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Ambient monitoring in smart home for independent living
Ambient monitoring is a much discussed area in the domain of smart home research. Ambient monitoring system supports and encourages the elders to live independently. In this paper, we deliberate upon the framework of an ambient monitoring system for elders. The necessity of the smart home system for elders, the role of activity recognition in a smart home system and influence of the segmentation method in activity recognition are discussed. In this work, a new segmentation method called area-based segmentation using optimal change point detection is proposed. This segmentation method is implemented and results are analysed by using real sensor data which is collected from smart home test bed. Set of features are extracted from the segmented data, and the activities are classified using Naive Bayes, kNN and SVM classifiers. This research work gives an insight to the researchers into the application of activity recognition in smart homes. Springer Nature Singapore Pte Ltd. 2019. -
Early detection of breast cancer using ER specific novel NIR fluorescent dye conjugate: A phantom study using FD-f-DOT system
Fluorescence diffuse optical tomography (f-DOT) is an imaging technique that can quantify the spatial distribution of fluorescent tracers in small animals and human soft tissues. Efficacy of f-DOT imaging can be improved by tagging a functional group to the dye. A novel estrogen receptor (ER) specific near-infrared (NIR) fluorescent dye conjugate was synthesized which can be effectively used for detecting breast cancer tissues at an early stage. Our novel dye, Near Infrared Dye Conjugate-2 (NIRDC-2), is a conjugate of 17?-estradiol with an analogue of Indocyanine Green dye, bis1,1-(4-sulfobutyl) indotricarbocyanine-5-carboxylic acid, sodium salt. Our present study focuses on imaging cylindrical silicone phantoms using Frequency Domain f-DOT system. Background absorption and scattering coefficients were 0.01mm-1 and 1mm-1 respectively. 10?M concentration of NIRDC-2 and Indocyanine Green (ICG) were administered separately into a cylindrical hole (target) of size 8mm diameter in the phantom. In-silico studies were performed to analyze the properties of dyes using experimental data. Absorption coefficient of 0.0002 mm-1 was recovered for the background. Fluorophore absorption coefficient at the target recovered were 0.000173 mm-1 and 0.000408 mm-1 for ICG and NIRDC-2 respectively. In comparison with ICG, our novel dye had a two fold higher target to background contrast. Recovered target position was accurate but size altered. In concurrence with the recovered fluorescent property and the cell lines studies carried out earlier, binding properties of NIRDC-2 makes it a potential probe for the early tumor detection using f-DOT system. COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only. -
Gravity modulation effect on ferromagnetic convection in a Darcy-Brinkman layer of porous medium
The influence of a timedependent body force on the threshold of convective instability in a magnetic fluid filled horizontal porous layer is investigated. The gravity modulation effect is treated by employing a perturbation method. The correction Rayleigh number is computedas a function of the modulation frequency, porous and magnetic parameters. It is expounded that, for small and reasonable values of the modulation frequency, gravity modulation and magnetic mechanism have opposing influence on the stability. The study further explicates that, when the gravity modulation frequency increases beyond all bounds, manifestation of the disappearance of the magnetic and porous medium effects on the stability is highly likely. Published under licence by IOP Publishing Ltd. -
Secured Electronic Transactions Using Visual Encryption: An E-Commerce Instance
The developments in the information technology has led the modern world to rely on the internet for digital information. People around the world depend on the internet for every information from general information to sharing confidential data over the network. Technology has grown so wide that even all the transactions are happening through online platforms. Along with this, there has been a rise in the security threats of the user's confidential data which are shared by the users while buying goods online. To maintain the security there are many authentication techniques available today like OTP, CAPTCHA etc. These security measures taken till now have been adequate till the present day but over time the hackers would find out ways to attack. Data breaches and hacking of user data would increase day by day if preventive measures are not taken time to time. This project focuses on providing security to the user's confidential data with a two way authentication technique. The aim of the project is to include one more security level to the existing online transaction system. The visual cryptographic method is used along with the OTP generating system. 2018 IEEE. -
Breaking News Recognition Using OCR
