bluuebunny/crossref_metadata_2025_split huggingface dataset:
Adaptive Fuzzy Controller Design for Solar And Wind Based Hybrid System
Authors: Rathaiah M , Ram Kishore Kumar Reddy P , Sujatha P 
Published: May 2018

Renewable Energy Resources plays an active role in standing against global warming and reduce the use of conventional energy sources. Hybrid systems formed by combining the renewable energy sources are efficient relatively. The intent of this paper is to furnish endurable power for frontier and far-off places with hybrid-system of architecture. The intended system embodying DFIG and solar PV based wind turbine. In solar systems, control mechanism is essential for improving the performance. This paper proposes a method of incremental conductance approach based MPPT Adaptive Fuzzy Logic Controller for grid connected PV system which is composed of a boost converter and a three phase inverter. Adaptive Fuzzy Logic Controller provides fast response and better %THD compared to Fuzzy and PI controllers. In solar system, MPPT will magnify solar output power value. The DFIG has two controllers Grid-Side Control (GSC) and Rotor-Side Control (RSC). The rated rotor speed and DC-link voltage are regulated by RSC and GSC through PI, Fuzzy Logic Controller and AFLC strategies. By using simulation studies performed by three control strategies, %THD analysis is carried out.
Enhancing the Quality of Underwater Images using Fusion of sequential Filters and Dehazing
Authors: Suganthy M , Lakshmi S , Palanivel S 
Published: May 2018

Effectively analyzing underwater images and identifying any object under the water has become a difficult task. Generally, the factors affecting underwater images are uneven lighting, low contrast, blunt colors, and characteristics of an object based on absorption and scattering of light. The proposed technique involves applying white balancing and contrast enhancement to the original image. The combination of filters namely homomorphic filtering, wavelet denoising, bilateral filter , adaptive filters are used and applied sequentially on the degraded underwater images. The results obtained showed that the proposed algorithm works well in refining the underwater image attributes. Peak Signal to Noise Ratio (PSNR) and Mean Squared Error (MSE) are used to evaluate performance of the algorithm.
A New Empirical Evaluation of Existing Methods for Estimating BDD Sizes
Authors: Raja Madasamy , Vidhya Lakshmi K , Raseen Mohamed 
Published: May 2018

Binary Decision Diagrams (BDDs) are very useful structures to represent Boolean function in VLSI synthesis. Time taken to build a BDD and obtaining its size plays a major role in the time of complexity of VLSI synthesis. This time complexity increases drastically as the number of input variables increases. Various models to estimate the size of the BDD, without actually building it already exists. These models claim to support both simplified and un-simplified Boolean functions. The models were developed under the justification that time to estimate will be far less compared to the time taken to actually build the BDD. There are two drawbacks with the existing model. First drawback is that, the current model just follows a random curve fit without any substantial mathematical support. Second drawback is the existing model is based on experimental results which used only less than ten variables. Since current practical functions may use hundreds of variables, there is no guarantee that the model is accurate enough. Given the two drawbacks, it becomes necessary to test the existing model for more complex circuits with hundreds of variables. In this paper the existing models were tested with standard benchmark circuits. Results were compared with actual BDD sizes of the benchmarks and the estimated sizes from the parameters of the benchmarks. Comparison of the results proved that existing models give poor results for the circuits with more than ten variables and existing models become inapplicable to most of the current practical functions that uses more than hundreds of variables.
Complex Number Vedic Multiplier and its Implementation in a Filter
Authors: Saraswathi N , Modi Lokesh , Nair Aatish 
Published: May 2018

