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The purpose of this paper is to improve an image defogging algorithm based on a dark channel prior and use this method to clear the foggy image on the Advanced RISC (Reduced Instruction Set Computing) Machines (ARM) platform.

The divided strategy of the foggy image was proposed through the estimation of the brightness and transmission thresholds. The two regions of the foggy image were processed using two transmissions. Many foggy images were tested using the improved method.

The finding resulting from this study is that a divided strategy has been proposed to use the image defogging. Compared with the existing methods, the running time of the improved method is less on the ARM platform.

Image enhancement is an important technology of digital images, and the quality of images plays a key role in the video monitoring and the intelligent transportation system.

This paper presented an improved image defogging method using the divided strategy and a substantial number of experimental results was provided to demonstrate this method.

This study provides a comprehensive framework of adaptation in triadic business relationship settings in the service sector. The framework is based on the industrial network approach (see, e.g., Axelsson & Easton, 1992; Håkansson & Snehota, 1995a). The study describes how adaptations initiate, how they progress, and what the outcomes of these adaptations are. Furthermore, the framework takes into account how adaptations spread in triadic relationship settings. The empirical context is corporate travel management, which is a chain of activities where an industrial enterprise, and its preferred travel agency and service supplier partners combine their resources. The scientific philosophy, on which the knowledge creation is based, is realist ontology. Epistemologically, the study relies on constructionist processes and interpretation. Case studies with in-depth interviews are the main source of data.

Current segmentation systems almost invariably focus on linear segmentation and can only divide text into linear sequences of segments. This suits cohesive text such as news feed but not coherent texts such as documents of a digital library which have hierarchical structures. To overcome the focus on linear segmentation in document segmentation and to realize the purpose of hierarchical segmentation for a digital library’s structured resources, this paper aimed to propose a new multi-granularity hierarchical topic-based segmentation system (MHTSS) to decide section breaks.

MHTSS adopts up-down segmentation strategy to divide a structured, digital library document into a document segmentation tree. Specifically, it works in a three-stage process, such as document parsing, coarse segmentation based on document access structures and fine-grained segmentation based on lexical cohesion.

This paper analyzed limitations of document segmentation methods for the structured, digital library resources. Authors found that the combination of document access structures and lexical cohesion techniques should complement each other and allow for a better segmentation of structured, digital library resources. Based on this finding, this paper proposed the MHTSS for the structured, digital library resources. To evaluate it, MHTSS was compared to the TT and C99 algorithms on real-world digital library corpora. Through comparison, it was found that the MHTSS achieves top overall performance.

With MHTSS, digital library users can get their relevant information directly in segments instead of receiving the whole document. This will improve retrieval performance as well as dramatically reduce information overload.

This paper proposed MHTSS for the structured, digital library resources, which combines the document access structures and lexical cohesion techniques to decide section breaks. With this system, end-users can access a document by sections through a document structure tree.

The idea of implementing supply chain management (SCM) principles for the construction industry was embraced by construction stakeholders to enhance the sector's performance. The analysis from the literature revealed that the implementation of SCM in the construction industry enhances the industry's value in terms of cost-saving, time savings, material management, risk management and others. The construction supply chain (CSC) can be managed using the pull or push system. This chapter also discusses the origin and proliferation of SCM into the construction industry. The chapter revealed that the concept of SCM has passed through five different eras: the creation era, the use of ERP, globalisation stage, specialisation stage and electronic stage. The findings from the literature revealed that we are presently in the fourth industrial revolution (4IR) era. At this stage, the SCM witnesses the adoption of technologies and principles driven by the 4IR. This chapter also revealed that the practice of SCM in the construction industry is centred around integration, collaboration, communication and the structure of the supply chain (SC). The forms and challenges hindering the adoption of these practices were also discussed extensively in this chapter.

The purpose of this paper is to examine how organizational resources: mass media corporate reputation and relative performance influences firms choice between organic, hybrid and inorganic growth strategies and how industry competition moderates this relationship.

Using panel data and Tobit regression on sample of firms from emerging markets, i.e. India, the study is conducted.

The results indicate that firm's corporate reputation, its relative performance with respect to competitors, positively influences hybrid growth strategy and negatively influences organic growth strategies. Further, results show that competition acts as a moderator of firm's relative performance and growth choice.

The study contribute to resource-based view of the firm and corporate reputation literature by the extending the deterministic role of corporate reputation to not only firms’ market-based performance but also strategic choice.

Social and environmental actors have been added to the stakeholder balancing act required of organizations in today’s competitive marketplace. To address this, the firms may create orientations to convey their strategic priorities. The purpose of this paper is to explore how different levels of environmental orientation (EO) and social orientation (SO) influence firm outcomes. This paper leverages logic from the too-much-of-a-good-thing effect to predict that firms must strategically align their resources with performance goals to optimize these resources.

The paper outlines a step-by-step guide that combines latent moderated structural equation modeling with response surface analysis to estimate curvilinear relationships. The approach leverages the benefits of both techniques to produce precise results and more nuanced – and meaningful – implications.

The procedure is effective in uncovering a curvilinear relationship between the indicator variables. Specifically, firms optimize environmental performance when EO is higher than SO. The opposite is the case for the outcome of social value and manager trust. Economic performance is highest when both indicators are simultaneously high.

