Tool wear monitoring using neuro-fuzzy techniques: a comparative study in a turning process

Tool wear detection is a key issue for tool condition monitoring. The maximization of useful tool life is frequently related with the optimization of machining processes. This paper presents two model-based approaches for tool wear monitoring on the basis of neuro-fuzzy techniques. The use of a neuro-fuzzy hybridization to design a tool wear monitoring system is aiming at exploiting the synergy of neural networks and fuzzy logic, by combining human reasoning with learning and connectionist structure. The turning process that is a well-known machining process is selected for this case study. A four-input (i.e., time, cutting forces, vibrations and acoustic emissions signals) single-output (tool wear rate) model is designed and implemented on the basis of three neuro-fuzzy approaches (inductive, transductive and evolving neuro-fuzzy systems). The tool wear model is then used for monitoring the turning process. The comparative study demonstrates that the transductive neuro-fuzzy model provides better error-based performance indices for detecting tool wear than the inductive neuro-fuzzy model and than the evolving neuro-fuzzy model

Global patient outcomes after elective surgery: prospective cohort study in 27 low-, middle- and high-income countries.

BACKGROUND: As global initiatives increase patient access to surgical treatments, there remains a need to understand the adverse effects of surgery and define appropriate levels of perioperative care. METHODS: We designed a prospective international 7-day cohort study of outcomes following elective adult inpatient surgery in 27 countries. The primary outcome was in-hospital complications. Secondary outcomes were death following a complication (failure to rescue) and death in hospital. Process measures were admission to critical care immediately after surgery or to treat a complication and duration of hospital stay. A single definition of critical care was used for all countries. RESULTS: A total of 474 hospitals in 19 high-, 7 middle- and 1 low-income country were included in the primary analysis. Data included 44 814 patients with a median hospital stay of 4 (range 2-7) days. A total of 7508 patients (16.8%) developed one or more postoperative complication and 207 died (0.5%). The overall mortality among patients who developed complications was 2.8%. Mortality following complications ranged from 2.4% for pulmonary embolism to 43.9% for cardiac arrest. A total of 4360 (9.7%) patients were admitted to a critical care unit as routine immediately after surgery, of whom 2198 (50.4%) developed a complication, with 105 (2.4%) deaths. A total of 1233 patients (16.4%) were admitted to a critical care unit to treat complications, with 119 (9.7%) deaths. Despite lower baseline risk, outcomes were similar in low- and middle-income compared with high-income countries. CONCLUSIONS: Poor patient outcomes are common after inpatient surgery. Global initiatives to increase access to surgical treatments should also address the need for safe perioperative care. STUDY REGISTRATION: ISRCTN5181700

Analysis and Adaptation of Q-Learning Algorithm to Expert Controls of a Solar Domestic Hot Water System

This paper discusses the development of a coupled Q-learning/fuzzy control algorithm to be applied to the control of solar domestic hot water systems. The controller brings the benefit of showing performance in line with the best reference controllers without the need for devoting time to modelling and simulations to tune its parameters before deployment. The performance of the proposed control algorithm was analysed in detail concerning the input membership function defining the fuzzy controller. The algorithm was compared to four standard reference control cases using three performance figures: the seasonal performance factor of the solar collectors, the seasonal performance factor of the system and the number of on/off cycles of the primary circulator. The work shows that the reinforced learning controller can find the best performing fuzzy controller within a family of controllers. It also shows how to increase the speed of the learning process by loading the controller with partial pre-existing information. The new controller performed significantly better than the best reference case with regard to the collectors’ performance factor (between 15% and 115%), and at the same time, to the number of on/off cycles of the primary circulator (1.2 per day down from 30 per day). Regarding the domestic hot water performance factor, the new controller performed about 11% worse than the best reference controller but greatly improved its on/off cycle figure (425 from 11,046). The decrease in performance was due to the choice of reward function, which was not selected for that purpose and it was blind to some of the factors influencing the system performance factor

Comportement des noeuds d'ossature en beton arme sous sollicitations alternees

CNRS T 63498 / INIST-CNRS - Institut de l'Information Scientifique et TechniqueSIGLEFRFranc

Annual efficiency of a commercial finishing operation of fattening of cattle with silvopastoral technology [Eficiencia anual en una operación comercial de ceba final de bovinos con la tecnología de silvopastoreo]

With the objective to evaluate the factors that affect performance related to the association of a mixture of pasture and Leucaena leucocephala ‘Perú’ for the end of cattle fattening, 22 fattening cycles were assessed in zebu bulls at the Represa #1 unit of Rectángulo de ceba in Camagüey, Cuba, from 2002 to 2012. Soil is brown without carbonates. The climate is savannah tropical wet (Aw) with 1183 mm of annual rainfall. The factors evaluated were: stocking rate (a/ha) and years assessed. The changes in the percentage of the pasture and Leucaena populations were recorded through plant counting. Daily weight gain indexes, income and expenses per operation were assessed. Leucaena ‘Perú’ reached final values of 93% (p<0.05) in its population, with an increase in the populations of Guinea grass and other pastures. High income was reached for the lowest charge (p<0.05) with 0.981 kg/a/d. Silvopastoral technology with the association of Leucaena leucocephala ‘Perú’-dryland grasses, allowed to obtain average daily weight gains over 0.800 kg/a/d at the end of the fattening of bulls which were held for ten years of evaluations with very suitable economic results according to such technology and the inputs levels applied

Chronic kidney disease acquired knowledge in a diabetic and hypertensive population using a translated and validated questionnaire

AbstractChronic kidney disease (CKD) is the progressive and irreversible functional and/or structural impairment of the kidney; its main etiologies include hypertension and diabetes. Mexico has the second highest prevalence of CKD worldwide with a high economic burden affecting public and private health systems. Patients with higher knowledge about CKD increase their adherence to preventive treatment. In this study we aim to describe the knowledge of CKD in a sample of Mexican high-risk population, comparing it with general Mexican population, medical students and nephrologists. A cross-sectional, observational study was performed divided in two phases: translation and validation of the knowledge questionnaire to Spanish, and cross-sectional survey to evaluate the knowledge of CKD in patients with diagnosis of diabetes and/or hypertension. We interviewed medical students, general population, and nephrologists to attain validation of the questionnaire in Spanish. The questionnaire was answered by 1,061 participants within the high-risk population. The results of the questionnaire were: 22/24, 18/24, 13.8/24, and 13.4/24 in nephrologists, medical students, normal subjects, and high-risk population, respectively. The questions with least correct answers were related to kidney functions and CKD risk factors. To our knowledge this is the first time a questionnaire for CKD knowledge is applied in Mexican population. These findings suggest poor understanding of kidney functions, risk factors, and symptoms of CKD. It is important not only to provide medical treatment to chronic illness but also awareness of the consequences of not achieving goals of treatment