Improving temperature stress resistance in spring maize by seed priming

Hafeez ur Rehman,Irfan Afzal,Muhammad Farooq,Tariq Azii,Shahzad Maqsood Ahmad Basra 단국대학교 국제농업협력연구소 2012 단국대학교 국제농업협력연구소 학술대회 Vol.2012 No.1

Chilling resistance at sowing is pre-requisite to avoid high temperature stress at terminal stage of spring planted maize crop. Seed priming offers promising solution to improve crop resistance against low or high temperature stress. Therefore, this study was conducted to evaluate the role of seed priming in improving the performance of spring planted maize under various sowing dates. Seeds of hybrid maize FH-810 were soaked in aerated solution of CaC}z (2.2%), moringa leaf extracts (MLE, 3.3%) and salicylic acid (SA, 50 mg L- 1 ) while dry and water soaked seeds (hydropriming) were used as controls. Both primed and untreated seeds were planted on 02 and 22 Feb, and 14 March. Late planted maize observed notable decline in mean emergence time than early planted crop owing to high temperature at planting. Both low and high temperature in early (02 Feb) and late (14 March) planted maize resulted in reduced seedling growth and tissue water status accompanied with elevated membrane electrolytes leakage. Moreover all the priming techniques improved the studied parameters of crop compared with control at all planting dates. Seed osmopriming with SA improved crop stress resistance by earlier emergence, increased seedling dry weight, tissue water status and improved membrane stability followed by osmopriming with CaC12.

Velocity selective optical pumping effects on ⁸⁵ Rb atoms from various coupling beam polarization configurations

Rehman, Hafeez Ur,Noh, Heung-Ryoul,Kim, Jin-Tae Elsevier 2017 OPTICS COMMUNICATIONS - Vol.402 No.-

<P><B>Abstract</B></P> <P>We have investigated velocity selective spectral profile variations of probe beam transmittance at <SUB> F g </SUB> = 3 → <SUB> F e </SUB> = 2 , 3 , and 4 hyperfine manifolds of <SUP> 85 </SUP> Rb atoms along with coherence effects at the <SUB> F g </SUB> = 3 → <SUB> F e </SUB> = 4 transition with various coupling laser polarization configurations and a fixed probe polarization ( <SUP> σ + </SUP> ). Laser linewidth, atomic velocity distributions, frequency mixing of the coupling and probe laser beams between degenerate magnetic sublevels, and polarization variations of the coupling beam with the probe beam fixed at the <SUB> F g </SUB> = 3 → <SUB> F e </SUB> = 4 transition were used to simulate the line profiles. The calculated transmittance signals are in good agreement with observed signals for each coupling laser polarization configuration.</P> <P><B>Highlights</B></P> <P> <UL> <LI> We investigate velocity selective optical pumping spectroscopy for <SUP> 85 </SUP> Rb atoms. </LI> <LI> We consider laser linewidth and frequency mixing of lasers in the calculation. </LI> <LI> The experimental results are compared with calculated results. </LI> </UL> </P>

Managing Paddy Soils to Improve Zn Bioavailability and Agronomic Performance of Fine Grain Aromatic Rice

Hafeez Ur Rehman,Faiz Rasool,Shahzad M A Basra,Abdul Wakeel 한국토양비료학회 2014 한국토양비료학회 학술발표회 초록집 Vol.2014 No.6

Mining public opinion: a sentiment based forecasting for democratic elections of Pakistan

Nawaz Asif,Ali Tariq,Hafeez Yaser,Rehman Saif ur,Rashid Muhammad Rizwan 대한공간정보학회 2022 Spatial Information Research Vol.30 No.2

