Platform Environment Research Articles

A wireless power transfer system for an autonomous underwater vehicle based on lightweight universal variable ring‐shaped magnetic coupling

SummaryThe existing wireless power transfer systems for autonomous underwater vehicles (AUVs) have problems due to long transmission distances and the unstable attitudes of AUVs, which result in poor system performance. To solve this problem, this paper proposes a lightweight universal variable ring‐shaped magnetic coupler for the shape characteristics of AUVs and the charging platform environment. In particular, the size of the magnetic coupler transmitter can be varied according to the size of the AUV, resulting in a close fit between the magnetic coupler transmitter and receiver, reducing the transmission distance and fixing the AUV attitude. To achieve a lightweight receiver and reduce the burden on the AUV, the design is optimized in terms of both the system topology and the magnetic coupler structure. First, the LCC‐S topology is used to reduce the number of components on the secondary side. Second, the use of a nanocrystalline ribbon as the core material effectively reduces the weight of the magnetic coupler receiver. Finally, a 300‐W experimental platform is built to verify the functionality of the designed magnetic coupler. The experimental results show that the system has a DC‐DC transfer efficiency of 86%. With the variable ring‐shaped magnetic coupler, the charging power can be increased by 7.2% when the transmission efficiency remains unchanged.

E-commerce Platform Data Governance Environment: Concepts, Elements and Implications

Multi-agent participation in data governance is the future trend of data governance research. However, multi-agent participation increases environmental uncertainty for enterprises to implement data governance activities to a certain extent, and the externalities generated by data governance activities still need to be studied. Taking E-commerce platform as an example, this paper aims to explore the conceptual elements of data governance environment and provide practical guidance for promoting multi-subject participation in the data governance process. By using the methods of literature research and theoretical deduction, this paper defines the concept of data governance environment for the first time, defines the core elements of data governance environment, and defines the data governance environment of E-commerce platform as an interactive system composed of data governance participants such as government, platform and users based on system theory and stakeholder theory. It is the space for data and information exchange during data governance activities, and it is the sum of factors that can directly or indirectly affect the data governance process of each participant. E-commerce platform data governance environment is mainly composed of government-level environment, platform-level environment and user-level environment. The environmental elements at the government-level include data policy and industrial policy; the environment at the platform-level consists of data environment and non-data environment; and the environment at the user-level includes personal cognitive ability, personal data literacy and personal privacy awareness.

Dynamics of control on digital platforms

AbstractDigital platforms are supraorganizational entities that use digital technology to facilitate interactions between diverse actors, leading to novel forms of organisation and accompanying forms of control. The current Information Systems (IS) literature, however, struggles to describe control on digital platforms in a way that does justice to the dynamic character of the phenomenon. Taking this as an opportunity, we follow the enactment of control over time and across parties in a hybrid ethnographic study of the social commerce platform Poshmark. Specifically, we conceptualise the dynamics of control as changes in the means of control—formal or informal—and the sources of control—operator or participants—over time. Tracking these conceptual dimensions, we identify the distinct ways control has changed on Poshmark. Synthesising these findings into four dynamics of control, we show that control on digital platforms is rarely static due to aggregate effects arising from the operator and from participant interactions with each other through the digital features deployed on the platform. Based on these insights, our study contributes to the IS literature on control by broadening the conception of control on digital platforms. The theoretical and practical insights generated in this paper thereby lay the foundation for the systematic study of the dynamics of control that are unique to platform environments.

메타버스 플랫폼을 활용한 평생교육의 학습 실재감이 몰입감, 흥미, 학습만족에 미치는 영향

Objectives This study aims to suggest strategies and implications for metabus education in lifelong education institutions. Methods For this purpose, 114 lifelong learners who use the metabus platform in Chungcheongbuk-do were tested to measure learning presence, immersion, interest, and learning satisfaction. In the structural equation model, learning presence as exogenous variable, immersion, interest, and learning satisfaction as endogenous variable were selected, and SPSS 21 and Smart PLS 3.0 statistical program were used. Results The results of this study are as follows: First, the design, background, and surrounding environment should be continuously provided to learners to choose a new environment of the metabus platform. Second, the interest of the class should be provided through the provision of credits to decorate the avatar through simple quizzes related to the class. Finally, it is necessary to increase the satisfaction of education by providing various benefits when developing metabus education programs and participating in education. Conclusions The results of this study provide strategies and implications for education to metabus lifelong education officials.

