bluuebunny/crossref_metadata_2025 huggingface dataset:
Enhanced Security Methods of Door Locking Based Fingerprint
Authors:   Department of Electronics and Communications Engineering, Jawaharlal Nehru Technological University, Anantapur (Andhra Pradesh) India., Alnabhi* Hashem , Al-naamani Yahya ,   Department of Electronics and Communications Engineering, Jawaharlal Nehru Technological University, Anantapur (Andhra Pradesh) India., Al-madhehagi Mohammed ,   Department of Electronics and Communications Engineering, Jawaharlal Nehru Technological University, Anantapur (Andhra Pradesh) India., Alhamzi Mohammed ,   Department of Electronics and Communications Engineering, Jawaharlal Nehru Technological University, Anantapur (Andhra Pradesh) India.
Published: January 2020

This paper presents an enhanced methodology in implementing and designing a security system for door locking purpose based on fingerprint, GSM technology, monitoring camera, alarm system and password system. This security system will provide enough security by limiting unauthorized people access and taking a record of those who pass through it. Sometimes unauthorized people or burglars try to break the door for evil intentions at a time when no one is available at a targeted place, so this paper introduces some security solutions for that problem and they are the main contribution of our paper. We introduce an alarm system to alert the people at the surroundings, GSM module that’s used to send an SMS message to the registered user’s (responsible person) and a web camera that’s used to take a video for a person who tries to break the lock, password keypad that’s used after fingerprint sensing to provide extra security. Definitely the registered users are the only persons who can access the lock, and the door closes after five seconds from the opening time. The method used to implement this experiment involves the use of a fingerprint scanner R305 that’s interfaced with Arduino microcontroller-ATMEGA328P to control the locking and unlocking process of a door. During all the opening and closing processes, the16x2 Liquid Crystal Display (LCD) displays some commands which can be used to instruct the users like, place your finger on the sensor, the door is opened, the door is closed, the message is sent, please enter the password etc. If an unregistered user tries to access the door using their fingerprints, automatically his/her access is denied. The proposed door lock security system is can be used at homes, offices, banks, hospitals, and in other governmental and private sectors. Our proposed system was tested in real-time and has shown competitive results compared to other projects using RFI and password.
Reconstruction of MR Images using Sparse Signal Sequences in Frequency Domain
Authors:   Research scholar, Dept. of CSE, KSSEM, Bengaluru-560109, India., M D* Deepak , P Karthik ,   Professor, Dept. Of ECE, KSSEM, Bengaluru-560109, India., Kumar S Sreedhar ,   Professor, Dep of CSE, Dr. TTIT , KGF, Kolar- 563120, Karnataka, India., H C Ravikumar ,   Assistant Professor, Dept. of ECE, Gousia Engineering college, Ramanagaram, India.
Published: January 2020

A new strategy for signal acquisition has emerged called Compressed Sensing (CS). The compressed sensing has gained attention in the filed of computer science, electrical engineering and mathematics. The Compressed Sensing is a mathematical approach of reconstructing a signal that is acquired from the dimensionally reduced data coefficients/less number of samples i.e. less than the Niquist rate. The data coefficients are high frequency component and low frequency component. The high frequency components are due to the rapid changes in the images (edges) and low frequency correspond provide the coarse scale approximation of the image, i.e. fine continuos surface. The idea is to retain only coarse scale approximation of the image i.e. the significant components that constitute the compressed signal. This compressed signal is the sparse signal which is so helpful during medical scenarios. During the Medical Resonance Imaging (MRI) scans, the patient undergoes many kinds difficulties like uncomfortness, patients are afraid of the scanning devices, h/she cannot be stable or changing his body positions slightly. Due to all these reasons, there can be a chance of acquiring only the less number of samples during the process of MRI scan. Even though the numbers of samples are less than the Nyquist rate, the reconstruction is possible by using the compressed sensing technique. The work has been carried out in the frequency domain to achieve the sparsity. The comparative study is done on percentage of different levels of sparsity of the signal. This can be verified by using Peak Signal Noise Ratio (PSNR), Mean Square Error (MSE) and Structural similarity (SSIM) methods which are calculated between the reference image and the reconstructed image. The finite dimensional signal has a sparsity and compressible representation. This sparsified data can be recovered from small set of linear, non-adaptive measurements. The implementation is done by using MATLAB.
Sentiment Analysis and Summarization of Social Media Content Using Topic Modeling
Authors:   Amity Institute of Information Technology, Amity University Uttar Pradesh, Lucknow Campus, Lucknow (India),, Mishra* Prerna , Rajnish Ranjana ,   Amity Institute of Information Technology, Amity University Uttar Pradesh, Lucknow Campus, Lucknow (India),, Kumar Pankaj ,   Department of Computer Science, Sri Ramswaroop College of Engineering & Technology, Lucknow, India.
Published: January 2020

