scholarly journals Real Time Cyberbullying Detection

2019 ◽  
Vol 9 (2) ◽  
pp. 5197-5201
Keyword(s):  
Social Networking ◽  
Detection System ◽  
Research Work ◽  
Real Life ◽  
Threshold Value ◽  
Cyber Bullying ◽  
Good Time ◽  
Online Harassment ◽  
Online Platforms ◽  
Cyberbullying Detection

Automated approaches for detecting cyberbullying on online platforms has remained a primary research concern over past years. Cyber bullying is defined as the use of electronic communication to bully a person, typically by sending messages of intimidating or threatening nature. The victims especially teenagers suffer from loss of confidence, depression, sleep disorder. The research on automated cyberbullying approach is mainly focused on data driven methods. Such methods work on a database of static texts, usually collected from online platforms and are not feasible for dynamic nature of a real-life social networking scenarios. The aim of our research is to develop a cyberbullying detection system using Fuzzy Logic. Three types of bullying emotions are considered in this research work namely aggression, abuse and threat. In the proposed approach chat between two users is continuously monitored and emotion present in each message is determined. Based on the emotion each user’s behavior is categorized as decent or bullying. If the detected bullying nature is higher than a defined threshold value the account of user is ceased and reported automatically. The proposed approach is tested with a chat application developed in Microsoft .Net Framework and approach can detect cyber bullying in good time. The proposed approach, if implemented with social networking platforms can serve as a useful aid for preventing online harassment. The developed algorithm can also be applied in surveillance and human behavioral analysis.

scholarly journals A Crowdsourcing Based Framework for Sentiment Analysis

2020 ◽  
Vol 16 (4) ◽  
pp. 285-295
Author(s):  
Fatima Zohra Ennaji ◽  
Abdelaziz El Fazziki ◽  
Hasna El Alaoui El Abdallaoui ◽  
Hamada El Kabtane
Keyword(s):  
Social Media ◽  
Social Networking ◽  
Sentiment Analysis ◽  
Real Life ◽  
Data Sources ◽  
Valuable Data ◽  
Analysis Process ◽  
Validity Check ◽  
Online Platforms ◽  
Majority Consensus

As social networking has spread, people started sharing their personal opinions and thoughts widely via these online platforms. The resulting vast valuable data represent a rich source for companies to deduct their products’ reputation from both social media and crowds’ judgments. To exploit this wealth of data, a framework was proposed to collect opinions and rating scores respectively from social media and crowdsourcing platform to perform sentiment analysis, provide insights about a product and give consumers’ tendencies. During the analysis process, a consumer category (strict) is excluded from the process of reaching a majority consensus. To overcome this, a fuzzy clustering is used to compute consumers’ credibility. The key novelty of our approach is the new layer of validity check using a crowdsourcing component that ensures that the results obtained from social media are supported by opinions extracted directly from real-life consumers. Finally, experiments are carried out to validate this model (Twitter and Facebook were used as data sources). The obtained results show that this approach is more efficient and accurate than existing solutions thanks to our two-layer validity check design.

scholarly journals Cyberbullying Detection Modelling at Twitter Social Networking

2018 ◽  
Vol 6 (2) ◽  
pp. 113 ◽  
Author(s):  
Ika Yunida Anggraini ◽  
Sucipto Sucipto ◽  
Rini Indriati
Keyword(s):  
Standard Deviation ◽  
Social Networking ◽  
Social Networking Sites ◽  
Cross Validation ◽  
Confusion Matrix ◽  
Cyber Bullying ◽  
Bayes Classifier ◽  
Validation Process ◽  
Cyberbullying Detection ◽  
Fold Cross Validation

