Showing papers by "Othman Omran Khalifa published in 2010"

English digits speech recognition system based on Hidden Markov Models

Abstract: This paper aims to design and implement English digits speech recognition system using Matlab (GUI). This work was based on the Hidden Markov Model (HMM), which provides a highly reliable way for recognizing speech. The system is able to recognize the speech waveform by translating the speech waveform into a set of feature vectors using Mel Frequency Cepstral Coefficients (MFCC) technique This paper focuses on all English digits from (Zero through Nine), which is based on isolated words structure. Two modules were developed, namely the isolated words speech recognition and the continuous speech recognition. Both modules were tested in both clean and noisy environments and showed a successful recognition rates. In clean environment and isolated words speech recognition module, the multi-speaker mode achieved 99.5% whereas the speaker-independent mode achieved 79.5%. In clean environment and continuous speech recognition module, the multi-speaker mode achieved 72.5% whereas the speaker-independent mode achieved 56.25%. However in noisy environment and isolated words speech recognition module, the multi-speaker mode achieved 88% whereas the speaker-independent mode achieved 67%. In noisy environment and continuous speech recognition module, the multi-speaker mode achieved 82.5% whereas the speaker-independent mode achieved 76.67%. These recognition rates are relatively successful if compared to similar systems.

Enhancing selective encryption for H.264/AVC using advanced encryption standard

Abstract: Video encryption algorithms have becomes an important field of research nowadays. As an increasing rate of applying video is getting high, the security of video data becomes more important. A digital media can be transmitted easily in real time anywhere at any time due to the advanced development of communications, Internet and multimedia technology. Information availability has increased dramatically with the advent of mobile devices. However, with this availability comes a problem of maintaining the security of information that is displayed in public. Many approaches have been used or proposed to provide security for information disseminated over the networks. These include encryption, authentication, and digital signatures. For video, the method has been adopted to protect unwanted interception and viewing of any video while in transmission over the networks. In this thesis, a development of an enhanced selective video encryption scheme for H.264/AVC based on Advanced Encryption Standard (AES) was reported. A proposed scheme been used instead of encrypting the entire video stream bit by bit, only the I-Frames bitstreams were encrypted. This scheme took into consideration the good features of former selective encryption algorithms with regard to computational complexity, and data compression performance. The proposed system was tested in the simulated environment using different video sequences. The experimental results show that the proposed method provides adequate security to video streams. It has no effect on compression ratio and does not reduce the original video compression efficiency. Moreover, the proposed scheme provides a good trade-off between encryption robustness, flexibility, and real-time processing. It is an appropriate ii technique for secure H.264 bitstreams that require transmission or storage in un-trusted intermediate devices.

Natural speaker-independent Arabic speech recognition system based on Hidden Markov Models using Sphinx tools

Abstract: This paper reports the design, implementation, and evaluation of a research work for developing a high performance natural speaker-independent Arabic continuous speech recognition system. It aims to explore the usefulness and success of a newly developed speech corpus, which is phonetically rich and balanced, presenting a competitive approach towards the development of an Arabic ASR system as compared to the state-of-the-art Arabic ASR researches. The developed Arabic AS R mainly used the Carnegie Mellon University (CMU) Sphinx tools together with the Cambridge HTK tools. To extract features from speech signals, Mel-Frequency Cepstral Coefficients (MFCC) technique was applied producing a set of feature vectors. Subsequently, the system uses five-state Hidden Markov Models (HMM) with three emitting states for tri-phone acoustic modeling. The emission probability distribution of the states was best using continuous density 16 Gaussian mixture distributions. The state distributions were tied to 500 senons. The language model contains uni-grams, bi-grams, and tri-grams. The system was trained on 7.0 hours of phonetically rich and balanced Arabic speech corpus and tested on another one hour. For similar speakers but different sentences, the system obtained a word recognition accuracy of 92.67% and 93.88% and a Word Error Rate (WER) of 11.27% and 10.07% with and without diacritical marks respectively. For different speakers but similar sentences, the system obtained a word recognition accuracy of 95.92% and 96.29% and a Word Error Rate (WER) of 5.78% and 5.45% with and without diacritical marks respectively. Whereas different speakers and different sentences, the system obtained a word recognition accuracy of 89.08% and 90.23% and a Word Error Rate (WER) of 15.59% and 14.44% with and without diacritical marks respectively.

