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Smart detection of rice purity and its grading
The main food in India is Rice. Be it the breakfast, lunch, dinner or some snacks, for everything the most preferred ingredient in Rice. In compared with north Indians, Rice is most used by South Indians. Today's youngsters from villages are migrating to cities in search of jobs after their education. Even farmers have stopped their cultivation and are working towards different business. So, the yield of rice is reduced in India. One more reason for this is because of the poor monsoon. Government is finding it challenging to supply rice to all its consumers. It is expected, because for Rice the consumers are more compared to its production. Government has decided to import the rice from the neighboring countries. This neighboring country knows the demand of rice in India and started supplying contaminated rice. Currently our Government has no technology to check the quality of the rice which they are getting imported, so the result is plastic rice arrived in India. Indirectly, India is in huge loss in terms of money and damages for its citizens health. So, there is a need of automated system to detect the quality of the rice that are imported. Another use of such automated system is that most of the people are not able to identify the type of the rice and the quality of the rice. This system helps even common man a facility in identifying the type and quality of rice. 2017 IEEE. -
A new trained ECG signal Classification method using Modified Spline Activated Neural Network
An ECG (Electrocardiogram) records the electrical activity of the heart and assess heart arrhythmia. Cardiac arrhythmia is an irregular heartbeat caused by unbalanced rhythm. In the past, several works were developed to produce automatic ECG-based heartbeat classification methods. In this work, a modified spline activated neural network, a new approach for cardiac arrhythmia classification by presenting the ECG signal preprocessing, the heartbeat segmentation techniques, the feature description methods and the learning algorithms used. The MIT-BIH arrhythmia database was used and experimented for testing and training. 2018 IEEE. -
Segmentation technique for medical image processing: A survey
Segmentation is one of the popular and efficient technique in context to medical image analysis. The purpose of the segmentation is to clearly extract the Region of Interest from the medical images. The main focus of this paper is to review and summarize an efficient segmentation method. While doing the comparison study on segmentation methods using the Support Vector Machine, K-Nearest Neighbors, Random Forest and the Convolutional Neural Network for medical image analysis identifies that Convolutional Neural Network works efficiently for doing in-depth analysis. The Convolutional Neural Network can be used as segmentation technique for achieving the high accuracy on medical image analysis. 2017 IEEE. -
Secure Bitcoin Transaction and IoT Device usage in Decentralized Application
In the recent years, there has been a boom in the number of connected devices due to developments in the field of Internet of things. This has also increased the requirements of security specification. The proposed method is introducing a secure information transmission system by using Blockchain technology. Blockchain is a relatively new technology which was introduced by stoshi nakamoto, which was also the basis for developing crypto currency [bitcoin]. Crypto currencies are made transparent and secure using their network architecture, which is a combo of a decentralized and distributed network. In this paper is try to exploit the same methodology used in crypto currencies to develope an IOT network, where the devices can talk to their peers in a secure manner. They explored all the different networks and features of developing a Decentralized application that is named as Dapp. 2018 IEEE. -
IOT based no-parking notifier system
Traffic congestion due to vehicles parked in No-parking zones has become a serious problem in major cities of India. Due to traffic congestion environment, economy and overall quality of life is affected. Hence it is high time to effectively manage the traffic congestion problem. With increase in number of vehicles, discipline in road regulation or traffic system becomes mandatory. The existing traffic system is very accurate but not efficient enough to monitor all the vehicles on the road. With the advent of new technology this problem can be tackled by using Wi-Fi enabled micro-controllers, RFID and cloud systems to monitor every vehicle on the road all the time. This becomes easy for the government in regulating its traffic rules with high efficiency without affecting the smoothness of the traffic. 2018 IEEE. -
Compact substrate integrated waveguide power divider with slot-loaded ground plane for dual-band applications
In this paper, a novel design of compact substrate integrated waveguide (SIW) dual-band power divider is proposed. The dual-band operation of the power divider is obtained by exploiting the loading of slots on the ground plane. The electric-dipole nature of these slots allows the power divider to exhibit a passband below the cutoff frequency of the SIW. An in-depth description of the proposed power divider, supported by detailed parametric analysis over the operating frequency bands is reported. Design examples are illustrated to achieve different operating frequency bands. To validate the design studies, a prototype of the dual-band power divider operating at 4.7 GHz and 11.7 GHz is designed, fabricated and tested. The measurement results are found to be in good agreement with the simulation results. 2018 IEEE. -
