PROBABILITY DISTRIBUTION OF TIME DURATION OF MANUAL OPERATION IN THE PRODUCTION OF GLASS EYES

When precise planning of capacities and times of production is needed, there must be precise data for calculation. Not all operations have to have a normal time duration distribution. Counting with average values or use values from guessed distribution can lead to mistakes in actual production planning. This article aims to determine time probability distributions to manual operations. Tests of goodness of fit are used to search for more suitable distributions. This approach is presented in a case study of glass eyes manufacturing. Results show that there can be differences between the estimated normal distribution and another more suitable one. By using tests of goodness of fit to define the correct distribution, more precise production and capacity planning results can be achieved.

Stone Age dwellings, sites and environment in coastal northern Norway: surveys and documentation of house-pit sites

The northernmost parts of Europe has a large number of sites with Stone Age house-pits, the majority of which date from c. 5000 BC onwards. Remarkably, the remains of these dwellings are many places still visible on the surface. In northern Norway, such dwellings concentrate in the coastal areas, with a more limited number found on inland sites. In order to use these in analyses of settlement duration, distribution and organization a more uniform and coherent documentation of both individual structures and site characteristics must be ensured. In an ongoing research project on Stone Age Demographics, we have developed and tested different levels of settlement site documentation, scaling from single structures over site topography to reconstruction of past environments. Through substantial surveying in our study region in coastal western Finnmark, northern Norway, we have collected extensive and uniform documentation of dwellings, sites and environment. This systematic documentation allows us to not just discuss dwellings within one specific site, but to consider also regional and supra-regional patterns and variability. This is required if we are to consider both spatial variation and temporal developments in the use and role of pit-houses.

Design and Analysis of Horizontal Axis Wind Turbine (HAWT) Blades Using CFD

Within the current years wind power is extensively taken into consideration and applied as one of the most promising renewable electricity assets. In the recent studies have a look at, aerodynamic analysis of horizontal axis turbine is achieved with the aid of using cfd. Blades which can be often possible for industrial grade wind turbines embody a directly span-wise profile in conjunction with airfoil fashioned go sections. Wind tunnel test is applied in order to check aerodynamic efficiency wind turbine blade. The goal of this study is to design a wind turbine. The layout manner includes the choice of the sun machine for max efficiency and wind turbine kind and the determination of the blade airfoil, pitch attitude distribution along the radius, and chord duration distribution along the radius. The pitch angle and chord period distributions are optimized primarily based on conservation of angular momentum and principle of aerodynamic forces on an airfoil. Blade element momentum (BEM) principle is first derived then used to conduct a parametric observe to be able to determine if the optimized values of blade pitch and chord period create the maximum green blade geometry. This work includes a discussion of the most important parameters in wind turbine blade layout to maximize efficiency. Keywords: Wind Turbine, HAWT, BEM Theory, Parametric Study, Maximization of efficiency etc.

Construction completion forecasting on the basis of statistical modeling and heterogeneous monitoring data

Modern construction represents a complex production process whose effective regulation is based on information about the period of construction works, obtained by way of monitoring. Any delay in the execution of certain works frustrates scheduled project commissioning, which results in increased project management costs, forfeits and lost benefits. Existing monitoring systems need to be improved through the use of probabilistic scheduling geared towards the forecasting of completion dates of certain works and the construction process as a whole. Construction monitoring may be improved by means of taking management quality into account by means of distributing random work durations in the process of statistical modeling of functions. The introduction of six random duration distribution functions, reflecting management quality, is proposed for the improvement of statistical modeling, whereas the use of scheduled durations of works is expedient for identifying optimistic characteristics. The data, extracted from monitoring reports, needs to be used as pessimistic distributions. Monitoring reports contain heterogeneous data, and they may even have no information on particular types of works. Therefore, pessimistic durations based on missing data should be calculated using the time-space analogy method.

