An Easy-to-use and Economic Experimental Apparatus for Motion Control Education

Motion control education in engineering requires hands-on experiments to catch the concept of feedback control, but experimental apparatus for motion control experiments is expensive, complex in mechanism and is hard to use it in general. In this paper, we develop an easy-to-use and economic experimental apparatus for motion control education using an open-source free operation system LINUX and a free real-time kernel RTAI. The developed apparatus is reliable in mechanical structure, and fast enough to realize 100 microsecond sampling time for real-time control purpose, and so it can test conventional PID control logics, various input shaping control logics and advanced motion control logics with cheap prices. The validity of the developed motion control apparatus is demonstrated by testing P, PD control logics and ZV input shapers experimentally

Uso de variables de mercado en la predicción de dificultades financieras para las empresas que cotizan en Vietnam

This paper aims to investigate the classification power of market variables as predictors in the financial distress prediction model for listed companies in a frontier market as Vietnam securities market. Data is collected from 70 financially distressed companies that suffer a loss in 3 consecutive years and 156 non-financially distressed companies in Vietnam from 2010 to 2017. Four different models have been constructed using Logit regression and SVM analysis technique to make a prediction in 1 to 3-year ahead. The analysis results show that combining accounting ratios with market variables such as price volatility and P/E can improve the classification ability of the ex-ante model. In addition, contrary to the results of related previous researches in emerging markets, in this study, Logit models outperform SVM models. Therefore, for future research, models that apply other machine learning classifiers such as Decision Tree (DT) or Neural Network (NN) should be investigated.Este artículo tiene como objetivo investigar el poder de clasificación de las variables del mercado como factores predictivos en el modelo de predicción de dificultades financieras para las empresas que cotizan en bolsa en un mercado fronterizo como el mercado de valores de Vietnam. Los datos se recopilan de 70 compañías con dificultades financieras que sufrieron una pérdida en 3 años consecutivos y 156 empresas sin dificultades financieras en Vietnam desde 2010 a 2017. Se han construido cuatro modelos diferentes utilizando regresión Logit y la técnica de análisis de SVM para hacer una predicción en 1 a 3 años por delante. Los resultados del análisis muestran que la combinación de ratios contables con variables de mercado como la volatilidad de los precios y el P / E puede mejorar la capacidad de clasificación del modelo ex ante. Además, a diferencia de los resultados de investigaciones anteriores relacionadas en mercados emergentes, en este estudio, los modelos Logit superan a los modelos SVM. Por lo tanto, para futuras investigaciones, se deben investigar los modelos que aplican otros clasificadores de aprendizaje automático, como el Árbol de decisiones (DT) o la Red neuronal (NN)

Two-Phase Defect Detection Using Clustering and Classification Methods

Autonomous fault management of network and distributed systems is a challenging research problem and attracts many research activities. Solving this problem heavily depends on expertise knowledge and supporting tools for monitoring and detecting defects automatically. Recent research activities have focused on machine learning techniques that scrutinize system output data for mining abnormal events and detecting defects. This paper proposes a two-phase defect detection for network and distributed systems using log messages clustering and classification. The approach takes advantage of K-means clustering method to obtain abnormal messages and random forest method to detect the relationship of the abnormal messages and the existing defects. Several experiments have evaluated the performance of this approach using the log message data of Hadoop Distributed File System (HDFS) and the bug report data of Bug Tracking System (BTS). Evaluation results have disclosed some remarks with lessons learned

An Extended Occlusion Detection Approach for Video Processing

Occlusions become conspicuous as failure regions in video processing when unified over time because the contraventions of the restriction of brightness have accumulated and evolved in occluded regions. The accuracy at the boundaries of the moving objects is one of the challenging areas that required further exploration and research. This paper presents the work in process approach that can detect occlusion regions by using pixel-wise coherence, segment-wise confidence and interpolation technique. Our method can get the same result as usual methods by solving only one Partial Differential Equations (PDE) problem; it is superior to existing methods because it is faster and provides better coverage rates for occlusion regions than variation techniques when tested against a varied number of benchmark datasets. With these improved results, we can apply and extend our approach to a wider range of applications in computer vision, such as background subtraction, tracking, 3D reconstruction, video surveillance, video compression

