Bilal Ghazal

Smart traffic light control system

Traffic light control systems are widely used to monitor and control the flow of automobiles through the junction of many roads. They aim to realize smooth motion of cars in the transportation routes. However, the synchronization of multiple traffic light systems at adjacent intersections is a complicated problem given the various parameters involved. Conventional systems do not handle variable flows approaching the junctions. In addition, the mutual interference between adjacent traffic light systems, the disparity of cars flow with time, the accidents, the passage of emergency vehicles, and the pedestrian crossing are not implemented in the existing traffic system. This leads to traffic jam and congestion. We propose a system based on PIC microcontroller that evaluates the traffic density using IR sensors and accomplishes dynamic timing slots with different levels. Moreover, a portable controller device is designed to solve the problem of emergency vehicles stuck in the overcrowded roads.

Multi control chandelier operations using XBee for home automation

Home automation systems aim to control all home activities and functionalities. Control can be done through a remote control that sends command signals wirelessly by means of infrared radiation, Bluetooth connectivity, or any other RF technology as well as via internet or GSM communication. The controlled target devices usually include domestic appliances, security and safety systems, HVAC systems, home theater, lights, and many other home tasks. In this study, we design, program, and implement a light chandelier with multiple functionalities. The operational modalities comprise manual and remote on/off, different working timers, daylight, romance option, light dimming, party style, on/off luminosity turning, password keys, and motion detection. The chandelier remote control uses XBee transceivers that fulfill secure commands and prevent any interference between similar systems. The remote control realization is based on PIC 16F877A microcontroller and supported by an LCD to display notifications.

Classification of Contrast Ultrasound Images using Autoregressive Model Coupled to Gaussian Mixture Model

Contrast ultrasound images are not clear enough to be directly adopted in the diagnostic. In fact, the ultrasound agents enhance the vascular zones but unfortunately the signals backscattered from agent and tissues are still close. Therefore, it is necessary to implement image-processing techniques to enhance the contrast echo and thus have the capability of classification. In this article, we apply a new approach based on the autoregressive model coupled to the Gaussian mixture model to represent both agent and tissue behaviors. Then, we process the resultant image by a classification method based on a fixed windows size in order to obtain a satisfying differentiation of the ultrasound image into two classes. Finally, we adopt the agent to tissue ratio (ATR) factor and the Fisher criterion to compare the performance of this method with existing techniques as harmonic and B mode.

Autoregressive modeling application for vascular zones detection in the contrast echographic images

Contrast agents are used in ultrasound imaging to enhance blood region and thereby separate the perfused area and the surrounding tissues. But unfortunately the signals backscattered from agent and tissues are still close. So it is necessary to implement signal processing to enhance the contrast echo. In this article, we apply the autoregressive model to exploit the nonlinear behavior agent properties. Then, we process the obtained pictures by a classification method followed by erosion dilatation algorithm to obtain a satisfying differentiation of the ultrasound image into two classes. The Agent to Tissue Ratio (ATR) factor is used to compare the performance of the methods, and the Fisher criterion is used to study the classification feasibility.

Parameter estimation of scattering components using matrix pencil based support vector regression

Time delay estimation is a fundamental signal-processing problem encountered in numerous applications. The backscattered signals emanating from a source and arriving at a receiver are usually represented by a model called the undamped exponential model. This model is used for narrowband signals whose time delays are usually estimated using super-resolution algorithms. For wideband signals, however, a geometric-theory-of-diffraction (GTD) based model is usually used to incorporate the frequency dependency of individual backscattered signals. In the literature, this model is approximated to allow for the application of existing super-resolution algorithms at the expense of estimation accuracy. This paper proposes a new model-independent estimation method called Matrix Pencil Based Support Vector Regression to overcome the limitations of existing methods. Simulation results show that the proposed algorithm succeeds in accurately estimating the time delays and frequency dependency parameters of the GTD-based model.

Wide-band slotted flower PIFA antenna for multimedia handhelds terminals

The rapid progress in wireless communication systems and handheld terminal devices has made the implementation of small multi-band antennas one of the main technical challenges. The number of wireless systems in which multimode mobile terminals are required to operate has been growing constantly in recent years. Nowadays handheld terminal phones use various cellular bands (GSM850/900/1800/1900 + 3G/4G/5G), wireless LAN, Bluetooth, Digital TV (DVB-H), FM radio, GPS, RFID, UWB, and WiMAX The narrow bandwidth constitutes the major disadvantage of microstrip antennas in most practical applications. This study proposes a new wideband small size flower-shaped PIFA antenna. The PIFA design has newest flower structure and is supported by two or three shorting pins. The layer patch is slotted by Allah name in Arabic. A capacitive feeding of the antenna was done via 50 Ω coaxial cable to achieve impedance matching. The simulation was done using the high frequency HFSS10 simulator for different scenarios. Simulated results on the return loss, the radiation pattern, and the gain are promising. The devised antenna could be implemented in many wireless communication standards such as PCS (1850-1990 MHz), UMTS (1920-2170 MHz), WLAN 802.11 b/g (2400-2484 MHz), WIMAX (2.5-2.69 GHz), and WIMAX (3.4-3.6 GHz).

Improvement of the GMM‐AR classification of multiframe contrast ultrasound images using gaussian filter

Despite the use of contrast agents that enhance the visualization of vascular zones, the backscattered signals from the contrast agent and tissue are still close which prevents the direct wide ultrasonic use in diagnosis. Thus, it was necessary to implement image‐processing techniques that enhance the contrast echo and have the capability of classification. We have applied a new approach based on the autoregressive model where an image of prediction errors is calculated in the first phase. Then, a Gaussian filter is applied in order to model well afterward both agent and tissue behaviors by a Gaussian mixture model. The Agent to Tissue Ratio (ATR)factor and Fisher criterion are adopted to compare the performance of this method with existing techniques as the harmonic and B mode techniques. The experiments conducted have shown the advantages of our proposed approach where an increasing of ATR and Fisher are recorded. In fact, our ATR attains 19.20 dB which represents a good improvement in comparison with B...