Computer Engineering

Vision based AGV (Automatic Guided Vehicle) with RTOS (uC/OS-II) is designed and developed for controlling two wheeled differential servo motor drive. In order to meet the demand of function, reliability, cost and real time performance compared to its commercial counterpart of general purpose computer the system is implemented with RTOS. The multi-processor embedded system with distributed architecture consists of a main-controller of vehicle management based on the ARM LPC2378, and a sub-controller of vision navigation based on the DSP BF533. The embedded RTOS uC/OS-II is used to construct a software development platform, on which different functions needed are described as several tasks, and a number of system services facilitate software realization. In the practical application of device reformation, a commercial AGV product is upgraded by the embedded vehicular controller we develop, on which a sophisticated algorithm of path tracking is implemented successfully and efficiently. The experimental result demonstrates the effectivity and advantages of the embedded multi-processor controller with the RTOS uC/OS-II presented in this paper versus its commercial competitor.

Abdominal elcetrocardiograms make it possible to dertermne the fetal heart rate and to detect multuiple fetuses and are often used during labor and delivery.the background noise due to muscular activity and feotus motion, however, often had an amplitude equal to or grater than that of fetal heartbeat.A still more serious problem is the mother’s heart beat,which has an amplitude 2 to 10 times grater thatn that of the fetal heartbeat, and often interferes in recording[1]. The Maternal ECG (MECG) is the main source of interference in Fetal ECG (FECG) monitoring. The MECG is detected at all electrodes placed on the mother’s skin (thoracic and abdominal). In the case of multi-fetal pregnancies the traditional adaptive filtering technique provides a “maternal clean“ signal consisting of the two fetal ECG signals. The noise was found to be too strong for the algorithm (and the naked eye) to notice any fetal heart signal[1]. This paper briefs the implementation of Adaptive noise cancellation algorithms such as LMS algorithm and RLS algorithm using MATLAB 6 (R12) suitable for real time implementation, which can be used during measurements, is being developed using VLSI. The best solution in case of multiple fetuses is the BSS filtering which has successfully been implemented in MATLAB.

Visual cryptography is special type of technique for encipher the confidential visual information (e.g. printed text, handwritten notes, and picture) in such a way, that decipher can be performed by human visual system (HVS) without any complex process, providing high security. In this paper a simple but robust visual cryptography scheme is proposed. In this scheme the secret is encrypted using symmetric key encryption algorithm, and then this encrypted data will be hidden into an image file, divided into parts called shares and then they are distributed to the participants. Thus accomplishing both data encoding and hiding. Only piling of shares does not revile the secret until shares are stacked together in a particular fashion and provided with the key. It can be used to hide the original secret information from an intruder or an unwanted user. The shares are very safe because separately they reveal nothing about the secret image. The algorithm proposed by this scheme reduces a considerable time for encryption and decryption in a much easier way and ensures the lossless transmissions of images. The proposed encryption algorithm in this study has been tested on some images and showed good results.

In any business network most important things that need to be addressed is up time. It depending on the size of the business and business network also, every minute downtime can more affect the productivity of the business employee and the business system that use the network. The address this within the adaptive security appliance (ASA) product line, Cisco offers high availability through a series of failover capabilities. When configured, they allow a deployed ASA to be mated with another ASA, which combine to offer little downtime if one of them encounters of failure [1]. This paper introduces the replication of data, it means both units carry data traffic and it also introduces how to secure our interesting traffic over the internet. VPN mainly used for security purpose we use VPN in many thing and many fields. It provides the secure and private network connection through the public internet; the VPN protects our data in many ways. VPN tunnel is an encrypted connection between our device and VPN sever.

Geospatial information gathered through different sensors and geographic objects is generally indistinct, vague and uncertain. The ambiguity turns out to be obvious due to the multi-granular formation of the multisensory satellite images and that directs to error accumulation at every stage. The main aim of this paper is to compare the K-Means and Fuzzy C-Means classification algorithm and find out the change detection in glacier classification by processing images taken over different time frames. The LANDSAT images correspond to the Himachal Pradesh region, one dated June 2005 and the other dated June 2010. To estimate the quality of remote sensing data the non-linear objective assessment parameters are used. Though the classification of glacier cover calculation, by improving the accurate geological classification, might be in a crude form but when projected on a larger scale, it can act as a great tool for research and analysis on a particular geographical location. The environment related bodies around the globe are deeply benefited from the valuable images provided by satellite imagery and their analysis help strategize different methods for environment protection in general and curb global warming in specific.

