Browsing by Author "Muhammad Aftab"

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    Determinants and Coping Strategies for Building Digital Resilience among Adolescents
    (UMT.Lahore, 2024) Muhammad Aftab
    The concept of resilience is complex and reflects how different people respond to stress, hardship, and challenging situations. The ability to handle digital risk issues requires the development of digital resilience. This research aimed to identify the determinants for building digital resilience among adolescents, while facing cyberbullying and assess their digital skills, coping strategies particularly in building digital resilience in (Lahore) Pakistan. The research applied a cross-sectional design and was adopted based on requiring the quantitative (n= 384) interviews of adolescents who are currently students of classes 9th and 10th in different public and private schools in Lahore, Pakistan, by conducting simple random sampling technique.
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    Machine Generated Deep Image Captioning with Style
    (UMT, Lahore, 2020) Muhammad Aftab
    A powerful tool for perceiving the physical world is sight. The study of computer vision aims to provide sight to artificial agents, enabling them to understand complex visual scenes. As a core topic in artificial intelligence and machine learning it has been the focus of extensive research, but is far from solved, with humans still outperforming artificial vision systems in most tasks. Communication between humans is primarily through language. Designing an agent that can communicate via language is an important goal for human-agent interaction and for building agents that can learn from the vast repositories of human knowledge. With these aims natural language processing is a core topic in artificial intelligence and machine learning. Like computer vision, natural language processing has been the focus of extensive research, but remains an open problem. This thesis seeks to connect two core topics in machine intelligence: vision and language. Although several topics exist at the intersection.In this research focus on automatic image captioning: generating natural language descriptions of image content. Automatic captioning involves both the image understanding problem from computer vision and the natural language generation problem from natural language processing. To improve communication the researcher endeavour to add an extra layer to automatic captioning in the form of linguistic style. Stylistic variations in language have a range of useful applications, such as: reaching a broad audience, reducing misinformation, and engaging viewers. With these applications in mind the research develop and evaluate novel methods capable of generating stylised captions for natural images. Previous research into image caption generation has focused on generating purely descriptive captions; In this research the focus is on generating visually relevant captions with a distinct linguistic style. Captions with style have the potential to ease communication and add a new layer of personalisation. First, the researcher consider naming variations in image captions, and propose a method for predicting context- dependent names that takes into account visual and linguistic information. This method makes use of a large-scale image caption dataset, which the researcher also use to explore naming conventions and report naming conventions for hundreds of 9 people. Next the researcher propose the SentiCap model, which relies on recent advances in artificial neural networks to generate visually relevant image captions with positive or negative sentiment. To balance descriptiveness and sentiment, the SentiCap model dynamically switches between two recurrent neural networks, one tuned for descriptive words and one for sentiment words. As the first published model for generating captions with sentiment, SentiCap has influenced a number of subsequent works. The researcher then investigate the sub-task of modelling styled sentences without images. The specific task chosen is sentence simplification: rewriting news article sentences to make them easier to understand. For this task the researcher design a neural sequence-to-sequence model that can work with limited training data, using novel adaptations for word copying and sharing word embeddings. Finally, the researcher present SemStyle, a system for generating visually relevant image captions in the style of an arbitrary text corpus. A shared term space allows a neural network for vision and content planning to communicate with a network for styled language generation. SemStyle achieves competitive results in human and automatic evaluations of descriptiveness and style. As a whole, this thesis presents two complete systems for styled caption generation that are first of their kind and demonstrate, for the first time, that automatic style transfer for image captions is achievable. Contributions also include novel ideas for object naming and sentence simplification. This thesis opens up inquiries into highly personalised image captions; large scale visually grounded concept naming; and more generally, styled text generation with content control.
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    Understanding People’s Perceptions about Digital and Actual Culture
    (UMT.lahore, 2022-09-12) Muhammad Aftab; Aiza Batool; Samman Iqbal
    This study was conduct on the actual culture and digital culture, that actual culture is the way of life through different methods, we interact with other members of society and the actual culture historically run from generation to generation and exists in society in various forms. Digital culture is the culture, which we see through different electronic gadgets and in cyberspace, which is connected through technology advancement and digital culture exists due to phenomena of digitalization and digital culture provides many facilities which make the life so easy and efficient these days. The objective of this study was to highlight the causes and consequences of digital culture, identify the factors behind the emergence of digital culture, relationship between actual and digital culture and why mostly people live on values of actual rather than digital culture, and change in attitudes of people due to digital culture. The qualitative research method is used in this research and we collected data through interview guide by targeting 10 male and 10 female participants and their subjective point of views were used in the data analysis in which we make themes that help to highlight the variation in responses. The study revealed that life of each individual is different due to various factors. The actual and digital culture have advantages and disadvantages and depending upon how you adopt it and life should have limited consumption of digital culture and actual culture of life is entirely different as compared to digital culture. After completion of this study, it will be easily to understand the position of a person if his life is passed through actual culture or digital culture only. The person is facing more challenges if his life is completely dependent upon digital culture and there are more drawbacks of digital culture rather than actual culture. The life should be balanced in both between actual and digital culture.