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In this work, the authors aim to provide a set of convenient methods for generating training data, and then develop a deep learning method based on point clouds to estimate the pose of target for robot grasping.

This work presents a deep learning method PointSimGrasp on point clouds for robot grasping. In PointSimGrasp, a point cloud emulator is introduced to generate training data and a pose estimation algorithm, which, based on deep learning, is designed. After trained with the emulation data set, the pose estimation algorithm could estimate the pose of target.

In experiment part, an experimental platform is built, which contains a six-axis industrial robot, a binocular structured-light sensor and a base platform with adjustable inclination. A data set that contains three subsets is set up on the experimental platform. After trained with the emulation data set, the PointSimGrasp is tested on the experimental data set, and an average translation error of about 2–3 mm and an average rotation error of about 2–5 degrees are obtained.

The contributions are as follows: first, a deep learning method on point clouds is proposed to estimate 6D pose of target; second, a convenient training method for pose estimation algorithm is presented and a point cloud emulator is introduced to generate training data; finally, an experimental platform is built, and the PointSimGrasp is tested on the platform.

Many metal workpieces have the characteristics of less texture, symmetry and reflectivity, which presents a challenge to existing pose estimation methods. The purpose of this paper is to propose a pose estimation method for grasping metal workpieces by industrial robots.

Dual-hypothesis robust point matching registration network (RPM-Net) is proposed to estimate pose from point cloud. The proposed method uses the Point Cloud Library (PCL) to segment workpiece point cloud from scenes and a trained-well robust point matching registration network to estimate pose through dual-hypothesis point cloud registration.

In the experiment section, an experimental platform is built, which contains a six-axis industrial robot, a binocular structured-light sensor. A data set that contains three subsets is set up on the experimental platform. After training with the emulation data set, the dual-hypothesis RPM-Net is tested on the experimental data set, and the success rates of the three real data sets are 94.0%, 92.0% and 96.0%, respectively.

The contributions are as follows: first, dual-hypothesis RPM-Net is proposed which can realize the pose estimation of discrete and less-textured metal workpieces from point cloud, and second, a method of making training data sets is proposed using only CAD models with the visualization algorithm of the PCL.

The purpose of this paper is threefold: to present internet of things (IoT)-based cyber-physical system (CPS) architecture framework to facilitate the integration of IoT and CPS; to implement an IoT-based CPS prototype based on the architecture framework for a PL application scenario of in a case study; and to devise evaluation methods and conduct experimental evaluations on an IoT-based CPS prototype.

The design research method, case study, emulation experiment method, and cost-benefit analysis are applied in this research. An IoT-based CPS architecture framework is proposed, and followed by the development of prototype system and testbed platform. Then, the emulation and experimental evaluation of IoT-based CPS are conducted on the testbed, and the experimental results are analyzed.

The emulation experiment results show that the proposed IoT-based CPS outperforms current barcode-based system regarding labor cost, efficiency, and operational adaptiveness. The evaluation of the IoT-based CPS prototype indicates significant improvements in PL tasks and reduced part inventory under a dynamic changing shop-floor environment.

The case study shows that the proposed architecture framework and prototype system can be applied to many discrete manufacturing industries, such as automobile, airplane, bicycle, home appliance, and electronics.

The proposed IoT-based CPS is among the first to address the need to integrate IoT and CPS for PL applications, and to conduct experimental evaluations and cost-benefit analysis of adopting IoT-based CPS for PL. This paper also contributes to the IoT research by using diverse research methods to offer broader insights into understanding IoT and CPS.

The purpose of this paper is to examine digital preservation of e-government in Ghana under the research question: what are the current digital preservation strategies being deployed across the ministries and agencies in Ghana?

Guided by a conceptual framework, underpinned by a quantitative approach, the paper uses the survey approach, to address the digital preservation strategies deployed across public sector organisations in Ghana. It underscores the link between the conceptual framework and the literature to analyse the various digital preservation strategies.

Backup strategy, migration, metadata and trusted repositories were noted as the most widely implemented preservation strategies across the ministries and agencies. On the other hand, cloud computing, refreshing and emulation were the least implemented strategies used to address the digital preservation challenges.

The paper adds to the existing conceptual underpinnings that have dominated the debate about data management, archival storage, preservation strategies, challenges and best practices of digital preservation of e-government.

This study draws its originality from the evidence of studies on digital preservation in Ghana as most studies have rather focussed on the preservation of documentary heritage, preservation and security of microfilms, preservation practices in the public records (Akussah, 2002; Ampofo, 2009; Festus, 2010). The emergence of this study addresses the knowledge gap in the preservation of digital records in a country where little attention has been accorded to digital preservation. The study also feeds into Ghana’s vision 2020 and the information communication technology policy document of the ministry of communication which aims at ensuring that Ghanaians have access to information and communication technology products and services.

The aim of this paper is to rethink the concept of significant properties in relationship to video game emulation.

In this paper, video games are examined as complex digital objects, that is digital objects that are constituted by multiple layers that are interconnected with other objects. Starting from the assumption that metadata are fundamental to individuate the authenticity and accuracy of a complex digital object, the research is based on the analysis of the most recent frameworks that propose a substantial use of metadata to perform gaming emulation.

Technical metadata are being used within emulation frameworks to describe digital environments and objects. Although metadata cannot be considered a definitive solution for preserving significant properties of video games, they should be used in a more extensive way across frameworks.

This paper tries to provide insights on video game properties that can help to refine the debate on emulation.

The purpose of this paper is twofold: first, to discuss key challenges associated with the use of either simulation or real-world application of intelligent autonomous vehicles (IAVs) in supply network operations; and second, to provide a theoretical and empirical evidence-based methodological framework that supports the integrated application of conceptualisation, simulation, emulation and physical application of IAVs for the effective design of digital supply networks.

