994 resultados para Motion classification


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Production machines for next generation LSIs such as 4G-DRAMs and for large liquid crystal displays such as 0.5mx0.5m size, and information equipment such as magnetic hard disks and DVDs must have the positioning accuracy of a nano-meter order. To realize such a high degree of the positioning accuracy, not only precision machine elements and mechanisms but also high precision sensors, actuators and controller design techniques becomes crucial. This paper introduces recent topics of precision positioning and motion control technology in Japan.

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In this work, image based estimation methods, also known as direct methods, are studied which avoid feature extraction and matching completely. Cost functions use raw pixels as measurements and the goal is to produce precise 3D pose and structure estimates. The cost functions presented minimize the sensor error, because measurements are not transformed or modified. In photometric camera pose estimation, 3D rotation and translation parameters are estimated by minimizing a sequence of image based cost functions, which are non-linear due to perspective projection and lens distortion. In image based structure refinement, on the other hand, 3D structure is refined using a number of additional views and an image based cost metric. Image based estimation methods are particularly useful in conditions where the Lambertian assumption holds, and the 3D points have constant color despite viewing angle. The goal is to improve image based estimation methods, and to produce computationally efficient methods which can be accomodated into real-time applications. The developed image-based 3D pose and structure estimation methods are finally demonstrated in practise in indoor 3D reconstruction use, and in a live augmented reality application.

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Työssä käydään läpi tukivektorikoneiden teoreettista pohjaa sekä tutkitaan eri parametrien vaikutusta spektridatan luokitteluun.

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This thesis studies the development of service offering model that creates added-value for customers in the field of logistics services. The study focusses on offering classification and structures of model. The purpose of model is to provide value-added solutions for customers and enable superior service experience. The aim of thesis is to define what customers expect from logistics solution provider and what value customers appreciate so greatly that they could invest in value-added services. Value propositions, costs structures of offerings and appropriate pricing methods are studied. First, literature review of creating solution business model and customer value is conducted. Customer value is found out with customer interviews and qualitative empiric data is used. To exploit expertise knowledge of logistics, innovation workshop tool is utilized. Customers and experts are involved in the design process of model. As a result of thesis, three-level value-added service offering model is created based on empiric and theoretical data. Offerings with value propositions are proposed and the level of model reflects the deepness of customer-provider relationship and the amount of added value. Performance efficiency improvements and cost savings create the most added value for customers. Value-based pricing methods, such as performance-based models are suggested to apply. Results indicate the interest of benefitting networks and partnership in field of logistics services. Networks development is proposed to be investigated further.

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The predominant type of liver alteration in asymptomatic or oligosymptomatic chronic male alcoholics (N = 169) admitted to a psychiatric hospital for detoxification was classified by two independent methods: liver palpation and multiple quadratic discriminant analysis (QDA), the latter applied to two parameters reported by the patient (duration of alcoholism and daily amount ingested) and to the data obtained from eight biochemical blood determinations (total bilirubin, alkaline phosphatase, glycemia, potassium, aspartate aminotransferase, albumin, globulin, and sodium). All 11 soft and sensitive, and 13 firm and sensitive livers formed fully concordant groups as determined by QDA. Among the 22 soft and not sensitive livers, 95% were concordant by QDA grouping. Concordance rates were low (55%) in the 73 firm and not sensitive livers, and intermediate (76%) in the 50 not palpable livers. Prediction of the liver palpation characteristics by QDA was 95% correct for the firm and not sensitive livers and moderate for the other groups. On a preliminary basis, the variables considered to be most informative by QDA were the two anamnestic data and bilirubin levels, followed by alkaline phosphatase, glycemia and potassium, and then by aspartate aminotransferase and albumin. We conclude that, when biopsies would be too costly or potentially injurious to the patients to varying extents, clinical data could be considered valid to guide patient care, at least in the three groups (soft, not sensitive; soft, sensitive; firm, sensitive livers) in which the two noninvasive procedures were highly concordant in the present study.