Methodological aspects of digital platform management

Digital platforms are the largest data aggregators and beneficiaries in the digital economy. Digital platforms operate at micro, meso, macro and mega levels in various formats and in almost all areas of human activi-ty. Platform companies have a number of unique competitive advantages compared to traditional com-panies and require specific methods, models and management tools. The research objective is to deter-mine the features of the functioning of digital platforms and develop methodological foundations for the formation of models for managing digital platforms. The theoretical and methodological basis of the study are the works of domestic and foreign scientists on the problems of managing digital platforms and digital transformation. Results. In the course of the research, the classification of digital platforms was generalized and systematized, based on the analysis of domestic and foreign experience in 10 classification criteria. Organizations and meta-organizations can have multiple types of boundaries, so there are ad-vantages to developing a holistic view that can reveal complementarity and interaction between them. Not-ing that there is an interaction between different types of boundaries, the boundaries of a digital platform can be defined as a combination of the scope, configuration, and digital interface of the platform. In addi-tion, it should be noted that due to the specifics of digital platforms, we consider it appropriate to single out the digital environment along with the external and internal, some of the digital environment factors can be attributed to the external environment, and some to the internal, while the boundaries of the digital envi-ronment are open. Analysis of the element-by-element model of the digital platform made it possible to highlight its distinctive features. The core value of a platform company is not a classic physical unit of val-ue, but an infrastructure that enables interaction between producers and consumers. Conclusion. Thus, key interaction design is the core of every digital platform. Key interaction is the reason why participants use digital platforms. The anatomy of a key interaction consists of four characteristics: value creation, connec-tion, consumption, compensation. Various participants can be categorized as platform core, platform par-ticipants, and platform environment.

Algorithms and hegemony in the workplace: Negotiating design and values in an Italian television platform

In recent years, several scholars have highlighted the necessity to scrutinize the practices and material settings in which algorithmic models are designed, in order to unpack the working activities and socio-cultural constructs underlying their production and deployment process. Drawing on a multisited ethnography, this paper investigates the practices of tech workers within the corporate environment of an internet television platform, the hierarchical relationships between different professional figures, and how these individuals frame algorithms and contribute to the enactment of these systems with their activities. Findings highlight the hierarchical organization of tech work and the subordination of operative figures to the goals imposed by business clients and to both internal and external forms of control. Specifically, it emerges how the subalternity of tech workers is materially and discursively constructed and forms of causal, dispositional and facilitative power exerted on them. In this environment, frictions, negotiations as well as concealing strategies by tech workers regarding the design and meaning of algorithms emerge, thus showing their cultural, contingent and multiple composition. Within the framework of Giddens’ structure/agency cycle, it is shown how everyday working activities and relationships contribute to the reproduction of hegemonic arrangements in the workplace, and how these hegemonic arrangements are at the core of algorithmic production, thus playing a key role in the framing, construction and enactment of these systems.

Amazon and Online Competitor Prices: The Role of Shipping Costs in a Hybrid Platform Environment

Amazon and Online Competitor Prices: The Role of Shipping Costs in a Hybrid Platform Environment

New traces of regulation of information platforms and a platform-based economy for the new public good

The paper offers the authors’ vision of a new problem for Ukraine, but not new for the Western and Eastern world – how to regulate some rising information platforms and the platform-based economy. The purpose of this article is to critically analyze the current global practice of public regulation of information platforms and, based on this, to determine new trajectories of their regulation for the greater public good and renewal of public administration. The step-by-step logic of the presentation of further material in the article is as follows: 1) critical generalization of the essential effects of information platforms for the economy and public administration; 2) modern transformations in the essence of the platform economy; 3) an overview of the essence of the existing state regulation of platforms, which departs from the regulation of purely competition, and is more aimed at the regulation of socio-economic development, 4) clarify the state and supranational regulatory approaches to platforms and the directions of their changes now in the Western world. In general, the paper is a continuation of the ongoing broad expert and political debates about what, how and who to regulate in the new platform environment, the participants of which are or soon will be almost all people. The authors pay considerable attention to the overview of regulatory issues, practices and approaches, and in particular to the latest European laws on digital markets and digital services. Together, these two laws establish a new trend to regulate not only competition, but also very broad socio-economic processes in countries that have already encountered practical difficulties in social transformations and conflicts, and this process will definitely not be quick.

