Types Of Users Research Articles

Complementary and Alternative Medicine/Therapy for Tobacco Cessation in India: A Secondary Analysis of GATS-1 and 2.

India has nearly 267 million adult tobacco users, with a slowly improving quitting rate. Among the many approaches to quitting the habit, such as counseling, nicotine replacement therapy, nicotine patch or gum, and prescribed allopathic medicines. Complementary and alternative medicine/therapy (CAM), a thousand-year-old practice in India, may also prove to be a potential method in tobacco cessation; however, there is scarce literature on the extent of use of CAM among tobacco users who attempt to quit the habit. Therefore, this study attempts to examine the potential of CAM as a strategy for tobacco control in India. We undertook a secondary analysis of the data from both rounds of the Global Adult Tobacco Survey (GATS 2009 and 2016). The dependent variable included in the analysis was the use of traditional medicine as a method for quitting tobacco in three types of users-smokers, smokeless tobacco users, and dual users. The prevalence of CAM use was reported, and Chi-square test was applied to find the factors significantly associated with the use of CAM among tobacco users considering a P value of 0.05 to be statistically significant. The overall prevalence of traditional medicine use for GATS-1 was observed to be more among dual users (4%), while for GATS-2, it was highest among smokers (3%). For both rounds of the GATS survey, the use of traditional medicine was found to be higher among males, rural residents, users with no education or less than primary education, and the eastern region. CAM has a promising potential for supporting tobacco cessation provided a concerted effort is undertaken to standardize pharmacopeia and establish robust clinical evidence. In addition, there is a need to create awareness, build the capacity of healthcare providers, and foster academic-industrial research in indigenous Ayurveda, Yoga, Naturopathy, Unani, Siddha, and Homeopathy (AYUSH) systems.

The institutional environment and gig platform transaction cost solutions

Abstract A growing number of labour market participants transact through gig platforms. This choice should reflect a reduction in transaction costs for platform users, compared to costs they meet when using alternative modes of governance. We exploit a unique cross-platform, cross-country data set of gig platform users to test the impact of the institutional environment in one of its dimensions – the strictness of labour market regulation (LMR) – on the ability of gig platforms to reduce users' transaction costs. According to our findings, the regulation indicator of both the user and platform countries influences transaction costs for platform users, even controlling for platform and user characteristics. The platform appears to reduce transaction costs most when users face stricter or weaker LMR, in a U-shaped effect. In the former case, the platform may provide an escape from labour regulations when hiring for tasks, while in the latter case, the platform can economize on the usual transaction costs of private contracting by administrating some types of users' activities.

TAILORING EFFECTIVE USE MODEL OF BIG DATA IN MANAGERIAL CONTEXT: INSIGHTS FROM AN EMPIRICAL STUDY IN ARMENIAN COMPANIES

This article explores the managerial dimensions of the big data phenomenon, focusing on the challenge of customizing an effective use model within companies. The central inquiry revolves around tailoring such a model to suit the specific needs of big data-user companies. To address this, the study adopts a conceptual framework proposed by Surbakti and his co-authors, which delineates the effective use of big data. The primary methodology involves quantitative analysis of data gathered from 211 surveys completed by Armenian industry professionals. Examination of the collected data through statistical analysis reveals the presence of two distinct cohorts within the realm of big data users: “novice users” and “advanced users.” The main theoretical contribution that we aim for in this research is empirically proving the global validity of the studied model and demonstrating its flexibility of application in these two types of use cases of big data. While the conceptual model is found to be applicable to both types of users, its implementation varies significantly between the two groups. Therefore, from a managerial point of view, our results lead a manager to first think about the maturity of its company in terms of big data. Implementing a solution is not enough. By thinking in terms of novice vs. advanced, it creates two different managerial courses of action. Moreover, we propose the variables a manager has to analyze depending on this maturity.

Why Do People Use Artificial Intelligence (AI)-Enabled Voice Assistants?

