bluuebunny/crossref_metadata_2025 huggingface dataset:
An Efficient Brain Tumor Classification Based on SOBS Method for MRI Brain Images
Authors:   Principal, Sadakathullah Appa College, Tirunelveli,India., Sathik Dr. M. Mohamed , gnanaselvi E. Synthiya judith ,   Research Scholar, Bharathiar University, Coimbatore, India
Published: November 2019

In the field of medical imaging, the segmentation and classification of brain tumors is a complex and important area of studies because it is essential for the intention of early tumor diagnosing and treatment of brain tumors and other neurologic complaints. Earlier segmentation methods require huge number of iterations, longer time and a reduced accuracy. Therefore, this article proposes a multi-stage strategy whereby tumor segmentation and classification can be accurately performed with lower error rate. The proposed system incorporates three phases such as prediction, segmentation along with morphological operations to solve the discontinuities. The proposed segmentation method is named as Self Organisation Based Segmentation (SOBS) method. It is compared with some of the deformable models in literature. Next Use the Gray Level Co-occurrence Matrix to extract features. Finally Use the Gray Level Co-occurrence Matrix to extract features and classify them into normal or abnormal. If it is classified as abnormal, then again classify into glioma or meningioma. The performance metrics such as accuracy, PSNR and MSE are used for scrutinize the performance of these methods. From the investigational outcomes, the classification accuracy was found to be very high using the proposed segmentation method SOBS with the Random Forest (RF) Classifier.
A Method for Calculating The Values of Forces Acting on The Roller-cone Bit Teeth
Authors:   Tyumen Industrial University, Institute of service management and industry, Tyumen, Russia., Pyalchenkov Dmitry Vladimirovich , Pyalchenkov Vladimir Alekseevich ,   Tyumen Industrial University, Transportation Institute, Tyumen, Russia., Dolgushin Vladimir Veniaminovich ,   Tyumen Industrial University, Institute of industrial technology and engineering, Tyumen, Russia., Kulyabin Gennadiy Andreevich ,   Tyumen Industrial University, Institute of geology and oil and gas production, Tyumen, Russia.
Published: November 2019

The results of an analytical study of the loading of elements of a roller-cone bit cutting structure are given. For an analytical assessment of the magnitude of the forces acting on the bit teeth, the bit is fixed in a static state in a string of drill pipes or a drill assembly, with each roller cone resting on a flat bottom with one tooth on which axial force acts from the bottom. For the disclosure of static indefinability, the equations of deformation of the system are compiled. Calculation of the loads acting on the cone rows was carried out in relation to the cutting structure layout for the Sh215,9K-PV bit cones. To determine the values of the forces acting on the teeth, the dependencies between the magnitude of the load acting on the roller cone and the vertical movement of this tooth, previously obtained analytically and experimentally, were used. It is established that the maximum load acts on the rows located in the middle part of the bit radius. The calculation results are confirmed experimentally. The results obtained can be used to optimize the design of the cutting structures and supports of roller-cone bits at the design stage.
Water Efficiency Management Strategies in Electric Engineering Generation Industries: an Epilogue
Authors:   Associate Professor, Atria Institute of Technology, India, Sri Dr. Perini Praveena
Published: November 2019

The impending jeopardies relating to dearth of water in performing the techno economic activity of production of electricity in power industries ushered gainful insights for this research paper for pursuing to reckon and quantify the renewable electric energy consumption of water by gauging at the foot prints. This research paper presses the need of the hour to persistently stimulate the electric generation industries to integrate the multidimensional anomalies of seasonal changes of monsoonal fresh water in the arena of Environmental micro and macro climate strategies. Taking cue of electric energy water sequential linkages using water foot printing technology this paper empirically estimated that, minimum water foot print was recorded in selected biomass and natural gas based electricity producing industries to yield 1000 kilowatt of electricity vis-à-vis selected Hydel power station, which has voracious appetite. This research has been performed with a field level investigation of assessing the magnitude of water scarcity by performing a documentation of exemplary investigative case study approach in selected regions of Andhra Pradesh.
The Data Mining Support Vector Machine Algorithm used for Detecting and Forecasting of Crimes
Authors:   Assistant Professor in the Department of IT, Vijaya Institute of Technology for Women, Enikepadu, AP, India., Bhavani Y. V. K. D.
Published: November 2019

Crime rate is expanding extremely more because of destitution and joblessness. With the current crime investigation techniques, officers need to invest a great deal of energy just as labor to recognize suspects and criminals. Anyway crime investigation procedure should be quicker and dynamic. As huge amount of data is gathered during crime investigation, data mining is a methodology which can be valuable in this viewpoint. Data mining is a procedure that concentrates valuable data from enormous amount of crime data with the goal that potential suspects of the crime can be recognized productively. Quantities of data mining techniques are accessible. Utilization of specific data mining system has more prominent impact on the outcomes acquired. So the exhibition of three data mining techniques will be analyzed against test crime and criminal database and best performing algorithm will be utilized against test crime and criminal database to recognize potential suspects of the crime. Data mining is a procedure of separating information from colossal amount of data put away in databases, data stockrooms and data archives. Clustering is the way toward consolidating data objects into gatherings. Here taken the Crime dataset from Chicago police website and implemented in MATLAB utilizing Support Vector Machine algorithm.
Design of a Robust Controller by LQG/LTR Formalism for Francis hydro Turbine Driving a Synchronous Generator
Authors:   department of Industrial Robotic, Faculty of Industrial Engineering, University of Douala, Douala, Cameroon., Aurelien* Yeremou Tamtsia , Léandre Nneme Nneme ,   department of electrical engineering, Higher Technical Teacher Training College, University of Douala, Douala, Cameroon., Hervé Samba Aimé ,   department of Industrial Robotic, Faculty of Industrial Engineering, University of Douala, Douala, Cameroon.
Published: November 2019

