ANTI-ODOUR TREATMENT ON 100% WOOL FABRIC USING COLORANTS FROM COFFEE GROUND RESIDUES

Coffee ground residues is considered as biomass and organic wastes that can be used for further application due to their deodorant properties. The purpose of this study is applying anti-odor treatment on 100% wool fabric by bi-functional dyeing process with colorant extracted from coffee ground residues. The extraction was done with water at 100ºC with different extracting ratio. The knitted wool fabrics were IR dyed with extracting solutions at 80ºC, 90 min, then dried at 60ºC, 30 min. The effectiveness of treatment on wool fabric was determined by colour strength K/S and FT-IR spectra. The colour fastness after hand wash were tested by AATCC standard to confirm the treatment after laundering, exhibited good color fastness at grade 4-5. The anti-odor effect was also evaluated according to AATCC 2017 Methods for Odor Evaluation of Textiles and other Materials for fabric before and after laundering, which proved the efficiency of deodorization of treated fabric by coffee residues extraction, even with strong odor like onio

H'mong mustard seed production calendar

H’mong mustard seed production calendars for awareness creation and capacity building activities in vegetable and seed production and storage among ethnic minority vegetable farming households in Northern Vietnam. Particularly designed with and for the H’Mong and Dao people in Lao Cai province and Thai people in Son La province in English and Vietnamese

Vegetable seed systems for ethnic minorities in northern Vietnam for enhanced nutrition and income

Vegetables are a main source of nutrition and income for ethnic minority farmers in Vietnam’s Northern highlands. While the consumption of vegetables and value chains for fresh retail produce and seed markets offer huge opportunities for household nutrition security and development, and particularly women inclusion, current smallholder systems suffer from multiple problems. The Integrated vegetable seed systems development project addressed these issues by elucidating how, and under what conditions, increased access and use of high-quality seed translates into enhanced smallholder nutrition and income security. This poster provides the project highlights presented at the NL-CGIAR Conference, 2-3 November 2022

French bean seed production calendar

French bean seed production calendars for awareness creation and capacity building activities in vegetable and seed production and storage among ethnic minority vegetable farming households in Northern Vietnam. Particularly designed with and for the H’Mong and Dao people in Lao Cai province and Thai people in Son La province in English and Vietnamese

Interest trade in agriculture sector between Vietnam and some WTO member countries

Based on secondary data from Uncomtrade, the article uses a gravity model to assess intra-industry trade of agricultural products between Vietnam and some WTO member countries. Research results show that in the period 2009-2018 Intra-agricultural trade between Vietnam and WTO member countries tends to increase over time as shown by the infra-agricultural trade index of agricultural products IIT. Productivity between Vietnam and China, Indonesia, Japan, Singapore, and Thailand were higher than other countries and relatively stable in the period 2009-2018. In addition, the results of quantitative analysis model show economic scale factors, per capita income, geographical distance, extent of economic openness, population size, and agricultural land area have a positive impact on intra-agricultural trade of Vietnam and some WTO member countries

Assessment of macroeconomic and ecological security of Vietnam in the current period

The article highlights the state of financial security in Vietnam in the period of 2000 - 2018. Based on secondary data collected from agencies such as the International Monetary Fund, the World Bank, and the State Bank of Vietnam Nam and based on four groups of indicators measuring financial security, namely the wealth level of the people, namely the wealth level of the people, economic scale and level of development, Prospects of economic growth, Economic stability. The research results show that before 2007, the level of integration of the economy was still low, so the financial security indicators were supported by the national debt situation, the ratio of high bad debt, High budget deficit, ineffective financial and monetary monitoring activities have not contributed much to security, and these indicators are quite low when compared to other countries in the region

A Cross-Country European Efficiency Measurement of Maritime Transport: A Data Envelopment Analysis Approach

