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| 1 | A Hybrid Quantum Inspired Particle Swarm Optimization and Least Square Framework for Real-time Harmonic Estimation显示文摘The power quality is becoming an extensively addressing aspect of the power system because of the sensitive operation of the smart grid, awareness of power quality, and the equipment of modern power systems. In this paper, we have conceived a new hybrid Quantum inspired particle swarm optimization and least square(QPSO-LS) framework for real-time estimation of harmonics presented in time-varying noisy power signals. The technique has strong, robust, and reliable search capability with powerful convergence properties. The proposed approach is applied to various test systems at different signal to noise ratio(SNR) levels in the presence of uniform and Gaussian noise. The results are presented in terms of precision, computation time, and convergence characteristics. The computation time decreases by 3-5 times as compared to the existing algorithms. The technique is further authenticated by estimating harmonics of real-time current or voltage waveforms, obtained from light emitting diode(LED) lamp and axial flux permanent magnet synchronous generator(AFPMSG). The results demonstrate the superiority of QPSO-LS over other methods such as LS-based genetic algorithm(GA), particle swarm optimization(PSO), bacterial foraging optimization(BFO), artificial bee colony(ABC), and biogeography based optimization with recursive LS(BBO-RLS) algorithms, in terms of providing satisfactory solutions with a significant amount of robustness and computation efficiency. | Abu Bakar Waqas Muhammad Mansoor Ashraf Yasir Saifullah | 2021 | Journal of Modern Power Systems and Clean Energy2021，9，6： | 3 |
| 2 | Coupling the k-nearest neighbor procedure with the Kalman filter for real-time updating of the hydraulic model in flood forecasting显示文摘The Kalman filter(KF) updating method has been widely used as an efficient measure to assimilate realtime hydrological variables for reducing forecast uncertainty and providing improved forecasts.However,the accuracy of the KF relies much on the estimates of the state transition matrix and is limited due to the errors inherit from parameters and variables of the flood forecasting models.A new real-time updating approach(named KN^2K) is produced by coupling the k-nearest neighbor(KNN) procedure with the KF for flood forecasting models.The nonparametric KNN algorithm,which can be utilized to predict the response of a system on the basis of the k most representative predictors,is still efficient when the descriptions for input-output mapping are insufficient.In this study,the KNN procedure is used to provide more accurate estimates of the state transition matrix to extend the applicability of the KF.The updating performance of KN^2K is investigated in the middle reach of the Huai River based on a onedimensional hydraulic model with the lead times ranging from 2 to 12 h.The forecasts from the KN^2K< are compared with the observations,the original forecasts and the KF-updated forecasts.The results indicate that the KN^2K method,with the Nash-Sutcliffe efficiency larger than 0.85 in the 12-h-ahead forecasts,has a significant advantage in accuracy and robustness compared to the KF method.It is demonstrated that improved updating results can be obtained through the use of KNN procedure.The tests show that the KN^2K method can be used as an effective tool for real-time flood forecasting. | Kailei Liu Zhijia Li Cheng Yao Ji Chen Ke Zhang Muhammad Saifullah | 2016 | International Journal of Sediment Research2016，31，2： | 3 |
| 3 | Assessment of Genetic Variation Within Indian Mustard (Brassica juncea) Germplasm Using Random Amplified Polymorphic DNA Markers显示文摘Genetic diversity among 45 Indian mustard (Brassica juncea L.) genotypes comprising 37 germplasm collections, five advance breeding lines and three improved cultivars was investigated at the DNA level using the random amplified polymorphic DNA (RAPD) technique. Fifteen primers used generated a total of 92 RAPD fragments, of which 81 (88%) were polymorphic. Of these, 13 were unique to accession 'Pak85559'. Each primer produced four to nine amplified products with an average of 6.13 bands per primer. Based on pairwise comparisons of RAPD amplification products, Nei and Li's