Combine to compete: improving fiscal forecast accuracy over time

Budget forecasts have become increasingly important as a tool of fiscal management to influence expectations of bond markets and the public at large. The inherent difficulty in projecting macroeconomic variables – together with political bias – thwart the accuracy of budget forecasts. We improve accuracy by combining the forecasts of both private and public agencies for Italy over the period 1993-2012. A weighted combined forecast of the deficit/ ratio is superior to any single forecast. Deficits are hard to predict due to shifting economic conditions and political events. We test and compare predictive accuracy over time and although a weighted combined forecast is robust to breaks, there is no significant improvement over a simple RW model.

Combine to compete: improving fiscal forecast accuracy over time

Budget forecasts have become increasingly important as a tool of fiscal management to influence expectations of bond markets and the public at large. The inherent difficulty in projecting macroeconomic variables – together with political bias – thwart the accuracy of budget forecasts. We improve accuracy by combining the forecasts of both private and public agencies for Italy over the period 1993-2012. A weighted combined forecast of the deficit/ ratio is superior to any single forecast. Deficits are hard to predict due to shifting economic conditions and political events. We test and compare predictive accuracy over time and although a weighted combined forecast is robust to breaks, there is no significant improvement over a simple RW model.

Delivery Reliability: Timely and Quantitative Accuracy in a Forest Industry Company

The primary objective of this thesis was to research delivery reliability of mill business unit of a forest industry company, especially timely and quantitative accuracy of sales orders. Delivery reliability is an important factor of customer satisfaction, which has a great influence for success of a company. The secondary objective was to find out reasons for possible problems of delivery reliability and give propositions for improvable performances. The empirical part of the thesis based on reporting database of the forest industry company’s ERP-software and detailed information of the mill system. The delivery reliability results of the mill business unit were compared to delivery reliability of similar mill business unit inside the forest industry company. The research results expressed problems in the supply chain. The delivery reliability reporting should be also developed further. This would advance delivery reliability monitoring. The improvement propositions of the thesis were logistic operation mode estimation, particular benchmarking of the compared mill business unit and more detailed survey on production delivery reliability.

Speaker diarization: Segmentation and clustering of speeches

Speaker diarization is the process of sorting speeches according to the speaker. Diarization helps to search and retrieve what a certain speaker uttered in a meeting. Applications of diarization systemsextend to other domains than meetings, for example, lectures, telephone, television, and radio. Besides, diarization enhances the performance of several speech technologies such as speaker recognition, automatic transcription, and speaker tracking. Methodologies previously used in developing diarization systems are discussed. Prior results and techniques are studied and compared. Methods such as Hidden Markov Models and Gaussian Mixture Models that are used in speaker recognition and other speech technologies are also used in speaker diarization. The objective of this thesis is to develop a speaker diarization system in meeting domain. Experimental part of this work indicates that zero-crossing rate can be used effectively in breaking down the audio stream into segments, and adaptive Gaussian Models fit adequately short audio segments. Results show that 35 Gaussian Models and one second as average length of each segment are optimum values to build a diarization system for the tested data. Uniting the segments which are uttered by same speaker is done in a bottom-up clustering by a newapproach of categorizing the mixture weights.

Accuracy and efficiency evaluation of point-centered quarter method variations for vegetation sampling in an araucaria forest

In order to verify Point-Centered Quarter Method (PCQM) accuracy and efficiency, using different numbers of individuals by per sampled area, in 28 quarter points in an Araucaria forest, southern Paraná, Brazil. Three variations of the PCQM were used for comparison associated to the number of sampled individual trees: standard PCQM (SD-PCQM), with four sampled individuals by point (one in each quarter), second measured (VAR1-PCQM), with eight sampled individuals by point (two in each quarter), and third measuring (VAR2-PCQM), with 16 sampled individuals by points (four in each quarter). Thirty-one species of trees were recorded by the SD-PCQM method, 48 by VAR1-PCQM and 60 by VAR2-PCQM. The level of exhaustiveness of the vegetation census and diversity index showed an increasing number of individuals considered by quadrant, indicating that VAR2-PCQM was the most accurate and efficient method when compared with VAR1-PCQM and SD-PCQM.