Explosion of Web 2.0 had made different social media platforms like Facebook, Twitter, Blogs, etc a data hub for the task of Data Mining. Sentiment Analysis or Opinion mining is an automated process of understanding an opinion expressed by customers. By using Data mining techniques, sentiment analysis helps in determining the polarity (Positive, Negative & Neutral) of views expressed by the end user. Nowadays there are terabytes of data available related to any topic then it can be advertising, politics and Survey Companies, etc. CSAT (Customer Satisfaction) is the key factor for this survey companies. In this paper, we used topic modeling by incorporating a LDA algorithm for finding the topics related to social media. We have used datasets of 900 records for analysis. By analysis, we found three important topics from Survey/Response dataset, which are Customers, Agents & Product/Services. Results depict the CSAT score according to Positive, Negative and Neutral response. We used topic modeling which is a statistical modeling technique. Topic modeling is a technique for categorization of text documents into different topics. This approach helps in better summarization of data according to the topic identification and depiction of polarity classification of sentiments expressed.
Influence of High reactive Metakaolin (HRM) on flexural strength of Concrete in combination with self-curing agents
Authors:   Research scholor Savitribai Phule Pune University, Pune, India., Suryawanshi* N. T. , Thakare S. B. ,   Principal, Anantrao Pawar College Of Engineering & Research Pune , India., Jain R. K. ,   Principal, Rajarshi Shahu College of Engineering, Tathawade, Pune , India., Saremi Hamid ,   UG. Student Department of Civil Engineering, Sapienza University, Italy, India.
Published: January 2020

The present study is directed to understand contribution of High reactive Meta kaolin in combination with self-curing agents on flexural strength of concrete of higher strength. Earlier studies revealed that ordinary Portland cement can be replaced by HRM and optimum replacement level is 10 %. It was also observed that compressive was found improved at the same replacement level. This optimum replacement level may get vary and mainly depends on the water cent ratio of mix. This study include experimental program to find out compressive strength of concrete of low water cement ratios varies in between 0.32 to 0.42.Result showed that the water cement ratios, it was found that w/c 0.38 provides compressive strength nearly equals to target mean strength and observed declined for other w/c ratios. The concrete produced of low water cement ratios likely to shrink in early days; this is because of insufficient water for hydration process. This is the reason due to which strength obtained for 0.32, 0.34, and 0.36 is not up to the mark. Hence in this research attempt was made to enhance strength of such low water cement ratios by addition of super absorbent polymers like Poly acrylic acid. No external curing is employed. The poly acrylic acid (PAA) is white granular powder has been tried as self -curing agent. It absorbs water, swells and releases water slowly during hydration process. From the experimentation it was observed that due to the addition of PAA, the compressive as well as flexural Strength of such low water cement is get enhanced and is about 90% of strength of control mix (water cured). Study also proposes relation between avg. flexural strength and w/c for different curing conditions with degree of confidence more than 90 %. Hence research promotes internal curing method for high strength concrete for low water cement ratios.
Novel Distance Metric for Touch less Footprint Based Identification Technique
Authors:   Pursuing Ph.D. Department of Computer Science, Babasaheb Bhimrao Ambedkar University, Lucknow., Gupta* Anshu , Raj Deepa ,   Assistant Professor, Department of Computer Science, Babasaheb Bhimrao Ambedkar University, Lucknow.
Published: January 2020

In this fast-paced technology-driven today's era, biometrics is not the new buzzword in the information security domain. Biometrics uses any physiological or/ and behavioral attribute/s of an individual for personal identification and/or verification. In biometrics, so many traits, like a fingerprint, face, palm, retina, iris, ECG, gait, voice, and signature, etc., have been used from ages to uniquely identify a human being. Biometrics based on Footprints is the latest practice for personal identification. Like fingerprints and palmprints, footprints of individuals carry uniqueness; hence can be used in biometrics for personal recognition. This work investigates the powerfulness of footprints by extracting texture and shape features using Principal Component Analysis (PCA) method based upon Eigenfeet and introduces a new distance metric during the matching phase. Experimental results show that the new distance metric shows better results in comparison to the Euclidean, Manhattan and Mahalanobis distances.
Improved Classification of Brain Tumor in MR Images using RNN Classification Framework
Authors:   Dept of CSE, Karpagam Institute of Technology, India., Kalaiselvi* K. , Karthikeyan C. ,   Dept of CSE, Karpagam Institute of Technology, India., Devi M. Shenbaga ,   Dept of CSE, Karpagam Institute of Technology, India., Kalpana C. ,   Dept of CSE, Karpagam Institute of Technology, India.
Published: January 2020

Classification of brain tumor for medical applications is considered as an important constraint in computer-aided diagnosis (CAD). In this paper, we study the classification of brain tumor by considering the constraint as a classification problem in order to segregate the tumors among pituitary tumors, gliomatumorand meningioma tumor. This method adopts deep learning principle to extract the brain features from the MRI images. In this study, Recurrent Neural Network is used to classify the extracted features from brain. The experiments are carried out in terms of three fold cross-validation process over MRI brain image dataset. The results show that the proposed RNN classifier classifies the brain tumors effectively with 98% of mean classification accuracy than other existing methods.
Diagnosis of Congestive Heart Failure from HRV signal using SVM classifier and Patient Specific cross validation
Authors:   PhD Research Scholar, Razabazar Science College, University of Calcutta, Kolkata, India, Sinha* Nabanita , Mandal Saurav ,   PhD Research Scholar, Razabazar Science College, University of Calcutta, Kolkata, India.
Published: January 2020

