Platform Architecture Research Articles

The vendor-agnostic EMPAIA platform for integrating AI applications into digital pathology infrastructures

Automated image analysis and artificial intelligence (AI) are becoming increasingly common in digital pathology software. While various proprietary pathology systems exist, there are no fully vendor-agnostic integration approaches for AI apps. This makes it difficult for vendors of AI solutions to integrate their products into the multitude of non-standard software systems in pathology.The EMPAIA Consortium is developing an open and decentralized platform allowing AI-based apps of different vendors to be integrated with existing clinical IT infrastructures. For this purpose, we defined, analyzed, and prioritized relevant use cases and identified requirements for an open platform to support these use cases. We then designed the platform architecture described here to meet these requirements based on web technologies.For all platform services open source reference implementations are available, that are used by developers of AI apps as an integration target. Developers of compatible clinical systems can either use and integrate components of the reference implementation or directly implement the interfaces as per specification, allowing apps to run in their clinical environment. Pathology laboratories can use both on-premises and cloud deployments of the platform. Apps can be obtained via a central marketplace so that pathologists can use them in their daily workflow.An adoption of this platform will enable interoperability among different existing digital pathology software systems. This reduces integration efforts for software vendors, while users will benefit from a wider variety of tools and a quicker availability of new and innovative methods. Ultimately, the platform will reduce barriers to market entry for AI vendors and provide pathologists with access to advanced AI tools.

The Systems Approach and Design Path of Electronic Bidding Systems Based on Blockchain Technology

The electronic tendering and bidding system has realized the digitalization, networking, and high integration of the whole process of tendering, bidding, bid evaluation, and contract, which has a wide range of applications. However, the trust degree, cooperation, and transaction efficiency of the parties involved in electronic bidding are low, and bidding fraud and collusion are forbidden repeatedly. Blockchain technology has the characteristics of decentralization, transparent transactions, traceability, non-tampering and forgery detection, and data security. This paper proposes a design path of an electronic bidding system based on blockchain technology, which aims to solve the efficiency, trust, and security of the electronic trading process. By building the underlying architecture platform of blockchain and embedding the business process of electronic bidding, this realizes the transparency, openness, and traceability during the whole process of electronic bidding. This paper uses qualitative and quantitative methods to prove the effectiveness of the system.

Critical success factors and architecture of innovation services models in data industry

Big data can be used by enterprises to discover their operating rules and make a forecast of their future operation. To successfully realize the benefits of big data analytics (BDA), an enterprise must rely on external heterogeneous information that is effectively combined and integrated. Enterprises, their upstream and downstream organizations, that utilize big data together form a data industry chain. This study discussed the potential bottlenecks and obstacles of big data-based business model innovation and data transaction platform construction in the business environment. It also explored the successful influencing factors in the big data industry, and applied the analytic hierarchy process to collect opinions from information technology professionals. Regarding the critical factors associated with BDA success, this study found that the experts attached the greatest importance to the maintenance of personal and business privacy and security during the data used with data de-identification being of utmost concern. Based on the results, this study proposed three innovative services models for the data industry. It further analyzed a role model based on the three proposed service models, and defined the rights and obligations of each role holder. Based on decentralization of the blockchain, a multi-layer cloud-based services platform architecture was designed to support data transactions, thereby ensuring the fairness and transparency of big data transactions.

Internet Plus Innovation and Entrepreneurship Education Model Based on Machine Learning Algorithms