This paper presents the design and application of a robust controller by Linear-Quadratic-Gaussian method with Loop-Transfer-Recovery (LQG \LTR) at the same time to carefully attain performance and robustness objectives. To improve Stability, the robust controller has been shown to provide good performance in normal operations conditions. Objectives cannot be suitable unless the controller can perpetuate such quality in the presence of plant uncertainties or any working conditions in the hydroelectric power plants. The approach is based to synthesizing a robust controller minimizing a quadratic criterion (controller LQG) while using the Loop Transfer Recovery (LTR), to restore robustness properties of the Estimator. In this study, we applied this robust control law on the model of a Francis hydro turbine. Computer simulations are carried out to establish a n d compare the performance and robustness of using the Infinite horizon control ( H ), internal model control (IMC), Proportional Integral Derived (PID) and LQG/LTR controllers.
Intelligent Air Pollution Prediction System using Internet of Things (Iot)
Authors:   Research Scholar, Department of Computer Science, GITAM (Deemed to be University), Visakhapatnam, Andhra Pradesh, India*, BHARATHI * R. UDAYA , SESHASHAYEE Dr. M. ,   Assistant Professor, Department of Computer Science, GITAM (Deemed to be University), Visakhapatnam, Andhra Pradesh, India
Published: November 2019

The internet of Things (IoT) is a path of action interconnected computes multiple procedures, mechanical along with sophisticated machines, things, and individuals to facilitate be certain remarkable identifiers and the ability of trade data over a framework lacking foreseeing human to human and human to machine correspondence, in these paper, an Internet of Things base framework is proposed, in favor of observing natural air contamination and forecast. This framework is able to exist used for observing air contaminations of specific zone and toward Air Quality examination just as gauging the air quality. We Proposed new framework resolve concentrate scheduled the observing of air contaminations, using the blend of IoT with Artificial Intelligence called Artificial Neural Network, and additional explicitly Long Short Term Memory (LSTM). The point in this paper is to discover the best expectation and prediction model for rise or fall of the specific air poisons like O3, NO2, SO2, and CO which are altogether viewed as destructive as indicated by WHO guidelines.
Automated Gesture Based Wireless Wheelchair Control by Means of Accelerometer
Authors:   Assistant professor, Dr. LankapallyBullayya Engineering College (for Women), Visakhapatnam, India,, Sridevi V. , Ishwarya P. ,   Assistant professor, Dr. LankapallyBullayya Engineering College (for Women), Visakhapatnam, India,, Chandra P.Surya ,   GITAM Institute of Technology, GITAM (Deemed to be University), Visakhapatnam, India, Kumar N. Suresh ,   Gandhi Institute of Technology, GITAM (Deemed to be University), Visakhapatnam, India
Published: November 2019

According to a research there are about 6 million populations in the world who are paralysed and needs a wheelchair for their mobility. Earlier the wheel chairs had to be moved and be externally supported by any person. To help overcome this “joystick-controlled wheelchairs” are developed. But in regular use, these joystick-controlled wheelchairs became difficult to use. Especially in the case of paralysed people, the use of joystick became more difficult due to the hard buttons and unidirectional use of the joysticks. To overcome these problems, we’ve tried to develop a “gesture-controlled wheelchair” which can be moved with a slight tilt of the hand. This can be used in both hands and can be controlled to come to the user from a distance. The current work is implemented with Arduino based devices such as Arsuino NANO and UNO processors and programmed through Arduino IDE.
A Fuzzy Logic Control Method for MPPT to Improve Solar System Efficiency
Authors:   Lecturer, Department of Electrical Engineering, Sanjay Bhokare Group of Institute Miraj, Maharashtra, India, Sutar Anurag A. , Butale M.C. ,   Assistance Professor, Dept. of Electrical Engineering Padmabhooshan Vasantraodada Patil Institute of Technology, Budhagaon, Maharashtra, India.
Published: November 2019

Solar energy is act clean as well as renewable source of energy. Hence the use of PV systems has used in many applications. Big-spread use has resulted in decreased solar panel production expenses. But the low effectiveness of a solar panel owing to variables such as solar insulation, clouds and shading impact continues one of the greatest issues. Due to variable concentrations of isolation, the panel output remains variable during cloudy weather. To increase the solar panel's efficiency, the maximum algorithm for power point tracking needed as it was discovered only a small percentage of the energy incident is transformed into electricity. DC-DC Converter (Boost Converter) design helps to increase the panel output, thereby improving effectiveness and output voltage using reasonable control technique. This article discusses the development of the fluctuating MPPT logic control to track the maximum output point and also to compensate for fluctuating power during cloudy weather. The suggested primary circuit block diagram. The simulation study is carried out and the proposed circuit is implemented by hardware. MATLAB Simulink is used for simulating the circuit.
Modified Gabor Wavelet Transform in Prediction of Cancerous Genes
Authors:   Electronics and Telecommunication Engineering, KIIT University, Bhubaneswar, India., Das Lopamudra , Kumar Anand ,   Electronics and Telecommunication Engineering, KIIT University, Bhubaneswar, India., Das J. K. ,   Electronics and Telecommunication Engineering, KIIT University, Bhubaneswar, India., Nanda* Sarita ,   Electronics and Telecommunication Engineering, KIIT University, Bhubaneswar, India.
Published: November 2019

