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| 1 | Detection of parathion methyl using a surface plasmon resonance sensor combined with molecularly imprinted films显示文摘An ultra-sensitive and highly selective parathion methyl(PM) detection method by surface plasmon resonance(SPR) combined with molecularly imprinted films(MIF) was developed. The PM-imprinted film was prepared by thermo initiated polymerization on the bare Au surface of an SPR sensor chip.Template PM molecules were quickly removed by an organic solution of acetonitrile/acetic acid(9:1,v/v), causing a shift of 0.58 in SPR angle. In the concentrations range of 10à13–10à10mol/L, the refractive index showed a gradual increase with higher concentrations of template PM and the changes of SPR angles were linear with the negative logarithm of PM concentrations. In the experiment, the minimum detectable concentration was 10à13mol/L. The selectivity of the thin PM-imprinted film against diuron,tetrachlorvinphose and fenitrothion was examined, but no observable binding was detected. The results in the experiment suggested that the MIF had the advantages of high sensitivity and selectivity. | Yuan Tan Israr Ahmad Tian-Xin Wei | 2015 | Chinese Chemical Letters2015，26，6： | 6 |
| 2 | Thymoquinone suppresses metastasis of melanoma cells by inhibition of NLRP3 inflammasome显示文摘 | Israr Ahmad Kashiff M. Muneer Iman A. Tamimi Michelle E. Chang Muhammad O. Ata Nabiha Yusuf | 2013 | Toxicology and Applied Pharmacology2013，，： | 1 |
| 3 | Key Factors for Determining Students' Satisfaction in Distance Learning Courses: A Study of Allama Iqbal Open University显示文摘 | Afzaal Ali Israr Ahmad | 2011 | Contemporary Educational Technology2011，2，2： | 1 |
| 4 | Key Factors for Deter- mining Students' Satisfaction in Distance Learn- ing Courses: A Study of Allama Iqbal Open Uni- versity 显示文摘 | Afzaal Ali Israr Ahmad | 2011 | Contemporary Educational Technolo- gy2011，2，2： | 1 |
| 5 | Deep Learning Method to Detect the Road Cracks and Potholes for Smart Cities显示文摘The increasing global population at a rapid pace makes road trafficdense;managing such massive traffic is challenging. In developing countrieslike Pakistan, road traffic accidents (RTA) have the highest mortality percentageamong other Asian countries. The main reasons for RTAs are roadcracks and potholes. Understanding the need for an automated system forthe detection of cracks and potholes, this study proposes a decision supportsystem (DSS) for an autonomous road information system for smart citydevelopment with the use of deep learning. The proposed DSS works in layerswhere initially the image of roads is captured and coordinates attached to theimage with the help of global positioning system (GPS), communicated tothe decision layer to find about the cracks and potholes in the roads, andeventually, that information is passed to the road management informationsystem, which gives information to drivers and the maintenance department.For the decision layer, we projected a CNN-based model for pothole crackdetection (PCD). Aimed at training, a K-fold cross-validation strategy wasused where the value of K was set to 10. The training of PCD was completedwith a self-collected dataset consisting of 6000 images from Pakistani roads.The proposed PCD achieved 98% of precision, 97% recall, and accuracy whiletesting on unseen images. The results produced by our model are higher thanthe existing model in terms of performance and computational cost, whichproves its significance. | Hong-Hu Chu Muhammad Rizwan Saeed Javed Rashid Muhammad Tahir Mehmood Israr Ahmad Rao Sohail Iqbal Ghulam Ali | 2023 | Computers, Materials & Continua2023，，4： | 1 |
| 6 | Pedestrian Physical Education Training Over Visualization Tool显示文摘E-learning approaches are one of the most important learning platforms for the learner through electronic equipment.Such study techniques are useful for other groups of learners such as the crowd,pedestrian,sports,transports,communication,emergency services,management systems and education sectors.E-learning is still a challenging domain for researchers and developers to find new trends and advanced tools and methods.Many of them are currently working on this domain to fulfill the requirements of industry and the environment.In this paper,we proposed a method for pedestrian behavior mining of aerial data,using deep flow feature,graph mining technique,and convocational neural network.For input data,the state-of-the-art crowd activity University of Minnesota(UMN)dataset is adopted,which contains the aerial indoor and outdoor view of the pedestrian,for simplification of extra information and computational cost reduction the pre-processing is applied.Deep flow features are extracted to find more accurate information.Furthermore,to deal with repetition in features data and features mining the graph mining algorithm is applied,while Convolution Neural Network(CNN)is applied for pedestrian behavior mining.The proposed method shows 84.50%of mean accuracy and a 15.50%of error rate.Therefore,the achieved results show more accuracy as compared to state-ofthe-art classification algorithms such as decision tree,artificial neural network(ANN). | Tamara al Shloul Israr Akhter Suliman A.Alsuhibany Yazeed Yasin Ghadi Ahmad Jalal Jeongmin Park | 2022 | Computers, Materials & Continua2022，，11： | 0 |
