Positive predictive values of Breast Imaging Reporting and Data System (BI-RADS®) categories 3, 4 and 5 in breast lesions submitted to percutaneous biopsy

Objective To evaluate the BI-RADS as a predictive factor of suspicion for malignancy in breast lesions by correlating radiological with histological results and calculating the positive predictive value for categories 3, 4 and 5 in a breast cancer reference center in the city of São Paulo. Materials and Methods Retrospective, analytical and cross-sectional study including 725 patients with mammographic and/or sonographic findings classified as BI-RADS categories 3, 4 and 5 who were referred to the authors' institution to undergo percutaneous biopsy. The tests results were reviewed and the positive predictive value was calculated by means of a specific mathematical equation. Results Positive predictive values found for categories 3, 4 and 5 were respectively the following: 0.74%, 33.08% and 92.95%, for cases submitted to ultrasound-guided biopsy, and 0.00%, 14.90% and 100% for cases submitted to stereotactic biopsy. Conclusion The present study demonstrated high suspicion for malignancy in lesions classified as category 5 and low risk for category 3. As regards category 4, the need for systematic biopsies was observed.

Market orientation and performance in entrepreneurial SMEs

Market orientation is the organizational culture that creates the necessary behaviors for continuous additional value for customers and thus continuous superior performance for the business. The field of market orientation has been studied repeatedly during the past two decades. Yet research has concentrated on large firms in large domestic markets creating a need for diversifying research. The master’s thesis at hand examined the general incidence of market orientation among SMEs from five different industries as well as its consequences on SME performance. The empirical part of the thesis was conducted with a web-based survey that resulted in 255 responses. The data of the survey was analyzed by statistical analysis. The incidence of market orientation varied among dimensions and market orientation did not show any direct effect on firm performance. Customer orientation was the only dimension that showed a direct (positive) effect. On the contrary, moderating effects were found which indicate that the effect of market orientation in SMEs is influenced by other factors that should receive further attention. Also industry specific differences were discovered and should be further examined.

Technology roadmap for new sales support and management system for crane manufacturing company

Sales configurators are essential tools for companies that offer complicated case specifically crafted products for customers. Most sophisticated of them are able to design an entire end product on the fly according to given constraints, calculate price for the offer and move the order into production. This thesis covers a sales configurator acquisition project in a large industrial company that offers cranes for its customers. The study spans the preliminary stages of a large-scale software purchase project starting from the specification of problem domain and ending up presenting the most viable software solution that fulfils the requirements for the new system. The project consists of mapping usage environment, use cases, and collecting requirements that are expected from the new system. The collected requirements involve fitting the new sales system into enterprise application infrastructure, mitigating the risks involved in the project and specifying new features to the application whilst preserving all of the admired features of the old sales system currently used in the company. The collected requirements were presented to a number of different sales software vendors who were asked to provide solution suggestions that would fulfil all the demands. All of the received solution proposals were exposed to an evaluation to determine the most feasible solutions, and the construction of evaluation criteria itself was a part of the study. The final outcome of this study is a short-list of the most feasible sales configurator solutions together with a description of how software purchase process in large enterprises work, and which aspects should be paid attention in large projects of similar kind.

Development of a Filter Aid Proportioning, Mixing, and Feeding System for a Polishing Filter

The purpose of this work was to study the characteristics of the most commonly used filter aid materials and their influences on the design of proportioning, mixing, and feeding system for polishing filter family. Based on the literature survey and hands-on experience a system was designed with defined equipment and capital and operating costs. The system was designed to serve precoating and bodyfeeding applications and is easily extended to be used in multiple filter processes. Also a test procedure was carried out where influences of flux and filter cloths to accumulated cake were studied. Filter aid is needed in challenging conditions to improve filtration efficiency and cleaning, and thus extend the operating life of the filter media. Filter aid preparation and feeding system was designed for the use of two different filter aids; precoat and bodyfeed. Precoating is used before the filtration step initiates. If the solids in the filterable solution have a tendency to clog the filter bag easily, precoat is used on the filter bag to obtain better filtration efficiency and quality. Diatomite or perlite is usually used as a precoating substance. The intention is to create a uniform cake to the overall surface of the filter cloth, with predetermined thickness, 2 – 5 mm. This ensures that the clogging of the filter cloth is reduced and the filtration efficiency is increased. Bodyfeed is used if the solids in the filterable solution have a tendency to form a sticky impermeable filter cake. The cake properties are enhanced by maintaining the permeability of the accumulating cake by using the filter aid substance as bodyfeed during the filtration process.

Strategic choices and performance – an empirical analysis of largest European and North American energy companies

Energy industry has gone through major changes globally in past two decades. Liberalization of energy markets has led companies to integrate both vertically and horizontally. Growing concern on sustainable development and aims to decrease greenhouse gases in future will increase the portion of renewable energy in total energy production. Purpose of this study was to analyze using statistical methods, what impacts different strategic choices has on biggest European and North American energy companies’ performance. Results show that vertical integration, horizontal integration and use of renewable energy in production had the most impact on profitability. Increase in level of vertical integration decreased companies’ profitability, while increase in horizontal integration improved companies’ profitability. Companies that used renewable energy in production were less profitable than companies not using renewable energy.

