Collaborative Object Research Articles

Clients and carers: Healthcare professionals’ roles in medical device development processes in SMEs

Purpose of the article With the call for patient-centred healthcare, designers and healthcare professionals collaborate increasingly, as both health and design researchers advocate closer engagement between the two. Yet the existing literature is scarce in describing the actual roles taken up by healthcare professionals in these collaborations. Addressing this gap, this article investigates the participation of healthcare professionals in medical device development in SMEs. Materials and methods The research context is Ankara, Turkey, where most design and development activities in medical sector are geared towards export substitution, undertaken with limited resources. The analysis is based on data gathered through semi-structured interviews with 32 professionals, including design professionals, managers, physiotherapists and engineers involved in the design of around 25 medical devices. Results and conclusion This article identifies four main roles that healthcare professionals take in medical device development: business partners, expert users, mediators, and medical professionals. These roles entail diverse responsibilities with various objects of collaboration with designers, making significant contributions to medical design.

Semi-decentralized Lyapunov-based formation control of multiple omnidirectional mobile robots

<p>This paper introduces an advanced formation control algorithm based on a Lyapunov approach for coordinating multiple omnidirectional mobile robots in collaborative object transport tasks. The semi-decentralized strategy ensures that the robots maintain a predefined geometric formation, crucial for stability during material transportation, and dynamically adapt to avoid collisions using onboard sensors. Experimental with a physical robot simulator demonstrates successful maintenance of line and triangle formations achieving an average side length maintenance of 1.00 meters with minimal deviation. Quantitative analysis across 30 experimental runs reveals consistent performance, with a maximum side length fluctuation of only 2 centimeters, validating the effectiveness of maintaining formation within a multi-robot system (MRS) framework. The Lyapunov-based approach proves to be an efficient method for cooperative object transport, achieving consistent performance with minimal deviation.</p>

Static Task Allocation Method for Multi-Machines in Cooperative Operations Combining OGFR-GA and MLW-Prim

Aiming at the operational efficiency of small farm machinery groups in cooperative operations in hilly areas, this study proposes a static task allocation model. This method combines the optimal gene fragment retention method based on a genetic algorithm (OGFR-GA) and the method for generating multi-loop weighted connected graphs based on Prim’s algorithm (MLW-Prim). The collaborative objective function for the harvester group was established by considering factors such as operation time, fuel consumption, and distance. The OGFR-GA was designed and applied multiple times to obtain several optimal gene fragments corresponding to the number of farm machines. These fragments were used as critical paths in the weighted connected graph generated based on farm machinery performance parameters and task parameters. The MLW-Prim method was proposed to construct this weighted connected graph and realize the static task allocation model for multi-machine cooperative operations. Simulation experiments showed that the model combining OGFR-GA and MLW-Prim achieved optimal values with fewer iterations, and reduced both group cost and cost variance compared to traditional algorithms. This method meets the static task allocation needs for multi-machine cooperative operations in agricultural production and can be integrated with intelligent operations in mountainous and hilly regions, laying a theoretical foundation for improving efficiency.

LJCD-Net: Cross-Domain Jamming Generalization Diagnostic Network Based on Deep Adversarial Transfer.

Global Navigation Satellite Systems (GNSS) offer comprehensive position, navigation, and timing (PNT) estimates worldwide. Given the growing demand for reliable location awareness in both indoor and outdoor contexts, the advent of fifth-generation mobile communication technology (5G) has enabled expansive coverage and precise positioning services. However, the power received by the signal of interest (SOI) at terminals is notably low. This can lead to significant jamming, whether intentional or unintentional, which can adversely affect positioning receivers. The diagnosis of jamming types, such as classification, assists receivers in spectrum sensing and choosing effective mitigation strategies. Traditional jamming diagnosis methodologies predominantly depend on the expertise of classification experts, often demonstrating a lack of adaptability for diverse tasks. Recently, researchers have begun utilizing convolutional neural networks to re-conceptualize a jamming diagnosis as an image classification issue, thereby augmenting recognition performance. However, in real-world scenarios, the assumptions of independent and homogeneous distributions are frequently violated. This discrepancy between the source and target distributions frequently leads to subpar model performance on the test set or an inability to procure usable evaluation samples during training. In this paper, we introduce LJCD-Net, a deep adversarial migration-based cross-domain jamming generalization diagnostic network. LJCD-Net capitalizes on a fully labeled source domain and multiple unlabeled auxiliary domains to generate shared feature representations with generalization capabilities. Initially, our paper proposes an uncertainty-guided auxiliary domain labeling weighting strategy, which estimates the multi-domain sample uncertainty to re-weight the classification loss and specify the gradient optimization direction. Subsequently, from a probabilistic distribution standpoint, the spatial constraint imposed on the cross-domain global jamming time-frequency feature distribution facilitates the optimization of collaborative objectives. These objectives include minimizing both the source domain classification loss and auxiliary domain classification loss, as well as optimizing the inter-domain marginal probability and conditional probability distribution. Experimental results demonstrate that LJCD-Net enhances the recognition accuracy and confidence compared to five other diagnostic methods.

