Emerging Trends in Electrical, Communications, and Information Technologies

With raising patient-to-nurse ratio in India, traditional patient monitoring system (drip systems) for intravenous infusion is a stressful challenge. The challenge arises due to the requirement of continuous monitoring of intravenous infusion with the aid of nurse or guardian. Any mistake or delays in tracking in this regard can cause diverse problems including reverse flow of blood upon entire draining of bottle, overdose of medicine or excess infusion of electrolytes and saline. To conquer this hassle, this work proposes a prototype to monitor drip infusion of patients where the status of the drip infusion is monitored using a sensor circuit and actuation as a voice alert to the nurse’s android unit. Along with this functionality in the proposed prototype, a module to handle the status of Electrocardiogram (ECG) signal which is obtained from ECG sensors is incorporated. The ECG readings can be continuously monitored with the help of the waveforms observed on the android unit. These provisions incorporated makes ease for the nurse/guardian in monitoring the drip infusion and ECG readings of the patients. Key sets are also provided to the patients to help them in the time of emergency where a voice alert is sent to the nurse’s android unit requesting for the service. Since all these functionalities have different levels of significance with respect to the nurse, this work provides a priority based service. Thus the work provides an effective way of monitoring the patients and utilizing man hours of the nurse efficiently.

This paper proposes a computer-based method to support medical science students in the detection of skin diseases accurately. It uses the Gaussian filter and applies the 2-D Wavelet Transformation and-2-D Inverse Wavelet Transformation techniques for the aim of image preprocessing in order to get rid of the noises, and segment skin cancer lesion by fusing edge-based and region-based segmentation approaches. The next step consists of applying Morphological filters to get rid of external noise and the interior one of the object, which remained in the segmented image as well as to soften the edges. Then, use the k-Nearest Neighbor (kNN) classifiers. The desired goal of this paper is to test the accuracy of the following proposed segmentation algorithm. The proposed method is tested on 133 images whereas 78 are malignant melanoma skin cancer type and 55 benign ones. This approach allowed detecting two different Pathological cases of skin lesions images which are malignant melanoma and benign nevi. The segmentation achieved 97.75% of accuracy for these two types of skin cancer lesions.

Although all databases frameworks let us make conventional (crisp) searches, there are only a few of them that take into account some flexible, fuzzy, expressive criteria. The few of them that provide some of these searching characteristics are restricted to a particular database format, as FleSe that is devoted to search in a flexible way over Prolog databases. We have extended FleSe framework by an extraordinary feature that allows users to query various conventional and modern databases such as Prolog, CSV, XLS, XLSX, MySQL, and MongoDB or JSON in a fuzzy way. We have developed an adaptable and configurable platform for it so that any user can personalize at run-time. The fuzzy searching criteria can be created and added in a very user-friendly way, so that any user can upload his/her conventional (crisp) database, define the fuzzy search criteria that he/she is interested in and search at the database flexibly and expressively using concepts as similarity, fuzziness, qualification, and negation.

Color helps to understand the semantic information of the image more accurately and reveals a lot more details which grayscale images cannot. By looking at an image, humans can automatically segment different objects present in an image making it easier for us to color an image. We propose a completely automated system to colorize grayscale images which learns to segment and color images in a realistic manner. We leverage the recent advancements in deep learning, Generative Adversarial Networks and improved cost functions, to overcome the problems of traditional Convolutional Neural Networks with image colorization. Given the unconstrained nature of the problem, we propose this algorithm to make a colorization model that achieves realistic colorizations. We have experimented different deep network architectures with various training algorithms and cost functions to come up with this network where we can clearly see realistic colors for given gray scale image and differentiate the characteristics of generative adversarial network from a traditional convolutional neural network.

CMOS technology and its sustainable scaling have been the facilitators for the design and modeling of computers that have been inciting a wider range of applications. A broad dependence on technology, voluminous data, and rising processing needs have imposed the technology-computer architecture duos to suffer from serious hardships that hinder transistor utilization and advertise the need for new devices. This stimulates novel architectures equidistant to novel technologies. With zillion advantages like tiny size, high power tolerance, remembering capacity, huge retention, high persistence, low reads and writes, 3D design ability, tight fit with portable devices, made memristor a breakthrough technology for all ongoing data-centric applications. This paper review about memristor In-Memory computing capabilities, and its potency in Combinational logic and propose an architecture that suits for real-time Image processing applications.

With the advent of technology, the impact of smartphones on business, health, psychology, education and social relations has increased. This paper presents germinal results of a study conducted to not only analyse but also predict the negative impact of smartphone usage. A survey was conducted in two parts, one for identifying impact of smartphones on academics of student and other to identify the effect on lives of adults who have finished their education. We used Natural Language Processing to conduct sentiment analysis on answers to subjective questions. Supervised Machine learning algorithms were used to conduct the analyses of impact of smartphones on academics whereas Unsupervised Machine Learning Algorithms were used to analyse the survey on adults. Neural Networks model was trained and tested on both the survey data. The results of these algorithms were compared and analysed to find which algorithm is better in which situations.

Water retention on magic square is a very recently introduced variation of magic square problem which has attracted a lot of attention from the research community over the years. Different approaches have been used to tackle this highly combinatorial optimization problem. In this paper, we have proposed an improved constraint-based local search approach that remedies all the identified shortcomings of the state-of-the-art technique. Several new methods such as greediness reduction technique, incremental calculation of the objective function and solving cycling problem through similarity checking have been incorporated within the proposed local search approach. Experimental results show that our proposed algorithm performs better than the existing technique with regards to solution quality and execution time.

Online Health Community (OHC) services are mostly employed for resolving problems of people with chronic diseases. OHCS also provide social support in addition with solutions to the problems. Social Support is of two forms: Emotional Support, Informational Support. The objective of this work is to analyze online healthcare forum and find the degree of support provided by the forum. In this work, 1200 discussions have been extracted from POZ, an Online HIV Forum. Initially the type of support groups has been identified by application different semi supervised approach. As a result, it has been identified that emotional support is more in the messages of the forum. Further regression has been applied to quantify the amount of emotional support in the discussion of the POZ forum. Various kinds of regression algorithms have been applied to model the degree of support in the messages.

