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OffSig-SinGAN: A Deep Learning-Based Image Augmentation model for Offline Signature Verification

Computers, materials & Continua 2023年第7期76卷 1267-1289页

作者： m.muzaffar hameed Rodina Ahmad Laiha mat Kiah Ghulam murtaza Noman mazhar Faculty of Computer Science and Information Technology University of MalayaKuala Lumpur46400Malaysia Department of Computer Science Bahauddin Zakariya UniversityMultan60000Pakistan Department of Computer Science Sukkur Institute of Business Administration UniversitySukkur65200Pakistan

Offline signature verification(OfSV)is essential in preventing the falsification of *** learning(DL)based OfSVs require a high number of signature images to attain acceptable ***,a limited number of signature samples are available to train these models in a real-world *** researchers have proposed models to augment new signature images by applying various ***,on the other hand,have used human neuromotor and cognitive-inspired augmentation models to address the demand for more signature ***,augmenting a sufficient number of signatures with variations is still a challenging *** study proposed OffSig-SinGAN:a deep learning-based image augmentation model to address the limited number of signatures problem on offline signature *** proposed model is capable of augmenting better quality signatures with diversity from a single signature image *** is empirically evaluated on widely used public datasets;*** quality of augmented signature images is assessed using four metrics like pixel-by-pixel difference,peak signal-to-noise ratio(PSNR),structural similarity index measure(SSIm),and frechet inception distance(FID).Furthermore,various experiments were organised to evaluate the proposed image augmentation model’s performance on selected DL-based OfSV systems and to prove whether it helped to improve the verification accuracy *** results showed that the proposed augmentation model performed better on the GPDSsyntheticSignature dataset than other augmentation *** improved verification accuracy rate of the selected DL-based OfSV system proved the effectiveness of the proposed augmentation model.

关键词： Signature forgery detection offline signature verification deep learning image augmentation generative adversarial networks

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R-IDPS: Real Time SDN-Based IDPS System for IoT Security

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Computers, materials & Continua 2022年第11期73卷 3099-3118页

作者： Noman mazhar Rosli Saleh Reza Zaba muhammad Zeeshan m.muzaffar hameed Nauman Khan Faculty of Computer Science and Information Technology University of MalayaKuala Lumpur50603Malaysia Centre for Research in Industry 4.0 University of MalayaKuala Lumpur50603Malaysia mImOS Berhad National Applied R&D CentreKuala Lumpur57000Malaysia School of Electrical Engineering and Computer Science National University of Sciences and TechnologyIslamabad44000Pakistan

The advent of the latest technologies like the Internet of things(IoT)transforms the world from a manual to an automated way of ***,IoT sector open numerous security *** traditional networks,intrusion detection and prevention systems(IDPS)have been the key player in the market to ensure *** challenges to the conventional IDPS are implementation cost,computing power,processing delay,and ***,online machine learning model training has been an *** these challenges still question the IoT network *** has been a lot of research for IoT based detection systems to secure the IoT devices such as centralized and distributed architecture-based detection *** centralized system has issues like a single point of failure and load balancing while distributed system design has scalability and heterogeneity *** this study,we design and develop an agent-based hybrid prevention system based on software-defined networking(SDN)*** system uses lite weight agents with the ability to scaleup for bigger networks and is feasible for heterogeneous IoT *** baseline profile for the IoT devices has been developed by analyzing network flows from all the IoT *** profile helps in extracting IoT device *** features help in the development of our dataset that we use for anomaly *** anomaly detection,support vector machine has been used to detect internet control message protocol(ICmP)flood and transmission control protocol synchronize(TCP SYN)flood *** proposed system based on machine learning model is fully capable of online and offline *** than detection accuracy,the system can fully mitigate the attacks using the software-defined technology SDN *** major goal of the research is to analyze the accuracy of the hybrid agent-based intrusion detection systems as compared to conventional centralized only solutions,especially under the flood attac

关键词： machine learning Internet of things software defined networking distributed denial of service attacks

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Synthesis of new 1,2,4-oxadiazolidin-5-ylthiophenes and thienopyrimidine derivatives by aza-Wittig reaction using a thienyl carbodiimide

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Chinese Chemical Letters 2012年第4期23卷 411-414页

作者： Afaf m.Abdel hameed Chemistry Department Faculty of ScienceMinia University

Azidation of aminothiophene derivative 1 afforded the corresponding azido derivative *** latter reacted with triphenylphosphine to afford iminophosphorane derivatives *** 3 with phenylisocyanate gave the highly reactive carbodiimide intermediate 4,which was reacted with different nitrones to afford new l,2,4-oxadiazolidin-5-ylidene-aminothiophenes 5a-c. Treatment of 4 with absolute EtOH at room temperature gave methyleneamino-5-（methylthio）thiophene 7,（methylthio）-3-（3- phenylureidothiophene）-2-carboxylate 8 or thienopyrimidine 9 and 10 at refluxing *** reaction of carbodiimide intermediate 4 with different secondary amines gave the new thienopyrimidines 11a-c.