Cybercrimes often happened in social networking sites. Cyber-bullying is a form of cybercrime that recently trended in one of popular social networking sites, Twitter. The practice of cyber-bullying on teenager can cause depression, murderer or suicidal thoughts and it needs a preventing action so it will not harmful to the victim. To prevent cyber-bullying a text mining modelling can be done to classify tweets on Twitter into two classes, bullying class and not bullying class. On this research we use Naïve Bayes Classifier with five stages of pre-processing : replace tokens, transform case, tokenization, filter stopwords and n-grams. The validation process on this research used 10-Fold Cross Validation. To evaluate the performance of the model a Confusion Matrix table is used. The model on 10-Fold Cross Validation phase works well with 77,88% of precision , 94,75% of recall and 82,50% of accuracy with +/-5,12%  of standard deviation.

scholarly journals Decision Tree: A Machine Learning for Intrusion Detection

2019 ◽  
Vol 8 (6S4) ◽  
pp. 1126-1130
Keyword(s):  
Machine Learning ◽  
Intrusion Detection ◽  
Detection System ◽  
Research Work ◽  
Machine Learning Techniques ◽  
Data Sets ◽  
Legitimate User ◽  
Learning Techniques ◽  
Three Stages

The Intrusion is a major threat to unauthorized data or legal network using the legitimate user identity or any of the back doors and vulnerabilities in the network. IDS mechanisms are developed to detect the intrusions at various levels. The objective of the research work is to improve the Intrusion Detection System performance by applying machine learning techniques based on decision trees for detection and classification of attacks. The methodology adapted will process the datasets in three stages. The experimentation is conducted on KDDCUP99 data sets based on number of features. The Bayesian three modes are analyzed for different sized data sets based upon total number of attacks. The time consumed by the classifier to build the model is analyzed and the accuracy is done.

scholarly journals Research on critical groundwater level under the threshold value of land subsidence in the typical region of Beijing

2015 ◽  
Vol 372 ◽  
pp. 507-510
Author(s):  
Y. Jiang ◽  
J.-R. Liu ◽  
Y. Luo ◽  
Y. Yang ◽  
F. Tian ◽  
...  
Keyword(s):  
Water Level ◽  
Water Table ◽  
Land Subsidence ◽  
Groundwater Level ◽  
Threshold Value ◽  
Scientific Basis ◽  
Good Time ◽  
Linear Regression Models ◽  
Control Plan ◽  
Time Space

Abstract. Groundwater in Beijing has been excessively exploited in a long time, causing the groundwater level continued to declining and land subsidence areas expanding, which restrained the economic and social sustainable development. Long years of study show good time-space corresponding relationship between groundwater level and land subsidence. To providing scientific basis for the following land subsidence prevention and treatment, quantitative research between groundwater level and settlement is necessary. Multi-linear regression models are set up by long series factual monitoring data about layered water table and settlement in the Tianzhu monitoring station. The results show that: layered settlement is closely related to water table, water level variation and amplitude, especially the water table. Finally, according to the threshold value in the land subsidence prevention and control plan of China (45, 30, 25 mm), the minimum allowable layered water level in this region while settlement achieving the threshold value is calculated between −18.448 and −10.082 m. The results provide a reasonable and operable control target of groundwater level for rational adjustment of groundwater exploited horizon in the future.

scholarly journals Design of a Wearable Eye-Movement Detection System Based on Electrooculography Signals and Its Experimental Validation

Biosensors ◽  
2021 ◽  
Vol 11 (9) ◽  
pp. 343
Author(s):  
Chin-Teng Lin ◽  
Wei-Ling Jiang ◽  
Sheng-Fu Chen ◽  
Kuan-Chih Huang ◽  
Lun-De Liao
Keyword(s):  
Eye Movement ◽  
Experimental Validation ◽  
Hardware Implementation ◽  
Detection System ◽  
Real Life ◽  
People With Disabilities ◽  
Research Area ◽  
General Purpose ◽  
Classification Algorithm ◽  
Human Computer Interface

