To the humanities: what does communication studies give?

ABSTRACT

This special issue of Review of Communication presents new offerings of the study of communication, forging present and future humanities. This Introduction engages the six essays in this special issue—which extend and intersect across categories of the humanistic study of communication: communication philosophy and ethics, rhetorical theory, history, pedagogy, criticism, and digital humanities—to explore their contributions in defense of the humanities. Taken together, these essays explore the study of communication as (1) a resource for inquiring and exchanging with concepts, practices, and embodiments of difference, the other, and the posthuman; (2) a means of examining the ontological, epistemological, technological, existential, performative, and ethical implications of our communicative being, our being constituted by symbolic action and mediated exchange in ever-present yet always variant material and affective environments, spaces, and places; (3) a discipline emerging from rhetoric, one of the original liberal arts, yet developing in transdisciplinary ways, transforming the binary of humanities and sciences; (4) a tool for decolonizing knowledge(s); (5) a tool for exploring, critiquing, engaging, and creating with the new media of our digital lives together; (6) a long-standing yet ever inventive method and mode for public humanities; and (7) a praxis of resistance. These essays bring to light what studying communication offers the humanities: a plural, public, reflexive, and ever inventive enterprise for examining being human together on this planet.     

最优化算法与纯元素谱剥离相结合的能量色散X射线荧光谱解谱方法

在进行能量色散X射线荧光光谱(EDXRF)解谱时,如果给定样品的元素构成,采用纯元素谱图剥离的方式会更加合理,但由于每个元素的谱线都不止一条,如果仅仅针对主线对齐做剥离,会导致结果的严重失真,同时剥离次序对解谱结果有较大影响。介绍了一种最优化算法与纯元素谱剥离相结合的EDXRF解谱方法,该方法以多个纯元素谱的强度大小和峰位漂移道数作为变量构建残差方程,并用最优化计算的方法去调整,直至残差达到极小。实验采用强度顺序剥离、能量顺序剥离和最优化算法拟合3种方法分别对谱线重叠较为严重的La-Ce-Pr-Nd混合液样品的L系谱线进行了解析,结果表明最优化计算方法拟合的谱图与原始谱的残差 (1415.0)比另两种方法(166094.0和3192.7)大幅度缩小,拟合谱与原始谱更为吻合,并且方法在实现时对初值不敏感,解谱精度也不依赖于剥离次序。     

Salience of public leaders’ “meaning making” in news coverage of a health crisis

Meaning making by leadership in a crisis is required to reduce uncertainty. We used analytic criteria for meaning making suggested by crisis management literature to investigate public leaders’ quotations in news coverage of a health crisis. The quotations were examined in terms of the five frame functions, which include offering a credible explanation of what happened, offering guidance, instilling hope, showing empathy, and suggesting that leaders are in control. The Middle East respiratory syndrome outbreak in South Korea was examined. As a result, the most salient frame function identified was displaying they are in control of the emergency, followed by offering guidance and explaining what happened. The salience of leaders’ meaning making disappeared in coverage by a liberal newspaper.     

Improved artificial bee colony algorithm based on escaped foraging strategy

This paper presents an improved artificial bee colony algorithm. Under the framework of the basic artificial bee colony algorithm, this paper redefines the artificial bee colony and introduces search strategies for group escape and foraging based on Levy flight. The proposed algorithm is named artificial bee colony algorithm based on escaped foraging strategy (EFSABC).There are different strategies for scout bees, onlookers, and free bees searching for honey sources in the EFSABC: all working bees relinquish old honey sources due to disturbance, and select different routines to seek new honey sources. Sixteen typical high-dimensional standard functions are used to verify the effectiveness of the proposed algorithm. The EFSABC algorithm outperforms the traditional artificial bee colony algorithm in all aspects.     

Multi-objective iterative optimization algorithm based optimal wavelet filter selection for multi-fault diagnosis of rolling element bearings

Rolling element bearings (REBs) play an essential role in modern machinery and their condition monitoring is significant in predictive maintenance. Due to the harsh operating conditions, multi-fault may co-exist in one bearing and vibration signal always exhibits low signal-to-noise ratio (SNR), which causes difficulties in detecting fault. In the previous studies, maximum correlated kurtosis deconvolution (MCKD) has been validated as an efficient method to extract fault feature in the fault signals. Nonetheless, there are still some challenges when MCKD is applied to fault detection owing to the rigorous requirements of multiple input parameters. To overcome limitation, a multi-objective iterative optimization algorithm (MOIOA) for multi-fault diagnosis is proposed. In this method, correlated kurtosis (CK) is taken as a criterion to select optimal Morlet wavelet filter using the whale optimization algorithm (WOA). Meanwhile, to further eliminate the effect of the inaccurate period on CK, the update process of period is incorporated. After that, the simulated and experimental signals are utilized to testify the validity and superiority of the MOIOA for multiple faults detection by the comparison with MCKD. The results indicate that MOIOA is efficient to extract weak fault features even with heavy noise and harmonic interferences.     

