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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

Two-dimensional perovskite SrNbO_(2) N with Zr doping for accelerating photoelectrochemical water splitting

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Journal of Materials Science & Technology 2023年第11期142卷 176-184页

作者： Thanh Tam Thi Tran van-Huy trinh Jeongsuk Seo Department of Chemistry College of Natural SciencesChonnam National University77 Yongbong-roBuk-guGwangju 61186South Korea

The superior ability of perovskite-type SrNbO_(2) N to absorb intensive visible light makes it a potential semiconductor to produce hydrogen and oxygen by photoelectrochemical(PEC)water splitting under *** surface morphologies,such as shape and structure,of the oxynitride strongly affect its photoactivity,although the mechanism has been hardly ***,we report a two-dimensional(2D)porous SrNbO_(2) N plate with Zr doping,nitrided from layered perovskite Sr_(5)Nb_(4)O_(15) and also its largely enhanced PEC water splitting ***^(4+)was doped in Sr_(5)Nb_(4)O_(15) during flux-assisted calcination using KCl,producing 2D-type truncated-octahedral Sr_(5)Nb_(4)O_(15):Zr plates approximately 50 nm in *** nitridation completely transformed Sr_(5)Nb_(4)O_(15):Zr to 2D single-crystalline SrNbO_(2) N:Zr with a large surface area,which was subsequently used to fabricate a thin and uniform photoanode by the spin coating *** a result,the Co(OH)_(x)/SrNbO_(2) N:Zr/FTO photoanode capable of absorbing visible light of up to 680 nm exhibited an activity of 2.0 mA cm^(-2) at 1.23 V vs the reversible hydrogen electrode for water splitting under AM 1.5G simulated *** improvement in photoactivity mainly originated from the 2D surface morphology of SrNbO_(2) N:Zr,which is clearly distinguishable from 3D-type *** to electrochemical analyses,the 2D structure of SrNbO_(2) N:Zr boosted the separation and accelerated the transfer of charges photogenerated during the water splitting,thus driving the reaction ***,the result empirically demonstrates that controlling the surface morphology of SrNbO_(2) N is an effective strategy to suppress the recombination of charges and minimize their diffusion pathway,eventually enhancing the PEC activity.

关键词： Solar water splitting Water oxidation BaNbO_(2)N Doping engineering Flux-assisted calcination Spin coating

Optimization of machine learning models for predicting the compressive strength of fiber-reinforced self-compacting concrete

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结构与土木工程前沿:英文版 2023年第2期17卷 284-305页

作者： Hai-van Thi MAI May Huu NGUYEN Son Hoang trinh Hai-Bang LY Civil Engineering Department University of Transport TechnologyHanoi 100000Vietnam Civil and Environmental Engineering Program Graduate School of Advanced Science and EngineeringHiroshima UniversityHiroshima 739-8527Japan

Fiber-reinforced self-compacting concrete(FRSCC)is a typical construction material,and its compressive strength(CS)is a critical mechanical property that must be adequately *** the machine learning(ML)approach to estimating the CS of FRSCC,the current research gaps include the limitations of samples in databases,the applicability constraints of models owing to limited mixture components,and the possibility of applying recently proposed *** study developed different ML models for predicting the CS of FRSCC to address these *** neural network,random forest,and categorical gradient boosting(CatBoost)models were optimized to derive the best predictive model with the aid of a 10-fold cross-validation technique.A database of 381 samples was created,representing the most significant FRSCC dataset compared with previous studies,and it was used for model *** findings indicated that CatBoost outperformed the other two models with excellent predictive abilities(root mean square error of 2.639 MPa,mean absolute error of 1.669 MPa,and coefficient of determination of 0.986 for the test dataset).Finally,a sensitivity analysis using a partial dependence plot was conducted to obtain a thorough understanding of the effect of each input variable on the predicted CS of *** results showed that the cement content,testing age,and superplasticizer content are the most critical factors affecting the CS.