Artificial-Intelligence-enabled voice assistants, such as Alexa and Siri, are increasingly replacing search engines as consumers actively employ the former to accomplish a variety of their day-to-day tasks. Technology providers as well as marketers increasingly work to leverage the use of voice assistants to engage their customers and offer them more personalized value propositions. This article examines the various consumption values associated with the use of voice assistants. Based on a theoretical framework rooted in the “theory of consumption values” (TCV), we undertake a mixed-methods approach that comprises interviews with experts (n = 5) and consumers (n = 30) as well as a cross-sectional survey with active users of voice assistants (n = 371). The article considers five consumption values—social identity, convenience, personification, perceived usefulness, and perceived playfulness—and two types of usage of voice assistants—information search and task function. Our findings contextualize and extend the TCV framework using voice assistant technology and obtain empirical support for the interrelation of consumption values. We find that social identity and personification have a strong positive association with both usefulness and playfulness. Furthermore, usefulness and playfulness are positively associated with information search and task function. In addition, trust and frequency of use significantly (and positively) moderate the association between usefulness and usage of voice assistants. Technology providers and marketers can capitalize on these findings to develop various voice-enabled applications and services that enhance the consumer experience and consumer engagement.

Spatiotemporal correlation and joint coverage probability in ultra‐dense mobile networks

AbstractIn the existing literature, for the spatial‐temporal characteristic of ultra‐dense network performances, the joint coverage probability is used to measure the correlation between different links or time‐slots due to channel and topological stability. However, the time‐variation introduces randomness and decreases correlation temporally and spatially due to user mobility, path‐loss and channel fading. In this paper, the expression of the joint coverage probability is derived to simultaneously analyze the effect of correlation and fluctuation among different time‐slots in ultra‐dense mobile networks by stochastic geometry. Specifically, the typical user moves out of the transmission range of the base station with handoff skipping and traditional handoff. In addition, the distance variation caused by the user's movement is considered in the analysis of the temporal correlation and the joint coverage probability. Simulation shows that the temporal correlation coefficient under handoff skipping is gradually greater than that under traditional handoff. The analytical results highlight the differences between the proposed network performance analysis and traditional analysis, validated through simulation.

Using artificial intelligence for exercise prescription in personalised health promotion: A critical evaluation of OpenAI's GPT-4 model.

The rise of artificial intelligence (AI) applications in healthcare provides new possibilities for personalized health management. AI-based fitness applications are becoming more common, facilitating the opportunity for individualised exercise prescription. However, the use of AI carries the risk of inadequate expert supervision, and the efficacy and validity of such applications have not been thoroughly investigated, particularly in the context of diverse health conditions. The aim of the study was to critically assess the efficacy of exercise prescriptions generated by OpenAI's Generative Pre-Trained Transformer 4 (GPT-4) model for five example patient profiles with diverse health conditions and fitness goals. Our focus was to assess the model's ability to generate exercise prescriptions based on a singular, initial interaction, akin to a typical user experience. The evaluation was conducted by leading experts in the field of exercise prescription. Five distinct scenarios were formulated, each representing a hypothetical individual with a specific health condition and fitness objective. Upon receiving details of each individual, the GPT-4 model was tasked with generating a 30-day exercise program. These AI-derived exercise programs were subsequently subjected to a thorough evaluation by experts in exercise prescription. The evaluation encompassed adherence to established principles of frequency, intensity, time, and exercise type; integration of perceived exertion levels; consideration for medication intake and the respective medical condition; and the extent of program individualization tailored to each hypothetical profile. The AI model could create general safety-conscious exercise programs for various scenarios. However, the AI-generated exercise prescriptions lacked precision in addressing individual health conditions and goals, often prioritizing excessive safety over the effectiveness of training. The AI-based approach aimed to ensure patient improvement through gradual increases in training load and intensity, but the model's potential to fine-tune its recommendations through ongoing interaction was not fully satisfying. AI technologies, in their current state, can serve as supplemental tools in exercise prescription, particularly in enhancing accessibility for individuals unable to access, often costly, professional advice. However, AI technologies are not yet recommended as a substitute for personalized, progressive, and health condition-specific prescriptions provided by healthcare and fitness professionals. Further research is needed to explore more interactive use of AI models and integration of real-time physiological feedback.

Identifying and characterizing superspreaders of low-credibility content on Twitter.

