As the information flow on the Internet keeps growing it becomes increasingly easy to miss important news which does not have a mass appeal. Combating this problem calls for increasingly sophisticated information retrieval methods. Pre-trained transformer based language models have shown great generalization performance on many natural language processing tasks. This work investigates how well such a language model, Open AI’s General Pre-trained Transformer 2 model (GPT-2), generalizes to information retrieval and classification of online news articles, written in English, with the purpose of comparing this approach with the more traditional method of Term Frequency-Inverse Document Frequency (TF-IDF) vectorization. The aim is to shed light on how useful state-of-the-art transformer based language models are for the construction of personalized information retrieval systems. Using transfer learning the smallest version of GPT-2 is trained to rank and classify news articles achieving similar results to the purely TF-IDF based approach. While the average Normalized Discounted Cumulative Gain (NDCG) achieved by the GPT-2 based model was about 0.74 percentage points higher the sample size was too small to give these results high statistical certainty. / Informationsflödet på Internet fortsätter att öka vilket gör det allt lättare att missa viktiga nyheter som inte intresserar en stor mängd människor. För att bekämpa detta problem behövs allt mer sofistikerade informationssökningsmetoder. Förtränade transformermodeller har sedan ett par år tillbaka tagit över som de mest framstående neurala nätverken för att hantera text. Det här arbetet undersöker hur väl en sådan språkmodell, Open AIs General Pre-trained Transformer 2 (GPT-2), kan generalisera från att generera text till att användas för informationssökning och klassificering av texter. För att utvärdera detta jämförs en transformerbaserad modell med en mer traditionell Term Frequency- Inverse Document Frequency (TF-IDF) vektoriseringsmodell. Målet är att klargöra hur användbara förtränade transformermodeller faktiskt är i skapandet av specialiserade informationssökningssystem. Den minsta versionen av språkmodellen GPT-2 anpassas och tränas om till att ranka och klassificera nyhetsartiklar, skrivna på engelska, och uppnår liknande prestanda som den TF-IDF baserade modellen. Den GPT-2 baserade modellen hade i genomsnitt 0.74 procentenheter högre Normalized Discounted Cumulative Gain (NDCG) men provstorleken var ej stor nog för att ge dessa resultat hög statistisk säkerhet.

Infrastructure projects, based on the Build-Operate-Transfer, (BOT), method, have been of interest to governments of developed and developing countries for some time, resulting in their worldwide use. Using the BOT method enables governments to reallocate risks and rewards to the private sector for larger infrastructure projects throughout the projects' operating life. In order to implement a BOT infrastructure project successfully, one of the essential requirements is to carry out a thorough analysis of risks relating to the project including the social, economic, environmental, political, legal, and the financial aspects. Due to the fact that the type of risk study required for large-scale projects is so sophisticated, and therefore expensive and time consuming, the government, due to lack of expertise and time, often obtains a project viability study from the private sector. This can cause problems in that the private sector may incur financial losses or even bankruptcy, unless the host government guarantees compensation to the losers of the bid. Because all parties have different targets which they wish to achieve from the project, a may conflict arise and cause lengthy negotiations, sometimes lasting for years which often result in the death of the project. The greatest opportunity for a successful outcome for a BOT project is obtained when the extensive efforts and costs involved in the risk study process are shared by all parties. The responsibility of the decision maker is to identify, understand and analyze the many risk factors both, qualitative, (linguistic in nature) and quantitative, that will affect funding, procurement, developing, construction and operation, before proceeding with the build stage of the project. Firstly, it is necessary to evaluate the quantitative Risk Factors subjectively, and list them in order of importance. Secondly, conduct an evaluation of the qualitative factors and since the consideration of qualitative factors is subjective, the decision maker will often limit the number of factors being evaluated possibly resulting in inconsistent results. This study proposes a decision framework, which would be useful in determining the influence of the qualitative Risk Factors on the project management of BOT infrastructure projects. A methodology is provided to enable the identification of interrelationships between the Risk Factors and their influence on the project. Using Analytical Hierarchy Process (AHP) techniques, which model the relationships between the Risk Factors, a validation of this approach will be sought using a decomposed evaluation method and also information obtained from three existing case studies, (the Channel Tunnel, Sulaibiya Wastewater Treatment and Reclamation Plant and Marsa Allam Airport). The results of the decomposed approach were compared to experts' holistic evaluations for the same case studies mentioned above. The findings indicate that the decomposed approach showed a strong correlation to the holistic approach. An evaluation of the risks for the Sulaibiya Wastewater Treatment and Reclamation Plant study is provided and suggestions made to highlight risks attached to such a project before it is actually undertaken. Using the decomposed approach enables the decision maker to see the contribution of each risk compared to all of the risks in the total project and will help to determine and subsequently minimize or preventing any risk factors and so considerably improving the risk management of the project.