Cancer is the leading cause of mortality all over the world which in general is the result of some kind of mutation in the genetic sequence. With recent advancements in Digital Signal Processing(DSP) techniques, it has become possible to classify cancerous gene sequences without carrying out extensive biological experiments. In this paper, the Geometric mapping technique along with Modified Gabor wavelet transform (MGWT) has been incorporated to segregate cancerous and non-cancerous gene sequences. This Gabor wavelet based transform technique used in the present research work benefits from the fact that it is independent of the window length which in conjunction with Geometric mapping is used to obtain the spectral components present in the signal accurately and with reduced complexity. This technique has been applied on numerous benchmark datasets and the results obtained prove the performance of the proposed method.
Statistics based evaluation of English Multi-Word Expressions
Authors:   Department of Computer Science, University of Delhi, Delhi, India,, Joon Rakhi , Singhal Archana ,   Department of Computer Science, IP College for Women, University of Delhi, Delhi, India.
Published: November 2019

The linguistic and statistical information extraction is an important aspect of text processing. The extraction of Multi Word Expression (MWEs) plays a key role in text processing as these are used to find correct meaning of a text phrase. MWEs are the lexical phrases consisting of two or more words conveying some different meaning together other than its constituent words. The linguistics in MWEs extraction is mainly related to the text information including the Part of Speech (POS) tags, grammar rules, related literature, and so on. It is important to extract the correct MWEs for a particular language as there exists variety and veracity in languages. The selection of MWEs are based on the statistical analysis of the MWEs extraction process. In the proposed work, the MWEs extraction is done for English dataset. Along with the existing statistical measures, i.e. Pointwise Mutual Information (PMI), Dice Coefficient (DC) and Modified Dice Coefficient (MDC), the additional measures, Lexical Fixedness (LF), Syntactic Fixedness (SF) and Relevance Measure (RM) are also been evaluated. The results are compared with the other existing approaches applied for English MWEs. The results shows that the proposed measures LF, SF and RM are more significant than existing measures to find the best statistics for the MWEs extraction process. The process model is generic in nature and not adhered to a particular language. It can also be applied for other languages by selecting POS tags for that particular language.
Authority and Power of the Law Relating to Cyber Deed Notary in Indonesia Era Industrial Revolution 4.0
Authors:   Faculty of Law, Universitas Wijaya Kusuma Surabaya, Surabaya, Indonesia., Chamidah* Dina , Krustiyati Atik ,   Faculty of Law, Universitas Surabaya, Surabaya, Indonesia., Purwadi Ari ,   Faculty of Law, Universitas Wijaya Kusuma Surabaya, Surabaya, Indonesia., Hadiwidjayanti Rizky ,   Faculty of Law, Universitas Airlangga, Surabaya, Indonesia., Bon Abdul Talib Bin ,   Fakulti Pengurusan Teknologi dan Perniagaan, Universiti Tun Hussein Onn Malaysia (UTHM), Johor, Malaysia.
Published: November 2019

This study aims to determine the authority of the notary in a deed on electronic transactions carried out by the parties domiciled outside the office of a notary and to know the power of a notary deed that created by Cyber Notary in Indonesia. The method used in this research is the approach of legislation (The Statute Approach) and the path of the legal concept analysis (Analytical and Conceptual Approach). The results showed that the authority of the electronic notary deed is not bound by a notary office area so that the legal position same with notary office by deed made by the notary on electronic transactions conducted in the region of the notary office. The strength of the notarial deed made by a cyber notary has not yet ensured legal certainty that the power of a notarial deed made together with the strength of the deed under the hand.
Texture based Leaf Disease classification using Machine Learning Techniques
Authors:   Assistant professor in Department of Computer Science and Engineering at APPA Institute of Engineering and Technology Kalaburgi- Karnataka., Arjunagi Mr. Shravankumar , Patil Dr. Nagaraj B. ,   Associate professor and HOD Dept. of CSE & ISE at Government College of Engineering, Raichur Karnataka
Published: November 2019

Machine learning techniques has emerged as a potential field in many of present day agricultural applications. One of these applications is the identification and classification of leaf diseases. In this paper, a triangular based and OTSU based methods are applied for segmentation, Textural features primarily based on GLCM are obtained for these segmented images using k-means clustering technique, further classification of different leaf disease is performed using an SVM based classification. The proposed method resulted in an overall classification accuracy of 70% using the triangular based segmentation with an AUC of 0.63.
Edge Based Segmentation in Medical Images
Authors:   Master of philosophy in computer science from Swami dayananda arts and science college , Manjakudi, Tamilnadu under Bharathidasan university Tiruchirapalli., B Karthicsonia , M Dr. Vanitha. ,   Asst professor of computer application department ,Alagappa university Karaikudi.
Published: November 2019

