Understanding Of Users Research Articles

Factors Influencing Use–diversity of Urban Parks: A Cross-cultural Study Between Chengdu (China) and Perth (Australia)

Urban parks are an essential component of city infrastructure providing multiple ecosystem services. While there are many studies exploring the usage of urban parks within a country, cross-country comparisons are rare. Comparative studies of use–diversity of urban parks between developing and developed countries are almost absent. To address this research gap, we have compared use–diversity of two major urban parks in China (Dufu Cottage in Chengdu—DC) and in Australia (Kings Park in Perth—KP). Using a post-occupancy survey questionnaire, we addressed two key questions: (a) is there any difference in use–diversity between these urban parks? And (b) which demographic and socio-economic factors influence use pattern of urban parks the most? We observed that, in general, use frequency is lower in DC when compared to KP. In both parks, the opportunity of physical activity is the most important motive for visitation. Most of the usage is concentrated during the weekends in DC; KP was used more consistently throughout the week. Various socio-demographic factors, such as gender, age, income level and frequency of visits, have some influence on frequency and diversity of usage. The impact of socio-demographic factors on the extent of use highlights the importance of understanding users’ profiles to adopt more targeted measures to address local demands. The study identified some common patterns and differences in use–diversity between the two parks, underscoring the potential for managers of these parks in both countries, for mutual learning and adopting best management practices.

Techniques for Enhancing User Engagement through Personalized Ads on Streaming Plat-forms

The rapid growth of streaming platforms has transformed the media consumption landscape, providing unique opportunities for advertisers to reach highly targeted audiences. Personalized advertising has emerged as a powerful tool to enhance user engagement by delivering relevant content tailored to individual preferences and behaviors. This paper explores the various techniques employed to optimize personalized ads, focusing on the role of data analytics, machine learning, and artificial intelligence in understanding user preferences and consumption patterns. By leveraging real-time data, advertisers can create dynamic, adaptive ads that resonate more deeply with users, leading to improved engagement and retention rates. Additionally, the study examines the ethical implications of data privacy and user trust, highlighting the balance between personalization and user consent. The findings suggest that strategic implementation of personalized ads, combined with a transparent approach to data usage, can significantly enhance user satisfaction and the overall effectiveness of advertising campaigns on streaming platforms. This abstract introduces the key techniques and challenges in personalizing ads for streaming platforms, emphasizing user engagement and ethical considerations.

Collective user switching behavior reveals the influence of TV channels and their hidden community structure

Television is the primary medium through which most families access entertainment and information in their daily lives. Thus, understanding users’ TV viewing behavior is meaningful for several practical issues, such as evaluating the influence of TV channels and providing personalized TV recommendations. However, most existing works regarding TV viewing data are limited to basic statistics (e.g., TV ratings). In this paper, we analyze a large-scale TV viewing dataset for a city in China via a complex network approach. We construct a directed network that characterizes the collective channel-switching behavior of viewers. By using the PageRank method, we reveal the influential TV channels that are more in line with people’s expectations than their rankings based on simple TV ratings. We further construct a network in which channels are linked according to their similarity in users’ switching preferences. This network exhibits a clear community structure, which can help TV stations understand which channels are in the bottleneck and which channels have potential. Overall, our work provides a system perspective to evaluate TV channels and their relationships.

Learning and Energy-efficient Renovation of Residential Buildings: The user Perspective

Renovation of residential buildings has gained more attention in recent years. There are several challenges connected to energy efficient renovation of existing buildings. European Commission acknowledges the challenges and emphasizes the need to replicate best practices and learn from lessons. Several research studies have been conducted on the topic of energy-efficient renovation of residential buildings, some of which have highlighted significant aspects that are to be considered in the renovation efforts / projects. One of the aspects is user perspective that encompasses, among other things, user involvement and user behaviour. Knowledge sharing and learning play a significant role in developing and ensuring the user behaviour that is suitable for harvesting the intended benefits of energy-efficient renovation efforts. There can be wonderful energy-efficient solutions that can reduce greenhouse gas emission and promote sustainability. But, if the solutions are not used appropriately by the user, then it will hinder achieving the expected positive effect. As a result, developing and implementing the solutions in the first place will lose its very purpose. This paper looks at the user perspective in energy-efficient renovation of residential buildings and describe the learning-points associated with it. Focusing on these learning-points and the user perspective itself has its implication on wider issues such as policy making and future energy consumption. In addition, this paper summarises basic knowledge on understanding users' behaviour regarding energy and consumption, as well as briefly describes tools and examples of research projects that incorporate the users' perspective in their design. This paper is based on narrative literature study. It touches upon aspects related to the Sustainable Development Goals 11 (Sustainable cities and communities) and 13 (Climate action), at least to a certain extent. This paper is connected to an EU-project called "REZBUILD" (https://rezbuildproject.eu/), which focuses on developing decision and planning support for accomplishing near zero-emission in renovation of residential buildings.