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The objective of the present study was to evaluate incentive spirometers using volume- (Coach and Voldyne) and flow-oriented (Triflo II and Respirex) devices. Sixteen healthy subjects, 24 ± 4 years, 62 ± 12 kg, were studied. Respiratory variables were obtained by respiratory inductive plethysmography, with subjects in a semi-reclined position (45º). Tidal volume, respiratory frequency, minute ventilation, inspiratory duty cycle, mean inspiratory flow, and thoracoabdominal motion were measured. Statistical analysis was performed with Kolmogorov-Smirnov test, t-test and ANOVA. Comparison between the Coach and Voldyne devices showed that larger values of tidal volume (1035 ± 268 vs 947 ± 268 ml, P = 0.02) and minute ventilation (9.07 ± 3.61 vs 7.49 ± 2.58 l/min, P = 0.01) were reached with Voldyne, whereas no significant differences in respiratory frequency were observed (7.85 ± 1.24 vs 8.57 ± 1.89 bpm). Comparison between flow-oriented devices showed larger values of inspiratory duty cycle and lower mean inspiratory flow with Triflo II (0.35 ± 0.05 vs 0.32 ± 0.05 ml/s, P = 0.00, and 531 ± 137 vs 606 ± 167 ml/s, P = 0.00, respectively). Abdominal motion was larger (P < 0.05) during the use of volume-oriented devices compared to flow-oriented devices (52 ± 11% for Coach and 50 ± 9% for Voldyne; 43 ± 13% for Triflo II and 44 ± 14% for Respirex). We observed that significantly higher tidal volume associated with low respiratory frequency was reached with Voldyne, and that there was a larger abdominal displacement with volume-oriented devices.

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The present study describes an auxiliary tool in the diagnosis of left ventricular (LV) segmental wall motion (WM) abnormalities based on color-coded echocardiographic WM images. An artificial neural network (ANN) was developed and validated for grading LV segmental WM using data from color kinesis (CK) images, a technique developed to display the timing and magnitude of global and regional WM in real time. We evaluated 21 normal subjects and 20 patients with LVWM abnormalities revealed by two-dimensional echocardiography. CK images were obtained in two sets of viewing planes. A method was developed to analyze CK images, providing quantitation of fractional area change in each of the 16 LV segments. Two experienced observers analyzed LVWM from two-dimensional images and scored them as: 1) normal, 2) mild hypokinesia, 3) moderate hypokinesia, 4) severe hypokinesia, 5) akinesia, and 6) dyskinesia. Based on expert analysis of 10 normal subjects and 10 patients, we trained a multilayer perceptron ANN using a back-propagation algorithm to provide automated grading of LVWM, and this ANN was then tested in the remaining subjects. Excellent concordance between expert and ANN analysis was shown by ROC curve analysis, with measured area under the curve of 0.975. An excellent correlation was also obtained for global LV segmental WM index by expert and ANN analysis (R² = 0.99). In conclusion, ANN showed high accuracy for automated semi-quantitative grading of WM based on CK images. This technique can be an important aid, improving diagnostic accuracy and reducing inter-observer variability in scoring segmental LVWM.

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Recent data from our laboratory have shown that patients with the indeterminate form of Chagas' disease can have impairment of left ventricular contractility, as evaluated by the slope of the left ventricle end-systolic pressure-dimension relationship. We also showed that Chagas' disease patients with minimal baseline wall motion abnormalities detected by two-dimensional echocardiography have more intense contractility impairment when compared to patients with the indeterminate form of the disease without this abnormality. The prognostic implications of these findings have not been established. We evaluated 59 patients (37-76 years, mean = 55 years) with different clinical forms of Chagas' disease, who had normal left ventricular global systolic function at baseline (57.6 ± 6.9%) and who had at least one additional echo during clinical follow-up (0.4-17.6; mean 4.6 years). Group 1 consisted of 14 patients with minor baseline left ventricle wall motion abnormalities and group 2 consisted of 45 patients without these abnormalities. During follow-up, global left ventricle systolic function deterioration was observed in 10 group 1 patients (71.4%) and in only 10 group 2 patients (22.2%; P < 0.005). Age and duration of follow-up were not independent determinants of left ventricular function deterioration in these patients. The present data indicate that mild segmental left ventricular wall motion abnormalities are associated with worsening of systolic function in Chagas' disease patients who have normal baseline global systolic performance.

