A New Encryption Mechanism Supporting the Update of Encrypted Data for Secure and Efficient Collaboration in the Cloud Environment

With the rise of remote collaboration,the demand for advanced storage and collaboration tools has rapidly increased.However,traditional collaboration tools primarily rely on access control,leaving data stored on cloud servers vulnerable due to insufficient encryption.This paper introduces a novel mechanism that encrypts data in‘bundle’units,designed to meet the dual requirements of efficiency and security for frequently updated collaborative data.Each bundle includes updated information,allowing only the updated portions to be reencrypted when changes occur.The encryption method proposed in this paper addresses the inefficiencies of traditional encryption modes,such as Cipher Block Chaining(CBC)and Counter(CTR),which require decrypting and re-encrypting the entire dataset whenever updates occur.The proposed method leverages update-specific information embedded within data bundles and metadata that maps the relationship between these bundles and the plaintext data.By utilizing this information,the method accurately identifies the modified portions and applies algorithms to selectively re-encrypt only those sections.This approach significantly enhances the efficiency of data updates while maintaining high performance,particularly in large-scale data environments.To validate this approach,we conducted experiments measuring execution time as both the size of the modified data and the total dataset size varied.Results show that the proposed method significantly outperforms CBC and CTR modes in execution speed,with greater performance gains as data size increases.Additionally,our security evaluation confirms that this method provides robust protection against both passive and active attacks.

Stony Brook’s High-Pressure Laboratory Collaborations with French Scientists

For more than a half century, my colleagues and I in the Stony Brook High Pressure Laboratory have profited from collaborations with French scientists in their laboratories in Orsay, Paris, Toulouse, Lille, Lyon, Strasbourg and Rennes. These interactions have included postdoctoral appointments of French colleagues in our laboratory as well as two année sabbatique by me;in 1983-84, in the Laboratoire de Géophysique et Géodynamique Interne at the Université Paris XI in Orsay and in 2020-2003 in the Laboratoire des Méchanismes et Transfert en Géologie at the Université Paul Sabatier in Toulouse. The objective of this report is to relate this history and to illustrate the scientific advances which resulted from these collaborations.

Data Cleaning Based on Stacked Denoising Autoencoders and Multi-Sensor Collaborations

Wireless sensor networks are increasingly used in sensitive event monitoring.However,various abnormal data generated by sensors greatly decrease the accuracy of the event detection.Although many methods have been proposed to deal with the abnormal data,they generally detect and/or repair all abnormal data without further differentiate.Actually,besides the abnormal data caused by events,it is well known that sensor nodes prone to generate abnormal data due to factors such as sensor hardware drawbacks and random effects of external sources.Dealing with all abnormal data without differentiate will result in false detection or missed detection of the events.In this paper,we propose a data cleaning approach based on Stacked Denoising Autoencoders(SDAE)and multi-sensor collaborations.We detect all abnormal data by SDAE,then differentiate the abnormal data by multi-sensor collaborations.The abnormal data caused by events are unchanged,while the abnormal data caused by other factors are repaired.Real data based simulations show the efficiency of the proposed approach.

Empowering digital twins with eXtended reality collaborations

Background The advancements of Artificial Intelligence,Big Data Analytics,and the Internet of Things paved the path to the emergence and use of Digital Twins(DTs)as technologies to“twin”the life of a physical entity in different fields,ranging from industry to healthcare.At the same time,the advent of eXtended Reality(XR)in industrial and consumer electronics has provided novel paradigms that may be put to good use to visualize and interact with DTs.XR technologies can support human-to-human interactions for training and remote assistance and could transform DTs into collaborative intelligence tools.Methods We here present the Human Collaborative Intelligence empowered Digital Twin framework(HCLINT-DT)integrating human annotations(e.g.,textual and vocal)to allow the creation of an all-in-one-place resource to preserve such knowledge.This framework could be adopted in many fields,supporting users to learn how to carry out an unknown process or explore others’past experiences.Results The assessment of such a framework has involved implementing a DT supporting human annotations,reflected in both the physical world(Augmented Reality)and the virtual one(Virtual Reality).Con-clusions The outcomes of the interface design assessment confirm the interest in developing HCLINT-DT-based applications.Finally,we evaluated how the proposed framework could be translated into a manufacturing context.

