Fuzzy Logic with Data Mining with respect to Prediction and Clustering Research Paper

Fuzzy Logic with Data Mining with respect to Prediction and Clustering - Research Paper Example According to Jemal and Ferlay (2004, p.69), breast cancer is currently one of the major health problems as well as the leading cause of death amongst women worldwide. Consequently early detection of cancer risks is one of the key ways of improving the prognosis of the disease. Although there are a number radiological techniques such as mammography that can be used in the early detection of breast cancer risks, the enormous data generated by these techniques often make it difficult for radiologists to accurately evaluate breast cancer data (Dorf and Robert, 2001, p.234). Artificial intelligence techniques such as fuzzy clustering algorithms can therefore significantly improve the diagnosis and evaluation of breast cancer risks through clustering of the particular data elements. Consequently the incorporation of fuzzy logic algorithms in data mining is a powerful tool that can be employed in the extraction, clustering, quantification and analysis of the data base information regarding the assessment and diagnosis of cancer risks. When dealing with uncertainties in databases, fuzzy logic clustering algorithms can be used to cluster different elements of data into various membership levels depending on their closeness (Castillo and Melin, 2008, p.94). For example, during the evaluation of breast cancer risks, mammogram data may possess some degree of fuzziness such as ill defined shapes, indistinct borders and different densities. In this regard, a fuzzy clustering algorithm can be one of the most effective ways of handling the fuzziness of data related to breast cancer. As an intelligent technique, Fuzzy logic data mining algorithms not only provide excellent analysis of the data but can also be used to develop accurate results that are easy to implement. One of the greatest potential advantages of incorporating fuzzy logic in data mining is the fact that such algorithms can significantly be used in the modeling of inaccurate, non linear and complex data systems b y implementing human knowledge and experience as a set of fuzzy rules that uses fuzzy variables for inference purposes (Nguyen and Walker, 2003, p. 96). For example when using fuzzy algorithm for the prediction and clustering of breast cancer data, the human experience and knowledge related to breast cancer risks can be expressed as a set of inference rules of deduction that are then attached to the fuzzy logic system. Another important advantage of fuzzy algorithms systems for prediction and clustering of breast cancer data is that they usually have a significantly high inference speed. This paper proposes a fuzzy clustering algorithm that can be used in the data mining of breast cancer data and consequently in the evaluation and prediction of cancer risks in patients with suspected cancer cases. Proposed single If-then fuzzy rule Assuming that we have a classification problem with an n-dimensional c-class pattern whose space is given by n-dimensional cube (0, 1), n as well as that the m patterns Xp=Xp1,†¦Xpn, where p=1,2,†¦..m, we will need to generate the fuzzy if then rule in which Xpi [0,1] for p=1,2,†¦., m, i =1,2,†¦..,n. Based on the proposed single fuzzy If-then rule that is based on the mean and standard deviation of the attribute values, the fuzzy rule will be generated for each of the classes. Consequently the fuzzy If then rule for the kth

Difficulties and Challenges of Nokia Company Essay

Difficulties and Challenges of Nokia Company - Essay Example From this study it is clear that net cash and value of liquid assets declined by $2 billion year-on-year, while it decreased by $9 billion as compared to the same quarter last year. Moreover, Microsoft assisted Nokia with $250m for "platform support payments", it implies that Nokia's operations have consumed $1.15 billion. According to Henry Blodget, if the situation remains same, Nokia is estimated to go bankrupt within two years. Henry's idea is a bit too extreme because Nokia can convert its assets into cash for recovery. However, once market losses confidence on a company's future, vendors demand payments and customers become hesitant that leads to nothing but crisis. Source: Jean-Louis Gassee, 2012. Huge volume of mobile phone is decreased by 16 percent. Even worse, average selling price (ASP) also declined by 18 percent to $44. In developing countries, Nokia is overtaken by Huawei and ZTE which are marketing smartphoens and feature phones at a very low price. According to the c hart above, Nokia's smartphone ship is also sinking. The volume is -51 percent as compared to the volume in same quarter last year. With $189 ASP, it cannot make give any financial boost since this is the production cost of one unit. However, Nokia is planning to counter them through Asha family of mobiles. Another hope for Nokia is the new Window Phone "smart device". Nokia's latest smatphone, Lumia's performance is also unidentified. This essay declares that another rumor, though well-supported by Mary Jo Foley, an authority on Microsoft, and The Verge, a credible blog, is that existing Lumia phone will not be upgraded to the next OS version, Windows Phone 8.The existing Windows Phone OS is based on the venerable Windows CE kernel. Regardless of veneration, Microsoft would have gone for a modern alternative for Windows Phone 8.It's better be rumor for Nokia because they have already convinced their customers that Symbian-based phones are useless in future. If they deal with Lumia in the same way, future would be even bleak (Gassee, 2012). Considering the rise of Android and iOS, an ex-Microsoft executive said that Nokia is not in the competition for devices but in a battle of ecosystems. Stephen Elop also announced that Nokia is moving from Symbian and Meego software platforms to Microsoft Windows Phone ecosystem. Gruber's source is Jean-Louis Gassee, he points out that Nokia's current devices are using old Symbian S60 stacks, comparatively new Symbian^3 and Symbian^4 engines, and Meego. He criticises Nokia and says how Nokia expects to stay in competition with the likes of Apple, Google, and HP when playing such a disorganized game. This paper outlines that on the other hand, Kotch finds that prevalaing perception that Nokia cannot handle two OS is unrealistic since other companies do it very successfully. The only problem with Nokia is that it is not an American company. He identifies that Nokia has more than two operating systems, for instance, S40 and so me others for cheap features and basic phones. According to Kotch Nokia's problem is not with the OS, but with the execution. While stating that Symbian is a feature, not a bug, Kotch   confirms that it is useless,