A gradient boosting decision tree approach for insider trading identification: An empirical model evaluation of China stock market

Insider trading is a kind of criminal behavior in stock market by using nonpublic information. In recent years, it has become the major illegal activity in China’s stock market. In this study, a combination approach of GBDT (Gradient Boosting Decision Tree) and DE (Differential Evolution) is proposed to identify insider trading activities by using data of relevant indicators. First, insider trading samples occurred from year 2007 to 2017 and corresponding non-insider trading samples are collected. Next, the proposed method is trained by the GBDT, and initial parameters of the GBDT are optimized by the DE. Finally, out-of-samples are classified by the trained GBDT–DE model and its performances are evaluated. The experiment results show that our proposed method performed the best for insider trading identification under time window length of ninety days, indicating the relevant indicators under 90-days time window length are relatively more useful. Additionally, under all three time window lengths, relative importance result shows that several indicators are consistently crucial for insider trading identification. Furthermore, the proposed approach significantly outperforms other benchmark methods, demonstrating that it could be applied as an intelligent system to improve identification accuracy and efficiency for insider trading regulation in China stock market.     

Latent communities of digital publications: The role of editors,followers, and advertisers

This research explores how digital publications may be turned into something more than just a meeting point for people who are seeking information and may become a latent community. The paper proposes that the network of editors, followers, and advertisers of digital publications determine the user sense of community towards the publication. While the pattern of connections among editors and followers reinforces the sense of community, advertisers act as intruders who weaken the feasibility of building a community. Data were collected from followers of digital publications. The dynamics of the sense of community is described as a process in which informational value and identification are essential to nurturing readers’ soft or hard commitment. Findings indicate that the strong ties between editors and followers as well as the diversity positively impacts on informational value and identification, whereas advertising intrusiveness diminishes the informational value.     

Modelling,simulation and identification of an engine air path electromechanical actuator

This paper deals with the modelling and the identification of an electromechanical Diesel engine actuator. The studied Bosch GPA-S actuator is designed for swirl/tumble flaps to control the air amount entering into the cylinder. This study aims to design a complete simulator that reproduces, with sufficient accuracy, the actuator dynamics taking into account the effects of the friction phenomenon. Hence, an overview of the actuator structure and its operation principle is first given. Then, its mathematical model as well as the nonlinearity, related to its behaviour, is discussed. Next, three identification procedures, which allow estimating both the system parameters and the friction model coefficients, are introduced. Finally, simulation results, using MATLAB, and experimental results, using LabVIEW, are presented demonstrating the effectiveness of the proposed techniques.     

基于CapsNet的汉字字形表征模型

提出基于胶囊神经网络(CapsNet)的汉字字形表征模型,通过表征汉字字形中的部件实现汉字字形的表征.首先,对任一汉字字形生成所有部件类别的表征向量.然后,根据部件存在概率,利用基于欧氏距离的离群点检测,选取相应的部件表征向量.最后,由选出的部件表征向量组成该汉字的字形表征.实验表明,文中模型在仅经过部件字形训练的情况下,即可有效识别汉字部件,同时自动生成汉字字形的有效表征.     

Optimized techniques for driving and control of the switched reluctance motor to improve efficiency

This work presents modeling, driving and classical speed control techniques for the switched reluctance motor. The aim is to improve the computational model, the control response and the machine efficiency. A parametric regression model was used to find the inductance profile of the switched reluctance motor and from the new inductance profile model. The drive and control techniques are shown: (i) with speed control acting on the excitation voltage and fixed switching angles, (ii) with speed control acting on the switching angles and fixed excitation voltage and (iii) with speed control acting on the excitation voltage, in this case, with dynamic switching angles and controller parameters. The inductance profile is represented by expression and inserted into the machine computer model, allowing greater precision and low computational cost. The speed control acting on the excitation voltage with dynamic controller parameters and dynamic switching angles allowed: (i) shorter response time for a wide range of control, (ii) higher efficiency, (iii) low computational cost and (iv) simplified implementation and maintenance. The techniques proposed in this work obtained precision of the computational model with respect to the system (in workbench) and optimized parameters in a wide range of the speed control, allowing an improvement of switched reluctance motor efficiency.     