Community-driven design: Collaborative objects, community-generated content, and the expanded role of architects

This article explores the intersection of digital architecture, collaborative creativity, and community engagement through our conceptual framework of Collaborative Objects. By enabling a shift from user-generated content to community-generated content in architecture, this new approach promotes democratic design processes. Practical illustrations are provided through a series of public case studies—H = N Co-Doodle, H = N BLOCK, and Meta Block Linz—highlighting the versatility of the Collaborative Objects framework embedded within expanded software applications. These studies address the formal and informal consequences, opportunities, and challenges of transforming static design elements into dynamic, community driven narratives. While recognizing the challenges inherent in this paradigm shift, the article concludes by emphasizing the compelling potential for more shared, inclusive, and community-oriented design processes in the architectural field.

Hydrogels for ameliorating osteoarthritis: Mechanical modulation, anti‐inflammation, and regeneration

AbstractOsteoarthritis (OA) is a chronic and degenerative disease with limited clinical options for effective suppression. Recently, significant endeavors have been explored to reveal its pathogenesis and develop treatments against OA. Hydrogels, designed with a striking resemblance to the extracellular matrix, offer a biomimetic interaction with biological tissues, presenting a promising avenue for OA amelioration. As a result, biocompatible hydrogels have been erected incorporating on‐demand bioactivities to optimize the intra‐articular microenvironment, thereby alleviating OA symptoms and fostering the eventual regeneration of articular joints. This review highlights the collaborative objectives underlying the establishment of this tissue microenvironment, encompassing mechanical modulation, anti‐inflammation, and tissue regeneration. Specifically, we consolidate recent advances in hydrogel‐based biomaterials, serving as the tissue engineering scaffolds to replicate the lubrication properties of natural joints or the bioactive agent‐loaded vehicles to combat localized inflammation. Additionally, hydrogels function as cell scaffolds to facilitate the maintenance of cellular homeostasis and contribute to the advancement of cartilage regeneration. Finally, this review outlines the prospective directions for hydrogel‐mediated OA therapies.

A Distributed Optimization Approach for Collaborative Object Lifting Using Multiple Aerial Robots

In the past decade, multi-robot collaborative object transport has garnered significant attention, with the majority of research targeting transport strategies. This study recasts the collaborative object lifting challenge into an optimization problem framework. Within this setup, each robot leverages a local evaluation function to determine its lifting location. Collectively, these robots strive to optimize a unified evaluation function. An intertwined equation constraint is embedded within the optimization schema, ensuring that the system’s mass center remains stable throughout the lifting process. Furthermore, we impose local feasibility constraints, thereby delimiting the optimal lifting location to a specified region. This research introduces several algorithms, differentiated based on the constraints applied to robot velocity. By harnessing these algorithms, robots can autonomously pinpoint the most apt lifting location that aligns with predetermined criteria. This methodology necessitates a robot to engage in exchanges of auxiliary variables solely with its immediate peers. Noteworthily, parameters such as location, velocity, and mass are accessed in a localized manner, reinforcing data privacy and reducing communication burdens. The paper concludes with a robust mathematical validation that underscores asymptotic convergence to the exact optimal lifting location, underpinned by numerical simulations which attest to the potency of the proposed algorithms.

The Virtual Research Environment: A multi-science analysis platform

One of the objectives of the ESCAPE collaboration, within the context of the implementation of the European Open Science Cloud, is integrating analysis workflows from Cosmology, Astrophysics and High Energy Physics into a common framework, making it easier for researchers to share data, software and analysis code. The development of the ESCAPE Science Projects (Dark Matter and Extreme Universe) relies on the implementation of the Virtual Research Environment, a prototype analysis platform deployed in the respect of FAIR data principles. The Virtual Research Environment’s main components are (1) an Authentication and Authorization layer, (2) a federated distributed storage solution, providing functionalities for data injection and replication through a Data Management and Orchestration software, (3) an interactive notebook interface that hides the complexity of the underlying infrastructure and facilitates browsing data catalogues and (4) computing processing power to run full end-to-end analyses through workflow schedulers and resource managers that also allow for pipelines’ preservation. This contribution will depict the collection of services and technologies that compose the Virtual Research Environment, hosted on a cloud infrastructure and managed by an open source, publicly available repository.

