User Goals Research Articles

Serving two masters – How dual price signals can undermine demand flexibility

Demand-side flexibility is often encouraged via demand response programs, where users are incentivized to adjust their electricity consumption based on price signals in tariffs. The design and implementation of these signals are vital, as they link conditions of the energy system with user behaviour. As a result of energy system separation into stages of generation, many users are required to simultaneously respond to two price signals. While existing research has mainly examined responses to a single signal, this study highlights the complexities when users must react to two signals simultaneously. It presents a case study using two distinct price signals: real-time pricing (RTP) and a demand charge, analysing the implications such dual price signals could have on users. The study reveals the empirical incompatibility of these signals, leading to conflicting user goals. Such interference complicates decision-making for demand flexibility, potentially eroding user trust in retailers and system operators. The study ends with proposing an alternative tariff, resolving the dual price situation, which facilitates user comprehension and decision-making, and thus enhances the potential for demand flexibility.

A bi-level dispatch optimization of multi-microgrid considering green electricity consumption willingness under renewable portfolio standard policy

Under the policy of renewable portfolio standard (RPS), many microgrid (MG) users with high electricity consumption are installed with renewable energy (RE) generation devices to complete their RE consumption responsibility and reduce carbon emissions. In view of the conflict between the goals of microgrid operators (MGO) and MG users, it is a challenge to achieve economic optimization for both MGO and MG users at the same time when they participate in system dispatch and complete RE consumption responsibility. Therefore, this paper proposes a bi-level noncooperative dispatch strategy that takes into account user satisfaction and RE consumption willingness. In this bi-level model, the upper level is led by an MGO who decides electricity retail prices, while the lower level is followed by MG users who participate in demand response (DR) and change electricity purchase strategies. First, a novel comprehensive evaluation model is formulated to evaluate users' willingness to consume green electricity. Based on this, users' consumption behavior of green and thermal electricity is modeled independently not only in electricity trading but also in power dispatching. Second, optimization objectives are established with the goal of maximizing MG users' welfare, including user satisfaction improvement and energy purchase cost reduction, as well as maximizing the revenue of the MGO. Then, a Stackelberg game model is constructed, and a differential evolution algorithm nested CPLEX is used to solve the Stackelberg game problem of balancing the interests of both parties. Finally, our simulation analysis shows that under the dispatch strategy in this paper, load peak-valley difference is reduced. In addition, when the green electricity generated within the system is sufficient, based on a high level of users' willingness to consume green electricity, the total consumption of green electricity is increased by 29.5% and the overall welfare of users is increased by 0.75%.

Easy‐to‐use personalized legal and financial planning tool for AD/ADRD caregivers and persons with dementia

AbstractBackgroundFinancial management is one of the most cited sources of stress among caregivers. Legal planning presents additional challenges. Only a small percentage of dementia caregivers report successfully completing necessary planning. Further, persons with dementia are vulnerable to fraud, scam, and inappropriate financial transactions. With stakeholder participation, we explored a novel solution using state‐of‐the‐art technology aimed to overcome impediments that have plagued prior legal and financial planning resources.Method18 stakeholders from 10 organizations across the U.S. serving persons with dementia and caregivers participated in two 60 to 90‐minute semi‐structured interviews that were recorded and transcribed. Qualitative stakeholder input was collected through an iterative process. During initial interviews, a mockup was shared to elicit feedback. There was a 3‐month wait after the first interviews to incorporate recommendations into the evolving prototype. During the second round of interviews, stakeholders evaluated the prototype progress based on feedback they previously provided. Stakeholders then completed an electronic survey to assess their overall confidence in the value of the future tool. A phase 1 prototype was designed using Adobe XD. Stakeholders influenced the content, layout, colors, and images with goals of clarity, usability, legibility, and simplicity. Included are a ‘how the tool works’ section; a wizard that guides users through a topic by asking questions, responding appropriately, a prioritized to‐do list; a chatbot; and a dashboard for viewing progress and sharing with selected care partners. Responses to questions were generated by legal and financial experts.ResultAll 18 stakeholders confirmed that financial management and legal planning are highly stressful for persons with dementia and their families and that there is a need for a tool of this type. 85% of the stakeholders indicated that were extremely satisfied, or very satisfied that the tool would be a beneficial product.ConclusionResults confirmed the need for and utility of an easy‐to‐use tool assisting in legal and financial planning. Phase 2 will incorporate additional content and features along with further review from legal and financial experts. Persons living with dementia and care partners will be included in the testing, evaluation, and further refinement of the technology tool.

