384 research outputs found
Multistep predictions for adaptive sampling in mobile robotic sensor networks using proximal ADMM
This paper presents a novel approach, using multi-step predictions, to the adaptive sampling problem for efficient monitoring of environmental spatial phenomena in a mobile sensor network. We employ a Gaussian process to represent the spatial field of interest, which is then used to predict the field at unmeasured locations. The adaptive sampling problem aims to drive the mobile sensors to optimally navigate the environment while the sensors adaptively take measurements of the spatial phenomena at each sampling step. To this end, an optimal sampling criterion based on conditional entropy is proposed, which minimizes the prediction uncertainty of the Gaussian process model. By predicting the measurements the mobile sensors potentially take in a finite horizon of multiple future sampling steps and exploiting the chain rule of the conditional entropy, a multi-step-ahead adaptive sampling optimization problem is formulated. Its objective is to find the optimal sampling paths for the mobile sensors in multiple sampling steps ahead. Robot-robot and robot-obstacle collision avoidance is formulated as mixed-integer constraints. Compared with the single-step-ahead approach typically adopted in the literature, our approach provides better navigation, deployment, and data collection with more informative sensor readings. However, the resulting mixed-integer nonlinear program is highly complex and intractable. We propose to employ the proximal alternating direction method of multipliers to efficiently solve this problem. More importantly, the solution obtained by the proposed algorithm is theoretically guaranteed to converge to a stationary value. The effectiveness of our proposed approach was extensively validated by simulation using a real-world dataset, which showed highly promising results. © 2013 IEEE
ADMM-based Adaptive Sampling Strategy for Nonholonomic Mobile Robotic Sensor Networks
This paper discusses the adaptive sampling problem in a nonholonomic mobile
robotic sensor network for efficiently monitoring a spatial field. It is
proposed to employ Gaussian process to model a spatial phenomenon and predict
it at unmeasured positions, which enables the sampling optimization problem to
be formulated by the use of the log determinant of a predicted covariance
matrix at next sampling locations. The control, movement and nonholonomic
dynamics constraints of the mobile sensors are also considered in the adaptive
sampling optimization problem. In order to tackle the nonlinearity and
nonconvexity of the objective function in the optimization problem we first
exploit the linearized alternating direction method of multipliers (L-ADMM)
method that can effectively simplify the objective function, though it is
computationally expensive since a nonconvex problem needs to be solved exactly
in each iteration. We then propose a novel approach called the successive
convexified ADMM (SC-ADMM) that sequentially convexify the nonlinear dynamic
constraints so that the original optimization problem can be split into convex
subproblems. It is noted that both the L-ADMM algorithm and our SC-ADMM
approach can solve the sampling optimization problem in either a centralized or
a distributed manner. We validated the proposed approaches in 1000 experiments
in a synthetic environment with a real-world dataset, where the obtained
results suggest that both the L-ADMM and SC- ADMM techniques can provide good
accuracy for the monitoring purpose. However, our proposed SC-ADMM approach
computationally outperforms the L-ADMM counterpart, demonstrating its better
practicality.Comment: submitted to IEEE Sensors Journal, revised versio
Revisiting the Approaches for Exploring Students’ Drive in Japanese Studies
Japanese Studies undergraduate programs offer students an engaging curriculum that provides a deep understanding of the Japanese language and culture. A degree in Japanese Studies equips students with valuable skills that are relevant in various fields, making it a popular choice worldwide. College students’ motivation is a critical factor in academic success and has been extensively studied in education. The paper aims to review the existing theories related to study motivation, language acquisition, study abroad drives, and motivation, then to consider the approaches and details that we could prioritize for investigating the motivations and drives of students majoring and minoring in Japanese Studies in universities
Invasive trees in Singapore: Are they a threat to native forests?
Tropical Conservation Science81201-21
Morphodynamic modeling and causes of closure of My A inlet
Morphodynamics and sediment transport of the My A inlet in the low flow season are modeled using Delft3D. The simulation model takes into account the forcing of waves, tides and river flows. Model outputs of sediment transport and morphological changes of allow analysing the mechanism and cause of inlet closure. The analysis shows that longshore sediment is accreted on the northern side of the inlet both on the ebb tidal delta and along the north coast, but onshore sediment transport by wave reworking is the main process to close the inlet
Board Independence and Financial Performance: Empirical Evidence on Mediating Role of Market Competition From the Vietnamese Market
Purpose: The aim of this study is to examine the effect of board independence on the financial performance of companies listed on the Vietnamese stock exchanges with the mediating role of market competition.
