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Impact of Fractures and Diagenesis on Reservoir Potential of Inner Ramp Paleocene Carbonates Exposed in Western Part of the Lesser Himalayas of Pakistan

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Journal of Earth Science 2023年第2期34卷 536-555页

作者： Waleed Tariq Gohar Rehman syed ahsan hussain gardezi Nawaz Ikram National Center of Excellence in Geology University of PeshawarPeshawarKhyber Pakhtunkhwa 25120Pakistan Department of Geology University of PeshawarPeshawarKhyber Pakhtunkhwa 25120Pakistan Geological Survey of Pakistan Azad Jammu&Kashmir DirectorateMuzaffarabad 13100Pakistan Institute of Geology University of Azad Jammu&KashmirMuzaffarabad 13100Pakistan

The outcrop investigations provide a better comprehension to interrelate facies-diagenesis and fracture networks for the evaluation of reservoir potential of the carbonate *** 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 ***,a second phase of deformation related to east-west compressions also identified which rotated the axes of preexisting *** 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 *** Lockhart Limestone was deposited in the inner ramp setting and microfacies types are packstone,wackestone and wacke-packstone with seven sub-microfacies *** has been identified that the Lockhart Limestone has the heterogeneous distribution of diagenetic and tectonic features throughout its *** observed diagenetic sequence is micritization,calcite cementation,dissolution,neomorphism,pyritization and *** results highlight that open and partially filled fractures may provide an interconnected network to promote fluid mobility,leading to higher values of fracture *** porosity values of the pore matrix were greater than fracture,resulting a significant impact on reservoir storage *** contrast,a negative impact on reservoir potential has been shown by stylolites,veins and dissolution ***,based on the overall studies,the Lockhart Limestone reve

关键词： lockhart limestone discrete fracture network modelling facies-diagenesis reservoir potential Nizampur Basin petroleum geology

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Translation of English Language into Urdu Language Using LSTM Model

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Computers, Materials & Continua 2023年第2期74卷 3899-3912页

作者： Sajadul Hassan Kumhar syed Immamul Ansarullah Akber Abid gardezi Shafiq Ahmad Abdelaty Edrees Sayed Muhammad Shafiq SSSUTMS Sehore466001India Department of Computer Science GDC SumbalJ&K193502India Department of Computer Science COMSATS University IslamabadIslamabad45550Pakistan Industrial Engineering Department College of EngineeringKing Saud UniversityP.O.Box 800Riyadh11421Saudi Arabia Department of Information and Communication Engineering Yeungnam UniversityGyeongsan38541Korea

English to Urdu machine translation is still in its beginning and lacks simple translation methods to provide motivating and adequate English to Urdu *** order tomake knowledge available to the masses,there should be mechanisms and tools in place to make things understandable by translating from source language to target language in an automated *** translation has achieved this goal with encouraging *** decoding the source text into the target language,the translator checks all the characteristics of the *** achieve machine translation,rule-based,computational,hybrid and neural machine translation approaches have been proposed to automate the *** this research work,a neural machine translation approach is employed to translate English text into *** Short Term Short Model(LSTM)Encoder Decoder is used to translate English to *** various steps required to perform translation tasks include preprocessing,tokenization,grammar and sentence structure analysis,word embeddings,training data preparation,encoder-decoder models,and output text *** results show that the model used in the research work shows better performance in *** results were evaluated using bilingual research metrics and showed that the test and training data yielded the highest score sequences with an effective length of ten(10).

