Monitoring of Landslides in Mountainous Regions based on FEM Modelling and Rain Gauge Measurements

Vietnam is a country heavily influenced by climate change. The effect of climate change leads to a series of dangerous phenomena, such as landslides. Landslides occur not only in the mountainous province, but also in Delta provinces, where hundreds of landslides are reported annually in the North-Western provinces of Vietnam. These events have catastrophic impact to the community as well as the economy. In mountainous areas, the conditions for landslides to occur are met frequently, especially after heavy rains or geological activity, causing harm to the community as well as damaging or destroying much needed infrastructure and key transport routes. However, in Vietnam, investment in mountainous regions has been often lower than in urban areas. The meteorology monitoring and forecasting systems are ill equipped and overloaded, so they cannot deliver earlier and more accurate forecasts for complex weather events, unable to provide timely warnings. It can be seen that in countries that landslide often occur, researchers have been trying to develop low cost and efficient landslide detection system. This paper precisely addressed the problems mentioned, by designing and implementing an efficient and reliable Landslide Monitoring and Early Warning (LMnE) system based on the 3G/2G mobile communication system, and a rain gauge at the field site along with a carefully FEM (finite element method) simulation using the rain density information on the server. The system uses advanced processing algorithms combining obtained data at the central station

Wireless Technology for Monitoring Site-specific Landslide in Vietnam

Climate change has caused an increasing number of landslides, especially in the mountainous provinces of Vietnam, resulting in the destruction of vital transport and other infrastructure. Current monitoring and forecasting systems of the meteorology department cannot deliver accurate and reliable forecasts for weather events and issue timely warnings. This paper describes the development of a simple, low cost, and efficient system for monitoring and warning landslide in real-time. The authors focus on the use of wireless and related technologies in the implementation of a technical solution and some of the problems of the wireless sensor network (WSN) related to power consumption. Promising compressed sensing (CS) based solution for landslide monitoring is discussed and evaluated in the paper

Develop algorithms to determine the status of car drivers using built-in accelerometer and GBDT

In this paper, we introduce a mobile application called CarSafe, in which data from the acceleration sensor integrated on smartphones is exploited to come up with an efficient classification algorithm. Two statuses, "Driving" or "Not driving," are monitored in the real-time manner. It enables automatic actions to help the driver safer. Also, from these data, our software can detect the crash situation. The software will then automatically send messages with the user's location to their emergency departments for timely assistance. The application will also issue the same alert if it detects a driver of a vehicle driving too long. The algorithm's quality is assessed through an average accuracy of 96.5%, which is better than the previous work (i.e., 93%)

Classification of cow’s behaviors based on 3-DoF accelerations from cow’s movements

Cow’s behavior classification helps people to monitor cow activities, thus the health and physiological periods of cows can be well tracked. To classify the behavior of cows, the data from the 3-axis acceleration sensor mounted on their neck is often used. Data acquisition and preprocessing of sensor data is required in this device. We acquire data from the 3-axis acceleration sensor mounted on the cows’neck and send to the microcontrollter. At the microcontroller, a proposed decision tree is applied in real-time manner to classify four important activities of the cows (standing, lying, feeding, and walking). Finally, the results can be sent to the server through the wireless transmission module. The test results confirm the reliability of the proposed device

High Sound-contrast Inverse Scattering by MR-MF-DBIM Scheme

In ultrasound tomography, cross-sectional images represent the spatial distribution of the physical parameters of a target of interest, which can be obtained based on scattered ultrasound measurements. These measurements can be obtained from dense datasets collected at different transmitter and receiver locations, and using multiple frequencies. The Born approximation method, which provides a simple linear relationship between the objective function and the scattering field, has been adopted to resolve the inverse scattering problem. The distorted Born iterative method (DBIM), which utilizes the first-order Born approximation, is a productive diffraction tomography scheme. In this article, the range of interpolation applications is extended at the multilayer level, taking into account the advantages of integrating this multilayer level with multiple frequencies for the DBIM. Specifically, we consider: (a) a multi-resolution technique, i.e., a multi-step interpolation for the DBIM: MR-DBIM, with the advantage that the normalized absolute error is reduced by 18.67% and 37.21% in comparison with one-step interpolation DBIM and typical DBIM, respectively; (b) the integration of multi-resolution and multi-frequency techniques with the DBIM: MR-MF-DBIM, which is applied to image targets with high sound contrast in a strongly scattering medium. Relative to MR-DBIM, this integration offers a 44.01% reduction in the normalized absolute error