Management zones using fuzzy clustering based on spatial-temporal variability of soil and corn yield

Clustering soil and crop data can be used as a basis for the definition of management zones because the data are grouped into clusters based on the similar interaction of these variables. Therefore, the objective of this study was to identify management zones using fuzzy c-means clustering analysis based on the spatial and temporal variability of soil attributes and corn yield. The study site (18 by 250-m in size) was located in Jaboticabal, São Paulo/Brazil. Corn yield was measured in one hundred 4.5 by 10-m cells along four parallel transects (25 observations per transect) over five growing seasons between 2001 and 2010. Soil chemical and physical attributes were measured. SAS procedure MIXED was used to identify which variable(s) most influenced the spatial variability of corn yield over the five study years. Basis saturation (BS) was the variable that better related to corn yield, thus, semivariograms models were fitted for BS and corn yield and then, data values were krigged. Management Zone Analyst software was used to carry out the fuzzy c-means clustering algorithm. The optimum number of management zones can change over time, as well as the degree of agreement between the BS and corn yield management zone maps. Thus, it is very important take into account the temporal variability of crop yield and soil attributes to delineate management zones accurately.

Percutaneous core biopsy of palpable breast lesions: accuracy of frozen section histopathological exam in the diagnosis of breast cancer

OBJECTIVE: to evaluate the accuracy of frozen section histopathology from fragments of tissue obtained by percutaneous core needle biopsy of palpable tumors in the diagnosis of breast cancer. METHODS: a cohort study was performed on 57 patients with palpable tumors and suspected breast cancer undergoing percutaneous thick needle core biopsy. The fragments were analyzed by the same pathologist. RESULTS: frozen section diagnosed 16 benign cases (28.6%) and 40 malignant (71.4%), whereas paraffin showed that 15 were benign (26.8%) and 41 malignant (73.2%). Histopathological examinations were concordant in 55 cases and there was one false-negative (6.2%). Statistics rates were: negative predictive value of 93.8%, positive predictive value of 100%, no false-positive (0%), one false negative (6.2%), specificity of 100%, sensitivity of 97 6%; observed agreement = 98.2%; expected agreement = 59.9%, Kappa = 0.955 [ 95% CI = 0.925-0.974, p < 0.01 ]. CONCLUSIONS: frozen section histopathological findings showed excellent correlation with the findings by the technique in paraffin in the fragments of palpable breast tumors obtained by thick needle percutaneous core biopsy (98.2% accuracy). Therefore, in these patients, it was possible to anticipate the diagnosis, staging and the breast cancer treatment planning.

Accuracy of sonography and hysteroscopy in the diagnosis of premalignant and malignant polyps in postmenopausal women

PURPOSE: To evaluate the accuracy of sonographic endometrial thickness and hysteroscopic characteristics in predicting malignancy in postmenopausal women undergoing surgical resection of endometrial polyps. METHODS: Five hundred twenty-one (521) postmenopausal women undergoing hysteroscopic resection of endometrial polyps between January 1998 and December 2008 were studied. For each value of sonographic endometrial thickness and polyp size on hysteroscopy, the sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) were calculated in relation to the histologic diagnosis of malignancy. The best values of sensitivity and specificity for the diagnosis of malignancy were determined by the Receiver Operating Characteristic (ROC) curve. RESULTS: Histologic diagnosis identified the presence of premalignancy or malignancy in 4.1% of cases. Sonographic measurement revealed a greater endometrial thickness in cases of malignant polyps when compared to benign and premalignant polyps. On surgical hysteroscopy, malignant endometrial polyps were also larger. An endometrial thickness of 13 mm showed a sensitivity of 69.6%, specificity of 68.5%, PPV of 9.3%, and NPV of 98% in predicting malignancy in endometrial polyps. Polyp measurement by hysteroscopy showed that for polyps 30 mm in size, the sensitivity was 47.8%, specificity was 66.1%, PPV was 6.1%, and NPV was 96.5% for predicting cancer. CONCLUSIONS: Sonographic endometrial thickness showed a higher level of accuracy than hysteroscopic measurement in predicting malignancy in endometrial polyps. Despite this, both techniques showed low accuracy for predicting malignancy in endometrial polyps in postmenopausal women. In suspected cases, histologic evaluation is necessary to exclude malignancy.

