Computer Science Engineering

—In order to retrieve images efficiently from a large
database, a unique method integrating color and texture features
using genetic programming has been proposed. Opponent color
histogram which gives shadow, shade, and light intensity invariant
property is employed in the proposed framework for extracting color
features. For texture feature extraction, fast discrete curvelet
transform which captures more orientation information at different
scales is incorporated to represent curved like edges. The recent
scenario in the issues of image retrieval is to reduce the semantic gap
between user’s preference and low level features. To address this
concern, genetic algorithm combined with relevance feedback is
embedded to reduce semantic gap and retrieve user’s preference
images. Extensive and comparative experiments have been conducted
to evaluate proposed framework for content based image retrieval on
two databases, i.e., COIL-100 and Corel-1000. Experimental results
clearly show that the proposed system surpassed other existing
systems in terms of precision and recall. The proposed work achieves
highest performance with average precision of 88.2% on COIL-100
and 76.3% on Corel, the average recall of 69.9% on COIL and 76.3%
on Corel. Thus, the experimental results confirm that the proposed
content based image retrieval system architecture attains better
solution for image retrieval.

This paper presents the local mesh co-occurrence
patterns (LMCoP) using HSV color space for image retrieval system.
HSV color space is used in this method to utilize color, intensity and
brightness of images. Local mesh patterns are applied to define the
local information of image and gray level co-occurrence is used to
obtain the co-occurrence of LMeP pixels. Local mesh co-occurrence
pattern extracts the local directional information from local mesh
pattern and converts it into a well-mannered feature vector using gray
level co-occurrence matrix. The proposed method is tested on three
different databases called MIT VisTex, Corel, and STex. Also, this
algorithm is compared with existing methods, and results in terms of
precision and recall are shown in this paper.

This manuscript contributes a new feature descriptor local mesh color texture pattern (LMCTP) by merging color and local spatial information for image retrieval system. The intended method combines the various features from a mixture of color spaces, the local mesh patterns of the input image. LMCTP descriptor discriminates information between the spatial color textural patterns of multi-spectral channels within the local region. It determines the relationship between surrounding neighbors of the opponent color channel. Beside this, a merged color space, I1QCb, is constructed by combining the I1 part of the I1I2I3 color space and the chromatic component images, Cb and Q, of the YCbCr and YIQ color spaces correspondingly so as to exploit the effect of joint color texture feature. The I1QCb color space, whose component of images having matching characteristics, increases the distinctive power for retrieval system. Then opponent color spaces I1Q, QCb and I1Cb are utilized for the capturing of LMCTP features.The feasibility of the proposed framework is experiments on benchmark databases such as MIT VisTex database (DB1), Corel 1000 database (DB2). Experimental study shows that the proposed pattern gives average retrieval precision of 99.8 for DB1 and 76.5 for DB2, respectively.

Active and programmable networks change the functionality of routers and switches by
using VPN endpoints and active packets. The authors present a new packet scheduling scheme called
active scheduling to control and maintain QoS parameters in virtual private networks (VPNs) within
the confines of adaptive and programmable networks. In active scheduling a VPN endpoint on the
router monitors the accumulated queuing delay for each service. To control and to keep the end-to-end
delay within the bounds, the delays of the packet transmitted are adjusted dynamically by VPN
endpoints on the routers spanning the VPN. If there is an increase or decrease in delay of packets, VPN
endpoints on a source node informs the destination node to adjust the delay of the packets. This keeps the end-to-end delay of services within the specified bounds and offers better QoS compared with VPNs using static priority scheduling. An algorithm for active scheduling is described and simulation results are presented and compared with priority scheduling.

