The aim of this study is to investigate the kinetics of copper removal from aqueous solutions using an electromembrane extraction (EME) system. To achieve this, a unique electrochemical cell design was adopted comprising two glass chambers, a supported liquid membrane (SLM), a graphite anode, and a stainless-steel cathode. The SLM consisted of a polypropylene flat membrane infused with 1-octanol as a solvent and bis(2-ethylhexyl) phosphate (DEHP) as a carrier. The impact of various factors on the kinetics constant rate was outlined, including the applied voltage, initial pH of the donor phase solution, and initial copper concentration. The results demonstrated a significant influence of the applied voltage on enhancing the rate of c

Compression is the reduction in size of data in order to save space or transmission time. For data transmission, compression can be performed on just the data content or on the entire transmission unit (including header data) depending on a number of factors. In this study, we considered the application of an audio compression method by using text coding where audio compression represented via convert audio file to text file for reducing the time to data transfer by communication channel. Approach: we proposed two coding methods are applied to optimizing the solution by using CFG. Results: we test our application by using 4-bit coding algorithm the results of this method show not satisfy then we proposed a new approach to compress audio fil

An Intelligent Internet of Things network based on an Artificial Intelligent System, can substantially control and reduce the congestion effects in the network. In this paper, an artificial intelligent system is proposed for eliminating the congestion effects in traffic load in an Intelligent Internet of Things network based on a deep learning Convolutional Recurrent Neural Network with a modified Element-wise Attention Gate. The invisible layer of the modified Element-wise Attention Gate structure has self-feedback to increase its long short-term memory. The artificial intelligent system is implemented for next step ahead traffic estimation and clustering the network. In the proposed architecture, each sensing node is adaptive and able to

In this paper, an algorithm is suggested to train a single layer feedforward neural network to function as a heteroassociative memory. This algorithm enhances the ability of the memory to recall the stored patterns when partially described noisy inputs patterns are presented. The algorithm relies on adapting the standard delta rule by introducing new terms, first order term and second order term to it. Results show that the heteroassociative neural network trained with this algorithm perfectly recalls the desired stored pattern when 1.6% and 3.2% special partially described noisy inputs patterns are presented.

Melanoma, a highly malignant form of skin cancer, affects individuals of all genders and is associated with high mortality rates, especially in advanced stages. The use of tele-dermatology has emerged as a proficient diagnostic approach for skin lesions and is particularly beneficial in rural areas with limited access to dermatologists. However, accurately, and efficiently segmenting melanoma remains a challenging task due to the significant diversity observed in the morphology, pigmentation, and dimensions of cutaneous nevi. To address this challenge, we propose a novel approach called DenseUNet-169 with a dilated convolution encoder-decoder for automatic segmentation of RGB dermascopic images. By incorporating dilated convolution,

This paper deals with novels for group of Iraqi Women novelists published in the time period 2003 – 2013, and the functioning of temporal anomalies in the Iraqi Women's narrative.
In general, the novel contains structural elements such as: the characters, events and the places, these elements must be collected by an artist creating a complete work of fiction. However the time dominates the other elements through progression and regaining called Time paradox, it has a modern critical importance because of its impact in highlighting of political, social and cultural events that make up the fictional environment which cast a shadow over other techniques. And that it is clear in the course of the narrative.

Background: A successful endodontic treatment is aimed at the sterilization of the entire pulp space. The use of extracts from Rhamnus prinoides as a novel irrigating material for root canal has not been studied . Hence, the antimicrobial efficacy of the alcoholic extract of Rhamnus prinoides as an irrigation material against E. faecalis was evaluated in comparison with the 2.5% sodium hypochlorite (NaOCL) solution used for root canals of permanent teeth. Methods: A total of 30 single-rooted human permanent teeth were thoroughly cleaned, shaped, and disinfected. Then, each tooth was subjected to a two-week infection with Enterococcus faecalis at 37 °C . Afterward, the samples were divided into three groups (10 teeth per group): 0.9

To maintain river flows necessary to meet social and ecological objectives, instream environmental flows are frequently used as a strategy. The capability of three alternative historical flow approaches to protect against low flows is shown in this study using gage stations in the Shatt Al-Hillah River in Iraq. The extension of the Shatt al-Hillah River is the focus of this research discussion on environmental flow assessment. The available data on discharge in this research were adopted for ten years from 2012-2021. Different flow methods were adopted to establish a minimum environmental flow in the Shatt Al-Hillah River. Three hydrological-based approaches: Tennant, modified Tennant, and low-flow metrics like 7Q10, wer