similarity coefficients were calculated to evaluate the relationships among the accessions. Pairwise similarity indices were higher among the oilseed accessions and cultivars showing narrow ranges of 0.77-0.99. An unweighted pair-group method with arithmetic averages cluster analysis based on these genetic similarities placed most of the collections and oilseed cultivars close to each other, showing a low level of polymorphism between the accessions used. However, the clusters formed by oilseed collections and cultivars were comparatively distinct from that of advanced breeding lines. Genetically, all of the accessions were classified into a few major groups and a number of individual accessions. Advanced breeding lines were relatively divergent from the rest of the accessions and formed independent clusters. Clustering of the accessions did not show any pattern of association between the RAPD markers and the collection sites. A low level of genetic variability of oilseed mustard was attributed to the selection for similar traits and horticultural uses. Perhaps close parentage of these accessions further contributed towards their little diversity. The study demonstrated that RAPD is a simple and fast technique to compare the genetic relationship and pattern of variation among the gene pool of this crop. | Muhammad Ayub Khan Malik Ashiq Rabbani Muhammad Munir Saifullah Khan Ajmal Muhammad Azim Malik | 2008 | Journal of Integrative Plant Biology2008，50，4： | 2 |
| 4 | In vivo laxative, anti-diarrheal, hepatoprotective and diuretic investigations of Sterculia diversifolia and its isolated compounds显示文摘OBJECTIVE:To investigated the laxative,anti-diarrheal,hepatoprotective and diuretic activity of Sterculia diversifolia and its isolated compounds.METHODS:The laxative activity was studied by counting wet stools while anti-diarrheal activity was performed by measuring gastrointestinal tract motility.Hepatoprotective activity was studied by biochemical and histo-pathological analysis while diuretic activity was performed by urine collection protocol.RESULTS:Doses of 30 and 100 mg/kg of crude methanolic extract of Sterculia diversifolia(MESD)stem bark and leaves,significantly(P<0.05,P<0.01)produced wet feces in subjects pretreated with atropine while 8-hydroxyquercetin and dihydroquercetin showed highly significant(P<0.001)results by increasing fecal weight and water contents without producing diarrhea.MESD stem bark and leaves also dose-dependently lowered diar-rhea while 8-hydroxyquercetin and dihydroquercetin showed highly significant(P<0.001)results by producing shaped stools in mice.MESD,8-hydroxyquercetin and dihydroquercetin offered significant protection against histopathological changes in the liver.Diuretic activity of Crude MESD stem bark and leaves extracts shows highly significant diuretic effect while dihydroquercetin showed better results than 8-hydroxyquercetin.CONCLUSION:It is concluded that Sterculia diversifolia and its isolated compounds bears laxative,anti-diarrheal,hepatoprotective and diuretic effects. | Fazle Rabbi Amir Zada Amna Nisar Muhammad Sohail Saifullah Khan Khalil Abid Ali Ahmad | 2021 | Journal of Traditional Chinese Medicine2021，41，5： | 2 |
| 5 | Addition of organic and inorganic P sources to soil – Effects on P pools and microorganisms显示文摘 | Muhammad Asghar Malik Petra Marschner Khalid Saifullah Khan | 2012 | Soil Biology and Biochemistry2012，，： | 1 |
| 6 | Evaluation of cotton germplasm for morphological and biochemical host plant UPdates resistance traits against sucking insect pests complex显示文摘Background:Sucking insect pests cause severe damage to cotton crop production.The development of insect resistant cotton cultivars is one of the most effective measures in curtailing the yield losses.Considering the role of morphological and biochemical host plant resista nee(HPR)traits in plant defense,12 cotton genotypes/varieties were evaluated for leaf area,leaf glanding,total soluble sugars,total soluble proteins,total phenolics,tannin and total flavonoids against fluctuating populations of whitefly,thrips and jassid under field conditions.Results:The population of these insects fluctuated during the growing seas on and remained above threshold level(whitefly>5,thrips>(8-10)f or jassid>1 per leaf)during late June and early July.Strong and negative association of whitefly(r=-0.825)and