Advances in Electromyogram Signal Classification to Improve the Quality of Life for the Disabled and Aged People

Abstract: Problem statement: The social demands for the Quality Of Life (QOL) are increasing with the exponentially expanding silver generation. To i mprove the QOL of the disabled and elderly people, robotic researchers and biomedical engineers have b een trying to combine their techniques into the rehabilitation systems. Various biomedical signals (biosignals) acquired from a specialized tissue, or gan, or cell system like the nervous system are the driv ing force for the entire system. Examples of biosig nals include Electro-Encephalogram (EEG), Electrooculogram (EOG), Electroneurogram (ENG) and (EMG). Approach: Among the biosignals, the research on EMG signal processing and controlling is currently expanding in various directions. EMG signal based r esearch is ongoing for the development of simple, robust, user friendly, efficient interfacing device s/systems for the disabled. The advancement can be observed in the area of robotic devices, prosthesis limb, exoskeleton, wearable computer, I/O for virt ual reality games and physical exercise equipments. An EMG signal based graphical controller or interfacin g system enables the physically disabled to use word processing programs, other personal computer software and internet. Results: Depending on the application, the acquired and pro cessed signals need to be classified for interpreting into mechanical forc e or machine/computer command. Conclusion: This study focused on the advances and improvements on different methodologies used for EMG signal classification with their efficiency, flexibility a nd applications. This review will be beneficial to the EMG signal researchers as a reference and comparison st udy of EMG classifier. For the development of robust, flexible and efficient applications, this study ope ned a pathway to the researchers in performing futu re comparative studies between different EMG classific ation methods.

Suitability of Using Symmetric Key to Secure Multimedia Data: An Overview

Abstract: With the increasing and continuous use of digital communications on the internet in recent times, security is becoming more and more relevant and important. However, special and reliable security is required for the many digital applications available such as video conferencing, digital television and mobile TV. The classical techniques of data security are not appropriate for the current multimedia usage. This study addresses the current algorithm of multimedia encryption schemes that have been proposed in the literature and description of multimedia security. It is a comparative study between symmetric key encryption and asymmetric key encryption in achieving an efficient, flexible and secure video data

Rainfall forecasting models using focused time-delay neural networks

Abstract: Rainfall forecasting is vital for making important decisions and performing strategic planning in agriculture-dependent countries Despite its importance, statistical rainfall forecasting, especially for long-term, has been proven to be a great challenge due to the dynamic nature of climate phenomena and random fluctuations involved in the process Artificial Neural Networks (ANNs) have recently become very popular and they are one of the most widely used forecasting models that have enjoyed fruitful applications for forecasting purposes in many domains of engineering and computer science The main contribution of this research is in the design, implementation and comparison of rainfall forecasting models using Focused Time-Delay Neural Networks (FTDNN) The optimal parameters of the neural network architectures were obtained from experiments while networks were trained to perform one-step-ahead predictions The daily rainfall dataset, obtained from Malaysia Meteorological Department (MMD), was converted to monthly, biannually, quarterly and monthly datasets Training and testing were performed on each of the datasets and corresponding accuracies of the forecasts were measured using Mean Absolute Percent Error For testing data, results indicate that yearly rainfall dataset gives the most accurate forecasts (9425%) As future work, more parameters such as temperature, humidity and sunshine data can be incorporated into the neural network for superior forecasting performance

Prediction of signal attenuation due to duststorms using mie scattering

Abstract: The present trend in radio design calls for the use of frequencies above 40 GHz for short links carrying wide-band digital communication signals. In order to utilize the new frequency band efficiently, signal attenuation studies due to duststorms is needed urgently for desert areas. This paper presents a mathematical model which has been developed to predict the signal attenuation due to duststorm. The proposed model enables the convenient calculation of the signal path attenuation based on Mie solution of Maxwell's equations for the scattering of electromagnetic wave by dust particles. The predicted values from the proposed mathematical model are compared with the measured values observed in Saudi Arabia and Sudan and show relatively close agreement.