Equality of ordinary and symbolic powers of Stanley-Reisner ideals

This paper studies properties of simplicial complexes for which the m-th symbolic power of the Stanley-Reisner ideal equals to the m-th ordinary power for a given m > 1. The main results are combinatorial characterizations of such complexes in the two-dimensional case. It turns out that there exist only a finite number of complexes with this property and that these complexes can be described completely. As a consequence we are able to determine all complexes for which the m-th ordinary power of the Stanley-Reisner ideal is Cohen-Macaulay for a given m > 1.Comment: 19 page

Visualizing thickness-dependent magnetic textures in few-layer Cr2Ge2Te6\text{Cr}_2\text{Ge}_2\text{Te}_6

Magnetic ordering in two-dimensional (2D) materials has recently emerged as a promising platform for data storage, computing, and sensing. To advance these developments, it is vital to gain a detailed understanding of how the magnetic order evolves on the nanometer-scale as a function of the number of atomic layers and applied magnetic field. Here, we image few-layer $\text{Cr}_2\text{Ge}_2\text{Te}_6$ using a combined scanning superconducting quantum interference device and atomic force microscopy probe. Maps of the material's stray magnetic field as a function of applied magnetic field reveal its magnetization per layer as well as the thickness-dependent magnetic texture. Using a micromagnetic model, we correlate measured stray-field patterns with the underlying magnetization configurations, including labyrinth domains and skyrmionic bubbles. Comparison between real-space images and simulations demonstrates that the layer dependence of the material's magnetic texture is a result of the thickness-dependent balance between crystalline and shape anisotropy. These findings represent an important step towards 2D spintronic devices with engineered spin configurations and controlled dependence on external magnetic fields.Comment: 15 pages, 4 figures, and supplementary informatio

Elevated Levels of Cell-Free Circulating DNA in Patients with Acute Dengue Virus Infection

BACKGROUND: Apoptosis is thought to play a role in the pathogenesis of severe dengue and the release of cell-free DNA into the circulatory system in several medical conditions. Therefore, we investigated circulating DNA as a potential biomarker for severe dengue. METHODS AND FINDINGS: A direct fluorometric degradation assay using PicoGreen was performed to quantify cell-free DNA from patient plasma. Circulating DNA levels were significantly higher in patients with dengue virus infection than with other febrile illnesses and healthy controls. Remarkably, the increase of DNA levels correlated with the severity of dengue. Additionally, multivariate logistic regression analysis showed that circulating DNA levels independently correlated with dengue shock syndrome. CONCLUSIONS: Circulating DNA levels were increased in dengue patients and correlated with dengue severity. Additional studies are required to show the benefits of this biomarker in early dengue diagnosis and for the prognosis of shock complication

Quality of Life and Suitability with Vietnamese Harmonious Face Index in Class III Malocclusion Patients

BACKGROUND: Maxillary Lefort I osteotomy, mandibular bilateral sagittal split ramus was frequently used in correcting skeletal class III malocclusion. There was a lack of research on class III malocclusion patients’ quality of life (QoL) after bimaxillary osteotomy. AIM: Class I Intermaxillary relationship was achieved, aesthetic was significantly improved. Significant improvement in Class III skeletal patients’ quality of life was acquired. The achievement of harmonious face would be beneficial to the facial aesthetics of patients, thus improving the quality of life. METHODS: Harmonious face index is an effective criterion in assessing the surgery’s outcome. In this study was conducted on 30 patients at Hanoi National Hospital of Odontostomatology, Viet Duc Hospital, and Hong Ngoc Hospital from April 2017 to April 2018, and it was a quasi-experimental study with self-comparison, 12 months follow up. RESULTS: Orthognathic surgery effectively corrected malocclusion crossbite, dental compensation, and helped to improve facial aesthetics. 100% of patients had the quality of life improved, good quality of life consisted of 86.7%. In comparison with a harmonious facial index of Kinh ethnic in Vietnam, 70% of patients achieved skeletal harmony, 63.3% of patients achieved dental harmony, 80% achieved soft tissue harmony. CONCLUSIONS: Vietnamese harmonious facial index should be used in planning and pre-surgical simulatio