International Journal of Intelligent Engineering and Systems

1

Authors: Santhosh Kumar Gangadharaiah, Hosahally Narayangowda Suresh

Automatic extraction of soft biometric characteristics of face image is an emerging research field in recent years. Among these soft biometrics, age estimation is very useful for several applications, like video surveillance, business intelligence, and search optimization in large databases. Generally, facial aging effects perceived in two main forms like, growth related transformations and textural variation. So, in order to generate an effective age classifier, both dimension and texture information should be used together. In this work, an age estimation system that is combination of dimension feature (Hybrid Principal Component Analysis (HPCA)) and textural feature (Log Gabor filter) for feature extraction, is used. The extracted feature values are classified by employing a multi-objective classifier named as Multi-Support Vector Machine (M-SVM). The result of the experiment shows that the proposed approach delivers a better age estimation rate on overlapping age group classes.

18

Authors: Premkumar Manoharan, Sumithira Rameshkumar, Sowmya Ravichandran3

In the field of power electronics, multilevel inverter plays a vital role for power quality improvement. The high switching frequency is used to obtain quality output waveform with a minimum amount of ripple content. The high voltage is reached by using voltage source inverter with almost zero harmonics without series connected switching devices. If the voltage level increased, the harmonic content of the output voltage waveform decreases in multistage converter. In this present work, single phase cascaded nine level inverter is designed for low powered microinverter and switching angles are produced by Selective Harmonic Elimination (SHE) technique. Each bridge in cascaded inverter will produce the output at different levels and allowing an overall nine level AC output voltage. Now-a-days, the solar photovoltaic is connected with microinverter is an efficient way of increasing the performance so that the proposed inverter derives an input from single PV module since it is module level inverter and it can provide good regulation for leads up to their rated capacity. The prototype is designed for 80W rating and the control signals are generated and processed using FPGA controller. The proposed inverter is designed and tested experimentally to verify the theoretical explanations and proposed design delivers high efficiency when compared with the conventional inverter at full load.

39

Authors: Jayapandian Natarajan

Cloud Computing reshapes the entire computing paradigm. In general, cloud computing means outsourcing available services and data storage in centralized scenario. In cloud computing task allocation is a major problem because multiple numbers of tasks are allocated to multiple numbers of processors for simultaneous processing. From the given list, tasks are queued according to the ascending order based on their duration. This paper is designed to solve the Task Scheduling problem, by using our proposed effective new approach of Backfilling algorithm. Depending upon the task duration, tasks are split into multiple threads for processing. Multiple thread tasks are processed in the basic concept of “gang scheduling” technique. Here we implement new backfilling algorithm concept to minimize the idle processing time of the processors. The existing Simple Backfilling Algorithm (SBA) is used to minimize the ideal time processing. Whereas comparatively Dynamic Cloud Scheduling using Backfilling Algorithm (DCBA) is designed to reduce the ideal time processing than SBA to carry out the process of both LQueue and SQueue simultaneously. At the outset, DCBA reduces the average waiting time. As mentioned the algorithm which is specified in the previous line that contains three level which represent the working speed of the algorithm. The first and second level of DCBA algorithm is comparatively similar to the performance of SBA algorithm. The maximum better performance was given in a queue size (q=1.5) by DCBA algorithm as compare to SBA algorithm. The existing type (Gang Scheduling) consist of two approaches namely Adaptive First Come First Serve (AFCFS) and Largest Job First Served (LJFS) that focus on non-parallel jobs with deadline. When compare to existing gang scheduling algorithm and SBA algorithm the average waiting time of DCBA has slight improvement in the loader level of the key. As the separation of the queue like LQ and SQ the waiting time and average waiting time is reduced comparatively.

57

Authors: Shriraghavan Madbushi, Rajeshree Raut, Mulpuri Santhi Sri Rukmini

In this paper, a novel method for detection of Primary User Emulation Attack (PUEA) by tagging (adding tag bits) a test signal in chaotic communication is proposed. The tagged test signal is masked by the secondary user using Lorenz chaotic attractor and sent over the channel. However, it doesn’t interfere with test signals of other secondary users. The Bit Error Rate (BER) analysis of the received test signal indicates whether the channel is free or is under PUEA. If the BER of the received signal is above the set threshold then it indicates an attack. Moreover, for the first time the concept of test signal to identify whether the channel is occupied by the primary user or an attacker is proposed. It is further suggested to compare the result of the proposed method with the database provided by Spectrum Bridge Inc. (SBI). It is worth mentioning here that the proposed method has made the use of the centralized control approach employed by the Federal Communications Commission (FCC) to combat PUEA. Simulation results in terms of the BER have been analysed and compared with other existing methods to show the efficacy of the proposed method.

