Types Of Platforms Research Articles

Impact of AI-Oriented Live-Streaming E-Commerce Service Failures on Consumer Disengagement—Empirical Evidence from China

Despite the popularity of AI-oriented e-commerce live-streaming, the service failures that can result from real-time interaction and instant transactions have not been taken seriously. This study aims to assess the failure of AI-oriented live-streaming e-commerce services and help retailers identify various risks. Based on expectancy disconfirmation theory and a stressor–strain–outcome framework, this study identified a comprehensive framework including information, functional, system, interaction, and aesthetic failures. The structural equation modeling (SEM) method is used to further examine its effect on consumers’ discontinuance behavior. Further research reveals the mediating role of consumer disappointment and emotional exhaustion, as well as the moderating role of the live-streaming platform type. These results shed light on the negative influence of AI-oriented live-streaming e-commerce service failures and contribute to the literature on live-streaming commerce, service failure, and virtual streamers.

Forward Chaining Method in Expert System for Diagnosing Pests and Plant Diseases: A Systematic Literature Review

Pest and disease attacks on plants are very detrimental factors for farmers. Lack of knowledge leads to a difficult diagnosis of attacks and slow control. The technology that can help farmers in diagnosing plant pests and diseases is the expert system. One of the most widely used algorithms is forward chaining. Although there have been many used further research is needed to determine the effectiveness of this method. This research wants to find out more advantages, types of platforms used, and benefits of expert systems with forward chaining algorithms. This study uses a systematic method literature review (SLR) to collect, assess, and analyze data systematically from various scientific articles. The results of the study show that the use of forward chaining has advantages and benefits for developers and farmers.

Depositional facies and evolution of sponge-microbial-constructed carbonate platforms in the lower Cambrian (Stage 3), Tarim basin, China: Understanding from anatomy

The early Cambrian was generally considered the earliest time interval while the archaeocyaths could act as the constructors in building reef framework although commonly coexisting with the microbial constructors (Epiphyton and Renalcis) in the course of the “Cambrian explosion”; however, this kind of metazoan-microbial buildups has not yet been reported in Tarim Basin. To delineate facies (associations), spatiotemporal variations, reef-building processes of metazoan-microbial constructed ramps/shelves and evolution, detailed anatomy was carried out upon the lower Cambrian Xiaoerbulak Formation (or Stage 3) exposed continuously along a marginal transect (∼2 km wide) in Aksu area, northwestern Tarim Basin. Three platform types with distinctive facies associations are distinguished: (1) sponge-microbial biostrome/mound-colonized homoclinal and distally-steepened ramps recorded respectively in the Lower Member and basal Middle Member, (2) Archaeocyath-Epiphyton reef- and microbial reef-rimmed platforms (or shelves) in the mid-upper Middle Member, and (3) microbial biostrome-colonized ramp in the Upper Member, thus illustrating the evolution from the ramp to reef-rimmed platform and final reversion to the ramp system. Four and a half third-order depositional sequences are further identified: one in the Lower Member, two in the Middle Member and one and half (TST) in the Upper Member, although, at least, one sequence was absent in the platform/ramp interior. All these can be well correlated with those in equivalent successions identified elsewhere around the world, implying a basic control of eustatic changes on platform development and evolution. Moreover, syndepositional faulting/sliding that occurred off the ramp margin, as demonstrated by slope failure/collapse, may have enhanced the relief difference between the inner and mid-outer ramps, promoting metazoan-microbes to colonize and build up wave-resistant architecture on the uplifting margin, forming the reef-rimmed platform (or shelf) system as typified in the Middle Member. Meanwhile, the development of wave-resistant, metazoan-microbial reef complexes also benefited from their concurrently-gained calcifying ability, which likely resulted from the instinctive biotic responses to the changes in climate and oceanic chemistry (i.e., pCO2, seawater Mg/Ca ratio) in the early Cambrian. The new datasets of this study fill previous information gap on the early Cambrian metazoan-involved buildups that had controlled the platform configuration and evolution in Tarim Basin, which thus are critically important for better understanding of climatic/environmental controls on their occurrence and evolution of the time-specific reef complexes in the course of “Cambrian Explosion”. Additionally, these datasets would provide a useful analogue for perceiving the facies-constrained porosity and heterogeneity in the deeply buried counterparts in the basin, helpful for making exploration strategy for the deeply-buried hydrocarbon resources.