In Wireless Sensor Network (WSN), the lifetime of sensor nodes strongly depends on battery power. Clustering provides an effective way for extending the life time of WSN by efficiently transferring data packets from source to sink. LEACH and PEGASIS are two popular hierarchical based routing protocols in WSN. LEACH goes through some limitations due to its cluster-based architecture, while PEGASIS lacks with dynamic nature. In this paper, we introduce an energy efficient routing protocol, named it as Pegasis-LEACH using Uniform distribution of cluster heads (PLEACH-U). The proposed method, PLEACH-U, addresses the hotspot issue and also the aforesaid issues of LEACH and PEGASIS. We show the efficacy our proposed routing protocol using simulations.

In early days the concept of Internet of Things (IOT) was focused on industrial automation only. But as the technology evolves people use IOT in different areas like commercial, health, residential and transportation. It helps to bring all individual devices on a common platform so that controlling and monitoring of individual device from centralized system is possible. Smart home system proves the IOT concept very finely. A home can be called as smart if it is remotely controlled and monitored, automated, secure and where home appliances are smart enough to change their status. This paper presents an Android mobile application implementation of smart home and prediction of electricity energy consumption which uses Wi-Fi and GSM as a communication media to communicate with Beagle Bone Black, the central processing system and for data analysis simple linear regression analysis is used. Smart home system is mainly concerned with the Automation and Security followed further with energy management and prediction of electricity energy consumption.

In this modern era, the rapid improvement of internet technologies makes the user comfortable in generating the data in an easier way. To analyse the user-generated data for classifying sentiment polarity into one of the three categories namely positive, negative and neutral, sentiment analysis is required. Sentiment analysis is the computational study of user opinions, moods, sentiments and other subjective elements of the text. Sentiment analysis can be implemented using lexicon based approaches and machine learning approaches (Bnadhane et al. in Procedia Comput Sci 45: 808-814 (2015), [1]). Sentiment lexicon can be used to maintain terms and their respective sentiment values. But, the existing sentiment lexicons cannot handle improved internet slang data and missing data. Hybrid lexicon can be generated by combining sentiment lexicon with domain-specific sentiment-bearing terms. In this work, we analyse and find the need for improving sentiment classification with derived knowledge from domain-specific contextual analysis and domain adopted lexicons. Finally, the analysis shows the need for the proposed sentiment classification to handle missing data.

With an alarming increase in pollution level in various parts of the world, the study of air pollution monitoring has become one of the most demanding areas in national and international arena. The paper makes an attempt to serve as a concise guide in providing basic understanding of types of remote sensing, sources of satellite data, geospatial data analysis, aerosol optical depth for air pollution monitoring. The paper gives important references on the datasets and available formats, prerequisite tools required for processing and analysis of the data. The futuristic insights finally discuss the role of machine learning in correcting AOD values as well as filling gaps for missing aerosol values when compared to ground based sensors.

Power quality plays an important role while transferring power to maintain uninterrupted and continuous supply to the consumer. Voltage sags, voltage swells, flickers, etc., are the common problems which degrade the power quality. So, this paper presents one of the means to overcome this, by including FACTS devices like ZSI (Impedance source inverter) based STATCOM in the network. The device is controlled using proposed unipolar and bipolar PWM techniques. The proposed methods can be used to overcome the disadvantages of the existing devices. Simulations of the proposed circuitsare shown and it is done using MATLAB/SIMULINK software.

This paper deals with the investigation on renewable energy potential areas in the union of Puducherry for the development of the standalone Hybrid (PV/Wind) electrification system. Optimization cum sensitivity results and ranking process are the basic evaluation parameters for this investigation. The various climatic zones identified (Puducherry, Karaikal, Mahe and Yanam) are located in the union territory of Puducherry region, India. A typical consumer demand profile was created for the selected zones on the basis of the database relating to the local distribution agency. The renewable resource availability ranges were obtained from NASA’s surface mythology database. HOMER Pro software has been used for estimation of the different feasible hybrid configurations. Region-wise winning configurations were treated into sensitivity analysis through different rates of diesel price variables. The investigations indicate Yanam Zone as a highly potential area for implementing the standalone hybrid electrification system among the other climatic zones of Puducherry union. The sensitivity analysis proves renewable energy rich area system holding the top rank, in terms of the best Techno-Economic Eco friendly electrification system. The system maintains the renewable fraction as 0.99 with a high quantity of power production and least Cost of Energy with reduced Net Present Cost (reduced into half value over normal system) and low green gas emission.

To maintain the voltage stability in the power system it is necessary to balance the flow of real and reactive power which can be achieved by the compensation techniques in the power system. Reactive power plays an important role to maintain the voltage stability in the power system because the flow of reactive power is depends upon the voltage magnitude, in case of voltage magnitude dips the unbalance of reactive power flow will occurs which results in overall instability of the power system So, there is need to design an model which can compensate the reactive power in the system to maintain the system voltage. STATCOM is one of the FACTs device used to maintain the flow of reactive power and hence, voltage stability in power system (Hingorani and Gyugyi, Understanding FACTS: concepts and technology of flexible AC transmission systems, [1]). This paper describes the mathematical modeling with inherent controlling capability of STATCOM helps to compensate the reactive power flow in the system which maintain the voltage stability. This will approach to the DFIG based wind farms using STATCOM also had been applied for offshore wind power plants to satisfy the grid codes (Tanaka et al., Reactive power compensation capability of a STATCOM based on two types of modular multilevel cascade converters for offshore wind application, 2017, [2], Ushkewar and Bodke, Compensation of reactive power in DFIG based wind farm using STATCOM, 2018, [3], Pereira et al., STATCOM to improve the voltage stability of an electric power system with high penetration of wind generation, 2016, [4]).

This paper presents a FEM analysis on impact of temperature variation on electrical parameters in a single phase shell type transformer. The designed transformer model is supplied by a constant current source. The open circuit voltage and core losses have been measured at two different temperatures of 300 K and 600 K respectively. From the analysis it is observed that the secondary voltage losses are increased with respect to temperature at a constant frequency of 50 Hz. The FEM studies are carried out by using QuickField software with more than 2.8 K nodes to improve the accuracy of measurements.

Distributed generation is the promising solution for most of the problems faced by Indian radial distribution system like high losses, low end voltages and peak demand. Determining the optimal location and optimal size is one of significant issues in the placement of distributed generation in the distribution system. This paper presents two methods, an Analytical method and CSA (Crow Search Algorithm) for the implementation of distributed generators (DG) on the radial feeders of the distribution systems. The analytical method is so simple and requires load flow solution only twice for determination of site and capacity of DG simultaneously. These methods determine the locations of DG to achieve minimum losses in the system. The main aim of this paper is to know the effect of load modeling and time varying loads on Distributed Generators placement. Distribution system loads are highly voltage sensitive and they are varying continuously. The methods are tested on IEEE standard 69-Bus system and the consequences are discussed and presented. The proposed methods have been implemented using “MATLAB” program and are capable of performing on a radial distribution system of any number of buses and laterals.

