An Efficient Query Optimizer with Materialized Intermediate Views in Distributed and Cloud Environment

In cloud computing environment hardware resources required for the execution of query using distributed relational database system are scaled up or scaled down according to the query workload performance. Complex queries require large scale of resources in order to complete their execution efficiently. The large scale of resource requirements can be reduced by minimizing query execution time that maximizes resource utilization and decreases payment overhead of customers. Complex queries or batch queries contain some common subexpressions. If these common subexpressions evaluated once and their results are cached, they can be used for execution of further queries. In this research, we have come up with an algorithm for query optimization, which aims at storing intermediate results of the queries and use these by-products for execution of future queries. Extensive experiments have been carried out with the help of simulation model to test the algorithm efficiency

Design and control of electronics based medical emergency system using a Quadcopter

Thesedays, there are many incidents that lead to road accidents, some being very severe. These accidents sometimes even result in loss of many lives. One of the major reasons for this loss is the lack of timely first aid. In fact, we observed from our survey conducted at an RTO that most deaths during accidents occur, due to delay or lack of first aid. The project focuses on developing a prototype of the system which would cater to the need of medical emergencies that arise during road accidents. This will be accomplished by use of a quadcopter which will deliver the required first aid. With this project, we are attempting to bring about faster accessibility to the patient, than other present means of medical emergency system. In order to achieve this goal, various means of communication will be utilized. The use of a camera will help to view the accident site. This will help to considerably bring down the death rates caused due to lack of timely first aid during accidents

Magnetic resonance imaging of cyclops lesion as a cause of persistent morbidity after anterior cruciate ligament reconstruction

Localized anterior arthrofibrosis (cyclops lesion) is having around 1-9.8% frequency rate after anterior cruciate ligament (ACL) reconstruction. It has been reported to be a significant cause of loss of knee extension after reconstruction of the ACL of the knee. We present a case report of a patient with prior ACL reconstruction who presented with pain and loss of extension following surgery. MR imaging revealed the typical features of cyclops lesion. Repeat arthroscopy excision of the lesion is the only treatment to reduce the morbidity of the patient

KNOWLEDGE REPRESENTATION OF SECURITY DESIGN PATTERN LANDSCAPE USING FORMAL CONCEPT ANALYSIS

Security design patterns are proven solutions to recurring security problems. They are classified into various categories, each containing a set of attributes. However, the large number of patterns and classification schemes makes it difficult to choose a pattern for a given security problem. To apply patterns effectively, there must be a systematic method of organizing the patterns, so that it is possible to look up a design pattern unambiguously according to its purpose. While a lot of research focuses on developing new patterns and classifications, these issues have not been adequately addressed. In this paper, we present a novel approach of applying Formal Concept Analysis (FCA) on a chosen set of patterns classified according to a common set of attributes. The resulting concept lattice can be used for mining knowledge from the concepts, identifying pattern groups, and their relationships with the goal of applying appropriate patterns to security requirements. We propose the use of FCA over conventional data analysis methods for the simplicity of data preparation, the discovery of hidden knowledge, and cluster interpretation, with a visual representation of the pattern domain

Data mining in radiology

Data mining facilitates the study of radiology data in various dimensions. It converts large patient image and text datasets into useful information that helps in improving patient care and provides informative reports. Data mining technology analyzes data within the Radiology Information System and Hospital Information System using specialized software which assesses relationships and agreement in available information. By using similar data analysis tools, radiologists can make informed decisions and predict the future outcome of a particular imaging finding. Data, information and knowledge are the components of data mining. Classes, Clusters, Associations, Sequential patterns, Classification, Prediction and Decision tree are the various types of data mining. Data mining has the potential to make delivery of health care affordable and ensure that the best imaging practices are followed. It is a tool for academic research. Data mining is considered to be ethically neutral, however concerns regarding privacy and legality exists which need to be addressed to ensure success of data mining