Delving Deep into NutriScan: Automated Nutrition Table Extraction and Ingredient Recognition

Abstract: Our paper introduces an innovative solution for automating the detection of nutrition tables and recognition of ingredients on packaged food products, addressing the growing demand for tools that facilitate the extraction of essential dietary information from food packaging. The increasing interest in healthy eating and dietary awareness underscores the need for precise and efficient tools to assist consumers and health-conscious individuals in making well-informed food choices. Harnessing state-of-the-art technology, we enhance the accuracy of nutrition table and ingredient detection through fine-tuning the EfficientDet model. We further extract textual content from these tables using PaddleOCR a sophisticated optical character recognition tool. Additionally, we employ regular expressions to meticulously capture crucial nutritional details, including salt or sodium content, carbohydrates, total fat, saturated fat, trans fat, protein values, additives, and allergens found in the product. To empower users in their dietary decision-making, we introduce a dynamic user preference system. Users can tailor their dietary requirements, specifying allergies and preferences for sugar, saturated fat, total fat, or salt content. Our system then evaluates food products and offers personalized recommendations including the nutri-score, indicating their alignment with the user's health goals. Extensive experimentation and evaluation confirm the high accuracy and efficiency of our method in both nutrition table and ingredient recognition. These paper underscores the transformative potential of our approach, which can revolutionize the accessibility of dietary information, encourage healthier eating habits, and promote dietary transparency

Modeling the user experience in virtual and real world transition by understanding the user goal value

Recent advancements in social computing have led to a significant impact on the boundary between the virtual and real worlds. This study explores the virtual world within digital games, using a mean-end chain model and the laddering method to conduct in-depth interviews. It was found that Convenience, Interactions with others, and Ease of use, were the main design attributes for users. The main consequences for the user are discovered to be the Sense of physical presence and Physical or emotional reality is affected. Important values sought by the player are Self-fulfillment and Make life easier. Interestingly, while virtual worlds can have positive effects on users' real lives, they also introduce negative consequences, such as desensitization. In response to these findings, initial steps are proposed to address this issue, including the creation of a structural framework for users transitioning between virtual and real worlds. This framework offers theoretical guidance for future game product development in three-dimensional virtual environments, ultimately enhancing the player experience.

Discovering semantic and visual hints with machine learning of real design templates to support insight exploration in informatics

Ideation is the process by which ideas are populated by exploring visuals and semantics as essential stimuli when dealing with creative problem-solving. Knowledge of such activity often desires frequent changes in user goals and insights. A common technique that utilizes pre-designed contents with semantic-visual concepts for ideation raises uncertainty in informatics. This adaptive workflow supports the exploration of many text descriptions and image previews from software products and service design templates. With three steps: 1) Extract and summarize semantic-visual features from design contents. 2) Use clusters of adapted information for multi-label classification. 3) Construct a design exploration model with visualization and exploration. This study has provided a glanceable workflow of ideation. Hence, engineering of the design knowledge supports semantic and visual hints for emerging pathways of continuous ideation and design exploration.

Exploring gender impact on collaborative care planning: insights from a community mental health service study in Italy

IntroductionPersonal recovery is associated with socio-demographic and clinical factors, and gender seems to influence the recovery process. This study aimed to investigate: i) differences in the recovery goals of men and women users of a community mental health service in Italy; ii) any differences by gender in recovery over six months using the Mental Health Recovery Star (MHRS).MethodsService users and staff completed the MHRS together at recruitment and six months later to agree the recovery goals they wished to focus on. Socio-demographic and clinical characteristics and ratings of symptoms (BPRS), needs (CAN), functioning (FPS), and functional autonomy (MPR) were collected at recruitment and six months follow-up. Comparisons between men and women were made using t-tests.ResultsTen women and 15 men completed the MHRS with 19 mental health professionals. Other than gender, men and women had similar socio-demographic, and clinical characteristics at recruitment. Women tended to choose recovery goals that focused on relationships whereas men tended to focus on work related goals. At follow-up, both men and women showed improvement in their recovery (MHRS) and women were less likely to focus on relationship related goals, perhaps because some had found romantic partners. There were also gains for both men and women in engagement with work related activities. Ratings of functional autonomy (MPR) improved for both men and women, and men also showed improvement in symptoms (BPRS) and functioning (FPS).ConclusionsOur findings suggest that collaborative care planning tools such as the MHRS can assist in identifying individualized recovery goals for men and women with severe mental health problems as part of their rehabilitation.

