Machine for visual inspection

The project was made during the Erasmus+ Program in Instituto Superior de Engenharia do Porto, Portugal. I had a pleasure to do this in Gislotica Mechanical Solution, Lda. This document presents a process of design a vertical inspection station for truck tires. The first part contains an introduction. There are information about Gislotica Company and also first analysis of problem. In next part is presented way to figured out the task and described all issues connected with designed machine. In last part were made some conclusions about problems and results. There is a place not only for sum up design process but also my develop during the project. I repeatedly pointed out which issues were new for me. A lot of times I focus on myself and gained experience and information about design process.

Tire inspection spreading machine

The aim of the project was to design in Solidworks and improve an existing Tire inspection machine. The project was developed in Gislotica - Mechanical Solutions, guided by ing. Rui Manuel Fazenda Silva who is a professor in ISEP. The designed device relates to the inspection of automobile tires for holes and weak places caused by punctures and usage. Such inspection includes careful examination of the inside surface of the tire which is difficult because of its cylindrical shape, stiff and resistant nature of the material out of which the tire is made. The whole idea is to provide a machine by which the walls of the tire may be spread and hold apart, presenting the inner surface for the worker to control. The device must also perform rotational and vertical movement of the tire. It is meant to provide inspection in hich there is no need for the controller to use force. It makes his work easier and more efficient.

Prevalence of refractive errors in students in Northeastern Brazil

To determine the prevalence of refractive errors in the public and private school system in the city of Natal, Northeastern Brazil. Methods: Refractometry was performed on both eyes of 1,024 randomly selected students, enrolled in the 2001 school year and the data were evaluated by the SPSS Data Editor 10.0. Ametropia was divided into: 1- from 0.1 to 0.99 diopter (D); 2- 1.0 to 2.99D; 3- 3.00 to 5.99D and 4- 6D or greater. Astigmatism was regrouped in: I- with-the-rule (axis from 0 to 30 and 150 to 180 degrees), II- against-the-rule (axis between 60 and 120 degrees) and III- oblique (axis between > 30 and < 60 and >120 and <150 degrees). The age groups were categorized as follows, in: 1- 5 to 10 years, 2- 11 to 15 years, 3- 16 to 20 years, 4- over 21 years. Results: Among refractive errors, hyperopia was the most common with 71%, followed by astigmatism (34%) and myopia (13.3%). Of the students with myopia and hyperopia, 48.5% and 34.1% had astigmatism, respectively. With respect to diopters, 58.1% of myopic students were in group 1, and 39% distributed between groups 2 and 3. Hyperopia were mostly found in group 1 (61.7%) as well as astigmatism (70.6%). The association of the astigmatism axes of both eyes showed 92.5% with axis with-the-rule in both eyes, while the percentage for those with axis againstthe- rule was 82.1% and even lower for the oblique axis (50%). Conclusion: The results found differed from those of most international studies, mainly from the Orient, which pointed to myopia as the most common refractive error, and corroborates the national ones, with the majority being hyperopia