Congestive heart failure (CHF) is popularly known fatal cardiac disease that occurs when pumping action of heart is lower than normal case. The purpose of this study is to the accurate diagnosis of CHF by improving classifier performance with effective features extraction and cross validation approach. The identification of significant features in electrocardiogram is highly important to detect congestive heart failure. Therefore ,this paper introduces a classifier based automated detection scheme with a novel approach of feature extraction from Heart rate Variability (HRV) signal for early prediction of CHF. The dynamical characteristics of HRV signal is analysed by computation of Largest Lyapunov Exponent. The statistical features are also evaluated to capture crucial variation in HRV signal to distinguish the abnormal and normal heart condition. The extracted features are subjected to Support Vector machine (SVM) classifier for automated discrimination of CHF from normal ECG signal. Experimental results evaluate the performance of extracted features and estimate the accuracy of the classification using the 10 fold cross validation and patient specific cross validation approach. Our experiment is validated by ECG data of normal and CHF subjects from Physionet database. The proposed system is efficient to the detect CHF with an average accuracy of 98.75%,, sensitivity 98.38%, values and 98.94%. Based on comparative study with the existing scientific research work to diagnose CHF, our proposed approach is found to be reliable and efficient for CHF diagnosis
Estimated Power Tariffmodel of Rayalaseema Thermal Power Plant 2x210 MW
Authors:   Associate Professor, Atria Institute of Technology, India., Sri* Dr. Perini Praveena
Published: January 2020

From times immemorial it is a conversant rudimentary fact that the State Electricity Boards of India were cash strapped with no exception of bifurcated Andhra Pradesh. To avert from such precarious and deteriorating economic situations of widening gap between increasing trend of cost of supply of electricity and meagre power tariffs, the restructuring of Andhra Pradesh State Electricity Board became quite inevitable according to the Electricity Reform Act of 1998 to ensure its commercial viability and efficiency. To usher gainful insights regarding rapid emergence of competitive markets in Thermal Electric Energy Industry, this research paper computes power tariff in Generation segment for Rayalaseema Thermal Power Plant with installed capacity of 2x210 MW both during Pro-Privatization Period and during Privatization Period with strict adherence to Central Electricity Regulation Commission ` (CERC) Guidelines. The estimated price per Kilo Watt Hour of electricity generated during pro privatization and during privatization was Rs.1.29 Paise per Kilowatt Hour and Rs.2.55 Paise per Kilowatt Hour. These calculations were based on the price opinionated and discriminatory techniques of pricing policies in partially monopolistically structure of Thermal Electricity Generation Industry. It comprises of recuperation of twelve-monthly static concerns and fixed expenditures that constitutes Interest on Principal amount rented, downgrading of assets, maneuvering operations and conservation measures of overwhelming expenditures, (eliminating energy feedstock), chargeable rate on income figured , interest on operational wealth at standard norm of production of electrical energy or voltage , productivity and lucrativeness of electric business in relation with equivalence or parity and energy inconstant duties and charges including feedstock fee with recouping for each unit or kilowatt of electric energy multifarious delivered. Value added to this, further estimations were carried out for projected power tariff for the tenure period ranging from 2019-2020 to 2031-2032 using statistical time series trend analysis. During all these future years similar trend is likely to be exhibited with estimated power tariff at Rs. 1.95 Paise per Kilo Watt Hour.
HETRP: High Energy Efficient Trustable Routing Protocol for Wireless Sensor Network
Authors:   Research Scholar, Sri Venkateswara University Gajraula, Uttar Pradesh-India, Vaquar* Musheer , Agarwal Prof.(Dr.) Sanjay Kumar ,   Professor, Dolphin (PG) Institute of Biomedical & Natural Sciences, Dehradun, Uttarakhand-India
Published: January 2020

Wireless sensor network environment based on limited resources technology. Energy is one of the most significant resources in such systems, so ideal utilization of energy is essential. A high energy efficient with trustable routing-protocol for Wireless_Sensor_Networks covered under this_paper. The protocol is trustworthy as far as data conveyance at the Base_Station. We assumed about portability in sensor nodes and in the base station. The proposed protocol depends on the cluster and hierarchical routing protocols. All clusters comprises of unique cluster-head-node and two-deputy-cluster-head-nodes, and several normal sensor-nodes. The cluster-head panel model introduced to optimize the re-clustering time and energy prerequisites. As consider the protocol trustworthiness, it lays finest exertion to guarantee a predetermined level of performance at the base-station. Contingent upon the network topology, transmit data from cluster head node to base station that done either by direct or indirect i.e. multi-hop way. Also, substitute ways are utilized for data transmission between a cluster head node and the base station. Thorough NS2 simulation-results delineate energy-efficiency, throughput, and delayed-lifetime of sensor-nodes affected by the proposed-protocol.
Challenge Faced in K-Means Clustering for the Choice of Automatic K-Value for Segmentation of Black Sigatoka Disease in Banana Leaves
Authors:   PG & Research, Department of Computer Science, Chikkanna Government Arts college, Tirupur (Tamil Nadu) India., Devi S.* Srivalli , Geetha Dr. A. ,   PG & Research, Department of Computer Science, Chikkanna Government Arts college, Tirupur (Tamil Nadu) India.
Published: January 2020