Complex numbers multiplication is a fundamental mathematical process in systems like digital signal processors (DSP). The main objective of complex number multiplication is to perform operations at lightning fast speed with less intake of power. In this paper, the best possible architecture is designed for a Real vedic multiplier based on the ancient Indian mathematical procedure known as URDHVA TIRYAKBHYAM SUTRA i.e. the structure of a MxM Vedic real multiplier architecture is developed. Then, a Vedic real multiplier solution of a complex multiplier is presented and its simulation results are obtained. The MxM Vedic real multiplier architecture, architecture of the Real Vedic multiplier solution for 32 x 32 bit complex numbers multiplication of complex multiplier and the architecture of a FIR filter has been code in Verilog and implementation is done through Modelsim 5.6 and Xilinx ISE 7.1 navigator.
Improved Query Processing in Web Search Engines Using Grey Wolf Algorithm
Authors: Pal Nishant , Chawla Akshat , Meena Priyadharsini A 
Published: May 2018

In Information systems working at a large scale where retrieval of information is an essential operation for example search engines etc. The users are not only concerned with the quality of results but also the time they consume for querying the data. These aspects lead to a natural tradeoff in which the approaches that lead to an increase in data have a similar larger response time and vice-versa. Hence, as the requirement for faster search query processing time along with efficient results is increasing, we need to identify other ways for increasing efficiency. This work proposes an application of the meta-heuristic algorithm called Grey Wolf Optimization (GWO) algorithm to improve Query Processing Time in Search Engines. The GWO algorithm is an alter ego of the way in which the grey wolves are organised and their hunting techniques. There are four categories of grey wolves in a single pack of grey wolves which are alpha, beta, delta, and omega respectively. They are used to work in a simulating hierarchy. These help achieve better search results at decrease query response timings.
Strength and Durability Studies on Geopolymer Recycled Aggregate Concrete
Authors: Saravanakumar P 
Published: May 2018

This paper aims to study the engineering and durability properties of fly ash-based geopolymer recycled aggregate concrete and the results were presented in this paper. The addition of recycled coarse aggregate (RCA) retrieved from construction and demolition(C&D) wastes showed promising function in construction industry as an alternative to natural aggregates. It conserves enormous quantities of natural resources and reduces the space required for the landfill disposal of C&D wastes. In this study an increment of 25% partial replacements by weight of natural aggregates with recycled aggregates in geopolymer concrete up to 100% replacements were studied. The concrete containing virgin aggregate and ordinary Portland cement was consider as control concrete and the results of geopolymer recycled aggregate concrete (GP-RAC) were compared with this. The fresh and mechanical properties of all the above four concrete mixes has been investigated. Results indicated that workability of geopolymer concrete decreases than control concrete and it took more than 24 hours to set. Geo polymer based recycled aggregate concrete exhibits better strength and durability performance than ordinary recycled aggregate concrete.
Object Detection Using Support Vector Machine and Convolutional Neural Network - A Survey
Authors: Khosla Rishi , Singh Yashovardhan , Balachander T 
Published: May 2018

Mobile Technologies have been in trend for quite some time and with the advances in machine learning, they have become more powerful. Computer Vision, Computational Analysis and Computer Graphics have changed over the course of time. In this Project, our aim is to figure out the domains in which Machine Learning can be applied to enhance the capabilities of a Mobile Device which would lead to a better and sustainable mobile user experience. The models we would use are a convolutional neural network (CNN), support vector machine (SVM) and scale-invariant feature transform (SIFT). This project uses the real-time image from a mobile device and does the classification and detection with the help of Tensor Flow and provides the result with a confidence score.
An Improved Bi-Level Thresholding Based Uncertainty Evaluation for Speech Enhancement in Non-Stationary Noises
Authors: Nageswara Rao S , Jaya Sankar K , D. Naidu C 
Published: May 2018

This paper proposes a new speech enhancement framework to improve the quality of speeches recorded under adverse acoustic environments based on the speech presence uncertainty. Since the uncertainty evaluation gives a more and clear discrimination about the speech and noise, this paper proposes a new uncertainty evaluation mechanism as a preprocessing mechanism to the noise suppression methods. This mechanism relates with energies of a noisy speech signal and classifies the speech segments and noise segments more perfectly. In addition to the quality enhancement, this approach also reduces the unnecessary computational burden over the speech processing system. Extensive simulations are carried out over the speech signals with different types of non-stationary noises like babble noise, exhibition noise, restaurant noise and train station noises and the performance is measured with the performance metrics namely the Output SNR, AvgSegSNR, PESQ and COMP. The comparative analysis of proposed approach over the conventional approaches shows an outstanding performance in all environments.
Design of Low Power UWB CMOS Low Noise Amplifier using Active Inductor for WLAN Receiver
Authors: Manjula S , Malleshwari M , Suganthy M 
Published: May 2018