In the assistive research area, human–computer interface (HCI) technology is used to help people with disabilities by conveying their intentions and thoughts to the outside world. Many HCI systems based on eye movement have been proposed to assist people with disabilities. However, due to the complexity of the necessary algorithms and the difficulty of hardware implementation, there are few general-purpose designs that consider practicality and stability in real life. Therefore, to solve these limitations and problems, an HCI system based on electrooculography (EOG) is proposed in this study. The proposed classification algorithm provides eye-state detection, including the fixation, saccade, and blinking states. Moreover, this algorithm can distinguish among ten kinds of saccade movements (i.e., up, down, left, right, farther left, farther right, up-left, down-left, up-right, and down-right). In addition, we developed an HCI system based on an eye-movement classification algorithm. This system provides an eye-dialing interface that can be used to improve the lives of people with disabilities. The results illustrate the good performance of the proposed classification algorithm. Moreover, the EOG-based system, which can detect ten different eye-movement features, can be utilized in real-life applications.

scholarly journals Effective Intrusion Detection System by using LOS Classifier

2019 ◽  
Vol 9 (2) ◽  
pp. 2961-2966
Keyword(s):  
Machine Learning ◽  
Cloud Computing ◽  
Intrusion Detection ◽  
Social Networking ◽  
Intrusion Detection System ◽  
Detection System ◽  
Learning Approaches ◽  
Area Unit ◽  
Hybrid Development

With winning advances like catch of Things, Cloud Computing and Social Networking, mammoth proportions of framework traffic associated information area unit made Intrusion Detection System for sort out security suggests the strategy to look at partner unapproved access on framework traffic. For Intrusion Detection System we are going to call attention to with respect to Machine Learning Approaches. it's accomplice rising field of enrolling which can explicitly act with a decent arrangement of less human affiliation. System gains from the data intentionally affirmation and makes perfect objectives. all through this paper we keep an eye on zone unit going to separated styles of Machine Learning pulls in near and had done relative examination in it. inside the last we keep an eye on territory unit going to foreseen the idea of hybrid development, that might be a blend of host principally and framework based for the most part Intrusion Detection System.

scholarly journals The Employment of Metaphor and Simile in Selected Siswati Poetry

2019 ◽  
Vol 15 (5) ◽  
pp. 181
Author(s):  
Jozi Joseph Thwala
Keyword(s):  
Literary Criticism ◽  
Textual Analysis ◽  
Language Skills ◽  
Research Work ◽  
Real Life ◽  
Connotative Meaning ◽  
Figures Of Speech ◽  
Poetic Diction ◽  
The Senses ◽  
The Mind

The focus of this research work on selected descriptive of images refers to the analytic survey of metaphor and simile. They are selected, defined, explained and interpreted. Their significances in bringing about poetic diction, licence, meaning, message and themes are highlighted. They are fundamental figures of speech that implicitly and explicitly display the emotive value, connotative meaning, literariness and language skills. The poetic images reflect and represent real life situations through poetic skills and meanings. The literary criticism, comparative and textual analysis is evident when the objects are looked at from animate to inanimate and inanimate to animate. They serve as basic methodologies that are backing the theories and strategies on selected figures of speech. Imagery is the use of words that brings picture of the mind of the receiver or recipient and appeal to the senses. It is, however, manifested in various forms for resemblances, contrasts and comparisons. Artistic language through images revealed poetic views, assertion and facts.

scholarly journals A Graph Mining Approach for Ranking and Discovering the Interesting Frequent Subgraph Patterns

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Saif Ur Rehman ◽  
Kexing Liu ◽  
Tariq Ali ◽  
Asif Nawaz ◽  
Simon James Fong
Keyword(s):  
Graph Mining ◽  
A Priori ◽  
Research Work ◽  
User Involvement ◽  
Threshold Value ◽  
Research Field ◽  
Frequent Subgraph Mining ◽  
Graph Data ◽  
Frequent Subgraph ◽  
Pattern Growth