Clustering is defined as grouping similar items . The three types of machine learning techniques are supervised, unsupervised and semi-supervised. In unsupervised technique, there are no class labels given to the input data. Clustering is a type of unsupervised learning technique. Recently clustering is applied in many fields such as medicine, agriculture, biology, computers, finance and robotics. Black sigatoka is a bacterial disease occurring commonly in banana plants .The research currently focuses on segmenting the disease area from non-diseased area.The segmentation class training is done via Trainable Weka Segmentation and we also do segmentation using k-means algorithm. In this paper we propose a novel approach for extraction of the black sigatoka diseased area on banana leaves from images using pixel color values and grouping them into their respective clusters accordingly. This is a segmentation cum clustering algorithm. The novel approach has been proposed to overcome the shortfall of k-means clustering when segmenting using automatic value selection for k-means by using silhouette values.Using this novel approach its easy to cluster and segment at the same time. The segmented image from this algorithm can be used in disease classification tasks.
Pollution Free Operation of Rail Vehicle with Diesel Engine using Fuel Cell
Authors:   Sr. Member IEEE, Member IEI, Head of Centre for Transportation & System Design, Bharat Heavy Electricals Limited Bhopal 462022, MP, India, Jafri* Naseam H. , Gupta Dr. Sushma ,   Professor, Department of Electrical Engineering Maulana Azad National Institute of Technology, Bhopal 462003, MP India.
Published: January 2020

Presently, energy used in rail transportation is fossil in nature, in case of electric vehicle, electricity which is generated mostly from coal/gas while in diesel engine driven vehicle oil /gas. Fossil energy sources inherently suffers from disadvantages such as limited in nature, damage to environment due to exhaust of greenhouse gases, noise pollution etc. Fuel cell not only overcome above demerits of diesel engine but offer other advantages such as energy recovery during braking, better dynamic response. A feasibility study of use fuel cell in place of diesel engine is presented in this paper. It briefly discuss fuel cell operation, its suitability for transient energy requirement of transportation application, necessity of energy storage system, simulation of potential of recovery of energy during braking. Present status of technology of drives, power conditioning is reviewed and a circuit topology for conversion of existing diesel engine based vehicle into fuel cell system is presented. Advantages of fuel cell hybrid electric vehicle (FCHEV) over conventional transportation vehicle is also discussed.
Harmonic Elimination of a PV Based Cascaded H-bridge Seven Level Inverter for Induction Motor Drive
Authors:   UIET, PU, Chandigarh, India, Gaur* Parul , Verma Yajvender Pal ,   UIET, PU, Chandigarh, India., Singh Preeti ,   UIET, PU, Chandigarh, India.
Published: January 2020

In today’s era, reliable and good quality power is an essential requirement in industry, which can be supplied by inverters at medium and high power. Most of the appliances in the industry require high power or medium power for their operation. Power electronics devices such as inverters work on medium voltage and high power and are suitable for industrial applications and renewable particularly Photovoltaic (PV) integration. Multilevel inverters are more superior to conventional inverters because of lower harmonics and switching losses, but as the number of levels increases, complexity also increases. Therefore, maintaining the harmonics at lower level and lesser complexity of multilevel inverters is a challenge for researchers. In this research paper, a novel approach for implementation of seven level cascaded H- bridge configuration of multilevel inverter using direct current source and photovoltaic panels has been demonstrated. The basic working principle of seven level cascaded hybrid bridge inverter, pulse width modulation techniques and total harmonic distortion are explained through simulations in Matlab and Xilinx 14.3 software and the same is experimentally validated through FPGA controller based Spartan 6. The designed seven level inverter results in lower total harmonic distortion with lesser complexity when used to connect PV panels.
Security Constrained Optimal Power Flow Problem Solution with Practical Constraints using HALOA
Authors:   Department of Electrical and Electronics, Chaitanya Bharathi Institute of Technology, Hyderabad, India., Balasubbareddy* M.
Published: January 2020

To solve the OPF problems with three objective functions like fuel cost minimization, emission and power loss. The proposed algorithm is hybridizing conventional Anti Lion optimization algorithm with Genetic algorithm. The considered objectives are solved by considering the equality and in-equality constraints along with practical constraints. The effectiveness of the proposed method is tested on the IEEE 30 bus test system and compared with existing literature. The proposed method gives the best optimal values for the minimizing the considered objectives.
Detecting Malicious Facebook Applications using LSTM Algorithm
Authors:   M.Tech in the Department of Computer Engineering at Government College of Engineering, Pune, Maharashtra, Choudhari* Mrs.Ayesha , Sharma Saurabh ,   Database Architect, Nagarro, Gurugram, India., Mane Dr.Sunil B. ,   Associate Professor in the Department of Computer Engineering and Information Technology at Government College of Engineering Pune (An Autonomous Institute of Govt. of Maharashtra), India.
Published: January 2020

