采用参考激励信号的语义细分法主观声品质评价

语义细分法是声品质以及声感知特征研究中最广泛采用的主观评价方法。但对于一些声品质指标,尤其是新提出的指标或评价者认识和观点不完全一致的指标,由于评价者尺度掌握的困难,采用传统语义细分法评价难以获得准确可靠的评价结果。为此,提出了采用参考激励信号的参考语义细分法评价程序,并研究了这种评价程序的性能表现。分析比较了两种语义细分法在评价者的个体重复性、团组一致性以及与成对比较法和计算结果的相关性。研究结果显示,对传统语义细分法难以获得稳定可靠评价结果的参量,参考语义细分法可以显著改善评价实验性能;对传统语义细分法可以获得稳定可靠评价结果的参量,参考语义细分法可以获得一致的评价结果,且改善了一些方面的性能。研究结果证明了采用参考激励信号的参考语义细分法的优越性。     

基于AHP和生理电的机器人语音交互认知负荷评价

目的 提出一种兼具主观测量和生理数据验证的机器人语音交互认知负荷的评价方案。方法 设计实验使受试者对不同的机器人语音交互系统进行体验，完成相应的任务并接受主观认知负荷测量，同时加以生理电信号测量。主观测量部分利用层次分析法（AHP）对传统的NASA-TLX量表进行改进，使得测量更加客观与细致；并利用生理信号测量的结果验证主观评价的可靠程度与实际意义。结果 得出不同语音交互系统认知负荷的主观评价数据与生理测量数据，两者相互印证，从而得到可靠的认知负荷评价结果，并进一步证明了评价系统本身的有效性。结论 基于AHP的基本原理，改进了NASA-TLX量表，并建立起了一套包含四个准则十四个指标的语音交互认知负荷评价体系，利用心率与皮肤电信号测量进行了辅助验证，提出了一种研究机器人语音交互用户体验的技术手段。     

Examination of effect of information sharing on businesses performance in the supply chain process

Nowadays, supply chain management (SCM) has become one of the focal points of competition. The importance of information sharing in SCM is gradually increasing in terms of improving the business performance. In this study, an attempt to determine the effect of information sharing in the supply chain process (SCP) on cost, financial and business performance, in general, was made. The attempt was made by means of a measuring tool which is based on a theoretical approach. For this purpose, the structural equation model (SEM) was established by taking into account the supply chain structure, SCP, supply chain flexibility, environmental uncertainties and information sharing latent structures in businesses and the cost and financial performance indicators. In this study, differently from most other studies, two performance variables were included, and the model was created by defining these variables, which could be measured with more than one indicator, as latent variables. For this purpose, the data obtained from a questionnaire study performed on large firms within the scope of ISO 1000 were used. An attempt to reveal the factors affecting the cost and financial performance of businesses in SCM was made in the study. As a result of the analyses performed, the proposed SEM model was tested by taking into account various compliance criteria, and the validity and reliability of the model were determined.     

Quality of research: which underlying values?

Traditional bibliometric indicators are considered too limited for some research areas such as humanities and social sciences because they mostly reveal a specific aspect of academic performance (quantity of publications) and tend to ignore a significant part of research production. The frequent misuses (e.g. improper generalizations) of bibliometric measures results in a substantial part of the research community failing to consider the exact nature of bibliometric measures. This study investigates the links between practices for assessing academic performance, bibliometric methods’ use and underlying values of research quality within the scientific community of University of Lausanne, Switzerland. Findings reveal four researcher profiles depending on research orientations and goals, ranging from those using “pure” quantitative tools to those using more subjective and personal techniques. Each profile is characterized according to disciplinary affiliation, tenure, academic function as well as commitment to quality values.     

Multiple-Technique Approach for Improving a Performance Measurement and Management System: Action Research in a Mining Company

Abstract

Many enterprises encounter difficulty in managing strategic goals and performance measures because of a lack of a systemic and objective procedure and method. Action research was conducted through a case study approach at a mining company to investigate this problem regarding performance measurement and management (PMM) and to identify potential solutions for application. This research proposes a multiple-technique approach (including the Delphi method, analytic network process, system dynamics simulation, dashboard visualization, and radio frequency identification tracking techniques) and a creative implementation framework for overcoming the shortcomings within a case company and those in the relevant performance measurement literature. This study demonstrates a step-by-step approach for establishing a PMM system using a real case example. Furthermore, for sustaining the effectiveness and efficiency of the PMM system, key performance indicators (KPIs) were continually monitored against a changing operational environment through design, measurement, analysis, and improvement processes to address problem areas occurring in the production and maintenance departments of a mining company. The benefits of the PMM system in practice are demonstrated by the outcomes of the mining company, with noticeable improvements observed in many KPIs.     

