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Distribution of toxic and trace metals in fish from the Black Sea: Implications for human health risks

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Emerging Contaminants 2024年第2期10卷 83-89页

作者： tanju Mutlu Recep Tayyip Erdogan University Vocational School of Technical SciencesRizeTurkiye

This study focused on the investigation of toxic and trace metal levels in fish caught from the Black Sea,which is facing pollution threats from various human *** also aimed to assess the potential health risks associated with consuming fish and contribute to the development of strategies for sustainable fisheries *** presence was observed in the muscle tissues of four commercially consumed fish species(anchovy,whiting,horse mackerel and red mullet)from nine different stations in the Black *** the metals,the highest average concentration was observed for aluminium(Al)in anchovy and the lowest concentration for cadmium(Cd)in ***,the levels were generally below the maximum allowable limits recommended by the FAo,WHo,EC,and Turkish Food *** study results showed that metal concentrations in the analyzed fish species did not pose significant non-carcinogenic health risks to *** research findings show that some fish species studied from the Black Sea exhibit high metal levels,the concentrations of toxic and trace elements are generally within acceptable thresholds for safe fish *** findings of this study are thought to help stakeholders develop strategies for environmental protection and sustainable fisheries management in the region.

关键词： Accumulation THQ Risk assessment Health risk

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

Robust design of sliding mode control for airship trajectory tracking with uncertainty and disturbance estimation

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Journal of Systems Engineering and Electronics 2024年第1期35卷 242-258页

作者： WASIM Muhammad ALI Ahsan CHoUDHRY Mohammad Ahmad SHAIKH Inam ul Hasan SALEEM Faisal Department of Aeronautics and Astronautics Engineering Institute of Space TechnologyIslamabad 44000Pakistan Department of Electrical Engineering University of Engineering and TechnologyTaxila 47080Pakistan Department of Measurements and Control Systems Silesian University of TechnologyGliwice 44-101Poland The Joint Doctoral School Silesian University of TechnologyGliwice 44-100Poland

The robotic airship can provide a promising aerostatic platform for many potential *** applications require a precise autonomous trajectory tracking control for *** has a nonlinear and uncertain *** is prone to wind disturbances that offer a challenge for a trajectory tracking control *** paper addresses the airship trajectory tracking problem having time varying reference path.A lumped parameter estimation approach under model uncertainties and wind disturbances is opted against distributed *** uses extended Kalman filter(EKF)for uncertainty and disturbance *** estimated parameters are used by sliding mode controller(SMC)for ultimate control of airship trajectory *** comprehensive algorithm,EKF based SMC(ESMC),is used as a robust solution to track airship *** proposed estimator provides the estimates of wind disturbances as well as model uncertainty due to the mass matrix variations and aerodynamic model *** stability and convergence of the proposed method are investigated using the Lyapunov stability *** simulation results show that the proposed method efficiently tracks the desired *** method solves the stability,convergence,and chattering problem of SMC under model uncertainties and wind disturbances.

关键词： airship chattering extended Kalman filter(EKF) model uncertainties estimation sliding mode controller(SMC)

Role of knowledge economy in managing demand-based environmental Kuznets Curve

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Geoscience Frontiers 2024年第4期15卷 397-410页

作者： Rukhsana Kalim Shajara ul-Durar Mubasher Iqbal Noman Arshed Muhammad Shahbaz Department of Economics and Statistics Dr.Hassan Murad School of ManagementUniversity of Management and TechnologyLahorePakistan University of Sunderland The School of Business ManagementEdinburgh BuildingChester RoadSunderland SR13SDUnited Kingdom Department of Economics Division of Management and Administrative SciencesUniversity of EducationLahorePakistan Department of International Trade and Finance School of Management and EconomicsBeijing Institute of TechnologyBeijingChina Center for Sustainable Energy and Economic Development Gulf University for Science and TechnologyHawallyKuwait

Aggregate demand or supply at equilibrium is commonly used as a representative of the macroeconomic activity of an economy whereby aggregate demand denotes the behaviour of individuals and ***,aggregate demand can also directly affect environmental deterioration via changes in aggregate *** study tried to explore this relationship,known as the demand-based Environmental Kuznets Curve(Demand EKC)and the role of different knowledge economy *** economy indicators are proposed to influence consumption patterns,altering the demand EKC that empirical studies have *** this purpose,secondary data for 147 countries were collected from 2008 to 2018,also classified as *** study found that aggregate demand significantly affects carbon *** long-run results are estimated using the Fully Modified ordinary Least Square *** factors like renewable energy consumption,population density,and financial development significantly affect carbon emissions in sample *** study has incorporated four pillars of a knowledge-based economy and the results showed that these indicators helped reduce consumption-related Co_(2) emissions.

