1,665 research outputs found
Smart Geo Expo, Seoul Korea 2019
No full textThis data is collected during Smart Geo Expo which was held in COEX center Seoul, Korea in 2019. It contains Wi-Fi data from Galaxy S8 and LG G6 which can be used to test indoor positioning techniques
Catastrophic factors involved in road accidents: Underlying causes and descriptive analysis
No full textIt contains the road accidents data for South Korea including various factors
Catastrophic factors involved in road accidents: Underlying causes and descriptive analysis
No full textIt contains the road accidents data for South Korea including various factors
Smart Geo Expo, Seoul Korea 2019
No full textThis data is collected during Smart Geo Expo which was held in COEX center Seoul, Korea in 2019. It contains Wi-Fi data from Galaxy S8 and LG G6 which can be used to test indoor positioning techniques
A Comparative study of major Indian e-bookshops
No full textKhan,
Imran. (2014). A Comparative study of major Indian e-bookshops. In
Ashraf, Tariq et al. (eds.). From brick to click: transforming libraries into
social spaces. New Delhi: Synergy Books, 2014, pp. 105-115 (ISBN:
978-93-82059-23-3)
Digitization of manuscripts in HMS Central Library, Jamia Hamdard (Hamdard University) New Delhi: a case study
No full textKhan,
Imran. (2014). Digitization of manuscripts in HMS Central Library, Jamia
Hamdard (Hamdard University) New Delhi: a case study. In Ashraf, Tariq
et al. (eds.). From brick to click: transforming libraries into social spaces.
New Delhi: Synergy Books, 2014, pp. 96-104 (ISBN: 978-93-82059-23-3)
Challenges and opportunities of collection development in digital libraries
No full textKhan,
Imran. (2016). Challenges and opportunities of collection development in
digital libraries. In Gulati, Puja
Anand, Ashraf, Tariq, Kumar, Sanjeev (eds.). Proceedings of the National
Conference on Building Digital India: Enhancing Capacities through Libraries
and Information (22nd-23rd November 2016: New Delhi). New
Delhi: Synergy Books, 2016, pp. 32-40 (ISBN: 978-93-82059-52-3)
sj-docx-1-dhj-10.1177_20552076231203802 - Supplemental material for Cervical cancer detection using K nearest neighbor imputer and stacked ensemble learningmodel
No full textSupplemental material, sj-docx-1-dhj-10.1177_20552076231203802 for Cervical cancer detection using K nearest neighbor imputer and stacked ensemble learningmodel by Xiaoyuan Chen, Turki Aljrees, Muhammad Umer, Oumaima Saidani, Latifah Almuqren, Olfa Mzoughi, Abid Ishaq and Imran Ashraf in DIGITAL HEALTH</p
Artificial intelligence-driven predictive framework for early detection of still birth
No full textPredictive modeling is becoming increasingly popular in the context of early disease detection. The use of machine learning approaches for predictive modeling can help early detection of diseases thereby enabling medical experts to appropriate medical treatments. Stillbirth prediction is a similar domain where artificial intelligence-based predictive modeling can alleviate this significant global health challenge. Despite advancements in prenatal care, the prevention of stillbirths remains a complex issue requiring further research and interventions. The cardiotocography (CTG) dataset is used in this research work from the UCI machine learning (ML) repository to investigate the efficiency of the proposed approach regarding stillbirth prediction. This research work adopts the Tabular Prior Data Fitted Network (TabPFN) model which was originally designed to solve small tabular classification. TabPFN is used to predict the still or live birth during pregnancy with 97.91% accuracy. To address this life-saving problem with more accurate results and in-depth analysis of ML models, this research work makes use of 13 renowned ML models for performance comparison with the proposed model. The proposed model is evaluated using precision, recall, F-score, Mathews Correlation Coefficient (MCC), and the area under the curve evaluation parameters and the results are 97.87%, 98.26%, 98.05%, 96.42%, and 98.88%, respectively. The results of the proposed model are further evaluated using k-fold cross-validation and its performance comparison with other state-of-the-art studies indicating the superior performance of TabPFN model
Analyzing Language and Power Relationship; A Critical Discourse Analysis of Imran Khan's Speeches
No full textLanguage has variety of roles in the lives of human beings. It speaks volumes about how someone uses language and makes it distinct from one culturally diverse person to another. Language in this sense plays a crucial role in determining how and what individuals say and, in turn, such language use in the political discourse will be reflected upon by others, positively or negatively. Politicians within any system, often depends on the language to assert power, persuade and convince people of their ideologies. This paper considers the language used by the Former Prime Minister of Pakistan, Mr. Imran Khan as demonstrated in his spoken political discourse. More specifically, it attempted to analyse the language as used by a well-known politician and leader. The study holds qualitative analysis of Mr. Imran Khan’s spoken political discourse to interpret Imran Khan’s word choices to reflect his intention in a political realm. For sure, it can convince and persuade people in believing particular desire, ideology or even action. For this purpose, Imran Khan during his leadership locally and internationally were analysed based on the theoretical framework of Fairclough's three-dimensional model. The study reveals several findings including Mr. Imran’s linguistic and rhetorical strategies in demonstrating his leadership in Pakistan and abroad
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