Personal Need Research Articles

Personalization of Affective Models Using Classical Machine Learning: A Feasibility Study

Emotion recognition, a rapidly evolving domain in digital health, has witnessed significant transformations with the advent of personalized approaches and advanced machine learning (ML) techniques. These advancements have shifted the focus from traditional, generalized models to more individual-centric methodologies, underscoring the importance of understanding and catering to the unique emotional expressions of individuals. Our study delves into the concept of model personalization in emotion recognition, moving away from the one-size-fits-all approach. We conducted a series of experiments using the Emognition dataset, comprising physiological and video data of human subjects expressing various emotions, to investigate this personalized approach to affective computing. For the 10 individuals in the dataset with a sufficient representation of at least two ground truth emotion labels, we trained a personalized version of three classical ML models (k-nearest neighbors, random forests, and a dense neural network) on a set of 51 features extracted from each video frame. We ensured that all the frames used to train the models occurred earlier in the video than the frames used to test the model. We measured the importance of each facial feature for all the personalized models and observed differing ranked lists of the top features across the subjects, highlighting the need for model personalization. We then compared the personalized models against a generalized model trained using data from all 10 subjects. The mean F1 scores for the personalized models, specifically for the k-nearest neighbors, random forest, and dense neural network, were 90.48%, 92.66%, and 86.40%, respectively. In contrast, the mean F1 scores for the generic models, using the same ML techniques, were 88.55%, 91.78% and 80.42%, respectively, when trained on data from various human subjects and evaluated using the same test set. The personalized models outperformed the generalized models for 7 out of the 10 subjects. The PCA analyses on the remaining three subjects revealed relatively little facial configuration differences across the emotion labels within each subject, suggesting that personalized ML will fail when the variation among data points within a subject’s data is too low. This preliminary feasibility study demonstrates the potential as well as the ongoing challenges with implementing personalized models which predict highly subjective outcomes like emotion.

Community Nurses' Perspectives on Conceptual Challenges Related to the Need for Nursing Care in Germany: A Constructivist Grounded Theory Study.

In Germany, a person's need for nursing care is assessed by evaluators according to the federal legal definition of the statutory long-term care insurance (LTCI). This definition and the associated standardized assessment tool constitute the conditions for providing nursing care in a community care setting in Germany. Furthermore, the community care setting is regulated by state law and negotiations between long-term care funds and associations of providers of nursing care. During nursing care, nurses engage in a variety of interactions with people. The extent to which the legal definition of the need for nursing care leads to challenges in these interactions is unclear. To address this knowledge gap, we conducted 22 problem-centered interviews with nurses in the community and analyzed the data using the constructivist grounded theory. The results revealed that the negotiation processes are settled within professional-family relationships and vary between the constructs of closeness and distance, advocacy and submission of responsibility, and ethos and technocracy; these are the central challenges nurses encounter in this setting. We discuss the implications and questions that arise from the findings for the nursing profession regarding its own current and future role as well as the design of nursing support in the community, to nurture more advanced nurse practitioners and community health nurses.

Math Gamification and ICT for University Learning: Systematic Review Article

The integration of math gamification and Information and Communication Technologies (ICT) in learning has been a subject of growing interest. This approach seeks to improve student motivation and performance by transforming mathematics teaching into a more interactive and hands-on experience in university education. In this research the PRISMA method was used, 80,000 academic papers were systematically reviewed on ICT-supported math gamification in education whereof 79,994 academic papers corresponding to other fields were excluded, selecting and using at the end 55 articles to conduct this research. Studies were identified that explored the effectiveness of this combination at different educational levels, with a particular emphasis on higher education. The results highlight a significant increase in student engagement and motivation, as well as improvement in knowledge retention as shown in the figures and tables of this research. Instant ICT feedback and the application of digital educational games contributed to have a more active learning adapted to individual needs. Although the results are encouraging, challenges remain, such as the need for personalization and equity in ICT access. Continued research seeks to perfect these strategies maximizing the benefits of gamification and ICT, highlighting the importance of adapting to the diversity of learning styles in mathematics education.