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The objective of this thesis is to develop and generalize further the differential evolution based data classification method. For many years, evolutionary algorithms have been successfully applied to many classification tasks. Evolution algorithms are population based, stochastic search algorithms that mimic natural selection and genetics. Differential evolution is an evolutionary algorithm that has gained popularity because of its simplicity and good observed performance. In this thesis a differential evolution classifier with pool of distances is proposed, demonstrated and initially evaluated. The differential evolution classifier is a nearest prototype vector based classifier that applies a global optimization algorithm, differential evolution, to determine the optimal values for all free parameters of the classifier model during the training phase of the classifier. The differential evolution classifier applies the individually optimized distance measure for each new data set to be classified is generalized to cover a pool of distances. Instead of optimizing a single distance measure for the given data set, the selection of the optimal distance measure from a predefined pool of alternative measures is attempted systematically and automatically. Furthermore, instead of only selecting the optimal distance measure from a set of alternatives, an attempt is made to optimize the values of the possible control parameters related with the selected distance measure. Specifically, a pool of alternative distance measures is first created and then the differential evolution algorithm is applied to select the optimal distance measure that yields the highest classification accuracy with the current data. After determining the optimal distance measures for the given data set together with their optimal parameters, all determined distance measures are aggregated to form a single total distance measure. The total distance measure is applied to the final classification decisions. The actual classification process is still based on the nearest prototype vector principle; a sample belongs to the class represented by the nearest prototype vector when measured with the optimized total distance measure. During the training process the differential evolution algorithm determines the optimal class vectors, selects optimal distance metrics, and determines the optimal values for the free parameters of each selected distance measure. The results obtained with the above method confirm that the choice of distance measure is one of the most crucial factors for obtaining higher classification accuracy. The results also demonstrate that it is possible to build a classifier that is able to select the optimal distance measure for the given data set automatically and systematically. After finding optimal distance measures together with optimal parameters from the particular distance measure results are then aggregated to form a total distance, which will be used to form the deviation between the class vectors and samples and thus classify the samples. This thesis also discusses two types of aggregation operators, namely, ordered weighted averaging (OWA) based multi-distances and generalized ordered weighted averaging (GOWA). These aggregation operators were applied in this work to the aggregation of the normalized distance values. The results demonstrate that a proper combination of aggregation operator and weight generation scheme play an important role in obtaining good classification accuracy. The main outcomes of the work are the six new generalized versions of previous method called differential evolution classifier. All these DE classifier demonstrated good results in the classification tasks.

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The authors propose a clinical classification to monitor the evolution of tetanus patients, ranging from grade I to IV according to severity. It was applied on admission and repeated on alternate days up to the 10th day to patients aged > or = 12 years admitted to the State University Hospital, Recife, Brazil. Patients were also classified upon admission according to three prognostic indicators to determine if the proposed classification is in agreement with the traditionally used indicators. Upon admission, the distribution of the 64 patients among the different levels of the proposed classification was similar for the groups of better and worse prognosis according to the three indicators (P > 0.05), most of the patients belonging to grades I and II of the proposed classification. In the later reclassifications, severe forms of tetanus (grades III and IV) were more frequent in the categories of worse prognosis and these differences were statistically significant. There was a reduction in the proportion of mild forms (grades I and II) of tetanus with time for the categories of worse prognostic indicators (chi-square for trend: P = 0.00006, 0.03, and 0.00000) whereas no such trend was observed for the categories of better prognosis (grades I and II). This serially used classification reflected the prognosis of the traditional indicators and permitted the comparison of the dynamics of the disease in different groups. Thus, it becomes a useful tool for monitoring patients by determining clinical category changes with time, and for assessing responses to different therapeutic measures.