jassid(r=-0.929)with seed cotton yield was observed.Mean population of insects were the highest in Glandless-1 followed by NIA-82 and NIA-M30.NIAB-Kiran followed by NI AB-878 and Sadori were the most resistant,with the mean population of 1.41,1.60,1.66(whitefly);2.24,232,2.53(thrips)and 037,0.31,036(jassid),respectively.The resistant variety NIAB-Kiran showed less soluble sugars(8.54 mg.g^(-1)),soluble proteins(27.11 mg.g^(-1))and more phenolic(36.56 mg.g^(-1))and flavonoids(13.10mg.g^(-1))as compared with the susceptible check Glandless-1.Moreover,all insect populations were positively correlated with total soluble sugars and proteins.Whitefly populations exhibited negative response to leaf gossypol glands,total phenolics,tannins and flavonoids.The thrips and jassid populations had a significant and negative correlation with these four biochemical HPR traits.Conclusion:The ide ntified resistant resources and HPR traits can be deployed against sucking in sect pests'complex in future breeding programs of developing insect resistant cotton varieties. | RIZWAN Muhammad ABRO Saifullah ASIF Muhammad Usman HAMEED Amjad MAH BOOB Wajid DEHO Zaheer Ahmed SIAL Mahboob Ali | 2021 | Journal of Cotton Research2021，4，3： | 0 |
| 7 | Optimal Parameter Estimation of Transmission Line Using Chaotic Initialized Time-Varying PSO Algorithm显示文摘Transmission line is a vital part of the power system that connects two major points,the generation,and the distribution.For an efficient design,stable control,and steady operation of the power system,adequate knowledge of the transmission line parameters resistance,inductance,capacitance,and conductance is of great importance.These parameters are essential for transmission network expansion planning in which a new parallel line is needed to be installed due to increased load demand or the overhead line is replaced with an underground cable.This paper presents a method to optimally estimate the parameters using the input-output quantities i.e.,voltages,currents,and power factor of the transmission line.The equivalentπ-network model is used and the terminal data i.e.,sending-end and receiving-end quantities are assumed as available measured data.The parameter estimation problem is converted to an optimization problem by formulating an error-minimizing objective function.An improved particle swarm optimization(PSO)in terms of time-varying control parameters and chaos-based initialization is used to optimally estimate the line parameters.Two cases are considered for parameter estimation,the first case is when the line conductance is neglected and in the second case,the conductance is considered into account.The results obtained by the improved algorithm are compared with the standard version of the algorithm,firefly algorithm and artificial bee colony algorithm for 30 number of trials.It is concluded that the improved algorithm is tremendously sufficient in estimating the line parameters in both cases validated by low error values and statistical analysis,comparatively. | Abdullah Shoukat Muhammad Ali Mughal Saifullah Younus Gondal Farhana Umer Tahir Ejaz Ashiq Hussain | 2022 | Computers, Materials & Continua2022，，4： | 0 |
| 8 | Diagnosis and Recommendation Integrated System Assessment of the Nutrients Limiting and Nutritional Status of Tomato显示文摘Tomato is an important field crop,and nutritional imbalances frequently reduce its yield.Diagnosis and Recommendation Integrated System(DRIS),uses ratios for nutrient deficiency diagnosis instead of absolute concentration in plant tests.In this study,local DRIS norms for the field tomatoes were established and the nutrient(s)limiting tomatoes yield were determined.Tomato leaves were analyzed for nutrients,to identify nutritional status using the DRIS approach.One hundred tomatoes fields were selected from Chatter Plain Khyber Pakhtunkhwa and the Sheikupura Punjab Pakistan.The first fully matured leaf was sampled,rinsed,dried and ground for analyzing P,K,Ca,Mg,Cu,Fe,Mn and Zn using an Inductively Coupled Plasma Atomic Emission Spectrophotometer(ICP AES).Plant tissue N and S were measured by the combustion method.The tomatoes yields were recorded at each location.The data were divided into high-yielding(≥3.79 kg/10 plant)and low-yielding(<3.79 kg/10 plant)populations and norms were computed using standard DRIS procedures.High-yielding