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Combining Entropy Optimization and Sobel Operator for Medical Image Fusion

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Computer Systems Science & Engineering 2023年第1期44卷 535-544页

作者： Nguyen Tu Trung tran thi ngan tran Manh Tuan To Huu Nguyen Faculty of Computer Science and Engineering Thuyloi University175 Tay SonDong DaHanoi010000Vietnam University of Information and Communication Technology Thai Nguyen UniversityThai Nguyen240000Vietnam

Fusing medical images is a topic of interest in processing medical *** is achieved to through fusing information from multimodality images for the purpose of increasing the clinical diagnosis *** fusion aims to improve the image quality and preserve the specific *** methods of medical image fusion generally use knowledge in many differentfields such as clinical medicine,computer vision,digital imaging,machine learning,pattern recognition to fuse different medical *** are two main approaches in fusing image,including spatial domain approach and transform domain *** paper proposes a new algorithm to fusion multimodal *** algorithm is based on Entropy optimization and the Sobel *** transform is used to split the input images into components over the low and high frequency ***,two fusion rules are used for obtaining the fusing *** rule,based on the Sobel operator,is used for high frequency *** second rule,based on Entropy optimization by using Particle Swarm Optimization(PSO)algorithm,is used for low frequency *** algorithm is implemented on the images related to central nervous system *** experimental results of the paper show that the proposed algorithm is better than some recent methods in term of brightness level,the contrast,the entropy,the gradient and visual informationfidelity for fusion(VIFF),Feature Mutual Information(FMI)indices.

关键词： Medical image fusion wavelet entropy optimization PSO Sobel operator

Picture-Neutrosophic Trusted Safe Semi-Supervised Fuzzy Clustering for Noisy Data

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Computer Systems Science & Engineering 2023年第8期46卷 1981-1997页

作者： Pham Huy Thong Florentin Smarandache Phung The Huan tran Manh Tuan tran thi ngan Vu Duc Thai Nguyen Long Giang Le Hoang Son Graduate University of Science and Technology Vietnam Academy of Science and TechnologyHanoi100000Vietnam Institute of Information Technology Vietnam Academy of Science and TechnologyHanoi100000Vietnam VNU Information Technology Institute Vietnam National UniversityHanoi100000Vietnam Department of Mathematics University of New MexicoGallup87301New MexicoUSA University of Information and Communication Technology Thai Nguyen UniversityThai Nguyen250000Vietnam Faculty of Computer Science and Engineering Thuyloi UniversityHanoi100000Vietnam

Clustering is a crucial method for deciphering data structure and producing new *** to its significance in revealing fundamental connections between the human brain and events,it is essential to utilize clustering for cognitive *** with noisy data caused by inaccurate synthesis from several sources or misleading data production processes is one of the most intriguing clustering *** data can lead to incorrect object recognition and *** research aims to innovate a novel clustering approach,named Picture-Neutrosophic Trusted Safe Semi-Supervised Fuzzy Clustering(PNTS3FCM),to solve the clustering problem with noisy data using neutral and refusal degrees in the definition of Picture Fuzzy Set(PFS)and Neutrosophic Set(NS).Our contribution is to propose a new optimization model with four essential components:clustering,outlier removal,safe semi-supervised fuzzy clustering and partitioning with labeled and unlabeled *** effectiveness and flexibility of the proposed technique are estimated and compared with the state-of-art methods,standard Picture fuzzy clustering(FC-PFS)and Confidence-weighted safe semi-supervised clustering(CS3FCM)on benchmark UCI *** experimental results show that our method is better at least 10/15 datasets than the compared methods in terms of clustering quality and computational time.

