized in a laboratory. This often results in multiple good quality embryos which can be cryopreserved through vitrification and used in a later cycle to increase the success chance of the treatment. The purpose of this pilot study was to evaluate vitrification and warming kits from Kitazato and Irvine Scientific regarding results and procedures. Human cleavage stage embryos (n=76) were thawed and cultured to the blastocyst stage. The blastocysts were scored according to Gardner and cryopreserved with vitrification and warming kits from either Kitazato (n=20) or Irvine Scientific (n=20). The warmed blastocysts were controlled after 2 and 4 hours for re-expansion and freeze injuries. The data was analysed with Fisher’s exact test and considered statistically significant if two-tailed p-value <0.05. The results showed no significant difference between the kits after 2 respectively 4 hours regarding re-expansion (p=0.432; p=0.492) or freeze injury (p=1.000; p=0.476). A significant difference was observed between group AB (with higher Gardner-score) and group C (with lower Gardner-score) in the degree of freeze injury (p=0.048; p=0.034), regardless of vitrification kit used. The details of the procedures differed somewhat between the kits, both having pros and cons, although overall procedures were equivalent. Further evaluation is needed before a change in method can be conducted.

This master thesis work presents a novel method of automatic essay scoring for Swedish national tests written by upper secondary high school students by deploying neural network architectures and linguistic feature extraction in the framework of Swegram. There are four sorts of linguistic aspects involved in our feature extraction: count-based,lexical morphological and syntactic. One of the three variants of recurrent network, vanilla RNN, GRU and LSTM, together with the specific model parameter setting, is implemented in the Automatic Essay Scoring (AES) modelling with extracted features measuring the linguistic complexity as text representation. The AES model is evaluated through interrater agreement with human assigned grade as target label in terms of quadratic weighted kappa (QWK) and exact percent agreement. Our best observed averaged QWK and averaged exact percent agreement is 0.50 and 52% over 10 folds among our all experimented models.

The diploma thesis deals with the analysis of current situation of information systém Hutchhouse’s company. Due to the analysis of the current situation of the system and due to suggestions of preventions for the information system should the compan achieves better results. The subject of the thesis is mainly a analysis of the company, then the analysis of the information system and identification of risks. Output of this diploma thesis are preventions which eliminate these risks accordingly.

Written skills are an essential evaluation criterion for a student’s creativity, knowledge, and intellect. Consequently, academic writing is a common part of university and college admissions applications, standardized tests, and classroom assessments. However, the task for teachers is quite daunting when it comes to essay scoring. Then Automated Essay Scoring may be a helpful tool in the decision-making by the teacher.  There have been many successful models with supervised or unsupervised machine learning algorithms in the eld of Automated Essay Scoring. This thesis work makes a comparative study among various neural network models with supervised machine learning algorithms and different linguistic feature combinations. It also proves that the same linguistic features are applicable to more than one language.  The models studied in this experiment include TextCNN, TextRNN_LSTM, Tex- tRNN_GRU, and TextRCNN trained with the essays from the Automated Student Assessment Prize (ASAP) from Kaggle competitions. Each essay is represented with linguistic features measuring linguistic complexity. Those features are divided into four groups: count-based, morphological, syntactic, and lexical features, and the four groups of features can form a total of 14 combinations.  The models are evaluated via three measurements: Accuracy, F1 score, and Quadratic Weighted Kappa. The experimental results show that models trained only with count-based features outperform the models trained using other feature combinations. In addition, TextRNN_LSTM performs best, with an accuracy of 54.79%, an F1 score of 0.55, and a Quadratic Weighted Kappa of 0.59, which beats the statistically-based baseline models.

Thesis deals with the problems of life insurance. On the basis of comparison of life insurance products for children of chosen commercial insurance companies, it contains evaluation and proposals for improvement of insurance products for children of Generali pojišťovna, a. s.

This diploma thesis analyses problems connected with motor insurance of the company Česká pojišťovna a.s. and contains the project to improvement the offer of this product in order to be competitive and corresponding to the requirements of client.

