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Survey on intrusion detection system based on analysis concept drift: Status and future directions
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Nowadays, internet security is a critical concern; the One of the most difficult study issues in network security is "intrusion detection". Fight against external threats. Intrusion detection is a novel method of securing computers and data networks that are already in use. To boost the efficacy of intrusion detection systems, machine learning and deep learning are widely deployed. While work on intrusion detection systems is already underway, based on data mining and machine learning is effective, it requires to detect intrusions by training static batch classifiers regardless considering the time-varying features of a regular data stream. Real-world problems, on the other hand, rarely fit into models that have such constraints. Furthermore, various uses in the real world, Data distributions in intrusion detection systems, for example, are non-stationary, which produce concept drift over time or non-stationary learning. The word "concept drift" is used to describe the process of changing one's mind about something in an online-supervised learning scenario, the connection between the input data and the target variable changes over time. We define adaptive learning, classify existing concept drift strategies, evaluate the most typical, distinct, and widely used approaches and algorithms, describe adaptive algorithm assessment methodology, and show a collection of examples, all of this is based on the assumption that you have a basic understanding of supervised learning. The survey examines the various aspects of concept drift in a comprehensive manner in order to think about the current fragmented "state-of-the-art". As a result, which intends to give scholars, industry analysts, and practitioners a comprehensive introduction to idea drift adaptability.

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Publication Date
Sat Jul 06 2013
Journal Name
Creative Construction Conference 2013
The challenges of governing public private partnership in Iraq infrastructure projects
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Public-private partnership (PPP) has been used over the past 20-30 years by governments in developed countries to meet the public demand for infrastructural services. In Iraq, the PPP concept is comparatively new to the Government of Iraq (GoI), where the government has historically taken most of the responsibility for providing public services. There are few PPP projects in Iraq. However, the number is increasing. Recently the Iraqi market has experienced a number of attempts of PPP in different sectors, especially after the new investment law in 2006. The aim of this paper is to evaluate the investment environment in Iraq and to indicate the main factors affecting PPP in particular for infrastructure projects. Some literature review and

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Publication Date
Fri Feb 28 2020
Journal Name
Iraqi Journal Of Agricultural Sciences (ijas)
PHYTOTOXICITY TEST OF KEROSENE-CONTAMINATED SOIL USING BARLEY
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This study was aimed to determine a phytotoxicity experiment with kerosene as a model of a total petroleum hydrocarbon (TPHs) as Kerosene pollutant at different concentrations (1% and 6%) with aeration rate (0 and 1 L/min) and retention time (7, 14, 21, 28 and 42 days), was carried out in a subsurface flow system (SSF) on the Barley wetland. It was noted that greatest elimination 95.7% recorded at 1% kerosene levels and aeration rate 1L / min after a period of 42 days of exposure; whereas it was 47% in the control test without plants. Furthermore, the percent of elimination efficiencies of hydrocarbons from the soil was ranged between 34.155%-95.7% for all TPHs (Kerosene) concentrations at aeration rate (0 and 1 L/min). The Barley c

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Publication Date
Thu Jan 04 2024
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
The impact of recent trends of the Central Bank of Iraq in activating bank credit for the private commercial banking sector
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Abstract:

                 Central banks seek to control and supervise credit and follow it up effectively due to the high credit risks surrounding it that may lead to damage to banks, and may even lead to damage to the reputation and confidence of the banking system as a whole.

The main role of supervisory control is to control credit by controlling it from excessive expansion during periods of economic inflation or its revitalization and improvement and expansion of credit transactions in cases of economic recession, or when central banks desire to support the national economy or support a sector of various

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Publication Date
Wed Apr 10 2019
Journal Name
Iraqi Journal Of Market Research And Consumer Protection
QUALITY SYSTEMS.POSSIBILITY OF IMPLEMENTING IN SOME LOCAL FOOD ESTABLISHMENTS: QUALITY SYSTEMS.POSSIBILITY OF IMPLEMENTING IN SOME LOCAL FOOD ESTABLISHMENTS
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In order to have an idea about what happens in Iraqi food establishments in relation to implement quality management system ISO 9001, this study was performed to show the actual situation of Iraqi food establishments concerning quality management system (ISO 9001:2015), reasons of implementing, factors that hinder implementing and problems faced high administration for getting establishments certification ISO 9001:2015. The study demonstrated from the questionnaire some difficulties to implement ISO 9001 for both of establishments that implemented the quality system or which in implementing of this international standard. The most important problems during implementing were business culture and costs and the most important proble

