ادامه مطلب ...
An expert system is a computer application that solves complicated problems that would otherwise require extensive human expertise. To do so, it simulates the human reasoning process by applying specific knowledge and interfaces. Expert systems also use human knowledge to solve problems that normally would require human intelligence. These expert systems represent the expertise knowledge as data or rules within the computer. These rules and data can be called upon when needed to solve problems. Books and manual guides have a tremendous amount of knowledge but a human has to read and interpret the knowledge for it to be used.
A system that uses human knowledge captured in a computer to solve problems that ordinarily require human expertise (Turban & Aronson, 2001).
A computer program designed to model the problem solving ability of a human expert (Durkin, 1994).
An intelligent computer program that uses knowledge and inference procedures to solve problems that was difficult enough to acquire significant human expertise for their solutions (Feigenbaum).
Expert systems typically have a number of several components. The knowledge base is the component that contains the knowledge obtained from the domain expert. Normally the way of representing knowledge is using rules. The inference engine is the component that manipulates the knowledge found in the knowledge base as needed to arrive at a result or solution. The user interface is the component that allows the user to query the system and receive the results of those queries. Many ES's also have an explanation facility which explains why a question was asked or how a result or solution was obtained.
There are several major application areas of expert system such as agriculture, education, environment, law manufacturing, medicine power systems etc. In this article we will review about agriculture, education, environment and medicine expert system. These four applications widely use among the practitioners due to the maturity of the field by revealing the acceptance of the technology by the commercial sectors.
ادامه مطلب ...Artificial vision gets sharper all the time. Artificial walking has made great robot strides. But artificial intelligence is brain-dead. Why? Because while researchers have built awesome technology, they've failed to grapple with philosophy.
Early computer scientists like Alan Turing and John von Neumann attempted to spin logic circuitry into thinking machines. So they designed their creations to excel at tasks they thought embodied the heights of human intellect: calculating sums, analyzing geometry, and playing chess. In 1958, a computer beat a human chess player — albeit an inexperienced one — for the first time. Buoyed by this success, researchers embarked on a long attempt to invent a machine that could (a) talk just like Turing, (b) walk around in a robot body looking at stuff, picking it up, and using it neatly, (c) read newspapers and maybe correct the editors, and (d) program its own successors.
The notion of intelligent machines inspired a blizzard of books and movies, but practical returns were meager. Over the years, computers failed one commonsense task after another: manipulating unfamiliar objects, understanding natural language, distinguishing a dog from a cat. Despite steady advances in hardware, no machine could think as far as to laugh at a pratfall or make a bad pun.
In pursuing human-style intelligence, the geeks blundered into the deepest, densest, darkest thickets of metaphysics: consciousness, cognition, perception, self-awareness, and how "we" manage to "know" what we know. It turns out that activities like playing chess — things that require sorting and searching — are relatively easy to program, whereas tasks that require some understanding of the world at large, like doing the laundry, are unbearably complex. The metaphysical issues around AI are at a standstill, mainly because metaphysics is old and canny and doesn't move forward in the linear manner of technology. Researchers, their grand illusions and ambitions dashed, fell into a long "AI winter" of shrunken budgets and general indifference.
Nowadays, Google "knows" pretty much anything you ask it. But its insanely fast and powerful work is modestly described as data-mining, not thinking. That vast, globe-spanning, superpowerful, ultrawealthy Web spider has yet to awaken and declare, "I am Google."
But if it starts writing philosophy, all bets are off.
Most towns have at least one “flashpoint” business—a place that’s famous for its turbo-charged workers and lines of eager customers. These are the local hot spots that are “always jumping,” places in which employee motivation and customer satisfaction fuel each other in a flashpoint of contagious enthusiasm.
But flashpoint businesses don’t just happen by lucky accident. They have to be made to happen. If there aren’t many such businesses, it can only be because so few owners and managers understand the simple 4-step process for creating a flashpoint culture in their own workplaces.
Not convinced such a process could be that simple? Not sure any such process could ever work in your own business setting? Here’s a quick and easy way to find out.
Step 1: Invite your employees to come up with some ideas for improving the customer experience. For this process to work, the ideas for changes in behavior or procedure need to come from the workers themselves. The old way is to dictate in memos or training programs the kinds of behaviors management wants employees to adopt, and then try to legislate these new behaviors into the workplace—a way that has never worked. Employees will only get behind a change if it’s one they believe in. And employees are always more likely to believe in a change if the idea for it comes from themselves, instead of their bosses.
Step 2: Choose one employee idea, and help the employee(s) implement it successfully. The objective is to make the workers who came up with the idea look like heroes in customers’ eyes. If there are costs associated with the idea, helping with implementation will mean providing funding for it. (Think of this cost as an investment in positive word-of-mouth, the most effective form of advertising on the planet). If the idea requires changing a policy or procedure, do everything possible to make the change. Eliminate all obstacles to successful implementation of the employees’ initiative.