Image segmentation is the method to fragment a given image into a number of Regions or objects. The level of detail to which the partition is carried depends on the problem being solved. Edge detection is mostly used techniques in digital image processing. Edge detection will preserve the structural properties of an image and filter out unwanted dsata. In this paper, Edge detection methods such as Sobel, Prewitt, Robert, Canny, and Laplacian of Gaussian (LOG) are used. These methods are used in image segmentation. Edge detection can be enhanced by combining with denoised image. Wiener filter, Gaussian Filter and Median Filters are used for noise reductionS. The results of various methods are analyzed by implemented in MATLAB.
Estimation of White Blood Cells using Convolutional Neural Network
Authors:   Asst.Prof(SG), CSE Department, Saveetha School of Engineering, Saveetha Institute on Medical and Technical Sciences, Chennai, India, Jeyavathana Dr. R. Beaulah , Jose P. ,   Associate Professor, CSE Department, DMI Engineering College, Aralvaimozhi, Nagercoil, India, Balasubramanian R. ,   CSE Department, Manonmaniam Sundaranar University, Tirunelveli, India,
Published: November 2019

Normally blood samples contain red blood cells, white blood cells and platelets. White blood cells are also called as leukocytes and they are the cells of immune system. The measure of White Blood Cells is so important for the doctors in diagnosing various diseases like leukemia or tissue damage etc. So, counting of White Blood Cells plays an important role. The manual counting of White Blood Cells in medical laboratories involves a device called Haemocytometer. But this process is extremely monotonous, time consuming, and leads to inaccurate results. In this work, image processing and deep learning mechanisms are used to locate and classify the White Blood Cells based on their categories. The White Blood Cells which are classified are counted and compared with the standard range of the types available in the human blood sample. By comparing the availability of White Blood Cells types, the normal and the abnormal blood samples are predicted accordingly. The dataset of the normal blood sample is obtained from the laboratory in biotechnology department and the datasets used for training in Convolutional Neural Network are attained from the website Leukocyte Images for Segmentation and Classification (LISC). This will increase efficiency and reduce the doctor’s burden as traditional manual counting is dull, tedious, and possibly subjective.
Dry Sliding Wear Behavior of AISI310 Stainless Steel with Low Temperature Salt Bath Nitriding and Gas Nitriding Processes
Authors:   PG Student, Mechanical Engineering, Gokaraju Rangaraju Institute of Engineering & Technology, Hyderabad, India, Naveen Ch. , Bhandhavi Ch. ,   Assistant Professor, Mechanical Engineering, Gokaraju Rangaraju Institute of Engineering & Technology, Hyderabad, India, Sree K.Ramya ,   Assistant Professor, Mechanical Engineering, Gokaraju Rangaraju Institute of Engineering & Technology, Hyderabad, India, Gandhi M.Mamatha ,   Assistant Professor, Mechanical Engineering, Gokaraju Rangaraju Institute of Engineering & Technology, Hyderabad, India, Subbiah Dr.Ram ,   Associate Professor, Mechanical Engineering, Gokaraju Rangaraju Institute of Engineering & Technology, Hyderabad, India
Published: November 2019

AISI 310 is an austenitic stainless steel that accomplished in high thermal applications like turbines, boiler parts etc. In this study AISI310 was treated with salt bath nit- -riding for 60min, 120min and 150min and gas nitriding for 6hrs, 12hrs and 18hrs at the temperature of 5700c respectively. Comparison study of nitrided specimens were performed under various metallographic tests like scanning electron microscope, X-ray Diffraction, pin on disc apparatus. Experimental results shown that when salt bath nitrided sample at 150min showed a white layer called “S-phase” layer which was detected. In gas nitriding also “S-phase” layer, an expanded austenite was observed, after 18 hrs, CrN phase was discovered after the decomposition of s-phase layer gas nitrided sample of 18hrs which showed the best corrosion resistance .Salt bath specimen 150 min showed minimum wear loss and gas nitrided sample of 18hrs showed more hardness, minimum wear and improved corrosion resistance compared to untreated sample.
Electricity Theft Detection Techniques for Urban Commercial Power Consumers
Authors:   Electrical Engineering Department, Faculty of Technology and Engineering, The M S University of Baroda, Dangar Bharat , Joshi S. K. ,   Electrical Engineering Department, Faculty of Technology and Engineering, The M S University of Baroda
Published: November 2019

In power utilities, including technical losses and those due to Unmetered Power Losses activity in urban commercial consumes, and relating to the impact of Unmetered Power Losses activity from a financial perspective and an economic. Finally, this paper provided an overview of MGVCL as the largest power utility in Gujarat and outlines its needs with respect to implementing solutions to minimise Unmetered Power Losses activity.
Authentication Framework for Kerberos Enabled Hadoop Clusters
Authors:   School of Information Technology and Engineering, VIT University, Vellore, Tamilnadu, India., M* Hena , Jeyanthi Dr. N. ,   School of Information Technology and Engineering, VIT University, Vellore, Tamilnadu, India.
Published: November 2019

