The matter of handwritten text recognition is as yet a major challenge to mainstream researchers. A few ways deal with this challenge have been endeavored in the most recent years, for the most part concentrating on the English pre-printed or handwritten characters space. Consequently, the need to effort a research concerning to Arabic texts handwritten recognition. The Arabic handwriting presents unique technical difficulties because it is cursive, right to left in writing and the letters convert its shapes and structures when it is putted at initial, middle, isolation or at the end of words. In this study, the Arabic text recognition is developed and designed to recognize image of Arabic text/characters. The proposed model gets a single line of Arabic text, which convert and segments into words and then segments into letters. A multilayer feed forward neural network is trained to recognize these segments as characters. The final results indicate and clarify that the proposed system perform an effective accuracy of recognition rated up to 83% for Arabic text.
Sewer sediment deposition is an important aspect as it relates to several operational and environmental problems. It concerns municipalities as it affects the sewer system and contributes to sewer failure which has a catastrophic effect if happened in trunks or interceptors. Sewer rehabilitation is a costly process and complex in terms of choosing the method of rehabilitation and individual sewers to be rehabilitated. For such a complex process, inspection techniques assist in the decision-making process; though, it may add to the total expenditure of the project as it requires special tools and trained personnel. For developing countries, Inspection could prohibit the rehabilitation proceeds. In this study, the researchers propos
... Show MoreThe turning process has various factors, which affecting machinability and should be investigated. These are surface roughness, tool life, power consumption, cutting temperature, machining force components, tool wear, and chip thickness ratio. These factors made the process nonlinear and complicated. This work aims to build neural network models to correlate the cutting parameters, namely cutting speed, depth of cut and feed rate, to the machining force and chip thickness ratio. The turning process was performed on high strength aluminum alloy 7075-T6. Three radial basis neural networks are constructed for cutting force, passive force, and feed force. In addition, a radial basis network is constructed to model the chip thickness ratio. T
... Show MoreThe uptake of Cd(II) ions from simulated wastewater onto olive pips was modeled using artificial neural network (ANN) which consisted of three layers. Based on 112 batch experiments, the effect of contact time (10-240 min), initial pH (2-6), initial concentration (25-250 mg/l), biosorbent dosage (0.05-2 g/100 ml), agitation speed (0-250 rpm) and temperature (20-60ºC) were studied. The maximum uptake (=92 %) of Cd(II) was achieved at optimum parameters of 60 min, 6, 50 mg/l, 1 g/100 ml, 250 rpm and 25ºC respectively.
Tangent sigmoid and linear transfer functions of ANN for hidden and output layers respectively with 7 neurons were sufficient to present good predictions for cadmium removal efficiency with coefficient of correlatio
... Show MoreEye loss may be caused as a result of eye trauma, accidents, or malignant tumors, which leads the patient to undergo surgery to remove the damaged parts. This research examines the potential of computer vision represented by Structure from Motion (SfM) photogrammetry in fabricating the orbital prosthesis as a noninvasive and low-cost technique. A low-cost camera was used to collect the data towards extracting the dense 3D data of the patient facial features following Structure from Motion-Multi View Stereo (SfM-MVS) algorithms. To restore the defective orbital, a Reverse Engineering (RE) based approach has been applied using the similarity RE algorithms based on the opposite healthy eye to rehabilitate the defected orbital precisely
... Show MoreOver the years, the prediction of penetration rate (ROP) has played a key rule for drilling engineers due it is effect on the optimization of various parameters that related to substantial cost saving. Many researchers have continually worked to optimize penetration rate. A major issue with most published studies is that there is no simple model currently available to guarantee the ROP prediction.
The main objective of this study is to further improve ROP prediction using two predictive methods, multiple regression analysis (MRA) and artificial neural networks (ANNs). A field case in SE Iraq was conducted to predict the ROP from a large number of parame
This research focuses on the services provided by news websites (IMN, Youm7, Huffington Post Arabic) to its audience of Internet users, as well as materials posted through its pages, trying to monitor and explain them to identify their types & features, and it›s functions, whether informational or non-informational, to know the technical potential of each of the news sites, with the entry of the latest technology information. The research used the analysis method to achieve the research objectives within the period from 1/1 to 31/1/2017. The researchers used the content analysis tool as a research tool to analyze the news sites and to know the services they provide through their pages. The research was divided into three parts, the
... Show MoreWith the spread of globalization, the need for translators and scholars has grown, as translation is the only process that helps bridge linguistic gaps. Following the emergence of artificial intelligence (AI), a strong competitor has arisen to the translators, sweeping through all scientific and professional fields, including translation sector, with a set of tools that aid in the translation process. The current study aims to investigate the capability of AI tools in translating texts rich in cultural variety from one language to another, specifically focusing on English-Arabic translations, through qualitative analysis to uncover cultural elements in the target language and determine the ability of AI tools to preserve, lose, or alter the
... Show MoreWith wireless sensor network (WSN) wide applications in popularity, securing its data becomes a requirement. This can be accomplished by encrypting sensor node data. In this paper a new an efficient symmetric cryptographic algorithm is presented. This algorithm is called wireless sensor network wavelet curve ciphering system (WSN-WCCS). The algorithm idea based on discrete wavelet transformation to generate keys for each node in WSN. It implements on hierarchical clustering WSN using LEACH protocol. Python programming language version 2.7 was used to create the simulator of WSN framework and implement a WSN-WCCS algorithm. The simulation result of the proposed WSN-WCCS with other symmetric algorithms has show
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