| 7 | On the monetary measures of global liquidity显示文摘This study constructs and examines the dynamics of theoretical and atheoretical measures of global liquidity,using monthly data on the components of broad money over the period 2001 M12-2017 M12 for 39 high income countries.We group the countries into five regional blocks as categorized by the World Bank:East Asia and the Pacific,Europe and Central Asia,Latin America and the Caribbean,Middle East and North Africa,and North America.The atheoretical measures exploited by this study comprise of the simple-sum,GDP-weighted growth rates and PCA based aggregation methods;whereas theoretical measures include the currency equivalent and Divisia index techniques of monetary aggregation.We employ a graphical approach to investigate the trends and dynamics of the aggregates overtime,and a cross-correlation between cyclical components of global real economic activity and the lag of cyclical components of the measures of global liquidity to gauge the strength of their associations.The findings of this study reveal that theoretical measures outperform atheoretical ones in effective delineation of financial and liquidity conditions,and policy stance.Their cyclical components are also strongly associated with those of global real business activity.The currency equivalent measure,besides being a leading indicator of the shift in policy stance,has a sturdy association with global real business activity.Moreover,the theoretical measures,as noted by some empirical studies,contain some information content that the atheoretical lack. | Israr Ahmad Shah Hashmi Arshad Ali Bhatti | 2019 | Financial Innovation2019，5，1： | 0 |
| 8 | Pattern of hepatitis C virus genotypes and subtypes circulating in war-stricken Khyber Pakhtunkhwa,Pakistan:Review of published literature显示文摘Infection due to hepatitis C virus(HCV) is a major cause of fibrosis and hepatocellular carcinoma in Pakistan. In the current review, pattern of HCV genotypes and subtypes in Khyber Pakhtunkhwa province was ascertained in light of the available literature. After thorough analysis, genotype 3(58.27%) was determined to be the leading HCV genotype,followed by genotypes 2(12.39%), 1(9.54%) and 4(0.86%). The proportions of genotypes 5 and 6 were recorded as 0.09% and 0.22% respectively. Subtype wise, 3 a accounted for 48.67%, followed by subtype 2 a(10.91%), 3 b(9.43%), 1 a(5.84%), 1 b(3.66%), 2 b(1.45%) and genotype 4 with its undefined subtypes contributed a portion of0.86%. The cumulative share of subtypes 1 c, 2 c, 3 c, 5 a and 6 a was less than 1%. In11.51% cases, the subtype was untypeable while in 7.17% cases mixed subtypes were recorded. Gender wise, proportions of most HCV subtypes were marginally higher among males as compared to females. On the basis of studied groups, 3 a was pervasive among all groups except in intravenous drug users where 2 a was the major HCV subtype.Similarly, based on various geographical locations(provincial divisions), subtype 3 a revealed a ubiquitous distribution. Conclusively, HCV 3 a persists to be the principal subtype across the province of Khyber Pakhtunkhwa. The considerable number of untypeable subtypes in most studies urges for an improved genotyping system on the basis of local sequence data and practice of sequencing for determination of underlying subtype in untypeable cases. Further, studies on identification of subtypes transmission pattern are imperative for assessment of transmission origin and reinforcement of efficient control strategies. In addition, the current review emphasizes the need of attention toward HCV risk groups and ignored southern side of Khyber Pakhtunkhwa province for better holistic understanding of HCV genotype distribution pattern in the province. | Abdul Waheed Khan Sadia Nawab Zeeshan Nasim Abdul Haleem Khan Syed Ishfaq Ahmad Fazli Zahir Israr Ud Din | 2017 | Asian Pacific Journal of Tropical Medicine2017，10，11： | 0 |
| 9 | Neural Machine Translation Models with Attention-Based Dropout Layer显示文摘In bilingual translation,attention-based Neural Machine Translation(NMT)models are used to achieve synchrony between input and output sequences and the notion of alignment.NMT model has obtained state-of-the-art performance for several language pairs.However,there has been little work exploring useful architectures for Urdu-to-English machine translation.We conducted extensive Urdu-to-English translation experiments using Long short-term memory(LSTM)/Bidirectional recurrent neural networks(Bi-RNN)/Statistical recurrent unit(SRU)/Gated recurrent unit(GRU)/Convolutional neural network(CNN)and Transformer.Experimental results show that Bi-RNN and LSTM with attention mechanism trained iteratively,with a scalable data set,make precise predictions on unseen data.The trained models yielded competitive results by achieving 62.6%and 61%accuracy and 49.67 and 47.14 BLEU scores,respectively.From a qualitative perspective,the translation of the test sets was examined manually,and it was observed that trained models tend to produce repetitive output more frequently.The attention score produced by Bi-RNN and LSTM produced clear alignment,while GRU showed incorrect translation for words,poor alignment and lack of a clear structure.Therefore,we considered refining the attention-based models by defining an additional attention-based dropout layer.Attention dropout fixes alignment errors and minimizes translation errors at the word level.After empirical demonstration and comparison with their counterparts,we found improvement in the quality of the resulting translation system and a decrease in the perplexity and over-translation score.The ability of the proposed model was evaluated using Arabic-English and Persian-English datasets as well.We empirically concluded that adding an attention-based dropout layer helps improve GRU,SRU,and Transformer translation and is considerably more efficient in translation quality and speed. | Huma Israr Safdar Abbas Khan Muhammad Ali Tahir Muhammad Khuram Shahzad Muneer Ahmad Jasni Mohamad Zain | 2023 | Computers, Materials & Continua2023，，5： | 0 |