The corporate world is intensively thinking of how to process vast datasets efficiently and securely. Apache Hadoop, an open source framework serves this requirement. Most of the current Hadoop technologies use Kerberos Authentication to incorporate security aspect to Hadoop, which suffers from numerous security and performance issues. The reliance on authentication credentials, a single point of failure as well as a single point of vulnerability, the insider threat and time synchronization problem adds to the list. A comprehensive review of various authentication issues in Kerberos-enabled Hadoop Clusters is provided in this paper. This paper proposes an authentication framework for Hadoop that uses an enhanced One-time Password (OTP) that can solve all the identified problems. The simulation results in Riverbed Modeler proves that the proposed model performs as good as traditional Kerberos Authentication Mechanism. A comparative analysis with existing mechanisms is also presented to strengthen the claims of proposed method
Development and Validation of Nusselt Number Correlations for Mixed Convection in an Arc-Shape Cavity
Authors:   Ph.D. Scholar, MAEER’s MIT Kothrud, Pune affiliated to SPPU, Pune and an Assistant Professor in Mechanical Engineering at Army Institute of Technology, Pune affiliated to SPPU, Pune., Gurav R B , Lele Mandar M ,   Professor, Department of Mechanical Engineering in MAEER’s MIT COE, Pune.
Published: November 2019

The analytical study has been performed to investigate the combined effects of lid movement and buoyancy force parameter on mixed convective flow in an arc-shape cavity. The dimensional analysis based on Buckingham π-Theorem is used in the present study. It results in correlations for Nusselt number in terms of non dimensionalized parameters, viz. Re, Pr, Gr, θ etc. The correlations developed are validated against the experimental data of horizontal arc- shape cavity and numerical data of inclined arc-shape cavity obtained from open literature. The correlation developed in the present study for horizontal arc-shape cavity is valid for wide ranges of Re varying from 30 to 1500 and Gr from 0 to 107. In inclined arc-shape cavity it is valid for Re varying from 30 to 1500, Gr from105 to 107 and inclination angle from 150to 600.The close agreement in the comparison between predicted results by correlation developed in the present study and reported Nu correlation shows the validity of the correlation.
Prediction using C4.5 Method and RFM Method for Selling Furniture
Authors:   Faculty of Computer Science, Mercu Buana University, Jakarta, Indonesia,, Budi* Ifan Nugroho , Ranggadara Indra ,   Faculty of Computer Science, Mercu Buana University, Jakarta, Indonesia., Prihandi Ifan ,   Faculty of Computer Science, Mercu Buana University, Jakarta, Indonesia., Kurnianda Nia Rahma ,   Faculty of Computer Science, Mercu Buana University, Jakarta, Indonesia., Suhendra  ,   Faculty of Computer Science, Mercu Buana University, Jakarta, Indonesia.
Published: November 2019

Based on sales transaction data in Borobudur Furniture, it can be seen that customer demand for furniture can be said to be large, therefore special methods are needed to estimate sales that are most in-demand by customers in the future, and also special methods used to provide customer loyalty ratings. The method used to predict sales is the C4.5 method, while the method used to provide customer ratings based on customer loyalty is the RFM method. Through the process of data mining with the C4.5 method, it was found that the five items most in demand by customers were wardrobe, office chairs, buffet tv, guest table, and sofa set. While using RapidMiner as a test, the precision results are 63.64%, 89.36% for recall and 60.81% for accuracy. While through the RFM analysis process that has been carried out, there are four categories of customers and the minimum RFM total point is 3 points while the maximum RFM total point is 12 points.
Spark Architecture and Fractional Artificial Bee Colony-Chaotic Fruitfly RideNN for Big data Classification in Internet of Things
Authors:   College of Information Engineering, Al-Nahrain University, Baghdad, Iraq., Yousir* Naeem Th.
Published: November 2019

The typical Internet of Things (IoT) device gathers a huge amount of data specifically termed as big data framework, which transfers the collected data from the sensing layer to the information processing layer. Various big data classification methods are adopted in the industrial applications, and smart cities, but accurately classifying the data in the IoT network poses a challenging task in the research community. Therefore, an effective big data classification model using spark-based architecture is proposed in this research. The big data classification is performed at the master node using the proposed Fractional Artificial Bee Colony- Chaotic Fruitfly Rider Optimization Algorithm (FABC-CFFRideNN). The concept of fictional computing is adopted by the rider optimization algorithm (ROA) to update the position of rider groups based on success rate and the foraging behavior of fruit flies along with the rider parameters is used to enhance to performance of data classification using the proposed CFFRideNN classifier. Moreover, the proposed Fractional Artificial Bee Colony- Chaotic Fruitfly Rider Optimization Algorithm attained better performance using the metrics, namely accuracy, specificity, and sensitivity with the values of 95.382%, 95.81%, and 98.824% for training percentage without node velocity.
Design 10-Transistor (10t) Sram using Finfet Technology
Authors:   ECE Dept., MRIIRS, Faridabad, India., Verma* Jyoti , Passi Abhiruchi ,   ECE Dept., MRIIRS, Faridabad, India., Sindhu Savita ,   CSE Dept. MRIIRS, Faridabad, India., Gayathiri S. ,   MRIIRS, Faridabad, India,
Published: November 2019

