Haider Th. Salim ALRikabi

Bio: Haider Th. Salim ALRikabi is an academic researcher from University of Wasit. The author has contributed to research in topics: Computer science & The Internet. The author has an hindex of 17, co-authored 41 publications receiving 569 citations. Previous affiliations of Haider Th. Salim ALRikabi include University College of Engineering.

Generation of high dynamic range for enhancing the panorama environment

Abstract: This paper presents a methodology for enhancement of panorama images environment by calculating high dynamic range. Panorama is constructing by merge of several photographs that are capturing by traditional cameras at different exposure times. Traditional cameras usually have much lower dynamic range compared to the high dynamic range in the real panorama environment, where the images are captured with traditional cameras will have regions that are too bright or too dark. A more details will be visible in bright regions with a lower exposure time and more details will be visible in dark regions with a higher exposure time. Since the details in both bright and dark regions cannot preserve in the images that are creating using traditional cameras, the proposed system have to calculate one using the images that traditional camera can actually produce. The proposed systems start by get LDR panorama image from multiple LDR images using SIFT features technology and then convert this LDR panorama image to the HDR panorama image using inverted local patterns. The results in this paper explained that the HDR panorama images that resulting from the proposed method is more realistic image and appears as it is a real panorama environment.

Enhanced Data Security of Communication System Using Combined Encryption and Steganography

Abstract: Data security has become a paramount necessity and more obligation in daily life. Most of our systems can be hacked, and it causes very high risks to our confidential files inside the systems. Therefore, for various security reasons, we use various methods to save as much as possible on this data, regardless of its different forms, texts, pictures, videos, etc. In this paper, we mainly rely on storing the basic image which should be protected in another image after changing its formal to composites using the DWT wavelet transform. The process of zeroing sites and storing their contents technique is used to carry the components of the main image. Then process them mathematically by using the exponential function. The result of this process is to obtain a fully encrypted image. The image required to be protected from detection and discrimination is hidden behind the encrypted image. The proposed system contains two algorithms. the first algorithm is used for encryption and hiding, but the second algorithm is designed for returning and decoding the main image to its original state with very efficiently.

The Detection of Counterfeit Banknotes Using Ensemble Learning Techniques of AdaBoost and Voting

Abstract: The movement of cash flow transactions by either electronic channels or physically created openings for the influx of counterfeit banknotes in financial markets. Aided by global economic integration and expanding international trade, attention must be geared at robust techniques for the recognition and detection of counterfeit banknotes. This paper presents ensemble learning algorithms for banknotes detection. The AdaBoost and voting ensemble are deployed in combination with machine learning algorithms. Improved detection accuracies are produced by the ensemble methods. Simulation results certify that the ensemble models of AdaBoost and voting provided accuracies of up to 100% for counterfeit banknotes.

The Interactive Role Using the Mozabook Digital Education Application and its Effect on Enhancing the Performance of eLearning

Abstract: The study examined the impact of the use of the Mozabook application for digital education in enhancing the performance of electronic-learning to ensure strategic educational success and the urgent need to use E-learning to increase and enable scientific knowledge to confront the exceptional circumstances that afflict the world in general and Iraq in particular for the spread of the Corona epidemic and its harm to society and home quarantine. Therefore, the diversity of software ap-plications available to teachers and students reflected the tremendous development and unique potential to achieve the goals of E-learning of what increased of knowledge of community awareness of how to use modern E-learning tools and in a way that ensures accuracy in use and awareness of its effective role in spreading education among the student community. The study aims to find better methods to deal and to prefer the role of digital education as in creating a knowledge-ability that meets the requirements of the educational process from methodological content, educational method and study tools such as blackboard, notebook, drawing tools and scientific, engineering, chemical, biological, geo-graphic and historical laboratories and other requirements that attract the student and his eagerness to study in this Digital education, so an application that works with three-dimensional technology was chosen with the availability of all audio, visual and sensory means to increase the interaction and desire of the student for the scientific subject, which is the educational Mozabook application. The study included test of major hypotheses, which leads to knowledge and determination of whether there is a correlation relationship, or an effect with significant moral, each according to its location for the application of the Mozabook digital educa-tion and E-learning. The two researchers selected academics and students as a field of the Ministry of Higher Education and Scientific Research for practical application based on the use of the questionnaire and the benefit of analyzing its results after its treatment using a number of statistical methods such as arithmetic mean, standard deviation, correlation coefficient, regression coefficient and path analysis.

Reducing the Data Rate in Internet of Things Applications by Using Wireless Sensor Network

Abstract: Du to the raising number of using Internet of Things (I O T) for personal and commercial devices and applications, as well as the continues needs for improving the quality of the performance for the internet – connected devices enhance the researchers to investigate solutions for managing the data through the network Because of the fact that the internet-connected devices needs addresses for each sensor node uses the IP-network and a large number of electronic modules is fabricated to be compatible with IPv4 only like NodeMcu, ESP8266, Arduino WIFI, and ESP32 with knowing that the IPv4 has a limited addresses number that will not be enough for the needs of IOT developments, Many researchers turned to IPv6. In the proposed system, another solution is suggested instead of the IPV6. The proposed idea is based on Non-IP Wireless Sensor Network (WSN) by connecting many sensing nodes to the sink-node that has an IP to forward the data to the server to be visualized in a web-portal. By this method, it is able to connect more than one node to the internet over only one IP, there for the data rate that are needed will be decreased. In addition, by using the non-IP network, the data rate and the power consuming by the sensor nodes have been reduced, the practical results are discussed for connecting four nodes over one IP4 and how it will reduce the data rate and the power consuming. In this work, the esp33 has been used as a Sink-node, and the wireless transceiver module( NRF24) has been utilized to transmit the data from nodes to esp32.

Inductive Teaching and Learning Methods: Definitions, Comparisons, and Research Bases

Abstract: Traditional engineering instruction is deductive, beginning with theories and progressing to the applications of those theories Alternative teaching approaches are more inductive Topics are introduced by presenting specific observations, case studies or problems, and theories are taught or the students are helped to discover them only after the need to know them has been established This study reviews several of the most commonly used inductive teaching methods, including inquiry learning, problem-based learning, project-based learning, case-based teaching, discovery learning, and just-in-time teaching The paper defines each method, highlights commonalities and specific differences, and reviews research on the effectiveness of the methods While the strength of the evidence varies from one method to another, inductive methods are consistently found to be at least equal to, and in general more effective than, traditional deductive methods for achieving a broad range of learning outcomes

Advanced Digital Signal Processing And Noise Reduction

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