Mohammed Mahmood Ali - Academia.edu (original) (raw)

Papers by Mohammed Mahmood Ali

International Journal of Engineering and Advanced Technology

Efficient utilization of social networking sites (SNS) had reduced communication delays, at the s... more Efficient utilization of social networking sites (SNS) had reduced communication delays, at the same time increased rumour messages. Subsequently, mischievous people started sharing of rumours via social networking sites for gaining personal benefits. This falsified information (i.e., rumour) creates misconception among the people of society influencing socio-economic losses by disrupting the routine businesses of private and government sectors. Communication of rumour information requires rigorous surveillance, before they become viral through social media platforms. Detecting these rumour words in an early stage from messaging applications needs to be predicted using robust Rumour Detection Models (RDM) and succinct tools. RDM are effectively used in detecting the rumours from social media platforms (Twitter, Linkedln, Instagram, WhatsApp, Weibo sena and others) with the help of bag of words and machine learning approaches to a limited extent. RDM fails in detecting the emerging r...

2021 International Conference on Data Analytics for Business and Industry (ICDABI), 2021

Teaching strategy using slides through video conference and recorded lectures are uploaded for im... more Teaching strategy using slides through video conference and recorded lectures are uploaded for imparting the knowledge to the learners via various online modes. There are few hurdles to understand a specific topic for learner from the video. The learners needs to put efforts and more time in listening and to reach the exact topic from the recorded lecture twice or thrice or sometimes moving to & fro the clips to understand the exact topic explained in the video for gaining knowledge. To overcome such issues, an attempt is made where the annotated indexing of lecture video to be embedded within the video for non-linear navigation to better understand the concerned topics point-wise. In this paper an algorithm to sequentially partition the lecture video into clusters and annotates the cluster by analyzing the contents of video by organizing the video in structured format which aids for efficient non-linear navigation. To access the performance of video partitioning process, we have chosen seven (7) online lecture videos of tutorials from different courses. Initially, we manually annotated required slides from the lecture videos and indexed it. Then, we used the proposed algorithm for these videos. We compared the results of extracted slides with the proposed approach using Recall and precision metrics. Our method achieved the good results when compared to other methods.

Social phishers continuously adapt the novel trapping techniques of prying usernames and password... more Social phishers continuously adapt the novel trapping techniques of prying usernames and passwords by establishing a friendly relationship through microblog messages using various social networking environments (SNEs) for financial benefits. APWG report of 2018 shows the successive rise in phishing attacks via URLS, fake Web sites, spoofed e-mail links, domain name usage, and social media content (APWG, Anti-Phishing Working Group report [1]). Innumerable defending techniques had been proposed earlier, but are still vulnerable due to exchange of compromised microblogs in SNEs resulting in leaking of confidential information and falling prey to phishers attack. To mitigate the latent fraudulent phishing mechanisms, there is a scope and an immense need to get rid of phishing attacks in SNEs. This paper surveys and analyzes the various social phishing detection and prevention mechanisms that are developed for SNEs.

Psychological Stress and Depression have been pinpointed repeatedly as significant issues contrib... more Psychological Stress and Depression have been pinpointed repeatedly as significant issues contributing to the weakening of physical and mental health. Nowadays stress is considered as the biggest threat to individual’s wellbeing. However stress can be a positive aspect in our daily life, but too much stress can rather be harmful to physical and emotional healthiness where as managing it, is a major concern for populations around the world. Hence, there is significant importance to detect stress in its early stages, before it turns into severe problem. Thus, this work analyses and brings together recent research studies carried for automatic stress detection observing over the dimensions executed along the four main modalities, viz., Psychological, Physiological, Behavioral and Social Media Interaction modalities, along with appropriate measurements, in order to give hints about the most appropriate ways and means to be used for Psychological Stress Detection. Keywords— Psychological...

Biological science is aimed towards improving the quality of human life by interventions in medic... more Biological science is aimed towards improving the quality of human life by interventions in medicine and life sciences. Different branches of biological sciences such as life, health, medicine and embryology have ample amount of information in Quran and Hadiths. The verses of Quran and narrations of Ahadith are scattered over various chapters. There is a need to design a tool which can integrate all this information and differentiate it accordingly for an in depth research. This will be a step towards the understanding of Quran for scientific community as the Quran says "Those who give thought to the creation of the heavens and the earth, [say], Our Lord, You did not create this aimlessly". This is the base to consider that the unidentified concepts in biotechnology must gain understanding from the illustrations of Quran and Prophet's narrations. We have framed an Ontology Knowledge acquisition system between the verses of Quran, narrations of Hadiths and biological co...