This master’s thesis deals with using Text mining as a method to predict tags of articles. It describes the iterative way of handling big data files, parsing the data, cleaning the data and scoring of terms in article using TF-IDF. It describes in detail the flow of program written in programming language Python 3.4.3. The result of processing more than 1 million articles from Wikipedia database is a dictionary of English terms. By using this dictionary one is capable of determining the most important terms from article in corpus of articles. Relevancy of consequent tags proves the method used in this case.

There has been a call from the national community of biologists and biology educators to increase biological literacy of undergraduate students, including understanding and application of core concepts. The structure and function relationship is a core concept identified by the wider biology community and by physiology faculty. Understanding of the core concept structure and function across multiple levels of organization may promote biological literacy. My research focused on the development of formative written assessment tools to provide insight into student understanding of structure and function in anatomy and physiology. In chapter two I developed automated scoring tools to facilitate the evaluation of written formative assessment based on structure and function. Formative written assessments allow students to demonstrate their thinking by encouraging students to use their diverse ideas to construct their responses. However, formative written assessments are not often used in the undergraduate biology classroom due to barriers, such as time spent grading and the intricacy of interpreting student responses. Automated scoring, such as lexical analysis and machine scoring, can examine student thinking in formative written responses. The core concept structure-function provides a foundation upon which many topics in anatomy and physiology can be built across all levels of organization. My research focused on the development of formative written assessment tools and automated scoring models to provide insight into student understanding of structure and function. My research objective was to examine student understanding of a core concept in anatomy and physiology by using automated scoring. Ten short answer questions were administered to students in a junior-level General Physiology course and a sophomore level Human Anatomy and Physiology course at a large Southeastern public university, and to students in Human Anatomy and Physiology courses at two Southeastern two-year colleges. Seventeen students were interviewed to determine if their responses to the short answer questions accurately reflected their thinking. Lexical analysis and machine scoring were used to build predictive models that can analyze student thinking about the structure-function relationship in anatomy and physiology with high agreement to human scoring. Less than half of the student responses in this study demonstrated conceptual understanding of the structure-function relationship. Automated scoring can successfully evaluate a large number of student responses in Human Anatomy and Physiology and General Physiology courses. In chapter three I compared conceptual understanding of structure and function in 2-yr and 4-yr student responses. Anatomy and physiology is taught at a variety of institutions, including 2-year community colleges and 4-year research universities. Regardless of the type of institution offering anatomy and physiology, conceptual understanding of the structure-function relationship is necessary to understand physiological processes. The focus of my research was to compare conceptual understanding of 2-year versus 4-year anatomy and physiology students by using written formative assessment. I hypothesize that differences in students’ academic readiness between two-year and four-year institutions may affect conceptual understanding and student performance. Based on prior research, I predict that there will be a difference in conceptual understanding of the core concept structure and function between two-year and four-year students in anatomy and physiology, and that the students at the two-year institution will not perform as well as the students at the four-year institution, as measured by performance on the constructed response questions. Responses to eight short answer essay questions were collected from students at both types of institutions from students in human anatomy and physiology over six semesters. My results demonstrated that there is a difference in conceptual understanding of the structure-function relationship between 2-year and 4-year students in anatomy and physiology with more 4-year students mentioning SRF concepts in their responses compared to the 2-year students. A potential reason for this difference may be college readiness. There was no difference in performance between institution types on structure-function concepts examined in the A&P II course. My results suggested that students may benefit from a focus on core concepts within the content of anatomy and physiology courses. This focus should occur in both the first and second semesters of anatomy and physiology. Instructors can use written formative assessment to allow students to demonstrate their conceptual understanding within the organ systems. In chapter four I investigated how question features affect student responses to anatomy and physiology formative assessment questions. Short answer essay questions contain features which are elements of the question which aid students in connecting the question to their existing knowledge. Varying the features of a question may be used to provide insight into the different stages of students’ emerging biological expertise and differentiate novice students who have memorized an explanation from those who exhibit understanding. I am interested in examining the cognitive level of questions, the use of guiding context/references in question prompts, and the order of questions, and how these features elicit student explanations of the core concept structure-function in anatomy and physiology. I hypothesized that varying the features of short answer questions may affect student explanations. Short answer questions based on the core concept ‘structure-function’ were administered to 767 students in a junior level General Physiology course and to 573 students in a sophomore level Human Anatomy and Physiology course at a large southeastern public university. Student responses were first human scored and then scored by using lexical analysis and machine scoring. Students were interviewed to examine their familiarity with levels of organization and to confirm their interpretation of the questions. Students demonstrated more conceptual understanding of four of the structure-function concepts when answering the understand questions and more conceptual understanding of two structure-function concepts when answering the apply questions. The question prompts provided a different context which may have influenced student explanations. There was no difference in conceptual understanding of the structure-function relationship with and without the use of a guiding context in the wording of the question prompt. For question sequence, students performed better on the last questions in the sequence, regardless of whether the last question was easier or more difficult. Instructors should provide students with questions in varying contexts and cognitive levels will allow students to demonstrate their heterogeneous ideas about a concept.

