In this paper, we propose a single-step Deep Neural Network (DNN) for CE, termed Iterative Sequential DNN (ISDNN), inspired by recent developments in data detection algorithms. ISDNN is a DNN based on the projected gradient descent algorithm for CE problems, with the iterative iterations transforming into a DNN using the deep unfolding method.

Lesson "Machine Vision" Chapter 9 - Camera Calibration and 3D Reconstruction, compiled including the following main contents: Camera calibration; Robot Camera Calibration; Pose estimation; Stereo vision.

The loss of life in floods is due to both drowning and/or the spread of disease epidemics. The objectives of this study is to focus on estimating appropriate methods and functions for assessing the potential damages to human life in river basin due to floods.

This paper demonstrates that, using multiple data points around each gateway allows for the creation of accurate coverage heat maps by using a proposed LoRaWAN coverage estimation algorithm. This method effectively identifies areas with varying signal strength across Da Nang City, highlighting where additional gateways are needed to improve network reliability.

This study introduces a practical and efficient methodology to improve the estimation of the ultimate axial bearing capacity of Pre-bored Grouted Planted Nodular (PGPN) piles, addressing a critical need in geotechnical engineering.

Efficient and accurate recognition of human interactions is crucial for numerous service applications, including security surveillance and public safety. In this paper, we propose a lightweight methodology for detecting human activity and interactions in video streams, specifically tailored for edge computing environments.

The study focuses on the prevalence of road traffic accidents in Vietnam, particularly along national highways, which are frequent and severe. Specifically, it examines National Highway 1A passing through Thanh Hoa province, utilizing statistics and geographic information systems (GIS) to identify high-risk areas.

This paper presents a novel approach to enhancing the accuracy of precipitation estimation in Central Vietnam using the Extreme Gradient Boosting (XGBoost) machine learning model. The proposed method integrates multi-source data, combining satellite imagery from Himawari-8, atmospheric reanalysis from ERA-5, and digital elevation models from ASTER DEM to train the model.

In this study, the Machine Learning (ML) approach has been adopted using Random Forest (RF) model to estimate the CBR of the soil based on 10 input parameters such as Plasticity Index (PI), Liquid Limit (LL), Silt Clay content (SC), Fine Sand content (FS), Coarse sand content (CS), Optimum Water Content (OWC), Organic content (O), Plastic Limit (PL), Gravel content (G), and Maximum Dry Density (MDD), which can be easily determined in the laboratory.

Adaptive Neuro-Based Fuzzy Inference System (ANFIS) and Particle Swarm Optimization (PSO) algorithms were utilized to produce numerical tools for predicting the bond strength between the concrete surface and carbon fiber reinforced polymer (CFRP) sheets.

The basic characteristics of sensor were investigated, and these experimental data were used for a machine learning. The results of the model validation proved to be a reliable way between the experiment and prediction values.

This research proposes a new approach that leverages low-cost digital cameras and deep learning technology for counting and extracting rice grain traits. Our study introduces a preprocessing step to separate rice grain regions from the input image background using color space conversion.

Bài giảng Phân tích số liệu mảng - Chương 5: Dynamic panel model. Chương này cung cấp cho sinh viên những nội dung gồm: giới thiệu về Dynamic panel model; ước tính hiệu ứng cố định và ngẫu nhiên; ước tính biến công cụ (phương pháp IV) (Anderson và Hsiao, 1982); 2SLS, phương pháp tiếp cận mô men tổng quát (GMM) (Arenalloand Bond, 1985);... Mời các bạn cùng tham khảo!

One of the main objectives for this thesis is to provide an extensive literature review on the knowledge of the failure of trees in general and specifically Eucalyptus. By doing so, gaps in the literature and research will be revealed and then the remaining objectives will be selected experimental work filling the gaps for Eucalypts.

Trade and world economic integration are seen as the impetus for accelerating the well-beings of the domestic Vietnamese communities and international community in the region. However, an understanding of the link between trade and economic integration from the perspective of Vietnam is missing. Empirical studies on Vietnamese trade are in lack to address these determinants (see, Le, 1996; Nguyen, 2010). This thesis identifies the key factors that have driven the impressive growth of Vietnamese exports during the world economic integration process (1986-2010). Importantly, this study applies the gravity equation to investigate these factors by the two aspects, namely, the aggregate and sectoral exports analysis.

This study develops an online unmanned UAV path-planning strategy for autonomous search and localisation of RF emitter. The UAV is equipped with Receiver Signal Strength (RSS) sensors to localise stationary radio frequency (RF) emitter. A high-fidelity non-linear measurement model of RF propagation in an urban environment is adopted for this purpose. The measurement model of the likelihood function is considered a Gaussian mixture.

The thesis's primary research objective is to identify the impacts of budgeting on the performance of Vietnamese SMEs. Specific research objectives include examining the impacts of business budget's different aspects on the performance of Vietnamese SMEs; evaluating the controlling and moderation role of firm size and the mediating role of managerial performance in the relationship between budgeting and business performance of Vietnamese SMEs.

The objective of this dissertation is to investigate that whether the investors can improve the performance of minimum – variance optimized portfolios by altering the estimators of covariance matrix input. Besides, based on the results of out – of – sample portfolio performance metrics, the dissertation is going to select the suitable estimators of covariance matrix for portfolio optimization on Vietnam stock market.

The research objective of the thesis is to consider how the change of covariance matrix factor will affect the results of portfolio selection and through that to find out whether investors have Is it possible to improve portfolio performance by adjusting the covariance matrix in the optimized model with the smallest variance.

The present investigation was under taken with the objectives to estimate genetic variability, heritability and genetic advance for yield and yield contributing components of cucumber. The experimental materials for this investigation were fourteen genotypes of cucumber consisting of parthenocarpic, gynoecious and monecious germplasms crossed in line × tester mating design produced thirty three hybrids (F1). Thirty three F1 crosses along with their parents were evaluated in two environments viz. Environment 1 (March-June), Environment 2 (AugustDecember) inside polyhouse for evaluation of their quantitative characters. The genotypes exhibited significant differences for all the traits under study in both environments. The genotypic coefficients of variation and phenotypic coefficients of variation were moderate to high for most of the characters.