This paper presents a low power Low Noise Amplifier (LNA) using 0.18µm CMOS technology for ultra wide band (UWB) applications. gm boosting common gate (CG) LNA is designed to improve the noise performance. For the reduction of on chip area, active inductor is employed at the input side of the designed LNA for input impedance matching. The proposed UWB LNA is designed using Advanced Design System (ADS) at UWB frequency of 3.1-10.6 GHz. Simulation results show that the gain of 10.74+ 0.01 dB, noise figure is 4.855 dB, input return loss <-13 dB and 12.5 mW power consumption.
An Atrial Fibrillation with Normal Limits using Signal Processing- A Review
Authors: Sathish S. , Mohanasundaram K 
Published: May 2018

Atrial fibrillation is an irregular heartbeat (arrhythmia) that can lead to the stroke, blood clots, heart failure and other heart related complications. This causes the symptoms like rapid and irregular heartbeat, fluttering, shortness of breath etc. In India for every around 4000 people eight of them are suffering from Atrial Fibrillation. P-wave Morphology. Abnormality of P-wave (Atrial ECG components) seen during sinus rhythm are associated with Atrial fibrillation. P-wave duration is the best predictor of preoperative atrial fibrillation. but the small amplitudes of atrial ECG and its gradual increase from isometric line create difficulties in defining the onset of P wave in the Standard Lead Limb system (SLL).Studies shows that prolonged P-wave have duration in patients (PAF) In this Study, a Modified Lead Limb (MLL) which solves the practical difficulties in analyzing the P-ta interval for both in healthy subjects and Atrial Fibrillation patients. P-Ta wave interval and P-wave duration can be estimated with following proposed steps which is applicable for both filtered and unfiltered atrial ECG components which follows as the clinical database trials. For the same the p-wave fibrillated signals that escalates the diagnosis follows by providing minimal energy to recurrent into a normal sinus rhythm.
Implementation of Parallel Execution Algorithm on Multiple Drives using PLC
Authors: Jayendran Sangita , Aruna Priya P 
Published: May 2018

Drive is one among the very vital equipment in any power industry which require continuous monitoring and inspection at frequent intervals. And this paper deals with the implementation of parallel execution of multiple drives using Programmable Logic Controller (PLC). We have designed the ladder code using Add on Instructions (AOI) which is the most used feature of RS Logix 5000. For the operation of each axis of a drive we require an instance of the AOI in the main routine. At every phase the failure mechanism is also added in order to take care of the failed conditions. Parallel execution of multiple drives can reduce the execution time by a huge a margin.
Security Vulnerabilities of Virtualization Technique
Authors: N Saravanan , A Umamakeswari 
Published: May 2018

Cloud computing is a computing model for delivering resources in a convenient manner from a shared pool. The resources provisioned and released on an on-demand basis with minimal intervention of service provider. Cloud Computing is becoming the platform for all kind of web based services. Virtualization is the key concept to adopt the cloud computing. Virtualization offers many benefits comparing to real physical machine implementation infrastructure. Even though virtualization provides lots of benefits, it is also brings several security vulnerabilities. This paper presents the security breaches of various virtualization techniques that are applied in virtual machines, in which health care records maintained.
Data Integrity Verification Using MPT (Merkle Patricia Tree) in Cloud Computing
Authors: Mathiyalahan Subasri , Manivannan Shobana , Nagasundaram Mahalakshmi , Ezhilarasie R 
Published: May 2018