Theoretical framework: The topic is based on agency theory, resource dependency theory and stewardship theory. The independence of the board of directors (BOD) is measured in two aspects: the duality and the non-executive members of BOD. This study approaches the measurement of market competition according to the Herfindahl-Hirschman index (HHI). After calculating the HHI, the study will classify companies in a highly competitive market or a low competitive market.
Design/methodology/approach: The study uses secondary data from the financial statements of companies listed on the Vietnamese stock market with the collection period from 2016 to 2020. The data analysis methods comprise of Pooled ordinary least squares (OLS), Fixed effects model (FEM), Random effects model (REM) and Generalized method of moments estimation (GMM).
Findings: The results of GMM showed that CEO duality is found to have a negative effect on the financial performance of listed firms. Meanwhile, the statistical evidence shows that the percentage of non-executive board members and market competition positively affect the financial performance. In addition, the evidence showed that market competition could reduce the positive influence of the percentage of non-executive board members on financial performance of listed companies.
Research, Practical & Social implications: The study has proposed some governance implications to improve the financial performance of listed firms such as limiting CEO duality, increasing the percentage of non-executive board members and empower the management board in a highly competitive market and choosing the appropriate size of the board.
Originality/value: The value of the study is to provide more scientific basis for policy makers in Vietnam and help listed companies choose and make decisions related to BOD to improve financial efficiency
Early detection of slight bruises in apples by cost-efficient near-infrared imaging
Near-infrared (NIR) spectroscopy has been widely reported for its useful applications in assessing internal fruit qualities. Motivated by apple consumption in the global market, this study aims to evaluate the possibility of applying NIR imaging to detect slight bruises in apple fruits. A simple optical setup was designed, and low-cost system components were used to promote the future development of practical and cost-efficient devices. To evaluate the effectiveness of the proposed approach, slight bruises were created by a mild impact with a comparably low impact energy of only 0.081 Joules. Experimental results showed that 100% of bruises in Jazz and Gala apples were accurately detected immediately after bruising and within 3 hours of storage. Thus, it is promising to develop customer devices to detect slight bruises for not only apple fruits but also other fruits with soft and thin skin at their early damage stages
Economic and Environmental Impacts of Harmful Non-Indigenous Species in Southeast Asia
Harmful non-indigenous species (NIS) impose great economic and environmental impacts globally, but little is known about their impacts in Southeast Asia. Lack of knowledge of the magnitude of the problem hinders the allocation of appropriate resources for NIS prevention and management. We used benefit-cost analysis embedded in a Monte-Carlo simulation model and analysed economic and environmental impacts of NIS in the region to estimate the total burden of NIS in Southeast Asia. The total annual loss caused by NIS to agriculture, human health and the environment in Southeast Asia is estimated to be US25.8–39.8 billion). Losses and costs to the agricultural sector are estimated to be nearly 90% of the total (US1.85 billion (US2.1 billion (US$0.9–3.3 billion), respectively, although these estimates are based on conservative assumptions. We demonstrate that the economic and environmental impacts of NIS in low and middle-income regions can be considerable and that further measures, such as the adoption of regional risk assessment protocols to inform decisions on prevention and control of NIS in Southeast Asia, could be beneficial
Confinement effect on solar thermal heating process of TiN solutions
We propose a theoretical approach to describe quantitatively the heating
process in aqueous solutions of dispersed TiN nanoparticles under solar
illumination. The temperature gradients of solution with different
concentrations of TiN nanoparticles are calculated when confinement effects of
the container on the solar absorption are taken into account. We find that the
average penetration of solar radiation into the solution is significantly
reduced with increasing the nanoparticle concentration. At high concentrations,
our numerical results show that photons are localized near the surface of the
solution. Moreover, the heat energy balance equation at the vapor-liquid
interface is used to describe the solar steam generation. The theoretical time
dependence of temperature rise and vaporization weight losses is consistent
with experiments. Our calculations give strong evidence that the substantially
localized heating near the vapor-liquid interface is the main reason for the
more efficient steam generation process by floating plasmonic membranes when
compared to randomly dispersed nanoparticles. The validated theoretical model
suggests that our approach can be applied towards new predictions and other
experimental data descriptions.Comment: 6 pages, 3 figures, accepted for publication in PCC
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