Mixed-effects conditional logistic regression is evidently more effective in the study of qualitative differences in longitudinal pollution data as well as their implications on heterogeneous subgroups. This study seeks that conditional logistic regression is a robust evaluation method for environmental studies, thru the analysis of environment pollution as a function of oil production and environmental factors. Consequently, it has been established theoretically that the primary objective of model selection in this research is to identify the candidate model that is optimal for the conditional design. The candidate model should achieve generalizability, goodness-of-fit, parsimony and establish equilibrium between bias and variab

يهدف البحث الى أعداد بعض تمرينات الاساسية لسلاح الشيش بأستخدام المرايا في تطوير قدرة مستوى تعلم الطالبات في المبارزة ومعرفة الفروق بين المجموعتين التجريبي والضابطة بتأثير استخدام المرايا في مستوى اداء بعض مهارات سلاح الشيش لطالبات المرحلة الثالثة , وقد أستخدمت الباحثتان المنهج التجريبي على عينة من طالبات المرحلة الثالثة , وقد بلغ عددهم (45) طالبة , وقد خرجت الباحثتين بعدة أستنتاجات وهي:- - أن المنهاج التعليمي

Orthodontic wires facilitate the required dental adjustments in the context of orthodontic therapy. The archwire has played a crucial role in orthodontic treatment, and the increasing emphasis on aesthetic preferences from patients, as well as the development of composite and ceramic brackets, have prompted investigations into aesthetic archwires that complement these brackets. Orthodontic wires are produced using a diverse range of materials. The utilisation of all available wire types can improve patient comfort, decrease chairside time, and shorten the overall duration of treatment. The individual clinician must possess comprehensive knowledge and comprehension of the various requirements and alternatives throughout the therapeut

The rapid advancements in wireless technology and digital electronics have led to the widespread adoption of compact, intelligent devices in various aspects of daily life. These advanced systems possess the capability to sense environmental changes, process data, and communicate seamlessly within interconnected networks. Typically, such devices integrate low-power radio transmitters and multiple smart sensors, hence enabling efficient functionality across wide ranges of applications. Alongside these technological developments, the concept of the IoT has emerged as a transformative paradigm, facilitating the interconnection of uniquely identifiable devices through internet-based networks. This paper aims to provide a comprehensive ex

Within the framework of big data, energy issues are highly significant. Despite the significance of energy, theoretical studies focusing primarily on the issue of energy within big data analytics in relation to computational intelligent algorithms are scarce. The purpose of this study is to explore the theoretical aspects of energy issues in big data analytics in relation to computational intelligent algorithms since this is critical in exploring the emperica aspects of big data. In this chapter, we present a theoretical study of energy issues related to applications of computational intelligent algorithms in big data analytics. This work highlights that big data analytics using computational intelligent algorithms generates a very high amo

The research aims to identify the meaning of drug addiction, which being one of the behavioral-deviation signs. It largely seems similar to alcohol-addiction. World health organization has defined drug addiction as a sporadic or chronic-state of intoxication emerges of recurrent-consumption of drugs that impact harmfully on individual and society. The second aim is to study the psychological and health implications on drugs’ users and thirdly to design a psychological-program for those who take drugs.     

         The economy is exceptionally reliant on agricultural productivity. Therefore, in domain of agriculture, plant infection discovery is a vital job because it gives promising advance towards the development of agricultural production. In this work, a framework for potato diseases classification based on feed foreword neural network is proposed. The objective of this work  is presenting a system that can detect and classify four kinds of potato tubers diseases; black dot, common scab, potato virus Y and early blight based on their images. The presented PDCNN framework comprises three levels: the pre-processing is first level, which is based on K-means clustering algorithm to detect the infected area from potato image. The s

The fingerprints are the more utilized biometric feature for person identification and verification. The fingerprint is easy to understand compare to another existing biometric type such as voice, face. It is capable to create a very high recognition rate for human recognition. In this paper the geometric rotation transform is applied on fingerprint image to obtain a new level of features to represent the finger characteristics and to use for personal identification; the local features are used for their ability to reflect the statistical behavior of fingerprint variation at fingerprint image. The proposed fingerprint system contains three main stages, they are: (i) preprocessing, (ii) feature extraction, and (iii) matching. The preprocessi