The impact of the language barrier on the management of multinational companies : a case study and survey, based exploration of the impact of the language barrier on the strategies, policies and systems by which multinational companies manage their subsidaries

The thesis begins with a conceptual model of the way that language diversity affects the strategies, organisation and subsidiary control policies of multinational companies. The model is based solely on the researcher'’ personal experience of working in a variety of international management roles, but in Chapter 2 a wide-ranging review of related academic literature finds evidence to support the key ideas. The model is developed as a series of propositions which are tested in a comparative case study, refined and then re-tested in a global survey of multinational subsidiaries. The principal findings of the empirical phases of the thesis endorse the main tenets of the model: - That language difference between parent and subsidiary will impair communication, create mistrust and impede relationship development. - That subsequently the feelings of uncertainty, suspicion and mistrust will influence the decisions taken by the parent company. - They will have heightened sensitivity to language issues and will implement policies to manage language differences. - They will adopt low-risk strategies in host countries where they are concerned about language difference. - They will use organisational and manpower strategies to minimise the consequences and risks of the communications problems with the subsidiary. - As a consequence the level of integration and knowledge flow between parent and subsidiary will be curtailed. - They will adopt styles of control that depend least on their ability to communicate with their subsidiary. Although there is adequate support for all of the above conclusions, on some key points the evidence of the Case Studies and Survey is contradictory. The thesis, therefore, closes with an agenda for further research that would address these inconsistencies.

Model and performance of a no-reference quality assessment metric for video streaming

Video streaming via Transmission Control Protocol (TCP) networks has become a popular and highly demanded service, but its quality assessment in both objective and subjective terms has not been properly addressed. In this paper, based on statistical analysis a full analytic model of a no-reference objective metric, namely pause intensity (PI), for video quality assessment is presented. The model characterizes the video playout buffer behavior in connection with the network performance (throughput) and the video playout rate. This allows for instant quality measurement and control without requiring a reference video. PI specifically addresses the need for assessing the quality issue in terms of the continuity in the playout of TCP streaming videos, which cannot be properly measured by other objective metrics such as peak signal-to-noise-ratio, structural similarity, and buffer underrun or pause frequency. The performance of the analytical model is rigidly verified by simulation results and subjective tests using a range of video clips. It is demonstrated that PI is closely correlated with viewers' opinion scores regardless of the vastly different composition of individual elements, such as pause duration and pause frequency which jointly constitute this new quality metric. It is also shown that the correlation performance of PI is consistent and content independent. © 2013 IEEE.

Footwear for gender recognition

Conventionally, biometrics resources, such as face, gait silhouette, footprint, and pressure, have been utilized in gender recognition systems. However, the acquisition and processing time of these biometrics data makes the analysis difficult. This letter demonstrates for the first time how effective the footwear appearance is for gender recognition as a biometrics resource. A footwear database is also established with reprehensive shoes (footwears). Preliminary experimental results suggest that footwear appearance is a promising resource for gender recognition. Moreover, it also has the potential to be used jointly with other developed biometrics resources to boost performance.

Binary sparse nonnegative matrix factorization

This paper presents a fast part-based subspace selection algorithm, termed the binary sparse nonnegative matrix factorization (B-SNMF). Both the training process and the testing process of B-SNMF are much faster than those of binary principal component analysis (B-PCA). Besides, B-SNMF is more robust to occlusions in images. Experimental results on face images demonstrate the effectiveness and the efficiency of the proposed B-SNMF.

Gabor-based region covariance matrices for face recognition

This paper presents a new method for human face recognition by utilizing Gabor-based region covariance matrices as face descriptors. Both pixel locations and Gabor coefficients are employed to form the covariance matrices. Experimental results demonstrate the advantages of this proposed method.

Service differentiation for the bandwidth request scheme in fixed IEEE 802.16 networks

IEEE 802.16 standards have been developed as one of the technical solutions for broadband wireless access systems. It has high data rate, large network coverage, flexible QoS schemes and cheap network deployment. Various flexible mechanisms related to QoS provisioning have been specified for uplink traffic at the medium access control (MAC) layer in the standards. Among the mechanisms, contention based bandwidth request scheme can be used to indicate bandwidth demands to the base station for the non-real-time polling and besteffort services. These two services are used for most application with unknown traffic characteristics. Due to the diverse QoS requirements of those applications, service differentiation (SD) is anticipated over the contention based bandwidth request scheme. In this paper we investigate the SD with the bandwidth request scheme by means of assigning different channel access parameters and bandwidth allocation priorities. The effectiveness of the differentiation schemes are evaluated by simulations. It is observed that the initial backoff window can be efficient in SD, and if combined with the bandwidth allocation priority, the SD performances will be better. ©2008 IEEE.

Determining the number of nodes for wireless sensor networks

The number of nodes has large impact on the performance, lifetime and cost of wireless sensor network (WSN). It is difficult to determine, because it depends on many factors, such as the network protocols, the collaborative signal processing (CSP) algorithms, etc. A mathematical model is proposed in this paper to calculate the number based on the required working time. It can be used in the general situation by treating these factors as the parameters of energy consumption. © 2004 IEEE.

Robust tensor analysis with L1-norm

Tensor analysis plays an important role in modern image and vision computing problems. Most of the existing tensor analysis approaches are based on the Frobenius norm, which makes them sensitive to outliers. In this paper, we propose L1-norm-based tensor analysis (TPCA-L1), which is robust to outliers. Experimental results upon face and other datasets demonstrate the advantages of the proposed approach. © 2006 IEEE.