Tabulation System Essay

Tabulation System Essay.

A computer is a device or machine for making calculations or controlling operations that are expressible in numerical or logical terms. Computers are constructed from components that perform simple well-define functions. The complex interactions of these components endow computers with the ability to process information. If correctly configured (usually by programming) a computer can be made to represent some aspect of a problem or part of a system. If a computer configured in this way is given appropriate input data, then it can automatically solve the problem or predict the behavior of the system.

System is a whole compounded of several parts or members, system, literary “composition” is a set of interacting or interdependent entities forming an integrated whole. A concept of an integrated whole can also be stated in terms of a system embodying a set of elements, and from relationships between an element of the set and elements not a part of the relational regime.

Tabulation means putting a data in a table.

Table means a diagram which has a few vertical and horizontal lines. It’s a presentation of a data in a lucid form. It is the act or process of tabulating and table displaying data in a compact form.

A tabulation system for delivery to a medium of data information suitably arranged for tabulation of character series and ruled lines, and a control for controlling the data information arrangement applied to the medium. The control operates to allow the medium to sequentially deliver out control information for defining desired vertical ruled lines (columns), information regarding a horizontal ruled line (row) defining the upper side of a field between adjacent vertical ruled lines, information regarding character series to be written in the field and control commands for the writing, and information regarding a horizontal ruled line defining the lower side of the field.

A computer program has been developed at Purdue University that will greatly reduce the time required to conduct a 4-H contest. The computer program, written in Clipper and Dbase 3.3 Plus, handles registration details including supplying confirmation notices and a printed receipt to all coaches; prints contestants labels; assigns and calculates class cuts when necessary; tabulates scores by age divisions (clover, junior, senior, etc.), organizations (4-H, FFA, etc.), and contest (diary, crops, horticulture, etc.); and ranks individuals and teams by individual classes and overall contest. The program sets and prints results in a variety of options to fit user needs.

4-H professionals frequently spend a considerable amount of time planning and conducting agricultural judging events. The computerized contest organizer and tabulation system developed at Purdue University helps eliminate problems encountered with judging events.

Some automated scoring program built in Excel and uses embedded formulas to calculate the final scores and rank the contestant of each heat. The scores will be written down on paper, and then transcribed to this program as time permits either during the heat, or immediately following. Some practice and experience with this program prior to a contest is highly recommended. Additionally, having a dedicated tabulator who is neither a judge nor a contestant would be ideal.

Today, events are everywhere and judges are always involved in tabulating results. An ideal computerized system that would give them a satisfaction for judging, and a system that fits their different needs would result to flexible module for them to access the system easily.

The Pangasinan State University (Lingayen Campus) has pageant events. The PSU is currently using MS Excel and MS Access in tabulating. But, that was prepared right before the said events and sometimes it does not accomplish the user’s expectations.

PSU College of Computer Science is in charge in providing the means for tabulating results for Pageant Contest. If a system for tabulation will be implemented multiple benefits will bring. The researchers conducted a research on the tabulation matters of the PSU since tabulation system does not still exist. Based on the interviewee and the observation, the researchers decided to promote high quality software and yet efficient to tabulate results. The system will be operated in Windows Based to make it more understandable and user friendly. The judges can determined whatever process he wants to execute.

In Purdue University the flow of their system starts with registering contestants, preparing confirmation letters, receipts and mailing labels, as well as tabulating scores can be extremely time-consuming. Purdue’s computerized contest organizer and tabulation program saves time by allowing contestant’s names and addresses, once entered, to be used to prepare registration forms and contest scorecards.

Purdue University developed a computerized contest organizer & tabulation system that will greatly reduce the time required to conduct a contest. This helps eliminate problems encountered with judging events. Computerized tabulation is less likely to result in scoring errors. When processing data by hand, errors may occur when transposing data from scorecards to a master score sheet and when adding scores. By using Purdue’s computerized contest organizer and tabulation program; errors are less likely to occur. Further, the system won’t tabulate final scores if data are missing, thereby giving verification that the data set is complete.

Results are available more quickly when using a computerized versus manual tabulation program. The computer adds scores, ranks individuals and teams, breaks ties, and divides contestants by division and age faster than a group of individuals. The program was developed to make the job of planning and conducting a judging event easier, given the normal problems encountered when manually performing judging tasks. With this study it discusses the flow of tabulation results and it talks about computerized contest organizer and tabulation system which also includes in the developed system. It can help the judges to insert and update records of contestants in a short period of time. This study relates with the proposed system through its fast and accurate tabulation of scores which is one of the systems features. Importance of the Study

The study would help the University by means of understanding the essence of computerized electronic tabulation. It could also serve as a basis for global study primarily of computerized tabulation. Different Universities are always involved in this event. In addition the study facilitate with the problem of the University in terms of tabulating results.

The study provides ideas to help the global and local community specially the Universities to adapt with the advance technology regarding Computerized Electronic Tabulation. The study also provides additional knowledge for those who are interested to undergo the same study.

The computerized tabulation will lessen the time, effort and money being consumed in preparing the means of tabulation. The different colleges of the university will also benefit with the use of the said system. Statement of the Problem

The study aimed to develop and implement Pageant Tabulation System in PSU. Specifically, the study sought to answer the following problems:

1. What was the existing system of the University in tabulating different event? 2. What were the challenges encountered with the existing system? 3. What were the security features?  4. What were the benefits?

Objectives of the Study

The main objective of the study was to develop and implement Pageant Tabulation System. 1. To identify the existing system of the University in relation to tabulating Pageant Contest. 2. To enumerate the challenges encountered with the existing system. 3. To identify the security features.

4. To determine the benefits.

Definition of Terms

The following terms are defined to clearly understand the terminology and concepts use in the study. Data – Are the important facts and figures regarding the contestants and judges such as names, personal information. Data Flow Diagram – A top down structured analysis and design tool, which consist primarily of rectangle with rounded corners representing how data and people interact. Electronic – is a device or technology associated with or employing low voltage current and solid state integrated circuits or components, usually for transmission and or processing of analog or digital data. System – composed of different modules, conceptual framework output. Tabulation – it is process were the result was computed and arranged sequentially. Table – means a diagram which has a few vertical and horizontal lines. Pageant – a beautification show, or an elaborate spectacle. Tabulator – either board of judge or scorer.

Judges – A person involved in evaluating the contestants and result.
Contestants – a person involved in contest, and performer.
Category – a classification or a class.
Percentage – rate or proportion of each hundred;
Rank – position; level;
Module – architectural unit of measurement;
Visual Basic – object oriented high level programming language based on Basic Language. It is used for writing applications as well as application generator. It provides a graphical environment in which you visually design the forms and controls that become the building blocks of your applications and is specifically designed to utilize internet. It comes with several controls that allow you to create web based applications, called Active X executable. CHAPTER 2

Methodology

This chapter presents the methodology, the data gathering techniques, the modeling and design used in analyzing the proposed system and the scope
delimitation of the study. This will serve as a guide to the researchers on how they will conduct the study’s objectives.

