Organic Fertilizer Production and Application in Vietnam

Crop production is an important subsector of Vietnam’s agriculture, has an impressive achievement in last 30 years and based on the intensive production with increasing use of chemical fertilizer and pesticide. Consequences are the negative effects on environment and human health and food safety. Organic agriculture has become a trend worldwide and is developing rapidly in the world. In Vietnam the certified organic farming area has expanded since 2012. Organic market revenue in Vietnam is estimated to be at $132.15 million a year. Most Vietnamese certified organic products are exported to international markets. Organic agriculture using organic fertilizer is one of Vietnam government’s priorities. Vietnam already produced organic fertilizer from different materials by using different production technologies, but the production capacity is small and does not meet the demand for organic agriculture. Vietnam government encourages, promotes the organic fertilizer production, application and has the policy to develop the organic fertilizer in Vietnam

Neural network based patient recovery estimation of a PAM-based rehabilitation robot

Rehabilitation robots have shown a promise in aiding patient recovery by supporting them in repetitive, systematic training sessions. A critical factor in the success of such training is the patient’s recovery progress, which can guide suitable treatment plans and reduce recovery time. In this study, a neural network-based approach is proposed to estimate the patient’s recovery, which can aid in the development of an assist-as-needed training strategy for the gait training system. Experimental results show that the proposed method can accurately estimate the external torques generated by the patient to determine their recovery. The estimated patient recovery is used for an impedance control of a 2-DOF robotic orthosis powered by pneumatic artificial muscles, which improves the robot joint compliance coefficients and makes the patient more comfortable and confident during rehabilitation exercises

SEDIMENT BUDGET AND EROSION ASSESSMENT OF THE HAIHAU COASTAL ZONE, NAMDINH PROVINCE, NORTHERN VIETNAM

Joint Research on Environmental Science and Technology for the Eart

Prescribed Performance Function Based Sliding Mode Control of Opposing Pneumatic Artificial Muscles to Enhance Safety

The field of rehabilitation robotics has seen a significant increase in the utilization of Pneumatic Artificial Muscle (PAM)-based systems in recent years. These systems have demonstrated great potential in assisting and enhancing human movements and motor functions. However, as with any system that involves human interaction, safety is of the utmost importance. It is essential to ensure that the tracking error is kept within a safe range to prevent harm to people and equipment. This research proposes a control strategy that combines the exponential reaching law with a prescribed performance function to enhance safety in PAM-based rehabilitation robots. The prescribed performance function is designed to regulate the tracking error within predetermined limits during short and long-term operations, thereby mitigating large oscillations that may damage mechanical structures and patients. The experimental results indicate that the proposed controller demonstrated superior tracking accuracy and safety performance compared to traditional control methods. It is hoped that the findings of this study will contribute to developing safe and effective rehabilitation systems for patients in need

Preliminary assessments of debris flow hazard in relation to geological environment changes in mountainous regions, North Vietnam