Value-added services and e-commerce platform competitiveness: a game theoretic approach

PurposeIn response to the intense competition in the platform economy, e-commerce platforms are actively introducing value-added services to maintain their competitiveness. However, how effective these value-added services are in fulfilling this purpose remains unclear. This paper explores how value-added services can enhance e-commerce platform competitiveness, measured by both user scale and reputation, considering the effect of network externalities.Design/methodology/approachA bilateral e-commerce platform with potential high-quality sellers and low-quality sellers on one side and potential buyers on the other side was chosen as research setting. Game theory models are constructed to simultaneously consider the behaviors of all actors (including sellers, buyers and the platform).FindingsOn the one hand, to increase the seller scale, basic services play a substituting role in determining the effect of value-added services. On the other hand, to increase the buyer scale and improve platform reputation, basic services play a fundamental role in determining the effect of value-added services. Furthermore, the higher the loss rate of the product value, the bigger the room for providing value-added services. With increasing loss rate of the product value, participating buyers who are attracted by value-added services are the fastest growing indicators; this indicates that the most significant effect of value-added services is its increase in the buyer scale.Practical implicationsBasic services determine the lower limit of platform competitiveness, while value-added services set the upper limit. The results of this paper can instruct different types of platforms to enhance their competitiveness in different ways.Originality/value(1) While previous studies on how to enhance platform competitiveness only considered scale or reputation separately, this paper applies a new perspective of platform competitiveness, namely the improvement of both the seller scale/buyer scale and platform reputation. (2) According to the characteristics of bilateral platforms, game theory models are constructed to explore how value-added services can enhance platform competitiveness considering both positive and negative network externalities. (3) The existing literature studies basic services and value-added services in a fragmented state; this paper contributes to research on value-added services by considering the mutual effect between basic and value-added services.

Gender Roles and Mobile Dating Applications: Exploring Links Between User Characteristics and Traditional Gender Expressions in Self-Presentations.

This linkage study examined the prevalence of traditional gender expressions in the textual and visual profile cues on mobile dating applications (MDA) (nbiographies = 396, npictures = 1352) of 396 young adults' (Mage = 22.39 years, SD = 2.86, 73% women) with attention to users' gender, sexual orientation, and platform type. For 184 users (Mage = 22.10 years, SD = 2.91, 75% women) media content data were linked to self-report survey data. Results showed that individuals aligned their self-presentations with traditional gender roles and expectations, and this link depended on their gender. No significant differences according to individuals' sexual orientation or platform type were found. Individuals' (hyper-) gender orientation also related to engagement in traditional gender expressions. Specifically, women with a stronger feminine gender orientation expressed more traditional femininity in their MDA profiles. For men, no significant associations between (aspects of) a masculine gender orientation and expressing traditional masculinity in their MDA profiles were found. Future research should further disentangle selective gendered self-presentations.

Amphibious vehicle's resistance optimization through neural networks and genetic algorithms

Amphibious vehicles, as a new type of aquatic and terrestrial transport platform, are increasingly involved in the existing transportation system. Resistance is a key factor that affects the efficiency and energy consumption of vehicles in aquatic sailing. Resistance reduction optimization design is a focal point and challenge in the design process of amphibious vehicles. In this paper, a resistance performance optimization method has been proposed based on neural networks and genetic algorithms. First, key parameters for the shape design are extracted based on a thorough understanding of the vehicle's performance. These parameters are used to construct a parameterized design space. Second, a training set is obtained based on the Latin hypercube sampling method and numerical calculation methods, and a test set is randomly generated. To achieve better resistance prediction performance, a method based on the genetic algorithm-optimized backpropagation Neural Network is proposed. Next, the resistance performance of the two operating conditions is optimized through the non-dominated sorting genetic algorithm II, and optimized configuration parameters are obtained, which has a 22.71% energy-saving ratio at cruising speed. Finally, the optimized configuration is analyzed using numerical calculation methods to validate the resistance prediction and optimization methods.

