Optical Mark Recognition (OMR) is the technology of electronically extracting intended data from marked fields, such as squareand bubbles fields, on printed forms. OMR technology is particularly useful for applications in which large numbers of hand-filled forms need to be processed quickly and with a great degree of accuracy. The technique is particularly popular with schools and universities for the reading in of multiple choice exam papers. This paper proposed OMRbased on Modify Multi-Connect Architecture (MMCA) associative memory, its work in two phases: training phase and recognition phase. The proposed method was also able to detect more than one or no selected choice. Among 800 test samples with 8 types of grid answer sheets and total 58000 questions, the system exhibits an accuracy is 99.96% in the recognition of marked, thus making it suitable for real world applications.
Abstract
The study aims to find out the impact of expectations and perceptions in determining the position of the customer service quality received by him. Represent the expectations and perceptions customer’s key of service quality determinants. The customer's requirements and needs main pivot, who must be built all events and activities and efforts of service organizations, including the hotel and organizations that operate in an environment known as highly competitive , intensification and complexity of the conditions set by the customer and increasing day after day. The study sample of three Luxury hotels in Kurdistan region of Iraq a model. The use of service quality m
... Show MoreThe research (The Aesthetics of Lumia Art in Contemporary Textile Arts: An Analytical Study) included four chapters, the first to explain the research problem summarized by the question: Does the art of Lumia achieve aesthetic values in contemporary textile arts?, and aims to: Identify the aesthetics of Lumia art and its applied uses in contemporary textile arts, within the time period (2013-2022). The third chapter included: research procedures and sample analysis (4) models according to the descriptive analytical approach, and the fourth chapter dealt with: results, conclusions and recommendations as well as sources.
Abstract The painful history of slavery has profoundly affected the identities and social interactions of Afro-Caribbean migrants, whose descendants continue to contend with prejudice and socio-economic marginalization. Andrea Levy's semi-autobiographical novel, The Long Song (2010), traces the turbulent history of Jamaica in the nineteenth century through the lens of Miss Kitty, a character based on Levy's great-great-great grandmother, who was born a slave on the plantation Amity in Saint Catherine's parish. The narrative blends the historical with the fictional and depicts various environmental contexts, inscribed meanings, and human exchanges, including the prominence of social situations perceived through race and class tensions ironic
... Show MoreThis work is licensed under a Creative Commons Attribution 4.0 International License. Abstract This study examines the working capital management
Represent choices Behaviorism available to the Managerial leaders one of the prerequisites to run any beginnings of a psychological or dilemmas Managerial barriers to working in the field of work has been varied these options until it had taken several kinds of which contributed to the left different impacts on the alleviation of these problems, which prompted the researcher to raising the problem of study within the framework of questionable content how to contribute to that shown by Choices Behaviorism accredited to the Managerial leaders in the management of frustration
... Show MoreThe gas-lift method is crucial for maintaining oil production, particularly from an established field when the natural energy of the reservoirs is depleted. To maximize oil production, a major field's gas injection rate must be distributed as efficiently as possible across its gas-lift network system. Common gas-lift optimization techniques may lose their effectiveness and become unable to replicate the gas-lift optimum in a large network system due to problems with multi-objective, multi-constrained & restricted gas injection rate distribution. The main objective of the research is to determine the possibility of using the genetic algorithm (GA) technique to achieve the optimum distribution for the continuous gas-lift injectio
... Show MoreThe internet of medical things (IoMT), which is expected the lead to the biggest technology in worldwide distribution. Using 5th generation (5G) transmission, market possibilities and hazards related to IoMT are improved and detected. This framework describes a strategy for proactively addressing worries and offering a forum to promote development, alter attitudes and maintain people's confidence in the broader healthcare system without compromising security. It is combined with a data offloading system to speed up the transmission of medical data and improved the quality of service (QoS). As a result of this development, we suggested the enriched energy efficient fuzzy (EEEF) data offloading technique to enhance the delivery of dat
... Show MoreThis abstract focuses on the significance of wireless body area networks (WBANs) as a cutting-edge and self-governing technology, which has garnered substantial attention from researchers. The central challenge faced by WBANs revolves around upholding quality of service (QoS) within rapidly evolving sectors like healthcare. The intricate task of managing diverse traffic types with limited resources further compounds this challenge. Particularly in medical WBANs, the prioritization of vital data is crucial to ensure prompt delivery of critical information. Given the stringent requirements of these systems, any data loss or delays are untenable, necessitating the implementation of intelligent algorithms. These algorithms play a pivota
... Show MoreDuring COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve
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