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Geochemical analysis of multi-element in archaeological soils from Tappe Rivi in Northeast Iran

Acta Geochimica 2022年第1期41卷 132-146页

作者： Abdulmannan Rouhani Hamidreza Azimzadeh ahad Sotoudeh Judith Thomalsky Hojat Emami Graduate of School of Natural Resources and Desert Studies Department of Environmental ScienceYazd UniversityYazdIran German Archaeological Institute Tehran BranchTehranIran Department of Soil Science Ferdowsi University of MashhadMashhadIran

Multi-element analysis in historical sites is a major issue in archaeological studies;however,this approach is almost unknown among Iranian *** multi-element analysis of soil is very important to evaluate anthropogenic *** aim of this study consists of assessing the potential usefulness of multi-elemental soil analysis,obtained by Analytical Jena atomic absorption spectrophotometer(AAS) and ICP-MS,to recognize ancient anthropogenic features on the territory of Tappe Rivi(North Khorasan,Iran).For that purpose,a total of 80 ancient soil samples were sampled from each soil horizon and cultural *** research involved Fe,Al,Cd,Cu,Ni,Co,Cr,Pb,and P which trace element samples were extracted according to the International Standard ISO 11466 and phosphorus samples by Olsen ***,the contamination of the soils was assessed based on enrichment factors(EFs) by using Fe as a reference *** geochemical/archaeological approach highlights that the content of most elements in the Parthian and Sassanid ages were significantly higher than the contents of the elements in other zones,which shows that by the development of the eras,the content of the elements has also ***,the accumulation of metals in the Rivi site was significantly higher than in the control *** the sampled zones,enrichment factor(EF) indicated that the enrichment of Cu and phosphate at the Parthian and Sassanid had the highest *** result is important because it shows that the amount of metals and human activities are directly related to each other during different ages.

关键词： Tappe Rivi Multi-element Phosphorus Ancient human impact Samalghan plain

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Investigation of factors affecting rural drinking water consumption using intelligent hybrid models

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Water Science and Engineering 2023年第2期16卷 175-183页

作者： Alireza Mehrabani Bashar Hamed Nozari Safar Marofi Mohamad Mohamadi ahad ahadiiman Department of Water Science and Engineering Faculty of AgricultureBu-Ali Sina UniversityHamedan 65178-38695Iran University of Kurdistan Sanandaj 66177-15175Iran Sustainable Development Office of Hamedan Water and Wastewater Company Hamedan 65159-14478Iran

Identifying the factors affecting drinking water consumption is essential to the rational management of water resources and effective environment protection. In this study, the effects of the factors on rural drinking water demand were studied using the adaptive neuro-fuzzy inference system (ANFIS) and hybrid models, such as the ANFIS-genetic algorithm (GA), ANFIS-particle swarm optimization (PSO), and support vector machine (SVM)-simulated annealing (SA). The rural areas of Hamadan Province in Iran were selected for the case study. Five drinking water consumption factors were selected for the assessment according to the literature, data availability, and the characteristics of the study area (such as precipitation, relative humidity, temperature, the number of subscribers, and water price). The results showed that the standard errors of ANFIS, ANFIS-GA, ANFIS-PSO, and SVM-SA were 0.669, 0.619, 0.705, and 0.578, respectively. Therefore, the hybrid model SVM-SA outperformed other models. The sensitivity analysis showed that of the parameters affecting drinking water consumption, the number of subscribers significantly affected the water consumption rate, while the average temperature was the least significant factor. Water price was a factor that could be easily controlled, but it was always one of the least effective parameters due to the low water fee.