The purpose of this essay is to look into how Jean Rhys describes the complexity of colonialism in the Caribbean and how it affected the colonized people and the European colonizers. Her novel Wide Sargasso Sea is considered to be a re-writing of Jane Eyre, but it also demonstrates social rankings and racial groupings in the colonial society. She does not only describe Mr. Rochester’s first wife, she also depicts the forbidden love story between Antoinette and her “coloured” cousin Sandi. The analysis will have a postcolonial approach by using postcolonial theory and concepts, for example, Said’s concept about the Other, Fanon’s ideas about the psychological effects on the oppressed and Bhabha’s theory about colonial mimicry.

Very long and noisy sequence data arise from biological sciences to social science including high throughput data in genomics and stock prices in econometrics. Often such data are collected in order to identify and understand shifts in trends, for example, from a bull market to a bear market in finance or from a normal number of chromosome copies to an excessive number of chromosome copies in genetics. Thus, identifying multiple change points in a long, possibly very long, sequence is an important problem. In this article, we review both classical and new multiple change-point detection strategies. Considering the long history and the extensive literature on the change-point detection, we provide an in-depth discussion on a normal mean change-point model from aspects of regression analysis, hypothesis testing, consistency and inference. In particular, we present a strategy to gather and aggregate local information for change-point detection that has become the cornerstone of several emerging methods because of its attractiveness in both computational and theoretical properties.

This thesis explores the fundamental ethics and purpose of elite higher education. Beginning with an inquiry into the history of American higher education, this work reveals that the U.S. News & World Report “Best College” and “Best University” ranking lists hold an increasingly important role in distinguishing institutions, particularly those within the elite tier. Following an examination of the U.S. News’ methodology, this analysis confronts concerns with individual access to elite institutions. Although there are potential changes to the U.S. News’ methodology that could improve institutional assessment, this thesis does not propose alternative rankings. Rather, it focuses on many institutions’ problematic choice to use the rankings as a guide for admissions and institutional practice. This work evaluates the potentially stratifying components of elite institutions and questions what American higher education inculcates in students. This endeavor concludes by providing suggestions for how to democratize elite institutions in order to realize their respective missions and improve access to educational opportunities. Chapter I: Introduction & Motivation Chapter II: History Chapter III: The U.S. News & World Report Rankings Chapter IV: The Current System of Higher Education Chapter V: For Society’s Benefit

Feature selection method is becoming an essential procedure in data preprocessing step. The feature selection problem can affect the efficiency and accuracy of classification models. Therefore, it also relates to whether a classification model can have a reliable performance. In this study, we compared an original feature selection method and a proposed frequency-based feature selection method with four classification models and three filter-based ranking techniques using a cancer dataset. The proposed method was implemented in WEKA which is an open source software. The performance is evaluated by two evaluation methods: Recall and Receiver Operating Characteristic (ROC). Finally, we found the frequency-based feature selection method performed better than the original ranking method.

This dissertation investigates data reduction strategies from a signal processing perspective in centralized detection and estimation applications. First, it considers a deterministic source observed by a network of sensors and develops an analytical strategy for ranking sensor transmissions based on the magnitude of their test statistics. The benefit of the proposed strategy is that the decision to transmit or not to transmit observations to the fusion center can be made at the sensor level resulting in significant savings in transmission costs. A sensor network based on target tracking application is simulated to demonstrate the benefits of the proposed strategy over the unconstrained energy approach. Second, it considers the detection of random signals in noisy measurements and evaluates the performance of eigenvalue-based signal detectors. Due to their computational simplicity, robustness and performance, these detectors have recently received a lot of attention. When the observed random signal is correlated, several researchers claim that the performance of eigenvalue-based detectors exceeds that of the classical energy detector. However, such claims fail to consider the fact that when the signal is correlated, the optimal detector is the estimator-correlator and not the energy detector. In this dissertation, through theoretical analyses and Monte Carlo simulations, eigenvalue-based detectors are shown to be suboptimal when compared to the energy detector and the estimator-correlator.

