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.
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Binary relations or interactions among bio-entities, such as proteins, set up the essential part of any living biological system. Protein-protein interactions are usually structured in a graph data structure called "protein-protein interaction networks" (PPINs). Analysis of PPINs into complexes tries to lay out the significant knowledge needed to answer many unresolved questions, including how cells are organized and how proteins work. However, complex detection problems fall under the category of non-deterministic polynomial-time hard (NP-Hard) problems due to their computational complexity. To accommodate such combinatorial explosions, evolutionary algorithms (EAs) are proven effective alternatives to heuristics in solvin
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A Modified version of the Generlized standard addition method ( GSAM) was developed. This modified version was used for the quantitative determination of arginine (Arg) and glycine ( Gly) in arginine acetyl salicylate – glycine complex . According to this method two linear equations were solved to obtain the amounts of (Arg) and (Gly). The first equation was obtained by spectrophotometic measurement of the total absorbance of (Arg) and (Gly) colored complex with ninhydrin . The second equation was obtained by measuring the total acid consumed by total amino groups of (Arg) and ( Gly). The titration was carried out in non- aqueous media using perchloric acid in glacial acetic acid as a titrant. The developed metho
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Lowering the emission, fuel economy and torque management are the essential
requirements in the recent development in the automobile industry. The main engine control
input that satisfies the above requirements is the throttling angle which adjusts the air mass
flow rate to the engine port. Due to the uncertainty and the presence of the nonlinear
components in its dynamical model, the sliding mode control theory is utilized in this work
for the throttle valve angle control system to design a robust controller for this system in the
presence of a nonlinear spring and Coulomb friction. A continuous sliding mode control law
which consists of a saturation function, instead of a signum function, and the integral of
ano
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Leap Motion Controller (LMC) is a gesture sensor consists of three infrared light emitters and two infrared stereo cameras as tracking sensors. LMC translates hand movements into graphical data that are used in a variety of applications such as virtual/augmented reality and object movements control. In this work, we intend to control the movements of a prosthetic hand via (LMC) in which fingers are flexed or extended in response to hand movements. This will be carried out by passing in the data from the Leap Motion to a processing unit that processes the raw data by an open-source package (Processing i3) in order to control five servo motors using a micro-controller board. In addition, haptic setup is proposed using force sensors (F
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Cancer is in general not a result of an abnormality of a single gene but a consequence of changes in many genes, it is therefore of great importance to understand the roles of different oncogenic and tumor suppressor pathways in tumorigenesis. In recent years, there have been many computational models developed to study the genetic alterations of different pathways in the evolutionary process of cancer. However, most of the methods are knowledge-based enrichment analyses and inflexible to analyze user-defined pathways or gene sets. In this paper, we develop a nonparametric and data-driven approach to testing for the dynamic changes of pathways over the cancer progression. Our method is based on an expansion and refinement of the pathway bei
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