Smart Shopping Assistant: A Multimedia and Social Media Augmented System with Mobile Devices to Enhance Customers’ Experience and Interaction

Multimedia, social media content, and interaction are common means to attract customers in shopping. However these features are not always fully available for customers when they go shopping in physical shopping centers. The authors propose Smart Shopping Assistant, a multimedia and social media augmented system on mobile devices to enhance users’ experience and interaction in shopping. Smart Shopping turns a regular mobile device into a special prism so that a customer can enjoy multimedia, get useful social media related to a product, give feedbacks or make actions on a product during shopping. The system is specified as a flexible framework to take advantages of different visual descriptors and web information extraction modules. Experimental results show that Smart Shopping can process and provide augmented data in a realtime-manner. Smart Shopping can be used to attract more customers and to build an online social community of customers to share their interests in shopping

Screening of endophytes from rubber trees (hevea brasiliensis) for biological control of Corticium salmonicolor

28 leaves and living-tissue samples of rubber tree (Hevea brasiliensis) were collected from Ho Chi Minh City, Binh Phuoc province and Binh Duong province (Viet Nam). We isolated and screened endophytes that have potential application as agents for biocontrol of Corticium salmonicolor, the agent of Pink Disease in rubber trees. As a result, 21 strains of endophytic bacteria and 14 strains of endophytic fungi were isolated. Antagonistic activity of the endophytes towards C. salmonicolor was checked by using a dual culture. Testing results showed that: T9, T15 and T16 strains have inhibited C. salmonicolor. T9 and T16 strains showed result that 100% of inhibiting C. salmonicolor at the concentration of 1:1. In the test of ability to kill C. salmonicolor, T9 and T16 strains showed that they could kill C. salmonicolor after 3 sprays of bacterial filtrate. T9 and T6 strains, which were identified by biochemical methods, have similar characteristics to Bacillus thuringiensis

ĐA DẠNG DI TRUYỀN QUẦN THỂ CÁ CHÌNH HOA (Anguilla marmorata) TẠI QUẢNG TRỊ

This study was conducted to evaluate the population genetic diversity of the wild Anguilla marmorata in Quang Tri province by comparing the DNA sequences of the mitochondrial control region (CR) gene with those of other giant mottled eel populations in the world. The results indicate that the genetic distance between individuals in the Quang Tri population ranged from 0 to 0.261, with an average of 0.024. Among 31 individuals, there were 203 distinct polymorphism sites (S), which led to 209 mutation sites (Eta) and 31 different haplotypes. The average number of distinct nucleotides (k) was 29,299. The nucleotide diversity factor (Pi) accounted for 26.09 × 10–3, and the minimum number of recombination processes (Rm) in the population was 51 events. The majority of eel samples collected at the site had close genetic relationships with those of the North Pacific population (27/31 individuals), and four eel samples had close genetic relationships with those of the South Pacific population. The finding of the four giant mottled eels in Quang Tri belonging to the South Pacific population is considered a significant result of this study.Nghiên cứu này được thực hiện nhằm đánh giá đa dạng di truyền của quần thể cá Chình hoa (Anguilla marmorata) tự nhiên tại tỉnh Quảng Trị dựa trên việc so sánh trình tự DNA của vùng gene điều khiển CR (control region) ty thể với các quần thể cá Chình hoa trên thế giới. Kết quả cho thấy khoảng cách di truyền giữa các cá thể trong quần thể dao động từ 0 đến 0,261, đạt trung bình 0,024. Trong 31 cá thể, 203 vị trí đa hình tách biệt (S) đã tạo ra 209 vị trí đột biến (Eta) với 31 kiểu haplotype khác nhau. Số lượng các nucleotide khác biệt trung bình là 29.299 (k); hệ số đa dạng nucleotide chiếm 26,09 × 10–3 (Pi); số lượng tối thiểu để xẩy ra quá trình tái tổ hợp (Rm) trong quần thể tương ứng với 51 sự kiện. Phần lớn cá thể thu được tại Quảng Trị có quan hệ di truyền gần gũi với quần thể cá Chình hoa Bắc Thái Bình Dương (27/31 cá thể) và 4 cá thể có mối quan hệ di truyền gần gũi với quần thể Nam Thái Bình Dương. Việc phát hiện các cá thể Chình hoa tại Quảng Trị có di truyền gần gũi với các cá thể thuộc Nam Thái Bình Dương được xem như một điểm đáng chú ý trong nghiên cứu này