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The objective of the present study was to evaluate breathing pattern, thoracoabdominal motion and muscular activity during three breathing exercises: diaphragmatic breathing (DB), flow-oriented (Triflo II) incentive spirometry and volume-oriented (Voldyne) incentive spirometry. Seventeen healthy subjects (12 females, 5 males) aged 23 ± 5 years (mean ± SD) were studied. Calibrated respiratory inductive plethysmography was used to measure the following variables during rest (baseline) and breathing exercises: tidal volume (Vt), respiratory frequency (f), rib cage contribution to Vt (RC/Vt), inspiratory duty cycle (Ti/Ttot), and phase angle (PhAng). Sternocleidomastoid muscle activity was assessed by surface electromyography. Statistical analysis was performed by ANOVA and Tukey or Friedman and Wilcoxon tests, with the level of significance set at P < 0.05. Comparisons between baseline and breathing exercise periods showed a significant increase of Vt and PhAng during all exercises, a significant decrease of f during DB and Voldyne, a significant increase of Ti/Ttot during Voldyne, and no significant difference in RC/Vt. Comparisons among exercises revealed higher f and sternocleidomastoid activity during Triflo II (P < 0.05) with respect to DB and Voldyne, without a significant difference in Vt, Ti/Ttot, PhAng, or RC/Vt. Exercises changed the breathing pattern and increased PhAng, a variable of thoracoabdominal asynchrony, compared to baseline. The only difference between DB and Voldyne was a significant increase of Ti/Ttot compared to baseline. Triflo II was associated with higher f values and electromyographic activity of the sternocleidomastoid. In conclusion, DB and Voldyne showed similar results while Triflo II showed disadvantages compared to the other breathing exercises.

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Since the times preceding the Second World War the subject of aircraft tracking has been a core interest to both military and non-military aviation. During subsequent years both technology and configuration of the radars allowed the users to deploy it in numerous fields, such as over-the-horizon radar, ballistic missile early warning systems or forward scatter fences. The latter one was arranged in a bistatic configuration. The bistatic radar has continuously re-emerged over the last eighty years for its intriguing capabilities and challenging configuration and formulation. The bistatic radar arrangement is used as the basis of all the analyzes presented in this work. The aircraft tracking method of VHF Doppler-only information, developed in the first part of this study, is solely based on Doppler frequency readings in relation to time instances of their appearance. The corresponding inverse problem is solved by utilising a multistatic radar scenario with two receivers and one transmitter and using their frequency readings as a base for aircraft trajectory estimation. The quality of the resulting trajectory is then compared with ground-truth information based on ADS-B data. The second part of the study deals with the developement of a method for instantaneous Doppler curve extraction from within a VHF time-frequency representation of the transmitted signal, with a three receivers and one transmitter configuration, based on a priori knowledge of the probability density function of the first order derivative of the Doppler shift, and on a system of blocks for identifying, classifying and predicting the Doppler signal. The extraction capabilities of this set-up are tested with a recorded TV signal and simulated synthetic spectrograms. Further analyzes are devoted to more comprehensive testing of the capabilities of the extraction method. Besides testing the method, the classification of aircraft is performed on the extracted Bistatic Radar Cross Section profiles and the correlation between them for different types of aircraft. In order to properly estimate the profiles, the ADS-B aircraft location information is adjusted based on extracted Doppler frequency and then used for Bistatic Radar Cross Section estimation. The classification is based on seven types of aircraft grouped by their size into three classes.

