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Using Information Technology for Comprehensive Analysis and Prediction in Forensic Evidence
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With the escalation of cybercriminal activities, the demand for forensic investigations into these crimeshas grown significantly. However, the concept of systematic pre-preparation for potential forensicexaminations during the software design phase, known as forensic readiness, has only recently gainedattention. Against the backdrop of surging urban crime rates, this study aims to conduct a rigorous andprecise analysis and forecast of crime rates in Los Angeles, employing advanced Artificial Intelligence(AI) technologies. This research amalgamates diverse datasets encompassing crime history, varioussocio-economic indicators, and geographical locations to attain a comprehensive understanding of howcrimes manifest within the city. Leveraging sophisticated AI algorithms, the study focuses on scrutinizingsubtle periodic patterns and uncovering relationships among the collected datasets. Through thiscomprehensive analysis, the research endeavors to pinpoint crime hotspots, detect fluctuations infrequency, and identify underlying causes of criminal activities. Furthermore, the research evaluates theefficacy of the AI model in generating productive insights and providing the most accurate predictionsof future criminal trends. These predictive insights are poised to revolutionize the strategies of lawenforcement agencies, enabling them to adopt proactive and targeted approaches. Emphasizing ethicalconsiderations, this research ensures the continued feasibility of AI use while safeguarding individuals'constitutional rights, including privacy. The anticipated outcomes of this research are anticipated tofurnish actionable intelligence for law enforcement, policymakers, and urban planners, aiding in theidentification of effective crime prevention strategies. By harnessing the potential of AI, this researchcontributes to the promotion of proactive strategies and data-driven models in crime analysis andprediction, offering a promising avenue for enhancing public security in Los Angeles and othermetropolitan areas.

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Publication Date
Tue Dec 31 2019
Journal Name
Iraqi Geological Journal
GEOHISTORY ANALYSIS AND BASIN DEVELOPMENT OF THE LATE BERRIASIAN-APTIAN SUCCESSION, SOUTHERN IRAQ
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The studied succession is deposited during late Berriasian-Aptian interval, which is represented by the Zubair, Ratawi, Yamama formations. The present study includes stratigraphic development and basin analysis for 21 boreholes (Rachi-1, 2; Rifaei-1, Diwan- 1; Ratawi-1, 2; Halfaia-5; West Qurna 12, 15; Nahr Umr-7,8; Zubair-47,49; North Rumaila- 72, 131, 158; Suba-7; Majnoon-2, 3 and Luhais-2, 12) distributed within 13 oil fields in the southern Iraq. The back-stripping process determined the original direction of basin depocenter for the studied succession. The Yamama basin in the study area stretches from southeast to southwest with single depocenters, it was located in the southeast of the study area near wells Mj-2, Mj-3.NR-8 and

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Publication Date
Sun Oct 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
discriminate analysis and logistic regression existence of multicolleniarty problem(Empirical Study on Anemia)
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The method binery logistic regression and linear discrimint function of the most important statistical methods used in the classification and prediction when the data of the kind of binery (0,1) you can not use the normal regression therefore resort to binary logistic regression and linear discriminant function in the case of two group in the case of a Multicollinearity problem between the data (the data containing high correlation) It became not possible to use binary logistic regression and linear discriminant function, to solve this problem, we resort to Partial least square regression.

In this, search the comparison between binary lo

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Publication Date
Thu Mar 01 2012
Journal Name
Journal Of Magnetism And Magnetic Materials
Structural analysis, magnetic and electrical properties of samarium substituted lithium–nickel mixed ferrites
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Publication Date
Mon Oct 17 2022
Journal Name
Sustainability
Analysis and Residual Behavior of Encased Pultruded GFRP I-Beam under Fire Loading
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In this paper, fire resistance and residual capacity tests were carried out on encased pultruded glass fiber-reinforced polymer (GFRP) I-beams with high-strength concrete beams. The specimens were loaded concurrently under 25% of the ultimate load and fire exposure (an increase in temperature of 700 °C) for 70 min. Subsequently, the fire-damaged specimens were allowed to cool and then were loaded statically until failure to explore the residual behaviors. The effects of using shear connectors and web stiffeners on the residual behavior were investigated. Finite Element (FE) analysis was developed to simulate the encased pultruded GFRP I-beams under the effect of fire loading. The thermal analyses were performed using the general-pu

