MLRS and Dynamic Segmentation for Traffic Congestion Management

Geomatics techniques is applied in many directions as a decision support tool, one of them is the organization and management of transportation. Traffic congestion is a serious problem, where the road behavior is influencing on people economically as well as intellectually/ Transportation networks are a specialized type of graph that models the logical and topological information in the real world. The road network includes multi-linear reference system (MLRS) based model that focuses on network topological analysis. It involves the collection of traffic data that describe the characteristics and geometry of road network, vehicle counts, speed, flow rates, density in order to define the congestion situation. The objective of this research is to integrate the rules of graph theory MLRS and dynamic segmentation (DS) to examine the significance of historical traffic information gathered through Geographic Information Systems (GIS) for solving the dynamic path analysis. This guides vehicles through the urban road network using the optimal  path taking into account the traffic conditions on the roads that change over the time

Effect of Surface Polishing on Nano-Hardness and Elastic Modulus of Different Resin Composites after Immersion in Alcoholic Medium

There has been a great tendency toward using resin composite in dentistry and exploring nano-hardness, elastic modulus, and effect of polishing on its mechanical properties after its artificial ageing. This study aimed to evaluate the effect of surface polishing of four different resin composites on their nano-hardness and elastic modulus. This effect was tested right after light curing of composite resin and after its artificial ageing (immersion in alcoholic medium). Nanoindentation test preparations, surface roughness, surface hardness, and scanning electron microscope were conducted across the four different resin composites: Clearfil AP-X (APX), Estelite Sigma Quick (ESQ), Beautifil II (BE2), and FiltekTM Supreme Ultra Universal restorative (FSU). We found that difference in fillers load and particle size are amongst the factors influencing hardness and modulus of elasticity. The APX is the highest in term of hardness due to fillers load and size while the ESQ is the lowest because all fillers in nano size and distributed homogenously. The significance of surface polishing of the studied resin composite restorations was highlighted. Future research may focus on exploring survival rate of polished and non-polished composite surfaces with emphasis on measuring degree of conversion and impacts of polished and non-polished surfaces on the individuals’ oral health quality of life

Applying Association Rules and Co-location Techniques on Geospatial Web Services

Most contemporary GIS have only very basic spatial analysis and data mining functionality and many are confined to analysis that involves comparing maps and descriptive statistical displays like histograms or pie charts. Emerging Web standards promise a network of heterogeneous yet interoperable Web Services. Web Services would greatly simplify the development of many kinds of data integration and knowledge management applications. Geospatial data mining describes the combination of two key market intelligence software tools: Geographical Information Systems and Data Mining Systems. This research aims to develop a Spatial Data Mining web service it uses rule association techniques and correlation methods to explore results of huge amounts of data generated from crises management integrated applications developed. It integrates between traffic systems, medical services systems, civil defense and state of the art Geographic Information Systems and Data Mining Systems functionality in an open, highly extensible, internet-enabled plug-in architecture. The Interoperability of geospatial data previously focus just on data formats and standards. The recent popularity and adoption of the Internet and Web Services has provided a new means of interoperability for geospatial information not just for exchanging data but for analyzing these data during exchange. An integrated, user friendly Spatial Data Mining System available on the internet via a web service offers exciting new possibilities for spatial decision making and geographical research to a wide range of potential users.   Keywords: Spatial Data Mining, Rule Association, Co-location, Web Services, Geospatial Dat

Performance Evaluation of Applying Fuzzy Multiple Regression Model to TLS in the Geodetic Coordinate Transformation

It is known that the classical technique for solving the linear regression problem of the geodetic transformation process is using least squares approach (LS). On the contrary, this research explores the application of total least squares (TLS) approach to solve linear regression with and without fuzzy multiple regression model in Bursa-Wolf similarity transformation process. In this research two groups of data sets are used; the first group is the solution points which are used to compute the values of the transformation parameters. The second is the check points that were used to assess the accuracy of the applied methods (in terms of mean and Root Mean Squares Errors RMSE). The applied four solutions show how the accuracy of TLS is relatively better than LS. The weight has a better effect on improving the accuracy of both cases, LS and TLS; however, its effects are greater on TLS. By using the fuzzy multiple regression models, the results improved further and the need for accurate weights/confidence is eliminated

Using an Extended Technology Acceptance Model to Uncover Variables Influencing Physicians’ Use Of EHR in Jordan: Insights from Alberta, Canada