76

Authors: Suyambu Karthick

Now a day the usage of Self-Organizing Networks (SONs) is increasing, because of its broad application. Unlike common networks, the SONs have the capability of reconfiguration, whenever any defect occurs in the network. However, while routing in this network, the loss of data occurs due to its security lack. Hence many researchers have presented their research for providing secure routing in various SONs. However, the security is still an issue in the routing of SONs especially in Wireless Sensor Network (WSN). Here in this paper, a novel protocol for the secure routing of WSNs has developed. The proposed protocol is named as Trust-Distrust Protocol (TDP). As per the proposed protocol, the routing is done in four stages. The initial stage is topology management using the k-means algorithm. The second stage is Link Quality Appraisal (LQA), where the quality of every network node is evaluated. The third stage is grading, in which it is based on the LQA value and a grade point is allotted to every node in the network. In the last stage, the most secure path for the routing is determined based on the grade points. The proposed protocol is tested in one of the major kinds of SONs, like WSN using the NS2. By comparing with the existing LEACH protocol, the performance is evaluated. Ultimately the proposed protocol outperformed the performance of the existing routing protocol and suggested for rounding in SONs.

93

Authors: Sadanand Ramchandrarao Inamdar, SathishBabu Basavaiah, Ravi Malleshappa Yadahalli

In Mobile Ad Hoc Network (MANET), the existing routing protocol may result in overhead and increased collisions during data transmission. In order to overcome this issue, in this paper, we propose to design a cooperation based directional routing protocol in MANET. Initially the source nodes discover neighbors by constructing the Directional Neighbour Table (DNT). Then the node with minimum transfer time is selected as best relay node. The transfer time is estimated using bio-inspired algorithm. Once the relay nodes are selected, the source node follows the Adaptive Directional Monitoring MAC (ADMMAC) protocol to transmit the data to the destination. In this technique, the nodes use the co-operative transmission mode when it requires transmitting the data packet faster. By simulation results, we show that the proposed technique minimizes the overhead and enhances the efficiency.

111

Authors: Mohamed Kasim Jannathl Firdouse, Mururgan Balasubramanian

Computed Tomography (CT) is the main source for analyzing the lung diseases and the preplanning of pulmonary surgeries. The accurate interpretation of chest CT scan makes a challenge to radiologists due to its complex visual nature. This paper proposes a novel method to segment the left and right lungs from the background of CT images to assist the pathologists for the easy and accurate diagnosis of pulmonary diseases. The segmentation of lung is a challenging task due to the anatomical difference of different people. This paper develops a novel algorithm namely successive peak based quantization transform (SPQT) to segment the lungs from the background. This method extracts 8 bit patterns from the input lung image and at last a BYTE data which is formed from 8 bit patterns is produced. Prior to SPQT lung segmentation, the lung image which may contain impulse noise is reduced into noise free one by using ‘Fuzzy Impulse Detection and Reduction Method’ (FIDRM). The novel lung image hikes the accuracy to a significant level than the existing algorithms.

132

Authors: Enumula Mahesh, Suman Maloji, Dhyapulai Nagendra Rao

Now a days Image forgery (IF) makes many problems in a society. Super Pixels Segmentation and ScaleInvariant Feature Transform based Image Forgery Detection (SPS-SIFT-IFD) has introduced to detect the forgeries in the images. The forgery region extraction algorithm replaces the features point with small SP as feature blocks and neighboring blocks that have similar local color features has been identified by the Scale-Invariant Feature Transform (SIFT) technique. Artificial Neural Network (ANN) classifier is used for better detection of forged parts in the original images. It applies the morphological operation to the merged regions to generate the detected forgery regions. The experimental results indicate that the SPS-SIFT-IFD scheme achieve much better detection results even under various challenging conditions compared with the existing Forgery Detection (FD) methods. Finally, SPSSIFT-IFD method performance is measure, in terms of Recall, Precision, False Measure, Sensitivity, Sensitivity, Accuracy and Gmean.

152

Authors: Manjula Thimsandra Ramakrishna, Raju Garudachar

Signal tracking loop in GNSS receivers play a major role of data extraction by tracking carrier phase. Under adverse signal conditions such as ionosphere scintillation, conventional tracking loops are less robust and hence are susceptible to loss of lock. Kalman filter’s inherent ability to adapt to signal conditions is one of the desirable features which improve the tracking performance. The paper analyses Linear Kalman filter technique of tracking signals in Navigation receiver under scintillation conditions and presents the improvements obtained with Linear Kalman filter based tracking method over conventional tracking method. Performance parameters such as phase error, carrier to noise ratio, correlator power and phase lock indicator are analysed in addition to highlighting the tuning merits of Kalman filter. NavIC L5 band signal modulated with simulated scintillation is used as test signal to analyse the performance of the Kalman filter based tracking method.

173

Authors: Samuel Peter James I, Ramasubramanian P, Magdalene Delighta Angeline D

The emotions of human in every part of a life are usual and unavoidable. The emotions uplift or cast down a person facing different situations in each moment. The main objective of this research work is to provide learning with emotional-based approach and to analyze the result using data mining algorithms. This paper examine how emotions involve the learners learning and the success of performance improvement of various learners under different environment that leads to the success of a learner. This study scrutinize the Emotional Intelligence (EI) and how it relates to academic performance. The key idea is to bring out different learning environments that focus on the learners’ positive emotional behavior and proceed according to the observed behavior. The proposed work uses Observe, Amend and Analysis (OAA) Method in the learning environment to enhance the learners learning and to evaluate performance using Data Mining Tools to enhance the future outcome. The experimental results show that with the proposed approach the learners learning is improved with positive emotions.

