Draft prediction models for soil engaging tines in two soils of Rio Grande do Sul, Brazil

The draft forces of soil engaging tines and theoretical analysis compared to existing mathematical models, have yet not been studied in Rio Grande do Sul soils. From the existing models, those which can get the closest fitting draft forces to real measure on field have been established for two of Rio Grande do Sul soils. An Albaqualf and a Paleudult were evaluated. From the studied models, those suggested by Reece, so called "Universal Earthmoving Equation", Hettiaratchi and Reece, and Godwin and Spoor were the best fitting ones, comparing the calculated results with those measured "in situ". Allowing for the less complexity of Reece's model, it is suggested that this model should be used for modeling draft forces prediction for narrow tines in Albaqualf and Paleudut.

Characterization of soil parameters of two soils of Rio Grande do Sul in modeling the prediction of tractive effort

The interaction between the soil and tillage tool can be examined using different parameters for the soil and the tool. Among the soil parameters are the shear stress, cohesion, internal friction angle of the soil and the pre-compression stress. The tool parameters are mainly the tool geometry and depth of operation. Regarding to the soils of Rio Grande do Sul there are hardly any studies and evaluations of the parameters that have importance in the use of mathematical models to predict tensile loads. The objective was to obtain parameters related to the soils of Rio Grande do Sul, which are used in soil-tool analysis, more specifically on mathematical models that allow the calculation of tractive effort for symmetric and narrow tools. Two of the main soils of Rio Grande do Sul, an Albaqualf and a Paleudult were studied. Equations that relate the cohesion, internal friction angle of the soil, adhesion, soil-tool friction angle and pre-compression stress as a function of water content in the soil were obtained, leading to important information for use of mathematical models for tractive effort calculation.

Prediction of free-stall occupancy rate in dairycattle barns through fuzzy sets

The goal of this study was to develop a fuzzy model to predict the occupancy rate of free-stalls facilities of dairy cattle, aiding to optimize the design of projects. The following input variables were defined for the development of the fuzzy system: dry bulb temperature (Tdb, °C), wet bulb temperature (Twb, °C) and black globe temperature (Tbg, °C). Based on the input variables, the fuzzy system predicts the occupancy rate (OR, %) of dairy cattle in free-stall barns. For the model validation, data collecting were conducted on the facilities of the Intensive System of Milk Production (SIPL), in the Dairy Cattle National Research Center (CNPGL) of Embrapa. The OR values, estimated by the fuzzy system, presented values of average standard deviation of 3.93%, indicating low rate of errors in the simulation. Simulated and measured results were statistically equal (P>0.05, t Test). After validating the proposed model, the average percentage of correct answers for the simulated data was 89.7%. Therefore, the fuzzy system developed for the occupancy rate prediction of free-stalls facilities for dairy cattle allowed a realistic prediction of stalls occupancy rate, allowing the planning and design of free-stall barns.

Magnetic susceptibility in the prediction of soil attributes in two sugarcane harvesting management systems

This study aimed to investigate the potential use of magnetic susceptibility (MS) as pedotransfer function to predict soil attributes under two sugarcane harvesting management systems. For each area of 1 ha (one with green sugarcane mechanized harvesting and other one with burnt sugarcane manual harvesting), 126 soil samples were collected and subjected to laboratory analysis to determine soil physical, chemical and mineralogical attributes and for measuring of MS. Data were submitted to descriptive statistics by calculating the mean and coefficient of variation. In order to compare the means in the different harvesting management systems it was carried out the Tukey test at a significance level of 5%. In order to investigate the correlation of the MS with other soil properties it was made the correlation test and aiming to assess how the MS contributes to the prediction of soil complex attributes it was made the multiple linear regressions. The results demonstrate that MS showed, in both sugarcane harvesting management systems, statistical correlation with chemical, physical and mineralogical soil attributes and it also showed potential to be used as pedotransfer function to predict attributes of the studied oxisol.

