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In the case of a product, simply changing the size column in the database from 16 to 14 ounces makes it look like the size has always been 14 ounces If sales decline because of the change, it s entirely up to an analyst looking at the data to remember when the change occurred and identify the change in size as an issue The advantage of Type I is clear: it s easy No extra work is required Data is changed and the primary key remains the same, so all history now reflects the current values as if they have never been different The great disadvantage of Type I is also clear: history is lost With Type I, it s impossible to credit a salesperson s sales to a previous manager, to determine when a product change was introduced, and so forth Another approach is the Type II slowly changing dimension This type of dimension structure does maintain history, usually by versioning the record and then setting a start date and end date for each version For example, a salesperson named Raju starts with a company on January 1, 2007 and works for Manager Bob A year later, that salesperson is reassigned to Manager Maria On the first record for salesperson Raju, the Start Date would be January 1, 2007 and the End Date would be January 1, 2008 A new record would be added for Raju that still maintained his employee ID (or some other key) but was now version 2, and had a Start Date of January 1, 2008 and no end date Sales would be tracked by the employee ID so that all of Raju s sales always belong to him Raju s sales records also have the date on which they occurred, so that sales in 2007 roll up to Bob while sales in 2008 roll up to Maria While simple on the surface, this can certainly complicate working with the data, because all queries must now look at the start and end dates for all of Raju s entries in the Employee dimension table The advantage of a Type II dimension is clear: history is preserved Companies will always be able to track when the change occurred so that prior sales will still roll up to the proper manager Product changes will be evident because a change will start a new record with a new start date The disadvantage of a Type II dimension is also clear: it s complicated It makes storing, retrieving, and summing data much harder Changes require an update to the existing record (to set the end date) and the insertion of a new record with a new version number and the start date Taking multiple records that represent a single product or employee and making them appear as one to the end user can be a challenge There are other ways of handling slowly changing dimensions There are Type III, and modifications of Type II and Type III The actual mechanisms are beyond the scope of this book, as the goal is to show how to consume the data once the warehouse is built Still, slowly changing dimensions are introduced here because many readers will be involved in the decision of how to store dimension data and track history, and an understanding of the tradeoffs is important.

LEOs will be good for high-speed networking, teleconferencing, Telemedicine, and interactive applications GEOs will be better for information downloading and video distribution, such as broadcasting and multicasting We re able to use GEO satellites to transport at least 24Mbps of broadcast IP data and over 2Mbps of point-to-point TCP/IP data The latter uses technologies such as TCP spoofing Several vendors have been using this technique for years to deliver Internet and Intranet content at high speed Ground terminals can use similar TCP spoofing technologies Nevertheless, there s still the 250millisecond delay that you just can t get around Any lossless protocol is going to have problems with this latency Even if TCP spoofing works, given TCP s 64-Kb buffer makes this somewhat suspect, there s the matter of other protocols such as IBM s SNA and other real-time protocols that are designed around landline performance

In sumo, two of the most important factors that make a winning bot are strength and technique Simply having the strongest bot doesn t mean that you will have a winning bot; and having the smartest bot doesn t mean that you will have a winning bot, either Your bot needs both of these skills Strength is related to pushing power From physics, we know that pushing force is equal to the coefficient of friction between the bot wheels multiplied by the weight of the bot This simple relationship pretty much tells you what you need to have in a strong bot: weight and traction The higher the coefficient of friction, the better the traction the bot will have The heavier the bot is, the greater the amount of force required to move it It is best to make your bot as heavy as possible for it s weight class For a mini sumo, this is 500 grams As for traction, soft wheels usually have better traction than hard wheels Some bots have placed rubber O-rings or rubber bands on the outside diameter of the wheel to improve traction, and others have used foam wheels like you see on model airplanes Weight and traction are the two most common ways to improve the performance of mini sumos The other way to win is to use better strategy during the actual contest This really comes down to the type of programs you use in your bot Some bots spin more than they move in straight lines Some bots use more sensors to improve vision capabilities, where others use a stealth approach to keep from being seen Some bots even use arms to try to capture or corral their opponent This is what makes robot sumo exciting, because it allows for many different types of bots to enter the competition In fact, biped and hexapod bots have competed and have even won some matches The Basic Stamp 1 microcontroller used in this example doesn t have the memory space for advanced software control You will need to use a different microcontroller such as the Basic Stamp 2 or the BasicX-24 from NetMedia (wwwbasicxcom).

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