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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
Tue Apr 30 2024
Journal Name
Iraqi Journal Of Science
Credit Card Fraud Detection Challenges and Solutions: A Review
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     Credit card fraud has become an increasing problem due to the growing reliance on electronic payment systems and technological advances that have improved fraud techniques. Numerous financial institutions are looking for the best ways to leverage technological advancements to provide better services to their end users, and researchers used various protection methods to provide security and privacy for credit cards. Therefore, it is necessary to identify the challenges and the proposed solutions to address them.  This review provides an overview of the most recent research on the detection of fraudulent credit card transactions to protect those transactions from tampering or improper use, which includes imbalance classes, c

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Publication Date
Fri Feb 21 2025
Journal Name
2025 First International Conference On Advances In Computer Science, Electrical, Electronics, And Communication Technologies (ce2ct)
Enhancing Cloud Security Implementing AI-Based Intrusion Detection Systems
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The increasing complexity of assaults necessitates the use of innovative intrusion detection systems (IDS) to safeguard critical assets and data. There is a higher risk of cyberattacks like data breaches and unauthorised access since cloud services have been used more frequently. The project's goal is to find out how Artificial Intelligence (AI) could enhance the IDS's ability to identify and classify network traffic and identify anomalous activities. Online dangers could be identified with IDS. An intrusion detection system, or IDS, is required to keep networks secure. We must create efficient IDS for the cloud platform as well, since it is constantly growing and permeating more aspects of our daily life. However, using standard intrusion

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Publication Date
Sun Oct 15 2023
Journal Name
Journal Of Yarmouk
Artificial Intelligence Techniques for Colon Cancer Detection: A Review
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Publication Date
Thu Dec 01 2022
Journal Name
Journal Of Engineering
Deep Learning-Based Segmentation and Classification Techniques for Brain Tumor MRI: A Review
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Early detection of brain tumors is critical for enhancing treatment options and extending patient survival. Magnetic resonance imaging (MRI) scanning gives more detailed information, such as greater contrast and clarity than any other scanning method. Manually dividing brain tumors from many MRI images collected in clinical practice for cancer diagnosis is a tough and time-consuming task. Tumors and MRI scans of the brain can be discovered using algorithms and machine learning technologies, making the process easier for doctors because MRI images can appear healthy when the person may have a tumor or be malignant. Recently, deep learning techniques based on deep convolutional neural networks have been used to analyze med

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Publication Date
Sun Jan 27 2019
Journal Name
Journal Of The College Of Education For Women
Cyber Crime and its Risks on Children
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Cybercrime and risks to children between the problems and solutions( An analytical study in the light of international, Arab and national statistics).
Lies the problem of the study to identify a new type of crime is different from the same traditional character of the crimes or what was customary since human creation up to the information revolution and we enter the era of globalization, which is also called (cyber crime) and their negative impact on all segments of society, especially children, as they the day of the most important social security threats, for all local and international communities alike , and those risks require collective action to various sectors and segments of society ,especially the educated classes in order t

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Publication Date
Wed Feb 01 2023
Journal Name
Baghdad Science Journal
Sediment Assessment of Al-Hindyia and Al-Abbasyia River / Iraq by aquatic oligocheata community as bioindicators
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             Bioindicators have an important role in assessing the quality of water bodies. Aquatic oligocheates, was used as a bioindicator to assess the sediment quality of Al-Hindyia and AL-Abbasyia river (branches of Euphrates River in Iraq). Two sites in each river have been   chosen for this purpose, site S1 was located at Al-Hindyia River and S2 at Al-Abbasyia River. Some kinds of biological indices were used in this study, comprising the percentage of oligochaetes in benthic invertebrates, ranged from 20.3-60.16%. While the percentage of Tubificidae within benthic invertebrates was close 43.3-43.9%.Index of pollution D ranged from 0.13-0.21. The maximum percentage of aquatic oligochaetes to insects larvae of family

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Publication Date
Wed Jun 07 2023
Journal Name
Journal Of Educational And Psychological Researches
Multiple Intelligence Test Item Selection-Based on Howard Gardner's MI Model Using a Generalized Partial Estimation Model: Ministry of Education \ Karkh First Directorate of Education
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The aim of the research is to examine the multiple intelligence test item selection based on Howard Gardner's MI model using the Generalized Partial Estimation Form, generalized intelligence. The researcher adopted the scale of multiple intelligences by Kardner, it consists of (102) items with eight sub-scales. The sample consisted of (550) students from Baghdad universities, Technology University, al-Mustansiriyah university, and Iraqi University for the academic year (2019/2020). It was verified assumptions theory response to a single (one-dimensional, local autonomy, the curve of individual characteristics, speed factor and application), and analysis of the data according to specimen partial appreciation of the generalized, and limits

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Publication Date
Mon May 27 2019
Journal Name
Al-khwarizmi Engineering Journal
Investigation the Influence of SPIF Parameters on Residual Stresses for Angular Surfaces Based on Iso-Planar Tool Path
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Incremental Sheet Metal Forming (ISMF) is a modern sheet metal forming technology which offers the possibility of manufacturing 3D complex parts of thin sheet metals using the CNC milling machine. The surface quality is a very important aspect in any manufacturing process. Therefore, this study focuses on the resultant residual stresses by forming parameters, namely; (tool shape, step over, feed rate, and slope angle) using Taguchi method for the products formed by single point incremental forming process (SPIF). For evaluating the surface quality, practical experiments to produce pyramid like shape have been implemented on aluminum sheets (AA1050) for thickness (0.9) mm. Three types of tool shape used in this work, the spherical tool ga

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Publication Date
Thu Dec 31 2015
Journal Name
Al-khwarizmi Engineering Journal
Experimental Study on the Effect of Insertion of Copper Lessing Rings in Phase Change Material (PCM) on the Performance of Thermal Energy Storage Unit
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Abstract

One of the most suitable materials to be used in latent heat thermal energy storage system (LHTES) are Phase change materials, but a problem of slow melting and solidification processes made many researchers focusing on how to improve their thermal properties. This experimental work concerned with the enhancing of thermal conductivity of phase change material. The enhancing method was by the addition of copper Lessing rings in phase change material (paraffin wax). The effect of diameter for the used rings was studied by using two different diameters (0.5 cm and 1cm). Also, three volumetric percentages of rings addition (3%, 6% and 10%) were tested for each diameter. The discharging process was done with

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Publication Date
Wed Mar 30 2022
Journal Name
Journal Of Economics And Administrative Sciences
Effects of Water Scarcity on Rural Household Economy
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This study examined the effects of water scarcity on rural household economy in El Fashir Rural Council / North Darfur State- western Sudan. Both quantitative and qualitative methods were used as to get a deeper understanding of the impact of water scarcity on the rural house economy in the study area. 174 households out of 2017 were selected from 45 villages which were distributed in eight village councils forming the study area. Statistical methods were used to manipulate the data of the study. The obtained results revealed that water scarcity negatively affected the rural household economy in the study area in many features. These include the followings: much family efforts and time were directed to fetch for water consequentl

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