Wavelet collocation method for numerical solution nth order Volterra integro diferential equations (VIDE) by expanding the unknown functions, as series in terms of chebyshev wavelets second kind with unknown coefficients. The aim of this paper is to state and prove the uniform convergence theorem and accuracy estimation for series above. Finally, some illustrative examples are given to demonstrate the validity and applicability of the proposed method.
Keywords: chebyshev wavelets second kind; integro-differential equation; operational matrix of integrations; uniform convergence; accuracy estimation.
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With the emerging need of hospitals to be more responsive, proactive and quick to fight against disease, the Virtual Medical Support App provides the transparency between doctors and patients and other users with secure access to information. The vision behind developing an online comprehensive virtual medical support application is to engage patients, doctors and hospitals. This smartphone app can be constantly accessible which involves and educates the patient, and provides a repository for patient and proper medication information. It Facilitate appropriate communication between all stakeholders - discussion chat or mail services.to use this application more securely login details are provided to registered user by administrator. This helps the doctor to maintain patients' records as authorized user. Users may be Patients, Doctors, Relatives, Nurses or Volunteers. The patients can interact with doctors, their relatives and other patients connected through this app., by chats, video calling, and blogs and also by group video chats. The app provides emergency messages which can be sent by patients themselves or hospital volunteers. Patient's all records, charts and progress reports can be maintained using this app. The Reports can be viewed by the Doctor, patient and their close relatives (who all are registered through this app).This system aims in bringing the patients, doctors, patient's relative, volunteer and nurses together in a virtual environment so that the patient is never alone. A help is always a call away.
Keywords -Adherence, Applications, Cloud, Multilingual, Reminder, VMS.
We display the Knowledge Management (KM)as a process, following a basic model based on seven dimensions. Our goal is to verify the level of effectiveness of KM in building incorporation and construction of enterprises located in Curitiba and its metropolitan area, Brazil. Therefore, we made a survey in a sample of local companies and analyzed the data using descriptive statistics. The results indicate the existence of processes and characteristics moderately associated with the KM, consistent with "Traditional Companies". We show a reference of where (in what dimension) and with which intensity the initiatives of the KM occur, allowing one to draw a profile of how knowledge is being managed by the contractors.The organizational culture dimension showed the greater effectiveness of KM, giving evidence that the organizational environment tends to be pleasant, prevailing freedom, trust and respect;fertile ground for the creation of knowledge.
Keywords– Civil construction, knowledg management,organizational processes and characteristics, sevendimensions of knowledge
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[5] L. A. do Nascimento and E. T. Santos, A indústria da construção na era da informação,Ambiente Construído, 3(1), 2003, 69-81
An association rule mining is important in data mining. Two Steps important in association rule mining. First, find the frequent itemset from dataset and Second, find the association rule from frequent itemsets. A frequent itemsets mining is crucial and most expensive step in association rule mining. In Apriori and Apriori-like principle it's known that the algorithms cannot perform efficiently due to high and repeatedly database passes. In this paper we proposed a improved technique for frequent itemset mining. This technique scan the database only once and reduces the number of transaction.
Keywords: Frequent, Support, Confidence
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[2] Han, J., J. Pei, and Y. Yin ,"Mining frequent patterns without candidate generation" Proceedings of the ACM, NY, pp. 1–12,2000.
[3] Hanbing Liu and Baisheng Wang," An Association Rule Mining Algorithm Based On A Boolean Matrix, Data Science Journal,2007.
[4] Wei Song, Bingru Yang and Zhangyan Xu, " Index-BitTableFI: An improved algorithm for mining frequent itemsets," Proceedings of the Elsevier, March 2008.
[5] Guoxiaoli, Fengli and Guoping, " Research on Mining Frequent Itemsets based on Bitwise AND Algorithm," Proceedings of the IEEE, 2011
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