关键词： ANFIS Water distribution network Simulated annealing algorithm Support vector machine Adaptive neuro-fuzzy inference system

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How to Detect Deepfake Videos

How to Detect Deepfake Videos

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作者： ahad ALI 西安理工大学

学位级别：硕士

今天,利用Deepfake技术进行基于脸部的更改的发展已经允许用某人的照片替换一张照片。因此,不仅可以进行版本调整,还可以使用人工智能和深度学习来替换从一个参与者到下一个参与者的面部动作。样品可以从静态照片创建。因此,活的有机体... 详细信息

今天,利用Deepfake技术进行基于脸部的更改的发展已经允许用某人的照片替换一张照片。因此,不仅可以进行版本调整,还可以使用人工智能和深度学习来替换从一个参与者到下一个参与者的面部动作。样品可以从静态照片创建。因此,活的有机体和漫画可以以生动的方式描绘。由于最近的数字化,很难分辨真假新闻。有说服力的deepfakes可以迅速触及成千上万的个人,似乎由于社交网站的范围和速度而产生有害后果。虽然在检测领域的科学调查很少,但本文调查了 90多个免费发布的在线内容项目和研究论文,以确定deepfakes的确切检测,深度假创新的优势和危害,假账户的深假货越来越有效,尽管特别是在某些情况下,它们是无法辨别的。在人工智能、模式识别和深入学习方面的加速进步已经产生了改变视频的新方法。然而,检测技术主要用于可敬的原因,包括医疗和娱乐原因,恶意的个人也因非法或邪恶的原因利用它。检测deepfake视频的策略包括循环卷积神经网络,长期卷积网络,胶囊网络分析,自动编码器和GAN。处理Deepfake带来的检测方法和问题的多种方法现已在研究中详细介绍。深度学习技术为各种开发任务带来了高精度。遗传算法的发展导致了令人惊讶的详细错误信息的产生,被认为是保密,治理以及全球防御的风险。利用多种深入学习技术,许多当代的假帐户算法被认为是一个布尔分类困难分离合法视觉与伪造版本。这些方法通过测量更大变异性网络产生的视错觉,行为差异和颜色差异来实现传感器的工作。然而,这些策略需要大量的合法和恶意信息用于特征学习,并且它们在采用现代算法方法的变化原因下的效率在样本间评估中受到显着影响。基于深度学习的电影,这是使用人工智能创建的,已经获得了很大的兴趣。面部改变可以通过使用Deepfake软件与质量有关来完成。到目前为止,大量的deepfake电影已经在这个万维网上传播,其中大部分将针对名人和领导者。这些录音经常被用来损害个人的声誉和影响选民,对全球和谐造成伤害。尽管deepfake技术既没有有益的也没有有害的特性,但由于不好的原因,它经常被使用。已经进行了一些研究,以避免某些事情对人类文明构成危险,例如开发工具和制定全球标准。已经在这个万维网上传播,其中大部分将针对名人和领导者。这些录音经常被用来损害个人的声誉和影响选民,对全球和谐造成伤害。尽管deepfake技术既没有有益的也没有有害的特性,但由于不好的原因,它经常被使用。已经进行了一些研究,以避免某些事情对人类文明构成危险,例如开发工具和制定全球标准。本文将展示算法视频检测研究的现状,包括生产系统,各种识别方法,包括可用的标准。已经发现,目前的诊断方法不足以用于现实世界的场景,因此未来的研究应该集中在泛化和恢复力上。随着假帐户软件的实施,改变脸部电影的主题在过去几年中越来越受欢迎,假帐户软件更加强调教学媒体改变照片和电影。利用算法网络,Deepfake技术可以将目标影片中的特征替换为视频文件中的特征。头部电影很容易用这个软件制作,尽可能方便地获得大量的证据。作为国家信任虚假账户的有效工具,相关研究的数量也是如此。在过去几年中,新传感技术的开发取得了巨大进展。对于初学者来说,deepfake识别的电影数据管理的数量正在增加。可用于学习的信息量已经增加,包括早期阶段的微小数据集到大规模数据集。此外,一些研究机构已经越来越意识到虚假账户电影的风险,并试图刺激这方面的研究。Google,Twitter以及Windows合作组织了算法识别任务,该任务旨在开发用于检测deepfake电影的创新产品。由于这些因素,许多成功的识别算法已经被设计出来,并且在假冒识别挑战中显示出惊人的结果。虽然已经取得了重大进展,但当前deepfake方法仍然存在许多关键缺陷。Deepfake技术的发展使创建的视频变得越来越逼真。在这种情况下,传统方法不太可能识别由数字deepfake技术创建的修改电影。评估和估计deepfake相关研究的持续改进以及增强调查技术确实至关重要。我们将在本研究中强调这一现有的deepfake视频识别系统,以鼓励虚假数据信息检索的增长为目标。利用各种优化功能以及deepfake创建和检测技术,我们广泛评估了深刻的生物识别技术在识别虚假账户方面的有效性。根据Celeb-DF和FaceForensics++deepfake集合的实验,深度人脸对齐在检测算法方面优于多个CNNs和光学感觉。在Celeb-DF数据库中,给出的结果表明曲线下的最佳区域表示为AUC,而Eer表示利用生物认证识别假账户的错误率相等。这样的EER小于在celeb-DF样本上计算的EER,例如多重CNN以及视觉输入。使用FaceForensics++样本计算AUC和EER。现有的卷积神经网络deepfake活动和任务,包括ResNet,MesoIncept