Car monitoring, alerting and tracking model: Enhancement with mobility and database facilities

Abstract: Statistics show that the number of cars is increasing rapidly and so is the number of car theft attempts, locally and internationally. Although there are a lot of car security systems that had been produced lately, but the result is still disappointing as the number of car theft cases still increases. The thieves are inventing cleverer and stronger stealing techniques that need more powerful security systems. This project “Car Monitoring and Tracking System” is being proposed to solve the issue. It introduces the integration between monitoring and tracking system. Both elements are very crucial in order to have a powerful security system. The system can send SMS and MMS to the owner to have fast response especially if the car is nearby. This paper focuses on using MMS and database technology, the picture of the intruder will be sent via local GSM/GPRS service provider to user (and/or) police. The Database offers the required information about car and owner, which will help the police or security authorities in their job. Moreover, in the event of theft local police and user can easily track the car using GPS system that can be link to Google Earth and other mapping software. The implementation and testing results show the success of prototype in sending MMS to owner within 40 seconds and receiving acknowledgment to the database (police or security unit) within 4 minutes. The timing and results are suitable to owner and police to take suitable action against intruder.

Comparison of supervised and unsupervised learning classifiers for human posture recognition

Abstract: Human posture recognition is gaining increasing attention in the fields of artificial intelligence and computer vision due to its promising applications in the areas of personal health care, environmental awareness, human-computer-interaction and surveillance systems. Human posture recognition in video sequences is a challenging task which is part of the more comprehensive problem of video sequence interpretation. In this paper, an intelligent human posture recognition system in video sequences is proposed. Firstly, the system was trained and evaluated to classify five different human postures using both supervised and unsupervised learning classifiers. The supervised classifier used was Multilayer Perceptron Feedforward Neural Networks (MLP) whilst for unsupervised learning classifiers, Self Organizing Maps (SOM), Fuzzy C Means (FCM) and K Means have been employed. Results indicate that MLP performs (96% accuracy) much better than SOMs, FCM and K Means which give accuracies of 86%, 33% and 31% respectively. Secondly, all the classifiers were then trained and evaluated again to classify two postures. With only 2 postures, the accuracies of all the classifiers have increased dramatically, especially for unsupervised classifiers. This shows that supervised learning classifiers are superior to unsupervised ones for the task of human posture recognition and that the unsupervised classifiers do not learn very well for cases where a lot of postures have to be learnt as compared to the supervised learning classifier which gives high accuracy in either case.

Video Compression Techniques: An Overview

Abstract: In this study, a new comparative study of video compression techniques was presented. Due to the rapid developments in internet technology and computers, popularity of video streaming applications is rapidly growing. Therefore today, storing and transmitting uncompressed raw video requires large storage space and network bandwidth. Special algorithms which take these characteristics of the video into account can compress the video with high compression ratios. This study demonstrates the representative efforts on video compression and presents the properties and limitations of: H.261, H.263, MPEG-1, MPEG-2, MPEG-4, MPEG-7 and H.264. However, we show that H.264 entails significant improvements in coding efficiency, latency, complexity and robustness. It provides new possibilities for creating better video encoders and decoders that provide higher quality video streams at maintained bit-rates (compared to previous standards), or, conversely, the same quality video at a lower bit-rate Hence, appropriate video compression techniques that meet video applications requirements have to be selected.