With the development of distributed generation (DG), the radial distribution systems are now being transformed to interconnected systems. So, it is essential to provide faster protection system to assure reliability. In this paper, a proposed strategy involving dual setting directional over current relays (DOCR) is used to design protection system. These relays are provided with standard inverse characteristics for over current elements and are designed to operate differently in forward and reverse directions based on the direction of fault current. So, the coordination problem with in the elements is designed with objective of minimizing overall operating time of relays. The optimization problem is taken as constrained non-linear programming problem. The proposed scheme is tested and compared with conventional approach, where relays are equipped with unidirectional settings. Both schemes are tested using the IEEE-14 bus test system and is designed to use synchronous generation for DG. The proposed scheme is found to be better and act faster than the conventional scheme, thus providing a quicker and reliable protection.

This paper demonstrates charging and discharging analysis of Li-Ion battery by the simulation model. It is present most commonly used rechargeable battery for Electric Vehicular Technology (EVT) in the year of 2016–17 by various companies at various power ratings. The desired parameters of the Li-Ion battery is used as a storage device for EVT and adopting parameters of the Li-Ion battery to the AC drives are tabulated and demonstrates. The Li-Ion battery results to the IM and PMSM drives of the different operating modes are discussing. Performance analysis of the battery parameters such as voltage, current, State Of Charge (SOC), and power is observed with the help of the MATLAB/Simulink platform for variable speed operation. The combination of Li-Ion battery and PMSM drive is suitable to the EVT, due to regenerative operation, less power consumption, high efficiency and high performance.

Fractional order PI Controller studies has been highlighted recently and it accepted as a best fit to conventional IOPI Controller. Still, FOPI Controller brings more tuning parameters into the restructured power system network. To analyze the potential of proposed system, FOFPI (Fuzzy + FOPI) Controller is placed to resolve the Load Frequency Control problem in a power system. The fuzzy logic control is non-linear and adaptive nature and this technique relies based on qualitative control rules and membership functions. Dynamic performance of the system is examined by area control error and error criteria. The FOFPI Controller designed in MATLAB or Simulink for the LFC problem shows better responses.

In this paper, the fabrication and characterization of a current mode, primary side controlled Flyback converter is carried out. Furthermore, the converter design specifications for Discontinuous Mode Conduction (DCM) of the converter are derived and used for simulation and designing purpose. The simulated results are then verified with the characterization results using a 30 W street light.

In recent times boost converter with seven-level inverter is a best choice of PV system with ac load. For elevating the DC level a reboost technology was used. DC can be converted into the AC with employment of seven level inverter. The very purpose of reboost is to enhance voltage gain. The purpose of the recommended closed loop Reboost Seven Level Inverter fed Induction Motor (RBSLIIM) system is to enhance the dynamic response of RBSLIFIM using two PI controllers. Simulink models are developed for PI and PI-PI controlled RBSLIIM systems. The results of PI and PI-PI RBSLIIM scheme point out that the dynamic behavior of Two loop PI is superior to PI controlled RBSLIIM system.

DC devices are gaining popularity in the present era, because of its reliability, efficiency, and ease of connection ReS because of its inexhaustible nature and abundant apply, are gaining. To harness DC supply from these sources DC/DC Converters (DC Conv) are required. But the DC supply is intermittent in nature from renewable energy sources (ReS), because of many dependencies like solar radiation for solar PV, wind velocity for wind mill, manure for bio-gas plant and gravitational pull of moon for tidal wave plant thus, we need multiple sources connected in proper series and parallel combinations to get required sustainable supply. Beside this DC micro-grid itself involves these disadvantages like it needs private DC distribution lines, protection of DC system is more difficult, load in DC systems needs power supply of higher efficiency. The paralleling of these DC Conv provides a pass way when load current exceeds a single module’s rating and helps when greater fault tolerance is required but it involves problems like power losses, circulating current, to system reset or shutdown or to even system damage. The problem here can be resolved by application of adaptive method as presented in the following paper.

Solar type distributed generation (DGs) becomes popular and extensively used by consumers as well as power producers on radial distribution systems. The presence of solar type DGs on radial lines affecting the switching operations of under load tap changers (ULTC) and shunt capacitors (SCs) in addition to power loss. This paper proposes a novel method in which reactive power of solar type DG and voltage controlled devices coordinated with particle swarm optimization (PSO) algorithm with the help of forecast load. Problem formulated as multi objective function with switching operational cost and power loss cost. Proposed method tested on 10 kV, 16 buses practical system in Matlab environment and results compared with conventional method to demonstrate the effectiveness without failing the grid conditions.

The one of most compelling challenges in the recent time is finding a way to encounter global and national energy demand with reducing harm to the environment. Those challenges can be encountered by the application of biomass gasifiers. The utilisation of biomass gasifiers are the vital source outcome of energy in various areas of the world, especially for remote areas, where electricity transmission is not possible by the supply of high-quality fossil fuels. Gasifier application plays key role in biomass utilization same as a renewable power resource by the gasification process; gasification is the thermo-chemical method by which carbonaceous (hydrocarbon) ingredients (like coal, petroleum coke, and biomass) can be transformed into synthesis gas or producer gas. Design of biomass gasifier is determined by the category of source fuel utilized and the portability of gassifier. Various categories of gasification arrangements have been established out of which some are commercialised. In Indian market, commonly downdraft type of gasifier is utilized because of the application of mechanical mode. The biomass gasifier application is also appropriate for the thermal type of energy mode. It will replace the abundant use of fossils fuels like petrol, diesel, naphtha oil, etc. This manuscript discusses about type of gasifiers used, their application, drawbacks associated with biomass and statistics of renewable in India.

This paper discuss the comparative analysis of the Flying Capacitor Multi Level Matrix Converter and the H-Bridge Multi Level Matrix Converter topologies (replacing the conventional two stage converter and simple matrix converter) connected to a DFIG machine feeding the rotor from the grid to increase the efficiency of the machine. The THDs are compared with the interconnection of the DFIG machine to the grid with flying capacitor and H-Bridge multi level matrix converter. The complete analysis and graphical representations of the voltage and currents of the DFIG machine stator are shown with FFT analysis of current waveform in MATLAB Simulink software.

