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This study examines the interactive effects of work values and organisational commitment on localisation.

This study draws on human capital theory, and reports on a survey of 200 expatriate managers working in Qatar.

We find that localisation is negatively associated with work values and positively associated with organisational commitment. Furthermore, work values appear to influence organisational commitment.

Despite a surfeit of literature on localisation of human resources, few studies previously have explored its relationship with work values and organisational commitment. This chapter presents empirical research on the issue from Qatar, a country in a region which remains under-researched in the literature.

Achieving localisation (the transfer of control to local actors) has proven extremely challenging in the development sector, and the humanitarian sector appears to be facing equal challenges. This chapter seeks to engage with that struggle and examine why this lesson has been so difficult to learn. Drawing on conference workshops and 10 key informant interviews, this paper examines the obstacles and opportunities for localisation, seeking to understand what makes it so hard for those who hold disproportionate power in humanitarian encounters to hand over power. The authors found a clear sense of localisation being a process rather than an outcome; optimism that momentum is slowly gathering towards this process, and a clear sense of the steps required to fully achieve it. Examining practitioners’ perspectives in this way adds an important voice to discussions of humanitarian practice.

Precise vehicle localization is a basic and critical technique for various intelligent transportation system (ITS) applications. It also needs to adapt to the complex road environments in real-time. The global positioning system and the strap-down inertial navigation system are two common techniques in the field of vehicle localization. However, the localization accuracy, reliability and real-time performance of these two techniques can not satisfy the requirement of some critical ITS applications such as collision avoiding, vision enhancement and automatic parking. Aiming at the problems above, this paper aims to propose a precise vehicle ego-localization method based on image matching.

This study included three steps, Step 1, extraction of feature points. After getting the image, the local features in the pavement images were extracted using an improved speeded up robust features algorithm. Step 2, eliminate mismatch points. Using a random sample consensus algorithm to eliminate mismatched points of road image and make match point pairs more robust. Step 3, matching of feature points and trajectory generation.

Through the matching and validation of the extracted local feature points, the relative translation and rotation offsets between two consecutive pavement images were calculated, eventually, the trajectory of the vehicle was generated.

The experimental results show that the studied algorithm has an accuracy at decimeter-level and it fully meets the demand of the lane-level positioning in some critical ITS applications.

The differential magnetic gradient tensor system is usually constructed from the three-axis magnetic sensor array. While the effects of measurement error, sensor performance and baseline distance on localization performance of such systems have been widely reported, the research about the effect of spatial design of sensor array is less presented. This paper aims to provide a spatial design method of sensor array and corresponding optimization strategy to localization based on magnetic tensor gradient to get the optimum design of the sensor array. Based on the results of simulation, magnetic localization systems constructed from the proposed array and the traditional array have been built to carry out a localization experiment. The results of experiment have verified the effectiveness of magnetic localization based on the proposed array.

The authors focus on the localization of the magnetic target based on magnetic gradient by using three-axis magnetic sensor array and combine a design method with corresponding optimization strategy to get the optimum design of the sensor array.

This paper provides an array design and optimization method for magnetic target localization based on magnetic gradient to improve the localization performance.

In this paper, the authors focus on the magnetic localization based on magnetic gradient by using three-axis magnetic sensors and study the effect of the spatial design of sensor array on localization performance.

Wireless network localization technology is very popular in recent years and has attracted worldwide attention. The purpose of this paper is to improve the localization accuracy of ultra-wideband (UWB) with lower localization error taking into consideration the special real environment with the closed long and narrow space.

The principle of multidimensional scaling (MDS), particle swarm optimization (PSO) and Taylor series expansion algorithm (Taylor-D) were introduced. A novel positioning algorithm, MDS-PSO-Taylor was proposed to minimize the localization error. MDS-PSO algorithm provided a more accurate preliminary coordinate by applying the PSO algorithm so that the Taylor-D was used for further enhancing the localization accuracy.

Experimental results manifested that the proposed algorithm, providing small localization error value and higher positioning accuracy, can effectively reduce errors and achieve better performance in terms of the considerable improvement of localization accuracy.

The presented study with the real environment test attempts to demonstrate the proposed algorithm is hopeful to be applied to the underground environment for in the future.

Robot localization in dynamic, cluttered environments is a challenging problem because it is impractical to have enough knowledge to be able to accurately model the robot’s environment in such a manner. This study aims to develop a novel probabilistic method equipped with function approximation techniques which is able to appropriately model the data distribution in Markov localization by using the maximum statistical power, thereby making a sensibly accurate estimation of robot’s pose in extremely dynamic, cluttered indoors environments.

The parameter vector of the statistical model is in the form of positions of easily detectable artificial landmarks in omnidirectional images. First, using probabilistic principal component analysis, the most likely set of parameters of the environmental model are extracted from the sensor data set consisting of missing values. Next, we use these parameters to approximate a probability density function, using support vector regression that is able to calculate the robot’s pose vector in each state of the Markov localization. At the end, using this density function, a good approximation of conditional density associated with the observation model is made which leads to a sensibly accurate estimation of robot’s pose in extremely dynamic, cluttered indoors environment.