Software Development and Methodology

The development will use RAD- a linear sequential software development process model that emphasized on development cycle using a component based construction approach, as a method that enables a development team to create a fully functional system within a very short period of time. This will be used to develop the system because of time constraints in the development schedule. RAD Model has the following phases:

Brainstorming. Brainstorming is a group creativity technique designed to generate a large number of idea for the solution of a problem. Brainstorming focuses on quantity rather than quality of ideas. The assumption is that the greater the number of ideas generated, the greater the chances of producing a radical and effective solution. The researchers establish a possible way to solve the problem including the planning, making, and designing. The researchers applied brainstorming in the study by discussing which of the important data to summarize, what the flow of the system must have. Also the researchers discussed the sources of data and what benefit the system can give. Requirements Gathering and Analysis. In order to filter the answer that would best suit to the problem, the researchers used an indispensable tool in gathering information.

The researchers validated their hypothesis by interviewing for the information needed in making the study. Based on the knowledge of the developers, it is evaluated and processed as requirements for the study which guide the developers in creating a prototype. Prototype System. The researchers then go on the making of the prototype of the study. Basically, the requirements gathered are transformed into requirements for the prototype. The researchers identified the needed features that would be included in the study. The intention of a prototype is to establish more refined user requirements. Object Creation. Other lesser features of the study are added into the prototype.

During this stage of study development, the researchers, specifically the programmer after processing requirements, analyzes intensively the objects to be created for the study. User Review. The initial system is reviewed by the intended users and makes suggestions to validate further requirements be added. Finalize Code. In this point the codes are finalized after the users are fully satisfied with the system. This activity contains documentations process and the output of the study. Deliver System. The delivery system involves training users on how to install and implement the system. This also involves user policies that help reduce security risk during the implementation of the system.

Tabulation System Essay

A glimpse of Big Data Essay

A glimpse of Big Data Essay.

“Big data is not a precise term; rather it’s a characterization of the never ending accumulation of all kinds of data, most of it unstructured. It describes data sets that are growing exponentially and that are too large, too raw or too unstructured for analysis using relational database techniques. Whether terabytes or petabytes, the precise amount is less the issue than where the data ends up and how it is used.”——Cite from EMC’s report “Big data: Big opportunity to create business value”.

When explosion happened in mobile network, cloud computing and internet technology, more and more different information appeared. In the past, the numerous terabyte data could be a disaster for any company, because it means high cost of storage and high performance CPU. However, in nowadays, companies discovered many facts they haven’t thought about these data before. Companies started to use data analytics technology to find business values from these terabyte or petabyte data. It seems to be a big opportunity instead of disaster for companies now.

Data is not only defined as structured data. When we talking about big data, it could be categorized into three types of data: structured data, unstructured data, and semistructured data (Please see Chart I).

Especially when internet and mobile internet developed rapidly, the unstructured data and semistructured data exploded. For example, a bank could draw a conclusion by analyze unstructured data to find out why number of churn increased. Most definitions of big data all talk about the size of data. However, size, or volume, is not the only characteristic of big data. There are other two characteristics, variety and velocity. Variety means big data generates from several of sources. Data type was no longer connected to structured data. According to the EMC’s report, most of big data related to unstructured data. Velocity means the speed of data production. Data was no long structured data which was stored in the structured database. Data could come from anywhere and anytime: mobile, censors, devices, manufacturing machine etc. The stream of data generates in real time. This means company’s action should be taken with this speed.

Structured data| Structured data is organized in structure. These data can be read and stored by computer. The form of structured data is structured data base that store specific data by methodology of columns and rows. | Unstructured data| Unstructured data refers to the data without identified structure. For example, video, audio, picture, text and so on. These data also called loosely structured data. | Semistructured data| Semistructured data organized in semantic entities. The data’s size and type in one group could be different. For example, XML and RSS feeds. This data try to reconcile the real world with computer based database.| Chart I. Three types of data.

Big data analytics

Big data analytics is not a technique. It is a terms that contains a lot of technologies (See EXHIBITION I). Based on enterprise’s different requirement, each program will use different technology to analyze data. However, with the big data’s development, some of these techniques become popular and useful. On the basis of the exhibition II, advanced analytics, visualization, real time, in-memory databases and unstructured data have strong-to-moderate commitment and strong potential growth.

The traditional techniques, for example, OLAP tools and hand-coded SQL, have gradually lost their place. When a bank want to find the reason why the number of customer churn increased, or marketing department decide to push precise advertisement to their customer, they need to analyze customer behavior. These data from customer service emails, phone call records, sales interview reports, login data from mobile devices, and so on. Almost all of these data cannot be analyzed by traditional data analytic techniques. That’s why these new techniques development so rapid and fierce. How a company adopt big data analytics?

According to the article “Big Data, Analytics and the Path from Insights to Value” published on MIT Sloan Management Review, the author categorized the company who used big data analytics into three stages (See Exhibition II). For most companies, it is easy to establish an enterprise data warehouses (EDW’s). However, how to interpret these data and finding the business value from these data become the most crucial factor for companies. Besides, so many techniques and tools behind the term big data. For any company who decide to adopt big data analytics, the leading obstacle is lacking of understanding of how to use analytics to improve their business. From the article, the author gave 5 recommendation to any company who wanted to adopt big data analytics.

1. Think Big. Focus on the biggest and highest value opportunities. Narrow down the options. 2. Start in the Middle. Within each opportunity, start with questions, not data. Company prefer to collect data and information at first place. In fact, start with questions could help company continue to narrow down the scope and define the most valuable direction. 3. Make analytics come alive. When Problem was defined, company need to apply analytics. Choosing the propriety tools to analyze the data. 4. Add, dong detract. Use centralized analytics. Every analysis is connected. 5. Build the parts, plan the whole. Big data from everywhere. The data will become more and more big and complex. Building the data infrastructure is crucial for big data analytics. Big Data, Big Opportunity

When company decide to concern big data, it means every department are involved. Big data is not IT department’s or analysts’ responsibility. In fact, big data analytics need information and help from sales, marketing, R&D, IT and even external sources. Today, number of companies have entered into big data market. The following chart lists some big organizations who have adopted big data analytics. Besides, some of them provide big data services to other companies

These organizations are just the tip of the iceberg. When big data converted from Blue Ocean to Red Ocean, some of these organizations have turned into services provider. This become a future trend in big data area. Big data needs expensive hardware and labor cost. Not every company can afford that. Besides, big data involved so many different computer technologies, not everyone understood all these techniques. For that matter, there will be more and more companies try to seek big data service from external environment. Using the external big data platform or tools could reduce the cost for building a totally new technique teams. What the companies need to do is finding the problem, narrow down the scope and sending the needs to services provider. When they get the analysis result, they could use the valued result to take the next action.

