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A simultaneous solution to the localization and mapping problem of a graph‐like environment by a swarm of robots requires solutions to task coordination and map merging. The purpose of this paper is to examine the performance of two different map‐merging strategies.

Building a representation of the environment is a key problem in robotics where the problem is known as simultaneous localization and mapping (SLAM). When large groups of robots operate within the environment, the SLAM problem becomes complicated by issues related to coordination of the elements of the swarm and integration of the environmental representations obtained by individual swarm elements. This paper considers these issues within the formalism of a group of simulated robots operating within a graph‐like environment. Starting at a common node, the swarm partitions the unknown edges of the known graph and explores the graph for a pre‐arranged period. The swarm elements then meet at a particular time and location to integrate their partial world models. This process is repeated until the entire world has been mapped. A correctness proof of the algorithm is presented, and different coordination strategies are compared via simulation.

The paper demonstrates that a swarm of identical robots, each equipped with its own marker, and capable of simple sensing and action abilities, can explore and map an unknown graph‐like environment. Moreover, experimental results show that exploration with multiple robots can provide an improvement in exploration effort over a single robot and that this improvement does not scale linearly with the size of the swarm.

The paper represents efforts toward exploration and mapping in a graph‐like world with robot swarms. The paper suggests several extensions and variations including the development of adaptive partitioning and rendezvous schedule strategies to further improve both overall swarm efficiency and individual robot utilization during exploration.

The novelty associated with this paper is the formal extension of the single robot graph‐like exploration of Dudek et al. to robot swarms. The paper here examines fundamental limits to multiple robot SLAM and does this within a topological framework. Results obtained within this topological formalism can be readily transferred to the more traditional metric representation.

The purpose of this paper is to provide a theoretical framework for predicting the next period financial behavior of bank mergers within a statistical-oriented setting.

Bank mergers are modeled combining a discrete variant of the Smoluchowski coagulation equation with a reverse engineering method. This new approach allows to compute the correct merging probability values via the construction and solution of a multi-variable matrix equation. The model is tested on real financial data relative to US banks collected from the National Information Centre.

Bank size distributions predicted by the proposed method are much more adherent to real data than those derived from the estimation method. The proposed method provides a valid alternative to estimation approaches while overcoming some of their typical drawbacks.

Bank mergers are interpreted as stochastic processes focusing on two main parameters, that is, number of banks and asset size. Future research could expand the model analyzing the micro-dynamic taking place behind bank mergers. Furthermore, bank demerging and partial bank merging could be considered in order to complete and strengthen the proposed approach.

The implementation of the proposed method assists managers in making informed decisions regarding future merging actions and marketing strategies so as to maximize the benefits of merging actions while reducing the associated potential risks from both a financial and marketing viewpoint.

To the best of the authors’ knowledge, this is the first study where bank merging is analyzed using a dynamic stochastic model and the merging probabilities are determined by a multi-variable matrix equation in place of an estimation procedure.

Despite the continuation of hospital mergers in many western countries, it is uncertain if and how hospital mergers impact the quality of care. This poses challenges for the regulation of mergers. The purpose of this paper is to understand: how regulators and hospitals frame the impact of merging on the quality and safety of care and how hospital mergers might be regulated, given their uncertain impact on quality and safety of care.

This paper studies the regulation of hospital mergers in The Netherlands. In a qualitative study design, it draws on 30 semi-structured interviews with inspectors from the Dutch Health and Youth Care Inspectorate (Inspectorate) and respondents from three hospitals that merged between 2013 and 2015. This paper draws from literature on process-based regulation to understand how regulators can monitor hospital mergers.

This paper finds that inspectors and hospital respondents frame the process of merging as potentially disruptive to daily care practices. While inspectors emphasise the dangers of merging, hospital respondents report how merging stimulated them to reflect on their care practices and how it afforded learning between hospitals. Although the Inspectorate considers mergers a risk to quality of care, their regulatory practices are hesitant.

This qualitative study sheds light on how merging might affect key hospital processes and daily care practices. It offers opportunities for the regulation of hospital mergers that acknowledges rather than aims to dispel the uncertain and potentially ambiguous impact of mergers on quality and safety of care.

The purpose of this paper is to merge the ontologies that remove the redundancy and improve the storage efficiency. The count of ontologies developed in the past few eras is noticeably very high. With the availability of these ontologies, the needed information can be smoothly attained, but the presence of comparably varied ontologies nurtures the dispute of rework and merging of data. The assessment of the existing ontologies exposes the existence of the superfluous information; hence, ontology merging is the only solution. The existing ontology merging methods focus only on highly relevant classes and instances, whereas somewhat relevant classes and instances have been simply dropped. Those somewhat relevant classes and instances may also be useful or relevant to the given domain. In this paper, we propose a new method called hybrid semantic similarity measure (HSSM)-based ontology merging using formal concept analysis (FCA) and semantic similarity measure.

The HSSM categorizes the relevancy into three classes, namely highly relevant, moderate relevant and least relevant classes and instances. To achieve high efficiency in merging, HSSM performs both FCA part and the semantic similarity part.

The experimental results proved that the HSSM produced better results compared with existing algorithms in terms of similarity distance and time. An inconsistency check can also be done for the dissimilar classes and instances within an ontology. The output ontology will have set of highly relevant and moderate classes and instances as well as few least relevant classes and instances that will eventually lead to exhaustive ontology for the particular domain.

In this paper, a HSSM method is proposed and used to merge the academic social network ontologies; this is observed to be an extremely powerful methodology compared with other former studies. This HSSM approach can be applied for various domain ontologies and it may deliver a novel vision to the researchers.

The HSSM is not applied for merging the ontologies in any former studies up to the knowledge of authors.