This paper discuss designing of low power, high-speed 10-Transistor (10T) SRAM and analysis of SRAM cell in Metal Oxide Semiconductor Field Effect Transistor (MOSFET) and FinFET technology. MOSFET is used widely in many areas, but below 40 nm technology control of channel region becomes extremely difficult. So there is a necessity for new innovative technology which allows designers to design below 40nm technology and can offer excellent control over gate thus reducing short channel effects. The designing of SRAM is analyzed using TANNER EDA tool and Microwind.
A Dual Security Scheme Based On DWT for Personnel Authentication
Authors:   Associate Professor, Electronics and Communication Engineering, Vishnu Institute of Technology, Bhimavaram,, Sivananthamaitrey* Mr. P. , Krishna V. Venkata ,   Electronics and Communication Engineering, Vishnu Institute of Technology, Bhimavaram, India., Ramesh Dr. Addanki Purna ,   Professor, Department of ECE, Vishnu Institute of Technology, Bhimavaram, India., Murthy Dr. P. S. N. ,   Professor, Electronics and Communication Engineering, Vignan's Institute of Information Technology, Visakhapatnam, India.
Published: November 2019

A biometric identification system that audits the presence of a person using real or behavioral features is safer than passwords and number systems. Present applications are mostly recognize an individual using the single modal biometric system. However, a single characteristic sometimes fails to authenticate accurately. Multimodal biometric technologies solve the problems that exist in the single biometric systems. It is very hard to identify images with low lighting environments using facial recognition system. By utilizing fingerprint recognition, this issue can be better addressed. This paper presents a dual personnel authentication system that incorporates face and fingerprint to improve security. For face identification, the Discrete Wavelet Transform (DWT) algorithm is used to acquire features from the face and fingerprint pictures. The technique used to integrate fingerprint and face is decision level fusion. By adding fingerprint recognition to the scheme, the proposed algorithm decreases the false rejection rate (FRR) in the face and fingerprint recognition and hence increases the accuracy of the authentication.
Development of IoT Middleware Broker Algorithm for Handling Multiple Event Based Protocol Requests
Authors:   Research Scholar at Department of Computer Engineering,Bharati Vidyapeeth (Deemed to be University) College of Engineering,Pune, India., Deshmukh Prof. S.A. , Vanjale Prof. Dr. S.B. ,   Department of Computer Engineering,Bharati Vidyapeeth (Deemed to be University) College of Engineering,Pune, India.
Published: November 2019

The IoT Middleware is an integration layer for many Sensors, Actuators, devices, and brokers. The core aim of broker is to receive the request from the gateway and to process the payload and forward to the controlling actuators. Existing middleware uses thediscovery and protocols request management. Proposed work is focused on middleware soft-broker development which can support incoming protocols of IoT gateways. This paper presents the newly developed algorithm for handling CoAPrequests. This can be very useful for industrial IoT systems where sensor systems are powerful.
A Convolutional Neural Network Based Disease Diagnosis in Wireless Capsule Endoscopy Images
Authors:   Research Scholar, Computer Science, Development Centre, Bharathiyar University, Coimbatore, Sathiya Mrs.R. , Magal Dr.R.Kalai ,   Associate Professor in Computer Science, Government Arts College for Men (Autonomous), Nandhanam, Chennai.
Published: November 2019

In wireless capsule endoscopy (WCE), a swallow-able miniature optical endoscope is used to transmit color images of the gastrointestinal tract. However, the number of images transmitted is large, taking a significant amount of the medical expert’s time to review the scan. In this research, we propose a technique to automate the abnormality detection in WCE images. We split the image into several patches and extract features pertaining to each block using a Convolutional neural network (CNN) to increase their generality while overcoming the drawbacks of manually crafted features. We intend to exploit the importance of color information for the task. Experiments are performed to determine the optimal color space components for feature extraction and classifier design. We obtained an area under receiver-operating-characteristic (ROC) curve of approximately 0.8 on a dataset containing multiple abnormalities.
Detection and Analysis of Stress using Machine Learning Techniques
Authors:   MTech Student , Department of CSE, MIT Aurangabad, Maharashtra, India., Baheti Ms. Reshma Radheshamjee , Kinariwala Mrs. Supriya ,   Professor , Department of CSE.MIT Aurangabad, Maharashtra, India.
Published: November 2019