Groundwater status and associated issues in the Mekong-Lancang River Basin： International collaborations to achieve sustainable groundwater resources

Groundwater is an important and readily available source of fresh water in the Mekong-Lancang River Basin. With a rapid population growth and increasing human activities, an increasing number of countries in the Mekong-Lancang River Basin are experiencing depleted and degraded groundwater supplies. In transboundary river basins, such as the Mekong-Lancang River, prioritizing the use of the shared aquifer by one riparian government may affect the opportunities of other riparian governments and lead to potential water conflicts between neighboring countries. To promote the sharing of strategies and information for the sustainable and equitable use of water resources of the shared basin, international collaborative workshops on groundwater resources have been organized for all Mekong-Lancang River countries. These workshops provide an opportunity to communicate and discuss nationally sensitive issues on groundwater by the associated countries, with topics covering multiple aspects of groundwater, such as the groundwater status in the basin, quality issues, water use conflicts, hydrological information gaps, management policies and capacity building for successful water resource management. Consensus has been reached by all countries on the importance of catchment-based groundwater management and the need for close communication among the countries. Strategies for managing transboundary aquifer issues must foster international collaboration based on the regional network, influence national networks and enhance the capacity to building maps and monitoring systems based on associated databases. The sustainability of water resources cannot be achieved without the integrated involvement and contributions by multiple countries and various stakeholders. Therefore, collaborative workshops provide a great opportunity to further our understanding of the hydrologic processes of the Mekong River Basin, share the benefits of the aquifer and provide a strategy and vision for sustainable water resource management in the Mekong-Lancang River countries.

Air-Ground Collaborative Mobile Edge Computing:Architecture,Challenges,and Opportunities

By pushing computation,cache,and network control to the edge,mobile edge computing(MEC)is expected to play a leading role in fifth generation(5G)and future sixth generation(6G).Nevertheless,facing ubiquitous fast-growing computational demands,it is impossible for a single MEC paradigm to effectively support high-quality intelligent services at end user equipments(UEs).To address this issue,we propose an air-ground collaborative MEC(AGCMEC)architecture in this article.The proposed AGCMEC integrates all potentially available MEC servers within air and ground in the envisioned 6G,by a variety of collaborative ways to provide computation services at their best for UEs.Firstly,we introduce the AGC-MEC architecture and elaborate three typical use cases.Then,we discuss four main challenges in the AGC-MEC as well as their potential solutions.Next,we conduct a case study of collaborative service placement for AGC-MEC to validate the effectiveness of the proposed collaborative service placement strategy.Finally,we highlight several potential research directions of the AGC-MEC.

Joint Task Allocation and Resource Optimization for Blockchain Enabled Collaborative Edge Computing

Collaborative edge computing is a promising direction to handle the computation intensive tasks in B5G wireless networks.However,edge computing servers(ECSs)from different operators may not trust each other,and thus the incentives for collaboration cannot be guaranteed.In this paper,we propose a consortium blockchain enabled collaborative edge computing framework,where users can offload computing tasks to ECSs from different operators.To minimize the total delay of users,we formulate a joint task offloading and resource optimization problem,under the constraint of the computing capability of each ECS.We apply the Tammer decomposition method and heuristic optimization algorithms to obtain the optimal solution.Finally,we propose a reputation based node selection approach to facilitate the consensus process,and also consider a completion time based primary node selection to avoid monopolization of certain edge node and enhance the security of the blockchain.Simulation results validate the effectiveness of the proposed algorithm,and the total delay can be reduced by up to 40%compared with the non-cooperative case.

Collaborative positioning for swarms:A brief survey of vision,LiDAR and wireless sensors based methods

As positioning sensors,edge computation power,and communication technologies continue to develop,a moving agent can now sense its surroundings and communicate with other agents.By receiving spatial information from both its environment and other agents,an agent can use various methods and sensor types to localize itself.With its high flexibility and robustness,collaborative positioning has become a widely used method in both military and civilian applications.This paper introduces the basic fundamental concepts and applications of collaborative positioning,and reviews recent progress in the field based on camera,LiDAR(Light Detection and Ranging),wireless sensor,and their integration.The paper compares the current methods with respect to their sensor type,summarizes their main paradigms,and analyzes their evaluation experiments.Finally,the paper discusses the main challenges and open issues that require further research.

