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jeasiq-1142
التعلم ألمنظمي وأثره في نجاح المنظمات دراسة ميدانية في شركات وزارة الأعمار والإسكان في العراق
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The world witness quality jumps under radical change in the management and work styles, through adopting organizational learning as a process of continuous improvements in response to environmental stimulus, in the knowledge age and turbulent competitive environment the organizational success concept is shift from the view narrow for financial performance and marketshare to long term view which focus on building strategic capabilities that provide a sustainable competitive advantage.

Considering the strategic role assumed for the companies of the Ministry of Construction and Housing to play it, these companies have been chosen to be the field in which questions of this study will be tested.

These questions concern the nature of level and influence of the organizational learning and organizational’s success. The aim of this study is to answer these questions. Data collected principally by questionnaire tool from a sample of (66) managers. Results proved that companies have acceptable level of organizational learning and success; organizational learning has significant influence in companies success.

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Publication Date
Wed Aug 30 2023
Journal Name
Baghdad Science Journal
Post COVID-19 Effect on Medical Staff and Doctors' Productivity Analysed by Machine Learning
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The COVID-19 pandemic has profoundly affected the healthcare sector and the productivity of medical staff and doctors. This study employs machine learning to analyze the post-COVID-19 impact on the productivity of medical staff and doctors across various specialties. A cross-sectional study was conducted on 960 participants from different specialties between June 1, 2022, and April 5, 2023. The study collected demographic data, including age, gender, and socioeconomic status, as well as information on participants' sleeping habits and any COVID-19 complications they experienced. The findings indicate a significant decline in the productivity of medical staff and doctors, with an average reduction of 23% during the post-COVID-19 period. T

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Hybrid CNN-based Recommendation System
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Recommendation systems are now being used to address the problem of excess information in several sectors such as entertainment, social networking, and e-commerce. Although conventional methods to recommendation systems have achieved significant success in providing item suggestions, they still face many challenges, including the cold start problem and data sparsity. Numerous recommendation models have been created in order to address these difficulties. Nevertheless, including user or item-specific information has the potential to enhance the performance of recommendations. The ConvFM model is a novel convolutional neural network architecture that combines the capabilities of deep learning for feature extraction with the effectiveness o

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Publication Date
Sun Oct 01 2023
Journal Name
Baghdad Science Journal
Using VGG Models with Intermediate Layer Feature Maps for Static Hand Gesture Recognition
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A hand gesture recognition system provides a robust and innovative solution to nonverbal communication through human–computer interaction. Deep learning models have excellent potential for usage in recognition applications. To overcome related issues, most previous studies have proposed new model architectures or have fine-tuned pre-trained models. Furthermore, these studies relied on one standard dataset for both training and testing. Thus, the accuracy of these studies is reasonable. Unlike these works, the current study investigates two deep learning models with intermediate layers to recognize static hand gesture images. Both models were tested on different datasets, adjusted to suit the dataset, and then trained under different m

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Publication Date
Wed Mar 16 2022
Journal Name
Journal Of Educational And Psychological Researches
The Extent to Which Future Skills are Employed During Teaching from the Viewpoint of Students of Islamic Studies and their Relationship to Students' Attitude towards Future Profession
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The research aims to identify the relationship between employing future skills during teaching from the viewpoint of students of Islamic studies at the Northern Border University, as well as their attitudes towards future professions. The researcher employed the correlational descriptive approach. The tools were a questionnaire for employing future skills, and a scale for the attitude towards the future profession. The two research tools were applied to a random sample of (242) male and female students from the department of Islamic Studies, College of Education and Arts. The findings showed that the total level of employing future skills and their three axes during teaching was average. It was also found that the attitude towards future

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Publication Date
Tue Jun 23 2020
Journal Name
Baghdad Science Journal
Anomaly Detection Approach Based on Deep Neural Network and Dropout
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   Regarding to the computer system security, the intrusion detection systems are fundamental components for discriminating attacks at the early stage. They monitor and analyze network traffics, looking for abnormal behaviors or attack signatures to detect intrusions in early time. However, many challenges arise while developing flexible and efficient network intrusion detection system (NIDS) for unforeseen attacks with high detection rate. In this paper, deep neural network (DNN) approach was proposed for anomaly detection NIDS. Dropout is the regularized technique used with DNN model to reduce the overfitting. The experimental results applied on NSL_KDD dataset. SoftMax output layer has been used with cross entropy loss funct

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Scopus (25)
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Publication Date
Mon Jan 01 2024
Journal Name
Baghdad Science Journal
Artificial Neural Network and Latent Semantic Analysis for Adverse Drug Reaction Detection
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Adverse drug reactions (ADR) are important information for verifying the view of the patient on a particular drug. Regular user comments and reviews have been considered during the data collection process to extract ADR mentions, when the user reported a side effect after taking a specific medication. In the literature, most researchers focused on machine learning techniques to detect ADR. These methods train the classification model using annotated medical review data. Yet, there are still many challenging issues that face ADR extraction, especially the accuracy of detection. The main aim of this study is to propose LSA with ANN classifiers for ADR detection. The findings show the effectiveness of utilizing LSA with ANN in extracting AD

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Publication Date
Tue Apr 01 2014
Journal Name
Journal Of Economics And Administrative Sciences
Scenario theory philosophy and methodologies
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Purpose: The purpose of this study was to clarify the basic dimensions, which seeks to indestructible scenarios practices within the organization, as a final result from the use of this philosophy.

Methodology: The methodology that focuses adoption researchers to study survey of major literature that dealt with this subject in order to provide a conceptual theoretical conception of scenarios theory  .

The most prominent findings: The only successful formulation of scenarios, when you reach the decision-maker's mind wa takes aim to form a correct mental models, which appear in the expansion of Perception managers, and adopted as the basis of the decisions taken. The strength l

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Publication Date
Wed Aug 30 2023
Journal Name
Baghdad Science Journal
Deep Learning-based Predictive Model of mRNA Vaccine Deterioration: An Analysis of the Stanford COVID-19 mRNA Vaccine Dataset
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The emergence of SARS-CoV-2, the virus responsible for the COVID-19 pandemic, has resulted in a global health crisis leading to widespread illness, death, and daily life disruptions. Having a vaccine for COVID-19 is crucial to controlling the spread of the virus which will help to end the pandemic and restore normalcy to society. Messenger RNA (mRNA) molecules vaccine has led the way as the swift vaccine candidate for COVID-19, but it faces key probable restrictions including spontaneous deterioration. To address mRNA degradation issues, Stanford University academics and the Eterna community sponsored a Kaggle competition.This study aims to build a deep learning (DL) model which will predict deterioration rates at each base of the mRNA

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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
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
SBOA: A Novel Heuristic Optimization Algorithm
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A new human-based heuristic optimization method, named the Snooker-Based Optimization Algorithm (SBOA), is introduced in this study. The inspiration for this method is drawn from the traits of sales elites—those qualities every salesperson aspires to possess. Typically, salespersons strive to enhance their skills through autonomous learning or by seeking guidance from others. Furthermore, they engage in regular communication with customers to gain approval for their products or services. Building upon this concept, SBOA aims to find the optimal solution within a given search space, traversing all positions to obtain all possible values. To assesses the feasibility and effectiveness of SBOA in comparison to other algorithms, we conducte

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Scopus (8)
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