Improving Texture Categorization with Biologically Inspired Filtering

Within the domain of texture classification, a lot of effort has been spent on local descriptors, leading to many powerful algorithms. However, preprocessing techniques have received much less attention despite their important potential for improving the overall classification performance. We address this question by proposing a novel, simple, yet very powerful biologically-inspired filtering (BF) which simulates the performance of human retina. In the proposed approach, given a texture image, after applying a DoG filter to detect the "edges", we first split the filtered image into two "maps" alongside the sides of its edges. The feature extraction step is then carried out on the two "maps" instead of the input image. Our algorithm has several advantages such as simplicity, robustness to illumination and noise, and discriminative power. Experimental results on three large texture databases show that with an extremely low computational cost, the proposed method improves significantly the performance of many texture classification systems, notably in noisy environments. The source codes of the proposed algorithm can be downloaded from https://sites.google.com/site/nsonvu/code.Comment: 11 page

Impact of provincial competitiveness index (PCI) on economic development in the Red River Delta, Vietnam

The development of an economy is significant since it has far-reaching implications for several industries. Particularly, the income levels of inhabitants in crucial locations must reach a specific threshold for an economy to flourish effectively. To achieve this goal, it is vital to determine the factors that affect economic development. A significant aspect that can improve people's living standards is enhanced competitiveness. Therefore, this study employs the generalized ordinary least squares (GLS) method to examine the provincial competitiveness index (PCI) on economic development as measured by per capita income in the Red River Delta of Vietnam. The panel data of eleven Red River Delta provinces from 2010 to 2021 was studied. The results indicate that the provincial competitiveness index has a beneficial impact on economic growth and contributes to an increase in the income levels of the populace. The study also shows that labor literacy rate and trade openness also contribute to economic development while labor growth rate inhibits long-term economic development. Governments need to analyze indicators to find solutions to improve national competitiveness. In particular, it is necessary to pay attention to the business environment, apply technology in handling administrative procedures and have policies to support business capital creation for domestic enterprises

A Comparison between Male and Female Lab Rats in Operant Conditioning

Undergraduate Basi

Distinguishing Antonyms and Synonyms in a Pattern-based Neural Network

Distinguishing between antonyms and synonyms is a key task to achieve high performance in NLP systems. While they are notoriously difficult to distinguish by distributional co-occurrence models, pattern-based methods have proven effective to differentiate between the relations. In this paper, we present a novel neural network model AntSynNET that exploits lexico-syntactic patterns from syntactic parse trees. In addition to the lexical and syntactic information, we successfully integrate the distance between the related words along the syntactic path as a new pattern feature. The results from classification experiments show that AntSynNET improves the performance over prior pattern-based methods.Comment: EACL 2017, 10 page

Asymptotic integration of linear differential-algebraic equations

Abstract. This paper is concerned with the asymptotic behavior of solutions of lin-ear differential-algebraic equations with asymptotically constant coefficients. Some re-sults of asymptotic integration which are well known for ordinary differential equations (ODEs) are extended to differential-algebraic equations (DAEs)

Eco-friendly Super Sulphated Cement Concrete Using Vietnam Phosphogypsum and Sodium Carbonate Na2CO3

Sustainable development is one of the critical topics in the construction industry today, especially in reducing CO2 emissions and production energy costs. There have been many studies worldwide on using ground granulated blast furnace slag combined with phosphogypsum (PG) to replace binder (B) in making concrete. However, this topic in Vietnam has not received much attention despite the large backlog of phosphogypsum waste. One of the main disadvantages limiting the feasibility of super-sulphated binders in concrete is the relatively slow hydration and hardening processes, which affect the rate of strength development of mortar and concrete, especially at an early age. In this study, the use of Na2CO3 salt as a quick, solid additive can overcome the disadvantages of this type of binder. Research results show that using 15 to 25% phosphorus gypsum waste (PG) and a combination of 60 to 80% finely granulated blast furnace slag (GGBFS) with a small amount of cement and an activator like Na2CO3can replace cement in making concrete. The concrete mix has good workability, and the maximum compressive strength after 28 days can reach over 50 MPa. Using industrial wastes as the main ingredients to make binders will improve sustainable development, reducing environmental pollution and the cost of mortar and concrete products in construction. Doi: 10.28991/CEJ-2022-08-11-06 Full Text: PD

Model reduction of unstable systems based on balanced truncation algorithm

Model reduction of a system is an approximation of a higher-order system to a lower-order system while the dynamic behavior of the system is almost unchanged. In this paper, we will discuss model order reduction (MOR) strategies for unstable systems, in which the method based on the balanced truncation algorithm will be focused on. Since each MOR algorithm has its strengths and weakness, practical applications should be suitable for each specific requirement. Simulation results will demonstrate the correctness of the algorithms

Structural, orientational, ontological conceptual metaphors and implications for language teaching

Language expressions in most languages are largely shaped by conceptual metaphors. However, the underlying metaphor that can help language learners better understand language expressions is often taken for granted. This article discusses how structural, orientation, ontological conceptual metaphors work in forming new language expressions or idioms. From this insight, several suggestions for EFL classes are made