With twenty million introduces a day [1], outsider applications area unit a big purpose behind the acknowledgment and addictiveness of Facebook. Tragically, programmers have finished the aptitude of exploitation applications for spreading malware and spam. the problem is as of currently important, as we discover that a minimum of thirteen you look after applications in our dataset sq. estimates malignant. Up hitherto, the examination network has fixated on police examination vindictive posts and battles. we tend to tend to point out the issue: Given a Facebook application, can we tend to tend to affirm if it's vindictive? Our key commitment is in making LSTM—Facebook's Rigorous Application Evaluator—ostensibly the essential instrument fixated on police examination malevolent applications on Facebook. to make LSTM, we tend to tend to utilize info assembled by perceptive the posting conduct of 111K Facebook applications seen crosswise over 2.2 million purchasers on Facebook. to start with, we tend to tend to come to a decision plenty of decisions that encourage North yankee nation to acknowledge harmful applications from kind ones. for instance, we discover that vindictive applications normally share names with elective applications, which they for the foremost half demand less authorizations than amiable applications. Second, contributory these recognizing decisions, we tend to show that LSTM can find malignant applications with ninety nine .5% exactness, with no imitative positives and a high obvious positive rate (95.9%). At long last, we tend to tend to research arrange of harmful Facebook applications and distinguish parts that these applications use to unfold. Curiously, we discover that few applications get together and bolster every other; in our dataset, we discover 1584 applications endorsing the being engendering of 3723 choice applications through their posts. Long haul, we tend to tend to examine LSTM as a stage toward creating Associate in Nursing freelance working dog for application appraisal and positioning, during this manner on caution Facebook purchasers before putting in applications.
Enviromental Impact of Municipal Solid Waste Landfill in North of Iraq
Authors:   Professor, Civil Engineering Department/ Near East University/ North Cyprus, Nicosia, Via Mersin 10, Turkey,, Gökҫekuş* Huseyin , Kassem Youssef ,   Assist. Professor, Civil Engineering Department/ Near East University/ North Cyprus, Nicosia, Via Mersin 10, Turkey,, Musa Muhammad Kh. ,   Ph.D. Students, Civil Engineering Department/ Near East University/ North Cyprus, Nicosia, Via Mersin 10, Turkey
Published: January 2020

solid wastage yielding in a landfill badly influenced the encompassing condition and people habitat nearer to landfill destinations. Landfill is the most established and the most widely recognized type of evacuation and transfer of waste, comprising the last discarding technique for solid waste in the city. It is outstanding that the effect of MSW landfills leads to contamination of every single natural segment. The negative natural effect of landfills diminished by employing preservation advancements and proper sold waste administration techniques. The nowadays investigation attempted observing of the city wastage landfill effect on the circumference. The spatial attributes of the region affected by the waste dumping and the conceivable effect of leachate utilizing phytotoxicity tests were done. The landfill is built, with base liner and leachate and landfill gas gathering and remedy and curing framework. The transition of leachate and gas from the corpus of landfill into the encompassing condition present a genuine natural concern, which mingle to groundwater squalor, air contamination with sway on atmosphere through methane outflow and potential wellbeing risks. This paper shows an influenced of solid waste land fill in environment. Populaces, particularly those living nearer to the landfill area contamination sources are in danger of both short and long haul impacts of natural, physical and chemical contaminants, including water and food borne sicknesses, substantial metals poisonings and other possibly dangerous components and mixes present noticeable all around, water, soil, particularly in north of Iraq. By and large, there is absence of vital strategies, guidelines and rules in all divisions and at all levels in connection to sheltered and ecological neighborly tasks in agribusiness, industry, vitality, and open administrations.
Image De-Blurring Based on Constraint Conditional Model
Authors:   Research scholar, Dept. of ECE, KSSEM, Bengaluru-560109, & Asst. Prof., Dept.of ECE, Ghousia College of Engg, Ramanagaram , India., H C* Ravikumar , Karthik P ,   Professor, Dept. of ECE, KSSEM, Bengaluru-560109, India.
Published: January 2020