This study tests the relationships between social and EOs and performance. As such, the exploratory data in this study are US-centric and self-assessment in design. These limitations open the door to confirmatory studies using objective outcome data and cross-cultural comparisons. Such studies should embrace more variables and examine potential moderating influences. Most importantly, future research should work to expand and verify the development of the eco-SO construct presented here, as the dynamics of these relationships have been overlooked in most social responsibility and sustainability research. Future studies should adopt this construct into extant models and also consider the dynamics and inter-organizational fit for partner firms with competing orientations.

For managers, the results show that conveying an environmental or social outcome has unique benefits to the firm. Further, there is an incentive to try and do both simultaneously. However, there is a critical point where the effects taper off, which can guide managers as they implement social and/or environmental strategies.

The research questions ask if a company can simultaneously deliver: economic value to shareholders, environmental value to the planet and social value to consumers while maintaining the trust of its managers. The results generally support that to fully serve one group, a firm must underserve another.

The study introduces SO as a valid construct to mirror EO and then models their interaction in three-dimensional space to present an optimal firm strategy.

We respond to calls from business schools (B-schools), apex education bodies, regulators, activist groups and researchers for more rigorous research to understand the future strategies of B-schools in India. We specifically examine the challenges posed by the current COVID-19 pandemic (and possible future similar eventualities) and the current and long-term strategies being planned to combat such crises.

To reveal the real-life scenario, semi-structured interviews were conducted with 22 academic leaders (Deans and Directors) of B-schools in India. These respondents were from both public and private institutions across the country. Open-ended questions were framed for exploration to help the authors understand the way forward in the Indian B-school context.

Findings reveal that B-schools in India are preparing themselves to overcome short-term challenges faced due to COVID-19 as well as transforming themselves through long-term strategies.

The study outlines strategic plans for some imaginative reassessments that B-schools may consider as a reaction to a pandemic-like emergency. The focus is on distinguishing the imperatives, creating a key guide for meeting immediate requirements, allotting assets in a prudent way to update educational course curricula and teaching methods and building the required academic infrastructure. The ability to focus on enduring changes (e.g. creating an e-learning framework and providing a safe and secure learning environment to students as per government mandates) will provide B-schools with a new lease of life in the future.

To analyze internationalization patterns among large Russian multinational corporations (MNCs).

Case study analysis of systematic internationalization attempts within three industries: IT, banking, and steel. For case studies, secondary data was used along with industry expert interviews.

The first finding is that Russian firms actively pursuing internationalization strategies through mergers and acquisitions (M&As) and greenfield investments were not as successful as several optimistic assessments had earlier suggested. Few global corporate champions emerged among Russian MNCs, despite a decade of record high outward foreign direct investments (OFDI). Secondly, we observed the unique trend of splitting operations between international and Russian businesses, which proved more sustainable than operating as a single firm. For example, the IBS-Luxoft group achieved success through gradual legal and organizational separation of branches in order to serve rising demand in developed markets and from its Russian business within the same industry. This double-headed strategy divides a business into two parts that are controlled by the same owners, but operate independently: one firm operates within the home market, while another firm aims to expand globally. This seems to be a typical trend, confirming recent findings for Russian small and medium enterprise (SME) internationalization and reinforcing earlier literature on institutional constraints in the Russian economy.

We analyzed major cases from three actively internationalizing industries. For each industry, we extensively analyzed one main case in particular. Industries’ choice also affects specific internationalization strategies.

This study identifies two distinct approaches in the literature on Russian business internationalization and attempts to combine both. We will also highlight organizational dilemmas as well as patterns in Russian businesses’ successful and failed internationalization strategies over the last decade. We identified an original double-headed internationalization strategy consisting of the separation of the national and global businesses, rather than leveraging their synergy. We will also question the established optimistic assessment of Russian MNC internationalization.

In this chapter, an air cargo shipment planning problem is considered by including individual risk factors of any sub-contracted agents. Due to competitive market conditions, air cargo forwarders are advised to remain flexible in operations. A mixed integer linear programming formulation including the potential for divisible activities is developed to model the shipment planning problem. To solve this complicated problem, we employ an ant colony optimization (ACO) methodology. Numerical examples are generated using data from both the extant literature and from a global air cargo company, allowing investigation of the viability of the novel methodology. We find that the algorithm/methodology provides effective solutions for small problem sizes.

Large-scale and precise three-dimensional (3D) map play an important role in autonomous driving and robot positioning. However, it is difficult to get accurate poses for mapping. On one hand, the global positioning system (GPS) data are not always reliable owing to multipath effect and poor satellite visibility in many urban environments. In another hand, the LiDAR-based odometry has accumulative errors. This paper aims to propose a novel simultaneous localization and mapping (SLAM) system to obtain large-scale and precise 3D map.

The proposed SLAM system optimally integrates the GPS data and a LiDAR odometry. In this system, two core algorithms are developed. To effectively verify reliability of the GPS data, VGL (the abbreviation of Verify GPS data with LiDAR data) algorithm is proposed and the points from LiDAR are used by the algorithm. To obtain accurate poses in GPS-denied areas, this paper proposes EG-LOAM algorithm, a LiDAR odometry with local optimization strategy to eliminate the accumulative errors by means of reliable GPS data.

On the KITTI data set and the customized outdoor data set, the system is able to generate high-precision 3D map in both GPS-denied areas and areas covered by GPS. Meanwhile, the VGL algorithm is proved to be able to verify reliability of the GPS data with confidence and the EG-LOAM outperform the state-of-the-art baselines.

A novel SLAM system is proposed to obtain large-scale and precise 3D map. To improve the robustness of the system, the VGL algorithm and the EG-LOAM are designed. The whole system as well as the two algorithms have a satisfactory performance in experiments.