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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

Facile synthesis of graphene anchored rare earth doped mixed metal ferrite nanorods:A potential candidate for azo dye mineralization

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Journal of Rare Earths 2024年第5期42卷 907-916,I0004页

作者： Tehmina Kousar muhammad Aadil Sonia Zulfiqar Sobhy MIbrahim Sidra Mubeen Warda hassan Kashuf Shafiq Farzana mahmood Institute of Chemical Sciences Bahauddin Zakariya UniversityMultan60800Pakistan Department of Chemistry Rahim Yar Khan CampusThe Islarnia University of BahawalpurRahim Yar Khan64200Pakistan Department of Chemistry Faculty of ScienceUniversity of Ostrava30.Dubna 22Ostrava70103Czech Republic Department of Chemical and Biological Engineering Iowa State UniversitySweeney Hall618 Bissell RoadAmeslowa50011United States Department of Biochemistry College of ScienceKing Saud UniversityPO.Box 2455Riyadh11451Saudi Arabi Department of Chemistry The Women University Multan66000Pakistan

Bandgap tuning using rare earth metals as dopants in ferrite-based photocatalytic materials has received a lot of interest because the Fermi 4f energy of these metals generates a sub-energy state in the bandgap generated by the overlapping of Fe-3d and O-2p ***,dysprosium-doped cobalt-nickel mixed ferrite(D-CNFO)and its graphene-reinforced composite(D-CNFO@G)were prepared and an ideal photocatalyst material for azo dye mineralization was proposed.A cost-effective combination of wetchemical and ultrasonication methods was used to prepare the doped and composite *** characterization methodologies were used to scrutinize the optical,compositional,structural,morphological,and photocatalytic characteristics of as-prepared *** X-ray diffraction analysis identified the spinel phase's(cubic)structure,while the electronic spectroscopy examination confirmed the prepared samples'rod-like *** UV/visible absorbance spectrum shows the higher light harvesting behavior of the D-CNFO@G in the visible *** mineralization performance of the DCNFO and D-CNFO@G composites was analyzed using Congo-red(an anionic dye),a well-known azo *** D-CNFO@G sample removes Congo-red dye at a rate almost 2.4%faster than the D-CNFO *** experiment involving trapping free radicals indicates that hydroxyl radical play s a crucial role in dye *** the D-CNFO@G catalyst is magnetic and can be isolated easily from the photocatalytic system,it shows an awkward cycle activity of more than 96%after five mineralization *** asprepared D-CNFO@G composite is proved as an excellent option for azo dye mineralization because of the combined impacts of rare earth doping,graphene reinforcement and nanotechnology.

关键词： azo-dye Composite Graphene Dy-doped Nanotechnology Rare earths

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

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)

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

巴基斯坦旁遮普中部仓鸮食性的季节性变化(英文)

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动物学报 2007年第3期53卷 431-436页

作者： muhammad mahmood-ul-hassan Mirza Azhar BEG Habib ALI Department of Wildlife and Ecosystem University of Veterinary and Animal Sciences Syed Abdul Qader Jilani Road Lahore 54000 Pakistan Department of Zoology and Fisheries University of Agriculture Faisalabad Pakistan Pakistan Museum of Natural History Islamabad Pakistan

在巴基斯坦对仓鸮食性的季节变化进行了研究。通过分析连续3年在6个地区搜集的2 360个仓鸮回吐食物团,发现其食物主要是小型哺乳动物(95.6 %)。其中,家(Suncus murinus)有最高的比例,达65.6%(冬季最多78%,夏季最少27%)。就生物量而言... 详细信息

在巴基斯坦对仓鸮食性的季节变化进行了研究。通过分析连续3年在6个地区搜集的2 360个仓鸮回吐食物团,发现其食物主要是小型哺乳动物(95.6 %)。其中,家(Suncus murinus)有最高的比例,达65.6%(冬季最多78%,夏季最少27%)。就生物量而言,小型哺乳动物占仓鸮食物总生物量的99% 。

关键词：仓鸮食性家 回吐食物团鼠类

巴基斯坦旁遮普中部横斑腹小鸮的食性(英文)