Can the prosocial benefits of episodic simulation transfer to different people and situational contexts?

Previous research has found that episodic simulation of events of helping others can effectively enhance intentions to help the same person involved and the identical situational context as the imagined scenarios. This ‘prosocial simulation effect’ is argued to reflect, at least in part, associative memory mechanisms whereby the simulation is reactivated when in the same situation as that imagined. However, to date, no study has examined systematically whether this ‘prosocial simulation effect’ can be transferred to response scenarios involving different people and/or situational contexts to the imagined scenarios, and if so, whether the degree of overlap with the imagined helping episode modulated the transfer effect. Across two experiments, we systematically varied the overlap of the simulated and response scenarios, both in terms of the persons in need and/or the situational contexts, and whether would influence the magnitude of prosocial simulation effect. Results from both experiments showed that the prosocial simulation effect can be transferred to response scenarios involving different people and situational contexts to the simulated scenarios. However, this finding was primarily driven by response scenarios that had a high degree of overlap to the simulated scenarios. The application of our findings to the practical implementation of simulation to promote prosociality in the real world is discussed.

Exploring return to work for patients with head and neck cancer.

The number of survivors of head and neck cancer (HNC) has steadily increased due to major advances in cancer care. However, cancer survivors who experience job loss face different challenges regarding return to work (RTW). Relatively few studies have integrated the experience encountered by patients. This mixed-methods study aimed to explore the experience and challenges of RTW in patients with HNC. Data were collected with structured questionnaires (n = 120) and semi-structured face-to-face interviews (n = 12). Relationships were found between patient's physical status, perceived stress, and social support. Patients who continued work, or not, had significant differences in reported physical function and stress. Four themes emerged from the qualitative data, including the perceived meaning of work, challenges for RTW, preparing for RTW, and social support. After diagnosis and treatment, patients perceived the meaning of work, such as personal value, responsibility, and financial need. They faced many challenges to RTW, including declining physical strength, workload, schedule rearrangement, speech difficulty, and changed appearance. In order to RTW, they prepared extensively and needed support from family and friends. This study revealed the experiences and challenges of RTW patients with HNC. The results allowed us to identify patients' concerns and ways that healthcare providers could improve the RTW process. Future studies may develop tailored approaches for RTW in healthcare and government policies.

Factors Influencing Interest In Entrepreneurship Among Bengkulu University Students Using The Theory Of Planned Behavior

This study involved seventh-semester students of Bengkulu University who are interested in entrepreneurship or already have a business and have taken entrepreneurship courses. The purpose of this study was to identify all the factors that influence students' entrepreneurial interests. Using Google Forms, an online questionnaire of fifty participants was used to collect data. The results of the research conducted using the theory of planned behavior show that the variables of self-efficacy, subjective norms, and need for achievement have a positive and significant influence on the entrepreneurial interest of Bengkulu University students. In other words, the stronger a person's self-efficacy, subjective norms, and need for achievement, the more interested in entrepreneurship they are.

An evolving learning style detection approach for online education using bipartite graph embedding

The increasingly widespread online education recently enabled a new form of teaching, learning, and overall educational outcome. However, the need of personalization is required as learners learn differently and learning follows a one-size-fits-all approach. Learning style is the most used personalization that plays an important role in learning. This learning style is a changeable trait that is influenced by the learner's behavior based on past experiences. As a result, knowing it over time helps to point learners in the right direction, motivate them, and enhance their learning outcomes. Research done so far does not take into account the changes in the behavior of learners, and the behavioral data is at large volume, making the existing approaches fail to capture and extract the behavior of learners efficiently. Inspired by these constraints, we propose an incremental learning style detection approach for online education with a bipartite graph embedding technique. We first construct a dynamic bipartite graph to represent the incremental interaction between learners and learning resources while learning. Then, introduce a dynamic bipartite graph embedding to learn the low dimensional representation of the constructed graph from the current and previous time. Finally, the low dimensional features are mapped to the selected Felder-Silverman learning style model (FSLSM) dimension each time to identify and group similar learners using the k-means clustering algorithm. The proposed approach can be integrated into different educational systems. Extensive experiments conducted using three datasets from 2015 KDD Cup courses demonstrate the effectiveness of our approach. Average of 93.19%, 95.76%, and 98.48% are achieved across the three datasets in accuracy compared to the existing approaches.