关键词： Machine translation Urdu language word embedding

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Reversible Watermarking Method with Low Distortion for the Secure Transmission of Medical Images

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Computer Modeling in Engineering & Sciences 2022年第3期130卷 1309-1324页

作者： Rizwan Taj Feng Tao Shahzada Khurram Ateeq Ur Rehman syed Kamran Haider Akber Abid gardezi Saima Kanwal School of Computer and Communication Lanzhou University of TechnologyLanzhouChina Faculty of Computing The Islamia University of BahawalpurBahawalpurPakistan Department of Electrical Engineering Government College UniversityLahorePakistan College of Internet of Things Engineering Hohai UniversityChangzhouChina Department of Computer Science COMSATS University IslamabadIslamabadPakistan

In telemedicine,the realization of reversible watermarking through information security is an emerging research ***,adding watermarks hinders the distribution of pixels in the cover image because it creates distortions(which lead to an increase in the detection probability).In this article,we introduce a reversible watermarking method that can transmit medical images with minimal distortion and high *** proposed method selects two adjacent gray pixels whose least significant bit(LSB)is different from the relevant message bit and then calculates the distortion *** use the LSB pairing method to embed the secret matrix of patient record into the cover image and exchange pixel *** results show that the designed method is robust to different attacks and has a high PSNR(peak signal-to-noise ratio)*** MRI image quality and imperceptibility are verified by embedding a secret matrix of up to 262,688 bits to achieve an average PSNR of 51.657 *** addition,the proposed algorithm is tested against the latest technology on standard images,and it is found that the average PSNR of our proposed reversible watermarking technology is higher(i.e.,51.71 dB).Numerical results show that the algorithm can be extended to normal images and medical images.

关键词： LSB reversible watermarking medical images security data distortion

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Analytical Hybrid Particle Swarm Optimization Algorithm for Optimal Siting and Sizing of Distributed Generation in Smart Grid

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Journal of Modern Power Systems and Clean Energy 2020年第6期8卷 1221-1230页

作者： syed Muhammad Arif Akhtar hussain Tek Tjing Lie syed Muhammad ahsan Hassan Abbas Khan the Department of Electrical and Electronic Engineering Auckland University of TechnologyAucklandNew Zealand the Department of Electrical Engineering Incheon National UniversityIncheonKorea the Department of Electrical Engineering Lahore University of Management SciencesLahorePakistan

In this paper,the hybridization of standard particle swarm optimisation(PSO)with the analytical method(2/3 rd rule)is proposed,which is called as analytical hybrid PSO(AHPSO)algorithm used for the optimal siting and sizing of distribution *** proposed AHPSO algorithm is implemented to cater for uniformly distributed,increasingly distributed,centrally distributed,and randomly distributed loads in conventional power *** demonstrate the effectiveness of the proposed algorithm,the convergence speed and optimization performances of standard PSO and the proposed AHPSO algorithms are compared for two *** the first case,the performances of both the algorithms are compared for four different load distributions via an IEEE 10-bus *** the second case,the performances of both the algorithms are compared for IEEE 10-bus,IEEE 33-bus,IEEE 69-bus systems,and a real distribution system of *** results show that the proposed AHPSO algorithm converges significantly faster than the standard *** results of the proposed algorithm are compared with those of an analytical algorithm,and the results of them are similar.

关键词： Siting and sizing of distributed generation distribution system hybrid algorithm loss minimization particle swarm optimization(PSO)

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Impediments of Cognitive System Engineering in Machine-Human Modeling

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Computers, Materials & Continua 2023年第3期74卷 6689-6701页

作者： Fayaz Ahmad Fayaz Arun Malik Isha Batra Akber Abid gardezi syed Immamul Ansarullah Shafiq Ahmad Mejdal Alqahtani Muhammad Shafiq National Institute of Electronics and Information Technology(NIELIT) J&K191132India Department of Computer Science&Engineering Lovely Professional University(LPU)Punjab144402India Department of Computer Science COMSATS University IslamabadIslamabad45550Pakistan Department of Computer Science Govt.Degree College Sumbal Kashmir193501India Industrial Engineering Department College of EngineeringKing Saud UniversityP.O.Box 800Riyadh11421Saudi Arabia Department of Information and Communication Engineering Yeungnam UniversityGyeongsan38541Korea

A comprehensive understanding of human intelligence is still an ongoing process,i.e.,human and information security are not yet perfectly *** understanding cognitive processes,designers can design humanized cognitive information systems(CIS).The need for this research is justified because today’s business decision makers are faced with questions they cannot answer in a given amount of time without the use of cognitive information *** researchers aim to better strengthen cognitive information systems with more pronounced cognitive thresholds by demonstrating the resilience of cognitive resonant frequencies to reveal possible responses to improve the efficiency of human-computer interaction(HCI).Apractice-oriented research approach included research analysis and a review of existing articles to pursue a comparative research model;thereafter,amodel development paradigm was used to observe and monitor the progression of CIS during *** scope of our research provides a broader perspective on how different disciplines affect HCI and how human cognitive models can be enhanced to enrich *** have identified a significant gap in the current literature on mental processing resulting from a wide range of theory and practice.

