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Performance analysis of antenna with different substrate materials at 60 GHz
With a tremendous demand on data rate and bandwidth utilization in RF communication systems, current research studies leads to explore the millimeter-wave unlicensed 57-64 GHz bandwidth of electromagnetic spectrum. This high frequency band is not channelized for long distance communication. However, it could be efficiently utilized for indoor and short range digital communication transmission systems for enhanced data rate and bandwidth utilization. This paper focused on designing antenna that utilizes 60 GHz frequency which falls under this spectrum by using different substrate materials such as like RT Duroid, FR4 Epoxy, Rogers RO3010 and GaAs for Rectangular Microstrip Antenna (RMSA). This research paper presents a detailed analysis on performance parameters comparison like gain, VSWR, return loss & radiation pattern analysis for the 60 GHz antenna designed with substrate materials having different properties. 2017 IEEE. -
Crown shaped broadband monopole fractal antenna for 4G wireless applications
This paper proposes a novel crown shaped fractal antenna design suitable for 4G wireless applications. One of the promising approaches in miniaturizing the antenna size is to use the fractal geometries. Several efforts have been made by various investigators around the globe to amalgamate benefits of fractal structures with electromagnetic concepts and applications. This paper outlines a new approach in designing broadband monopole 2.1 GHz fractal antenna. The design starts with square patch antenna and goes up to third iteration for obtaining better performance and impedance matching. The proposed antenna was designed and simulated using the HFSS EM simulator. Performance analysis of the antenna was done with characteristics such as return loss, VSWR, efficiency and radiation pattern found to be good at 2.1 GHz. Wireless application demands miniaturization in system as well as antenna size with better performance, hence attempts have been made to reduce the size and improve the gain, efficiency and bandwidth of the proposed antenna. 2017 IEEE. -
An approach for efficient capacity management in a cloud
Cloud computing is an emerging technology where computing resources such as software and hardware are accessed over the internet as a service to customers. In the past, due to less demand, cloud capacity management was not critical. However, with the increase in demand, capacity management has become critical. Cloud customers can frequently use web-based portals to provision and de-provision virtual machines on demand. Due to dynamic changes as per the demand, managing capacity becomes a challenging task. In this paper, we discuss the emergence of cloud computing, traditional versus cloud computing, and how capacity management can be efficiently handled in a cloud. A detail on high availability of virtual machines in a cloud using the N+1 model is discussed in this paper. With templates, many repetitive installation and configuration tasks can be avoided. We discuss the sizing of templates and the overheads of using virtual machines. We suggest ideal combinations of sizing templates to create virtual machines with optimum utilization of blades. Finally we discuss a few benefits of efficient capacity management in cloud computing. 2017 IEEE. -
Phonon limited diffusion thermopower in phosphorene
A theoretical investigation of diffusion thermopower, Sd, of phosphorene employing Boltzmann transport formalism is presented. We assume carriers in phosphorene to be scattered by in-plane single and flexural two-phonon processes via deformation potential coupling. Our calculations of Sd in phosphorene show that, at low temperatures (T?< 20 K) Sd increases linearly with temperature and for the range of temperatures considered single phonon contribution to Sd dominates. As function of carrier concentration, ns, considered (1016?1018 m-2), at T = 300K, Sd decreases from 189?V/K to 9.9 ?V/K. 2017 Author(s). -
A comparitive study on traditonal healthcare system and present healthcare system using cloud computing and big data
Cloud computing is one the emerging technology which provides all the necessary resources required for day to day operations of an organization in a virtual environment. It is also known as green computing as it reduces the physical existence of the hardware resources. Health is being considered as a basic right for an individual. Even though there are advancements in the healthcare sector of India when compared to earlier stages, there is still a need for betterment in this sector. In order to make progress in this field, constant learning and better economic standards are needed. This paper provides a comparative view of the progress made by India in the healthcare sector after the introduction of two major technologies such as cloud computing and big data. 2017 IEEE. -
Optimal location and parameters of GUPFC for transmission loss minimization using PSO algorithm
Transmission losses are one of the major losses faced by our power system. Reduction of transmission losses will benefit us by saving a large amount of power. The transmission losses can be reduced by placing FACTS devices in the power system. Among all the FACTS devices Unified Power Flow Controller (UPFC) and Generalized Unified Power Flow Controller (GUPFC) are the best. Incorporating the GUPFC in to the power system and placing it to the optimal location and setting its output to optimal values can reduce the transmission losses. This paper explains the way to locate the optimal location of GUPFC and finding the optimal setting using PSO algorithm to reduce the total transmission losses. Voltage variation is taken as the criteria for finding the location and PSO is used for finding the settings of GUPFC. This study is conducted on an IEEE 14-bus system using MATLAB software. 2017 IEEE. -
The secured data provenance: Background and application oriented analysis