关键词： Kuznets Curve Knowledge economy Higher education Institutional quality Innovation Technology

Re-analysis of temperature dependent neutron capture rates and stellarβ-decay rates of^(95-98)Mo

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Chinese Physics C 2024年第9期48卷 142-149页

作者： Abdul Kabir Jameel-Un Nabi Muhammad Tahir Abdul Muneem Zain ul Abideen Space and Astrophysics Research lab National Centre of GIS and Space ApplicationsDepartment of Space ScienceInstitute of Space TechnologyIslamabad 44000Pakistan University of Wah Quaid AvenueWah Cantt 47040PunjabPakistan Faculty of Engineering Sciences GIK Institute of Engineering Sciences and TechnologyTopi 23640Khyber PakhtunkhwaPakistan

The neutron capture rates and temperature dependent stellar beta decay rates of Mo isotopes are investigated within the framework of the statistical code TALYS v1.96 and the proton neutron quasi particle random phase approximation(pn-QRPA)*** Maxwellian average cross-section(MACS)and neutron capture rates for the^(95-98)Mo(n,γ)^(96-99)Mo radiative capture process are analyzed within the framework of the statistical code TALYS v1.96 based on the phenomenological nuclear level density model and gamma strength *** present model-based computations for the MACS are comparable to the existing measured *** sensitivity of stellar weak interaction rates to various densities and temperatures is investigated within the framework of the pn-QRPA *** attention is paid to the impact of thermally filled excited states in the decaying nuclei(^(95-98)Mo)on electron emission and positron capture ***,we compare the neutron capture rates and stellar beta decay *** is found that neutron capture rates are higher than stellar beta decay rates at both lower and higher temperatures.

关键词： cross-section TALYS nuclear level density decay rates capture rates

Role of renewable,non-renewable energy consumption and carbon emission in energy efficiency and productivity change:Evidence from G20 economies

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Geoscience Frontiers 2024年第4期15卷 474-493页

作者： Wasi ul Hassan Shah Gang Hao Hong Yan Nan Zhu Rizwana Yasmeen Gheorghi Dinca˘f a School of Management Zhejiang Shuren UniversityHangzhou 310015China Department of Management Sciences City University of Hong KongHong KongChina School of Management Zhejiang Shuren UniversityHangzhou 310015China The Western Business School Southwestern University of Finance and EconomicsChengduChina School of Economics and Management Panzhihua UniversityPanzhihua 617000SichuanChina Department of Finance and Accounting Transilvania University of BrașovBrașovRomania

The challenge of achieving sustainable economic development with a secure environmental system is a global challenge faced by both developed and developing *** Efficiency(EE)is crucial in achieving sustainable economic growth while reducing ecological *** research utilizes the Slack-Based Measure Data Envelopment Analysis(SBM-DEA)and the Malmquist-Luenberger Index(MLI)method to evaluate EE and productivity changes from 1995 to 2020 across G20 *** study uses four different input-output bundles to gauge the impact of renewable and non-renewable energy consumption and carbon emissions on EE and productivity *** study results show that including renewable energy consumption improves the average EE from 0.783 to 0.8578,but energy productivity declines from 1.0064 to *** bad output(carbon emissions)in the estimation process enhances renewable EE and productivity change,resulting in an average EE of 0.6678 and MLI of *** change is identified as the primary determinant of energy productivity growth in scenarios 1 and 2,while technical efficiency determines energy productivity change in scenarios 3 and *** Kruskal-Wallis test reveals a significant statistical difference between the mean EE and MLI scores of G20 countries.

关键词： Renewable energy DEA Energy Efficiency Productivity change Carbon emissions

Deep Learning Based Efficient Crowd Counting System

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Computers, Materials & Continua 2024年第6期79卷 4001-4020页

作者： Waleed Khalid Al-Ghanem Emad ul Haq Qazi Muhammad Hamza Faheem Syed Shah Amanullah Quadri Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityRiyadh12372Saudi Arabia Centre of Excellence in Cybercrime and Digital Forensics Naif Arab University for Security SciencesRiyadh14812Saudi Arabia Center of Excellence for Information Assurance(CoEIA) King Saud UniversityRiyadh12372Saudi Arabia

Estimation of crowd count is becoming crucial nowadays,as it can help in security surveillance,crowd monitoring,and management for different *** is challenging to determine the approximate crowd size from an image of the crowd’s *** in this research study,we proposed a multi-headed convolutional neural network architecture-based model for crowd counting,where we divided our proposed model into two main components:(i)the convolutional neural network,which extracts the feature across the whole image that is given to it as an input,and(ii)the multi-headed layers,which make it easier to evaluate density maps to estimate the number of people in the input image and determine their number in the *** employed the available public benchmark crowd-counting datasets UCF CC 50 and ShanghaiTech parts A and B for model training and testing to validate the model’s *** analyze the results,we used two metrics Mean Absolute Error(MAE)and Mean Square Error(MSE),and compared the results of the proposed systems with the state-of-art models of crowd *** results show the superiority of the proposed system.

