t-Self-Compacting Concrete (SCC) reduces environmental noise and has more workability. This research presents an investigation of the behavior of SCC under mechanical loading (impact loading). Two types of cement have been used to produce SCC mixtures, Ordinary Portland Cement (OPC) and Portland Limestone Cement (PLC), which reduces the emission of carbon dioxide during the manufacturing process. The mixes were reinforced with Carbon Fiber Reinforced Polymer (CFRP) which is usually used to improve the seismic performance of masonry walls, to replace lost steel reinforcements, or to increase column strength and ductility. Workability tests were carried out for fresh SCC. Prepared concrete slabs of 500×500×50mm were tested for lo

This studies deals with investigated the potential of a Iraqi bentonite clay for the adsorption of bromo phenol red dye from contaminated water. Impulse adsorption experiments were performed. The contact time influence of initial dye concentration, temperature, pH, ionic strength, partical size adsorbent and adsorbent dosage on bromo phenol red adsorption are investigated in a series of batch adsorption experiments. Adsorption equilibrium data were analyzed and described by the Freundlich, Langmuir and temkin isotherms equations. Thermodynamic parameters inclusive the Gibbs free energy (∆G• ), enthalpy (∆H• ), and entropy (∆S• ), were also calculated. These parameters specified that adsorption of bromo phenol red onto bentonite

 This studies deals with investigated the potential of a Iraqi bentonite clay for the adsorption of bromo phenol red dye from contaminated water. Impulse adsorption experiments were performed. The contact time influence of initial dye concentration, temperature, pH, ionic strength, partical size adsorbent  and adsorbent dosage on bromo phenol red  adsorption  are investigated in a series of batch adsorption experiments. Adsorption equilibrium data were analyzed and described by the Freundlich, Langmuir and temkin isotherms equations. Thermodynamic parameters inclusive the Gibbs free energy (∆G•), enthalpy (∆H•), and entropy (∆S•), were also calculated. These parameters specified tha

Highly plastic soils exhibit unfavorited properties upon saturation, which produce different defects in engineering structures. Attempts were made by researchers to proffer solutions to these defects by experimenting in practical ways. This included various materials that could possibly improve the soil engineering properties and reduce environmental hazards. This paper investigates the strength behavior of highly plastic clay stabilized with brick dust. The brick dust contents were 10%, 20%, and 30% by dry weight of soil. A series of linear shrinkage and unconfined compression tests were carried out to study the effect of brick dust on the quantitative amount of shrinkage experienced by highly plastic clay and the undra

The quality of groundwater is just as important as its quantity. The kinds and concentration of salts in groundwater depend on the environment, movement, and the source of the groundwater. During the field work, 20 samples have been collected from water wells from Al-Salman basin for two seasons represent wet and dry seasons in November 2017 and April 2018. After water well samples have been analyzed the Electrical conductivity values range from (2260 to 5500) μS/cm for dry season and range from (2540 to 5630) μS/cm for wet season, the Total dissolved solids values range from (1289 to 3582) ppm for dry season and range from (1710 to 3960) ppm for wet season, and pH values range from (7.11 to 7.3) for dry and wet seasons. The Hydroc

The recent development in communication technologies between individuals allows for the establishment of more informal collaborative map data projects which are called volunteered geographic information (VGI). These projects, such as OpenStreetMap (OSM) project, seek to create free alternative maps which let users add or input new materials to the data of others. The information of different VGI data sources is often not compliant to any standard and each organization is producing a dataset at various level of richness. In this research the assessment of semantic data quality provided by web sources, e.g. OSM will depend on a comparison with the information from standard sources. This will include the validity of semanti

          Fruits sorting, recognizing, and classifying are essential post-harvest operations, as they contribute to the quality of food industry, thereby increasing the exported quantity of food. Today, an automated system for fruit classification and recognition is very important, especially when exporting to markets where quality of fruit must be high. In this study, the advantages and disadvantages of the various shape-based feature extraction algorithms and technologies that are used in sorting, classifying, and grading of fruits, as well as fruits quality estimation, are discussed in order to provide a good understanding of the use of shape-based feature extraction techniques.

The investigation of signature validation is crucial to the field of personal authenticity. The biometrics-based system has been developed to support some information security features.Aperson’s signature, an essential biometric trait of a human being, can be used to verify their identification. In this study, a mechanism for automatically verifying signatures has been suggested. The offline properties of handwritten signatures are highlighted in this study which aims to verify the authenticity of handwritten signatures whether they are real or forged using computer-based machine learning techniques. The main goal of developing such systems is to verify people through the validity of their signatures. In this research, images of a group o

     Automated medical diagnosis is an important topic, especially in detection and classification of diseases. Malaria is one of the most widespread diseases, with more than 200 million cases, according to the 2016 WHO report. Malaria is usually diagnosed using thin and thick blood smears under a microscope. However, proper diagnosis is difficult, especially in poor countries where the disease is most widespread. Therefore, automatic diagnostics helps in identifying the disease through images of red blood cells, with the use of machine learning techniques and digital image processing. This paper presents an accurate model using a Deep Convolutional Neural Network build from scratch. The paper also proposed three CNN