Indicators of ‘innovation as a process’

Innovation as a process is related to the business viewed as a process. A process cannot be captured through the indicators of input/output, which are the most commonly accepted variables. Indicators of technological characteristics also limit the scope of measurement. Moreover, these indicators have often to be constructed upon non-gaussian variables that are not amenable to additive operations. This paper identifies a methodology to identify process innovation variables, some of which are gaussian and some are not. A few simple indicators are then constructed, using additive operations, upon both additive and non-additive variables. The additive variables yield generalisable indicators and the non-additive variables yield self-assessment type indicators. Both types can be used as process performance measurement systems. Examples of the values that these indicators take up, have been shown for nine firms. This vindicates the assumption on the applicability of these indicators.     

Organizational environment and performance of research groups—A typological analysis

In this paper an attempt is made to construct a typology of research units according to a set of organizational features and relate the resulting classification to a set of performance measures. The organizational features include (i) resources and facilities for research; (ii) Communication and transfer of new ideas; (iii) Planning and organization of research; and (iv) Social psychological environment for research. The performance measure include (i) General R&D effectiveness, which essentially connotes the quality dimension of research performance; (ii) Recognition of the work of the research unit by the scientific community; (iii) User-oriented effectiveness; and (iv) Administrative effectiveness (budget and schedule compliance). This study is based on the subset of empirical data on 220 research units collected in India for the third round of the UNESCO International Comparative Study on the Organization and Performance of Research Units (ICSOPRU). Twenty three measures of organizational environment, operationalized by multiple indicators, were chosen as discriminant criteria for the construction of the typology, using a classification computer programme SYSTIT (Systeme' de Typologie Iterative). The relationship between typology groupings and performance measures was analyzed through multiple correspondence analysis. This study brings out that resources and facilities for research are a necessary but not a sufficient condition of performance. The sufficiency condition implies a positive work environment, effective communication within and outside the research group and a conceptually exciting research programme.     

A Method for Identifying Variables for Predicting STEM Enrollment

This research examines demographic, academic, attitudinal, and experiential data from the Cooperative Institutional Research Program (CIRP) for over 12,000 students at two universities to test a methodology for identifying variables showing significant differences between students intending to major in science, technology, engineering, or mathematics (STEM) versus non‐STEM subjects. The methodology utilizes basic statistical techniques to identify significant differences between STEM and non‐STEM students within seven population subgroups based upon school attended, race/ethnicity, and gender. The value of individual variables is assessed by how consistently significant differences are found across the subgroups. The variables found to be most valuable in identifying STEM students reflect both quantitative and qualitative measures. Quantitative measures of academic ability such as SAT mathematics score, high school grade point average, and to a lesser extent SAT verbal score are all indicators. Qualitative measures including self‐ratings of mathematical ability, computer skills, and academic ability are also good indicators.     

Measurement in clinical vs. biological medicine: the Rasch model as a bridge on a widening gap

In the dominant Bio-medical paradigm Medicine is mostly Biology applied to Man. Measurement in Biology stems from physical sciences and has established validity. This is not the case for whole-person variables such as behaviors and psychic conditions (disability, pain, knowledges). The very existence of these variables can only be inferred by observing samples of representative behaviors. The quantity of the inferred variable may only come from subjective and discrete counts (scores) of events (coming in a questionnaire). Contemporary statistics demonstrated that raw scores intrinsically lack fundamental properties for scientific measurement, whatever their algebraic manipulations. This adds to the stigmatization of Clinical Medicine as "soft science", compared to Bio-medicine. In the 1960s Georg Rasch inaugurated a new statistical approach allowing transformation of raw scores into objective linear measures comparable to physical measures. This may help the Bio-medical paradigm to redirect resources from laboratory bench back to bedside.     

