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Effective photocatalytic conversion of formic acid using iron,copper and sulphate doped TiO_(2)

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Journal of Central South University 2022年第11期29卷 3592-3607页

作者： ZOUHEIR Morad tanji karim NAVIO Jose Antonio HIDALGO María Carmen JARAMILLO-PAEZ Cesar Augusto KHERBECHE Abdelhak Ecole Supérieure de Technologie de Fès UniversitéSidi Mohammed Ben AbdellahRoute d’ImouzzerBP 2427FèsMaroc Instituto de Ciencia de Materiales de Sevilla(ICMS) Centro Mixto Universidad de Sevilla-CSICAmérico Vespucio 4941092 SevillaSpain

In this paper,the combined addition of copper or iron and sulphate ions onto TiO_(2) prepared by a simple sol-gel method is studied for formic acid photocatalytic conversion.A wide structural and morphological characterization of the different photocatalysts was performed by X-ray diffraction(XRD),N_(2)-physisorption for BET surface area measurements,scanning and transmission electronic microscopies(SEM and TEM),UV-Vis diffuse spectroscopy(DRS)and X-ray photoelectron spectroscopy(XPS),in order to correlate the physico-chemical properties of the materials to their photocatalytic efficiencies for formic acid *** have shown important differences among the catalysts depending on the metal *** TiO_(2)/Cu(1%Cu)was the best photocatalyst obtaining about 100% formic acid conversion in only 5 *** appropriate physico-chemical features of this photocatalyst,given by the addition of combined copper and sulphate ions,explain its excellence in photocatalytic reaction.

关键词： copper iron sulphation doping TiO_(2) photocatalysis

Steel Surface Defect Detection Using Learnable Memory Vision Transformer

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Computers, Materials & Continua 2025年第1期82卷 499-520页

作者： Syed Tasnimul karim Ayon Farhan Md.Siraj Jia Uddin Department of Computer Science and Engineering BRAC UniversityDhaka1212Bangladesh Department of AI and Big Data Endicott CollegeWoosong UniversityDaejeon34606Republic of Korea

This study investigates the application of Learnable Memory Vision Transformers(LMViT)for detecting metal surface flaws,comparing their performance with traditional CNNs,specifically ResNet18 and ResNet50,as well as other transformer-based models including Token to Token ViT,ViT withoutmemory,and Parallel *** awidely-used steel surface defect dataset,the research applies data augmentation and t-distributed stochastic neighbor embedding(t-SNE)to enhance feature extraction and *** techniques mitigated overfitting,stabilized training,and improved generalization *** LMViT model achieved a test accuracy of 97.22%,significantly outperforming ResNet18(88.89%)and ResNet50(88.90%),aswell as the Token to TokenViT(88.46%),ViT without memory(87.18),and Parallel ViT(91.03%).Furthermore,LMViT exhibited superior training and validation performance,attaining a validation accuracy of 98.2%compared to 91.0%for ResNet 18,96.0%for ResNet50,and 89.12%,87.51%,and 91.21%for Token to Token ViT,ViT without memory,and Parallel ViT,*** findings highlight the LMViT’s ability to capture long-range dependencies in images,an areawhere CNNs struggle due to their reliance on local receptive fields and hierarchical feature *** additional transformer-based models also demonstrate improved performance in capturing complex features over CNNs,with LMViT excelling particularly at detecting subtle and complex defects,which is critical for maintaining product quality and operational efficiency in industrial *** instance,the LMViT model successfully identified fine scratches and minor surface irregularities that CNNs often *** study not only demonstrates LMViT’s potential for real-world defect detection but also underscores the promise of other transformer-based architectures like Token to Token ViT,ViT without memory,and Parallel ViT in industrial scenarios where complex spatial relationships are *** research m

关键词： Learnable Memory Vision Transformer(LMViT) Convolutional Neural Networks(CNN) metal surface defect detection deep learning,computer vision image classification learnable memory gradient clipping label smoothing t-SNE visualization

Self-supervised Learning for Speech Emotion Recognition Task Using Audio-visual Features and Distil Hubert Model on BAVED and RAVDESS Databases

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Journal of Systems Science and Systems Engineering 2024年第5期33卷 576-606页

作者： karim Dabbabi Abdelkarim Mars Research Unite of Analyse and Processing of Electrical and Energetic Systems Faculty of Sciences of TunisTunis El-Manar University2092Tunis-Tunisia Research Laboratory in Algebra Numbers Theory and Intelligent SystemsFaculty of Sciences of Monastir90 Mohamed V street5000-MonastirTunisia