Innovation and entrepreneurship is a spiritual attitude. With the dissemination and wide application of the concept and technology of “Internet Plus,” Internet Plus innovative thinking has had a strong impact on innovation and entrepreneurship education, such as teaching concepts, changes in teaching methods, optimization of teaching staff and curriculum systems, and resource sharing. Therefore, according to the actual needs of innovation and entrepreneurship teaching in colleges and universities, this paper combines the concept of Internet and college education with the help of machine learning algorithms to build a new education system. First, the article designs the overall platform architecture and core business processes and develops and implements front-end and various platform functions. The system includes different modules such as preschool skill diagnosis, online learning, stage testing and evaluation, information and resource sharing, team building and project implementation management, and so on. Then, the experiment shows that the precision rate, recall rate, and F1 value of the system are all high, indicating that the system is stable and efficient. Finally, it briefly expounds the development strategies of the Internet Plus education model under the influence of relevant systems, which will help students and teachers develop innovation and entrepreneurship theories and improve students’ knowledge quality. The combination of Internet technology and innovation and entrepreneurship teaching can make innovation education more in line with the current learning needs and promote the improvement of entrepreneurship ability.

Micro and milli-chamber bioreactors for human induced pluripotent stem cell culture: Model and experimental validation

One of the main interests in developing microfluidic platforms is the lab-on-a-chip (LOC) applications, including the use of microdevices for the culture of prokaryotic and eukaryotic cells for different applications. In this context, the trapping and control of Micro/nano-scale bubbles have been considered as it becomes a field of growing concern addressing many challenges in LOC applications. In the present work, we present a novel microfluidic bioreactor based on the micropillar design that reduces stresses caused by bubbles on the cell growth in the microchip. The combination of one chamber with 3-pillars and 10-pillars design with the channel heights of 270 µm and 2 mm were evaluated. Computational fluid dynamics simulations (CFD) were conducted to investigate the flow dynamics in the new designs. Numerical values of velocity were compared with those obtained by experimental flow tests to evaluate the performance of the proposed microdevice. Finally, the functionality of the new milli-bioreactor design was validated by culturing human induced pluripotent stem cells (hiPSC) for 5 days. Cell growth, viability and sustain pluripotency were successfully proved using a new platform architecture. This multidisciplinary research provides new insights into the chemical engineering and operability of micro and milli-bioreactors with prospects for future industrial applications.

Seismic Imaging and 3D Architecture of Yongle Atoll of the Xisha Archipelago, South China Sea

AbstractYongle atoll in the Xisha (Paracel) Archipelago is an isolated carbonate platform developed on Precambrian metamorphic and Mesozoic volcanic rocks since the early Miocene. To identify the 3D stratigraphic architecture and evolution of this platform, 13 high‐resolution seismic profiles and shallow‐to‐deep water multi‐beam data were processed and analyzed to reveal seismic facies, sequence boundary reflectors, seismic units, and platform architecture. Nine types of seismic facies were recognized based on their geometry, which included seismic amplitude, continuity, and termination patterns; additionally, six reflections, i.e., Tg, T60, T50, T40, T30, and T20, were identified in the Cenozoic strata. Five seismic units, SQ1 (lower Miocene), SQ2 (middle Miocene), SQ3 (upper Miocene), SQ4 (Pliocene), and SQ5 (Quaternary), were identified from bottom to top across the platform. The platform grew rapidly in the middle Miocene and backstepped in the late Miocene–Pliocene. Here, we discuss the developmental characteristics and evolution of the Yongle Atoll, in combination with drilling wells, which can be divided into four stages: the initiation stage in the early Miocene, the flourishing stage in the middle Miocene, the partial‐drowning stage in the late Miocene–Pliocene, and modern atoll in the Quaternary.

Feasibility of UTS Smart Home to Support Sustainable Development Goals of United Nations (UN SDGs): Water and Energy Conservation

The Sustainable Development Goals of the United Nations strive to maximize development needs, while minimizing environmental deterioration, without jeopardizing the needs of future generations. Nevertheless, due to urbanization, the escalating trend in natural-resource use, particularly electricity and water, is currently a crucial challenge for sustainable development. One of the promising options is the smart home, which is an extension of building automation with smart characteristics in monitoring, analyzing, controlling, and cloud computing with networked smart devices. Due to the lack of appropriate infrastructure and conscious consumption, its global adoption in the construction industry remains low. We present a technical feasibility of a multi-functional experimental smart home to support the Sustainable Development Goals of the United Nations in terms of water and energy conservation. The layered architecture of the cloud platform with an application program interface enables seamless integration of heterogeneous smart-home technologies and data sources. Use cases demonstrated its capacity to conserve electrical energy and water resources in support of the United Nations’ Sustainable Development Goals. Aside from that, the smart home’s electricity self-consumption of at least three autonomy days was confirmed with zero emissions and electricity bills, and a reduced supply-water consumption.