It is with the advancement of overwhelming wireless internet access in mobile environments, users and usage data has become huge and voluminous on regular basis. For instance, the financial transactions performed via online by users are unsecure and unauthenticated in many contexts. Methods and algorithms exist for secure data transmission over different channels, perhaps lacks to achieve high performance with respect to the basic goals of security; confidentiality, integrity, availability at a considerable level. The origin of the data i.e., by whom the original transaction thread have been started, is the critical question to be answered while finalizing with the financial transaction. This concept of 'history of data' have attained good attention by the researchers from many decades at different application domains and is named as Data Provenance. However, provenance with security has got a little progress with research in the recent times especially in cyber security. This study focuses on the security aspects of data provenance with a unique approach in cryptography. The blend of these two technologies could provide an indigenous solution for securing the provenance of the related data. 2016 IEEE. -
A framework for smart transportation using Big Data
In the current era of information technology, data driven decision is widely recognized. It leads to involvement of the term 'Big Data'. The use of IOT and ICT deployment is a key player of the smart city project in India. It leads to smart transportation systems with huge amounts of real time data that needs to be communicated, aggregated, interpreted, analyzed and maintained. These technologies enhance the effective usage of smart transportation systems, which is economical and has a high social impact. Social applications like transportation can be benefited by using IOT, ICT and big data analytics to give better prediction. In this paper, we present how big data analytics can be used to build a smart transportation system. Increasing traffic and frequent jams in today's scenario are becoming a routine, citizens are facing various health issues due to the bad transportation systems such as high blood pressure, stress, asthma due to air and noise pollution. In smart transportation mobility can be easily implemented as most of the citizens use smartphones. It can be easily linked to smart traffic signals to achieve the objective of smart transportation. Smart transportation is a key component to attract companies as it leads to better services, business planning, support beneficial environment and social behavior. 2016 IEEE. -
Hybrid short term load forecasting using ARIMA-SVM
In order to perform a stable and reliable operation of the power system network, short term load forecasting is vital. High forecasting accuracy and speed are the two most important requirements of short-term load forecasting. It is important to analyze the load characteristics and to identify the main factors affecting the load. ARIMA method is most commonly used, as it predict the load purely based on the historical loads and no other assumptions are considered. Therefore there is a need for Outlier detection and correction method as the prediction is based on historical data, the historical data may contain some abnormal or missing values called outliers. Also the load demand is influenced by several other external factors such as temperature, day of the week etc., the Artificial Intelligence techniques will incorporate these external factors which improves the accuracy further. In this paper a hybrid model ARIMA-SVM is used to predict the hourly demand. ARIMA is used to predict the demand after correcting the outliers using Percentage Error (PE) method and its deviation is corrected using SVM. Main objective of this method is to reduce the Mean Absolute percentage Error (MAPE) by introducing a hybrid method employing with outlier detection technique. The historical load data of 2014-2015 from a utility system of southern region is taken for the study. It is observed that the MAPE error got reduced and its convergence speed increased. 2017 IEEE. -
A Survey on Enhancing System Performance of Wireless Sensor Network by Secure Assemblage Based Data Delivery
To provide secure data transmission in Cluster Wireless Sensor Networks (CWSNs), the challenging task is to provide an efficient key management technique. To enhance the performance of sensor networks, clustering approach is used. Wireless Sensor Network (WSN) comprises of large collection of sensors having different hardware configurations and functionalities. Due to limited storage space and battery life, complex security algorithms cannot be used in sensor networks. To solve the orphan node problem and to enhance the performance of the WSN, authors introduced many secure protocols such as LEACH, Sec-LEACH, GS-LEACH and R-LEACH, which were not secure for data transmission. The energy consumption in existing approach is more due to overhead incurred in computation and communication in order to achieve security. This paper studies about different schemes used for secure data transmission. We are proposing new methodology called IBDS and EIBDS that will increase the performance of WSN by reducing computational overhead and also increases resilience against the adversaries. 2017 IEEE. -
Parametrical variation and its effects on characteristics of microstrip rectangular patch antenna
This paper represents a brief description about design of rectangular microstrip patch antenna and its parameter effects in size, efficiency and compactness and parametric analysis in terms of return loss, bandwidth, directivity and gain by using same and different dielectric substrate materials with same and different thickness of rectangular microstrip patch antenna. The important parameters of patch such as L, W, r and h has its own impact in antenna characteristics. This parametrical impact is studied and verified. As thickness of dielectric substrate increases, the gain & directivity of rectangular microstrip patch antenna decreases and bandwidth increases. As r increases, the size of the antenna decreases but when height of dielectric substrate increase antenna size also increases. There will be always a compromise between miniaturization and other antenna characteristics. This antenna is designed for microstrip feed line technique and with center frequency (f0) at 4GHz. The parametric analysis is obtained by comparing the simulated results of rectangular microstrip patch antenna for different cases. The proposed antenna is simulated using HFSS tool at resonance frequency of 4 GHz. 2017 IEEE. -