Furthermore, these services provider will not only focus on big companies. The new fashion is to provide friendly interface and easy to use product to individual customer. What behind big data will be still mystery for people, however, the face or terminal of big data will become more and more friendly and simple. There is an example: Twithink. Twithink is a program invented by a MIT group. They provide customized twitter behavior analysis for customer. This program could draw some conclusion by analysis the unstructured information on Twitter. They collected the gender, location, time, key words, images, etc. from tweets. Then they analysis these data under certain arithmetic to draw conclusions. The last research was the Election in 2012. The latest research is Gun Control discussion which still in progress.

Problem and threats.

Although big data has many opportunity and advantage for enterprises, it still has some disadvantages. The first crucial problem is privacy invasion. After you searched one product on Amazon, the next time when you login to Amazon, you will find the products you may interested which was Amazon pushed to you. This is called precise advertisement. However, you even didn’t know when amazon collected your information. Another example was Google Analyst, company embedded code into their website to collect people’s internet behavior.

These things happened every day and everywhere. It is hard to argue this action is right or wrong. Maybe some are good. However, if personal data is sold or published by someone, it will affect individual’s daily life. It will become a crucial problem. The Second problem is information’s validity. According to the article “With big data comes big responsibilities” points out that “big data sets are never complete”. If data is insufficient, the analysis result would be invalid or distorted. The invalid information would guide company to wrong direction and cause a big loss. Thus, big data also has two side. How to use it to create more value for company is the first consideration for all managers.

Reference

1. “Office 2013 Brings BI, Big Data to Windows 8 Tablets.” ZDNet. N.p., n.d. Web. 25 Jan. 2013. 2. “Big Recognition for IBM Big Data.” Smarter Computing Blog Big Recognition for IBM Big Data Comments. N.p., n.d. Web. 25 Jan. 2013. 3. “Big Data.” Wikipedia. Wikimedia Foundation, 26 Jan. 2013. Web. 26 Jan. 2013. 4. “Structured Data.” Webopedia. N.p., n.d. Web. 26 Jan. 2013. 5. “Unstructured Data.” Webopedia. N.p., n.d. Web. 26 Jan. 2013. 6. Group of EMC. Big Data: Big Opportunities to Create Business Value. Rep. EMC, n.d. Web. 26 Jan. 2013. 7. Philip Russom. Big Data Analytics. N.p.: TDWI, 2011. Print. 8. Lavalle, Steve. “Big Data, Analytics and the Path from Insights to Value.” MIT Sloan Management Review Winter 2011: 21-31. Web. 9. “大数据已成红海?!全球十四个大数据公司全面盘点!.” N.p., n.d. Web. 26 Jan. 2013. 10. “IBM InfoSphere Platform Big Data, Information Integration, Data Warehousing, Master Data Management, Lifecycle Management & Data Security.” IBM InfoSphere Platform Big Data, Information Integration, Data Warehousing,
Master Data Management, Lifecycle Management & Data Security. N.p., n.d. Web. 26 Jan. 2013. 11. “Amazon Web Services, Cloud Computing: Compute, Storage, Database.” Amazon Web Services, Cloud Computing: Compute, Storage, Database. N.p., n.d. Web. 26 Jan. 2013. 12. “Oracle Big Data Appliance.” Oracle Big Data Appliance. N.p., n.d. Web. 26 Jan. 2013. 13. “Google BigQuery Feedback on This Document.” Google BigQuery. N.p., n.d. Web. 26 Jan. 2013. 14. “EMC Greenplum Data Computing Appliance – Data Warehousing, Data Analytics (FW).”EMC Greenplum Data Computing Appliance – Data Warehousing, Data Analytics (FW). N.p., n.d. Web. 26 Jan. 2013. 15. “Teradata.” Data Appliance, Data Warehouse, Business Intelligence –. N.p., n.d. Web. 26 Jan. 2013. 16. “Twithinks.” TwiThinks. N.p., n.d. Web. 26 Jan. 2013.

17. Eria Naone. With Big Data Comes Big Responsibilities. N.p.: MIT Technology Review, n.d. 2011.

A glimpse of Big Data Essay

Group-based assignment Essay

Group-based assignment Essay.

Assignment

Each coursework group will be allocated two real-life companies that are publicly traded on a U.S. stock market. To find out the names of your group’s two companies, please visit the BMAN23000 Blackboard site: the names of the companies allocated to each coursework group, and the names of the students allocated to each coursework group, are given in the Group and Company Allocation file available from the BMAN23000 Blackboard site. The file indicates which of the two real-life companies you should treat as “Company A” and which as “Company B”.

Besides the company names, the Group and Company Allocation file also provides the companies’ identifiers: their PERMNO and GVKEY; these identifiers are used to collect company data from the databases as described below. No further data (besides that in the Group and Company Allocation file) is provided. It is the responsibility of each team (and all team members) to collect all necessary data required to complete the assignment.

Suitable databases are available and described below.

Part 1

To complete this part, you will require data on your two companies’ monthly common-stock returns from January 2002 to December 2011. Required:
a) Suppose you are advising an investor who wants to invest all her wealth in the stock of just one of the two companies allocated to your coursework group (Company A or Company B). i) Provide brief descriptions of Company A and of Company B. ii) Next, compare and contrast the stock return performance of the two companies’ common stocks over the calendar period using monthly return data from Jan 2002 to Dec 2011. Specifically, calculate the mean, variance and standard deviation of the monthly returns of the two stocks separately.

iii) Briefly comment on your results and make a stock recommendation. b) Now suppose you are advising an investor who is considering investing all her wealth in a portfolio consisting of the two companies’ common stock held together. i) Calculate the mean, variance and standard deviation of the returns of portfolio comprising the two stocks with equal weights (i.e. 50:50). Next repeat the calculations for alternative portfolio weights, including 20:80, 40:60, 60:40, and 80:20. You may choose to construct additional portfolios (but remember the portfolio weights need to add to 100%). Report your results in a table. Compare and contrast your findings with those of the single-stock portfolios in part (aii).

ii) Illustrate your results in part (bi), along with the single-stock results in part (aii), in a graph plotting the trade-off between the mean and standard deviation of the portfolio returns. iii) In the trade-off graph in part (ii), indicate the efficient frontier (assuming the stocks of Company A and B are the only available assets). iv) Finally, identify the minimum variance portfolio in the tradeoff graph.

To do so, you can use trial and error, or the method outlined by Copeland, Weston and Shastri (Financial Theory and Corporate Policy, 4th International Edition, pp116-7; a copy of the relevant pages will be on the BMAN23000 Blackboard site). Report the portfolio weights of the minimum-variance portfolio, and the mean, variance and standard deviation of returns of the minimum-variance portfolio. v) Based on your findings in the previous parts, briefly explain to the investor how to choose her optimal portfolio assuming the two stocks are the only assets available to her. Also briefly indicate how your advice would change if other assets became available to the investor.

Part 2

The senior management of Company A employ you to advise them on the cost of capital the company should use to calculate net present value and decide whether or not to undertake a new investment project. You may assume that the new project is comparable to the average of the company’s existing projects in all respects. Make sure you correctly identify which of your two companies is “Company A”. Note also that you were allocated randomly drawn and randomly paired companies. Therefore, Company B is probably not a useful comparable for Company A’s new project.

