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.
This article describes how to predict different types of multiple reflections in pre-track seismic data. The characteristics of multiple reflections can be expressed as a combination of the characteristics of primary reflections. Multiple velocities always come in lower magnitude than the primaries, this is the base for separating them during Normal Move Out correction. The muting procedure is applied in Time-Velocity analysis domain. Semblance plot is used to diagnose multiples availability and judgment for muting dimensions. This processing procedure is used to eliminate internal multiples from real 2D seismic data from southern Iraq in two stages. The first is conventional Normal Move Out correction and velocity auto picking and
... Show MoreThe research included five sections containing the first section on the introduction o research and its importance and was addressed to the importance of the game of gymnastic and skilled parallel bars effectiveness and the importance of biochemical variables, either the research problem that there is a difference in learning this skill and difficulty in learning may be one of the most important reasons are falling and injury Has a negative impact on the performance and lack of sense of movement of is one of the obstacles in the completion of the skill and the goal of research to design a device that helps in the development of biochemical changes to skill of rear vault dismount with one-half twist on parallel bars in gymnastics . And the n
... Show MoreWith its rapid spread, the coronavirus infection shocked the world and had a huge effect on billions of peoples' lives. The problem is to find a safe method to diagnose the infections with fewer casualties. It has been shown that X-Ray images are an important method for the identification, quantification, and monitoring of diseases. Deep learning algorithms can be utilized to help analyze potentially huge numbers of X-Ray examinations. This research conducted a retrospective multi-test analysis system to detect suspicious COVID-19 performance, and use of chest X-Ray features to assess the progress of the illness in each patient, resulting in a "corona score." where the results were satisfactory compared to the benchmarked techniques. T
... Show MoreEnvironmental Tax is deemed as one of the most important tools that can be used to eliminate the problem of oil –based environment pollution resulted out of oil products processes and this has been significantly approved by the experience in those leading countries in the field of protecting the environment against pollution whereas oil-producing countries which are rather awkward in maintaining the environment such as Iraq , suffer from notorious environmental effects pertaining to oil product processes.
The problem of the research is represented the increased and constant rise in the volume of the environmental pollutants resulted from the processes managed by the intern
... Show MoreAbstract: The increased interest in developing new photonic devices that can support high data rates, high sensitivity and fast processing capabilities for all optical communications, motivates a pre stage pulse compressor research. The pre-stage research was based on cascading single mode fiber and polarization maintaining fiber to get pulse compression with compression factor of 1.105. The demand for obtaining more précised photonic devices; this work experimentally studied the behavior of Polarization maintaining fiber PMF that is sandwiched between two cascaded singe mode fiber SMF and fiber Bragg gratings FBG. Therefore; the introduced interferometer performed hybrid interference of both Mach-Zehnder
... Show MoreOffline handwritten signature is a type of behavioral biometric-based on an image. Its problem is the accuracy of the verification because once an individual signs, he/she seldom signs the same signature. This is referred to as intra-user variability. This research aims to improve the recognition accuracy of the offline signature. The proposed method is presented by using both signature length normalization and histogram orientation gradient (HOG) for the reason of accuracy improving. In terms of verification, a deep-learning technique using a convolution neural network (CNN) is exploited for building the reference model for a future prediction. Experiments are conducted by utilizing 4,000 genuine as well as 2,000 skilled forged signatu
... Show MoreIn recent years, social media has been increasing widely and obviously as a media for users expressing their emotions and feelings through thousands of posts and comments related to tourism companies. As a consequence, it became difficult for tourists to read all the comments to determine whether these opinions are positive or negative to assess the success of a tourism company. In this paper, a modest model is proposed to assess e-tourism companies using Iraqi dialect reviews collected from Facebook. The reviews are analyzed using text mining techniques for sentiment classification. The generated sentiment words are classified into positive, negative and neutral comments by utilizing Rough Set Theory, Naïve Bayes and K-Nearest Neighbor
... Show More