Showing papers by "Vignan University published in 2013"

Proactive, reactive and hybrid multicast routing protocols for Wireless Mesh Networks

Abstract: Wireless Mesh Networks comes under the category of mobile ad-hoc networks with fixed positions of nodes to communicate to the internet through a single gateway or more than one gate way. In order to provide a multi point communication within the mesh network, a multicast routing protocol is required. Multicast routing is a key technology for modern communication networks. Multicast Routing becomes a prominent technology for wireless communication networks various multicast routing protocols are developed for internet and ad-hoc communications This paper gives the overview of some of the existing proactive, reactive and hybrid multicast routing protocols over WMNs with its strengths and weaknesses. The following multicast routing protocols are selected for their performance comparison; they are On Demand Multicast Routing Protocol(ODMRP), Multicast Ad hoc On Demand distance Vector (MAODV) Protocol, Multicast Open Shortest Path First (MOSPF), Ad hoc Multicasting Routing Protocol(AM Route) and Optimized Polymorphic Hybrid Multicast Routing Protocol(OPHMR). Among them, MOSPF and AM Route is a proactive routing protocol and OPHRM is a Hybrid routing protocol while MAODV and ODMRP are reactive multicast routing protocols.

Emotion recognition in speech using MFCC and wavelet features

Abstract: Recognition of emotions from speech is one of the most important sub domains in the field of affective computing. Six basic emotional states are considered for classification of emotions from speech in this work. In this work, features are extracted from audio characteristics of emotional speech by Mel-frequency Cepstral Coefficient (MFCC), and Subband based Cepstral Parameter (SBC) method. Further these features are classified using Gaussian Mixture Model (GMM). SAVEE audio database is used in this work for testing of Emotions. In the experimental results, SBC method out performs with 70% in recognition compared to 51% of recognition in MFCC algorithm.

Detecting unusual customer consumption profiles in power distribution systems — APSPDCL

Abstract: Energy supplied by the power utility does not reach to the consumer end as a whole A portion of energy is lost in the distribution system because of Technical and Nontechnical losses The objective of this paper is to detect the Non-technical losses by monitoring customer irregular consumption profiles in power distribution system with the help of data-mining techniques As a first step fuzzy C-Means clustering is performed to group customers of same consumption patterns Then fuzzy based classification technique applied with help of fuzzy membership function and the distances of cluster centers are measured by Euclidean distance, and the distances are normalized and ordered with unitary index score, the highest score represents fraudsters The approach was tested on a real data, showing good performance in tasks of fraud and measurement defect detection comparing with theft record of Power Distribution Company

A Square Wave Generator Using Single CMOS DCCII

Abstract: In this paper, square wave generator using a single second generation differential current conveyor (DCCII) is proposed. The proposed square wave generator consists of two resistors and a single grounded capacitor. CMOS gpdk 180 ㎚ technology was used for designing the proposed circuit. The mathematical analysis, simulation results and experimental results of the proposed circuit are discussed. And its time period can be tuned independently either by the grounded capacitor C, or, by the resistor R1. Later, the circuit was built with commercially available current feedback amplifiers (AD844), passive components used externally and tested for waveform generation and tunability. Obtained results demonstrate good agreement with theoretical values.

Development of supercritical fluid (carbon dioxide) based ultra performance convergence chromatographic stability indicating assay method for the determination of clofarabine in injection

Abstract: The present study reports the development and validation of a stability indicating assay method for clofarabine in injection on a UPC2™ (ultra performance convergence chromatography) instrument, which utilizes the unrealized potential of supercritical fluid chromatography. The use of UPC2™ provides a single viable technique that is a sustainable, reduced cost, and green technology that lowers the use of organic solvents. Based on this advantage, we explored a simple and robust method in order to increase sample throughput and productivity to quantify clofarabine in the presence of its potential impurities and other degradants. The separation was achieved on a BEH-2-ethyl pyridine (BEH 2EP) column (100 mm × 3.0 mm I.D. with an average pore diameter of 1.7 μm) by using methanol as a co-solvent and carbon dioxide as a mobile phase in the ratio of 30:70. The detection is carried out at a wavelength of 254 nm. We are able to achieve the separation of clofarabine from its potential impurities and other degradants in less than 6 minutes with a low amount of solvent consumption. The new method is validated in accordance with the ICH-guidelines and exhibited good intra- and inter-day precision, accuracy and linearity (r2 ≥ 0.999) over a range of 50% to 150% of target concentration.