plant population had a statistically greater mean S and Fe than the low-yielding population.The average balance index,the sum of functions,for S and Fe were−11.04 and−5.17 which reflected deficiency of S and Fe.Plant nutrients norms established may optimize plant nutrition in field tomatoes for high yield. | Rabia Manzoor Mohammad Saleem Akhtar Khalid Saifullah Khan Taqi Raza Muhammad Ishaq Asif Rehmani Carl Rosen Muhammad Khalil ur Rehman Nahla Zidan Fahad MAlzuaibr Nisreen MAbdulsalam Najla AKhateeb Majid Alhomrani Abdulhakeem SAlamri Javeed Ahmad Lone Muhammad Ammar Raza Ayman El Sabagh | 2022 | Phyton-International Journal of Experimental Botany2022，91，12： | 0 |
| 9 | Push-Based Content Dissemination and Machine Learning-Oriented Illusion Attack Detection in Vehicular Named Data Networking显示文摘Recent advancements in the Vehicular Ad-hoc Network(VANET)have tremendously addressed road-related challenges.Specifically,Named Data Networking(NDN)in VANET has emerged as a vital technology due to its outstanding features.However,the NDN communication framework fails to address two important issues.The current NDN employs a pull-based content retrieval network,which is inefficient in disseminating crucial content in Vehicular Named Data Networking(VNDN).Additionally,VNDN is vulnerable to illusion attackers due to the administrative-less network of autonomous vehicles.Although various solutions have been proposed for detecting vehicles’behavior,they inadequately addressed the challenges specific to VNDN.To deal with these two issues,we propose a novel push-based crucial content dissemination scheme that extends the scope of VNDN from pullbased content retrieval to a push-based content forwarding mechanism.In addition,we exploitMachine Learning(ML)techniques within VNDN to detect the behavior of vehicles and classify them as attackers or legitimate.We trained and tested our system on the publicly accessible dataset Vehicular Reference Misbehavior(VeReMi).We employed fiveML classification algorithms and constructed the bestmodel for illusion attack detection.Our results indicate that RandomForest(RF)achieved excellent accuracy in detecting all illusion attack types in VeReMi,with an accuracy rate of 100%for type 1 and type 2,96%for type 4 and type 16,and 95%for type 8.Thus,RF can effectively evaluate the behavior of vehicles and identify attacker vehicles with high accuracy.The ultimate goal of our research is to improve content exchange and secureVNDNfromattackers.Thus,ourML-based attack detection and preventionmechanismensures trustworthy content dissemination and prevents attacker vehicles from sharing misleading information in VNDN. | Arif Hussain Magsi Ghulam Muhammad Sajida Karim Saifullah Memon Zulfiqar Ali | 2023 | Computers, Materials & Continua2023，76，9： | 0 |
| 10 | Adaptive state estimation of groundwater contaminant boundary input flux in a 2-dimensional aquifer显示文摘In many circumstances involving heat and mass transfer issues,it is considered impractical to measure the input flux and the resulting state distribution in the domain.Therefore,the need to develop techniques to provide solutions for such problems and estimate the inverse mass flux becomes imperative.Adaptive state estimator(ASE)is increasingly becoming a popular inverse estimation technique which resolves inverse problems by incorporating the semi-Markovian concept into a Bayesian estimation technique,thereby developing an inverse input and state estimator consisting of a bank of parallel adaptively weighted Kalman filters.The ASE is particularly designed for a system that encompasses independent unknowns and/or random switching of input and measurement biases.The present study describes the scheme to estimate the groundwater input contaminant flux and its transient distribution in a conjectural two-dimensional aquifer by means of ASE,which in particular is because of its unique ability to efficiently handle the process noise giving an estimation of keeping the relative error range within 10%in 2-dimensional problems.Numerical simulation results show that the proposed estimator presents decent estimation performance for both smoothly and abruptly varying input flux scenarios.Results also show that ASE enjoys a better estimation performance than its competitor,Recursive Least Square Estimator(RLSE)due to its larger error tolerance in greater process noise regimes.ASE's inherent deficiency of being slower than the RLSE,resulting from the complexity of algorithm,was also noticed.The chosen input scenarios are tested to calculate the effect of input area and both estimators show improved results with an increase in input flux area especially as sensors are moved closer to the assumed input location. | Muhammad Malik Nauman Murtuza Mehdi Asif Iqbal Muhammad Saifullah Abu Bakar Brahim Aissa Dk Nur Afiqah Jalwati Puteri Amer Farhan Rafique | 2019 | Journal of Groundwater Science and Engineering2019，7，4： | 0 |