Design and evaluation of lightweight IEEE 802.11p-based TDMA MAC method for road side -to-vehicle communications

Abstract: Wireless vehicular communications (WVC) has been identified as a key technology for intelligent transportation systems (ITS) for a few years ago. IEEE 802.11p is the proposed standard for physical and MAC layer of WVC devices. The main objective of the standard is to change the frame format and increase delay spread tolerance introduced by vehicle mobility, in which the channel bandwidth is scaled from 20 MHz i.e. 802.11a to 10 MHz i.e. 802.11p. This paper proposes TDMA technique with fixed time slots and guard band between slots to ensure interoperability between wireless devices communicate in rapidly changing environment where transactions must be completed in small timeframe. The new TDMA sub-layer is proposed to be on-top of the conventional 802.11p MAC. The simulation results present the performance analysis and validate the efficiency of the proposed scheme.

A Hyperbola-Pair Based Lane Detection System for Vehicle Guidance

Abstract: methods used to carry out these functions involve camera- based systems relying on computer vision and image processing. In many proposed systems (2), lane detection consists of the localization of specific primitives such as the road markings of the surface of painted roads. Although this restriction simplifies the process of detection, two situations can disturb the process: the presence of other vehicles on the same lane and the partial occlusion of road markings ahead of the vehicle due to the presence of shadows caused by trees, buildings etc. This paper presents vision- based approach capable of reaching a real time performance in detection and tracking of structured road boundaries (painted or unpainted lane markings) with slight curvature, which is robust enough in presence of shadow conditions. Road boundaries are detected by fitting a parallel hyperbola pairs to the edges of the lane after applying the edge detection and Hough transform. The remainder of the paper is arranged as follows: Section II highlights some recent driver assist systems, Section III provides an overview of the proposed algorithm, Section IV provides results for various experimental conditions and Section V concludes and presents directions for future work.

Development of an Arabic text-to-speech system

Abstract: Research on Text-to-speech technology has received the interest of professional researchers in many languages which is a consequence of wide range of applications where Text-To-Speech is implemented. However, Arabic language, spoken by millions of people as an official language in 24 different countries, gained less attention compared with other languages despite the fact that it has a religious value for more than 1.6 billion Muslim worldwide. These facts exhibit the need for a high quality, small size, and completely free Arabic TTS with the ability of future improvements. The vowelized written text of Arabic language carries the pronunciation rules with limited exceptions, so rule-based system with an exception dictionary for words that fail with those letter-to-phoneme rules may be a much more reasonable approach. This paper is a development of a rule-based text- to- speech Hybrid synthesis system which is a combination formant and concatenation techniques with acceptable naturalness. The simulation results of the system shows good quality in handling word, phrase, and sentence level compared to other available Arabic TTS systems. The accuracy of the overall system is 96%. Further improvements need to be done for stressed syllable position and intonation.

Foreground segmentation-based human detection with shadow removal

Abstract: Recent research in video surveillance system has shown an increasing focus on creating reliable systems utilizing non-computationally expensive technique for observing humans' appearance, movements and activities, thus providing analytical information for advanced human behaviour analysis and realistic human modelling. In order for the system to function, it requires robust method for detecting human form from a given input of video streams. In this paper, we present a human detection technique suitable for video surveillance. The technique we propose includes background subtraction, foreground segmentation, and shadow removal. The proposed detection technique will first try to extract all foreground objects from the background and then moving shadows will be eliminated by a shadow detection algorithm. Finally, we perform a morphological reconstruction algorithm to recover the distorted foreground objects after shadow removal process. We define certain features that describe human and match them with the final objects obtained from earlier processing. The experimental result proves its validity and accuracy in various fixed outdoor and indoor video scenes.

