A Robust Transformation-Based Learning Approach Using Ripple Down Rules for Part-of-Speech Tagging

In this paper, we propose a new approach to construct a system of transformation rules for the Part-of-Speech (POS) tagging task. Our approach is based on an incremental knowledge acquisition method where rules are stored in an exception structure and new rules are only added to correct the errors of existing rules; thus allowing systematic control of the interaction between the rules. Experimental results on 13 languages show that our approach is fast in terms of training time and tagging speed. Furthermore, our approach obtains very competitive accuracy in comparison to state-of-the-art POS and morphological taggers.Comment: Version 1: 13 pages. Version 2: Submitted to AI Communications - the European Journal on Artificial Intelligence. Version 3: Resubmitted after major revisions. Version 4: Resubmitted after minor revisions. Version 5: to appear in AI Communications (accepted for publication on 3/12/2015

Average symbol error rate analysis of reconfigurable intelligent surfaces-assisted free-space optical link over log-normal turbulence channels

Optical wireless communication (OWC) has attracted significant interest recently in academia and industry. Free-space optical (FSO) communication systems are where free space acts as a communication channel between transceivers that are line of sight (LOS) for the successful transmission of optical signals. The FSO transmissions through the atmosphere, nevertheless, bring significant challenges, besides the uncertainty of atmospheric channels, especially the signal fading due to the atmospheric turbulence, attenuation and pointing errors caused by the random beam misalignments between transceivers, signal obstruction due to buildings or trees can pre-vent the transmitted message to reach the destination. This study theoretically investigates the average symbol error rate (ASER) of reconfigurable intelligent surfaces (RIS) assisted FSO link over log-normal turbulence channels. The RIS effect is examined by considering the influence of link distance, transmitted optical power, and quadrature amplitude modulation (QAM) scheme on the ASER

Grid search of multilayer perceptron based on the walk-forward validation methodology

Multilayer perceptron neural network is one of the widely used method for load forecasting. There are hyperparameters which can be used to determine the network structure and used to train the multilayer perceptron neural network model. This paper aims to propose a framework for grid search model based on the walk-forward validation methodology. The training process will specify the optimal models which satisfy requirement for minimum of accuracy scores of root mean square error, mean absolute percentage error and mean absolute error. The testing process will evaluate the optimal models along with the other ones. The results indicated that the optimal models have accuracy scores near the minimum values. The US airline passenger and Ho Chi Minh city load demand data were used to verify the accuracy and reliability of the grid search framework

PURIFICATION OF PHOSPHOGYPSUM FOR USE AS CEMENT RETARDER BY SULPHURIC ACID TREATMENT

Phosphogypsum is a by-product of the wet phosphoric acid production. In this study, chemical compositions of phosphogypsum waste (PG) in Hai Phong diammonium phosphate plant (DAP1) and Lao Cai diammonium phosphate plant (DAP2) in Vietnam were surveyed for the purpose of gypsum recovery by P2O5, F removal to meet TCVN11833 for use treated gypsum as cement retarder. Studies of impurities P2O5, F, TOC removal by sulfuric acid 10 % at 28 0C was presented. The results found that the combination of a low concentration of sulfuric acid treatment, washing, lime neutralizing, and thermal treatment was successful in Phoshogypsum treatment for use as cement retarder. The cement test proved that treated PG could partially replace natural gypsum as a retarder.Keywords:  phosphogypsum treatment, phosphorus pentoxide removal, calcium sulfate transition phase, cement retarder.

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

Analysis on the performance of reconfigurable intelligent surface-aided free-space optical link under atmospheric turbulence and pointing errors

Free-space optical (FSO) communication can provide the cost-efficient, secure, high data-rate communication links required for applications. For example, it provides broadband Internet access and backhauling for the fifth-generation (5G) and the sixth-generation (6G) communication networks. However, previous solutions to deal with signal loss caused by obstructions and atmospheric turbulence. In these solutions, reconfigurable intelligent surfaces (RISs) are considered hardware technology to improve the performance of optical wireless communication systems. This study investigates the pointing error effects for RIS-aided FSO links under atmospheric turbulence channels. We analyze the performance of RIS-aided FSO links influenced by pointing errors, atmospheric attenuation, and turbulence for the subcarrier quadrature amplitude modulation (SC-QAM) technique. Atmospheric turbulence is modeled using log-normal distribution for weak atmospheric turbulence. Several numerical outcomes obtained for different transmitter beam waist radius and pointing error displacement standard deviation are shown to quantitatively illustrate the average symbol error rate (ASER)

PSDiff: Diffusion Model for Person Search with Iterative and Collaborative Refinement

Dominant Person Search methods aim to localize and recognize query persons in a unified network, which jointly optimizes two sub-tasks, \ie, detection and Re-IDentification (ReID). Despite significant progress, two major challenges remain: 1) Detection-prior modules in previous methods are suboptimal for the ReID task. 2) The collaboration between two sub-tasks is ignored. To alleviate these issues, we present a novel Person Search framework based on the Diffusion model, PSDiff. PSDiff formulates the person search as a dual denoising process from noisy boxes and ReID embeddings to ground truths. Unlike existing methods that follow the Detection-to-ReID paradigm, our denoising paradigm eliminates detection-prior modules to avoid the local-optimum of the ReID task. Following the new paradigm, we further design a new Collaborative Denoising Layer (CDL) to optimize detection and ReID sub-tasks in an iterative and collaborative way, which makes two sub-tasks mutually beneficial. Extensive experiments on the standard benchmarks show that PSDiff achieves state-of-the-art performance with fewer parameters and elastic computing overhead