Required:

a) Calculate investors’ required returns on Company’s A’s equity. Remember, there are many ways of estimating investors’ required returns (see Lectures 1-2, Semester 2). You should use two alternative ways of calculating the required returns to check how sensitive your result is to using different methods; i.e. to check the robustness of your result. For example, you could use the Fama-French three-factor model in addition to the Security Market Line (SML), which uses a single factor (beta). See e.g. the article by Fama and French (1997) in the suggested readings below. b) Calculate Company’s A’s debt cost of capital.

The bond yield can be calculated as Yield = risk-free rate + credit spread. Data on the approximate credit spread for a given credit rating is provided in the section on Debt data below. For simplicity, you may assume that the only securities outstanding of the company are common stock (equity) and long-term debt. Note that the after-tax cost of debt is lower than the pre-tax cost of debt if there is a tax advantage of debt relative to equity (interest tax shield). c) Calculate the cost of capital (that is, the appropriate discount rate to calculate the net present value) of Company A’s new investment project.

d) Clearly explain your calculations and methods used in parts (a) to (c). Among other things, note explicitly whether your results are in terms of monthly or yearly returns (either or both are acceptable as long as clearly labeled). Briefly describe and justify the data and (proxy) measures you are using. State and discuss any assumptions you are making (including assumptions about the financing of the project). e) Briefly discuss any limitations of your analysis and how (given more time and information) you might refine your analysis in the future.

Collecting data

To complete the assignment, your group will need to collect various sorts of data which can be downloaded from the Wharton Research Data Services (WRDS) website, http://wrds.wharton.upenn.edu/. To sign in on WRDS, use the following:

username: bm23000
password: KT6zuu1

Note the use of capitals and lower-case letters. At the end of the password is the number 1 (one) – not the lower-case letter l. To get accustomed to downloading data use the link to the support on the left hand side of the page. Then click on Query Demo which is under Basic Help. This leads you through an example of how to download data from COMPUSTAT. Most of the data you need will be on the CRSP data set, the COMPUSTAT North America data set, and the Fama-French data set. Please note the terms and conditions for use of the WRDS data.

Equity data

Download the equity return data from the CRSP database. After signing in on WRDS, go to the Select a Data Set: window on the left of the screen, click on the down arrow and select CRSP. Always search by the PERMNO identifier when downloading data on your company from the CRSP data set. The PERMNO of each of your two companies is given in the Group and Company Allocation file. You will need to download the monthly holding period returns. Holding period returns are defined as follows: [pic]

where rit is the holding period return for company i for month t, pit is the price of company i at the end of month t, dit is any dividend declared ex div during month t adjusted to an end-of-month basis, and pit−1 is the price of company i at the start of month t (adjusted if necessary for any changes in capitalizations to make it comparable with pit). If you want to express returns in percent (%) you have to multiply the equation for the (decimal) holding return above by 100. Make sure you convert returns collected from different data sources to the same units (decimals or percent). In your baseline calculations use monthly return data from Jan 2002 to Dec 2011.

The total market value of the equity (market capitalization) can be calculated by multiplying the number of shares outstanding by the price of the shares. The number of shares and the share price are available from the CRSP data set. To go to the Fama-French data set on WRDS, go back to the WRDS home page: in the Select a Data Set: window (on the left of the screen) select Fama-French Portfolios and Factors. From the Fama-French data set, you can download the excess returns on the market (rm − rf ), the Fama-French factors, and the risk-free rate (rf ). Click on Factors-Monthly Frequency on the left-hand side of the page when in the Fama-French database on WRDS.

Debt data

The data on debt can be downloaded from the COMPUSTAT North American database. On the WRDS home page, in the Select a Data Set: scroll-down menu on the left of the screen select Compustat; when the Compustat page comes up select Compustat Monthly Updates North America (on the left below the Select a Data Set: scroll-down menu). On the next screen, select either Fundamentals Quarterly (or Fundamentals Yearly) to select debt values; or select Ratings to collect credit ratings. (There may be a brief delay while the system displays results saved by other users in the past. Please ignore these save results.) To identify your company on Compustat, use the company’s GVKEY (not its PERMNO). Fundamentals Quarterly/Yearly: Scroll down to the window that allows you to select Quarterly Data Items; within the window scroll down again until you find the variable DLTTQ — long term debt – total; tick this variable and submit your query to download the data.

For simplicity, you may assume that long term debt – total is equivalent to the market value of debt for your company. It is important to note that the long term debt data is in Millions (because it is Compustat data); by contrast, the data on equity values (e.g. shares outstanding) is from CRSP and is in Thousands. Ratings: Select an appropriate credit rating for your company. For simplicity, you may assume that your company only has long-term debt, so the appropriate rating is S&P Long-Term Domestic Issuer Credit Rating. Note that there are no data on the time-series of bond returns for individual companies on the WRDS database.

In fact, you do not need (to construct) the time-series of bond returns to complete the assignment – you only need to download one observation of the credit rating and one observation of the debt value. See e.g. Berk and DeMarzo (Section 12.4, Chapter 12 in the second edition only) for details on how to calculate the debt cost of capital. The bond yield can be calculated as Yield = risk-free rate + credit spread. Data on the approximate credit spread (at start of 2012) for companies with a given credit rating are shown in the table below:

|For large manufacturing firms |For financial service firms | |Rating is |Spread is |Rating is |Spread is | |D |20.00% |D |16.00% | |C |12.00% |C |14.00% | |CC |10.00% |CC |12.50% | |CCC |8.00% |CCC |10.50% | |B- |6.00% |B- |6.25% | |B |4.00% |B |6.00% | |B+ |3.25% |B+ |5.75% | |BB |2.50% |BB |4.75% | |BB+ |2.00% |BB+ |4.25% | |BBB |1.50% |BBB |2.00% | |A- |1.00% |A- |1.50% | |A |0.85% |A |1.40% | |A+ |0.70% |A+ |1.25% | |AA |0.50% |AA |0.90% | |AAA |0.35% |AAA |0.70% |

Figures are in per cent per annum.

Source: Damodaran Online http://pages.stern.nyu.edu/~adamodar/ (accessed Jan. 2012). In the event that the rating of your company is not shown in the table above, you should use the spread for the next lower rating. Alternatively, you may search for, and use, other sources of information. In either case, please briefly explain your data and method in your report (e.g. in a short footnote).

Estimating equity betas

You can estimate the CAPM beta of Company A’s equity using the following regression: [pic] where rit is the monthly return on the company’s stock, rmt the monthly return on the market, rft the monthly return on a “risk-free” asset, and (it is the error term. In your baseline calculations use monthly return data from January 2002 to December 2011. In your calculations you should use the Fama-French data set as the source for market excess returns and the risk-free rate. Calculations can be done in Excel. You will need to ensure that the Analysis ToolPak has been added in. You can easily check this by clicking on Tools in the menu at the top of the screen in Excel. If it has been added, Data Analysis… will appear in the list. If Data Analysis… is not there, click on Add-Ins… and check (i.e., tick) the Analysis ToolPak box.