Objectives of University Industry Collaboration in Nepal: Observation of Students, Professors and Industrial Leaders

The collaborative relationship between university and industry is becoming crucial research phenomena for professors, students, industrial leaders, government and the general public in the advanced developing as well as underdeveloped economies. It has become more imperative to the management schools and institutes and research centers. In the prevailing knowledge economy universities are called to produce innovative and creative manpower ready to job in the organizations. This research was conducted in Nepalese business management schools operating under the three leading universities, namely Tribhuvan University, Pokhara University and Kathmandu University. Apart from the students and professors, the perception of business community leaders also has been included in regard to attainability of the objectives of university industry collaboration in Nepal. The objective of the study was to find the perception of students, course facilitators and industrial leaders about the level of attainability of the stated objective of UIC. With some differences all respondentsfound the objectives of UIC are attainable in Nepal. Such kind of research is important to the universities, especially business management educators, the industries and the government to frame education policy and curriculum.

Trust and Objects: Trust Building Capacities of Objects in Interorganizational Collaboration

Research has paid attention to individual dispositions of trust and the interpersonal trust relations among boundary spanners leaving little attention to objects in relation to trust building in interorganizational collaboration processes. This study explores the dynamic relation between trust and objects in interorganizational collaboration. A longitudinal study of an innovative tele-home monitoring service involving health professionals from hospitals, municipalities, and general practice clinics forms the empirical context for this study.
 This study demonstrates that trust is not alone a human feature but also a dimension of objects since objects mediate and build trust among actors by creating a focused communication and shared knowledge, improving predictalibility and transparency in behavior and decision-making, and creating visibility about work contexts and tasks. In the context of this paper these three features denote objects’ trust building capacities which support shared problem-solving and collaboration. The study, however, also show a flipside of objects where they may create mistrust and thereby act as barriers for collaboration. Overall, these insights contribute to the literature about trust in interorganizational collaboration processes by foregrounding the role of objects in trust building processes and exploring their trust building capacities.

The Role of Object Physical Properties in Human Handover Actions: Applications in Robotics

Observing how humans interact with each other and how they manipulate objects, offer insight on interaction mechanisms and how these are influenced by the physical properties of the used objects. These insights can support a more informed design of robot controllers meant to manipulate objects in collaboration with humans. In this work we study human-to-human handovers of cups filled with various amount of liquid and textures, and investigate to which extent the manipulation strategy depends on: (i) the individual preference, (ii) whether the cup is filled with water or not, and (iii) the cup physical properties. An analysis of the human giver’s hand acceleration, velocity, and position during the handover of different cups under two liquid level conditions, allows to distinguish between careful and not-careful (normal) manipulation. We quantify to which extent the liquid level inside the cups influences the carefulness level of human manipulation. Lastly, our study reveals that the cups’ physical properties, such as fragility, breakability, and deformability, play a role in shaping the carefulness of the manipulation. We apply these findings to human-robot scenarios by developing a robot controller capable of detecting, in real-time, if the human is being more careful than normal, and adapting the robot’s approach of interaction accordingly. Additionally, we show that the detection of a careful manipulation, depending on the experimental context, may provide the robot with information concerning the human partner’s intention or need for (manipulation) assistance.

Satellite–Terrestrial Collaborative Object Detection via Task-Inspired Framework

Recently, buoyed by advances in the space industry, low Earth orbit (LEO) satellites have become an important part of the Internet of Things (IoT). LEO satellites have entered the era of a big data link with IoT, how to deal with the data from the satellite IoT is a problem worthy of consideration. Conventional object detection method in optical remote sensing simply transmits the raw data to the ground. However, it ignores the properties of the images and the connection with the downstream task. To obtain efficient data transmission and accurate object detection, we propose a task-inspired satellite-terrestrial collaborative object detection framework called STCOD. It detects regions of interest (ROIs) and adopts a block-based adaptive sampling method to compress the background (BG) in optical remote sensing images by introducing satellite edge computing (SEC) on satellites. The STCOD framework also sets the transmission priority of image blocks according to their contributions to the task and uses fountain code to ensure the reliable transmission of important image blocks. We build a whole software simulation framework to validate our method, including the satellite module, the transmission module, and the terrestrial module. Extensive experimental results show that the STCOD framework can reduce the amount of downlink data decreased by 50.04% while losing the detection accuracy by 0.54%. In our simulated satellite-terrestrial link, the STCOD framework can reduce the number of satellite-to-terrestrial transmissions by half. When the packet loss rate is between 5% and 20%, the detection accuracy is lost only 0.05% to 0.5%.