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动物学报 2007年第1期53卷 64-68页

作者： muhammad mahmood-ul-hassan Mirza Azhar BEG muhammad MUSHTAQ-ul-hassan Shahnaz Ahmed RANA Department of Wildlife and Ecosystem University of Veterinary and Animal SciencesSyed abdul Qader Jilani RoadLahore 54000Pakistan Department of Zoology and Fisheries University of AgricultureFaisalabadPakistan Department of Zoology Govt.College UniversityFaisalabadPakistan

横斑腹小鸮(Athene brama)是巴基斯坦旁遮普中部农业生态系统中最常见但研究匮乏的猛禽。我们通过分析吐弃块(n=498)以了解其季节性和地域性食性变化。结果显示:小型哺乳类占所有食物生物量的98.4%,而昆虫类在数量上占据绝对优势(56.4%... 详细信息

横斑腹小鸮(Athene brama)是巴基斯坦旁遮普中部农业生态系统中最常见但研究匮乏的猛禽。我们通过分析吐弃块(n=498)以了解其季节性和地域性食性变化。结果显示:小型哺乳类占所有食物生物量的98.4%,而昆虫类在数量上占据绝对优势(56.4%)。在小型哺乳类食物中,鼠类(38.8%)是稳定的食物成分。而在昆虫食物中,甲虫最多(42.8%)。横斑腹小亦捕食鼩鼱类(2.3%)和鸟类(1.7%)。昆虫类食物还有蟑螂(6.4%)、臭虫(3.3%)、蝗虫(6.7%)和蚂蚁(3.2%)。小家鼠(Mus musculus)和柔毛鼠(Rattus meltada)在鼠类食物中出现频次最多。不同地区中,Hafizabad的食物多样性最高(2.07),而秋季的食物多样性最高(1.99)。

关键词：甲虫食性多样性家鼠小鼩鼱

Impact of numerous larval diets on the biology of pink bollworm Pectinophora gossypiella(Saunders)(Lepidoptera:Gelechiidae)under laboratory conditions

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Journal of Cotton Research 2024年第1期7卷 69-78页

作者： AKHTAR Shamim ARIF muhammad Jalal GOGI muhammad Dildar HAQ Imran-ul Department of Entomology University of Agriculture FaisalabadPunjabPakistan Ayub Agricultural Research Institute(Entomological Research Institute) FaisalabadPunjabPakistan Department of Plant Pathology University of AgricultureFaisalabadPunjabPakistan

Background Pink bollworm,Pectinophora gossypiella(Saunders)(Lepidoptera:Gelechiidae)has become a poten-tial pest of cotton by causing substantial yield losses around the world including *** in view the facts like limited research investigations,unavailability,and high cost of artificial diet’s constituents and their premixes,the present research investigations on the dietary aspect of *** were *** larvae of *** were reared on different diets that were prepared using indigenous *** standard/laboratory diet com-prised of wheat germ meal 34.5 g,casein 30.0 g,agar–agar 20.0 g,sucrose 10.0 g,brewer’s yeast 5.0 g,α-cellulose 1.0 g,potassium-sorbate1.5 g,niplagin 0.5 g,decavitamin 0.01 g,choline-chloride 0.06 g,maize-oil 3.30 g,honey 2.0 g,and water 730.0 *** to cotton bolls and wheat germ meal were okra seed sprouts,okra fruit,cottonseed meal,and okra seed meals,which were included in the study to introduce an efficient and economic mass-rearing *** The larval development completed in 19.68d±0.05 d with a weight of 20.18mg±0.20 mg at the fourth instar fed on the cottonseed meal-based diet instead of wheat germ meal based *** the same diet,84.00%±4.00%,17.24 mg±0.03 mg,and 7.76d±0.06 d were recorded as pupae formation,pupal weight,and pupal duration,*** emergence,76.00%±1.00%was recorded from pupae collected from larvae raised on cottonseed meal-based *** male and female moths lived for 40.25d±0.10 d,and 44.34d±0.11 d,*** deposited 21.28±0.04 eggs per day with the viability of 65.78%±0.14%.The larval mortal-ity at the fourth instar was 37.20%±1.36%and malformed pupation of 12.00%±1.41%was *** of wheat germ meal with that of local meals(cottonseed and okra seed)in the standard laboratory diet has saved 463.80 to 467.10 PKR with 1.62 to 1.63 cost economic returns,*** This research is of novel nature as it provides a concis

关键词： Artificial diets Cottonseed meal Laboratory rearing Pectinophora gossypiella Wheat germ meal

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