数控机床加工非圆曲线的程序编制方法

对在数控机床上不能直接进行插补加工的非圆曲线、列表函数，提出了用三次样条函数插值、用双圆弧逼近加工轮廓线的方法，并给出了在计算机上予以实现的流程图。     

刀具磨损声谱特征的分析

刀具在切削过程中，会产生大量的声信号。文中运用统计方法对切削声信号进行了深入分析，并对可听阈内的声信号按低频带、中频带和高频带分别进行了功率谱分析。研究结果表明，切削声信号中100—8kHz频带内的特征频率分量反映了刀具磨损状态及其变化规律，这为利用声信号进行刀具实时在线监测奠定了基础。     

HSn70-1B铜管在碱性NaCl溶液中的腐蚀行为

利用表面分析技术和电化学方法研究了HSn70- 1B 铜管在碱性NaCl溶液中的腐蚀行为.在自腐蚀状态下，HSn70-1B铜管表面生成以Cu2 O为主的表面膜；在阳极极化电位下表面CuCl的生成反应为一级反应，电极表面形成CuCl膜 后，存在极限电流密度；电化学阻抗频谱(EIS)有2个容抗弧，随Cl-含量的增加，容抗弧 逐渐收缩，弥散性增大.     

边坡堆积体锚索钻孔工艺探讨

在堆积体及破碎的岩体边坡锚索施工中较容易出现卡钻、埋钻、洗孔困难等现象,而且施工安全、质量、进度、成本得不到很好的控制。采用跟管钻进工艺钻至一定深度后,换用φ138直钎继续钻进至终孔,并在钻进过程中进行必要的固壁灌浆,以利于非跟管段的孔壁稳定,避免卡钻、埋钻等现象的发生,有利于减少事故、提高功效;此方法可用于各种特殊地质情况,钻进方法更加稳妥,钻进速度更快,施工质量更好,投资更省。     

Exploring the Belief Systems of Software Development Professionals

It is commonly accepted that an individual's beliefs and actions are based on his or her assessment and perceptions of the world. In order to determine what practices an individual is likely to follow at any given time, it is necessary to understand the individual's behavioral intention in a given circumstance. From an Information Technology perspective, a software development professional's belief systems are potentially the basis for the adoption and implementation of new and innovative work practices and processes. In this article, we explore the belief systems of software development professionals in order to understand the beliefs underlying intention and practice, and we seek answers about how they adopt or reject new and innovative software development processes and practices. The results point out a strong influence of past experiences, personality types, and repeated behavior on current software development processes and practices in industrial settings.     

Case‐based approach for supporting strategy decision making

The practice of strategy decision making proves that when the management board is strongly limited in its capacity to take rational actions, specifically in the context of great decision complexity and uncertainty, it is considered good practice to refer to experience through reasoning by analogy. In this paper, we would like to concentrate on supporting strategic decisions in small and medium enterprises (SMEs). The complexity of analogy‐based reasoning has its roots in an attempt to solve new problems based on past cases from a different domain, while we will focus on case‐based approach for a single domain. Additionally, we have chosen case‐based reasoning as a suitable decision‐making paradigm because it is corresponds to managers’ decision‐making behaviour. We present the STRATEGOS case‐based reasoning system for supporting strategic decision making by SMEs management boards and then the system evaluation by the dozens of chief executive officers (CEOs) from SMEs is presented. The results of the survey are promising and show the remarkable correspondence of the proposed solution with expectations and strategic behaviour of CEOs.     

An integrated DEMATEL and Fuzzy ANP techniques for evaluation and selection of outsourcing provider for a telecommunication company

In recent years, strategy aspects related to core competency, risk analysis and organizational flexibility especially have been growing. This trend has led researchers and industries to become more interested in the multi-criteria decision making (MCDM) models for selecting outsourcing providers. The efficiency of decision-making mostly depends on the ability of decision-makers analyzing the complex cause and effect relationship between criteria and taking effective actions based on the analysis. Using an analytical method to select the most eligible outsourcing provider is significant for a company which desires to improve its competitiveness. In this study, a fuzzy integrated multi-criteria decision making method for evaluation and determination of an outsourcing provider for a telecommunication company is analyzed by using DEMATEL and Fuzzy ANP multi-criteria decision making techniques. First, DEMATEL method is used in order to put forward the interrelationship among the main criteria which are determined in the study for outsourcing selection process. Then, local weights of the sub-criteria and sub-subcriteria are calculated by Fuzzy ANP approach on the basis of cause-effect relationships that are exposed through DEMATEL method. The local weights are put into ANP supermatrix, and calculations are implemented to select out the most eligible outsourcing provider.     

Data-based multiple-model prediction of the production rate for hematite ore beneficiation process

The prediction of the production rate of the hematite ore beneficiation process is important to plant-wide optimization. This paper presents a data-based multi-model approach to predict the production rate with multiple operating modes. The inputs of the predictive model are the performance indices of each unit process, and the output is the global production index (the production rate) of the hematite ore beneficiation process. The multiple models are developed by integrating the fuzzy clustering algorithm and machine learning algorithm. A global model, Takagi–Sugeno–Kang fuzzy model, and multiple neural network model were compared using the data obtained from a practical industrial process, and the effectiveness of the proposed algorithm was proven.     

Supervised Distance Preserving Projections: Applications in the quantitative analysis of diesel fuels and light cycle oils from NIR spectra

In this work, we discuss a recently proposed approach for supervised dimensionality reduction, the Supervised Distance Preserving Projection (SDPP) and, we investigate its applicability to monitoring material's properties from spectroscopic observations. Motivated by continuity preservation, the SDPP is a linear projection method where the proximity relations between points in the low-dimensional subspace mimic the proximity relations between points in the response space. Such a projection facilitates the design of efficient regression models and it may also uncover useful information for visualisation. An experimental evaluation is conducted to show the performance of the SDPP and compare it with a number of state-of-the-art approaches for unsupervised and supervised dimensionality reduction. The regression step after projection is performed using computationally light models with low maintenance cost like Multiple Linear Regression and Locally Linear Regression with k-NN neighbourhoods. For the evaluation, a benchmark and a full-scale calibration problem are discussed. The case studies pertain the estimation of a number of chemico-physical properties in diesel fuels and in light cycle oils, starting from near-infrared spectra. Based on the experimental results, we found that the SDPP leads to parsimonious projections that can be used to design light and yet accurate estimation models.