关键词：深度假检测人脸检测人脸裁剪机器学习训练模型

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Design Principles-Based Interactive Learning Tool for Solving Nonlinear Equations

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Computer Systems Science & Engineering 2022年第3期40卷 1023-1042页

作者： ahad Alloqmani Omimah Alsaedi Nadia Bahatheg Reem Alnanih Lamiaa Elrefaei Computer Sciences Department Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddahSaudi Arabia Electrical Engineering Department Faculty of Engineering at ShoubraBenha UniversityCairoEgypt

Interactive learning tools can facilitate the learning process and increase student engagement,especially tools such as computer programs that are designed for human-computer ***,this paper aims to help students learn five different methods for solving nonlinear equations using an interactive learning tool designed with common principles such as feedback,visibility,affordance,consistency,and *** also compares these methods by the number of iterations and time required to display the *** study helps students learn these methods using interactive learning tools instead of relying on traditional teaching *** tool is implemented using the MATLAB app and is evaluated through usability testing with two groups of users that are categorized by their level of experience with *** with no knowledge in root-finding confirmed that they understood the root-finding concept when interacting with the designed *** positive results of the user evaluation showed that the tool can be recommended to other users.

关键词： Graphical user interface(GUI) interactive learning tool design principles nonlinear equations experimental design

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The effect of replacing pnictogen elements on the physical properties of SrMg_2X_2(X=N,P,As,Sb,Bi) Zintl compounds

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Chinese Physics B 2018年第4期27卷 369-375页

作者： G Murtaza Abdul ahad Khan M Yaseen A Laref Naeem Ullah Inayat ur Rahman Materials Modelling Labortary Department of PhysicsIslamia College University Department of Physics University of the Peshawar Department of Physics University of AgricultureFaisalabad Department of Physics and Astronomy College of ScienceKing Saud University Department of Physics City University of Hong Kong

The effect of replacing the anion from N to Bi down the group in the periodic table is investigated on SrMg2X2（X = N,P,As,Sb,Bi）.A full potential linearized augmented plane wave plus local orbitals method is used along with different exchange–correlation potentials to obtain the lattice constants,phonons,electronic,and optical properties of the Sr Mg2X2（X = N,P,As,Sb,Bi） Zintl compounds.A good agreement is achieved and our calculations are validated by previous experimental and theoretical *** compounds have shown stable dynamical behavior with gamma centered longitudinal response having no imaginary *** band structures reveal the semiconducting nature of the *** Pnictogen（X）-p state contributed mainly in the valence band and the Sr-d state forms the conduction of the *** charge transfer and low overlapping of the atomic densities indicates the preferable ionic bonding character of these *** the optical properties,real and imaginary parts of dielectric function,complex refractive index,birefringence,reflectivity,and optical conductivity are *** compounds can be utilized in the optical and optoelectronic devices.

