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.
The proliferation of manipulated multimedia content poses a significant threat in an era heavily reliant on social networks as primary information sources. Despite numerous countermeasures targeting specific attack types, the seamless nature of image manipulation challenges the differentiation between authentic and altered visuals. This study aims to detect fake images generated by StyleGAN2-ADA using watermark analysis and image content analysis techniques. The first experiment evaluates the performance of watermarking techniques in the spatial (Least Significant Bit (LSB)) and frequency (Discrete Cosine Transform (DCT)) domains using real-life imagery. Then, watermarked images are used as input to the StyleGAN2-ADA model to genera
... Show MoreThis effort is related to describe and assess the performance of the Iraqi cement sample planned for oil well-cementing jobs in Iraq. In this paper, major cementing properties which are thickening time, compressive strength, and free water in addition to the rheological properties and filtration of cement slurry underneath definite circumstances are experimentally tested. The consequences point to that the Iraqi cement after special additives encounter the requests of the API standards and can consequently is used in cementing jobs for oil wells. At this research, there is a comparative investigation established on experimental work on the effectiveness of some additives that considered as waste materials which are silica fume, baux
... Show MoreThe current study focuses on utilizing artificial intelligence (AI) techniques to identify the optimal locations of production wells and types for achieving the production company’s primary objective, which is to increase oil production from the Sa’di carbonate reservoir of the Halfaya oil field in southeast Iraq, with the determination of the optimal scenario of various designs for production wells, which include vertical, horizontal, multi-horizontal, and fishbone lateral wells, for all reservoir production layers. Artificial neural network tool was used to identify the optimal locations for obtaining the highest production from the reservoir layers and the optimal well type. Fo
The normalized difference vegetation index (NDVI) is an effective graphical indicator that can be used to analyze remote sensing measurements using a space platform, in order to investigate the trend of the live green vegetation in the observed target. In this research, the change detection of vegetation in Babylon city was done by tracing the NDVI factor for temporal Landsat satellite images. These images were used and utilized in two different terms: in March 19th in 2015 and March 5th in 2020. The Arc-GIS program ver. 10.7 was adopted to analyze the collected data. The final results indicate a spatial variation in the (NDVI), where it increases from (1666.91 𝑘𝑚2) in 2015 to (1697.01 𝑘𝑚2)) in 2020 between the t
... Show MoreG-system composed of three isolates G3 ( Bacillus),G12 ( Arthrobacter )and G27 ( Brevibacterium) was used to detect the mutagenicity of the anticancer drug, cyclophosphamide (CP) under conditions similar to that used for standard mutagen, Nitrosoguanidine (NTG). The CP effected the survival fraction of isolates after treatment for 15 mins using gradual increasing concentrations, but at less extent comparing to NTG. The mutagenic effect of CP was at higher level than that of NTG when using streptomycin as a genetic marker, but the situation was reversed when using rifampicin resistant as a report marker. The latter effect appeared upon recording the mutagen efficiency (ie., number of induced mutants/microgram of mutagen). Measuring the R
... Show MoreThe question of estimation took a great interest in some engineering, statistical applications, various applied, human sciences, the methods provided by it helped to identify and accurately the many random processes.
In this paper, methods were used through which the reliability function, risk function, and estimation of the distribution parameters were used, and the methods are (Moment Method, Maximum Likelihood Method), where an experimental study was conducted using a simulation method for the purpose of comparing the methods to show which of these methods are competent in practical application This is based on the observations generated from the Rayleigh logarithmic distribution (RL) with sample sizes
... Show MoreCar drivers hear many kinds of noise inside their vehicles' cabins, and the most annoying ones are the noise generated by tires, engines, and outside winds. Noise affects the comfort of the passengers inside the cabin, and it’s sad to say that modern cars are noisier in many kinds of noise signals due to using a lot of plastic materials in new budget cars. For expensive and luxury cars, the problem is solved by using better sound insulation materials, but for the budget ones, the approach used here is effective. It is called Active Noise Cancellation and can be done using analog or digital electronics. An operational amplifier and filters are used for the analog one, and in the digital one, signal processor chips are used. In engineeri
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