CONSTRUCTIVE AND INVESTIGATE THE GENERALIZED CONVOLUTION WITH THE WEIGHT FUNCTION FOR THE FOURIER COSINE AND SINE TRANSFORMS

Joint Research on Environmental Science and Technology for the Eart

Regional conflict management: challenges of the border disputes of Cambodia, Laos, and Vietnam

"Dieser Beitrag analysiert Grenzstreitigkeiten Kambodschas, Laos und Vietnams. Gelöste und ungelöste Konflikte, als auch weitere Trends im Management von Grenzstreitigkeiten werden dabei betrachtet. Herausforderungen in der Umsetzung von Vereinbarungen sowie in der Schlichtung noch ungelöster Dispute und deren Implikationen auf das regionale Konfliktmanagement werden adressiert. Die Studie zeigt auf, dass Laos und Vietnam beträchtliche Fortschritte im Management und in der Lösung ihrer Grenzstreitigkeiten gemacht machen, während Kambodscha bis dato weniger erfolgreich war." (Autorenreferat)"This study analyzes the border disputes of Cambodia, Laos, and Vietnam, respectively. Both settled and unsettled disputes are encompassed. The study outlines the settlements reached and the remaining unsettled disputes. Furthermore, the broader trends in managing the border disputes are analyzed and remaining challenges, both in implementing agreements and in managing the unsettled disputes, are addressed. So are the implications for regional conflict management. The study displays that both Laos and Vietnam have made considerable progress in both managing and settling their existing border disputes, whereas Cambodia has thus far been less successful." (author's abstract

Automatic detection of pavement crack feature on images taken from specialized road surface survey vehicle

Approaching to PDCA (Plan - Do - Check - Take Action) in management of infrastructure asset requires digital transformation, sufficient data and strong database supporting management, analysis as well as creation of data-driven decision making tools. For pavements, data including condition indicators such as roughness and rutting depth are collected automatically during the survey vehicle travelling. However, pavement crack ratio and crack features of pattern and segmentation have not been detected by the system but manual in the case in Vietnam. The paper presents result of research on algorithm of statistic machine learning model in AI applying deep learning algorithm to automatically detect crack feature on pavement photos for enhancement of the performance and productivity of current survey technology. In the research, a deep architecture using convolutional neural network (CNN) for crack segmentation on gray scale images has been developed. The results show the CNN model for crack segmentation is better than other methods using traditional digital processing such as the Gabor filters or threshold and machine learning such as Adaboost

A review on chemical profiles and biological activities of essential oil from some plants belonging to family Scrophulariaceae

Scrophulariaceae is a large family, many species of which have been reported to have a wide range of biological activities and uses as folk medicines. The essential oils from species belonging to this family mainly contain monoterpene hydrocarbons, oxygenated monoterpenes, sesquiterpene hydrocarbons, oxygenated sesquiterpenes and non-terpenes. Furthermore, their essential oils have been reported to have a variety of biological activities such as antimicrobial, antioxidant, insecticidal etc. The objective of this review is to provide a brief overview of the chemical composition and biological activities of the essential oils isolated from different parts of species included in the Scrophulariaceae family. In addition, this paper also introduces the therapeutic potentials and provides the evidence for future medicinal applications of those species

Generalized Convolution Transforms and Toeplitz Plus Hankel Integral Equations

Mathematics Subject Classification: 44A05, 44A35With the help of a generalized convolution and prove Watson’s and Plancherel’s theorems. Using generalized convolutions a class of Toeplitz plus Hankel integral equations, and also a system of integro-differential equations are solved in closed form

Assessment and Simulation of Impacts of Climate Change on Erosion and Water Flow by Using the Soil and Water Assessment Tool and GIS: Case Study in Upper Cau River basin in Vietnam

The Upper Cau river basin which plays an important role in socio-economic developments the North of Vietnam is sensitive to changes of climate influencing flows, erosion, and water resources. The main objective of this study is to assess and simulate impacts of climate change on erosion and water flow in the basin. Using a GIS database and Soil and Water Assessment Tool (SWAT) model, the water flow and soil loss were assessed with data in period 1980-1999 called the based period, then simulated until 2100 considering the medium emission scenario (B2). The simulation result showed that the total annual runoff and soil loss tends to increase compared to the base period. For flow, the change rate of the simulation period is higher than the base period; the water flow rate will increase by 0.22% (2020-2039) and up to 1.37% (2080-2100). The total annual soil loss of the simulation period at Gia Bay station tends to increase steadily compared to the baseline, namely by 6.2% (2020-2039) and 25.5% (2080-2100). Overall, the result in this study shows that effects of climate changes on the basin are severe enough under the scenario B2 which is useful for authorities for basin management.ReferencesAli R., McFarlane D., Varma S., Dawes W., Emelyanova I., Hodgson G., Charles S., 2012. Potential climate change impacts on groundwater resources of south-western Australia. Journal of Hydrology, 475, 456-472. doi: http://dx.doi.org/10.1016/j.jhydrol.2012.04.043 Arnell N. W., 2004. Climate change and global water resources: SRES emissions and socio-economic scenarios. Global Environmental Change, 14(1), 31- 52. doi:10.1016/j.gloenvcha.2003.10.006 Arnold J. G., Fohrer N., 2005. SWAT2000: Current capabilities and research opportunities in applied watershed modeling. Hydrol. Proc., 19(3), 563-572. 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Influence of biofertilizer produced using drumstick (Moringa oleifera L.) unused parts on the growth performance of two leafy vegetables