A user satisfaction model for mobile government services: a literature review.

User satisfaction is essential for the success of an organisation. With the development of government service delivery through mobile platforms, a compatible measurement model must be found to measure user satisfaction with performing such services through a mobile government portal. Measuring user satisfaction with mobile government services is necessary nowadays due to the increasing popularity of smart devices. Research on mGovernment users’ satisfaction is lacking, leading to difficulties in understanding users’ expectations. In the present study, systematic literature reviews have been used to analyze users’ satisfaction with mGovernment portals and propose a comprehensive model compatible with such contexts. The results show that government agencies can evaluate users’ satisfaction using the proposed model of six quality constructs: usability, interaction, consistency, information, accessibility, and privacy and security. The study recommends improving the evaluation strategies of mGovernment portals regularly to ensure they fit with challenges. Measuring user satisfaction at mGovernment services encourages the user to perform the transactions through such online platforms, increasing the digitalization process and reducing the cost and efforts for both the service provider and end-users.

Design Model of Cultural and Creative Products Using User Perception Demand Mining.

People are becoming more and more aware of the value of design throughout a product's entire life cycle as a result of the fierce competition for industrial products that exists today. The life of a product involves its design, manufacture, sale, and use, and how well these links are managed determines the product's positioning in terms of value in the eyes of consumers. The key to the functional integration of the design is monitoring the entire process and applying the user's emotional needs. A useful tool for assessing users' emotional needs is the perceptual image of a product. An artificial intelligence-driven method for product perceptual design is proposed, and its efficacy is demonstrated by the design of an optometer. This method addresses the issues of incomplete measurement and insufficient sample collection in the traditional users' perceptual cognition measurement. The findings demonstrate that extracting users' perceptual cognition through text mining can assist designers in better understanding users' perceptual needs, resulting in designed products that are more likely to meet users' expectations for satisfaction. A design approach that can increase users' psychological acceptance of products and boost their competitiveness is the perceptual design method, which combines human and artificial intelligence.

Knowledge about public health programs in Brazil and their correlation with the Brazilian Unified Health System: short communication

Objective: To know the notable public health programs in Brazil and their associations with the Unified Health System. Methods: This is a short communication about important public health programs in Brazil. Scientific articles published in the last ten years were used. The choice was made through searches in scientific databases. Results: It was noted that the user's understanding can be an indispensable source of knowledge for designing evaluations of the care process as well as the results obtained with the applicability of certain models and/or assistance programs. Therefore, despite the adversities, which are not few, the Unified Health System has several public health programs considered international references. Conclusion: The programs mentioned, as well as other existing ones, must be carried out effectively and in accordance with the needs and epidemiological specificities of each territory. However, there are significant services that support health promotion, prevention of risks, injuries, and diseases, understanding morbidity, reducing years lost due to disability and increasing the quality of life of individuals and populations.

ORCLSim: A System Architecture for Studying Bicyclist and Pedestrian Physiological Behavior through Immersive Virtual Environments

Injuries and fatalities for vulnerable road users, especially bicyclists and pedestrians, are on the rise. To better inform design for vulnerable road users, we need to evaluate how bicyclist and pedestrian behavior and physiological states change in different roadway design and contextual settings. Previous research highlights the advantages of using immersive virtual environments (IVEs) in conducting bicyclist and pedestrian studies. These environments do not put participants at risk of injury, are low cost compared to on-road or naturalistic studies, and allow researchers to fully control variables of interest. In this paper, we propose a framework, Omni-Reality and Cognition Lab Simulator (ORCLSim), to support human sensing techniques within IVEs to evaluate bicyclist and pedestrian physiological and behavioral changes in different contextual settings. To showcase this framework, we present two case studies, where pilot data from five participants’ physiological and behavioral responses in an IVE setting are collected and analyzed, representing real-world roadway segments and traffic conditions. Results from these case studies indicate that physiological data are sensitive to road environment changes and real-time events in the IVE, especially changes in heart rate and gaze behavior. In addition, our preliminary data indicate participants may respond differently to various roadway settings (e.g., signalized vs. unsignalized intersections). By analyzing these changes, future studies can identify how participants’ stress level and cognitive load are impacted by the surrounding environment. The ORCLSim system architecture is a prototype that can be customized for future studies in understanding users’ behavioral and physiological responses in virtual reality settings.