Backstepping patterns of an isolated carbonate platform in the northern South China Sea and its implication for paleoceanography and paleoclimate

Backstepping of carbonate platform margins is an important process for understanding how carbonate platform responds to paleoenvironment changes. The products of backstepping, such as backstepped margin, backstepping surface and backstepping succession have been widely documented on both modern and ancient platforms around the world. However, the causes of platform backstepping have not been understood fully yet. This study presents a detailed description of variations in backstepping pattern of Xuande platform in the northern South China Sea using 2D seismic and bathymetric data. The results show two episodes of backstepping events occurred during the late Middle Miocene and the latest Miocene to the Early Pliocene. The former backstepping event occurred on the eastern margin of the platform and likely resulted from upwelling and turbulence related to the onset of contour currents in the Xisha Archipelago. The latter backstepping event shows a change of backstepping distances at different platform margins with more pronounced backstepping along the winter-monsoon windward side compared to the corresponding leeward side. It is proposed that this event was largely the result of vigorous currents and waves impinging on the platform margins related to an intensification of the East Asian monsoon and a relative sea-level rise. A difference in hydrodynamic energy was responsible for the variations in backstepping distances at platform margins. Platform margins exposed to higher-energy environment backstepped further than margins exposed to lower-energy envrionment. Results from this work indicate the morphology and stratigraphic architecture of carbonate platforms are strongly controlled by the hydrodynamic energy, here related to currents and waves driven by East Asian monsoon winds.

The Design and Implementation of Geospatial Information Verification Middle Platform for Natural Resources Government Affairs

Geospatial Information Verification Mid-End Platform for Natural Resource Administration is designed in response to issues such as repeated development, low scalability, and inconsistent verification rules in existing approval and supervision application systems. We first discussed the architecture of the middle platform and micro-services and also examined the business requirements. Secondly, we presented the architecture of the spatial information verification platform. Finally, the application method in the construction land approval business is introduced. Practical applications proved that the spatial information verification platform is highly scalable and maintainable, with reusable business components and data services for a variety of government affairs application systems.

Promoting Online Civility Through Platform Architecture

This study tests whether the architecture of a social media platform can encourage conversations among users to be more civil. It was conducted in collaboration with Nextdoor, a networking platform for neighbors within a defined geographic area. The study involved: (1) prompting users to move popular posts from the neighborhood-wide feed to new groups dedicated to the topic and (2) an experiment that randomized the announcement of community guidelines to members who join those newly formed groups. We examined the impact of each intervention on the level of civility, moral values reflected in user comments, and user’s submitted reports of inappropriate content. In a large quantitative analysis of comments posted to Nextdoor, the results indicate that platform architecture can shape the civility of conversations. Comments within groups were more civil and less frequently reported to Nextdoor moderators than the comments on the neighborhood-wide posts. In addition, comments in groups where new members were shown guidelines were less likely to be reported to moderators and were expressed in a more morally virtuous tone than comments in groups where new members were not presented with guidelines. This research demonstrates the importance of considering the design, structure, and affordance of the online environment when online platforms seek to promote civility and other pro-social behaviors.