A New Deep Learning-Based Zero-Inflated Duration Model for Financial Data Irregularly Spaced in Time

In stock trading markets, trade duration (i. e., inter-arrival times of trades) usually exhibits high uncertainty and excessive zero values. To forecast conditional distribution of trade duration, this study proposes a hybrid model called “DL-ZIACD” for short, which addresses the problem of excessive zero values by a zero-inflated distribution. Meanwhile, dynamics of the distribution time-varying parameters are captured by a specially designed deep learning (DL) architecture in which the behavioral patterns of large traders and small individual traders are represented separately by different blocks. The proposed hybrid model takes advantage of the strong fitting ability of deep learning methods while allowing for providing a probabilistic output. This paper empirically applied the established model to a large-scale dataset, containing 9,900,000 transactions of the Chinese Shenzhen Stock Exchange 100 Index (SZSE 100) constituents. To the best of our knowledge, no previous studies have applied conditional duration models to a dataset of such a large scale. For both the central location forecasting and the extreme quantile forecasting, our proposed model exhibited significant superiority over the benchmark models, which indicates that our DL-ZIACD model can provide accurate forecasts in conditional duration distribution.

Estimating Group Stress Level by Measuring Body Motion

Understanding employee stress has become a key issue for top management for corporate growth and risk reduction. So far, annual employee satisfaction surveys (ESs) have been conducted to assess the soundness of an organization. However, since it is difficult to collect questionnaires quantitatively and continuously, there is a need for a practical method that can be used to frequently measure group stress levels with a small burden on employees. We propose such a method and evaluated four combinations of approaches, using activity/rest duration distributions from body motion data and generating estimation models on an individual/group basis. The optimal result was obtained when modeling was made on a group basis by using the activity duration distribution (r = 0.928, p < 0.001, estimation error: 1.36%), making it possible to assess the degree of the stress of employees quantitatively and easily, and this showed the possibility of this method being useful as a management guide for companies.

Characterization of Air-Quality Degradation Episodes of PM10 in the Metropolitan Area of São Paulo and Their Relationship with Meteorological Conditions

Air pollution is one of the main environmental problems in large urban centers, affecting people’s health and impacting quality of life. The Metropolitan Area of São Paulo (MASP) presents frequent exceedances of air-quality standards in inhalable particulate matter (PM10), a consequence of pollutant emissions modulated by meteorological conditions. This study aims to identify and characterize PM10persistent exceedance events (PEE) inthe MASP between 2005 and 2017, relating them to meteorological conditions. The criteria used to select the events were: (i) events that occurred in at least 50% of the air-quality monitoring stations chosen for this study and, (ii) among the events that met the first criterion, those with a duration equal to or greater than five days, which correspond to the 80% percentile of the event duration distribution. A total 71 persistent episodes of exceedance were selected. The results show that the exceedance of PM10 lasted up to 14 consecutive days and was predominant in the austral winter, accompanied by an increase in maximum temperature (T), a decrease in wind speed (WS) and relative humidity (RH), and a wind direction predominantly from the northwest during the peak concentration of the pollutant. On average, a concentration increase of 60% was observed at the peak of the PEE.

Changes in data management contribute to temporal variation in gestational duration distribution in the Swedish Medical Birth Registry

Multiple factors contribute to gestational duration variability. Understanding the sources of variability allows to design better association studies and assess public health measures. Here, we aimed to assess geographical and temporal changes in the determination of gestational duration and its reporting in Sweden between 1973 and 2012. Singleton live births between 1973 and 2012 were retrieved from the Swedish Medical Birth Register. Gestational duration trends in percentiles and rates of pre- and post-term deliveries were analyzed by plotting the values over time. Temporal changes in gestational duration based on ultrasound and last menstrual period (LMP) estimation methods were compared. Intervals between LMP date and LMP-based due date were analyzed to assess changes in expected gestational duration. In total, 3 940 577 pregnancies were included. From 1973 until 1985, the median of gestational duration estimated based on LMP or ultrasound decreased from 283 to 278 days, and remained stable until 2012. The distribution was relatively stable when ultrasound-based estimates were used. Until the mid-1990s, there was a higher incidence than expected of births occurring on every seventh gestational day from day 157 onward. On an average, these gestational durations were reported 1.8 times more often than adjacent durations. Until 1989, the most common expected gestational duration was 280 days, and thereafter, it was 279 days. The expected gestational duration varied from 279 to 281 days across different Swedish counties. During leap years, the expected gestational duration was one day longer. Consequently, leap years were also associated with significantly higher preterm and lower post-term delivery rates than non-leap years. Changes in data handling and obstetrical practices over the years contribute to gestational duration variation. The resulting increase in variability might reduce precision in association studies and hamper the assessment of public health measures aimed to improve pregnancy outcomes.