Search results

Free Open Source Softwares (FOSS) witnessed the development of many very good alternatives to proprietary softwares. These free softwares can be localized in several local languages. This paper aims to illustrate a very interesting empirical investigation on FOSS. Several significant benefits of localization are described in introduction and subsequent sections.

Although the localization process is standard and well documented for most of the FOSS, it is a more complex task as it involves coordination among developers, linguists and domain experts. Hence, a very few open source softwares are successfully localized in Indian languages. In this paper, the authors present an approach that they have used for GIMP (GNU Image Manipulation Program) software Marathikaran (localization in Marathi language) project of by Rajya Marathi Vikas Sanstha of Maharashtra Government (RMVS), India.

This localization project has been described by RMVS as a pilot project that would guide such similar localizations in many other Indian languages for other popular open source softwares.

The localization work overcomes the general misconception that regional languages are good only for communication (Boli Bhasha) but cannot be used for dissemination of knowledge (Gyan Bhasha). This work is notably contributing to language preservation, language revitalization and Digital India Initiative.

This work is the pioneering work in this domain for Marathi language with respect to GIMP. The authors presented systematic steps used to localize the GIMP software in Marathi language (from 2% to 100%).

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.

This paper aims to explore the key risk factors affecting the Personnel Localization Management of international construction projects under the major public emergencies represented by the novel coronavirus pneumonia pandemic (hereinafter COVID-19) and how the public emergency affected the Personnel Localization Management from three levels: staff turnover rate, the number of different personnel, the salary and performance of workers. The paper also helps to enhance the construction enterprises' response capacity of major public emergencies and provides a comprehensive framework of optimization strategies for the Personnel Localization Management of international construction projects (hereinafter projects).

The main research method of this paper is the case study, and ten representative international construction projects are selected for case study in China construction enterprises (hereinafter CCE). And this study used the failure mode and effects analysis (FMEA) and comparative analysis to find out all potential risk factors under the COVID-19 and analyze how the epidemic affects the Personnel Localization Management of projects which based on the primary data from 10 projects obtained through in-depth interviews and the secondary data from China First Metallurgical Group and Central South Construction Group's Overseas Enterprise.

The findings show that the outbreak of the major public emergencies not only greatly increased eight risk factors but also directly led to an increase in staff turnover rate. Meanwhile, the numbers of Chinese and local managers and workers are all affected, and an increase in the number and the salary performance of local workers can be reduced, to a certain extent, to the cost-to-output ratio of the projects. The findings would help construction enterprises better cope with Personnel Localization Management and enhance the response capacity of major public emergencies.

This study will broaden researchers' horizons regarding “Personnel Localization Management under major public emergencies” and “risk factors of Personnel Localization Management in an international context.” Furthermore, construction enterprises looking for a better mechanism of Personnel Localization Management can benefit from research findings and lessons learned from the authors' case study during or before an outbreak of major public emergency. Lastly, the framework of optimization strategies for Personnel Localization Management can be used both for research purposes and practice issues in international construction projects.

The findings from the authors' case study offer the direction for international construction enterprises in China and other countries to formulate effective measures, strengthen overseas business and establish a crisis management mechanism for Personnel Localization Management under major public emergencies, and the findings provide emergency plans for projects to improve the public crisis handling capacity and respond to major public emergencies such as the COVID-19.

This study analyzes the impact of the COVID-19 on the Personnel Localization Management of international construction projects from the perspective of personnel. This study provides a theoretical reference for the international construction industry to actively respond to major public emergencies. Besides, the research is conducive to improving the emergency response mechanism in the construction industry, and further promoting the high-quality and globalized development of international construction.

This study provides other researchers with a comprehensive understanding of the risk factors affecting the Personnel Localization Management of projects under the COVID-19 and insight for further research on localization management, risk management, and project management.

Localization of the nodes is crucial for gaining access of different nodes which would provision in extreme areas where networks are unreachable. The feature of localization of nodes has become a significant study where multiple features on distance model are implicated on predictive and heuristic model for each set of localization parameters that govern the design on energy minimization with proposed adaptive threshold gradient feature (ATGF) model. A received signal strength indicator (RSSI) model with node estimated features is implicated with localization problem and enhanced with hybrid cumulative approach (HCA) algorithm for node optimizations with distance predicting.

Using a theoretical or empirical signal propagation model, the RSSI (known transmitting power) is converted to distance, the received power (measured at the receiving node) is converted to distance and the distance is converted to RSSI (known receiving power). As a result, the approximate distance between the transceiver node and the receiver may be determined by measuring the intensity of the received signal. After acquiring information on the distance between the anchor node and the unknown node, the location of the unknown node may be determined using either the trilateral technique or the maximum probability estimate approach, depending on the circumstances using federated learning.

