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Deep Learning-Based Digital Image Forgery Detection Using Transfer Learning

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Intelligent Automation & Soft Computing 2023年第12期38卷 225-240页

作者： emad ul haq qazi Tanveer Zia Muhammad Imran Muhammad Hamza Faheem Center of Excellence in Cybercrimes and Digital Forensics(CoECDF) Naif Arab University for Security Sciences(NAUSS)Riyadh14812Saudi Arabia School of Engineering Information Technology and Physical SciencesFederation UniversityBrisbaneQLD 4000Australia

Deep learning is considered one of the most efficient and reliable methods through which the legitimacy of a digital image can be *** the current cyber world where deepfakes have shaken the global community,confirming the legitimacy of a digital image is of great *** the advancements made in deep learning techniques,now we can efficiently train and develop state-of-the-art digital image forensic *** most traditional and widely used method by researchers is convolution neural networks(CNN)for verification of image authenticity but it consumes a considerable number of resources and requires a large dataset for ***,in this study,a transfer learning based deep learning technique for image forgery detection is *** proposed methodology consists of three modules namely;preprocessing module,convolutional module,and the classification *** using our proposed technique,the training time is drastically reduced by utilizing the pre-trained *** performance of the proposed technique is evaluated by using benchmark datasets,i.e.,BOW and BOSSBase that detect five forensic types which include JPEG compression,contrast enhancement(CE),median filtering(MF),additive Gaussian noise,and *** evaluated the performance of our proposed technique by conducting various experiments and case scenarios and achieved an accuracy of 99.92%.The results show the superiority of the proposed system.

关键词： Image forgery transfer learning deep learning BOW dataset BOSSBase dataset

Electroencephalogram (EEG) Brain Signals to Detect Alcoholism Based on Deep Learning

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Computers, Materials & Continua 2021年第6期67卷 3329-3348页

作者： emad-ul-haq qazi Muhammad Hussain Hatim A.AboAlsamh Visual Computing Lab Department of Computer ScienceCollege of Computer and Information SciencesKing Saud UniversityRiyadh11543Saudi Arabia

The detection of alcoholism is of great importance due to its effects on individuals and *** alcoholism detection system(AADS)based on electroencephalogram(EEG)signals is effective,but the design of a robust AADS is a challenging ***’current designs are based on conventional,hand-engineered methods and restricted *** by the excellent deep learning(DL)success in many recognition tasks,we implement an AAD system based on EEG signals using DL.A DL model requires huge number of learnable parameters and also needs a large dataset of EEG signals for training which is not easy to obtain for the AAD *** order to solve this problem,we propose a multi-channel Pyramidal neural convolutional(MP-CNN)network that requires a less number of learnable *** the deep CNN model,we build an AAD system to detect from EEG signal segments whether the subject is alcoholic or *** validate the robustness and effectiveness of proposed AADS using KDD,a benchmark dataset for alcoholism detection *** order to find the brain region that contributes significant role in AAD,we investigated the effects of selected 19 EEG channels(SC-19),those from the whole brain(ALL-61),and 05 brain regions,i.e.,TEMP,OCCIP,CENT,FRONT,and *** results show that SC-19 contributes significant role in AAD with the accuracy of 100%.The comparison reveals that the state-of-the-art systems are outperformed by the *** proposed AADS will be useful in medical diagnosis research and health care systems.

关键词： Electroencephalogram convolutional neural network deep learning alcoholism

Identification of Software Bugs by Analyzing Natural Language-Based Requirements Using Optimized Deep Learning Features

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Computers, Materials & Continua 2024年第3期78卷 4379-4397页

作者： qazi Mazhar ul haq Fahim Arif Khursheed Aurangzeb Noor ul Ain Javed Ali Khan Saddaf Rubab Muhammad Shahid Anwar Department of Computer Science and Engineering and International Bachelor’s Program in Informatics Yuan Ze UniversityZhongliTaoyuan320315Taiwan Department of Computer Science National University of PakistanRawalpindiPunjab46000Pakistan Department of Computer Software Engineering MCSNational University of Sciences and TechnologyIslamabad44000Pakistan Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityP.O.Box 51178Riyadh11543Saudi Arabia Department of Computer Science School of PhysicsEngineering and Computer ScienceUniversity of HertfordshireHatfieldAL109ABUK Department of Computer Engineering College of Computing and InformaticsUniversity of SharjahSharjah27272United Arab Emirates Department of AI and Software Gachon UniversitySeongnam-SI13120South Korea

Software project outcomes heavily depend on natural language requirements,often causing diverse interpretations and issues like ambiguities and incomplete or faulty *** are exploring machine learning to predict software bugs,but a more precise and general approach is *** bug prediction is crucial for software evolution and user training,prompting an investigation into deep and ensemble learning ***,these studies are not generalized and efficient when extended to other ***,this paper proposed a hybrid approach combining multiple techniques to explore their effectiveness on bug identification *** methods involved feature selection,which is used to reduce the dimensionality and redundancy of features and select only the relevant ones;transfer learning is used to train and test the model on different datasets to analyze how much of the learning is passed to other datasets,and ensemble method is utilized to explore the increase in performance upon combining multiple classifiers in a *** National Aeronautics and Space Administration(NASA)and four Promise datasets are used in the study,showing an increase in the model’s performance by providing better Area Under the Receiver Operating Characteristic Curve(AUC-ROC)values when different classifiers were *** reveals that using an amalgam of techniques such as those used in this study,feature selection,transfer learning,and ensemble methods prove helpful in optimizing the software bug prediction models and providing high-performing,useful end mode.

