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Increasing Safety in Highways Transit Systems by Using Ethical Artificial Intelligence AI

“Smart city” projects have become fully developed and are actively using video analytics. Our study looks at how video analytics from surveillance cameras can help manage urban areas, making the environment safer and residents happier. Every year hundreds of people fall on subway and railway lines. The causes of these accidents include crowding, fights, sudden health problems such as dizziness or heart attacks, as well as those who intentionally jump in front of trains. These accidents may not cause deaths, but they cause delays for tens of thousands of passengers. Sometimes passers-by have time to react to the event and try to prevent it, or contact station personnel, but computers can react faster in such situations by using ethical AI. Video analytics systems can “see” a person on the tracks instantly, and automatically give trains a red light while issuing an alarm sound, as happens in modern car cameras when they give out sound and images through the associated alarm device in the event of any emergency occurring near the car.

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Publication Date
Sun Dec 30 2007
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Prediction of Fractional Hold-Up in RDC Column Using Artificial Neural Network

In the literature, several correlations have been proposed for hold-up prediction in rotating disk contactor. However,
these correlations fail to predict hold-up over wide range of conditions. Based on a databank of around 611
measurements collected from the open literature, a correlation for hold up was derived using Artificial Neiral Network
(ANN) modeling. The dispersed phase hold up was found to be a function of six parameters: N, vc , vd , Dr , c d m / m ,
s . Statistical analysis showed that the proposed correlation has an Average Absolute Relative Error (AARE) of 6.52%
and Standard Deviation (SD) 9.21%. A comparison with selected correlations in the literature showed that the
developed ANN correlation noticeably

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Publication Date
Sun Nov 26 2017
Journal Name
Journal Of Engineering
Compression Index and Compression Ratio Prediction by Artificial Neural Networks

Information about soil consolidation is essential in geotechnical design. Because of the time and expense involved in performing consolidation tests, equations are required to estimate compression index from soil index properties. Although many empirical equations concerning soil properties have been proposed, such equations may not be appropriate for local situations. The aim of this study is to investigate the consolidation and physical properties of the cohesive soil. Artificial Neural Network (ANN) has been adapted in this investigation to predict the compression index and compression ratio using basic index properties. One hundred and ninety five consolidation results for soils tested at different construction sites

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Publication Date
Wed Feb 21 2024
Journal Name
Al-rafidain Journal Of Medical Sciences ( Issn 2789-3219 )
Perceptions of Senior Pharmacy Students Towards the Impact of Artificial Intelligence on University Education and Scientific Writing: A Qualitative Study

Background: The roles of AI in the academic community continue to grow, especially in the enhancement of learning outcomes and the improvement of writing quality and efficiency. Objectives: To explore in depth the experience of senior pharmacy students in using artificial intelligence for academic purposes. Methods: This qualitative study included face-to-face individual interviews with senior pharmacy students from March to May 2023 using a pre-planned interview guide of open-ended questions. All interviews were audio-recorded. Thematic analysis was used to analyze the data. Results: The results were obtained from 15 in-depth face-to-face interviews with senior pharmacy students (5th and 4th years). Eight participants were male, and seven

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Publication Date
Mon Jul 01 2024
Journal Name
Journal Of Food Process Engineering
Artificial intelligence‐based modeling of novel non‐thermal milk pasteurization to achieve desirable color and predict quality parameters during storage
Abstract<sec><label></label><p>This study proposed using color components as artificial intelligence (AI) input to predict milk moisture and fat contents. In this sense, an adaptive neuro‐fuzzy inference system (ANFIS) was applied to milk processed by moderate electrical field‐based non‐thermal (NP) and conventional pasteurization (CP). The differences between predicted and experimental data were not significant (<italic>p</italic> > 0.05) for lightness (<italic>L</italic>*), redness‐greenness (<italic>a</italic>*), yellowness‐blueness (<italic>b</italic>*), total color differences (∆<italic>E</italic>), hue angle (<italic>h</italic></p></sec> ... Show More
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Publication Date
Fri Oct 30 2020
Journal Name
Journal Of Economics And Administrative Sciences
Development of human resources and their role in achieving artificial intelligence A survey of the views of a sample of workers in the cement plant