Mutational pressure dictates synonymous codon usage in freshwater unicellular α - cyanobacterial descendant Paulinella chromatophora and β - cyanobacterium Synechococcus elongatus PCC6301

Abstract: Comparative study of synonymous codon usage variations and factors influencing its diversification in α - cyanobacterial descendant Paulinella chromatophora and β - cyanobacterium Synechococcus elongatus PCC6301 has not been reported so far In the present study, we investigated various factors associated with synonymous codon usage in the genomes of P chromatophora and S elongatus PCC6301 and findings were discussed Mutational pressure was identified as the major force behind codon usage variation in both genomes However, correspondence analysis revealed that intensity of mutational pressure was higher in S elongatus than in P chromatophora Living habitats were also found to determine synonymous codon usage variations across the genomes of P chromatophora and S elongatus Whole genome sequencing of α-cyanobacteria in the cyanobium clade would certainly facilitate the understanding of synonymous codon usage patterns and factors contributing its diversification in presumed ancestors of photosynthetic endosymbionts of P chromatophora

Design and implementation of an automatic beverages vending machine and its performance evaluation using Xilinx ISE and Cadence

Abstract: This paper describes the design and implementation of an automatic beverages vending machine using FSM as this technique has more advantages compared to previous ones used in vending machine design. The whole design is functionally verified using Xilinx ISE simulator 13.1 and the generated bit stream file has implemented in Virtex 5 XC5VLX50T FPGA board and its physical design has performed using Cadence Encounter and evaluated its optimized parameters.

A sinusoidal oscillator using single Operational Transresistance Amplifier

Abstract: This paper illustrates a sinusoidal oscillator based on Operational Transresistance Amplifier (OTRA). The proposed oscillator circuit consists of one OTRA and few passive components to generate the oscillations. The condition of oscillation and frequency of oscillation of the proposed circuit is controlled by a single grounded resistor. CMOS gpdk 180 nm technology was used to test the overall performance of the proposed circuit. The OTRA circuit has been built using commercially available current feedback operational amplifier (AD844 AN) and later passive components are connected externally and tested for waveform generation. The simulated and experimental results are presented and the tunability of the grounded resistor is given. The results obtained demonstrate excellent agreement with theoretical values.

Facial expression classification using Kernel based PCA with fused DCT and GWT features

Abstract: Although many approaches for facial expression recognition have been proposed in the past, most of them yielding poor recognition performance with single feature extraction method The objective of this paper is to propose an innovative method based on fusion of local and global features for better classification rate Gabor wavelets(GWT) are used to extract Local features and Discrete Cosine Transform (DCT) is used to extract global features from facial expression images To reduce dimensionality of extracted features and better classification performance Kernel Principal Components Analysis (KPCA) is applied Wavelet fusion method is used to fuse the features extracted from GWT and DCT Finally the images are classified into 6 different basic emotions like surprise, fear, sad, joy, anger and disgust using Radial Basis Function(RBF) Neural Network classifier The performance of the proposed method is evaluated on Cohn-Kanade database The results of proposed algorithm exhibit high performance rate of about 99% in person dependent facial expression recognition

Parallel processing of enhanced K-means using OpenMP

Abstract: Cluster Analysis plays a vital responsibility in scientific investigation and business applications. K-Means clustering algorithm is broadly used as a partitioning technique. K-Means clustering algorithm is not much suitable for huge voluminous of data sets. Iterative clustering with K-Means has more Execution time. To avoid such, A Parallel Partitioning of enhanced K-Means algorithm using OpenMP is proposed to handle the outliers with optimized execution time without affecting the accuracy. The experiments are performed on diabetes, soya beans and supermarket by considering multi-core systems with 768, 683 and 4627 instances respectively. The proposed method outperforms with an accuracy of 74.76% for diabetes dataset with an execution time of 56secs, soya beans datasets with an accuracy of 82.34% with an execution time 54secs and supermarket datasets with an accuracy of 80.45% with 54secs of execution time.