Phonetically rich and balanced speech corpus for Arabic speaker-independent continuous automatic speech recognition systems

Abstract: This paper describes an efficient framework for designing and developing Arabic speaker-independent continuous automatic speech recognition systems based on a phonetically rich and balanced speech corpus. The speech corpus contains 415 sentences recorded by 42 (21 male and 21 female) Arabic native speakers from 11 Arab countries representing three major regions (Levant, Gulf, and Africa). The developed system is based on the Carnegie Mellon University (CMU) Sphinx tools. The Cambridge HTK tools were also used in some testing stages. The speech engine uses 3-emitting state Hidden Markov Models (HMM) for tri-phone based acoustic models. Based on experimental analysis of 4.07 hours of training speech data, the acoustic model used continuous observation's probability model of 16 Gaussian mixture distributions and the state distributions were tied to 400 senons. The language model contains both bi-grams and tri-grams. The system obtained 91.23% and 92.54% correct word recognition with and without diacritical marks respectively.

Phonetically rich and balanced arabic speech corpus: An overview

Abstract: Lack of spoken and written training data is one o f the main issues encountered by Arabic automatic speech recognition (ASR) researchers. Almost all written and spoken corpora are not readily available to the public and many of them can only be obtained by purchasing from the Linguistic Data Consortium (LDC) or the European Language Resource Association (ELRA). There is more shortage of spoken training data as compared to written training data resulting in a great need for more speech corpora in order to serve different domains of Arabic ASR. The available spoken corpora were mainly collected from broadcast news (radios and televisions), and telephone conversations having certain technical and quality shortcomings. In order to produce a robust speaker-independent continuous automatic Arabic speech recognizer, a set of speech recordings that are rich and balanced is required. The rich characteristic is in the sense that it must contain all the phonemes of Arabic language. It must be balanced in preserving the phonetics distribution of Arabic language too. This set of speech recordings must be based on a proper written set of sentences and phrases created by experts. Therefore, it is crucial to crea te a high quality written (text) set of the sentences and phrases before recording them. This work adds a new kind of possible speech data for Arabic language based text and speech applications besides other kinds such as broadcast news and telephone conversations. Therefore, this work is an invitation to all Arabic ASR developers and research groups to explore and capitalize.

The challenges of wireless internet access in vehicular environments

Abstract: The economics of currently available broadband access technologies motivate for innovate and deploy new system designs and applications in vehicular communication. The widely available and flexible Wi-Fi technique meets the cost and suitability targets for vehicular applications. To cope with the special requirements of vehicular, amendments of 802.11 standards at the MAC and PHY protocol level has been introduced in IEEE802.11p. IEEE 802.11p is the proposed standard for physical and MAC layer of wireless access in vehicular environment (WAVE) devices. The main objective of the new standard is to amend 802.to support vehicle mobility up to 150km/hr and distance 1000km by changing the frame format and increase delay spread tolerance introduced, in which the channel bandwidth is scaled from 20 MHz in 802.11a to 10 MHz in 802.11p. This paper reviews the challenges of wireless internet connectivity in vehicular communication. Transmission range, data handover and security are also covered in the paper. Other related works is reviewed and analyzed as well.

PC sound card based instrumentation and control

Abstract: The availability of inexpensive PC sound cards that can simultaneously play and record stereo digital audio files permits a single PC or laptop or netbook to function as both a signal generator and as a dual-channel recording digital oscilloscope. This paper presents how sound card with Matlab Data Acquisition Toolbox can be utilized for instrumentation and control. The buffer hardware circuit or signal conditioning circuit is developed and implemented to enable sound card to be functioned like oscilloscope. Preliminary results showed that sound card with the developed software has a good potential for instrumentation and control.

Design and optimization of linear array antenna based on the analysis of direction of arrival (DOA) estimation and beamforming algorithms

Abstract: This paper presents the design of 16-element linear array for smart antenna application. Conventional patch antenna is optimized to operate at 1.85GHz (3G applications) by using CST Microwave Studio parameterization. Accurate inter-element spacing has been designed to remove the mutual coupling which causes shifting of the maximum beam pattern towards undesired locations and shifting of the resonant frequency to higher frequency ranges. Narrow beams are also attainted by implementing the complex weights created by LMS beamforming algorithm.