关键词： compressive strength self-compacting concrete artificial neural network decision tree CatBoost

Emotion Recognition with Capsule Neural Network

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Computer Systems Science & Engineering 2022年第6期41卷 1083-1098页

作者： Loan trinh van Quang H.Nguyen Thuy Dao Thi Le School of Information and Communication Technology Hanoi University of Science and TechnologyHanoi10000Vietnam Faculty of Information Technology University of Transport and CommunicationsHanoi10000Vietnam

For human-machine communication to be as effective as human-tohuman communication, research on speech emotion recognition is *** the models and the classifiers used to recognize emotions, neural networks appear to be promising due to the network’s ability to learn and the diversity in configuration. Following the convolutional neural network, a capsuleneural network (CapsNet) with inputs and outputs that are not scalar quantitiesbut vectors allows the network to determine the part-whole relationships thatare specific 6 for an object. This paper performs speech emotion recognition basedon CapsNet. The corpora for speech emotion recognition have been augmented byadding white noise and changing voices. The feature parameters of the recognition system input are mel spectrum images along with the characteristics of thesound source, vocal tract and prosody. For the German emotional corpus EMODB, the average accuracy score for 4 emotions, neutral, boredom, anger and happiness, is 99.69%. For Vietnamese emotional corpus BKEmo, this score is94.23% for 4 emotions, neutral, sadness, anger and happiness. The accuracy scoreis highest when combining all the above feature parameters, and this scoreincreases significantly when combining mel spectrum images with the featuresdirectly related to the fundamental frequency.

关键词： Emotion recognition CapsNet data augmentation mel spectrum image fundamental frequency

Autophagy modulates physiologic and adaptive response in the liver

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Liver Research 2023年第4期7卷 304-320页

作者： trinh van Le Nhung Hai Truong Ai Xuan L.Holterman Laboratory of Stem Cell Research and Application University of Science-VNUHCMHo Chi Minh CityVietnam Vietnam National University Ho Chi Minh CityVietnam Faculty of Biology and Biotechnology University of Science-VNUHCMHo Chi Minh CityVietnam Department of Pediatrics and Surgery University of Illinois College of MedicineChicago and PeoriaILUSA

Autophagy is a physiological process that is ubiquitous and essential to the disposal or recycling of damaged cellular organelles and misfolded proteins to maintain organ homeostasis and *** importance in the regulation of liver function in normal and pathological conditions is increasingly *** review summarizes how autophagy regulates epithelial cell-and non-epithelial cellspecific function in the liver and how it differentially participates in hepatic homeostasis,hepatic injury response to stress-induced liver damage such as cholestasis,sepsis,non-alcoholic and alcohol-associated liver disease,viral hepatitis,hepatic fibrosis,hepatocellular and cholangiocellular carcinoma,and ***-based interventional studies for liver diseases that are currently registered in *** are *** the broad and multidirectional autophagy response in the liver,a more refined understanding of the liver cell-specific autophagy activities in a context-dependent manner is necessary。

关键词： Autophagy Biliary epithelial cell Hepatitis Hepatocellular carcinoma Hepatic stellate cell Hepatocyte

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

Novel Time Series Bagging Based Hybrid Models for Predicting Historical Water Levels in the Mekong Delta Region, Vietnam

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Computer Modeling in Engineering & Sciences 2022年第6期131卷 1431-1449页

作者： Nguyen Thanh Hoan Nguyen van Dung Ho Le Thu Hoa Thuy Quynh Nadhir Al-Ansari Tran van Phong Phan Trong trinh Dam Duc Nguyen Hiep van Le Hanh Bich Thi Nguyen Mahdis Amiri Indra Prakash Binh Thai Pham Institute of Geography Vietnam Academy of Science and TechnologyHanoi10000Viet Nam Department of Civil Environmental and Natural Resources EngineeringLulea University of TechnologyLulea97187Sweden Institute of Geological Sciences Vietnam Academy of Science and Technology(VAST)Dong DaHanoi10000Viet Nam University of Transport Technology Thanh XuanHa Noi10000Viet Nam Department of Watershed&Arid Zone Management Gorgan University of Agricultural Sciences&Natural ResourcesGorgan***Iran DDG(R)Geological Survey of India Gandhinagar382010India

