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| 1 | Interventions for improvement in unsafe injection practices in Pakistan显示文摘 | Khabir Ahmad Naveed Zafar Janjua Hasan Bin Hamza Mohammad Imran Khan Syed Ahsan Raza | 2005 | International Journal of Infectious Diseases2005，，4： | 1 |
| 2 | Distortion-product otoacoustic emissions in nonacoustic tumors of the cerebellopontine angle显示文摘 | Mobley SR Odabasi Onur Ahsan Syed | 2002 | Otolaryngol Head Neck Surg2002，126，： | 1 |
| 3 | Two phase relative permeabilities for gas and water in selected European coals显示文摘 | Sevket Durucan Mustafa Ahsan Ji-Quan Shi Amer Syed Anna Korre | 2014 | Fuel2014，，： | 1 |
| 4 | Intestinal ascariasis: the commonest cause of bowel obstruction in children at a tertiary care center in Kashmir显示文摘 | Aejaz Ahsan Baba Syed Mudasir Ahmad Khursheed Ahmad Sheikh | 2009 | Pediatric Surgery International2009，，12： | 1 |
| 5 | Wound management and restrictive arm movement following cardiac device implantation evidence for practice显示文摘 | Bavnbek K Ahsan SY Sandem J | 2010 | Eur J Cardiovasc Nuts2010，9，2： | 1 |
| 6 | Epidemiology and prevention of hepatocellular carcinoma显示文摘 | Silvia Franceschi Syed Ahsan Raza | 2008 | Cancer Letters2008，，1： | 1 |
| 7 | Impact of petroleum and non-petroleum indices on financial development in Oman显示文摘This study analyzes the impact of petroleum and non-petroleum indices on the financial development of the Sultanate of Oman from 1978 to 2017.To this end,it uses the petroleum proxy of oil rents(%of gross domestic product,GDP)and the non-petroleum proxy of industry(including construction)value added(%of GDP);agriculture,forestry,and fishing value added(%of GDP);and services value added(%of GDP)to determine the effect on financial development,measured by the amount of domestic credit extended to the private sector by banks(%of GDP).It applies an autoregressive distributed lag(ARDL)model.The long-term equation illustrates that the agriculture and industry GDPs have a negative and significant relationship with domestic credit in Oman.However,the oil and service sector GDPs promote financial development.The short-term equation illustrates that the oil,agricultural,and service sectors have positive and significant effects on domestic credit.The conclusion is that the economy of Oman is still in the first phase of economic diversification.Accordingly,the government should use oil revenues to develop various non-oil industrial sectors.This would enhance the country’s competitiveness in the global economy and positively contribute to improving the liquidity of the banking sector for stimulating credit at the macroeconomic level. | Faris Nasif Alshubiri Omar Ikbal Tawfik Syed Ahsan Jamil | 2020 | Financial Innovation2020，6，1： | 1 |
| 8 | Wound management and restrictive arm movement following cardiac device implantation-evi dence for practice? 显示文摘 | Bavnbek K Ahsan SY | 2010 | European Journal of Cardiovascular Nursing2010，9，2： | 1 |
| 9 | A Level与中国高中化学新课程标准之比较研究显示文摘本文将英体系下的A Level课程中化学课程目标,课程内容以及课程评价等几方面和国内目前的高中新课标进行对比研究,找出其设置特点,以期对我国新课程化学课程教学研究提供借鉴和启示。 | 马艳芝 Syed Mozammil Ahsan | 2008 | 化学教学2008，，10： | 1 |
| 10 | Impact of Fractures and Diagenesis on Reservoir Potential of Inner Ramp Paleocene Carbonates Exposed in Western Part of the Lesser Himalayas of Pakistan显示文摘The outcrop investigations provide a better comprehension to interrelate facies-diagenesis and fracture networks for the evaluation of reservoir potential of the carbonate rocks.In this paper,we targeted Kahi-Section(Nizampur Basin)and Peeran Tangai-Section(Kalachitta Range)to analyze structural-kinematics,Discrete Fracture Network Modelling,microfacies identification and diagenesis to interpret their impact on reservoir potential of Lockhart Limestone(Paleocene).The structural grain within the study area mostly represents the typical east-west trending tight to overturned folds and north-dipping thrust faults that mimic the north-south Indo-Eurasian collision.However,a second phase of deformation related to east-west compressions also identified which rotated the axes of preexisting structures.Fracture analysis revealed that extensional fractures are oriented at high angle to bedding and are differentiated into three orthogonal sets trending northeast-southwest,northwest-southeast and east-west,whereas,the shear fractures formed two conjugate sets trending northeastsouthwest.The Lockhart Limestone was deposited in the inner ramp setting and microfacies types are packstone,wackestone and wacke-packstone with seven sub-microfacies types.It has been identified that the Lockhart Limestone has the heterogeneous distribution of diagenetic and tectonic features throughout its extent.The observed diagenetic sequence is micritization,calcite cementation,dissolution,neomorphism,pyritization and compaction.The results highlight that open and partially filled fractures may provide an interconnected network to promote fluid mobility,leading to higher values of fracture permeability.The porosity values of the pore matrix were greater than fracture,resulting a significant impact on reservoir storage capacity.In contrast,a negative impact on reservoir potential has been shown by stylolites,veins and dissolution seams.However,based on the overall studies,the Lockhart Limestone revealed the prospect of a good reservoir unit in the study area. | Waleed Tariq Gohar Rehman Syed Ahsan Hussain Gardezi Nawaz Ikram | 2023 | Journal of Earth Science2023，34，2： | 0 |
