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.
Seepage occurs under or inside structures or in the place, where they come into contact with the sides under the influence of pressure caused by the difference in water level in the structure U / S and D / S. This paper is designed to model seepage analysis for Kongele (an earth dam) due to its importance in providing water for agricultural projects and supporting Tourism sector. For this purpose, analysis was carried out to study seepage through the dam under various conditions. Using the finite element method by computer program (Geo-Studio) the dam was analysed in its actual design using the SEEP / W 2018 program. Several analyses were performed to study the seepage across Kongele
Background : Coronary artery disease is theunderlying cause in approximately two thirds of
patients with systolic heart failure ;
Coronary artery angiogriphy may be useful to
define the presence ,
Anatomical characteristics ,and functional
significance of Coronary artery disease in
selected heart failure patients with or without signs
and aymptoms of Coronary artery disease.
Objectives: to verify the clinical usefulness of
coronary angiography (CA) in congestive heart
failure (CHF) patients with no history of ischemic
heart disease and to identify predictive factors for
performing coronary angiography to patients with
congestive heart failure with no obvious ischemia.
Methods :this is a cross-ses
Background:Measurement of hemoglobin A1c (A1C) is a renowned tactic for gauging long-term glycemic control, and exemplifies an outstanding influence to the quality of care in diabetic patients.The concept of targets is open to criticism; they may be unattainable, or limit what could be attained, and in addition they may be economically difficult to attain. However, without some form of targeted control of an asymptomatic condition it becomes difficult to promote care at allObjectives: The present article aims to address the most recent evidence-based global guidelines of A1C targets intended for glycemic control in Type 2 Diabetes Mellitus (T2D).Key messages:Rationale for Treatment Targets of A1C includesevidence for microvascular and ma
... Show MoreVarious theories have been proposed since in last century to predict the first sighting of a new crescent moon. None of them uses the concept of machine and deep learning to process, interpret and simulate patterns hidden in databases. Many of these theories use interpolation and extrapolation techniques to identify sighting regions through such data. In this study, a pattern recognizer artificial neural network was trained to distinguish between visibility regions. Essential parameters of crescent moon sighting were collected from moon sight datasets and used to build an intelligent system of pattern recognition to predict the crescent sight conditions. The proposed ANN learned the datasets with an accuracy of more than 72% in comp
... Show Moreالناصر، عامر عبد الرزاق عبد المحسن والكبيسي، صلاح الدين عواد كريم. 2018. إمكانية تبني الحوسبة السحابية الهجينة في الجامعات العراقية : دراسة تحليلية باستخدام أنموذج القبول التكنولوجي. مجلة الإدا
The large number of failure in electrical power plant leads to the sudden stopping of work. In some cases, the necessary reserve materials are not available for maintenance which leads to interrupt of power generation in the electrical power plant unit. The present study, deals with the determination of availability aspects of generator in unit 5 of Al-Dourra electric power plant. In order to evaluate this generator's availability performance, a wide range of studies have been conducted to gather accurate information at the level of detail considered suitable to achieve the availability analysis aim. The Weibull Distribution is used to perform the reliability analysis via Minitab 17, and Artificial Neural Networks (ANNs) by approaching o
... Show MoreAbstract: The international community now places significant emphasis on achieving zero carbon emissions, requiring both new researchers and experienced policymakers to prioritise this goal. This article examines the effects of carbon taxes, carbon cap and trade, renewable energy (RE) production and consumption, and economic growth (EG) on carbon emission reduction in the United States, Japan, Canada, and Australia. The study collected secondary data from the World Development Indicators (WDI) secondary source spanning the years 1991 to 2022. The study examines the relationship between variables using the cross-sectionally augmented autoregressive distributed lag (CS-ARDL) approach. The findings indicate that carbon taxes, carbon cap and tr
... Show MoreAs tight gas reservoirs (TGRs) become more significant to the future of the gas industry, investigation into the best methods for the evaluation of field performance is critical. While hydraulic fractured well in TRGs are proven to be most viable options for economic recovery of gas, the interpretation of pressure transient or well test data from hydraulic fractured well in TGRs for the accurate estimation of important reservoirs and fracture properties (e.g. fracture length, fracture conductivity, skin and reservoir permeability) is rather very complex and difficult because of the existence of multiple flow profiles/regimes. The flow regimes are complex in TGRs due to the large hydraulic fractures n
Abstract: Recently, there is increasing interest in using mode-division multipelexing (MDM) technique to enhace data rate transmission over multimode fibers. In this technique, each fiber mode is treated as a separate optical carrier to transfer its own data. This paper presents a broadband, compact, and low loss three-mode (de)multiplexer designed for C+L band using subwavelength grating (SWG) technology and built-in silicon-on-insulator SOI platform. SWG offers refractive index engineering for wider operating bandwidth and compact devices compared to conventional ones. The designed (de)multiplex deals with three modes (TE0, TE1, and TE2) and has a loss > -1 dB and crosstalk < −15 dB, and its operation c
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