Zafar Saeed

Zafar Saeed
University of Central Punjab · Department of Computer Science

Ph.D. (Computer Science)

About

16
Publications
3,254
Reads
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197
Citations
Citations since 2017
11 Research Items
197 Citations
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Introduction
Research Interests: Event detection from micro-blogs, Social Computing and Text Mining

Publications

Publications (16)
Article
Full-text available
As big data, its technologies, and application continue to advance, the Smart Grid (SG) has become one of the most successful pervasive and fixed computing platforms that efficiently uses a data-driven approach and employs efficient information and communication technology (ICT) and cloud computing. As a result of the complicated architecture of cl...
Article
Full-text available
The nonlinear transformation concedes as S-box which is responsible for the certainty of contemporary block ciphers. Many kinds of S-boxes are planned by various authors in the literature. Construction of S-box with a powerful cryptographic analysis is the vital step in scheming block cipher. Through this paper, we give more powerful and worthy S-b...
Article
Users are capable of noticing, listening, and comprehending concurrent information simultaneously, but in conventional speech-based interaction methods, systems communicate information sequentially to the users. This mismatch implies that the sequential approach may be under-utilising human perception capabilities and restricting users to seek info...
Article
Full-text available
Massive advances in internet infrastructure are impacting e-healthcare services compared to conventional means. Therefore, extra care and protection is needed for extremely confidential patient medical records. With this intention, we have proposed an enhanced image steganography method, to improve imperceptibility and data hiding capacity of stego...
Chapter
Full-text available
Social media has become a useful source for detecting real-life events. This paper presents an event detection application EveSense. It detects real-life events and related trending topics from the Twitter stream and allows users to find interesting events that have recently occurred. It uses a novel Dynamic Heartbeat Graph (DHG) approach, which ef...
Article
Tweets about everyday events are published on Twitter. Detecting such events is a challenging task due to the diverse and noisy contents of Twitter. In this paper, we propose a novel approach named Weighted Dynamic Heartbeat Graph (WDHG) to detect events from the Twitter stream. Once an event is detected in a Twitter stream, WDHG suppresses it in l...
Article
Full-text available
In the last few years, Twitter has become a popular platform for sharing opinions, experiences, news, and views in real-time. Twitter presents an interesting opportunity for detecting events happening around the world. The content (tweets) published on Twitter are short and pose diverse challenges for detecting and interpreting event-related inform...
Preprint
Full-text available
Tweets about everyday events are published on Twitter. Detecting such events is a challenging task due to the diverse and noisy contents of Twitter. In this paper, we propose a novel approach named Weighted Dynamic Heartbeat Graph (WDHG) to detect events from the Twitter stream. Once an event is detected in a Twitter stream, WDHG suppresses it in l...
Chapter
Full-text available
Huge mounds of data are generated every second on the Internet. People around the globe publish and share information related to real-world events they experience every day. This provides a valuable opportunity to analyze the content of this information to detect real-world happenings, however, it is quite challenging task. In this work, we propose...
Article
Full-text available
Recent advances in the development of high-throughput tools have significantly revolutionized our understanding of molecular mechanisms underlying normal and dysfunctional biological processes. Here we present a novel computational tool, transcription factor search and analysis tool (TrFAST), which was developed for the in silico analysis of transc...
Article
Full-text available
It is a common observation nowadays that the personal information of user is difficult to manage, the material which is copied by the users to their personal system are often forgotten by the users. So when they require their information it becomes very difficult to find the relevant information from huge repository. We have introduced a method usi...

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