This paper proposes a novel method of designing discrete cosine transform using Vedic mathematics. Multipliers are fundamental and area intensive component in the architecture of any DSP system. In many circumstances, there are situations where the complexity and delay of the whole circuit increases because of inefficient multipliers. So it is necessary to reduce such complexity of Multipliers for efficient DSP architecture. The design of Vedic Multiplier is aimed to create such. The design is based on the Sutras of ancient Indian Vedic mathematics which was rediscovered from Vedas between 1911 and 1918 .The whole of Vedic mathematics is based on 16 sutras and manifests unified structure of mathematics. The DCT algorithm is based on ‘Urdhva-Tiryak’ sutra .It is expected that the Vedic architecture reduces the space and time hence the complexity of the multiplier when implemented in digital domain. The algorithm is implemented using verilog HDL and is tested and verified. It is found to reduce the space and increases the speed by when compared to conventional dct using array multiplier. The multiplier can be substituted for conventional multipliers in various applications. The exploration of Vedic algorithms in Digital Signal Processing may prove to be extremely advantageous. Hence it can be applied for discrete cosine transform application.

In this paper a method has been proposed that uses static partitioning for improving classification of time components of EEG signals. The main idea is that different windows of signals have different power in classification. So with removing some ineffective windows from signals, the power of classification might be increased. For finding best combination of windows, Genetic Algorithm (GA) was applied. For extracting appropriate features, Common Spatial Pattern (CSP) was derived for five class problem. It applied onto each window distinguishably, and the final feature vector was obtained from placing these feature vectors altogether. LDA was used for classifying tasks. The proposed method was applied on a dataset of five mental tasks in which 30% of dataset were used for testing system. The experimental results show that window selection by GA will increase the accuracy of algorithm. This technique increased the accuracy from 69% into 95.3% for 25 windows and into 100% for 50 windows. So with changing number of windows, the accuracy of algorithm will be changed. Another important parameter is ’m’ that is the number of spatial patterns selected by CSP.

Regression testing leads to running many tests many times. Hence it requires more cost. The most robust and straight forward technique for regression testing is to accumulate all integration tests and rerun them whenever new components are integrated into the system. This requires developers to keep all tests up-to-date, to evolve them as the subsystem interfaces changes and to add new integration tests as new services or new subsystems are added. As regression testing can become time consuming, test suite minimization (also known as Test Suite Reduction) technique is best suited to tackle it . In this paper we have explained the heuristic approach to solve this optimization problem.

This paper presents a Product recommendation system based on metric analysis of product descriptions. The developed system ranks the catalog of products and offers corresponding items to the user’s request while, at the same time, selecting the most diverse items. An algorithm for ranking is developed. Based on the request, the recommendation system finds the distance from this request to all documents from the collection of data. The request and the collection of data are sets of features. The system ranks the results in accordance with the following rules: minimizes the distance from the query to the relevant results, maximizes the distance from the query to the irrelevant results and maximizes the distance between the relevant query results. For ranking, Heterogeneous Euclidean-Overlap Metric (HEOM) of clothes catalogue items is used. HEOM metric uses different attribute distance functions to measure distances between objects in mixed scales. A dataset of clothes catalogue items is collected. The system, in addition to the basic attributes given as text descriptions of product, uses attributes based on expert description such as fashion, psychological age and attractiveness. The dataset has features of text, linear and nominal scales. The computational experiment shows the effectiveness of the proposed algorithm. The importance of features of the collection of data is defined. A software product demonstrating the recommendation system in action is developed.

Video on demand (VOD) service is widely used nowadays to watch online videos. Video on demand has evolved as a major Problem implementation for network. This research aims to design a suitable grid computing system to enhance performance of video on demand. The goal of using Grid computing system is to create the simple but large and powerful virtual computer with large collection of heterogeneous systems sharing resources. User can submit request for video to grid server without necessary knowing where it will be execute. It is the responsibility of the grid server to distribute request among several servers (clusters). The results we get optimize resource usage, load balance, and time delay for delivering video file. The MATLAB simulation program is designed to compare old server performance with Grid server performance focusing on time delay and system throughput, which decreases Video delay 60 % - 70%.