Accuracy Analysis of Frequency Converter Estimates in Diagnostic Applications

Transportation of fluids is one of the most common and energy intensive processes in the industrial and HVAC sectors. Pumping systems are frequently subject to engineering malpractice when dimensioned, which can lead to poor operational efficiency. Moreover, pump monitoring requires dedicated measuring equipment, which imply costly investments. Inefficient pump operation and improper maintenance can increase energy costs substantially and even lead to pump failure. A centrifugal pump is commonly driven by an induction motor. Driving the induction motor with a frequency converter can diminish energy consumption in pump drives and provide better control of a process. In addition, induction machine signals can also be estimated by modern frequency converters, dispensing with the use of sensors. If the estimates are accurate enough, a pump can be modelled and integrated into the frequency converter control scheme. This can open the possibility of joint motor and pump monitoring and diagnostics, thereby allowing the detection of reliability-reducing operating states that can lead to additional maintenance costs. The goal of this work is to study the accuracy of rotational speed, torque and shaft power estimates calculated by a frequency converter. Laboratory tests were performed in order to observe estimate behaviour in both steady-state and transient operation. An induction machine driven by a vector-controlled frequency converter, coupled with another induction machine acting as load was used in the tests. The estimated quantities were obtained through the frequency converter’s Trend Recorder software. A high-precision, HBM T12 torque-speed transducer was used to measure the actual values of the aforementioned variables. The effect of the flux optimization energy saving feature on the estimate quality was also studied. A processing function was developed in MATLAB for comparison of the obtained data. The obtained results confirm the suitability of this particular converter to provide accurate enough estimates for pumping applications.

Modeling, optimizing and simulating robot calibration with accuracy improvement

This work describes techniques for modeling, optimizing and simulating calibration processes of robots using off-line programming. The identification of geometric parameters of the nominal kinematic model is optimized using techniques of numerical optimization of the mathematical model. The simulation of the actual robot and the measurement system is achieved by introducing random errors representing their physical behavior and its statistical repeatability. An evaluation of the corrected nominal kinematic model brings about a clear perception of the influence of distinct variables involved in the process for a suitable planning, and indicates a considerable accuracy improvement when the optimized model is compared to the non-optimized one.

Accuracy of modelling and identification of malfunctions in rotor systems: experimental results

The accuracy of modelling of rotor systems composed of rotors, oil film bearings and a flexible foundation, is evaluated and discussed in this paper. The model validation of different models has been done by comparing experimental results with numerical results by means. The experimental data have been obtained with a fully instrumented four oil film bearing, two shafts test rig. The fault models are then used in the frame of a model based malfunction identification procedure, based on a least square fitting approach applied in the frequency domain. The capability of distinguishing different malfunctions has been investigated, even if they can create similar effects (such as unbalance, rotor bow, coupling misalignment and others) from shaft vibrations measured in correspondence of the bearings.

Online peer to peer lending: clustering borrowers using self-organizing maps

The purpose of this thesis is to find out whether all the peer to peer lenders are unworthy of credit and also if there are single qualities or combinations of qualities that determine the probability of default of a person or group of people. Distinguishing qualities are searched with self-organizing maps (SOM). Qualities and groups of people found by the self-organizing map are then compared to the average. The comparison is carried out by looking how big proportion of borrowers meeting the criteria is two months or more behind with their payments. Research data used is collected by an Estonian peer to peer lending company during the years of 2011-2014. Data consists of peer to peer borrowers and information gathered from them.

Accuracy of replication in the polymerase chain reaction. Comparison between Thermotoga maritima DNA polymerase and Thermus aquaticus DNA polymerase

For certain applications of the polymerase chain reaction (PCR), it may be necessary to consider the accuracy of replication. The breakthrough that made PCR user friendly was the commercialization of Thermus aquaticus (Taq) DNA polymerase, an enzyme that would survive the high temperatures needed for DNA denaturation. The development of enzymes with an inherent 3' to 5' exonuclease proofreading activity, lacking in Taq polymerase, would be an improvement when higher fidelity is needed. We used the forward mutation assay to compare the fidelity of Taq polymerase and Thermotoga maritima (ULTMA™) DNA polymerase, an enzyme that does have proofreading activity. We did not find significant differences in the fidelity of either enzyme, even when using optimal buffer conditions, thermal cycling parameters, and number of cycles (0.2% and 0.13% error rates for ULTMA™ and Taq, respectively, after reading about 3,000 bases each). We conclude that for sequencing purposes there is no difference in using a DNA polymerase that contains an inherent 3' to 5' exonuclease activity for DNA amplification. Perhaps the specificity and fidelity of PCR are complex issues influenced by the nature of the target sequence, as well as by each PCR component.