Stabilization Control of the Differential Mobile Robot Using Lyapunov Function and Extended Kalman Filter

This paper presents the design of a control model to navigate the differential mobile robot to reach the desired destination from an arbitrary initial pose. The designed model is divided into two stages: the state estimation and the stabilization control. In the state estimation, an extended Kalman filter is employed to optimally combine the information from the system dynamics and measurements. Two Lyapunov functions are constructed that allow a hybrid feedback control law to execute the robot movements. The asymptotical stability and robustness of the closed loop system are assured. Simulations and experiments are carried out to validate the effectiveness and applicability of the proposed approach.Comment: arXiv admin note: text overlap with arXiv:1611.07112, arXiv:1611.0711

Simulation of Leksell Gamma Knife-4C System with Different Phantoms Using PHITS and Geant4

This study used PHITS and Geant4 code packages to simulate a Leksell Gamma Knife system in order to determine radiation dose distribution in two types of phantoms. The results observed in the water phantom with configurations of single source and 201 sources are in good accord with the prior research, including both simulation and experiment. Several characteristics of Leksell Gamma Knife 4C, such as dose profiles, output factor, FWHM, and penumbra size, are calculated based on Monte Carlo simulations, which show the best consistency with other results. The output factors for collimators of 14 mm, 8 mm, and 4 mm are 0.984, 0.949, and 0.872, respectively. The simulation results with an adult mesh-type reference phantom reveal considerable similarities with the established radiosurgery plans. It indicates that the absorbed dose in brain tumors was highest when utilizing the 18 mm collimator and subsequently reduced with collimator size to 0.65, 0.25, and 0.5 with the 14 mm, 8 mm, and 4 mm collimators, respectively. The absorbed dose has a very low value for other essential organs and decreases with distance from the brain tumor. These findings may explain why the dose to organs decreases linearly as target distance, volume, and collimator size increase

Accounting conservatism and banking expertise on board of directors

Previous studies show mixed evidence of the role of banking expertise on the board of directors on accounting conservatism. In this paper, we add to this growing literature by providing an innovative way to measure banking expertise based on life-time working history in banks of all individual directors on the board. We find that accounting conservatism is negatively affected by banking expertise on the board. Also, the results indicate that banking expertise on the board has a more pronounced impact on accounting conservatism when firms have high bankruptcy risk and when firms have high financial leverage. The evidence has some implications for boards of directors

Maximal LpL^p-regularity for stochastic evolution equations

We prove maximal $L^p$-regularity for the stochastic evolution equation \{{aligned} dU(t) + A U(t)\, dt& = F(t,U(t))\,dt + B(t,U(t))\,dW_H(t), \qquad t\in [0,T], U(0) & = u_0, {aligned}. under the assumption that $A$ is a sectorial operator with a bounded $H^\infty$-calculus of angle less than $\frac12\pi$ on a space $L^q(\mathcal{O},\mu)$. The driving process $W_H$ is a cylindrical Brownian motion in an abstract Hilbert space $H$. For $p\in (2,\infty)$ and $q\in [2,\infty)$ and initial conditions $u_0$ in the real interpolation space \XAp we prove existence of unique strong solution with trajectories in L^p(0,T;\Dom(A))\cap C([0,T];\XAp), provided the non-linearities F:[0,T]\times \Dom(A)\to L^q(\mathcal{O},\mu) and B:[0,T]\times \Dom(A) \to \g(H,\Dom(A^{\frac12})) are of linear growth and Lipschitz continuous in their second variables with small enough Lipschitz constants. Extensions to the case where $A$ is an adapted operator-valued process are considered as well. Various applications to stochastic partial differential equations are worked out in detail. These include higher-order and time-dependent parabolic equations and the Navier-Stokes equation on a smooth bounded domain \OO\subseteq \R^d with $d\ge 2$. For the latter, the existence of a unique strong local solution with values in (H^{1,q}(\OO))^d is shown.Comment: Accepted for publication in SIAM Journal on Mathematical Analysi

n-Gram-based text compression

We propose an efficient method for compressing Vietnamese text using n-gram dictionaries. It has a significant compression ratio in comparison with those of state-of-the-art methods on the same dataset. Given a text, first, the proposed method splits it into n-grams and then encodes them based on n-gram dictionaries. In the encoding phase, we use a sliding window with a size that ranges from bigram to five grams to obtain the best encoding stream. Each n-gram is encoded by two to four bytes accordingly based on its corresponding n-gram dictionary. We collected 2.5 GB text corpus from some Vietnamese news agencies to build n-gram dictionaries from unigram to five grams and achieve dictionaries with a size of 12 GB in total. In order to evaluate our method, we collected a testing set of 10 different text files with different sizes. The experimental results indicate that our method achieves compression ratio around 90% and outperforms state-of-the-art methods.Web of Scienceart. no. 948364

Varietal effects on methane intensity of paddy fields under different irrigation management

Alternate wetting and drying irrigation (AWD) has been shown to decrease water use and trace gas emissions from paddy fields. Whereas genotypic water use shows little variation, it has been shown that rice varieties differ in the magnitude of their methane emissions. Management and variety-related emission factors have been proposed for modelling the impact of paddy production on climate change; however, the magnitude of a potential reduction in greenhouse gas emissions by changing varieties has not yet been fully assessed. AWD has been shown to affect genotypic yields and high-yielding varieties suffer the greatest loss when grown under AWD. The highest yielding varieties may not have the highest methane emissions; thus, a potential yield loss could be compensated by a larger reduction in methane emissions. However, AWD can only be implemented under full control of irrigation water, leaving the rainy seasons with little scope to reduce methane emissions from paddy fields. Employing low-emitting varieties during the rainy season may be an option to reduce methane emissions but may compromise farmers’ income if such varieties perform less well than the current standard. Methane emissions and rice yields were determined in field trials over two consecutive winter/spring seasons with continuously flooded and AWD irrigation treatments for 20 lowland rice varieties in the Mekong Delta of Vietnam. Based on the results, this paper investigates the magnitude of methane savings through varietal choice for both AWD and continuous flooding in relation to genotypic yields and explores potential options for compensating farmers’ mitigation efforts

A Big Data Smart Agricultural System: Recommending Optimum Fertilisers For Crops

Nutrients are important to promote plant growth and nutrient deficiency is the primary factor limiting crop production. However, excess fertilisers can also have a negative impact on crop quality and yield, cause an increase in pollution and decrease producer profit. Hence, determining the suitable quantities of fertiliser for every crop is very useful. Currently, the agricultural systems with internet of things make very large data volumes. Exploiting agricultural Big Data will help to extract valuable information. However, designing and implementing a large scale agricultural data warehouse are very challenging. The data warehouse is a key module to build a smart crop system to make proficient agronomy recommendations. In our paper, an electronic agricultural record (EAR) is proposed to integrate many separate datasets into a unified dataset. Then, to store and manage the agricultural Big Data, we built an agricultural data warehouse based on Hive and Elasticsearch. Finally, we applied some statistical methods based on our data warehouse to extract fertiliser information such as a case study. These statistical methods propose the recommended quantities of fertiliser components across a wide range of environmental and crop management conditions, such as nitrogen (N), phosphorus (P) and potassium (K) for the top ten most popular crops in EU