International Journal of Communication and Networking System, 2015
In spatial-temporal applications, moving objects identify the particular locations called locatio... more In spatial-temporal applications, moving objects identify the particular locations called location based services and update the locations continuously to the server. Due to the enormous collections of moving objects, many spatial-temporal access techniques are developed to process user queries efficiently. Spatial- temporal access methods are classified into four categories: (1) Indexing the past data, (2) Indexing the current data, (3) Indexing the future data, and (4) Indexing data at all points of time [1]. Spatial objects whose position changes for every seconds. It helps to find the moving objects i.e., vehicles moving on the road networks, finding the position of the aeroplanes or any criminals etc. To achieve this an innovative indexing techniques needed to update data frequently.
Heart disease is the leading cause of death for both men and women. This is the case in the India... more Heart disease is the leading cause of death for both men and women. This is the case in the India and worldwide. More than half of all people who die due to heart disease are men. Earlier detection following the treatment would reduce the serious cause. We have lot of data with prescriptions for the patient. The help of the technology in Data mining (DM) and Machine Learning (ML) would substantially improve the diagnosis accuracy. Many researchers, in recent times, have been using several data mining or machine learning classification techniques to help the health care industry and the professionals to predict heart related diseases. This survey paper describes a focused survey of machine learning (ML) and data mining (DM) classification methods for heart disease prediction. In addition we reviewed data mining techniques and Machine learning classification algorithms, its processes, tools, related works and their different types of techniques can effectively decide whether the patient is suffering from heart disease or not. Moreover, we reviewed Evaluation Measures for different types of classification algorithms on Data Mining and Machine Learning domain. Therefore, we can easily measure the two or more algorithm with same dataset for same problem. Finally comes with best suitable algorithm for predict heart disease.
Communications in Computer and Information Science, 2012
In this paper we extract the cluster by using numerical as well as statistical methods for improv... more In this paper we extract the cluster by using numerical as well as statistical methods for improving efficiency using efficient algorithms of k-means in data mining. So, Data mining is defined as finding hidden information in a database it has been called exploratory data analysis, data driven discovery, and deductive learning.[1] clustering is usually accomplished by determining the similarity among the data on predefined attributes. The most similar data are grouped into clusters. This paper proposes a method for making the k-means algorithm and Bisection method for more effective and efficient, so as to getting better cluster.
The extensive usages of cellular devices, hand-held devices, and GPS equipments facilitates envir... more The extensive usages of cellular devices, hand-held devices, and GPS equipments facilitates environments where almost all entities are much aware of its own localities. Such locations demand for novel query processing systems to competently upkeep location-aware servers. Enormous amount of continuous fixed and moving ST queries, if any deferral of query response outcomes in an outdated response where moving-objects are unremittingly fluctuating their locations. Queries are enhanced centrally based on multiple measures such as spatial topological associations, temporal and attribute correlations. Simulation results shows that the proposed scheme is highly scalable for large scale spatio-temporal queries and also has the added advantage of minimizing the energy consumption due to query and data transmission.
International Journal of Communication and Networking System, 2015
In spatial-temporal applications, moving objects identify the particular locations called locatio... more In spatial-temporal applications, moving objects identify the particular locations called location based services and update the locations continuously to the server. Due to the enormous collections of moving objects, many spatial-temporal access techniques are developed to process user queries efficiently. Spatial- temporal access methods are classified into four categories: (1) Indexing the past data, (2) Indexing the current data, (3) Indexing the future data, and (4) Indexing data at all points of time [1]. Spatial objects whose position changes for every seconds. It helps to find the moving objects i.e., vehicles moving on the road networks, finding the position of the aeroplanes or any criminals etc. To achieve this an innovative indexing techniques needed to update data frequently.
Heart disease is the leading cause of death for both men and women. This is the case in the India... more Heart disease is the leading cause of death for both men and women. This is the case in the India and worldwide. More than half of all people who die due to heart disease are men. Earlier detection following the treatment would reduce the serious cause. We have lot of data with prescriptions for the patient. The help of the technology in Data mining (DM) and Machine Learning (ML) would substantially improve the diagnosis accuracy. Many researchers, in recent times, have been using several data mining or machine learning classification techniques to help the health care industry and the professionals to predict heart related diseases. This survey paper describes a focused survey of machine learning (ML) and data mining (DM) classification methods for heart disease prediction. In addition we reviewed data mining techniques and Machine learning classification algorithms, its processes, tools, related works and their different types of techniques can effectively decide whether the patient is suffering from heart disease or not. Moreover, we reviewed Evaluation Measures for different types of classification algorithms on Data Mining and Machine Learning domain. Therefore, we can easily measure the two or more algorithm with same dataset for same problem. Finally comes with best suitable algorithm for predict heart disease.
Communications in Computer and Information Science, 2012
In this paper we extract the cluster by using numerical as well as statistical methods for improv... more In this paper we extract the cluster by using numerical as well as statistical methods for improving efficiency using efficient algorithms of k-means in data mining. So, Data mining is defined as finding hidden information in a database it has been called exploratory data analysis, data driven discovery, and deductive learning.[1] clustering is usually accomplished by determining the similarity among the data on predefined attributes. The most similar data are grouped into clusters. This paper proposes a method for making the k-means algorithm and Bisection method for more effective and efficient, so as to getting better cluster.
The extensive usages of cellular devices, hand-held devices, and GPS equipments facilitates envir... more The extensive usages of cellular devices, hand-held devices, and GPS equipments facilitates environments where almost all entities are much aware of its own localities. Such locations demand for novel query processing systems to competently upkeep location-aware servers. Enormous amount of continuous fixed and moving ST queries, if any deferral of query response outcomes in an outdated response where moving-objects are unremittingly fluctuating their locations. Queries are enhanced centrally based on multiple measures such as spatial topological associations, temporal and attribute correlations. Simulation results shows that the proposed scheme is highly scalable for large scale spatio-temporal queries and also has the added advantage of minimizing the energy consumption due to query and data transmission.
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