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Publication Date
Mon Oct 01 2012
Journal Name
Iraqi Journal Of Physics
Nanostructural study of Ti-Ni binary alloy prepared by mechanical alloying
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In the present study, a powder mixture of elements Ti and Ni was mechanically alloyed in a high energy ball mill. Microstructure of the nanosized amorphous milled product in different stages of milling has been characterized by X- ray diffraction, scanning electron microscopy and differential thermal analysis. We found that time of mechanical alloying is more significant to convert all crystalline structure to the amorphous phase. Nanocrystalline phase was achieved as a result of the mechanical alloying process. The results also indicates that the phase transformation and the grain size occurs in these alloys are controlled by ball milling time

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Publication Date
Thu Dec 28 2017
Journal Name
Al-khwarizmi Engineering Journal
Aircraft Lateral-Directional Stability in Critical Cases via Lyapunov Exponent Criterion
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Based on Lyapunov exponent criterion, the aircraft lateral-directional stability during critical flight cases is presented. A periodic motion or limit cycle oscillation isdisplayed. A candidate mechanism for the wing rock limit cycle is the inertia coupling between an unstable lateral-directional (Dutch roll) mode with stable longitudinal (short period) mode. The coupling mechanism is provided by the nonlinear interaction of motion related terms in the complete set equations of motion. To analyze the state variables of the system, the complete set of nonlinear equations of motion at different high angles of attack are solved. A novel analysis including the variation of roll angle as a function of angle of attack is proposed. Furthermore

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Publication Date
Mon Dec 20 2021
Journal Name
Baghdad Science Journal
Design of L-Band Multiwavelength Laser for TDM/WDM PON Application
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This paper presents on the design of L-Band Multiwavelength laser for Hybrid Time Division Multiplexing/ Wavelength Division Multiplexing (TDM/WDM) Passive Optical Network (PON) application. In this design, an L-band Mulltiwavelength Laser is designed as the downstream signals for TDM/WDM PON. The downstream signals ranging from 1569.865 nm to 1581.973 nm with 100GHz spacing. The multiwavelength laser is designed using OptiSystem software and it is integrated into a TDM/WDM PON that is also designed using OptiSystem simulation software. By adapting multiwavelength fiber laser into a TDM/WDM network, a simple and low-cost downstream signal is proposed. From the simulation design, it is found that the proposed design is suitable to be used

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Self-Localization of Guide Robots Through Image Classification
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The field of autonomous robotic systems has advanced tremendously in the last few years, allowing them to perform complicated tasks in various contexts. One of the most important and useful applications of guide robots is the support of the blind. The successful implementation of this study requires a more accurate and powerful self-localization system for guide robots in indoor environments. This paper proposes a self-localization system for guide robots.  To successfully implement this study, images were collected from the perspective of a robot inside a room, and a deep learning system such as a convolutional neural network (CNN) was used. An image-based self-localization guide robot image-classification system delivers a more accura

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Publication Date
Thu Dec 28 2017
Journal Name
Al-khwarizmi Engineering Journal
Tuning PID Controller by Neural Network for Robot Manipulator Trajectory Tracking
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Ziegler and Nichols proposed the well-known Ziegler-Nichols method to tune the coefficients of PID controller. This tuning method is simple and gives fixed values for the coefficients which make PID controller have weak adaptabilities for the model parameters variation and changing in operating conditions. In order to achieve adaptive controller, the Neural Network (NN) self-tuning PID control is proposed in this paper which combines conventional PID controller and Neural Network learning capabilities. The proportional, integral and derivative (KP, KI, KD) gains are self tuned on-line by the NN output which is obtained due to the error value on the desired output of the system under control. The conventio

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Publication Date
Tue Jan 01 2019
Journal Name
International Journal Of Machine Learning And Computing
Facial Emotion Recognition from Videos Using Deep Convolutional Neural Networks
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Its well known that understanding human facial expressions is a key component in understanding emotions and finds broad applications in the field of human-computer interaction (HCI), has been a long-standing issue. In this paper, we shed light on the utilisation of a deep convolutional neural network (DCNN) for facial emotion recognition from videos using the TensorFlow machine-learning library from Google. This work was applied to ten emotions from the Amsterdam Dynamic Facial Expression Set-Bath Intensity Variations (ADFES-BIV) dataset and tested using two datasets.

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Scopus (58)
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