Utilization of wearable smartwatch and its application among Saudi population

Study purposeIt is important to understand the users' perceptions toward the use of smartwatches and the various factors that affect the adoption of smart watches. These findings would contribute to the literature in understanding users' usage, preferences, needs, and expectations about smartwatches that would aid smartwatches designers and also decision-makers in integrating the smartwatch technology in various service-enabled areas such a healthcare, e-learning etc. To address this gap, the objective of this study was formulated to understand the actual consumers' perceptions of toward the use of smartwatches and explore the critical factors affecting the adoption and intention to use smartwatches in the Kingdom of Saudi Arabia.MethodsA cross-sectional study was designed to assess the actual perception of use smartwatches and to investigate the influencing factors that affect the utilization among Saudi population using the survey technique. Questionnaire design was based on the domains of Technology Acceptance Model (TAM) to determine the factors affecting smartwatches utilization. The sample composed of Saudi Arabian residents aged 18 years and above. The response rate for the online questionnaire that was distributed through the social media applications was 58.61% representing 135 participants. The data was collected in November 2020 and analyzed using the Statistical Packages for Software Sciences (SPSS).ResultsThe prevalence of participants who had knowledge about smartwatch was 94.1%. When comparing the demographic characteristics between those owning and not owning a smartwatch, it was found that educational level (X2 = 9.365; p = 0.025) and knowledge about smartwatch (X2 = 7.897; p = 0.005) had significant relationship with owning a smartwatch. When comparing between design aesthetic, perceived usefulness, ease of use, enjoyment and healthology in relation to the socio demographic characteristics, it was found that respondents in the older age group (≥45 years) (F = 11.797; p <0.001) and those with master degree (F = 3.449; p = 0.002) observed to have significantly lower mean score in design aesthetic while females exhibited significantly higher score in perceived enjoyment and healthology (T = −3.629; p = 0.001) as well as design aesthetic (T = −2.070; p = 0.043).ConclusionFactors such as age, education, gender, income can significantly affect the adoption of wearable devices in Saudi Arabia.

Quality of information on weight loss drugs from South American websites

In the face of digital technologies that help search for health information, an assessment of the quality of available information is necessary. This study aimed to evaluate the quality of information on weight loss drugs on websites available in South America. Websites from five countries in South America, Argentina, Brazil, Chile, Colombia and Uruguay, were selected using the Google search tool in Portuguese and Spanish, with content about weight loss drugs. The quality of the information was analyzed using a specific health tool, while the pharmacological content was analyzed using a tool specifically created by the Delphi method. Seventy-six websites from Argentina, Brazil and Chile (20 websites each) and Colombia and Uruguay each with eight evaluated websites, were analyzed. Uruguay presented low-quality information on all websites for all the dimensions analyzed, while Brazil and Colombia presented low-quality information in the pharmacological dimension. In the final data, 92% (p = 0.9934) of the websites were considered low quality and the rest were of moderate quality. We observed low-quality information on South American websites regarding weight loss drugs where there is a risk that the user's understanding and ultimately their quality of life may be adversely affected. • Weight loss drugs websites in South America have a low quality of information. • Internet information on obesity pharmacology presented the worst quality. • The lack of regulation on the internet spreads fake news.

Clinical pharmacist's responsibility for the patients safety in drug information centers at Al-Basra District – Iraq

Drug information center (DIC) is an academy that provides objective, free and updated information on drugs and their use, and communicates to the different categories of users for better understanding and benefit of patients. Therefore, DIS belongs to an organization that provides information services about medications. The overall aim of the DIC is to promote rational medications use through scientific, objective, updated, free and evaluated information. The purpose of this research was to assess the use of drug information centers by health care professionals to improve medication safety. A data of six months were collected from November-2021 until May- 2022. The number of questions during this period was counted and all these questions were analyzed. 24% of these questions were made by the, 40%made by the pharmacist, 13% were made by the nurse and 19% were made by the patients. A total number of requests were responded during the 6 months period are 298 requests. This explains the importance of DIC in answering questions and providing adequate information about medicines.

