Types Of Platforms Research Articles

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.

User experience and interface assessment for metaverse platforms on nurses and nursing students: A cross-sectional study

BackgroundThe metaverse, a rapidly evolving virtual environment, offers new opportunities for healthcare education. The effectiveness of the metaverse as a learning tool depends on user readiness and platform characteristics. AimThis study aimed to examine the current use of metaverse platforms among nurses and nursing students in South Korea and explore the relationship between user characteristics and their metaverse experience, focusing on presence, usability, and user experience. DesignThis was a cross-sectional descriptive study. SettingsRegistered nurses and nursing students from various healthcare settings and educational institutions in South Korea participated in this study. ParticipantsThis study included 428 participants, comprising 188 nurses and 240 nursing students. MethodsBetween September and November 2022, participants provided voluntary informed consent. The participants engaged with one of the following two metaverse platforms: ZEPETO (mobile-based) or Gather (screen-based). After four structured exploration phases, the participants completed online questionnaires. These surveys assessed general characteristics, metaverse self-efficacy, sense of presence, usability, and user experience. ResultsMost participants had previous experience with the metaverse and rated their metaverse self-efficacy at 3.60. Nurses scored higher than nursing students in terms of presence, usability, and user experience in the metaverse. Higher work self-efficacy in nurses and academic self-efficacy in nursing students were associated with more positive experiences in the metaverse. Nurses consistently rated higher across all subdomains of presence, usability, and user experience than nursing students. The type of metaverse platform also significantly influenced user experience. ConclusionsA significant proportion of Korean nurses and nursing students are familiar with the metaverse, reflecting a global trend towards virtual environments in education and healthcare. Although the metaverse holds promise for healthcare education, its effectiveness depends on user readiness, platform characteristics, and the development of a reliable, structured, and user-friendly educational programme.

Development of Cell Culture Platforms for Study of Trabecular Meshwork Cells and Glaucoma Development.

Various cell culture platforms that could display native environmental cue-mimicking stimuli were developed, and effects of environmental cues on cell behaviors were studied with the cell culture platforms. Likewise, various cell culture platforms mimicking native trabecular meshwork (TM) composed of juxtacanalicular, corneoscleral and uveal meshwork located in internal scleral sulcus were used to study effects of environmental cues and/or drug treatments on TM cells and glaucoma development. Glaucoma is a disease that could cause blindness, and cause of glaucoma is not clearly identified yet. It appears that aqueous humor (AH) outflow resistance increased by damages on pathway of AH outflow can elevate intraocular pressure (IOP). These overall possibly contribute to development of glaucoma. For the study of glaucoma, static and dynamic cell culture platforms were developed. Particularly, the dynamic platforms exploiting AH outflow-mimicking perfusion or increased IOP-mimicking increased pressure were used to study how perfusion or increased pressure could affect TM cells. Overall, potential mechanisms of glaucoma development, TM structures and compositions, TM cell culture platform types and researches on TM cells and glaucoma development with the platforms were described in this review. This will be useful to improve researches on TM cells and develop enhanced therapies targeting glaucoma.

Summer cooling island effects of blue-green spaces in severe cold regions: A case study of harbin, China

Blue-green spaces exhibit a cooling island effect in urban thermal environments. This study, through field measurements combined with thermal comfort indices and CFD simulations, explored the summer cooling island effect in micro-scale blue-green spaces of severe cold regions, summarizing the spatiotemporal characteristics of the effect. Measurements were conducted in Harbin at three water bodies of varying sizes and shapes, revealing a notable cooling island effect at a distance of 6–8 m from the water. The highest Mean Cooling Island Intensity (MCII) of 3.18 °C was recorded at 10 a.m. in a circular water body with compound vegetation. Furthermore, the combination of water bodies and vegetation proved more effective in reducing temperatures than single factors alone, with the peak coupling effect of 6.37 °C at 6 m from the water at 11 a.m. Thermal environment surveys determined Harbin's Neutral Universal Thermal Climate Index (UTCI) temperature range to be 13.3–25.06 °C. Additionally, modeling and optimization comparisons in ENVI-met confirmed that adding a small number of deciduous trees to grassland areas and altering the type of waterside platform can optimize the thermal environment. This research provides a solid foundation for the optimized design of blue-green spaces in severe cold regions.

