A NUMERICAL SOLUTION TO DIFFERENT TYPES OF ECONOMIC LOAD DISPATCH PROBLEMS

This paper presents a newly proposed Novel TANAN's Algorithm (NTA) for solving different types of Economic Load Dispatch (ELD) problems. The main objective of NTA is to minimize the total fuel cost of the generating units, subjected to limits on generator power output, power loss and valve point loading effect. The NTA is a simple numerical random search approach based on a parabolic TANAN function. This paper presents an application of NTA to ELD problems for different IEEE standard test systems. The proposed method is compared with various optimization techniques and the simulation results show that the proposed algorithm outperforms previous optimization methods

Development of an Epileptic Seizure Detection Application based on Parallel Computing

Abstract—Epileptic seizure detection in a large database of Electroencephalography (EEG) signals needs to be a time constrained process for real-time analysis. Epileptic seizure detection algorithms are designed to obtain and analyze a group of neural signals and recognize the presence of seizure occurrence. The computational cost of the algorithms should be minimized to reduce the processing time and memory consumption. Automated epileptic seizure detection using optimized feature selection improves the classification accuracy, but it occupies more processing time during the Artifact Removal (AR) stage. So, the execution time is greatly reduced by introducing task parallelism in the artifact removal stage. By harnessing parallel computing the computational overhead and processing time are decreased. An epileptic seizure detection application is developed and analyzed with respect to execution time, speedup, and parallel efficiency. The application was developed in Intel Pentium(R) Dual-core CPU with processor clock rate of 2.60 GHz, memory of 1.96 GB, and operating system of Windows X

A New Trace Backing Algorithm And Circular List Join Or Maximizing Streaming Data Join

An increasing number of database queries are executed by interactive users and applications. Since the user is waiting for the database to respond with an answer, the initial response time of producing the first results is very important. The user can process the first results while the database system efficiently completes the entire query. The state-of-art join algorithms are not ideal for this setting. Adaptive join algorithms have recently attracted a lot of attention in emerging applications where data is provided by autonomous data sources through heterogeneous network environments. The main advantage of adaptive join techniques is that they can start producing join results as soon as the first input tuples are available, thus improving pipelining by smoothing join result production and by masking source or network delays. Since the response time of the queries places a vital role in adaptive join, the join techniques like Hash Join, Sort Merge Join cannot be used because they require some prework before producing the join result. The only possible join technique that can be used in adaptive join is Nested Loop Join. In Nested Loop Join each row of the outer relation is compared with each row of the inner relation. The no. of comparisons done by the nested loop join can be reduced by using a technique called trace backing. In trace backing technique whenever a miss match occurs, the next tuple of the outer relation is compared with the mismatched inner relation tuple, instead of looping all the tuples of the inner relation. Finally a new circular linked list join method is discussed which may be a better option to perform streaming data Join