Construction of Edge Computing Platform Using 3D LiDAR and Camera Heterogeneous Sensing Fusion for Front Obstacle Recognition and Distance Measurement System

This research aims to utilise heterogeneous sensor fusion using 3D Light Detection and Ranging (LiDAR) and cameras, combined with an object recognition system and a ranging system, to construct an edge computing platform such that a vehicle equipped with the platform can perform computations offline in real time. This work comprises two main sections: the first is heterogeneous fusion, and the second is obstacle recognition and ranging detection. To achieve heterogeneous sensor fusion, 3D–3D point matching was used to find rigid body transformation between two sensors and finally project the LiDAR 3D point cloud image onto the 2D image. For object recognition, YOLOv4-Tiny was used as the detection network. A lightweight network architecture and high computational speed could be effectively used on edge computing hardware with limited performance. Further, by drawing the bounding box, we could detect the point cloud within the bounding box to estimate the distance to the obstacle. For detecting distance, we conducted experiments in two ways: ‘minimum point in box’ and ‘median point in box’ and compared the results. With heterogeneous sensor fusion, object recognition and the ranging system, detecting the category and distance of obstacles ahead of the vehicle was possible in real time. Furthermore, integrating the edge computing platform architecture enabled moving the entire system offline, making it an independent system that returns results in real time. Finally, a dynamic test was conducted on a road. The experiment showed that the detection speed of YOLOv4-Tiny in the dynamic test was higher than 60 FPS, and the accuracy rate surpassed 70%. Furthermore, the distance detection error of the 3D LiDAR was less than 3 cm, which is sufficiently accurate to be applied to complex environments on roads.

Construction of School-Enterprise Cooperation Practice Teaching System under the Big Data Internet of Things Industry Collaborative Innovation Platform.

The school-enterprise cooperation practice teaching system has increasingly become the core of the field of education research on the basis of the Internet and mobile communications. Based on the big data IoT theory and relying on the industrial collaborative innovation platform, this study designs and implements a general service platform for school-enterprise cooperation practice teaching for IoT applications. The platform is divided into two parts: the IoT data transmission part and the Web practice teaching service section. On the Internet of Things big data transmission platform, after the big data processing provided by the intelligent industry collaborative innovation end is completed, it disguises as a web practical teaching service platform built by the Internet of things framework based on B/S architecture. It solves the problem of data transmission on the order of millions. During the simulation process, the platform realizes flexible deployment and automatic integration of online upgrades. The code management script module based on scripts such as SQL, Python, and shell can complete the online platform. The automatic upgrade finally achieves the goals of the platform being easy to maintain, simple to deploy, and flexible in business logic. The experimental results show that starting from the actual situation of a digital intelligent collaborative innovation platform in a university, the practical teaching system designed and implemented adopts the object-oriented development method, and has a three-tier architecture of the collaborative innovation platform. In addition, the functional modularization and standardization reach 88.7% and 79.4%, respectively, effectively improving the performance of the practical teaching system.

The Usage of Designing the Urban Sculpture Scene Based on Edge Computing.

To not only achieve the goal of urban cultural construction but also save the cost of urban sculpture space design, EC (edge computing) is combined with urban sculpture space design and planning first. Then it briefly discusses the service category, system architecture, advantages, and characteristics of urban sculpture, as well as the key points and difficulties of its construction, and the layered architecture of EC for urban sculpture spaces is proposed. Secondly, the cloud edge combination technology is adopted, and the urban sculpture is used as a specific function of the edge system node to conduct an in-depth analysis to build an urban sculpture safety supervision system architecture platform. Finally, the actual energy required for implementation is predicted and evaluated, the specific monitoring system coverage is set up, and some equations are made for calculating the energy consumption of the monitored machines according to the number of devices and route planning required by the urban sculpture safety supervision system. An optimization algorithm for energy consumption is proposed based on reinforcement learning and compared with the three control groups. The results show that when the seven monitoring devices cover detection points less than 800, the required energy consumption increases linearly. When the detection devices cover more than 800 detection points, the required energy consumption is stable and varies from 10000 to 12000; that is, when the number of monitoring devices is 7, the optimal number of monitoring points is about 800. When the number of detection points is fixed, increasing the number of monitoring devices in a small range can reduce the total energy consumption. The optimization algorithm based on the reinforcement learning proposal can obtain an approximate optimal solution. The research results show that the combination of edge computing and urban sculpture can expand the function of urban sculpture and make it serve people better.

