Augmented reality-based BIM multi-user collaboration system

The rapid development of building information modelling(BIM) and its enabling technologies has attracted extensive attention in the field of architecture, engineering and construction(AEC). By combining BIM models with the real world, the potential of BIM can be further exploited with the help of augmented reality(AR) technology. However, a BIM model usually involves a huge amount of data. Considering the limited computing capability of current mobile devices, these applications therefore suffer from significant performance problems, especially model loading and rendering problems. To this end, an AR-based multi-user BIM collaboration system, which can realise the on-demand dynamical loading of the BIM model by using the block-wise loading strategy of model transformation, thus solving the problem of model loading delay, was proposed. In addition, dynamic rendering technology is adopted to solve the problem of rendering lag. Experimental results show that the realisation of virtual-reality fusion and interaction for the BIM model and remote multi-user collaboration can effectively improve work efficiency and intelligence in the engineering field.

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.

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.

Resource Allocation in Multi-User Cellular Networks:A Transformer-Based Deep Reinforcement Learning Approach

To meet the communication services with diverse requirements,dynamic resource allocation has shown increasing importance.In this paper,we consider the multi-slot and multi-user resource allocation(MSMU-RA)in a downlink cellular scenario with the aim of maximizing system spectral efficiency while guaranteeing user fairness.We first model the MSMURA problem as a dual-sequence decision-making process,and then solve it by a novel Transformerbased deep reinforcement learning(TDRL)approach.Specifically,the proposed TDRL approach can be achieved based on two aspects:1)To adapt to the dynamic wireless environment,the proximal policy optimization(PPO)algorithm is used to optimize the multi-slot RA strategy.2)To avoid co-channel interference,the Transformer-based PPO algorithm is presented to obtain the optimal multi-user RA scheme by exploring the mapping between user sequence and resource sequence.Experimental results show that:i)the proposed approach outperforms both the traditional and DRL methods in spectral efficiency and user fairness,ii)the proposed algorithm is superior to DRL approaches in terms of convergence speed and generalization performance.

Hybrid Block Diagonalization Precoding for Multi-User Weighted Sum-Rate Maximization

This paper studies large-scale multi-input multi-output(MIMO)orthogonal frequency division multiplexing(OFDM)communications in a broadband frequency-selective channel,where a massive MIMO base station(BS)communicates with multiple users equipped with multi-antenna.We develop a hybrid precoding design to maximize the weighted sum-rate(WSR)of the users by optimizing the digital and the analog precoders alternately.For the digital part,we employ block-diagonalization to eliminate inter-user interference and apply water-filling power allocation to maximize the WSR.For the analog part,the optimization of the PSN is formulated as an unconstrained problem,which can be efficiently solved by a gradient descent method.Numerical results show that the proposed block-diagonal hybrid precoding algorithm can outperform the existing works.

Community detection on elite mathematicians’collaboration network

Purpose:This study focuses on understanding the collaboration relationships among mathematicians,particularly those esteemed as elites,to reveal the structures of their communities and evaluate their impact on the field of mathematics.Design/methodology/approach:Two community detection algorithms,namely Greedy Modularity Maximization and Infomap,are utilized to examine collaboration patterns among mathematicians.We conduct a comparative analysis of mathematicians’centrality,emphasizing the influence of award-winning individuals in connecting network roles such as Betweenness,Closeness,and Harmonic centrality.Additionally,we investigate the distribution of elite mathematicians across communities and their relationships within different mathematical sub-fields.Findings:The study identifies the substantial influence exerted by award-winning mathematicians in connecting network roles.The elite distribution across the network is uneven,with a concentration within specific communities rather than being evenly dispersed.Secondly,the research identifies a positive correlation between distinct mathematical sub-fields and the communities,indicating collaborative tendencies among scientists engaged in related domains.Lastly,the study suggests that reduced research diversity within a community might lead to a higher concentration of elite scientists within that specific community.Research limitations:The study’s limitations include its narrow focus on mathematicians,which may limit the applicability of the findings to broader scientific fields.Issues with manually collected data affect the reliability of conclusions about collaborative networks.Practical implications:This study offers valuable insights into how elite mathematicians collaborate and how knowledge is disseminated within mathematical circles.Understanding these collaborative behaviors could aid in fostering better collaboration strategies among mathematicians and institutions,potentially enhancing scientific progress in mathematics.Originality/value:The study adds value to understanding collaborative dynamics within the realm of mathematics,offering a unique angle for further exploration and research.