2017 International Conference on Energy, Communication, Data Analytics and Soft Computing (ICECDS), 2017

Most of corrupted images due to various degradations involve filtration process, to efficiently m... more Most of corrupted images due to various degradations involve filtration process, to efficiently make use of image scenes in image processing. Particularly, the outdoor image scenes are degraded due to cloudy medium in the atmosphere (i.e., impurities in air). Such as Haziness, mist, and smog are the phenomena of atmospheric absorption that scatter the image scenes. Moreover, many computer vision applications, works on input images, fail to work efficiently because of degraded images. Removing those deficiencies with the use of image haze removal techniques will assist in image comprehension and computer applications (aerial imagery or image classification). This paper surveys the existing de-hazing techniques that aid in filtering the haze from captured images and later replace with the improvised hazy free image(s).

Contactless Healthcare Facilitation and Commodity Delivery Management During COVID 19 Pandemic, 2021

International Journal of Intelligent Systems and Applications in Engineering, 2018

Spreading of Unwanted microblogs from Social Networking Sites (SNS) is pervasive in social media ... more Spreading of Unwanted microblogs from Social Networking Sites (SNS) is pervasive in social media that leads to unaccountable disturbances such as Mental disorders, Wastage of precious time, Break-up of relationships, Stressness giving birth to psychological health problems and many more. To overcome these problems, the immense necessity is to ignore those unwanted microblogs in SNS, which is uncontrollable by humans due to addiction towards social media. Even the literate people fall prey to psychological stress from SNS. This seriousness of stress related issues is very rarely attended by researchers, to tackle such vicious microblogs. The prediction strategy is proposed named as Stress Detection Framework (SDF) to analyze the stress in microblog. SDF is developed using Ontology based Information Extraction technique using Probabilistic Model (GSHL & TreeAlignment Algorithm), set of pre-defined knowledge based logical rules that constitutes of low-level attributes (simple textual, linguistic words) and visual features (emoticons & Images) and social Interaction (Likes and Dislikes) to detect and predict stress in microblog messages.SDF is compared with TeniStrength that has shown an increase of 94.2% of stress detection rate. The experimental results obtained will aid to take precise decision for blocking/eradicating/ segregating stress related microblogs from Social media (especially SNS).

International Journal of Intelligent Systems and Applications in Engineering, 2018

One of the mental threat for individual's health identified is Psychological stress from social m... more One of the mental threat for individual's health identified is Psychological stress from social media data. Hence, necessity is to predict and manage stress before it turns into a serious problem. However, Conventional stress detection methods exist, that rely on psychological scales & physiological devices that need full of victims participation which is time-consuming, complex and expensive. With the trending growth of social networks, people are addicted towards sharing personal moods via social media platforms to influence other users, leading to stressfulness. The developed novel hybrid model Psychological Stress Detection (PSD), automatically detect the victims's psychological stress from social media data. It comprises of three (3) modules Probabilistic Naïve Bayes Classifier, Visual (Hue, Saturation, Value) and Social, to leverage text, image post and social interaction information; we defined set of stress-related textual 'F = {f1, f2, f3, f4}', visual 'vF = {vf1, vf2}', and social features 'sf' to predict stress from social media content. Experimental results show the proposed PSD model improves the detection process when compared to TensiStrength and Teenchat framework, PSD achieves 95% of Precision rate. PSD model will assist in developing stress detection tools for mental health agencies.

International Conference on Pattern Recognition, Informatics and Medical Engineering (PRIME-2012), 2012

Deceptive Phishing is the major problem in Instant Messengers, much of sensitive and personal inf... more Deceptive Phishing is the major problem in Instant Messengers, much of sensitive and personal information, disclosed through socio-engineered text messages for which solution is proposed[2] but, detection of phishing through voice chatting technique in Instant Messengers is not yet done which is the motivating factor to carry out the work and solution to address this problem of privacy in Instant Messengers (IM) is proposed using Association Rule Mining (ARM) technique a Data Mining approach integrated with Speech Recognition system. Words are recognized from speech with the help of FFT spectrum analysis and LPC coefficients methodologies. Online criminal's now-a-days adapted voice chatting technique along with text messages collaboratively or either of them in IM's and wraps out personal information leads to threat and hindrance for privacy. In order to focus on privacy preserving we developed and experimented Anti Phishing Detection system (APD) in IM's to detect deceptive phishing for text and audio collaboratively.