A new method for generating cryptographically strong sequences of pseudo random bits for stream cipher

Abstract: The increasing privacy risks associated with the recent growth of multimedia streaming applications raised a big industry demand for secure and efficient stream cipher. The fact that stream ciphers do not expand messages, and tolerant to biterrors, make it highly desirable for many communication applications. During the last one and half decade several cryptosystems have been put forward, many of them have been more or less attacked. In one of the stages of stream cipher's development, it is required to design a cryptographically strong pseudo random bit generator (PRBG). In this paper a new method for generating secure sequences of pseudo random Bits for stream cipher using random map is presented, detailed statistical results of the generated bit sequences is showed, and finally a comparison with a true random sequence results is done.

Position-based QoS multicast routing protocol for mobile Ad Hoc networks

Abstract: Recently, the necessity of applications where many users have to interact in a close manner over mobile Ad-Hoc networks gains high popularity. Multicast communication is essential in this type of applications to reduce the overhead of group communication. For group-oriented multimedia applications Quality of Service (QoS) provision is a basic requirement, which makes an efficient QoS multicast routing protocol a very important issue. This paper proposes a location-based QoS multicast routing protocol via cooperation between Network and MAC layers. Along with this protocol, a location and group membership management scheme has been proposed. Unlike some of multicast routing protocols, the proposed approach limits maintaining the network topology to certain nodes to reduce control overhead and reduce bandwidth consumption. Our proposed protocol is scalable for large area networks with large multicast members regardless of the network density. Also, it achieves a significant reduction in processing overhead compared to flat QoS algorithms.

Performance evaluation of MPEG-4 video transmission over IEEE802.11e

Abstract: Transmitting MPEG-4 video over Wireless Local Area Networks is expected to be an important component of many emerging multimedia applications. One of the critical issues for multimedia applications is to ensure that the Quality of Service (QoS) requirement to be maintained at an acceptable level. The IEEE802.11 working group developed a standard called IEEE802.11e to support Quality of Service (QoS) in WLANs. This standard aims to support QoS by providing differentiated classes of service at the Medium Access Control (MAC) layer to enhance the ability of physical layers to deliver time-critical traffic in the presence of traditional data packets. In this Paper, Network Simulator 2 (NS-2) & Evalvid are used as simulation tool to evaluate the Performance of MPEG-4 Video Transmissions over IEEE802.11e. A modification of the parameters of NS-2 and Evalvid were done to present the evaluated method. This has allowed us to control the different design metrics values such as Frame/Packet loss, PSNR & Decodable Frame Rate (Q). In this paper, we evaluate a framework which consists of a MAC-centric cross-layer architecture to allow MAC layer to retrieve video streaming packet information, and a single-video multi-level queue to prioritize I/P/B slice (packet) delivery, the evaluated systematic scheme shows better results for lower packet loss, higher PSNR & Decodable Frame Rate (Q) for MPEG-4 video transmission over IEEE 802.11e..

Watermarking in Safe Region of frequency domain using complex-valued Neural Network

Abstract: It has been discovered by computational experiments that Complex Back-Propagation (CBP) algorithm is well suited for learning complex pattern [1], and it has been reported that this ability can successfully be applied in image processing with complex values. In this paper, a watermarking scheme based on Complex-Valued Neural Network, CVNN trained by CBP in transform domain is proposed. Fast Fourier Transform, FFT is used to obtain the complex values (real and imaginary part) of the host image. The complex values form the input data of CVNN. Neural networks performs best on detection, mapping, classification, learning and adaption. These features are employed to simulate the Safe Region (SR) to embed the watermark, thus, watermark are appropriately mapped to the safe region of selected coefficients. The implementation results have shown that this watermarking algorithm has high level of imperceptibility.