Privacy-Preserving Healthcare and Medical Data Collaboration Service System Based on Blockchain and Federated Learning

As the volume of healthcare and medical data increases from diverse sources,real-world scenarios involving data sharing and collaboration have certain challenges,including the risk of privacy leakage,difficulty in data fusion,low reliability of data storage,low effectiveness of data sharing,etc.To guarantee the service quality of data collaboration,this paper presents a privacy-preserving Healthcare and Medical Data Collaboration Service System combining Blockchain with Federated Learning,termed FL-HMChain.This system is composed of three layers:Data extraction and storage,data management,and data application.Focusing on healthcare and medical data,a healthcare and medical blockchain is constructed to realize data storage,transfer,processing,and access with security,real-time,reliability,and integrity.An improved master node selection consensus mechanism is presented to detect and prevent dishonest behavior,ensuring the overall reliability and trustworthiness of the collaborative model training process.Furthermore,healthcare and medical data collaboration services in real-world scenarios have been discussed and developed.To further validate the performance of FL-HMChain,a Convolutional Neural Network-based Federated Learning(FL-CNN-HMChain)model is investigated for medical image identification.This model achieves better performance compared to the baseline Convolutional Neural Network(CNN),having an average improvement of 4.7%on Area Under Curve(AUC)and 7%on Accuracy(ACC),respectively.Furthermore,the probability of privacy leakage can be effectively reduced by the blockchain-based parameter transfer mechanism in federated learning between local and global models.

NAVIGATING CHALLENGES TOGETHER 3rd AIWW calls for regional and global collaboration in the field of water resources

The 3rd Asia International Water Week (AIWW),themed"Enhancing Our Future Water Security,"concluded in Beijing on September 26.Delegates from the many Asian countries attending the event widelyrecognized the water governance philosophy proposed by Chinese President Xi Jinping:"prioritizing water conservation,balancing water distribution in time and space,and taking a systematic approach to water management with the synergy of government and market."

Runout prediction of potential landslides based on the multi-source data collaboration analysis on historical cases

Long runout landslides involve a massive amount of energy and can be extremely hazardous owing to their long movement distance,high mobility and strong destructive power.Numerical methods have been widely used to predict the landslide runout but a fundamental problem remained is how to determine the reliable numerical parameters.This study proposes a framework to predict the runout of potential landslides through multi-source data collaboration and numerical analysis of historical landslide events.Specifically,for the historical landslide cases,the landslide-induced seismic signal,geophysical surveys,and possible in-situ drone/phone videos(multi-source data collaboration)can validate the numerical results in terms of landslide dynamics and deposit features and help calibrate the numerical(rheological)parameters.Subsequently,the calibrated numerical parameters can be used to numerically predict the runout of potential landslides in the region with a similar geological setting to the recorded events.Application of the runout prediction approach to the 2020 Jiashanying landslide in Guizhou,China gives reasonable results in comparison to the field observations.The numerical parameters are determined from the multi-source data collaboration analysis of a historical case in the region(2019 Shuicheng landslide).The proposed framework for landslide runout prediction can be of great utility for landslide risk assessment and disaster reduction in mountainous regions worldwide.

Effects of nursing team communication and collaboration on treatment outcomes in intensive care unit patients with severe pneumonia

BACKGROUND Severe pneumonia is a common severe respiratory infection worldwide,and its treatment is challenging,especially for patients in the intensive care unit(ICU).AIM To explore the effect of communication and collaboration between nursing teams on the treatment outcomes of patients with severe pneumonia in ICU.METHODS We retrospectively analyzed 60 patients with severe pneumonia who were treated at the ICU of the hospital between January 1,2021 and December 31,2023.We compared and analyzed the respiratory mechanical indexes[airway resistance(Raw),mean airway pressure(mPaw),peak pressure(PIP)],blood gas analysis indexes(arterial oxygen saturation,arterial oxygen partial pressure,and oxygenation index),and serum inflammatory factor levels[C-reactive protein(CRP),procalcitonin(PCT),cortisol(COR),and high mobility group protein B1(HMGB1)]of all patients before and after treatment.RESULTS Before treatment,there was no significant difference in respiratory mechanics index and blood gas analysis index between 2 groups(P>0.05).However,after treatment,the respiratory mechanical indexes of patients in both groups were significantly improved,and the improvement of Raw,mPaw,plateau pressure,PIP and other indexes in the combined group after communication and collaboration with the nursing team was significantly better than that in the single care group(P<0.05).The serum CRP and PCT levels of patients were significantly decreased,and the difference was statistically significant compared with that of nursing group alone(P<0.05).The levels of serum COR and HMGB1 before and after treatment were also significantly decreased between the two groups.CONCLUSION The communication and collaboration of the nursing team have a significant positive impact on respiratory mechanics indicators,blood gas analysis indicators and serum inflammatory factor levels in the treatment of severe pneumonia patients in ICU.

