Wireless Body Area Sensor Networks (WBASNs) have garnered significant attention due to the implementation of self-automaton and modern technologies. Within the healthcare WBASN, certain sensed data hold greater significance than others in light of their critical aspect. Such vital data must be given within a specified time frame. Data loss and delay could not be tolerated in such types of systems. Intelligent algorithms are distinguished by their superior ability to interact with various data systems. Machine learning methods can analyze the gathered data and uncover previously unknown patterns and information. These approaches can also diagnose and notify critical conditions in patients under monitoring. This study implements two s

Information about soil consolidation is essential in geotechnical design. Because of the time and expense involved in performing consolidation tests, equations are required to estimate compression index from soil index properties. Although many empirical equations concerning soil properties have been proposed, such equations may not be appropriate for local situations. The aim of this study is to investigate the consolidation and physical properties of the cohesive soil. Artificial Neural Network (ANN) has been adapted in this investigation to predict the compression index and compression ratio using basic index properties. One hundred and ninety five consolidation results for soils tested at different construction sites

Birds of prey (Raptors) are top predator avian species that many migrate annually through Mesopotamian marshes in southern Iraq toward their wintering grounds in Arabia and Africa, while others are breeding residents; however, information on their current status is scarce. From January 2016 to April 2019, a total of 20 field expeditions were conducted in the geographical zone of the Mesopotamian marshes, wetlands of international importance. The survey covered the Central Marshes, Al-Hammar and Hawizeh Marsh. One of the objectives of the field surveys is to list the raptors species that wintering and/or migrating through the Mesopotamian marshes and to understand their current spatial and temporal distribution. In the present study, a to

Dry environment study forms an important part in the field of applies geomorphology for
the wide rang of its lands which form most of the world, homeland, and Iraqi lands specially,
and what these lands include of scientific cases which needs to be searched and investigated.
They include rocks, land shapes, water supplements, its ancient soil and its active diggings are
all signs of the environment changes and effects that these lands under take over time, with
continuous remains of its features of characteristics under geo morphological dry
circumstances which works to slow change average, when the geomorphologic fearers varies
in this environment and what it contain of important economical resource. As to participl

The current study aims to find a new plan to manage the water quality of the western part of the Hammar Marsh to reduce the salts that cause problems for the marshes and preserve their environmental life by isolating the southwestern part of the Hammar Marsh by closing the outlet under the railway embankment. The outlet is discharging saline water to the east-western part of Al Hammar Marsh. After isolating the southwestern part of the marsh, a new outlet is proposed. The impact of the flow hydrodynamics on improving the water quality was simulated using the SMS model. The hydrodynamics and water quality simulation models for the marsh are : a hydrodynamic model and average depth (SMS RMA2) and a two-dimensional water quality model (SMS

The central marshes are one of the most important wetlands/ecosystems in the southern area of Iraq. This study evaluates the bed soil's mechanical, physical, and chemical properties at certain southern Iraqi central marshes sites. This was conducted to investigate their types and suitability for enhancing the agricultural reality of most field crops and for construction purposes. Soil samples were collected from 15 sites at 10-100 cm depth. Hence, numerous parameters were determined: index properties, unconfined compressive strength, direct shear strength, consolidation, texture, and sieve analysis, water content, specific gravity, dry density, permeability, pH, total soluble salts (TSS), organic materials (OM) and total

The method of solving volterra integral equation by using numerical solution is a simple operation but to require many memory space to compute and save the operation. The importance of this equation appeares new direction to solve the equation by using new methods to avoid obstacles. One of these methods employ neural network for obtaining the solution.

This paper presents a proposed method by using cascade-forward neural network to simulate volterra integral equations solutions. This method depends on training cascade-forward neural network by inputs which represent the mean of volterra integral equations solutions, the target of cascade-forward neural network is to get the desired output of this network. Cascade-forward neural

Imaging by Ultrasound (US) is an accurate and useful modality for the assessment of gestational age (GA), estimation fetal weight, and monitoring the fetal growth during pregnancy, is a routine part of prenatal care, and that can greatly impact obstetric management. Estimation of GA is important in obstetric care, making appropriate management decisions requires accurate appraisal of GA. Accurate GA estimation may assist obstetricians in appropriately counseling women who are at risk of a preterm delivery about likely neonatal outcomes, and it is essential in the evaluation of the fetal growth and detection of intrauterine growth restriction. There are many formulas are used to estimate fetal GA in the world, but it's not specify fo