| 11 | Robust Length of Stay Prediction Model for Indoor Patients显示文摘Due to unforeseen climate change,complicated chronic diseases,and mutation of viruses’hospital administration’s top challenge is to know about the Length of stay(LOS)of different diseased patients in the hospitals.Hospital management does not exactly know when the existing patient leaves the hospital;this information could be crucial for hospital management.It could allow them to take more patients for admission.As a result,hospitals face many problems managing available resources and new patients in getting entries for their prompt treatment.Therefore,a robust model needs to be designed to help hospital administration predict patients’LOS to resolve these issues.For this purpose,a very large-sized data(more than 2.3 million patients’data)related to New-York Hospitals patients and containing information about a wide range of diseases including Bone-Marrow,Tuberculosis,Intestinal Transplant,Mental illness,Leukaemia,Spinal cord injury,Trauma,Rehabilitation,Kidney and Alcoholic Patients,HIV Patients,Malignant Breast disorder,Asthma,Respiratory distress syndrome,etc.have been analyzed to predict the LOS.We selected six Machine learning(ML)models named:Multiple linear regression(MLR),Lasso regression(LR),Ridge regression(RR),Decision tree regression(DTR),Extreme gradient boosting regression(XGBR),and Random Forest regression(RFR).The selected models’predictive performance was checked using R square andMean square error(MSE)as the performance evaluation criteria.Our results revealed the superior predictive performance of the RFRmodel,both in terms of RS score(92%)and MSE score(5),among all selected models.By Exploratory data analysis(EDA),we conclude that maximumstay was between 0 to 5 days with the meantime of each patient 5.3 days and more than 50 years old patients spent more days in the hospital.Based on the average LOS,results revealed that the patients with diagnoses related to birth complications spent more days in the hospital than other diseases.This finding could help predict the future length of hospital stay of new patients,which will help the hospital administration estimate and manage their resources efficiently. | Ayesha Siddiqa Syed Abbas Zilqurnain Naqvi Muhammad Ahsan Allah Ditta Hani Alquhayz M.A.Khan Muhammad Adnan Khan | 2022 | Computers, Materials & Continua2022，，3： | 0 |
| 12 | Explainable Artificial Intelligence Solution for Online Retail显示文摘Artificial intelligence(AI)and machine learning(ML)help in making predictions and businesses to make key decisions that are beneficial for them.In the case of the online shopping business,it’s very important to find trends in the data and get knowledge of features that helps drive the success of the business.In this research,a dataset of 12,330 records of customers has been analyzedwho visited an online shoppingwebsite over a period of one year.The main objective of this research is to find features that are relevant in terms of correctly predicting the purchasing decisions made by visiting customers and build ML models which could make correct predictions on unseen data in the future.The permutation feature importance approach has been used to get the importance of features according to the output variable(Revenue).Five ML models i.e.,decision tree(DT),random forest(RF),extra tree(ET)classifier,Neural networks(NN),and Logistic regression(LR)have been used to make predictions on the unseen data in the future.The performance of each model has been discussed in detail using performance measurement techniques such as accuracy score,precision,recall,F1 score,and ROC-AUC curve.RF model is the bestmodel among all five chosen based on accuracy score of 90%and F1 score of 79%followed by extra tree classifier.Hence,our study indicates that RF model can be used by online retailing businesses for predicting consumer buying behaviour.Our research also reveals the importance of page value as a key feature for capturing online purchasing trends.This may give a clue to future businesses who can focus on this specific feature and can find key factors behind page value success which in turn will help the online shopping business. | Kumail Javaid Ayesha Siddiqa Syed Abbas Zilqurnain Naqvi Allah Ditta Muhammad Ahsan M.A.Khan Tariq Mahmood Muhammad Adnan Khan | 2022 | Computers, Materials & Continua2022，，6： | 0 |
| 13 | Enhancing Collaborative and Geometric Multi-Kernel Learning Using Deep Neural Network显示文摘This research proposes a method called enhanced collaborative andgeometric multi-kernel learning (E-CGMKL) that can enhance the CGMKLalgorithm which deals with multi-class classification problems with non-lineardata distributions. CGMKL combines multiple kernel learning with softmaxfunction using the framework of multi empirical kernel learning (MEKL) inwhich empirical kernel mapping (EKM) provides explicit feature constructionin the high dimensional kernel space. CGMKL ensures the consistent outputof samples across kernel spaces and minimizes the within-class distance tohighlight geometric features of multiple classes. However, the kernels constructed by CGMKL do not have any explicit relationship among them andtry to construct high dimensional feature representations independently fromeach other. This could be disadvantageous for learning on datasets with complex hidden structures. To overcome this limitation, E-CGMKL constructskernel spaces from hidden layers of trained deep neural networks (DNN).Due to the nature of the DNN architecture, these kernel spaces not onlyprovide multiple feature representations but also inherit the compositionalhierarchy of the hidden layers, which might be beneficial for enhancing thepredictive performance of the CGMKL