Flow pattern identification and measurement techniques in gas-liquid-liquid three-phase flow: A review

The simultaneous flow of gas, oil, and water forms various flow patterns due to the complex interfacial relationships. Three-phase flow patterns are classified as the gas-liquid and liquid-liquid flow patterns. Pressure drop, void fraction, liquid holdup, and phase distribution are important characteristics of the three-phase flow. These characteristics are generally associated with the three-phase flow patterns. Hence, the knowledge about flow patterns can help to predict the overall behavior of the three-phase flow. Studies have been conducted to identify three-phase flow pattern and their characteristics at various superficial velocities of gas, oil, and water. The major purpose of the studies is to gather information about the three-phase co-current flow and use it for improvement of the efficiency of the flow systems. Therefore, the accuracy of the measurement technique is critical. Several types of flow pattern identification and measurement techniques have been developed to improve accuracy and provide high-quality results. In this article, classical and advanced techniques used for the three-phase flow identification and measurement have been reviewed. The survey will help the researchers working in the area of multiphase flow to choose the right technique based on the objectives of the studies.     

Metacarpophalangeal joint patterns based personal identification system

This paper introduces a novel approach for identity authentication system based on metacarpophalangeal joint patterns (MJPs). A discriminative common vector (DCV) based method is utilized for feature selection. In the literature, there is no study using whole MJP for identity authentication, exceptionally a work (Ferrer et al., 2005) using the hand knuckle pattern which is some part of the MJP draws the attention as a similar study. The originality of this approach is that: whole MJP is firstly used as a biometric identifier and DCV method is firstly applied for extracting the feature set of MJP. The developed system performs some basic tasks like image acquisition, image pre-processing, feature extraction, matching, and performance evaluation. The feasibility and effectiveness of this approach is rigorously evaluated using the k-fold cross validation technique on two different databases: a publicly available database and a specially established database. The experimental results indicate that the MJPs are very distinctive biometric identifiers and can be securely used in biometric identification and verification systems, DCV method is successfully employed for obtaining the feature set of MJPs and proposed MJP based authentication approach is very successful according to state of the art techniques with a recognition rate of between 95.33% and 100.00%.     

山茶籽油真实属性鉴别方法研究进展

山茶籽油是一种纯天然高级食用植物油,富含油酸、亚油酸等功能性成分,具有抗衰老、提高免疫力、预防肥胖等作用。近年山茶籽油因其具有极高的营养价值,备受人们关注。然而,一些不法商贩为了谋取利益,在山茶籽油中掺入低价食用油欺骗消费者,扰乱其市场秩序。因此,为了保障消费者的合法权益和山茶籽油的良性发展,研究者必须采用相应的检测方法鉴别其真实属性。本文综述各类检测方法在鉴别山茶籽油真实属性中的应用现状,如理化分析法、光谱法、色谱法、电子鼻技术等,并根据当前鉴别方法存在的缺陷,对未来分析山茶籽油真实属性的研究趋势进行展望,旨在为食用植物油的掺杂掺假检测提供理论参考。     

A simple screen to detect hybrids between native and introduced Phragmites australis in the United States and Canada

In much of the United States and Canada, the common reed consists of both a native subspecies Phragmites australis americanus, and a highly invasive introduced subspecies P. australis australis. DNA testing is generally used to distinguish them definitively and is necessary to detect hybridization. We report a group of single nucleotide polymorphisms and indels in the nuclear NRT2 gene of Phragmites that differentiate North American native and European-introduced populations. All native samples tested were identical in NRT2 sequence over 1564 bases except for two positions. There were nine positions, consisting of seven base substitutions and two indels, at which all introduced samples were fixed for a different allele than the native samples. For the two indels, samples collected from northern Europe were also fixed for the same allele as the introduced samples collected across North America. One of the indels was easily detected by a PCR-RFLP assay and provides a rapid and inexpensive way to screen for hybrids between native and European-introduced populations of Phragmites and thus can facilitate more widespread surveillance for hybrids between native and introduced populations in North America.     

广州国际会议展览中心标志系统设计

以广州国际会议展览中心标志系统的设计为例,对设计手法及理念进行了探讨,希望能对今后类似设施的设计有所启迪。