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1,651 results on '"Ahmad, Farooq"'

1. New Inequalities of Simpson’s type for differentiable functions via generalized convex function

Author

Farooq, Shan E., Shabir, Khurram, Qaisar, Shahid, Ahmad, Farooq, and Almatroud, O. A.

Subjects
Mathematics, QA1-939
Abstract

This article presents some new inequalities of Simpson’s type for differentiable functions by using $(\alpha ,m) $-convexity. Some results for concavity are also obtained. These new estimates improve on the previously known ones. Some applications for special means of real numbers are also provided.

Published
2021
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38. District Wise Price Forecasting of Wheat in Pakistan using Deep Learning

Author

Rasheed, Ahmed, Younis, Muhammad Shahzad, Ahmad, Farooq, Qadir, Junaid, and Kashif, Muhammad

Subjects
Computer Science - Machine Learning, Computer Science - Artificial Intelligence
Abstract

Wheat is the main agricultural crop of Pakistan and is a staple food requirement of almost every Pakistani household making it the main strategic commodity of the country whose availability and affordability is the government's main priority. Wheat food availability can be vastly affected by multiple factors included but not limited to the production, consumption, financial crisis, inflation, or volatile market. The government ensures food security by particular policy and monitory arrangements, which keeps up purchase parity for the poor. Such arrangements can be made more effective if a dynamic analysis is carried out to estimate the future yield based on certain current factors. Future planning of commodity pricing is achievable by forecasting their future price anticipated by the current circumstances. This paper presents a wheat price forecasting methodology, which uses the price, weather, production, and consumption trends for wheat prices taken over the past few years and analyzes them with the help of advance neural networks architecture Long Short Term Memory (LSTM) networks. The proposed methodology presented significantly improved results versus other conventional machine learning and statistical time series analysis methods., Comment: 9 pages, submitted to IEEE Access

Published
2021

39. COVID-19 Digital Contact Tracing Applications and Techniques: A Review Post Initial Deployments

Author

Shahroz, Muhammad, Ahmad, Farooq, Younis, Muhammad Shahzad, Ahmad, Nadeem, Boulos, Maged N. Kamel, Vinuesa, Ricardo, and Qadir, Junaid

Subjects
Computer Science - Computers and Society
Abstract

The coronavirus disease 2019 (COVID-19) is a severe global pandemic that has claimed millions of lives and continues to overwhelm public health systems in many countries. The spread of COVID-19 pandemic has negatively impacted the human mobility patterns such as daily transportation-related behavior of the public. There is a requirement to understand the disease spread patterns and its routes among neighboring individuals for the timely implementation of corrective measures at the required placement. To increase the effectiveness of contact tracing, countries across the globe are leveraging advancements in mobile technology and Internet of Things (IoT) to aid traditional manual contact tracing to track individuals who have come in close contact with identified COVID-19 patients. Even as the first administration of vaccines begins in 2021, the COVID-19 management strategy will continue to be multi-pronged for the foreseeable future with digital contact tracing being a vital component of the response along with the use of preventive measures such as social distancing and the use of face masks. After some months of deployment of digital contact tracing technology, deeper insights into the merits of various approaches and the usability, privacy, and ethical trade-offs involved are emerging. In this paper, we provide a comprehensive analysis of digital contact tracing solutions in terms of their methodologies and technologies in the light of the new data emerging about international experiences of deployments of digital contact tracing technology. We also provide a discussion on open challenges such as scalability, privacy, adaptability and highlight promising directions for future work., Comment: 31 pages, 3 figures and 1 table

Published
2021

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