Assessment of Battery Technologies for Future of Electro-Mobility in Emerging Markets
In the outset of economic growth, the emerging country like India faces challenges due to rapid urbanization, infrastructure and city-congestion. The increased demand for mobility and a pivotal role of internal combustion engines from decades in the transportation segment have led to two influencing factors i.e., increased dependency on the oil import from fuel rich countries and alarming levels of emission. Hence it is essential for a country like India to venture into newer technologies to reform the transportation segment, reduce the dependency on the oil import and also has a positive impact on the pollutants. There are few technological barriers for the development of electric vehicles over internal combustion (IC) engines in terms of cost and performance of the vehicle. Along with the reduction of emissions, the electric vehicles should exhibit considerably good specific energy density and specific power density to emulate over the conventional (IC) engines. The three major constituents of electric vehicles are the battery, electric engine and the controller. The energy storage device forms the crux of the electric vehicle and has a significant role in its performance as well as forms the expensive component of the vehicle. Hence this paper involves the evaluation of various battery technologies, their performance requirements and options feasible for electric vehicles of the future. 2018 IEEE. -
Automatic Measurement and Differentiation of Traffic Volume Count
Traffic volume in India is growing drastically over the past few decades. This leads to an increased need of constructing more highways and underpasses. In order to have the definite knowledge of traffic volume, and to design the width and thickness of the pavements, periodical conduction of traffic census is necessary. At present, the evaluation of traffic volume is conducted manually. This system is tiresome and lacks accuracy. The data obtained from the traffic census decides the sanction of new highways, underpasses, or flyovers which involves huge investments. Hence, the accuracy of this data is very critical. In this paper, we propose an automatic tool that helps to measure the traffic volume and differentiate the vehicles using video processing tools in MATLAB. The proposed algorithm consists of the following steps: i Foreground Detection ii Blob Detection iii Blob Analysis iv Vehicle differentiation Counting. 2018 IEEE. -
Ground Truncated Broadband Slotted Circular Microstrip Antenna
In this growing era of wireless technology, large sized devices have become obsolete. In response to the increasing demand for miniaturization over the past decades, microstrip antennas have drawn attention due to its various features like light weight, low cost, small in size and its greater resistivity to shock and vibrations. These can also easily get conformed to any surface. These antennas are also capable of operating at high frequencies, providing large bandwidth and gain by using various techniques slots and truncation of shapes. This report describes the design, simulation, fabrication and measurement results of a microstrip fed Slotted Circular Microstrip Antenna for broadband applications. The antenna was designed for an operating frequency of 2.45 GHz on a double side printed FR4 substrate measuring 55 mm x 55 mm x 1.6 mm with ?r of 4.4. It measured a very large resonant band of 1.3 - 9.05 GHz at a return loss level as low as -36.5 dB at 7.98 GHz. A maximum gain of 2.46 dB was achieved at 2.33 GHz. The enhancement in bandwidth was achieved by truncation in ground and inclusion of thin circular slot. The HFSS version 18.2 software and VNA model Anritsu SA20E were used for simulation and measurement respectively. It is found that the simulation and measurement results agree. 2018 IEEE. -
Professional chat application based on natural language processing
There has been an emerging trend of a vast number of chat applications which are present in the recent years to help people to connect with each other across different mediums, like Hike, WhatsApp, Telegram, etc. The proposed network-based android chat application used for chatting purpose with remote clients or users connected to the internet, and it will not let the user send inappropriate messages. This paper proposes the mechanism of creating professional chat application that will not permit the user to send inappropriate or improper messages to the participants by incorporating base level implementation of natural language processing (NLP). Before sending the messages to the user, the typed message evaluated to find any inappropriate terms in the message that may include vulgar words, etc., using natural language processing. The user can build an own dictionary which contains vulgar or irrelevant terms. After pre-processing steps of removal of punctuations, numbers, conversion of text to lower case and NLP concepts of removing stop words, stemming, tokenization, named entity recognition and parts of speech tagging, it gives keywords from the user typed message. These derived keywords compared with the terms in the dictionary to analyze the sentiment of the message. If the context of the message is negative, then the user not permitted to send the message. 2018 IEEE. -
