The provision of safe water for people is a human right; historically, a major number of people depend on groundwater as a source of water for their needs, such as agricultural, industrial or human activities. Water resources have recently been affected by organic and/or inorganic contaminants as a result of population growth and increased anthropogenic activity, soil leaching and pollution. Water resource remediation has become a serious environmental concern, since it has a direct impact on many aspects of people’s lives. For decades, the pump-and-treat method has been considered the predominant treatment process for the remediation of contaminated groundwater with organic and inorganic contaminants. On the other side, this tech

A hand gesture recognition system provides a robust and innovative solution to nonverbal communication through human–computer interaction. Deep learning models have excellent potential for usage in recognition applications. To overcome related issues, most previous studies have proposed new model architectures or have fine-tuned pre-trained models. Furthermore, these studies relied on one standard dataset for both training and testing. Thus, the accuracy of these studies is reasonable. Unlike these works, the current study investigates two deep learning models with intermediate layers to recognize static hand gesture images. Both models were tested on different datasets, adjusted to suit the dataset, and then trained under different m

Background: The prevalence of deep veins thrombosis, complicating total knee replacement in Asian countries, has not been fully appreciated in comparison to western countries as there are few studies on that. There is an important correlation between the evidence of deep veins thrombosis in the lower extremity and likelihood of   pulmonary embolism later one . Because of its noninvasive nature, duplex ultrasound has become one of the initial dependable modality for the cheek out of deep veins thrombosis after total knee replacement  . Therefore, this study was designed to evaluate the outcome of asymptomatic after total knee replacement by duplex ultrasound among Iraqi patients.

Methods: This

This paper investigates some exact and local search methods to solve the traveling salesman problem. The Branch and Bound technique (BABT) is proposed, as an exact method, with two models. In addition, the classical Genetic Algorithm (GA) and Simulated Annealing (SA) are discussed and applied as local search methods. To improve the performance of GA we propose two kinds of improvements for GA; the first is called improved GA (IGA) and the second is Hybrid GA (HGA).

The IGA gives best results than GA and SA, while the HGA is the best local search method for all within a reasonable time for 5 ≤ n ≤ 2000, where n is the number of visited cities. An effective method of reducing the size of the TSP matrix was proposed with

The traditional shortest path problem is mainly concerned with identifying the associated paths in the transportation network that represent the shortest distance between the source and the destination in the transportation network by finding either cost or distance. As for the problem of research under study it is to find the shortest optimal path of multi-objective (cost, distance and time) at the same time has been clarified through the application of a proposed practical model of the problem of multi-objective shortest path to solve the problem of the most important 25 commercial US cities by travel in the car or plane. The proposed model was also solved using the lexicographic method through package program Win-QSB 2.0 for operation

The proton momentum distributions (PMD) and the elastic
electron scattering form factors F(q) of the ground state for some
even mass nuclei in the 2p-1f shell for 70Ge, 72Ge, 74Ge and 76Ge are
calculated by using the Coherent Density Fluctuation Model (CDFM)
and expressed in terms of the fluctuation function (weight function)
|F(x)|2. The fluctuation function has been related to the charge
density distribution (CDD) of the nuclei and determined from the
theory and experiment. The property of the long-tail behavior at high
momentum region of the proton momentum distribution has been
obtained by both the theoretical and experimental fluctuation
functions. The calculated form factors F (q) of all nuclei under s

Longitudinal data is becoming increasingly common, especially in the medical and economic fields, and various methods have been analyzed and developed to analyze this type of data.

In this research, the focus was on compiling and analyzing this data, as cluster analysis plays an important role in identifying and grouping co-expressed subfiles over time and employing them on the nonparametric smoothing cubic B-spline model, which is characterized by providing continuous first and second derivatives, resulting in a smoother curve with fewer abrupt changes in slope. It is also more flexible and can pick up on more complex patterns and fluctuations in the data.

The longitudinal balanced data profile was compiled into subgroup

       Copper Phthalocyanine (CuPc) thin film with and without multi-walled carbon nanotubes (MWCNTs) is prepared using the solution based method and used in gas sensor and solar cell applications. The structural characteristics of the CuPc thin films showed a single peak around 7^o with the preferred orientation for charge transportation. Using atomic force microscopy (AFM), morphological properties show a rough surface with some aggregates and ribbons. The optical absorption properties were determined using UV-Visible absorption spectroscopy; the optical band gap has varied after adding MWCNTs to CuPc. Electrical conductivity of CuPc:MWCNTs composite is higher than that of the pure CuPc. The CuPc thin film sensr have sh