Improvisation of localization for wireless sensor network has become one of the prime design features for estimating the different conditional changes externally and internally. One such feature of improvement is observed in this paper, via HCA where each feature of localization is depicted with machine learning algorithms imparting the energy reduction problem for each newer localized nodes in Section 5. All affected parametric features on energy levels and localization problem for newer and extinct nodes are implicated with hybrid cumulative approach as in Section 4. The proposed algorithm (HCA with AGTF) has implicated with significant change in energy levels of nodes which are generated newly and which are non-active for a stipulated time which are mentioned and tabulated in figures and tables in Section 6.

Localization of the nodes is crucial for gaining access of different nodes which would provision in extreme areas where networks are unreachable. The feature of localization of nodes has become a significant study where multiple features on distance model are implicated on predictive and heuristic model for each set of localization parameters that govern the design on energy minimization with proposed ATGF model. An RSSI model with node estimated features is implicated with localization problem and enhanced with HCA algorithm for node optimizations with distance predicting.

This paper aims to extend the traditional conceptualization of localization, which has largely focused on recruitment, by examining “employability” and “retention” as crucial determinants of localization success.

Using survey data from local (Emirati) employees in private sector organizations in the United Arab Emirates (UAE), the authors develop a holistic model of localization and test the relationships between stereotypes, organizational socialization, employability and retention outcomes, using Smart-PLS.

Among the main findings are the significant influence of stereotypes on organizational socialization (OS) experiences of Emirati employees, with a negative relationship between “work ethics stereotypes” and perceptions of OS experiences. Strong evidence is also found for the indirect effects of OS experiences on retention of Emirati employees, mediated by employability.

This study contributes to the literature on localization by examining the relationships between key variables not examined together in previous research. In terms of limitations, the cross-sectional nature of the study prevents the identification of direction of causality among these relationships. Since employee integration, as part of localization efforts, is a gradual process, future research should include longitudinal studies.

Employability has emerged as a significant challenge for organizations and governments working to implement successful localization initiatives. This study’s findings highlight several opportunities for organizational and governmental policy interventions to support successful localization.

The authors’ holistic model extends localization literature by providing evidence for the role of stereotypes and employability as key constructs to be examined along with OS experiences and retention.

Self-localization of an underwater robot using global positioning sensor and other radio positioning systems is not possible, as an alternative onboard sensor-based self-location estimation provides another possible solution. However, the dynamic and unstructured nature of the sea environment and highly noise effected sensory information makes the underwater robot self-localization a challenging research topic. The state-of-art multi-sensor fusion algorithms are deficient in dealing of multi-sensor data, e.g. Kalman filter cannot deal with non-Gaussian noise, while parametric filter such as Monte Carlo localization has high computational cost. An optimal fusion policy with low computational cost is an important research question for underwater robot localization.

In this paper, the authors proposed a novel predictive coding-biased competition/divisive input modulation (PC/BC-DIM) neural network-based multi-sensor fusion approach, which has the capability to fuse and approximate noisy sensory information in an optimal way.

Results of low mean localization error (i.e. 1.2704 m) and computation cost (i.e. 2.2 ms) show that the proposed method performs better than existing previous techniques in such dynamic and unstructured environments.

To the best of the authors’ knowledge, this work provides a novel multisensory fusion approach to overcome the existing problems of non-Gaussian noise removal, higher self-localization estimation accuracy and reduced computational cost.

This paper aims to study the localization problem for autonomous industrial vehicles in the complex industrial environments. Aiming for practical applications, the pursuit is to build a map-less localization system which can be used in the presence of dynamic obstacles, short-term and long-term environment changes.

The proposed system contains four main modules, including long-term place graph updating, global localization and re-localization, location tracking and pose registration. The first two modules fully exploit the deep-learning based three-dimensional point cloud learning techniques to achieve the map-less global localization task in large-scale environment. The location tracking module implements the particle filter framework with a newly designed perception model to track the vehicle location during movements. Finally, the pose registration module uses visual information to exclude the influence of dynamic obstacles and short-term changes and further introduces point cloud registration network to estimate the accurate vehicle pose.

Comprehensive experiments in real industrial environments demonstrate the effectiveness, robustness and practical applicability of the map-less localization approach.

This paper provides comprehensive experiments in real industrial environments.

The system can be used in the practical automated industrial vehicles for long-term localization tasks. The dynamic objects, short-/long-term environment changes and hardware limitations of industrial vehicles are all considered in the system design. Thus, this work moves a big step toward achieving real implementations of the autonomous localization in practical industrial scenarios.

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.