Platform Architecture Research Articles

Design of Remote Slit Lamp Diagnosis Platform Based on IoT Technology

In order to realize the diagnosis of slit lamp in cross-regional patients and improve the real-time and convenience of diagnosis, a remote slit lamp diagnosis platform based on Internet of Things (IoT) technology is designed. Firstly, the feasibility of remote slit lamp is analyzed. Secondly, the IoT platform architecture of doctor/server/facility (D/S/F) is proposed and a remote slit lamp is designed. Finally, the performance of the remote slit lamp diagnostic platform is tested. The platform solves the communication problem of distributed slit lamps and realizes respectively numerical control of multi-area slit lamp by multi-eye experts. The test results show that the remote control delay of the platform is less than 20 ms, which supports multiple experts to diagnose multiple patients separately.

Qbnb: An innovative C2B2C2B2C e-commerce mode for integrated on-demand services.

The traditional supply-side-driven e-commerce modes provide consumers with massive amounts of structured information about goods and services. Due to the lack of a tailor-made ability to describe, explain, and accurately understand unstructured service demands, existing technologies and service modes still struggle to fully explore, articulate, and meet the personalized, high-quality, and urgent service demands of the disadvantaged groups in e-commerce. This paper innovatively proposes the concept of "integrated services on demand" and develops its C2B2C2B2C-based "Qbnb" e-commerce mode, operation mechanism and intermediary platform architecture. After conducting exploratory operation training, it demonstrates that the Qbnb mode can effectively achieve centralized allocation of idle social surplus service capacity to cater to the needs of disadvantaged groups in e-commerce. Compared to the traditional e-commerce service mode, Qbnb will significantly expand service demand and capacity, achieve higher service efficiency, and create a broader service consumption market, resulting in many more job opportunities.

Ascertaining the impact of e-service quality on e-loyalty for the e-commerce platform of liner shipping companies

Focusing on the e-commerce platforms provided by major global liner shipping companies (LSCs), this study explores how e-service quality (e-SQ) influences e-loyalty (e-LY) and establish benchmarks for individual customers. We initially employed structural equation modeling to develop a research framework, and then we transformed this framework into a network data envelopment analysis model. Our findings revealed that the e-SQ of LSCs has a significant positive impact on the e-satisfaction (e-SA) and e-LY of their customers. Additionally, we observed that trust plays a significant moderating role in the relationship between e-SA and e-LY. Through benchmark analysis, we found that for small-scale shippers, virtually no slack exists between their benchmark and actual perception. However, the slack increased as the scale of the shipper increased, implying that LSCs have provided an e-SQ that exceeds the expectations of their large-scale customers. Meanwhile, it’s crucial for LSCs to pay attention to specific aspects such as the architecture of e-commerce platforms and privacy protection because the slacks of these e-SQ items are relatively small. Furthermore, the large slacks in e-LY for large-scale shippers imply that their e-LY leaves much room for improvement compared with that of small-scale shippers. Overall, our study underscores the importance of maintaining or elevating e-SQ standards to reinforce e-LY while considering the mediating and moderating effects of e-SA and trust in the context of the e-commerce platforms provided by major LSCs.

Automation of Calculations in the Design of an Integrated Energy System Based on its Digital Twin

The construction of integrated energy systems (IES) based on traditional energy systems that operate separately ensures higher efficiency and reliability of energy supply to consumers. IES are complex objects for design. The digital twin is a tool that allows one to integrate all the tools necessary for design in a single information space. Software tools that implement the digital twin of IES and are developed for their design require high flexibility in organizing calculations, which is due to the need to simulate a variety of equipment and involve a wide set of methods and mathematical models. Automating the construction of the computing subsystem is an effective solution to overcome the above difficulties. The article proposes a methodological approach to automating the construction of the computing subsystem of the digital twin of the IES. In accordance with the proposed approach, automated construction is performed on the basis of a software platform using modern metaprogramming tools. When building, the concept of Model-Driven Engineering is implemented and knowledge formalized in the form of ontologies is used. The article outlines the components of the proposed methodological approach to automating the construction of the computing subsystem of the digital twin of the IES, which include the following: principles of software platform development; software platform architecture; technique for automated construction of the digital twin computing subsystem; principles for ensuring the universality of software components. The digital twin obtained as a result of the practical application of the proposed methodological approach makes it possible to carry out computer and mathematical modeling of the IES in the virtual space, exploring various configurations of its construction. The implementation of modeling within the framework of the digital twin of IES makes it possible to implement flexible and efficient approaches to solving the problems of designing IES and to obtain design recommendations that can be implemented when building real IES. Keywords: methodological approach, digital twin, automation of computing, automation of programming, Model-Driven Engineering, metaprogramming, ontology, integrated energy system