The non-edible parts of Moringa oleifera, such as stems, branches or leaf petioles, have often been discarded while the leaves are consumed as a vegetable or are used to produce organic fertilizer. This study aimed to determine the optimal conditions for producing Moringa organic fertilizer (MOF) from previously unused parts and to compare these fertilizers with cow manure and bio-organic fertilizer. Seventy kilograms of the unused Moringa parts were blended with fifty kilograms of manure, 0.2 kilogram of Trichoderma-based product and two kilograms of superphosphate. The mixture was incubated at different intervals, including 5, 7 or 9 weeks. Next, the effects of MOF on the growth, yield, ascorbic acid content and Brix of lettuce and mustard spinach were also determined and compared with other organic fertilizers (cow manure and bio-organic fertilizer). Results of the study revealed that 25 tons per ha of MOF were significantly superior to those treated with cow manure and bio-organic fertilizer in the case of vegetable yields. Further, 7 weeks of MOF incubation was found suitable to produce an optimal yield during the various incubation period. These results suggested that the Moringa non-edible parts can make organic fertilizer and enhance growth, yield, and leafy vegetable production

A Bibliometric Analysis of Studies Concerning Policy Issues in Covid-19 Pandemic

This research analysed the studies of policy on issues related to COVID-19. The results show the most productive countries, the most frequently cited sources, the most co-occurred topics of studies concerning policy issues since the epidemic was a breakout at the beginning. The data in this research were collected from the Scopus database with two search terms, "COVID-19" and "policy" of the social science domain, and published from the first day of 2020 to the search time (September 10, 2020). The final dataset consists of 384 valid documents analysed by descriptive statistics, and co-occurrence analysis was applied in R. Among 46 countries, the United States, the United Kingdom, Australia, China, India, and Italy are the leading countries that published these studies. Almost all the funded scholars focused on Europe, the Americas, and Asia. The main topics of the articles are "working in COVID-19 period", "community health and social support," "using ICT in teaching and learning," "human rights." Within funded studies, four interesting topics are "social well-being," "ICT infrastructure," "agricultural policy," and "born-digital." This study presents the current situation of how studies concerning policy issues have been issued to respond to the COVID-19 pandemic

Molecular phylogeny of Annonaceae species from Binh Chau-Phuoc Buu Nature Reserve based on two chloroplast gene regions

In this study, based on molecular biology techniques, the matK and trnL-F regions of ten Annonaceae species grown in Binh Chau-Phuoc Buu Nature Reserve, Vietnam were successfully amplified and sequenced for the first time. Along with other highly homologous DNA sequences from the GenBank database, the molecular phylogeny of ten studied species was also established. By using the alignment tool of NCBI database, the percentage of identity among sequences of studied species was also presented. The study aims to partially contribute to the further understanding of the evolutionary relationships among Annonaceae species

HYBRID END-TO-END APPROACH INTEGRATING ONLINE LEARNING WITH FACE-IDENTIFICATION SYSTEM

To date, facial recognition has been one of the most intriguing, interesting research topics over years. It requires some specific face-based algorithms such as facial detection, facial alignment, facial representation, and facial recognition as well; however, all of these algorithms derive from heavy deep learning architectures that cause limitations for development, scalability, flawed accuracy, and deployment into publicity with mere CPU servers. It also calls for large datasets containing hundreds of thousands of records for training purposes. In this paper, we propose a full pipeline for an effective face recognition application which only uses a small Vietnamese celebrity dataset and CPU for training that can solve the leakage of data and the need for GPU devices. It is based on a face vector-to-string tokens algorithm then saves face’s properties into Elasticsearch for future retrieval, so the problem of online learning in Facial Recognition is also tackled. Comparison with another popular algorithm on the dataset, our proposed pipeline not only outweighs the accuracy counterpart, but it also achieves a very speedy time inference for a real-time face recognition application