The world's digital information ecosystem continues to struggle with the spread of misinformation. Prior work has suggested that users who consistently disseminate a disproportionate amount of low-credibility content-so-called superspreaders-are at the center of this problem. We quantitatively confirm this hypothesis and introduce simple metrics to predict the top superspreaders several months into the future. We then conduct a qualitative review to characterize the most prolific superspreaders and analyze their sharing behaviors. Superspreaders include pundits with large followings, low-credibility media outlets, personal accounts affiliated with those media outlets, and a range of influencers. They are primarily political in nature and use more toxic language than the typical user sharing misinformation. We also find concerning evidence that suggests Twitter may be overlooking prominent superspreaders. We hope this work will further public understanding of bad actors and promote steps to mitigate their negative impacts on healthy digital discourse.

Performance of the Typical User in RIS-Assisted Indoor Ultra Dense Networks

Performance of the Typical User in RIS-Assisted Indoor Ultra Dense Networks

Application and construction of traditional cultural and creative product design platform based on digital art elements

Abstract In recent years, using digital platforms as a carrier to promote the development of cultural and creative products has become a new trend in cultural and creative industries. After analyzing the application of traditional cultural and creative product design platforms, the study mines the audience comment text of traditional cultural and creative products based on the improved TF-IDF algorithm, logistic regression and sentiment analysis algorithm to analyze the consumer’s concern elements and sentiment tendency. Then, the user demand elements of the traditional cultural and creative product design platform are summarized, and the types and priorities of the user demand elements are determined by combining the questionnaire survey and the Kano model. The traditional cultural and creative product design platform is constructed on digital art elements and the platform’s system architecture design is carried out on this basis. Consumer satisfaction is supported by the attributes and services of traditional cultural and creative products. With the best performance in terms of services, the proportion of positive emotions is 90.64%, but there is still room for improvement in packaging, price, and design. The priority of user demand elements was determined, with service perceptibility, service process, and content being the important levels of demand. Based on the research needs of typical users of the platform, the construction of a traditional cultural and creative product design platform based on digital art elements has been realized.

ТЕОРЕТИКО-ПРИКЛАДНІ ЗАСАДИ ЕКОНОМІЧНОЇ ОЦІНКИ ЯКІСНИХ ХАРАКТЕРИСТИК ПРИРОДНОГО ГАЗУ

The article examines the theoretical and applied foundations for the economic evaluation of natural gas quality characteristics, significantly impacting its efficient utilization and cost for consumers. The relevance stems from natural gas's importance as an energy source. The authors analyze classical (comparative price method, cost analysis) and modern (risk analysis, economic-mathematical modeling) methods for assessing gas quality. Key influencing factors are identified: competition level, government regulation, gas usage type, and technological equipment level. The principles outlined include determining quality indicators and their interrelationships; the impact of characteristics on efficiency across industries; evaluation methods considering extraction, transportation, and processing costs; pricing scenario modeling; and analysis of regulation and market mechanisms. The necessity of an integrated approach for decision-making regarding efficient use of varying gas qualities is substantiated. Emphasis is placed on analyzing quality indicators (calorific value, density, Wobbe index, component content) and their interrelationships based on real data. Investigating the impact of characteristics on the efficiency of use in industry, energy, and the municipal sector is crucial. Calculating the economic efficiency of using varying quality gas in these sectors, considering preparation, transportation, and processing costs, is essential. The development of methodological approaches for the economic evaluation of quality indicators, considering extraction, transportation, and processing costs, is underscored. Modeling pricing scenarios for varying quality gas and assessing the impact on consumer costs is vital. Building economic-mathematical models for demand/supply forecasting and simulating market operation with different pricing schemes is recommended. The analysis of the impact of changing quality parameters on consumer costs due to changes in extraction, transportation, and gas preparation is emphasized. The analysis of regulation and market pricing mechanisms for varying quality gas is highlighted. Developing recommendations for authorities, companies, and enterprises to optimize the use of varying quality gas for maximum efficiency and cost reduction is important. A comprehensive approach combining theoretical developments and applied research will form the foundation for management decisions on the efficient use of varying gas qualities.