The Regression function in Excel can be found in the Data Analysis… part of the Tools menu. When you click on Regression, you will be asked to input a Y range and an X range. In the SML equation (of the CAPM), the Y range is your company’s excess return (rit – rft) while the X range is the excess return on the market (rmt – rft). See Lectures 1-2 (Semester 2) for more details including interpretations of the regression coefficients. Please remember to use the Help menu in Excel.

Report requirements

Please adhere to the School’s policy on coursework as outlined in the Assessed Coursework Rules on the MBS UG intranet: https://ughandbook.portals.mbs.ac.uk/Myassessment/Assessedcoursework.aspx . Provide a report of no more than eight (8) pages inclusive of everything: tables, references, appendices, etc. As outlined in the next section, you are required to attach a standardized cover sheet that can be downloaded from the BMAN23000 Blackboard site. The eight-page limit does not include this standardized cover sheet: you can submit up to eight pages PLUS the standardized cover sheet. You do not need an additional cover sheet or a table of contents.

There will be penalties for exceeding the page limit. Specifically, a penalty of five percentage points will be applied (i.e. five marks will be deducted from your group mark) for submitting a report that is one page over the limit. Two or more pages over the limit will attract a penalty of ten percentage points. You are required to adhere to the formatting outlined in the Assessed Coursework Rules. If you do not adhere to the prescribed formatting, a penalty of five percentage points will be applied to your group mark. In addition, your report will be reformatted (you may be asked to provide an electronic copy for this purpose), and if applicable, page-limit penalties will be applied to the re-formatted version.

Submitting the Coursework

The deadline for submission of the group report and the Individual Contribution form is 15.00 (3pm) on Thursday 9 May 2013. It is advisable to submit your report and form one or several days before the final deadline to avoid any last-minute rush and complications. For further details on coursework submission, the UG Office opening times, and the School’s policy on the late submission of coursework, please read the Assessed Coursework Rules on the MBS UG Intranet: https://ughandbook.portals.mbs.ac.uk/Myassessment/Assessedcoursework.aspx . Each group is required to submit TWO HARD COPIES of the report to the Undergraduate Office in Room D20, MBS East (i.e., Undergraduate Services, Manchester Business School, The University of Manchester, Room D20, MBS East, Booth Street West, Manchester M15 6PB, Tel. +44 (0) 161 275 4011), no later than 3pm on Thursday 9 May 2013. Each copy of the report must have a completed cover sheet.

The (blank) cover sheet you should use will be available on the BMAN23000 Blackboard site. The cover sheet must contain the coursework group number and all the registration numbers of the individuals in that group. Do not write your names anywhere on the report, as it will be marked anonymously. Each student should personally keep an electronic copy of the project and may be required to provide this at a later date. Separately from the group report, each member of a coursework group must submit ONE HARD COPY of the completed Individual Contribution form to the Undergraduate Office in Room D20, MBS East, no later than 3pm on Thursday 9 May 2013.

The (blank) Individual Contribution form can be downloaded from the BMAN23000 Blackboard site. The form must give your registration number and group number. A penalty of five percentage points will be applied (i.e. five marks will be taken off your individual mark) if you do not submit your individual contribution sheet (on time). It is your responsibility to make sure that the assignment is submitted on time and in the correct manner. The School accepts no responsibility for the loss of assignments not submitted in the appropriate way. Please note that plagiarism is a very serious offence. You should read the University guidelines on plagiarism.

Feedback

Written feedback for each team will be available at the same time as the exam results. You will be able to see your team’s feedback form at the Undergraduate Office (D20, MBS East).

The Groups

You will be allocated randomly by the course coordinator to a coursework group. Coursework groups will consist of approximately 6 students attending the same workshop. Occasionally the groups will have 5 or 7 members. Students who were not registered for a BMAN23000 workshop on Campus Solutions by the end of Week 2 (in Semester 2) were not allocated to a coursework group. Please check the Group and Company Allocation file on Blackboard. If your name does not appear on the file, you need to contact the Undergraduate Office (D20, MBS East) urgently. It is your responsibility to ensure that you are registered and allocated to a coursework group. If you are not allocated to a group, you may receive a mark of zero for the coursework.

Simple ground rules for group work
1. Exchange contact details (email addresses, mobile phone numbers, etc.).
2. Fix a schedule of meetings.
3. Ensure you attend every group meeting.
4. Agree an agenda.
5. Don’t allow one person to monopolize the meeting, though avoid unnecessary interruptions. If necessary, suggest giving others a chance to speak. 6. Encourage everyone to participate; invite ideas from quiet individuals. 7. Try to be constructive and only criticize ideas, not individuals. 8. Stick to a timetable—for meetings and for assigned tasks. 9. Ensure everyone understands what your group goal is and how you have agreed to achieve this. Document this in writing. Each group member should keep documentary evidence showing how they personally contributed to achieving the group goal. 10. Think about how the overall exercise can be divided into smaller tasks. 11. Coordinate the tasks:

• which tasks need to be completed before subsequent ones? • who wants to do which task?
• how do you assign tasks that nobody wants to do?
• is the workload equally shared?

The idea of the project is to simulate as closely as possible what happens in the team-based projects in the business world. Discussion of choices of calculation/methodology etc. should occur within the group in order to come to a group decision on the best way to proceed. You should realise that any disagreement or difficulties between group members is a problem for the whole group. It could result in a lower group mark. One aspect of group skills is overcoming these problems if they arise (it is no good complaining to your tutor or the course convenors.) Try to identify any problems early. Raise and discuss them before they become unmanageable.

Try to deal with them as group problems, not as individual, personal issues. Note that neither the lecturers nor the workshop leaders will sort out group problems for you: they are for the group to sort out (but see below on what ‘powers’ you have if you have a free rider). Keep evidence of your work and your contribution to the group report, such as copies of correspondence and draft work you completed, in case you are asked to proof that you did not free ride.

Required (for the individual part)

As part of your submission each group member must fill out and submit an Individual Contribution assessment form. These forms are to be submitted separately from the group report. They will be kept confidential, so the only way any of your teammates will know how you graded them is if you tell them. When completing the individual contribution form, you need to use your fellow group members’ individual “student group numbers” and not their names nor their registration numbers.

The Group and Company allocation file gives the individual “student group number” for each individual member of your coursework group. The file is available on Blackboard. You do NOT require the registration numbers of the other group members. You are required to rank each individual group member according to their contribution relative to the rest of the group. You will allocate each individual a grade. The grading range will be −−, −, 0, + and ++, where double minus (−−) is the lowest (worst) grade, and double plus (++) is the highest (best); you can think of these grades as fail through to first class. If you award a double minus (−−) you must explain in your Individual Contribution form why you awarded this.

How Do I Assess Performance?