The Regulatory Architecture of Digital Platforms: A Perspective of Life Cycle and Risk Management

The rise of internet platforms meets people’s needs for a better life. However, the platforms also pose the risk of ecological monopolies. Using the methodology of economic analysis of law, with the help of ANT theory, the laws governing the operation of the platform ecosystem are discovered, and the paper analyzes the life cycle of digital platform development and figures out that the regulatory strategy for platforms should be adjusted to follow its life cycle and adopt more intuitive evaluation criteria for assessing market power. Meanwhile, the regulatory strategy for plat-forms could fully guarantee the active participation of multiple subjects, such as operators and consumers, in the platform’s governance. With the continuous advancement of data and algorithm technology, new content service providers will continue to emerge, and a new industry is developing. Besides the dynamic track analysis of platforms’ life cycles, another static research outcome is also given in this research. To ensure that the algorithmic technologies developed by the platform truly contribute to economic and social development and the well-being of people, the right to interpret algorithms and the establishment of scenario-based regulation of algorithms should be established.

A biotic perspective on the Oligo-Miocene evolution of the Maldives carbonate platform from forward stratigraphic modelling (Indian Ocean)

Forward stratigraphic modelling is a fast-developing modelling approach, used to test conceptual models, and predict stratigraphic architecture and depositional facies from basin to reservoir scales. Published subsurface applications demonstrate its added value by integrating multidisciplinary data as well as geological concepts into its constraints. When applied to carbonate depositional systems, composed of multiple sediment factories, the co-operating and interdependent production mechanisms remain poorly studied. By applying the technique to a well-studied section of the Maldives carbonate platform, a specific model design—adapted to the geological age and setting, and constrained by available data—sheds light on the interaction of its carbonate producers. The results yield a naturalistic depositional facies distribution and offer insight in the changing relationship between biotic communities during the platform evolution. After calibration, the reference model unequivocally links the formerly proposed genetic model to the seismostratigraphic architecture. Furthermore, the results show how environmental changes (seemingly of secondary impact compared to changes in physical accommodation in the stratigraphic record) can induce substantial fluctuations in carbonate production rates of biotic communities, affect the ecological accommodation, and thus impact the platform architecture. Therefore, it is crucial to treat carbonate production rates during periods of environmental change as variables with associated uncertainties in a forward stratigraphic model setup.

PGRNIG: novel parallel gene regulatory network identification algorithm based on GPU.

Molecular biology has revealed that complex life phenomena can be treated as the result of many gene interactions. Investigating these interactions and understanding the intrinsic mechanisms of biological systems using gene expression data have attracted a lot of attention. As a typical gene regulatory network (GRN) inference method, the S-system has been utilized to deal with small-scale network identification. However, it is extremely difficult to optimize it to infer medium-to-large networks. This paper proposes a novel parallel swarm intelligent algorithm, PGRNIG, to optimize the parameters of the S-system. We employed the clone selection strategy to improve the whale optimization algorithm (CWOA). To enhance the time efficiency of CWOA optimization, we utilized a parallel CWOA (PCWOA) based on the compute unified device architecture (CUDA) platform. Decomposition strategy and L1 regularization were utilized to reduce the search space and complexity of GRN inference. We applied the PGRNIG algorithm on three synthetic datasets and two real time-series expression datasets of the species of Escherichia coli and Saccharomyces cerevisiae. Experimental results show that PGRNIG could infer the gene regulatory network more accurately than other state-of-the-art methods with a convincing computational speed-up. Our findings show that CWOA and PCWOA have faster convergence performances than WOA.

