In many oil fields only the BHC logs (borehole compensated sonic tool) are available to provide interval transit time (Δtp), the reciprocal of compressional wave velocity VP.

   To calculate the rock elastic or inelastic properties, to detect gas-bearing formations, the shear wave velocity VS is needed. Also VS is useful in fluid identification and matrix mineral identification.

   Because of the lack of wells with shear wave velocity data, so many empirical models have been developed to predict the shear wave velocity from compressional wave velocity. Some are mathematical models others used the multiple regression method and neural network technique.

   In this study a number of em

Abstract: The utility of DNA sequencing in diagnosing and prognosis of diseases is vital for assessing the risk of genetic disorders, particularly for asymptomatic individuals with a genetic predisposition. Such diagnostic approaches are integral in guiding health and lifestyle decisions and preparing families with the necessary foreknowledge to anticipate potential genetic abnormalities. The present study explores implementing a define-by-run deep learning (DL) model optimized using the Tree-structured Parzen estimator algorithm to enhance the precision of genetic diagnostic tools. Unlike conventional models, the define-by-run model bolsters accuracy through dynamic adaptation to data during the learning process and iterative optimization

With the escalation of cybercriminal activities, the demand for forensic investigations into these crimeshas grown significantly. However, the concept of systematic pre-preparation for potential forensicexaminations during the software design phase, known as forensic readiness, has only recently gainedattention. Against the backdrop of surging urban crime rates, this study aims to conduct a rigorous andprecise analysis and forecast of crime rates in Los Angeles, employing advanced Artificial Intelligence(AI) technologies. This research amalgamates diverse datasets encompassing crime history, varioussocio-economic indicators, and geographical locations to attain a comprehensive understanding of howcrimes manifest within the city. Lev

Cardiovascular disease (CVD) remains the leading cause of mortality in women. Estimating cardiovascular risk using prediction models is essential for guiding preventive strategies. Despite progress, conventional risk models still omit critical women-specific factors, limiting their accuracy. Precision medicine, supported by artificial intelligence, provides a framework to integrate these overlooked determinants. This approach may help close existing gaps in cardiovascular risk prediction. Sex-specific biomarkers that contribute to overall cardiovascular risk can be incorporated into risk assessment tools to improve prevention strategies, early detection, and personalized intervention. The integration of imaging-derived variables enh

Shallow foundations have been commonly used to transfer load to soil layer within the permissible limits of settlement based on the bearing capacity of the soil. For most practical cases, the shape of the shallow foundation is of slight significance. Also, friction resistance forces in the first layers of soils are negligible due to non-sufficient surrounding surface area and compaction conditions. However, the bearing capacity of a shallow foundation can be increased by several techniques. Geocell is one of the geosynthetic tool applied mainly to reinforce soil. This study presents a numerical approach of honeycombed geocell steel panels reinforcing the sandy soil under shallow foundation, and several parameters are investigated such as th

Background: Orthodontic mini-implants are increasingly used in orthodontics and the bone density is a very important factor in stabilization and success of mini-implant. The aim of this study was to observe the relationship among maximum bite force (MBF); body mass index (BMI); face width, height and type; and bone density in an attempt to predict bone density from these variables to eliminate the need for CT scan which have a highly hazard on patient. Materials and Methods: Computed tomographic (CT) images were obtained for 70 patients (24 males and 46 females) with age range 18-30 years. The maxillary and mandibular buccal cortical and cancellous bone densities were measured between 2nd premolar and 1st molar at two levels from the alveol

This study investigates the changes occurring in the province of Basra using geospatial methods and analyzes the variations in land surface temperature among the various types of land cover. For the months of July and December in the years 2013 and 2021, Landsat images were used in Landsat 8 OLI/TIRS, and satellite images were processed using ArcGIS 10.8 software. The study's categories for land use and land cover were generated through the application of supervised classification techniques, and the land surface temperature was calculated using data from a satellite sensor's brightness temperature. According to the study's findings, there has been an increase in urban areas (including barren land). From 2013 to 2021, a greater correlati

 The distribution of chilled water flow rate in terminal unit is a major factor used to evaluate the performance of central air conditioning unit. In this work, a theoretical chilled water distribution in the terminal units has been studied to predict the optimum heat performance of terminal unit. The central Air-conditioning unit model consists of cooling/ heating coil (three units), chilled water source (chiller), three-way and two-way valve with bypass, piping network, and pump. The term of optimization in terminal unit ingredient has two categories, the first is the uniform of the water flow rate representing in statically permanents standard deviation (minimum value) and the second category is the maximum heat transfer rate fro

ANN 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