Maritime Data Mining for Marine Safety Based on Deep Learning: Southern Vietnam Case Study

High-speed passenger vessels, integrated river and sea vessels, container vessels, oil tankers, and other underwater vehicles operating in maritime traffic are among the types of vessels that must be equipped with AIS and VHF. The safety of navigation is one of the major problems in the maritime sector, particularly in Vietnam. Furthermore, marine traffic in the seaport zone is a common and difficult issue to manage in areas with a high volume of vessel traffic, mostly in places where the infrastructure supporting navigation is inadequately developed to meet the rapidly growing demands of the contemporary world. Therefore, it is necessary to create an integrated maritime management system to improve the efficiency of data exploitation and support maritime safety. To address this challenge, this study suggests a Maritime Traffic State Prediction (MTSP) model to predict traffic conditions in the channels where real-time data collection is insufficient in some specific locations. We recommend a deep learning method using Long Short-Term Memory (LSTM) networks to predict the safe path of the vessel in case of missing data segments. The findings have shown that the proposed approach encourages the mining of historical vessel data for maritime traffic, is ready to be applied, and can easily be implemented in a computer program or a web-based app

Applying convolutional neural networks for limited-memory application

Currently, convolutional neural networks (CNN) are considered as the most effective tool in image diagnosis and processing techniques. In this paper, we studied and applied the modified SSDLite_MobileNetV2 and proposed a solution to always maintain the boundary of the total memory capacity in the following robust bound and applied on the bridge navigational watch & alarm system (BNWAS). The hardware was designed based on raspberry Pi-3, an embedded single board computer with CPU smartphone level, limited RAM without CUDA GPU. Experimental results showed that the deep learning model on an embedded single board computer brings us high effectiveness in application

MOTIVATION TO STUDY ENGLISH OF NON-ENGLISH MAJORED FRESHMEN

Motivation is regarded as an influential factor in the success of any activity. It plays a significant role in reaching the desired goals, including learning English. This research aims to analyze the students' motivation and factors affecting their motivation to learn English. The population of this study was 326 freshmen in nine faculties of natural sciences at Tay Do University. The quantitative data was collected through the questionnaire and analyzed by SPSS software. The results show that the students had motivation to learn English, but their motivation levels were not high. Additionally, the students had both intrinsic and extrinsic motivation. However, the latter was higher than the former. Moreover, the results also indicate factors affecting learners’ motivation. The research findings contribute to improving English teaching and learning quality in Vietnam in general and in Tay Do University in particular. Article visualizations

Preparation of Ti/TiO2-PANi electrodes by combining method of thermal treatment with polymerization processing and their electrochemical property

Ti/TiO2-PANi-electrodes were synthesized by combining method of thermal treatment of titanium substrate with chemical polymerization processing of aniline on which. Their morphological structure was observed by scanning electron microscopy. The presence of PANi and TiO2 were indicated by infrared spectra and X-ray diffraction, respectively. Their electrochemical properties were characterized by cyclic voltammetry and impedance spectroscopy. The results showed that their photoelectrochemical property with light on in 0.5 M H2SO4 indicating a n-conductor that depended on PANi thickness covered TiO2-layer among them the best one obtained by oxidative temperature of 500 oC for 30 minutes during thermal treatment of titanium substrate connected with an immersing into acidic aniline solution for only 8 min during polymerization

A Novel Wideband Circularly Polarized Antenna for RF Energy Harvesting in Wireless Sensor Nodes

A novel wideband circularly polarized antenna array using sequential rotation feeding network is presented in this paper. The proposed antenna array has a relative bandwidth of 38.7% at frequencies from 5.05 GHz to 7.45 GHz with a highest gain of 12 dBi at 6 GHz. A corresponding left-handed metamaterial is designed in order to increase antenna gain without significantly affecting its polarization characteristics. The wideband circularly polarized antenna with 2.4 GHz of bandwidth is a promising solution for wireless communication system such as tracking or wireless energy harvesting from Wi-Fi signal based on IEEE 802.11ac standard or future 5G cellular. A potential application of this antenna as a receiving antenna for RF-DC device to obtain DC power for a wireless sensor node from Wi-Fi signal is shown

Isolation and characterization of Rhizobium spp. and Bradyrhizobium spp. from legume nodules

