This paper introduces a novel nonparametric hybrid cyber-intelligence-based statistical process control and anomaly detection framework in time series data. It is developed to overcome the shortcomings of the classical control schemes in dealing with complex, abnormal, and noisy input data, especially when it is autocorrelated. The proposed methodology combines three technical pillars: First, it utilizes a bidirectional long-short-term memory architecture (Bi-LSTM) to capture long-term time dependency and learn nonlinear patterns, leaving only true deviations as residuals that remove trends and noises from the market. Second, it adopts the Golden Eagle Optimizer (GEO) algorithm for optimal parameter selection. This intelligent algorithm tunes the smoother factor (l) and the control boundary (L) at a certain sample size to minimize the Average Run Length (ARL) of the nonparametric exponentially weighted moving average (NPEWMA-SR) scheme. Third, the framework is validated via R software. The framework was applied to Google's daily trading data using different sample sizes (10, 30, 60, 120, 250, 365, 600, 900, and 1245) days of 2026, to detect the shift in the system, within 2 trading days, achieving an In-control Average Run Length ARL0 = 499.6 and an Out-of-control Average Run Length ARL1 = 1.65 days. The system demonstrated high statistical stability, a very low false alarm rate, and the best statistical sensitivity among all sample sizes. These results prove its effectiveness across small, medium, and large samples, making it a powerful early warning system for monitoring market volatility.
The aim of this paper is to shed the light on the concepts of agency theory by measuring one of the problems that arise from it, which is represented by earnings management (EM) practices. The research problem is demonstrated by the failure of some Iraqi banks and their subsequent placement under the supervision of the Central Bank of Iraq, which was attributed, in part, to the inadequacy of the agency model in protecting stakeholders in shareholding institutions, as well as EM, pushed professional institutions to adopt the corporate governance model as a method to regulate the problem of accounting information asymmetry between the parties to the agency. We are using the Beneish M-score model and the financial analysis equations in
... Show MoreCitric acid is an essential ingredient for the manufacture of (12) key industrial chemicals. Citric acid use is increasing steadily with a high annual growth rate as a result of the development of ever more sophisticated applications. Citric acid is widely utilized in the food and pharmaceutical industries due to its low toxicity when compared to other acidulous. Other uses for citric acid can be found in cleaning supplies and detergents. Based on information from a review of the literature, Citric acid production substrates and methods for surface fermentation, submerged fermentation, solid-state fermentation, and international market expansion are all covered in the current review study. Finally, there is still much to learn about the
... Show MoreThe global oil market is one of the most important markets in the world and occupies especially for countries consuming and producing countries, and the status of understanding of the mechanism for determining prices in the market help to stand on many factors affecting oil demand and supply of oil and geopolitical factors, climate and alternative sources of energy .. etc. factors, and that the main objective of the research is to study the causes and results left behind by the oil price shocks in the world market, and the movement of these factors be through a cycle of energy that explain the strength of competition between these factors and their effects on prices, when demand increases evolution Large image leads to significan
... Show MoreA substantial percentage of the world’s energy consumption (almost 40%) and carbon dioxide (CO2) emissions (around 37%) come from the construction industry, especially schools. This work presents a new hybrid artificial intelligence (AI) engineering model that aims to maximize energy performance on campuses in a holistic way. Modules for data-driven forecasting, metaheuristic optimization, and real-time adaptive control are all part of the concept. A thorough energy simulation of a university campus building is used in conjunction with the AI model to assess its performance through a co-simulation framework. Findings show that yearly peak electricity demand may be reduced by 18.7% and total site energy consumption by 22.4% when co
... Show MoreIntroduction The Hybrid Gamma Camera (HGC) is being developed to enhance the localisation of radiopharmaceutical uptake in targeted tissues during surgical procedures such as sentinel lymph node (SLN) biopsy. Purpose To assess the capability of the HGC, a lymph-node-contrast (LNC) phantom was constructed for an evaluative study simulating medical scenarios of varying radioactivity concentration and SLN size. Materials and methods The phantom was constructed using two methyl methacrylate PMMA plates (8 mm thick). The SLNs were simulated by drilling circular wells of diameters ranging between 10 mm and 2.5 mm (16 wells in total) in one plate. These simulated SLNs were placed underneath scattering material with thicknesses ranging between 5 mm
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