Existing pre-trained models like Distil HuBERT excel at uncovering hidden patterns and facilitating accurate recognition across diverse data types, such as audio and visual information. We harnessed this capability to develop a deep learning model that utilizes Distil HuBERT for jointly learning these combined features in speech emotion recognition (SER). Our experiments highlight its distinct advantages: it significantly outperforms Wav2vec 2.0 in both offline and real-time accuracy on RAVDESS and BAVED datasets. Although slightly trailing HuBERT’s offline accuracy, Distil HuBERT shines with comparable performance at a fraction of the model size, making it an ideal choice for resource-constrained environments like mobile devices. This smaller size does come with a slight trade-off: Distil HuBERT achieved notable accuracy in offline evaluation, with 96.33% on the BAVED database and 87.01% on the RAVDESS database. In real-time evaluation, the accuracy decreased to 79.3% on the BAVED database and 77.87% on the RAVDESS database. This decrease is likely a result of the challenges associated with real-time processing, including latency and noise, but still demonstrates strong performance in practical scenarios. Therefore, Distil HuBERT emerges as a compelling choice for SER, especially when prioritizing accuracy over real-time processing. Its compact size further enhances its potential for resource-limited settings, making it a versatile tool for a wide range of applications.

关键词： Wav2vec 2.0 Distil HuBERT HuBERT SER audio and audio-visual features

On Direct Limits of Finite Products of Fields as Subrings of a Commutative Ring

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Algebra Colloquium 2016年第2期23卷 243-249页

作者： D. karim Department of Mathematics Faculty of Nador University Mohamed First P.O. Box 300 62702 Nador Morocco

Let R be a commutative ring. In this paper, we develop the existence of direct limits of finite products of fields as subrings of R.

关键词： Artinian ring direct limit of finite products of fields infinite product von Neumann regular ring zero-dimensional ring

On Crossed Product Algebras over Henselian Valued Fields

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Algebra Colloquium 2020年第3期27卷 389-404页

作者： Driss Bennis karim Mounirh Faculty of Sciences Research Center CeReMAR Mohammed V University in RabatRabatMorocco

Let D be a tame central division algebra over a Henselian valued field E,D be the residue division algebra of D,E be the residue field of E,and n be a positive *** prove that M_(n)(D)has a strictly maximal subfield which is Galois(resp.,abelian)over E if and only if M_(n)(D)has a strictly maximal subfield K which is Galois(resp.,abelian)and tame over E withГ_(K)■Г_(D),whereГ_(K)andГ_(D)are the value groups of K and D,*** partially generalizes the result proved by Hanke et *** 2016 for the case n=1.

关键词： (graded)Brauer group valued division algebras Henselization graded division algebras gauges

Conservation of challenging endemic plant species at high risk of extinction in arid mountain ecosystems:a case study of Rosa arabica Cré*** Egypt

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Journal of Mountain Science 2021年第10期18卷 2698-2721页

作者： karim OMAR Ibrahim ELGAMAL Nature Conservation Sector Ministry of EnvironmentCairo 11728Egypt United Nation Development Program(UNDP) Cairo 2007Egypt

Rosa arabica Cré*** a perennial shrub belonging to the family *** is endemic to the high mountain area of *** Protected Area(SCPA)in southern Sinai,Egypt,and is listed as one of the most 100 threatened plants in the ***,it has been listed as critically endangered by IUCN Red List due to its small extent of occurrence and tiny population *** reported the continuous decline in habitat quality for this species and the urgent need to carry out on-ground conservation ***,this research aims to conserve Rosa arabica through in situ practices by implementing the following steps,respectively:a)evaluate the current conservation status through IUCN Red List to extract the environmental factors controlling the species’distribution necessary for establishing the recovery program,b)determine the potential species habitat suitability under the current climate conditions using Maxent,and c)based on the previous two steps,the translocation process for *** in the suitable habitat will be done after the simple layering process as one of the most effective traditional vegetative methods for wild cultivation for this *** steps aimed to reduce the impact of threats and the risk of extinction through increasing the population size,the Extent of Occurrence(EOO),and the Area of Occupancy(AOO).We extracted the environmental factors controlling the target species’distribution and habitat suitability range using the IUCN Red List assessment and Species Distribution Model(SDM).The most suitable habitat for *** is predicted in the middle northern parts of SCPA,with the highest suitability in the High *** of driest quarter,precipitation of wettest month,precipitation of coldest quarter,and aspect are the highest mean contributors determining the distribution of *** in *** arabica potential distribution covers 324.4 km^(2)(7.46%)of the total SCPA area(4350 km^(2)).This area is divided into:18.1 km^(2)high

关键词： Mountain ecosystems Recovery Translocations Layering Conservation Species distribution modelling Maxent IUCN Red List

Generating Adversarial Samples on Multivariate Time Series using Variational Autoencoders

