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Counterfeited transparent zinc oxide film produced by decorative sol gel

j.rao1, 2, winfield*, 1, koh1, 2, and crean1, 2

1 Tyndall National College, Lee Maltings, Vista Row, Cork, Ireland.

2 Department of Microelectronics Engineering, University College Cork, Cork, Ireland received June 12, 2007, amended April 3, 2008, was accepted April 7, 2008 published online July 21, 2008.

The formed track pattern is further densified

Provide retains a stable conductor film embossed.

shape.M an optimal zinc sol gel content was identified.

The embossed film has a great ratio of transparency.

83% in visible areas. Optical bandgap energy is evaluated yes ev. The influence of the Zno Sol Gel film on the parameters of the synthesis and decoration of the microstructure, the morphology and the optical transparency of the fabricated structure are described.

Transparent zinc oxide film type.

Sols are used to produce reliefs.

Rao, also koh1 h 2,s . o 'Brien1, transgenic Crean1,2

1 Tyndall Air Force Base, Lee Maltings Ethnographic College, Prospect, Cork, Irish Platoon.

2 Faculty of Mechanical Engineering, M.Sc.**, Cork, Ireland.

Received amendments on June 12, 2007 on April 3, 2008, accepted on April 7, 28.

There's nothing more frustrating than having a lot of useless things in a system that lacks the most basic features. At the same time, eliminating unnecessary features can make the system more reliable, insisting that the design is as simple as possible. Complex design can only mean waste and increased input.

Over-design is a common problem, and under-design can lead to design flaws.

Worldwide experience has shown that Shell Global Solutions is 65 per cent over-designed and 10 per cent under-designed, affecting the overall functionality of the system. System detection and maintenance by the system is based on experience and intuition, which can lead to interference and increased costs to the system.

Shell Global Solutions.

It's really frustrating for a system to have a lot of useless features and weak essential features. Reducing unused functions also makes the system more stable and as simple as possible. Complexity means waste and increased costs.

Product complexity is a common problem, and substandard design makes it difficult to achieve perfection.

Globally, we can see that 65% of Shell's global optimisation solutions find that 65% of applications or systems are simple and complex, and 10% of products or systems are not fully technologically advanced. This also represents a common weakness in the management of machinery and equipment.

Testing the maintenance level and functionality of a system is often intuitive, and the costs associated with intuition are much higher than what is actually needed.

Shell Global Optimisation.

over

There is nothing more frustrating than having a system with a lot of unnecessary features, but an important aspect that is lacking. In addition, the elimination of unnecessary features results in a more reliable system design that makes it as simple as possible. Complex opportunities are wasted and increase costs.

While over-engineering is a very common problem, under-engineering is often more detrimental to the success of the design.

Global experience has shown that shell global solutions are about sixty-five percent of the instrument's functionality, while over-engineered travel is actually 10% under-engineered and can therefore represent a weak link in the management of the entire authenticity of the facility. Maintenance and functional level testing is often carried out based on system intuition, experience leads to more intervention and higher associated costs than necessary. ”

Shell global solutions.

First paragraph:

If you have a system that comes with a lot of unnecessary features, none of which is substantial, what could be more frustrating?

What's more, removing those unnecessary features results in a more reliable system that is as simple as possible in design. Complexity only leaves more opportunities for things that are useless and costly.

。Human resource planning.

Enzymes are a process of understanding the future of human resources needed by the organization. This process can be directed to applicable directions and goals, as well as appropriate policies, strategies, projects, and procedures to meet the organization's human resource needs, thereby increasing productivity. With the help of enzymes, managers can have a sufficient number of qualified workers to be properly trained and deployed at the right time and place for these talents ([Haynes and Bandt, 2002] and [Liu, 2006]) Biles and Rue (2000) proposed a four-step process for horseradish peroxidase treatment

1) Determine the goals of the organization; (2) identify the skills and expertise required (needs), (3) determine the net human resource requirements; (4) Formulate an action plan. In the second step, the requirements are either judged or mathematically used. Methods of judgment include interviews with experts and employers and experts (Delphi method, questionnaires).

Mathematical methods include time series analysis, regression analysis, productivity ratios, and grey**. Different kinds of ** are suitable for different scopes and implement different advantages and disadvantages. Simple ratios and trends are useful for a short-term, stable environment, however, for long-term and accurate analysis and strategic requirements that require careful consideration of the impact of human resource requirements and their influencing factors.

The purpose of the regression model is to build a factor model of the correlation of the dependent variable in order to make ** and explain the impact that the independent variable has in (delurgio, 1998) the dependent variable. In this study, regression analysis was used to determine the influencing factors of human resource demand, and the impact of the factors was compared with the impact of human resources in restaurants of different sizes.

Influencing factors of human resources in hotels.

Horseradish peroxidase begins to understand the tissues affected by internal and external factors because these factors interact with each other. Many factors affect human resource needs: demographics, policies, economic conditions, technology, skills, laws, socio-cultural, competition, sales**, budgets, organizational strategies, and the workforce (Biles and Rue, 2000), which is a particular degree of organization from the country-wide level.