Proceedings of The 2014 International Conference on Control, Instrumentation, Energy and Communication (CIEC), 2014

Lung cancer is the leading cause of cancer-related deaths worldwide. Classification and character... more Lung cancer is the leading cause of cancer-related deaths worldwide. Classification and characterization of cancer treatment strategies are essential in the current medical era. Gene mutations and their altered expressions is the base of cancer development. Analyzing these gene mutations and gene expression data for the phenotypic classification of lung cancer is proposed in this paper. Genomic and proteomic data sets (Biomarkers) of Non-Small Cell Lung Cancer (NSCLC) and its two major subtypes, Squamous Cell Cancer (SCC) and adenocarcinoma (ADC) were analyzed in this study. The biomarkers included in genomic and proteomic data sets are microRNAs, genes and their proteins. An integrated classification decision tree induction algorithm is applied on these biomarkers of NSCLC cancers for making predictions. Knowledge derived by the proposed algorithm has high classification accuracy with the ability to predict the cancer type. Cross-validation technique is applied that further enhances the classification accuracy of J48 algorithm. Thus our contribution includes the construction of decision tree using J48 weka tool for lung cancer subtypes and predict the lung cancer type for unknown class. Secondly we have compared the outputs obtained using J48 algorithm with improved decision tree (J48). Through the construction of decision tree, totally top ten classification rules are obtained using the apriori algorithm (weka tool) for predicting lung cancer. The average correction classification accuracy is nearly 99.7%, but many of the rules which are of user interest are pruned. The classification rules obtained by improved decision tree are dependent on user decision that helps to derive unlimited rules based on selection of attribute values. The improved decision tree has shown a good improvement over J48 algorithm. The findings are considered as helpful reference rules in diagnosis and drug development of SCC and ADC cancers. The accurate differential diagnosis of lung cancer by the knowledge of biomarkers could reduce the pain of histopathological examination of the patients.

2014 International Conference on Computational Science and Computational Intelligence, 2014

In recent years, with the development of digital image techniques and digital albums in the Inter... more In recent years, with the development of digital image techniques and digital albums in the Internet, the use of digital image retrieval process has increased dramatically. An image retrieval system is a computer system for browsing, searching and retrieving images from large databases of digital images. In order to increase the accuracy of image retrieval, a content-based image retrieval system(CBIR) based on interactive genetic algorithm (IGA) is proposed. Color, texture and edge have been the primitive low level image descriptors in content based image retrieval systems. In this paper we proposed a system that splits the retrieval process into two stages. In the query stage, the feature descriptors of a query image were extracted and then used to evaluate the similarity between the query image and those images in the database. In the evolution stage, the most relevant images were retrieved by using the IGA. IGA is employed to help the users identify the images that are most satisfied to the users' need. The experimental evaluation of the system is based on a 10000 WANG color image database. Experimental results demonstrate the feasibility of the proposed approach.

International Journal of Internet Technology and Secured Transactions, 2013

Instant messengers IMs and social networking sites SNS such as Facebook may contain harmful and s... more Instant messengers IMs and social networking sites SNS such as Facebook may contain harmful and suspicious messages, which is of national security concerns. Organised crimes have adopted online chatting technique to send these suspicious messages as these systems have all the facilities and could serve as platform to spread across their information widely through socio-engineered and general text messages. A solution to this problem is to detect suspicious messages from the typed messages. In this paper, we proposed a suspicious message detection system SMDs to detect suspicious messages. SMDs framework makes use of databases where instant messages are stored and an ontology information extraction technique which is able to detect suspicious messages using probabilistic models. The objective of SMDs framework is to trace the identified criminals by browsing their profile details available from their e-mail account, where suspicious messages are discovered during online chat. Experimental analysis is evaluated using the user generated content UGC testbed which consist of suspicious messages for eight different test cases with user-defined threshold value tested using SMDs. The results obtained shows high precision rate compared to the existing state-of-the-art systems.

Scalability and efficiency is the major problem for classification algorithms in data mining, for... more Scalability and efficiency is the major problem for classification algorithms in data mining, for large databases. We have suggested improvements to an existing C4.5 decision tree Algorithm. Particularly, when decision tree induction, used to construct the decision tree. In this paper Attribute oriented induction (AOI) and relevance analysis incorporated with concept hierarchy's knowledge and height-balancing tree (AVL tree) for construction

Lecture notes in networks and systems, Aug 25, 2022