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. Lev

Asset management involves efficient planning of economic and technical performance characteristics of infrastructure systems. Managing a sewer network requires various types of activities so the network can be able to achieve a certain level of performance. During the lifetime of the network various components will start to deteriorate leading to bad performance and can damage the infrastructure. The main objective of this research is to develop deterioration models to provide an assessment tool for determining the serviceability of the sewer networks in Baghdad city the Zeppelin line was selected as a case study, as well as to give top management authorities the appropriate decision making. Different modeling techniques

The aim of the research is to know the level of time management application and its impact on the performance of the job, a survey search in the general company for communication and information technology and provide recommendations that help employees to optimize the use of time and improve performance, which is an important element in controlling the various functions of the company. In order to achieve the objectives of the research, the questionnaire was based on two main variables and distributed to a random sample of (44) employees in the company out of (308) employees, thus the proportion of the sample (14%). After collecting the samples from the sample, there are (6) incomplete forms that have been retri

Big data analysis is essential for modern applications in areas such as healthcare, assistive technology, intelligent transportation, environment and climate monitoring. Traditional algorithms in data mining and machine learning do not scale well with data size. Mining and learning from big data need time and memory efficient techniques, albeit the cost of possible loss in accuracy. We have developed a data aggregation structure to summarize data with large number of instances and data generated from multiple data sources. Data are aggregated at multiple resolutions and resolution provides a trade-off between efficiency and accuracy. The structure is built once, updated incrementally, and serves as a common data input for multiple mining an

One of the most important features of the Amazon Web Services (AWS) cloud is that the program can be run and accessed from any location. You can access and monitor the result of the program from any location, saving many images and allowing for faster computation. This work proposes a face detection classification model based on AWS cloud aiming to classify the faces into two classes: a non-permission class, and a permission class, by training the real data set collected from our cameras. The proposed Convolutional Neural Network (CNN) cloud-based system was used to share computational resources for Artificial Neural Networks (ANN) to reduce redundant computation. The test system uses Internet of Things (IoT) services through our ca

One of the most important features of the Amazon Web Services (AWS) cloud is that the program can be run and accessed from any location. You can access and monitor the result of the program from any location, saving many images and allowing for faster computation. This work proposes a face detection classification model based on AWS cloud aiming to classify the faces into two classes: a non-permission class, and a permission class, by training the real data set collected from our cameras. The proposed Convolutional Neural Network (CNN) cloud-based system was used to share computational resources for Artificial Neural Networks (ANN) to reduce redundant computation. The test system uses Internet of Things (IoT) services th

A sensitive spectrophotometric method was developed for the estimation of cefdinir (CFD), a cephalosporin species. This study involves two methods, and the first method includes the preparing of azo dye by the reaction of CFD diazonium salt with 4-Tert-Butylphenol (4-TBP) and 2-Naphthol (2-NPT) in alkaline medium, which shows colored dyes measured at λmax 490 and 535 nm, respectively. Beer's law was obeyed along the concentration range of (3-100) μg.ml-1. The limits of detection were 0.246, 0.447 μg.ml-1 and molar absorptivities were 0.6129×104, 0.3361×104 L.mol-1cm-1 for (CFD-4-TBP) and (CFD-2-NPT), respectively. The second method includes preconcentration for cefdinir dyes by using cloud point extraction in the presence of Triton

The research aims at integrating the disclosure of the business models with the qualitative characteristics of accounting information. To achieve this, the elements of the business model should be identified and disclosed, and then study the possibility of integrating the disclosure of the business model with the qualitative characteristics of accounting information.

To achieve this objective, the research was based on the indicators of disclosure of the business model of the International Accounting Standards Board to measure the disclosure of the business model.

The research reached a number of conclusions, the most important of which were as follows:

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