Applied bioinformatics tools for analysis of Microrna-214 expression and prediction of its potential targets genes in Nasopharyngeal carcinoma

miRNA (microRNA) are short RNA molecules in length from 20 to 24 nucleotides that have been shown to play an important role in regulating gene expression in many different types of human cancer. Meanwhile, miRNA-214 is one of the known miRNAs involved in the formation of nasopharyngeal carcinoma (NPC) through overexpression that promotes proliferation and development of cancer cells. However, in Vietnam, the study of miR-214 related to NPC has not been conducted yet. With the aims to develop the further studies of miR-214 on NPC in Vietnamese patients, in this initial study, we conducted the analysis of miR-214 expression in previous publications, as well as the prediction of miR-214 potential target genes, which involved in many cellular pathways. Here we applied bioinformatics tools to predict miRNAs and their targets, and discuss the role of miR-214 in the context of human cancers. As the results, miR-214 acted as the oncogenic roles in NPC, relevanted to many pathways, such as cell proliferation, apoptosis, metastasis and invasion through the its target genes LTF, Bim, Bax, LINC0086, etc. In conclusion, the use of computional approaches facilitate the further experimental validation of miRNAs in general, particularly miR-214, in Vietnamese NPC patients

Modelling nitrous oxide (N2O) emission from rice field in impacts of farming practices: A case study in Duy Xuyen district, Quang Nam province (Central Vietnam)

Nitrous oxide (N2O) emisison from paddy soil via the soil nitrification and denitrification processes makes an important contribution to atmospheric greenhouse gas concentrations. The soil N2O emission processes are controlled not only by biological, physical and chemical factors but also by farming practices. In recent years, modeling approach has become popular to predict and estimate greenhouse gas fluxes from field studies. In this study, the DeNitrification–DeComposition (DNDC) model were calibrated and tested by incorporating experimental data with the local climate, soil properties and farming management, for its simulation applicability for the irrigated rice system in Duy Xuyen district, a delta lowland area of Vu Gia-Thu Bon River Basin regions. The revised DNDC was then used to quantitatively estimate N2O emissions from rice fields under a range of three management farming practices (water management, crop residue incorporation and nitrogen fertilizer application rate). Results from the simulations indicated that (1) N2O emissions were significantly affected by water management practices; (2) increases in temperature, total fertilizer N input substantially increased N2O emissions. Finally, five 50-year scenarios were simulated with DNDC to predict their long-term impacts on crop yield and N2O emissions. The modelled results suggested that implementation of manure amendment or crop residue incorporation instead of increased nitrogen fertilizer application rates would more efficiently mitigate N2O emissions from the tested rice-based system.Phát thải nitơ ôxít (N2O) từ canh tác lúa nước (thông qua quá trình nitrat hóa và phản nitrat hóa) đóng góp đáng kể vào tổng lượng khí nhà kính có nguồn gốc từ sản xuất nông nghiệp. Quá trình phát thải N2O là không chỉ phụ thuộc vào các yếu tố sinh-lý-hóa học mà còn phụ thuộc các phương pháp canh tác. Trong những năm gần đây, việc ứng dụng mô hình hóa nhằm tính toán và ước lượng sự phát thải khí nhà kính ngày càng trở lên phổ biến. Trong nghiên cứu này, số liệu quan trắc từ thí nghiệm đồng ruộng và dữ liệu về đất đai, khí hậu, biện pháp canh tác được sử dụng để kiểm nghiệm và phân tích độ nhạy của mô hình DNDC (mô hình sinh địa hóa). Sau đó, mô hình được sử dụng để tính toán lượng N2O phát thải trong canh tác lúa nước dưới các phương thức canh tác khác nhau (về chế độ tưới, mức độ vùi phụ phẩm, bón phân hữu cơ, phân đạm) tại huyện Duy Xuyên, thuộc vùng đồng bằng thấp của lưu vực sông Vu Gia-Thu Bồn. Kết quả kiểm định chỉ ra rằng (1) sự phát thải N2O bị ảnh hưởng đáng kể do sự thay đổi chế độ tưới; (2) nhiệt độ tăng và lượng phân bón N tăng sẽ làm tăng phát thải N2O. Kết quả mô phỏng về tác động lâu dài (trong 50 năm) của các yếu tố đến năng suất cây trồng và phát thải N2O cho thấy: Việc sử dụng phân hữu cơ và phụ phẩm nông nghiệp thay thế cho việc bón phân đạm sẽ giúp giảm phát thải N2O đáng kể