Short-Term Real-Time Reservoir Operation for Irrigation

Abstract: The development and management of irrigation facilities has been recognized as the key to national development in India. Despite their high priority and massive investments, the performance of major irrigation projects has been disappointing. Substantial benefits can be achieved from relatively small increases in operating efficiencies. The main objective of this study is to develop a short-term, real-time reservoir operating policy in a multicrop, multiseason environment integrating reservoir release decisions with field irrigation requirements. A real-time reservoir operation model defines the set of releases to be made into each offtake on the main canals of a reservoir for a known set of release targets, reservoir storage state, and forecasted inflow in the current period, minimizing the deficit function. An intercrop allocation model allocates reservoir releases of the current period among competing crops. On implementing the irrigation decisions of the intercrop allocation model for the curr...

Gabor based face recognition with dynamic time warping

Abstract: Many approaches are proposed for face recognition from last three decades but they are challenging the problems like illumination, pose and scaling variations. In this paper a new methodology has been proposed for improving the efficiency of face recognition based on local feature extraction using Gabor Wavelets. The extracted features are classified using non linear matching algorithm like Dynamic Time Warping (DTW). DTW is a technique which is used to identify an optimal warp between two feature vectors. Based on the constraints of DTW it provides better accuracy than the existing methods with Euclidean distance. The proposed method has given 96.19% recognition rate on Grimace face database, 86.38% of recognition rate on ORL and 90.67% on Yale like standard bench mark face databases.

Performance evaluation of different SRAM topologies using 180, 90 and 45 nm technology

Abstract: The design of various standard SRAM topologies with different technologies has been designed and tested for delay and power dissipation with respect to the different supply voltages For this consideration, different topologies viz 6T, 7T, 8T, 9T and 10T SRAM cells have taken And these cells are designed using generic process development kit (gpdk) 45, 90 and 180 nm technologies And all these are tested in cadence tool The detailed analysis about these cells functionality and their characteristic behavior with the applied parameter of supply voltage is presented The results of the delay, power dissipation with respect to the Vdd are plotted using MATLAB software Also their layouts were designed and tabulated their areas

Implementation of a full adder circuit with new full swing EX-OR/EX-NOR gate

Abstract: The Ex-OR and Ex-NOR gates are the basic building blocks of various digital system applications like adder, comparator, and parity generator/checker and encryption processor. This paper proposes a full swing pass transistor based Ex-OR/Ex-NOR gate which gives better driving capability, less propagation delay and low power dissipation as compared to the existing Ex-ORlEx-NOR circuits, and by modifying the existed circuits. Full adder is an essential component for the design and development of all type of processors like digital signal processors, microprocessors etc. So, in this paper a full adder is constructed by using the new proposed Ex-OR/Ex-NOR gate. All the existed and proposed circuits have been simulated using Cadence 180nm CMOS technology file at different supply voltages ranging from 0.6 V to 3.3 V. The simulation result demonstrates that the delay, power dissipation and power-delay product (PDP) of the proposed design are better than existed design.

Image enhancement using DT-CWT based cycle spinning methodology

Abstract: This paper proposes an effective resolution enhancement approach for images such as satellite images as well as normal images. In this method DT-CWT and bicubic interpolation were used. The proposed method was tested on well-known benchmark images. Finally Peak Signal to Noise Ratio (PSNR) and visual results of the proposed method out performs the state of art image resolution enhancement techniques.

Performance analysis of a new CMOS output buffer

Abstract: A new CMOS output buffer with low switching noise and load adaptability is presented in this paper. The proposed circuit consists of two stages; first stage is set to reduce switching noise, static power dissipation and also output ringing. The second stage involves enough speed and full dynamic range. The performance of the proposed circuit is examined using Cadence and the model parameters of a 180 nm CMOS process. The simulation results have confirmed that the proposed output buffer can reduce propagation delay compared with the previous designs. The topology reports low sensitivities and has features suitable for VLSI implementation.

