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This paper aims to propose a biologically inspired processing architecture to recognize and classify fabrics with respect to the weave pattern (fabric texture) and yarn color (fabric color).

By using the fabric weave patterns image identification system, this study analyzed the fabric image based on the Hierarchical-MAX (HMAX) model of computer vision, to extract feature values related to texture of fabric. Red Green Blue (RGB) color descriptor based on opponent color channels simulating the single opponent and double opponent neuronal function of the brain is incorporated in to the texture descriptor to extract yarn color feature values. Finally, support vector machine classifier is used to train and test the algorithm.

This two-stage processing architecture can be used to construct a system based on computer vision to recognize fabric texture and to increase the system reliability and accuracy. Using this method, the stability and fault tolerance (invariance) was improved.

Traditionally, fabric texture recognition is performed manually by visual inspection. Recent studies have proposed automatic fabric texture identification based on computer vision. In the identification process, the fabric weave patterns are recognized by the warp and weft floats. However, due to the optical environments and the appearance differences of fabric and yarn, the stability and fault tolerance (invariance) of the computer vision method are yet to be improved. By using our method, the stability and fault tolerance (invariance) was improved.

The purpose of this paper is to propose a novel collaborative trend prediction method to estimate the status of trending topics by crowdsourcing the wisdom in web search engines. Government officials and decision makers can take advantage of the proposed method to effectively analyze various trending topics and make appropriate decisions in response to fast-changing national and international situations or popular opinions.

In this study, a crowdsourced-wisdom-based feature selection method was designed to select representative indicators showing trending topics and concerns of the general public. The authors also designed a novel prediction method to estimate the trending topic statuses by crowdsourcing public opinion in web search engines.

The authors’ proposed method achieved better results than traditional trend prediction methods and successfully predict trending topic statuses by using the crowdsourced wisdom of web search engines.

This paper proposes a novel collaborative trend prediction method and applied it to various trending topics. The experimental results show that the authors’ method can successfully estimate the trending topic statuses and outperform other baseline methods. To the best of the authors’ knowledge, this is the first such attempt to predict trending topic statuses by using the crowdsourced wisdom of web search engines.

In this chapter we develop a monthly output index of the U.S. transportation sector covering air, rail, water, truck, transit, and pipeline activities. We call it the transportation services index (TSI). Separate indexes for freight and passenger are also constructed. Before the development of TSI, there was no comprehensive monthly measure of the economic activity by all modes of transportation. Since policymakers are increasingly concerned about the critical role transportation plays in enabling economic growth, monitoring of TSI can provide them with insights about the current and future state of the economy. Fortunately we find that our monthly transportation services output index (TSI), which is based on a new measurement approach, matches very well with the annual transportation output figures produced by the Bureau of Labor Statistics (BLS) and the Bureau of Economic Analysis (BEA). Some analysis reported in this chapter indicate that the cyclical movements in the transportation output appear to be more synchronized with the growth slowdowns rather than full-fledged recessions of the U.S. economy. The index has led the turning points of the 6 National Bureau of Economic Research (NBER)-defined growth cycles over the period with an average lead-time of 6 months at peaks and 5 months at troughs.

Tourism and natural hazards share a long pathway, owing to the fragile existential status of certain tourist destinations and voluntary and involuntary intervention of mankind in the business of natural environment. Over a course of history, numberless natural hazards prevailed and left behind some of the colossal and collateral damage on the physicality and virtuality of destinations. Volume of studies contended this direct and inverse association. Resultantly, impact measurement, ongoing imagery issues and future forecasting have been made to ease out the tourist destination from the consequences of natural hazards. Moreover, considering the inner fabric of tourism system (demand and supply side), natural hazards have been foreseen as unwanted yet necessary event to be emphasized and taken care of. Predominantly, in the existing global milieu of maximum human intervention in the climatic cycle and its outcomes in the form of global warming, climate concerns, natural hazards have been considered as inevitable and destined. Hence, it needs a comprehensive literature-based study to assess the risk factor of natural hazards on the tourist destinations. This study, in acquiescence to address this grey section, intends to explore the existing studies (drafted on the risks impacts of natural hazards on demand, supply and ancillary segments of tourism) and structure the findings thematically and orchestrate these findings in the existing body of literature. Implications from the findings have been presented.

The purpose of this paper is to examine the relationships among three dimensions of service quality that influence overall internet banking service quality and its subsequent effect on customer satisfaction in a New Zealand banking context.

Internet banking service customers of a national bank in New Zealand completed a self‐administered questionnaire. Data obtained from the customers were analysed using the SEM‐based partial least squares (PLS) methodology.

The results show significant relationships among online customer service quality, online information system quality, banking service product quality, overall internet banking service quality and customer satisfaction.