关键词： Carbodiimide Cycloaddition 1 2 4-Oxadiazolidin-5-ylideneaminothiophene derivatives Thienopynmidine Aza-Wittig reaction

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Impact on Transportation Cost after CPEC

Impact on Transportation Cost after CPEC

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作者： m mehtab muzaffar 中北大学

学位级别：硕士

本论文研究了通过中巴经济走廊CPEC的中国货物的运输问题,特别是通过实际评估针对其中的运输费用和运输时间进行了研究。本研究的重点在于发现在与运输成本和运输成本相关的阶段内,进口和价格是否会受到任何好的甚至是不利的影响,并找... 详细信息

本论文研究了通过中巴经济走廊CPEC的中国货物的运输问题,特别是通过实际评估针对其中的运输费用和运输时间进行了研究。本研究的重点在于发现在与运输成本和运输成本相关的阶段内,进口和价格是否会受到任何好的甚至是不利的影响,并找出与运输成本和运输时间的影响路径,主要目的是找出CPEC对中国制造产品的进口和成本的影响。这项研究使用了各种来源的成本数据,如航运企业和货运代理数据等。数据调查包括分类拆分、配送成本和行程周期等方面,并考察了企业对供应链的功能、活动和流程的了解是用来提取成本信息。本文首先综述了运输费用在供应链管理中的重要性和运输时间在供应链管理中的重要性。分析了巴基斯坦的地理、气候、经济和政府政策等多个因素,并将这些因素合并成一个整体描述,描述它们如何影响出口成本和时间周期。在分析货物路径时,CPEC项目的初始目标也考虑在内,讨论中还考虑了中国的贸易量和目前的航线过境时间。研究结果表明包括对德国、法国、沙特阿拉伯、阿曼和其他8个港口的供应链效益中大大节省了成本和时间,同时CPEC在运输时间和成本方面肯定会给供应链系统和台湾等地区带来巨大的利益。

关键词： CPEC 供应链

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Utilization of iron oxide bearing pellets waste for preparing hard and soft ferromagnetic glass ceramics

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Journal of Advanced Ceramics 2014年第4期3卷 259-268页

作者： Salwa A.m.ABDEL-hameed Ibrahim m.HAmED Nehal A.ERFAN Glass Research Department National Research CenterDokkiCairoEgypt Chemical Engineering Department Faculty of EngineeringMinia UniversityMiniaEgyp

About 8%of the imported iron oxide pellets burdens to Egypt are *** this paper,broken pellets waste(BPW)is used as raw material for the preparation of hard magnetic glass ceramics(HmGC)as well as soft magnetic glass ceramics(SmGC).About 54 wt%and 37 wt%of BPW are used to prepare SmGC and HmGC,*** thermal analysis(DTA)reveals two broad exothermic peaks for HmGC at 591℃and 697℃,whereas one exothermic peak at 820℃is detected for SmGC.X-ray diffraction(XRD)shows the crystallization of hematite as the sol phase in BPW,and meanwhile,Zn-ferrite and Ba-hexaferrite are identified in SmGC and HmGC,*** electron microscopy(TEm)reveals the crystallization of nanosize particles of~20 nm for SmGC and~12 nm for *** scanning magnetometer(VSm)reveals an increase in saturation magnetization from~1 emu/g for BPW to~77 emu/g for SmGC and 21 emu/g for HmGC.