关键词： Zintl compounds band structure optical response

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Hydrodynamics and suspended sediment transport at tidal inlets of Salut Mengkabong Lagoon, Sabah, Malaysia

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International Journal of Sediment Research 2010年第4期25卷 399-410页

作者： Md.Azharul HOQUE Bobita Golam ahad Ejria SALEH University Malaysia Sabah Kota Kinabalu 88999 SabahMalaysia

Salut-Mengabong Lagoon is located at the west coast of Sabah facing the South China Sea. At the bay side of the main inlet the lagoon splits into Salut and Mengabong Channels. Sediment dynamics at the inlets of the lagoon have recently received considerable attention. But any direct measurement of hydrodynamics and sediment flux are yet to be well documented. This study covers the field measurements of current velocity, water flux, suspended sediment concentration and sediment flux across the three transects (main inlet, Salut entrance and Mengkabong entrance) during typical spring and neap tidal cycles in southwest monsoon and northeast monsoon. Temporal variations and timeaveraged values of measured parameters are discussed. The inlets of Salut-Mengkabong Lagoon are found to be ebb-dominated. The time-averaged velocities during spring tidal measurements are found to be higher in the main inlet followed by Mengkabong entrance and Salut entrance. Suspended sediment concentration and sediment fluxes are substantially higher in spring tidal cycles compared to the same in neap tidal cycles. During spring tidal cycles, ebb tidal sediment fluxes are higher than the flood tidal fluxes. The ebb dominated flux across the main inlet led to the large ebb shoal.

关键词： Hydrodynamics Suspended sediment Lagoon Tidal inlet Salut Mengkabong

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Comparison of CNN-based deep learning architectures for rice diseases classification

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Artificial Intelligence in Agriculture 2023年第3期9卷 22-35页

作者： Md Taimur ahad Yan Li Bo Song Touhid Bhuiyan Department of Computer Science and Engineering Daffodil International UniversitySavarBangladesh School of Mathematics Physics and Computing University of Southern QueenslandToowoombaAustralia School of Engineering University of Southern Queensland ToowoombaAustralia Department of Computer Science and Engineering Faculty of Science and Information TechnologyDaffodil International UniversityBangladesh

Although convolutional neural network(CNN)paradigms have expanded to transfer learning and ensemble models from original individual CNN architectures,few studies have focused on the performance comparison of the applicability of these techniques in detecting and localizing rice ***,most CNN-based rice disease detection studies only considered a small number of diseases in their *** these shortcomings were addressed in this *** this study,a rice disease classification comparison of six CNN-based deep-learning architectures(DenseNet121,Inceptionv3,MobileNetV2,resNext101,Resnet152V,and Seresnext101)was conducted using a database of nine of the most epidemic rice diseases in *** addition,we applied a transfer learning approach to DenseNet121,MobileNetV2,Resnet152V,Seresnext101,and an ensemble model called DEX(Densenet121,EfficientNetB7,and Xception)to compare the six individual CNN networks,transfer learning,and ensemble *** results suggest that the ensemble framework provides the best accuracy of 98%,and transfer learning can increase the accuracy by 17%from the results obtained by Seresnext101 in detecting and localizing rice leaf *** high accuracy in detecting and categorisation rice leaf diseases using CNN suggests that the deep CNN model is promising in the plant disease detection domain and can significantly impact the detection of diseases in real-time agricultural *** research is significant for farmers in rice-growing countries,as like many other plant diseases,rice diseases require timely and early identification of infected diseases and this research develops a rice leaf detection system based on CNN that is expected to help farmers to make fast decisions to protect their agricultural yields and quality.

关键词： Deep learning Convolutional neural networks(CNNs) Transfer learning Plant leaf disease detection

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Standardization of proton-induced x-ray emission technique for analysis of thick samples

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Chinese Physics B 2015年第9期24卷 171-176页

作者： Shad Ali Johar Zeb Abdul ahad Ishfaq Ahmad M.Haneef Jehan Akbar Department of Physics Hazara University National Center of Physics (NCP)

This paper describes the standardization of the proton-induced x-ray emission（PIXE） technique for finding the elemental composition of thick samples. For the standardization, three different samples of standard reference materials（SRMs） were analyzed using this technique and the data were compared with the already known data of these certified SRMs. These samples were selected in order to cover the maximum range of elements in the periodic table. Each sample was irradiated for three different values of collected beam charges at three different times. A proton beam of 2.57 Me V obtained using 5UDH-II Pelletron accelerator was used for excitation of x-rays from the sample. The acquired experimental data were analyzed using the GUPIXWIN software. The results show that the SRM data and the data obtained using the PIXE technique are in good agreement.