This master thesis discusses employees appraisal in a selected organization. The theoretical part is devoted to expressions from the area of staff appraisal. Topics such as performance management, performance appraisal and work performance are clarified. Further the common process of employees appraisal is described, including its meaning and functionality. appraisal criteria are specified and selected appraisal metods are described. A specific chapter is devoted to forced distribution method. In the end of this part characteristics of high quality and effective employees appraisal are listed. In the empirical part a specific organization is presented, including description and analysis of used employees appraisal system. The goal of the research is through the analysis of the employees appraisal system and with the help of interviews with its employees determine the characteristics of a quality employees appraisal system. Based on the results of the conducted research recommendations leading to higher efectivity of employees appraisal are formed. Keywords: performance appraisal, performance management, appraisal metods, forced ranking

This thesis deals with the performance evaluation of a selected group of insurance companies. The text is divided into several parts and begins with the explanation of theoretical frameworks for both insurance and the ranking process. This knowledge is then applied to the object of analysis. Mainly the financial performance of insurers was assessed, by means of the so-called spread indicator. Hence, part of the analysis is also a cost of equity calculation with the help of the Capital Asset Pricing Model. The outcome of this work is the ranking of analyzed insurance companies by their financial performance in 2007-2009. The contribution of the work can be seen not only in forming the ranking, but in demonstration of a practical application of the chosen methodology as well as in description of its advantages and disadvantages.

L’objectif de cette thèse a été de proposer une approche robuste pour traiter le problème de la recherche dela réponse précise à une question.Notre première contribution a été la conception et la mise en œuvre d’un modèle de représentation robuste de l’informationet son implémentation. Son objectif est d’apporter aux phrases des documents et aux questions de l’informationstructurelle, composée de groupes de mots typés (segments typés) et de relations entre ces groupes. Ce modèle a été évalué sur différents corpus (écrits, oraux, web) et a donné de bons résultats, prouvant sa robustesse.Notre seconde contribution a consisté en la conception d’une méthode de réordonnancement des candidats réponsesretournés par un système de questions-réponses. Cette méthode a aussi été conçue pour des besoins de robustesse, ets’appuie sur notre première contribution. L’idée est de comparer une question et le passage d’où a été extraite une réponse candidate, et de calculer un score de similarité, en s’appuyant notamment sur une distance d’édition.Le réordonnanceur a été évalué sur les données de différentes campagnes d’évaluation. Les résultats obtenus sontparticulièrement positifs sur des questions longues et complexes. Ces résultats prouvent l’intérêt de notre méthode, notreapproche étant particulièrement adaptée pour traiter les questions longues, et ce quel que soit le type de données. Leréordonnanceur a ainsi été évalué sur l’édition 2010 de la campagne d’évaluation Quaero, où les résultats sont positifs. / The objective of this work is to introduce a new robust approach to treat the problem of finding the correctanswer to a question.Our first contribution is the design and implementation of a robust representation model for information. The aim is torepresent the structural information of sentences of documents and questions structural information. This representation iscomposed of typed groups of words (typed segments) and relations between these groups. This model has been evaluatedon several corpus (written, oral, web) and achieved good resultats, which proves his robustness.Our second contribution consisted is the design of a re-ranking method of a set of the candidate answers output by thequestion-answering system. This re-ranking method is based on the structural information representation. The general ideais to compare a question and a passage from where a candidate answer was extracted, and to compute a similarity score by using a modified edit distance we proposed.Our re-ranking method has been evaluated on the data of several evaluation campaigns. The results are quite goodon long and complex questions. These results show the interest of our method : our approach is quite adapted to treatlong question, whatever the type of the data. The re-ranker has been officially evaluated on the 2010 edition of the Quaeroevaluation campaign, with positives results.