Twitter has emerged as outstanding and most prominent social media in today’s technological age. The data proliferates in quick and words with its activities trigger get fast responses from the users. This platform is perfect for promoting political perspectives, particularly when election campaigns are on its peak. Political trends on Twitter media has been contemplated in the course of recent years. In the past research, both supervised and unsupervised methodologies have been used to analyze the Twitter trends. Most of the Tweet classification approaches utilized built in Dictionaries, Naı¨ve Bayes, K-Nearest Neighbors (KNN), decision tree and Support Vector Machines (SVM) classifiers. However, in case of democratic election these trends can be mined to predict the winning party. However, all such approaches produce poor results due to language issues, low accuracy, limited access to internet and lower literacy rate in less developed countries such as Pakistan. This research study, find the best possible way for collection of tweets related to different political parties and build a prediction model that may analyze sentiments and opinions expressed by peoples in their Tweets. In this research work, a prediction based model along with novel similarity measure has been proposed to predict the election results of political parties in Pakistan. The proposed work is composed of data collection, preprocessing, aspect extraction, aspect refinement and final prediction using Bayesian theorem. Form the experimental results, it is concluded that proposed approach perform better than existing techniques by obtaining almost 98% accuracy and efficiently cover the limitations of existing studies.

Mining public opinion: a sentiment based forecasting for democratic elections of Pakistan

Nawaz Asif,Ali Tariq,Hafeez Yaser,Rehman Saif ur,Rashid Muhammad Rizwan 대한공간정보학회 2022 Spatial Information Research Vol.30 No.1

Twitter has emerged as outstanding and most prominent social media in today’s technological age. The data proliferates in quick and words with its activities trigger get fast responses from the users. This platform is perfect for promoting political perspectives, particularly when election campaigns are on its peak. Political trends on Twitter media has been contemplated in the course of recent years. In the past research, both supervised and unsupervised methodologies have been used to analyze the Twitter trends. Most of the Tweet classification approaches utilized built in Dictionaries, Naı¨ve Bayes, K-Nearest Neighbors (KNN), decision tree and Support Vector Machines (SVM) classifiers. However, in case of democratic election these trends can be mined to predict the winning party. However, all such approaches produce poor results due to language issues, low accuracy, limited access to internet and lower literacy rate in less developed countries such as Pakistan. This research study, find the best possible way for collection of tweets related to different political parties and build a prediction model that may analyze sentiments and opinions expressed by peoples in their Tweets. In this research work, a prediction based model along with novel similarity measure has been proposed to predict the election results of political parties in Pakistan. The proposed work is composed of data collection, preprocessing, aspect extraction, aspect refinement and final prediction using Bayesian theorem. Form the experimental results, it is concluded that proposed approach perform better than existing techniques by obtaining almost 98% accuracy and efficiently cover the limitations of existing studies.

Effect of different tab materials in the tensile testing of GFRP

Deviprakash Jyothishmathi Devan,Razi Ur Rehman,Tom Sunny,Farrukh Hafeez,Amjad Alsakarneh 대한기계학회 2023 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.37 No.9

Glass fiber reinforced polymer composites (GFRP) are widely replacing conventional materials due to their improved machinability and high strength to weight ratio. Content and tensile tests are two of the basic approaches used in characterizing GFRP. The content test was performed to determine the reinforcement, matrix, and void content. The void content of 1.8 percent causes moisture absorption leading to fiber pull out and breakage. The failure of the specimens after the tensile test was primarily associated with interfacial debonding. Different tab materials and adhesives were considered for performing the tensile test. Stainless steel and galvanized iron tabs showed considerable slippage during the transverse tensile test. However, the slippage rate was remarkably lower when tabs of the same specimen material and similar thickness were used. The effect of tab geometry and adhesive strength was found to be less significant compared to tab material and adhesive thickness. Stiffness in the longitudinal direction was found to be six times higher than in the transverse direction.

Smart Real-Time Video Surveillance Platform for Drowsiness Detection Based on Eyelid Closure

Tayab Khan, Muhammad,Anwar, Hafeez,Ullah, Farman,Ur Rehman, Ata,Ullah, Rehmat,Iqbal, Asif,Lee, Bok-Hee,Kwak, Kyung Sup WILEY INTERSCIENCE 2019 WIRELESS COMMUNICATIONS AND MOBILE COMPUTING Vol.2019 No.-

