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This paper aims to propose a method for summarizing the topics of tweets using the Wikipedia category structure as common knowledge for supplementing the understanding of the Twitter user’s interests. There are many topics in the tweets, and the topics can be treated as a tree structure. However, when the topic hierarchy is constructed using existing hierarchal clustering approach, the granularity of tweet groups differs for each user. For summarizing the topics, identification of the topics which are heterogeneous and which are not is necessary because it is easy to understand if several groups are categorized into parent groups. However, if the group units are different for each user, a number of users’ interests cannot be summarized. If some tweets are grouped into the presidential election, and the others are into Donald Trump, there cannot be a count of how many users are interested in Donald Trump.

One solution of this issue is to construct topic structures by mapping one common tree structure. In this paper, a method is proposed for constructing the topic structure using the Wikipedia category tree similar to a common tree structure. The tweets are categorized, mapped to titles of articles in the Wikipedia category tree and then visualized as the hierarchal structure to the users.

The effectiveness of the proposed hierarchal topic structure is confirmed. In theme “politics”, the proposed method works well. The main reason is that there are many technical terms about politics in the Wikipedia categories and articles. It was found that a number of the terms of politics do not have multiple meanings, multiple semantics. However, in theme “sports”, the proposed method does not perform well. The main reason for this case is that there are a number of names of people present as topic names.

One important feature of the proposed method is that it is easy to grasp not only about the topics which are heterogeneous or homogeneous with each other but also consider the missing time when extracting topics. Another feature is that the topic structures for multiple users are easy to compare with each other.

The purpose of this paper is to ensure power efficiency in wireless sensor networks (WSNs) through a new framework-oriented middleware, based on a biologically inspired mechanism that uses an evolutionary multi-objective optimization algorithm. The authors call this middleware framework multi-objective optimization for wireless sensor networks (MONet).

In MONet, the middleware level of each network node autonomously adjusts its routing parameters according to dynamic network conditions and seeks optimal trade-offs among performance objectives for a balance of its global performance. MONet controls the cooperation between agents (network nodes) while varying transmission paths to reduce and distribute power consumption equitably on all the sensor nodes of network. MONet-runtime uses a modified TinyDDS middleware platform.

Simulation results confirm that MONet allows power efficiency to WSN nodes while adapting their sleep periods and self-heal false-positive sensor data.

The framework implementation is lightweight and efficient enough to run on resource-limited nodes such as sensor nodes.

This chapter explores what video games can teach us in light of the ongoing sixth mass extinction in the history of our planet, allegedly caused by global warming and the over-consumption of vital resources. Games made and played by nonhuman actors can shed light on the situatedness and partiality of our knowledge regarding the boundaries that separate and differentiate human and nonhuman, interactivity and passivity, entertainment and boredom, and life and death. Nonhuman games help us to articulate the space and time in-between these dualisms and have the potential to re-route gaming (and game studies) from false myths of agency, interactivity, and instrumentalism, and the masculinism inherent in these notions. Nonhuman games are companions for earthly survival, and as such they can be taken as useful references when considering a more ethical approach to the ecological crisis of the Anthropocene. The chapter investigates notions of posthumanism, interpassivity, and contemporary critiques of the early assumptions of game studies on the agency of human players. It looks at video games that play by themselves, idle and incremental games, and the emergence of nonplaying characters in ludic and open-world simulations. It explores forms of automatic play and the use of bots and Artificial Intelligence (AI) in online role-playing games, procedurally generated virtual environments, and games that far exceed the lifespan of their players.

To provide a brief survey of the literature directed towards the analysis of warranty claim data.

For convenience, this survey of the analysis of warranty claims data is somewhat arbitrarily be classified by topics as follows: age‐based claims analysis, aggregated warranty claims analysis, marginal counts of claims analysis, warranty claims analysis by using covariates, estimation of lifetime distribution using supplementary data, two‐dimensional warranty, warranty costs analysis, sales lag and reporting lag analysis, and forecasts of warranty claims.

Emphasis is placed on a discussion of different kinds of warranty claims data selected from reviews and on a comparison of the statistical models and methods used to analyze such data.

Since the literature on product warranty data is vast, more work on this problem is needed.

This review points out why warranty claims data is important and gives a survey of the literature pertaining to the analysis of such data. The emphasis is on the analysis of minimal databases of real warranty data, constructed by combining information from different sources, which can be collected economically and efficiently through service networks. The research is applicable for those responsible for product reliability, product design decisions and warranty management in manufacturing industries.

The paper reviews different statistical models and methods used to analyze warranty claims data. The statistical models and methods presented are be valuable and meaningful tools for product reliability and warranty management and analysis.