SYNGAS PRODUCTION FROM CO2-REFORMING OF CH4 OVER SOL-GEL SYNTHESIZED Ni-Co/Al2O3-MgO-ZrO2 NANOCATALYST: EFFECT OF ZrO2 PRECURSOR ON CATALYST PROPERTIES AND PERFORMANCE

Ni-Co/Al2O3-MgO-ZrO2 nanocatalyst with utilization of two different zirconia precursors, namely, zirconyl nitrate hydrate (ZNH) and zirconyl nitrate solution (ZNS), was synthesized via the sol-gel method. The physiochemical properties of nanocatalysts were characterized by XRD, FESEM, EDX, BET and FTIR analyses and employed for syngas production from CO2-reforming of CH4. XRD patterns, exhibiting proper crystalline structure and homogeneous dispersion of active phase for the nanocatalyst ZNS precursor employed (NCAMZ-ZNS). FESEM and BET results of NCAMZ-ZNS presented more uniform morphology and smaller particle size and consequently higher surface areas. In addition, average particle size of NCAMZ-ZNS was 15.7 nm, which is close to the critical size for Ni-Co catalysts to avoid carbon formation. Moreover, FESEM analysis indicated both prepared samples were nanoscale. EDX analysis confirmed the existence of various elements used and also supported the statements made in the XRD and FESEM analyses regarding dispersion. Based on the excellent physiochemical properties, NCAMZ-ZNS exhibited the best reactant conversion across all of the evaluated temperatures, e.g. CH4 and CO2 conversions were 97.2 and 99% at 850 ºC, respectively. Furthermore, NCAMZ-ZNS demonstrated a stable yield with H2/CO close to unit value during the 1440 min stability test.

Imaging and Characterisation of Dirt Particles in Pulp and Paper

Dirt counting and dirt particle characterisation of pulp samples is an important part of quality control in pulp and paper production. The need for an automatic image analysis system to consider dirt particle characterisation in various pulp samples is also very critical. However, existent image analysis systems utilise a single threshold to segment the dirt particles in different pulp samples. This limits their precision. Based on evidence, designing an automatic image analysis system that could overcome this deficiency is very useful. In this study, the developed Niblack thresholding method is proposed. The method defines the threshold based on the number of segmented particles. In addition, the Kittler thresholding is utilised. Both of these thresholding methods can determine the dirt count of the different pulp samples accurately as compared to visual inspection and the Digital Optical Measuring and Analysis System (DOMAS). In addition, the minimum resolution needed for acquiring a scanner image is defined. By considering the variation in dirt particle features, the curl shows acceptable difference to discriminate the bark and the fibre bundles in different pulp samples. Three classifiers, called k-Nearest Neighbour, Linear Discriminant Analysis and Multi-layer Perceptron are utilised to categorize the dirt particles. Linear Discriminant Analysis and Multi-layer Perceptron are the most accurate in classifying the segmented dirt particles by the Kittler thresholding with morphological processing. The result shows that the dirt particles are successfully categorized for bark and for fibre bundles.

Researching Manufacturing Planning and Control system and Master Scheduling in a manufacturing firm.

The objective of this thesis is to research Manufacturing Planning and Control (MPC) system and Master Scheduling (MS) in a manufacturing firm. The study is conducted at Ensto Finland Corporation, which operates on a field of electrical systems and supplies. The paper consists of theoretical and empirical parts. The empirical part is based on weekly operating at Ensto and includes inter-firm material analysis, learning and meetings. Master Scheduling is an important module of an MPC system, since it is beneficial on transforming strategic production plans based on demand forecasting into operational schedules. Furthermore, capacity planning tools can remarkably contribute to production planning: by Rough-Cut Capacity Planning (RCCP) tool, a MS plan can be critically analyzed in terms of available key resources in real manufacturing environment. Currently, there are remarkable inefficiencies when it comes to Ensto’s practices: the system is not able to take into consideration seasonal demand and react on market changes on time; This can cause significant lost sales. However, these inefficiencies could be eliminated through the appropriate utilization of MS and RCCP tools. To utilize MS and RCCP tools in Ensto’s production environment, further testing in real production environment is required. Moreover, data accuracy, appropriate commitment to adapting and learning the new tools, and continuous developing of functions closely related to MS, such as sales forecasting, need to be ensured.