Bankruptcy prediction using fuzzy methods

In this thesis, a classi cation problem in predicting credit worthiness of a customer is tackled. This is done by proposing a reliable classi cation procedure on a given data set. The aim of this thesis is to design a model that gives the best classi cation accuracy to e ectively predict bankruptcy. FRPCA techniques proposed by Yang and Wang have been preferred since they are tolerant to certain type of noise in the data. These include FRPCA1, FRPCA2 and FRPCA3 from which the best method is chosen. Two di erent approaches are used at the classi cation stage: Similarity classi er and FKNN classi er. Algorithms are tested with Australian credit card screening data set. Results obtained indicate a mean classi cation accuracy of 83.22% using FRPCA1 with similarity classi- er. The FKNN approach yields a mean classi cation accuracy of 85.93% when used with FRPCA2, making it a better method for the suitable choices of the number of nearest neighbors and fuzziness parameters. Details on the calibration of the fuzziness parameter and other parameters associated with the similarity classi er are discussed.

Uterine Doppler velocimetry of the uterine arteries in the second and third trimesters for the prediction of gestational outcome

PURPOSE: The aim of this longitudinal study was to investigate the value of uterine artery Doppler sonography during the second and third trimesters in the prediction of adverse pregnancy outcome in low-risk women. METHODS: From July 2011 to August 2012, a total of 205 singleton pregnant women presenting at our antenatal clinic were enrolled in this prospective study and were assessed for baseline demographic and obstetric data. They underwent ultrasound evaluation at the time of second and third trimesters, both included Doppler assessment of bilateral uterine arteries to determine the values of the pulsatility index (PI) and resistance index (RI) and presence of early diastolic notch. The endpoint of this study was assessing the sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of Doppler ultrasonography of the uterine artery, for the prediction of adverse pregnancy outcomes including preeclampsia, stillbirth, placental abruption and preterm labor. RESULTS: The mean age of cases was 26.4±5.11. The uterine artery PI and RI values for both second (PI: 1.1±0.42 versus 1.53±0.59, p=0.002; RI: 0.55±0.09 versus 0.72±0.13, p=0.000 respectively) and third-trimester (PI: 0.77±0.31 versus 1.09±0.46, p=0.000; RI: 0.46±0.10 versus 0.60±0.14, p=0.010 respectively) evaluations were significantly higher in patients with adverse pregnancy outcome than in normal women. Combination of PI and RI >95th percentile and presence of bilateral notch in second trimester get sensitivity and specificity of 36.1 and 97% respectively, while these measures were 57.5 and 98.2% in third trimester. CONCLUSIONS: According to our study, it seems that uterine artery Doppler may be a valuable tool for the prediction of a variety of adverse outcomes in second and third trimesters.

Criteria for prediction of metastatic axillary lymph nodes in early-stage breast cancer

PURPOSE: To estimate the likelihood of axillary lymph node involvement for patients with early-stage breast cancer, based on a variety of clinical and pathological factors. METHODS: A retrospective analysis was done in hospital databases from 1999 to 2007. Two hundred thirty-nine patients were diagnosed with early-stage breast cancer. Predictive factors, such as patient age, tumor size, lymphovascular invasion, histological grade and immunohistochemical subtype were analyzed to identify variables that may be associated with axillary lymph node metastasis. RESULTS: Patients with tumors that are negative for estrogen receptor, progesterone receptor, and HER2 had approximately a 90% lower chance of developing lymph node metastasis than those with luminal A tumors (e.g., ER+ and/or PR+ and HER2-) - Odds Ratio: 0.11; 95% confidence interval: 0.01-0.88; p=0.01. Furthermore, the risk for lymph node metastasis of luminal A tumors seemed to decrease as patient age increased, and it was directly correlated with tumor size. CONCLUSION: The molecular classification of early-stage breast cancer using immunohistochemistry may help predicting the probability of developing axillary lymph node metastasis. Further studies are needed to optimize predictions for nodal involvement, with the aim of aiding the decision-making process for breast cancer treatment.

