Computer Engineering

Impulse noise is the major factor that affects the image during signal acquisition and transmission. Here an efficient simple edge preserving denoising technique is used to remove the impulse noise. To avoid the possible misdetection this technique does not affect the noise free pixel. It uses different directional edges to preserve the edge information. The experimental result shows excellent performances in terms of quantitative evaluation and visual quality. The design cost is also low because it needs only two line memory buffer and less computational complexity.

WSNs are the widely used for the process of sensing and transmitting the data of any environment based on the application and they are mainly employed for the real-time applications. In the real-time applications, the WSNs are advantageous but the efficiency and the system performance are degraded because of the phenomenon termed as congestion. The occurrence of congestion affects the life-time of the nodes resulting in the poor throughput of the network. Thus, in order to enable effective transmission and to enhance the throughput of the network, an efficient congestion control method is required. Accordingly, the literatures present various approaches for the controlling the congestion that occurs in the network and it is very clear that the accuracy of the control mechanism is the outstanding issue at present. Therefore, the need for an effective congestion management system arises that outperforms the current approaches in terms of accuracy, congestion rate, and the packet drop rate. Thus, this review article presents the detailed review of 17 research papers that present the recommendation approaches based on neural networks, fuzzy-logic model, hybrid method, and learning-based models. Additionally, the detailed discussion of the survey taxonomy in terms of the simulation tools and performance metrics are clearly reviewed and analyzed. The research issues of various conventional methods are presented in the literature section along with the description of the methods that promote the researchers towards a better contribution of the congestion control mechanism.

The impact of COVID-19 are felt around the world and all sectors specially technology sector. In today’s era we can say that every business are completely depend upon Information technology. Cloud Technology is the most prominent technology by which company manage their resource that is required to perform computing and share the information with security through Internet. Toady’s every company want to migrate on cloud computing but selecting the right cloud service vender which meet the company’s requirement is most important. In this paper n this Paper, the main three cloud computing service provider namely Microsoft Azure, and Amazon Web Services and Google Cloud, were studied. Also, we compare the services they offer. This study main aims of this research paper to helping those organization who want to migrate to cloud computing and choose the correct service provider which meets their business requirement.

Mobile Ad hoc Wireless Network is a collection of wireless mobile node forming a temporary network without the support of any predefined infrastructure using the unlicensed radio spectrum frequency of Industrial Scientific Medical (ISM) band as per the standard of IEEE.802.11. In Mobile Ad hoc Networks, all devices have equal status and are free to associate with any other Ad hoc Network. Ad hoc mode can be deployed anywhere easily without requiring major infrastructure. It is a decentralized network. Users are mobile in this network and can access data from anywhere. In Ad hoc wireless mode, from source node to destination node requires help of other nodes presents in the vicinity of a node. Nodes behave as a source and destination and as a router or intermediate node which forward data for other nodes . Routing becomes on the most complicated challenges prevailing in Ad hoc Wireless Networks. Routing is based on multi hop and so no default route is available .Traditional classification of Ad hoc network routing is table driven and on-demand driven protocols. Table driven routing protocols try to maintain consistent, up-to-date routing information from each node to every other node. Energy is considered as a vital resource that needs to be preserved in order to extend the life time and stability of the Ad hoc Wireless Networks. In particular, mobility changes network connectivity and it can reduce the stability of the link of nodes and it can reduce the performance of throughput. In order to overcome these issues in Ad hoc Wireless Networks, Optimization techniques are proposed. Routing protocols has two noteworthy arrangements are unipath and multipath. The current work assesses execution of an on-demand multipath routing protocol called Adhoc On-demand Multipath Distance Vector (AOMDV) routing. This paper suggests an energy-aware Genetic Algorithm (GA) based Multipath Routing. GA has been referred as one of the meta-heuristic strategies applied to take care of the optimization issues utilizing the simulation of the conduct of the hereditary operators. Simulation results shown the high accuracy and quality of the suggested technique for the optimization strategies performed by the Genetics Algorithm.