An evaluation of digital intervention for perinatal depression and anxiety: A systematic review

<abstract> <p>Digital intervention has been shown to be helpful in improving perinatal mental health. However, the design characteristics of such interventions have not been systematically reviewed. Considering that a lack of support—especially from a partner—is one of the major contributing factors to perinatal depression and anxiety, it is crucial to determine whether digital interventions have included partner participation. In this review, we systematically examined the design characteristics of digital interventions related to perinatal depression and anxiety and aimed to determine whether partner participation was incorporated as part of the interventions. Based on the PRISMA 2020 guidelines, five databases (PubMed, EBSCO, Cochrane, ProQuest, and Scopus) were searched. Narrative results of design characteristics were developed to provide a framework for the design and evaluation of the studies. A total of 12 intervention studies from China, Sweden, Australia, New Zealand, Singapore, Norway, and the United Kingdom were included. Across all studies, internet cognitive behavioral therapy and mindfulness therapy were overwhelmingly utilized as the major intervention approaches. While all studies reported reduced depressive symptoms after the intervention, only four studies reported subsequent decreased levels of both depressive and anxiety symptoms. Only one study included partner support in the intervention. Cognitive behavioral therapy and mindfulness therapy, two of the most common intervention approaches, were found to be effective in alleviating perinatal depression and anxiety. Partner participation should be prioritized in designing digital interventions to ensure comprehensive and easily accessible social support for persons in need.</p> </abstract>

Assessing acceptance and feasibility of a conversational agent to support individuals living with post-traumatic stress disorder.

Post-traumatic stress disorder (PTSD) is a pervasive health concern affecting millions of individuals. However, there remain significant barriers to providing resources and addressing the needs of individuals living with PTSD. To address this treatment gap, we have collaborated with clinical experts to develop PTSDialogue-a conversational agent (CA) that aims to support effective self-management of PTSD. In this work, we have focused on assessing the feasibility and acceptance of PTSDialogue for individuals living with PTSD. We conducted semi-structured interviews with individuals living with PTSD ( ). Participants were asked about their experiences with the PTSDialogue and their perceptions of its usefulness in managing PTSD. We then used bottom-up thematic analysis with a qualitative interpretivist approach to analyze the interview data. All participants expressed that PTSDialogue could be beneficial for supporting PTSD treatment. We also uncovered key opportunities and challenges in using CAs to complement existing clinical practices and support longitudinal self-management of PTSD. We highlight important design features of CAs to provide effective support for this population, including the need for personalization, education, and privacy-sensitive interactions. We demonstrate the acceptability of CAs to support longitudinal self-management of PTSD. Based on these findings, we have outlined design recommendations for technologies aiming to reduce treatment and support gaps for individuals living with serious mental illnesses.

