Artificial intelligence (AI) is entering many fields of life nowadays. One of these fields is biometric authentication. Palm print recognition is considered a fundamental aspect of biometric identification systems due to the inherent stability, reliability, and uniqueness of palm print features, coupled with their non-invasive nature. In this paper, we develop an approach to identify individuals from palm print image recognition using Orange software in which a hybrid of AI methods: Deep Learning (DL) and traditional Machine Learning (ML) methods are used to enhance the overall performance metrics. The system comprises of three stages: pre-processing, feature extraction, and feature classification or matching. The SqueezeNet deep learning model was utilized to resize images and feature extraction. Finally, different ML classifiers have been tested for recognition based on the extracted features. The effectiveness of each classifier was assessed using various performance metrics. The results show that the proposed system works well, and all the methods achieved good results; however, the best results obtained were for the Support Vector Machine (SVM) with a linear kernel.
With the recent developments of technology and the advances in artificial intelligent and machine learning techniques, it becomes possible for the robot to acquire and show the emotions as a part of Human-Robot Interaction (HRI). An emotional robot can recognize the emotional states of humans so that it will be able to interact more naturally with its human counterpart in different environments. In this article, a survey on emotion recognition for HRI systems has been presented. The survey aims to achieve two objectives. Firstly, it aims to discuss the main challenges that face researchers when building emotional HRI systems. Secondly, it seeks to identify sensing channels that can be used to detect emotions and provides a literature review
... Show MoreFeature selection algorithms play a big role in machine learning applications. There are several feature selection strategies based on metaheuristic algorithms. In this paper a feature selection strategy based on Modified Artificial Immune System (MAIS) has been proposed. The proposed algorithm exploits the advantages of Artificial Immune System AIS to increase the performance and randomization of features. The experimental results based on NSL-KDD dataset, have showed increasing in performance of accuracy compared with other feature selection algorithms (best first search, correlation and information gain).
This work is focused on the design parameters and activity of artificial human finger for seven grips. At first, obtained the ideal kinematics of human fingers motion by analyzing the grips video which were recorded using a single digital camera recorder fitted on a tripod in sagital plane while the hand is moving. Special motion analysis software (Dartfish) the finger joint angles were studied using the video recording. Then the seven grips were modeled using static torque analysis, which calculates the amount of torque applied on the fingers joint grip depending on the results of the kinematic analysis. The last step of the work was to design the actuator (Muscle Wire) of artificial finger for the seven grips in a simple design approac
... Show MoreIn this research Artificial Neural Network (ANN) technique was applied to study the filtration process in water treatment. Eight models have been developed and tested using data from a pilot filtration plant, working under different process design criteria; influent turbidity, bed depth, grain size, filtration rate and running time (length of the filtration run), recording effluent turbidity and head losses. The ANN models were constructed for the prediction of different performance criteria in the filtration process: effluent turbidity, head losses and running time. The results indicate that it is quite possible to use artificial neural networks in predicting effluent turbidity, head losses and running time in the filtration process, wi
... Show MoreThe Foreign Account Tax Compliance Act (FATCA) basically targets US citizens’ accounts hold at foreign banks and financial institutions blush, seems and non-financial sector by the Act:( retirement plan companies, investment funds, hedge funds and family investment companies.)
The non Compliance of Foreign of financial institutions act will lead to financial looses and harm regarding reputation, especially for the countries that rely on foreign relations in their financial and banking activities, in addition to deducting 30 % of their total incomes and sales coming from the USA. These institutions can avoid it by entering into agreement with the Internal Revenue Service's to be foreign financial institutions complied with the a
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Abstract
Despite the fact of the importance and effectiveness of supporting the pricing policy for agriculture sector in Iraq, but this policy has stopped in supporting those agriculture production needs, and it was confined to support the final product only, and supporting the strategic corps exclusively after the U.S. Invasion in 2003, but after 2008 the state has returned to support some of this policy activities through providing financial loans through the agricultural initiative campaign, with trillions of iraqi dinars without any use, also providing support to some of the agricultural production needs such as fertilizers , tractors and agricultural combines, in addition supporting the pricing policy for the
... Show MorePurpose: This research seeks to provide a point of view based on the creation of sustainable value to the customer of the banks in the context of total quality management and relationship marketing. It aims to develop a model to measure the value of sustainable customer peduncular under total quality management PAL (administrative leadership, involvement of employees, continuous improvement, process improvement, staff training), through the mediation of relationship marketing and objective dimensions (administrative leadership, involvement of employees, continuous improvement, improving processes , staff training), and to explore any of the variables and dimensions more influential in the creation of sustainable value to the cust
... Show MoreThe photooxidative degradation process of plastics caused by ultraviolet irradiation leads to bond breaking, crosslinking, the elimination of volatiles, formation of free radicals, and decreases in weight and molecular weight. Photodegradation deteriorates both the mechanical and physical properties of plastics and affects their predicted life use, in particular for applications in harsh environments. Plastics have many benefits, while on the other hand, they have numerous disadvantages, such as photodegradation and photooxidation in harsh environments and the release of toxic substances due to the leaching of some components, which have a negative effect on living organisms. Therefore, attention is paid to the design and use of saf
... Show MoreThis work highlights the estimation of the Al-Khoser River water case that disposes of its waste directly into the Tigris River within Mosul city. Furthermore, the work studies the effects of environmental and climate change and the impact of pollution resulting from waste thrown into the Al-Khoser River over the years. Al-Khoser River is located in the Northern Mesopotamia of Mosul city. This study aims to detect the polluted water area and the polluted surrounding area. Temporal remote sensing data of different Landsat generations were considered in this work, specifically Enhanced Thematic Mapper Plus of 2000 and Operational Land Imager of 2015. The study aims to measure the amount of pollution in the study area over 15 years
... Show MoreIntroduction Periodontal diseases are ranked among the most common health problems affecting mankind. These conditions are initiated by bacterial biofilm, which is further modulated by several risk factors. Objectives To investigate the association of different risk factors with periodontal...