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Spatial and temporal analysis of acute respiratory infections (ARIs) in Southern Punjab, Pakistan
Munazza Fatima,Rehman Mehmood Khattak,Sue. C. Grady,Ibtisam Butt,Sana Arshad,Till Ittermann,Henry Volzke 대한공간정보학회 2022 Spatial Information Research Vol.30 No.4
Acute Respiratory Infections (ARI) is a main health issue of Pakistan. This study deals to visualize the spatial distribution of ARIs in first instance and further to investigate their underlying temporal pattern in Bahawalpur district of Southern Punjab Pakistan. The main purpose is to measure spatial patterns of ARIs which might be helpful for better understanding its environmental determinants and leads to hypothesis generation for further investigation. Study design selected to conduct this research is of descriptive and exploratory nature. Epidemiological data of ARIs was collected mainly through 115 health centres from the study area for year 2010 to 2012 and was used to map spatial patterns of ARIs through Inverse distance weighted (IDW) spatial interpolation and Spatial Autocorrelation and Cluster Outlier Analysis. Results show that the clusters of ARIs were found mainly around urban units of tehsils. The study also suggests the set of remedies and policy changes addressing the local environmental problems and to reducing the incidence of ARIs through collaboration of local government and community.
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Zahid Hussain Khand,Sana Gul,Manisha Kumari,Ghulam Mujtaba Sheikh,Noureen Fatima,Kainat Fareed Memon International Journal of Computer ScienceNetwork S 2023 International journal of computer science and netw Vol.23 No.7
Machine learning with its high precision algorithms, Precision agriculture (PA) is a new emerging concept nowadays. Many researchers have worked on the quality and quantity of PA by using sensors, networking, machine learning (ML) techniques, and big data. However, there has been no attempt to work on trends of artificial intelligence (AI) techniques, dataset and crop type on precision agriculture using internet of things (IoT). This research aims to systematically analyze the domains of AI techniques and datasets that have been used in IoT based prediction in the area of PA. A systematic literature review is performed on AI based techniques and datasets for crop management, weather, irrigation, plant, soil and pest prediction. We took the papers on precision agriculture published in the last six years (2013-2019). We considered 42 primary studies related to the research objectives. After critical analysis of the studies, we found that crop management; soil and temperature areas of PA have been commonly used with the help of IoT devices and AI techniques. Moreover, different artificial intelligence techniques like ANN, CNN, SVM, Decision Tree, RF, etc. have been utilized in different fields of Precision agriculture. Image processing with supervised and unsupervised learning practice for prediction and monitoring the PA are also used. In addition, most of the studies are forfaiting sensory dataset to measure different properties of soil, weather, irrigation and crop. To this end, at the end, we provide future directions for researchers and guidelines for practitioners based on the findings of this review.
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Money Demand Function: A Not-So-Fond Farewell in the Light of Financial Development
Masudul Hasan Adil,Neeraj Hatekar,Sana Fatima,Ibrahim Nurudeen,Shan Mohammad 세종대학교 경제통합연구소 2022 Journal of Economic Integration Vol.37 No.1
This study investigates the stability issues of real money balances considering financial development. We estimate real narrow (M1) and broad (M3) money demand in India during the post-financial reform, from 1996:Q2 to 2016:Q3. To check the short- and long-run relationships, this study uses the autoregressive distributed lag model of cointegration and other various time series techniques. After incorporating financial development into money demand, we determined short- and long-run relationships and a well-defined open-economy stable money demand specification (M1 and M3) in India. Having established money demand function, the policymaker and central bankers can use monetary aggregates as an indicator or information variable to predict output gaps and inflationary expectations under the inflation-targeting framework.
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Valliani, Arif,Ahmed, Bilawal,Nanji, Kashmira,Valliani, Salimah,Zulfiqar, Beenish,Fakih, Misbah,Mehdi, Mehwish,Khan, Anam,Sheikh, Sana Arshad,Fatima, Nida,Ahmad, Sobia,Farah, Fariya,Saleem, Shaheera,A Asian Pacific Journal of Cancer Prevention 2012 Asian Pacific journal of cancer prevention Vol.13 No.5
Background: Use of smoke-less tobacco (SLT) is very common in South and South-East Asian countries. It is significantly associated with various types of cancers. The objectives of this study were to assess the proportion of hospital staff that use SLT, and to identify the factors associated with its use and their practices. Methods: In a cross-sectional study, 560 staff of two tertiary care hospitals were interviewed in the year 2009. Nurses, ward boys and technicians were counted as a paramedic staff while drivers, peons, security guards and housekeeping staff were labeled as non-paramedic staff. SLT use was considered as usage of any of the following: betel quid (paan) with or without tobacco, betel nuts with or without tobacco (gutkha) and snuff (naswar). Results: About half (48.6%) of the hospital staff were using at least one type of SLT. Factors found to be statistically significant with SLT were being a male (OR=2.5; 95% CI=1.8-3.7); having no/fewer years of education (OR=1.7; 95% CI=1.2-2.4) and working as non-paramedic staff (OR=2.6; 95% CI=1.8-3.8). Majority of SLT users were using it on regular basis, for > 5 years and keeping the tobacco products in the oral cavity for >30 minutes. About half of the users started due to peer pressure and had tried to quit this habit but failed. Conclusion: In this study, about half of the study participants were using SLT in different forms. We suggest educational and behavioral interventions for control of SLT usage.
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