关键词： magnetic materials nanostructure pellets waste

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Credit Card Fraud Detection Using Improved Deep Learning models

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Computers, materials & Continua 2024年第1期78卷 1049-1069页

作者： Sumaya S.Sulaiman Ibraheem Nadher Sarab m.hameed Computer Science Department Al-Mustansiriya UniversityBaghdad10001Iraq Computer Science Department University of BaghdadBaghdad10001Iraq Faculty of Basic Education Al-Mustansiriya UniversityBaghdad10001Iraq

Fraud of credit cards is a major issue for financial organizations and *** fraudulent actions become more complex,a demand for better fraud detection systems is *** learning approaches have shown promise in several fields,including detecting credit card ***,the efficacy of these models is heavily dependent on the careful selection of appropriate *** paper introduces models that integrate deep learning models with hyperparameter tuning techniques to learn the patterns and relationships within credit card transaction data,thereby improving fraud *** deep learning models:AutoEncoder(AE),Convolution Neural Network(CNN),and Long Short-Term memory(LSTm)are proposed to investigate how hyperparameter adjustment impacts the efficacy of deep learning models used to identify credit card *** experiments conducted on a European credit card fraud dataset using different hyperparameters and three deep learning models demonstrate that the proposed models achieve a tradeoff between detection rate and precision,leading these models to be effective in accurately predicting credit card *** results demonstrate that LSTm significantly outperformed AE and CNN in terms of accuracy(99.2%),detection rate(93.3%),and area under the curve(96.3%).These proposed models have surpassed those of existing studies and are expected to make a significant contribution to the field of credit card fraud detection.

关键词： Card fraud detection hyperparameter tuning deep learning autoencoder convolution neural network long short-term memory resampling

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Two mADS-box proteins,AGL9 and AGL15,recruit the FIS-PRC2 complex to trigger the phase transition from endosperm proliferation to embryo development in Arabidopsis

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molecular Plant 2024年第7期17卷 1110-1128页

作者： Shen Zhang Devasantosh mohanty Adnan muzaffar min Ni Department of Plant and microbial Biology University of Minnesota at Twin CitiesSaint PaulMinnesota MN 55108United States of AmericaUSA

Spatiotemporal regulation of gene expression by polycomb repressive complex 2(PRc2)is critical for animal and plant *** Arabidopsis fertilization independent seed(FIS)-PRC2 complex functions specifically during plant reproduction from gametogenesis to seed *** a double fertilization event,triploid endosperm proliferates early,followed by the growth of a diploid embryo,which replaces the endosperm in Arabidopsis and many *** genes critical for endosperm proliferation such as IKkU2 and mINI3 are activated after *** we report that two mADS-box AGAmOUS-LIKE(AGL)proteins associate with the key endosperm proliferation loci and recruit the FIS-PRC2 repressive complex at 4-5 days after pollination(DAP).Interestingly,AGL9 and AGL15 only accumulate toward the end of endosperm proliferation at 4-5 DAP and promote the deposition of H3K27me3 marks at key endosperm proliferation *** of AGL9 and AGL15 or overexpression of AGL9 or AGL15 significantly influence endosperm proliferation and ***-wide analysis with cleavage Under Targets and tagmentation(CUT&Tag)sequencing and RNA sequencing revealed the landscape of endosperm H3K27me3 marks and gene expression profiles in Col-0 and agl9 ***&Tag qPCR also demonstrated the occupancy of the two mADS-box proteins and FIS-PRC2 on a few representative target *** studies suggest that mADS-box proteins could potentially recruit PRc2 to regulate many other developmental processes in plants or even in fungi and animals.

关键词： AGL9 AGL15 embryo endosperm IKU2 mEDEA mINI3

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Pythagorean Fuzzy Einstein Aggregation Operators with Z-Numbers:Application in Complex Decision Aid Systems

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Computer modeling in Engineering & Sciences 2023年第12期137卷 2795-2844页

作者： Shahzad Noor Abbasi Shahzaib Ashraf m.Shazib hameed Sayed m.Eldin Institute of mathematics Khwaja Fareed University of Engineering&Information TechnologyRahim Yar Khan64200Pakistan Center of Research Faculty of EngineeringFuture University in EgyptNew Cairo11835Egypt

The primary goal of this research is to determine the optimal agricultural field selection that would most effectively support manufacturing producers in manufacturing production while accounting for unpredictability and reliability in their *** PFS is known to address the levels of participation and *** begin,we introduce the novel concept of a PFZN,which is a hybrid structure of Pythagorean fuzzy sets and the *** PFZN is graded in terms of membership and non-membership,as well as reliability,which provides a strong advice in real-world decision support *** PFZN is a useful tool for dealing with uncertainty in decision-aid *** PFZN is a practical way for dealing with such uncertainties in decision-aid *** list of aggregation operators:PFZN Einstein weighted averaging and PFZN Einstein weighted geometric,is established under the novel Pythagorean fuzzy *** is a more precise mathematical instrument for dealing with precision and *** core of this research is to develop a numerical algorithmto tackle the uncertainty in real-life problems using *** show the applicability and effectiveness of the proposed algorithm,we illustrate the numerical case study related to determining the optimal agricultural *** main purpose of this work is to describe the extended EDAS approach,then compare the proposed methodology with many other methodologies now in use,and then demonstrate how the suggested methodology may be applied to real-world *** addition,the final ranking results that were obtained by the devised techniques weremore efficient and dependable in comparison to the results provided by other methods presented in the literature.