关键词： Crowd counting EfficientNet multi-head attention convolutional neural network transfer learning

CapsNet-FR: Capsule Networks for Improved Recognition of Facial Features

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Computers, Materials & Continua 2024年第5期79卷 2169-2186页

作者： Mahmood ul Haq Muhammad Athar Javed Sethi Najib Ben Aoun Ala Saleh Alluhaidan Sadique Ahmad Zahid farid Department of Computer System Engineering University of Engineering&TechnologyPeshawar25000Pakistan College of Computer Science and Information Technology Al-Baha UniversityAlaqiq65779-7738Saudi Arabia REGIM-Lab:Research Groups in Intelligent Machines National School of Engineers of Sfax(ENIS)University of SfaxSfax3038Tunisia Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh84428Saudi Arabia EIAS:Data Science and Blockchain Laboratory College of Computer and Information SciencesPrince Sultan UniversityRiyadh11586Saudi Arabia Department of Computer Sciences Bahria University Karachi CampusKarachi541004Pakistan Department of Electrical Engineering Abasyn UniversityPeshawar25000Pakistan

Face recognition (FR) technology has numerous applications in artificial intelligence including biometrics, security,authentication, law enforcement, and surveillance. Deep learning (DL) models, notably convolutional neuralnetworks (CNNs), have shown promising results in the field of FR. However CNNs are easily fooled since theydo not encode position and orientation correlations between features. Hinton et al. envisioned Capsule Networksas a more robust design capable of retaining pose information and spatial correlations to recognize objects morelike the brain does. Lower-level capsules hold 8-dimensional vectors of attributes like position, hue, texture, andso on, which are routed to higher-level capsules via a new routing by agreement algorithm. This provides capsulenetworks with viewpoint invariance, which has previously evaded CNNs. This research presents a FR model basedon capsule networks that was tested using the LFW dataset, CoMSATS face dataset, and own acquired photos usingcameras measuring 128 × 128 pixels, 40 × 40 pixels, and 30 × 30 pixels. The trained model outperforms state-ofthe-art algorithms, achieving 95.82% test accuracy and performing well on unseen faces that have been blurred orrotated. Additionally, the suggested model outperformed the recently released approaches on the CoMSATS facedataset, achieving a high accuracy of 92.47%. Based on the results of this research as well as previous results, capsulenetworks perform better than deeper CNNs on unobserved altered data because of their special equivarianceproperties.

关键词： CapsNet face recognition artificial intelligence

Design of an Efficient and Provable Secure Key Exchange Protocol for HTTP Cookies

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Computers, Materials & Continua 2024年第7期80卷 263-280页

作者： Waseem Akram Khalid Mahmood Hafiz Burhan ul Haq Muhammad Asif Shehzad Ashraf Chaudhry Taeshik Shon Graduate School of Engineering Science and Technology National Yunlin University of Science and TechnologyYunlin64002TaiwanChina Future Technology Research Center National Yunlin University of Science and TechnologyYunlin64002TaiwanChina Department of Computer Science Lahore Garrison UniversityLahore54920Pakistan Department of Computer Science and Information Technology College of EngineeringAbu Dhabi UniversityAbu Dhabi69911United Arab Emirates Department of Software Engineering Faculty of Engineering and ArchitectureNisantasi UniversityIstanbul34398Turkey Department of Cybersecurity Ajou UniversitySuwon16499Republic of Korea

Cookies are considered a fundamental means of web application services for authenticating various Hypertext Transfer Protocol(HTTP)requests andmaintains the states of clients’information over the *** cookies are exploited to carry client patterns observed by a *** client patterns facilitate the particular client’s future visit to the corresponding ***,security and privacy are the primary concerns owing to the value of information over public channels and the storage of client information on the *** protocols have been introduced that maintain HTTP cookies,but many of those fail to achieve the required security,or require a lot of resource *** this article,we have introduced a lightweight Elliptic Curve Cryptographic(ECC)based protocol for authenticating client and server transactions to maintain the privacy and security of HTTP *** proposed protocol uses a secret key embedded within a *** proposed protocol ismore efficient and lightweight than related protocols because of its reduced computation,storage,and communication ***,the analysis presented in this paper confirms that proposed protocol resists various known attacks.

关键词： Cookies authentication protocol impersonation attack ECC