Multi-User Collaborative Assembly Planning over the Internet

Due to the increasing complexity of products and for the distributed product development, more closely collaborative work among designers is required. A collaborative assembly planning approach is proposed to support assembly planning in a networked environment. The working procedure is depicted and the key techniques including collaborative-planning-oriented assembly decomposition modeling, assembly assignment modeling, and sub-plans merging are addressed. By incorporating visual models at client side with assembly application models at server side, a web-based supporting environment for collaborative assembly planning has been developed using VRML and Java-EAI techniques. A case study is given to illustrate the feasibility and validity of the idea.

Closed BER expression of multi-user DS UWB systemsin indoor fading channel

The bit error rate （BER） performance of multi-user direct spreading bi-phase shift keying （DSBPSK） direct impulse ultra wideband （UWB） systems is analyzed and simulated based on a statistical indoor multi-path fading channel model. The BER of the system is theoretically derived and given in closed form, which is expressed in terms of channel parameters and system parameters such as pulse width parameter, pulse repeat period, user number and pulse waveform. With this BER expression, the effect of these parameters on the system performance can be evaluated in a uniform way. Simulation results well match the theory numerical results, and prove that the multi-access interference （MAI） of DS-BPSK UWB is a normal distribution.

Dynamic business process modeling and verification for inter-organizational collaboration

To achieve an on-demand and dynamic composition model of inter-organizational business processes, a new approach for business process modeling and verification is introduced by using the pi-calculus theory. A new business process model which is multi-role, multi-dimensional, integrated and dynamic is proposed relying on inter-organizational collaboration. Compatible with the traditional linear sequence model, the new model is an M x N multi-dimensional mesh, and provides horizontal and vertical formal descriptions for the collaboration business process model. Finally, the pi-calculus theory is utilized to verify the deadlocks, livelocks and synchronization of the example models. The result shows that the proposed approach is efficient and applicable in inter-organizational business process modeling.

Adaptive resource allocation in downlink multi-user MC-CDMA systems

The joint channel and power allocation in the downlink transmission of multi-user multi-carrier code division multiple access（MC-CDMA） systems are investigated and the throughput maximization problem is considered as a mixed integer optimization problem. For simplicity of analysis, the problem is divided into two less complex sub-problems： power allocation and channel allocation, which can be solved by a suboptimal adaptive power allocation （APA）algorithm and an optimal adaptive channel allocation （ACA） algorithm, respectively. By combining APA and ACA algorithms, an adaptive channel and power allocation scheme is proposed. The numerical results show that the proposed APA algorithm is more suitable for MC-CDMA systems than the conventional equal power allocation algorithm, and that the proposed channel and power allocation scheme can significantly improve the system throughout performance.

Intercultural Collaboration in Group Work at Chinese Universities

The empirical work on intercultural communication issues at university settings have mainly focused on the minority cul-tural groups and the majority groups are usually neglected.Most Chinese scholars are engaged in the development of cross-cultural communication competence of the Chinese EFL learners,the few researches on intercultural relations in Chinese universities are also on the international students.To compare the attitudes and motivations of both the International Students in China(ISCs)and the Chinese Home Students(CHSs)in intercultural collaboration(IC)in the group work,group discussion and questionnaire survey areemployed.Survey of the 445 CHSs and 87 ISCs show that the IC environment at Chinese universities is far from satisfactory.Those who have IC experiences find they have encountered difficulties in adapting to each other's language,race,religion,agenda,etc.Chinese students'language difficulty is regarded both groups as the first obstacle in their collaboration,but personality is the first concern in their choice of a workmate.Neither language proficiency nor IC courses are significant factor in their motivation for IC involvement.What they want most is the real collaboration opportunities and programs.The findings may provide some reference for Chinese universities in their construction of international and intercultural campus environment.

Optimal subcarrier allocation for cognitive radio with multi-user OFDM and distributed antenna

The subcarrier allocation problem in cognitive radio（CR）networks with multi-user orthogonal frequency-division multiplexing（OFDM）and distributed antenna is analyzed and modeled for the flat fading channel and the frequency selective channel,where the constraint on the secondary user（SU）to protect the primary user（PU）is that the total throughput of each PU must be above the given threshold instead of the ＂interference temperature＂.According to the features of different types of channels,the optimal subcarrier allocation schemes are proposed to pursue efficiency（or maximal throughput）,using the branch and bound algorithm and the 0-1 implicit enumeration algorithm.Furthermore,considering the tradeoff between efficiency and fairness,the optimal subcarrier allocation schemes with fairness are proposed in different fading channels,using the pegging algorithm.Extensive simulation results illustrate the significant performance improvement of the proposed subcarrier allocation schemes compared with the existing ones in different scenarios.