Causes and Behavioral Evolution of Negative Electronic Word-of-Mouth Communication: Considering the Mediating Role of User Involvement and the Moderating Role of User Self-Construal

The purpose of this study is to develop a framework to examine the intrinsic driving paths of negative electronic word-of-word. In this paper, the “contextual” factor—user involvement, and the “individual” factor—user self-construal were selected to consider their influence on the model path. Data were collected using online questionnaires; then, the model and hypotheses were tested using structured equation model (SEM) software. The research results showed that, firstly, negative online shopping experiences positively influence eWOM motivations, and user involvement partially mediated the relationship between negative product quality, negative online shopping platform environments and negative eWOM motivations; secondly, there was a significant correlation between negative eWOM motivations and eWOM behavior, and the personality traits of the communicators themselves influenced the path of “negative eWOM motivation-negative eWOM behavior”. In addition, the user’s self-construal has a significant moderating effect on the “eWOM motivation–immediate eWOM behavior” path under immediate eWOM behavior.

A systematic analysis of the power skiving process using a novel gear manufacturing simulation software

The complex kinematics of power skiving along with demanding requirements for specialised machines and tools create the need for accurate simulation of the manufacturing process. Pertinent simulations of the chip geometry and developing cutting forces may offer invaluable information regarding the expected tool life. In this work, a novel simulation software is presented aiming to predict the chip geometry and the developed cutting forces within the user-friendly environment of a commercial CAD platform. Several case studies regarding spur and helical gears are considered to showcase the proposed software's utility in simulating the production of industrial gears. The produced gear flanks are verified by direct comparison with the theoretical ones, whereas the calculated forces are validated with respect to measured forces obtained from the literature. The verified software can greatly streamline industrial gear processes by optimizing the process of power skiving.

SWOT Analysis and Recommendations about the Cross-border E-commerce AliExpress Russia

with the development of information technology and cross-border logistics, and the bilateral trade policy support, cross-border e-commerce between China and Russia experienced a rapid growth in the past decade. To date, AliExpress Russia, the e-commerce platform under Alibaba Group, becomes the largest cross-border e-commerce platform in Russia. Although the transaction scale of AliExpress Russia, as reflected by Gross Merchandise Volume, achieved a steady growth in recent years, the market share of AliExpress Russia was gradually overtaken by Wildberries and Ozon (two Russian e-commerce enterprises) since 2018. This paper is aiming to determine the underlying reasons on the declination of the market share encountered by AliExpress Russia. A systematic analytical method, the SWOT analysis, is employed to reveal the internal and external environment of the cross-border platform simultaneously. It is possible to determine the problem of infringement and counterfeiting, costly and inefficient logistics, and underdeveloped credit system are three internal factors impinging the development of AliExpress Russia platform. Moreover, increased level of market competition combined with tightened cross-border e-commerce policy are two external threats. It is believed that the Alibaba Group should adopt the SO (Strengths – Opportunities) and ST (Strengths – Threats) strategy to combine its internal advantages and external opportunities while minimizing its potential risk exposure. By optimizing supply chain system, deepening localization process, constructing a diversified payment system with high reliability, and improving the companies’ core competitiveness, AliExpress Russia can seize the opportunity of promising future Russian e-commerce market and develop its brand influence.

Large-Scale Distributed System and Design Methodology for Real-Time Cluster Services and Environments

The demand for a large-scale distributed system, such as a smart grid, which includes real-time interconnection, is rapidly increasing. To provide a seamless connected environment, real-time communication and optimal resource allocation of cluster microgrid platforms (CMPs) are essential. In this paper, we propose two techniques for real-time interconnection and optimal resource allocation for a large-scale distributed system. In particular, to configure a CMP, we analyze the data transfer rate and utilization rate from the intelligent electronic device (IED), collecting the power production data to the individual controller. The details provided in this paper are used to design a sample value, i.e., raw data transfer, on the basis of the IEC 61850 protocol for mapping. The choice of sampled values is to attain the critical time requirement, data transmission of current transformers, voltage transformers, and protective relaying of less than 1 s without complicating the real-time implementation. Furthermore, in this paper, a way to determine the optimal number of physical resources (i.e., CPU, memory, and network) for a given system is discussed. CPU ranged from 0.9 to 0.98 while each cluster increased from 10 to 1000. With the same condition, memory utilized almost 100% utilization from 0.98 to 1. Lastly, the network utilization rate was 0.96 and peaked at 1 at most. Based on the results, we confirm that a large-scale distributed system can provide a seamless monitoring service to distribute messages for each IED, and this can provide a configuration for CMP without exceeding 100% utilization.

