AES-Based Encoding and Decoding Images using MATLAB
A Novel Technique of Sign Language Recognition System using Machine Learning for Differently Abled Person
Implementation of Machine Learning Techniques for Depression in Text Messages: A Survey
A Study of Ransomware Attacks on Windows Platform
Techniques of Migration in Live Virtual Machine and its Challenges
Efficient Agent Based Priority Scheduling and LoadBalancing Using Fuzzy Logic in Grid Computing
A Survey of Various Task Scheduling Algorithms In Cloud Computing
A Viable Solution to Prevent SQL Injection Attack Using SQL Injection
A Computational Intelligence Technique for Effective Medical Diagnosis Using Decision Tree Algorithm
Integrated Atlas Based Localisation Features in Lungs Images
The term data warehouse was first used by Inmon in 1990 which he defined as “A warehouse is a subject oriented, integrated, time-invariant and nonvolatile collection of data in support of management decision making process” [Inmon, 1990]. On the other hand, Ralph Kimball provided a much simpler definition of the data warehouse. In the book ‘The Data Warehouse Toolkit’ he said that a data warehouse is “a copy of transaction data specifically structured for query and analysis” [Inmon and Kimball, 1996]. This paper provides theoretical description of data ware housing. Implementation of clinical Data warehousing were analyzed, finally evaluating them. The proto type considered for implementation has been collected from the East Hospital London Clinical Data Warehouse Project.
The MapReduce programming model provides an exciting opportunity to process massive volumes of heterogeneous data using map and reduce tasks in parallel. In the recent time, a number of efforts has been made to improve the performance of the job’s execution. The performance of the job’s execution can be improved further by considering the network traffic. In this paper, an optimistic distributed algorithm is proposed to deal with the significant optimization problem for handling large size data. The optimistic distributed algorithm is more efficient than the distributed algorithm. Finally, simulation results show that the proposal can significantly reduce network traffic cost.
Machine to Machine (M2M) communication system has started gaining its real world momentum with the introduction of the Internet and mobile technology into this system. Several works have come up to use this integrated system into many different vertical solutions and tried to bind one solution platform for many monolithic systems. This work tackles the first step of implementing IoT communication platform. This paper describes about the wireless fire detection, monitoring system based on IoT. A monitoring system of alarm for fire detection using was developed an Arduino controller. The circuit includes a buzzer and temperature sensor. Arduino microcontroller and the other application components are connected to a LAN or WiFi Protocol. All the data taken from the sensor will be sent to the monitoring system and displays in the monitoring system wirelessly.
Automated Teller Machines (ATMs) enable customers to perform financial transactions like cash withdrawal, check balances or credit mobile phones with the help of the machine and without any human intervention. In this paper, a speech recognition system is developed for ATMs for performing financial transactions. Since speech is the most natural and easiest mode of communication, communication between the customer and the ATM can be performed easily through speech. This allows ATM machines to communicate with the customers using the stored speech samples and the user communicates with the machine through spoken digits. Here, two speech recognition systems are developed using the feature extraction techniques Discrete Wavelet Transforms (DWT) and Wavelet Packet Decomposition (WPD). The classifier used along with both the methods is Artificial Neural Network (ANN). Both methods produced good recognition accuracies of 87.575% and 85.5% each, but DWT and ANN combination produced better results than WPD and ANN.
In the world of automating tasks and reducing human effort, it is essential for a computer to be able to produce text like humans. This will enable us to let the computer work on insignificant tasks, such as create a summary for an advertisement or a product as well as generate a different outlook on most things like a sequel for a movie or a book. In this paper, the authors aim to review different approaches that have been implemented for generating text based output and devise the most optimal approach that can be used. In this they have compared four different methods used to generate text from various scenarios.