| 11 | Author’s Age and Gender Prediction on Hotel Review Using Machine Learning Techniques显示文摘Author’s Profile(AP)may only be displayed as an article,similar to text collection of material,and must differentiate between gender,age,education,occupation,local language,and relative personality traits.In several informationrelated fields,including security,forensics,and marketing,and medicine,AP prediction is a significant issue.For instance,it is important to comprehend who wrote the harassing communication.In essence,from a marketing perspective,businesses will get to know one another through examining items and websites on the internet.Accordingly,they will direct their efforts towards a certain gender or age restriction based on the kind of individuals who comment on their products.Recently many approaches have been presented many techniques to automatically detect user age and gender from the language which is based on text,documents,or comments on social media.The purpose of this research is to classify age(18–24,25–34,35–49,50–64,and 65–70)and gender(male,female)from a PAN 2014 Hotel Reviews dataset of the English language.The usage of six machine learning models is the main emphasis of this work,including the methods of Support Vector Machine(SVM),Random Forest(RF),Naive Bayes(NB),Logistic Regression(LR),Decision Tree(DT)and K-Nearest Neighbors(KNN). | Muhammad Hood Khan Bilal Khan Saifullah Jan Muhammad Imran Chughtai | 2023 | Journal on Big Data2023，5，1： | 0 |
| 12 | Concept of Yager operators with the picture fuzzy set environment and its application to emergency program selection显示文摘Purpose-The aim of this study as to find out an approach for emergency program selection.Design/methodology/approach-The authors have generated six aggregation operators(AOs),namely picture fuzzy Yager weighted average(PFYWA),picture fuzzy Yager ordered weighted average,picture fuzzy Yager hybrid weighted average,picture fuzzy Yager weighted geometric(PFYWG),picture fuzzy Yager ordered weighted geometric and picture fuzzy Yager hybrid weighted geometric aggregations operators.Findings-First of all,the authors defined the score and accuracy function for picture fuzzy set(FS),and some fundamental operational laws for picture FS using the Yager aggregation operation.After that,using the developed operational laws,developed some AOs,namely PFYWA,picture fuzzy Yager ordered weighted average,picture fuzzy Yager hybrid weighted average,PFYWG,picture fuzzy Yager ordered weighted geometric and picture fuzzy Yager hybrid weighted geometric aggregations operators,have been proposed along with their desirable properties.A decision-making(DM)approach based on these operators has also been presented.An illustrative example has been given for demonstrating the approach.Finally,discussed the comparison of the proposed method with the other existing methods and write the conclusion of the article.Originality/value-To find the best alternative for emergency program selection. | Muhammad Qiyas Muhammad Ali Khan Saifullah Khan Saleem Abdullah | 2020 | International Journal of Intelligent Computing and Cybernetics2020，13，4： | 0 |
| 13 | 太阳能集热器强化传热技术的局限性与挑战显示文摘目前,太阳能集热器在可再生能源领域发挥着至关重要的作用,这在核心能源专家和研究界得到了广泛的认可。由于这种太阳能收集技术的高能量转换率,迫切需要评价方法,以期改善传热过程。前期研究人员主要致力于工作流体的增强上,而忽略了其他同样有助于增强太阳能集热器传热过程的技术,这使得其他方向的研究逐渐过时了。本研究的主要目的是提供最新的进展和方法,以加强太阳能集热器的传热过程的最新概述。研究了传统技术和创新技术,探讨了它们在提高热性能和整体系统效率方面的有效性。对太阳能集热器强化传热技术的最新研究进行了全面的文献综述。确定了主要挑战、知识差距和局限性,并推荐了潜在的未来研究方案。这篇全面的综述将作为研究人员和主要能源参与者的指南,为太阳能集热器领域提供参考的研究方向。 | Lukman Ahmed OMEIZA Muhammad ABID Yathavan SUBRAMANIAN Anitha DHANASEKARAN MdMosfiqur RAHMAN Saifullah Abu BAKAR Kateryna KOZAK Ukashat MAMUDU Abul Kalam AZAD | 2023 | Journal of Central South University2023，30，11： | 0 |
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