Data integrity of outsourced data is main problem in CSP (cloud service provider). Space overhead and computation complexity are very high issue in recent PDP(Provable Data Possession) verification schemes. To overcome such issues MPDP (Mobile Provable Data Possession) schemes using hash tree data structure and Boneh-Lynn-Snacham short signature scheme have been used over decade. Data dynamics is well supported in MPDP scheme via block less verification, dynamic data operations, stateless verification, and verification out sourcing. But still there are some operations which can be performed much more efficiently in some other way than that of the two methods prescribed above. Operations in particular, data modification operations like insertion and deletion operations is somewhat difficult or in other words time consuming in hash tree data structure. In this paper, we have deployed an improved hash tree structure called MPT (Merkle Patricia Tree) for integrity checking.MPT is combination of MHT (Merkle Hash Tree) and patricia tree where each node consists of key-value pairs. As of now, MPT has been used only in block chain technology for providing authentication of transactions through Ethereum.
Design and Implementation of Smart and Low Cost Multi-task Farming System Using Arduino
Authors: Shasi Kiran Uppu , Arya Shanu , Rajasekaran M 
Published: May 2018

Using the idea of IOT this project explain the multi-task farming system using Arduino. The system uses a Wi-Fi module in which system is connected to the internet. A motor and two valve are controlled by this module for transporting the water to the farm on receiving the signal from a water level sensor and soil moisture indicator. This system explain the illustration of Internet of Things (IOT). This concept does the work like weeding, spraying water, harvesting, etc. The system also does the work like determining the humidity of the soil and measuring the physical environmental factor which can be monitored by any individual from anywhere they want and the data gets recorded in the database of the webpage or the app through IOT connection and the individual gets a notification on their cellular phone through message so that he can operate the system through a push message or can be done through the mobile app if there is any requirement to the field that to be taken care of.
Huffman coding packet balancer based data compression techniques in Wireless Sensor Network
Authors: Rao Varun , Nukala Sandeep , G Abirami , R Deepa , Venkataraman Revathi 
Published: May 2018

In Wireless Sensor Networks, sensor devices perform sensing and communicating task over a network for data delivery from source to destination. Due to the heavy loaded information, during packet transmission, sensor node will drain off its energy frequently, thus led to packet loss. The novelty of the proposed work is mainly reducing the loss of packet and energy consumption during transmission. Thus, Huffman coding packet balancer select the best path between the intermediate nodes and are compared based on transmitting power, receiving and sensing power these measure the QOS in wireless sensor network. To satisfy the QOS of the node, compressed packet from source to destination is done by choosing the best intermediate node path. The advantages of the proposed work is minimum packet loss and minimize the end to end delay. Sparse recovery is used to reconstruct the path selection when there is high density of node.
Optical Compute Engine Using Deep CNN
Authors: Zaveri Zainab , Gosain Dhruv , Prakash M Arul 
Published: May 2018

We present an optical compute engine with implementation of Deep CNNs. CNNs are designed in an organized and hierarchical manner and their convolutional layers, subsampling layers alternate with each other, thus the intricacy of the data per layer escalates as we traverse in the layered structure, which gives us more efficient results when dealing with complex data sets and computations. CNNs are realised in a distinctive way and vary from other neural networks in how their convolutional and subsampling layers are organised. DCNNs bring us very proficient results when it comes to image classification tasks. Recently, we have understood that generalization is more important when compared to the neural network’s depth for more optimised image classification. Our feature extractors are learned in an unsupervised way, hence the results get more precise after every backpropagation and error correction.
A Modern Approach for Software Cost Estimation using Neural Networks
Authors: AleemBasha Shaik. , P. Singh R 
Published: May 2018

Programming planning estimation and examination especially, cost estimation exercises have been in the point of convergence of thought for a few associations. Maker explores the usage of the ace result declaration and machine learning methods using intelligent framework and moreover focusing COCOMO II method to manage estimate the cost of programming. Few basic techniques in the usage of neural framework in surveying programming cost. Made to great degree exact results, however the genuine incident in their work was a direct result of the way that the precision of the report depended enthusiastically on the degree of the planning set [4]. Getting the hardship in implementing neural frameworks, the maker makes a dynamic neural framework that would at first use COCOMO II. Sorting out upgrades and its results the amount of instructive gathering augmentations with commitment from ace finalizing that effects the studying strategy.
Stimulating electrode Design for Implantable Sub Retina Research Application: A Novel Approach
Authors: Alavanthar T , Ellappan V 
Published: May 2018