Order-of-addition experiments: A review and some new thoughts

Abstract

The study of order-of-addition (OofA) experiments is prevalent in many scientific and industrial areas. The statistical design of experiments (DOE) will considerably improve the efficiency of OofA experiments. Designing and modeling the OofA experiments have increasingly received a great deal of attention. In this article, we review the latest work on the design and model of OofA experiments, and introduce some new thoughts. We believe that this article will motivate fruitful applications in real OofA experiments as well as future developments in the methodology.     

补偿强反光体表面红外测温误差的算法研究

针对运动强反光体表面温度实时测量困难、精度低这一难点,本文从红外测温原理入手,分析并揭示了红外测温精度易受到被测物体反射率、测量距离、测量环境、红外入射角等因素的影响。根据铝板材加工设备轧辊表面测温实际需要设计了一种利用红外传感器实现对强反光体表面温度点对点测量的方案。通过对测量数据的研究分析建立了一种基于斯忒藩定律的红外入射角度补偿算法,以此减小因红外入射角度变化产生的测温误差。实验结果证明本方法能较好地弥补红外入射角度变化产生的测温误差,提高测温精度。该补偿算法运算简单,适应性强,为改善入射角度变化对测温精度影响提供了新的方法。     

A similarity hybrid harmony search algorithm for the Team Orienteering Problem

The Harmony Search (HS) is a metaheuristic algorithm, which is inspired from the composition of music harmonies. The functionality and flexibility of HS contribute to the development of successful methodologies for different kind of scientific problems. The aim of this paper is to propose a variant of the classic HS algorithm in order to provide competitive solutions for the Team Orienteering Problem (TOP). We introduce the Similarity Hybrid Harmony Search (SHHS) algorithm as an alternative and innovative optimization method. The SHHS follows the standard procedure of HS with some modifications and includes a new strategy called “similarity process”. Two versions of the proposed method have been developed, the static version with predefined values for the parameters of the method and the dynamic one with dynamic adjustment of the parameters. The SHHS algorithm is applied to the known benchmark instances of TOP. The dynamic of the algorithm is tested through a complete solution analysis which gives the superiority of the dynamic version compared to the static one. The results of both versions of the proposed algorithm indicate the positive performance against other effective and robust optimization algorithms from the literature.     

Two-level intelligent modeling method for the rate of penetration in complex geological drilling process

The rate of penetration (ROP) model is of great importance in achieving a high efficiency in the complex geological drilling process. In this paper, a novel two-level intelligent modeling method is proposed for the ROP considering the drilling characteristics of data incompleteness, couplings, and strong nonlinearities. Firstly, a piecewise cubic Hermite interpolation method is introduced to complete the lost drilling data. Then, a formation drillability (FD) fusion submodel is established by using Nadaboost extreme learning machine (Nadaboost-ELM) algorithm, and the mutual information method is used to obtain the parameters, strongly correlated with the ROP. Finally, a ROP submodel is established by a neural network with radial basis function optimized by the improved particle swarm optimization (RBFNN-IPSO). This two-level ROP model is applied to a real drilling process and the proposed method shows the best performance in ROP prediction as compared with conventional methods. The proposed ROP model provides the basis for intelligent optimization and control in the complex geological drilling process.     

基于卷积神经网络优化TLD运动手势跟踪算法

针对TLD（Tracking-Learning-Detection）算法在光照变化不均、遮挡严重、跟踪目标模糊等情况下会出现跟踪失败的问题，提出一种基于卷积神经网络优化TLD运动手势跟踪算法。选取手势特征作正样本，其背景作负样本，获取手势HOG特征并投入到卷积神经网络中加以训练，得到手势检测分类器，从而确定目标手势区域，实现手势的自动识别；再利用TLD算法对手势进行跟踪与学习，对正负样本进行估计检测并实时校正，同时运用SURF特征匹配更新跟踪器。实验结果验证，该算法对比TLD经典算法跟踪精度提高了4.24%，增强了运动手势的跟踪效果，相比经典跟踪算法拥有更高鲁棒性。