How to perform and report an impactful analysis using partial least squares: Guidelines for confirmatory and explanatory IS research

Partial least squares path modeling (PLS-PM) is an estimator that has found widespread application for causal information systems (IS) research. Recently, the method has been subject to many improvements, such as consistent PLS (PLSc) for latent variable models, a bootstrap-based test for overall model fit, and the heterotrait-to-monotrait ratio of correlations for assessing discriminant validity. Scholars who would like to rigorously apply PLS-PM need updated guidelines for its use. This paper explains how to perform and report empirical analyses using PLS-PM including the latest enhancements, and illustrates its application with a fictive example on business value of social media.     

Multi-Purpose Forensics of Image Manipulations Using Residual- Based Feature

The multi-purpose forensics is an important tool for forge image detection. In this paper, we propose a universal feature set for the multi-purpose forensics which is capable of simultaneously identifying several typical image manipulations, including spatial low-pass Gaussian blurring, median filtering, re-sampling, and JPEG compression. To eliminate the influences caused by diverse image contents on the effectiveness and robustness of the feature, a residual group which contains several highpass filtered residuals is introduced. The partial correlation coefficient is exploited from the residual group to purely measure neighborhood correlations in a linear way. Besides that, we also combine autoregressive coefficient and transition probability to form the proposed composite feature which is used to measure how manipulations change the neighborhood relationships in both linear and non-linear way. After a series of dimension reductions, the proposed feature set can accelerate the training and testing for the multipurpose forensics. The proposed feature set is then fed into a multi-classifier to train a multi-purpose detector. Experimental results show that the proposed detector can identify several typical image manipulations, and is superior to the complicated deep CNN-based methods in terms of detection accuracy and time efficiency for JPEG compressed image with low resolution.     

Density estimates on the unit simplex and calculation of the mode of a sample

This paper addresses reliable and efficient calculation of the mode of a multivariate sample, which is a classical fusion function. In particular, we focus on the inputs given on the unit simplex, when aggregating elements of Atanassov intuitionistic fuzzy sets, interval-valued fuzzy sets and their extensions, as well as compositional data. We outline the use of a specially designed 2-additive fuzzy measures and the Choquet integral for the purposes of reducing computational complexity in higher dimensions. We present computational analysis and benchmark four different methods of density-based mode estimation.     

Towards the Unified Principles for Level 5 Autonomous Vehicles

The rapid advance of autonomous vehicles (AVs) has motivated new perspectives and potential challenges for existing modes of transportation. Currently, driving assistance systems of Level 3 and below have been widely produced, and several applications of Level 4 systems to specific situations have also been gradually developed. By improving the automation level and vehicle intelligence, these systems can be further advanced towards fully autonomous driving. However, general development concepts for Level 5 AVs remain unclear, and the existing methods employed in the development processes of Levels 0–4 have been mainly based on task-driven function development related to specific scenarios. Therefore, it is difficult to identify the problems encountered by high-level AVs. The essential logical and physical mechanisms of vehicles have hindered further progression towards Level 5 systems. By exploring the physical mechanisms behind high-level autonomous driving systems and analyzing the essence of driving, we put forward a coordinated and balanced framework based on the brain–cerebellum–organ concept through reasoning and deduction. Based on a mixed mode relying on the crow inference and parrot imitation approach, we explore the research paradigm of autonomous learning and prior knowledge to realize the characteristics of self-learning, self-adaptation, and self-transcendence for AVs. From a systematic, unified, and balanced point of view and based on least action principles and unified safety field concepts, we aim to provide a novel research concept and develop an effective approach for the research and development of high-level AVs, specifically at Level 5.     

电气化铁路既有线深路堑扩堑石方控制爆破

介绍电气化铁路既有线无隔墙台阶爆破扩堑方法。沿既有线方向设置低台阶 ,边界处布置光爆孔 ,采用“同列同段和列间微差”的起爆网路。采用自制的“炮被”和架设“钢管排架”阻挡飞石、滚石和滑石 ,确保了既有线的安全。文中还概述了“炮被”和“钢管排架”的制做以及作者的认识和体会。     

气体间隔装药技术在边坡控制爆破中的研究

针对弓长岭露天矿西端帮固定坑线(公路)下残存有较大规模磁铁矿体的现状，为保证其充分合理回收，研究采用气体间隔装药技术来实施爆破。气体间隔装药的药柱爆炸后产生爆轰波压力或压应力效应，空气间隔柱的存在会有效降低爆轰波的初始压力，使药柱两端的空气间隔段过粉碎现象减少，爆破作用时间延长，从而保护边坡。     

含高承压水黄土层中注浆堵水的理论与实践

在高承压水黄土层中掘井筒，使用冷冻法似乎又成了工程定例，但其高昂的施工费用常令建设者望而却步。而运用廉价的普通注浆的方法进行堵水能保证井筒安然通过，国内外鲜有成功 例。     

Solving method of generalized nonlinear dynamic least squares for data processing in building of digital mine

Data are very important to build the digital mine. Data come from many sources, have different types and temporal states. Relations between one class of data and the other one, or between data and unknown parameters are more nonlinear. The unknown parameters are non-random or random, among which the random parameters often dynamically vary with time. Therefore it is not accurate and reliable to process the data in building the digital mine with the classical least squares method or the method of the common nonlinear least squares. So a generalized nonlinear dynamic least squares method to process data in building the digital mine is put forward. In the meantime, the corresponding mathematical model is also given. The generalized nonlinear least squares problem is more complex than the common nonlinear least squares problem and its solution is more difficultly obtained because the dimensions of data and parameters in the former are bigger. So a new solution model and the method are put forward to solve the generalized nonlinear dynamic least squares problem. In fact, the problem can be converted to two sub-problems, each of which has a single variable. That is to say, a complex problem can be separated and then solved. So the dimension of unknown parameters can be reduced to its half, which simplifies the original high dimensional equations. The method lessens the calculating load and opens up a new way to process the data in building the digital mine, which have more sources, different types and more temporal states.     

三次NURBS曲线轮廓的数控加工编程处理

在给定具体型值点的条件下 ,通过反求工程 ,构造出三次NURBS曲线的参数方程 ,并提出了一种利用最小二乘圆对NURBS曲线进行分段圆弧逼近的数控编程方法 ,它基于NURBS曲线的矩阵表示 ,在满足精度的要求下 ,可使拟合圆弧段数最少 ,并能够减小拟合误差、简化数值计算和编程 ,从而减少CAD系统与CNC系统的数据传送 ,提高了加工效率和质量     

断层分形分布之间的相关关系

根据断层几何和其物理机理与特征，分析了断层数目分布、位移分布和间距分布的分形维之间的相关性。建立了断层系统表面迹的分形模型，研究了断层分形分布的分形维数与断层系统表面迹线分维的相关关系。只要测定出任意两种分布的分维就能推算出其它分布的分维值。