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IEEE/CAA Journal of Automatica Sinica 2021年第9期8卷 1523-1538页

作者： Samuel Harford Fazle karim Houshang Darabi Department of Mechanical and Industrial Engineering University of Illinois at ChicagoChicagoIL 60607 USA

Classification models for multivariate time series have drawn the interest of many researchers to the field with the objective of developing accurate and efficient ***,limited research has been conducted on generating adversarial samples for multivariate time series classification *** samples could become a security concern in systems with complex sets of *** study proposes extending the existing gradient adversarial transformation network(GATN)in combination with adversarial autoencoders to attack multivariate time series classification *** proposed model attacks classification models by utilizing a distilled model to imitate the output of the multivariate time series classification *** addition,the adversarial generator function is replaced with a variational autoencoder to enhance the adversarial *** developed methodology is tested on two multivariate time series classification models:1-nearest neighbor dynamic time warping(1-NN DTW)and a fully convolutional network(FCN).This study utilizes 30 multivariate time series benchmarks provided by the University of East Anglia(UEA)and University of California Riverside(UCR).The use of adversarial autoencoders shows an increase in the fraction of successful adversaries generated on multivariate time *** the best of our knowledge,this is the first study to explore adversarial attacks on multivariate time ***,we recommend future research utilizing the generated latent space from the variational autoencoders.

关键词： Adversarial machine learning deep learning multivariate time series perturbation methods

Correlation of p53 over-expression and alteration in p53 gene detected by polymerase chain reaction-single strand conformation polymorphism in adenocarcinoma of gastric cancer patients from India

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World Journal of Gastroenterology 2009年第11期15卷 1381-1387页

作者： Sajjad karim Arif Ali Department of Bio-technology Jamia Millia IslamiaNew Delhi 110025India Center of Excellence in Genomic Medicine Research King Abdulaziz UniversityPO Box 80216 Jaddah-21589Kingdom of Saudi Arabia

AIM： To study the alterations in p53 gene among Indian gastric cancer patients and to correlate them with the various clinicopathological parameters. METHODS： A total of 103 gastric cancer patients were included in this study. The p53 alterations were studied by both immunohistochemical method as well as polymerase chain reaction （PCR）-single strand conformation polymorphism （SSCP） analysis. We only studied four （exon 5, 6, 7, and 8） of the 11 ,p53 exons. The alterations in p53 were also correlated with respect to various clinicopathological parameters. RESULTS： Among 103 cases, p53 over-expression and alteration were detected in 37 （35.92%） and 19 （18.44%） cases, respectively. Most of the ,p53 alterations were found at exon 5 （31.54%）, followed by exon 6 （26.31%）, exon 7 （21.04%） and exon 8 （21.04%）. A significant correlation of p53 overexpression was found with p53 alteration （P = 0.000）. Concordance between ,p53 alteration （as detected by SSCP） and over-expression [as detected by immunohistochemistry （IHC）] was found in 75% cases. We found that IHC-positive/SSCP-negative cases accounted for 21% of cases and IHC-negative/SSCP- positive cases accounted for remaining 4% cases. CONCLUSION： Our results show that p53 gene mutations are significantly correlated with p53 protein over-expression, with 75% concordance in over-expression and alteration in the p53 gene, but 25% disconcordance also cautions against the assumption that p53 over-expression is always associated with a gene mutation. There may be other mechanisms responsible for stabilization and accumulation of p53 protein with no evidence of gene mutation that reflect an accumulation of a non-mutated protein, or a false negative SSCP result.

关键词： Gastric cancer p53 Single strandconformation polymorphism Gene mutation Immunohistochemistry

Divide and recombine approach for warranty database: estimating the reliability of an automobile component

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Data Science and Management 2024年第2期7卷 119-128页

作者： Md Rezaul karim Department of Statistics University of RajshahiRajshahi6205Bangladesh

The continuously updated database of failures and censored data of numerous products has become large, and on some covariates, information regarding the failure times is missing in the database. As the dataset is large and has missing information, the analysis tasks become complicated and a long time is required to execute the programming codes. In such situations, the divide and recombine (D&R) approach, which has a practical computational performance for big data analysis, can be applied. In this study, the D&R approach was applied to analyze the real field data of an automobile component with incomplete information on covariates using the Weibull regression model. Model parameters were estimated using the expectation maximization algorithm. The results of the data analysis and simulation demonstrated that the D&R approach is applicable for analyzing such datasets. Further, the percentiles and reliability functions of the distribution under different covariate conditions were estimated to evaluate the component performance of these covariates. The findings of this study have managerial implications regarding design decisions, safety, and reliability of automobile components.

关键词： Weibull regression model Warranty database Reliability EM algorithm Divide and recombine approach Managerial implications