Every year tens of millions of people suffer from depression and few of them get proper treatment on time. So, it is crucial to detect human stress and relaxation automatically via social media on a timely basis. It is very important to detect and manage stress before it goes into a severe problem. A huge number of informal messages are posted every day in social networking sites, blogs and discussion forums. This paper describes an approach to detect the stress using the information from social media networking sites, like tweeter.This paper presents a method to detect expressions of stress and relaxation on tweeter dataset i.e. working on sentiment analysis to find emotions or feelings about daily life. Sentiment analysis works the automatic extraction of sentiment related information from text. Here using TensiStrengthframework for sentiment strength detection on social networking sites to extract sentiment strength from the informal English text. TensiStrength is a system to detect the strength of stress and relaxation expressed in social media text messages. TensiStrength uses a lexical approach and a set of rules to detect direct and indirect expressions of stress or relaxation. This classifies both positive and negative emotions based on the strength scale from -5 to +5 indications of sentiments. Stressed sentences from the conversation are considered &categorised into stress and relax. TensiStrength is robust, it can be applied to a widevarietyofdifferent social web contexts. Theeffectiveness of TensiStrength depends on the nature of the tweets.In human being there is inborn capability to differentiate the multiple senses of an ambiguous word in a particular context, but machine executes only according to the instructions. The major drawback of machine translation is Word Sense Disambiguation. There is a fact that a single word can have multiple meanings or "senses." In the pre-processing part-of-speech disambiguation is analysed and the drawback of WSD overcomes in the proposed method by unigram, bigram and trigram to give better result on ambiguous words. Here, SVM with Ngram gives better resultPrecision is65% and Recall is 67% .But, the main objective of this technique is to find the explicit and implicit amounts of stress and relaxation expressed in tweets.
Matlab Simulation For Fault Analysis of Electrical Circuit on Hyperspectral Signal Processing
Authors:   Assistant Professor, CITE, Manonmaniam Sundaranar University, Tirunelveli, Tamilnadu, India., Devi* Dr.T.Arumuga Maria , Muthukumar D. ,   Research Scholar, CITE, Manonmaniam Sundaranar University, Tirunelveli, Tamilnadu, India, S. Saji.K. ,   Research Scholar, CITE, Manonmaniam Sundaranar University, Tirunelveli, Tamilnadu, India.
Published: November 2019

The power system contains generation, transmission and Distribution. Abnormal conditions which cause flow of huge current in the conductors through improper paths in the circuit can be defined as a fault. The fault created transient parts which contain inexhaustible flaw data and are resistant to the framework's anomaly have been broadly utilized in the fault examination. The simulation findings demonstrate the system voltage and load currents effects of faults. In this paper, the different voltage circuit information levels will be evaluated using Hyperspectral processing and it is used to determine the exact difference in voltage magnification and evaluate it through signal processing.
Fuzzy Controller Based Reserve Management in Hybrid Microgrid for Frequency Regulation
Authors:   Electrical and Electronics department, CVR College of Engineering, Hyderabad, India., V* Phani kumar K.S. , Venkateshwarlu S. ,   Electrical and Electronics department, CVR College of Engineering, Hyderabad, India.
Published: November 2019

Power quality is a growing concern with sensible and critical loads asking for stringent frequency regulations. The distributed generation sources like Solar Photovoltaic, Diesel Generator, Fuel Cells, and Battery driven Electric Vehicles (BEV) are considered as power sources in the system. For the power-sharing among these generators, a central controller with a novel simple adaptive-additive control strategy is used. Each source has a local controller to regulate the power outputs. This paper presents a Neuro-Fuzzy controller for operating Solar Photovoltaic power at a Limited Power Point while a novel Neuro-Tuned-Fuzzy Controller decides which BEVs to be connected to the microgrid by giving a priority value to each BEV. The simulation results show the coordinated operation of the central and local controllers to regulate the power outputs of the sources was effective to manage reserves and achieve frequency regulation.
PAPR Reduction and Encryption Based On Hybrid Optimized PTS and Chaotic-DFT Sequences in OFDM System
Authors:   Electronics and Communication Engineering Bankura Unnayani Institute of Engineering West Bengal, Sarkar Mrinmoy , Kumar Asok ,   Dean of Students welfareVidyasagar University Midnapur, West Bengal, Maji Prof Bansibadan ,   ProfessorECE DepartmentNIT Durgapur, West Bengal
Published: November 2019

In high-speed wireless applications, because of the high-speed compatibility of the OFDM, it is a significant signal processing approach. In general, an efficient spectral multi-carrier modulation strategy is named OFDM, which gets impact via the issues of high PAPR. Because of the limited BW availability, the demand for high-speed applications is increasing. Due to the high data requirement, the various subcarriers are increased in OFDM, hence it made the difficult with PAPR (peak-to-average power ratio). To achieve better results by reducing the PAPR is the foremost problem on OFDM. In this paper, a hybrid optimized PTS is used to decrease the PAPR and the data will be encrypted by the DFT based chaotic sequences. A new Hybrid Whale Optimization and Moth Flame Optimization (HWOMFO) is introduced in this paper. It will generate a weighting factor for the PTS. PTS is the foremost strategy in OFDM for reducing the PAPR with low distortion. The minimum performance on computational complexity and PAPR achieved by this paper. The new combination of optimization approaches provides efficient best combination of phase rotational factors. The new hybrid optimization gives fast convergence quality and low complex and also this combination provides better than others. The proposed scheme is executed in MATLAB simulation and performance will be evaluated using parameters such as BER regards to SNR, complementary cumulative distribution function (CCDF) of PAPR and the outputs are associated depends on computation time. However, the experimental results show that compared with existing approaches, our proposed strategy gives better PAPR reduction with respect to SNR.
Handoff Decisions in Hetnets using Fuzzy Logic and Machine Learning Techniques
Authors:   Research Scholar, Department of Electrical engineering, Jamia Millia Islamia University, Mahajan Payal , Prof. Zaheeruddin  ,   Professor, Department of Electrical engineering, Jamia Millia Islamia University
Published: November 2019

