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Afed Ullah Khan Waqar Ahmad,Muhammad Far Fayaz Ahmad Khan,Baig Ammar Ahmad,Shah Liaqat Ali,Khan Jehanzeb 한국대기환경학회 2020 Asian Journal of Atmospheric Environment (AJAE) Vol.14 No.2
Precipitation, air temperature and Normalized Difference Vegetation Index (NDVI) data of 32 sites for a period of 1983 to till date in Pakistan were collected with the objective of studying the effects of vegetation on precipitation and air temperature in Pakistan. Spatial trends were assessed for NDVI, precipitation and air temperature (maximum and minimum). Increasing trends were observed at 18, 20, 24 and 26 number of monitoring stations for NDVI, precipitation and maximum and minimum temperature respectively. The trends of NDVI were compared with the trends of precipitation and maximum and minimum temperature in hilly and urban areas. NDVI and precipitation showed parallel trends in hilly areas at 64% of the monitoring stations. Whereas, only 53% of the stations displayed parallel trends in urban areas. 71% of the stations showed opposite NDVI and maximum temperature trends and 79% of the stations showed opposite NDVI and minimum temperature trends in hilly areas. However, in urban areas only 47% and 41% of the stations showed opposite trends of NDVI and maximum temperature and NDVI and minimum temperature respectively. Pearson’s correlation coefficients were calculated to determine the effects of vegetation on precipitation and air temperature (maximum and minimum) in hilly and urban areas. The results showed that there exists positive relationship between NDVI and precipitation and negative relationship between NDVI and temperature (maximum and minimum) in most of the hilly areas. However, in urban areas, the positive relationship between NDVI and precipitation exists only in 47% of the stations and negative relationships between NDVI and maximum temperature and between NDVI and minimum temperature exist only in 47% and 41% of the stations respectively. Results of the current study suggest afforestation practices at country level to reduce climate change effects.
Ahmad Waqar,Hussain Babar 한국국제경제학회 2024 International Economic Journal Vol.38 No.2
The objective of this study is to investigate the effects of the shadow economy on environmental pollution and how this effect depends on the levels of corruption. The study utilizes an annual panel dataset of 127 selected developing countries worldwide, spanning from 2002 to 2018, and employs the Generalized Method of Moments (GMM) technique, which effectively addresses potential endogeneity issues in the model. The estimation results reveal that the shadow economy increases the level of environmental pollution. Furthermore, the results indicate that corruption intensifies the impacts of the shadow economy on environmental pollution. This highlights a significant complimentary between the shadow economy and corruption, indicating that an increase in the levels of corruption will lead to an increase the shadow economy and will also strengthen its harmful impact on environmental pollution through the channel of corruption. Additionally, the estimates remain robust when using alternative measure of the shadow economy.
A Fault Tolerant Data Management Scheme for Healthcare Internet of Things in Fog Computing
( Waqar Saeed ),( Zulfiqar Ahmad ),( Ali I. Jehangiri ),( Nader Mohamed ),( Arif I. Umar ),( Jamil Ahmad ) 한국인터넷정보학회 2021 KSII Transactions on Internet and Information Syst Vol.15 No.1
Fog computing aims to provide the solution of bandwidth, network latency and energy consumption problems of cloud computing. Likewise, management of data generated by healthcare IoT devices is one of the significant applications of fog computing. Huge amount of data is being generated by healthcare IoT devices and such types of data is required to be managed efficiently, with low latency, without failure, and with minimum energy consumption and low cost. Failures of task or node can cause more latency, maximum energy consumption and high cost. Thus, a failure free, cost efficient, and energy aware management and scheduling scheme for data generated by healthcare IoT devices not only improves the performance of the system but also saves the precious lives of patients because of due to minimum latency and provision of fault tolerance. Therefore, to address all such challenges with regard to data management and fault tolerance, we have presented a Fault Tolerant Data management (FTDM) scheme for healthcare IoT in fog computing. In FTDM, the data generated by healthcare IoT devices is efficiently organized and managed through well-defined components and steps. A two way fault-tolerant mechanism i.e., task-based fault-tolerance and node-based fault-tolerance, is provided in FTDM through which failure of tasks and nodes are managed. The paper considers energy consumption, execution cost, network usage, latency, and execution time as performance evaluation parameters. The simulation results show significantly improvements which are performed using iFogSim. Further, the simulation results show that the proposed FTDM strategy reduces energy consumption 3.97%, execution cost 5.09%, network usage 25.88%, latency 44.15% and execution time 48.89% as compared with existing Greedy Knapsack Scheduling (GKS) strategy. Moreover, it is worthwhile to mention that sometimes the patients are required to be treated remotely due to non-availability of facilities or due to some infectious diseases such as COVID-19. Thus, in such circumstances, the proposed strategy is significantly efficient.
Compounds Toxicity Prediction Using Convolution Neural Network Model
Waqar Ahmad,Kil To Chong 제어로봇시스템학회 2021 제어로봇시스템학회 각 지부별 자료집 Vol.2021 No.12
The compound toxicity is its ability to cause damaging effects on single cell or cells group or organ of the body. Due to bioassay advancements in recent years, new drugs emerged day by day and hence chemical toxicity data also increased. Moreover, traditional toxicity analysis methods failed to process large amount of toxicity data. Using these large amount of toxicity data, deep learning methods are useful for building Quantitative structure-activity relationship (QSAR) models for toxicity prediction. We used the convolution neural network model for toxicity prediction using SMILES images. This method achieved the 79% F1-score for toxic and non-toxic predictions. We hope that out model will contribute towards toxicity prediction in de novo drug discovery.
Ahmad Nawaz,Habib Ali,Muhammad Sufyan,Muhammad Dildar Gogi,Muhammad Jalal Arif,Abid Ali,Muhammad Qasim,Waqar Islam,Noman Ali,Imran Bodla,Madiha Zaynab,Khalid Ali Khan,Hamed A. Ghramh 한국응용곤충학회 2020 Journal of Asia-Pacific Entomology Vol.23 No.1
The lepidopteran insect pests have significant importance in vegetable production. The present study was performed to investigate the baseline studies about the assessment of feeding and consumption potential, utilization indices and losses promises of leafworm, Spodoptera litura (Fab.) on Okra. The data regarding feeding potential, food utilization and consumption indices as well as losses of different larval instars were recorded and subjected to appropriate statistical analysis. The results showed that, in the beginning, the approximate digestibility of various instars was increase, e.g. third instar (51.36%–64.03%), fourth instar (63.42%–69.45%) and fifth instar (70.25%–76.10%). However, after a certain period, the digestibility was decreased and efficiency to convert the ingested food into biomass varied significantly. The consumption index values increased with an increase in time but the consumption and growth rate was declined of fourth instar larvae. The ingestion and digestion increased of third (10.01–13.06, 8.32–11.91 mg), fourth (11.27–17.28, 10.96–14.03 mg) and fifth (12.60–19.40, 11.93–15.28 mg) larval instars. The corrected weight of consumed leaves increased with a gain in body weight. However, in the third instar, a decline was observed on the last day of feeding. Maximum leaf area was consumed by fifth instar larvae (44.66 cm 2 ) followed by fourth (35.41 cm 2 ) and third (27.98 cm 2 ) instars. In conclusion, all the dependent parameters, including food utilization potential, consumption indices and losses were higher for fifth instar larvae than others. These results emphasized the re-establishment of fundamental (economic threshold level: ETL, economic injury level: EIL) integrated pest management concepts.