The Research on Left-Behind Adolescents’Time Management Disposition

Objective:To explore the time management tendency of left-behind adolescents,compare the differences of time management of left-behind.Methods:The questionnaire studies the adolescents students of major labor.Results:Left-behind adolescents are tend to form bad time management tendency(t<2.55,p<0.01)and among these left-behind adolescents there are great individual differences(F>4.24,p>0.05);16-year-old time is a critical period of forming social value of time management(F>4.24,p>0.05),the grade(F_((2,331))=3.74,p=0.03),and whether the only child(t=2.26,p=0.03)has priority to the impact of time management;the children’s age when their parents left.The left period of their parents,the parents who go out,and the visit interval all these factors affect the adolescents’time management tendency(R^(2)>0.21,p<0.001).

Inventory Management and Demand Forecasting Improvement of a Forecasting Model Based on Artificial Neural Networks

Forecasting is predicting or estimating a future event or trend.Supply chains have been constantly growing in most countries ever since the industrial revolution of the 18th century.As the competitiveness between supply chains intensifies day by day,companies are shifting their focus to predictive analytics techniques to minimize costs and boost productivity and profits.Excessive inventory(overstock)and stock outs are very significant issues for suppliers.Excessive inventory levels can lead to loss of revenue because the company's capital is tied up in excess inventory.Excess inventory can also lead to increased storage,insurance costs and labor as well as lower and degraded quality based on the nature of the product.Shortages or out of stock can lead to lost sales and a decline in customer contentment and loyalty to the store.If clients are unable to find the right products on the shelves,they may switch to another vendor or purchase alternative items.Demand forecasting is valuable for planning,scheduling and improving the coordination of all supply chain activities.This paper discusses the use of neural networks for seasonal time series forecasting.Our objective is to evaluate the contribution of the correct choice of the transfer function by proposing a new form of the transfer function to improve the quality of the forecast.

Applying tuberculosis management time to measure the tuberculosis infectious pool at a local level in Ethiopia

Background:Measuring the size of the infectious pool of tuberculosis(TB)is essential to understand the burden and monitor trends of TB control program performance.This study applied the concept of TB management time to estimate and compare the size of the TB infectious pool between 2009 and 2014 in West Gojjam Zone of Amhara Region,Ethiopia.Methods:New sputum smear-positive and smear-negative pulmonary TB(PTB)and retreatment cases who attended 30 randomly selected public health facilities in West Gojjam Zone from October 2013 to October 2014 were consecutively enrolled in the study.In order to determine the infectious period,the TB management time(number of days from the onset of cough until start of anti-TB treatment)was computed for each patient category.The number of undiagnosed TB cases was estimated and hence the TB management time for the undiagnosed category was calculated.The total size of the TB infectious pool during the study period for the study zone was estimated as the annual number of infectious person days.Results:New smear-positive and smear-negative PTB cases contributed 25,050 and 12,931 infectious person days per year to the TB infectious pool,respectively.The retreatment and presently undiagnosed cases contributed 8840 and 34,310 infectious person days per year,respectively.The total size of the TB infectious pool in West Gojjam Zone during the study period was estimated at 81,131 infectious person days per year or 3405 infectious person days per 100,000 population per year.Compared to a similar study done in 2009 in the study area,the current study showed reduction of the TB infectious pool by 244,279 infectious person days.Conclusions:TB management time is a simple and practical tool that may help to estimate and compare the changes in the size of the TB infectious pool at local level.It may also be used as an indicator to monitor the changes in TB control program performance.

A Study on an Extensive Hierarchical Model for Demand Forecasting of Automobile Components

Demand forecasting and big data analytics in supply chain management are gaining interest.This is attributed to the wide range of big data analytics in supply chain management,in addition to demand forecasting,and behavioral analysis.In this article,we studied the application of big data analytics forecasting in supply chain demand forecasting in the automotive parts industry to propose classifications of these applications,identify gaps,and provide ideas for future research.Algorithms will then be classified and then applied in supply chain management such as neural networks,k-nearest neighbors,time series forecasting,clustering,regression analysis,support vector regression and support vector machines.An extensive hierarchical model for short-term auto parts demand assess-ment was employed to avoid the shortcomings of the earlier models and to close the gap that regarded mainly a single time series.The concept of extensive relevance assessment was proposed,and subsequently methods to reflect the relevance of automotive demand factors were discussed.Using a wide range of skills,the factors and co-factors are expressed in the form of a correlation characteristic matrix to ensure the degree of influence of each factor on the demand for automotive components.Then,it is compared with the existing data and predicted the short-term historical data.The result proved the predictive error is less than 6%,which supports the validity of the prediction method.This research offers the basis for the macroeconomic regulation of the government and the production of auto parts manufacturers.