Some Words of Warning

1. Personal feelings must be put to one side. Don’t forget, you have to justify why someone was worth a −−. If your reasons for awarding these are wholly unreasonable, they could be counted against you. 2. Free riders will receive a mark of zero. If you do nothing for the assignment, you can expect a mark of zero because you will be deemed not to have done the assignment. Please note that just turning up to one or two meetings and not saying anything counts as not doing the assignment. To avoid a mark of zero, you have to contribute. See below for further details.

Suggested Criteria

Please note that when filling in the ‘Individual Contributions’ form, use your teammates’ STUDENT GROUP NUMBERS, not their names or registration numbers. 1. Was the individual cooperative/indifferent/uncooperative in drawing up a plan of how the work should proceed? 2. Did the individual attend all/some/none of the meetings?

3. Did the individual contribute anything in the meetings? 4. Was the contribution (if any) in meetings always negative or was the individual constructive in trying to help solve problems? 5. Was any criticism personal or was it constructive criticism of ideas?[1] 6. Did the individual contribute to the computations or the writing of the report or both? 7. Was the individual cooperative in getting the work done or was getting them to contribute like trying to get blood out of a stone? 8. Was the individual a good ‘team player’?

Free Rider Problems

A question that may arise is ‘what can we do person X who has done nothing, despite requests.’ The answer is straightforward: on the Individual Contribution form, you have it within your power to award a −− (double minus) to person X. Remember to give person X’s student group number – not name or registration number). Recall that if you award a −−, you have to explain why.

How are the individual contribution marks used?

The individual contribution sheets will be examined to check that all the group members contributed to the project. A group member who receives double minus (−−) from all or most of the other group members will receive a coursework mark of zero. Anyone at risk of being awarded a mark of zero will be contacted by the course convenors and given the chance to defend themselves. In order to proof your contribution (if necessary), please keep evidence of your involvement. This includes saving relevant email correspondence and keeping copies of work you did. You could keep minutes of meetings, written details of work allocation, deadlines for work to be completed, and receipts of completed work. If you cannot prove that you contributed (after getting double minus marks from all or most other group members), you will receive a mark of zero. It is the convenors who determine whether someone was a free rider and receives a mark of zero based on all available evidence.

Assessment

For information on the kinds of criteria that will be used in assessing the projects, please see details of assessment criteria in your programme handbook. Please note the School policy on plagiarism and on late submission as outlined in the Assessed Coursework Rules on the MBS UG Intranet. Also be aware of the penalties (outline above) for exceeding the page limit, using non-standard formatting, and for failure to submit a completed Individual Contribution form. Please note that the teaching staff on this course will not read or comment on any drafts of the project before it is officially handed in.

Blackboard forum

Questions concerning the coursework can be posted on the BMAN23000 Blackboard discussion forum. The forum will be monitored by teaching assistants in consultation with the course lecturers. There are some rules relating to the forum: • Do not expect the forum to be a place where you can engage in question and answer sessions with members of staff. The forum is a place where students can engage in staff-monitored discussion with other students about issues and difficulties relating to the project. • The forum is not a substitute for thinking: do not expect other to do your thinking for you. • Questions posted on the forum that have already been answered will not be answered again. It is up to you to search through questions and responses that have already been posted to see if your particular question/issue has been already addressed. • Do not expect questions to be answered as soon as they are posted. • Please use the web support for WRDS to learn how to download data before turning to the forum.

Suggested readings
In addition to the reading associated with the lectures and workshops, and the course textbook Berk J. and P. DeMarzo Corporate Finance, 2nd edition (Note that the material in Chapter 12 of the 2nd edition is important and not available in the first edition). you may find the following useful:

Brealey, R. A. and S. C. Myers. Principles of Corporate Finance, 9th ed. Chapters 9-10. Copeland, T., Weston, J. and K. Shastri. Financial Theory and Corporate Policy, 4th International Edition, pp116-7. Fama, E.F. and K.R. French, 1997, Industry costs of equity, Journal of Financial
Economics 43, 153–193. Articles in academic journals including the Fama-French article (above) can be downloaded from the John Rylands Library: http://www.library.manchester.ac.uk/searchresources/electronicjournals/ . ———————–

[1] Remember, someone who disagrees with an idea you have, or criticizes an idea you have, is not necessarily criticizing you personally.

Group-based assignment Essay

Battery Monitoring System Essay

Battery Monitoring System Essay.

The modular measuring system consists of two different types of monitoring units, a battery block-voltage monitoring unit and a battery current- and temperature monitoring unit. Following the discussion of the measuring hardware, a LabView realization of a universal BMS software is described in detail. Due to the flexible design of the LabView BMS, the system is able to perform control and surveillance activities for any kind of battery application and battery technology (e. g. Pb, VRLA, NiCd, NiMH etc. ).

The BMS was originally designed for VRLR batteries in uninterruptible power supply systems (UPS), but was also tested in electric vehicles (VW CityStromer, BMW).

In a second step, a universal battery management system (BMS) was realized as a LabView application. The use of a personal computer instead of a microcontroller leads to much higher flexibility of the BMS and allows easy adaptation to various kinds of battery applications and battery technologies. The LabView-based BMS controls data acquisition, performs data processing, visualization and storage and provides a graphic user interface.

Apart from monitoring features, the BMS evaluates the measured data and interacts with external components, such as the charger, the temperature regulation system and the inverter controller. A modem battery management system, in contrast to simple battery monitors, is capable of actively affecting battery operation. Before the presentation of the new measuring hardware and the LabView-based battery management system, the main principles and general structure of a BMS are discussed. I INTRODUCTION I1

Strong requirements concerning battery life-time, reliability and energy-efficiency are imposed on modem battery applications, e. g. , on batteries in unintermptible power supply systems (UPS) or batteries in electric vehicles (EV). These high demands can only be met by employing sophisticated battery monitoring and management systems. At present, battery users (e. g. in telecommunication energy supply or in power stations) know too little about the state of their batteries to draw economically optimized decisions concerning maintenance and replacement.

The employment of a battery monitoring and management system helps finding the right time for battery maintenance and replacement and, in addition, will lengthen the service intervals due to taking active influence on battery operation. GENERAL STRUCTURE OF A BMS Fig. 1 shows the general structure of a battery management system and divides the tasks to be performed into logical blocks [2, 8, 91. Battery management systems require battery data (battery block-voltages, current and temperature) and environmental data (temperature). Furthermore, application depending system data is needed.

To obtain these values, a specialized data acquisition system is used. An example of a suitable data acquisition system for BMS is pre1. sented in chapter 1 1 The following logical block of a BMS (see Fig. 1) performs the data processing. Apart from decoding the transmitted measured values, this block calculates battery quantities (e. g. entire battery voltage, average battery temperature, etc. ), integrates quantities like the battery current and performs statistical analysis (e. g. distribution of block voltages, deviation of block voltages from the average block voltage, etc. . Furthermore, the data procession unit needs information about the present maximum and minimum limit of block voltages, the maximum battery current etc. This information is either deduced from the system’s battery model or can be provided directly by the user (“parameter correction”). The parameters of the battery model have to be continuously adapted to the measured and computed quantities (e. g. , temperature, average load current) to ensure that the model accurately represents the battery’s present state. 630

To control battery operation, battery management systems require the accurate measurement of battery block voltages, battery current and battery temperatures. Therefore, in a first step, a modular data acquisition system, specifically designed for battery applications, was built. The measuring hardware consists of two different types of monitoring units, a battery block-voltage monitoring unit (VMU) and a battery current- and temperature monitoring unit (CMU), which have been developed in cooperation with SIEMENS AG, Erlangen.