Rhizobia topic has been re-focused in recent years because of new findings on their traits not only as nitrogen-fixing bacteria but also as plant growth-promoting rhizobacteria. When combing rhizobial strains with novel biological carriers (e.g., biochar) for inoculant production, it brings great potential for improving soil health in long-term. Appreciating this trend, this study is designed to isolate and characterize local rhizobial strains from legume fields using the conventional method with some modifications to increase efficiency in rhizobial identification. As a result, 17 rhizobial strains were isolated and classified biochemically that genetic identification outcome confirmed 10 strains belong to 07 different Rhizobium species as R. mayense, R. paknamense, R. pusense, R. miluonense, R. tropici, R. phaseoli, and R. multihospitium while the rest belong to 06 various Bradyrhizobium species as B. elkanii, B. centrosematis, B. guangxiense, B. liaoningense, B. yuanmingense, and B. arachidis. Thermal and saline tolerant tests together with seed germination tests also performed on these rhizobial strains to gain data on their responses to abiotic stresses. By comparing rice and mung bean GI values, we can assess the effectiveness of each rhizobial strains to help seeds at their early germination

Early State Prediction Model for Offshore Jacket Platform Structural Using EfficientNet-B0 Neural Network

Offshore Jacket Platforms (OJPs) are often affected by environmental components that lead to damage, and the early detection system can help prevent serious failures, ensuring safe operations and mining conditions, and reducing maintenance costs. In this study, we proposed a prediction model based on Convolutional Neural Networks (CNNs) aimed at determining the early stage of the OJP structure’s abnormal status. Additionally, the EfficientNet-B0 Deep Neural Network classifies normal and abnormal states, which may cause problems, by using displacement signal analysis at specific areas taken into account throughout the test. Displacement data is transferred to a 2D scalogram image by applying a continuous Wavelet converter that shows the state of the work. Finally, the scalogram image data set is used as the input of the neural network, and feasibility experimental results compared with other typical neural networks such as GoogLeNet and ResNet-50 have verified the effectiveness of the approach

Corporate Culture - Externally Committed Values: The Case Study of a Technology and Telecommunications Enterprise Listed on The Vietnam Stock Market

This study investigates the external endorsement of corporate cultural values based on Martin and Frost's (1988) model. The research findings reveal that FPT Corporation significantly emphasizes Humanism, Financial, and Product values in its business activities over the three years T-T+2. The corporate culture contributes a vital role in fostering the growth of the organization. The study's longitudinal evaluation demonstrates that it is appropriate that FPT spends a prime concern on Humanism since employee commitment and dedication are crucial for the company's present success. Moreover, the high emphasis on Financial and Product values is well-founded because transparent financial reporting is essential to prevent misinterpretations and attract investment, while the quality of the products symbolizes the company's credibility and ensures substantial revenue generation

A national program to advance dementia research in Vietnam

Abstract Background As Vietnam and other low- and middle-income countries (LMIC) experience a rapid increase in the number of people living with dementia, an acute need exists to strengthen research capacity to inform policy, improve care and support, and develop national dementia plans. We describe the development and early outcomes of an National Institutes of Health (NIH)/National Institute on Aging (NIA)-funded national dementia research capacity building program in Vietnam. Methods The research capacity building program commenced in 2019 and has three components: (1) Vietnam Alzheimer’s and other dementias research Network (VAN), (2) a mentored pilot grant program, and (3) research training, networking, and dissemination activities. The pilot grant program funds Vietnamese researchers for one to two years to conduct research focusing on Alzheimer’s Disease and Alzheimer’s Disease Related Dementias (AD/ADRD). Grants are reviewed and scored using NIH criteria, and priority is given to pilot grants with policy relevance and potential for future funding. An international pool of high-income country (e.g., United States, Australia, and United Kingdom) mentors has been engaged and mentors paired with each funded project. Training and networking activities include workshops on AD/ADRD research topics and regular meetings in conjunction with Vietnam’s annual national dementia/geriatric conferences. Dissemination is facilitated through targeted outreach and the creation of a national network of institutions. Results Over four years (2019–2023), we received 62 applications, reviewed 58 applications, and funded 21 projects (4–5 per year). Funded investigators were from diverse disciplines and institutions across Vietnam with projects on a range of topics, including biomarkers, prevention, diagnosis, neuropsychological assessment, family caregiver support, dementia education, and clinical trials. A network of 12 leading academic and research institutions nationwide has been created to facilitate dissemination. Six research training workshops have been organized and included presentations from international speakers. Grantees have published or presented their studies at both national and international levels. The mentoring program has helped grantees to build their research skills and expand their research network. Conclusion This research capacity building program is the first of its kind in Vietnam and may serve as a useful model for other LMIC