Infrastructuring of Digital Platforms

Digital platforms expand into multiple adjoining business domains for revenue maximization purposes. Governments also use digital platforms for public welfare in multiple interrelated sectors. Such horizontal growth transforms digital platforms as digital infrastructure which consequently increases its e-adoption. This research determines combinations of platform attributes which drive the infrastructuring of digital platforms. Results of this research will enable platform mangers to, a priori, embed such attributes in platform architecture to achieve platform objectives. Fuzzy-set qualitative comparative analysis (fsQCA) research methodology followed by a descriptive cross-analysis has been used in this research. Five key result sets emerge, which, inter alia, indicate that criticality, ubiquity, and generativity are key attributes driving the infrastructuring of digital platforms, unlike earlier research results showing modularity and heterogeneity as key attributes. fsQCA research method with a set theory approach is more suitable for such configurational analysis compared to multivariate techniques.

Design and implementation of a monitoring platform based on beidou high precision positioning technology

Traditional BDS positioning technology has limitations in accuracy, robustness, and availability in certain real-time monitoring applications. Therefore, this article designs and implements a monitoring platform based on Beidou high-precision positioning technology to solve the limitations of traditional BDS positioning technology and provide more accurate, reliable, and real-time positioning services. The research first analyzes and optimizes the positioning algorithms of the existing Beidou system to improve the accuracy of position measurement. Then apply the optimized algorithm to the system architecture of the monitoring platform to achieve high-precision positioning function. Finally, design a suitable user interface and data processing module so that users can easily obtain and analyze positioning data. Through experimental verification, this platform has achieved high accuracy and stability in position measurement. Users can obtain real-time location information through this platform and further analyze and process it.

Digital Signal Processing Oriented Electronic Communication Engineering Applications and Practices

This paper first describes the applications of digital signal processors in software radio, speech compression coding, modems and GPS systems, demonstrating the versatility of digital signal processors in practical communication systems. Next, digital signal processing oriented electronic communication practices are presented in the system design section to design high performance communication systems for specific communication needs and environmental conditions. The digital signal processing platform used in the platform architecture is optimized for signal processing and data transmission. The BER is 0.008% when the signal-to-noise ratio is -10 dB. The time complexity of digital signal processing is 7.2 ms when the number of communication nodes is 1000. It shows that digital signal processing oriented electronic communication engineering is important for improving the performance, reliability and efficiency of communication systems.

Parallel Fractional Stochastic Gradient Descent With Adaptive Learning for Recommender Systems

The structural change toward the digital transformation of online sales elevates the importance of parallel processing techniques in recommender systems, particularly in the pandemic and post-pandemic era. Matrix factorization (MF) is a popular and scalable approach in collaborative filtering (CF) to predict user preferences in recommender systems. Researchers apply Stochastic Gradient Descent (SGD) as one of the most famous optimization techniques for MF. Paralleling SGD methods help address Big Data challenges due to the wide range of products and the sparsity in user ratings. However, these methods’ convergence rate and accuracy are affected by the dependency between the user and item latent factors, specifically in large-scale problems. Besides, the performance is sensitive to the applied learning rates. This paper proposes a new parallel method to remove dependencies and boost speed-up by using fractional calculus to improve accuracy and convergence rate. We also apply adaptive learning rates to enhance the performance of our proposed method. The proposed method is based on Compute Unified Device Architecture (CUDA) platform. We evaluate the performance of our proposed method using real-world data and compare the results with the close baselines. The results show that our method can obtain high accuracy and convergence rate in addition to high parallelism.

Архитектурный метод проектирования геоинформационной платформы в составе цифровой платформы межведомственного взаимодействия в интересах обороны

The purpose of the study is to substantiate the stages of the architectural method of designing a geoinformation platform as part of a digital one, for interdepartmental cooperation, in the view of National defense. Five approaches to designing complex digital management platforms are explained. The content of their architecture concept is introduced and considered. The essence of the functional, system and technical architectures of the design object, which together make its systemic form, is described. The principles of developing the architecture of a digital geoinformation platform are formulated. Based on them and the content of the functional, system and technical architectures of the object planning, the stages of the method of projecting a geoinformation platform as part of a digital one, for the declared goal, are described. It is concluded that the use of the architectural design method at the preliminary stage will allow, on the one hand, to perform reengineering of information on the mentioned functional processes, taking into account spatial data and cartographic visualization; and, on the other hand, to form operational and technical requirements for establishing the required platform

Smart Classroom in the Era of Education Informatization 2.0

The advent of the era of education informatization 2.0 has brought challenges and opportunities to the educational technology work of colleges and universities. As an important part of education informatization, smart classroom has an important theoretical framework and technical support system. This paper analyzes the characteristics of the era of education informatization 2.0, discusses the concept and importance of smart classrooms, and compares them with traditional classrooms. At the same time, through innovative practices and case studies, the innovative achievements and effect evaluation of educational technology work in colleges and universities are demonstrated. In addition, this paper also introduces the technical support system of the smart classroom, including the functions and architecture of the smart education platform, and the application of big data, artificial intelligence, cloud computing, and mobile learning Xi in the smart classroom. Finally, this paper looks forward to the future-oriented development trend of educational technology in colleges and universities, and puts forward suggestions for the development of smart classrooms and the future prospects of educational technology work in colleges and universities.

