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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
Sun Apr 30 2023
Journal Name
Iraqi Geological Journal
Evaluating Machine Learning Techniques for Carbonate Formation Permeability Prediction Using Well Log Data
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Machine learning has a significant advantage for many difficulties in the oil and gas industry, especially when it comes to resolving complex challenges in reservoir characterization. Permeability is one of the most difficult petrophysical parameters to predict using conventional logging techniques. Clarifications of the work flow methodology are presented alongside comprehensive models in this study. The purpose of this study is to provide a more robust technique for predicting permeability; previous studies on the Bazirgan field have attempted to do so, but their estimates have been vague, and the methods they give are obsolete and do not make any concessions to the real or rigid in order to solve the permeability computation. To

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Publication Date
Tue Mar 30 2021
Journal Name
Baghdad Science Journal
Experimental Evidence of Chaotic Resonance in Semiconductor Laser
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In this paper, an experimental study has been conducted regarding the indication of resonance in chaotic semiconductor laser.  Resonant perturbations are effective for harnessing nonlinear oscillators for various applications such as inducing chaos and controlling chaos. Interesting results have been obtained regarding to the effect of the   chaotic resonance by adding the frequency on the systems. The frequency changes nonlinear dynamical system through a critical value, there is a transition from a periodic attractor to a strange attractor. The amplitude has a very relevant impact on the system, resulting in an optimal resonance response for appropriate values related to correlation time. The chaotic system becomes regular under

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Publication Date
Tue Dec 20 2022
Journal Name
Bulletin Of The Iraq Natural History Museum (p-issn: 1017-8678 , E-issn: 2311-9799)
SURVEY AND UPDATING CHECKLIST OF DIPTERAN SPECIES WITH FORENSIC IMPORTANCE
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In the present investigation, 24 adult dipteran species with forensic importance belonging to 13 genera and 8 families that were collected from different localities of Iraq. The specimens were identified by different taxonomical keys; in addition the date and localities of collecting specimens were recorded.

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Publication Date
Thu Jun 01 2023
Journal Name
Ifip Advances In Information And Communication Technology
Rapid Thrombogenesis Prediction in Covid-19 Patients Using Machine Learning
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Machine Learning (ML) algorithms are increasingly being utilized in the medical field to manage and diagnose diseases, leading to improved patient treatment and disease management. Several recent studies have found that Covid-19 patients have a higher incidence of blood clots, and understanding the pathological pathways that lead to blood clot formation (thrombogenesis) is critical. Current methods of reporting thrombogenesis-related fluid dynamic metrics for patient-specific anatomies are based on computational fluid dynamics (CFD) analysis, which can take weeks to months for a single patient. In this paper, we propose a ML-based method for rapid thrombogenesis prediction in the carotid artery of Covid-19 patients. Our proposed system aims

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Publication Date
Tue Dec 05 2023
Journal Name
Baghdad Science Journal
An Observation and Analysis the role of Convolutional Neural Network towards Lung Cancer Prediction
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Lung cancer is one of the most serious and prevalent diseases, causing many deaths each year. Though CT scan images are mostly used in the diagnosis of cancer, the assessment of scans is an error-prone and time-consuming task. Machine learning and AI-based models can identify and classify types of lung cancer quite accurately, which helps in the early-stage detection of lung cancer that can increase the survival rate. In this paper, Convolutional Neural Network is used to classify Adenocarcinoma, squamous cell carcinoma and normal case CT scan images from the Chest CT Scan Images Dataset using different combinations of hidden layers and parameters in CNN models. The proposed model was trained on 1000 CT Scan Images of cancerous and non-c

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Publication Date
Wed Sep 29 2021
Journal Name
Molecules
A Comprehensive Review for Groundwater Contamination and Remediation: Occurrence, Migration and Adsorption Modelling
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The provision of safe water for people is a human right; historically, a major number of people depend on groundwater as a source of water for their needs, such as agricultural, industrial or human activities. Water resources have recently been affected by organic and/or inorganic contaminants as a result of population growth and increased anthropogenic activity, soil leaching and pollution. Water resource remediation has become a serious environmental concern, since it has a direct impact on many aspects of people’s lives. For decades, the pump-and-treat method has been considered the predominant treatment process for the remediation of contaminated groundwater with organic and inorganic contaminants. On the other side, this tech

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Publication Date
Sun Jan 24 2016
Journal Name
Al-academy
The effectiveness of balance in building formal relationships for media evidence: ساهرة عبد الواحد حسن
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The media guide is a small-sized printed medium, whose importance is highlighted through the specific information it carriesThe task of the guide lies in the clarity of these indications and making a positive impact on the recipient with understanding so it is a means for the purpose of reaching the effect and effectiveness of the message symbols from the movements of lines in which elements that are supposed to be equal in the performance of their functions and the purpose of their existence gather to achieve the mental response of perception, understanding and enjoyment. It must be in an objective unity based on the balance in this distribution. To form a formal organizational unit and an integrated system, the result of which is to gi

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Publication Date
Wed Mar 10 2021
Journal Name
Baghdad Science Journal
Study for evidence of bacteria contamination in the southern part of the Diyala River / Iraq
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Were studied some bacteria evidence of pollution as well as the total number of live bacteria in the waters of the Diyala river and selected five stations within the 17 km final Diyala River before its mouth in the Tigris River was the first before the new bridge of the Diyala River about 4 km and the second after the mouth of the water purification plant Rustumiya suit inverselywith temperatures

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Publication Date
Wed Mar 05 2025
Journal Name
Lecture Notes In Networks And Systems
Leveraging AI for Disaster Management: A Comprehensive Review of Applications and Challenges
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Publication Date
Fri Dec 01 2023
Journal Name
Al-khwarizmi Engineering Journal
Secure Seaport Management System using Blockchain Technology
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Worldwide, shipping documents are still primarily created and handled in the traditional paper manner. Processes taking place in shipping ports as a result are time-consuming and heavily dependent on paper. Shipping documents are particularly susceptible to paperwork fraud because they involve numerous parties with competing interests. With the aid of smart contracts, a distributed, shared, and append-only ledger provided by blockchain technology allows for the addition of new records. In order to increase maritime transport and port efficiency and promote economic development, this paper examines current maritime sector developments in Iraq and offers a paradigm to secure the management system based on a hyper-ledger fabric blockchain p

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