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), Decision Trees (DT), K-nearest neighbor (KNN), and Logistic Regression (LR), have been used to identify the parameters that allow for effective price estimation. These approaches were tested on a data set of an extensive Indian airline network. When it came to estimating flight prices, the results demonstrate that the Decision tree method is the best conceivable Algorithm for predicting the price of a flight in our particular situation with 89% accuracy. The SGD method had the lowest accuracy, which was 38 %, while the accuracies of the KNN, NB, ADA, and LR algorithms were 69 %, 45 %, and 43 %, respectively. This study's presented methodologies will allow airline firms to predict flight prices more accurately, enhance air travel, and eliminate delay dispersion. Index Terms— Machine learning, Prediction model, Airline price prediction, Software testing,
The need for quick airborne transportation is critical, especially in emergencies. Drones with suspended payloads might be used to accomplish quick airborne transportation. Due to the environment or the drone's motion, the slung load may oscillate and lead the drone to fall. The altitude and attitude controls are the backbones of the drone's stability, and they must be adequately designed. Because of their symmetrical and simple structure, quadrotor helicopters are one of the most popular drone classes. In this work, a genetic algorithm with two weighted terms fitness function is used to adjust a Proportional-Integral-Derivative (PID) controller to compensate for the altitude and attitude controllers in a quadrotor drone
... Show MoreGreen nanotechnology is a thrilling and rising place of technology and generation that bracesthe ideas of inexperienced chemistry with ability advantages for sustainability, protection, andthe general protection from the race human. The inexperienced chemistry method introduces aproper technique for the production, processing, and alertness of much less dangerous chemicalsubstances to lessen threats to human fitness and the environment. The technique calls for inintensity expertise of the uncooked materials, particularly in phrases in their creation intonanomaterials and the resultant bioactivities that pose very few dangerous outcomes for peopleand the environment. In the twenty-first century, nanotechnology has become a systematic
... Show MoreStatic Synchronous Series Compensator (SSSC) is a well known device for effectively regulating the active power flow in a power system. In this paper, the SSSC linearized power flow equations are incorporated into Newton-Raphson algorithm in a MATLAB written program to investigate the control of active poweer flow and the transient stability of a five bus and a thirty bus IEEE test systems, during abnormal conduction (three phase fault near buses). A comparison of the results obtained for the base case without SSSC and with it to investigate the effectiveness of the device on both of the active power flow and the transient stability.
An adaptive nonlinear neural controller to reduce the nonlinear flutter in 2-D wing is proposed in the paper. The nonlinearities in the system come from the quasi steady aerodynamic model and torsional spring in pitch direction. Time domain simulations are used to examine the dynamic aero elastic instabilities of the system (e.g. the onset of flutter and limit cycle oscillation, LCO). The structure of the controller consists of two models :the modified Elman neural network (MENN) and the feed forward multi-layer Perceptron (MLP). The MENN model is trained with off-line and on-line stages to guarantee that the outputs of the model accurately represent the plunge and pitch motion of the wing and this neural model acts as the identifier. Th
... Show MoreKinematics is the mechanics branch which dealswith the movement of the bodies without taking the force into account. In robots, the forward kinematics and inverse kinematics are important in determining the position and orientation of the end-effector to perform multi-tasks. This paper presented the inverse kinematics analysis for a 5 DOF robotic arm using the robotics toolbox of MATLAB and the Denavit-Hartenberg (D-H) parameters were used to represent the links and joints of the robotic arm. A geometric approach was used in the inverse kinematics solution to determine the joints angles of the robotic arm and the path of the robotic arm was divided into successive lines to accomplish the required tasks of the robotic arm.Therefore, this
... Show MoreWe propose a novel strategy to optimize the test suite required for testing both hardware and software in a production line. Here, the strategy is based on two processes: Quality Signing Process and Quality Verification Process, respectively. Unlike earlier work, the proposed strategy is based on integration of black box and white box techniques in order to derive an optimum test suite during the Quality Signing Process. In this case, the generated optimal test suite significantly improves the Quality Verification Process. Considering both processes, the novelty of the proposed strategy is the fact that the optimization and reduction of test suite is performed by selecting only mutant killing test cases from cumulating t-way test ca
... Show MoreThe subject of social capital is of great importance, as it provides an analytical framework for researchers interested in understanding the impact of the Internet on many dimensions of human and social life. And because social networking sites have infiltrated societies and produced new variables at the level of human and social communication, this study came to examine the relationship between the use of the social networking site Facebook and the accumulation of social capital among a sample of University of Algeria 3 students, by researching the variables of intensity of use and patterns of use as independent variables and their relationship to social capital. The results of the field study revealed a strong relationship between the
... Show MoreBackground: Chemokine (C-X-C motif) ligand (CXCL9) has an important role recruiting the T-lymphocytes and immune response after infection by inducing T-cells accumulation around the areas associated with infections. However, this role is poorly known in relation with Toxoplasma gondii infection and also in association with thyroid hormones, which the present study is focused on. Methods: Eighty-seven women were included in this study for the period between September 2021 and February 2022. Blood samples of uninfected healthy pregnant, in addition to aborted and pregnant women infected with toxoplasmosis, were collected. Sera were then obtained and stored at -10°C. Toxo-latex agglutination test was done, followed by detec
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