Interference Management Using Distance-based Clustering Method for D2D Communication Underlaying Multicell Cellular Network

Device-to-Device (D2D) communication is a technology candidate to support the next generation of cellular communication networks. D2D has the potential to boost the efficiency of frequency resources and system capacity. Generally, D2D performs in-band underlaying or shares frequency channels with traditional cellular users, which can cause co-channel interference problems between these two types of users. This paper offers a solution through a clustering technique for D2D users (DUEs) to reduce interference among DUEs. Clustering technique is performed on DUEs by allocating different frequency channels in a group, in order to reduce the interference effects experienced. Thus, it is expected that through this proposed method, both D2D and cellular users can experience better signal quality with minimal interference effects. Two systems have been considered i.e., the conventional/baseline system and the system with the proposed clustering method. The simulation results show that the SINR (Signal to Interference plus Noise Ratio) values and throughput for the proposed system compared to the baseline system has increased. The SINR result obtained is 16.8 dB for the baseline system and 17.68 dB for the proposed system, and resulting an improvement of 5.4%. Therefore, applying the proposed clustering method is able to increase acceptability of the desired signals for the observed DUEs. Then, the throughput value also increases by 5%, i.e., from 56.17 to 59 Mbps, which the system with the proposed clustering method provides a better increase in data transmission speed compared to the baseline system.

Named entities, naming practices, and their meanings – linguistic types and cultural contexts

Abstract Although names exist in all languages of the world, their formal and functional manifestations show great diversity. Due to their embeddedness in socio-cultural and historical contexts, an anthropological-linguistic approach that brings together linguistic and cultural facts is required to capture the full meaning of names and naming practices. Overall, names are given to entities of cultural importance and of significance for humans in social life; name usage and name-giving practices reflect social beliefs and cultural values; and their meaning is strongly shaped by cultural and historical contexts. This paper provides a typological, cross-linguistic overview of named entities, kinds of naming practices, and types of meanings associated with names, name giving, and name usage, which are illustrated with numerous examples from Australia, Europe, and Africa. Therefore, it also offers a structural framework for the contributions in this issue.

오팔세대의 팬덤 활동 유형 분석 고찰

This study aimed to explore the types and characteristics of Opal Generation's fandom activities by focusing on singer Lim Young-Woong's fandom community, “Hero Generation,” which is the largest of the Opal Generation's fandoms. We also analyzed the new pop culture phenomena they create to suggest new directions and strategies for the pop culture industry. To this end, we conducted a topic modeling analysis on 2340 news big data cases, and based on the derived topics, we classified the usage types of Opal Generation fandom into seven dimensions. Based on the results of this study, it is suggested that the Opal Generation is leading a new cultural phenomenon through active fandom activities and content participation, and it is significant to promote a deeper understanding of Opal Generation fandom.

Proposal for an Inspection Tool for Damaged Structures after Disasters

This study focuses on the development of a multifunctional Expert System (ES) called post-seismic damage inspection tool (PSDIT), a powerful tool which allows the evaluation, the processing and the archiving of the collected data stock after earthquakes. PSDIT can be operated by two user types; an ordinary user (engineer, expert or architect) for the damage visual inspection and an administrative user for updating the knowledge and / or for adding or removing the ordinary user. The knowledge acquisition is driven by a hierarchical knowledge model, the Information from investigation reports, and those acquired through feedback from expert / engineer questionnaires are part.

Accessibility of Virtual Museum Spaces in the 21st Century in Turkey

Museums, which are the embodiment of art, exhibition, culture, and science, have started to offer virtual space experiences as well as traditional physical space experiences in recent years. In addition to the development of technology, the pandemic, which started in 2019 and affected the whole world, has also been effective in accelerating the transformation of museums from physical space to virtual space. The increasing use of virtual museums directly concerns different user groups in terms of accessibility. In a physical museum experience, solutions that appeal to different types of users are generally produced. Thanks to these solutions, an individual with any disability can be included in the space with all senses such as sight, touch, smell, and hearing during a museum visit, while the lack of inclusion of all senses in the virtual space experience causes the experience to be more limited. This study discusses this limitation in terms of accessibility. How can the virtual space experience be more accessible for different types of users? Can different solutions be offered to all user groups for a better understanding of the space and the art product? These questions constitute the research questions of this study. In this context, this study aims to examine how accessible virtual museums are. The study has conducted this inquiry through 59 virtual museums in Turkey. As a method, virtual museums were classified and tabulated in terms of their accessibility levels in line with their characteristics. It was concluded that there are deficiencies in the experience of different types of users and various suggestions were made in terms of virtual accessibility.