Cross-domain coreference modeling in dialogue state tracking with prompt learning

Dialogue state tracking (DST) is to identify user goals from dialogue context and it is an essential component in task-oriented dialogue systems. In multi-domain task-oriented dialogues, a user often refers to the information mentioned in the previous context when the topic is transferred to another domain. Accurate modeling of the cross-domain coreference plays an important role in building qualified DST systems. As far as we know, there is only one work attempting to model the cross-domain coreference phenomenon in DST. However, it still has low efficiency and suffers from the difficulty of handling the complex reasoning over the dialogue context. To tackle these problems, in this paper, we propose a simple but effective DST model, called Coref-DST, to track the cross-domain coreference slots. Instead of predicting the actual values via complex reasoning, Coref-DST directly identifies the coreferred domains and slots from the dialogue context. Moreover, a domain-specific prompt method is proposed to predict all the slot values in a domain simultaneously, so as to better capture the relationship among the slots. The extensive experimental results on the MultiWOZ 2.3 dataset demonstrate that Coref-DST not only outperforms the state-of-the-art DST baselines but also has higher efficiency of training and inference.

Penerapan Goal Directed Design dalam Perancangan Ulang User Interface pada Admin Marketplace BUILD ID

Build Id is a website and application-based marketplace that provides various construction needs, both products and services. The Build Id design by PT Semen Baturaja Tbk is aimed at the community as a form of implementing digital transformation in Indonesia. But the design process, to requires evaluation and improvement before it is inaugurated. This is done to avoid complaints, which can reduce the performance of applications and companies. This study aims to help design the Build Id user interface so that it is more focused on the features to be implemented so that the results can match the user's needs. In testing, this study uses the Goal Directed Design method which focuses on designing application designs by identifying user goals and needs. The results of the test prove that the Build Id marketplace for Admins is running well and as expected.

ENHANCING PRAGMATIC KNOWLEDGE WITH CHATGPT: BENEFITS AND CONSIDERATIONS

Pragmatic knowledge, or the ability to use language appropriately in social situations, is a crucial aspect of effective communication. ChatGPT, a chatbot based on the GPT-3 language model, has the potential to serve as a tool for improving pragmatic knowledge. ChatGPT is trained on a large dataset of human conversation and can generate responses that are coherent, diverse, and context-specific. By providing opportunities for users to practice their language use in a variety of contexts and real-time feedback, ChatGPT can help language learners to develop their pragmatic skills. However, the use of ChatGPT also raises several challenges and ethical considerations. Understanding the benefits and challenges of using ChatGPT for pragmatic language learning will be crucial in determining its potential as a tool for language learning. The purpose of this paper is to evaluate the benefits and challenges of using ChatGPT for pragmatic language learning. To understand the potential of ChatGPT for pragmatic language learning, the researchers review the main features and capabilities of ChatGPT. This includes its ability to generate a response in different styles and registers and how it can be used for pragmatic language acquisition. The challenges and limitations of ChatGPT are also examined, including its imperfect simulation of human conversation, reliance on large amounts of data, and potential to reinforce stereotypes or biases. The researchers discuss the potential benefits of ChatGPT, including its ability to simulate natural conversation, generate diverse and context-specific responses, and adapt to the user's language level and learning goals. In addition, to providing valuable practice in simulating natural conversation, ChatGPT’s ability to generate coherent and context-specific responses can also help the user to develop their pragmatic skills, such as understanding and interpreting the intended meanings of others. The researchers consider the ethical implications of using ChatGPT for pragmatic language learning and the need for further research in this area. Overall, this paper provides a nuanced perspective on the potential and limitations of ChatGPT as a tool for enhancing pragmatic knowledge.