New Media's Influence in Shaping Political Awareness, Attitudes and Behaviours: The Media Literacy as a Moderator and Peer Influence as a Mediator

This comparative study delves into the intricate dynamics of new media's influence on political awareness, attitudes, and behaviors among university students in China and Malaysia. It examines how various factors, including media literacy and peer influence, moderate and mediate the relationship between new media consumption habits and political education outcomes. Through a mixed-methods approach, data were collected from Chinese and Malaysian university students, exploring their engagement with different types of new media platforms, content delivery methods, frequency of exposure, perceived credibility of sources, and the influence of peer networks. The study identifies significant challenges and opportunities posed by the evolving digital landscape in both countries, addressing issues such as misinformation, echo chambers, commercialization, digital divide, and disparities in access. Findings reveal nuanced differences in the impact of new media on political education between the two cultural contexts, highlighting the importance of context-specific interventions and educational strategies.

Conceptual Framework for Unified E-Government Web Platform

Abstract Technological development has an impact on various areas, and governments from all over the world search to make a smooth transition from traditional to digital, by adopting dedicated software solutions aiming to facilitate the interaction of citizens with public institutions. These platforms are designed to improve the citizens relationship with government by facilitating various processes and tasks. The importance of having a unified web platform is easily justified. Citizens are no longer in need of searching different platforms for their specific needs, dealing with a lot of interfaces and accounts, as all are gathered in one, maintaining a robust, complex system that is easy to use. Therefore, they would benefit from an integrated digital environment, that meet their needs and expectations, also providing security and privacy of confidential and personal information. The authors present the value of creating such an environment, that has a high technical level, that is user-centered and accessible for interactions between citizens and government. Designing and implementing a unified e-government web platform requires the analysis of various factors and aspects such as user interface, processes, services, security measures, integration with social media platforms, collaborative environment, and many others. First, an investigation on specific literature was made to offer a context to the present research and be used as a starting point, highlighting the main factors related to e-government and the impact of this type of platforms. The model proposed by the authors encapsulates considerations on both sides: government and citizens to offer a detailed understanding on e-government platforms.

DEVELOPMENT OF SOCIAL MEDIA STRATEGIES IN ONLINE NEWS PUBLISHER INDUSTRY (A Case Study In Kapanlagi Youniverse)

Impact of the COVID-19 pandemic has changed the condition of online news publisher industry both in term of economic and existence. The aim of this research is to find out the condition of social media communication strategy KapanLagi Youniverse as a media group in Indonesia for strengthening brand equity. The theoretical foundation of this research is using the Circular Model of SoMe for Social Communications and Brand Equity’s dimension Theory. The research method that will be used in this research is qualitative research with the design of a study case, which the data collected by interview and observation. The result of this research shows that in the pandemic situation KapanLagi Youniverse (KLY) could rise through strengthening their existence as a media group in Indonesia. Social media communication strategy of KapanLagi Youniverse uses the aspect of share (cross platform social media and type of content), optimize (PESO model), manage (media monitoring and user experience), and engage (interactivity and media community approach) in strengthening brand equity. Keywords: Social Media Communication Strategy, Online News Publisher Industry, Brand Equity, Pandemic

Crowdfunding in Portugal—Using the Raize Platform to Ensure the Sustainability of Companies and Projects