In the study the modified Elephant Herd Optimization (EHO) algorithm is developed and designed by utilizing the distributed power flow controller (DPFC) for improving power quality (PQ) in smart grid (SG). The modification of the EHO algorithm is performed based on the Recurrent Neural Network (RNN) algorithm. The novelty in this proposed study is the enhancement of the PQ in SG from the disturbances occurred power system controller utilized the DPFC. Initially, the proposed system power flow is evaluated and the Multi Wavelet Transform (MWT) is employed to feature extraction process of the power parameters for PQ disturbances. If the output signal has any disturbances then the output signal is controlled by the proposed controller based DPFC. The proposed algorithm is employed to retain the sustained DC-link voltage of DPFC by controlling the output voltage to improve the PQ. Then the implementation process is made by the Matlab/Simulink simulation platform. The capability of the proposed system is based an evaluation of the output response and the comparative analysis with some different techniques like PSO, BAT and CFA-PSO algorithm.

Now a days the Energy change and environmental troubles like air pollution and global warming are increases. To mitigate these troubles the renewable energy sources such as photo voltaic energy, Wind energy and etc. are introduced. This paper presents the analysis of day and night utilization of PV Solar farm as STATCOM to meet the load demand without Power Quality disturbances. The PV Solar farm produce power during day time and made completely idle during night time. During day time the inverter is used for real power generation and during night time it is used to meet the load demand with enhanced efficiency by controlling Voltage, Current, Real, Reactive powers and with Damping controls. For the analysis of PV-STATCOM performance it is proposed a hybrid algorithm which includes the principles of CSO and PSO algorithms. The CSO algorithm is used to achieve the control of above parameters and PSO algorithm is used to enhance the position of roosters of CSO algorithm. The Control Strategies of Voltage, Current, Real and Reactive powers were validated through MATLAB/Simulink Platform.

Optimal tuning of Power System Stabilizers (PSSs) parameters using Grey Wolf Optimization (GWO) algorithm is presented in this paper. Selection of the parameters of power system stabilizers which simultaneously stabilize system oscillations is converted to a simple optimization problem which is solved by a Grey Wolf Optimization (GWO) algorithm. The efficiency of the proposed method has been tested on two cases of multi-machine systems include 3-machine 9 buses system. The proposed method of tuning the PSS is an attractive alternative to conventional fixed gain stabilizer design as it retains the simplicity of the conventional PSS and at the same time guarantees a robust acceptable performance over a wide range of operating and system condition.

This paper proposes a novel method (PSOMSF) to unified power flow controller (UPFC) for dynamic stability enhancement of single machine infinite bus system (SMIB). This method consists of multi stage fuzzy damping controller and particle swarm optimization (PSO) method used for fixing the fuzzy bounds. Two stages of fuzzy controllers are designed in such a way the first fuzzy controller exhibits PI behavior and second fuzzy controller exhibits PD behavior and the combination exhibits PID behavior. PSO adjusts the bounds of fuzzy sets to get minimum error in frequency deviations and hence to improve the dynamic stability. The proposed method designed in Matlab environment and tested SMIB system. Effectiveness of the proposed controller is compared with conventional power system stabilizer (PSS) and genetic algorithm based multi stage fuzzy damping controller (GAMSF).

Designing an electrical power distribution system requires many stages of planning and rigorous calculations. One of the vital, integral parts of the planning process is selection of the conductors for design and upgrade of the distribution system. An ideal conductor set should minimise the combined investment cost of conductors and the annual cost of distribution system energy losses while complying the thermal capacity of conductors, system voltage profiles limits and provide best voltage profile for farthest end customers. Proposed method aims to reach the best optimal conductor selection for existing distribution system by solving the optimisation technique using the teaching learning-based optimisation technique with less parameter control. Simulations are executed and discussed by calculating the customer loss allocation before and after the optimal conductor selection in the distribution system. The examined results show the efficacy of the proposed algorithm to satisfy the objective function and constraints.

The paper illustrates analytical approach to integrate a hybrid PV-ESS unit for lowering energy losses and increasing voltage profile of distribution network and for optimal sizing and time scheduling of charging/discharging of Energy Storage System (ESS) which is integrated in distribution networks. The conceptual design and modeling of solar-PV unit, ESS unit and hybrid PV-ESS unit has been introduced to get individual unit sizes from hybrid PV-ESS unit. This approach makes non-dispatchable PV unit into a dispachable unit with a hybrid PV-ESS unit. Multi objective index, MOI based analytical terms have been developed to find the optimal size of hybrid unit (PV-ESS). This analytical approach was tested on IEEE-33 test system to obtain the performance characteristics: system losses, annual energy losses and voltage profile of distribution network with hybrid PV-ESS unit and to get optimal size of Energy storage system (ESS) and schedule of charging/discharging energy during a day cycle.

With the cumulative addition in power demand, interconnection of power system is crucial to route the power station operate in specific limitations to encounter the power burden optimally and also diminish the rate of active power generation. One of the objectives for the steam run power plants is to reduce fuel consumption by assigning source power to every component (economic dispatch) focus to equal and unequal limitations optimally. This importance is due to power savings. ELD is the utmost significant issues to be resolved in the process and forecasting of a electrical system. This work presents an approach of Genetic Algorithm (GA) for finest load scheduling of steam run power plants to catch the universal optimum dispatch clarification. The genetic set of rules centered best approach explains the ELD problem. The core indication behind genetic set of rules is, all units should allocate the essential power load at lowest coal cost, though sustaining the coordination limitations. Simulation is executed on assessment system with six generators using Mat-lab. The results are shown for 24 h loads with optimal generation of 6 generators including transmission losses and cost of real power generation.

Generally, wind energy resources have characteristics of randomness and uncontrollability, which leads to uncertainty, intermittency and volatility of its outputs Therefore, great challenges in coordinating it with a large hydrothermal system. In this article, solves multi-objective short-term hydrothermal scheduling (MOSTHTS) problem integrated wind power generation using an effective and specific parameter less algorithm of Non-dominated Sorting Teaching Learning Based Optimization (NSTLBO) algorithm. The problem has been modelled in the form of multi-objective functions which includes fuel cost of thermal and wind generators, transmission loss and environmental emissions such as NOx, SOx and COx with various constraints of hydrothermal and wind systems. The interaction of the present NSTLBO algorithm is to decrease the operating cost of thermal and wind generators, transmission losses and different kinds of emissions. By applying this algorithm a set of non-dominated solutions are created. A fuzzy decision making approach has been involved on these solution in order to identify the best comprise solution among the group of solutions. The practicability of the proposed approach has been demonstrated on a sample test system which consists of four hydro, four thermal and two wind units. The experimental finding of this method has been compared with that of well established techniques in order to validate the performance of the test results.

