iBeacon-based indoor positioning system: from theory to practical deployment

Developing an indoor positioning system became essential when global positioning system signals could not work well in indoor environments. Mobile positioning can be accomplished via many radio frequency technology such as Bluetooth low energy (BLE), wireless fidelity (Wi-Fi), ultra-wideband (UWB), and so on. With the pressing need for indoor positioning systems, we, in this work, present a deployment scheme for smartphone using Bluetooth iBeacons. Three main parts, hardware deployment, software deployment, and positioning accuracy assessment, are discussed carefully to find the optimal solution for a complete indoor positioning system. Our application and experimental results show that proposed solution is feasible and indoor positioning system is completely attainable

Smartphone indoor positioning based on enhanced BLE beacon multi-lateration

In this paper, we introduce a smartphone indoor positioning method using bluetooth low energy (BLE) beacon multilateration. At first, based on signal strength analysis, we construct a distance calculation model for BLE beacons. Then, with the aims to improve positioning accuracy, we propose an improved lateral method (range-based method) which is applied for 4 nearby beacons. The method is intended to design a real-time system for some services such as emergency assistance, personal localization and tracking, location-based advertising and marketing, etc. Experimental results show that the proposed method achieves high accuracy when compared with the state of the art lateral methods such as geometry-based (conventional trilateration), least square estimation-based (LSE-based) and weighted LSE-based

RESEARCH ON NEARSHORE WAVE CONDITIONS AT NHAT LE COASTAL AREA (QUANG BINH PROVINCE) BY USING MIKE21-SW

Research on marine dynamics, including coastal wave motions, is a concern of countries in the world in general and Vietnam in particular. Coastal wave dynamics has a direct impact on human activities including coastal construction, shipping, irrigation, aquatic resources exploitation, etc. The coastal area of Nhat Le, Quang Binh is one of the areas strongly influenced by the coastal wave regime which increases the risk of coastal erosion, estuarine sedimentation, destroys the economic life, affects marine fishing and directly affects the tourist beach area. This article aims to introduce some research results based on the application of MIKE21-SW model of the Danish Hydraulic Institute (DHI) to simulate coastal wave regime in Nhat Le coastal zone, Quang Binh province. The model results are verified by real-time wave data in long-term from the WaMoS® II Radar System at Quang Binh station. The results show that there are many similarities in wave height and direction between the computational model and the actual observation data from the radar system. This result will be an important basis for research and application for coastal protection, reduction in river mouth sedimentation, clearing and flood drainage in the study area

Constrained Twin Variational Auto-Encoder for Intrusion Detection in IoT Systems

Intrusion detection systems (IDSs) play a critical role in protecting billions of IoT devices from malicious attacks. However, the IDSs for IoT devices face inherent challenges of IoT systems, including the heterogeneity of IoT data/devices, the high dimensionality of training data, and the imbalanced data. Moreover, the deployment of IDSs on IoT systems is challenging, and sometimes impossible, due to the limited resources such as memory/storage and computing capability of typical IoT devices. To tackle these challenges, this article proposes a novel deep neural network/architecture called Constrained Twin Variational Auto-Encoder (CTVAE) that can feed classifiers of IDSs with more separable/distinguishable and lower-dimensional representation data. Additionally, in comparison to the state-of-the-art neural networks used in IDSs, CTVAE requires less memory/storage and computing power, hence making it more suitable for IoT IDS systems. Extensive experiments with the 11 most popular IoT botnet datasets show that CTVAE can boost around 1% in terms of accuracy and Fscore in detection attack compared to the state-of-the-art machine learning and representation learning methods, whilst the running time for attack detection is lower than 2E-6 seconds and the model size is lower than 1 MB. We also further investigate various characteristics of CTVAE in the latent space and in the reconstruction representation to demonstrate its efficacy compared with current well-known methods

An Analysis of Shoreline Changes Using Combined Multitemporal Remote Sensing and Digital Evaluation Model