Research on Abnormal Behavior Prediction by Integrating Multiple Indexes of Student Behavior and Text Information in Big Data Environment

With the wide application of information technologies such as big data, the Internet of Things, and cloud computing, college students have accumulated a large amount of personal information and daily behavior data in their daily studies and life. How to dynamically integrate multidimensional information of students to build accurate student portraits, using multi-indicator data of student behavior and comment texts, and finding out students with abnormal behavior from among many students has become an important problem to be solved. This paper proposes an abnormal behavior prediction method integrating multiple indicators of student behavior and text information (ABPM-IMISBTI) for the problem of abnormal behavior prediction of college students in the big data environment. First, given the problems of multidimensionality, timeliness, and dynamics of student behavior information fusion in the construction of student behavior portraits, by integrating students’ objective tags and subjective tags, an optimized K-means algorithm based on a cloud platform environment is proposed. Second, aiming at the problem of insufficient text information analysis in the analysis of students’ abnormal behavior, the ABPM-IMISBTI method is proposed to solve the prediction of students’ abnormal behavior through long and short-term memory networks (LSTM) combined with student behavior multi-index data and text information. Finally, this paper takes student achievement prediction as an example for verification. The experimental results show that, compared with other prediction methods, the ABPM-IMISBTI method proposed in this paper can improve the accuracy of student behavior prediction, and then quickly determine the abnormal behavior of students, to improve the level of education management in universities and promote the development of safe campuses, smart campuses, and smart education.

Biostratigraphy and paleoenvironmental significance of Paleogene foraminiferal assemblages from Dashte Zari area in High Zagros, West Iran

The Paleogene carbonate deposits of Pabdeh and Jahrum formations are widespread from the northwest (Dashte Zari area) to the southwest of the Shahrekord region in the High Zagros Mountains of Iran and record the lateral and upward transition from open marine into the shallow water environment. The Pabdeh Formation shows a succession of open marine pelagic and hemipelagic limestone, argillaceous limestone, and argillaceous chert. It consists of planktonic wackestone, pellet-planktonic wackestone, mudstone with planktonic foraminifera, and radiolarian siliceous wackestone, which accumulated within the Zagros Foreland Basin. The planktonic foraminifers are assigned to the Late Paleocene–Late Eocene and correspond to subtropical and tropical Zones P4b–E15. The Jahrum Formation is represented by bioclast-bearing limestone and calcarenite. It consists of benthic foraminiferal wackestone, benthic foraminiferal-red algal packstone, and bioclast-intraclast packstone deposited in a shallow platform environment. The Jahrum Formation is inter-fingered in the upper part of the Pabdeh Formation and finally overlies it conformably during the Bartonian–Priabonian. Shallowing and off-lap relationships record basin shrinking, while repeated inter-fingering signals moderate tectonic subsidence. Both formations are disconformably covered by the Late Oligocene–Miocene Asmari Formation. Keywords: biostratigraphy, Pabdeh Formation, Zagros, Paleogene, Iran.

Molecular record of the SPICE event in well YD2, Tarim Basin: Insights from catalytic hydropyrolysis of kerogens

The Steptoean Positive Carbon Isotope Excursion (SPICE) event is extensively documented in globally distributed carbonate and organic-rich successions of slope and platform environments during the late Cambrian (ca. 497–494 Ma). Despite numerous studies, its regional manifestation remains controversial because of the major uncertainty of the redox conditions in sedimentary paleoenvironments and its effect on the changes in the biota. Biogeochemical processes that occurred during the SPICE event are important for assessing whether the excursion is associated with the co-evolution of organisms and environments. In this study, we investigated the changes in plankton and paleoenvironment at the molecular level by combining kerogen elemental analysis, catalytic hydropyrolysis (HyPy), and gas chromatography-mass spectrometry (GC-MS) analyses of saturates and aromatics with published carbon isotopic data. The three fluorene series, gammacerane/C30hopane (G/C30H) and pristine/phytane (Pr/Ph) ratios demonstrated that the shallow shelf seawater changed significantly from relatively reducing to oxidizing and back to reducing conditions during the SPICE interval coupled with a regression-transgression cycle. The phytoplankton during the rise of the SPICE were mainly organic-walled, such as cyanobacteria, various acritarchs, and algae, as evidenced by terpanes, hopanes, and steranes. Significant decreases in phytoplankton diversity and abundance coincided with the peak of the SPICE, corresponding to the most oxidized and hypersaline periods during the SPICE event in the eastern Tarim Basin. Plankton assemblages diversified significantly with increasing living space due to the rise of sea-level during the post-SPICE period. Therefore, this study supports the idea that plankton groups changed dramatically with the environment, and its revolution followed the SPICE into the Great Ordovician Biodiversification Event.