First, this study performs a critical review of the extant literature to identify major benefits and shortcomings related to the use of either simulation modelling or real-word application of physical IAVs. Second, commercial and bespoke software applications, along with a three-dimensional validation and verification emulation tool, are developed to evaluate an IAV’s operations in a conceptual warehouse. Third, a commercial depth-sensor is used as a test bed in a physical setting.

The results demonstrate that conceptual and simulation modelling should be initially used to explore alternative supply chain operations in terms of ideal performance while emulation tools and real-world IAV test beds are eminent in validating preferred digital supply chain design options.

The provided analysis framework was developed using literature evidence along with experimental work and research experience, without consulting any industry experts. In addition, this study was developed based on the application of a single physical device application as a test bed and, thus, the authors should further progress with the testing of a physical IAV in an industrial warehouse.

The study provides bespoke simulation modelling and emulation tools that can be useful for supply chain practitioners in effectively designing network operations.

This work contributes in the operations management field by providing both a multi-stage methodological framework and a practical “toolbox” for the proactive assessment and incorporation of IAVs in supply network operations.

Based on a three‐level digital preservation framework, the purpose of this paper is to suggest a solution for long‐term digital preservation for the public administration sector, in the form of a centralised intermediate repository, on the basis of the concept of cloud computing.

By means of a thorough review of the literature in this area and an analysis of the current state of the art, the paper investigates a three‐level digital preservation framework with a focus on the public sector. It cross‐links this framework with the cloud computing concept, in order to propose an appropriate solution.

The mapping of six factors of digital preservation to three levels of digital preservation shows that using appropriate steps supported by suitable strategies and policies enables the public administration sector to take advantage of modern information technology and solve the demanding and critical problem of digital preservation.

The paper suggests an organisational and technological solution in the form of a centralised digital preservation repository within a cloud computing framework, to aid both organisations of the public sector which deal with active life cycle document phases and archives and libraries which deal with passive phases of documents and records.

The paper addresses the difficulties of digital preservation implementation in the public administration sector. The findings indicate that while developing and implementing digital preservation, the public administration sector should formulate common policies and solutions based on the suggested results of this paper and, in doing so, maximise the benefits of current technologies.

The purpose of this paper is to examine the characteristics of managing records in a cloud computing environment and compare these with existing archiving models, exemplified by the open archival information system (OAIS) reference model.

The authors compare the functional entities in OAIS with a layered model of cloud computing, in which services are abstracted and shared between layers.

It is concluded that there are a number of areas where OAIS does not integrate well with cloud computing systems. Based on the findings, a new layered model for a cloud archiving system is defined using the concepts and information types from the OAIS reference model. The proposed model allows the sharing of functionality and information objects by making them available as services to higher layers. The model covers the entire document lifecycle, making archive functionality such as preservation planning possible at an early stage and helping to simplify records transfer.

The model provides a simple, OAIS compatible approach to representing how digital objects and necessary metadata can be transferred from content creation systems to archives systems.

Whereas a lot of research has been done on the technical aspects of cloud storage, there is a lack of focus on how to comprehensively integrate records transfer and preservation in cloud systems. This paper fills in some of the gaps.

The purpose of this paper is to propose a concept of cloud auction robot (CAR) and its execution platform for transforming perishable food supply chain management. A new paradigm of goods-to-person auction execution model is proposed based on CARs. This paradigm can shift the management of traditional manual working to automated execution with great space and time saving. A scalable CAR-enabled execution system (CARES) is presented to manage logistics workflows, tasks and behavior of CAR-Agents in handling the real-time events and associated data.

An Internet of Things enabled auction environment is designed. The robot is used to pick up and deliver the auction products and commends are given to the robot in real-time. CARES architecture is proposed while integrating three core services from auction workflow management, auction task management, to auction execution control. A system prototype was developed to show its execution through physical emulations and experiments.

The CARES could well schedule the tasks for each robot to minimize their waiting time. The total execution time is reduced by 33 percent on average. Space utilization for each auction studio is improved by about 50 percent per day.

The CAR-enabled execution model and system is simulated and verified in a ubiquitous auction environment so as to upgrade the perishable food supply chain management into a new level which is automated and real-time. The proposed system is flexible to cope with different auction scenarios, such as different auction mechanisms and processes, with high reconfigurability and scalability.

The below-average innovative capacity of the tourism sector raises the question on the potentials of digital business ecosystems (DBEs) to overcome these shortages at a destination level – especially within a smart city environment. Using the example of the German Capital Berlin, this article aims to discuss both the possibilities and inhibitors of innovative knowledge-creation by building scenarios on one specific design option: the integration of digital deep learning (DL) functionalities and traditional organizational learning (OL) processes.

Using the qualitative GABEK-method, major characteristics of a DBE as resource-, platform- and innovation systems are analyzed toward their interactions with the construction of basic action models (as the basic building blocks of knowledge).

Against the background of the research findings, two scenarios are discussed for future evolution of the Berlin DBE, one building on cultural emulation as a trigger for optimized DL functionalities and one following the idea of cultural engineering supported by DL functionalities. Both scenarios focus specifically on the identified systemic inhibitors of innovative capabilities.

While this study highlights the potential of the GABEK method to analyze mental models, separation of explicit and latent models still remains challenging – so does the reconstruction of higher order mental models which require a combined take on interview techniques in the future.

The resulting scenarios innovatively combine concepts from OL theory with the concept of DBE, thus indicating possible pathways into a tourism future where the limitations of human learning capacities could be compensated through the targeted support of general artificial intelligence (AI).