VMUs have already been employed in the SIEMENS Masterguard UPS in order to provide the system’s microcontrollerbased BMS with the required measured data. 0-7803-5069-3 /98/$10. 00 01998 IEEE Fig. 1 Structure of a battery monitoring and management system (BMS). In Fig. 1, the logical block “parameter adaptation” is responsible for battery parameter determination and update. The “monitoring” block in Fig. 1 performs fault detection and user information activities. Fault detection checks if a battery quantity has exceeded or is likely to exceed its allowed limits.

Measured data, alarm messages and information related to service or maintenance needs are given to the user interface by the monitoring block. In contrast to the monitoring block, the “management” block is responsible for fault avoidance, which aims to keep the battery within certain limits of operation. If a quantity is going to exceed a limit, the management system reacts, for example, by activating the cooling system. In extreme situations, e. g. , in the case of exhaustive discharge, the fault avoidance may limit or even interrupt the current to protect the cells against reversion.

Furthermore, the management block is able to control intelmethod, preligent charging algorithms like the IU,,, sented in [3], which limits the maximum of each battery block-voltage instead of just limiting the entire battery voltage during the time of constant-voltage charge. In Fig. 1, the external components, which are influenced by the management block (charger, coolingheating system, inverter controller) are summed up in the “control” block. The hnctional block “in-/output” represents the user interface which gives selected data and messages to the user and which allows user intervention, e. . the correction of battery or system parameters. Data selection as well as data storage are represented through the logical block “data management”. 111 DATA ACQUISITION SYSTEM Fig. 2 shows the structure of the measuring and data acquisition system, consisting of battery block-voltage monitoring units (VMU) and current- and temperature monitoring units (CMU) [ 1,2]. Data transfer between the measuring units (any number and sequence is possible) and the data acquisition unit (DAU), which represents the interface to the data processing block of Fig. , is performed via a fiber-optic transmission system (FOTS). Optic data transmission provides electric insulation of the modular measuring system and leads to high immunity against electromagnetic noise. Power supply for the VMU and CMU is drawn directly from the measured batteries which minimizes the number of electrical connections and therefore leads to an easy and fast installation. The VMU measures up to eight voltages each ranging from 0. 3 V to 16 V with an accuracy of 0. 15 YO, which enables the measurement of single-cell and block voltages for any type of battery.

Depending on the shunt resistor, the CMU is able to measure battery current, e. g. , over a range fiom OA up to f 300 A. The CMU also measures battery temperature (-5OC to 6OOC). When the battery management system does not need measured data, the monitoring units rest in a stand-by mode during which the modules’ power consumption is negligible compared to the self-discharge of the batteries. As soon as measured values are needed, the units are switched on by the central data acquisition unit using the fiber-optic transmission ring.

After some setup-routines are completed, the VMUs and CMUs start the measuring process. As soon as data is available, the modules store the measured values in their transmission buffers. Receiving a so called “data-locomotive”, the first module 631 214 –. . – I t Data Acquisition Unit I 1 I —-I Fibre Optic Transmission System (FOTS) T T t 8 block voltages Fig. 2 8 block voltages 8 block voltages 5 temperatures and 3 currents t 5 temperatures and 3 currents t Structure of the measuring and data acquisition system [ 11.

The electric data input and data output signals of the serial port (TxD, RxD) are transformed into optic signals and are transmitted via the fiber optic transmission system. The electric handshake signals RTS and CTS as well as DSR, DTR and DCD are not transmitted so that, on the one hand, only one transmission ring is needed, but, on the other hand, hardware handshake signals cannot be used. Therefore, during the development of the LabView BMS much effort had to be taken to ensure the synchronization of data communication between the measuring units (CMU and VMU) and the personal computer.

Having started the Labview application for the first time, the user is asked to provide obligatory system information, e. g. , the number and sequence of the measuring units, the value of the shunt resistor for current measurement, the time between new measurement requests and the paths for data storage. At the moment, the presented system is pre-configured to deal with up to eight measuring modules. The default time interval between measurement requests is set to four seconds, but can be augmented as well as shortened (down to one second) by the user. After the receipt of a valid data chain, LabView decodes the transmitted data.

If the decoded data is recognized as measured values (and not as error message) these values are compared with the corresponding maximum and minimum limits. If a measured value exceeds the tolerated interval an alarm message is generated and shown on the graphic user interface. The minimum and maximum limits may be set by the user, or be deduced from an appropriate battery model. User interface: A screen shot of the user interface called “front panel”, can be seen in Fig. 3. On the front panel, the user can provide input information. Besides, the average battery interrupts the measuring process and starts sending the data-locomotive ollowed by its own measured data to the next module in the ring. This module recognizes the locomotive and the transmitted data and attaches to the data chain its own measured values. The central acquisition unit is able to decode the received data chain as it knows the order of the monitoring units [l]. IV LABVIEW-BASED UNIVERSAL AND BATTERY MONITORING MANAGEMENT SYSTEM (BMS) LabView (Laboratory Virtual Instrument Engineering Workbench) from National Instruments Corporation is a software development application which uses a graphical programming language, G, to create programs in block diagram form.

Since LabView includes libraries of functions for data acquisition, serial instrument control, data analysis, data presentation and data storage it commends itself for the BMS application. LabView programs are called “virtual instruments (VI)”. These VIS consist of an interactive user interface (“front panel”, see Fig. 3), a dataflow diagram that serves as the source code, and icon connections that allow the VI to be called from higher level VIS [ 5 ] . As the BMS is executed on a personal computer, it offers higher flexibility and much more graphic tools for data visualization than microcontroller-based systems.

