In this paper, we had analyzed a large scale Diabetic data sets for several patients to find the length of time taken for treatment for each class of Diabetes and the risk of re-admission of diabetic patients performi...
In this paper, we had analyzed a large scale Diabetic data sets for several patients to find the length of time taken for treatment for each class of Diabetes and the risk of re-admission of diabetic patients performing Bigdata analytics, the type of diabetes and its outcome which acted as a high risk sample of patient data sets. We have collected and integrated different sources of diabetic information for several patients, from primary and secondary treatment information to administrative information, to analyze novel view of patient care processes such as type of treatments and every patient behaviors on which results multifaceted nature of chronic care that we take into our account to predict the survival factors and length of stay. Nowadays by using electronic medical equipments with high quality and high degree calibrations, we are able to gather large amounts of real-time diabetic data sets. The requires the usage of distributed platforms for making BigData analysis that results on making decisions based on available data and its trends. This type of Bigdata analysis allows geographical and environmental information of patients’ enables the capability of interpreting the ethnicity of data gathered and extract new analysis to identify survival options and treatment timelines (LOS) from them.
作者：
Meera AlphyAjay SharmaPhD Scholar
Department of Computer Science and Engineering SRM University Haryana India Assistant Professor
Department of Computer Science and Engineering SRM University Haryana India
The Web usage mining is the application of data mining, which is used to extract useful information from the online community. The World Wide Web contains at least 4.73 billion pages according to Indexed Web and it co...
The Web usage mining is the application of data mining, which is used to extract useful information from the online community. The World Wide Web contains at least 4.73 billion pages according to Indexed Web and it contains at least 228.52 million pages according Dutch Indexed web on 6th august 2015, Thursday. It's difficult to get needed data from these billions of web pages in World Wide Web. Here is the importance of web usage mining. Personalizing the search engine helps the web user to identify the most used data in an easy way. It reduces the time consumption; automatic site search and automatic restore the useful sites. This study represents the old techniques to latest techniques used in pattern discovery and analysis in web usage mining from 1996 to 2015. Analyzing user motif helps in the improvement of business, e-commerce, personalisation and improvement of websites.
Cloud computing is a latest expertise in information technology field in today's era. It allows online allocation of dynamic resources over internet through pay per use concept. Dynamic load balancing methods are ...
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Cloud computing is a latest expertise in information technology field in today's era. It allows online allocation of dynamic resources over internet through pay per use concept. Dynamic load balancing methods are generally used for distributing the workloads to different virtual machines evenly in cloud to avoid overload criteria. Optimized load balancers have to be used for smoother performance of work in cloud environment. The dynamic load balancers give high user satisfaction and maximum resource utilization ratio and hence achieve high performance and greater resource utilization of system. Dynamic allocation of applications makes the sessions to be transferred from one site to another as and when needed. This paper mainly focuses on various dynamic load balancing methods used for optimized resource management in cloud.
This paper describes the simulation of a distributed generation system with storage technologies. The simulation is performed using a SCADA software for a distributed generation system, considering the generation cost...
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This paper describes the simulation of a distributed generation system with storage technologies. The simulation is performed using a SCADA software for a distributed generation system, considering the generation cost, the load and the availability of the system's generating units. Also, a storage unit is added to the system. An overview of the storage technologies is also presented.
This paper describes the mathematical modeling of the optimal power flow problem. The purpose is to optimize the power flow for a whole day, for a system in which several distributed generators (DGs) have been added. ...
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This paper describes the mathematical modeling of the optimal power flow problem. The purpose is to optimize the power flow for a whole day, for a system in which several distributed generators (DGs) have been added. There are two objective functions which are minimized, the generation cost and the total power losses of the system, while satisfying equality and inequality constraints. The optimization is performed for different DGs and load scale factors. The other generators from the system have a 1 scale factor.
This paper introduces a novel arterial blood pressure (ABP) signal model that generates statistically accurate synthetic signals with known characteristics. Using parameter identification from real ABP signals to form...
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This paper introduces a novel arterial blood pressure (ABP) signal model that generates statistically accurate synthetic signals with known characteristics. Using parameter identification from real ABP signals to form base parameter templates, our model applies stochastic processes to modulate cardiac cycle period and shape. A real-time control component modulates model parameters between cycle boundaries to emulate properties of real cardiovascular signals, such as arrhythmia, ectopic beats, resonances in the heart-rate variability spectrum, and respiratory cycle modulation of ABP signal amplitude. We present several examples to illustrate the capability of the proposed model.
The purpose of this paper is to measure the sustainability of corporate through using the relationship of major shareholder using complex system. As a result of case study, we can find two types of meaningful network....
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The purpose of this paper is to measure the sustainability of corporate through using the relationship of major shareholder using complex system. As a result of case study, we can find two types of meaningful network. First type is the clustering according to connectivity among major shareholders. Second Type is the network according to corporate group. First type shows small world network and characteristics of corporate group such like business style, decision making speed and owner risk. Second type shows scale-free network and investment preference according flowing power law in stock market. Third type is the clustering according to industry sector of stock focusing on Information Technology.
Artificial Intelligence federates numerous scientific fields in the aim of developing machines able to assist human operators performing complex treatments---most of which demand high cognitive skills (e.g. learning o...
ISBN:
(数字)9781627054478
Artificial Intelligence federates numerous scientific fields in the aim of developing machines able to assist human operators performing complex treatments---most of which demand high cognitive skills (e.g. learning or decision processes). Central to this quest is to give machines the ability to estimate the likeness or similarity between things in the way human beings estimate the similarity between stimuli. In this context, this book focuses on semantic measures: approaches designed for comparing semantic entities such as units of language, e.g. words, sentences, or concepts and instances defined into knowledge bases. The aim of these measures is to assess the similarity or relatedness of such semantic entities by taking into account their semantics, i.e. their meaning---intuitively, the words tea and coffee, which both refer to stimulating beverage, will be estimated to be more semantically similar than the words toffee (confection) and coffee, despite that the last pair has a higher syntactic similarity. The two state-of-the-art approaches for estimating and quantifying semantic similarities/relatedness of semantic entities are presented in detail: the first one relies on corpora analysis and is based on Natural Language Processing techniques and semantic models while the second is based on more or less formal, computer-readable and workable forms of knowledge such as semantic networks, thesauri or ontologies. Semantic measures are widely used today to compare units of language, concepts, instances or even resources indexed by them (e.g., documents, genes). They are central elements of a large variety of Natural Language Processing applications and knowledge-based treatments, and have therefore naturally been subject to intensive and interdisciplinary research efforts during last decades. Beyond a simple inventory and categorization of existing measures, the aim of this monograph is to convey novices as well as researchers of these domains toward a better unders
With the increasing grid penetration levels of wind power, there is a large need for the energy reserves for grid support during under-frequency conditions. Such energy reserves are created by operating the wind farm ...
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