Many academics have concentrated on applying machine learning to retrieve information from databases to enable researchers to perform better. A difficult issue in prediction models is the selection of practical strategies that yield satisfactory forecast accuracy. Traditional software testing techniques have been extended to testing machine learning systems; however, they are insufficient for the latter because of the diversity of problems that machine learning systems create. Hence, the proposed methodologies were used to predict flight prices. A variety of artificial intelligence algorithms are used to attain the required, such as Bayesian modeling techniques such as Stochastic Gradient Descent (SGD), Adaptive boosting (ADA), Deci

Honeywords are fake passwords that serve as an accompaniment to the real password, which is called a “sugarword.” The honeyword system is an effective password cracking detection system designed to easily detect password cracking in order to improve the security of hashed passwords. For every user, the password file of the honeyword system will have one real hashed password accompanied by numerous fake hashed passwords. If an intruder steals the password file from the system and successfully cracks the passwords while attempting to log in to users’ accounts, the honeyword system will detect this attempt through the honeychecker. A honeychecker is an auxiliary server that distinguishes the real password from the fake passwords and t

This research supports the UN’s 2030 Agenda and its goals of ending poverty and hunger. Fruit and vegetable (FandV) lose their freshness and weight when stored at unsuitable temperatures and relative humidity. This study was conducted in Baghdad governorate, located at latitude 33.3128057 and longitude 44.3614875, in the Karrada region from February 27 to April 17, 2024. It compared the effectiveness of different storage technologies, including evaporative cooling, various air velocities, and diverse packaging methods, against sustainable and nonpackaging approaches. The study employed an air cooler with a volume of 2000 ft3/s and insulated packaging. Temperature and relative humidity were recorded in the storage environment

Nanosilica was extracted from rice husk, which was locally collected from the Iraqi mill at Al-Mishikhab district in Najaf Governorate, Iraq. The precipitation method was used to prepared Nanosilica powder from rice husk ash, after treating it thermally at 700°C, followed by dissolving the silica in the alkaline solution and getting a sodium silicate solution. Two samples of the final solution were collected to study the effect of filtration on the purity of the sample by X-ray fluorescence spectrometry (XRF). The result shows that the filtered samples have purity above  while the non-filtered sample purity was around  The structure analysis investigated by the X-ray diffraction (XRD), found that the Nanosilica powder has an amorphous

Large quantities of contaminated carwash wastewater are produced per day from carwash places. Extensively it contains large quantities of chemicals from detergents, oil, grease, heavy metals, suspended solids, types of hydrocarbons, and biological contents. A novel electrocoagulation treatment by foil electrodes was conducted to remove COD, turbidity, Total Dissolved Solids (TDS) from contaminated carwash wastewater and decrease its Electrical Conductivity (EC). A thin layer of aluminum foil is used as an electrode in this treatment process. The effects of different voltage and treatment times were studied. The best result was found at a voltage of 30 volts and treatment time 90 minute where the removal efficiency of COD

Optical Mark Recognition (OMR) is an important technology for applications that require speedy, high-accuracy processing of a huge volume of hand-filled forms. The aim of this technology is to reduce manual work, human effort, high accuracy in assessment, and minimize time for evaluation answer sheets. This paper proposed OMR by using Modify Bidirectional Associative Memory (MBAM), MBAM has two phases (learning and analysis phases), it will learn on the answer sheets that contain the correct answers by giving its own code that represents the number of correct answers, then detection marks from answer sheets by using analysis phase. This proposal will be able to detect no selection or select more than one choice, in addition, using M

The manual classification of oranges according to their ripeness or flavor takes a long time; furthermore, the classification of ripeness or sweetness by the intensity of the fruit’s color is not uniform between fruit varieties. Sweetness and color are important factors in evaluating the fruits, the fruit’s color may affect the perception of its sweetness. This article aims to study the possibility of predicting the sweetness of orange fruits based on artificial intelligence technology by studying the relationship between the RGB values of orange fruits and the sweetness of those fruits by using the Orange data mining tool. The experiment has applied machine learning algorithms to an orange fruit image dataset and performed a co