Gain Ratio as Attribute Selection Measure in Elegant Decision Tree to Predict Precipitation

Abstract: Prediction of precipitation is a necessary tool in meteorology. To date, it is technologically and scientifically a challenging task for scientists and researchers around the globe. Rainfall is a liquid form of precipitation that depends primarily on humidity, temperature, pressure, wind speed, dew point, and so on. Because rainfall depends on several parameters, its prediction becomes very complex. Approaches such as the back propagation, linear regression, support vector machine, Bayesian networks, and fuzzy logic can be applied, but their rate of prediction is very low, which leads to unpredictable results. This paper aims at improving the prediction of precipitation compared to Supervised Learning in Quest (SLIQ) decision trees, especially when datasets are large. Because SLIQ decision trees take more computational steps to find split points, they consume more time and thus cannot be applied to huge datasets. An elegant decision tree using gain ratio as an attribute selection measure is adopted, which increases the accuracy rate and decreases the computation time. This approach provides an average accuracy of 76.93% with a reduction of 63% in computational time over SLIQ decision trees.

High DHA dosage from algae oil improves postprandial hypertriglyceridemia and is safe for type-2 diabetics

Abstract: Postprandial refers to diet induced changes in plasma concentrations of sugars, amino acids and fats be- tween 0 and 6 h following a meal. This review details the fat transport through lipoprotein particles and triglyceride frac- tions in the postprandial plasma. The long-chain omega-3 fatty acid docosahexaenoic acid (DHA) is more active in postprandial plasma and is more abundantly incorporated into the surface phospholipid fraction of lipoproteins. A survey of controlled clinical trials in the literature demon- strates that 1,000 mg to 2,000 mg DHA daily is effective to treat hypertriglyceridemia (HTG), mixed dyslipidemia and most effectively controls elevated postprandial triglycerides (TG). TG is a marker for total fat in circulation. Omega-3 fatty acids lower fasting and postprandial TG, an activity first discovered in 1971 in Greenlandic Inuits. Low TG and high DHA were coincident with the absence of type 2 diabetes. It is now known that DHA is the major structural and functional omega-3 component of lipoproteins in hu- man plasma. DHA is the omega-3 to most substantially increase by mass in the phospholipid fraction of very low- density lipoproteins (VLDL), low density lipoproteins (LDL) and high density lipoproteins (HDL). DHA is most effective at raising HDL levels and improves the omega-3 index in red blood cells (RBC). DHA intake also correlates with greater than 25 % reductions of fasting TG and greater than 40 % reductions in postprandial TG. Postprandial HTG is common in the type 2 diabetes; therefore, we considered the safety of DHA from Schizochytrium sp. algae oil and the evidence for risk reduction of coronary vascular disease (CVD) and type 2 diabetes. Recent clinical trials suggest high DHA intake from Chromista algae controls plasma TG, but does not appear to control glucocentric markers or cholesterol levels. DHA directly affects postprandial TG transport, but has little effect on insulin function and insulin resistance. Applications for use in South Asian diabetics are considered. 1,200 mg algae DHA daily over 3 months is an optimized program for direct control of postprandial HTG and is safe for type 2 diabetics.

Design of automatic cotton picking robot with Machine vision using Image Processing algorithms

Abstract: Agricultural sector is desperately in need of engineering outcomes such as Automation, Information Technology and more recently Robotic Technology. Cotton Cultivation in India occupying a big share in commercial crops is facing a major problem of picking the cotton from the plants by the labor as the labor costs are increasing these days. This paper aims at achieving a prominent solution with the use of Machine vision together with Image Processing and Microcontrollers for identification, recognition, and processing of the cotton image as such and picking the cotton with robotic arms to yield maximum production in a day per hectare. Research and development in perceptual system for robots enabled the agricultural sector to catch hold of the technology in reducing the overall cost. These intelligent robots use variety of visual sensors to detect objects with respect to their identity, position, color, orientation in 3D pattern at the fields. This paper also proposes at the new algorithms in Image processing of the cotton to extract the feature, modeling and matching. These are Artificial Intelligence for Robotic Vision, Image Processing for Segmentation, feature measurement such as invariants, size and shape, texture and scene analysis and controlling the robotic arms in desired angle.