Image capturing is more vulnerable to the various physical limitations such as defocus, low lighting and camera shaking; this makes the image blurry and noisy. Moreover De-blurring is the process to recover the original image from the given degraded image. De-blurring technique uses the estimated blur kernel for achieving the optimal restored image with the sharp features, however the accuracy has been one of the major concern , hence in this paper we use Constrained Conditional model (CCM) for restoring the image. Moreover, here two different methods are integrated i.e. conditional model and convergence operator, these two combined learns the model and efficiently and provides the better results. In order to evaluate the proposed model, Levin dataset is used by considering the two eminent model metric i.e. PSNR and SSIM and CCM based model outperforms the other state-of-art technique.
Energy Efficient Target Tracking Method for Multi-Sensory scheduling in Wireless Sensor Networks
Authors:   Research scholar , Dept of Electronics and communication engineering, AMC engineering college, Bangalore, India., Lokesh* Deepika , Reddy Dr N V Uma ,   Professor and Head, Dept. Electronics and communication Engineering , AMC engineering college, Bangalore, India.
Published: January 2020

Data collection utilizing wireless sensors networks (WSNs) has been utilized for surveillance, monitoring environment, animal etc. Target tracking of maneuvering objects is an essential need of modern life. Nonetheless, because of diverse nature of sensor and complex environment, sensors measurement errors need to be minimized considering diverse motion states in process of tracking (sensing) operation. Enhancing network lifetime (i.e., reducing energy dissipation of sensor nodes) and improving tracking quality are major concern of target tracking using WSN. Form improving network energy efficiency, multi-sensory target tracking method has been modelled using Kalman Filter (KF) by existing target tracking method. The KF based model are affected due to presence of noise or missing data. For overcoming research issues this paper present an H-infinity filter (HF) to evaluate fusion for maneuvering target tracking in WSN. Further, to minimize the estimation errors and reduces/controlling the effects of outliers fuzzy H-infinity (FHF) filter for target tracking WSN is presented. Experiment outcome shows proposed HF and FHF fusion model attain better performance than existing KF based method for clustered based WSN in terms of positional and velocity root mean square error and energy dissipation.
Detection and Measure Carstensz Glacier Area Changes Using Machine Learning Technique
Authors:   Student, Computer Science Department, Bina Nusantara University, Jakarta, Indonesia., Suwandi* Rizaldi , Isa Sani Muhamad ,   Lecturer and Researcher, Computer Science Department, Bina Nusantara University, Jakarta, Indonesia.
Published: January 2020

Using satellite data for acquiring glacier outlines has become more popular in the last decade. Glacier change assessment is the main goal for deriving glacier outlines. It's important to make the best method to generate the glacier outline as there most of the glacier outline is made with manual delineation and spectral thresholding. This research used a machine learning model to deriving the glacier pixels from satellite data. The model trained using more than 80 thousand of a glacier and non-glacier pixels. The model that trained has been proved to able classified a glacier pixel with more than 99% accuracy in one of the best experiments. The NDSI (Normalized Difference Snow Index) proved to be the key feature to classifying glaciers and shown to be one the best combination with NDSI + GLCM + TIFF (Band 4). This model hopefully can be further expanded and installed directly in satellite so we can instantly make a glacier outline without any manual delineation or spectral thresholding needed.
Fault Classification Accuracy Measurement for a Distribution System with Artificial Neural Network without using Signal Processing Technique
Authors:   Dept of Electrical Engg, Government College of Engineering, Chandrapur, Gondwana University, Gadchiroli,M.S.,India., Khond* S. V. , Dhomane G.A. ,   Dept of Electrical Engg, Government College of Engineering,, Amravati, M.S.,India.
Published: January 2020

Faults occurring on electrical distribution network are unpredictable and needs to be cleared at the earliest so as to reduce power outage time. Hence fault detection and their classification plays important role. In this research paper the fault classification accuracy was measured for an electrical power distribution network with artificial neural network without using any signal processing method. Although many digital signal processing methods are developed to enhance electrical fault classification accuracy, it is essential to measure it for comparison when no signal processing method is used. Fault classification was considered as a pattern recognition application of neural networks. Two layer feed forward back propagation neural network was used as classifier. IEEE 13 bus distribution feeder was simulated in MATLAB with Simulink for collecting the input data. The simulation results show that the faults can be classified satisfactorily. L-G, L-L and L-L-L faults were simulated for measuring the accuracy of fault classification.
Heuristic Computational Matrix Method for Marathi Grammar Checker
Authors:   Department of Computer Engineering, Vishwakarma Institute of Information Technology, Pune, India., Bhirud* Nivedita S. , Bhavsar R.P. ,   School of Computer Sciences, Kavayitri Bahinabai Chaudhari North Maharashtra University, Jalgaon, India., Pawar B.V. ,   School of Computer Sciences, Kavayitri Bahinabai Chaudhari North Maharashtra University, Jalgaon, India.
Published: January 2020