The research topic was chosen as a result of the importance of human resource in business organizations in general and the industrial process in particular. Without the human resource, business organizations cannot continue and achieve success and excellence, and the research problem has been diagnosed in the lack of sales of General Cement Company’s northern products, despite their distinctiveness, standing, and reputation in The market and its products with standard specifications, and through this problem, the following questions were raised:                                                    &nbs

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Publication Date
Mon Aug 28 2023
Journal Name
Journal Of Planner And Development
Increasing the design efficiency of roads in Al-Shatrah city center by achieving adequacy for car parking

        The research deals with the analysis of the city's commercial center using geographic information systems to solve the problem of congestion by evaluating the efficiency and adequacy of car parking lots according to local and Arab standards. Undoubtedly, the importance of car parking areas, as they are not within the desired efficiency within the city, will lead to congestion and traffic becomes very difficult. Thus, the transportation service loses its most important characteristic, which is the ease of movement. Therefore, there has become an urgent need to study and analyze it, as well as to verify the adequacy of the service, and the amount of deficit required to be provided to solve the tra

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Publication Date
Sat Jan 01 2022
Journal Name
Revista Iberoamericana De Psicología Del Ejercicio Y El Deporte
THE EFFECT OF USING GAMES IN DEVELOPING SOME CONCEPTS OF TRAFFIC SAFETY FOR FIFTH GRADE PRIMARY STUDENTS

Abstract The purpose of this paper is to preparing small games for fifth graders. And to identify the impact of these small games in developing some concepts of traffic safety for fifth graders. The two researchers used the experimental method to solve the research problem, and the research community was identified with students. The fifth grade of primary school in the province of Baghdad and a sample was chosen from the private Baghdad Primary School, which numbered (60) male and female students. They were distributed equally into two groups by simple random method (experimental and control groups). As for the most important conclusions reached by the two researchers, it is the presence of an effect of small games in developing some conce

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Publication Date
Wed Jul 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
Increasing the Setting Time of Local Gypsum (Joss) by the Use of TGP additive
Abstract<p>This research presents a study of using an additive for the objective of increasing the setting time of a material used in several aspects in the constructional field, this material is “Local-Gypsum” which is locally called “Joss”, and the additive used in this study is “Trees Glue Powder” denoted by “TGP”. Nine mixtures of Local-gypsum (joss) had been experimented in the current study to find their setting time, these mixes were divided into three groups according to their water-joss ratios (W/J) (0.3, 0.4 and 0.5), and each group was sub-divided into three sub-groups according to their TGP contents (0.0%, 0.3% and 0.6%). It was found that, when TGP is added with the </p> ... Show More
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Publication Date
Mon Mar 30 2009
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Prediction of bubble size in Bubble columns using Artificial Neural Network

In the literature, several correlations have been proposed for bubble size prediction in bubble columns. However these correlations fail to predict bubble diameter over a wide range of conditions. Based on a data bank of around 230 measurements collected from the open literature, a correlation for bubble sizes in the homogenous region in bubble columns was derived using Artificial Neural Network (ANN) modeling. The bubble diameter was found to be a function of six parameters: gas velocity, column diameter, diameter of orifice, liquid density, liquid viscosity and liquid surface tension. Statistical analysis showed that the proposed correlation has an Average Absolute Relative Error (AARE) of 7.3 % and correlation coefficient of 92.2%. A

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Publication Date
Mon Feb 01 2016
Journal Name
International Journal Of Applied Mathematics & Statistical Sciences
Topological Structures Using Mixed Degree Systems in Graph Theory

This paper is concerned with introducing and studying the M-space by using the mixed degree systems which are the core concept in this paper. The necessary and sufficient condition for the equivalence of two reflexive M-spaces is super imposed. In addition, the m-derived graphs, m-open graphs, m-closed graphs, m-interior operators, m-closure operators and M-subspace are introduced. From an M-space, a unique supratopological space is introduced. Furthermore, the m-continuous (m-open and m-closed) functions are defined and the fundamental theorem of the m-continuity is provided. Finally, the m-homeomorphism is defined and some of its properties are investigated.

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