A novel continual reinforcement learning-based expert system for self-optimization of soft real-time systems

Virtual globes are soft real-time systems, which stream multi-resolution data sets and render world-scale landscapes in real-time. Such systems require an adaptation mechanism to fulfill user and quality of experience (QoE) requirements. Configuration and tuning of parameters to optimize system performance is challenging due to run-time uncertainties. In this work, we propose a continual reinforcement learning-based expert system for self-optimization of a soft real-time system to meet user and quality objectives. The proposed system is capable of learning continuously by utilizing the previously learned knowledge to fulfill adaptation requirements. The proposed managing system interacts with a managed system and evolves a knowledge base of adaptation rules for run-time optimization of the managed system to meet user and quality objectives. We devise a learning classifier system for the evolution, storage, and transfer of adaptation rules using a code fragments-based rich encoding scheme. We transform user goals, system states, and execution environment conditions into observable states. We validated the proposed system for the same and cross-domain knowledge transfer and reuse scenarios for different user goals and execution environments. The results of the proposed system are compared with baseline and state-of-the-art methods where the proposed system outperformed the methods in terms of adaptation accuracy.

A Study on User-Centered Brand Design from the context of Experience Design: Focused on Pet Supplies Industry in China

The pet supplies industry in China has experienced rapid growth in recent years, leading to intensified market competition. Consequently, brands are in need of a new dimension of experience that focuses on understanding user needs and issues while building brand loyalty and trust. This study proposes a user-centered brand design model consisting of three phases: user needs discovery, issue definition, and scenario development. Employing the MEOWMO brand and the E-MOW value system as a case study, the model combines quantitative and qualitative research methods, including surveys and user experience scenarios, to help brands precisely define user needs and convey brand value. The research identifies a trend where users tend to trust brands that align with their psychological cognition and concepts. Therefore, constructing user experience scenarios aids in recognizing user expectations, goals, and issues, encouraging user participation in co-creation and ultimately enhancing brand loyalty. This model provides brands with a new direction to bolster their impact and user loyalty in the pet supplies industry. It also offers theoretical support for user-centered brand design, aiding brands in survival and value enhancement in a fiercely competitive market.

Commodification of the Subject in Presentations of Virtual Sexual Identity

When the profiles created in social networks and the content produced are examined, the problem of commodification of the subject, especially in sexual identity presentations, draws attention. For this reason, in this study, emotions, thoughts, values and situations that cause objectification of people were investigated. This research has four aims: to create a conceptual framework regarding the sexuality perception of obscene content producers in social media, to investigate the motivations that cause people to create obscene content, to identify common points that affect the network preferences of content producers and to contribute to the literature on social media studies. For this purpose, case analysis method, one of the qualitative research methods, was used. The data were collected from social media applications named Instagram, Tender, Twitter by using purposeful criterion sampling method. Users who stand out with their sexual identity presentation on these platforms were asked questions in four different categories. These categories are users' opinions about the phenomenon of sexuality, the reasons for their social network preferences, why they prefer the presentation of sexual identity (common goals) and the problems they experience on these platforms. The findings of the research are as follows: The phenomenon of sexuality is seen as an escape from real life, freedom, pleasure, communication tools and discovery. The reasons why the participants prefer social networks are the ease of access, ease of sharing, the fact that these applications carry less risk than in real life, and the advantage of control. The common goals of users are economic freedom, recognition and self-realization. Problems arising from the presentation of sexual identity are disconnection from real life, exclusion, harassment and depression. Our results clearly show that sexual identity presentations created through social media applications commodify the individual and individual values. We think that our results will contribute to the current literature and will be good ground for new research to be conducted.

Assessment of the Influence of Contextual Issues in Evaluating eHealth Systems Usability in Tanzania

The adoption of eHealth systems in healthcare facilities has rapidly increased in many countries. However, the main challenge has been the quality and level of usability of those adopted systems, and the complexity of the challenge varies from one country to another based on contextual issues. Usability is also linked to contextual issues, which have a direct impact on deciding the methods for providing services on similar systems. This research focuses on assessing the influence of contextual issues on metrics that are applicable for evaluating the usability of eHealth systems through a case study of Tanzania. The findings of this research were obtained through the quantitative method, and the analysis was performed through structural equation modelling (SEM) using AMOS and SPSS applications. It is evident from this research that contextual factors, such as user characteristics, goals and tasks, technical environment, physical environment, and resources and technology, significantly impact the usability metrics that are important to the evaluation of eHealth systems. The usability metrics for eHealth systems identified in this research include navigation visibility, accessibility, perceived ease of use, error correction, internal collaboration, information quality, external collaboration, technical quality, guide and support, and perceived benefits. This study also revealed that the usability evaluation of eHealth systems should consider both common metrics and specific metrics in order to uncover both general information system and health context-specific usability issues