Now a day’s, population and their requirements are increasing rapidly. Hence, enhancement of reliability of electrical components in power system also increases. In wind power conversion dc capacitor plays an important role to minimize harmonics, ripple currents and voltage spikes. Hence, improving the life span and reliability of a capacitor is more important. In literature, back to back converter has been used for improving life time of a capacitor. Apart from this PI controller is also used to improving the voltage profile. In a case study 1.2 MW Permanent Magnetism Synchronous Generator (PMSG) wind turbine is considered and real field mission profiles are transformed (i.e. wind speed and ambient temperature) into thermal and current stresses to estimate the reliability of dc-link capacitor. In this paper, Maximum Power Point Tracking (MPPT) controller for DC-DC Booster converter having the Power Signal Feedback is proposed to get better reliability or life time of a dc-capacitor. In addition to this, reduction of ripple current and losses is also proposed. The proposed method is implemented in MATLAB simulation software.

A Two layer hemispherical dielectric resonator antenna (HDRA) fed by a coaxial probe is rigorously analyzed here. The method of moment technique and Green’s function is used to obtain the probe current from which the input impedance of the DRA is calculated. The magnetic frill source model is considered. The piecewise sinusoidal (PWS) expansion mode is used and the results are compared. The Dielectric layers Permittivites and layer thickness between the outer and inner hemisphere are optimized for broadband operation of the coaxial probe fed DRA. Frequency tuning of the antenna structure is demonstrated, which maintains the broadband characteristics. Probe location (centered and offset) and length of the coaxial probe are optimized to obtain better impedance bandwidth and stable radiation pattern. The radiation characteristic of the antenna is also investigated in this research work. Simulations were carried out using HFSS v12.0 and it is observed that better impedance bandwidth and stable radiation pattern are obtained across the frequency range between 4–11 GHz.

As the networks on chips is used for designing the multi-processor system on chips, this platform have been typically guaranteed for hard real time property, and for the use of shared resources in a network. The service guarantees has to be provided by the network with respect to bandwidth and latency for a different communications flow. Thus message passing communications between the processor cores are implemented for the network on chip. The TDM is used for controlling the communications over the structures of router, links and network interface. The two main contribution of area efficient are (i) The TDM schedule with combined asynchronous router and (ii) The micro-architecture of NIs. In concert with the design resulted with the transforming the data in a pipelined manner which means transmitting the data from the local memory of send core to the local memory of the receive core, without using any dynamic attributions, buffering and local synchronization. The router also uses the two phase bundled data hand shake latches based on the mousetrap latch controller and it is extended with the gated mechanism for reducing the energy consumption. Network interface is used for integrating the DMA and the TDM functionalities. The dual ported local memory is used for avoiding buffering, flow controls and synchronization. Thus obtained result is verified with respect to area, power and gates.

To design cost and energy efficient memory cell various designs are introduced in recent days. The power consumed by the memory cell array is reduced at nanometer scale but increases if frequency of operation increases. The search operation consumes more power and to reduce it TCAMs were introduced which compares entire data with search bit in single clock cycle. In past TCAMs were designed using MOSFET devices. These devices suffer from second order effects below 45 nm. This paper presents a FinFET based TCAM cell array designed in 14 nm technology. The memory device proposed works faster, has Low Matchline Voltage Swing and Search Line Activity. The proposed FinFET design is efficient when compared to CMOS methods where a 93.3 and 96% less power is obtained. An energy reduction of 10.97 and 60.08% is observed when compared to existing method 1 and 2 respectively.

Floating-point arithmetic units form the backbone of the state-of-the-art digital signal processing algorithms. Low power and area efficient design is always a key requirement for applications that use these algorithms. This requirement is more relevant for computationally intensive jobs that use higher-order multipliers. This paper attempts to study the possibility of addressing this issue using vedic arithmetic based floating-point unit. Vedic mathematics is an ancient Indian mathematics system that has come back to prominence in the last century. In this paper, we design a IEEE 754 single precision floating-point multiplier with the integer multiplication being carried out in a vedic mathematics style using different sutras. Nikhilam and Urdhva Tiryagbhyam sutras and their combination are used to design the same. This implementation is compared with conventional implementations using Booth and array multipliers. The designs are simulated using Verilog and synthesized using gpdk 90 nm technology. The results show that vedic multiplier based design gives competing results for multipliers of larger sizes. Low power and area efficient design is achieved for higher order multipliers when the design is based on the combination of Nikhilam and Urdhva Tiryagbhyam sutras. Thus for DSP applications using large multipliers, it is envisaged this approach of vedic multiplier design would lead to more efficient system implementations.

Health care organizations are adopting IoT Cloud with wireless sensor networks that is beneficial, especially when administering the condition of a greater number of patients and their resulting data storage are taken into account. Considering the case of patients fed with Intravenous [IV] fluids in Intensive Care Unit [ICU], it is essential to administer the flow rate and fluid level of gravity fed bottles in real-time, either by an attendant or duty nurse allotted to that bed. Manual negligence in such a scenario may lead to the death of patient, in the worst case. In this paper, a new design for IV bottle is suggested and a wireless sensor network [WSN]-based liquid level and drop count measuring system is developed. The system is built around the Texas Instruments CC3200, Ultrasonic sensor HC-SR04, LM35 temperature sensor, and GSM SIM900A. The proposed system can also be used to track the status anywhere wirelessly by Wi-Fi and Cellular systems. Thus, possible danger to the patient such as blood loss, back flow of blood due to negligence of nursing can be overcome by monitoring to fluid level and flow-rate. Whole day, 24 h. It is possible to extend the work for private cloud of a nursing home or hospital to maintain secrecy.

Modern medical imaging studies have a defiance problem to detect the abnormalities that lead to early diagnosis of the disease. Medical image processing deals with the detailed study of human organs and extracting the discernible information called ROI. In medical images even a minute portion of the image has a great concern in diagnosis and also has chances for wrong prophesy. Image segmentation is highly referred technique for exact separation of image for the accurate diagnosis. In this paper segmentation of brain image is implemented using morphology and segmentation operators to simplify image description, distinguishing the quality, perceptibility and cognizability of the image. The image segmentation operators like Sobel, Prewitt, Gaussian, Average, Laplacian, LoG and Unsharp are applied on DICOM brain image having tumor. The results are evaluated considering the ROI pertaining to tumor. This paper submits a comprehensive report of the techniques to perceive brain image segmentation and find out the abnormality. These results exemplify the segmented image and the best suitable operator for brain tumor segmentation and the ROI. Exact identification and separation of tumor helps for quality of appearance and classification of malignancy for the possible treatment.