Multi-Robot Collaborative Hunting in Cluttered Environments With Obstacle-Avoiding Voronoi Cells

This work proposes an online collaborative hunting strategy for multi-robot systems based on obstacle-avoiding Voronoi cells in a complex dynamic environment. This involves firstly designing the construction method using a support vector machine(SVM) based on the definition of buffered Voronoi cells(BVCs). Based on the safe collision-free region of the robots, the boundary weights between the robots and the obstacles are dynamically updated such that the robots are tangent to the buffered Voronoi safety areas without intersecting with the obstacles. Then, the robots are controlled to move within their own buffered Voronoi safety area to achieve collision-avoidance with other robots and obstacles. The next step involves proposing a hunting method that optimizes collaboration between the pursuers and evaders. Some hunting points are generated and distributed evenly around a circle. Next, the pursuers are assigned to match the optimal points based on the Hungarian algorithm.Then, a hunting controller is designed to improve the containment capability and minimize containment time based on collision risk. Finally, simulation results have demonstrated that the proposed cooperative hunting method is more competitive in terms of time and travel distance.

Robust and Trustworthy Data Sharing Framework Leveraging On-Chain and Off-Chain Collaboration

The proliferation of Internet of Things(IoT)systems has resulted in the generation of substantial data,presenting new challenges in reliable storage and trustworthy sharing.Conventional distributed storage systems are hindered by centralized management and lack traceability,while blockchain systems are limited by low capacity and high latency.To address these challenges,the present study investigates the reliable storage and trustworthy sharing of IoT data,and presents a novel system architecture that integrates on-chain and off-chain data manage systems.This architecture,integrating blockchain and distributed storage technologies,provides high-capacity,high-performance,traceable,and verifiable data storage and access.The on-chain system,built on Hyperledger Fabric,manages metadata,verification data,and permission information of the raw data.The off-chain system,implemented using IPFS Cluster,ensures the reliable storage and efficient access to massive files.A collaborative storage server is designed to integrate on-chain and off-chain operation interfaces,facilitating comprehensive data operations.We provide a unified access interface for user-friendly system interaction.Extensive testing validates the system’s reliability and stable performance.The proposed approach significantly enhances storage capacity compared to standalone blockchain systems.Rigorous reliability tests consistently yield positive outcomes.With average upload and download throughputs of roughly 20 and 30 MB/s,respectively,the system’s throughput surpasses the blockchain system by a factor of 4 to 18.

Informationist roles and collaborations in curriculum innovation at the University of Michigan＇s A.Alfred Taubman Health Sciences Library

To address the ultimate mission to be ＂ a valued partner,fully integrated into the work of the university and providing leadership in knowledge management for education, research, patient care, and community outreach＂,the University of Michigan A. Alfred Taubman Health Sciences Library(THL） has transformed from retitling librarians as informationists to shifting from a service to a collaboration focus. Infomationists at THL have spent several years building relationships and expertise to be true partners in curriculum integration and innovation within the health sciences schools and colleges at the University of Michigan and the curricular integration has becoming a constantly evolving process for THL informationists. Current article focus on how THL convert the librarian into informationist and how to make collaborations in curriculum innovation within different departments to furtherly improve the status of THL library in the University.

Multi-Stakeholder Business Models： Designing Out Wicked Problems

The paper is a part of an ongoing study, labelled as ＂Designing out wicked problems＂ - a design science research （DSR） study with the purpose of developing, implementing, and evaluating a methodology framework for designing multi-stakeholder business models. The objective of the current paper is to evaluate the business model design framework within a DSR framework. The research is conducted as three-year case study at three sites： The Danish police, with a key player in the Danish energy sector, and the municipality of the Danish capital, Copenhagen. The research method is action research, with a structure of planning-action-evaluation process conducted with the case owners - as well as design science methodology, where an artifact （the multi-stakeholder business model design concept） is created, evaluated and altered to improve its functionality. The finding of this study is that the maturity of the application domain - the type of problem the concept is trying to solve - as well as of the concept itself, is low. The conclusion is thus that the knowledge contribution of the study is of a unique invention character which will lay the foundation for further evaluation and research.