algorithm on complex data withnatural hierarchical structures, for example, image data. Furthermore, ourproposed scheme handles image data by constructing kernel spaces from aconvolutional neural network (CNN). Considering the effectiveness of CNNarchitecture on image data, these kernel spaces provide a major advantageover the CGMKL algorithm which does not exploit the CNN architecture forconstructing kernel spaces from image data. Additionally, outputs of hiddenlayers directly provide features for kernel spaces and unlike CGMKL, do notrequire an approximate MEKL framework. E-CGMKL combines the consistency and geometry preserving aspects of CGMKL with the compositionalhierarchy of kernel spaces extracted from DNN hidden layers to enhance the predictive performance of CGMKL significantly. The experimental results onvarious data sets demonstrate the superior performance of the E-CGMKLalgorithm compared to other competing methods including the benchmarkCGMKL. | Bareera Zafar Syed Abbas Zilqurnain Naqvi Muhammad Ahsan Allah Ditta Ummul Baneen Muhammad Adnan Khan | 2022 | Computers, Materials & Continua2022，，9： | 0 |
| 14 | Empirical Thermal Investigation of Oil-Immersed Distribution Transformer under Various Loading Conditions显示文摘The distribution transformer is the mainstay of the power system.Its internal temperature study is desirable for its safe operation in the power system.The purpose of the present study is to determine direct comprehensive thermal distribution in the distribution transformers for different loading conditions.To achieve this goal,the temperature distribution in the oil,core,and windings are studied at each loading.An experimental study is performed with a 10/0.38 kV,10 kVA oil–immersed transformer equipped with forty–two PT100 sensors(PTs)for temperature measurement installed inside during its manufacturing process.All possible locations for the hottest spot temperature(HST)are considered that made by finite element analysis(FEA)simulation and losses calculations.A resistive load is made to achieve 80%to 120%loading of the test transformer for this experiment.Working temperature is measured in each part of the transformer at all provided loading conditions.It is observed that temperature varies with loading throughout the transformer,and a detailed map of temperature is obtained in the whole test transformer.From these results,the HST stays in the critical section of the primary winding at all loading conditions.This work is helpful to understand the complete internal temperature layout and the location of the HST in distribution transformers. | Syed Ali Raza Ahsan Ullah Shuang He Yifeng Wang Jiangtao Li | 2021 | Computer Modeling in Engineering & Sciences2021，，11： | 0 |
| 15 | An Efficient Impersonation Attack Detection Method in Fog Computing显示文摘Fog computing paradigm extends computing,communication,storage,and network resources to the network’s edge.As the fog layer is located between cloud and end-users,it can provide more convenience and timely services to end-users.However,in fog computing(FC),attackers can behave as real fog nodes or end-users to provide malicious services in the network.The attacker acts as an impersonator to impersonate other legitimate users.Therefore,in this work,we present a detection technique to secure the FC environment.First,we model a physical layer key generation based on wireless channel characteristics.To generate the secret keys between the legitimate users and avoid impersonators,we then consider a Double Sarsa technique to identify the impersonators at the receiver end.We compare our proposed Double Sarsa technique with the other two methods to validate our work,i.e.,Sarsa and Q-learning.The simulation results demonstrate that the method based on Double Sarsa outperforms Sarsa and Q-learning approaches in terms of false alarm rate(FAR),miss detection rate(MDR),and average error rate(AER). | Jialin Wan Muhammad Waqas Shanshan Tu Syed Mudassir Hussain Ahsan Shah Sadaqat Ur Rehman Muhammad Hanif | 2021 | Computers, Materials & Continua2021，，7： | 0 |
| 16 | It is 2015: What are the best diagnostic and treatment options for Ménière's disease?显示文摘Ménière's disease(MD) is a common cause of recurrent vertigo. Its pathophysiology is still unclear and controversial. The most common histological finding in postmortem temporal bone studies of patients is endolymphatic hydrops(EH). However, not all cases of hydrops are associated with MD and it may represent the end point of various etiologies. The diagnostic criteria for MD have undergone changes during the past few decades. A recent collaboration among specialty societies in United States, Europe and Japan has given rise to a new set of guidelines for the diagnosis and classification of MD. The aim is to develop international consensus criteria for MD that would help improve the quality of data collected from patients. The diagnosis of MD can be difficult in some cases as there is no gold standard for testing. Previous use of audiometric data and electrocochleography are poorly sensitive as screening tools. Recently magnetic resonance imaging as a diagnostic tool for identifying EH has gained popularity in Asia and Europe. Vestibular evoked myogenic potentials are also used but lack specificity. Finally, the treatment for MD has improved with the introduction of intratympanic treatments with steroids and gentamicin as well as less invasive treatment with the Meniett device. | Safeer Shah Abel Ignatius Syed Ahsan | 2016 | World Journal of Otorhinolaryngology2016，6，1： | 0 |
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