Online Education Management Information System (OEMIS): A Case Study for Primary Schools in Iraq

An Online Education Management Information System (OEMIS) is a structured scheduled and managed system for the collect, process and retrieves information about the three main components: school profile, Student Enrolment and Staff information. It also provides all the statistical data, reports, queries and dissemination of information needed to support the key activities and decision-makers in the Ministry of Education, Directorates and schools. These include but not limited to: data about the number of teachers for a specific course in a school, a province, in the whole of the country or the number of students passing or repeaters for one school or more. This study will identify the requirement model and proposed design of a web based educational management information system (OEMIS) for primary schools in Ministry of Education of Iraq

Hybrid model of post-processing techniques for Arabic optical character recognition

Optical character recognition (OCR) is used to extract text contained in an image. One of the stages in OCR is the post-processing and it corrects the errors of OCR output text. The OCR multiple outputs approach consists of three processes: differentiation, alignment, and voting. Existing differentiation techniques suffer from the loss of important features as it uses N-versions of input images. On the other hand, alignment techniques in the literatures are based on approximation while the voting process is not context-aware. These drawbacks lead to a high error rate in OCR. This research proposed three improved techniques of differentiation, alignment, and voting to overcome the identified drawbacks. These techniques were later combined into a hybrid model that can recognize the optical characters in the Arabic language. Each of the proposed technique was separately evaluated against three other relevant existing techniques. The performance measurements used in this study were Word Error Rate (WER), Character Error Rate (CER), and Non-word Error Rate (NWER). Experimental results showed a relative decrease in error rate on all measurements for the evaluated techniques. Similarly, the hybrid model also obtained lower WER, CER, and NWER by 30.35%, 52.42%, and 47.86% respectively when compared to the three relevant existing models. This study contributes to the OCR domain as the proposed hybrid model of post-processing techniques could facilitate the automatic recognition of Arabic text. Hence, it will lead to a better information retrieval

The UX of banking application on mobile phone for novice users

The aim of this article is to discuss how different factors affect the decision of intention to use and adopt mobile health applications using the extended technology acceptance model (TAM) among older adults in Iraq. “Perceived usefulness (PU), perceived ease of use (PEU), subjective norm (SN), and facilitating conditions (FC)” were four key predictors. Gender and age were included as factors for moderating the impact of two key TAM components in the proposed model (PU and PEU) on intention to use and adoption behaviors. The results of the past studies indicated that PU, PEU and SN were important predictors of adoption of mobile health applications among older adults in Iraq, While PU, SN, and FC were important predictors of the intention to use mobile health applications. Previous studies highlighted a strong impact of PEU on the intention to use mobile health applications on older adults than for younger adults. Implications are discussed for future research and practices