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Within the existing health care system, a significant percentage of Americans over the age of 65 will have need of extended health care. Yet the extended care industry has little information as to how consumers will make a choice among placement options. The results of this study describe both the need recognition and pre‐selection search stages of the decision process and the impact of need recognition on subsequent search activity. The information obtained from an influential person as the problem is being defined appears to have a complex relationship with pre‐selection search, with initial information leading to less search but additional information increasing search activity. Contrary to previous studies, pre‐selection search was found to be fairly extensive, increasing with time availability.

In spite of the emphasis on needs by marketing scholars almost no research efforts directed towards this topic have been reported in the organisational buying behaviour literature. The nature of organisational buying needs is explored, and how various organisational and environmental factors influence and direct recognition of such needs. A model of organisational need recognition is developed, and based on relevant research a set of inter‐related propositions of how various organisational and environmental factors influence organisational need recognition is proposed. Managerial implications are highlighted.

Human assembly process recognition in human–robot collaboration (HRC) has been studied recently. However, most research works do not cover high-precision and long-timespan sub-assembly recognition. Hence this paper aims to deal with this problem.

To deal with the above-mentioned problem, the authors propose a 3D long-term recurrent convolutional networks (LRCN) by combining 3D convolutional neural networks (CNN) with long short-term memory (LSTM). 3D CNN behaves well in human action recognition. But when it comes to human sub-assembly recognition, the accuracy of 3D CNN is very low and the number of model parameters is huge, which limits its application in human sub-assembly recognition. Meanwhile, LSTM has the incomparable superiority of long-time memory and time dimensionality compression ability. Hence, by combining 3D CNN with LSTM, the new approach can greatly improve the recognition accuracy and reduce the number of model parameters.

Experiments were performed to validate the proposed method and preferable results have been obtained, where the recognition accuracy increases from 82% to 99%, recall ratio increases from 95% to 100% and the number of model parameters is reduced more than 8 times.

The authors focus on a new problem of high-precision and long-timespan sub-assembly recognition in the area of human assembly process recognition. Then, the 3D LRCN method is a new method with high-precision and long-timespan recognition ability for human sub-assembly recognition compared to 3D CNN method. It is extraordinarily valuable for the robot in HRC. It can help the robot understand what the sub-assembly human cooperator has done in HRC.

The purpose of this paper is to explore the needs of men experiencing domestic abuse from the perspective of the professionals supporting them.

An all Wales qualitative study, 20 semi-structured interviews were completed with managers and practitioners of domestic abuse services supporting men. Interviews were analysed using thematic analysis.

Analysis identified six themes: against the tide of recognition, a need to recognise and accept domestic abuse, knowledge of provision, low numbers of men, resources (time and funding) and rebuilding. However, against the tide of recognition was central. Domestic abuse is understood as a heteronormative and gendered experience; abused men defy these notions.

Findings cannot be generalised across the UK. This study offers a valuable base on which to build future knowledge. Future research might consider recruiting larger samples or follow up qualitative findings with a larger quantitative survey.

This paper presents the manager and practitioner views of the service needs and solutions for men. They perceive that abused men need to recognise and accept victimisation, have knowledge of provision and know it is acceptable to seek help and receive practical support.

Increasing recognition cannot be achieved in isolation. A shared commitment is required from policy, practice and research to raise the agenda for abused men.

This is an under-researched area. This paper is the first to explore the needs of men through the lens of domestic abuse professionals.

One MNC′s attempts to develop empowerment strategies are reviewed. These strategies are based on a cross‐cultural study of employee needs in the company′s Australian, German and Japanese subsidiaries. Although the need to control stands out in each of the three countries, employee needs patterns are different. The needs for economic security, belongingness, recognition, self‐worth, and control relate with each in different configurations and patterns. Because of significant differences in employee needs patterns, empowerment strategies enabling employees to fulfil their need to control cannot be transferred from one culture to another without major adjustments. In some instances very little is needed to empower an employee while in others almost nothing works. Some light is shed on why, within an MNC, a similar amount of control over their work and work environments empowers Japanese workers much more than their Australian and German counterparts.