Trimmed helicoids: an architectured soft structure yielding soft robots with high precision, large workspace, and compliant interactions

The development and use of architectured structures is changing the means by which we design and fabricate soft robots. These materials utilize their topology and geometry to control physical and mechanical structural properties. We propose an architectured structure based on trimmed helicoids that allows for independent regulation of the bending and axial stiffness which facilitates tuneability of the resulting soft robot properties. Leveraging FEA and computational analysis we select a geometry that provides an optimal trade-off between controllability, sensitivity to errors in control, and compliance. By combining these modular trimmed helicoid structures in conjunction with control methods, we demonstrate a meter-scale soft manipulator that shows control precision, large workspace, and compliant interactions with the environment. These properties enable the robot to perform complex tasks that leverage robot-human and robot-environment interactions such as human feeding and collaborative object manipulation.

Distinguishing collaboration from related elements of crime

The article is devoted to the distinction between the corpus delicti of crimes under Article 111-1 of the Criminal Code of Ukraine “Collaboration” and related crimes. Scientific articles by researchers who studied who have studied the objective and subjective features of collaboration have been analysed. It is stated that collaboration differs from high treason by the nature of the acts constituting the objective element of the crime, the time of the crime and the subject of the crime. The collaboration is distinguished from aiding and abetting the aggressor State by the subject of collaboration.The set of actions that make up the objective side of the specified crimes also has differences. The difference between the creation of illegal paramilitary formations and collaborative activities lies in the object of the crime. In addition, the crime provided for in Part 7 of Article 111-1 of the Criminal Code of Ukraine is committed in the conditions of the Ukrainian territory occupation as a result of the invasion of the aggressor state troops. The collaborative activity must be distinguished from the crime provided for in Article 436-2 of the Criminal Code of Ukraine “Justification, recognition as legitimate, denial of the armed aggression of the russian federation against Ukraine, glorification of its participants”. The differences are in the object of the crime. In addition, collaboration can only be carried out in the occupied territory.It is proposed to make changes to the Criminal Code of Ukraine. In particular, it is proposed to define the concept of subversive activity, which is used in Article 111 of the Criminal Code of Ukraine. It is necessary to specify the list of actions that can be considered as assisting the enemy in subversive activities. Establish clear distinctions between collaborative activities and assisting the enemy in subversive activities. It is necessary to solve other problematic issues of qualification of violations of the legislation of Ukraine under Article 111-1 of the Criminal Code of Ukraine or other articles of the Code containing similar offenses.

Research on the collaborative evolution process of information in public health emergencies based on complex adaptive system theory and social network analysis: a case study of the COVID-19 pandemic.

This review aimed to elucidate the significance of information collaboration in the prevention and control of public health emergencies, and its evolutionary pathway guided by the theory of complex adaptive systems. The study employed time-slicing techniques and social network analysis to translate the dynamic evolution of information collaboration into a stage-based static representation. Data were collected from January to April 2020, focusing on the COVID-19 pandemic. Python was used to amass data from diverse sources including government portals, public commentary, social organizations, market updates, and healthcare institutions. Post data collection, the structures, collaboration objectives, and participating entities within each time slice were explored using social network analysis. The findings suggest that the law of evolution for information collaboration in public health emergencies primarily starts with small-scale collaboration, grows to full-scale in the middle phase, and then reverts to small-scale in the final phase. The network's complexity increases initially and then gradually decreases, mirroring changes in collaboration tasks, objectives, and strategies. The dynamic pattern of information collaboration highlighted in this study offers valuable insights for enhancing emergency management capabilities. Recognizing the evolving nature of information collaboration can significantly improve information processing efficiency during public health crises.

Manipulation Guidance Field for Collaborative Object Manipulation in VR

Object manipulation is a fundamental interaction in virtual reality (VR). Efficient and accurate manipulation is important for many VR applications, especially collaborative VR applications. We introduce a collaborative method based on the manipulation guidance field (MGF) to improve manipulation accuracy and efficiency. MGF aims to guide users of different manipulation types to different manipulation viewpoints to efficiently and collaboratively manipulate objects. First, we introduce the concept of MGF and its construction method. Two strategies are offered to accelerate the MGF updating process. A collaborative manipulation method to manipulate objects using the guidance of MGF is then proposed. Finally, a user study (n = 36 participants) was conducted to evaluate the efficiency and accuracy of our MGF-based collaborative object manipulation method in three scenes: (1) Livingroom scene; (2) WaveHouse scene; (3) Pipe scene. Compared to a control method without MGF, the results show that our MGF-based method has significantly reduced task completion time, position error, rotation error, and task load.

