The smart city concept has attracted high research attention in recent years within diverse application domains, such as crime suspect identification, border security, transportation, aerospace, and so on. Specific focus has been on increased automation using data driven approaches, while leveraging remote sensing and real-time streaming of heterogenous data from various resources, including unmanned aerial vehicles, surveillance cameras, and low-earth-orbit satellites. One of the core challenges in exploitation of such high temporal data streams, specifically videos, is the trade-off between the quality of video streaming and limited transmission bandwidth. An optimal compromise is needed between video quality and subsequently, rec

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

One of the most enduring expressions of urban poverty in developing countries is the proliferation of slums and informal settlements .these settlements have the most deplorable living and environmental conditions within the city and are characterized by inadequate water supply, squalid conditions of environmental sanitation .overcrowded and dilapidated habitation, hazardous location .insecure tenure and vulnerability to serious health risks among many others .its in recognition of the of the development challenges to significantly improve the lives of at least 800000 people allover the country So our objectives in this research are the ensuring of a durable improvement of housing conditions and housing environment of poor people

The development of information systems in recent years has contributed to various methods of gathering information to evaluate IS performance. The most common approach used to collect information is called the survey system. This method, however, suffers one major drawback. The decision makers consume considerable time to transform data from survey sheets to analytical programs. As such, this paper proposes a method called ‘survey algorithm based on R programming language’ or SABR, for data transformation from the survey sheets inside R environments by treating the arrangement of data as a relational format. R and Relational data format provide excellent opportunity to manage and analyse the accumulated data. Moreover, a survey syste

Abstract

The Classical Normal Linear Regression Model Based on Several hypotheses, one of them is Heteroscedasticity as it is known that the wing of least squares method (OLS), under the existence of these two problems make the estimators, lose their desirable properties, in addition the statistical inference becomes unaccepted table. According that we put tow alternative,  the first one is  (Generalized Least Square) Which is denoted by (GLS), and the second alternative is to (Robust covariance matrix estimation) the estimated parameters method(OLS), and that the way (GLS) method neat and certified, if the capabilities (Efficient) and the statistical inference Thread on the basis of an acceptable

There is an assumption implicit but fundamental theory behind the decline by the time series used in the estimate, namely that the time series has a sleep feature Stationary or the language of Engle Gernger chains are integrated level zero, which indicated by I (0). It is well known, for example, tables of t-statistic is designed primarily to deal with the results of the regression that uses static strings. This assumption has been previously treated as an axiom the mid-seventies, where researchers are conducting studies of applied without taking into account the properties of time series used prior to the assessment, was to accept the results of these tests Bmanueh and delivery capabilities based on the applicability of the theo

Crime is one of the most severe challenges facing States, and strives to find preventive measures, reduce its seriousness, and prevent them; due to developments, crimes have increased, and emerging new patterns of crimes, there is an urgent need to prevent crimes and reduce their effects. Modernizing its punitive system and diverting it to correctional rehabilitative justice to redress the prejudice caused by the crime and rehabilitate the convicted person by using alternative measures to short-term imprisonment. This research emphasizes alternative sanctions' value to minimizing short-term imprisonment penalties and their impact on societal security through several goals like, the negative consequences, justifications, and alternatives

Apium graveolens has been utilized for a multitude of purposes due to its diverse pharmacological characteristics. On the other hand, little is known about how the fatty acids (saturated and unsaturated) terpenes and steroids found in Iraqi Apium graveolens affect the human cancer cells. The purpose of this study was to examine the effects of Iraqi Apium graveolens petroleum ether extract on the human prostate cancer cell line (PC3). Subsidiary extraction and phytochemical analysis by GC/MS were performed.The dry and fresh aerial parts (leaves and stem) of Apium graveolens were extracted using a Soxhlet device with 70 % ethanol, then fractionated with petroleum ether. Then Gas Chromatography System was used to identify the bioactive

The objective of this study is to apply Artificial Neural Network for heat transfer analysis of shell-and-tube heat exchangers widely used in power plants and refineries. Practical data was obtained by using industrial heat exchanger operating in power generation department of Dura refinery. The commonly used Back Propagation (BP) algorithm was used to train and test networks by divided the data to three samples (training, validation and testing data) to give more approach data with actual case. Inputs of the neural network include inlet water temperature, inlet air temperature and mass flow rate of air. Two outputs (exit water temperature to cooling tower and exit air temperature to second stage of air compressor) were taken in ANN.