Adaptation options for agricultural cultivation systems in the South Central Coast under the context of climate change: Assessment Report.

This report highlights the results of consultation meetings and field visits organized by the Department of Crop Production and the CGIAR Research Program on Climate Change, Agriculture and Food Security in Southeast Asia in association with the three offices of the Department of Agriculture and Rural Development in the South Central Coast provinces of Binh Thuan, Ninh Thuan, and Khanh Hoa, in combination with consultation with the provinces in the conference: “Summing up crops production in the Winter-Spring season in 2018-2019, implementing the Summer-Autumn season, Main rice season in 2019 for the South Central Coast and the Central Highlands” held by the Ministry of Agriculture and Rural Development in Tam Ky City, Quang Nam Province on 12 April 2019. The meetings underlined the progress made by the provinces on climate change adaptation and mitigation, options for risk reductions in agricultural production, and conversion of crop structure as results of implementing the guidelines of the provinces and the Sector, especially, solutions for reservation and efficient and economic use of water under the context of climate change. This assessment report also reviews some issues related to the agricultural transformation of the region in adapting to risks caused by climate change. They are based on comparative advantages in terms of geographical location and market of key agricultural products. This report also points out shortcomings in using land and unreasonable points in managing and using important natural resources, especially water, and provides recommendations for the agricultural transformation and inter-regional connection with the Central Highlands and the Southeast. The team also introduces climate-related risks maps and adaptation plans (CS MAP) which is applied in the five provinces in the Mekong Delta Region, and hopes this solution’s expansion shall be supported by the Ministry of Agriculture and Rural Development and the provinces

PIZZA: A Powerful Image-only Zero-Shot Zero-CAD Approach to 6 DoF Tracking

Estimating the relative pose of a new object without prior knowledge is a hard problem, while it is an ability very much needed in robotics and Augmented Reality. We present a method for tracking the 6D motion of objects in RGB video sequences when neither the training images nor the 3D geometry of the objects are available. In contrast to previous works, our method can therefore consider unknown objects in open world instantly, without requiring any prior information or a specific training phase. We consider two architectures, one based on two frames, and the other relying on a Transformer Encoder, which can exploit an arbitrary number of past frames. We train our architectures using only synthetic renderings with domain randomization. Our results on challenging datasets are on par with previous works that require much more information (training images of the target objects, 3D models, and/or depth data). Our source code is available at https://github.com/nv-nguyen/pizzaComment: 3DV Ora

An SHO-based approach to timetable scheduling: A case study

University timetable scheduling, which is a typical problem that all universities around the world have to face every semester, is an NP-hard problem. It is the task of allocating the right timeslots and classrooms for various courses by taking into account predefined constraints. In the current literature, many approaches have been proposed to find feasible timetables. Among others, swarm-based algorithms are promising candidates because of their effectiveness and flexibility. This paper investigates proposing an approach to university timetable scheduling using a recent novel swarm-based algorithm named Spotted Hyena Optimizer (SHO) which is inspired by the hunting behaviour of spotted hyenas. Then, a combination of SA and SHO algorithms also investigated to improve the overall performance of the proposed method. We also illustrate the proposed method on a real-world university timetabling problem in Vietnam. Experimental results have indicated the efficiency of the proposed method in comparison to other competitive metaheuristic algorithm such as PSO algorithm in finding feasible timetables.Web of Science5443942

A HEDGE ALGEBRAS BASED CLASSIFICATION REASONING METHOD WITH MULTI-GRANULARITY FUZZY PARTITIONING

During last years, lots of the fuzzy rule based classifier (FRBC) design methods have been proposed to improve the classification accuracy and the interpretability of the proposed classification models. Most of them are based on the fuzzy set theory approach in such a way that the fuzzy classification rules are generated from the grid partitions combined with the pre-designed fuzzy partitions using fuzzy sets. Some mechanisms are studied to automatically generate fuzzy partitions from data such as discretization, granular computing, etc. Even those, linguistic terms are intuitively assigned to fuzzy sets because there is no formalisms to link inherent semantics of linguistic terms to fuzzy sets. In view of that trend, genetic design methods of linguistic terms along with their (triangular and trapezoidal) fuzzy sets based semantics for FRBCs, using hedge algebras as the mathematical formalism, have been proposed. Those hedge algebras-based design methods utilize semantically quantifying mapping values of linguistic terms to generate their fuzzy sets based semantics so as to make use of fuzzy sets based-classification reasoning methods proposed in design methods based on fuzzy set theoretic approach for data classification. If there exists a classification reasoning method which bases merely on semantic parameters of hedge algebras, fuzzy sets-based semantics of the linguistic terms in fuzzy classification rule bases can be replaced by semantics - based hedge algebras. This paper presents a FRBC design method based on hedge algebras approach by introducing a hedge algebra- based classification reasoning method with multi-granularity fuzzy partitioning for data classification so that the semantic of linguistic terms in rule bases can be hedge algebras-based semantics. Experimental results over 17 real world datasets are compared to existing methods based on hedge algebras and the state-of-the-art fuzzy sets theoretic-based approaches, showing that the proposed FRBC in this paper is an effective classifier and produces good results