Human Factors Engineering and Usability as Key Drivers for Design of Device Suited for Urine Filtration and Enrichment

Evidence-based practices (EBPs) are not always straightforward to implement in a design process, as impacts can be difficult to assess in practice and appropriate methods are not yet established. User-centered design (UCD) offers opportunities to improve implementation of EBPs. UCD refers to the use of rigorous and validated engineering tools to design technology interfaces focused on user goals, such as device safety, effectiveness, efficiency, and user satisfaction. UCD has the potential to improve six core elements of patient-centered care: (i) education and shared knowledge, (ii) free flow of information, (iii) patient engagement, (iv) teamwork, (v) attention to non-medical aspects of care, and (vi) respect for patient preferences. Technological advances in medicine over the past few decades have provided patients with a variety of inventions, such as electronic health record patient portals, home-based medical devices, and smartphone apps. Effective application of UCD principles results in patient-centered inventions that are more likely to ease patients’ treatment burden, improve their care experience, increase patient engagement, and enable patients to become more self-sufficient. Here, the URICH device design process is used as case-example to demonstrate the inclusion of usability testing and all users as early as possible in the product design and development process.

(Digital Presentation) Application of Plasma Cleaning in the Preservation and Restoration of Cultural Heritage

The chemical reactivity of metals at inappropriate climate conditions can be a threat to metallic cultural heritage. It is known that oxygen plays an important role in the corrosion and decay of metallic objects. Oxide formation is among the most prevalent destructive phenomena in this field. The metallic archaeological objects lose their original shape due to the oxide layer that develops on their surface. Among physical-mechanical and chemical techniques used in the past to remove the oxide layer from these antiques, Cold plasma technology has been proposed as a novel safe method to successfully achieve this goal. In a plasma medium, which can be formed by an electrical discharge, chemically reactive species exhibit a unique behavior in response to the injected gas type, electrical and chemical parameters, etc. This special behavior aids in achieving the user's goal through physicochemical phenomena. In this study, Hydrogen gas, with its reductive character, in the plasma phase provides free radicals of Hydrogen reacting to the copper oxide layer on ancient coins. As a result of this plasma reduction reaction, separation of the oxide layer from the copper surface is achievable. This phenomenon which is called Plasma cleaning, is a type of etching. Plasma cleaning does not destroy surface structure and information contained within metallic heritage artifacts. The feasibility of this non-destructive cleaning method has been investigated for the preservation and restoration of ancient copper coins dating back roughly 300 years ago. These ancient copper coins were exposed to a cold hydrogen plasma for 120 minutes. Results show that Tenorite and Spertiniite formed on the surface of coins have been successfully removed. The black color of Tenorite, a type of copper oxide, gives a dark appearance to copper coins' surface, and Spertitnite, as a copper hydroxide, exhibits a blue-green color on copper coins. According to the results, after 2 hours of hydrogen plasma treatment, not only these green spots have been removed, but also the dark appearance of the entire surface of the coin has been reduced. This amount of clearance is a good result considering the untreated area. Moreover, Figure 1 illustrates the coin's surface using SEM (A) before and (B) after Hydrogen plasma treatment. These images were obtained at a 200x magnification from the surface. In contrast to Figure 1(A), which had heavily polluted surfaces, case B's dark pollution has been removed, reducing the amount of darkness on the coin's surface. This study shows the efficacy of Plasma cleaning for the preservation and restoration of ancient copper coins. Figure 1

