广义空间调制系统的正则化OMP检测算法

在广义空间调制（GSM）系统中,最大似然（ML）检测可以取得最优的检测性能,然而其计算复杂度随激活天线数的增加急剧增长。针对这一问题,提出了一种基于稀疏重构理论的低复杂度检测算法——正则化正交匹配追踪（ROMP）算法。该算法首先根据信道矩阵和当前残差的内积选取多个候选激活天线索引,接着对候选天线索引按正则化标准进行可靠性验证,剔除错误索引,缩小信号的搜索空间,最后通过求解最小二乘问题估计信号。仿真结果表明,与经典的正交匹配追踪（OMP）算法相比,所提算法以少许复杂度的增加为代价极大提升了检测性能,能够在检测性能与复杂度之间取得更好的折中。     

海南城乡居民消费水平差异性分析和预测

从1985-2018年海南城乡居民收入、消费数据出发,分别建立消费关于收入、消费差距关于收入差距的自回归模型,结果表明农村居民当期消费更易受近期收入和消费水平的影响,具有不稳定性。再利用GM(1,1)模型预测城乡居民收入差距,结合自回归模型,完成未来10年海南城乡消费差距的预测：收入差距和消费差距将呈直线递增趋势,收入差距的增幅高于消费差距增幅。缩小海南城乡居民消费差距的根本途径在于缩小收入差距,应因地制宜,切实提高农民收入水平。     

基于PCA/FCM的企业信用评价研究

针对我国企业信用评价问题的特点,文章分析了企业信用评价基本原则和主要影响因素,建立了企业信用评价指标体系。企业信用评价是一类包括一系列独立变量的分类问题,将主成分分析与模糊理论引入信用评价中,构建基于PCA/FCM的企业信用评价模型,这使得模型更接近人们的思维方式、指标赋权更为客观。应用该模型及SPSS11.0、MATLAB7.0对所选企业研究显示:该模型非常有效和实用。     

基于组合模型下的河南省粮食生产相关投入分析及产量趋势预测

以河南省粮食总产量存在的波动性入手,应用主成分分析法对粮食生产相关投入进行组合提取分析,并对未来5年河南省粮食总产量进行建模预测。通过主成分分析显示,一是提取了农业基础资源投入与农业现代化水平因子及农业政策因子,贡献率分别为72.668%和15.429%;二是乡村从业人员与粮食产量趋势呈负相关,是由于随着农业生产多方面的投入增多,从中减少了一部分劳动力。运用所建立的GM(1,1)模型预测,未来5年,河南省粮食总产量仍将保持平缓增长的发展趋势,到2022年将达到7389.58万吨。该研究结果可作为相关部门制定粮食发展规划和政策措施的重要参考。     

Calendar Effects on the Amsterdam Stock Exchange

For daily data on a value-weighted index of all shares in the Netherlands (1981-1998), we find abnormally high returns in the pre-Christmas period of the second half of December and around the turn of the month, whereas returns are negative and volatility is relatively high on the Mondays where the previous week's return is below zero. Furthermore, our evidence indicates the presence of an ARCH(1) effect. Our intraday results based on an equal-weighted index of the leading shares in the Netherlands (1986-1993) reveal a U-shaped return pattern over each trading day, Monday morning excluded. Moreover, our tests reveal repeated price adjustments mostly in the same direction around and over non-trading periods. We argue that the arrival of private information is affected by strategic and behavioral factors incompatible with the risk-return paradigm.     

Job analysis: a strategic human resource management practice

This study examined the impact of job analysis on organizational performance among 148 companies based in the United Arab Emirates (UAE), a Gulf-region country. Survey results indicated that a practice of proactive job analysis was strongly related to organizational performance. This relationship was strongest to the extent that companies maintained HR information systems, accorded HR greater involvement in strategic planning and emphasized competency-based characteristics of employees in the job analysis approaches they used. The findings suggest that a company-wide policy of job analysis is an important source of competitive advantage in its own right, and merits due attention of HR professionals, line managers and top management. The study extends the findings of the HR–performance research pursued in Western countries to a non-Western context.     