A review of forest fire research directions

Forest fires cause environmental and economic damages every year, especially in the southern part of Europe. Approaches to estimate the fire risk vary from practical to scientific, since different professions as firefighters, meteorologists, soldiers and foresters are involved. The Internet of Things enables to connect different sources of information in one place, however, the understanding of usage and processes that caused the disaster sometimes is missing. The aim of this article is to give a comprehensive overview of nowadays possibilities for fighting with the fires and categorization of different methods, techniques and approaches. Considering the timeline of the information about fires we are dealing with, we propose three categories: past which mostly refers to analysis, present which encompasses monitoring and future covering forecasting. Each of the categories is described in detail, confirmed with related work and examples, and enriched with challenges and future directions. Dealing with forest fires is very complex, therefore it is difficult to deal with all proposed categories at the same time. However, due to the growing amount of available information and increasing interest of scientists from different research fields, there are more examples of intertwined areas dealing with forest fires. It is expected that in the future it will be possible, in real time, to handle various sources of data and forecast fire danger and risk with high spatial and temporal resolution.

Exploring user experience in digital libraries through questionnaire and eye-tracking data

In the field of digital libraries, research on user experience is sparse, especially in terms of emotions, impressions, and stimulation evoked by interaction with the digital library. Given the many different methods and tools available for assessing user experience, two questionnaires and eye-tracking were explored to see how each can contribute to understanding user experience in digital libraries. An eye-tracking study with 30 participants was carried out using two digital libraries. Analysis of the questionnaires revealed that overall, one digital library was experienced more positively, with the difference most evident in the hedonic quality. The eye-tracking data revealed different gaze patterns in the two digital libraries, with significant difference in measure values particularly on the search boxes. When eye-tracking was combined with the questionnaire data, several correlations were found, indicating that the search box position and the intuitiveness of the homepage had an impact on the user experience.

“I Don’t Think So”: Summarizing Policy Disagreements for Agent Comparison

With Artificial Intelligence on the rise, human interaction with autonomous agents becomes more frequent. Effective human-agent collaboration requires users to understand the agent's behavior, as failing to do so may cause reduced productivity, misuse or frustration. Agent strategy summarization methods are used to describe the strategy of an agent to users through demonstrations. A summary's objective is to maximize the user's understanding of the agent's aptitude by showcasing its behaviour in a selected set of world states. While shown to be useful, we show that current methods are limited when tasked with comparing between agents, as each summary is independently generated for a specific agent. In this paper, we propose a novel method for generating dependent and contrastive summaries that emphasize the differences between agent policies by identifying states in which the agents disagree on the best course of action. We conducted user studies to assess the usefulness of disagreement-based summaries for identifying superior agents and conveying agent differences. Results show disagreement-based summaries lead to improved user performance compared to summaries generated using HIGHLIGHTS, a strategy summarization algorithm which generates summaries for each agent independently.

Interest identification from browser tab titles: A systematic literature review

Modeling and understanding users interests has become an essential part of our daily lives.A variety of business processes and a growing number of companies employ various tools to such an end. The outcomes of these identification strategies are beneficial for both companies and users: the former are more likely to offer services to those customers who really need them, while the latter are more likely to get the service they desire.Several works have been carried out in the area of user interests identification. As a result, it might not be easy for researchers, developers, and users to orient themselves in the field; that is, to find the tools and methods that they most need, to identify ripe areas for further investigations, and to propose the development and adoption of new research plans.In this study, to overcome these potential shortcomings, we performed a systematic literature review on user interests identification. We used as input data browsing tab titles. Our goal here is to offer a service to the readership, which is capable of systematically guiding and reliably orienting researchers, developers, and users in this very vast domain.Our findings demonstrate that the majority of the research carried out in the field gathers data from either social networks (such as Twitter, Instagram and Facebook) or from search engines, leaving open the question of what to do when such data is not available.