关键词： Safe semi-supervised fuzzy clustering picture fuzzy set neutrosophic set data partition with noises fuzzy clustering

Building the ARIMA Model for Forecasting the Production of Vietnam’s Coffee Export

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Journal of Applied Mathematics and Physics 2024年第4期12卷 1237-1246页

作者： Duy Quang Phung Quoc Thang Trinh Quang Truong Do ngan Giang Nguyen Van Ha Nguyen Gia Khiem Ngo thi Minh Ngoc tran Faculty of Technology and Data Science Foreign Trade University Hanoi Vietnam School of Economics and International Business Foreign Trade University Hanoi Vietnam

Coffee is a significant industry, accounting for 3% of Vietnam’s GDP, with annual export turnover consistently exceeding USD 3 billion. Despite global economic challenges affecting purchasing power at various times, Vietnam’s coffee exports in December 2023 continued to surge, reaching the highest level in the past 9 months at 190,000 tons, a 59.3% increase compared to November 2023, but still a slight 3.5% decrease from the same period last year. The export turnover reached USD 538 million, a 51% increase from November 2023 and a 26.4% increase from the same period last year. Therefore, forecasting the coffee export volume holds significant importance for coffee producers nationwide. this research employs the Box-Jenkins method to construct an ARIMA model for forecasting Vietnam’s coffee export volume based on annual data published by the General Statistics Office. Results indicate that among the models considered, the ARIMA(1, 1, 2) model is the most suitable. The study also provides short-term forecasts for Vietnam’s coffee export volume. However, the current model is limited to forecasting and is not yet optimized, as the assumed linearity in the model is a simplification.

关键词： ARIMA Forecasting Coffee Export Volume Data Science

Fusing Satellite Images Using ABC Optimizing Algorithm

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Computer Systems Science & Engineering 2023年第9期46卷 3901-3909页

作者： Nguyen Hai Minh Nguyen Tu Trung tran thi ngan tran Manh Tuan University of Information and Communication Technology Thai Nguyen UniversityThai Nguyen240000Vietnam Faculty of Computer Science and Engineering Thuyloi University175 Tay SonDong DaHanoi010000Vietnam

Fusing satellite(remote sensing)images is an interesting topic in processing satellite *** result image is achieved through fusing information from spectral and panchromatic images for *** this paper,a new algorithm based on based the Artificial bee colony(ABC)algorithm with peak signalto-noise ratio(PSNR)index optimization is proposed to fusing remote sensing images in this ***,Wavelet transform is used to split the input images into components over the high and low frequency ***,two fusing rules are used for obtaining the fused *** first rule is“the high frequency components are fused by using the average values”.The second rule is“the low frequency components are fused by using the combining rule with parameter”.The parameter for fusing the low frequency components is defined by using ABC algorithm,an algorithm based on PSNR index *** experimental results on different input images show that the proposed algorithm is better than some recent methods.

关键词： Remote sensing image satellite images image fusion wavelet PSNR optimization ABC

Radiative decays D*(s)→ D(s)γ in covariant confined quark model

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Chinese Physics C 2024年第2期48卷 45-56页

作者： C.T.tran M.A.Ivanov P.Santorelli Q.C.Vo Department of Physics HCMC University of Technology and EducationVo Van Ngan 1700000 Ho Chi Minh CityVietnam Bogoliubov Laboratory of Theoretical Physics Joint Institute for Nuclear Research141980 DubnaRussia Dipartimento di Fisica"E.Pancini" Universitàdi Napoli Federico ⅡComplesso Universitario di Monte S.AngeloVia CintiaEdificio 680126 NapoliItaly Istituto Nazionale di Fisica Nucleare Sezione di Napoli80126 NapoliItaly University of Science 700000 Ho Chi Minh CityVietnam

Radiative decays D((s))*→D((s))γare revisited in light of new experimental data from the BaBar and BESⅢ*** radiative couplings gD*Dγencoding nonperturbative QCD effects are calculated in the framework of the covariant confined quark model developed by *** compare our results with other theoretical studies and experimental *** couplings(in GeV-1)|g(D*+D+γ)|=0.45(9)and|g(D*0D0γ)|=1.72(34)calculated in our model agree with the corresponding experimental data|g(D*+D+γ)|=0.47(7)and|g(D*0D0γ)|=1.77(16).The most interesting case is the decay Ds*→Dsγ,for which a recent prediction based on light-cone sum rules at next-to-leading order|gDs*Dsγ|=0.60(19)deviates from the first(and only to date)lattice QCD result|gDs*Dsγ|=0.11(2)at nearly3σ.Our calculation yields|gDs*Dsγ|=0.29(6),which falls somehow between the two mentioned results,although it is larger than those predicted in other studies using quark models or QCD sum rules.