This study aims to analyse the reasons why entrepreneurs choose to use collaborative financing through the Raize platform to finance their companies or projects through peer-to-peer crowdfunding (loans). This study is pertinent because it deals with an innovative, differentiated topic that presents itself as a possible disruptive form of financing and an alternative to traditional bank financing. Its use and significant take-up and the rapid and continuous growth of users on this type of crowdfunding platform is a strong sign of the need to better understand and study this phenomenon, its benefits, weaknesses, gaps and future mutations. Based on a comprehensive literature review and sound research methods such as exploratory qualitative multiple-case analysis, the aim is to gain a comprehensive understanding of the reasons why entrepreneurs and businesses choose crowdfunding through the Raize platform as a financing alternative. The aims of this study are to understand how financial accessibility, trust in the investor community, ease of use of the platform, competitiveness of fees and preference for crowdfunding over bank financing influence entrepreneurs’ decision to fund themselves through the Raize platform. The results reveal that entrepreneurs opt for the Raize platform due to a combination of factors. These reasons, clearly highlighted, provide a deeper understanding of entrepreneurs’ decision making in relation to financing their projects through crowdfunding. This study not only contributes to the literature on crowdfunding and entrepreneurship, but also offers practical pointers for entrepreneurs looking to obtain funding through a new financing system that is offered through the Raize platform, as it continues to support innovation and business growth in Portugal. Such funding contributes to and enhances the sustainability of companies in terms of their funding profile and attractive positioning in the market.

A Comprehensive Study of Blockchain Technology and Its Role in Promoting Sustainability and Circularity across Large-Scale Industry

Blockchain technology has evolved as an innovative strategy that substantially transformed industries by offering a variety of applications across multiple domains including manufacturing, construction, supply chain, food, health, energy, transport and retailing industry. By offering a decentralized ledger that enables the source-tracking of materials and goods, blockchain enables a quick, safe, and open information platform. Blockchain is emerging around the globe in industries but limited studies have comprehensively examined its practical implementation toward industrial sustainability and circularity. This paper aimed to provide a comprehensive and thoughtful discussion of blockchain demand, literature gaps in blockchain implementation, type of blockchain platforms in large-scale industries and their contribution toward sustainability by utilizing the systematic literature review methodology. The descriptive analysis of 185 selected articles by thematic analysis provides an overview of the emergence of blockchain over the years and its practical implications in large-scale industries. The novelty of the paper is the in-depth discussion of the major industries of the various sectors that are utilizing different blockchain frameworks, especially P2P, in order to achieve sustainability and circularity in economy. Furthermore, the challenges and barriers that hinder blockchain adoption have also been evaluated.

SMaLL: Software for Rapidly Instantiating Machine Learning Libraries

Interest in deploying deep neural network (DNN) inference on edge devices has resulted in an explosion of the number and types of hardware platforms that machine learning (ML) libraries must support. High-level programming interfaces, such as TensorFlow, can be readily ported across different devices; however, maintaining performance when porting the low-level implementation is more nuanced. High-performance inference implementations require an effective mapping of the high-level interface to the target hardware platform. Commonly, this mapping may use optimizing compilers to generate code at compile time or high-performance vendor libraries that have been specialized to the target platform. Both approaches rely on expert knowledge across levels to produce an efficient mapping. This makes supporting new architectures difficult and time-consuming. In this work, we present a DNN library framework, SMaLL, that is easily extensible to new architectures. The framework uses a unified loop structure and shared, cache-friendly data format across all intermediate layers, eliminating the time and memory overheads incurred by data transformation between layers. Each layer is implemented by specifying its dimensions and a kernel , the key computing operation of that layer. The unified loop structure and kernel abstraction allows the reuse of code across layers and computing platforms. New architectures only require a few hundred lines in the kernel to be redesigned. To show the benefits of our approach, we have developed software that supports a range of layer types and computing platforms; this software is easily extensible for rapidly instantiating high-performance DNN libraries. An evaluation of the portability of our framework is shown by instantiating end-to-end networks from the MLPerf:tiny benchmark suite on five ARM platforms and one x86 platform (an AMD Zen 2). We also show that the end-to-end performance is comparable to or better than ML frameworks such as TensorFlow, TVM, and LibTorch.

Integration of metformin-loaded MIL-100(Fe) into hydrogel microneedles for prolonged regulation of blood glucose levels

The transdermal drug delivery based on microneedles (MNs) provides a suitable and painless self-administration for diabetic patients. In this work, the hydrogel-forming MNs were firstly fabricated using poly(vinyl alcohol) (PVA) and chitosan (CS) as matrix. A hypoglycemic drug, metformin (Met), had been loaded into MIL-100(Fe). Then, both of free Met and Met-loaded MIL-100(Fe) were integrated into hydrogel-forming MNs for regulation of blood glucose levels (BGLs) on diabetic rats. After penetrated into the skin, the free Met could be firstly released from MNs. Due to the absorption of interstitial fluid and subsequent release of loaded Met from MIL-100(Fe), leading to a sustainable and long-term drug release behaviors. A notable hypoglycemic effect and low risk of hypoglycemia could be obtained on diabetic rat models in vivo. The as-fabricated hydrogel-forming MNs expected to become a new type of transdermal drug delivery platform for transdermal delivery of high-dose drugs to form a long-term hypoglycemic effect.