Uticaj stereotipa na interkulturalnu komunikaciju

Broadly speaking, stereotyping is a cognitive mechanism that underlies all aspects of intercultural processes-the way individuals perceive members of other groups shapes their attitudes and behavior towards them and influence different types of intercultural interactions and worldviews Based on the assumption that positive stereotypes about people who come from other cultures are used in human communication as an expression of each person's need to simplify all impressions and representations in order to understand the world and the people around them, positive stereotypes can facilitate communication. On the other hand, negative stereotypes in intercultural communication can lead to complete misunderstandings because it is assumed that all people within a certain group have the same characteristics. Therefore, both positive and negative stereotypes in intercultural communication can result in unfounded generalisations, false evaluations and oversimplifications, thus forming the basis for unfair behavior and labelling towards those to whom they refer, in addition to discrimination and interpersonal conflicts. In the search for a model for successful intercultural communication, the principle that culturally specific information should not be applied to all members of a cultural group and that the uniqueness of each member of the group must be respected can be considered extremely important. Stereotypical classifications should not be resistant to change as they relate to relationships between people, which are highly susceptible to change. Successful intercultural communicators should be able to form an opinion based on their communication experience and independent observations, free from stereotypes that they may have consciously or unconsciously gained. Also, viewing the world from the prism of others, not only from our own egocentric and ethnocentric position, and not allowing stereotypes to act as "filters", which allow in only what is similar to our cultural behavior, are important in preventing the adverse effects of stereotypes on communication. Therefore, a recommendable model of successful and efficient intercultural communication is unburdened by bias and stereotypes towards the members of cultural groups different from our own.

Plot Dynamic Adaptation and Character Interaction Design of Artificial Intelligence in Musical Theater Performing Arts

Abstract In recent years, artificial intelligence technology has received widespread attention in the field of artistic creation. This paper proposes the use of intelligent software to create a musical work that matches the emotions of the audience when they watch a musical performance so as to mobilize the development of the musical plot and to involve the virtual digital man in the performance of the musical to increase the interactivity of the characters. Both the music automatic generation software and the application of the virtual digital person need to match the rhythm of the performance. Accordingly, this paper proposes a multimodal emotion recognition model based on deep learning, which is applied to recognize the audience’s emotions in real time to create music that matches the plot development and reasonable role interaction. Through simulation experiments, the average recognition rate of multimodal based on decision layer fusion is 84.8%, which is slightly higher than the average recognition rate based on feature fusion and much higher than the average recognition rate of single-modal speech emotion (67.5%) and face expression (78.5%). 76% and 73% of the audience members liked the “music” and “character” elements of the musical performance with AI technology, and 62% of the audience members expressed their desire to watch it again.

Identyfikacja i poczucie dumy młodych Amerykanów polskiego i tybetańskiego pochodzenia

Ethnic diversity in the United States is a dynamic phenomenon that affects all aspects of the country’s social, economic and cultural life. This is one of the characteristics that defines American identity and makes the United States one of the most diverse countries in the world. The article focuses on the identity of young Americans of Polish and Tibetan origins living in the Tri-State Area (Connecticut, New Jersey and New York). Students attending Polish and Tibetan Saturday Schools were selected for the study. These are two distinct ethnic groups, but it is assumed that maintaining the cultural heritage of their ancestors is what characterizes both of them. The research results confirm this thesis and indicate that the sense of identity is a natural need of a young person, expressed in a dual cultural pattern and a developmental task that should be undertaken. In both studies, a strong sense of pride in ethnic origin emerged, although it was articulated in different ways by young people. Students from both groups presented high cultural competences in their country of origin and country of residence.

Mendeteksi Faktor-faktor Pressure Terhadap Kecurangan Laporan Keuangan Menggunakan Artificial Neural Network

Fraudulent financial statements are the result of misstatements resulting from intentional acts or omissions, which could materially mislead readers of the financial statements. The focus in this research is to determine the most important pressure factors in detecting fraudulent financial statements. Pressure is one of the fraud risk factors in the fraud triangle. Pressure is a condition felt by management due to incentives to commit fraud, consisting of: financial stability by proxy (GPM, ACHANGE, SCHANGE, CATA, SALAR, SALTA, INVSAL), external pressure (LEV, FINANCE, FREEC), personal financial need (OSHIP), and financial target (ROA). Data collection method using secondary data on the manufacturing sector firms that are publicly listed on the Indonesia Stock Exchange in 2017-2021. The research method used is quantitative and the sampling method uses a purposive sampling technique, obtained 137 sample companies with 685 total data observed. Data were analyzed using an Artificial Neural Network. The findings indicated that the gross profit margin (GPM), cash flow from operating to total assets (CATA), demand for financing (FINANCE), leverage (LEV) and return on total assets (ROA) is the most important proxy in detecting fraudulent financial statement, while other proxies are not too important in detecting fraudulent financial statements.