As Internet usage grows exponentially, network security issues become increasingly important. Network security measures are needed to protect data during transmission. Various security controls are used to prevent the access of hackers in networks. They are firewall, virtual private networks and encryption algorithms. Out of these, the virtual private network plays a vital role in preventing hackers from accessing the networks. A Virtual Private Network (VPN) provides end users with a way to privately access information on their network over a public network infrastructure such as the internet. Using a technique called “Tunneling”, data packets are transmitted across a public routed network, such as the internet that simulates a point-to-point connection. Virtual private networks provide customers with a secure and low-cost communication environment. The basic structure of the virtual circuit is to create a logical path from the source port to the destination port. This path may incorporate many hops between routers for the formation of the circuit. The final, logical path or virtual circuit acts in the same way as a direct connection between the two ports. The K-Cost Optimized Delay Satisfied Virtual Private Networks Tree Provisioning Algorithm connects VPN nodes using a tree structure and attempts to optimize the total bandwidth reserved on the edges of the VPN tree that satisfies the delay requirement. It also allows sharing the bandwidth on the links to improve the performance. The proposed KCDVT algorithm computes the optimal VPN Tree. The performance analysis of the proposed algorithm is carried out in terms of cost, the number of nodes, and the number of VPN nodes, delay, asymmetric ratio and delay with constraints with Breadth First Search Algorithm. The KCDVT performs better than the Breadth First Search Algorithm.

As internet usage grows exponentially, network security issues
become increasingly important. Network security measures are
needed to protect data during transmission. Various security controls
are used to prevent the access of hackers in networks. They are
firewall, virtual private networks and encryption algorithms. Out of
these, the virtual private network plays a vital role in preventing
hackers from accessing the networks. A Virtual Private Network
(VPN) provides end users with a way to privately access information
on their network over a public network infrastructure such as the
internet. Using a technique called “Tunneling”, data packets are
transmitted across a public routed network, such as the internet that
simulates a point-to-point connection. Virtual private networks
provide customers with a secure and low-cost communication
environment. The basic structure of the virtual circuit is to create a
logical path from the source port to the destination port. This path
may incorporate many hops between routers for the formation of the
circuit. The final, logical path or virtual circuit acts in the same way
as a direct connection between the two ports. Our proposed
Provisioning Restorable Virtual Private Networks Algorithm (PRA) is
used to combine the provisioning and restoration algorithms to
achieve better results than the ones obtained by independent
restoration and provisioning. In order to ensure service quality and
availability in Virtual Private Networks, seamless recovery from
failures is essential. The quality of service of the Virtual Private
Networks is also improved due to the combination of provisioning and
restoration. The bandwidth sharing concept is also applied in link to
improve the quality of service in the Virtual Private Network. The
performance analysis of the proposed algorithm is carried out in
terms of cost, the number of nodes, the number of VPN nodes, delay,
asymmetric ratio and delay with constraints with Disjoint Path
Algorithm and Approximation Restoration Virtual Private Networks
Algorithm. The Provisioning Restorable Virtual Private Networks
Algorithm performs better than the Disjoint Path Algorithm.

This Paper involves the design of complementary  Metal  Oxide semiconductor  - Voltage  Controlled  Oscillator  (CMOS  -  VCO). Design is supposed to be area efficient, since the previous  methods  uses  Current  Starved  VCO’S, which are complex in architectures. Current starved
VCO’S  uses  more  number  of  Transistors  that occupies Larger Area and consumed more power. This Current Starved VCO introduces huge amount of parasitic effect, which is undesirable but it is also unavoidable. Their effect can be minimised by using CMOS Based Ring Oscillator VCO. This is because of the usage of  less number of transistors in Ring Oscillator VCO. This Paper involves the designing of  VCO  using  Ring  Oscillators.  At  first,  the Inverters  are  designed.  Then,  these  inverters  are replicated  to  form  Ring  Oscillator.  The  Ring Oscillators in this Paper uses Three Stage Inverters. Ring Oscillator VCO consumes less area and less power  since  they  use  less  number  of  Transistors compared  to  Current  Starved  VCO.  Design  and Performance Analysis of VCO is done in cadence schematic editor using Cadence Virtuoso 180 nm technology. This approach results in the reduction of Area  by  minimizing  transistors  in  an  operating Frequency of 3.42 GHz with the Power supply of 1.2 Volt. This report includes the results that are obtained during circuit simulation.

The Quad Tree Decomposition based performance
analysis of compressed image data communication for lossy and
lossless through wireless sensor network is presented. Images have
considerably higher storage requirement than text. While transmitting
a multimedia content there is chance of the packets being dropped
due to noise and interference. At the receiver end the packets that
carry valuable information might be damaged or lost due to noise,
interference and congestion. In order to avoid the valuable
information from being dropped various retransmission schemes have
been proposed. In this proposed scheme QTD is used. QTD is an
image segmentation method that divides the image into homogeneous
areas. In this proposed scheme involves analysis of parameters such
as compression ratio, peak signal to noise ratio, mean square error,
bits per pixel in compressed image and analysis of difficulties during
data packet communication in Wireless Sensor Networks. By
considering the above, this paper is to use the QTD to improve the
compression ratio as well as visual quality and the algorithm in
MATLAB 7.1 and NS2 Simulator software tool.