Phage T4-based colorimetric sensing material and its application to develop a time-dependent bacteria sensing platform for long-term detection of food contamination

Herein, we have developed a new type of bacteria-sensing platform for the naked-eye detection of Escherichia coli (E. coli) via a one-spot sample injection process. The platform comprised chlorophenol red-β-d-galactopyranoside (CPRG), isopropyl β-d-thiogalactopyranoside (IPTG), bacteriophages and two carbohydrates namely, maltodextrin and trehalose. CRPG and IPTG detected the β-galactosidase released from the bacteria and enhance its productivity, respectively. Bacteriophages were used as bioreceptors, and two carbohydrates protected phages during thermal process enabling long-term use of the platform. The developed material was characterized using scanning electron microscopy, energy-dispersive X-ray spectroscopy, and X-ray photoelectron spectroscopy to determine the presence of the phages in the microcapsules. The detection property of the sensing material was examined using different strains of E. coli. Cold water-soluble guar gum was used as the stable gel matrix to increase the reactivity of platform toward samples stored at low temperature. The final prototype was tested using food samples containing different E. coli strains to demonstrate its food applicability with long-term use. This approach may provide an efficient and feasible phage-based sensing platform for the detection of bacterial contamination in food samples.

Consumer Purchasing Decisions to Buy Ornamental Plants through E-Commerce in Denpasar City

Ornamental plants have an attractive aesthetic value as well as being visually appealing when planted outdoors or indoors. E-commerce has revolutionized consumer purchasing habits, expanding its influence to diverse sectors, such as the ornamental plant industry. This study investigates the type of platform used in the ornamental plant business in Denpasar and examines the influence of convenience, content, response, security, and trust in purchasing decisions for ornamental plants through e-commerce in Denpasar. The results of this study are that convenience and trust have a positive and insignificant effect on purchasing decisions. Content, security, and response have a positive and significant effect on purchasing decisions. response has a significant effect on increasing purchasing decisions for ornamental plants through e-commerce in Denpasar.

A typology of evaluative health platforms: Commercial interests and their implications for patient voice

Interactions in the healthcare system today involve an important new set of actors: evaluative health platforms (EHPs). These platforms are not neutral intermediaries, but active moderators of how patients express opinions, choose providers, and consume health-related information. This paper adds to our understanding of the varied and evolving commercial interests of EHPs and the implications these have for patient voice. We analyze 71 platforms in the USA, UK, and Germany and identify five ideal types: subscribers, analyzers, advertisers, regulators, and scammers. Each platform type enacts a unique competitive strategy through an evaluative infrastructure which constrains but also generates possibilities for patient voice. Based on our typology, we develop three contributions. First, we nuance universalizing claims about the consequences of platform capitalism by specifying the diverse strategies underpinning competition between EHPs in different countries, and showing how each strategy leads evaluative infrastructures to develop in ways that impact patient voice. Second, we show how patients can navigate the challenges of a complex EHP space by exercising their ability to choose between platforms. Finally, we outline the conditions platforms need to fulfil to become empowering. Overall, this study highlights the varied and complex relationship between platform business models and user voice, which exists not only in healthcare, but also in many other fields.