VIBE: A Design Space for VIsual Belief Elicitation in Data Journalism

AbstractThe process of forming, expressing, and updating beliefs from data plays a critical role in data‐driven decision making. Effectively eliciting those beliefs has potential for high impact across a broad set of applications, including increased engagement with data and visualizations, personalizing visualizations, and understanding users' visual reasoning processes, which can inform improved data analysis and decision making strategies (e.g., via bias mitigation). Recently, belief‐driven visualizations have been used to elicit and visualize readers' beliefs in a visualization alongside data in narrative media and data journalism platforms such as the New York Times and FiveThirtyEight. However, there is little research on different aspects that constitute designing an effective belief‐driven visualization. In this paper, we synthesize a design space for belief‐driven visualizations based on formative and summative interviews with designers and visualization experts. The design space includes 7 main design considerations, beginning with an assumed data set, then structured according to: from who, why, when, what, and how the belief is elicited, and the possible feedback about the belief that may be provided to the visualization viewer. The design space covers considerations such as the type of data parameter with optional uncertainty being elicited, interaction techniques, and visual feedback, among others. Finally, we describe how more than 24 existing belief‐driven visualizations from popular news media outlets span the design space and discuss trends and opportunities within this space.

Twitter User Representation Using Weakly Supervised Graph Embedding

Social media platforms provide convenient means for users to participate in multiple online activities on various contents and create fast widespread interactions. However, this rapidly growing access has also increased the diverse information, and characterizing user types to understand people’s lifestyle decisions shared in social media is challenging. In this paper, we propose a weakly supervised graph embedding based framework for understanding user types. We evaluate the user embedding learned using weak supervision over well-being related tweets from Twitter, focusing on 'Yoga’, 'Keto diet’. Experiments on real-world datasets demonstrate that the proposed framework outperforms the baselines for detecting user types. Finally, we illustrate data analysis on different types of users (e.g., practitioner vs. promotional) from our dataset. While we focus on lifestyle-related tweets (i.e., yoga, keto), our method for constructing user representation readily generalizes to other domains.

Evaluation of integrated daylighting and electric lighting design projects: Lessons learned from international case studies

This article presents and discusses the lessons learned from the monitoring of 25 integrated daylighting and electric lighting international case study projects. The case studies consist of real occupied buildings that have been monitored as part of the International Energy Agency (IEA) SHC Task 61/EBC Annex 77 Programme. The general goal of the case studies was to balance lighting energy use with occupants’ visual and non-visual requirements. This was achieved using innovative solutions for daylighting and electric lighting with advanced controls, but also implementing simple and out-of-the-box strategies. The findings suggest that energy demands for lighting can significantly be reduced by combining sensible daylight provision, efficient lighting sources, and advances in controls. Yet, the effective achievement of project goals requires adequate monitoring, fine-tuning, and verification. The findings also suggest that the adoption of “integrative” lighting – that is, lighting systems that address both visual and non-visual responses – is getting increasingly popular. Catering to non-visual requirements will likely drive further innovation in lighting technology. Currently, there is limited investment available for developing daylighting systems for integrative lighting, and the current related electric strategies often come at the risk of energy rebound effects. Overall, providing daylighting and understanding user requirements are fundamental steps towards achieving quality projects, with potential benefits beyond saving energy.

Fashion-MNIST Clothing Classification using Deep Learning

Online fashion market is constantly growing, and an algorithm capable of identifying garments can help companies in the clothing sales sector to understand the profile of potential buyers and focus on sales targeting specific niches, as well as developing campaigns based on the taste of customers and improve user experience. Artificial Intelligence approaches able to understand and label humans’ clothes are necessary, and can be used to improve sales, or better understanding users. Convolutional Neural Network models have been shown efficiency in image c1assification. It presents four different Convolutional Neural Networks models that used Fashion-MNIST dataset. Fashion-MNIST is a dataset made to help researchers finding models to classify this kind of product such as clothes, and the paper that describes it presents a comparison between the main classification methods to find the one that better label this kind of data. The main goal of this project is to provide future research with better comparisons between classification methods.

Analysis Designers' Process of Insight Generation through Empathy with Users

AbstractThis study aims to investigate the good way to generate insight through empathy with users. The fifteen experiment participants drew thinking processes of understanding users and defining insight statements while generating insight statements based on a given interview transcript. The thinking processes were assessed by qualitative coding, and the insight statements were evaluated. The results identified the types of thinking that should be avoided when gaining insights. This paper proposes a framework to categorise designers’ process of gaining insight.