Step 3: Make it easy for customers to give positive feedback about the new initiative. It’s always good business practice to hear what your customers have to say—but few businesses make it convenient and easy for customers to give feedback on a regular basis. To test this process, make a point of soliciting feedback that relates specifically to the idea the employees implemented. Use various methods to collect feedback, especially that most powerful method of all: simple face-to-face conversation with the customers themselves.
Step 4: Let the employee(s) bask in the motivational effect of the positive feedback. This is where the magic begins. Let’s say an employee came up with the idea of installing a bench so senior citizens would no longer have to stand while waiting in line. When delighted seniors begin to rave about the convenience of the bench, tell them, "This bench was actually Terry’s idea. In fact, Terry, could you come over here for a moment—these folks would like to tell you something about your bench"
And now watch the effect this feedback has on Terry. You’re watching the first spark of the flashpoint effect: customer satisfaction driving up employee motivation, and employee motivation driving up customer satisfaction.
Once you’ve seen how well the process works, apply it again. And again. Keep the ball rolling by holding regular employee brainstorming sessions to come up with a rich supply of new ways to delight customers. Break a typical customer transaction down into its individual steps, and get employees thinking about ways to add a “wow factor” element in each step. Not every idea will be implemented, of course, but make sure enough are implemented to keep the positive customer feedback flowing in. And give your workers opportunities to hear this feedback directly from their customers. Immediate positive feedback from delighted customers is the primary motivational fuel all flashpoint businesses use to keep the fires of employee enthusiasm burning hot and bright.
Copyright Paul Levesque.
About the Author
E-commerce (electronic commerce or EC) is the buying and selling of goods and services on the Internet, especially the World Wide Web. In practice, this term and a newer term, e-business, are often used interchangably. For online retail selling, the term e-tailing is sometimes used.
E-commerce can be divided into:
As a place for direct retail shopping, with its 24-hour availability, a global reach, the ability to interact and provide custom information and ordering, and multimedia prospects, the Web is rapidly becoming a multibillion dollar source of revenue for the world's businesses. A number of businesses already report considerable success. As early as the middle of 1997, Dell Computers reported orders of a million dollars a day. By early 1999, projected e-commerce revenues for business were in the billions of dollars and the stocks of companies deemed most adept at e-commerce were skyrocketing. Although many so-called dotcom retailers disappeared in the economic shakeout of 2000, Web retailing at sites such as Amazon.com, CDNow.com, and CompudataOnline.com continues to grow.
In early 1999, it was widely recognized that because of the interactive nature of the Internet, companies could gather data about prospects and customers in unprecedented amounts -through site registration, questionnaires, and as part of taking orders. The issue of whether data was being collected with the knowledge and permission of market subjects had been raised. (Microsoft referred to its policy of data collection as "profiling" and a proposed standard has been developed that allows Internet users to decide who can have what personal information.)
EDI is the exchange of business data using an understood data format. It predates today's Internet. EDI involves data exchange among parties that know each other well and make arrangements for one-to-one (or point-to-point) connection, usually dial-up. EDI is expected to be replaced by one or more standard XML formats, such as ebXML.
E-commerce is also conducted through the more limited electronic forms of communication called e-mail, facsimile or fax, and the emerging use of telephone calls over the Internet. Most of this is business-to-business, with some companies attempting to use e-mail and fax for unsolicited ads (usually viewed as online junk mail or spam) to consumers and other business prospects. An increasing number of business Web sites offer e-mail newsletters for subscribers. A new trend is
Thousands of companies that sell products to other companies have discovered that the Web provides not only a 24-hour-a-day showcase for their products but a quick way to reach the right people in a company for more information.
Security includes authenticating business transactors, controlling access to resources such as Web pages for registered or selected users,
Dealing with costs, while not the most exciting portion of project management, is certainly one of the most interesting to the sponsor and doubtless to a great majority of your stakeholders. Although you may find cost planning tedious, having an accurate cost estimate will make life a whole lot easier when you start project execution.
Cost planning includes all of the processes to identify what you need to complete the project and what the costs will be. Resource planning is the process of determining what resources you need on your project and the quantity of each resource. Resources include people, equipment, and materials. Cost estimating is the process of determining what you will spend on the work required to complete your project. The accuracy of a cost estimate can vary depending on the type of estimate you are using.
Numerous techniques are used to create project estimates. Analogous or top down estimates use expert judgment and historical data to provide a high level estimate for the entire project or a phase or deliverable. Parametric modeling uses a mathematical model to create the estimates. The definitive method creates the project estimate by adding up individual estimates from each work package.
Cost budging takes the cost estimates and allocates them across the project schedule. A cost baseline is produced to use for forecasting and tracking.