This paper aims to study and converse the theoretical model of neural stimulation implant electrodes with the electrochemical aspects of design. The study investigates the practically realizable hypothetical model of minimal invasive retinal implant (miRI) stimulating electrodes for restoring lost sight of patients blinded by degenerative retinal diseases. The basic elemental methods of charge injection by the stimulation electrode to tissue are pointed out. A prologue on the developments of vision implants and electrode characteristics were presented. We communicated the most important factors considered in this design stage of modeling, such as electrode position, size, impedance, charge injection capability, temperature change of the targeted retinal tissue and it’s surrounding for vision implant system. In this design, a mathematical model is created to investigate for the all above said factors which influence implants positioned at internal surface of the retinal tissue. This investigation gives an initial step in design verification before the fabrication.
Parametric Optimization and Control of Heat Exchanger using Linear Quadratic Controller and Dynamic Matrix Controller
Authors: Kesavan E , Divya N , Gowthaman N , Manoharan S 
Published: May 2018

Heat exchanger plays a important role in many unitsas they have the capability to hold different temperarure and pressure range. In this paper the linear quadratic controller and Dynamic matrix controller is implemented for heat exchanger system. The out let temperature of the tube is controlled by monitoring the inlet flow rate by using different controllers. The model of the system has been obtained from experimental data using system identification technique. The LQR and DMC is compared by analyze the servo performance in the system in terms of settling time, overshoot and rise time.
Implementing DMZ in Improving Network Security of Web Testing in STMIK AKBA
Authors: Iskandar Akbar , Virma Elisabet , Saleh Ahmar Ansari 
Published: May 2018

The aims of this research are to design and to implement network security system in internal web testing using DeMilitarized Zone Method and Microtic Router on Siakad server of STMIK AKBA. Data analysis techniques that possible to use is descriptive method. The significances of the study are 1) to avoid the attack of cracker who intend to access the system without permissions and 2) to improve network securityon web testing services on Siakad server of STMIK AKBA. The data are obtained by having literature review and observation. Literature review assists the researchers to collect the theory on DeMilitarised Zone Method and the previous studies which were used as comparison to the recent study. Obervation was carried out directly to the field to observe the running system. Based on the results and discussion, it is shown that the aplication of DeMilitarized Zone Method on microtic can secure the web testing on Siakad server of STMIK AKBA and can maintain the whole series of online services that are available in the server.
Mobile based application for prediction of diabetes mellitus: FHIR Standard
Authors: Sharma Meenakshi , Aggarwal Himanshu 
Published: May 2018

Presently physicians providing clinical decision along clinical guidelines manually on basis of manual query to patients that involve documentation files of lab reports, medication description etc., that make practice sluggish and arduous. With development of mobile based application provide assistance to physician in providing quick decision in appropriate manner as patient data available any-time from any-where that will enhance quality of care in field of healthcare. HL7 standard promotes FHIR(Fast Health Interoperability Resource) standard and health information technology for mobile-health. Mobile health is not a vertical field, but a kind of horizontal field that has cut various impact of healthcare domains. This application provide the effective health management of patient's electronic health record with ease of user friendly interface, that can be accessed on role based authentication by numbers of actors like patient, physician, clinic staff and patient's family etc. Basically this study projected decision support system for prediction of chronic disease-Diabetic- Mellitus using FHIR(Fast Health Interoperability Resource) as standard for interoperability among hospital information system. Application provide physician's structured series of symptoms/signs as uploaded by patients, laboratory and staff. Series of questioner along with outcomes are formed, all outcomes appraised and tested by team of medical domain experts.