关键词： Cognitive-IoT human-computer interaction decision making

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Enhancing Collaborative and Geometric Multi-Kernel Learning Using Deep Neural Network

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Computers, Materials & Continua 2022年第9期72卷 5099-5116页

作者： Bareera Zafar syed Abbas Zilqurnain Naqvi Muhammad ahsan Allah Ditta Ummul Baneen Muhammad Adnan Khan Department of Mechatronics and Control Engineering University of Engineering and TechnologyLahore54890Pakistan Department of Information Sciences Division of Science and TechnologyUniversity of EducationLahore54000Pakistan Riphah School of Computing&Innovation Faculty of ComputingRiphah International UniversityLahore CampusLahore54000Pakistan Department Software Gachon UniversitySeongnam13120Korea

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 hidde

关键词： CGMKL multi-class classification deep neural network multiplekernel learning hierarchical kernel spaces

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Ontology-Based News Linking for Semantic Temporal Queries

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Computers, Materials & Continua 2023年第2期74卷 3913-3929页

作者： Muhammad Islam Satti Jawad Ahmed Hafiz syed Muhammad Muslim Akber Abid gardezi Shafiq Ahmad Abdelaty Edrees Sayed Salman Naseer Muhammad Shafiq Faculty of Computing Riphah International UniversityI-14 CampusIslamabad44000Pakistan Department of Computer Science Zabsolutions SZABISTIslamabadPakistan Department of Computer Science COMSATS University IslamabadIslamabad45550Pakistan Industrial Engineering Department College of EngineeringKing Saud UniversityP.O.Box 800Riyadh11421Saudi Arabia Department of Information Technology University of the Punjab Gujranwala CampusGujranwala52250Pakistan Department of Information and Communication Engineering Yeungnam UniversityGyeongsan38541Korea

Daily newspapers publish a tremendous amount of information disseminated through the *** available and easily accessible large online repositories are not indexed and are in an un-processable *** major hindrance in developing and evaluating existing/new monolingual text in an image is that it is not linked and *** is no method to reuse the online news images because of the unavailability of standardized benchmark corpora,especially for South Asian *** corpus is a vital resource for developing and evaluating text in an image to reuse local news systems in general and specifically for the Urdu *** of indexing,primarily semantic indexing of the daily news items,makes news items impracticable for any ***,the most straightforward search facility does not support these unindexed news *** study addresses this gap by associating and marking the newspaper images with one of the widely spoken but under-resourced languages,i.e.,*** present work proposed a method to build a benchmark corpus of news in image form by introducing a web *** corpus is then semantically linked and annotated with daily news *** techniques are proposed for image annotation,free annotation and fixed cross examination *** second technique got higher *** news ontology in protégéusing OntologyWeb Language(OWL)language and indexed the annotations under *** application is also built and linked with protégéso that the readers and journalists have an interface to query the news items ***,news items linked together will provide complete coverage and bring together different opinions at a single location for readers to do the analysis themselves.

