On the Sensor Classification Scheme of Robotic Manipulators

This paper analyzes the signals captured during impacts and vibrations of a mechanical manipulator. The Fourier Transform of eighteen different signals are calculated and approximated by trendlines based on a power law formula. A sensor classification scheme based on the frequency spectrum behavior is presented.

Towards a classification scheme for musical sounds

Signal Processing: Algorithms, Architectures, Arrangements, and Applications (SPA), 2013

High-Accuracy Low-Cost RTK-GPS for an Unmanned Surface Vehicle

This work presents a low cost RTK-GPS system for localization of unmanned surface vehicles. The system is based on the use of standard low cost L1 band receivers and in the RTKlib open source software library. Mission scenarios with multiple robotic vehicles are addressed as the ones envisioned in the ICARUS search and rescue case where the possibility of having a moving RTK base on a large USV and multiple smaller vehicles acting as rovers in a local communication network allows for local relative localization with high quality. The approach is validated in operational conditions with results presented for moving base scenario. The system was implemented in the SWIFT USV with the ROAZ autonomous surface vehicle acting as a moving base. This setup allows for the performing of a missions in a wider range of environments and applications such as precise 3D environment modeling in contained areas and multiple robot operations.

A Clinical Support System Based on Quality of Life Estimation

Quality of life is a concept influenced by social, economic, psychological, spiritual or medical state factors. More specifically, the perceived quality of an individual's daily life is an assessment of their well-being or lack of it. In this context, information technologies may help on the management of services for healthcare of chronic patients such as estimating the patient quality of life and helping the medical staff to take appropriate measures to increase each patient quality of life. This paper describes a Quality of Life estimation system developed using information technologies and the application of data mining algorithms to access the information of clinical data of patients with cancer from Otorhinolaryngology and Head and Neck services of an oncology institution. The system was evaluated with a sample composed of 3013 patients. The results achieved show that there are variables that may be significant predictors for the Quality of Life of the patient: years of smoking (p value 0.049) and size of the tumor (p value < 0.001). In order to assign the variables to the classification of the quality of life the best accuracy was obtained by applying the John Platt's sequential minimal optimization algorithm for training a support vector classifier. In conclusion data mining techniques allow having access to patients additional information helping the physicians to be able to know the quality of life and produce a well-informed clinical decision.

Impact of RIFLE Classification in Liver Transplantation

Acute renal failure (ARF) is common after orthotopic liver transplantation (OLT). The aim of this study was to evaluate the prognostic value of RIFLE classification in the development of CKD, hemodialysis requirement, and mortality. Patients were categorized as risk (R), injury (I) or failure (F) according to renal function at day 1, 7 and 21. Final renal function was classified according to K/DIGO guidelines. We studied 708 OLT recipients, transplanted between September 1992 and March 2007; mean age 44 +/- 12.6 yr, mean follow-up 3.6 yr (28.8% > or = 5 yr). Renal dysfunction before OLT was known in 21.6%. According to the RIFLE classification, ARF occurred in 33.2%: 16.8% were R class, 8.5% I class and 7.9% F class. CKD developed in 45.6%, with stages 4 or 5d in 11.3%. Mortality for R, I and F classes were, respectively, 10.9%, 13.3% and 39.3%. Severity of ARF correlated with development of CKD: stage 3 was associated with all classes of ARF, stages 4 and 5d only with severe ARF. Hemodialysis requirement (23%) and mortality were only correlated with the most severe form of ARF (F class). In conclusion, RIFLE classification is a useful tool to stratify the severity of early ARF providing a prognostic indicator for the risk of CKD occurrence and death.

An automatic voice pleasantness classification system based on prosodic and acoustic patterns of voice preference

In the last few years the number of systems and devices that use voice based interaction has grown significantly. For a continued use of these systems the interface must be reliable and pleasant in order to provide an optimal user experience. However there are currently very few studies that try to evaluate how good is a voice when the application is a speech based interface. In this paper we present a new automatic voice pleasantness classification system based on prosodic and acoustic patterns of voice preference. Our study is based on a multi-language database composed by female voices. In the objective performance evaluation the system achieved a 7.3% error rate.