AbstractGraph mining is a well-established research field, and lately it has drawn in considerable research communities. It allows to process, analyze, and discover significant knowledge from graph data. In graph mining, one of the most challenging tasks is frequent subgraph mining (FSM). FSM consists of applying the data mining algorithms to extract interesting, unexpected, and useful graph patterns from the graphs. FSM has been applied to many domains, such as graphical data management and knowledge discovery, social network analysis, bioinformatics, and security. In this context, a large number of techniques have been suggested to deal with the graph data. These techniques can be classed into two primary categories: (i) a priori-based FSM approaches and (ii) pattern growth-based FSM approaches. In both of these categories, an extensive research work is available. However, FSM approaches are facing some challenges, including enormous numbers of frequent subgraph patterns (FSPs); no suitable mechanism for applying ranking at the appropriate level during the discovery process of the FSPs; extraction of repetitive and duplicate FSPs; user involvement in supplying the support threshold value; large number of subgraph candidate generation. Thus, the aim of this research is to make do with the challenges of enormous FSPs, avoid duplicate discovery of FSPs, and use the ranking for such patterns. Therefore, to address these challenges a new FSM framework A RAnked Frequent pattern-growth Framework (A-RAFF) is suggested. Consequently, A-RAFF provides an efficacious answer to these challenges through the initiation of a new ranking measure called FSP-Rank. The proposed ranking measure FSP-Rank effectively reduced the duplicate and enormous frequent patterns. The effectiveness of the techniques proposed in this study is validated by extensive experimental analysis using different benchmark and synthetic graph datasets. Our experiments have consistently demonstrated the promising empirical results, thus confirming the superiority and practical feasibility of the proposed FSM framework.

scholarly journals Survey on queueing models with standbys support

2018 ◽  
Vol 28 (1) ◽  
pp. 3-20 ◽  
Author(s):  
Sreekanth Kolledath ◽  
Kamlesh Kumar ◽  
Sarita Pippal
Keyword(s):  
Research Work ◽  
Real Life ◽  
Real System ◽  
Queueing Models ◽  
Valuable Insight ◽  
Present Survey ◽  
Survey Article ◽  
Work Done ◽  
Interesting Area ◽  
Modelling System

This paper is a survey article on queueing models with standbys support. Due to many real life applications of queueing models, it has become an interesting area for researchers and a lot of research work has been exerted so far. It is worthwhile to examine the performance based analysis for queueing modelling system as it provides a valuable insight to the tractability of the system and accelerates its efficiency. The provision of standbys to the queueing modelling of a real system is needed for smooth functioning in the presence of its unavoidable failures. The present survey provides a dig into the research work done, and emphasis the sequential developments on queueing models with standbys support.

scholarly journals HOW TO OBTAIN A GLOBAL REFERENCE THRESHOLD IN AHP/ANP

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Claudio Garuti
Keyword(s):  
Real Life ◽  
Absolute Measurement ◽  
Threshold Value ◽  
Rate Of Change ◽  
Current Status ◽  
Medical Diagnoses ◽  
Specific Objective ◽  
Global Threshold ◽  
Disaster Assessment ◽  
The Difference

This paper has two main objectives. The first objective is to provide a mathematically grounded technique to construct local and global thresholds using the well-known rate of change method. The next objective, which is secondary, is to show the relevance and possibilities of applying the AHP/ANP in absolute measurement (AM) compared to the relative measurement (RM) mode, which is currently widely used in the AHP/ANP community. The ability to construct a global threshold would help increase the use of AHP/ANP in the AM mode (rating mode) in the AHP/ANP community. Therefore, if the first specific objective is achieved, it would facilitate reaching the second, more general objective.   For this purpose, a real-life example based on the construction of a multi-criteria index and threshold will be described. The index measures the degree of lag of a neighborhood through the Urban and Social Deterioration Index (USDI) based on an AHP risks model. The global threshold represents the tolerable lag value for the specific neighborhood. The difference or gap between the neighborhood’s current status (actual USDI value) and this threshold represents the level of neighborhood deterioration that must be addressed to close the gap from a social and urban standpoint. The global threshold value is a composition of 45 terminal criteria with their own local threshold that must be evaluated for the specific neighborhood. This example is the most recent in a large list of AHP applications in AM mode in vastly different decision making fields, such as risk disaster assessment, environmental assessment, the problem of medical diagnoses, social responsibility problems, BOCR analysis for the evolution of nuclear energy in Chile in the next 20 years and many others. (See list of projects in Appendix).

Sign in / Sign up

Export Citation Format

Share Document