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Detection of Suicidal Ideation on Twitter using Machine Learning & Ensemble Approaches
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Suicidal ideation is one of the most severe mental health issues faced by people all over the world. There are various risk factors involved that can lead to suicide. The most common & critical risk factors among them are depression, anxiety, social isolation and hopelessness. Early detection of these risk factors can help in preventing or reducing the number of suicides. Online social networking platforms like Twitter, Redditt and Facebook are becoming a new way for the people to express themselves freely without worrying about social stigma. This paper presents a methodology and experimentation using social media as a tool to analyse the suicidal ideation in a better way, thus helping in preventing the chances of being the victim of this unfortunate mental disorder. The data is collected from Twitter, one of the popular Social Networking Sites (SNS). The Tweets are then pre-processed and annotated manually. Finally, various machine learning and ensemble methods are used to automatically distinguish Suicidal and Non-Suicidal tweets. This experimental study will help the researchers to know and understand how SNS are used by the people to express their distress related feelings and emotions. The study further confirmed that it is possible to analyse and differentiate these tweets using human coding and then replicate the accuracy by machine classification. However, the power of prediction for detecting genuine suicidality is not confirmed yet, and this study does not directly communicate and intervene the people having suicidal behaviour.

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Publication Date
Wed May 09 2018
Journal Name
International Journal Of Advanced Computer Science And Applications
New Techniques to Enhance Data Deduplication using Content based-TTTD Chunking Algorithm
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Publication Date
Sun Jan 01 2023
Journal Name
Organization, Technology And Management In Construction: An International Journal
Using the ordinal priority approach for selecting the contractor in construction projects
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Abstract<p>Effective decision-making process is the basis for successfully solving any engineering problem. Many decisions taken in the construction projects differ in their nature due to the complex nature of the construction projects. One of the most crucial decisions that might result in numerous issues over the course of a construction project is the selection of the contractor. This study aims to use the ordinal priority approach (OPA) for the contractor selection process in the construction industry. The proposed model involves two computer programs; the first of these will be used to evaluate the decision-makers/experts in the construction projects, while the second will be used to formul</p> ... Show More
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Publication Date
Mon Sep 23 2019
Journal Name
Baghdad Science Journal
Hazard Rate Estimation Using Varying Kernel Function for Censored Data Type I
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     In this research, several estimators concerning the estimation are introduced. These estimators are closely related to the hazard function by using one of the nonparametric methods namely the kernel function for censored data type with varying bandwidth and kernel boundary. Two types of bandwidth are used:  local bandwidth and global bandwidth. Moreover, four types of boundary kernel are used namely: Rectangle, Epanechnikov, Biquadratic and Triquadratic and the proposed function was employed with all kernel functions. Two different simulation techniques are also used for two experiments to compare these estimators. In most of the cases, the results have proved that the local bandwidth is the best for all the

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Publication Date
Thu Jun 01 2023
Journal Name
Journal Of Engineering
Proposing a General Formula for Evaluating the Parametric Cost Using MLR Method
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This research takes up address the practical side by taking case studies for construction projects that include the various Iraqi governorates, as it includes conducting a field survey to identify the impact of parametric costs on construction projects and compare them with what was reached during the analysis and the extent of their validity and accuracy, as well as adopting the approach of personal interviews to know the reality of the state of construction projects. The results showed, after comparing field data and its measurement in construction projects for the sectors (public and private), the correlation between the expected and actual cost change was (97.8%), and this means that the data can be adopted in the re

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Publication Date
Wed Mar 05 2025
Journal Name
Lecture Notes In Networks And Systems
Using Artificial Intelligence to Enhance Family Cohesion and Promote Positive Social Values
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Publication Date
Sun Jun 07 2015
Journal Name
Baghdad Science Journal
Optimum conditions for Inulinase production by Aspergillus niger using solid state fermentation
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Thirty local fungal isolates according to Aspergillus niger were screened for Inulinase production on synthetic solid medium depending on inulin hydrolysis appear as clear zone around fungal colony. Semi-quantitative screening was performed to select the most efficient isolate for inulinase production. the most efficient isolate was AN20. The optimum condition for enzyme production from A. niger isolate was determined by busing a medium composed of sugar cane moisten with corn steep liquor 5;5 (v/w) at initial pH 5.0 for 96 hours at 30 0C . Enzyme productivity was tested for each of the yeast Kluyveromyces marxianus, the fungus A. niger AN20 and for a mixed culture of A. niger and K. marxianus. The productivity of A. niger gave the highest

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Publication Date
Wed Jan 15 2003
Journal Name
كلية الترا ث الجامعة
Estimating an Exponentiated Expanded Power Function Distribution Using an Artificial Intelligence Algorithm
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The distribution of the expanded exponentiated power function EEPF with four parameters, was presented by the exponentiated expanded method using the expanded distribution of the power function, This method is characterized by obtaining a new distribution belonging to the exponential family, as we obtained the survival rate and failure rate function for this distribution, Some mathematical properties were found, then we used the developed least squares method to estimate the parameters using the genetic algorithm, and a Monte Carlo simulation study was conducted to evaluate the performance of estimations of possibility using the Genetic algorithm GA.

Publication Date
Sat Mar 07 2026
Journal Name
Academic Science Journal
Estimation Monthly Mean, Temperature using Correlation Formula in different provinces in Iraq
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Publication Date
Thu May 28 2015
Journal Name
International Journal Of Recent Scientific Research
HYBRID MACHINES PET/CT SCANNERS BY USING 18F, 82SR AND 68GE RADIONUCLIDE
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The increased use of hybrid PET /CT scanners combining detailed anatomical information along withfunctional data has benefits for both diagnostic and therapeutic purposes. This presented study is to makecomparison of cross sections to produce 18F , 82Sr and68Ge via different reactions with particle incident energy up to 60 MeV as a part of systematic studies on particle-induced activations on enriched natNe, natRb, natGa 18O,85Rb, and 69Ga targets, theoretical calculation of production yield, calculation of requiredtarget and suggestion of optimum reaction to produce: Fluorine-18 , Strontium-82 andGermanium-68 touse in Hybrid Machines PET/CT Scanners.

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Publication Date
Thu Oct 30 2025
Journal Name
Ieee Access
Optic Flow Estimation for Human Spine Movements Using a Motion Capture System
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Human interaction technology based on motion capture (MoCap) systems is a vital tool for human kinematics analysis, with applications in clinical settings, animations, and video games. We introduce a new method for analyzing and estimating dorsal spine movement using a MoCap system. The captured data by the MoCap system are processed and analyzed to estimate the motion kinematics of three primary regions; the shoulders, spine, and hips. This work contributes a non-invasive and anatomically guided framework that enables region-specific analysis of spinal motion which could be used as a clinical alternative to invasive measurement techniques. The hierarchy of our model consists of five main levels; motion capture system settings, marker data

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