High-Content Analysis of Breast Cancer Using Single-Cell Deep Transfer Learning

High-content analysis has revolutionized cancer drug discovery by identifying substances that alter the phenotype of a cell, which prevents tumor growth and metastasis. The high-resolution biofluorescence images from assays allow precise quantitative measures enabling the distinction of small molecules of a host cell from a tumor. In this work, we are particularly interested in the application of deep neural networks (DNNs), a cutting-edge machine learning method, to the classification of compounds in chemical mechanisms of action (MOAs). Compound classification has been performed using image-based profiling methods sometimes combined with feature reduction methods such as principal component analysis or factor analysis. In this article, we map the input features of each cell to a particular MOA class without using any treatment-level profiles or feature reduction methods. To the best of our knowledge, this is the first application of DNN in this domain, leveraging single-cell information. Furthermore, we use deep transfer learning (DTL) to alleviate the intensive and computational demanding effort of searching the huge parameter's space of a DNN. Results show that using this approach, we obtain a 30% speedup and a 2% accuracy improvement.

C-reactive protein at 24 hours after hospital admission may have relevant prognostic accuracy in acute pancreatitis: a retrospective cohort study

Introduction: C-reactive protein (CRP) and Bedside Index for Severity in Acute Pancreatitis (BISAP) have been used in early risk assessment of patients with AP. Objectives: We evaluated prognostic accuracy of CRP at 24 hours after hospital admission (CRP24) for in-hospital mortality (IM) in AP individually and with BISAP. Materials and Methods: This retrospective cohort study included 134 patients with AP from a Portuguese hospital in 2009---2010. Prognostic accuracy assessment used area under receiver---operating characteristic curve (AUC), continuous net reclassification improvement (NRI), and integrated discrimination improvement (IDI). Results: Thirteen percent of patients had severe AP, 26% developed pancreatic necrosis, and 7% died during index hospital stay. AUCs for CRP24 and BISAP individually were 0.80 (95% confidence interval (CI) 0.65---0.95) and 0.77 (95% CI 0.59---0.95), respectively. No patients with CRP24 <60 mg/l died (P = 0.027; negative predictive value 100% (95% CI 92.3---100%)). AUC for BISAP plus CRP24 was 0.81 (95% CI 0.65---0.97). Change in NRI nonevents (42.4%; 95% CI, 24.9---59.9%) resulted in positive overall NRI (31.3%; 95% CI, − 36.4% to 98.9%), but IDI nonevents was negligible (0.004; 95% CI, − 0.007 to 0.014). Conclusions: CRP24 revealed good prognostic accuracy for IM in AP; its main role may be the selection of lowest risk patients.

EVALUATION OF METHODS IN DETECTING VANCOMYCIN MIC AMONG MRSA ISOLATES AND THE CHANGES IN ACCURACY RELATED TO DIFFERENT MIC VALUES

INTRODUCTION: Methicillin-Resistant Staphylococcus aureus (MRSA) presenting reduced susceptibility to vancomycin has been associated to therapeutic failure. Some methods used by clinical laboratories may not be sufficiently accurate to detect this phenotype, compromising results and the outcome of the patient. OBJECTIVES: To evaluate the performance of methods in the detection of vancomycin MIC values among clinical isolates of MRSA. MATERIAL AND METHODS: The Vancomycin Minimal Inhibitory Concentration was determined for 75 MRSA isolates from inpatients of Mãe de Deus Hospital, Porto Alegre, Brazil. The broth microdilution (BM) was used as the gold-standard technique, as well as the following methods: E-test® strips (BioMérieux), M.I.C.E® strips (Oxoid), PROBAC® commercial panel and the automated system MicroScan® (Siemens). Besides, the agar screening test was carried out with 3 µg/mL of vancomycin. RESULTS: All isolates presented MIC ≤ 2 µg/mL for BM. E-test® had higher concordance (40%) in terms of global agreement with the gold standard, and there was not statistical difference among E-test® and broth microdilution results. PROBAC® panels presented MICs, in general, lower than the gold-standard panels (58.66% major errors), while M.I.C.E.® MICs were higher (67.99% minor errors). CONCLUSIONS: For the population of MRSA in question, E-test® presented the best performance, although with a heterogeneous accuracy, depending on MIC values.

The impact of questions rotation in response accuracy

Dissertação apresentada como requisito parcial para obtenção do grau de Mestre em Estatística e Gestão de Informação

Classification of varieties of pasteurella pestis strains isolated in the interior of the state of Pernambuco-Brazil

Studies were made on the biochemical behavior of 100 strains of P.pestis isolated in Northeastern Brazil with regard to production of nitrous acid, reduction of nitrates to nitrltes, and aciáification of glycerol. Results showed that 98 strains can be classified as "orientalis variety", while the remaining two could not be included in any of the existing "varieties".