Development of a digital educational platform for studying radio engineering courses

The main tasks solved with the help of a digital educational platform with interactive learning opportunities are a remote process of obtaining knowledge, providing permanent access to educational materials, and monitoring the level of students’ performance. This paper considers the development of a digital educational platform for the remote study of modern Ultra high frequency (UHF) and Extremely high frequency (EHF) radio systems. The architecture of the developed platform is a client-server. The server part includes a database of collected laboratory results, and the client part is responsible for displaying and outputting the necessary information. The list of virtual labs that are part of the educational platform, as well as devices and measuring instruments used in the virtual laboratory is presented. An example of a lab with remote access implemented using the Unity 3D application development tool is given. This digital educational platform will be used by students of the «Radio Engineering, Electronics and Telecommunications» educational program to study radio engineering courses. It is shown that the use of virtual laboratory work in the educational process can replace real expensive equipment, as well as consolidate practical skills in training.

A Comprehensive Analysis of Automated Threat Modeling Solution Company: Threat Modeler Software, Inc.

Purpose: Effective Security Threat modeling in an enterprise depends on the efficient tools used for modeling. The Threat modeling tool market has multiple players that provide platforms to automate the Threat modeling process in enterprises. Threat Modeler Software, Inc. is one such platform provider company. The paper aims to explore the company and its platform's features. Design/Methodology/Approach: This paper explores the documentation available on Threat Modeler Software, Inc. to understand the features, working principles, and company information. Features are further explored by performing hands-on Threat modeling using the trial edition of the platform. SWOC analysis of the company is performed to analyze the factors affecting the company as a Threat modeling platform provider. Findings/Result: Threat Modeler Software, Inc.’s platform has innovative features that enable automated Threat modeling. SWOC analysis has identified some of the challenges that the company has. The competitor list showed commercial and open-source competitors in the race to create Threat modeling platforms. The innovative culture of the Threat Modeler Software, Inc. must continue to provide new features making the Threat modeling experience unique. Originality/Value: This paper studies Threat Modeler platform's architecture and explores important features of the platform. Capabilities of the features and their importance is studied. SWOC analysis is performed to identify factors affecting the company. A list of different threat modeling platforms is built to understand the current competitors for Threat Modeler Software, Inc. Paper Type: Case study.

Characterizing the Capabilities of Internet of Things Analytics Through Taxonomy and Reference Architecture

The increasing prevalence of business cases utilizing internet of things (IoT) analytics, coupled with the diversity of IoT analytics platforms and their capabilities, poses an immense challenge for organizations seeking to make the best choice of IoT analytics platform for their specific use cases. Aiming to characterize the capabilities of IoT analytics, this article presents a reference architecture for IoT analytics platforms created through a qualitative content analysis of online reviews and published implementation architectures of IoT analytics platforms. A further contribution is a taxonomy of the functional and cross-functional capabilities of IoT analytics platforms derived from the analysis of published use cases and related business surveys. Both the reference architecture and the associated taxonomy provide a theoretical basis for further research into IoT analytics capabilities and should therefore facilitate the evaluation, selection, and adoption of IoT analytics solutions through a unified description of their capabilities and functional requirements.

Helix Multi-layered: a context broker federation for an efficient cloud-to-things continuum

Next-generation networks offer a flexible virtualized infrastructure that aligns back-end platforms for the Internet of Things with the management and orchestration (MANO) platforms. Together, they can synchronously support and improve application performance while establishing a cloud-to-things continuum. This study examines the architecture of the Helix Multi-layered technology platform designed for the management and distributed processing of context information through horizontal and vertical data federation techniques through a multi-level approach. We set out the architecture of the Helix Multi-layered platform with regard to its internal components, operating modes, and steps of its integration process, together with the 5th Generation (5G) mobile network infrastructure mediated by the Novel Enablers for Cloud Slicing (NECOS), a Lightweight Slice-Defined Cloud (LSDC) platform. The integration of NECOS and Helix Multi-layered platforms is examined in a test laboratory. In the article, experiments are carried out to compare the internal processing time of Helix Broker with that of Orion Context Broker, FIWARE’s main context broker. An assessment is made of the performance of some operating modes with the aim of achieving low latency in communication between the devices located at the edge. The experiments showed One-Way-Delay (OWD) values close to those of the Ultra-Reliable Low Latency Communications (uRLLC) requirements that are expected in 5G mobile networks.