关键词： standardization thick samples PIXE analysis

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Use of axial dispersion model for determination of Sherwood number and mass transfer coefficients in a perforated rotating disc contactor

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Chinese Journal of Chemical Engineering 2017年第1期25卷 53-61页

作者： Mehdi Asadollahzadeh Alireza Hemmati Meisam Torab-Mostaedi Mansour Shirvani ahad Ghaemi Zahra Sadat Mohsenzadeh Nuclear Fuel Cycle Research School Nuclear Science and Technology Research Institute P.O. Box： 11365-8486 Tehran Iran School of Chemical Engineering Iron University of Science and Technology Tehran P.O. Box 16765-163 Iran Department of Chemical Engineering Faculty of Engineering South Tehran Branch Islamic Azad University Iran

The mass transfer process in a perforated rotating disk contactor(PRDC) using a toluene-acetone-water system was *** volumetric overall mass transfer coefficients are calculated in a PRDC *** mass transfer directions are considered in *** influences of operating variables containing agitation rate,dispersed and continuous phase flow rates and mass transfer in the extraction column are *** to obtained results,mass transfer is significantly dependent on agitation rate,while the dispersed and continuous phase flow rates have a minor effect on mass transfer in the extraction ***,a novel empirical correlation is developed for prediction of overall continuous phase Sherwood number based on dispersed phase holdup,Reynolds number and mass transfer *** has been great agreement between experimental data and predicted values using a proposed correlation for all operating conditions.

关键词： Perforated rotating disk contactor Mass transfer coefficient dispersed phase holdup Interfacial area

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Deep learning long short-term memory combined with discrete element method for porosity prediction in gravel-bed rivers

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International Journal of Sediment Research 2023年第1期38卷 128-140页

作者： Duong Tran Anh ahad Hasan Tanim Daniel Prakash Kushwaha Quoc Bao Pham Van Hieu Bui HUTECH University Center for River Harbor and Landslide Research Chittagong University of Engineering & Technology Govind Ballabh Pant University of Agriculture and Technology Institute of Applied Technology Thu Dau Mot University Faculty of Mechanical Engineering Thuyloi University

The porosity of gravel riverbed material often is an essential parameter to estimate the sediment transport rate, groundwater-river flow interaction, river ecosystem, and fluvial geomorphology. Current methods of porosity estimation are time-consuming in simulation. To evaluate the relation between porosity and grain size distribution(GSD), this study proposed a hybrid model of deep learning Long Short-Term Memory(LSTM) combined with the Discrete Element Method(DEM). The DEM is applied to model the packing pattern of gravel-bed structure and fine sediment infiltration processes in threedimensional(3D) space. The combined approaches for porosity calculation enable the porosity to be determined through real time images, fast labeling to be applied, and validation to be done. DEM outputs based on the porosity dataset were utilized to develop the deep learning LSTM model for predicting bed porosity based on the GSD. The simulation results validated with the experimental data then segregated into 800 cross sections along the vertical direction of gravel pack. Two DEM packing cases, i.e., clogging and penetration are tested to predict the porosity. The LSTM model performance measures for porosity estimation along the z-direction are the coefficient of determination(R~2), root mean squared error(RMSE), and mean absolute error(MAE) with values of 0.99, 0.01, and 0.01 respectively, which is better than the values obtained for the Clogging case which are 0.71, 0.14, and 0.03, respectively. The use of the LSTM in combination with the DEM model yields satisfactory results in a less complex gravel pack DEM setup, suggesting that it could be a viable alternative to minimize the simulation time and provide a robust tool for gravel riverbed porosity prediction. The simulated results showed that the hybrid model of the LSTM combined with the DEM is reliable and accurate in porosity prediction in gravel-bed river test samples.

关键词： Numerical modeling Discrete element method LSTM Bed porosity Gravel-bed river

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