192

Authors: Pushpa Mohan, Kiran Kumari Patil

In India Rice and ragi are the two pre-eminent crops that stable’s the food of eastern and southern part of the country. These two crops mainly grown in rain fed areas, which receives heavy annual rainfall. In this scenario, Mysore district is undertaken for experiment analysis. As the region receives heavy rainfall (782mm). In this region the rainfall rate is high but the productivity of this crops are very low due to irrelevant crop cultivation. In order to overcome this concern, an advanced technology named Weighted-Self Organizing Map (W-SOM) is employed for accurate crop and weather prediction, which is the combination of both Self Organizing Map (SOM) and Learning Vector Quantization (LVQ). In this paper, the prediction accuracy is enhanced by minimizing the Within Class Error (WCE) among the clusters. Therefore, this new approach outcome shows a clear idea about suitable crop cultivation in Mysore. Experimental outcome shows that the proposed approach improved accuracy in crop and weather prediction up to 0.5-2% compared to the existing methods: SOM, Kernel-Nearest Neighbors (KNN) and Ensemble Neural Network (ENN).

208

Authors: Puttaswamy Gowda Vanajakshi, Murugavelu Mathivanan, Thangamuthu Senthil Kumaran

There is a big challenge in speech recognition system due to variability of the spoken languages and also speech signal is degraded due the environmental noise. Therefore speech recognition system requires pre-processing, which plays vital role to restore speech signal more effectively. Many challenges are there to restore the speech from different noisy environment. In this paper, proposed method is divided into two parts. First part is Kannada speech restoration, the modified wiener filter is proposed to restore the Kannada speech signal with very good speech quality. The experimental results are verified for different types of noise by varying input Signal to Noise Ratio (SNR) from -20dB to 5 decibels (dB). Second part is Autocorrelation based Kannada speech recognition system. Autocorrelation technique gives better output SNR for degraded input SNR with -20dB. The Autocorrelation is the simple method to recognize the isolated Kannada word in speech signal. This proposed technique results 100% recognition rate for male, female, with different accents.

225

Authors: Kasarla Satish Reddy, Hosahally Narayangowda Suresh

Reconfigurable Finite Impulse Response (RFIR) filter plays an important role in Software Defined Ratio (SDR) systems, whose filter co-efficient change dynamically during runtime. In this paper, Low Cost Carry Bypass adder Reconfigurable Finite Impulse Response (LC-CBA-RFIR) is introduced to perform the RFIR filter operations. DRAM-based Reconfigurable Partial Product Generators (DRPPG) consists of MUX and dual port distributed RAM, which has co-efficient to perform a FIR filter operation. With the help of Verilog code, the RFIR filter architecture was verified in Modelsim software. The same Verilog code was used to analyse the ASIC performances such as area, power and delay Area Power Product (APP), Area Delay Product (ADP) as well as FPGA performances such as LUT, flip flop, slice and frequency. After implementing ASIC and FPGA, all the performance improved in LC-CBA-RFIR method compared to the conventional methods.

246

Authors: Sunitha Mallasetty Shivamallaiah, Kwadiki Karibasappa

Nowadays, wireless communication plays a major role in sending information from one area to another in an effective way. In wireless communication, the important parameters are coverage area, power consumption, lifetime, and Black Hole (BH) detection in network with interconnected mobile nodes. Ant Colony Optimization (ACO) is used for finding shortest path in the Network. ACO helps in choosing another path, if there is any malicious node in the network. Data is secured using Dual Rivest-Shamir-Adleman (DRSA) technique and Black Hole Detection (BD) is used for identifying malicious node in the network. For efficient wireless system these parameters have been optimized, several algorithms have been applied to optimize the performance parameters and detect the BH in the network. Efficient BH identification with optimized routing algorithm is implemented in secured environment by using Dual RSA. The ACO-DRSA-BD algorithm precisely detected the BH Node (BHN) in finding the proper solution for data transmission using ACO and secured environment using DRSA. Hence, “ACO-DRSA-BD” finds proper solutions for transmitting data in the presence of BH Attacks and enhancing better performance parameters in terms of throughput, routing overhead and energy consumption.

266

Authors: Ammar Djerioui, Dehimi Ouali, Mohamed Ladjal

This paper proposes a sliding mode control strategy for hybrid power system (HPS). The hybrid power system consists of four-leg voltage source Inverter Bridge. The HPS ensures full compensation for harmonic phase currents, neutral current, reactive power compensation and unbalanced nonlinear load currents. The Sliding Mode control strategy with a three dimensional space vector modulation deals with power quality enhancement in standalone power-supply systems with the key objective to compensate for AC side load and phase disturbances that result essentially from the presence of nonlinear and unbalanced loads. The four-leg voltage source inverters play an important role by providing both balanced and unbalanced loads with clean power and balanced output voltage. The simulation results show that the performance of the four-leg HPS with the proposed control algorithm.