A Model to Predict the Influence of Inconsistencies in Thermal Barrier Coating (TBC) Thicknesses in Pistons of IC Engines
LHR (Low heat Rejection) engines comprise of components that are modified with ceramic Thermal Barrier Coatings (TBC) to derive improvements in performance, fuel efficiency, combustion characteristics and life. In addition to engine parameters, the ability of TBCs (250 - 300?m thick) to function favorably depends on materials technology related factors such as surface-connected porosity, coating surface roughness, uniformity and consistency in coating thickness [1]. Right since the nineties, emphasis has been placed on the complexity of piston contours from a coating processing standpoint because the piston bowl geometry although appears simple, is actually quite complex. Robotic plasma gun manipulation programs have been developed to obtain uniform coating properties and thicknesses which are highly classified information. Thicker coatings offer better thermal insulation characteristics but in thickness deficient regions, TBCs may be as thin as ?30 microns. Applied via the 'line of sight' process, in the Atmospheric Plasma Spray System the coating thickness does not get developed adequately if the components comprise of contours with shadow regions. Thus the coating quality of a LHR engine heavily depends upon the shape of the engine components. This affects the barrier effects offered by the TBC and is reflected via generation of unwanted thermal gradients in the combustion chamber and on the external piston walls that adversely influence the engine performance. Extensive diesel engine cycle simulation and finite-element analysis of the coatings have been conducted to understand their effects on (a) diesel engine performance and (b) stress state in the coating and underlying metal substructure. Research work presented here involves the need and developmental efforts made via Computational Fluid Dynamics (CFD) to generate a model via ANSYS - Fluent simulation software that predicts the temperature gradient across TBCs of various ceramics and coating thicknesses. The geometric model was developed using the dimensions obtained using a CMM (Coordinate Measuring Machine) in Solidworks and the mesh was developed in Altair Hypermesh. The generated mesh consists of 221938 elements. Interfaces were created between the piston-bond coat-top coat surfaces. The Ansys-FLUENT CFD code solves the energy equation to find out the temperature drop in the piston for different combustion temperatures. Although most of the cavities presented are not rectangular, incompressible and steady laminar flow was assumed. The Semi-Implicit Method for Pressure-linked Equations (SIMPLE) was used to model the interaction between pressure and velocity. The energy variables were solved using the second order upwind scheme. In addition, the CFD program uses the Standard scheme to find the pressure values at the cell faces. Convergence was determined by checking the scaled residuals and ensuring that they were less than 10-6 for all variables. Two cases with combustion temperatures varying between 700 and 800 K were developed in Ansys FLUENT, wherein the thickness was deficient in the 'shadow' region. The model was validated via experimentation involving thermal shock cycle tests in prototype burner rig facility and measuring the temperature drop across the TBC as well. Non uniform coatings, leading to non-uniform drop in temperature across the thickness are most likely to affect the lubrication system of the engine and therefore the performance. Substantial efforts must be directed towards development of consistent and uniformly thick coatings for optimum performance of the LHR engine. 2017 Elsevier Ltd. All rights reserved. -
Cluster analysis for european neonatal jaundice
The objective of this paper is to propose and analyze clustering techniques for neonatal jaundice which will help in grouping the babies of similar symptoms. A variety of methods have been introduced in the literature for neonatal jaundice classification and feature selection. As far as we know, clustering techniques are not used for neonatal jaundice data set. This paper studies and proposes clustering techniques such as K-Means, Genetic K-Means and Bat K-Means for jaundice disease. To find the number of clusters elbow method is used. The clusters are validated using RMSE, SI and HI. The experimental results carried out in this paper shows bat k-means clustering performs better than K-means and genetic K-means. 2018, Springer International Publishing AG. -
Enhancement of coal nanostructure and investigation of its novel properties
Coal is a mineral and is extensively used as a solid fuel in developing nations and has a sizeable share in the global fossil fuel reserve. Utilization of this resource generates excess spoil and large volume of low grade waste to the environment. In recent years there have been serious research on enhancing its value and exploring the utility of this carbonaceous material to novel carbon materials. The Minerals, Metals & Materials Society 2018. -
A classified study on semantic analysis of video summarization
In today's world data represented in the form of a video are prolific and has increased the requisite of storage devices unconditionally. These video sets takes up a huge space for amassing data and takes a long time to ascertain the content that requires a higher cognitive process for content search and retrieval. The efficient method for storing video data is to remove high-degree redundancies and for creating an index of important events, objects and a preview video based on vital key-frames. These requirements imbibes the need to build algorithms that can concise the necessity of space and time for video and adequate approaches are to be developed to solve the needs of summarization. The three effective attributes for a semantic summarized video system are Un-supervision, efficient and dynamically scalable system that can help in reducing time and space complexities. Dimensionality reduction based on sub space analysis helps in plummeting the multidimensional data into a low-dimensional data to enable faster feature extraction and summarization. In this paper we have made a study and description related to several summarization methodologies for video's that are available. 2017 IEEE. -