Maritime transport, which includes shipping and port operations, is the fundamental basis of international trade and globalization. In transportation management, efficiency is critical for verifying performance and proposing the best countermeasure to meet predetermined goals. Various efforts in this field have been made to solve this problem satisfactorily. However, the significant proportion of conventional approaches are based on long-term observations and professional expertise, with only a few exceptions based on practice-based historical data. Data Envelopment Analysis (DEA) is a non-parametric technique for analyzing various output and input variables parallelly. The efficiency of maritime transport in European countries is explored using a two-stage DEA approach based on Malmquist and Epsilon-Based Measure (EBM). First, the Malmquist model analyses countries’ total productivity growth rates and their breakdown into technical efficiency (catch-up) and technology change (frontier-shift). Second, the EBM model is used to determine the efficiency and inefficiency of the maritime transportation systems in each European country. Apart from identifying the best-performing countries in specific areas over the study period (2016–2019), the results highlight that the gap in applying the EBM method to maritime transport has been successfully closed and that the emerging paradigm, when combined with the Malmquist model, can be a sustainable and appropriate evaluation model for other research areas

A Cross-Country European Efficiency Measurement of Maritime Transport: A Data Envelopment Analysis Approach

Maritime transport, which includes shipping and port operations, is the fundamental basis of international trade and globalization. In transportation management, efficiency is critical for verifying performance and proposing the best countermeasure to meet predetermined goals. Various efforts in this field have been made to solve this problem satisfactorily. However, the significant proportion of conventional approaches are based on long-term observations and professional expertise, with only a few exceptions based on practice-based historical data. Data Envelopment Analysis (DEA) is a non-parametric technique for analyzing various output and input variables parallelly. The efficiency of maritime transport in European countries is explored using a two-stage DEA approach based on Malmquist and Epsilon-Based Measure (EBM). First, the Malmquist model analyses countries’ total productivity growth rates and their breakdown into technical efficiency (catch-up) and technology change (frontier-shift). Second, the EBM model is used to determine the efficiency and inefficiency of the maritime transportation systems in each European country. Apart from identifying the best-performing countries in specific areas over the study period (2016–2019), the results highlight that the gap in applying the EBM method to maritime transport has been successfully closed and that the emerging paradigm, when combined with the Malmquist model, can be a sustainable and appropriate evaluation model for other research areas

Investigation and Optimization of the C-ANN Structure in Predicting the Compressive Strength of Foamed Concrete

Development of Foamed Concrete (FC) and incessant increases in fabrication technology have paved the way for many promising civil engineering applications. Nevertheless, the design of FC requires a large number of experiments to determine the appropriate Compressive Strength (CS). Employment of machine learning algorithms to take advantage of the existing experiments database has been attempted, but model performance can still be improved. In this study, the performance of an Artificial Neural Network (ANN) was fully analyzed to predict the 28 days CS of FC. Monte Carlo simulations (MCS) were used to statistically analyze the convergence of the modeled results under the effect of random sampling strategies and the network structures selected. Various statistical measures such as Coefficient of Determination (R2), Mean Absolute Error (MAE), and Root Mean Squared Error (RMSE) were used for validation of model performance. The results show that ANN is a highly efficient predictor of the CS of FC, achieving a maximum R2 value of 0.976 on the training part and an R2 of 0.972 on the testing part, using the optimized C-ANN-[3–4–5–1] structure, which compares with previous published studies. In addition, a sensitivity analysis using Partial Dependence Plots (PDP) over 1000 MCS was also performed to interpret the relationship between the input parameters and 28 days CS of FC. Dry density was found as the variable with the highest impact to predict the CS of FC. The results presented could facilitate and enhance the use of C-ANN in other civil engineering-related problems

A Two-Stage DEA Approach to Measure Operational Efficiency in Vietnam’s Port Industry

Logistics services aid import and export businesses located near ports in terms of ease and efficiency in the globalization era. Furthermore, economic growth and global import–export volumes immediately impact the port industry. This research aims to develop a two-stage Data Envelopment Analysis (DEA) model for measuring the performance efficiency of Vietnam’s top 18 seaports. The DEA resampling technique is used to forecast future performance, and the DEA Malmquist model analyzes efficiency improvement. First, the forecast data for the next three years, from 2021 to 2023, were obtained by resampling Lucas weight prediction with the highest accuracy. The results indicate that 12 out of all ports achieved an average progressive production efficiency over the entire study period of 2018–2023. Further, most ports have advanced slightly in technological efficiency, indicating that the determinants of increased productivity are the technical efficiency change indexes. This work contributes to the body of knowledge by being the first to apply the resampling technique in conjunction with the Malmquist model to forecast performance efficiency in the domain of the seaport sector. Furthermore, the managerial implications serve as a beneficial reference for operation managers, policymakers, and researchers when comparing the operational efficacy of seaports to diverse logistical scenarios