Analysis of Collaborations Between Small-Medium Companies and Universities Based on Joint Research Projects

University-industry collaborations have been recognized as an important factor for the creation of innovation. Although the university-industry collaborations have been mainly conducted by large companies in Japan so far, the small-medium companies rather than large companies are accumulated in regional areas. However, there are a lot of problems in the university-industry collaborations of the small-medium companies. In this paper, the collaborations between small-medium companies and universities are analyzed based on joint research projects. The results show that the joint research projects of small-medium companies for collaboration partners are not conducted enough. Moreover, the results also show that the average budget per project of small-medium companies is low according to the detailed data of Niigata University. The active area of company and university in research and development is discussed. The stage map that proceeds to commercialization for the collaborations between small-medium companies and universities is made and discussed. Based on these results, the problems of the university-industry collaborations of small-medium companies for collaboration partners are extracted.

International Collaborations In Geodesy Advance Geoscience Research

UNAVCO supports geoscience research at 113 US academic Member institutions,and another 104 Associate Member institutions include international universities,laboratories,observatories,academies of science,and a museum.This diverse membership shares UNAVCO’s purpose at home and abroad,giving UNAVCO global reach in advancing geodesy.Since the mid-1980s,modern geodesy has evolved into a cutting-edge,multi-faceted toolbox with remarkably diverse research and real-world applications,including studies and observation or forecasting of solid-Earth hazards,the dynamics of the atmosphere,climate,near-Earth space environment,and of key environmental parameters such as water storage,soil moisture,and seaand lake-level changes.UNAVCO operates facilities on behalf of the U.S.National Science Foundation to support investigators who use geodetic tools across all of these Earth and atmospheric domains.UNAVCO has built a number of large dense regional networks of GPS stations,including the Earth Scope Plate Boundary Observatory in North America,the COCONetCaribbean network,TLALOCNet in Mexico,GNET in Greenland,and ANET in Antarctica.Going forward,UNAVCO plans to federate the Plate Boundary Observatory(USA),TLALOCNet(Mexico),and COCONet(Caribbean)GPS networks as the Network of the Americas,with upgrades to state-of-the-art,multi-sensor,multi-GNSS observations.While UNAVCO community scientists actively engage in using space and terrestrial geodetic techniques to study geodynamics at all scales,this proliferation of continuous networks is the basis for a suite of recent contributions that focus on improved daily positioning to sense Earth’s elastic response and other perturbations to loading by atmospheric and surface water,oceans,and ice.Day-to-day and sub-daily variations in the GPS vertical and horizontal correlate to increasingly well-understood short-term mass variability,such as monsoonal flooding in Bangladesh,sub-daily changes in tidal loading at continent scales,day-to-day surface water and ice storage in the western U.S.,variations in the rate of GIA in Greenland across a variety of scales,and improved understanding of the inter-annual variation in sea level rise due to changes in terrestrial water storage.

Applying Nearpod to the Teaching Chinese as a Second Language Class to Enhance Interactions and Collaborations in the Secondary Schools

The quick spread of the epidemic since 2019 together with fast advancing of technology has exposed teachers to online education,including Teaching Chinese as a Second Language(TCSL)classrooms.Some Chinese as a Second Language(CSL)teachers were reluctant to utilize technology tools in their teaching due to the lack of technological knowledge.Thus,this study designed a CSL curriculum with the lens of the TPACK framework(Technological Pedagogical Content Knowledge).Nearpod was specifically adopted as a web-based technology tool to support the teaching Chinese language due to its powerful functions provided.Nearpod allows teachers to design interactive activities in multiple ways to facilitate interactions and collaboration in the CSL learning process.This paper aimed to help Chinese teachers improve their understanding of how to effectively integrate technology into CSL teaching.Chinese teachers will develop a deeper comprehension of distance teaching from the perspectives of technology,pedagogy,and content knowledge,enhance students’deeper learning,and promote interaction and collaboration in L2 class.The effective use of the technology can develop language skills in a meaningful context knowledge with the guidance of pedagogical content knowledge.