Why this thesis is needed. This thesis is motivated by the falling school results of Swedish 15-year-olds, a lack of IT tools in Swedish schools and a call for turning the theory on formative assessment into practice. Previous research that is used in the thesis. This thesis mainly builds on the research done by John Hattie which is presented in his book Visible Learning from 2009, Wiliam & Thompson's research on effective formative assessment from 2007, Pachler et al. research on formative e-assessment from 2010 and Panadero & Jonsson's research on scoring rubrics from 2013. Research question. What key aspects should be taken into consideration when designing and implementing an IT tool based on scoring rubrics which aims to support formative assessment according to the key strategies for effective formative assessment as identified by Wiliam & Thompson (2007)? Method. To answer this question I chose a qualitative approach of parallel paper prototyping where I iteratively exposed the design and my ideas during focus groups to teachers, a headmaster, employees at The Swedish National Agency for Education and high school students, followed by an evaluation of the key topics that surfaced during the focus groups. Results. The results consist of eight key aspects to take into consideration when designing and implementing such a tool. Discussion and future research. Finally I discuss the implications of my findings and present directions for future research which include the construction of the tool, further investigation of the key aspects identified in this study, identification of additional key aspects and more. / Varför denna avhandling behövs. Denna avhandling motiveras av de fallande skolresultaten hos svenska 15-åringar, en brist på IT-verktyg i svenska skolor och ett rop efter att vända forskning inom formativ bedömning till praktik. Tidigare forskning som används. Denna avhandling bygger i huvudsak på forskningen av John Hattie som presenteras i hans bok Visible Learning från 2009, William & Thompsons forskning på effektiv formativ bedömning från 2007, Pachler et al. forskning på formativ e-bedömning från 2010 och Panadero & Jonssons forskning på betygsmatriser från 2013. Forskningsfråga. Vilka nyckelaspekter ska tas i åtanke vid utveckling av ett IT-verktyg baserat på betygsmatriser som stödjer formativ bedömning enligt de fem nyckelstrategierna för effektiv formativ bedömning som formulerats av Wiliam & Thompson (2007)? Metod. För att besvara denna fråga valdes en kvalitativ metod där parallell pappersprototypning användes under ett antal iterationer av fokusgrupper under vilka designen och tidigare diskussionpunkter diskuterades med lärare, en rektor, anställda vid Skolverket samt gymnasiestudenter. Fokusgrupperna följdes upp med en utvärdering av de största diskussionpunkterna som dök upp. Resultat. Resultaten består av åtta nyckelaspekter att ha i åtanke vid utveckling av ett sådant verktyg. Diskussion och framtida forskning. Slutligen diskuteras implikationerna av resultaten och direktioner för framtida forskning framförs. Dessa direktioner inkluderar utveckling av verktyget, vidare utredning av de nyckelaspekter som hittats i denna avhandling, identifikation av ytterligare nyckelaspekter och mer.