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The traffic flow pattern of the material distribution activity within the Canadian Forces was evaluated. The aim was to validate the current operation of the material traffic system. Sample transportation data were collected, and the traffic flow pattern and utilisations of the Canadian Forces′ scheduled tractor‐trailer units were statistically inferred. Because historical material traffic data were lacking, the material traffic flow pattern for this one‐time snapshot of the transportation system did not provide a basis from which any trend on the Canadian Forces′ vehicle utilisation could be established.

This chapter extends the univariate forecasting method proposed by Wang, Luc, and Hsiao (2013) to forecast the multivariate long memory model subject to structural breaks. The approach does not need to estimate the parameters of this multivariate system nor need to detect the structural breaks. The only procedure is to employ a VAR(k) model to approximate the multivariate long memory model subject to structural breaks. Therefore, this approach reduces the computational burden substantially and also avoids estimation of the parameters of the multivariate long memory model, which can lead to poor forecasting performance. Moreover, when there are multiple breaks, when the breaks occur close to the end of the sample or when the breaks occur at different locations for the time series in the system, our VAR approximation approach solves the issue of spurious breaks in finite samples, even though the exact orders of the multivariate long memory process are unknown. Insights from our theoretical analysis are confirmed by a set of Monte Carlo experiments, through which we demonstrate that our approach provides a substantial improvement over existing multivariate prediction methods. Finally, an empirical application to the multivariate realized volatility illustrates the usefulness of our forecasting procedure.

Aim of the present monograph is the economic analysis of the role of MNEs regarding globalisation and digital economy and in parallel there is a reference and examination of some legal aspects concerning MNEs, cyberspace and e‐commerce as the means of expression of the digital economy. The whole effort of the author is focused on the examination of various aspects of MNEs and their impact upon globalisation and vice versa and how and if we are moving towards a global digital economy.

Discusses the 6th ITCRR, its breadth of textile and clothing research activity, plus the encouragement given to workers in this field and its related areas. States that, within the newer research areas under the microscope of the community involved, technical textiles focuses on new, ‘smart’ garments and the initiatives in this field in both the UK and the international community at large. Covers this subject at length.

The purpose of this work is to implement an ambient intelligence (AmI) testbed to improve human sleeping conditions.

The implemented testbed is composed of the sensor node, sink node and actor node. As sensor node, the authors use a microwave sensor module (MSM) called DC6M4JN3000, which emits microwaves in the direction of a human or animal subject. These microwaves reflect back off the surface of the subject and change slightly in accordance with movements of the subject’s heart and lungs. As sink node, the authors use Raspberry Pi 3 Model B computers. In the sink node, the data are processed and then clustered by the k-means clustering algorithm. Then, the result is sent to the actor node (Reidan Shiki PAD module), which can be used for cooling and heating the bed.

The authors carried out simulations and experiments. Based on the simulation results, it was found that the room lighting, humidity and temperature have different effects on humans during sleeping. The best performance is shown when LIG parameter is 10 units, HUM parameter is 50 and TEM parameter is 25. Based on experimental results, it was found that the implemented AmI testbed has a good effect on humans during sleeping.

For simulations, three input parameters were considered. However, new parameters that affect human sleeping conditions also need to be investigated. Further, the experiments were carried out for one person. More extensive experiments with multiple people are needed to have a better evaluation.

In this research work, a new fuzzy-based system was implemented to improve human sleeping conditions. The authors presented three new input parameters to evaluate the output (sleeping condition). The authors implemented and evaluated a testbed and showed that the implemented AmI testbed has a good effect on humans during sleeping, thus improving their quality of life (QoL).

We document the emergence of the Lead Independent Director (LID) board role in a sample of U.S. firms from 1999–2015. We find that firms that adopt an LID board role are larger and have more independent boards, higher institutional investor holdings, and an NYSE listing. Firms with greater anticipated benefits from monitoring also adopt an LID role, e.g., firms with dual CEO-Chairman, with more takeover defense mechanisms, and with higher cash holdings. Using an event study methodology, we find that investors respond positively to the adoption of an LID board role. Lastly, using instrumental variables to address endogeneity in the LID board role, we find that firms with an LID are more likely to terminate poorly performing CEOs. Taken as a whole, these results suggest that the LID board role enhances firm value and improves the quality of corporate governance.

This study analyses the advantages and weaknesses of using Facebook to aid the learning of Japanese as a foreign language.

A questionnaire survey was conducted to collect data from 100 Hong Kong Japanese language learners (who are generally fluent in Chinese and English), ranging from total amateur to advanced learners (Japanese Language Proficiency Test (JLPT) qualified at different levels).

The authors' results suggest that the advantages of using Facebook to help learn Japanese include: (1) serving as a free-of-charge, casual, and convenient learning platform; (2) enriching learners' knowledge beyond the language learning and (3) encouraging interactive and collaborative learning with other users for practicing the language. However, the low credibility and unstructured educational materials posted on Facebook and being easily distracted by other Facebook feeds are the major weaknesses of learning a language through Facebook. Furthermore, the authors' result shows that Facebook is especially effective for Japanese learning when learners fall into either one of the following groups: young, female, or intermediate (N2/3) learners.

Scant studies focus on the aid of learning Japanese via Facebook, especially Hong Kong learners' perceptions, or generally in the East. Therefore, this study aims to fill this research gap. The authors' findings will facilitate the students, teachers, and language institutions from Hong Kong and other countries to improve the students' effectiveness in learning and teaching Japanese.