关键词： covariant quark model radiative decay charmed meson

A comparative analysis of weight-based machine learning methods for landslide susceptibility mapping in Ha Giang area

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Big Earth Data 2023年第4期7卷 1005-1034页

作者： Thanh Trinh Binh Thanh Luu trang Ha thi Le Duong Huy Nguyen Trong Van tran thi Hai Van Nguyen Khanh Quoc Nguyen Lien thi Nguyen Faculty of Computer Science Phenikaa UniversityYen NghiaHa DongHanoi 12116Vietnam Phenikaa Research and Technology Institute(PRATI) A&A Green Phoenix Group JSCNo.167 Hoang NganTrung HoaCau GiayHanoi 11313Vietnam Northwestern Geological Division General Department of Geology and Minerals of VietnamHanoiVietnam Youth union office Thuyloi University175 Tay SonDong DaHanoiVietnam Center of Remote Sensing and Geohazards Vietnam Institute of Geosciences and Mineral ResourcesHanoiVietnam

Landslide susceptibility maps (LSMs) are very crucial for planningpolicies in hazardous areas. However, the accuracy and reliability ofLSMs depend on available data and the selection of suitable *** study is conducted to produce LSMs by combinations of machinelearning methods and weighting techniques for Ha Giang province,Vietnam, where has limited data. In study area, we gather 11 landslideconditioning factors and establish a landslide inventory *** the weights of classes (or factors) is very important toprepare data for machine learning methods to generate LSMs. Wefrst use frequency ratio (FR) and analytic hierarchy process (AHP)techniques to generate the weights. Then, random forest (RF), supportvector machine (SVM), logistic regression (LR), and AHP methods arecombined with FR and AHP weights to yield accurate and reliableLSMs. Finally, the performance of these methods is evaluated by fivestatistical metrics, ROC and R-index. The empirical results have shownthat RF is the best method in terms of R-index and the five metrics, *** rate (0.9661), FP rate (0.0), ACC (0.9835), MAE (0.0046), and RMSE(0.0350) for this study area. this study opens the perspective of weightbasedmachine learning methods for landslide susceptibility mapping.

关键词： Landslide logistic regression random forest SvM Vietnam

Knowledge and attitude toward COVID-19 among healthcare workers at District 2 Hospital, Ho Chi Minh City

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Asian Pacific Journal of Tropical Medicine 2020年第6期13卷 260-265页

作者： Huynh Giao Nguyen thi Ngoc Han tran Van Khanh Vo Kim ngan Vo Van Tam Pham Le An Faculty of Public Health University of Medicine and Pharmacy at Ho Chi Minh CityVietnam Department of Infectious Diseases University Medical Center Ho Chi Minh CityVietnam Department of Scientific Research District 2 HospitalHo Chi Minh CityVietnam Department of Nursing District 2 HospitalHo Chi Minh CityVietnam Faculty of Nursing and Medical Technology University of Medicine Pham Ngoc Thach at Ho Chi Minh CityVietnam Center for the Training of Family Medicine Faculty of MedicineUniversity of Medicine and Pharmacy at Ho Chi Minh CityVietnam

Objective:To assess the knowledge and attitude toward coronavirus disease-2019(COVID-19)among healthcare workers at District 2 Hospital in Ho Chi Minh City(HCMC).Methods:A cross-sectional study was performed between January 2020 and February 2020 at District 2 Hospital.A systematic random sampling strategy was carried out and the data was collected through a self-administered questionnaire of the knowledge and attitude of healthcare workers regarding *** analysis was reported to describe the demographic,mean knowledge and attitude score of healthcare *** statistics including t-test,ANOVA and Spearman’s correlation were used to evaluate the relationship between study ***:A total of 327 eligible healthcare workers had a mean score of knowledge and attitude of 8.17±1.3(range 4-10)and 1.86±0.43(range 1-5),*** showed good knowledge and a positive ***,approximately two thirds of the participants knew the mode of transmission,the isolation period and treatment(67.0%,65.8%,and 58.4%,respectively),and 82.3%and 79.8%,respectively,held positive attitude regarding the risk of personal and family members getting *** was a negative correlation between knowledge scores and attitude scores(r=-0.21,P<0.001).Additionally,healthcare workerspredominately used social media to inform themselves about COVID-19(91.1%).Conclusions:The majority of healthcare workers had good knowledge and positive attitude toward ***,the level of some knowledge and attitude lower than that expected for their position level towards the *** education interventions and campaigns are required for healthcare workers.