This chapter aims at providing an understanding of the research and devlopment (R&D) process in the pharmaceutical industry, by exploring the methodological challenges and approaches in the assessment of the determinants of innovation in the pharmaceutical industry. It (i) discusses possible methodological approaches to model occurrence of events; (ii) describes in detail competing risks duration models as the best methodological option in light of the nature of pharmaceutical R&D processes and data; (iii) concludes with an estimation strategy and overview of potential covariates that have been found to correlate with the likelihood of failure of R&D pharmaceutical projects.

Investigating the influence of intensive distribution and sales promotion towards customer-based brand equity, repurchase intention and word-of-mouth (WOM) (study on Suzuki car owners in PT Surya Batara Mahkota Wilayah Nusa Tenggara Timur).

The research was conducted in East Nusa Tenggara (NTT) and the analysis unit was customers of PT. Surya Batara Mahkota NTT (PT SBM NTT) as the owner of the Suzuki car. The population is 1,782 Suzuki car owners who bought their cars from PT SBM NTT, based on data from 2015. The sampling technique is the multi-stage area sampling.

Incentives distribution had significant and positive influence towards brand equity and repurchase intention. Sales promotion had significant and positive influence towards word-of-mouth (WOM), but it did not have influence towards brand equity. Brand equity had significant influence towards repurchase intention and WOM. On the other hand, repurchase intention did not have influence towards WOM.

The originality of this study was that the researchers did not find a previous study that discussed the relationship between intensive distribution and repurchase intention, between sales promotion and WOM and between customer-based brand equity and WOM. Previous studies used different variables as determinants of positive WOM.

The main purpose of this study was to propose theoretical calculation models to evaluate the theoretical bending strengths of welded wide-flange section steel beams with local buckling at elevated temperatures.

Steady-state tests using various test parameters, including width-thickness ratios (Class 2–4) and specimen temperatures (ambient temperature, 400, 500, 600, 700, and 800°C), were performed on 18 steel beam specimens using roller supports to examine the maximum bending moment and bending strength after local buckling. A detailed calculation model (DCM) based on the equilibrium of the axial force in the cross-section and a simple calculation model (SCM) for a practical fire-resistant design were proposed. The validity of the calculation models was verified using the bending test results.

The strain concentration at the local buckling cross-section was mitigated in the elevated-temperature region, resulting in a small bending moment degradation after local buckling. The theoretical bending strengths after local buckling, evaluated from the calculation models, were in good agreement with the test results at elevated temperatures.

The effect of local buckling on the bending behaviour after the maximum bending strength in high-temperature regions was quantified. Two types of calculation models were proposed to evaluate the theoretical bending strength after local buckling.

Purpose: The research investigates the presence of technology ideologies in consumer discourse on tourism and hospitality robots.

Design/methodology/approach: Using a netnographic approach, the research involved immersion in online discourses and collection of consumer posts from a variety of social media platforms. Data was subjected to a thematic analysis informed by the technology ideology framework described in the literature review.

Findings: Online consumer narratives about tourism and hospitality robots are dynamic and varied and reveal a multitude of technology ideology-related positions. The research confirms the applicability of the technology ideology framework to online discourses on service robots and finds that anthropomorphism triggers additional concerns.

Research implications: The findings suggest that future research on the acceptance and use of service robots should go beyond psychological concepts.

Practical implications: Without uncovering and understanding technology sensemaking processes with respect to service robots, the introduction of service robots in hospitality and tourism might trigger consumer resistance or lead to inferior service experiences.

Social implications: The research suggests that sensemaking of technology, specifically service robots, is complex and colored by pertinent ideologies. Policies and regulations regarding service robot adoption and implementation should consider these various positions.

Originality/value: The paper introduces technology sensemaking and technology ideology as important theoretical frameworks to understand consumer perceptions, attitudes, uses and relationships in regard to service robots in hospitality and tourism contexts.

This chapter measures financial integration in 10 industries over 4 different periods. We use two robust measures of integration: (i) the Pukthuanthong and Roll (2009)’s multi-factor R-square and (ii) the Volosovych (2011)’s integration index. Both measures, based on PCA, indicate that the difference between the level of integration over the period 2009–2012 (“Post-Lehman” era) and the level of integration over the period 1994–1998 (“Post-Liberalizations” era) is relatively high. In addition, the level of financial integration across international equity markets decreased during the late 1990s. This suggests that de jure integration does not necessarily improve de facto integration. Overall, our findings give rise to a “diversification benefits-insurance benefits trade-off.”