Automated diagnostic aids: The effects of aid reliability on users' trust and reliance

We examined the effects that different levels of, and changes in, automation reliability have on users' trust of automated diagnostics aids. Participants were presented with a series of testing trials in which they diagnosed the validity of a system failure using only information provided to them by an automated diagnostic aid. The initial reliability of the aid was either 60, 80 or 100% reliable. However, for participants initially provided with the 60%-reliable aid, the accuracy of the aid increased to 80% half way through testing, whereas for those initially provided the 100%-reliable aid, the aid's reliability was reduced to 80%. Aid accuracy remained at 80% throughout testing for participants in the 80%-reliability group. Both subjective measures (i.e. perceived reliability of the aids and subjective confidence ratings) and objective measures of performance (concurrence with the aid's diagnosis and decision times) were examined. Results indicated that users of automated diagnostic aids were sensitive to different levels of aid reliabilities, as well as to subsequent changes in initial aid reliabilities. However, objective performance measures were related to, but not perfectly calibrated with, subjective measures of confidence and reliability estimates. These findings highlight the need to distinguish between automation trust as a psychological construct that can be assessed only through subjective measures and automation reliance that can only be defined in terms of performance data. A conceptual framework for understanding the relationship between trust and reliance is presented.     

Attention-Aware Network with Latent Semantic Analysis for Clothing Invariant Gait Recognition

Gait recognition is a complicated task due to the existence of co-factors like carrying conditions, clothing, viewpoints, and surfaces which change the appearance of gait more or less. Among those co-factors, clothing analysis is the most challenging one in the area. Conventional methods which are proposed for clothing invariant gait recognition show the body parts and the underlying relationships from them are important for gait recognition. Fortunately, attention mechanism shows dramatic performance for highlighting discriminative regions. Meanwhile, latent semantic analysis is known for the ability of capturing latent semantic variables to represent the underlying attributes and capturing the relationships from the raw input. Thus, we propose a new CNN-based method which leverages advantage of the latent semantic analysis and attention mechanism. Based on discriminative features extracted using attention and the latent semantic analysis module respectively, multi-modal fusion method is proposed to fuse those features for its high fault tolerance in the decision level. Experiments on the most challenging clothing variation dataset: OU-ISIR TEADMILL dataset B show that our method outperforms other state-of-art gait approaches.     

一种新的潜在语义分析语言模型

提出了基于聚类的方法实现词的快速量化表示,并由此导出潜在语义分析语言模型预测置信度,同时运用新提出的几何加权静态插值方式同三元文法模型相结合,构建了一种新的潜在语义分析语言模型,并将其应用于汉语语音识别。实验表明其效率和性能均优于传统基于奇异值分解的潜在语义分析语言模型,相比于三元文法模型,识别错误率相对下降为3．6％～7．1％左右,并为有效量化表示词对进一步提高潜在语义分析语言模型性能提供了新的途径。     

基于主成分层次分析的产品设计语义差分评价研究

目的 以外观设计评价为研究对象,提出一种语义差分评价方法。方法 运用主成分分析法,对初始多维语义进行主成分提取,得出综合语义指标和分值,再通过层次分析法构建综合语义指标的主观评价矩阵,最终得出综合语义分值。结论 针对46款热销女士洗发水瓶的外观设计样本,实现了语义差分评价。运用主成分—层次分析—语义差分评价的方法,实现了近似语义的归类。依据综合语义权值,得出了语义差分分值,并适用于较大样本的外观设计评价。     

Absolute and specific measures of research group excellence

A desirable goal of scientific management is to introduce, if it exists, a simple and reliable way to measure the scientific excellence of publicly funded research institutions and universities to serve as a basis for their ranking and financing. While citation-based indicators and metrics are easily accessible, they are far from being universally accepted as way to automate or inform evaluation processes or to replace evaluations based on peer review. Here we consider absolute measurements of research excellence at an amalgamated, institutional level and specific measures of research excellence as performance per head. Using biology research institutions in the UK as a test case, we examine the correlations between peer review-based and citation-based measures of research excellence on these two scales. We find that citation-based indicators are very highly correlated with peer-evaluated measures of group strength, but are poorly correlated with group quality. Thus, and almost paradoxically, our analysis indicates that citation counts could possibly form a basis for deciding on, how to fund research institutions, but they should not be used as a basis for ranking them in terms of quality.     

