Crime is a threat to any nation’s security administration and jurisdiction. Therefore, crime analysis becomes increasingly important because it assigns the time and place based on the collected spatial and temporal data. However, old techniques, such as paperwork, investigative judges, and statistical analysis, are not efficient enough to predict the accurate time and location where the crime had taken place. But when machine learning and data mining methods were deployed in crime analysis, crime analysis and predication accuracy increased dramatically. In this study, various types of criminal analysis and prediction using several machine learning and data mining techniques, based on the percentage of an accuracy measure of the previous work, are surveyed and introduced, with the aim of producing a concise review of using these algorithms in crime prediction. It is expected that this review study will be helpful for presenting such techniques to crime researchers in addition to supporting future research to develop these techniques for crime analysis by presenting some crime definition, prediction systems challenges and classifications with a comparative study. It was proved though literature, that supervised learning approaches were used in more studies for crime prediction than other approaches, and Logistic Regression is the most powerful method in predicting crime.
Today we are witnessing huge scientific and technical progress so we need more skills and methods of thinking that needs to be acquired by the teacher, as the importance of computers in education there are many teachers suffering of the difficulty in teaching for pupils . researchers tried to find a good suitable way with the technological interests for now which represent by computer design software and the introduction of enrichment activities in the curriculum because it is one of a contemporary trends for the development of the Arabic language with various levels of education and knowing if this program has negative or positive impact.
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... Show MoreEarly detection of brain tumors is critical for enhancing treatment options and extending patient survival. Magnetic resonance imaging (MRI) scanning gives more detailed information, such as greater contrast and clarity than any other scanning method. Manually dividing brain tumors from many MRI images collected in clinical practice for cancer diagnosis is a tough and time-consuming task. Tumors and MRI scans of the brain can be discovered using algorithms and machine learning technologies, making the process easier for doctors because MRI images can appear healthy when the person may have a tumor or be malignant. Recently, deep learning techniques based on deep convolutional neural networks have been used to analyze med
... Show MoreIn architectural learning, it is difficult to stimulate cultural awareness through the traditional education approaches, which results in historic places being neglected as knowledge sources. This research explores the premise that sketch-based visual storytelling may act as a generative approach to connect cognition, emotion, and behavior in historical contexts. The study adopts a qualitative methodology to explore a learning experience comprising two phases: the first is a formal educational setting, and the second is a historical and cultural context, aiming to investigate the role of sketch-based storytelling in enhancing cultural awareness. MAXQDA was employed to code the students’ storyboards on three levels of cultural awareness, m
... Show MoreTo date, comprehensive reviews and discussions of the strengths and limitations of Remote Sensing (RS) standalone and combination approaches, and Deep Learning (DL)-based RS datasets in archaeology have been limited. The objective of this paper is, therefore, to review and critically discuss existing studies that have applied these advanced approaches in archaeology, with a specific focus on digital preservation and object detection. RS standalone approaches including range-based and image-based modelling (e.g., laser scanning and SfM photogrammetry) have several disadvantages in terms of spatial resolution, penetrations, textures, colours, and accuracy. These limitations have led some archaeological studies to fuse/integrate multip
... Show Moreمستخلص البحث كان الهدف من البحث هو معرفة نسب نجاح وفشل بعض المهارات الهجومية المركبة من ثلاث مهارات بكرة السلة للشباب.، إذ لوحظ بأنه لا تكتمل عملية التقدم من خلال إتقان المهارات الأساسية الهجومية المفردة فقط وإنما في القدرة على الدقة والثبات في أداء الربط فيما بينها (التركيب)، وعكس ما تقدم يعد واحد من الأسباب التي تسبب ضعفاً في المستوى ومما يزيد من الأخطاء في الأداء تبعاً لذلك. وفي ضوء ما تقدم تم تصوير ست مباري
... Show MoreThis research was aimed to study the osmotic efficiency of the draw solutions and the factors affecting the performance of forward osmosis process : The draw solutions used were magnesium sulfate hydrate (MgSO4.7H2O) pojtassium chloride (KCL), calcium chloride (CaCl2) and ammonium bicarbonate (NH4HCO3). It was found that water flux increases with increasing draw solution concentration, and feed solution flow rate and decreases with increasing draw solution flow rate and feed solution concentration. And also found that the efficiency of the draw solutions is in the following order:
CaCl2> KCI > NH4HCO3> MgSO4.7H
This article describes how to predict different types of multiple reflections in pre-track seismic data. The characteristics of multiple reflections can be expressed as a combination of the characteristics of primary reflections. Multiple velocities always come in lower magnitude than the primaries, this is the base for separating them during Normal Move Out correction. The muting procedure is applied in Time-Velocity analysis domain. Semblance plot is used to diagnose multiples availability and judgment for muting dimensions. This processing procedure is used to eliminate internal multiples from real 2D seismic data from southern Iraq in two stages. The first is conventional Normal Move Out correction and velocity auto picking and
... Show MoreThis research will cover different aspects of estimating process of construction work in a desert area. The inherent difficulties which accompany the cost estimating of the construction works in desert environment in a developing country, will stem from the limited information available, resources scarcity, low level of skilled workers, the prevailing severe weather conditions and many others, which definitely don't provide a fair, reliable and accurate estimation. This study tries to present unit price to estimate the cost in preliminary phase of a project. Estimations are supported by developing mathematical equations based on the historical data of maintenance, new construction of managerial and school projects.
... Show MoreThis paper presents theoretical parametric study of the curvature ductility capacity for reinforced concrete column sections. The study considers the behavior of concrete and reinforcing steel under different strain rates. A computer program has been written to compute the curvature ductility taking into account the spalling in concrete cover. Strain rate sensitive constitutive models of steel and concrete were used for predicting the moment-curvature relationship of reinforced concrete columns at different rate of straining. The study parameters are the yield strength of main reinforcement, yield strength of transverse reinforcement, compressive strength of concrete, spacing of ties and the axial load. The results indicated that hi
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