Global collaboration of eye research--personal experience

On December 9,2023,I was privileged to be honored and participate in the Dr.Chi Chao Chan Symposium on Global Collaboration of Eye Research as the Global Eye Genetic Consortium(GEGC)session,which was held in the 16th Congress of the Asia-Pacific Vitreo-Retina Society(APVRS)in Hong Kong.Along with my talk on“Global collaboration of eye research:personal experience”,other prominent international speakers provided their own perspectives on opportunities for networking,collaboration,and exchange of ideas with global leaders and experts in ophthalmic practice,research,and education.

CRBFT:A Byzantine Fault-Tolerant Consensus Protocol Based on Collaborative Filtering Recommendation for Blockchains

Blockchain has been widely used in finance,the Internet of Things(IoT),supply chains,and other scenarios as a revolutionary technology.Consensus protocol plays a vital role in blockchain,which helps all participants to maintain the storage state consistently.However,with the improvement of network environment complexity and system scale,blockchain development is limited by the performance,security,and scalability of the consensus protocol.To address this problem,this paper introduces the collaborative filtering mechanism commonly used in the recommendation system into the Practical Byzantine Fault Tolerance(PBFT)and proposes a Byzantine fault-tolerant(BFT)consensus protocol based on collaborative filtering recommendation(CRBFT).Specifically,an improved collaborative filtering recommendation method is designed to use the similarity between a node’s recommendation opinions and those of the recommender as a basis for determining whether to adopt the recommendation opinions.This can amplify the recommendation voice of good nodes,weaken the impact of cunningmalicious nodes on the trust value calculation,andmake the calculated resultsmore accurate.In addition,the nodes are given voting power according to their trust value,and a weight randomelection algorithm is designed and implemented to reduce the risk of attack.The experimental results show that CRBFT can effectively eliminate various malicious nodes and improve the performance of blockchain systems in complex network environments,and the feasibility of CRBFT is also proven by theoretical analysis.

Collaborative Optimization of a Matrix Manufacturing System Based on Overall Equipment Effectiveness

When several traditional flow-shop lines operate in parallel,the operation mode with no communication between production lines will no longer be the optimal production paradigm.This paper describes matrix manufacturing systems(MMS)in a general manner from the perspective of related works,comparing different manufacturing organizational forms and their characteristics.Subsequently,MMS are extracted during the parallel production of multiple surface mount technology(SMT)lines.An overall equipment effectiveness(OEE)online calculation model and a collaborative optimization method are proposed based on the OEE of the MMS.The innovative idea of this study is to divide existing multiple parallel SMT lines into MMS.The efficiency of each matrix unit(MU)was calculated,and a collaborative optimization method was proposed based on an indicator(OEE).In this paper,an example of eight SMT lines is presented.The partitioning of MUs,OEE calculation of each MU,and the low OEE unit collaborative optimization method are described in detail.Through a case study,the architecture of the collaborative optimization model for the MMS was constructed and discussed.Finally,the improvement in the OEE proved the effectiveness and usability of the proposed architecture.

Joint Task Allocation and Resource Optimization for Blockchain Enabled Collaborative Edge Computing

Collaborative edge computing is a promising direction to handle the computation intensive tasks in B5G wireless networks.However,edge computing servers(ECSs)from different operators may not trust each other,and thus the incentives for collaboration cannot be guaranteed.In this paper,we propose a consortium blockchain enabled collaborative edge computing framework,where users can offload computing tasks to ECSs from different operators.To minimize the total delay of users,we formulate a joint task offloading and resource optimization problem,under the constraint of the computing capability of each ECS.We apply the Tammer decomposition method and heuristic optimization algorithms to obtain the optimal solution.Finally,we propose a reputation based node selection approach to facilitate the consensus process,and also consider a completion time based primary node selection to avoid monopolization of certain edge node and enhance the security of the blockchain.Simulation results validate the effectiveness of the proposed algorithm,and the total delay can be reduced by up to 40%compared with the non-cooperative case.