It takes a lot of time to classify the banana slices by sweetness level using traditional methods. By assessing the quality of fruits more focus is placed on its sweetness as well as the color since they affect the taste. The reason for sorting banana slices by their sweetness is to estimate the ripeness of bananas using the sweetness and color values of the slices. This classifying system assists in establishing the degree of ripeness of bananas needed for processing and consumption. The purpose of this article is to compare the efficiency of the SVM-linear, SVM-polynomial, and LDA classification of the sweetness of banana slices by their LRV level. The result of the experiment showed that the highest accuracy of 96.66% was achieved by the

Passes the Arab order moment political precision of disruption and discord and
differences of countless between its components and its parts because of the suffering he
endured and the suffering now from internal disturbances as a result of lack of cohesion
relations intra-and cultural, historical and lack of interaction between these components so
that became the focus of the policies and interests is an unprecedented degree , reduced with
the joint Arab action to the minimum, and began to focus on the interests of special
regulations.
This is with regard suffering internally, but externally the regime Arab Regional is absent the
biggest influence on international decisions because of the courtesies which were ca

This work presents external morphological study of the leafhopper Empoasca decedens
Paoli, 1932 particularly male genitalia, which were dissected and illustrated.
The genus Empoasca Walsh (Typhlocybinae: Empoascini) contains small, slender, fragile
and generally green leafhoppers. The overall length ranges from 3-3.5 mm. Members of this
genus are charachterized by their uniformly green color, inner and outer apical cells of
forewing not attaining wing apex, second and third apical cells are sessile or triangular or
even short stalked, submarginal vein of hindwing extends around wing apex and turned
beneath costal margin, apical thirds of tibiae and tarsal segments including claws are
prominently green while other

Two samples of (Ag NPs-zeolite) nanocomposite thin films have been prepared by easy hydrothermal method for 4 hours and 8 hours inside the hydrothermal autoclave at temperatures of 100°C. The two samples were used in a photoelectrochemical cell as a photocatalyst inside a cell consisting of three electrodes: the working electrode photoanode (AgNPs-zeolite), platinum as a cathode electrode, and Ag/AgCl as a reference electrode, to study the performance of AgNPs-zeolite under dark current and 473 nm laser light for water splitting. The results show the high performance of an eight-hour sample with high crystallinity compared with a four-hour sample as a reliable photocatalyst to generate hydrogen for renewable energies.

This study investigates the influence of Strategic Consensus (SC) on Organizational Performance (OP), with Strategic Alignment (SA) serving as a mediating variable, within private academic institutions in Iraq. The research utilized scales developed to measure each variable: SC, OP, and SA, all of which are unidimensional. The sample comprised 131 senior participants, including deans and faculty council members, with questionnaires distributed across three institutions: Dijla University College (35 respondents), Baghdad College of Economic Sciences (31 respondents), and the University of Uruk (65 respondents). Data analysis employed various statistical techniques, including normality testing, confirmatory factor analysis, descriptive statis

Precise forecasting of pore pressures is crucial for efficiently planning and drilling oil and gas wells. It reduces expenses and saves time while preventing drilling complications. Since direct measurement of pore pressure in wellbores is costly and time-intensive, the ability to estimate it using empirical or machine learning models is beneficial. The present study aims to predict pore pressure using artificial neural network. The building and testing of artificial neural network are based on the data from five oil fields and several formations. The artificial neural network model is built using a measured dataset consisting of 77 data points of Pore pressure obtained from the modular formation dynamics tester. The input variables

Health and safety problem can be described by statistics it can only be understood by knowing and feeling the pain, suffering, and depression. Health and safety has a legal responsibility to protect it for everyone who can affect in the workplace. This includes manufacturers, suppliers, designers and controllers of work places and employees. Work injury is one of the major problems in manufacturing and production systems industries; it is reduced production efficiency and affects the cost. To gain flexibility from a traditional manufacturing system and production efficiency, this paper is about the application of estimating technology to preview and synthesis of Lost Time of Work Injuries in industry systems aims to provide a safe workin

Currently, one of the topical areas of application of machine learning methods is the prediction of material characteristics. The aim of this work is to develop machine learning models for determining the rheological properties of polymers from experimental stress relaxation curves. The paper presents an overview of the main directions of metaheuristic approaches (local search, evolutionary algorithms) to solving combinatorial optimization problems. Metaheuristic algorithms for solving some important combinatorial optimization problems are described, with special emphasis on the construction of decision trees. A comparative analysis of algorithms for solving the regression problem in CatBoost Regressor has been carried out. The object of

Support vector machine (SVM) is a popular supervised learning algorithm based on margin maximization. It has a high training cost and does not scale well to a large number of data points. We propose a multiresolution algorithm MRH-SVM that trains SVM on a hierarchical data aggregation structure, which also serves as a common data input to other learning algorithms. The proposed algorithm learns SVM models using high-level data aggregates and only visits data aggregates at more detailed levels where support vectors reside. In addition to performance improvements, the algorithm has advantages such as the ability to handle data streams and datasets with imbalanced classes. Experimental results show significant performance improvements in compa