<p>The current work investigated the combustion efficiency of biodiesel engines under diverse ratios of compression (15.5, 16.5, 17.5, and 18.5) and different biodiesel fuels produced from apricot oil, papaya oil, sunflower oil, and tomato seed oil. The combustion process of the biodiesel fuel inside the engine was simulated utilizing ANSYS Fluent v16 (CFD). On AV1 diesel engines (Kirloskar), numerical simulations were conducted at 1500 rpm. The outcomes of the simulation demonstrated that increasing the compression ratio (CR) led to increased peak temperature and pressures in the combustion chamber, as well as elevated levels of CO₂ and NO mass fractions and decreased CO emission values un

The purpose of this research is to test the ability of the true strength index To time and manage trading in the financial market to select the best stocks and achieve a higher return than the Simple buy and hold strategy. And To achieve the objectives of the research, it relied on the main hypothesis, which is By using the True Strength Index to manage trading decisions buying and selling, can be achieved higher returns than the buy and hold strategy . The research community has been identified with all stocks listed on the Iraq Stock Exchange. Implementing the financial research tests requires selecting a sample from the research community that fulfills the test requirements according to a number of conditions So (38) companies we

This paper describes the problem of online autonomous mobile robot path planning, which is consisted of finding optimal paths or trajectories for an autonomous mobile robot from a starting point to a destination across a flat map of a terrain, represented by a 2-D workspace. An enhanced algorithm for solving the problem of path planning using Bacterial Foraging Optimization algorithm is presented. This nature-inspired metaheuristic algorithm, which imitates the foraging behavior of E-coli bacteria, was used to find the optimal path from a starting point to a target point. The proposed algorithm was demonstrated by simulations in both static and dynamic different environments. A comparative study was evaluated between the developed algori

Energy efficiency is a significant aspect in designing robust routing protocols for wireless sensor networks (WSNs). A reliable routing protocol has to be energy efficient and adaptive to the network size. To achieve high energy conservation and data aggregation, there are two major techniques, clusters and chains. In clustering technique, sensor networks are often divided into non-overlapping subsets called clusters. In chain technique, sensor nodes will be connected with the closest two neighbors, starting with the farthest node from the base station till the closest node to the base station. Each technique has its own advantages and disadvantages which motivate some researchers to come up with a hybrid routing algorit

I've been in this work to prepare some complexes containing mixed Kandat with some transitional elements which new complexes according to the best of our knowledge and to refer to the information from the Internet until I have been studying this diagnosis Aalmakdat

‎ This research aims to estimate stock returns, according to the ‎Rough Set Theory ‎approach, ‎test ‎its effectiveness and accuracy in predicting stock returns and their potential in the ‎field of ‎financial ‎markets, and rationalize investor decisions. The research sample is totaling (10) ‎companies traded at Iraq Stock Exchange. The results showed a remarkable ‎ ‎Rough Set Theory application in data reduction, contributing to the rationalization of ‎investment ‎decisions. The most prominent conclusions are the capability of rough set theory ‎in ‎dealing with financial data and applying it for forecasting stock ‎returns.‎The ‎research provides those interested in investing stocks in financial

The COVID-19 pandemic has necessitated new methods for controlling the spread of the virus, and machine learning (ML) holds promise in this regard. Our study aims to explore the latest ML algorithms utilized for COVID-19 prediction, with a focus on their potential to optimize decision-making and resource allocation during peak periods of the pandemic. Our review stands out from others as it concentrates primarily on ML methods for disease prediction.To conduct this scoping review, we performed a Google Scholar literature search using "COVID-19," "prediction," and "machine learning" as keywords, with a custom range from 2020 to 2022. Of the 99 articles that were screened for eligibility, we selected 20 for the final review.Our system

Most intrusion detection systems are signature based that work similar to anti-virus but they are unable to detect the zero-day attacks. The importance of the anomaly based IDS has raised because of its ability to deal with the unknown attacks. However smart attacks are appeared to compromise the detection ability of the anomaly based IDS. By considering these weak points the proposed
system is developed to overcome them. The proposed system is a development to the well-known payload anomaly detector (PAYL). By
combining two stages with the PAYL detector, it gives good detection ability and acceptable ratio of false positive. The proposed system improve the models recognition ability in the PAYL detector, for a filtered unencrypt

Abstract
A two electrode immersion electrostatic lens used in the design
of an electron gun, with small aberration, has been designed using
the finite element method (FEM). By choosing the appropriate
geometrical shape of there electrodes the potential V(r,z) and the
axial potential distribution have been computed using the FEM to
solve Laplace's equation.
The trajectory of the electron beam and the optical properties of
this lens combination of electrodes have been computed under
different magnification conditions (Zero and infinite magnification
conditions) from studying the properties of the designed electron
gun can be supplied with Abeam current of 5.7*10-6 A , electron
gun with half acceptance

The knowledge related with lexical items can be realized as including relations of meaning a cross words. Words that share a similarity of meaning are called to be synonymous, and words that share a contrary of meaning are called to be antonymous. Both of them are universal linguistic phenomenon that exist in terms of linguistic system of every language. The present study aims at finding out areas of difficulty that Iraqi EFL learners encounter in the use of synonymy and antonymy, both on the recognition and production levels. Also tries to detect the main reasons behind such difficulties. A diagnostic test of two parts, namely, recognition and production, is designed. The test is built to include two linguistic phenomenon which are: synony