Gastric adenocarcinoma: contribute of computed tomography in preoperative T nad N staging

RESUMO:Os recentes progressos na imagiologia médica possibilitaram um papel de destaque para a Tomografia Axial Computorizada Multicorte no estadiamento do carcinoma do estômago (GA). Foi objetivo deste estudo avaliar a acuidade desta técnica no estadiamento T (invasão mural) e N (ganglionar) e avaliar fatores de prognóstico como fatores de representação/substituição para melhorar a referida acuidade. Sessenta e nove pacientes operados a carcinoma gástrico (GA) entre Janeiro de 2010 e Julho de 2012 e avaliados por Tomografia Computorizada, a maioria recorrendo a técnica de multicorte com distensão gástrica, foram estadiados retrospetivamente por três imagiologistas. Utilizaram-se critérios de avaliação referidos na literatura especializada e fatores de substituição/representação nos estadios menos eficazes. O estadiamento T revelou acuidade de 66,7% e sensibilidade de 92% e a acuidade, sensibilidade e especificidade obtidas para o estadiamento N foram respetivamente 49%, 40,9% e 64%. Usando um fator de substituição de estadiamento diagnóstico T4/N2 para mudar o estadiamento N2 obtido por MDCT para estadiamento N3A aumentaria a acuidade do estadiamento N para 59% e a sensibilidade para 58,1% e baixaria a especificidade para 61,5%, embora essa mudança não fosse estatisticamente significativa (Teste exato de Fisher 0,159). Em conclusão a acuidade de uma técnica simples de MDCT com distensão gástrica no estadiamento T e N do GA está dentro dos valores citados na literatura e fatores de substituição/representação como o estadiamento T4 e o tipo Difuso da classificação de Lauren podem melhorar a acuidade do estadiamento N.-------------- ABSTRACT: Recent innovations in medical sectional imaging have allowed a major role of multi-detector computed tomography (MDCT) in staging of gastric adenocarcinoma (GA). The purpose of this study was to evaluate the accuracy of this technique in depth of mural invasion (T) and nodal (N) staging of GA and to evaluate prognostic factors as surrogate factors to improve such accuracy. Sixty nine patients operated to GA between January 2010 and July 2012 that underwent Computed Tomography, the majority through Multidetector Computed Tomography (MDCT) with gastric distention, were staged retrospectively by three imagiologists with state-of-the-art criteria and surrogate prognostic factors were analyzed for less accurate stages. MDCT T-staging was 66,7 % accurate with a sensibility of 92 % and there was a 49 % accuracy, 40,9 % sensibility and 64 % specificity for N Staging. Using a surrogate factor of T4/N2 diagnostic staging to change diagnostic MDCT N2 disease to N3A disease would increase accuracy of N staging to 59% and sensibility to 58,1% and would decrease specificity to 61,5 %, although that change was not statistically significant (Fisher´s Exact Test 0,159)In conclusion the accuracy of a simple hydro-MDCT technique in T and N staging of GA is in the range of values cited in the literature and surrogate factors as diagnostic T4 disease and diffuse type of Lauren´s Classification may improve the accuracy of N staging.

Assessing the impacts of land use and land cover change on hydrology of watershed: a case study on Gigel-Abbay Watershed, Lake Tana Basin, Ethiopia

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

Diagnosic Classification: Results from a Clinical Experience of Three Years with DC: 0–3

Infancy and early childhood are characterized by a dynamic and ever changing process. Since the beginning of their clinical work at the Infancy Unit, the authors were concerned with individual assessment and the questions about the role played by parents as well as by babies in pathology and intervention.In this article, the authors begin with a description of the path that led them to the selection of DC 0–3 as a diagnostic classification system and how this has been instrumental in helping them to better define infant psychopathology and guide them in treatment orientations. Next, they present the results of the applicationof Axis I and II of DC: 0–3 in their clinical population in the years 1997, 1998, and 1999. The objectives of this study were to learn more about the distribution of mental disorders in a clinical population up tofour years of age. The authors attempted to separate infants at risk for developing psychic disorders from those presenting current psychopathology as well as the possible influence of demographic features on this distribution, to define a target population and design adapted therapeutic measures. The identification of these objectives provides the rationale for the use of a diagnostic tool, like DC: 0–3, which is essential to plan clinical activity, to evaluate therapeutic efficacy, and to develop specific programs.