Automatic Crack Detection in Built Infrastructure Using Unmanned Aerial Vehicles

This paper addresses the problem of crack detection which is essential for health monitoring of built infrastructure. Our approach includes two stages, data collection using unmanned aerial vehicles (UAVs) and crack detection using histogram analysis. For the data collection, a 3D model of the structure is first created by using laser scanners. Based on the model, geometric properties are extracted to generate way points necessary for navigating the UAV to take images of the structure. Then, our next step is to stick together those obtained images from the overlapped field of view. The resulting image is then clustered by histogram analysis and peak detection. Potential cracks are finally identified by using locally adaptive thresholds. The whole process is automatically carried out so that the inspection time is significantly improved while safety hazards can be minimised. A prototypical system has been developed for evaluation and experimental results are included.Comment: In proceeding of The 34th International Symposium on Automation and Robotics in Construction (ISARC), pp. 823-829, Taipei, Taiwan, 201

CAMELLIA SPHAMII (THEACEAE, SECT. PIQUETIA), A NEW TAXON OF YELLOW FLOWER FROM LANGBIANG BIOSPHERE RESERVE, VIETNAM

Camellia sphamii is described and illustrated as a new species of section Piquetia from Hamasin village, D’ran town, Don Duong district, Lam Dong province, Vietnam. C. sphamii is similar to C. proensis (Quach, Luong et al., 2021) but differs from it in several morphological features: mature leaves cordate at base, young leaves purple; pericarp 7–8 mm thick with dense hair on the outer surface, flower buds ovate, ferruginous; sepals 5, hemisphere, concave, finely hairy on the outer surface, sparsely hairy on the inside, petals 7, finely hairy on the outer surface, with translucent margin, concave; style 5, ½ basally united; capsule 5 locular. Information on its phenology, distribution, ecology, and conservation status is also provided

THE DIVERSITY OF YELLOW CAMELLIAS IN THE CENTRAL HIGHLANDS, VIETNAM

The Central Highlands (Tây Nguyên) is a center of yellow camellia diversity in Vietnam and the world. The Central Highlands contains 18 of Vietnam’s yellow camellia species, accounting for 37% of yellow camellia species in Vietnam and 28% of yellow camellia species worldwide. Moreover, all 18 yellow camellia species in the Central Highlands are endemic to Vietnam. The camellias of the Central Highlands belong to nine sections, accounting for 75% of the world. The yellow colors occur in three groups: pale yellow, yellow, and yellow with compound colors. The yellow camellia distribution is dispersed at 500–1600 m elevation in evergreen broadleaf forests and mixed wood-bamboo forests

Sound-Dr: Reliable Sound Dataset and Baseline Artificial Intelligence System for Respiratory Illnesses

As the burden of respiratory diseases continues to fall on society worldwide, this paper proposes a high-quality and reliable dataset of human sounds for studying respiratory illnesses, including pneumonia and COVID-19. It consists of coughing, mouth breathing, and nose breathing sounds together with metadata on related clinical characteristics. We also develop a proof-of-concept system for establishing baselines and benchmarking against multiple datasets, such as Coswara and COUGHVID. Our comprehensive experiments show that the Sound-Dr dataset has richer features, better performance, and is more robust to dataset shifts in various machine learning tasks. It is promising for a wide range of real-time applications on mobile devices. The proposed dataset and system will serve as practical tools to support healthcare professionals in diagnosing respiratory disorders. The dataset and code are publicly available here: https://github.com/ReML-AI/Sound-Dr/.Comment: 9 pages, PHMAP2023, PH

An unknown input observer-EFIR combined estimator for electro-hydraulic actuator in sensor fault tolerant control application