Scheduling of track inspection and maintenance activities in railroad networks

The U.S. railroad companies spend billions of dollars every year on railroad track maintenance in order to ensure safety and operational efficiency of their railroad networks. Besides maintenance costs, other costs such as train accident costs, train and shipment delay costs and rolling stock maintenance costs are also closely related to track maintenance activities. Optimizing the track maintenance process on the extensive railroad networks is a very complex problem with major cost implications. Currently, the decision making process for track maintenance planning is largely manual and primarily relies on the knowledge and judgment of experts. There is considerable potential to improve the process by using operations research techniques to develop solutions to the optimization problems on track maintenance. In this dissertation study, we propose a range of mathematical models and solution algorithms for three network-level scheduling problems on track maintenance: track inspection scheduling problem (TISP), production team scheduling problem (PTSP) and job-to-project clustering problem (JTPCP). TISP involves a set of inspection teams which travel over the railroad network to identify track defects. It is a large-scale routing and scheduling problem where thousands of tasks are to be scheduled subject to many difficult side constraints such as periodicity constraints and discrete working time constraints. A vehicle routing problem formulation was proposed for TISP, and a customized heuristic algorithm was developed to solve the model. The algorithm iteratively applies a constructive heuristic and a local search algorithm in an incremental scheduling horizon framework. The proposed model and algorithm have been adopted by a Class I railroad in its decision making process. Real-world case studies show the proposed approach outperforms the manual approach in short-term scheduling and can be used to conduct long-term what-if analyses to yield managerial insights. PTSP schedules capital track maintenance projects, which are the largest track maintenance activities and account for the majority of railroad capital spending. A time-space network model was proposed to formulate PTSP. More than ten types of side constraints were considered in the model, including very complex constraints such as mutual exclusion constraints and consecution constraints. A multiple neighborhood search algorithm, including a decomposition and restriction search and a block-interchange search, was developed to solve the model. Various performance enhancement techniques, such as data reduction, augmented cost function and subproblem prioritization, were developed to improve the algorithm. The proposed approach has been adopted by a Class I railroad for two years. Our numerical results show the model solutions are able to satisfy all hard constraints and most soft constraints. Compared with the existing manual procedure, the proposed approach is able to bring significant cost savings and operational efficiency improvement. JTPCP is an intermediate problem between TISP and PTSP. It focuses on clustering thousands of capital track maintenance jobs (based on the defects identified in track inspection) into projects so that the projects can be scheduled in PTSP. A vehicle routing problem based model and a multiple-step heuristic algorithm were developed to solve this problem. Various side constraints such as mutual exclusion constraints and rounding constraints were considered. The proposed approach has been applied in practice and has shown good performance in both solution quality and efficiency.

Method of numerical correction of errors occasioned by delay of records during the monitoring of environmental variables of interest for animal production

As condições de ambiente térmico e aéreo, no interior de instalações para animais, alteram-se durante o dia, devido à influência do ambiente externo. Para que análises estatísticas e geoestatísticas sejam representativas, uma grande quantidade de pontos distribuídos espacialmente na área da instalação deve ser monitorada. Este trabalho propõe que a variação no tempo das variáveis ambientais de interesse para a produção animal, monitoradas no interior de instalações para animais, pode ser modelada com precisão a partir de registros discretos no tempo. O objetivo deste trabalho foi desenvolver um método numérico para corrigir as variações temporais dessas variáveis ambientais, transformando os dados para que tais observações independam do tempo gasto durante a aferição. O método proposto aproximou os valores registrados com retardos de tempo aos esperados no exato momento de interesse, caso os dados fossem medidos simultaneamente neste momento em todos os pontos distribuídos espacialmente. O modelo de correção numérica para variáveis ambientais foi validado para o parâmetro ambiental temperatura do ar, sendo que os valores corrigidos pelo método não diferiram pelo teste Tukey, a 5% de probabilidade dos valores reais registrados por meio de dataloggers.

Errors in preparation and medication management in nursing professionals

The preparation and administration of medications is one of the most common and relevant functions of nurses, demanding great responsibility. Incorrect administration of medication, currently constitutes a serious problem in health services, and is considered one of the main adverse effects suffered by hospitalized patients. Objectives: Identify the major errors in the preparation and administration of medication by nurses in hospitals and know what factors lead to the error occurred in the preparation and administration of medication. Methods: A systematic review of the literature. Deined as inclusion criteria: original scientiic papers, complete, published in the period 2011 to May 2016, the SciELO and LILACS databases, performed in a hospital environment, addressing errors in preparation and administration of medication by nurses and in Portuguese language. After application of the inclusion criteria obtained a sample of 7 articles. Results: The main errors identiied in the pr eparation and administration of medication were wrong dose 71.4%, wrong time 71.4%, 57.2% dilution inadequate, incorrect selection of the patient 42.8% and 42.8% via inadequate. The factors that were most commonly reported by the nursing staff, as the cause of the error was the lack of human appeal 57.2%, inappropriate locations for the preparation of medication 57.2%, the presence of noise and low brightness in preparation location 57, 2%, professionals untrained 42.8%, fatigue and stress 42.8% and inattention 42.8%. Conclusions: The literature shows a high error rate in the preparation and administration of medication for various reasons, making it important that preventive measures of this occurrence are implemented.