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Subjects with chronic obstructive pulmonary disease (COPD) present breathing pattern and thoracoabdominal motion abnormalities that may contribute to exercise limitation. Twenty-two men with stable COPD (FEV1 = 42.6 ± 13.5% predicted; age 68 ± 8 years; mean ± SD) on usual medication and with at least 5 years of diagnosis were evaluated at rest and during an incremental cycle exercise test (10 watts/2 min). Changes in respiratory frequency, tidal volume, rib cage and abdominal motion contribution to tidal volume and the phase angle that measures the asynchrony were analyzed by inductive respiratory plethysmography at rest and during three levels of exercise (30-50, 70-80, and 100% maximal work load). Repeated measures ANOVA followed by pre-planned contrasts and Bonferroni corrections were used for analyses. As expected, the greater the exercise intensity the higher the tidal volume and respiratory frequency. Abdominal motion contributed to the tidal volume increase (rest: 49.82 ± 11.19% vs exercise: 64.15 ± 9.7%, 63.41 ± 10%, and 65.56 ± 10.2%, respectively, P < 0.001) as well as the asynchrony [phase angle: 11.95 ± 7.24° at rest vs 22.2 ± 15° (P = 0.002), 22.6 ± 9° (P < 0.001), and 22.7 ± 8° (P < 0.001), respectively, at the three levels of exercise]. In conclusion, the increase in ventilation during exercise in COPD patients was associated with the major motion of the abdominal compartment and with an increase in the asynchrony independent of exercise intensity. It suggests that cycling exercise is an effective way of enhancing ventilation in COPD patients.

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The aim of this study was to analyze clinical aspects, hearing evolution and efficacy of clinical treatment of patients with sudden sensorineural hearing loss (SSNHL). This was a prospective clinical study of 136 consecutive patients with SSNHL divided into three groups after diagnostic evaluation: patients with defined etiology (DE, N = 13, 10%), concurrent diseases (CD, N = 63, 46.04%) and idiopathic sudden sensorineural hearing loss (ISSHL, N = 60, 43.9%). Initial treatment consisted of prednisone and pentoxifylline. Clinical aspects and hearing evolution for up to 6 months were evaluated. Group CD comprised 73% of patients with metabolic decompensation in the initial evaluation and was significantly older (53.80 years) than groups DE (41.93 years) and ISSHL (39.13 years). Comparison of the mean initial and final hearing loss of the three groups revealed a significant hearing improvement for group CD (P = 0.001) and group ISSHL (P = 0.001). Group DE did not present a significant difference in thresholds. The clinical classification for SSNHL allows the identification of significant differences regarding age, initial and final hearing impairment and likelihood of response to therapy. Elevated age and presence of coexisting disease were associated with a greater initial hearing impact and poorer hearing recovery after 6 months. Patients with defined etiology presented a much more limited response to therapy. The occurrence of decompensated metabolic and cardiovascular diseases and the possibility of first manifestation of auto-immune disease and cerebello-pontine angle tumors justify an adequate protocol for investigation of SSNHL.

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The objective of the present study was to evaluate the characteristics of acute kidney injury (AKI) in AIDS patients and the value of RIFLE classification for predicting outcome. The study was conducted on AIDS patients admitted to an infectious diseases hospital inBrazil. The patients with AKI were classified according to the RIFLE classification: R (risk), I (injury), F (failure), L (loss), and E (end-stage renal disease). Univariate and multivariate analyses were used to evaluate the factors associated with AKI. A total of 532 patients with a mean age of 35 ± 8.5 years were included in this study. AKI was observed in 37% of the cases. Patients were classified as "R" (18%), "I" (7.7%) and "F" (11%). Independent risk factors for AKI were thrombocytopenia (OR = 2.9, 95%CI = 1.5-5.6, P < 0.001) and elevation of aspartate aminotransferase (AST) (OR = 3.5, 95%CI = 1.8-6.6, P < 0.001). General mortality was 25.7% and was higher among patients with AKI (40.2 vs17%, P < 0.001). AKI was associated with death and mortality increased according to RIFLE classification - "R" (OR 2.4), "I" (OR 3.0) and "F" (OR 5.1), P < 0.001. AKI is a frequent complication in AIDS patients, which is associated with increased mortality. RIFLE classification is an important indicator of poor outcome for AIDS patients.