Sensors based automated wheelchair

Abstract: Physically challenged persons may not be able to steer their wheelchair conveniently with the available assistive technologies. Though there are many methods available in recent times to enable their motility, they require efficient and precise control which is most of the times not possible. In recent times there are various control systems that are developed and under developing stage especially for people with various disorders and disabilities. In this project each eye will be having IR transmitter and receiver. Transmitter IR will transmit the light over iris and reflected light will received by IR receiver. Depending upon the intensity of reflected light falling on the receiver, the controller will be understand the user intention of wheelchair movement. Now controller will take the decision of moving forward, left or right as long as IR receiver receives the directions information from the user. DC motors are used to apply torque to the individual wheels so that direction control can be ensured. This system enables the patient to have command over the chair, its direction of movement and the system will also will also sense and alarm the user about the obstacles in the path to avoid any severe consequences the accelerometer monitors the inclination of the wheelchair. This wheelchair helps the patient to move in environments with ramps and doorways of little space by establishing communication between human eye iris and IR sensor.

A Gini Index Based Elegant Decision Tree Classifier to Predict Precipitation

Abstract: Water is one of the most important of nature's gifts to the living creatures on Earth. Rainfall is one form of precipitation, and it primarily depends on humidity, temperature, pressure, wind speed, dew point, and so on. The present research is focused on using the gini index as an attribute selection measure in an elegant decision tree to predict precipitation for voluminous datasets. This study aims at improving the prediction of precipitation over the supervised learning in a Quest decision tree, especially when the datasets are large. A decision tree using the gini index increases the accuracy rate while decreasing computational time by reducing the computation of total split points. This approach provides an average accuracy of 72.98% with a reduction of 63% in computational time over a SLIQ decision tree.

Preparation and Characterization of R.F. Magnetron Sputtered Mo:ZnO Thin Films

Abstract: The ZnO and Mo:ZnO thin films were deposited by radio frequency magnetron sputtering on quartz and intrinsic silicon (100) substrates at a fixed combined partial pressure mbar of Ar

Analysis of Two New Voltage Level Converters With Various Load Conditions

Abstract: The use of level converter in dual supply voltage circuits is one of the most effective ways to reduce power consumption To prevent static current, level converter is introduced as an interface at each low-to-high boundary The design of an efficient level converter with least power consumption and overheads delay is one of the major design constraints In this paper, two new level converter circuits with low power consumption are proposed for less propagation delay and load adaptability The proposed level converter circuits are examined using cadence and the design parameters of a 180 nm CMOS process The simulation results exhibit that proposed level converter can reduce propagation delay and increase speed over the existing circuits available These level converters are simulated for different loads and operating conditions The proposed level converter can operate at different values of V DDL as +1 V, +18 V, +2 V and V DDH of +33 V The topology reports low sensitivity and has features suitable for VLSI implementation The proposed circuits are suited for low power design without degrading performance

An efficient multimodal person authentication system using Gabor and sub band coding

Abstract: This paper presents fusion of two biometric traits, i.e., face and speech, at matching score level fusion. The features are extracted from the pre-processed images of face and speech. Gabor Wavelet and Discrete Cosine Transform (DCT) are used to extract facial features and Sub Band Coding (SBC) is used to extract features from speech signals. These features of a probe image are compared with training images of each trait and then calculate matching score. The individual scores generated after each matching are passed to the fusion module. The final score is then used to declare the person as genuine or an impostor. The proposed method is tested on ORL database and it outperforms with False Acceptance Rate of 0.75% and False Rejection Rate of 1.24%.

A Novel Decision Tree Approach for the Prediction of Precipitation Using Entropy in SLIQ

Abstract: The rising tendency of population of every nation is one of the severe stumbling blocks to arrest its economic growth, particularly in the third world countries like India, not able to address even the basic needs of its people. It is high time to have introspection for the deficiencies and find a remedy. The major basic need is food, a product of agriculture. Agriculture mainly depends on rainfall. Prediction of precipitation is a complex phenomenon. Till now many of the researchers have tried their best for predicting the precipitation but in vain, since the prediction is quite complex with neural networks, back propagation, fuzzy logic etc. Hence, we found that data mining is an emerging, efficient, easily implementable tool, which predicts the useful patterns for the prediction of rainfall in a very short time. Supervised Learning In Quest, an efficient data mining decision tree algorithm is applied in the prediction of precipitation. The present research illustrates the Supervised Learning In Quest decision tree algorithm using entropy, which estimates the prediction of precipitation with an average accuracy of 74.92% and the knowledge extraction is purely based on historical data.