The impacts of the COVID-19 pandemic have transformed the global outlook for international higher education. Given the rapid shift to online learning, the Tokyo Convention in the Asia-Pacific entrusted to UNESCO has become an important policy framework to facilitate regional collaboration, authoritative information sharing and recognition of qualifications across diverse modes of learning. This paper examines the role of the Tokyo Convention to establish an inclusive platform for monitoring and collaborative governance of mobility and internationalization based on fair and transparent recognition policies and practices in the Asia-Pacific.

In August 2019, a standardized survey instrument was sent by the Secretariat of the Tokyo Convention Committee at UNESCO Bangkok to competent recognition authorities in 46 countries in the Asia-Pacific, including the eight State Parties to the Tokyo Convention that ratified the Convention as of the reporting period. In total, qualitative data from n = 27 countries/states was received and analyzed to assess implementation of the Tokyo Convention throughout the region. The research design illustrates how normative instruments such as the Tokyo Convention are monitored and assessed over time.

A multi-stakeholder approach based on collaborative governance is needed to effectively monitor implementation and implications of the Tokyo Convention for diverse higher education stakeholders in the Asia-Pacific region.

Implications include establishing baseline data and methods for monitoring implementation of the Tokyo Convention. Based on collaborative governance theory, the paper explores potential for a multi-stakeholder approach to promote mutual accountability in the Asia-Pacific and to develop mechanisms for inclusive participation in the governance of the forthcoming Global Convention on recognition.

As the first systematic review of its kind, this paper includes a unique dataset and insights into UNESCO's methodology to monitor implementation of standard-setting instruments for qualifications recognition in the Asia-Pacific.

Knowing how to target the African‐American market effectively is of great importance, as this segment has different values, needs and wants, and buying power. This study explores the initial stages of the decision‐making process of African‐American mothers who have a child or children under the age of seven who wear play‐wear. This study identifies children's clothing needs, advertising information used in the search process, stores searched and frequency of shopping, and the types of fabric and decorations preferred by the mothers. The findings from the focus group interviews suggest that African‐American mothers have unique needs to be met for their children's clothing. They rely on external search with an emphasis on magazines. They prefer cotton fabrics and decorations representing flowers or animals.

This is a comparative study of employee needs patterns in eight international subsidiaries of a multinational corporation. Although in each country the need to control one′s work environment emerges as the most dominant need, four different needs patterns are identified. The resulting patterns suggest that specific strategies are necessary for employee motivation in different cultural environments. Strategies that enhance work motivation in one country should be reviewed carefully before being transferred to another.

The purpose of this paper is to describe a speech and character combined recognition engine (SCCRE) developed for working on personal digital assistants (PDAs) or on mobile devices. Also, the architecture of a distributed recognition system for providing a more convenient user interface is discussed.

In SCCRE, feature extraction for speech and for character is carried out separately, but the recognition is performed in an engine. The client recognition engine essentially employs a continuous hidden Markov model (CHMM) structure and this CHMM structure consists of variable parameter topology in order to minimize the number of model parameters and to reduce recognition time. This model also adopts the proposed successive state and mixture splitting (SSMS) method for generating context independent model. SSMS optimizes the number of mixtures through splitting in mixture domain and the number of states through splitting in time domain.

The recognition results show that the developed engine can reduce the total number of Gaussian up to 40 per cent compared with the fixed parameter models at the same recognition performance when applied to speech recognition for mobile devices. It shows that SSMS can reduce the size of memory for models to 65 per cent and that for processing to 82 per cent. Moreover, the recognition time decreases 17 per cent with the SMS model while maintaining the recognition rate.

The proposed system will be very useful for many on‐line multimodal interfaces such as PDAs and mobile applications.

The purpose of this paper is to survey and analyse the literature emanating from less developed countries (LDCs) and international agencies and dealing with their perception of the needs of LDCs for scientific and technical information (STI) in relation to social and economic development.