The unstable and uncertain nature of natural rubber prices makes them highly volatile and prone to outliers, which can have a significant impact on both modeling and forecasting. To tackle this issue, the author recommends a hybrid model that combines the autoregressive (AR) and Generalized Autoregressive Conditional Heteroscedasticity (GARCH) models. The model utilizes the Huber weighting function to ensure the forecast value of rubber prices remains sustainable even in the presence of outliers. The study aims to develop a sustainable model and forecast daily prices for a 12-day period by analyzing 2683 daily price data from Standard Malaysian Rubber Grade 20 (SMR 20) in Malaysia. The analysis incorporates two dispersion measurements (IQR/3 and Sn) and three levels of IO contamination 0%, 10%, and 20%. The results indicate that using the Huber weighting function with the IQR/3 measurement to build the AR(1)-GARCH(2,1) model leads to better sustainability. These findings have the potential to enhance the GARCH model by modifying the weighting function of the M-estimator
Electronic banking services appeared as a result of laying the foundations for the application of electronic automation in the banking field, and despite the clear expansion in its adoption and implementation as an inevitable necessity imposed by international and national developments, its application was not ideal according to the level that was expected to occur after the abandonment of traditional banking services, which produced some risks Which is evident in the absence of a legal system, whether at the level of proving and authoritative electronic banking services such as electronic signature, Or at the level of protecting the confidentiality of these services and ensuring that they are not exp
... Show MoreObjective: Comprehending microbial diversity and antibiotic resistance patterns is essential for efficient treatment protocols. This study sought to determine the incidence of bacterial and fungal pathogens responsible for burn and wound infections and their antibiotic susceptibility profiles. Methods: This cross-sectional study involved 140 patients with burn or wound infections. Sterile swabs and pus aspiration were employed to collect samples, which were subsequently processed using standard microbiological procedures. Antibiotic resistance was determined using the Kirby-Bauer disc diffusion method, following Clinical and Laboratory Standards Institute (CLSI) guidelines. Data was analysed using IBM SPSS version 25.0, and the Chi-
... Show MoreBackground: Survey of the occlusion in population groups usually include in their objections the academic assessment of occlusal feature, the planning resources for public health treatment programmers, the comparison of different population and the screening of groups for orthodontic treatment. Likewise a thorough investigation of the occurrence of malocclusions among school–students would be of major importance in the planning of orthodontic treatment in the public dental health services. For this purpose it is necessary to have detailed information on the prevalence of individual malocclusion among boys and girls at different ages distributed regionally, and moreover, an analysis of the need for orthodontic treatment in the different sc
... Show MoreVarious literary studies have investigated the psychological, social and cultural effects of traumatic events. They give voice to traumatised victims and enable them to convey and confront their traumas. However, these studies present a one-sided view, concentrating largely on the presentation of trauma in the industrial societies of the Western world. Recently, increasing attention has been devoted to identifying and depicting the forms and types of trauma that have been experienced in marginalised and neglected societies, such as the Iraqi society. Iraq has witnessed the unexpected fall of a brutal dictatorship, Western invasion and an unprecedented rise of sectarian discourses. This extreme violence has deeply affected many aspec
... Show MoreAdvanced strategies for production forecasting, operational optimization, and decision-making enhancement have been employed through reservoir management and machine learning (ML) techniques. A hybrid model is established to predict future gas output in a gas reservoir through historical production data, including reservoir pressure, cumulative gas production, and cumulative water production for 67 months. The procedure starts with data preprocessing and applies seasonal exponential smoothing (SES) to capture seasonality and trends in production data, while an Artificial Neural Network (ANN) captures complicated spatiotemporal connections. The history replication in the models is quantified for accuracy through metric keys such as m
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