Hadoop-Based Political and Ideological Big Data Platform Architecture and Pattern Mining in Higher Education

There is a growing opportunity for self-improvement within the realm of higher education, represented by the combination of big data technologies and higher education. The Education Big Data Processing Framework (EBDPF) is the name of the platform that is the subject of this article, which focuses on the development of an advanced big data processing platform. In order to process huge datasets in an effective manner, the platform makes use of Hadoop's big data storage architecture, in addition to Hive, Flume, and Sqoop for data collection and synchronization, respectively. In this study, the implementation of standard data mining techniques is investigated through the use of MapReduce programming. More specifically, the study investigates the execution efficiency and scalability of these algorithms within the Hadoop platform. The data clustering task in data mining is chosen as a representative problem in this study so that the effectiveness of the EBDPF may be evaluated accordingly. An implementation of the clustering job that is based on MapReduce is created and tested on the Hadoop platform. Extensive experiments are conducted with a range of cluster sizes and data sizes. The findings provide more evidence that Hadoop distributed systems are more efficient and successful than traditional methods when it comes to managing data mining applications. The extended performance analysis of computing power not only provides evidence that the platform is currently effective, but it also provides a signal that it has a significant amount of potential that has not yet been utilized. At the convergence of big data technology and higher education, the EBDPF emerges as a strong and promising framework, demonstrating considerable steps in accelerating data processing within educational contexts. In conclusion, the EBDPF is a framework that demonstrates significant progress.

Twitter and divides in the Dutch parliament: social and political segregation in the following, @-mentions and retweets networks

ABSTRACT MPs communication on Twitter with other MPs may facilitate forming cross-party solidarity networks and provide public micro deliberation but may also be segregated leading to information bubbles and political polarization. That party-based division lines are running through the online communication networks of politicians is a well-established finding in social media studies; however important knowledge gaps have remained on the complexity of Twitter’s multilayered network developments and their interrelatedness with socio-demographic segregation. Here, we integrate the online-network literature with that on the political consequences of the digital architecture of social media platforms to theorize and scrutinize the extent to which and why Twitter following, @-mentioning and retweeting networks among MPs are segregated along party lines and sex, age and ethnicity. Our unique dynamic take allows us to rigorously study network segregation, including feedback mechanisms between Twitter layers, based on descriptive network statistics and SIENA analyses for Dutch MPs at three time points. The findings show that political segregation patterns are strongest within the retweet layer and weakest for @-mentions. The interrelations between the Twitter network layers aggravate party-based segregation over time. MP Twitter networks are not consistently segregated along social dimensions.

РАЗВИТИЕ АРХИТЕКТУРЫ ИНТЕЛЛЕКТУАЛЬНЫХ ТРАНСПОРТНЫХ СИСТЕМ

The paper analyzes the role of a complete architecture of intelligent transport systems (ITS) in ensuring their effectiveness. Many countries or groups of countries have ITS architecture with successful results of its application in practice. It is shown that the ITS architecture is constantly being updated and this is a characteristic trend. The paper proposes new approaches to the formation of the architecture of the integration platform within ITS. The scheme of organisation of data flows in different loops of software tools of the integration platform is developed. It is proposed to separate the control loops proper transport system data and identification data, which describe a partisipant of the ITS (digital object) with the expansion of capabilities in a cooperative ITS. It is possible to organise linked chains of identification of ITS digital objects, to participate in the formation of network structures for ITS work processes, describing the behaviour of digital objects during ITS processes and the behaviour of end users in accordance with the properties of network structures.

The Game-based Learning (GbL) Platform with Generative AI to Enhance Digital and Technology Literacy Skills

The GbL platform, or game-based learning platform, with generative AI is a research tool initiated from the combination of game-based learning concepts and generative artificial intelligence technology; thereby, this platform is intended to be used as a guideline for the instruction management, in which learners can respond and interact with the real-time activities by means of gamification. The objectives of this research are (1) to study and synthesize the conceptual framework of the GbL platform with generative AI to enhance digital and technology literacy skills, (2) to develop the architecture of the GbL platform with generative AI to enhance digital and technology literacy skills, and (3) to study the results of the development of the GbL platform with generative AI to enhance digital and technology literacy skills. The results of this research show that (1) the overall elements suitability of the architecture of the GbL platform with generative AI is at the highest level (Mean = 4.51, SD = 0.48), and (2) the overall suitability of the architecture of the GbL platform with generative AI is at the highest level (Mean = 4.59, SD = 0.41). Nevertheless, there are still some research gaps in this study; that is, this study was conducted with quite a small sample group and it focuses mainly on the results of evaluation on the architecture of the GbL platform. Therefore, this research is regarded merely as a pilot study designated for feasibility study to further develop the GbL platform that can be put in practical use in the future.