How Consumer Photo Reviews and Online Platform Types Influence Luxury Hotel Booking Intentions Through Envy

When booking hotels, travelers often rely on content created by other consumers to inform their decisions. This study examines the effect of consumer-generated photos of luxury hotels, specifically those that emphasize the quality of one’s experiences versus the quality of the hotel’s facilities, as well as the type of platform through which such photos are shared, such as social media versus review websites. Drawing on the Social Comparison Theory, this study aims to understand how these factors influence a consumer’s booking intention and overall attitude toward hotels by examining the role of envy. An online experiment employing a 2 (photo content: experience-focused vs. facility-focused) × 2 (platform type: Instagram vs. Tripadvisor) between-subjects design was conducted with 275 American adults. Results showed that photo content significantly influenced the levels of envy among consumers. Specifically, experience-focused photos generated significantly higher levels of envy than did facility-focused photos. Furthermore, envy fully mediated the relationship between photo content and consumer attitudes and behaviors. Both interaction and moderated mediation were found between photo content and platform type. This research contributes to the Social Comparison Theory and the corresponding literature on envy, specifically in the context of luxury hotel marketing and social media consumer behavior. Additionally, it offers practical insights for hotel online review managers to consider, such as which types of photo content and photo sharing platforms to prioritize in order to enhance business value.

A Systematic Review of Multi-Objective Evolutionary Algorithms Optimization Frameworks

The study of evolutionary algorithms (EAs) has witnessed an impressive increase during the last decades. The need to explore this area is determined by the growing request for design and the optimization of more and more engineering problems in society, such as highway construction processes, food and agri-technologies processes, resource allocation problems, logistics and transportation systems, microarchitectures, suspension systems optimal design, etc. All of these matters refer to specific highly computational problems with a huge design space, hence the obvious need for evolutionary algorithms and frameworks, or platforms that allow for the implementing and testing of such algorithms and methods. This paper aims to comparatively analyze the existing software platforms and state-of-the-art multi-objective optimization algorithms and make a review of what features exist and what features might be included next as further developments in such tools, from a researcher’s perspective. Additionally, it is essential for a framework to be easily extendable with new types of problems and optimization algorithms, metrics and quality indicators, genetic operators or specific solution representations and results analysis and comparison features. After presenting the most relevant existing features in these types of platforms, we suggest some future steps and the developments we have been working on.

A multi-organization epigenetic age prediction based on a channel attention perceptron networks.

DNA methylation indicates the individual's aging, so-called Epigenetic clocks, which will improve the research and diagnosis of aging diseases by investigating the correlation between methylation loci and human aging. Although this discovery has inspired many researchers to develop traditional computational methods to quantify the correlation and predict the chronological age, the performance bottleneck delayed access to the practical application. Since artificial intelligence technology brought great opportunities in research, we proposed a perceptron model integrating a channel attention mechanism named PerSEClock. The model was trained on 24,516 CpG loci that can utilize the samples from all types of methylation identification platforms and tested on 15 independent datasets against seven methylation-based age prediction methods. PerSEClock demonstrated the ability to assign varying weights to different CpG loci. This feature allows the model to enhance the weight of age-related loci while reducing the weight of irrelevant loci. The method is free to use for academics at www.dnamclock.com/#/original.

Towing Analysis and Validation of a Fully Assembled Floating Offshore Wind Turbine Based on an Experimental Study

The offshore wind sector is moving into deep waters and using floating platforms to harness the higher wind speeds in exposed locations. There are various floating platform types currently in development, but semi-submersibles are considered the most prominent early movers. Such floaters need to be towed to and from wind farm locations for installation, special cases of repair and decommissioning. As with any other offshore activity, metocean limits exist for towing operations which can impact the development of a wind farm. It is important to calculate the motion and loads of the platform before commencing the towing operations and to check whether they exceed the defined limits to enable safe execution. In this paper, two approaches using two different numerical tools to predict the motion of a fully assembled floating wind platform under tow are presented and compared. A potential flow-based method derived from a low forward speed approach and a hybrid approach combining potential flow and Morison equation methods are investigated, and the numerical predictions are compared and validated against experimental results. Both methods demonstrate accurate predictions, depending on the wave condition and towing speed, albeit differing in execution time and the simplicity of the simulation setup. The first method was found to provide good predictions of the motion in low-speed (0.514–1.543 m/s) towing conditions. The second method provides better results for all the towing speeds and wave heights. As the wave height and towing speed increase, deviations from experiments were observed, signifying non-linear phenomena that are difficult to analyse using the mentioned potential-flow-based methods.