Cua Dai estuary belonged to Quang Nam province is considered to be one of the localities of Vietnam having a complex erosion and accretion process. In this area, sandbars are recently observed with lots of arguments about the causes and regimes of formation. This could very likely result of not reliable source of information on shoreline evolution and a lack of historical monitoring data. Accurately identification of shoreline positions over a given period of time is a key to quantitatively and accurately assessing the beach erosion and accretion. The study is therefore to propose an innovative method of accurately shoreline positions for an analysis of coastal erosion and accretion in the Cua Dai estuary. The proposed technology of multitemporal remote sensing and digital evaluation model with tidal correction are used to analyse the changes in shoreline and estimate the rate of erosion and accretion. An empirical formula is, especially, exposed to fully interpret the shoreline evolution for multiple scales based on a limitation of satellite images during 1965 to 2018. The results show that there is a significant difference of shoreline shift between corrections and non-corrections of tidal. Erosion process tends to be recorded in the Cua Dai cape located in the Cua Dai ward, especially in the An Luong cape located in the Duy Hai commune with the length of 1050 m. Furthermore, it is observed that there is much stronger erosion in the north side compared with south side of Cua Dai estuary

Estimating the cost of illness of acute Japanese encephalitis and sequelae care in Vietnam and Laos: a cross-sectional study

Background Japanese encephalitis (JE) is a leading cause of acute encephalitis syndrome and resulting neurological disability in Asia and the Western Pacific. This study aims to estimate the cost of acute care, initial rehabilitation and sequelae care, in Vietnam and Laos. Methodology We conducted a cross-sectional retrospective study using a micro-costing approach from the health system and household perspectives. Out-of-pocket direct medical and non-medical costs, indirect costs, and family impact were reported by patients and/or caregivers. Hospitalization costs were extracted from hospital charts. Acute costs covered expenditures from pre-hospital to follow-up visits while sequelae care costs were estimated from expenditures in the last 90 days. All costs are in 2021 US dollars. Principal findings 242 patients in two major sentinel sites in the North and South of Vietnam and 65 patients in a central hospital in Vientiane, Laos, with laboratory-confirmed JE were recruited regardless of age, sex, and ethnicity. In Vietnam, the mean total cost was $3,371 per acute JE episode (median$2,071, standard error [SE] $464) while annual costs were$404 for initial sequelae care (median $0, SE$220) and $320 for long-term sequelae care (median$0, SE $108). In Laos, the mean hospitalization costs in acute stage were$2,005 (median $1,698, SE$279) and the mean annual costs were $2,317 (median$0, SE $2,233) for initial sequelae care and$89 (median $0, SE$57) for long-term sequelae care. In both countries, most patients did not seek care for their sequelae. Families perceived extreme impact from JE and 20% to 30% of households still had sustained debts years after acute JE. Conclusions JE patients and families in Vietnam and Laos suffer extreme medical, economic, and social hardship. This has policy implications for improving JE prevention in these two JE-endemic countries

GENETIC POLYMORPHISM OF 23 Y-CHROMOSOME SHORT TANDEM REPEAT LOCI IN THE KINH POPULATION OF VIETNAM

Y-chromosome microsatellites or short tandem repeats (STRs) have been proved to be ideal markers to delineate the differences between individuals in human population. Nowadays, Y-STR testing using the PowerPlex® Y23 amplification kit is considered as an extremely sensitive analysis method and has the potential to be used to perform forensic caseworks, and to explore the complexity in population substructures. However, little is known about the forensic Y-chromosome databases in the Vietnam population. In this study, 23 Y-STR loci (DYS576, DYS389I, DYS389 II, DYS448, DYS19, DYS391, DYS481, DYS549, DYS533, DYS438, DYS437, DYS570, DYS635, DYS390, DYS439, DYS392, DYS393, DYS458 DYS456, DYS643, YGATAH4, and DYS385a/b) were investigated in 120 non-related males of the Kinh population in Northern Vietnam using PowerPlex® Y23 system kit (Promega). Our results showed that allele frequencies of 23 loci in the sample population, with the calculated average gene diversity (GD) for each locus, ranged from 0.24 (DYS438) to 0.92 (DYS385a/b). In addition, a total of 120 different haplotypes were found, all of them were unique. Therefore, we found that the haplotype diversity was 1 with a discrimination capacity of 100%, which serves as an essential prerequisite for using Y-chromosomal STR with PowerPlex® Y23 System kit in forensic application in Vietnam. We also compared genetic distances between Kinh population and 10 other neighboring populations from Y-chromosome haplotype reference database (YHRD). The Kinh population is significantly different from other populations. In conclusion, it was indicated that the 23 Y-STR loci were highly genetically polymorphic in the Kinh population in Vietnam and might be of great value in forensic application