DNA based cryptography to improve usability of authenticated access of electronic health records
The quality of health care has been drastically improved with the evolution of Internet. Electronic health records play a major role in interoperability and accessibility of patients data which helps in effective and timely treatment irrespective of the demographic area. The proposed model is to ensure and monitor maternal health during pregnancy and to create awareness alerts (options include messages, voice alerts or flash the system) based on the individual health record. The system aims to prevent maternal death due to medical negligence and helps to make recommendations to prevent future mortality based on medical history and take appropriate action. Authentication is a critical aspect considering the trade-off between usability and security whereas data breach and related cybercrime are major concerns in health care. The proposed model uses DNA based authentication techniques to ensure usability and confidentiality of electronic data, Aadhaar to prevent unauthorized access to patients data in case of emergency without affecting availability. 2018, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering. -
PCRS: Personalized Course Recommender System Based on Hybrid Approach
The traditional system of selecting courses to carry out research work is time consuming, risky and a tedious task, that not only badly affect the performance but the learning experience of a researcher as well. Therefore, choosing appropriate courses in seminal years could help to do research in a better way. This Study presents a recommender system that will suggest and guide a learner in selecting the courses as per their requirement. The Hybrid methodology has been used along with ontology to retrieve useful information and make accurate recommendations. Such an approach may be helpful to learners to increase their performance and improve their satisfaction level as well. The proposed recommender systems would perform better by mitigating the weakness of basic individual recommender systems. 2018 The Authors. Published by Elsevier B.V. -
Design considerations of an inductive sensor for segmented mirror telescopes
The Segmented mirror technology has become natural choice for any optical telescope larger than 8 meter in size, where small mirror segments are aligned and positioned with respect to each other to an accuracy of few tens of nanometer. Primary mirror control system with the help of edge sensor and soft linear actuator maintains that alignment which changes due to gravity and wind loading. For any segmented mirror telescope edge-sensor plays very critical role. It should have very high spatial resolution (few nanometer), large range, multidimensional sensing, high temporal stability as well as immunity towards relative change in temperature and humidity. Though capacitive sensors are widely used for this purpose, however, their inherent sensitivity towards humidity and dust make them unsuitable for telescopes operating at humid low altitude regions. Whereas, inductance based sensors, working on the principal of mutual inductance variation between two planar inductor coils, produce promising results in such a situation. Looking at stringent requirements, design and development of a planar inductive sensor is a challenge. As a first step toward sensor development, we have explored the design aspects of it. The inductive coils are first simulated and analyzed using electromagnetic FEA software for different coil parameters. The design considerations include optimization of coil parameters such as geometry of coils, trace densities, number of turns, etc. and operational requirements such as number of degree of freedoms to be sensed, range of travel, spatial resolution, as well as required sensitivity. The simulation results are also verified through experimentation. In this first paper we report the design and analysis results obtained from FEA simulations. 2018 SPIE. -
Monitoring nyiragongo volcano using a federated cloud-based wireless sensor network
Current Nyiragongo Volcano observatory systems yield poor monitoring quality due to unpredictable dynamics of volcanic activities and limited sensing capability of existing sensors (seismometers, acoustic microphones, GPS, tilt-meter, optical thermal, and gas flux). The sensor node has limited processing capacity and memory. So if some tasks from the sensor nodes can be uploaded to the server of cloud computing then the battery life of the sensor nodes can be extended. The cloud computing can be used both for processing of aggregate query and storage of data. The two principal merits of this paper are the clear demonstration that the Cloud Computing model is a good fit with the dynamic computational requirements of Nyiragongo volcano monitoring and the novel optimization algorithm for seismic data routing. The proposed new model has been evaluated using Arduino-Atmega328 as hardware platform, Eucalyptus/Open Stack with Orchestra-Juju for Private Sensor Cloud connected to some famous public clouds such as Amazon EC2, ThingSpeak, SensorCloud and Pachube. 2017 IEEE. -
An improvised grid resource allocation and classfication through regression
The resource allocation is one of the important mechanisms of grid computing, which helps to assign the available resources very efficiently. The one of the issue of grid computing is fixing the target nodes during the grid job execution. In existing method, resource monitored data are collected from grid then jobs are allocated to the resources based on available data, through regression algorithm. In this method total execution time of an application and run time of jobs should be high. The proposed method mitigate running time by classify the resources in the data collected from grid based on dwell time using novel classification algorithm. It reduces the jobs run time and fit the best available resources to the jobs in the computational grid. 2017 IEEE.