Metaphorical User Simulators for Evaluating Task-oriented Dialogue Systems

Task-oriented dialogue systems (TDSs) are assessed mainly in an offline setting or through human evaluation. The evaluation is often limited to single-turn or is very time-intensive. As an alternative, user simulators that mimic user behavior allow us to consider a broad set of user goals to generate human-like conversations for simulated evaluation. Employing existing user simulators to evaluate TDSs is challenging as user simulators are primarily designed to optimize dialogue policies for TDSs and have limited evaluation capabilities. Moreover, the evaluation of user simulators is an open challenge. In this work, we propose a metaphorical user simulator for end-to-end TDS evaluation, where we define a simulator to be metaphorical if it simulates a user’s analogical thinking in interactions with systems. We also propose a tester-based evaluation framework to generate variants, i.e., dialogue systems with different capabilities. Our user simulator constructs a metaphorical user model that assists the simulator in reasoning by referring to prior knowledge when encountering new items. We estimate the quality of simulators by checking the simulated interactions between simulators and variants. Our experiments are conducted using three TDS datasets. The proposed user simulator demonstrates better consistency with manual evaluation than an agenda-based simulator and a seq2seq model on three datasets; our tester framework demonstrates efficiency and has been tested on multiple tasks, such as conversational recommendation and e-commerce dialogues.

Understanding the social inclusion needs of people living in mental health supported accommodation

ObjectivesTo identify the social inclusion needs that were (i) most commonly identified and (ii) most and least commonly prioritised as support planning goals for mental health service users living in supported accommodation, using the online Social Inclusion Questionnaire User Experience (SInQUE). We qualitatively examined mental health supported accommodation staff and servicer users’ views on barriers to offering support with two less commonly prioritised areas: help finding a partner and feeling less lonely.MethodsAnonymous SInQUE data were collected during a completed study in which we developed and tested the online SInQUE. Four focus groups were conducted with mental health supported accommodation staff (N = 2) and service users (N = 2).ResultsThe most common social inclusion needs identified by service users (N = 31) were leisure activities, finding transport options, and feeling less lonely. Of the needs identified, those that service users and staff least frequently prioritised as support planning goals were having company at mealtimes, getting one’s own furniture, feeling less lonely, help with finances, and help finding a partner. In the focus groups, staff and service users identified barriers to helping with loneliness and finding a partner which related to staff and service users themselves, supported accommodation services, and wider societal factors.

Life Cycle Cost Analysis of Pumping System through Machine Learning and Hidden Markov Model

The pumping system is a critical component in various industries and consumes 20% of the world’s energy demand, with 25–50% of that energy used in industrial operations. The primary goal for users of pumping systems is to minimise maintenance costs and energy consumption. Life cycle cost (LCC) analysis is a valuable tool for achieving this goal while improving energy efficiency and minimising waste. This paper aims to compare the LCC of pumping systems in both healthy and faulty conditions at different flow rates, and to determine the best AI-based machine learning algorithm for minimising costs after fault detection. The novelty of this research is that it will evaluate the performance of different machine learning algorithms, such as the hybrid model support vector machine (SVM) and the hidden Markov model (HMM), based on prediction speed, training time, and accuracy rate. The results of the study indicate that the hybrid SVM-HMM model can predict faults in the early stages more effectively than other algorithms, leading to significant reductions in energy costs.

Staff perceptions of factors affecting the use of RAS-DS to support collaborative mental health practice

BackgroundThe Recovery Assessment Scale: Domains and Stages (RAS-DS) was designed to be both a recovery outcome measure and a tool to enhance service-user control over their recovery journey. While extensively and globally used in mental health services for the former purpose, routine use for the latter purpose is yet to be realised. The aim of this study was to identify barriers, facilitators and additional supports needed for RAS-DS to be used to support service user participation, goal setting and recovery action planning.MethodsAn online survey was conducted of mental health workers who had engaged with RAS-DS, including fixed choice and open-ended questions. Data were analysed using descriptive statistics and interpretive content analysis respectively.ResultsThe 65 respondents reported more frequent use of RAS-DS as an outcome measure than as a collaboration tool and more than half reported difficulties in using it in this way. Factors that they described as influencing the use of RAS-DS as a tool for collaboration and support included: previous experiences with RAS-DS; organisational supports and policies; awareness of the RAS-DS amongst colleagues; RAS-DS related training and support; staff time and capacity; the format of RAS-DS; service user population or context; and respondents’ own active efforts.ConclusionsExtending the use of RAS-DS, an already widely used tool, to routinely support recovery-oriented practice has both efficiency and service user empowerment benefits. However further work is needed to enable this including: provision of co-designed, accessible training resources; a user platform including built in guidance; and strategies to promote management understanding and valuing of the enhanced recovery-orientation opportunities inherent in RAS-DS use.