Forecasting errors, directional accuracy and profitability of currency trading: The case of EUR/USD exchange rate

We provide a comprehensive study of out-of-sample forecasts for the EUR/USD exchange rate based on multivariate macroeconomic models and forecast combinations. We use profit maximization measures based on directional accuracy and trading strategies in addition to standard loss minimization measures. When comparing predictive accuracy and profit measures, data snooping bias free tests are used. The results indicate that forecast combinations, in particular those based on principal components of forecasts, help to improve over benchmark trading strategies, although the excess return per unit of deviation is limited.

Treating Students' Errors in Oral Production

[Sin resumen]

Test of a Smock System on CPR Primary Emergency Measures and Medical Errors During Simulated Emergencies

Rates of survival of victims of sudden cardiac arrest (SCA) using cardio pulmonary resuscitation (CPR) have shown little improvement over the past three decades. Since registered nurses (RNs) comprise the largest group of healthcare providers in U.S. hospitals, it is essential that they are competent in performing the four primary measures (compression, ventilation, medication administration, and defibrillation) of CPR in order to improve survival rates of SCA patients. The purpose of this experimental study was to test a color-coded SMOCK system on:1) time to implement emergency patient care measures 2) technical skills performance 3) number of medical errors, and 4) team performance during simulated CPR exercises. The study sample was 260 RNs (M 40 years, SD=11.6) with work experience as an RN (M 7.25 years, SD=9.42).Nurses were allocated to a control or intervention arm consisting of 20 groups of 5-8 RNs per arm for a total of 130 RNs in each arm. Nurses in each study arm were given clinical scenarios requiring emergency CPR. Nurses in the intervention group wore different color labeled aprons (smocks) indicating their role assignment (medications, ventilation, compression, defibrillation, etc) on the code team during CPR. Findings indicated that the intervention using color-labeled smocks for pre-assigned roles had a significant effect on the time nurses started compressions (t=3.03, p=0.005), ventilations (t=2.86, p=0.004) and defibrillations (t=2.00, p=.05) when compared to the controls using the standard of care. In performing technical skills, nurses in the intervention groups performed compressions and ventilations significantly better than those in the control groups. The control groups made significantly (t=-2.61, p=0.013) more total errors (7.55 SD 1.54) than the intervention group (5.60, SD 1.90). There were no significant differences in team performance measures between the groups. Study findings indicate use of colored labeled smocks during CPR emergencies resulted in: shorter times to start emergency CPR; reduced errors; more technical skills completed successfully; and no differences in team performance.

A retrospective study examining the nature, contributory factors and predictors of dispensing errors in community pharmacy

Introduction: Since 2005, the workload of community pharmacists in England has increased with a concomitant increase in stress and work pressure. However, it is unclear how these factors are impacting on the ability of community pharmacists to ensure accuracy during the dispensing process. This research seeks to extend our understanding of the nature, outcome, and predictors of dispensing errors. Methodology: A retrospective analysis of a purposive sample of incident report forms (IRFs) from the database of a pharmacist indemnity insurance provider was conducted. Data collected included; type of error, degree of harm caused, pharmacy and pharmacist demographics, and possible contributory factors. Results: In total, 339 files from UK community pharmacies were retrieved from the database. The files dated from June 2006 to November 2011. Incorrect item (45.1%, n = 153/339) followed by incorrect strength (24.5%, n = 83/339) were the most common forms of error. Almost half (41.6%, n = 147/339) of the patients suffered some form of harm ranging from minor harm (26.7%, n = 87/339) to death (0.3%, n = 1/339). Insufficient staff (51.6%, n = 175/339), similar packaging (40.7%, n = 138/339) and the pharmacy being busier than normal (39.5%, n = 134/339) were identified as key contributory factors. Cross-tabular analysis against the final accuracy check variable revealed significant association between the pharmacy location (P < 0.024), dispensary layout (P < 0.025), insufficient staff (P < 0.019), and busier than normal (P < 0.005) variables. Conclusion: The results provide an overview of some of the individual, organisational and technical factors at play at the time of a dispensing error and highlight the need to examine further the relationships between these factors and dispensing error occurrence.

