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.
Epithelial and stromal communications are essential for normal uterine functions and their dysregulation contributes to the pathogenesis of many diseases including infertility, endometriosis, and cancer. Although many studies have highlighted the advantages of culturing cells in 3D compared to the conventional 2D culture system, one of the major limitations of these systems is the lack of incorporation of cells from non‐epithelial lineages. In an effort to develop a culture system incorporating both stromal and epithelial cells, 3D endometrial cancer spheroids are developed by co‐culturing endometrial stromal cells with cancerous epithelial cells. The spheroids developed by this method are phenot
Blockchain has garnered the most attention as the most important new technology that supports recent digital transactions via e-government. The most critical challenge for public e-government systems is reducing bureaucracy and increasing the efficiency and performance of administrative processes in these systems since blockchain technology can play a role in a decentralized environment and execute a high level of security transactions and transparency. So, the main objectives of this work are to survey different proposed models for e-government system architecture based on blockchain technology implementation and how these models are validated. This work studies and analyzes some research trends focused on blockchain
... Show MoreThis research explores the use of solid polymer electrolytes (SPEs) as a conductive medium for sodium ions in sodium‐ion batteries, presenting a possible alternative to traditional lithium‐ion battery technology. The researchers prepare SPEs with varying molecular weight ratios of polyacrylonitrile (PAN) and sodium tetrafluoroborate (NaBF4) using a solution casting method with dimethyl formamide as the solvent. Through optical absorbance measurements, we identified the PAN:NaBF4 (80:20) SPE composition as having the lowest energy band gap value (4.48 eV). This composition also exhibits high thermal stability based on thermogravimetric analysis results.
The effect of refrigerant injection techniques on the performance of heat pump system based on exergy analysis was studied theoretically. Three refrigerant injection techniques were used; the first was achieved by injected vapour in volume ratios from 1 to 7% in the accumulator. The second was injection liquid refrigerant in the discharge line with the aid of Liquid Pressure Amplification (LPA) pump, with volume ratios from 1 to 10%. The third was a hybrid injection with volume ratios of injected vapour and liquid varied from 1 to 3% and 1 to 10%; respectively. The following improvements in cycle performance were observed. For vapour injection technique, the best ratio of injection was 5%, the exergy destruction reduced
... Show MoreResearching the effects of the research and technological development contract, determining its extent and demarcating the boundaries of the obligations imposed in it, is the cornerstone of economic growth and development, because defining these obligations removes the ambiguity and conflict between interests, by stating the rights owed to each party and even trying to reconcile them, or impose protection by specifying guarantees that are compatible with the essence of the R&D contract, For the purpose of studying the subject thoroughly, we will divide this research into two sections. The first is devoted to identifying the parties to the research and technological development contract. As for the other topic, we will explain the obligation
... Show MorePredicting permeability is a cornerstone of petroleum reservoir engineering, playing a vital role in optimizing hydrocarbon recovery strategies. This paper explores the application of neural networks to predict permeability in oil reservoirs, underscoring their growing importance in addressing traditional prediction challenges. Conventional techniques often struggle with the complexities of subsurface conditions, making innovative approaches essential. Neural networks, with their ability to uncover complicated patterns within large datasets, emerge as a powerful alternative. The Quanti-Elan model was used in this study to combine several well logs for mineral volumes, porosity and water saturation estimation. This model goes be
... Show MoreIn this study, multi-objective optimization of nanofluid aluminum oxide in a mixture of water and ethylene glycol (40:60) is studied. In order to reduce viscosity and increase thermal conductivity of nanofluids, NSGA-II algorithm is used to alter the temperature and volume fraction of nanoparticles. Neural network modeling of experimental data is used to obtain the values of viscosity and thermal conductivity on temperature and volume fraction of nanoparticles. In order to evaluate the optimization objective functions, neural network optimization is connected to NSGA-II algorithm and at any time assessment of the fitness function, the neural network model is called. Finally, Pareto Front and the corresponding optimum points are provided and
... Show MorePeriodontal disease is typically treated with mechanical debridement of the tooth surface. It may, however, be insufficient to eradicate pathogenic microorganisms on its own. Because of the microbial etiology of periodontitis, systemic or local antibiotic therapy is used as an adjunct treatment. The present study aimed to determine the effects of curcumin gel on Porphyromonas gingivalis. Eleven patients with stage II and III periodontitis were registered in the study. A double-blinded split-mouth design followed. Periodontal pockets were distributed into 2 groups; the test group received scaling and root planing along with curcumin gel, while the control group received scaling and root planing along with a placebo gel. Plaque index,
... Show MoreThis study aims to model the flank wear prediction equation in metal cutting, depending on the workpiece material properties and almost cutting conditions. A new method of energy transferred solution between the cutting tool and workpiece was introduced through the flow stress of chip formation by using the Johnson-Cook model. To investigate this model, an orthogonal cutting test coupled with finite element analysis was carried out to solve this model and finding a wear coefficient of cutting 6061-T6 aluminum and the given carbide tool.