Collaborative Governance Dalam Memajukan Kebudayaan Bali Melalui Pola Pembangunan Semesta Berencana Menuju Bali Era Baru di Kota Denpasar

ABSTRACT
 The strengthening and promotion of Balinese Culture in the City of Denpasar is manifested in the form of policies to achieve the goals set through the Regional Development Vision of Bali Nangun Sat Kerthi Loka Bali which is realized by creating a collaborative governance. The collaboration that took place to achieve this goal was carried out by several collaborators, namely from the government sector (Denpasar City Culture Office, Denpasar City Tourism Office, and Denpasar City Traditional Village Council); private sector (Naluri Manca); and community owners of MSMEs in Denpasar City. By carrying out good collaboration management, the objectives of the related collaboration above are expected to be able to create strengthening and promotion of culture in the city of Denpasar itself. This study aims to find out how the implementation of collaborative governance in advancing Balinese culture in the city of Denpasar. This research uses descriptive qualitative method with data collection techniques in the form of observation, interviews, and documentation. The results of this study indicate that collaborative governance that is running in advancing Balinese culture in the city of Denpasar is still not maximal in fulfilling the indicators or criteria for the success of a collaboration. This can be seen from the eight indicators used, only four indicators are able to be fulfilled by the ongoing collaboration, where this collaboration has not been able to meet the indicators of network structure, governance, trust among the participants, and access to resources. 

The Small Tourism Enterprise Operators’ Networking in Dealing with the Changing Business Environment

The entrepreneur’s ability to networking is particularly critical when dealing with business turbulence, such as that affected by the COVID-19 pandemic. This study aims to analyze the STE operators manage their networks during the changing business environment affected by earthquake and COVID-19 pandemic in Lombok. Data was collected from twenty-one tourism entrepreneurs through semi-structured observations and interviews, and analyzed using content analysis. The study identifies three categories: parties involved in the network (tourism managers, tourism authorities, transport operators, destination communities, and tourists), linking methods (management network approach) and collaboration objectives (management network objectives). After the earthquake (when business turbulence was still not so intense), STE managers used direct physical contact, social media, and online partners to expand their networks, developing more cooperation (rather than collaboration) to create social exchange benefits. During the COVID-19 pandemic (when business turbulence was more intense), STE managers increased their use of social media to deepen their networks and focused on developing collaborations with a limited number of partners to reap the benefits of economic exchange. This study recommends local government intervention in improving the ability of STE management networks and building online-based networks.

Game—FloraPark (the Flower Game): A Supply Chain Contract and Collaboration Simulation

Intensive competition among supply chains often forces trading partners to collaborate despite their conflict of interests. Supply chain contracts and collaboration theory is well established in the academic literature to align the interests but much less conveyed to students and industry professionals for a practical impact. Although the Beer Game captures the bullwhip effect and the value of information sharing, it ignores the conflict of interests, that is, price and quantity bargaining, among the trading partners. We describe a new online teaching game, the FloraPark simulation (“the flower game” at https://flower.gamespots.net/ ), based on real-life events in the international fresh-cut flower supply chains, for students to learn supply chain collaboration via contracts in a setting of multiple supply chains competing in the same market. Students play trading partners in the flower supply chains and experiment with the push, pull, and advanced purchasing discount contracts by negotiating wholesale prices and quantities to achieve the conflicting objectives of (1) collaboration to beat other supply chains, and (2) bargaining to protect their own interests from their trading partners. Supplemental Material: The e-companion is available at https://doi.org/10.1287/ited.2022.0035 .

Objects of Collaboration: Roles and Sequences of Objects in Spanning Knowledge Group Boundaries in Design

AbstractSpanning knowledge group boundaries is both a source of and barrier to design performance and innovation. Objects—from prototypes to kanban boards—are frequently used in cross-functional design practice, but their associated outcomes appear varied and dependent not only on the objects themselves but on how, when, and by whom they are used. We conducted a two-year ethnography within a turbomachinery design company to understand how professional engineering designers span knowledge group boundaries to advance their designs and design processes. Our findings identify three roles of objects of collaboration: routinizing cross-boundary interaction, translating information across boundaries, and motivating joint negotiation or discovery. We illustrate two prominent outcomes—the co-discovery of a design risk, opportunity, or bottleneck and the co-design of a joint integrated solution—and describe two object role sequences from which these outcomes seem to follow. These findings are significant because they suggest ways for designers to effectively use objects to span knowledge group boundaries.