Understanding Financial Literacy, Financial Resilience and Investment Decisions: A Case of Two Cities from India

The present study assessed the status of the financial literacy (FL) levels and examined its impact on the investment decisions of the investors from the cities of Ahmedabad and Vadodara in Gujarat state. We measured FL using a multi-dimensional construct of financial behaviour, attitude and knowledge. Investment decisions were analysed taking the six proxies – neutral information, personal financial need, macroeconomic indicators, accounting information, advocate information and firm image. The study revealed a high level of FL among the respondents with 62.50% of the respondents being highly financially literate and the remaining having a comparatively lower degree of FL. Though, respondents exhibited a higher level of financial literacy, they still lacked required degree of understanding of advanced financial and investment topics. Using simple linear regression, we found that investors’ investment decisions were significantly positively impacted by their levels of FL. This study has implications for employers, policymakers, regulatory authorities and financial education providers to achieve financial inclusion and well-being goals by devising appropriate strategies and interventions for individuals with varying level of FL.

Electronic Banking and Its Impact on Customer Satisfaction of Nepalese Commercial Banks

Electronic Banking and its impact on customer satisfaction of Nepalese commercial banks explores the relationship between internet banking and customer satisfaction. Internet banking allows customers to conduct real-time banking transactions electronically, offering convenience and accessibility. Utilizing a descriptive and casual comparative research design, the study examines internet banking users across 20 commercial banks in Nepal, focusing on Nepal Investment Bank Limited, Nabil Bank Limited, and Himalayan Bank Limited. Through purposive sampling, 150 respondents were selected, with 50 from each bank, for primary data collection. The findings indicate high levels of satisfaction with online banking services, with respondents expressing agreement on various aspects such as ease of website navigation, meeting personal needs, and prompt service delivery. Correlation analysis reveals positive and significant relationships between customer satisfaction and key factors including efficiency, personal need fulfillment, reliability, responsiveness, site organization, and user friendliness. Finding suggest that a strong association between internet banking and customer satisfaction. These findings underscore the importance of internet banking in enhancing customer experience and satisfaction within the Nepalese commercial banking sector. Electronic banking and its impact on customer satisfaction of Nepalese commercial banks.

Factors Affecting Investment Decisions of Permanent School Teachers in Pokhara

Investing is the use of money to increase its worth or generate more revenue. This article has been designed to examine the factors affecting investment decision of permanent school teachers in Pokhara. This study is based on causal comparative research design. It has used structured questionnaire to collect information. Samples were selected by multi sampling technique, selecting the than Chhorepatan Resource Center by purposive sampling in the first and selecting 139 permanent school teachers by simple random sampling in the second stage. The Total population of permanent school teachers of Pokhara Metropolitan City was 1,588 and targeted population was 211. The reliability of data is checked by calculating Cronbach Alpha and it was 0.77. Accounting information (AI), Firm`s Image (FI), Advocate Recommendation (AR), Personal Financial Need (PFA) and Dividend Policy (DP) were independent variable and Investment Decision (ID) was dependent variable. This research discovered that 61.2% of permanent teachers invest their fund in equity share. Lump sum investment method was more popular than systematic investment plan and monthly investment. 80% of permanent teachers invest less than 20% of their savings. Respondents prefers both cash and stock dividend policy. Regular income was found as main objective of investment. Friends and coworker’s advice was also considering while investing in equity share. This research has also presumed that there was positive significant relation between investment decisions and decision factors. It is suggested to the investors of stock market, to analyze the fundamental factors of issuer and the issuer should follow regular dividend policy to attract the value investors toward their securities.