Handover is a vital part of any wireless Mobile Communication Network. Efficient handover algorithms provide a gain in monetary cost effective method for enhancement in the capacity and QOS(quality of services) of cellular system. The work reported here presents a handover decision support system for wireless heterogenous communication. Fuzzy inference system along with neural network techniques in Matlab has been used for the development of the system.Results for performance of five different neural network techniques have been drawn on basis of their training time,classification accuracy and number of neurons taken. The neural tools used here are Back propagation, Radial Basis Function, Nave Bayes, Bayes net and C4.5 decision tree. On the basis of their performance, a best neural tool has been selected for the use in making handover decisions in wireless communication systems and it is seen that among all the neural network tools C 4.5 decision tree gives the better results in terms of classification accuracy and training time for handover decisions.
PENGARUH TEKHNIK BABY SPA TERHADAP PERKEMBANGAN MOTORIK DAN KENAIKAN BERAT BADAN BAYI
Authors: Puteri Vita Triani Adi , Taufik Syarief , Nurul Melyana
Published: November 2019

Abstract

Background: Baby Spa is a series of stimulation of growth and development of children by combining baby gym services, baby swimming and baby massage. In the Kedungmundu District Health Center, it was found that the incidence of infants who had poor nutrition were 6 babies, malnutrition were 3 infants and those who suffered from growth disorder were 15 infants. Objective: This research was aimed to find out the influence of baby spa techniques on motor development and increase in baby's weight. Method: this study used Quasi Experiment method with Pre and Post test with control group design, data analysis used Dependent T Test and Independent T test. Results: There were differences in motor development before and after the treatment, it obtained p Value of 0.001in the treatment group and p value of 0.041 in the control group. There were differences in infant weight gain before and after baby spa (P Value 0,000) in the treatment group and no difference increase in baby’s weight (P Value 0.061) in the control group, there is the influence of giving Baby Spa techniques and baby massage to baby’s motor development in the two groups (P Value 0.021), there is the influence of Baby Spa techniques and baby massage on baby’s weight in the second group (P Value 0.04). Conclusions: There are differences in motor development and increase of baby weight in both groups, and there are effects of Baby Spa techniques and baby massage on motor development and baby’s weight increase in baby aged 4-12 months in each group.

 

Keywords : Baby Spa, Motor Development, and increasing of baby’s weight

 

Abstract

Baby spa merupakan rangkaian stimulasi tumbuh kembang anak dengan memadukan layanan senam bayi (baby gym), berenang (baby swim) dan pijat bayi (baby massage). Hasil survey pendahuluan yang dilakukan di puskesmas kedungmundu semarang didapatkan hasil bayi yang mengalami kurang gizi sebanyak 6 bayi, gizi buruk sebanyak 3 bayi dan yang mengalami keterlambatan perkembangan motorik sebanyak 15 bayi. The Aim Of Research : Mengetahui pengaruh tekhnik baby spa terhadap perkembangan motorik dan kenaikan berat badan bayi. Research Methode : Jenis penelitian menggunakan quasi eksperimental design dengan rancangan penelitian menggunakan pretest - posttest with control group design. Sampel yang diambil dalam penelitian ini adalah bayi usia 4 – 12 bulan yang berjumlah 30 bayi. Analisa data menggunakan dependent sample t – test. The Result : Ada pengaruh pemberian teknik baby spa pada kelompok perlakuan dan pijat bayi pada kelompok kontrol terhadap perkembangan motorik bayi dengan hasil nilai P value 0,021 dan ada pengaruh pemberian teknik baby spa pada kelompok perlakuan dan pijat bayi pada kelompok control terhadap kenaikan berat badan bayi dengan hasil nilai P value 0,04. Conclusion: Ada pengaruh teknik baby spa terhadap perkembangan motorik dan kenaikan berat badan bayi.

 

Keywords : Teknik Baby Spa, Perkembangan motorik bayi, Kenaikan berat badan bayi
PERANCANGAN DAN IMPLEMENTASI SISTEM MONITORING PRESTASI AKADEMIK DAN AKTIVITAS SISWA DI SMP NEGERI 1 JARAI DENGAN METODE WATERFALL
Authors: Sasmita
Published: November 2019

Proses monitoring kegiatan akademik di SMP Negeri 1 Jarai masih berjalan manual dikarnakan penyimpanan datanya masih tersebar disetiap guru bidang studi masing-masing yang diinput ke microsoft excel terkadang datanya kurang akurat. Dari permasalahan tersebut, maka dibuat sebuah sistem pengolahan data prestasi akademik untuk mengatur penentuan prestasi akademik tiap siswa, dimana data prestasi yang berupa nilai, dan kegiatan ekstrakulikuler akan  dapat lebih mudah diproses dan laporannya dapat dibuat dengan mudah. Keuntungan dari sistem ini data yang berupa nilai dan kegiatan ekstrakulikuler tersimpan dengan rapi. Metode Waterfall yang digunakan dalam penelitian ini dengan perangkat desain menggunakan UML. Prangkat yang digunakan untuk membuat sistem ini adalah PHP sebagai bahasa pemograman serta MySQL sebagai databasenya. Sistem ini dapat diterapkan dalam proses monitoring prestasi akademik, Sehingga data prestasi akademik dapat tersimpan dengan baik. Hasil yang didapat dari penelitian ini berupa Website Monitoring Prestasi Akademik dan Aktivitas Siswa Di SMP Negeri 1 Jarai yang dapat mempermudah mengontrol dan mengevaluasi kegiatan yang berhubungan dengan prestasi akademik.