<P>We propose drowsiness detection in real-time surveillance videos by determining if a person’s eyes are open or closed. As a first step, the face of the subject is detected in the image. In the detected face, the eyes are localized and filtered with an extended Sobel operator to detect the curvature of the eyelids. Once the curves are detected, concavity is used to tell whether the eyelids are closed or open. Consequently, a concave upward curve means the eyelid is closed whereas a concave downwards curve means the eye is open. The proposed method is also implemented on hardware in order to be used in real-time scenarios, such as driver drowsiness detection. The evaluation of the proposed method used three image datasets, where images in the first dataset have a uniform background. The proposed method achieved classification accuracy of up to 95% on this dataset. Another benchmark dataset used has significant variations based on face deformations. With this dataset, our method achieved classification accuracy of 70%. A real-time video dataset of people driving the car was also used, where the proposed method achieved 95% accuracy, thus showing its feasibility for use in real-time scenarios.</P>

Fisheries and Aquaculture sector of Pakistan: The recent trends, issues and developments

Muhammad Akmal,Muhammad Hafeez-ur-Rehman,Noor Khan,Fayyaz Rasool,Farzana Abbas,Sumaira Abbas,Hamda Azmat,Shakeela Parveen 한국수산해양기술학회(구 한국어업기술학회) 2017 한국수산해양기술학회 학술발표대회 Vol.2017 No.11

Financial Distress Prediction Using Adaboost and Bagging in Pakistan Stock Exchange

Fayaz Hussain TUNIO,Yi DING,Amad Nabi AGHA,Kinza AGHA,Hafeez Ur Rehman Zubair PANHWAR 한국유통과학회 2021 The Journal of Asian Finance, Economics and Busine Vol.8 No.1

Default has become an extreme concern in the current world due to the financial crisis. The previous prediction of companies’ bankruptcy exhibits evidence of decision assistance for financial and regulatory bodies. Notwithstanding numerous advanced approaches, this area of study is not outmoded and requires additional research. The purpose of this research is to find the best classifier to detect a company’s default risk and bankruptcy. This study used secondary data from the Pakistan Stock Exchange (PSX) and it is time-series data to examine the impact on the determinants. This research examined several different classifiers as per their competence to properly categorize default and non-default Pakistani companies listed on the PSX. Additionally, PSX has remained consistent for some years in terms of growth and has provided benefits to its stockholders. This paper utilizes machine learning techniques to predict financial distress in companies listed on the PSX. Our results indicate that most multi-stage mixture of classifiers provided noteworthy developments over the individual classifiers. This means that firms will have to work on the financial variables such as liquidity and profitability to not fall into the category of liquidation. Moreover, Adaptive Boosting (Adaboost) provides a significant boost in the performance of each classifier.

Cadmium stress in rice: toxic effects, tolerance mechanisms, and management: a critical review

Rizwan, M.,Ali, S.,Adrees, M.,Rizvi, H.,Zia-ur-Rehman, M.,Hannan, F.,Qayyum, M. F.,Hafeez, F.,Ok, Y. S. Springer Science + Business Media 2016 Environmental Science and Pollution Research Vol.23 No.18

<P>Cadmium (Cd) is one of the main pollutants in paddy fields, and its accumulation in rice (Oryza sativa L.) and subsequent transfer to food chain is a global environmental issue. This paper reviews the toxic effects, tolerance mechanisms, and management of Cd in a rice paddy. Cadmium toxicity decreases seed germination, growth, mineral nutrients, photosynthesis, and grain yield. It also causes oxidative stress and genotoxicity in rice. Plant response to Cd toxicity varies with cultivars, growth condition, and duration of Cd exposure. Under Cd stress, stimulation of antioxidant defense system, osmoregulation, ion homeostasis, and over production of signaling molecules are important tolerance mechanisms in rice. Several strategies have been proposed for the management of Cd-contaminated paddy soils. One such approach is the exogenous application of hormones, osmolytes, and signaling molecules. Moreover, Cd uptake and toxicity in rice can be decreased by proper application of essential nutrients such as nitrogen, zinc, iron, and selenium in Cd-contaminated soils. In addition, several inorganic (liming and silicon) and organic (compost and biochar) amendments have been applied in the soils to reduce Cd stress in rice. Selection of low Cd-accumulating rice cultivars, crop rotation, water management, and exogenous application of microbes could be a reasonable approach to alleviate Cd toxicity in rice. To draw a sound conclusion, long-term field trials are still required, including risks and benefit analysis for various management strategies.</P>