Majority of the pulmonary diseases and their identification rely on geometric progression of lung spaces. Most common types of lung diseases include abnormalities categorised as Interstitial lung diseases (ILD) like sarcoidosis, idiopathic pulmonary fibrosis (IPF), malignant nodules, extrinsic allergic alveolitis (EAA) and honey comb structures from the infectious disorders is a very difficult task for diagnosis. For clinical practices, images are accumulated and stored in digital representation like MRI and CT to facilitate corresponding diagnosis. Some of the physicians can’t provide inadequacy in image parts which are known as (ROI) region of interest. Researchers converse at focusing on ROI coding to guarantee the use of multiple and randomly shaped ROI’s in image depicting the importance of ROI confining the background regions that can be exhibited by varying the levels of quality. This paper highlights the medical image ROI segmentation that delineates the diseased part using morphological algorithm. This paper addresses working on reliable methods for diagnosis and prognosis of the pulmonary diseases. Segmentation of ROI for the detection of CT lung pattern abnormalities likely nodules, sarcoidosis, IPF and honeycomb are done based on morphology in this research work. The techniques used to decoct medical information helps the radiologists for early diagnosis of ILD to figure out appropriate treatment.

The recent era evolved with many new technologies with new multiple access technique. New technique known IDMA is emerging in fourth and fifth generation mobile communication systems. In this article we have analysis different multiple access techniques in Rayleigh channel using equalization technique using adaptive filters. IDMA-interleave division multiple access technique gives a efficient performance over CDMA, MC-CDMA using chip by chip iterative detection in multipath channel with lesser receiver design complexity. Equalization process with IDMA multiple accesses in multipath single channel gives desirable bit error rate performance with faster convergence rate and track stability compared with conventional CDMA and MC-CDMA in multiuser channel. Detailed expression with variable values is defined in article. In article different equalization adaptive filters used are LMS, RLS and variable forgetting factor RLS algorithm. This article gives performance for single user as well as multiuser channel in Rayleigh channel.

Wireless Sensor Networks are gaining popularity in various fields and areas. But these nodes are vulnerable as they are open networks and easily accessible. The major challenge is to have a secure data transmission between the nodes. To establish a secure transmission, we require a security scheme like a cryptographic algorithm, but this also requires a secure key distribution between nodes. The WSN’s have constraints like limited area, power and memory which restrict all the categories of cryptographic algorithm. Depending upon the criteria’s and constraints, cryptographic algorithm like Elliptic Curve Cryptography (ECC) is best suitable for WSN’s environment. ECC has a smaller key size, high security and less computation time which makes the node an efficient crypto system. This paper describes the implementation of ECC cryptosystem for WSN for secure key and data transmission between the nodes.

The object detection using radar mounted on quadcopter is achieved by a mobile radar which can be taken to any place or location with the help of quadcopter and can be used to detect if there is any unidentified object in its protected area. The quadcopter used is made with Arduino Uno controller and it has a RC (Remote control) remote which works of radio frequency for controlling its direction of motion. The radar has been developed by an ultrasonic sensor which uses ultrasonic waves to detect objects and a servo motor is used to rotate the ultrasonic sensor to cover the entire protected area. The radar has been made wireless with the help of RF (radio frequency) transmitter and receiver module which sends the data on the PC (Personal computer) wirelessly. There are two circuits for the radar namely transmitter and receiver circuits. The transmitter circuit has been mounted on a quadcopter, which can take the radar to any location in its coverage area which makes the radar mobile.

Quantum-dot Cellular Automata (QCA) is one of the emerging transistors less nanotechnology implemented utilizing electron tunneling with the given potential. In this paper, we proposed a design for 2:1 multiplexer in QCA using NON MAJORITY GATE. In this work, a new design of NAND and NOR gates are proposed. By using the NAND gate structure, the proposed multiplexer is implemented. The multiplexer functionality is implemented by the design tool QCA Designer © 2005 Version 2.0.3.

This paper introduces a new concept of Image Fusion technique. This technique is implemented in reducing impulse noise from the digital images and to acquire noise free image. Image fusion technique means that fusing or combination of two or more images with different or similar constraints to form a single image with all the information in each image not being strayed. Normally to reduce noise from an image we use different filtering algorithms and the outputs of those algorithms are fused together to form a perfect image without noise. In this paper we intend to use five different filtering algorithms individually on the image captured by a sensor. The outputs of those five algorithms are fused to form an image free of noise. The image obtained by using this process is of high in quality compared to the images procured by individually de noising them.

In the modern era, in the transportation sector, automobiles play a vital role. Exhausts of motor vehicles majorly cause air pollution which is the primary ingredient in the smog creation in some large cities. These automobiles produce harmful exhausts in which pollutants such as oxides of nitrogen, carbon monoxide, carbon dioxide, Suspended particulate matter, Hydrocarbons, and ozone. Such exhausts cause hazardous diseases to the living beings which in turn leads to the Decrease of lifespan also. To overcome this effect, an embedded system can be designed to detect these pollutants and their levels using semiconductor gas sensors. Everything is monitored and controlled by the microcontroller in the embedded system. This paper mainly focuses on detecting and controlling the air pollution and thereby maintaining the Eco-friendly environment.

The Number of observable facts and structures that are accessible with an airglow images which are captured by an All Sky Imager (ASI). All of these images are required to convert from the spherical coordinating system into the rectangular coordinating image system. The spatial calibration is also most important for the perfect measurement of gravity wave characteristics, plasma characteristics and OH emission parameters in the upper atmosphere, mesosphere, ionosphere study when that calibrations are used in real life dimensions. In this paper, we expressed an effective and simple technique for the coordinate mapping and the spatial calibration for accurate dimensions used in real world life and also implemented the same procedure by using Matlab R2013a. The pixel resolutions of OH image of 840 nm, a mesospheric image of 557.7 nm and ionospheric image of 630 nm are measured. These pixel resolutions are nearly same and measuring technique is very simple than other method used in the same area.