Little attention has been given in the literature to understanding the service quality dimensions that influence overall internet banking service quality and the specific outcome of customer satisfaction. By expanding previous research in internet banking service quality, this paper empirically examines the relationships between three service quality dimensions, overall internet banking service quality and customer satisfaction.

The purpose of this paper is to discuss the Schur D‐stability and the vertex stability of interval matrices (including point matrix obviously). Some new sufficient conditions (criteria) are proposed which guarantee the interval matrix is Schur D‐stable. This results are shown to be less conservative than those in recent literatures. In addition, two equivalence relations between the Schur D‐stability and the vertex stability of interval matrices will be proposed and a new Schur D‐stability range of an interval matrix presented.

Matrix eigenvalues theory and matrix measure approach.

Several simple sufficient conditions (criteria) for guaranteeing the Schur D‐stability of interval matrices are derived, two equivalence relations between the Schur D‐stability and the vertex stability of interval matrices are proposed, and a new Schur D‐stability range of an interval matrix is presented.

Control theory or stability theory. These stability criterion possess simple forms and provide useful tools to check Schur D‐stability of interval matrices (including point matrix) at first stage.

The paper provides useful tools to check Schur D‐stability of interval matrices (including point matrix) at first stage.

Two equivalence relations between the Schur D‐stability and the vertex stability for general interval matrices (including point matrix) are proposed, such that the conditional limitations for tridiagonal matrix in recent papers are broken. A new Schur D‐stability range of an interval matrix is presented, and several simple sufficient conditions are obtained which guarantee the Schur D‐stability of interval matrices (including point matrix).

This study adopts a narrative approach to understanding women’s life experiences from a feminist perspective. How Taiwanese women of different generations have lived their lives and what has and has not changed was investigated through a gender lens. The narrators include the author and her grandmother, born in 1975 and 1927, respectively. They each re-experience and reconfirm the markings of their pasts, psychological conditions, and bodies through deep dialogue. The two stories span approximately 50 years and manifest the patriarchal culture in Taiwanese society at different times.

This study finds that although the stories of these two women from different generations appear distinct in their own way, similar ‘dilemmas’ can be observed in their gender experiences: for example, women get married to men’s family; the value system of lineage and succession creates a tendency to expect to have boys; women need to get married to get their status recognition; and through home, women learn gender roles and gender norms.

However, the study shows progress: women’s education brings economic independence and yields a sense of accomplishment from work or school; women of different generations have different perceptions during the awakening of gender consciousness. The current findings contribute to understanding the working principles of gender relations, which reinforce the patriarchal system despite its appearance changing over time.

The purpose of this paper is to review and critique the literature dealing with the relationship between intellectual capital (IC) and innovation, and to outline the future of this research field.

Structured literature review (SLR).

The relationship between IC and innovation has been examined in great detail; however, much remains to be understood regarding the way of approaching and conceptualising both IC and innovation according to the current business environment. Moreover, academic literature on the IC-innovation relationship shows a disconnection between academia, and both business practice and policy-making, in this research domain.

Since the study was developed by one person, the results could be influenced by her subjective interpretation. In addition, only journal articles published between 2006 and 2015 have been examined.

This paper contributes to IC literature by providing a unique SLR of the IC-innovation field of research. The paper points to pathways for future research in the IC-innovation domain.

This study examines how intellectual capital (IC) drives firm performance via the lens of dynamic capabilities (DCs). Drawing on resource-based view (RBV) and dynamic capability view (DCV), the authors elaborate the mediating role of learning, integration and reconfiguration DC in the Indian banking context.

A sample of 358 top- and middle-level managers from the Indian banking sector was administered with structured questionnaires for data collection. Structural equation modeling (SEM) and Sobel test were used to analyze the data and test the hypothesized mediating effect.

The findings reveal that learning and integration DCs are key mediators in IC and banks' performance relationships in an emerging economy context. In contrast, the analysis revealed partial mediating role of reconfiguration DC. Furthermore, the learning DC has been identified as the primary mediating mechanism for transforming bank's IC into performance benefits.

This study provides an important implication for the IC and DC link by empirically developing and validating a model in the Indian banking sector and making a several contributions to the related literature. This sector needs to incorporate and strengthen their IC and DCs to attain enhanced performance in today's dynamic environment. Bank managers can use these findings to bring their knowledge-related activities to channelize specific DCs to transform banks' IC when seeking to improve overall performance. Theoretically, this study extends previous research by outlining a set of organizational elements that tend to influence firm performances with the help of IC, learning, integration and reconfigurations DCs.

Although several studies have investigated the links between IC, DC and firm performance, studies on emerging economies are scarce. This study is one of the most in-depth investigations of the relationship between IC, learning, integration and reconfiguration DCs and firm performance in an integrated framework, with a particular focus on the banking sector of an emerging economy.