A5009591817- Advanced Malware Detection Techniques
- Topic Modeling
- Network Security and Intrusion Detection
- Spam and Phishing Detection
- Internet Traffic Analysis and Secure E-voting
- Biomedical Text Mining and Ontologies
- Sentiment Analysis and Opinion Mining
- Natural Language Processing Techniques
- Text and Document Classification Technologies
- IoT and Edge/Fog Computing
- Digital and Cyber Forensics
- Recommender Systems and Techniques
- Semantic Web and Ontologies
- Software Engineering Research
- Imbalanced Data Classification Techniques
- Scientific Computing and Data Management
- Anomaly Detection Techniques and Applications
- Customer churn and segmentation
- Advanced Text Analysis Techniques
- Digital Media Forensic Detection
- Consumer Market Behavior and Pricing
- Mental Health via Writing
- Image and Video Quality Assessment
- Blockchain Technology Applications and Security
- Genetics, Bioinformatics, and Biomedical Research
National University of Sciences and Technology
2015-2024
Conference Board
2019
Bahria University
2016-2017
National University of Science and Technology
2013-2014
Middle East College
2014
Research Organization of Information and Systems
2013
University of the Sciences
2012
Ollscoil na Gaillimhe – University of Galway
2011
University of Manchester
2008-2009
The Signalling System No. 7 (SS7) is used in GSM/UMTS telecommunication technologies for signalling and management of communication. It was designed on the concept private boundary walled technology having mutual trust between few national/multinational operators with no inherent security controls 1970s. Deregulation, expansion, merger data networks have vanquished walls hence increasing number service providers, entry points, interfaces to SS7 network, which made it vulnerable serious...
There has been a rapid increase in dietary ailments during the last few decades, caused by unhealthy food routine. Mobile-based assessment systems that can record real-time images of meal and analyze it for nutritional content be very handy improve habits and, therefore, result healthy life. This paper proposes novel system to automatically estimate attributes such as ingredients value classifying input image food. Our method employs different deep learning models accurate identification. In...
Artificial intelligence has been widely used in the field of dentistry recent years. The present study highlights current advances and limitations integrating artificial intelligence, machine learning, deep learning subfields including periodontology, endodontics, orthodontics, restorative dentistry, oral pathology. This article aims to provide a systematic review clinical applications within different fields dentistry. preferred reporting items for reviews (PRISMA) statement was as formal...
Automated dental imaging interpretation is one of the most prolific areas research using artificial intelligence. X-ray systems have enabled clinicians to identify diseases. However, manual process disease assessment tedious and error-prone when diagnosed by inexperienced dentists. Thus, researchers employed different advanced computer vision techniques, as well machine deep learning models for diagnoses imagery. In this regard, a lightweight Mask-RCNN model proposed periapical detection....
Medical Expert Systems is an active research area where data analysts and medical experts are continuously collaborating to make these systems more accurate therefore, useful in real life. Recent surveys by World Health Organization indicated a great increase number of diabetic patients the deaths that attributed diabetes each year. Therefore, early diagnosis major concern among researchers practitioners. The paper presents application automatic multilayer perceptron (AutoMLP) which combined...
Given the high prevalence and detrimental effects of unintentional falls in elderly, fall detection has become a pertinent public concern. A Fall Detection System (FDS) gathers information from sensors to distinguish routine activities order provide immediate medical assistance. Hence, integrity collected data becomes imperative. Presence missing values data, caused by unreliable delivery, lossy sensors, local interference synchronization disturbances so forth, greatly hamper credibility...
In today's world, mental health diseases have become highly prevalent, and depression is one of the problems that has widespread. According to WHO reports, second-leading cause global burden diseases. proliferation such issues, social media proven be a great platform for people express themselves. Thus, user's can speak deal about his/her emotional state health. Considering high pervasiveness disease, this paper presents novel framework detection from textual data, employing Natural Language...
In today's interconnected world, cybersecurity has emerged as a critical domain for ensuring the integrity, confidentiality, and availability of digital assets. Within this sphere, insider threats represent unique particularly insidious class security risks, originating not from external hackers but within organization itself. These are perpetrated by individuals with inside information concerning organization's practices, data, computer systems. Traditional measures like firewalls,...
Continuous proliferation of hate speech in different languages on social media has drawn significant attention from researchers the past decade. Detecting is indispensable irrespective scale use language, as it inflicts huge harm society. This work presents a first resource for classifying severity addition to offensive and content. Current research mostly limits classification its primary categories, such racism, sexism, hatred religions. However, targeted at protected characteristics also...
Low power and lossy networks have been an active area of research due to their large number potential applications in different environments like health, environment monitoring entertainment domain. Numbers protocols proposed for routing these using metrics hop count, delay, bandwidth etc. The working group IETF has done one major contribution form a proactive gradient based protocol low (RPL). However, network having few mobile sinks calculating gradients approach is costly terms energy....
Adverse drug reactions (ADRs) are the undesirable effects associated with use of a due to some pharmacological action drug. During last few years, social media has become popular platform where people discuss their health problems and, therefore, source share information related ADR in natural language. This paper presents an end-to-end system for modelling detection from given text by fine-tuning BERT highly modular Framework Adapting Representation Models (FARM). overcame predominant...
Software engineers post their opinions about various topics on social media that can be collectively mined using Sentiment Analysis. Analyzing this opinion is useful because it provide insight into developers’ feedback tools and topics. General-purpose sentiment analysis do not work well in the software domain most of these are trained movies review datasets. Therefore, efforts underway to develop domain-specific for Engineering (SE) domain. However, existing SE struggle compute negative...
BioHackathon 2010 was the third in a series of meetings hosted by Database Center for Life Sciences (DBCLS) Tokyo, Japan. The overall goal is to improve quality and accessibility life science research data on Web bringing together representatives from public databases, analytical tool providers, cyber-infrastructure researchers jointly tackle important challenges area silico biological research. theme 'Semantic Web', all attendees gathered with shared producing Semantic their respective...