According to Cho and Huang (2001), the demand for human resources is affected by economic factors, social factors, overall operations, and employee characteristics. Past studies have divided the influencing factors of human resource demand into three categories: organizational factors, industrial factors, and macroeconomic factors, which are summarized as follows:

。Statistical modeling.

El (2004) argues that the variables in must regress the theoretical basis of the analysis, or the results will be distorted and misleading. Therefore, this study refers to previous studies [Qiu and Lui, 2001], [Lui, 2004], [Davidson Suda et al., 2006, Lundtorp], [this report, 2000], [Krakover, 2000], [Go and Lamivudine, 1997], [Athanasopoulos and Hyndman, 2008] and [Lee and Warner, 2006]) to ensure an ideal regression model. From the establishment of variables, previous studies have shown that the hotel industry is extremely sensitive to the risk of fluctuations in the macroeconomic environment, therefore, it can be indirectly deduced that macroeconomic factors such as consumer price index (CPI) and gross domestic product (GDP) are likely to affect the demand for hotel human resources.

In addition, research shows that exchange rates can also affect the hotel's human resource needs; Therefore, this study collects and calculates the historical average monthly exchange rate (e) for the New Taiwan dollar (city) will regression model. Among the organizational factors, individual economic variables such as operating income and size of the hotel are the main drivers of the hotel's human resource demand. In this study, the average room per hotel (room) was used as a variable to reflect the size of the hotel.

In addition, because there are a variety of business items in hotels in Taiwan, this study further divides operating income into three types: room tax (ER1), food and beverage tax (ER2), and other taxes (ER3). In addition to the above factors, the large number of foreign tourists visiting Taiwan (TR) also affects the hotel's human resource requirements, so these data are also included.

In addition, past studies have shown that the demand for human resources affects occupancy rates. However, study-related trials have shown that "occupancy" and "room revenue" are too highly correlated among independent variables (> 80), creating collinear problems.

Therefore, this study only includes room income analysis. All of these factors constituted 8 independent variables in this study. Therefore, the hotel's human resource demand function (QD) should be written like this.

1) ("d" for "demand"):

1) QD = Q(uh, room, E, CPI, GDP, TR), uh = ER1 + ER2 + ER3.

With the normal functioning of the market mechanism, the total number of employees is certainly satisfied by the emotional IQ of the hospitality industry (y). (2) Hotel human resource demand function ("t" represents "time"):

2) = Q: First room, E, Resident Consumption ** Index (CPI), GDP, TR), to establish a statistical model to establish a solid theoretical basis, especially the impact of the gray correlation analysis of hotel human resource demand, this study uses Y as the dependent variable, and combines the emotional IQ. (1) Emotional IQ to build an average hotel human resource demand model.

Statistical modeling.

Gujarat (2004) argues that the variables in regression analysis must have a theoretical basis, otherwise the results will be distorted and misleading. Therefore, this study refers to ([Zhao, Huang, 2001], [Huang, 2004], [Davidson et al.. [Baum and Lundtorp, 2000], [Krakover, 2000], [Qu Lin, 1997], [Athanasopoulos and Heindeman, 2008] and [Lee and Warner, 2006]) to ensure an ideal regression model.

In setting up variables, past research has shown that the hospitality industry is very sensitive to fluctuations in the macroeconomic environment; Therefore, it can be inferred that macroeconomic variables such as the Consumer Price Index (CPI) and Gross Domestic Product (GDP) have the potential to affect the demand for hotel human resources. In addition, the study shows that the currency exchange rate will also affect the hotel with human resource demand, therefore, the new Taiwan dollar (yuan) (5) collected and calculated by this study will enter the historical monthly average of the regression model.

Among the organizational factors, such as the hotel's operating income and the size of the microeconomic variables, are the main driving forces for the hotel's human resource needs. This study uses the average room (room) per hotel as a variable to reflect the size of the hotel.

In addition, because there are different businesses in the hotel's projects in Taiwan, the study is further divided into three broad categories of business revenue: room revenue (ER1), food and beverage revenue (ER2), and other revenue (ER3). In addition to the above factors, the number of international visitors to Taiwan (TR) also has an impact on the hotel's human resource needs, so this data is also included.

In addition, past studies have shown that occupancy affects the demand for human resources. However, the correlation test results show that the "occupancy rate" and "room revenue" between the independent variables are too highly correlated (", which creates a collinearity problem. Therefore, this study only includes spatial analysis income.

All of these factors make up the eight independent variables of this study, so the human resource demand function (quantum dots) of a hotel can be written as an equation. (1) ("D" means "requirement"): 1) Quantum dots = ask (ER, E, CPI, GDP, TR) where estrogen receptors = ER1 + ER2 + ER3 With the market mechanism, the EQ of the total number of employees employed by the hospitality industry (Y) will certainly meet the normal functioning of the total number of employees.

2) The function of human resource demand for hotels ("t" shape means "time"): 2) yt = Q(ER, electro, CPI, GDP, text) In order to build a statistical model based on a solid theoretical basis to specifically analyze the impact of hotel human resource demand, as a dependent variable y in this study, combined with the formula. (1) Establish a model of human resource demand for the average of a hotel.