Travel time reliability with and without the dynamic use of hard shoulder:Field assessment from a French motorway

Traffic management aims to ensure a high quality of service for most users by decreasing congestion and increasing safety. However, uncertainty regarding travel time decreases the quality of service and leads end-users to change their routes and schedules even when the average travel time is low, Indicators describing travel time reliability are being developed and should be used in the future both for the optimization and the assessment of active traffic management operation. This paper describes a managed lane experience on a motorway weaving section in France - hard shoulder running operation in rush hours. The paper is focused on travel time reliability indicators and their use for reliability assessment. It provides some discussions about the advantages and drawbacks of reliability indicators under different traffic conditions. It particularly shows the difference between using buffer times and buffer indexes. The paper also discusses the difficulty of interpreting the skew of travel time distribution for travel reliability,

New reference trajectory optimization algorithm for a flight management system inspired in beam search

With the objective of reducing the flight cost and the amount of polluting emissions released in the atmosphere, a new optimization algorithm considering the climb, cruise and descent phases is presented for the reference vertical flight trajectory. The selection of the reference vertical navigation speeds and altitudes was solved as a discrete combinatory problem by means of a graphtree passing through nodes using the beam search optimization technique. To achieve a compromise between the execution time and the algorithm＇s ability to find the global optimal solution, a heuristic methodology introducing a parameter called ‘‘optimism coefficient was used in order to estimate the trajectory＇s flight cost at every node. The optimal trajectory cost obtained with the developed algorithm was compared with the cost of the optimal trajectory provided by a commercial flight management system（FMS）. The global optimal solution was validated against an exhaustive search algorithm（ESA）, other than the proposed algorithm. The developed algorithm takes into account weather effects, step climbs during cruise and air traffic management constraints such as constant altitude segments, constant cruise Mach, and a pre-defined reference lateral navigation route. The aircraft fuel burn was computed using a numerical performance model which was created and validated using flight test experimental data.

MANUFACTURING AND SERVICES:FROM MASS PRODUCTION TO MASS CUSTOMIZATION

Manufacturing and services constitute two of the five sectors of every country＇s economy;depending on the maturity of the economy,they are-in terms of employment-typically the two largest sectors.The outputs or products of an economy can also be divided into goods products（due to manufacturing,construction,agriculture and mining） and services products.To date,the goods and services products have,for the most part,been mass produced;it is the premise of this paper that recent technological advances-including flexible manufacturing,cloud computing,nanotechnology and smart sensing-can better enable the transformation from mass production to mass customization.We regard mass customization as the simultaneous and real time management of supply and demand chains,based on a taxonomy that can be defined in terms of its underpinning component and management foci.From a components perspective,we first consider the value chain of supplier,manufacturer,assembler,retailer,and customer,and then develop a consistent set of definitions for supply and demand chains based on the location of the customer order penetration point.From a management perspective,we classify the methods that are employed in the management of these chains,based on whether supply and/or demand are flexible or fixed.Interestingly,our management taxonomy highlights a very critical research area at which both supply and demand are flexible,thus manageable.Simultaneous management of supply and demand chains sets the stage for mass customization which is concerned with meeting the needs of an individualized customer market.Simultaneous and real time management of supply and demand chains set the stage for real time mass customization（e.g.,wherein a tailor first laser scans an individual＇s upper torso and then delivers a uniquely fitted jacket within a reasonable period,while the individual is waiting）.The benefits of real time mass customization cannot be over-stated as goods and services become indistinguishable and are co-produced-as ＂servgoods＂-in real time,resulting in an overwhelming economic advantage.