In cerebrum tumor conclusion, clinicians coordinate their restorative information and mind attractive reverberation imaging (X-ray) sweeps to get the nature and obsessive attributes of mind tumors and to settle on treatment choices. Be that as it may, physically identifying and sectioning cerebrum tumors in the present mind X-ray, where an extensive number of X-ray examines taken for every patient, is dull and subjected to entomb and intra eyewitness recognition and division fluctuation. As result various strategies have been proposed as of late to fill this hole, yet at the same time there is no generally acknowledged computerized method by clinicians to be utilized as a part of clinical floor because of exactness and vigor issues. In view of this perception, a mechanized calculation, Various levelled Centroid Shape Descriptor (HCSD) for mind tumor identification and restorative specialists’ help with encouraged and quickened determination technique has been produced.

The Fifth Generation (5G) cell systems are imminent. The 5G grant higher information exchange limit constrain than the fourth period supporting broadband. The 5G will support ultra-strong device to-device and gigantic machine form correspondence. For laying out the 5G organizes new coding designs are displayed. The coding plans are Low Density Parity Check (LDPC), Low Density Symbol Check (LDSC). The coding plan, LDPC is utilized for information and polar codes for control data. What’s more, another coding plan LDSC is used to check a tiny bit at a time investigation. These coding plans are utilized for blunder adjustment and enhanced information rates. Inside the paper, proposes an estimation technique for a low Bit Error Rate (BER) of LDSC codes. The execution of Sum Product Algorithm (SPA) inside LDSC decoder is portrayed in this paper. The redress term is utilized to enhance the deciphering execution of min whole calculation. For LDSC decoder, BER diminishes with increment in the Signal to Noise Ratio (SNR).

Images captured in open air environments are normally destroyed due to the existence of awful climate conditions. The impact of murkiness is extensively spread; the anticipated transmission ought to be uniformly changed over the spot. This paper proposed the Koschmieder’s Model to clear such corrupted pictures from dehazing. To safeguard more points of interest and right the shading twisting, an answer in light of Koschmieder’s Model is presented. The proposed method provides parallel or significantly higher quality with bring down multifaceted nature by connecting with the best in class single picture dehazing techniques. With a specific end goal to confirm the high perceivability remaking and productivity of the proposed method, comparable investigations are conveyed toward the end.

In recent days, the automatic extraction of salient object regions from video data is the most significant for visual analytical solutions. It also brings up more challenges, including pose differences amongst background and foreground objects, motion patterns etc. In this project, a framework of co-segmentation is presented in order to discover or segment the objects in a joint fashion from multiple videos and frames. Feature extraction is one of the main steps in object detection. For this feature extraction, Here introduce a speed up Robust features (SURF) flow descriptor to integrate the object features from the video frames in an optical manner. This novel SURF flow can extract foreground object over the complete video dataset.

5G with Millimeter Wave! The most foreseen future innovation normal in the following decade for remote correspondences. Interest for high information rates and extensive data transfer capacities and limit took an understanding concentration at millimeter wave frequencies. Anyway still a few difficulties should be routed to take live of this proposed framework. One of such test is plan of high gain and mandate reception apparatus with pillar controlling abilities, In this paper we show composed, recreated and manufactured fix receiving wire and straight radio wire cluster for V-band. The fix reception apparatus and its straight cluster configuration is displayed and reenacted in matlab and the outcomes demonstrated that the accomplished gain is around 10 dBi with great directivity, and bar guiding of ±250 which can be proper model for 5G little cell correspondences. The created display likewise demonstrated palatable coordinating outcomes with the demonstrated and reenacted outline.

Noise signals corrupt the information available in a channel. Most of the noise sources are additive. The signals are corrupted by the noises and it loses its quality. This paper presents the detail analysis of the adaptive estimator for noise cancellation in multichannel system using different optimization technique. Different noise cancellation techniques are available in the literature like matched filtering, wavelet transform and statistical analysis. This paper presents the evolutionary methodology approach using Artificial Bee Colony and Particle swarm optimization for the optimization of multichannel adaptive filter l. The investigation of the efficiency of the method was evaluated using a real time ECG data. The noise in the ECG signal is removed using the multichannel adaptive filter using evolutionary optimization technique.

Mobile Adhoc network (MANET) is a distributed infrastructure-less network of mobile nodes where there are no preinstalled routers to route the data. Routing is achieved by the network mobile nodes which automatically configure themselves flexibly to operate as a host or as a router for routing. The level of cooperation achieved among the nodes in any particular region to get routes for data transfer defines the network communication. The routing protocols of several different types have been developed for finding the best fit paths and for satisfying the requirements of QoS. The objectives of QoS routing are, selecting of the best path specific to the communication requirements with efficient network state information (Zhang et al. in Wirel Commun Mob Comput 2008:10 pp, 2018 [8]), and maximum network utilization by the users. Orthogenesis based Genetic algorithm is devised towards QoS fitness scope aware route discovery for MANETs called as QFSRD. The QFSRD is proposed in the aim of achieving QoS under multi objectives. This paper devised under QFSRD is a GA based approach that concludes the set of best fit energy efficient multi objective QoS routes for mobile ad hoc routing. This paper analyze the performance of QFSRD, GAMAN and E-GAMAN. Performance is analyzed for metrics throughput, Packet delivery ratio and energy consumption. Results shows that the performance of proposed algorithm QFSRD is best compare to GAMAN and E-GAMAN.

Information security is increasing progressively essential in the advanced world. Protected Image Broadcast has a capability of being received for mass correspondence. A few stenographic systems for transmitting data without bringing doubt are found up in [1–5]. Anyway another protected photograph Broadcast procedure is proposed, known as anonymous part unmistakable montage photograph which enables the client to safely transmit a photograph under the front of another photograph of same size, This paper exhibits a methodology called Reversible data hiding with LSB technique where montage photograph age has done by isolating the anonymous photograph into pieces and changing their separate shading attributes into relating squares of the objective photograph. Use of the Pixel shading changes yields the lossless recouped photograph in view of the untransformed shading space esteems. Age of the key assumes an essential job to regain the anonymous photograph from the montage photograph in lossless way. At last a similar methodology can be performed on recordings likewise which wipes out the flashing ancient rarity to accomplish the lossless information recuperation in movement related recordings. The exploratory outcomes demonstrate great powerful conduct against all coincidental and unintentional assaults and contrast with the regular calculations.

