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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
Mon Dec 20 2021
Journal Name
Baghdad Science Journal
Performance Analysis on Multiple Device Connections of Small Office Home Office Network
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Malaysia has been supported by one of the high-speed fiber internet connections called TM UniFi. TM UniFi is very familiar to be used as a medium to apply Small Office Home Office (SOHO) concept due to the COVID-19 pandemic. Most of the communication vendors offer varieties of network services to fulfill customers' needs and satisfaction during the pandemic. Quality of Services is queried by most users by the fact of increased on users from time to time. Therefore, it is crucial to know the network performance contrary to the number of devices connected to the TM UniFi network. The main objective of this research is to analyze TM UniFi performance with the impact of multiple device connections or users' services. The study was conducted

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Publication Date
Mon Mar 11 2019
Journal Name
Baghdad Science Journal
Results on a Pre-T_2 Space and Pre-Stability
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This paper contains an equivalent statements of a pre-  space, where  are considered subsets of with the product topology. An equivalence relation between the preclosed set  and a pre-  space, and a relation between a pre-  space and the preclosed set  with some conditions on a function  are found. In addition, we have proved that the graph  of  is preclosed in if  is a pre-  space, where the equivalence relation  on  is open.

     On the other hand, we introduce the definition of a pre-stable ( pre-stable) set by depending on the concept of a pre-neighborhood, where we get that every stable set is pre-stable. Moreover, we obtain that

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Publication Date
Thu Dec 13 2018
Journal Name
Iraqi National Journal Of Nursing Specialties
The Effect of Toxoplasma Gondii on DNA SequenceAlteration among BreastCancer Patients
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Objective: The study aims to determine the effect of Toxoplasma gondii infection on the
genetic sequence of breast cancer patients in the Medical City Hospital – Tumor Unit /
Iraq-Baghdad.
Methodology: A study was carried out in the City of Medicine / Oncology Unit / Baghdad,
during the period 1st June 2016 to 15
th March 2017. Forty samples of tissue and serum
were collected from patients who complaining from Breast cancer and infected with
Toxoplasmosis. Forty sera samples were taken from patients complaining from parasitic
infection only; without breast cancer as control group. Data is analyzed by using of
descriptive and inferential data analysis methods.
Results: The results show that there is an effe

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Publication Date
Tue Dec 20 2022
Journal Name
2022 4th International Conference On Current Research In Engineering And Science Applications (iccresa)
Noise Detection and Removing in Heart Sound Signals via Nuclear Norm Minimization Problems
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Heart sound is an electric signal affected by some factors during the signal's recording process, which adds unwanted information to the signal. Recently, many studies have been interested in noise removal and signal recovery problems. The first step in signal processing is noise removal; many filters are used and proposed for treating this problem. Here, the Hankel matrix is implemented from a given signal and tries to clean the signal by overcoming unwanted information from the Hankel matrix. The first step is detecting unwanted information by defining a binary operator. This operator is defined under some threshold. The unwanted information replaces by zero, and the wanted information keeping in the estimated matrix. The resulting matrix

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Publication Date
Sun Nov 01 2020
Journal Name
2020 2nd Annual International Conference On Information And Sciences (aicis)
An Enhanced Multi-Objective Evolutionary Algorithm with Decomposition for Signed Community Detection Problem
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Publication Date
Fri Aug 12 2022
Journal Name
Future Internet
Improved DDoS Detection Utilizing Deep Neural Networks and Feedforward Neural Networks as Autoencoder
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Software-defined networking (SDN) is an innovative network paradigm, offering substantial control of network operation through a network’s architecture. SDN is an ideal platform for implementing projects involving distributed applications, security solutions, and decentralized network administration in a multitenant data center environment due to its programmability. As its usage rapidly expands, network security threats are becoming more frequent, leading SDN security to be of significant concern. Machine-learning (ML) techniques for intrusion detection of DDoS attacks in SDN networks utilize standard datasets and fail to cover all classification aspects, resulting in under-coverage of attack diversity. This paper proposes a hybr

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Publication Date
Sun Apr 30 2023
Journal Name
Iraqi Journal Of Science
An Evolutionary Algorithm with Gene Ontology-Aware Crossover Operator for Protein Complex Detection
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     Evolutionary algorithms (EAs), as global search methods, are proved to be more robust than their counterpart local heuristics for detecting protein complexes in protein-protein interaction (PPI) networks. Typically, the source of robustness of these EAs comes from their components and parameters. These components are solution representation, selection, crossover, and mutation. Unfortunately, almost all EA based complex detection methods suggested in the literature were designed with only canonical or traditional components. Further, topological structure of the protein network is the main information that is used in the design of almost all such components. The main contribution of this paper is to formulate a more robust E

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Publication Date
Sun Jun 30 2024
Journal Name
International Journal Of Intelligent Engineering And Systems
Eco-friendly and Secure Data Center to Detection Compromised Devices Utilizing Swarm Approach
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Modern civilization increasingly relies on sustainable and eco-friendly data centers as the core hubs of intelligent computing. However, these data centers, while vital, also face heightened vulnerability to hacking due to their role as the convergence points of numerous network connection nodes. Recognizing and addressing this vulnerability, particularly within the confines of green data centers, is a pressing concern. This paper proposes a novel approach to mitigate this threat by leveraging swarm intelligence techniques to detect prospective and hidden compromised devices within the data center environment. The core objective is to ensure sustainable intelligent computing through a colony strategy. The research primarily focusses on the

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Publication Date
Mon Mar 15 2021
Journal Name
Al-academy
Effect of formation Methods on Sintering Process of Ceramic Materials: هديل سلمان سعيد
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The current research is concerned with methods of formation and their effect on the sintering process of ceramic materials. The research is divided into a number of chapters. The first chapter addressed the research structure (the research problem, importance, objective, limits, and it also defined the terms used in the research). The second chapter addressed the theoretical framework, where the theoretical framework has been divided into three sections. The first section dealt with methods of formation of ceramic materials including: Plasticizing method 2- semi-dry pressing method 3- dry pressing method 4- extrusion method 5- casting method.
The researcher found that there is a clear difference between the methods through her formati

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Publication Date
Tue Oct 08 2002
Journal Name
Iraqi Journal Of Laser
Effect of Gas Mixture on the Output Characteristics of a CW CO2 Laser
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In this work, the effect of partial amounts of gases in gas mixture of a CW CO2 laser on the output power was investigated. Also their effect on the condition determining the glow-discharge self-sustaining required for pumping the active medium was studied. Two fit relations were derived to predict the output laser power and the electric field to unit pressure ratio as functions to the partial amounts of gases. Results presented in this work could be used fruitfully to determine some of the optimum operational conditions of glow-discharge low-power CW CO2 lasers.

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