ChSO-DNFNet: Spam detection in Twitter using feature fusion and optimized Deep Neuro Fuzzy Network

The usage of social networking platforms for interaction and meeting has grown significantly. However, as social networks continue to expand, Twitter has emerged as a vital social media for real life and has become a major source of spam. To address the aforementioned problems, spam identification on social media becomes an increasingly crucial task. The features that are present in the high dimension data of social networks cannot be used effectively by the existing approaches. In order to filter the spam information in social media, a Chimp Sailfish Optimization-based Deep Neuro Fuzzy Network (ChSO-based DNFN) is proposed. The proposed method effectively performs well under high dimensional data in real platform environment using deep learning classifier. It is more robust and generates optimal result and also reduces the computational complexity problems. Additionally, the proposed approach demonstrated improved performance in terms of metrics like precision, recall, and F-measure, which were measured using a 5k continuous dataset and yielded values of 0.894, 0.903, and 0.898, respectively.

Platformization as a Structural Dimension for Public Service Media in Germany: The funk Content Network and the New Interstate Media Treaty

As social media is constantly gaining in importance, public service media (PSM) is forced to create content that fits the environment of social media platforms (SMPs). In Germany, the content network funk by the ARD and ZDF represents a change in the thinking of PSM and policy makers. Since platformization affects PSM institutionally and structurally, German media regulators are addressing platformization in the context of the new Interstate Media Treaty. The article aims to discuss the treaty’s orientation toward digital platforms and SMPs as it attempts to subject them to the control of local state media authorities. Algorithms and data-driven content curation are policed in terms of transparency and non-discrimination, and to ensure that public value content is not marginalized. To enforce this, I would argue, the treaty has to acknowledge the importance of platformization as a structural prerequisite that enables PSM to serve its public demand.

Multi-service value chains collaboration for repairperson resources selection using a many-objective evolutionary algorithm with adaptive reference vectors

When facing with rising demand for repair services and technical problems, service stations with limited resources suffer a decline in service quality. However, high-quality service is essential for customer retention. The purpose of this paper is to solve the problem by sharing and allocating repairperson resources across multi-service value chains in order to improve the quality of after-sales repair services. Firstly, based on the multi-service value chain collaboration model in a third-party cloud platform environment, a repairperson resources selection model is proposed to balance the multi-service value chain repairperson resources, considering the interests of resource users, resource providers, and the third-party cloud platform simultaneously. Secondly, a many-objective evolutionary algorithm with adaptive reference vectors(EAARV) is designed to solve the resources selection model with an irregular Pareto front. Finally, a case study is conducted to compare the performance of EAARV with seven state-of-the-art evolutionary optimization algorithms for solving many-objective optimization problems and to validate its viability. The experimental results show that EAARV outperforms others in solving the repairperson resources selection problem, and the selection model considering multi-service value chains collaboration is proven to promote the utilization of service resources. The satisfaction rate of repairperson resources with multi-service value chains collaboration is significantly higher than the single-service value chain collaboration. Meanwhile, the parameters of EAARV are analyzed and an ablation experiment is conducted to further evaluate the influence of each component in EAARV on the performance.

Methodology to integrate augmented reality and pattern recognition for crack detection

AbstractIn‐field visual inspections have inherent challenges associated with humans such as low accuracy, excessive cost and time, and safety. To overcome these barriers, researchers and industry leaders have developed image‐based methods for automatic structural crack detection. More recently, researchers have proposed using augmented reality (AR) to interface human visual inspection with automatic image‐based crack detection. However, to date, AR crack detection is limited because: (1) it is not available in real time and (2) it requires an external processing device. This paper describes a new AR methodology that addresses both problems enabling a standalone real‐time crack detection system for field inspection. A Canny algorithm is transformed into the single‐dimensional mathematical environment of the AR headset digital platform. Then, the algorithm is simplified based on the limited headset processing capacity toward lower processing time. The test of the AR crack‐detection method eliminates AR image‐processing dependence on external processors and has practical real‐time image‐processing.

Depositional environments and transgression-regression cycles in the Mural Limestone, central Sonora, Mexico

Results of analytical studies in the Mural Limestone of the Bisbee Group exposed in northwest Mexico, carried out to determine the paleo-bathymetry of the marine depositional environment, reveal that deposition occurred in a restricted carbonate platform environment, varying from inner-neritic to shelf margin with the development of lagoon, shoal and biohermal conditions, reflecting minor transgression-regression cycles. Furthermore, the fossiliferous content and lithological characteristics support the interpretation that the studied section corresponds to the transition between Cerro La Puerta and Cerro La Espina members of the Mural Limestone.