Autonomous process collaboration framework for C4ISR system interoperation

Interoperability plays an important role in the joint command, control, communication, computer, intelligence, surveillance, reconnaissance(C4 ISR) operations. Coordinating and integrating operational processes to fulfill a common mission are challenged by the ever-changing battlefield and hence requires a cross-organizational process management that produces an autonomous, flexible and adaptable architecture for collaborative process evolution. The traditional business process collaboration pattern is based on the predefined "public-view" perspective and cannot meet the requirement of the joint task operations. This paper proposes a flexible visibility control mechanism and a dynamic collaboration framework for modeling and generating collaborative processes. The mechanism allows collaborators to define a set of visibility rules to generate different views of the private processes for different collaborations, which gives a great flexibility for the collaboration initiator to decide on an appropriate collaboration pattern. The framework supports collaborators to dynamically and recursively add a new process or even a new organization to an existing collaboration. Moreover, a formal representation of the processes and a set of generation algorithms are provided to consolidate the proposed theory.

Multi-User Connection Performance Assessment of NOMA Schemes for Beyond 5G

Non-orthogonal multiple access(NOMA)is proved to be useful to satisfy the requirements of beyond 5th generation such as massive multi-user connection.Here we compare the performances of two NOMA schemes:low code rate spreading(LCRS)scheme and interleaver division multiple access(IDMA)scheme.It is found that LCRS is superior to IDMA when number of users is small due to coding gain achieved.While IDMA is preferred when number of users is high because repetition applied in IDMA can suppress multi-user interference effectively.And interleaver is important in IDMA for randomizing the interference.Also,this paper evaluates the impact of channel decoder.It is observed that Log-MAP decoder has much better performance than that of Max-Log-MAP when number of users is large.Thus,it is recommended to use Log-MAP decoder in NOMA in high user overloading case.We also compared the performance of NOMA by using different type of channel codes.We find that NOMA using specific convolutional code has a better performance than that of using specific LDPC code when number of users is high.

Clustering approach based on hierarchical expansion for community detection of scientific collaboration network

This study presents a clustering algorithm based on hierarchical expansion to solve the problem of community detection in scientific collaboration network. The characteristics of achievements information related to scientific and technological domains are analyzed,and then an ontology that represents their latent collaborative relations is built to detect clusters from the collaboration network. A case study is conducted to collect a data set of research achievements in the electric vehicle field and better clustering results are obtained. A hierarchical recommendation framework that enriches the domain ontologies and retrieves more relevant information resources is proposed in the last part of this paper. This work also lays out a novel insight into the exploitation of scientific collaboration network to better classify achievements information.

Spatial Structure,Hierarchy and Formation Mechanisms of Scientific Collaboration Networks:Evidence of the Belt and Road Regions

Scientific collaboration has become an important part of the people-to-people exchanges in the Belt and Road initiative,and remarkable progress has been made since 2013.Taking the 65 countries along the Belt and Road(BRI countries)as the research areas and using collaborated Web of Science(WOS)core collection papers to construct an international scientific collaboration matrix,the paper explores the spatial structure,hierarchy and formation mechanisms of scientific collaboration networks of 65 countries along the Belt and Road.The results show that:1)Beyond the Belt and Road regions(BRI regions),Central&Eastern Europe,China and West Asia&North Africa have formed a situation in which they all have the most external links with other countries beyond BRI regions.China has the dominant role over other BRI countries in generating scientific links.The overall spatial structure has changed to a skeleton structure consisting of many dense regions,such as Europe,North America,East Asia and Oceania.2)Within the Belt and Road regions,Central&Eastern Europe has become the largest collaboration partner with other sub-regions in BRI countries.The spatial structure of scientific collaboration networks has transformed from the‘dual core’composed of China and the Central&Eastern Europe region,to the‘multi-polarization’composed of‘one zone and multi-points’.3)The hierarchical structure of scientific collaboration networks presents a typical‘core-periphery’structure,and changes from‘single core’to‘double cores’.4)Among the formation mechanisms of scientific collaboration networks,scientific research strength and social proximity play the most important roles,while geographical distance gradually weakens the hindrance to scientific collaboration.