Spelling, morphology, syntax and semantics are the important areas of Natural Language (NL) sentence analysis. Syntax checking of a sentence is broadly referred as a ‘grammar checking’, however it also involves morphological analysis hence technically it is a multidimensional problem. Syntax of a natural language defines permissible sentence structures and constraints on constituents such as their order and unification constraints. It is a purely theoretical aspect and considered as computationally trivial rule enforcement problem. Rule formulation needs expert labour work and is costly and time consuming affair. Modern data driven language engineering approach advocates use of minimal knowledge base (linguistic information) and relies on knowledge extraction from tagged data. It is difficult to find such tagged data for non-English natural languages like Marathi (Indian Language). Considering these facts for grammar checking problem, we have come up with intuitional heuristic method for Marathi grammar checking which uses basic syntactic cues and minimal lexical information. We have modeled this heuristic method scientifically using basic matrix comparison operation. Our approach relies on syntactic cues like word ending, verb ending. We have tested our method on handcrafted Marathi sentences catering different Marathi sentence structures (one hundred and fifty three). The performance is measured using precision and recall metrics. The system has yielded 83% precision and 93% recall on sample data. This approach can be exploited for well structured text documents typically in the closed domains like legal, official, educational etc.
Design of Enhanced Dynamic Resource Allocation Framework for Heterogeneous Cloud Environment
Authors:   Associate Professor, PG & Research Department of Computer Science, Bishop Heber College, Trichy. Affiliated to Bharathidasan University,Trichy, Jayasimman L. , Dhanalakshmi* V.Geetha ,   Research Scholar, PG & Research Department of Computer Science, Bishop Heber College, Trichy. Affiliated to Bharathidasan University, Trichy.
Published: January 2020

Cloud is a heterogeneous environment which is used to provide computing infrastructure as a service to the users. Cloud services are delivered to the users based on the demand received from the cloud service users. The best quality of a business model is to satisfy the product demand on time. Cloud is a business model to enable computing infrastructure everywhere. The cloud resources are scheduled and allocated to the users based on the requirement. Resource allocation in cloud computing environment is suffered by lack of improper monitoring, measurement and on time delivery of resources. This may affect the business growth of cloud service providers. This paper proposes an enhanced dynamic resource allocation framework to allocate resources based on the demands as well as cost of the resources to the users. The demand is forecasted based on the previous request repository. Fastcaster analyzes previous demands on different time and predicts future demands. Resources are prepared and to be in a ready state for allocation. The paper also describes the procedure of the proposed dynamic resource allocation technique for efficient allocation of resources in the cloud. The main focus of this framework is to schedule and allocate the resources which are in demand by the users on time also considered cost of the resources. Framework initiates a new paradigm of a single point of service delivery for all cloud services.
A New Cryptographic Scheme Involving Finite State Machine and Recurrence Matrix
Authors:   Phd, Computer Science and Engineering from Sarvepalli Radhakrishnan University, Bhopal, (MP) India., Mittal* Mr.Ayush
Published: January 2020

The object of this paper is to develop a new cryptographic scheme involving finite state machine and Mersenne's recurrence matrix. The proposed algorithm is more secure cryptographic algorithm that solves many problems which are facing now days. For secure communication the designed encryption scheme involving finite state machine and recurrence matrix maintained the secrecy of the message.
Improvement of Information Technology Career Path by using Apriori and Ontology on Mobile Application
Authors:   Assistant Professor in Information Technology Department, Faculty of Science and Technology, Suan Sunandha Rajabhat University, Thailand., Nuameesri* Sumitra , Poomhiran Lap ,   Ph.D. student in Information Technology, Faculty of Information Technology Department, King Mongkut’s University of Technology North Bangkok, Thailand.
Published: January 2020

In Thailand, the joblessness rate is continually expanding for new graduates. But information technology careers are nevertheless popular in business in this digital age. Finding a way to support students to know the career direction that is suitable for them and is ready before going out for a job is therefore very valuable. However, most students do not know which occupation is best for them and are concern about the need to educate themselves and build up information that is suitable for their current career. This paper presents the Thai mobile application for predicting a student's career based on subject results and guidance of training courses for information technology career path using the Apriori algorithm and ontology technique with the longest matching approach in the process of Thai word segmentation. The developed mobile application was tested in black box by experts and evaluated the satisfaction by users. The result shows that the developed mobile application was the highest effective with the high consensus for the evaluation of user satisfaction.
Optimization of Effective Parameters During Electric Discharge Machining of Incoloy 800
Authors:   Mechanical Department, National Institute of Technical Teachers training (NITTTR) Sector 26, Chandigarh, India., Kumar* Nishant , Rao P Sudhakar ,   Mechanical Department, National Institute of Technical Teachers training (NITTTR) Sector 26, Chandigarh, India.
Published: January 2020

Experimental work is totally focused on the inclusive work material Incoloy 800 because of its low cost and effective thermal properties The aim of this proposed work is to find out the optimum condition using RSM technique under the influence of effective parameters which includes MRR, TWR, Surface Roughness so that process parameters such as pulse on time, current, voltage can be optimized while working with Incoloy 800 as a work material. Incoloy 800 has inevitable properties in heat application and machining because of its nickel, chromium and iron content. It also comes under the category of super alloy having various important application in aerospace industries. Chromium present in the alloy helps in heat resistance. Internal oxidation during machining is resisted by iron present in the alloy. The nickel content present in Incoloy 800 maintains ductile and austenitic structure. Therefore, alloy 800 can be machined easily as per desired shape. Because of its moderate strength, low cost and good resistance to oxidation and carburization at elevated temperatures, alloy 800 and its grades are center of attraction for alloy manufacturing companies.
Feature Based Identification of Web Page Noise through K-Means Clustering
Authors:   School of Computer Sciences, Kavayitri Bahinabai Chaudhari North Maharashtra University, Jalgaon, India., Bhamare* S. S. , Pawar B. V. ,   School of Computer Sciences, Kavayitri Bahinabai Chaudhari North Maharashtra University, Jalgaon, India.
Published: January 2020