In this research paper, a high throughput memory efficient pipelining architecture for Fast Efficient Set Partitioning in Hierarchical Trees (SPIHT) image compression system is explained. The main aim of this paper is to compress and implement the image without any loss of information. So, we are using spatial oriented tree approach in Fast Efficient SPIHT algorithm for compression and Spartan 3 EDK kit for hardware implementation analysis purpose. Integer wavelet transform is used for encoding and decoding process in SPIHT algorithm. Here, we are using pipelining architecture to implement it in FPGA kit because pipeline architecture is more suitable for hardware utility purpose. Generally an image file will occupy more amount of space. In order to reduce the memory size no loss during transmission we are using this approach. By this way we are attained maximum PSNR value, CR and also produced very high accurate image after decompression, when compared with the results of other previous algorithms. In this module, the hardware tools used are dual core processor and FPGA Spartan 3 EDK kit and the software tool windows 8 operating system and the tool kit is MATLAB 7.8.

In this research paper, consists of compressing the images within each pixel before the storage processes, hence the
size of the memory gets reduced. This can be done by the proposed method namely block based compression algorithm which
uses the differential coding scheme. Here, differential values are captured and then quantized. The differential coding scheme
uses the concept of selecting the brightest pixel as the reference pixel. The difference between brightest pixel and subsequent
pixel is calculated and quantized. Hence, their range is compressed and the spatial redundancy can be removed using block
based compression algorithm. Thus, the proposed scheme reduces the accumulation of error and also, reduces the requirement
of memory. Thus the Peak Signal to Noise Ratio (PSNR) value can be improved and Bits Per Pixel (BPP) value can be
reduced. The future scope of the project is that the quality of the image can be further improved with high peak signal to noise
ratio value using some other compression techniques.

In recent years the satellite communication has been growing for the development of rapid and efficient techniques for the storage and transmission of satellite images. The science of reducing the number of bits required to represent the image is called image compression.
The aim of this paper is to reduce the size of the image, while transmitting the original image. This reduced image is called as compressed image. The compressed image is being transmitted and it is reconstructed in the receiving side so that the compressed image is being decompressed to obtain the original image. And also transmission of such satellite
image increases communication accuracy but requires less bandwidth. In most systems, the amount of intimation that the user wishes to communicate or store necessities some form of compression for efficient and reliable use of communication or storage system. Although
several well-known compression techniques exist, many of them require computationally intensive algorithm. In addition to that many compression techniques introduce unwanted attribute such as loss of intimation. This is a major problem in satellite imaging where image degradation may be critical. By considering the above, this paper is to use the wavelet to
improve the compression ratio as well as visual quality which is implemented by the famous algorithm called sub band coding and decoding algorithm in MATLAB 7.1 software tool.

The Simulation based VLSI Implementation of
FELICS (Fast Efficient Lossless Image Compression System)
Algorithm is proposed to provide the lossless image compression and
is implemented in simulation oriented VLSI (Very Large Scale
Integrated). To analysis the performance of Lossless image
compression and to reduce the image without losing image quality
and then implemented in VLSI based FELICS algorithm. In FELICS
algorithm, which consists of simplified adjusted binary code for
Image compression and these compression image is converted in
pixel and then implemented in VLSI domain. This parameter is used
to achieve high processing speed and minimize the area and power.
The simplified adjusted binary code reduces the number of arithmetic
operation and achieved high processing speed. The color difference
preprocessing is also proposed to improve coding efficiency with
simple arithmetic operation. Although VLSI based FELICS
Algorithm provides effective solution for hardware architecture
design for regular pipelining data flow parallelism with four stages.
With two level parallelisms, consecutive pixels can be classified into
even and odd samples and the individual hardware engine is
dedicated for each one. This method can be further enhanced by
multilevel parallelisms.

