IRAQI JOURNAL OF COMPUTERS, COMMUNICATIONS, CONTROL AND SYSTEMS ENGINEERING

Autoregressive (AR) random fields are widely use to describe changes in the status of real-physical objects and implemented for analyzing linear & non-linear models. AR models are Markov processes with a higher order dependence for one-dimensional time series. Actually, various estimation methods were used in order to evaluate the autoregression parameters. Although in many applications background knowledge can often shed light on the search for a suitable model, but other applications lack this knowledge and often require the type of trial errors to choose a model. This article presents a brief survey of the literatures related to the linear and non-linear autoregression models, including several extensions of the main mode models and the models developed. The use of autoregression to describe such system requires that they be of sufficiently high orders which leads to increase the computational costs

In this paper the porous silicon (PS) was fabricated by photo electrochemical technique. Deposition of Cu2O thin film on nanocrystal-lines silicon by pulse laser was deposited by using the Tattoo removal laser, 2J and 1064 nm wavelength, and high purity Cu target at 350K in static air. Surface morphology and Photoluminescence for PS and Cu2O/Ps were investigated.

Electrocardiogram (ECG) examination via computer techniques that involve feature extraction, pre-processing and post-processing was implemented due to its significant advantages. Extracting ECG signal standard features that requires high processing operation level was the main focusing point for many studies. In this paper, up to 6 different ECG signal classes are accurately predicted in the absence of ECG feature extraction. The corner stone of the proposed technique in this paper is the Linear predictive coding (LPC) technique that regress and normalize the signal during the pre-processing phase. Prior to the feature extraction using Wavelet energy (WE), a direct Wavelet transform (DWT) is implemented that converted ECG signal to frequency domain. In addition, the dataset was divided into two parts – one for training and the other for testing purposes Which have been classified in this proposed algorithm using support vector machine (SVM). Moreover, using MIT AI2 Companion was developed by MIT Center for Mobile Learning, the classification result was shared to the patient mobile phone that can call the ambulance and send the location in case of serious emergency. Finally, the confusion matrix values are used to measure the proposed classification performance. For 6 different ECG classes, an accuracy ration of about_98.15% was recorded. This ratio became 100% for 3 ECG signal classes and decreases to 97.95% by increasing ECG signal to 7 classes.

Sign language is the basic way to communicate and understand ideas among people with disabilities, deaf and dumb, and to recognize and understand the meanings of the motions and the gestures used by them that requires knowledge of certain features such as hand position, form, motion, directions and facial expressions. Moreover, the extraction of image features is important and it plays a vital role in further analysis of image processing. Extracting the special features of the isolated Arabic sign language (ArSL) words based on Discrete Cosine Transform (DCT) was proposed in current paper. By monitoring and tracking the trajectory of the hands when single hand movement or double hands extract the required features. That is the independent sign language word features vector is incorporated as an input into the classification stage to derive the meaning of the word as voice or text. The research data were collected in cooperation with the Ministry of Labor and Social Affairs of Iraq with the assistance of the Special Needs Department and up to 40 words of isolated sign language collected. Two signs were taken as examples of feature extraction (Happy and water). Since the word happy gives an example of a sign word performed by two hands, on the other hand, the word water is performed with one hand, the Arabic sign language contains different words, part of them are performed with one hand and the other part with both hands.

Due to the recent advancements in the fields of Micro Electromechanical Sensors (MEMS), communication, and operating systems, wireless remote monitoring methods became easy to build and low cost option compared to the conventional methods such as wired cameras and vehicle patrols. Pipeline Monitoring Systems (PMS) benefit the most of such wireless remote monitoring since each pipeline would span for long distances up to hundreds of kilometers. However, precise monitoring requires moving large amounts of data between sensor nodes and base station for processing which require high bandwidth communication protocol. To overcome this problem, In-Situ processing can be practiced by processing the collected data locally at each node instead of the base station. This Paper presents the design and implementation of In-situ pipeline monitoring system for locating damaging activities based on wireless sensor network. The system built upon a WSN of several nodes. Each node contains high computational 1.2GHz Quad-Core ARM Cortex-A53 (64Bit) processor for In-Situ data processing and equipped in 3-axis accelerometer. The proposed system was tested on pipelines in Al-Mussaib gas turbine power plant. During test knocking events are applied at several distances relative to the nodes locations. Data collected at each node are filtered and processed locally in real time in each two adjacent nodes. The results of the estimation is then sent to the supervisor at base-station for display. The results show the proposed system ability to estimate the location of knocking event.

spatial division multiplexing (SDM) system has been considered as promising systems due to its ability to transport a higher bit rate for longer transmission distance. However, nonlinear phase noise (NPN (degrades SDM system performance. In this paper, we propose return-to-zero (RZ)-coded phase-conjugated twin waves (PCTWs) to improve the effectiveness of nonlinear distortion cancellation in the SDM system. In this approach, the PCTWs are modulated by m-array quadrature amplitude modulation (mQAM) then RZ encoded. After that, RZ-mQAM PCTWs are co-propagated over two fibres links. The received signals are superimposed to suppress the NPN. An analytical model that characterizes the performance of spatial-multiplexed (SM) RZ-coded PCTWs scheme is developed. Moreover, we numerically investigate the system performance with 4QAM format at 20Gsymbol/s rate. The results display that the performance is substantially better for the proposed scheme. Transmission reaches of both 4QAM PCTWs and RZ-4QAM PCTWs schemes are extended by 77.8% and 100%, respectively, in contrast with the 4QAM scheme.

The objective of this paper is to design a robust controller for a system modeled as a two-mass system, with a flexible coupling. Here, the flexible Joint between two-mass systems is characterized by a spring. In fact, a two-mass system represents most of an industrial drive, like rolling mill drives, automated arms, conveyor belts, and so on, that has a flexible joint, for which oscillation suppression and robust control against model uncertainties and external disturbances are very important. The proposed controller is based on sliding mode control with a back-stepping approach. Two subsystems (upper and lower) strategies are proposed for two- mass systems. On this basis, the classical sliding mode controller for each subsystem based on Lyapunov stability theory and sliding mode control theory is addressed to eliminate the influences of the parametric uncertainties, nonlinearities, and external disturbance load with the aid of sliding mode perturbation observer. Finally, comprehensive simulations are conducted to demonstrate the excellent performance of the proposed method.

In this paper, a fiber Bragg grating (FBG) strain sensor is simulated utilizing OptiGrating software. Then the proposed sensor is integrated into the wavelength division multiplexing (WDM) communication system via OptiSystem software in order to evaluate its performance as a strain sensor. The proposed WDM system has 4-channels with NRZ modulation format and 100 GHz frequency spacing. According to the results, the degradation in the receiving signal reaching the limitation value (6 for Q-factor and 10E-9 for BER) at applied strain ranging from 170 με–to– 180 με.