Identifying and recognition of breaking news in most of the TV channels in different backgrounds with varying positions from a static image plays a significant role in journalism and multimedia image processing. Now a days its very challenging to isolate only breaking news from headlines due to overlapping of many categories of news, keeping all this in mind, a novel methodology is proposed in this paper for detecting specific text as a breaking news from a given multimedia image. Basic digital image processing techniques are used to detect text from the images. The methods like MSER (Maximally Stable Extremal Regions) and SWT (Stroke Width Transform) are used for text detection. The proposed work focuses on extraction of text in breaking news images also discusses the different methods to overcome existing challenges in text detection along with different types of breaking news datasets collected from various news channels are used to identify text from images and comparative study of different text detection methods. The comparative study proves that MSER and SWT is a better technique to detect text in images. Finally using OCR (Optical Character Recognition) technique to extract the breaking news text from the detected regions will help in easy indexing and analysis for journalism and common people. Extensive experiments are carried out to demonstrate the effectiveness of the proposed approach. 2019, Springer Nature Singapore Pte Ltd. -
An Efficient Preprocessing Step for Retinal Vessel Segmentation via Optic Nerve Head Exclusion
Retinal vessel segmentation plays a significant role for accurate diagnostics of ophthalmic diseases. In this paper, a novel preprocessing step for retinal vessel segmentation via optic nerve head exclusion is proposed. The idea relies in the fact that the exclusion of brighter optic nerve head prior to contrast enhancement process can better enhance the blood vessels for accurate segmentation. A histogram based intensity thresholding scheme is introduced in order to extract the optic nerve head which is then replaced by its surrounding background pixels. The efficacy of the proposed preprocessing step is established by segmenting the retinal vessels from the optic nerve head excluded image enhanced using CLAHE algorithm. Experimental works are carried out with fundus images from DRIVE database. It shows that 1%3% of improvement in terms of TPR measure is achieved. 2019, Springer Nature Singapore Pte Ltd. -
Thermorheological and magnetorheological effects on Marangoni-Ferroconvection with internal heat generation
Marangoni convectiveinstability in a ferromagnetic fluid layer in the presence of a spatial heat sourceand viscosity variation is examined by means of the classical linear stability analysis. The higher order Rayleigh-Ritz technique is used to compute the critical Marangoni number. The effective viscosity of the ferromagnetic liquid is taken to be a quadratic function of both the temperature and magnetic field strength. It is shown that the ferromagnetic fluid is significantly influenced by the effect of viscosity variation and is more prone to instability in the presence of heat source compared to that when viscosity is constant. On comparing the corresponding results of heat source and heat sink it is found that heat sink works in tandem with the effect of viscosity variation if magnetic field dependence of viscosity dominates over temperature dependence. If the temperature dependence of viscosity dominates, the effects of viscosity variation and heat sink are mutually antagonistic. Published under licence by IOP Publishing Ltd. -
Classification of Vehicle Make Based on Geometric Features and Appearance-Based Attributes Under Complex Background
Vehicle detection and recognition is an important task in the area of advanced infrastructure and movement administration. Many researchers are working on this area with different approaches to solve the problem since it has a many challenge. Every vehicle has its on own unique features for recognition. This paper focus on identifying the vehicle brand based on its geometrical features and diverse appearance-based attributes like colour, occlusion, shadow and illumination. These attributes will make the problem very challenging. In the proposed work, system will be trained with different samples of vehicles belongs to the different make. Classify those samples into different classes of models belongs to same make using Neural Network Classifier. Exploratory outcomes display promising possibilities efficiently. 2019, Springer Nature Singapore Pte Ltd. -
Recognition of Signature Using Neural Network and Euclidean Distance for Bank Cheque Automation
Handwritten signature recognition plays significant role in automatic document verification system in particularly bank cheque authorization. The proposed method focuses on A novel technique for offline signature recognition approach for bank cheque based on zonal features and regional features. These combined features are used to find genuinety of signature using Euclidean distance as a metric. Extensive experiments are carried out to exhibit the success of the recommended approach. 2019, Springer Nature Singapore Pte Ltd. -
Compression Based Modeling for Classification of Text Documents
Classification of text data one of the well known, interesting research topic in computer science and knowledge engineering. This research article, address the classification of text files issue using lzw text compression algorithms. LZW is a lossless compression technique which requires two pass on the input data. These two passes are treated separately as training stage and text stage for classification of text data. The proposed compression based classification technique is tested on publically available datasets. Results of the experiments shows the effectiveness of the proposed algorithm. 2019, Springer Nature Singapore Pte Ltd. -
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. -
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. -
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. -
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. -
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. -
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. -
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). -
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). -
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. -
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.