Image segmentation is the process of dividing images according to its characteristics like color and objects present in the images. The general segmentation problem involves the partitioning of a given image into a number of homogeneous segments, such that the union of any two neighbouring segments yields a heterogeneous segment. This can further be used for surgical planning, to avoid open surgery. The techniques used are namely gray scaling, edge detection, contrast enhancement, watershed segmentation and finally marking the region of interest. Comparision of different edge detection techniques based on peak signal to noise ratio and root mean square error is performed. Finally Watershed segmentation uses the intensity as a parameter to segment the whole image data set. The results show that Watershed Segmentation can successfully segment a tumor. All the mentioned modules and techniques have been implemented in MATLAB environment for the brain tumor detection using input MR images and the part of modules like edge detection, thresholding and high pass filter are also implemented in FPGA using Verilog in Xilinx environment, the advantage being speed enhancement and re-configurability.

Being future technocrats we tossed this idea with an aim to provide service to the society. Providing an overture for the visually impaired, to make them feel self-reliant and thus raise their status in the society is the ultimate aim of our project. The proposed concept consists of a smart stick that generates voice output using the voice arrays and pre programmed microcontrollers. This tool encompasses five constructive features. The pre-eminent feature is the Obstacle Tracer which uses ultrasonic sensors to detect the obstacles on the person’s way and redirects them appropriately using voice commands. Area Detector uses the GPS module to figure out the location and gives the output as voice stream. Destination alerter generates a voice alert to the person on reaching a landmark (such as bus stop, bank, post office etc….) In addition to these our contrivance also has the Onboard Alerter module that informs the person when a bus enters the boarding area. This uses the transmitters in the bus and receivers in the contrivance. The Off Board Alerter specifies the subsequent bus stops as soon as the person boards on the bus. Thus our appliance will help the visually impaired person to be independent in his own path.

In this paper, we design a cloud computing supported logistics tracking information management system to support whole-ranged and real-time logistics tracking services. The logistics cloud provides customers with a way to tap into - anywhere, anytime - the power needed to more efficiently run their businesses. The logistics cloud helps in making efficient and easy processes of global supply chains. The information about shipments with suppliers, transportation providers, and end users is quicker using the cloud. One of the greatest advantages of the logistics cloud is that there is a complete balance of sharing the resources among all the business companies.

A novel algorithm for effectively fusing Alzheimer’s effected medical images is proposed in this paper. Fusing is done in the Undecimated Discrete Wavelet Transform (UDWT) domain. Firstly, the RGB images are converted in to NTSC images and then UDWT is applied. In UDWT domain, Low frequency subbands are fused using maximum selection rule and high frequency subbands are fused according to the Modified Spatial Frequency (MSF). Lastly, fused image is obtained by inverse UDWT. The fused NTSC is again converted in to RGB image for fused RGB image. Superiority of the proposed method is presented and justified. Fused image quality is verified with various quality metrics i.e., Peak Signal to Noise Ratio (PSNR), Entropy, Spatial Frequency (SF) etc.,

To develop a 3D computational model of a Surface Acoustic Wave based sensor in order to understand the SAW wave propagation characteristics built with enhanced sensitivity. A Surface Acoustic Wave (SAW) is an acoustic wave propagating along the surface of a solid material. SAW’s are featured in many kinds of electronic components including filters, oscillators, sensors, etc. SAW devices typically use electrodes on a piezoelectric material to convert an electrical signal to a SAW and back again. In this model we investigate the resonance frequencies of a SAW gas sensor, which consists of an Inter Digitated Transducer (IDT) etched onto a piezoelectric LiNbO3 (Lithium Niobate) substrate and covered with a thin Poly Isobutylene (PIB) film. The mass of the PIB film increases as PIB selectivity adsorbs CH2Cl2 (Dichrolomethane, DCM) in the air. This causes a shift in resonance to a slightly lower frequency.

In this paper, a novel technique to improve the performance of the LMS method is implemented. As noise is characterized in the low frequency region, the volume of the passive absorbers used increases. Hence, we go in for active methods of suppression. Conventional noise controllers are adaptive filters with the parameters updated mainly on the least mean square basis. It is shown how the least-mean squares algorithm (LMS) can be implemented by using the graphical language LabVIEW. The LMS algorithm under pins the vast majority of current signal processing adaptive algorithm including noise cancellation, beamforming, deconvolution, equalization and so on. It will be shown that labVIEW is a convenient and powerful method of implementing such algorithms.