Wireless sensor Network (WSN) is a self- governing
system used for monitoring. WSN with structural
health monitoring (SHM) system is used to monitor the
operations and health status of the structures. In the
deployment of the backup sensors, the WSN aims to
achieve a fault tolerance mechanism by placing a set of
backup sensors. In the process of deploying the backup
sensors, we follow a distributed approach in which the
nodes are grouped into clusters. From each clusters,
the separable point, isolated point are critical middle
point are determined through which the backup
sensors are placed. By achieving the fault tolerance
mechanism, the energy is consumed and the lifetime of
the sensor nodes are increased. The simulation results
show the advantages of achieving the fault tolerance
mechanism.

Structural health monitoring (SHM) system is increased with consideration of an engineering fields and it is commonly utilized in various three dimensional (3D) structures such buildings, bridges, hospitals, industries and nuclear power planet. The traditional works
are mostly utilized in two dimensional structures and it includes some drawbacks, such as, harsh environments may occur the sensor failures. When the number of faulty sensors are increased in the acceptable level, the SHM system yields an undependable monitoring or prediction of the structural performance. To overcome these drawbacks the proposed
work is developed. Initially, the Wireless sensor formation, in this stage, collects the set of sensor deceives which are placed in 3D structure. After that, the sensor send the signal to destination. It is utilized to identify the problem which are present in the path or not. Then modified particle swarm optimization algorithm is offered the optimal solution. In
this stage the novelty is presented. Dijkstra’s algorithm is utilized to identify the shortest path between two sensor which are presented in 3D structure and it utilizes to identify the signal strength. Then the link fitness is utilized to evaluate the bandwidth. Next, the round trip time is estimated, it is utilized to identify the path is which are free or not. Then the data are aggregated. Finally, the aggregated data are collected from sink node. These dataare utilized to find out the fault which is present in 3D structure. The main advantage of the work is reduced number of sensors, improve reliability and provide a robust system.

Structural Health Monitoring (SHM) has been considered to afford up-to-date information about the state of structures by assessing structural vibration responses and further physical phenomena and disorders. Determining the structure conditions is not an easy task which
is associated with complex civil structures. The main objective of SHM is earlier damage detection, inspection cost reduction and lifetime estimation. The modern improvements of wireless sensor networks paid attention in the field of structural health monitoring. The deployment of sensors are expected to provide the rich information about civil structures
in an effective manner. The main limitations of sensors (small memory size, small communication throughput, limited speed of the CPU) reduce the effectiveness of SHM. We propose concoction node fault discovery approach in order to provide reliable communication in the wireless environment specifically having lot of obstacles. The HRPD algorithm
select the Line of sight (LOS) nodes based on extracted RSS features which is higher than non LOS. The selected intermediate LOS nodes transmit the collected sensing information to the base station with reduced energy consumption. The Statistical link parameter estimation
supports to detect the optimal path through continuous analysis of link metrics such like link bandwidth, response time and queue size. The LOS fault tolerant approach determines the faulty LOS nodes, and direct the system towards survivability. The simulation results shows that our proposed approach minimize the energy depletion and enhances the
sensor node’s life time. The application of the proposed work helps to monitor the structural health of buildings, bridges and towers with high quality monitoring mechanism.

As a result of the continuous materialization of various internet and broadcasting technologies, Various File Transfer Protocols (FTP) has been used. Due to the rise of various mobile based network terminologies,
there is a need of enhancing security measures for the Bluetooth technologies. In this paper, we propose a virus model based on the application network of Bluetooth which is the most popular among these
Smartphone Mobile Users. We also compare the behaviors of virus spreading in Bluetooth and email network based Models. We find that while Bluetooth5 provides a platform for File Transfer, it also
provides the same chance for virus spreading. And virus will spread faster in Bluetooth,network if users turning it on unnecessary conditions.

In our today’s world scenario the number of smart wireless devices which are attacked by malicious users are increasing in number. In
this paper, we have introduced a discrete epidemiological scheme and an alternate approach to analyze the spatio-temporal architecture
scheme of multi-connection mobile platform. An investigation relied approach is delivered for the cybernetic tranceiving devices those
are being vulnerable to the malicious worm assaults alongside with human interactions and worm prevention measures. This approach
considers the communication between the smart devices and their capability to provoke its unique heterogeneous characteristics. The
results obtained from this investigation depicts that, our proposed approach is capable of identifying cybernetic worm propagation and
provision for the determination of worm spreading in the wireless medium