关键词： Natural language processing software bug prediction transfer learning ensemble learning feature selection

Is economic fitness helpful in achieving environmental sustainability in BRICS economies?A risk exposure perspective

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Chinese Journal of Population,Resources and Environment 2024年第2期22卷 109-117页

作者： Jabbar ul-haq Hubert Visas Muhlis Can qazi Muhammad Adnan Hye Noreen Aslama Department of Economics University of SargodhaSargodha 40100Pakistan School of International Trade&Economics University of International Business and EconomicsBeijing 100029China Middle East University Amman 11831Jordan Vishi Higher Institute DoualaCameroon BETA Akademi Social Sciences Research Lab(SSR Lab)Istanbul 34000Turkey Academic Research and Development Wing DubaiUnited Arab Emirates

A country’s ability to create complex goods and diversify its lines of products is essential for addressing all types of *** a country’s vulnerability to extreme climatic events,such as droughts,superstorms,and other natural disasters,and its capacity for successful adaption,is an essential global need that has been *** study examines the role of economic fitness(EF)in addressing climate change risk ex‐posure in BRICS countries in the context of the environmental Kuznets curve using panel data from 1995 to *** threshold methodology is employed to ascertain the nonlinear relationship between EF and climate change risk exposure(i.e.,Notre Dame Global Adaptation Initiative Country Index(ND-GAIN)).In addition,empirical associations were estimated using panel-corrected standard errors,Driscoll-Kraay standard errors,and feasible generalized least squares estimation *** findings demonstrated an inverted N shaped link between EF and ***,even after controlling for significant ND-GAIN influencing variables such as gross domestic product per capita,financial development,and urbanization,our robustness checks revealed significant and consistent findings.

关键词： Economic fitness Climate change BRICS countries Environmental Kuznets Curve Notre Dame Index

Trends in species distribution modelling in context of rare and endemic plants:a systematic review

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Ecological Processes 2022年第1期11卷 525-535页

作者： Ammad Waheed qazi Zafeer Saqib Muhammad Zaman‑ul‑haq Department of Environmental Science International Islamic University IslamabadIslamabad 46000Pakista

Background:Many research papers have utilized Species Distribution Models to estimate a species’current and future geographic distribution and environmental *** study aims to(a)understand critical features of SDMs used to model endemic and rare species and(b)to identify possible constraints with the collected *** present systematic review examined how SDMs are used on endemic and rare plant species to identify optimal practices for future ***:The evaluated literature(79 articles)was published between January 2010 and December *** number of papers grew considerably over *** studies were primarily conducted in Asia(41%),Europe(24%),and Africa(2%).The bulk of the research evaluated(38%)focused on theoretical ecology,climate change impacts(19%),and conservation policy and planning(22%).Most of the papers were published in publications devoted to biodiversity conservation,ecological or multidisciplinary *** degree of uncertainty was not disclosed in most studies(81%).Conclusion:This systematic review provides a broad overview of the emerging trends and gaps in the SDMs *** majority of studies failed to present uncertainties and error ***,when model performance estimates are given,the model results will be highly effective,allowing for more assurance in the predictions they ***,based on our systematic review,we recommend that in the future rare and endemic SDMs should represent uncertainty levels and estimates of errors in the modelling process.

关键词： Species distribution modelling Endemic Rare Uncertainty measures Model validation

Partial Splenic Artery Embolization in Cirrhosis Is a Safe and Useful Procedure

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Open Journal of Gastroenterology 2018年第9期8卷 327-336页

作者： Fakhar Ali qazi Arisar Syed Hasnain Ali Shah Tanveer ul haq Section of Gastroenterology Department of Medicine The Aga Khan University Hospital Karachi Pakistan Section of Interventional Radiology Department of Radiology The Aga Khan University Hospital Karachi Pakistan

Background: Portal Hypertension is a common complication of cirrhosis. It leads to splenomegaly which manifests with features of hypersplenism. This results in leucopenia which increases the likelihood of sepsis and prevents treatment with interferon. Thrombocytopenia increases the risk of bleeding including variceal bleeds which make the anemia worse. This study was done to determine the usefulness and safety of partial splenic artery embolization (PSAE) in portal hypertension due to cirrhosis. Methods: Patients with PSAE were identified by using International Classification of Diseases (ICD)-10 coding from medical records and their charts were reviewed retrospectively. 25 patients underwent splenic artery embolization at The Aga Khan University Hospital Karachi from November 2000 to December 2016. 18 patients who underwent PSAE for disabling hypersplenism caused by cirrhosis were included. Patients who were under 18 year of age, or in whom PSAE were performed for reasons other than cirrhosis and those with missing records/incomplete data were excluded (n = 7). Information was collected regarding demographic details, procedure indications, nature, technique, clinical efficacy, repeat embolization and complications along with laboratory and radiological investigations. Results: Eighteen patients of cirrhosis with a mean age of 43.47 ± 10.926 years, of which 14 were males, underwent PSAE (19 procedures). Indications were severe hypersplenism which precluded treatment with interferon and ribavirin (n = 8) and recurrent Gastro-oesophageal variceal (GOV) bleeds due to advanced Child-Pugh grade and thrombocytopenia (n = 10). Hematological parameters improved significantly following PSAE. Three out of eight patients successfully completed interferon + ribavirin treatment for hepatitis C (HCV) infection post PSAE, and GOV bleeds stopped in eight out of 10 patients. Complications included mild Left upper quadrant (LUQ) abdominal pain n = 9 (47.3%), post-embolization syndrom

关键词： Partial Splenic Artery Embolization Chronic Liver Disease Cirrhosis Hyper-splenism Safety Outcome