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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 accurate solution for indoor robot navigation. The more accurate solution of the guide robotic system opens a new window of the self-localization system and solves the more complex problem of indoor robot navigation. It makes a reliable interface between humans and robots. This study successfully demonstrated how a robot finds its initial position inside a room. A deep learning system, such as a convolutional neural network, trains the self-localization system as an image classification problem.  The robot was placed inside the room to collect images using a panoramic camera. Two datasets were created from the room images based on the height above and below the chest. The above-mentioned method achieved a localization accuracy of 98.98%.

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Publication Date
Fri Jan 01 2021
Journal Name
International Journal Of Agricultural And Statistical Sciences
DYNAMIC MODELING FOR DISCRETE SURVIVAL DATA BY USING ARTIFICIAL NEURAL NETWORKS AND ITERATIVELY WEIGHTED KALMAN FILTER SMOOTHING WITH COMPARISON
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Survival analysis is widely applied in data describing for the life time of item until the occurrence of an event of interest such as death or another event of understudy . The purpose of this paper is to use the dynamic approach in the deep learning neural network method, where in this method a dynamic neural network that suits the nature of discrete survival data and time varying effect. This neural network is based on the Levenberg-Marquardt (L-M) algorithm in training, and the method is called Proposed Dynamic Artificial Neural Network (PDANN). Then a comparison was made with another method that depends entirely on the Bayes methodology is called Maximum A Posterior (MAP) method. This method was carried out using numerical algorithms re

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Publication Date
Mon Nov 30 2020
Journal Name
Journal Of Economics And Administrative Sciences
The Impact Of Adopting The Social Responsibility On Marketing Performance An Applied Study on NAFTAL Company
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This research paper aims at studying the effect of adopting the corporate social responsibility on marketing performance indicators, where the study adopted the descriptive method for theoretical concepts, in addition to the statistical approach by using the SPSS v25 program to analyze the questionnaire and test the hypotheses of the study. The results showed that there is a positive correlation between social responsibility and marketing performance indicators, and the study found that it is better for NAFTAL Company to mix the environmental and social responsibilities in order to improve its marketing performance. Also, the study recommended that Naftal should adopt the four responsibilities equally, correctly and make its work

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Publication Date
Fri Jan 01 2016
Journal Name
Ieee Access
Towards an Applicability of Current Network Forensics for Cloud Networks: A SWOT Analysis
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In recent years, the migration of the computational workload to computational clouds has attracted intruders to target and exploit cloud networks internally and externally. The investigation of such hazardous network attacks in the cloud network requires comprehensive network forensics methods (NFM) to identify the source of the attack. However, cloud computing lacks NFM to identify the network attacks that affect various cloud resources by disseminating through cloud networks. In this paper, the study is motivated by the need to find the applicability of current (C-NFMs) for cloud networks of the cloud computing. The applicability is evaluated based on strengths, weaknesses, opportunities, and threats (SWOT) to outlook the cloud network. T

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Publication Date
Sat Aug 12 2017
Journal Name
Journal Of Engineering
Prepare rules spatial data for soils and the Calculation of an Area in Iraq for Industrial Purposes using Geographic Information Systems (GIS)
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      The process of soil classification in Iraq for industrial purposes is important topics that need to be extensive and specialized studies. In order for the advancement of reality service and industrial in our dear country, that a lot of scientific research touched upon the soil classification in the agricultural, commercial and other fields. No source and research can be found that touched upon the classification of land for industrial purposes directly. In this research specialized programs have been used such as geographic information system software The geographical information system permits the study of local distribution of phenomena, activities and the aims that can be determined in the loca

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Publication Date
Thu Dec 01 2016
Journal Name
Journal Of Engineering
Robustness Assessment of Regional GNSS Geodetic Networks for Precise Applications
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Over the past few decades, the surveying fieldworks were usually carried out based on classical positioning methods for establishing horizontal and vertical geodetic networks. However, these conventional positioning techniques have many drawbacks such as time-consuming, too costly, and require massive effort. Thus, the Global Navigation Satellite System (GNSS) has been invented to fulfill the quickness, increase the accuracy, and overcome all the difficulties inherent in almost every surveying fieldwork. This research assesses the accuracy of local geodetic networks using different Global Navigation Satellite System (GNSS) techniques, such as Static, Precise Point Positioning, Post Processing Kinematic, Session method, a

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Publication Date
Tue Dec 25 2018
Journal Name
Summaries Of Working Papers, Research And Experiments
E-learning at the College of Mass Communication, subject: public relations campaigns as a model
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Publication Date
Fri Feb 21 2025
Journal Name
Applied System Innovation
Utilizing Soft Computing Techniques to Estimate the Axial Permanent Deformation of Asphalt Concrete
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Rutting is a crucial concern impacting asphalt concrete pavements’ stability and long-term performance, negatively affecting vehicle drivers’ comfort and safety. This research aims to evaluate the permanent deformation of pavement under different traffic and environmental conditions using an Artificial Neural Network (ANN) prediction model. The model was built based on the outcomes of an experimental uniaxial repeated loading test of 306 cylindrical specimens. Twelve independent variables representing the materials’ properties, mix design parameters, loading settings, and environmental conditions were implemented in the model, resulting in a total of 3214 data points. The network accomplished high prediction accuracy with an R

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Publication Date
Thu Feb 19 2026
Journal Name
Journal Mustansiriyah Of Sports Science
The Impact of an Educational Curriculum according to the Five-year Learning Cycle on Some Offensive Skills in Basketball for Female Students
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Modern trends have appeared recently in educational thought that call for the achievement of the outcomes of the educational process. Some of these trends are the development of individual thinking skills, considering the individual differences, and learning basic skills. The five-year learning cycle is one of these models. It is called as five-year learning cycle because it passes through five stages. These five stages are: (operate - discover - clarify - expand – Evaluate), which make the learner as the main axis for activating thinking processes. This can be done by organizing study materials through research, investigation, and identifying concepts by himself, as in learning sports skills that depend on motor performance and teamwork,

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Human Pose Estimation Algorithm Using Optimized Symmetric Spatial Transformation Network
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Human posture estimation is a crucial topic in the computer vision field and has become a hotspot for research in many human behaviors related work. Human pose estimation can be understood as the human key point recognition and connection problem. The paper presents an optimized symmetric spatial transformation network designed to connect with single-person pose estimation network to propose high-quality human target frames from inaccurate human bounding boxes, and introduces parametric pose non-maximal suppression to eliminate redundant pose estimation, and applies an elimination rule to eliminate similar pose to obtain unique human pose estimation results. The exploratory outcomes demonstrate the way that the proposed technique can pre

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Publication Date
Tue Dec 31 2019
Journal Name
Journal Of Economics And Administrative Sciences
The Impact of Emotional Intelligence on Employee Performance in Saudi Arabia Banking Sector
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Saudi Arabia’s banking sector plays an important role in the country’s development as it is among the leading sectors in the financial sector. Considering, two main Saudi banks (The National Commercial Bank and Saudi American bank), the present study aims to observe the impact of emotional intelligence on employee performance. The components of emotional intelligence affecting employee performance include self-management, relationship management, self-awareness, and social awareness. A quantitative methodology was applied to analyse the survey results of 300 respondents over the period from 2018 to 2019. The results show that there was a significant positive impact of self-management, self-awareness, and relationship manageme

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