CRITICAL ELEMENTS OF DISABILITY MODELS AS DETERMINANTS OF TRAVEL INTENTION OF PEOPLE WITH DISABILITIES TOWARDS NATURAL AND CULTURAL DESTINATIONS

The present empirical study aims to determine the key factors influencing the travel intention of persons with disabilities who live across the Tungurahua Province, Ecuador. A cross-sectional survey was conducted between September 2019 and mid-March 2020, and collected 473 valid questionnaires containing critical components of the medical and social models of disability. Collected data were quantitatively analysed with multiple regression analysis. Results showed that some crucial elements of the social model of disability (i.e., socio-demographic features and destination quality dimensions) and an element of the medical model of disability (i.e., dependency or need of other persons) significantly affect the travel intentions of persons with disabilities (p<0.001). Findings allowed to conceptualise a new theoretical framework to potentially address and solve accessible and inclusive issues of persons with disabilities from Tungurahua Province-Ecuador and other international nations with similar natural and cultural attractions.

FINANCIAL SHENANIGANS AND COMPANY CHARACTERISTICS IN INDONESIA PUBLIC COMPANY

Financial shenanigans are moves made by a company's management with the intention of falsifying the company's financial status and stated performance. The goal of this study is to clarify if financial considerations and company size have an impact on a company's propensity to engage in financial misdeeds in Indonesian public companies. Financial leverage, financial stability, personal financial need, and return on assets are the financial characteristics that were examined in this study. An Indonesian firm that has gone public serves as the study's sample. Purposive sampling was used in this study's sampling. This study's analysis method makes use of multiple linear regression. The findings revealed that the company was unaffected by all variables except for financial leverage.

Polyagonists in Type 2 Diabetes Management.

This review summarizes the new developments in polyagonist pharmacotherapy for type 2 diabetes. Several dual- and triple-agonists targeting different pathogenic pathways of type 2 diabetes have entered clinical trials and have led to significant improvements in glycaemia, body weight, fatty liver, and cardio-renal risk factors, with variable adverse event profiles but no new serious safety concerns. Combining agents with complementary and synergistic mechanisms of action have enhanced efficacy and safety. Targeting multiple pathogenic pathways simultaneously has led to enhanced benefits which potentially match those of bariatric surgery. Tirzepatide, cotadutide, BI456906, ritatrutide, and CagriSema have entered phase 3 clinical trials. Outcomes from published clinical studies are reviewed. Efficacy-safety profiles are heterogeneous between agents, suggesting the potential application of precision medicine and need for personalized approach in pharmacological management of type 2 diabetes and obesity. Polyagonism has become a key strategy to address the complex pathogenesis of type 2 diabetes and co-morbidities and increasing number of agents are moving through clinical trials. Heterogeneity in efficacy-safety profiles calls for application of precision medicine and need for judicious personalization of care.

УЛУЧШЕНИЕ СИСТЕМЫ ВЗЫСКАНИЯ АЛИМЕНТОВ В КАЗАХСТАНЕ: ПРОБЛЕМЫ И ПЕРСПЕКТИВЫ

The main purpose of this study is to develop recommendations and practical solutions aimed at ensuring a more effective recovery of alimony and protecting the interests of children and other persons in need. The analysis of current legislation, international experience, judicial practice, and scientific research aimed at regulating issues of alimony liability is carried out. The relevance of this topic is due to the need to solve the systemic problems that families face when collecting alimony, as well as the importance of ensuring justice and the material well-being of children. The study examines key aspects of alimony recovery systems in Kazakhstan, including legal regulation, organizational mechanisms, sanctions applied to ensure the fulfillment of alimony obligations, and measures to support families. The methodology includes the analysis of international experience, the study of expert opinions, and the analysis of the effectiveness of measures taken in Kazakhstan. The results of the study reveal problems such as income instability and evasion of obligations, as well as successful practices, including the introduction of a Unified Register of Debtors and the tightening of debtor liability. The conclusions are aimed at proposing concrete measures to automate processes, tighten the responsibility of debtors, create a unified coordination structure, and improve information exchange. The proposed recommendations are intended to improve the system of alimony collection, ensuring more equitable and effective functioning in the interests of families and children in Kazakhstan.