| 10 | Towards a Dynamic Virtual IoT Network Based on User Requirements显示文摘The data being generated by the Internet of Things needs to be stored,monitored,and analyzed for maximum IoT resource utilization.Software Defined Networking has been extensively utilized to address issues such as heterogeneity and scalability.However,for small-scale IoT application,sometimes it is considered an inefficient approach.This paper proposes an alternate lightweight mechanism to the design and implementation of a dynamic virtual network based on user requirements.The key idea is to provide users a virtual interface that enables them to reconfigure the communication flow between the sensors and actuators at runtime.The throughput of the communication flow depends on the data traffic load and optimal routing.Users can reconfigure the communication flow,and virtual agents find the optimal route to handle the traffic load.The virtual network provides a user-friendly interface to allow physical devices to be mapped with the corresponding virtual agents.The proposed network is applicable for all systems that lie in the Internet of Things domain.Results conclude that the proposed network is efficient,reliable,and responsive to network reconfiguration at runtime. | Faisal Mehmood Shabir Ahmad Israr Ullah Faisal Jamil DoHyeun Kim | 2021 | Computers, Materials & Continua2021，，11： | 0 |
| 11 | A discussion on cotton transformation during the last decade (2010–2021);an update on present trends and future prospects显示文摘The introduction of genetically modified(GM)cotton in 1996 in the US and its worldwide spread later rejuvenated cotton production in many parts of the world.The evolution is continued since then and currently,the 3rd and fourth generation of same GM cotton is grown in many parts of the world.The GM cotton introduced in 1996 was simple Bt cotton that expressed a single Cry1Ac gene,the later generation carried multiple Cry genes along with the genes controlling herbicide tolerance.Current day GM cotton does not only give stable resistance against lepidopteran insects but also facilitates the farmers to spray broad-spectrum herbicides without harming the crop.The evolution of GM cotton is continued both on the basic and applied side and interventions have been introduced during the last decade.Earlier the cotton transformation was limited to Cocker strains which are getting possible in many other varieties,too.It is successful with both gene gun,and Agrobacterium and inplanta transformation has made it a routine activity.Apart from overexpression studies for various purposes including biotic,abiotic,and quality traits,RNAi and genome editing are explored vigorously.Through this review,we have tried to explore and discuss various interventions for improving transformation protocols,the applications of cotton transformation,and future strategies being developed to get maximum benefits from this technology during the last decade. | QANDEEL‑E‑ARSH AZHAR Muhammad Tehseen ATIF Rana Muhammad ISRAR Mahwish KHAN Azeem Iqbal KHALID Shahzad RANA Iqrar Ahmad | 2021 | Journal of Cotton Research2021，4，4： | 0 |
| 12 | Robust Adaptive Multi-Switching Synchronization of Multiple Different Orders Unknown Chaotic Systems显示文摘Multi-switching synchronizatio of multiple different orders unknown chaotisystems confines hacking in the digital transmission process.Similarly,the suppression of undesirable chattering increases synchronization performance.This paper proposes a new robust synchronization contro technique and discusses the MSS of multiple different orders UC systems.This controller accomplishe quick convergence reduces the transient oscillations,an the rate of convergence decreases in the vicinity of the origin that causes the suppression of chattering.Analysis based on the Lyapunov direct method assures this convergence behavior with any positive values of the feedback gains.This work also provides parameters updated law that estimates the true values of unknown parameters.Numerical examples of five UC systems different orders are simulated.The computer based graphical results validate the efficiency and performance of the proposed RASC technique and the synchronization strategy when compare to peer works.In the simulation,the proposed synchronization strategy successfully recovers an encrypted received image on a communication channel.The article suggests some future research problems to extend the use of the proposed work. | MUHAMMAD Shafiq ISRAR Ahmad AMBUSAIDI Mohammed BASHIR Naderi | 2020 | Journal of Systems Science & Complexity2020，33，5： | 0 |
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