The authors validate their method in an indoor office environment with 34 unique artificial landmarks. Further, they show that the accuracy remains high, even when they significantly increase the dynamics of the environment. They also show that compared to those appearance-based localization methods that rely on image pixels, the proposed localization strategy is superior in terms of accuracy and speed of convergence to a global minima.

By using easily detectable, and rotation, scale invariant artificial landmarks and the maximum statistical power which is provided through the concept of missing data, the authors have succeeded in determining precise pose updates without requiring too many computational resources to analyze the omnidirectional images. In addition, the proposed approach significantly reduces the risk of getting stuck in a local minimum by eliminating the possibility of having similar states.

The purpose of this paper is twofold: first, to understand Emirati nationals’ perceptions of the role of workforce localisation policies in their professional aspirations and growth and, second, to determine the role of higher education and job attributes in the achievement of their goals. The study uses a hierarchy-based model/road map to improve localisation efforts by attempting to aid understanding of the relationships and barriers hindering these processes.

The study follows a two-stage process. In the first stage, a questionnaire-based survey was administered to 207 Emirati postgraduate students from public and private universities based in two major Emirates: Abu Dhabi and Dubai. The sample data were analysed by basic descriptive statistics in the form of cross-relationships and rank correlation tests. In the second stage, an interpretive structural modelling approach was used to develop a hierarchy-based structural model of the barriers to localisation.

Emiratis younger than 30 years old consider localisation as an enabling factor in their professional success in contrast to those older than 30 years old. The results also indicate that working female Emiratis have significantly more positive attitudes regarding the contribution of localisation towards their professional success than that of their male counterparts. However, both genders see a mismatch in efforts being made to better equip themselves for the workplace. The hierarchy-based model delineates variables that could contribute to making localisation a successful employment programme in the United Arab Emirates (UAE).

The findings of this study relate to the UAE. However, there are similar localisation programmes that have been implemented in other Gulf Cooperation Council states. Hence, while the results of this study are relevant to the UAE, they may not be generalisable to the entire Gulf region.

It is proposed that the research findings and the structural model of relationships may help policy makers develop suitable strategies to strengthen the Emirati localisation programme.

This study makes a contribution to the literature and can serve as a guide to policy makers for localisation programmes. This is achieved by analysing the attitude of UAE nationals studying at higher education institutions. Furthermore, the study presents a hierarchy-based model of the barriers to localisation that explains the root causes of the problem.

The purpose of this paper is to develop a Biblical basis for localization as against globalization. This paper argues that the normative direction of Biblical thought is toward the localization of socio‐economic activity. A case study is made for the developing world today relevant to localization.

An evaluation is made of normative Biblical teaching that might have bearing on the localization of socio‐economic activity. How this teaching could apply to the contemporary developing world is assessed.

Normative Biblical teaching is oriented toward localization. This emphasis is capable of being applied in the developing world.

The case that normative Biblical teaching is in favour of localization rather then dispersal (and thereby globalization) has not been made previously. For those who believe that normative Biblical teaching has relevance today, the localization bias challenges the widespread acceptance of globalization.

Robot localization technology has been widely studied for decades and a lot of remarkable approaches have been developed. However, in practice, this technology has hardly been applied to common day-to-day deployment scenarios. The purpose of this paper is to present a novel approach that focuses on improving the localization robustness in complicated environment.

The localization robustness is improved by dynamically switching the localization components (such as the environmental camera, the laser range finder and the depth camera). As the components are highly heterogeneous, they are developed under the robotic technology component (RTC) framework. This simplifies the developing process by increasing the potential for reusability and future expansion. To realize this switching, the localization reliability for each component is modeled, and a configuration method for dynamically selecting dependable components at run-time is presented.

The experimental results show that this approach significantly decreases robot lost situation in the complicated environment. The robustness is further enhanced through the cooperation of heterogeneous localization components.

A multi-component automatic switching approach for robot localization system is developed and described in this paper. The reliability of this system is proved to be a substantial improvement over single-component localization techniques.

Through an empirical inquiry into manufacturing joint ventures companies in Vietnam setting, this paper aims to examine the relationships among knowledge sharing and its antecedents such as organisational culture, ethics, and human resources localization.

An analysis of data returned from a questionnaire survey among middle level managers in these manufacturing joint ventures companies was conducted via analysis of variance and structural equation modelling.

The study findings display the correspondence between control culture and ethics of justice. Flexibility culture, on the other hand, tends to nurture ethics of care, which in turn positively impact localization of intellectual capital. The influence of intellectual capital localization on knowledge sharing is also discerned.

The study offers insight into the linkage pattern of knowledge sharing and its antecedents, organisational culture, ethics, and human resources localization, in manufacturing joint venture companies in a Vietnam business context.