How does stress experienced on instagram differ from threads? Comparing social media fatigue based on platform types

Social media fatigue in individuals has been recognized as a significant consequence and has attracted considerable attention in numerous studies. Prior research on social media fatigue has predominantly focused on investigating the direct relationship between stressors and fatigue. Nevertheless, there has been a conspicuous lack of discussion concerning the psychological variable contributing to fatigue. This study aims to address this gap by proposing that the time cost plays a crucial role in mediating the relationship between stressors and fatigue. Furthermore, we propose potential variables that could alleviate these sources of stress, thereby adopting a more comprehensive methodology compared to previous investigations on fatigue. Additionally, through a multi-group analysis based on types of social media (text-based vs. image-based), we explore the relationships between stressors, time cost, and fatigue. This approach is intended to supplement the literature on social media fatigue, confined mainly to analyzing a single platform. The empirical results validate the mediating role of time cost and demonstrate differences in stress perception between platforms. This study expands upon the theoretical framework of social media fatigue and proposes customized strategies for social media types, enhancing academic and practical comprehension.

Synthesis of eco-friendly multifunctional dextran microbeads for multiplexed assays

There has been an increasing demand for simultaneous detection of multiple analytes in one sample. Microbead-based platforms have been developed for multiplexed assays. However, most of the microbeads are made of non-biodegradable synthetic polymers, leading to environmental and human health concerns. In this study, we developed an environmentally friendly dextran microbeads as a new type of multi-analyte assay platform. Biodegradable dextran was utilized as the primary material. Highly uniform magnetic dextran microspheres were successfully synthesized using the Shirasu porous glass (SPG) membrane emulsification technique. To enhance the amount of surface functional groups for ligand conjugation, we coated the dextran microbeads with a layer of dendrimers via a simple electrostatic adsorption process. Subsequently, a unique and efficient click chemistry coupling technique was developed for the fluorescence encoding of the microspheres, enabling multiplexed detection. The dextran microbeads were tested for 3-plex cytokine analysis, and exhibited excellent biocompatibility, stable coding signals, low background noise and high sensitivity.

Fuzzy Logic-Based Driving Decision for an Omnidirectional Mobile Robot Using a Simulink Dynamic Model

This scientific paper presents the development and validation process of a dynamic model in Simulink used for decision-making regarding the locomotion and driving type of autonomous omnidirectional mobile platforms. Unlike traditional approaches relying on differential equations, this study uses Simulink’s block-based diagrams, offering a simpler and efficient development process. Importantly, the dynamic model accounts for friction forces, a critical factor for energy monitoring. The model’s validation is conducted experimentally, ensuring its accuracy and reliability. This paper formulates mathematical models for both conventional and Mecanum wheel configurations, facilitating energy-efficient driving strategies. By decomposing resistive forces into inertial and frictional components using the Jacobian matrix, this study accurately simulates electrical current consumption during robot motion. Through fuzzy decision algorithms utilizing parameters such as energy consumption, travel time, precision, and desired maneuverability, this paper proposes a method for determining the optimal locomotion mode for mobile platforms with Mecanum wheels. Overall, this research brings a new contribution to the field of mobile robotics by providing a comprehensive framework for dynamic modeling and it offers the possibility to drive omnidirectional robots in an energy-efficient manner.

Calculating the Environmental Benefit of Reuse Platforms

AbstractReuse platforms are contributing to the circular economy by hosting or mediating unwanted products or materials until new users are found. This saves products from premature disposal on one hand, and avoids new products purchase on the other. Translating this resource efficiency and waste minimisation into GHG emission avoidance can support the relevance of reuse platforms in fostering a circular economy and promoting climate protection through resource preservation and potential GHG emission reductions. The authors present the analysis of existing reuse methodologies and point out incomplete considerations in terms of LCA modules and Corporate Carbon Footprint of reuse platforms [11]. This paper fills the gap in literature by formulating a holistic methodology for calculating benefits of reuse in terms of GHG emissions for the whole reuse sector and provides an application guide for 4 different types of reuse platforms. This new approach is then illustrated by applying it to a reuse enterprise Zündstoffe Materialvermittlung Dresden (ZUMADD) case study, for which data was gathered for 2 years under Dresden Future City Project (2019–2022). The results show that the project could save 13,301 kg of CO2e emissions through mediating 6,213 kg of material for reuse.