Adoption rates for electronic health records (EHR) remain low in developing nations, even though health information technologies undoubtedly enhance the quality of service delivery and healthcare institutions’ overall efficiency. In this research, researchers employed a technology acceptance integrated model to analyze what factors are most important in encouraging physicians in Jordan to adopt EHR. This framework was created after a thorough review of the relevant literature and with input from physicians in Alberta, Canada, a province with an openly disclosed high rate of electronic health record adoption. To achieve its aim, the present study used a quantitative correlational research strategy. Data were acquired from a convenient sample size of 413 web-based survey participants recruited from the target population of physicians practicing in the public and private healthcare sectors in Jordan. The study’s hypotheses were tested with structural equation modeling. Physicians’ behavioral intentions were shown to be strongly predicted by factors including perceived usefulness, perceived ease of use, perceived ’privacy and security,’ financial incentives, and self-efficacy, which collectively accounted for 57.8% of the total variance in behavioral intention. Perceived usefulness had the highest influence on intentions, followed by self-efficacy, perceived ”privacy and security,” and perceived ease of use, with financial incentives having the smallest impact on intentions. Accordingly, healthcare practitioners must consider these variables while developing and validating interpretations about HER adoption. This study concludes with several implications for healthcare directors, policymakers, and providers of health information systems, in addition to suggestions for future research areas

Smart and Multifunctional Fiber-Reinforced Composites of 2D Heterostructure-Based Textiles

Smart and multifunctional fiber reinforced polymer (FRP) composites with energy storage, sensing, and heating capabilities have gained significant interest for automotive, civil, and aerospace applications. However, achieving smart and multifunctional capabilities in an FRP composite while maintaining desired mechanical properties remains challenging. Here, a novel approach for layer-by-layer (LBL) deposition of 2D material (graphene and molybdenum disulfide, MoS2)-based heterostructure onto glass fiber fabric using a highly scalable manufacturing technique at a remarkable speed of ≈150 m min−1 is reported. This process enables the creation of smart textiles with integrated energy storage, sensing, and heating functionalities. This methodology combines gel-based electrolyte with a vacuum resin infusion technique, resulting in an efficient and stable smart FRP composite with an areal capacitance of up to ≈182 µF cm−2 at 10 mV s−1. The composite exhibits exceptional cyclic stability, maintaining ≈90% capacitance after 1000 cycles. Moreover, the smart composite demonstrates joule heating, reaching from ∼24 to ∼27 °C within 120 s at 25 V. Additionally, the smart composite displays strain sensitivity by altering electrical resistance with longitudinal strain, enabling structural health monitoring. These findings highlight the potential of smart composites for multifunctional applications and provide an important step toward realizing their actual real-world applications

Toward bridging future irrigation deficits utilizing the shark algorithm integrated with a climate change model

Climate change is one of the most effectual variables on the dam operations and reservoir water system. This is due to the fact that climate change has a direct effect on the rainfall–runoff process that is influencing the water inflow to the reservoir. This study examines future trends in climate change in terms of temperature and precipitation as an important predictor to minimize the gap between water supply and demand. In this study, temperature and precipitation were predicted for the period between 2046 and 2065, in the context of climate change, based on the A1B scenario and the HAD-CM3 model. Runoff volume was then predicted with the IHACRES model. A new, nature-inspired optimization algorithm, named the shark algorithm, was examined. Climate change model results were utilized by the shark algorithm to generate an optimal operation rule for dam and reservoir water systems to minimize the gap between water supply and demand for irrigation purposes. The proposed model was applied for the Aydoughmoush Dam in Iran. Results showed that, due to the decrease in water runoff to the reservoir and the increase in irrigation demand, serious irrigation deficits could occur downstream of the Aydoughmoush Dam

Cystic Fibrosis in Egyptian Children: Achievements and Future Directions

Cystic fibrosis (CF) is the most common potentially lethal and life-shortening genetic disease caused by mutations of the cystic fibrosis transmembrane conductance regulator (CFTR) gene. Clinical consequences of the CFTR defect are site-specific and range from severe (lungs, pancreas, male reproductive tract) to mild (intestine) to asymptomatic (sweat glands). In many developing countries CF has remained largely unrecognized, and inadequately managed, resulting in avoidable death or suffering in infancy, childhood, and adulthood. Delivering adequate CF services is met by substantial difficulties as the spectrum and distribution of CF in Egypt are still not well known. Against this background, the aim of this work is to emphasize the challenges facing initiation of a CF center in low privileged settings with the objectives of improving diagnosis, survival, and to eventually provide optimum management. Strategies for the implementation and development of CF services, as well as proper collection and documentation of patient data are therefore of vital importance. The characterization of the prevalence and molecular genetics of CF in Egypt is of utmost importance so that appropriate genetic counseling to CF patients and their families can be achieved and to pave the way for new treatment modalities