A Comparative Analysis of English Test Scores in the Vietnamese National High School Graduation Examination During the Period 2020-2023

English is the most used language online, with nearly one billion users typing and chatting in the language. English is now widely spoken throughout the world and is necessary for people to be able to communicate and fit into the real world. In Vietnamese high schools, learning English has become an important task for students. The aim of this paper is to cary out a comparative analysis of English test scores (ETSs) in the Vietnamese National High School Graduation Examination during the period 2020-2023. In this study, datasets of English test scores during the period 2020-2023 were first collected. To find patterns of ETSs, the frequency of ETSs was firstly calculated. Histograms were then used to plot the frequency against ETSs to study the distribution of ETSs in each year. Finally, a comparative analysis of ETSs during the period was carried out. It was found that the distribution of ETSs during the period 2020-2023 was skewed to the right, which shows that the number of high ETSs tends to be more prominent. In addition, the high ETSs in 2021 were found to be much higher than those obtained from the yeas of 2020, 2022 and 2023. Findings in this study suggest that ETSs during the period 2020-2023 met the requirements for graduate recognition. It can be concluded that the role of English language in career advancement is undeniable in this era of globalization. Keywords: Comparative analysis, English Test Scores, Vietnamese National High School Graduation Examination, Period 2020-2023.

Adaptive refined random orthogonal matching pursuit algorithm for FBMC/OQAM MIMO framework

The fifth generation of wireless communication is anticipated to provide improved quality of service and enhanced data rates to the end users. One such technology that stands out as a potential transmission scheme for 5G systems is Filter Bank Multicarrier using Offset Quadrature Amplitude Modulation (FBMC/OQAM) with an effective channel estimation technique for improved performance. However, due to the inherent imaginary interference, channel estimation methods relying on preamble structures in FBMC/OQAM systems exhibit sub-optimal performance, particularly within Multiple-Input Multiple-Output (MIMO) setups. For channel estimation schemes based on compressed sensing, the inherent sparsity of wireless channels can be exploited for accurate channel reconstruction and overall performance improvement.We propose a novel compressed sensing based algorithm namely, Adaptive Refined Random Orthogonal Matching Pursuit (ARROMP), for MIMO-FBMC system with Coordinated MultiPoint (CoMP) scheduling. This algorithm adaptively selects a support set by utilizing a double threshold for the minimization of mean squared error and for accurate channel reconstruction. The proposed algorithm's performance is compared with existing Orthogonal Matching Pursuit (OMP) schemes such as random OMP, refined random OMP, and least square-based estimation. The numerical simulations suggest that the proposed adaptive algorithm provides performance improvement in terms of reduced Mean Squared Error (MSE) of channel reconstruction and Bit Error Rate (BER). Moreover, the proposed ARROMP algorithm for MIMO-FBMC is rigorously tested with CoMP scheduling for a cellular network using frequency division duplex mode. The proposed system presents significant improvements in throughput and spectral efficiency for all types of cell users, including cell-edge users. The simulation results validate the improved performance of the proposed algorithm with CoMP scheduling over the existing single-cell system with no coordination.

Healing Applications in Hospital Interiors: Ceramic Art

Healthcare facilities include complex partnerships that accommodate different types of users to meet the needs of the healthcare sector and require the collaboration of many disciplines to meet these needs. Hospitals, which contain the outputs of different fields of expertise from city scale to industrial product scale, are fed by the fields of engineering, architecture, and interior architecture in terms of space. Interior design, on the other hand, is divided into theoretical and practical specializations related to building types. The fact that health buildings have significant differences from other buildings due to their function and the obligations that would be met is of great importance in terms of the benefit to be provided to the public by the studies to be carried out in the field. Hospital buildings and spaces are constructed and designed according to the standards determined by the shade's laws, regulations, or guidelines where they are to be built. In this context, the study aims to provide a public contribution with art outputs that would positively affect the recovery of the user for the spaces that are generally open to the use of users in hospital interiors by researching the standards in the framework of international standards. However, since traditional and modern art contents have different spatial needs; ceramic art outputs, which are included in traditional art, focus on the specific evaluation of the research with its visual and tactile character. Using qualitative research methods; hospital construction guidelines and literature research were carried out by data collection and inductive methods. The research aims to make theoretical and practical contributions to the healing space with ceramic artworks/objects in the field of architecture and design.