Measuring Corporate Environmental Performance: A Methodology for Sustainable Development

Assessing corporate environmental performance (CEP) that is both comprehensive and consistent with sustainable development both for society and companies, while at the same time taking heed of the facts and interests of each stakeholder, is not a simple feat. Due to the multidimensional character of the sustainability concept, several questions must be considered in the evaluation process: (i) the qualitative nature of indicators and the complexity of developing a synthetic index; (ii) the difficulty of choosing properly statistical techniques for aggregation and (iii) the difficulty of introducing stakeholders’ preferences in the assessment models. This paper is an attempt to address this challenge by developing a framework for the assessment of CEP, based on the application of a fuzzy multi‐criterion decision‐making (MCDM) method. To achieve positive scores in a CEP assessment, an organization should be strategically committed and engage in environmental management and governance structures that are translated into good results in terms of both engagement and operational performance. Unless such premises are explicitly incorporated into the assessment criteria, the results would reveal that the CEP measurement could not be brought into a line with an earnest ambition of achieving true sustainable development. Copyright © 2015 John Wiley & Sons, Ltd and ERP Environment     

Identifying R&D partners through Subject-Action-Object semantic analysis in a problem & solution pattern

Today’s companies still rely heavily on expert knowledge rather than quantitative data with a systematic approach to effectively identify and choose Research and Development (R&D) partners. It is advantageous to identify and select potential R&D partners using a Problem & Solution (P&S) pattern. This paper presents a novel process for identifying R&D partners on the basis of solution similarities that assist technology managers in understanding the relationships between research targets. First, we choose a thematic dataset that contains problems and quantitative data with relative topic terms. Then, we extract Subject-Action-Object semantic structures in a P&S pattern from the dataset, and identify various solutions to a technical problem, with each as a subject. In addition, we provide correlation mapping to visualise the text characters and identify R&D partners. Finally, we validate the proposed method through a case study of the dye-sensitized solar cells sector.     

Drivers and barriers to the adoption and diffusion of Sustainable Jet Fuel (SJF) in the U.S. Pacific Northwest

Sustainable Jet Fuel (SJF) represents an important component of the airline industry's strategy to simultaneously reduce GHG emissions while meeting a growing demand for international air travel. SJFs also have the potential to provide fuel supply diversification and security, enhance fuel price stability and provide regional/rural economic development benefits. This paper measures and ranks perceived drivers and barriers to an economically viable SJF industry in a unique U.S. region, the U.S. Pacific Northwest (PNW), through personal interviews with key aviation fuel supply chain stakeholders conducted from June to September 2015. In addition to providing a fertile arena for this first effort to systematically assess these drivers and barriers, the U.S. PNW is unique due to the region's long strategic focus on aviation innovation and its importance to the regional economy, the seminal efforts in the region to outline a path forward on SJF beginning in 2010, and the relatively small population spread over a large geographic area with a limited number of “hub” airport nodes which geographically concentrates aviation fuel demand and distribution. Nineteen stakeholder interviewees acknowledge that, in order for regional SJF adoption-diffusion to occur, airline jet fuel buyers must drive the process, particularly as they deal with greenhouse gas (GHG) emission issues and related policy considerations. Important perceived barriers to SJF industry scale-up in the U.S. PNW include the high production costs of SJF and related issues, such as fuel logistics and quality control in the transport, storage, and blending of SJFs. Perceptions around chain-of-custody issues, such as blending, tracking, and crediting of SJFs and future SJF market share projections for the year 2030 were also examined. Incorporating stakeholder input into discussions about adding blended SJF into the U.S. aviation fuel supply provides needed insight for the biofuels industry, policymakers, and researchers.     

Frontline employees׳ attitudes towards self-service technologies: Threats or opportunity for job performance?

Increasing diffusion of self-service technologies (SSTs) on the points of sale impacts on traditional retailing from several perspectives. For instance, SSTs have direct effect on front-line employees. Indeed, they may cause a potential reduction in personal contacts with clients, reduction of workers, modifying the job conditions and so on. To date, the effect of SSTs on the points of sale has been mainly investigated from a consumers׳ perspective, by mainly focusing on consumers׳ acceptance and usage of these systems. The aim of this paper is to make employees׳ point of view clearly emerge, through a qualitative approach focusing on the investigation of employees׳ perception of the consequences of these technologies on job performance. The content analysis based on exploratory in-depth interviews involves 250 frontline employees. Authors examine the success of technology from employee׳s standpoint by evaluating their attitude and considering the impact on their job performance perception. In this way, the analysis allows defining new variables which are not previously investigated, such as the perception of speed for task completion, which emerged as the most important factor for employees׳ self-evaluation. Hence, this study offers support for evaluating job performance considering the specific case of SSTs in the frontline employees as initial insights rather than definitive understandings.