MR Brain Tumor Classification and Segmentation Via Wavelets
Timely, accurate detection of magnetic resonance (MR) images of brain is most important in the medical analysis. Many methods have already explained about the tumor classification in the literature. This paper explains the method of classifying MR brain images into normal or abnormal (affected by tumor), abnormality segments present in the image. This paper proposes DWT-discrete wavelet transform in first step to extract the image features from the given input image. To reduce the dimensions of the feature image principle component Analysis (PCA) is employed. Reduced extracted feature image is given to kernel support vector machine (KSVM) for processing. The data set has 90 brain MR images (both normal and abnormal) with seven common diseases. These images are used in KSVM process. Gaussian Radial Basis (GRB) kernel is used for the classification method proposed and yields maximum accuracy of 98% compared to linear kernel (LIN). From the analysis, compared with the existing methods GRB kernel method was effective. If this classification finds abnormal MR image with tumor then the corresponding part is separated and segmented by thresholding technique. 2018 IEEE. -
Academic workbench for streetlight powered by solar PV system using internet of everything (IoE)
Renewable energy is one of the growing trend in developing countries. Rapid development of renewable energy leads to the economic benefits and reduce environmental pollution. According to current scenario 20 to 40 percent of the power generated is consumed by streetlights. The problems faced by the current street lighting systems are when there is availability of light there is no proper utilization. Sun intensity shift is not constant all the time, it varies as the climate changes. Real time monitoring and control using intelligent algorithm avoids energy wastage during day time. ZigBee as a communication protocol current and voltage values are sent and received. Base Controller (Single Board Computer) acts as an interphase between the communication protocol and the cloud account. Remote client application is developed to control and monitor streetlight. 2018 IEEE. -
IoT based continuous monitoring of cardiac patients using Raspberry Pi
In the recent development the Internet of Things (IoT) brings all electronics objects in to a single domain and it is easy to access everything through internet. The applications of IoT are Smart agriculture, Smart Home, Smart City, Smart health monitoring system etc. The automation of health care is one of the application which monitors the patient health status using IoT to make medical equipments more efficient by monitoring the patient's health, in which identifies the body conditions and reduces the human error. A health care monitoring system is used to monitor patient's body parameters for the particular disese and obtain the various values about it. The heart rate monitor is one of the in system using IoT to recognize the cardic patients condition and monitor the status in emergency situations. It monitors the heart rate of the patient with long term cardiovascular disease. Here the Arduino based microcontroller is used to communicate to the sensors such as pulse sensor and ECG Sensor. The system can analyze the signal, extract features from it, detect the normal or abnormal conditions with the help of Raspberry Pi and the results of the ECG signals is sent to the web server. It ensures the signal transmission of heart rate signal to the database through IoT. This also suggests doctors to care the patient follow-up their patient using the patient's data stored in the database. Thus IoT brings one of the solution for cardiac patient monitoring and also reduces the complexity between patient outcome and technology. 2018 Author(s). -
K-shell jump ratio and jump factor of 3d elements
Employing a simple 2?-geometrical configuration method, K-shell absorption jump ratio and jump factor have been estimated in a few 3d elements viz. Co, Ni, Cu and Zn. The target elements in the form of thin foils were excited using 32.86 keV K X-ray photons from a weak137Cs radioactive source. The emitted K X-rays were detected using a low energy HPGe X-ray detector spectrometerand the K X-ray production cross-section and K X-ray intensity ratios for all the target elements were measured. Then, using the measured data, the K-shell absorption jump factor and jump ratios have been evaluated. The obtained results agree within the experimental uncertainties with previous values reported in the literature. 2018 Author(s). -
An Iot Application to Monitor the Variation in Pressure to Prevent the Risk of Pressure Ulcers in Elderly
Pressure sores are a common form of skin problem which occurs with patients who are bedridden or immobile. It is believed that the occurrence of ulcers due to pressure can be prevented. Making best use of resources available and providing comfort to the patient, it is very much important to identify people at risk and provide preventive measures. This work is associated with a method to analyze pressure from pressure points on bedridden patients. A system is presented in this work that continuously monitors the pressure from pressure points using force sensors and sends an alarm to the nurses or caretakers if there is a variation in the pressure exerted on a specific area. 2018 IEEE. -