关键词： Annotations corpus information retrieval semantic ontology

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Robust Length of Stay Prediction Model for Indoor Patients

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Computers, Materials & Continua 2022年第3期70卷 5519-5536页

作者： Ayesha Siddiqa syed Abbas Zilqurnain Naqvi Muhammad ahsan Allah Ditta Hani Alquhayz M.A.Khan Muhammad Adnan Khan Department of Mechatronics and Control Engineering University of Engineering and TechnologyLahore54000Pakistan Department of Information Sciences Division of Science and TechnologyUniversity of EducationLahore54000Pakistan Department of Computer Science and Information College of Science in ZulfiMajmaah UniversityAl-Majmaah11952Saudi Arabia Riphah School of Computing&Innovation Faculty of ComputingRiphah International UniversityLahore CampusLahore54000Pakistan Pattern Recognition and Machine Learning Lab Department of SoftwareGachon UniversitySeongnam13557Korea

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 *** management does not exactly know when the existing patient leaves the hospital;this information could be crucial for hospital *** could allow them to take more patients for *** a result,hospitals face many problems managing available resources and new patients in getting entries for their prompt ***,a robust model needs to be designed to help hospital administration predict patients’LOS to resolve these *** 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,*** been analyzed to predict the *** 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 *** results revealed the superior predictive performance of the RFRmodel,both in terms of RS score(92%)and MSE score(5),among all selected *** 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 *** on the average LOS,results revealed that the patients with diagnoses related to birth complications spent more days in the hospital than other *** finding coul

关键词： Length of stay machine learning robust model random forest regression

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Explainable Artificial Intelligence Solution for Online Retail

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Computers, Materials & Continua 2022年第6期71卷 4425-4442页

作者： Kumail Javaid Ayesha Siddiqa syed Abbas Zilqurnain Naqvi Allah Ditta Muhammad ahsan M.A.Khan Tariq Mahmood Muhammad Adnan Khan Department of Computer Science University of South AsiaLahore54000Pakistan Department of Mechatronics and Control Engineering University of Engineering and TechnologyLahore54000Pakistan Department of Information Sciences Division of Science and TechnologyUniversity of EducationLahore54000Pakistan Riphah School of Computing and Innovation Faculty of ComputingRiphah International UniversityLahore CampusLahore54000Pakistan Division of Science and Technology University of EducationLahore54000Pakistan Pattern Recognition and Machine Learning Lab Department of SoftwareGachon UniversitySeongnam13557Korea

Artificial intelligence(AI)and machine learning(ML)help in making predictions and businesses to make key decisions that are beneficial for *** 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 *** this research,a dataset of 12,330 records of customers has been analyzedwho visited an online shoppingwebsite over a period of one *** 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 *** 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 *** performance of each model has been discussed in detail using performance measurement techniques such as accuracy score,precision,recall,F1 score,and ROC-AUC *** model is the bestmodel among all five chosen based on accuracy score of 90%and F1 score of 79%followed by extra tree ***,our study indicates that RF model can be used by online retailing businesses for predicting consumer buying *** research also reveals the importance of page value as a key feature for capturing online purchasing *** 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.

关键词： Explainable artificial intelligence online retail neural network random forest regression

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An Efficient Impersonation Attack Detection Method in Fog Computing

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Computers, Materials & Continua 2021年第7期68卷 267-281页

作者： Jialin Wan Muhammad Waqas Shanshan Tu syed Mudassir hussain ahsan Shah Sadaqat Ur Rehman Muhammad Hanif Engineering Research Center of Intelligent Perception and Autonomous Control Faculty of Information TechnologyBeijing University of TechnologyBeijing100124China Faculty of Computer Science and Engineering Ghulam Ishaq Khan Institute of Engineering Sciences and TechnologyTopi23460Pakistan Department of Electronics Engineering FICTBalochistan University of Information TechnologyEngineering and Management SciencesQuetta87300Pakistan Department of Computer Science Namal InstituteMianwali42200Pakistan

Fog computing paradigm extends computing,communication,storage,and network resources to the network’s *** the fog layer is located between cloud and end-users,it can provide more convenience and timely services to ***,in fog computing(FC),attackers can behave as real fog nodes or end-users to provide malicious services in the *** attacker acts as an impersonator to impersonate other legitimate ***,in this work,we present a detection technique to secure the FC ***,we model a physical layer key generation based on wireless channel *** 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 *** compare our proposed Double Sarsa technique with the other two methods to validate our work,i.e.,Sarsa and *** 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).

关键词： Fog computing double Sarsa attack detection physical layer key security

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