The kitchen turn in Socialist Yugoslavia: Women, materiality, and (un)paid labor, 1950s-1970s

The article shows the trajectory of Yugoslav kitchen design between early 1950s and early 1970s, from its pathbreaking emergence within home economies institutions and women’s organizations to mass production, commercialization, and popularization by the furniture industry. Centered on two case studies –the Swedish kitchen designed by Branka Tancig in 1954 and Cocktail 68, designed by Biala Leban in 1968– the article explores temporal and qualitative changes in Yugoslav kitchenscapes with several critical junctions –women’s activism, home economics, kitchen design, and women’s (un)paid labor. We argue that the initial expert focus on producing simplified, efficient kitchens for modern households has been transformed in the light of economic, social, and artistic changes from the mid-1960s into an industry-driven promotion of elaborate and colorful kitchen designs. This transformation, however, should not be seen in a dichotomic manner; although the differences in design were strongly linked to changing materialities, and their symbolic values while promoting an entirely dissimilar type of user, all were a result of efforts in standardization and modernization driven by Yugoslav women’s professional activities in architecture, design, and home economics. By weaving together these different themes, we bring new insights into the history of Yugoslav design, materiality, science, women’s expertise, organizing labor, and transnationalism in the 1950s and 1960s.

Actioning usability study findings in the development of the ADLIFE integrated care digital tools.

Introduction: The ADLIFE project aims to improve the quality of life of older people with advanced chronic diseases by providing integrated intelligent personalised care via a digitally enabled holistic and integrated supportive care ICT Toolbox. The two interlinked user-facing tools are firstly, a Personalised Care Plan Management Platform (PCPMP) used by healthcare professionals; and secondly, a Patient Empowerment Platform (PEP) that patients and their informal caregivers use to promote patient self-management. 
 The impact of the ADLIFE digital tools will be explored in a 12-month pilot study conducted across 7 clinical sites in 6 countries to evaluate their impact on a range of health-related, implementation and socio-economic outcomes.
 The development of digital tools needs to be done in continuous collaboration with target end-users. Feedback from prototype testing with typical user scenarios is crucial to identify any remaining issues to resolve ahead of the deployment of such tools. We present the findings from a pre-deployment usability study conducted on the ADLIFE Toolbox.
 Methods: Pilot sites recruited 3-5 participants for their feedback on the PCPMP and PEP tools. Usability data was collected using a standardised Questionnaire for User Interface Satisfaction (QUIS), administered online, following a training workshop and testing by the participants. One site collected feedback via a Patient and Public Involvement (PPI) approach for the PEP tool as an option for the activity timeline. The questionnaire responses were analysed to identify the key areas of improvement. The analysis includes a standard scoring system giving an indication of users’ satisfaction with each facet of interest. These scores identify specific features of the ADLIFE tools that have lower usability scores, allowing useful improvements to be made before deployment in the main ADLIFE pilot study. Additional free text comments are used to complement the QUIS scores and provide greater depth of understanding around specific usability issues. PPI responses were analysed separately as the group did not test the tool directly.
 Results: 13 responses were received for PCPMP and 18 for PEP. Overall, the study participants (excluding 10 PPI participants) scored both tools above average, with scores over 66% on average in all questionnaire categories (scores of over 6 out of 9, average score on this scale is 4.5). Some areas of usability scored lower, such as task progression and highlighting where input is required. Together with comments elaborating on scores given, those areas are being assessed further for prioritising updates to the tools and also to be considered in the study planning, such as training materials and communication channels. The PPI feedback provided insight into how ADLIFE tools can fit within the wider context of healthcare and technology. 
 Conclusions: The usability studies have provided an opportunity to get feedback from participants similar to the ADLIFE study participants and make improvements to the ADLIFE tools, training and communication ahead of the pilot study start.
 Acknowledgements: ADLIFE has received funding from the EU Horizon 2020 research and innovation programme under grant agreement no. 875209. The authors thank all partners within ADLIFE for their cooperation and valuable contribution.