Knowledge Transmission among Preservation Practitioners in Dubai

The economic importance and strategic position of the Middle East have epistemologically twisted most of its true cultural recognition. Both late urban definition and mutual communications have crippled some of its Bedouin societies from proving their participation in global culture. Each society has some to share in human accumulative know-how, but geo-political environments and barriers have lots to do in such mutuality. Many investigations have proved effective transmission of knowledge, but also pointed out black and mysterious zones within the societies themselves. The main obstacle is generated from the oral Arabic culture itself, when episteme is conditioned with biological memory, synchronized interchange and ethical referrals. The necessity of scientific and standard approaches of archeological research and architectural preservation exist and is proven to be of value in preservation of architectural knowledge. However, it is distinctly a hard task to use such standards to challenge the fast urbanization and social developments of our time. While archeological research is apart from contemporary explanations, preservation research is proposed as being more important. Investigations on building concepts require in-depth analysis of habits and behaviors of both craftsmen and beneficiaries, which is a folkloric approach. The lack of linguistic research blocks sufficient use of traditional poetry, literature and folklore to reproduce evidence of technologies from the past. Obviously, the limited natural resources in the Arabian Peninsula have simplified both the architectural setting and construction methodologies and hidden the natural creativity or know-how of earlier societies. Unique architectural contributions need not be limited to definitions of monumental constructs or other impressive achievements. Rather, architecture is defined mainly by cultural and epistemological expressions. This is important in discovering the continuity and distribution of societies in human and global civilization. It is also important to include Middle Eastern architecture in the ongoing intensive identification of architectural perspectives. Despite the late attention that has been given to preservation activities in Arabic States in the Persian Gulf, it is time to start assessment and evaluation of architectural traditions to challenge the remarkably fast development that is occurring. Various organizational, social and political factors are involved in the few serious attempts that have been made. Interventions by ambitious ruling powers have alternatively supported or thwarted such efforts. Lessons can be learned from these examples that highlight effective approaches useful in maintaining the immovable heritage elements in underdeveloped countries. These elements contain most of the remaining important and creative features of human architectural inputs that now benefit most of the globe. International involvement may be drawn to fill scientific gaps and requirements, while paths for serious cooperation are blocked with either hesitation or insufficient awareness of the matter. Bridging the true knowledge needs not only willingness, but also serious identification of both obvious and unconscious motivations that rule decision-making and practice. The conclusions may support the ongoing development of methodologies and professional practices

The Relationship between Unemployment and Inflation in Sudan: An Empirical Analysis, 1992-2015

This study investigated from an empirical point of view, the relationship between unemployment and inflation in Sudan during the period 1992-2015. Annual time series data has been used in the analysis to estimate the model for the period under consideration. Data for the study were obtained from central bank of Sudan and central bureau of statistics. Using these data, Granger test is applied to estimate the causal relationship between unemployment and inflation. The results provided that unemployment does not Granger cause Inflation, and inflation dose not Granger cause unemployment. Thus, there is no causality relationship between inflation rates and unemployment rates in Sudan from 1992-2015

Financial market index prediction using machine learning

The present work aims to tackle the crucial objective of forecasting values for a range of financial market indices in order to maximize income while minimizing potential losses. This study utilizes a comparative analysis approach to examine the performance of artificial neural networks (ANNs) and decision tree models in predicting stock market movements in Saudi Arabia (KSA). The analysis is conducted using a daily database. The predictive models included in this study are constructed using historical stock market data, which encompasses the time period from January 1, 2013, to October 4, 2023. The primary objective of these models is to generate accurate projections specifically for the Tadawul Daily Index. The main objective of this study is to evaluate and contrast the effectiveness of artificial neural network (ANN) and decision tree models in predicting the performance of the stock market in Saudi Arabia. The analysis demonstrates that the decision tree model has a somewhat lower predictive capability when compared to the artificial neural network (ANN) model. The present study utilizes statistical metrics, namely root-mean-squared error (RMSE) and mean absolute error (MAE), to assess and quantify the accuracy of predictions. Moreover, a thorough examination is undertaken, encompassing a range of relevant statistical indicators, and visually representing the data series using graphical means. The utilization of a diverse methodology serves to augment knowledge and facilitate a comprehensive grasp of the intrinsic daily patterns observed in the Tadawul Daily Index. The objective is to enhance the understanding and examination of the complexities of the stock market, so empowering investors and financial analysts to make educated choices that match with their strategic goals and risk management methods. The studys findings provide significant contributions to the field of financial market prediction, specifically in the Kingdom of Saudi Arabia

