Abstract: Non-linear Class-F PA has drawn a great attention among all different classes of PAs because of their capability of giving high power, providing good PAE and work in high frequency .The problem of class F PA is Poorlinearity.The efficiency linearity and complexity of class (F) power amplifier depend on the load network. In this research, Class-F amplifier with carefully chosen bias points , input and output impedance, designed load matching network and harmonic traps to get linearity and efficiency greeting with (GSM) application . The load network was designed by low pass flitter and matching network was designed to obtain the required optimum impedance at fundamental only to reduce complexity of PA and adding radial stub to provide a short circuit for higher degree harmonics and improve the linearity . The final design produced a PAE of 75.6% with 29.5dBm output power with (16dB) gain and TH distorted -46dBc.

Abstract: The timing criterions represented by the time center of mass flow (CT), spring pulse onset (S.P.O) and time of flood peak discharge (TP) of rivers are considered good indicators for the climate change occurs on their watershed areas. Spring snowmelt is a main water resources for large number of rivers in the world such as lesser Zab river in Iraq. An analysis for the daily discharge of lesser Zab measured at Dokan station and for climatic data such as temperature and rainfall measured at Alsulaymania meteorological station is carried out for spring and winter seasons of the 50 water years (1960-2009) after dividing this study period into two equal consecutive eons.The results indicate an early advance for the average values of these above criterions in the second eon by 5 , 5 and 15 days respectively in-comparison with the first eon as a result of early snowmelt feeding the river due to increasing temperature in the second eon (1.33)°c and decreasing rainfall (16) mm. The earlyadvance in the timing criterions of the flow hydrograph occur from snowmelt may effect on the storage efficiency and operation of reservoirslocated on the river and require taking these hydrological changes intoconsiderationinthewaterresourcesprojects.

Abstract: The main challenge in an automated diagnostic system for the early diagnosis of melanoma is the correct segmentation. In skindermoscope images manyartifacts such as ruler markings, air bubbles and hairsmust be removed to correctly diagnosis skin cancer. This paper focuses on the use of image processing techniques to automatically detects and removes hairs and ruler markings from dermoscopy images. The proposed algorithm includes two main steps: firstly, hairs and ruler marking are isolatedby generating a binary image mask include these artifacts only. The suggested mask procedure start with separate RGB dermoscopy images to the red, green and blue color components.Utilizingred channelto create the mask by applying noise removing on this plan, then adaptive canny edge detector is used for refinement by morphological operators. Secondly, the white regions ofthe mask are repaired based onpolygonsinpainting. Experiment on a number of dermoscopy images demonstrates that the proposed method produces superior results compared to existing techniques.

Abstract: Skin cancer has been the most common and represents 50% of all new cancers detected each year. If detected at an early stage, simple and economic treatment can cure it mostly. Accurate skin lesion segmentation is critical in automated early diagnosis system. This paper present a triple segmentation procedure based on the pixels distribution Bell-shaped (Normal), J-shaped, Reverse J-shaped and U-shaped peaks that is bimodal. According to the nature of dermoscopy images distributions, three segmentation methods are used to identify the normal skin cancer from malignant skin and to extract the tumor region. First, active contours are used for bell distribution shape. Second segmentation is done using adjusted ant colony optimization when the U-shaped peaks distribution was classify. Third segmentation strategies apply adaptive threshold for two J-shapes. Experiments on synthetic and real dermoscopy images demonstrate the advantages of the proposed methods that is able to produce ant colony optimization accurate segmentation when applied to a large number of skin cancer (melanoma) images.

Abstract: The maininterest in adaptive filters continues to grow as they begin to find practical applications in areassuch as channel equalization, echo cancellation, noise cancellation and many other adaptive signal-processing applications. The work presented in this paper focuses on optimizingmost popular adaptive filtering algorithms namely Least Mean Square (LMS) algorithm, Normalized Least Mean Square (NLMS) and Recursiveleast Squares (RLS) by using genetic optimizer approach. The tap-length are updated with the three adaptive algorithms according to the value of mean square error based on genetic style. The simulation results for noise cancellation in speechenhancementdemonstrate the good performance of the proposed algorithm in attenuating the noise with less hardware resources complexity.It is a nicetradeoff betweenhardware complexity, SNR ratioand the convergence speed.

Abstract: Abstract The quadrature power amplifier (QPA) is used in a CMOS radio frequencies (RF) amplifier for wireless communication system such as WLAN and mobile communication(W-CDMA).Because of its high efficiency at high frequency operation and good linearity.This paper presents a design and analysis in the timeand frequency domains for quadrature power amplifier based on 90-nm CMOS technology.The Class D power amplifier is used in the QPA configuration, because ofthe switch mode amplifiers provide amplification for modulated signals at RF with high efficiency and linearity. The quadrature signals are to be directly amplified by using a QPA without decomposing these signal to a phase and amplitude signal because of the lack of its separate avoid and the linearity and bandwidth requirements, thus reducing power consumption. The results obtained show that the QPA can be used in a wide band spectrum. The amplifier has very good power added efficiency (PAE%) about (70.5%)and IDM3 is (-62.6dBm) at maximum output power (24.35dBm) and input power greater than (20dBm). The amplitude distortionhas been obtained in this work about (1.36 dB/dB), and phase distortion about(0.27 degree/dB).

Abstract: The PID algorithm is the most popular controller used within the process industries. Robust easily understood algorithm could provide excellent control performance despite of the varied dynamic characteristic of process plant. However, the tuning of the PID controller parameters are not easy and does not give the optimal required response, especially with non-linear system. In the last years emerged several new intelligent optimization technique like, Adaptive Tabu search (ATS), Particle Swarm Optimization (PSO) techniques to get better control of the speed. This Paper deals with the speed control of single Phase Induction Motor with closed loop PID controller using (ATS) as intelligent optimization technique . The system is simulated using Matlab/Simulink GUI environment and the results are discusses. The Ziegler– Nichols methods for tuning PID controller is represent as a point of comparison. The intelligent optimization technique ATS is propos to tune the PID controller parameters to get optimal results of the closed loop of PID - ATS Controller. The Simulation results show the effectiveness of the propose method, which has get number of advantages.

Abstract: Object recognition in computer vision is the task of finding a given object in an image or video sequence. During the last decades it has received increasing attention from the computer vision community for a variety of reasons, ranging from counting objects for industrial application to the development of practical biometric systems and interactive, emotion-aware and capable human–machine interfaces. There are variety of approaches for object recognition problem, depending on the type of object, the degree of freedom of the object and the target application. Template matching is the most advanced and intensively developed areas of computer vision and has been a classical approach to the problems of locating and recognizing of an object in the image. The object of this paper is to improve the reliability of object recognition by describing a modified method for template matching based on the Sum of Squared Differences (SSD) equation, that gives the highest margin between other template matching methods, the main advantage is that the high margin resulting from it can be considered as more safe to avoid wrongly detecting /recognizing an object.