关键词： Pythagorean fuzzy Z-number Einstein weighted averaging Pythagorean fuzzy Z-number Einstein weighted geometric decision making

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Radical scavenging and antibacterial activity of Arnebia benthamii methanol extract

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Asian Pacific Journal of Tropical medicine 2012年第10期5卷 766-772页

作者： Showkat A Ganie Asima Jan Sabeera muzaffar Bilal A Zargar Rabia Hamid m Afzal Zargar Department of Biochemistry University of Kashmir Department of Food Science and Technology University of Kashmir Department of Pharmaceutical Sciences University of Kashmir

Objective:To evaluate in vitro antioxidant and antibacterial activity of methanolic extract of Arnebia benthamii（***） whole ***:Plasmid damage was analyzed by agarose gell *** thymus DNA was monitored by TBARS ***, reducing power and lipid peroxidation was evaluated by using standard *** assay was monitored by disc diffusion ***:DPPH radical scavenging and hydroxyl radical scavenging potential of the plant revealed that the extract to be active radical ***(Fe3+-Fe2+) power and lipid peroxidation inhibition efficiency（TBARS assay） of the extract was also evaluated and the extract showed promising activity in preventing lipid peroxidation and might prevent oxidative damages to *** extract offered a significant protection against plasmid and calf thymus UNA damage induced by hydroxyl radicals. The extract was also evaluated on different bacterial strains and the maximum antibacterial activity was exhibited against Escherichia coli（***） when compared with standard drug. Conclusions:These findings demonstrate that the methanol extract of *** has excellent anti-oxidant activities and could be considered as a potential source of lead molecules for pharmaceutical industries.

关键词： Free radicals Lipid peroxidation DPPH TBARS DNA damage Antibacterial activity Arnebia benthamii

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Experimental studies and artificial neural network modeling of surface tension of aqueous sodium L-prolinate solutions and piperazine blends

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Chinese Journal of Chemical Engineering 2019年第8期27卷 1904-1911页

作者： muhammad Shuaib Shaikh A.m.Shariff m.A.Bustam Sahil Garg Khadija Qureshi Pervez hameed Shaikh Inamullah Bhatti Department of Chemical Engineering Mehran University of Engineering&Technology JamshoroSindh 76062Pakistan CO2 Research Centre(CO2RES) Universiti Teknologi PETRONASBandar Seri Iskandar 32610PerakMalaysia School of Chemical Engineering The University of QueenslandSt Lucia 4072Australia Office of Research Innovation and Commercialization(ORIC) Mehran University of Engineering&Technology JamshoroSindh 76062Pakistan

The surface tension study is very crucial for the design of CO2 gas absorption contacting equipment. The significance of the surface tension has been increasing due to its consideration in various technological fields. This property influences the mass transfer and hydrodynamics of gas absorption systems, mainly multiphase systems, in which the interface between gas and liquid exists. Therefore, in this study, surface tension of aqueous solutions of sodium L-prolinate(SP) and piperazine(PZ) blends were measured at ten different temperatures from(298.15 to 343.15) K. The SP mass fractions were 0.10, 0.20, and 0.30;while the mass fractions of PZ were 0.02 and 0.05. The experimental results showed that the surface tension increase with increasing the mass fractions of SP and PZ in aqueous blends, and decrease linearly with rising temperature. The experimental data of surface tension were correlated by two empirical correlations as a function of temperature and mass fractions for estimating the predicted data using the optimized correlation coefficients. moreover, the modeling of surface tension data was carried out using Artificial Neural Network(ANN) approach. The results obtianed from ANN modeling were compared with applied empirical correlation. It was found that the ANN approach outperformed the empirical correlation used in this study. Besides, a quantitative analysis of variation(ANOVA) was performed in order to determine the significance of data. The surface tension of aqueous SP and SP + PZ was also compared with various conventional solvents.

关键词： Surface tension L-Prolinate Piperazine Correlation Prediction Neural network

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