The specular reflection (SR) occurs in an image due to reflection from surface and affects the overall interpretation of the image. In medical image analysis, SR images reduce the diagnostic accuracy. Hence, the paper reports the analysis of various SR detection techniques and suggests the best one for automatic detection of SR pixels. The present work compares three state-of-art methodologies of SR detection and three automatic threshold selection techniques. We suggest the combination of ‘Alsaleh’ method adapted by ‘Kittler’ auto-selection technique for accurate SR detection. The SR free Cervix image will lead to the early detection of Cervix cancer.

There are so many reasons for vehicle accidents and the first reason amongst is less alertness of the driver; this may be because of driver’s fatigue or drowsiness. With the introduction of the automatic driver assistance system ADAS, there is possibility to avoid the accidental damage which is happening due to the said reason. To develop such system, two problems are required to be solved. One is prediction of the drowsiness and the other one is controlling the movement of vehicle. The theme of the paper; is to review various control algorithms used to develop shared steering control systems appropriate to implement the ADAS. For this a vehicle model is developed and described to solve the problem with model based development technique. The vehicle model developed is a two-dimensional 2D and 3D mathematical state-space model of laterally moving vehicle which is most suitable to design a shared steering control system. Finally the response of the vehicle state-space model, simulated for unit pulse input, is analyzed with MATLAB software.

Automatic Test Pattern Generation (ATPG) is the most useful technique for the testing of VLSI designs. In recent times with the increase in the size and complexity of designs, the probability of the occurrence of defects also increases. There-fore testing has become very difficult for complex circuits or designs such as System On Chips (SOC). The solution to this problem is the Embedded Deterministic Test (EDT) which involves in addition of some logic structures to the complex designs to minimize the total cost of the test, the volume of the test and memory usage of ATE (Automatic Test Equipment). In this paper, the analysis of ISCAS’89 benchmark circuits are done by using Embedded Deterministic Test (EDT) to improve the test coverage. Retargeting stage is proposed in-order to compact the test sets produced during ATPG.

Head-pose estimation considers the most popular area of research. Estimating the head pose variation in the correct way from faces shots is an essential step for building interactive vision-based applications. In this work, a head-pose estimation system that predicts a head-pose angle for students during studying is proposed. The bounding-box method for face detection is used and a high-dimensional vector-space of faces using HOG features is adopted. A mixture of linear regression technique is applied to determine how to map high-dimensional vector-space onto bounding-box shifts and both head-pose parameters. The performance of the proposed system is evaluated and checked using the absolute error between the predicted angle and the target angle, after that, the mean absolute error (MAE) is computed along with standard deviation (STD).

This paper focuses on the improved prediction of diabetes over the very famous Pima Indians dataset. This work focuses on the ensembled result of Non-linear support vector machines (SVM) aggregated with partial least square classifier (PLS). The idea behind this is to get the advantage of kernel transformations from the Non-Linear methods of SVM and dimensionality reduction from PLS. This unique combination makes the ensembled classifier efficient which can be observed after comparing it with the previous classifiers. So this method is also compared with the leading classifiers like decision tree, neural network, linear SVM and also with the ensembled models of these classifiers by applying majority voting. In all the cases, the proposed method is doing better than the rest of the methods.

In this paper the conventional circular patch antenna has been modified to operate at a frequency of 15 GHz which has been assigned for 5G communication. To get the optimum result a circular slot has been inserted which provided the broadband property. The design and the simulation was done using HFSS to verify the return loss plot and the resonant frequency the design was again done by the CST software. an optimisation has been implemented for the circular slot. The return loss, VSWR, Antenna Gain, peak directivity etc. parameters has been calculated. The FR4 epoxy material has been chosen for the substrate and the copper material is taken into account for both ground plane and patch. The dimension of the substrate and the ground plane is 50 mm × 50 mm.

Border Surveillance and security are of prime concern for any country. The utilization of modern smart technologies empowers strong border security. It is an imperative need to advance these technologies for better security. In this research, we employ machine learning techniques in Remote Video Surveillance for real-time threat level detection and classification of targets crossing borders. The algorithm used for the machine learning based detection of objects in the videos in this research is the Viola-Jones algorithm. This algorithm requires a training set of both positive and negative images, for the purpose of which, a collection of positive and negative images was used for the training of the algorithm for objects such as humans, vehicles, and handguns. A threat level classifier and alert warning system were also added to classify and annotate the videos in real-time for each frame. The threat level classifier performs four-fold categorization of the real-time video into—safe, low, medium, and high (danger). The alert warning system specifies the type of warning based on the type of intrusion (human, vehicle, or weapon) detected. For the algorithm proposed in this work, the accuracy for the human detection is an average of 94.93%, the accuracy for the vehicle detection is an average 95.2%, and the accuracy for the weapons detection is an average of 97.67%. The accuracy of our proposed method (97%) was much higher than that of the compared previously published method (64%) for object detection.

The communication between the deaf people and the hearing community is the challenging task. To overcome this barrier automatic sign language recognition plays an important role. It helps to remove the communication barrier between them. A Convolutional Neural Network (CNN) based approach for Marathi sign language is presented in this paper to help understand and interpret the hand gestures made for Marathi alphabets. This system using CNN is an automated process of constructing the handcrafted feature from gesture images. The system is able to recognize 25 Marathi sign language (MSL) alphabets with a testing accuracy of 99.28%.

The paper reports a multiband filtenna design and analysis. The design provides multifunctional ability with its application area in WLAN and WiMax bands. The proposed filtenna operates over 2.4/5.2 GHz for WLAN and 3.5 GHz for WiMAX applications. First band is achieved by patch antenna with U shaped radiator. For next two bands additional L shaped strips and I shaped strips along with patch rotated by 45°. The design is analyzed using CST microwave studio. The proposed filtenna shows a passband from 2.3 to 2.6 GHz (lower WLAN band); 3.25–4.1 GHz (WiMax band); and 4.4 to 5.4 GHz (1 GHz). The filtenna is compact in size with a dimension of 46.90 × 51.15 mm (width × length). Hence, this is very useful for WLAN and Wi MAX applications.

Image encryption has evolved significantly over the years. This paper proposes an image encryption system using Arnold’s cat map transformation and Snow stream cipher. In our proposed scheme, the image is first scrambled using Arnold’s transformation and then the selected scrambled image pixels are XORed with the Snow cipher keystream sequence to produce the cipher image. Performance of the proposed scheme is analyzed based on several statistical properties. We have observed encouraging statistical properties of the cipher image bitstream making our encryption scheme suitable for applications that requires secured transportation of images.