Kernel-Based Ranking. Methods for Learning and Performance Estimation

Machine learning provides tools for automated construction of predictive models in data intensive areas of engineering and science. The family of regularized kernel methods have in the recent years become one of the mainstream approaches to machine learning, due to a number of advantages the methods share. The approach provides theoretically well-founded solutions to the problems of under- and overfitting, allows learning from structured data, and has been empirically demonstrated to yield high predictive performance on a wide range of application domains. Historically, the problems of classification and regression have gained the majority of attention in the field. In this thesis we focus on another type of learning problem, that of learning to rank. In learning to rank, the aim is from a set of past observations to learn a ranking function that can order new objects according to how well they match some underlying criterion of goodness. As an important special case of the setting, we can recover the bipartite ranking problem, corresponding to maximizing the area under the ROC curve (AUC) in binary classification. Ranking applications appear in a large variety of settings, examples encountered in this thesis include document retrieval in web search, recommender systems, information extraction and automated parsing of natural language. We consider the pairwise approach to learning to rank, where ranking models are learned by minimizing the expected probability of ranking any two randomly drawn test examples incorrectly. The development of computationally efficient kernel methods, based on this approach, has in the past proven to be challenging. Moreover, it is not clear what techniques for estimating the predictive performance of learned models are the most reliable in the ranking setting, and how the techniques can be implemented efficiently. The contributions of this thesis are as follows. First, we develop RankRLS, a computationally efficient kernel method for learning to rank, that is based on minimizing a regularized pairwise least-squares loss. In addition to training methods, we introduce a variety of algorithms for tasks such as model selection, multi-output learning, and cross-validation, based on computational shortcuts from matrix algebra. Second, we improve the fastest known training method for the linear version of the RankSVM algorithm, which is one of the most well established methods for learning to rank. Third, we study the combination of the empirical kernel map and reduced set approximation, which allows the large-scale training of kernel machines using linear solvers, and propose computationally efficient solutions to cross-validation when using the approach. Next, we explore the problem of reliable cross-validation when using AUC as a performance criterion, through an extensive simulation study. We demonstrate that the proposed leave-pair-out cross-validation approach leads to more reliable performance estimation than commonly used alternative approaches. Finally, we present a case study on applying machine learning to information extraction from biomedical literature, which combines several of the approaches considered in the thesis. The thesis is divided into two parts. Part I provides the background for the research work and summarizes the most central results, Part II consists of the five original research articles that are the main contribution of this thesis.

Mild developmental dyslexia in university students: diagnosis and performance features in L1, L2, and L3

Avhandling visar att lindrig dyslexi påverkar läs- och skrivprestationer hos högpresterare. Särdrag träder tydligast fram i främmande språk och vid hantering av språkljud i krävande testuppgifter. Även om dyslexirelaterade problem vanligtvis är lindriga hos universitetsstudenter, är det centralt att dessa identifieras, eftersom de ses påverka akademiska prestationer. Avhandlingen lägger fram det första finlandssvenska dyslexitestet normerat för universitetsnivå (FS-DUVAN) och ger verktyg för utredning av läs- och skrivsvårigheter hos unga vuxna i Svenskfinland. Avhandlingen utforskar också språkspecifika särdrag av dyslexi hos högpresterande finlandssvenska universitetsstudenter i läs- och skrivuppgifter i svenska, finska och engelska. Detaljerade felanalyser visar att studenter med dyslexi speciellt har problem med kopplingar mellan språkljud och bokstav i det främmande språket engelska, som också i detta avseende är komplext. Resultat i komplexa kognitiva testuppgifter som förutsätter hantering av språkljud pekar på svikt i fonologisk processering, som betecknas som den huvudsakliga underliggande kognitiva nedsättningen vid utvecklingsbetingad dyslexi.

Evaluation of covering materials in individual shelters and its effects on physiological responses and performance of dairy calves

In Tropical regions, the animal performance is often affected by climate conditions. This study aimed to evaluate covering materials in individual shelters, normally used to house dairy calves, and its influence on the calves physiology and performance. The design used was completely randomized, with a 2x3 factorial arrangement to compare the averages of 5% through the Tukey's test, i.e., both genders- and three types of covering in the shelters (Z - zinc; AC - asbestos cement; and WPAC - white-painted asbestos cement). Parameters evaluated included daily weight gain (DWG), dry matter intake (DMI), feed conversion (FC), rectal temperature (RT), and respiratory frequency (RF). Results showed significant differences (P < 0.05) among males (1.04kg/day) and females (0.74kg/day) for DWG and interaction between gender and treatment (P < 0.05) for zinc covering (0.562kg/day for females and 1.120kg/day for males). Significant differences were also observed in FI of animals housed under shelters with the covering of zinc (48.35kgDM/day for females and 96.91 kgDM/day for males). There were no significant differences (P > 0.05) in the FC and the RT, and there were significant differences (P < 0.05) for RF in the Z treatments (56.9 mov.min-1), WPAC (62.2 mov.min-1) and FC (70.25 mov.min-1). It was concluded that different covering materials did not affect performance and dry matter intake of dairy calves. However, the animals' physiology of thermoregulation was altered by the different covering materials used in individual shelters.