A Distance-Based Method for Attribute Reduction in Incomplete Decision Systems

There are limitations in recent research undertaken on attribute reduction in incomplete decision systems. In this paper, we propose a distance-based method for attribute reduction in an incomplete decision system. In addition, we prove theoretically that our method is more effective than some other methods

An Empirical Analysis of the Prominent Roles of Taxations in the Synchronicity on Boost of Maritime Industry in Singapore

This research examines the causal nexuses of the taxations and financial elements in the synchronistic policy that Singapore has applied to radically boost its maritime & offshore fields to develop its economic growths and make Singapore to be a remarkable country in the world in term of ships building volumes, the numbers of ship registries, and the numbers of deadweight in thousands tons arriving at ports nowadays. There are several factors relating to the economic growths and increased numbers of vessels arriving at ports for instant those are the volumes of import & export merchandises, prices of petrochemical and refined oils, services, etc. In this research, it is aimed at decipher the real effectiveness, the interferences, and the prominent roles of corporate tax (TAX) when it is employed together with the domestic credit to private sector (CRE_X1), the real interest rate (RRATE_X2), and the listed stock companies (STOCK_CO) in one synchronous-financial model during the 1980- 2014 period by using the co-integration and vector error correction models for Granger causality tests, and based on the empirical findings, policymakers could find some interesting issues to their developing plans, hopefully. Keywords: Maritime & Offshore Industry, Economic growth, Co-integration, Granger causality tests, Singapore. JEL Classifications: C1; C

Unveiling the Impact of Human Influence on Species Distributions in Vietnam: A Case Study Using Babblers (Aves: Timaliidae)

As developing countries give priority to economic growth, the effects of development threaten natural habitats and species distributions. Over the course of two decades, Vietnam has rapidly developed, especially in the expansion of agricultural production. However, no study has quantitatively measured the effects of recent human impact on the effects of past species distributions in Vietnam. We use locality data collected from multiple natural history collections, including several in Vietnam, to infer past species distributions. We assess habitat availability of five common babbler species (Aves: Timaliidae) using distribution models with data prior to rapid development that followed political reform. Overlaying the Global Human Influence Index with predicted distributions highlights the human impact on these distributions. Three important patterns emerge: (1) human impact influences common Timaliidae distributions similarly, (2) widespread species distributions show higher fragmentation due to human influence compared to narrowly distributed species in Vietnam, and (3) less than 20% of distributions overlap with nationally declared protected areas. We emphasize that conservation efforts should not only prioritize individual species, but also focus efforts on a regional scale, and that the use of museum data can be highly informative in conservation analyses. There are current obstacles to enforcing conservation of Vietnam’s already fragmented habitats, but our results suggest there is still time to reevaluate conservation approaches

Position control for haptic device based on discrete-time proportional integral derivative controller

Haptic devices had known as advanced technology with the goal is creating the experiences of touch by applying forces and motions to the operator based on force feedback. Especially in unmanned aerial vehicle (UAV) applications, the position of the end-effector Falcon haptic sets the velocity command for the UAV. And the operator can feel the experience vibration of the vehicle as to the acceleration or collision with other objects through a forces feedback to the haptic device. In some emergency cases, the haptic can report to the user the dangerous situation of the UAV by changing the position of the end-effector which is be obtained by changing the angle of the motor using the inverse kinematic equation. But this solution may not accurate due to the disturbance of the system. Therefore, we proposed a position controller for the haptic based on a discrete-time proportional integral derivative (PID) controller. A Novint Falcon haptic is used to demonstrate our proposal. From hardware parameters, a Jacobian matrix is calculated, which combines with the force output from the PID controller to make the torque for the motors of the haptic. The experiment was shown that the PID has high accuracy and a small error position

Datasets of land use change and flood dynamics in the vietnamese mekong delta

This paper compiles the data associated with a research article published in STOTEN [1]. The data set represents figures, tables, and images illustrating the temporal and spatial distribution of land use and flood dynamics from 2000 to 2020 in the Vietnamese Mekong Delta (VMD). The MODIS imageries were freely accessed online via the NASA website [2] and processed to land use and flood maps based on the algorithms by Sakamoto et al. [3,4]. The MODIS products show a high validation with statistical data and radar satellites [1]. The datasets of flood map and land use, therefore, are available to scientists, engineers, and policy-makers in agricultural management associated with flood management in the VMD. They could be used for policy settings, household livelihood assessment as well as other economic analyses for the VMD region due to the change of land use and flooding dynamics

ChatGPT as a Math Questioner? Evaluating ChatGPT on Generating Pre-university Math Questions

Mathematical questioning is crucial for assessing students problem-solving skills. Since manually creating such questions requires substantial effort, automatic methods have been explored. Existing state-of-the-art models rely on fine-tuning strategies and struggle to generate questions that heavily involve multiple steps of logical and arithmetic reasoning. Meanwhile, large language models(LLMs) such as ChatGPT have excelled in many NLP tasks involving logical and arithmetic reasoning. Nonetheless, their applications in generating educational questions are underutilized, especially in the field of mathematics. To bridge this gap, we take the first step to conduct an in-depth analysis of ChatGPT in generating pre-university math questions. Our analysis is categorized into two main settings: context-aware and context-unaware. In the context-aware setting, we evaluate ChatGPT on existing math question-answering benchmarks covering elementary, secondary, and ternary classes. In the context-unaware setting, we evaluate ChatGPT in generating math questions for each lesson from pre-university math curriculums that we crawl. Our crawling results in TopicMath, a comprehensive and novel collection of pre-university math curriculums collected from 121 math topics and 428 lessons from elementary, secondary, and tertiary classes. Through this analysis, we aim to provide insight into the potential of ChatGPT as a math questioner.Comment: Accepted at the 39th ACM/SIGAPP Symposium On Applied Computing (SAC 2024), Main Conferenc