Debris flow, widely viewed by geo-scientists as a special combination of landslide and flash flood, causes devastating damages to people and environment in northern mountainous regions of Vietnam. Field observations in the areas damaged by debris flows in northern Vietnam identified types of soils and rocks that were more likely to cause debris flows. Unlike flash floods, almost debris flows occurred at the end of the rainy season when soils and rocks were water-oversaturated thus mechanically weak; this is when pore water pressure decreases, lowering the strength from the soil. Landslides causing debris flows are commonly current slides. The tip of a landslide is often confined within a stream that has a permanent or seasonal flow. Debris flows mainly occur in proluvium, colluvial deposits or tectonic breccia zones. However, not a debris flow initiated in a tectonic breccia zone has been recorded in the northern mountainous regions of Vietnam. Colluvial deposits have been intensively investigated by many researchers worldwide. These deposits are commonly formed in neo-tectonic active zones, weak bed rocks, particularly old metamorphic rocks such as sericite shale, terrigenous and Cenozoic or late Mesozoic volcanic sedimentary rocks that are distributed at steep slopes and/or highly differentiated reliefs. These features appear to be a prerequisite for the exogenous processes, including rolling stones, falling rocks, landslides and surface erosions to occur. To study the mechanical and physical properties of colluvial deposits, the most practical approach is conducting experiments with large-sized samples or on-site experiments. However, this approach is expensive and not always favorable. Applying the rock mechanical theory, it is possible to examine C, j values if values of geological characteristics of rock blocks are known. Thus, the present study attempts clarify the cause-feedback relationship between the change of geological environment and geological hazard in general, and debris flows, in particular, providing a basic scientific insight for studying and predicting debris flows.ReferencesBauziene L., 2000. Colluvisols as a component of erosional and accumulative soil cover structures of east lithuania. European soil Bureau -  research report (7), 147-151.Hoek E., Marinos P., 2007. A brief history of the development of the Hoek-Brown failure criterion, Soils and Rocks, 2, 1-8.Irfan T.Y., Tang K.Y., 1992. Effect of the coarse fractions on the shear strength of colluvium. Geo report No 23, Geotechnical Engineering office, Civil Engineering Department Hong Kong.Lai K. W., 2011. Geotechnical properties of colluvial and alluvial deposits in Hong Kong. The 5th cross-strait Conf on Structural and geotechnical engineering (SGE-5), 735-744, Hong Kong China, 13-15 July 2011.Ngo Van Liem, Phan Trong Trinh, Hoang Quang Vinh, Nguyen Van Huong, Nguyen Cong Quan, Tran Van Phong, Nguyen Phuc Dat, 2016. Analyze the correlation between the geomorphic indices and recent tectonics of the Lo River fault zone in southwest of Tam Dao range, Vietnam J. Earth Sci., 38(1), 1-13.Richard E. Gray, 2008. Landslide problems on appalachian colluvial slopes. Geohazards in transportation in the appalachian region, Charleston, WV.Robert W. Fleming, Johnson M. Arvid, 1994. Landslide in Colluvium. U.S. Geological Survey Bulletin 2059-B.Tran Trong Hue (edit), 2004. Integrated assessment of geological disasters in Vietnam territory and prevention solutions (Phase II: The northern mountainous provinces), Report on Phase II of the Independent National project. Institute of Geology, Hanoi, 2003.Tran Van Tu (edit), 1999. Study of the scientific basis of formation and development of mountain floods (including flash floods), proposing the solution of warning,  mitigation, and reduction of natural disasters and damage.  Report of the project of the Vietnam Centre for Science and Technology, 1998 - 1999.Tran Van Tu, 2012. Scientific basis and method to set up the map of zonation area for sweeping flood, Journal of Sciences of the Earth, 34(3), 7-13

Le portail g-INFO pour surveiller la grippe Influenza A

Le portail g-INFO pour surveiller la grippe Influenza

An active learning framework for duplicate detection in SaaS platforms

With the rapid growth of users’ data in SaaS (Software-as-a-service) platforms using micro-services, it becomes essential to detect duplicated entities for ensuring the integrity and consistency of data in many companies and businesses (primarily multinational corporations). Due to the large volume of databases today, the expected duplicate detection algorithms need to be not only accurate but also practical, which means that it can release the detection results as fast as possible for a given request. Among existing algorithms for the deduplicate detection problem, using Siamese neural networks with the triplet loss has become one of the robust ways to measure the similarity of two entities (texts, paragraphs, or documents) for identifying all possible duplicated items. In this paper, we first propose a practical framework for building a duplicate detection system in a SaaS platform. Second, we present a new active learning schema for training and updating duplicate detection algorithms. In this schema, we not only allow the crowd to provide more annotated data for enhancing the chosen learning model but also use the Siamese neural networks as well as the triplet loss to construct an efficient model for the problem. Finally, we design a user interface of our proposed deduplicate detection system, which can easily apply for empirical applications in different companies

Duplicate identification algorithms in SaaS platforms

Existing duplicate records is one of the most common issues in many Software-as-as-Service (SaaS) platforms. In this paper, we study the duplicate identification problem in one specific SaaS platform related to quality and compliance management by using the address information. We interpret all typical mistakes from users that can generate the existent duplicated organizations in a given dataset, collected from the SaaS platform. Also, we create another set by crawling location data from Open Address (US Zone). We compare different methods, including Bag-of-words (using Cosine Distance), Record Linkage Toolkits, and Siamese Neural Networks using the triplet loss, in terms of precision, recall, and F1-score. The experimental results show that using Siamese Neural Networks can achieve a better performance in comparison with other techniques. We plan to publish our Open Address dataset and all implementation codes to facilitate further research in the related fields

A Framework for paper submission recommendation system

Nowadays, recommendation systems play an indispensable role in many fields, including e-commerce, finance, economy, and gaming. There is emerging research on publication venue recommendation systems to support researchers when submitting their scientific work. Several publishers such as IEEE, Springer, and Elsevier have implemented their submission recommendation systems only to help researchers choose appropriate conferences or journals for submission. In this work, we present a demo framework to construct an effective recommendation system for paper submission. With the input data (the title, the abstract, and the list of possible keywords) of a given manuscript, the system recommends the list of top relevant journals or conferences to authors. By using state-of-the-art techniques in natural language understanding, we combine the features extracted with other useful handcrafted features. We utilize deep learning models to build an efficient recommendation engine for the proposed system. Finally, we present the User Interface (UI) and the architecture of our paper submission recommendation system for later usage by researchers