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Publication Date
Wed Jul 31 2024
Journal Name
Cureus
Neuro-Ophthalmic Manifestations of Carotid Cavernous Fistulas: A Systematic Review and Meta-Analysis
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Publication Date
Wed May 27 2020
Journal Name
Acta Biologica Szegediensis
Phytochemical analysis, cytotoxicity and antioxidant activity of cuckoo pint (Arum maculatum) leaf extract
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Arum maculatum is traditionally used for the control of many diseases and illnesses such as kidney pain, liver injury, hemorrhoids. However, the detailed biomedical knowledge about this species is still lacking. This study reports on the bioactive components and the possible mechanisms underlying the antioxidant, anti-inflammatory and cytotoxic activity of A. maculatum leaf extract. Gas chromatography-mass spectrometry (GC-MS) was used for phytochemical analysis. Assay of 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide ) (MTT) was used to determine the cytotoxicity in the murine cell line L20B upon exposure to different extract concentrations for 24 h. Enzyme-linked immunosorbent assay (ELISA) was used to detect pro-in

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Publication Date
Tue Dec 22 2020
Journal Name
Clinical And Experimental Dental Research
Prevalence and factors influencing reporting of true periodontal chief complaints: A retrospective analysis
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Abstract<sec><title>Objectives

To investigate the prevalence of true periodontal chief complaints (CC) and the factors affecting their reporting by patients with periodontal diseases (PD).

Materials and Methods

This cross‐sectional study was based on retrospective analysis of available periodontal records. Different personal and demographic variables were obtained from these records including CC, age, gender, working status, past medical/dental history, smoking status and diagnosis. In addition, clinical parameters of plaque index, gingival index, probing pocket depth (PPD), and number of missing teeth. Periodontal CC were r

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Publication Date
Sat Jan 01 2022
Journal Name
Structural Durability &amp; Health Monitoring
Seismic Analysis of Reinforced Concrete Silos under Far-Field and Near-Fault Earthquakes
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Publication Date
Sun Feb 24 2019
Journal Name
Iraqi Journal Of Physics
Measuring the concentration of uranium for adults teeth in adjacent areas of Tigris river in Baghdad city using nuclear track detector CR-39
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In this study, the fission track registration technique with the CR-39 detector are using to determination the uranium concentrations for seventeen samples of teeth distributed in four districts in Baghdad City .Five samples taken from both Al-Durra District and Al-Jadiriyia District, Four samples taken from Al-Karrda (Alaatar street) Taken four samples and three samples taken from Al-Zuafrania and by 0.5gm in weight and 1.5 mm in thickness. The uranium concentrations in teeth samples measured by using fission tracks registration in (CR-39) track detector that caused by the bombardment of (U) with thermal neutrons from (241 Am-Be) neutron source that has flux of (5 ×103 n cm-2 s-1). The concen

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Publication Date
Sun Sep 30 2012
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Development of PVT Correlation for Iraqi Crude Oils Using Artificial Neural Network
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Several correlations have been proposed for bubble point pressure, however, the correlations could not predict bubble point pressure accurately over the wide range of operating conditions. This study presents Artificial Neural Network (ANN) model for predicting the bubble point pressure especially for oil fields in Iraq. The most affecting parameters were used as the input layer to the network. Those were reservoir temperature, oil gravity, solution gas-oil ratio and gas relative density. The model was developed using 104 real data points collected from Iraqi reservoirs. The data was divided into two groups: the first was used to train the ANN model, and the second was used to test the model to evaluate their accuracy and trend stability

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