This paper is specifically a detailed review of the Spatial Quantile Autoregressive (SARQR) model that refers to the incorporation of quantile regression models into spatial autoregressive models to facilitate an improved analysis of the characteristics of spatially dependent data. The relevance of SARQR is emphasized in most applications, including but not limited to the fields that might need the study of spatial variation and dependencies. In particular, it looks at literature dated from 1971 and 2024 and shows the extent to which SARQR had already been applied previously in other disciplines such as economics, real estate, environmental science, and epidemiology. Accordingly, evidence indicates SARQR has numerous benefits compared to traditional regression models: These estimates are robust to outliers and heterogeneous spatial effects and capture fully conditional distributions with respect to mean regression models. The review supports future work toward enhancing estimation approaches and possible SARQR application extensions to other fields. The spatial modeling has applicability in the research, decision-making, and profession formulation because it encourages a broader SARQR application in economic analysis, infrastructure planning, and public health policy. Future research must aim at refining estimation methods and integrating SARQR with other models of analysis to optimize its usefulness in utilizing sophisticated spatial data.
This paper explores VANET topics: architecture, characteristics, security, routing protocols, applications, simulators, and 5G integration. We update, edit, and summarize some of the published data as we analyze each notion. For ease of comprehension and clarity, we give part of the data as tables and figures. This survey also raises issues for potential future research topics, such as how to integrate VANET with a 5G cellular network and how to use trust mechanisms to enhance security, scalability, effectiveness, and other VANET features and services. In short, this review may aid academics and developers in choosing the key VANET characteristics for their objectives in a single document.
A growing and pressing need for Speech Enhancement Algorithms (SEAs) has emerged with the proliferation of hearing devices and mobile devices that aim to improve speech intelligibility without sacrificing speech quality. Recently, a tremendous number of studies have been conducted in the field of speech enhancement. This study aims to map the field of speech enhancement by conducting a systematic literature review to provide comprehensive details of recently proposed SEAs. This systematic review aims to highlight research trends in SEAs and direct researchers to the most important topics published between 2015 and 2024. It attempts to address seven key research questions related to this topic. Moreover, it covers articles available
... Show MoreWater is necessary for sustainable development and healthy society. Groundwater, often, is not sufficient and protected for direct human consumption. Due to increase in the density of population the requirement of water is increasing. In this work, the assessment of groundwater quality was conducted in the south-west part of Basrah province. Spatial variations in the quality of groundwater in the study area have been analyzed utilizing GIS technique. The geochemical parameters of groundwater samples including pH, EC, TDS, Ca, Mg, Na, Cl, HCO3, SO4, and NO3 were assessed in this study. Information maps of the study area have been actually prepared to make use of the GIS spatial
... Show MoreGreenhouses are provide that produce of vegetable in non times seasons production by controlling the various environmental factors that appropriate atmosphere in temperature and humidity for the growth of plants in the plastic houses and owner plastic.
The objective of this research is to study of the most important natural and human factors affecting the Greenhouses in the province of Baghdad and study geographic distribution for the Greenhouses in the province.
Some properties on curriculum geographical descriptive analytical that used in describe and analysis of data and information that could be available from Directorate of agriculture in Baghdad to 2014. As it turns out that district of Mahmudiya acquired (45.3%) of the total
Lowpass spatial filters are adopted to match the noise statistics of the degradation seeking
good quality smoothed images. This study imply different size and shape of smoothing
windows. The study shows that using a window square frame shape gives good quality
smoothing and at the same time preserving a certain level of high frequency components in
comparsion with standard smoothing filters.
The spatial variation of regional development means that some regions to be a center of activities and services and job opportunities and economic development, and are usually in major urban centers, while lacking in other regions to such activities and services. Perhaps the studies of spatial variation SPATIAL INEQUALITY, regional development, REGIONAL DEVELOPMENT has had the greatest impact on the operations of regional planning in particular the study of the regional dimension of any city requires that you review the basis and theoretical framework, which refers to the inevitability of the existence of disparities across regions, due to the properties of the regions population and economic political and environmental The study
... Show MoreANN modeling is used here to predict missing monthly precipitation data in one station of the eight weather stations network in Sulaimani Governorate. Eight models were developed, one for each station as for prediction. The accuracy of prediction obtain is excellent with correlation coefficients between the predicted and the measured values of monthly precipitation ranged from (90% to 97.2%). The eight ANN models are found after many trials for each station and those with the highest correlation coefficient were selected. All the ANN models are found to have a hyperbolic tangent and identity activation functions for the hidden and output layers respectively, with learning rate of (0.4) and momentum term of (0.9), but with different data
... Show MoreIn recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction acc
... Show MoreThe 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 (I
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