A Study of The Saudi Stock Market Using Some Statistical Models

The objective of this paper is to estimate the diversification effects/benefits of an investment in a portfolio consisting of the South African Industrial (J520) and the Financial (J580) Indices using the Generalised Pareto Distributions (GPDs) with an extreme value Gumbel copula. The GPD is used as the marginal distribution to both assets to better characterize the extreme risk of returns in both Indices tails. The extreme value Gumbel copula captures the dependence structure (co-movement) of the financial assets in the portfolio. The Akaike information criterion (AIC) and Bayesian information criterion (BIC) goodness of fit tests and the scatterplots indicate that the upper tail of the gains (the larger gains) risk and the losses tail (the larger losses) are best captured using the extreme value Gumbel copula. Monte Carlo simulation of an equally weighted portfolio of the two Indices is used to estimate the portfolio risk. The univariate marginal risks and the portfolio risks are used to calculate the diversification effects/benefits. The results show that there are benefits in diversification since the riskiness of the portfolio is less than the sum of the risk of the two financial assets. This implies that VaR, although not additive theoretically, is sub-additive in this practical situation. This property of sub-additivity represents the benefits of diversification for a portfolio. The implication is that investors investing in individual risky assets can benefit from constructing such a portfolio to reduce extreme risk. Due to high dependence and contagion between developed markets/Global markets, this is useful information for local and international investors seeking a portfolio which includes developing countries market Indices, such as South African assets, which are less correlated with other Global markets, thereby reducing the risk of contagion

Conserved Quantities in f(R)f(R) Gravity via Noether Symmetry

This paper is devoted to investigate $f(R)$ gravity using Noether symmetry approach. For this purpose, we consider Friedmann Robertson-Walker (FRW) universe and spherically symmetric spacetimes. The Noether symmetry generators are evaluated for some specific choice of $f(R)$ models in the presence of gauge term. Further, we calculate the corresponding conserved quantities in each case. Moreover, the importance and stability criteria of these models are discussed.Comment: 14 pages, accepted for publication in Chin. Phys. Let

A hybrid contextual framework to predict severity of infectious disease: COVID-19 case study

Infectious disease is a particular type of disorder triggered by organisms and transmitted directly or indirectly from an infected one like COVID-19. The global economy and public health are immensely affected by COVID-19, a recently emerging infectious disease. Artificial Intelligence can be helpful to predict the severity rating of COVID-19 which assists authorities to take appropriate measures to mitigate its spread in different regions, hence it results in economic reopening and reduces the degree of mortality. In this paper, a hybrid contextual framework is proposed which incorporates content embedding of Standard Operating Procedure’s (SOPs) auxiliary description along with COVID-19 temporal features of the respective region as side information. The word embedding techniques are incorporated to generate distributed representation of SOPs auxiliary description. The higher representation of auxiliary description is obtained by utilizing content embedding and then combined with temporal features to build counties profiles. These county profiles are fed into a profile learner based on an ensemble algorithm to predict the severity level of COVID-19 in different regions. The proposed contextual framework is evaluated on public datasets provided by healthdata.gov and the National Centers for Environmental Information. A comparison of the proposed contextual framework with other state-of-the-art approaches has demonstrated its ability to accurately predict the severity level of COVID-19 in different regions

Adaptive power control aware depth routing in underwater sensor networks

Underwater acoustic sensor network (UASN) refers to a procedure that promotes a broad spectrum of aquatic applications. UASNs can be practically applied in seismic checking, ocean mine identification, resource exploration, pollution checking, and disaster avoidance. UASN confronts many difficulties and issues, such as low bandwidth, node movements, propagation delay, 3D arrangement, energy limitation, and high-cost production and arrangement costs caused by antagonistic underwater situations. Underwater wireless sensor networks (UWSNs) are considered a major issue being encountered in energy management because of the limited battery power of their nodes. Moreover, the harsh underwater environment requires vendors to design and deploy energy-hungry devices to fulfil the communication requirements and maintain an acceptable quality of service. Moreover, increased transmission power levels result in higher channel interference, thereby increasing packet loss. Considering the facts mentioned above, this research presents a controlled transmission power-based sparsity-aware energy-efficient clustering in UWSNs. The contributions of this technique is threefold. First, it uses the adaptive power control mechanism to utilize the sensor nodes’ battery and reduce channel interference effectively. Second, thresholds are defined to ensure successful communication. Third, clustering can be implemented in dense areas to decrease the repetitive transmission that ultimately affects the energy consumption of nodes and interference significantly. Additionally, mobile sinks are deployed to gather information locally to achieve the previously mentioned benefits. The suggested protocol is meticulously examined through extensive simulations and is validated through comparison with other advanced UWSN strategies. Findings show that the suggested protocol outperforms other procedures in terms of network lifetime and packet delivery ratio