Prediction of 3D structure and ligand-binding properties : ABC transporters and flavodiiron proteins from Synechocystis sp. strain PCC 6803

Cyanobacteria are unicellular, non-nitrogen-fixing prokaryotes, which perform photosynthesis similarly as higher plants. The cyanobacterium Synechocystis sp. strain PCC 6803 is used as a model organism in photosynthesis research. My research described herein aims at understanding the function of the photosynthetic machinery and how it responds to changes in the environment. Detailed knowledge of the regulation of photosynthesis in cyanobacteria can be utilized for biotechnological purposes, for example in the harnessing of solar energy for biofuel production. In photosynthesis, iron participates in electron transfer. Here, we focused on iron transport in Synechocystis sp. strain PCC 6803 and particularly on the environmental regulation of the genes encoding the FutA2BC ferric iron transporter, which belongs to the ABC transporter family. A homology model built for the ATP-binding subunit FutC indicates that it has a functional ATPbinding site as well as conserved interactions with the channel-forming subunit FutB in the transporter complex. Polyamines are important for the cell proliferation, differentiation and apoptosis in prokaryotic and eukaryotic cells. In plants, polyamines have special roles in stress response and in plant survival. The polyamine metabolism in cyanobacteria in response to environmental stress is of interest in research on stress tolerance of higher plants. In this thesis, the potd gene encoding an polyamine transporter subunit from Synechocystis sp. strain PCC 6803 was characterized for the first time. A homology model built for PotD protein indicated that it has capability of binding polyamines, with the preference for spermidine. Furthermore, in order to investigate the structural features of the substrate specificity, polyamines were docked into the binding site. Spermidine was positioned very similarly in Synechocystis PotD as in the template structure and had most favorable interactions of the docked polyamines. Based on the homology model, experimental work was conducted, which confirmed the binding preference. Flavodiiron proteins (Flv) are enzymes, which protect the cell against toxicity of oxygen and/or nitric oxide by reduction. In this thesis, we present a novel type of photoprotection mechanism in cyanobacteria by the heterodimer of Flv2/Flv4. The constructed homology model of Flv2/Flv4 suggests a functional heterodimer capable of rapid electron transfer. The unknown protein sll0218, encoded by the flv2-flv4 operon, is assumed to facilitate the interaction of the Flv2/Flv4 heterodimer and energy transfer between the phycobilisome and PSII. Flv2/Flv4 provides an alternative electron transfer pathway and functions as an electron sink in PSII electron transfer.

Prediction of transients and control reactions in a transonic wind tunnel

This work describes a lumped parameter mathematical model for the prediction of transients in an aerodynamic circuit of a transonic wind tunnel. Control actions to properly handle those perturbations are also assessed. The tunnel circuit technology is up to date and incorporates a novel feature: high-enthalpy air injection to extend the tunnel’s Reynolds number capability. The model solves the equations of continuity, energy and momentum and defines density, internal energy and mass flow as the basic parameters in the aerodynamic study as well as Mach number, stagnation pressure and stagnation temperature, all referred to test section conditions, as the main control variables. The tunnel circuit response to control actions and the stability of the flow are numerically investigated. Initially, for validation purposes, the code was applied to the AWT ("Altitude Wind Tunnel" of NASA-Lewis). In the sequel, the Brazilian transonic wind tunnel was investigated, with all the main control systems modeled, including injection.

Solution of aerospace problems using structured and unstructured strategies

Products developed at industries, institutes and research centers are expected to have high level of quality and performance, having a minimum waste, which require efficient and robust tools to numerically simulate stringent project conditions with great reliability. In this context, Computational Fluid Dynamics (CFD) plays an important role and the present work shows two numerical algorithms that are used in the CFD community to solve the Euler and Navier-Stokes equations applied to typical aerospace and aeronautical problems. Particularly, unstructured discretization of the spatial domain has gained special attention by the international community due to its ease in discretizing complex spatial domains. This work has the main objective of illustrating some advantages and disadvantages of numerical algorithms using structured and unstructured spatial discretization of the flow governing equations. Numerical methods include a finite volume formulation and the Euler and Navier-Stokes equations are applied to solve a transonic nozzle problem, a low supersonic airfoil problem and a hypersonic inlet problem. In a structured context, these problems are solved using MacCormack’s implicit algorithm with Steger and Warming’s flux vector splitting technique, while, in an unstructured context, Jameson and Mavriplis’ explicit algorithm is used. Convergence acceleration is obtained using a spatially variable time stepping procedure.

