Image compression plays an important role in reducing the size and storage of data while increasing the speed of its transmission through the Internet significantly. Image compression is an important research topic for several decades and recently, with the great successes achieved by deep learning in many areas of image processing, especially image compression, and its use is increasing Gradually in the field of image compression. The deep learning neural network has also achieved great success in the field of processing and compressing various images of different sizes. In this paper, we present a structure for image compression based on the use of a Convolutional AutoEncoder (CAE) for deep learning, inspired by the diversity of human eye

The complexity and variety of language included in policy and academic documents make the automatic classification of research papers based on the United Nations Sustainable Development Goals (SDGs) somewhat difficult. Using both pre-trained and contextual word embeddings to increase semantic understanding, this study presents a complete deep learning pipeline combining Bidirectional Long Short-Term Memory (BiLSTM) and Convolutional Neural Network (CNN) architectures which aims primarily to improve the comprehensibility and accuracy of SDG text classification, thereby enabling more effective policy monitoring and research evaluation. Successful document representation via Global Vector (GloVe), Bidirectional Encoder Representations from Tra

This paper provides the result of an investigation to use of crushed clay brick as
aggregates in producing concrete. Eight different crushed clay brick aggregate concretes were
used in this investigation. Compressive strength, splitting tensile strength and pulse velocity of
crushed clay brick aggregates concrete were determined and compare to natural aggregate
concrete. The compressive strength of crushed clay brick aggregates concretes were always
lower than the compressive strength of natural aggregates concrete regardless the age of
concrete, but the crushed clay brick aggregates concrete showed better performance as the age of
concrete increases and average reduction in compressive strength were 33.5% at the age

This study aimed at comparing the performance of vertical, horizontal and hybrid subsurface flow systems in secondary treatment for the effluent wastewater from the primary basins at Al-Rustumia wastewater treatment plant, Baghdad, Iraq. The treatments were monitored for six weeks while the testsduration were from 4 to 12 September 2018 under continuous wastewater feeding for chemical oxygen demand (COD), total suspended solid (TSS),ammonia-nitrogen(NH₄-N) and phosphate (PO₄-P) in comparison with FAO and USEPA standards for effluent discharge to evaluate the suitability of treated water for irrigation purposes. Among the systems planted with Phragmites Australia, the hybrid subsurface flow system which cons

Support vector machine (SVM) is a popular supervised learning algorithm based on margin maximization. It has a high training cost and does not scale well to a large number of data points. We propose a multiresolution algorithm MRH-SVM that trains SVM on a hierarchical data aggregation structure, which also serves as a common data input to other learning algorithms. The proposed algorithm learns SVM models using high-level data aggregates and only visits data aggregates at more detailed levels where support vectors reside. In addition to performance improvements, the algorithm has advantages such as the ability to handle data streams and datasets with imbalanced classes. Experimental results show significant performance improvements in compa

The sorption of Cu²⁺ ions from synthetic wastewater using crushed concrete demolition waste (CCDW) which collected from a demolition site was investigated in a batch sorption system. Factors influencing on sorption process such as shaking time (0-300min), the initial concentration of contaminant (100-750mg/L), shaking speed (0-250 rpm), and adsorbent dosage (0.05-3 g/ml) have been studied. Batch experiments confirmed that the best values of these parameters were (180 min, 100 mg/l, 250 rpm, 0.7 g CCDW/100 ml) respectively where the achieved removal efficiency is equal to 100%. Sorption data were described using four isotherm models (Langmuir, Freundlich, Redlich-Peterson, and Radke-Prausnitz). Results proved that the pure ads

Concrete is widely used in construction materials since early 1800's. It has been known that concrete is weak in tension, so it requires some addition materials to have ductile behavior and enhance its tensile strength and strain capacity to improve their uses. In this study reactive powder concrete (RPC) was used with steel fiber by using different types of cement; (Ordinary Portland cement (OPC) and/or Portland- Limestone cement (PLC)) with three types of mixtures (OPC at the first mix, 50 % OPC and 50 % PLC at the second mix and PLC at the third mix). The behavior of RPC with steel fibers on compressive strength and tensile strength of concrete with different ages of curing (7, 14, 28 and 60) days and shrinkage have been studied. The clo

Background: The vasoconstricting agents: nor-adrenaline and 5- hydroxytryptamine
(5-HT) have a stimulant action on smooth muscle contractility of the rat vas deferens.
Objective: This study aimed to investigate the effect of exposure to continuous
darkness and continuous light on the contractility of the vasa deferntia smooth
muscles from rats to applied nor-adrenaline and 5-HT.
Method: Male albino wistar rats were divided into 3 experimental groups. Group 1:
Control animals, were exposed to the ordinary photoperiod each day. Group 2: Rats
were kept in a dark room. Group 3: In a room under a bright artificial light.
All animals were killed after 4 weeks.
Results: Vasa deferentia preparations from continuous dar