Analysis of objective and subjective data using fuzzy coding and multiple correspondence analysis: principle and example in a sitting posture study

Fuzzy coding vs. crisp coding and then local coding vs. global coding is proposed to transform a quantitative scale into a category scale. Such a transformation technique is seen as the most general one to investigate either heterogeneous but quantitative variables or variables with different scale models (both quantitative and qualitative). A major point of fuzzy coding is that space modalities can be built very early in the statistical analysis process and from a discussion between several specialists. The multiple correspondence analysis (MCA) is proposed to investigate a table where the data come from fuzzy coding; the table rows corresponding to the empirical situations and the columns to the space modalities of the respective variables. Two examples are considered. First, a didactic data set is designed in order to compare the principal component analysis, the MCA with crisp coding and the MCA with fuzzy coding. Second, an example about a sitting posture study is considered in order to show the possibility of achieving relationships between objective and subjective data. The empirical situations correspond to adjustment combinations of the seat, the table and the backrest; the variables are posture indicators and subjective assessments. The main result is that the subjective variables have a much more consistent evolution with the adjustments than the objective ones. Consequently, there is a poor connection between these two sets of variables. The backrest is the furniture setting with the highest influence. From the interpretation of the MCA factor planes, it is possible to find the best and the worst adjustment combinations.     

基于数据指标体系的网络消费商业模式创新模型构建研究

目的 对网络消费商业模式可度量评估的创新模型进行构建研究,从而揭示其创新机会。方法 以设计与数据驱动商业模式创新的理念来组织网络消费商业模式的内容要素与创新路径,并以用户为中心创建面向网络消费商业模式内容要素的度量框架,在此基础上探索以绩效度量系统（PMS）为原理的基于数据指标体系的创新模型。结果 设计师可以利用设计思维参与并引导商业模式创新设计,以用户为中心生成有效的商业模式内容要素及相关绩效指标,加强企业绩效的基准管理。结论 以用户为中心,重构网络消费商业模式的5个内容要素与创新路径;以价值驱动因素为基础设计和选择内容要素的度量参考项,从而构建度量框架;绩效度量系统（PMS）包括财务和非财务关键绩效指标（KPI）,可以支持商业模式创新过程;基于关键绩效指标（KPI）与价值驱动因素的强关联性,通过衡量已有15个价值驱动因素（度量参考项）来设计相应的44个关键绩效指标（KPI）,最终生成创新模型。     

Toward establishing a unified metric for performance and learning goal orientations

Findings in the goal orientation literature are convoluted due to sample and scale dependent interpretations and potentially the use of inappropriate measurement models for ordinal data. The purpose of this investigation was to explore the possibility of developing a common metric in order to enhance communication among goal orientation researchers using different scales. A simultaneous calibration of four commonly used goal orientation scales was undertaken to investigate if item responses meet the unidimensionality requirement of Rasch models and hence provided a common metric. Participants were 305 third year psychology students at a large University in France. Results indicated that 30 of 36 learning goal and 28 of 33 performance goals items from the four scales defined unidimensional constructs. Correlations between person measures from the four scales and the simultaneous calibration for both learning goal and performance goals support the interpretation of unidimensional variables. Raw score to interval measure conversion tables provide goal orientation researchers using different scales a common metric for interpretation and statistical analyses. Limitations and extensions of this research are discussed.     

基于声漫步法的森林公园声景喜好度评价研究

为探究森林公园中声景的客观物理量和人主观感受的心理量之间的关系,根据声景生态学和心理物理学的相关理论,通过声漫步法和语义差异法对森林公园中的地球物理声、生物声和人工声进行主观喜好度评价,同时测量客观的物理指标,通过对主客观数据进行拟合建立了森林公园声景喜好度评价模型,并结合三者各自对应的评价模型构建了森林公园声景喜好度评价模型。在森林公园规划中,可应用该模型将森林公园中的声级数据近似模拟为声景感受得分,以仿真来访者的主观感受,为森林公园建设和开发提供参考依据,以期为声景观资源的有效管理提供一定的理论参考。     

基于眼动实验的服装纹样布局方案意象评价模型

目的 针对目前服装纹样布局方案评价中主观性较强、方案评选角度单一、结果可靠性不佳的问题,将客观生理数据测量和主观意象评价相结合,探索用户非主观意识下生理认知数据与心理主观评价间的关系。方法 采用形状文法设计实验样本,建立意象词汇空间,通过问卷调查与眼动实验获取主观意象打分和眼动生理指标数据;数据进行相关性分析,采用单因变量偏最小二乘回归对不同意象词对下主观意象评价值与眼动生理指标之间的相关关系进行拟合,并对拟合后的评价模型进行分析与验证。结果 得出在不同的意象词汇的刺激下,主观评价与眼动生理指标之间存在较高相关性。结论 意象评价模型可以有效准确地反映出用户对服装纹样布局方案的主观评价,为服装纹样布局方案评选提供一种更加客观的评价方式。