关键词： Knowledge Attitude COVID-19 Healthcare worker District 2 Hospital

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越南大学生学术汉语写作元认知研究

越南大学生学术汉语写作元认知研究

作者： tran KIM ngan 华东师范大学

学位级别：硕士

与听、说、读相比,汉语写作是许多学习汉语者公认最常遇到的问题。写作是一种“输出”的学习模式,要求学习者了解语言并能够熟练运用。而学术汉语写作的要求更高,对语体、逻辑、语篇结构及引用等方面都有特殊要求。本研究从元认知切入... 详细信息

与听、说、读相比,汉语写作是许多学习汉语者公认最常遇到的问题。写作是一种“输出”的学习模式,要求学习者了解语言并能够熟练运用。而学术汉语写作的要求更高,对语体、逻辑、语篇结构及引用等方面都有特殊要求。本研究从元认知切入考察越南大学生对学术汉语写作的总体认知的认知。通过问卷调查、访谈法,考查了334名越南大学生对学术汉语写作的元认知现状。研究发现:1.越南学习者对自身普通汉语语言能力的认知态度比较乐观,而对于自身学术汉语写作能力认知评价较低;越南华裔学生普遍比非华裔学生对于自身总体汉语语言能力评价好;2.学术汉语写作经历及汉语水平等级对越南大学生学术汉语写作元认知知识有较大的影响;性别、学生类别、学习时长在元认知知识这维度上没有显著差异。关于学术汉语写作元认知策略,不同性别与不同汉语水平的越南大学生学术汉语写作的元认知策略略有差异;学生类别、学习时长、是否有过学术汉语写作的经历在元认知策略情况差别不大。3.在元认知知识的三个维度中,元认知任务知识高于元认知策略知识和元认知主体知识。4.在对学术汉语写作元认知策略知识和普通汉语写作元认知策略知识的判断上,越南学生判断准确率不高;5.越南学生对学术汉语写作元认知策略知识的认知和元认知策略能力的认知呈显著正相关,学生掌握的学术汉语写作元认知策略越丰富,其对于自身学术汉语写作的元认知策略能力的认知就越好。6.撰写学术汉语过程中,消极元认知体验出现的次数高于积极元认知体验。基于上述研究成果,本文认为学校应当开设相关的门课。汉语教师应消除学生对汉语写作的偏见、加强学生元认知的训练、关心学生的情绪及时化解学生的负面情绪。而学生本身应加强学术汉语写作的元认知、保持良好的情绪、培养制定计划的习惯。

关键词：学术汉语写作元认知越南学生

Effects of acute doxorubicin treatment on hepatic proteome lysine acetylation status and the apoptotic environment

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World Journal of Biological Chemistry 2014年第3期5卷 377-386页

作者： Amie J Dirks-Naylor Samir A Kouzi Joseph D Bero ngan TK tran Sendra Yang Raean Mabolo School of Pharmacy Wingate University

AIM: To determine if doxorubicin(Dox) alters hepatic proteome acetylation status and if acetylation status was associated with an apoptotic environment. METHODS: Doxorubicin(20 mg/kg; Sigma, Saint Louis, MO; n = 8) or NaCl(0.9%; n = 7) was administered as an intraperitoneal injection to male F344 rats, 6-wk of age. Once animals were treated with Dox or saline, all animals were fasted until sacrifice 24 h later. RESULTS: Dox treatment decreased proteome lysine acetylation likely due to a decrease in histone acetyltransferase activity. Proteome deacetylation may likely not be associated with a proapoptotic environment. Dox did not increase caspase-9,-8, or-3 activation nor poly(adenosine diphosphate-ribose) polymerase-1 cleavage. Dox did stimulate caspase-12 activation, however, it likely did not play a role in apoptosis induction. CONCLUSION: Early effects of Dox involve hepatic proteome lysine deacetylation and caspase-12 activa-tion under these experimental conditions.

关键词： Sirtuin 1 Sirtuin 3 Caspase Apoptosis Acetylation Histone deacetylase Histone acetyltransferase