Business intelligence viewpoint on managerial decision-making : Ill-structured problems and decision support systems

Vaikka liiketoimintatiedon hallintaa sekä johdon päätöksentekoa on tutkittu laajasti, näiden kahden käsitteen yhteisvaikutuksesta on olemassa hyvin rajallinen määrä tutkimustietoa. Tulevaisuudessa aiheen tärkeys korostuu, sillä olemassa olevan datan määrä kasvaa jatkuvasti. Yritykset tarvitsevat jatkossa yhä enemmän kyvykkyyksiä sekä resursseja, jotta sekä strukturoitua että strukturoimatonta tietoa voidaan hyödyntää lähteestä riippumatta. Nykyiset Business Intelligence -ratkaisut mahdollistavat tehokkaan liiketoimintatiedon hallinnan osana johdon päätöksentekoa. Aiemman kirjallisuuden pohjalta, tutkimuksen empiirinen osuus tunnistaa liiketoimintatiedon hyödyntämiseen liittyviä tekijöitä, jotka joko tukevat tai rajoittavat johdon päätöksentekoprosessia. Tutkimuksen teoreettinen osuus johdattaa lukijan tutkimusaiheeseen kirjallisuuskatsauksen avulla. Keskeisimmät tutkimukseen liittyvät käsitteet, kuten Business Intelligence ja johdon päätöksenteko, esitetään relevantin kirjallisuuden avulla – tämän lisäksi myös dataan liittyvät käsitteet analysoidaan tarkasti. Tutkimuksen empiirinen osuus rakentuu tutkimusteorian pohjalta. Tutkimuksen empiirisessä osuudessa paneudutaan tutkimusteemoihin käytännön esimerkein: kolmen tapaustutkimuksen avulla tutkitaan sekä kuvataan toisistaan irrallisia tapauksia. Jokainen tapaus kuvataan sekä analysoidaan teoriaan perustuvien väitteiden avulla – nämä väitteet ovat perusedellytyksiä menestyksekkäälle liiketoimintatiedon hyödyntämiseen perustuvalle päätöksenteolle. Tapaustutkimusten avulla alkuperäistä tutkimusongelmaa voidaan analysoida tarkasti huomioiden jo olemassa oleva tutkimustieto. Analyysin tulosten avulla myös yksittäisiä rajoitteita sekä mahdollistavia tekijöitä voidaan analysoida. Tulokset osoittavat, että rajoitteilla on vahvasti negatiivinen vaikutus päätöksentekoprosessin onnistumiseen. Toisaalta yritysjohto on tietoinen liiketoimintatiedon hallintaan liittyvistä positiivisista seurauksista, vaikka kaikkia mahdollisuuksia ei olisikaan hyödynnetty. Tutkimuksen merkittävin tulos esittelee viitekehyksen, jonka puitteissa johdon päätöksentekoprosesseja voidaan arvioida sekä analysoida. Despite the fact that the literature on Business Intelligence and managerial decision-making is extensive, relatively little effort has been made to research the relationship between them. This particular field of study has become important since the amount of data in the world is growing every second. Companies require capabilities and resources in order to utilize structured data and unstructured data from internal and external data sources. However, the present Business Intelligence technologies enable managers to utilize data effectively in decision-making. Based on the prior literature, the empirical part of the thesis identifies the enablers and constraints in computer-aided managerial decision-making process. In this thesis, the theoretical part provides a preliminary understanding about the research area through a literature review. The key concepts such as Business Intelligence and managerial decision-making are explored by reviewing the relevant literature. Additionally, different data sources as well as data forms are analyzed in further detail. All key concepts are taken into account when the empirical part is carried out. The empirical part obtains an understanding of the real world situation when it comes to the themes that were covered in the theoretical part. Three selected case companies are analyzed through those statements, which are considered as critical prerequisites for successful computer-aided managerial decision-making. The case study analysis, which is a part of the empirical part, enables the researcher to examine the relationship between Business Intelligence and managerial decision-making. Based on the findings of the case study analysis, the researcher identifies the enablers and constraints through the case study interviews. The findings indicate that the constraints have a highly negative influence on the decision-making process. In addition, the managers are aware of the positive implications that Business Intelligence has for decision-making, but all possibilities are not yet utilized. As a main result of this study, a data-driven framework for managerial decision-making is introduced. This framework can be used when the managerial decision-making processes are evaluated and analyzed.