Water level predictions in the river,lake and delta play an important role in flood *** year Mekong River delta of Vietnam is experiencing flood due to heavy monsoon rains and high *** subsidence may also aggravate flooding problems in this ***,accurate predictions of water levels in this region are very important to forewarn the people and authorities for taking timely adequate remedial measures to prevent losses of life and *** are so many methods available to predict the water levels based on historical data but nowadays Machine Learning(ML)methods are considered the best tool for accurate *** this study,we have used surface water level data of 18 water level measurement stations of the Mekong River delta from 2000 to 2018 to build novel time-series Bagging based hybrid ML models namely:Bagging(RF),Bagging(SOM)and Bagging(M5P)to predict historical water levels in the study *** of the Bagging-based hybrid models were compared with Reduced Error Pruning Trees(REPT),which is a benchmark ML *** data of 19 years period was divided into 70:30 ratio for the *** data of the period 1/2000 to 5/2013(which is about 70%of total data)was used for the training and for the period 5/2013 to 12/2018(which is about 30%of total data)was used for testing(validating)the *** of the models was evaluated using standard statistical measures:Coefficient of Determination(R2),Root Mean Square Error(RMSE)and Mean Absolute Error(MAE).Results show that the performance of all the developed models is good(R2>0.9)for the prediction of water levels in the study ***,the Bagging-based hybrid models are slightly better than another model such as ***,these Bagging-based hybrid time series models can be used for predicting water levels at Mekong data.

关键词： Computational techniques bagging water level time series algorithms

Dam deformation analysis based on BPNN merging models

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Geo-Spatial Information Science 2018年第2期21卷 149-157页

作者： Jingui Zou Kien-trinh Thi Bui Yangxuan Xiao Chinh van Doan School of Geodesy and Geomatics Wuhan UniversityWuhanChina Geomatics Centre Thuyloi UniversityHanoiVietnam Institute of Technique Special Engineering Le Quy Don Technical UniversityHanoiVietnam

Hydropower has made a significant contribution to the economic development of Vietnam,thus it is important to monitor the safety of hydropower dams for the good of the country and the *** this paper,dam horizontal displacement is analyzed and then forecasted using three methods:the multi-regression model,the seasonal integrated auto-regressive moving average(SARIMA)model and the back-propagation neural network(BPNN)merging *** monitoring data of the Hoa Binh Dam in Vietnam,including horizontal displacement,time,reservoir water level,and air temperature,are used for the *** results indicate that all of these three methods can approximately describe the trend of dam deformation despite their different forecast ***,their short-term forecasts can provide valuable references for the dam safety.

关键词： Dam deformation analysis multi-regression model Back-propagation Neural Network(BPNN) Seasonal Integrated Auto-regressive Moving Average(SARIMA)model merging model

Granulocyte colony-stimulating factor reduces biliary fibrosis and ductular reaction in a mouse model of chronic cholestasis

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Liver Research 2023年第1期7卷 90-98页

作者： trinh van Le Thanh Minh Dang Huy Quang Do Ai-Xuan Le Holterman Hong-Thuy Phan-Thi Thong Tan Tran Nhung Hai Truong Laboratory of Stem Cell Research and Application University of Science-VNUHCMHo Chi Minh CityVietnam Vietnam National University Ho Chi Minh CityVietnam Department of Pediatrics and Surgery University of Illinois College of MedicineChicagoILUSA Faculty of Biology and Biotechnology University of Science-VNUHCMHo Chi Minh CityVietnam

Background:Biliary atresia is a rare congenital bile duct disease that is the leading cause of liver fibrosis in *** colony-stimulating factor(GCSF)is a potential therapy for hepatocellular diseases,but data on GCSF for cholestatic conditions remain *** and methods:The current study examines the role of GCSF in improving bile duct obstruction in *** doses were administered:10.0 mg/kg/day and 61.5 mg/kg/day,which is the animal equivalent dose of 5.0 mg/kg in *** days(D7)after bile duct ligation(BDL),Swiss mice were treated with phosphate buffered saline or GCSF for 5 *** intrahepatic adaptive response of BDL mice was evaluated on postsurgical days D12,D19,and ***:Treatment with 61.5 mg/kg of GCSF resulted in a significant increase in circulating leukocytes and neutrophils on *** of liver injury,as shown by reduced aspartate aminotransferase levels,increased albumin levels and survival rate,as well as reduced intrahepatic inflammation and hepatic myeloperoxidase expression,downregulated ductular proliferation,periportal fibroblast activation,and fibrosis,enhanced expressions of hepatocyte growth factor,peroxisome proliferator-activated receptoralpha,and ki67,and suppressed expression of cleaved caspase-3 protein,was noted after treatment with 61.5 mg/kg of ***,GCSF treatment was associated with an increased number of intrahepatic cd3-Sca1tc-Kitt bone marrow cells.

关键词： Bile duct ligation(BDL) Biliary fibrosis Ductular reaction Granulocyte colony-stimulating factor(GCSF) Hepatic stellate cell(HSC)