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Within smart homes, ambient sensors are used to monitor interactions between users and the home environment. The data produced from the sensors are used as the basis for the inference of the users' behaviour information. Partitioning sensor data in response to individual instances of activity is critical for a smart home to be fully functional and to fulfil its roles, such as correctly measuring health status and detecting emergency situations. The purpose of this study is to propose a similarity‐based segmentation approach applied on time series sensor data in an effort to detect and recognise activities within a smart home.

The paper explores methods for analysing time‐related sensor activation events in an effort to undercover hidden activity events through the use of generic sensor modelling of activity based upon the general knowledge of the activities. Two similarity measures are proposed to compare a time series based sensor sequence and a generic sensor model of an activity. In addition, a framework is developed for automatically analysing sensor streams.

The results from evaluation of the proposed methodology on a publicly accessible reference dataset show that the proposed methods can detect and recognise multi‐category activities with satisfying accuracy, in addition to the capability of detecting interleaved activities.

The concepts introduced in this paper will improve automatic detection and recognition of daily living activities from timely ordered sensor events based on domain knowledge of the activities.

This chapter describes the redevelopment of the Open Language Chief Executive Personality Tool (OLCPT), a language-based machine learning (ML) tool for assessing executives' traits along the five factor model (FFM) of personality (openness to experience, conscientiousness, extraversion, agreeableness, and neuroticism). Whereas the initial release of the OLCPT demonstrated the viability of using supervised machine learning to unobtrusively assess executives' personality traits, recent advances in artificial intelligence (AI) related to large language models (LLMs) warranted revisiting its development. After applying LLM embeddings and performing other updates, including expanding the training sample, the redeveloped tool (available at https://zenodo.org/records/10800801) achieved substantially higher convergent validity than the initial release. The updated tool also demonstrates strong discriminant validity and reliability, and it can measure traits not included in the initial version (narcissism and humility). These improvements demonstrate the potential value of continuously updating existing, computer-aided measures in strategy and management research. Yet, such efforts may not always be feasible or even necessary. Thus, we also use this chapter to offer guidelines for determining when updating similar measures is worthwhile, urging scholars to carefully consider how existing tools perform and the relevance of advancements to the technologies underlying them. We conclude with additional suggestions for advancing measurement in our field, including keeping up with emerging technologies, encouraging complementary approaches to enable triangulation, avoiding the use of advanced techniques without carefully considering their applicability in a given context, and being realistic about what we ask for during the review process and what we consider a meaningful contribution in our field.

Research suggests that student drug use is substantially higher than that of the general population and while the UK Government’s current Drug Strategy emphasises the importance of PSHE in preventing young people from becoming drug users, there is a lack of research investigating the longer-term effectiveness of drug prevention education, and students’ views using qualitative methods. The purpose of this paper is to gain a holistic understanding into university students’ lived experiences of recreational class A drug taking and the drug education taught in English secondary schools.

Five interviews with university students were undertaken and thematically analysed using an ideographic case study approach alongside a qualitative content analysis of publicly available drug education resources and policy documents.

The normalisation of drug taking at university and social micro-pressures to assimilate group norms were key contributing factors to participants’ drug use. While the content of drug education in PSHE is grounded in theory, its implementation is not.

This study extends upon existing theories of normalisation of drug use at university through the concept of micro-pressures to offer an explanation of the process by which students assimilate group norms through the implicit threat of not fitting in.

The present paper is a phenomenological study of capital inflow, economic growth and financial crisis in the Southeast Asian countries in general and Malaysia in particular. The paper seeks to explain how unregulated capital inflow in an open economy leads to unsustainable growth It comes to the broad conclusion that although capital inflow is conducive to economic growth, it may also generate the problem of macroeconomic vulnerability and unsustainability, and in such a situation, the occurrence of financial crisis may not be an uncommon possibility.

This chapter critically engages with ways that teaching excellence has been operationalised in practice. Specific focus is on developing individual teaching excellence, rewarding of success and recognition of teaching excellence and the building of evidence around what works in teaching for the benefits of students. We consider the daily interactions with students that form the basis of frameworks of teaching excellence before arguing that operationalisations of teaching excellence are highly context specific and operate at the level of institutions and the whole higher education sector. We discuss the criteria that underpin teaching excellence awards. This includes governance as well as development frameworks. After considering the complex links between research and teaching and the importance of the disciplinary dimension of teaching excellence, the chapter finally looks at the skills and attributes commonly associated with individual teacher excellence and argues that these are exceptionally difficult to pin down let alone measure. It concludes with some reflections on some of the challenges faced by institutions as they seek to develop the quality of teaching whilst meeting the requirements of the TEF.

To determine the most popular entries on library ready reference web sites and the role of visibility in the selection of resources.

Ready reference web sites of 100 American libraries were examined, for a census of the most frequently selected online resources. The dates of news, library and online media coverage were considered for specific tools, to explain their prominence.

Early publicity for web tools was found to be an important element in their relative popularity as choices for library web sites.

The date on which a given web resource became well known among librarians can only be estimated from media reports, not proved. Additional study could establish the frequency with which libraries modify their ready reference web sites and investigate why other resources of comparable quality have not become as popular.

The paper shows that early visibility plays a role in librarians' selection of web resources that is rarely mentioned in discussions of selection criteria.

The purpose of this paper is to address the issue of failing to psychometrically test questionnaire instruments when measuring university students’ attitudes towards plagiarism. These issues are highlighted by a psychometric evaluation of a commonly used (but previously untested) plagiarism attitudinal scale.

The importance of psychometric testing is shown through an analysis of a commonly used scale using modern techniques (e.g. Rasch analysis) on 131 undergraduate education students at an Australian university.

Psychometric analysis revealed the scale to be unreliable in its present form. However, when reduced to an eight-item subscale it became marginally reliable.

The main implication of this paper is that questionnaire instruments cannot be assumed to function as they are intended without thorough psychometric testing.

The paper offers valuable insight into the psychometric properties of a previously untested but commonly used plagiarism attitudinal scale.

The paper offers a straightforward and easy to understand introduction to researchers in higher education who use questionnaires/surveys in their research but lack an understanding of why psychometric testing is so critical. While similar papers have been written in other fields which advocate psychometric approaches, such as Rasch analysis, this has not been the case in higher educational research (or mainstream educational research for that matter).

This study examines the effects of market orientation on the performance of retail outlets in Zimbabwe, a low-income country (LIC). LIC retailers operate at the nexus of subsistence marketplaces and the market economy. Socioeconomic, cultural and regulative institutions are more dynamic and differ substantially from the industrialized West. This provides an interesting context in which to test the generalizability of market orientation theory. A covariance structure model of the hypothesized relations indicates that market orientation improves performance. Reward systems have a positive effect on market orientation and a positive indirect effect on performance through market orientation. However, consistent with the characteristics of Zimbabwe, which are not unexpected in the LIC institutional context, interdepartmental conflict, centralization, and formalization do not have significant effects on market orientation. The results suggest that the market orientation–performance link generalizes but that some antecedents of market orientation identified in previous research may not apply in LICs.