Fade Margin Analysis Due to Duststorm Based on Visibility Data Measured in a Desert

Abstract: Problem statement: The fade margin analysis of microwave propagation in areas affected by duststorm had been presented in this study. Approach: Based on long term duststorm data recorded in Riyadh-Saudi Arabia, the fade margin due to duststorm effects estimated. Results: The fade margin due to duststorm then derived under various water contents during the storm. Conclusion/Recommendations: It was particularly shown that duststorm have comparable effects on link reliability for typical storms.

Forward masking threshold estimation using neural networks and its application to parallel speech enhancement

Abstract: Forward masking models have been used successfully in speech enhancement and audio coding. Presently, forward masking thresholds are estimated using simplified masking models which have been used for audio coding and speech enhancement applications. In this paper, an accurate approximation of forward masking threshold estimation using neural networks is proposed. A performance comparison to the other existing masking models in speech enhancement application is presented. Objective measures using PESQ demonstrates that our proposed forward masking model, provides significant improvements (5-15 %) over four existing models, when tested with speech signals corrupted by various noises at very low signal to noise ratios. Moreover, a parallel implementation of the speech enhancement algorithm was developed using Matlab parallel computing toolbox.

Effect of frequency on fade slope based on rain attenuation data measured in malaysia

Abstract: Wave propagation at higher frequencies is highly influenced by rain. The measured rain attenuation data was collected from January 1999 to April 2000 at 15, 23 26, and 38 GHz frequencies for terrestrial microwave links in Malaysia. This research investigated the effects of frequency on the fade slope. The fade slope was analyzed using the measured data and it is found that the distribution for the fade slope is similar for all four frequencies and independent of frequencies.

Geographical Multicast Quality of Service Routing Protocol for Mobile Ad-Hoc Networks

Abstract: Recently, the necessity of applications where many users have to interact in a close manner over mobile Ad- Hoc networks gains high popularity. Multicast communication is essential in this type of applications to reduce the overhead of group communication. For group-oriented multimedia applications Quality of Service (QoS) provision is a basic requirement, which makes an efficient QoS multicast routing protocol a very important issue. This paper proposes a location-based QoS multicast routing protocol via cooperation between Network and MAC layers. Along with this protocol, a location and group membership management scheme has been proposed. To further reduce the control overhead and bandwidth consumption, we apply clustering strategy by partitioning the network topology into hexagon cells. Thus, maintaining the network topology is limited to certain nodes. The performance of the proposed protocol is evaluated using GloMoSim simulation environment. Simulation results show that our approach provides high packet delivery ratio associated with low control overhead.

Toward effective computational archetype for image guided neuro-surgery

Abstract: In recent years, the advantages offered by Image Guided Surgery (IGS)/ Computer Aided Surgery (CAS) to patients and medical professionals during a minimally-invasive surgical operation are overwhelming. Imaging techniques have had immense growth in their sophistication and can provide the surgeon with high quality guidance. This notwithstanding there is still room for improvement in almost all the areas of IGS application and stages such area as computational time which impedes its full deployment in intra-operative surgical interventional, segmentation, registration, visualization, plus IGS application software and instrumentation. This paper presents a model for the attainment of a more effective computational scheme by looking at possible computational improvement at all stages of IGS procedure but focusing on two aspects of IGS relating to intra-operative surgical intervention. If implemented, it will result into fast and better anatomical segmentation and fast computational scheme.

Design and fabrication of an intelligent irrigation control system

Abstract: This paper describes the design and fabrication of an intelligent Irrigation control system that allows intelligent control of the water applied to the field at right amounts and times. The system should have the capabilities to measure the water content in the soil so water can be applied as needed. The WATERMARK soil moisture sensor based on the measurement of the soil tension will provide the measurement of the water content. The system measures the soil tension, soil temperature and rain status and records the data in a file for future reference. It will apply water to field if a certain level of soil water tension is reached. This intelligent Irrigation control system is suitable for universities, research centers and farms where a control of the soil water content is required. The system can be used to study the water requirements for crops so irrigation can be scheduled efficiently.