Therefore, the central unit of the diagram in Fig. 1 as well as the in-/output interfaces have been realized as a LabView application. Data acquisition: For communication between the measuring system and LabView (request for and receipt of measured values) one of the serial ports of the personal computer is used. 632 27-4 Fig. 3 Front panel of the LabView-based BMS eight measuring channels and can localize the battery block, which is exceeding its operation limits. Fig. 4 shows the display for module 1. The measured voltage of block 1 has exceeded ts maximum limit and, therefore, has caused the alarm message on the front panel. If the is in doubt, whether the battery,s usable ca- temperature, up to six currents of parallel battery strings and the entire battery voltage are constantly monitored. Fault detection: In case of an alarm message, the corresponding monitoring unit is marked. Clicking on the “module #,’button, the user gets detailed information about the module’s block 1 1 block2 1 block3 1 block4 block5 block6 block7 block8 i Fig. 4 Detailed information about measuring module 1 633 acity might have decreased, it is possible to run a battery-check discharge, which helps recognizing and localizing defective cells. This battery-check, which could be defined as a part of the fault detection functions (monitoring) of the BMS, but also as a part of active intervention (management) is described below (see “fault avoidance and intervention”). Data processing: ment, the battery charger, which performs a blockvoltage limiting and therefore battery protecting charging algorithm (1Uma), is connected to the BMS via a second RS 232 serial port. It is anticipated that future BMS applications, e. . , BMS in electric vehicles, will use modem fieldbus configurations, such as CAN bus, which will lead to more flexible, open systems. Data management: Apart from calculating the entire battery voltage and the average temperature, LabView calculates the battery’s state of charge using a modified Peukert equation [2,6,7]. Switching the button “SOC” the state of charge of the battery strings is shown on the display. Furthermore, the distribution of block voltages is displayed. The histogram of the measured voltages can be seen by clicking on the “voltage distribution” button.

Fault avoidance and intervention: Depending on the width of the voltage distribution, e. g. during floating operation, or depending on a decreasing usable battery capacity, the BMS is able to recognize if a so-called “battery conditioning” (in case of lead acid batteries) should be performed and gives a corresponding message to the user . A “battery conditioning” algorithm performs a special sequence of discharging and recharging periods which reverses to a certain extent aging of the batteries. A typical example of reversible damages of lead acid batteries is the so-called “premature capacity loss” [4].

To allow analysis of the data at a later moment, the measured values as well as the messages given to the user are continuously stored. This default storage mode is useful for battery examination in research and development. Using the BMS for common battery applications an event-controlled storage mode can be chosen, which stores a measured value, if it is significantly different form the value before. For future commercial battery applications, for example, battery leasing, another simple storage mode, which only records the alarm messages on the user display, could easily be employed.

V SUMMARY To determine the decreasing battery capacity in case of batteries during floating operation (UPS-batteries), it is possible to run a battery-check discharge (e. g. 10% of nominal battery capacity). During the battery check the battery block-voltages are recorded and compared with the corresponding values from previous tests. In case of significant deviations, the battery’s usable capacity Qo has probably decreased as well. Therefore, a “battery conditioning” has to be recommended.

If a measured temperature exceeds its limits or the differences between the measured temperatures exceed a predefined limit, a water circulation system is switched on. This system may either cool or heat the batteries or may just establish a uniform temperature distribution. Parameter adaptation: In this paper, a new developed, flexible LabView-based battery management system is presented. Through the LabView realization of the BMS (in contrast to older microprocessor based concepts [3]) it was possible to create an easily adaptable monitoring and management system for any kind of battery application.

Additional monitoring or management features for BMS can easily be added to the LabView software. Even unforeseen demands on BMS, that may turn up with the usage of new battery technologies, can be met without problems. VI ACKNOWLEDGEMENTS The authors would like to thank SIEMENS AG, Erlangen for supporting the development of the presented battery measuring system and, furthermore, acknowledge D. Linzen for his contributions to this project. VI1 REFERENCES A. Lohner, S. Buller, E. Karden, R. W.

De Doncker, “Development of a Highly Accurate, Universal and Inexpensive Measuring System for Battery Management Systems”, 15” Electric Vehicle Symposium (EVS), 1998, Brussels (Belgium) E. Karden, P. Mauracher, A. Lohner, “Battery Management Systems for Energy-Efficient Battery Operation: Strategy and Practical Experience”, 1 3 ~ Electric Vehicle Symposium, 1996, Osaka (Japan), Vol. 2 pp. 91-98 The amount of charge Qo which can be stored in and discharged from a battery at nominal values of current and temperature, is in general not equal to the nominal capacity QN, which is an effect of aging.

Therefore, which is a model parameter of the modified Peukert equation, has to be updated regularly, e. g. , during the conditioning cycles. Due to the modular structure of the LabView application, more sophisticated battery models may be implemented according to individual user’s requirements. Control interfaces: eo, Apart from communication between LabView and the measuring system for data acquisition, the BMS has to have other interfaces to control external components such as the cooling system or the battery charger. At the mo634 A. Lohner, E.

Karden, R. W. De Doncker, “Charge Equalizing and Lifetime Increasing with a New Charging Method for VRLA Batteries”, 19” International Telecommunication Energy Conference, 1997, Melbourne (Australia), pp. 407-41 1 27-4 [4] A. Lohner, “Batteriemanagement fQr verschlossene Bleibatterien am Beispiel von USV-Anlagen”, Dissertation am Institut fiir Stromrichtertechnik und Elektrische Antriebe, RWTH-Aachen, 1998 [5] National Instruments Corporation, “LabView User Manual”, Part Number 320999A-01, 1996 Edition [6] R. Giglioli, A. Buonarota, P. Menga, M.

Ceraol “Charge and Discharge Fourth Order Dynamic Model of the Lead-Acid Battery”, 10* Electric Vehicle Symposium, Hongkong, 1990, pp. 371-382 [7] W. Peukert, “Uber die Abhangigkeit der Kapazitat von der Entladestromstiirke bei Bleiakkumulatoren”, ETZ, Band 18, 1897 [SI E. Dowgiallo jr. “Innovative On-Board Instrumentation for EV Battery Characterization”, DOEEPRI Beta Battery Workshop 8,1991, pp. 215-218 [9] H. Kahlen, B. Hauck “Batteriemanagementsysteme fiir Traktionsbatterien”, Fachtagung der Deutschen Gesellschaft fiir elektrische StraBenfahrzeuge (dges), 1995, Berlin 635

Battery Monitoring System Essay

Airline Reservation System Essay

Airline Reservation System Essay.

Airlines search results are presented in an easy-to-use Matrix that displays a vast array of travel options for you. When customers prefer a specific travel itinerary, they offer the widest range of flight options and fares. User’s privacy is very important to us at Arabian Travels. With that in mind, we have established and implemented information handling practices for that we believe are consistent with the highest standards and best practices of organizations doing business.

SEA Airlines have prepared a detailed privacy policy because they believe users should know as much as possible about our practices so that they can make an informed decision about the extent of our firm.

1. 2ABOUT THE PROJECT SEA Airlines is a site, which helps the flight travelers. Its mission is to offer flexible leisure travelers a quick and easy way to get better deals on airline tickets. Through partnerships with leading travel companies, it can negotiate special prices that can’t be found anywhere else.

The working of the project is as follows. The first page provides several links.

The Home link contains several informations about the site; it provides a link to the login page. In the Login link a user have to login before ordering for tickets. An already registered user can simply type in -hisher valid username and password, and then click the “Login” button. But those visitors who are not registered have to go to the registration page before they login. In that page user have to enter First name, Last name, Address, Postal Code, City, Phone number, Username and password. About Us Link contains some information regarding SEA Airlines and its developers.

After registration user can reserve the seats in particular flights by using the flights date and time. The user can enter the number of seats required and the details of the passengers by specifying adult or child.

Airline Reservation System Essay