Twitter sentiment for analysing different types of crimes
Online social media like a twitter play a vital role as it helps to track the Spatialoral on social media data with respect crime rate. With the very fast evolving of users in social media, sentimental analysis has become an excellent source of information in decision making. Twitter is one of the most popular social networking site for communication and a primary source of information. More than 150 million users publish above 500 million 140 character TWEETS each day. Tweets have become a basis for product recommendation using sentimental analysis. This paper explains the approach for analyzing the sentiments of the users about a particular crime event tweets posted by the active users. The results so obtained will let you know about the change in the public opinion about the crime events whether it's positive or negative and to find out emotions on different types of crimes. 2018 IEEE. -
Reflector Backed Conical Dielectric Resonator Antenna with Enhanced Gain
This paper reports a wideband, high gain, slot coupled reflector backed conical dielectric resonator antenna (DRA). The key findings of the work are as follows; i) the antenna operates over 7.73-8.3 GHz, with peak gain of 10.32 dBi, ii) an gain enhancement > 5dBi achieved by placing a reflector below the ground plane, iii) the measured results best matches with their measured counter parts, iv) the antenna deals with many advantages, including performance, volume, and fabrication feasibility. From application point of view the developed model can be successfully used for X-band wireless communication. 2018 IEEE. -
IOT Based Smart Agriculture System
Smart agriculture is an emerging concept, because IOT sensors are capable of providing information about agriculture fields and then act upon based on the user input. In this Paper, it is proposed to develop a Smart agriculture System that uses advantages of cutting edge technologies such as Arduino, IOT and Wireless Sensor Network. The paper aims at making use of evolving technology i.e. IOT and smart agriculture using automation. Monitoring environmental conditions is the major factor to improve yield of the efficient crops. The feature of this paper includes development of a system which can monitor temperature, humidity, moisture and even the movement of animals which may destroy the crops in agricultural field through sensors using Arduino board and in case of any discrepancy send a SMS notification as well as a notification on the application developed for the same to the farmer's smartphone using Wi-Fi/3G/4G. The system has a duplex communication link based on a cellularInternet interface that allows for data inspection and irrigation scheduling to be programmed through an android application. Because of its energy autonomy and low cost, the system has the potential to be useful in water limited geographically isolated areas. 2018 IEEE. -
Optimized Metamaterial Loaded Square Fractal Antenna for Gain and Bandwidth Enhancement
This paper presents a report on the enhanced performance of an optimized metamaterial loaded square fractal antenna (OMSFA). The design and simulation of the antenna was carried out using Electronic Desk Top HFSS version 18.2 software. The antenna layer spreads over an area of 23 square millimeter on a FR4 substrate whose dielectric permittivity is 4.4. The substrate size measures an area of 46 mm X 28 mm, with 1.6 mm thickness. Also the design includes a microstrip feed and truncated ground. The antenna resonates well with a deep return loss of-38.9 dB in a broad bandwidth of 3.2 GHz (128 %) between 2 GHz and 5.2 GHz. The OMSFA produces enhanced gain of 9.8 dB at 2.5 GHz. The radiation is more focused due to the effect of metamaterial loading. The proposed antenna is recommended for wireless application in the lower region (S band) of the microwave spectrum. 2018 IEEE. -
A comprehensive investigation on machine learning techniques for diagnosis of down syndrome
Down Syndrome is a chromosomal disease which causes many physical and cognitive disabilities. Down Syndrome patients are more vulnerable than any other patient. Medical experts started knowing it now with keen awareness. In recent years it has become a field of interest for many researchers, medical experts and social organisation. For the researchers it is an area of interest where very little work is done and a lot to be explored. Machine Learning consists of different processing levels like pre-processing, segmentation, feature selection and classification. Each level contains a vast set of techniques like filters, segmentation algorithms and classifiers. Machine Learning is one of the most popular algorithm, which is used to automate the decision making process with higher rate of accuracy in less time with least error rate. Machine Learning proved its significance with highest rate of accuracy in decision making and problem solving in almost all the fields but automated decision making in medical science is still a challenge. This paper reviews the different works done in the field of Down Syndrome using Machine Learning applied on different medical images, and the techniques like pre-processing, segmentation, feature selection and classification. The aim of this research work is to analyse and identify the Machine Learning methodologies that works efficiently to detect Down Sundrome. 2017 IEEE.