Platform Organizations and Fields: Exploring the Influence of Field Conditions on Platformization Processes

This article contributes to the debate on the platformization of society by presenting a theoretical framework that describes the influence of strategic action fields (SAFs) on the emergence of platform architectures. It shifts the focus from already successful platforms to contested processes of platformization, understood as the gradual reorganization of fields around the architectures of digital platforms. To assess the influence of fields on platformization processes, the article combines the architectural view of platforms and the theory of SAFs. The resulting framework emphasizes that platform organizations may occupy powerful positions in fields, but they also depend on the contributions of users and complementors to establish these positions in the first place. Therefore, the forms and outcomes of platformization are influenced by the conditions in SAFs, particularly the stage in the field’s temporal trajectory and the field position of platform organizations. By re-examining a growing body of empirical research, the article distinguishes platformization processes in emerging, stable, and transforming fields, and presents scenarios for each case. By theorizing a wide range of platformization processes and outcomes beyond disruption, the article offers a nuanced understanding of the proliferation of digital platforms and the influence of platform organizations in contemporary societies.

Data-centric workloads with MPI_Sort

Sorting is a fundamental task in computing and plays a central role in information technology. The advent of rack-scale and warehouse-size data processing shaped the architecture of data analysis platforms towards supercomputing. In turn, established techniques on supercomputers have become relevant to a wider range of application domains. This work is concerned with multi-way mergesort with exact splitting on distributed memory architectures. At its core, our approach leverages a novel and parallel algorithm for multi-way selection problems. Remarkably concise, the algorithm relies on MPI_Allgather and MPI_ReduceScatter_block, two collective communication schemes that find hardware support in most high-end networks. A software implementation of our approach is used to process the Terabyte-size Data Challenge 2 signal, released by the SKA radio telescopes organization. On the supercomputer considered herein, our approach outperforms the state of the art by up to 2.6X using 9,216 cores. Our implementation is released as a compact open source library compliant to the MPI programming model. By supporting the most popular elementary key types, and arbitrary fixed-size value types, the library can be straightforwardly integrated into third-party MPI-based software.

The hybrid augmented intelligence open innovation platform's architecture and scheme, which combine interconnected virtual and actual systems

The hybrid augmented intelligence open innovation platform's architecture and scheme, which combine interconnected virtual and actual systems

The Hybrid Augmented Intelligence Open Innovation Platform's Architecture and Scheme, Which Combines Interconnected Virtual and Actual Systems

The Hybrid Augmented Intelligence Open Innovation Platform's Architecture and Scheme, Which Combines Interconnected Virtual and Actual Systems

Application of Digital Twin Technology for the Digitization of Railway Maintenance Services in compliance with European Regulation EU 779/2019.

This paper delves into the application of Digital Twin Technology (DTT) in the digitalization of assets, processes, and services to improve maintenance performance in railway applications in the context of European Regulation EU 779/2019. Digitalization plays a pivotal role in certifying the suitability of rolling stock in the railway sector. The primary objective of this study is to meticulously examine the fundamental tasks required to build a digital twin in this specific context. The process involves the contributions of key entities fulfilling specific roles: the maintenance and asset certification service provider ensures the integrity and compliance of rolling stock; specialists in IoT and process automation, along with experts in software platforms and services, are tasked with implementing the technological aspects of the digital twin. As a result, a methodology is proposed for the integration of digital design that combines three approaches: Service approach, platform architecture, and model-based asset digitalization. This paper delineates critical stages, from data acquisition and management to model creation and information integration, highlighting the crucial role of DTT in this process. Furthermore, the challenge of digitalization in situations where assets and processes are in an initial state of low or non-existent digitalization is underscored. A profound understanding of digital assets, information layers, and underlying models becomes crucial in the context of the current challenges of railway digitalization.

Peripheral Creator Cultures in India, Ireland, and Turkey

Drawing on Indian, Irish, and Turkish YouTube creators’ perceptions of their work, this article focuses on peripheral creator work cultures to broaden the understanding of creator labor precarity. We situate creator labor within not only the platform architectures but also within the geographical specificities of media production, distribution, and consumption. In doing so, we demonstrate that peripheral creators face distinctive struggles for visibility and survival in screen industries that emerge from their heterogeneous sociocultural and linguistic contexts. Based on the interviews with creators and streaming service executives conducted between 2017 and 2023, the findings reveal that creators’ choice of language and place of practice distinctly affects their global reach, visibility, and their ability to sustain a career in screen industries.