This paper presents a novel unknown input observer (UIO) integrated extended finite impulse response (EFIR) estimator (UIOEFIR) and its application for an effective sensor fault tolerant control of an electro-hydraulic-actuator (EHA). The proposed estimator exploits the UIO structure in the EFIR filter. Thus, it requires only a small number of historical data (N) whilst ensuring threefold: i) Sensor fault and system-state estimation accuracy under time-correlated noise ii) The number of estimator-design-parameters is significantly minimized. iii) Robust residual generation. A Lyapunov-stability-based theory is carried out to study its convergence condition. Next, an EHAbased test rig has been setup and sensor FTC is performed by carrying this estimator as a part of fault diagnosis algorithm to evaluate its performance by both simulation and realtime experiments. Results highlight that under optimal setting (N = Nopt), the estimator performance is near-accurate to the very-well-developed Extended Kalman Filter-based unknown input observer in an undisturbed condition but significantly outperformed while dealing with time-correlated noise under the same control environment. The estimator also shows its robustness under below-optimal setting (downgrading Nopt by 50%.) while performing in real-time sensor fault-tolerant control

Identify aerodynamic derivatives of the airplane attitude channel using a spiking neural network

The paper proposes a method for identifying aerodynamic coefficient derivatives of aircraft attitude channel using spiking neural network (SNN) and Gauss-Newton algorithm based on data obtained from actual flights. Using SNN combination with Gauss-Newton iterative calculation algorithm allows the identification of aerodynamic coefficient derivatives in a nonlinear model for aerodynamic parameters with higher accuracy and faster calculation time. The paper proposes an algorithm to train the SNN multi-layer network by Normalized Spiking Error Back Propagation (NSEBP), in which, in the forward propagation period, the time of output spikes is calculating by solving quadratic equations instead of detection by traditional methods. The phase of propagation of errors backward uses the step-by-step calculation instead of the conventional gradient calculation method. The identification results are compared with the results when using the RBN network to prove the algorithm efficienc

Multicriteria Evaluation Of Tourism Potential In The Central Highlands Of Vietnam: Combining Geographic Information System (GIS), Analytic Hierarchy Process (AHP) And Principal Component Analysis (PCA)

Tourism potential provides an indication for the tourism development opportunities of regions and sites. This paper deals with a multicriteria evaluation of the tourism potential in the Central Highlands of Vietnam. The study area is located in the Southeast Asian monsoon tropical climatic zone, and offers both natural and cultural tourism resources. GIS-based cost distance analysis was used to calculate the travel time along the road and using other transportation networks. Then an Analytic Hierarchy Process (AHP) was applied to determine a weighting coefficient for each criterion in multicriteria evaluation. Principal Component Analysis (PCA) was processed next to AHP, allowing combination of the internal and external tourism potentials of the considered sites. Both AHP and PCA approaches were based on a certain number of alternatives, and take multiple criteria and conflicting objectives into consideration. The results show that the Central Highlands have considerable potential for tourism development at 99 potential eco-tourism sites and 45 potential cultural tourism sites. However, the region is now faced with poor tourism infrastructure with low external potential. An improvement of tourism infrastructure, service quality, and strengthened linkages with other tourist sites is indicated to diversify the tourism products and increase the attractiveness of regional destinations

Diet of Odorrana chapaensis (Bourret, 1937) from Son La Province, Vietnam

Since there is currently a lack of data on the natural history and feeding ecology of Odorrana chapaensis, which was listed in the IUCN Red List (2019), we herein provided the feeding ecology of this amphibian species is virtually lacking. We herein provide data about the diet of O. chapaensis based on the results of our field work in Ngoc Chien Commune, Muong La District and Xim Vang Commune, Bac Yen District, Son La Province, Vietnam. We used the stomach-flushing method to obtain the stomach contents of 85 individuals at two survey sites. A total of 20 prey categories with 334 items, comprising 299 items of invertebrates and 35 unidentified items, were found in the stomachs of O. chapaensis. The dominant prey items of O. chapaensis were Araneae, Polydesmida, insect larvae, Blattodea, Coleoptera, Dermaptera, Lepidoptera, Hymenoptera, and Orthoptera. The importance index for these categories ranged from 3.5% to 32.5%. Coleoptera was the category with the highest frequency of prey items; its representatives were found in 45 stomaches.