MEASURES TO IMPROVE THE LEARNING QUALITY OF BASKETBALL SUBJECT FOR NON-SPECIALIZED STUDENTS AT BAC NINH SPORTS UNIVERSITY OF VIETNAM UNDER THE CREDIT-BASED TRAINING SYSTEM

In using conventional scientific research methods in the field of physical training and sports, we selected and built the content of 04 measures to improve the quality of teaching Basketball subject for non-specialized students of Bac Ninh Sport University of Viet Nam under the credit-based training system, at the same time test the theory on the feasibility of measures by an expert method. The result showed that the selected and built measures were feasible and could be applied in practice to improve the quality of teaching Basketball subject for non-specialized students at Bac Ninh Sport University of Viet Nam under the credit-based training system.  Article visualizations

THE RELATIONSHIP BETWEEN COOPERATION, SUPPLY CHAIN PERFORMANCE AND TOUR OPERATOR PERFORMANCE: A CASE STUDY OF TOURISM SUPPLY CHAIN IN VIETNAM

Cooperation among members in the supply chain is essential and is a core element in the supply chain management strategy. This article uses a combination of qualitative and quantitative analysis methods. Structural equation modeling (SEM) demonstrates the relationship between cooperation, tourism supply chain performance, and operator performance in Vietnam. Research collected data from 242 domestic and international tour operators located in major Vietnam cities such as Ho Chi Minh City, Hanoi City, Da Nang City, and Can Tho City. The study has demonstrated that cooperation positively affects tourism supply chain performance and operator performance. Besides, tourism supply chain performance benefits operator performance in the Vietnamese tourism supply chain

A long range, energy efficient internet of things based drought monitoring system

The climate change and global warning have been appeared as an emerging issue in recent decades. In which, the drought problem has been influenced on economics and life condition in Vietnam. In order to solve this problem, in this paper, we have designed and deployed a long range and energy efficient drought monitoring based on IoT (Internet of Things) for real time applications. After being tested in the real condition, the proposed system has proved its high dependability and effectiveness. The system is promising to become a potential candidate to solve the drought problem in Vietnam

Synthesis of gelatin stabilized gold nanoparticles with seed particles enlargement by gamma Co-60 irradiation

Gold nanoparticles (AuNPs) with size from 13 to ~36 nm were synthesized by γ-irradiation method using gelatin as stabilizer. The AuNPs with controllable size were prepared using various concentration of Au3+ from 0.5 to 2 mM and seed particle enlargement with different ratios of [Au3+]/[Auo] up to 50. Maximum absorption wavelength (λmax) was measured by UV-Vis spectroscopy, and particle size was determined from TEM images. Results showed that the size of AuNPs increased with the Au3+ concentration. The seed enlargement approach is efficient to control the size of AuNPs. The value of λmax shifted from 527.5 nm (seed particles) to 537.5 nm, and the size of AuNPs increased from 13 nm (seed particles) to ~36 nm for concentration ratio of [Au3+]/[Auo] up to 40. Thus, γ-irradiation method is favorable for production of AuNPs with controllable size and high purity. The AuNPs/gelatin synthesized by γ-irradiation with the advantages of environmental friendly and mass production process may be potentially promising for applications in medicines, cosmetics and in other fields as well. Keywords. Gold, Nanoparticles, Gelatin, γ-irradiation

A framework for reviewing laws and policies for climate resilience – The case of the Vietnamese Mekong Delta

This article proposes a framework for reviewing to what extent laws and policies of a legal system support climate resilience. This article adopts the social-ecological system (SES) resilience theory and translates its core features into an operational framework which consists of four legal dimensions crucial for promoting climate resilience – adaptiveness of law, distributive justice, broad participation, and cross-scale interactions, and further identifies several indicators below each dimension. Then this article operationalizes the four legal dimensions via reviewing current Vietnamese climate adaptation laws and policies to assess to what extent they promote a climate-resilient Vietnamese Mekong Delta (VMD). While various barriers can be found in the current legal framework and policies which impede climate resilience, the latest National Climate Change Adaptation Plan demonstrates great improvement in facilitating climate resilience in a just, participatory and coordinated manner