This article seeks to highlight the challenges and issues that face merging higher education institutions and also to outline some of the challenges in integrating the quality assurance systems during the pre‐, interim and post‐merger phases in a merged university.

Case studies of merged and merging institutions were critiqued to compare the similarities and differences. A range of issues experienced by two universities that recently merged in South Africa is explored.

It is clear that merging institutions is a thorny issue, and cannot be resolved quickly. The merging of institutions brings with it a whole host of challenges. The current literature review has found that merging higher education institutions globally is invariably unpredictable, as the institutions experience multifaceted complexities.

The lessons learned from this newly merged university can be a very useful resource and guide to those in leadership positions.

This article contributes to the current pool of information and offers practical guidance and assistance to institutions that have merged or are in the process of merging.

The complexity of business environments often causes organizations to produce several inconsistent views of the same business process (BP), leading to fragmentation. BP view integration attempts to produce an integrated view from different views of the same model, facilitating the management of BP models.

To study the trends of BP view integration, the authors conduct an extensive and systematic literature review to summarize findings since the 1970s. With a starting corpus of 918 documents, this survey draws up a systematic inventory of solutions used in academia and industry. By narrowing it down to 71 articles, the authors discuss in-depth 17 BP integration techniques papers, classifying each solution according to 9 criteria.

The authors' study shows that most view-integration methods (11) utilize annotation-based matching, based on formal merging rules. While most solutions are formalized, only approximately half are validated with a real-world use case scenario. View integration can be applied to areas other than database schema integration and BP view integration.

By summarizing existing knowledge up to June 2021, the authors explore possible future research directions. The authors highlight the application of view integration to the blockchain research area, where stakeholders can have different views on the same blockchain. The authors expect that this study contributes to interdisciplinary research across view integration, namely to the context of blockchain.

This survey serves to pave the way for future trends, where the authors highlight the application of view integration to blockchain research.

The generation of inverted indexes is one of the most computationally intensive activities for information retrieval systems: indexing large multi‐gigabyte text databases can take many hours or even days to complete. We examine the generation of partitioned inverted files in order to speed up the process of indexing. Two types of index partitions are investigated: TermId and DocId.

We use standard measures used in parallel computing such as speedup and efficiency to examine the computing results and also the space costs of our trial indexing experiments.

The results from runs on both partitioning methods are compared and contrasted, concluding that DocId is the more efficient method.

The practical implications are that the DocId partitioning method would in most circumstances be used for distributing inverted file data in a parallel computer, particularly if indexing speed is the primary consideration.

The paper is of value to database administrators who manage large‐scale text collections, and who need to use parallel computing to implement their text retrieval services.

Several online services offer functionalities to access information from “big research graphs” (e.g. Google Scholar, OpenAIRE, Microsoft Academic Graph), which correlate scholarly/scientific communication entities such as publications, authors, datasets, organizations, projects, funders, etc. Depending on the target users, access can vary from search and browse content to the consumption of statistics for monitoring and provision of feedback. Such graphs are populated over time as aggregations of multiple sources and therefore suffer from major entity-duplication problems. Although deduplication of graphs is a known and actual problem, existing solutions are dedicated to specific scenarios, operate on flat collections, local topology-drive challenges and cannot therefore be re-used in other contexts.

This work presents GDup, an integrated, scalable, general-purpose system that can be customized to address deduplication over arbitrary large information graphs. The paper presents its high-level architecture, its implementation as a service used within the OpenAIRE infrastructure system and reports numbers of real-case experiments.

GDup provides the functionalities required to deliver a fully-fledged entity deduplication workflow over a generic input graph. The system offers out-of-the-box Ground Truth management, acquisition of feedback from data curators and algorithms for identifying and merging duplicates, to obtain an output disambiguated graph.

To our knowledge GDup is the only system in the literature that offers an integrated and general-purpose solution for the deduplication graphs, while targeting big data scalability issues. GDup is today one of the key modules of the OpenAIRE infrastructure production system, which monitors Open Science trends on behalf of the European Commission, National funders and institutions.

A configurable reference model can be used to assist in the development and management of business processes in complex, multi-stakeholder environments. The purpose of this paper is to demonstrate a process design in such environments via configurable process reference modelling, using airports as an example.

Existing reference modelling methods around process modelling, merging and configuration are extended to include contextual and spatial factors using the design science methodology. The approach is empirically based on a set of business process management notation (BPMN) models for international passenger departures, consolidated from five Australian airport case studies via document analysis, interviews and observation.

The use of contextual factors and operational scenarios, structured using the proposed approach, facilitated efficient cross-organisational comparison for configuring processes to suit the needs of a target organisation. The resulting configurable model integrates the perspectives of organisational stakeholder groups with that of the customer in a transparent and unambiguous graphical representation. It is a reusable tool with low data collection needs for each use.

Future research should include: version management; how to keep the model current; configurability via modelling objects other than gateways; and cross-discipline application (e.g. as a foundation for quantitative decision-making models).

This is the first reported application of configurable reference modelling to airport passenger facilitation. Methodological contributions include the addition of space-sensitive process elements and notation to BPMN; guidelines for systematically deriving contextual factors associated with process variants across similar organisations; and overall normative guidelines for inductively developing a configurable process reference model.

This is a qualitative study of eight merged organizations. They consist of a unique sector, namely Catholic men's religious provinces. The study attempts to determine characteristics of successful mergers by understanding the processes and dynamics of mergers when membership needs to be involved and in some cases give approval of the merger. Regardless of the initiation of the merger or the processes utilized it appears that three factors and one result bring about success. A clear mission-driven purpose, authentic leadership, and inclusive engagement are essential elements of any process. They set the path for building trust among members and organizations, which may result in organizational renewal.