Linear prediction in optical spectroscopy

A linear prediction procedure is one of the approved numerical methods of signal processing. In the field of optical spectroscopy it is used mainly for extrapolation known parts of an optical signal in order to obtain a longer one or deduce missing signal samples. The first is needed particularly when narrowing spectral lines for the purpose of spectral information extraction. In the present paper the coherent anti-Stokes Raman scattering (CARS) spectra were under investigation. The spectra were significantly distorted by the presence of nonlinear nonresonant background. In addition, line shapes were far from Gaussian/Lorentz profiles. To overcome these disadvantages the maximum entropy method (MEM) for phase spectrum retrieval was used. The obtained broad MEM spectra were further underwent the linear prediction analysis in order to be narrowed.

Prediction of market switching and delisting events from OMX First North Nordic multilateral stock exchange

This thesis studies the predictability of market switching and delisting events from OMX First North Nordic multilateral stock exchange by using financial statement information and market information from 2007 to 2012. This study was conducted by using a three stage process. In first stage relevant theoretical framework and initial variable pool were constructed. Then, explanatory analysis of the initial variable pool was done in order to further limit and identify relevant variables. The explanatory analysis was conducted by using self-organizing map methodology. In the third stage, the predictive modeling was carried out with random forests and support vector machine methodologies. It was found that the explanatory analysis was able to identify relevant variables. The results indicate that the market switching and delisting events can be predicted in some extent. The empirical results also support the usability of financial statement and market information in the prediction of market switching and delisting events.

Warranty Prediction Using Weibull Simulation

The main objective of this master’s thesis is to examine if Weibull analysis is suitable method for warranty forecasting in the Case Company. The Case Company has used Reliasoft’s Weibull++ software, which is basing on the Weibull method, but the Company has noticed that the analysis has not given right results. This study was conducted making Weibull simulations in different profit centers of the Case Company and then comparing actual cost and forecasted cost. Simula-tions were made using different time frames and two methods for determining future deliveries. The first sub objective is to examine, which parameters of simulations will give the best result to each profit center. The second sub objective of this study is to create a simple control model for following forecasted costs and actual realized costs. The third sub objective is to document all Qlikview-parameters of profit centers. This study is a constructive research, and solutions for company’s problems are figured out in this master’s thesis. In the theory parts were introduced quality issues, for example; what is quality, quality costing and cost of poor quality. Quality is one of the major aspects in the Case Company, so understand-ing the link between quality and warranty forecasting is important. Warranty management was also introduced and other different tools for warranty forecasting. The Weibull method and its mathematical properties and reliability engineering were introduced. The main results of this master’s thesis are that the Weibull analysis forecasted too high costs, when calculating provision. Although, some forecasted values of profit centers were lower than actual values, the method works better for planning purposes. One of the reasons is that quality improving or alternatively quality decreasing is not showing in the results of the analysis in the short run. The other reason for too high values is that the products of the Case Company are com-plex and analyses were made in the profit center-level. The Weibull method was developed for standard products, but products of the Case Company consists of many complex components. According to the theory, this method was developed for homogeneous-data. So the most im-portant notification is that the analysis should be made in the product level, not the profit center level, when the data is more homogeneous.