Some problems and errors in cytogenetic biodosimetry

Human radiosensitivity is a quantitative trait that is generally subject to binomial distribution. Individual radiosensitivity, however, may deviate significantly from the mean (by 2-3 standard deviations). Thus, the same dose of radiation may result in different levels of genotoxic damage (commonly measured as chromosome aberration rates) in different individuals. There is significant genetic component in individual radiosensitivity. It is related to carriership of variant alleles of various single-nucleotide polymorphisms (most of these in genes coding for proteins functioning in DNA damage identification and repair); carriership of different number of alleles producing cumulative effects; amplification of gene copies coding for proteins responsible for radioresistance, mobile genetic elements, and others. Among the other factors influencing individual radioresistance are: radioadaptive response; bystander effect; levels of endogenous substances with radioprotective and antimutagenic properties and environmental factors such as lifestyle and diet, physical activity, psychoemotional state, hormonal state, certain drugs, infections and others. These factors may have radioprotective or sensibilising effects. Apparently, there are too many factors that may significantly modulate the biological effects of ionising radiation. Thus, conventional methodologies for biodosimetry (specifically, cytogenetic methods) may produce significant errors if personal traits that may affect radioresistance are not accounted for.

Big Code Applications and Approaches

The availability of a huge amount of source code from code archives and open-source projects opens up the possibility to merge machine learning, programming languages, and software engineering research fields. This area is often referred to as Big Code where programming languages are treated instead of natural languages while different features and patterns of code can be exploited to perform many useful tasks and build supportive tools. Among all the possible applications which can be developed within the area of Big Code, the work presented in this research thesis mainly focuses on two particular tasks: the Programming Language Identification (PLI) and the Software Defect Prediction (SDP) for source codes. Programming language identification is commonly needed in program comprehension and it is usually performed directly by developers. However, when it comes at big scales, such as in widely used archives (GitHub, Software Heritage), automation of this task is desirable. To accomplish this aim, the problem is analyzed from different points of view (text and image-based learning approaches) and different models are created paying particular attention to their scalability. Software defect prediction is a fundamental step in software development for improving quality and assuring the reliability of software products. In the past, defects were searched by manual inspection or using automatic static and dynamic analyzers. Now, the automation of this task can be tackled using learning approaches that can speed up and improve related procedures. Here, two models have been built and analyzed to detect some of the commonest bugs and errors at different code granularity levels (file and method levels). Exploited data and models’ architectures are analyzed and described in detail. Quantitative and qualitative results are reported for both PLI and SDP tasks while differences and similarities concerning other related works are discussed.

Learning from errors: Psychological, relational, and cultural aspects

Although errors might foster learning, they can also be perceived as something to avoid if they are associated with negative consequences (e.g., receiving a bad grade or being mocked by classmates). Such adverse perceptions may trigger negative emotions and error-avoidance attitudes, limiting the possibility to use errors for learning. These students’ reactions may be influenced by relational and cultural aspects of errors that characterise the learning environment. Accordingly, the main aim of this research was to investigate whether relational and cultural characteristics associated with errors affect psychological mechanisms triggered by making mistakes. In the theoretical part, we described the role of errors in learning using an integrated multilevel (i.e., psychological, relational, and cultural levels of analysis) approach. Then, we presented three studies that analysed how cultural and relational error-related variables affect psychological aspects. The studies adopted a specific empirical methodology (i.e., qualitative, experimental, and correlational) and investigated different samples (i.e., teachers, primary school pupils and middle school students). Findings of study one (cultural level) highlighted errors acquire different meanings that are associated with different teachers’ error-handling strategies (e.g., supporting or penalising errors). Study two (relational level) demonstrated that teachers’ supportive error-handling strategies promote students’ perceptions of being in a positive error climate. Findings of study three (relational and psychological level) showed that positive error climate foster students’ adaptive reactions towards errors and learning outcomes. Overall, our findings indicated that different variables influence students’ learning from errors process and teachers play an important role in conveying specific meanings of errors during learning activities, dealing with students’ mistakes supportively, and establishing an error-friendly classroom environment.