Web pages has pieces of information which are of unequal importance like navigational bar, copyright notice, links, advertisement etc. and these are considered as noise or insignificant items of web page for web mining. Web page informative content is only useful for performing effective web mining task and presence of noise on web page can hamper the result of this task. Web page has several features including information location, occupied area and its contents. Content data in different portions of an internet web page has dissimilar significance weights according to its location, occupied location and content that are considered to be features of the web page. The position of contents and importance of contents play a vital role in identification of noise in web pages for removal. In this paper web page feature based method is proposed for identification of noise from web pages. K-means clustering technique is applied to classify main content information and noise content information into two clusters of web pages based on these features. For performance evaluation of clustering method, accuracy, precision, f-measure, and recall are calculated.
Genomic Scoring Detection in Carcinoma to Mast Cells by using Hybrid Algorithms of Data Mining
Authors:   Assistant Professor, Pg and Research Department Of Computer Science and Applications, Vivekanandha College Of Arts And Sciences For Women (Autonomous), Tiruchengode, Tamil Nadu, India., Muruganandam* S. , Subbaiah Dr. S. ,   Assistant Professor,Sri Krishna Arts and Science College, Coimbatore, Tamil Nadu, India.
Published: January 2020

It concentrated on assessing the discovery of lung disease in patients with Data mining methods. The mining is a learning revelation to burrow the tremendous measure of information into the required signatures. It changes over the crude information into a reasonable format.A classification of the information dependent on the required viewpoints from the concealed revelation is a basic work on Data mining. It starts the half and half technique contains Correlated Feature Selection, Random subset which aides of pre-preparing, Classification (SRF, MP and AR, WIHW), Zero R, Clustering (Hierarchical), 10 cross Validation (PCA), and Visualization by applying the preparation informational collection. Subsequently, pre-processing used to expel the deformity framework which gives the consistency of the information by utilizing the information mining methods. What's more, it analyzes the uprightness of information with change on the covariance framework separately. Particularly in the arbitrary subset used to uncover the preparation information to progress on the irritation distinguishing framework. It proceeds onward to isolate the information before done at this point to the bunching which controls the mean blunder identification on the given framework. Zero R predicts the imperfection framework specifically organ degenerative of the human body. It orders the information handling due to applying the CFS techniques. It gives the best precise outcome while connected the 10 cross-approvals to envision the deformity framework which gets to the AIS (Artificial Immune System). At last, it found the probability and best result for recognizing the lung malignant growth and the different portrayals precisely.
Design and Development of Rukma Vimana Nozzle
Authors:   Assistant professor, Mechanical Engineering, Institute of aeronautical Engineering college, Hyderabad, India., Reddy M. Prashanth , Prasad Prof. V V S H ,   Professor , Mechanical Engineering, Institute of aeronautical Engineering college, Hyderabad, India., Rao* Dr.G.V.R.Seshagiri ,   Professor , Mechanical Engineering, Institute of aeronautical Engineering college, Hyderabad, India., Kumar C.Labesh ,   Assistant professor, Mechanical Engineering, Institute of aeronautical Engineering college, Hyderabad, India
Published: January 2020

Rukma vimana is a part extraction from vimana Shastra. This project deals with nozzle system of ancient rukma vimana for vertical take-off systems. Nozzle design is very important to provide the necessary lift to the vimana. In the vimana Shastra a provision has been identified to create external heat supply to the streamed flow system in nozzle. In the present work external heat is applied to the nozzle section and to estimate the coefficient of lift. An attempt is being made to create CAD modelling and perform ANSYS fluent analysis to validate theoretical correlations. Keywords: Bumper, dynamic and modal analysis,
Retention of Nurses in Medium Size Health Care Units -Role of Work Life Balance, Compensation and Work Environment
Authors:   Department of Management Studies, School of Management Studies, Sathyabama Institute of Science and Technolgy,Chennai, India., S* Umamaheswari , S Radhika ,   Department of Electrical and Electronics Engineering, School of Electrical and Electronics, Sathyabama Institute of Science and Technolgy,Chennai, India., A Chandrasekar ,   Department of CSE, St.Joseph’s College of Engineering,Chennai,India.
Published: January 2020

This paper evaluates the impact of compensation, work life balance and work environment towards organization commitment of nurses who belong to less attended medium size health care units in and around Chennai City in India. It also deals with the impact of organization commitment towards retention of nurses. From the findings it is evident that the commitment of nurses in the hospital increases their likelihood of continuation. Also it reveals that compensation is the predominant factor followed by work life balance and work environment in enhancing organization commitment.