• Journal of Information Technology Applications and Management
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• v.31 no.1
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• pp.97-112
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• 2024

In order to verify the factors affecting the acceptance of Serious Games for Healthcare (SGHs), this study developed a hierarchical model of general and specific benefit and risk factors affecting the intention to use SGHs based on the valence framework. As a result based on 199 samples, it was revealed that perceived customization and perceived schedule flexibility had a positive effect on the perceived benefits, which, in turn, had a positive effect on the intention to use SGHs. However, among the specific risk factors, only privacy risk had a positive effect on perceived risk, but it did not have a effect on SGHs usage intention. The results related to the fact that the survey respondents were potential users of SGHs and the bias that may overestimate the benefits provided by SGHs called optimistic bias. Based on these findings, some implications were presented such as the spread and distribution of SGHs to the ordinary persons, improvement of negative perceptions of games, and the need for data-based services to refine customized services for SGHs.

• Healthcare Informatics Research
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• v.24 no.4
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• pp.309-316
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• 2018

Objectives: Both the valence and arousal components of affect are important considerations when managing mental healthcare because they are associated with affective and physiological responses. Research on arousal and valence analysis, which uses images, texts, and physiological signals that employ deep learning, is actively underway; research investigating how to improve the recognition rate is needed. The goal of this research was to design a deep learning framework and model to classify arousal and valence, indicating positive and negative degrees of emotion as high or low. Methods: The proposed arousal and valence classification model to analyze the affective state was tested using data from 40 channels provided by a dataset for emotion analysis using electrocardiography (EEG), physiological, and video signals (the DEAP dataset). Experiments were based on 10 selected featured central and peripheral nervous system data points, using long short-term memory (LSTM) as a deep learning method. Results: The arousal and valence were classified and visualized on a two-dimensional coordinate plane. Profiles were designed depending on the number of hidden layers, nodes, and hyperparameters according to the error rate. The experimental results show an arousal and valence classification model accuracy of 74.65 and 78%, respectively. The proposed model performed better than previous other models. Conclusions: The proposed model appears to be effective in analyzing arousal and valence; specifically, it is expected that affective analysis using physiological signals based on LSTM will be possible without manual feature extraction. In a future study, the classification model will be adopted in mental healthcare management systems.

• Knowledge Management Research
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• v.19 no.3
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• pp.173-187
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• 2018

This study was aimed at suggesting an integrative framework for creating collective intelligence and enhancing group performance after reviewing previous studies including those related to learning organizations, organizational learning, knowledge management, and collective intelligence. In the first, we examined that the similarities and differences between collective intelligence and other similar concepts, such as learning organizations, organizational learning, and knowledge management. Next, an integrative framework for creating collective intelligence and channeling it into strong group performance were suggested. In this process, we reviewed conditions for creating collective intelligence and segmented the major variables as expectancy, valence, and instrumentality, according to Vroom's (1964) expectancy theory. Characteristics of problems and the roles of leaders were respectively considered as valence for inducing collaboration and expectancy for managing probability to achieve goals. Instrumental factors were also adopted from conditions for creating group intelligence suggested from several researchers, such as creativity, openness, willingness for working together, horizontal communication, centralization in decision making, and building effective information and communication technology system and active usage of it. We discussed two potentially disputable matters about the scope and level of collective intelligence and group performance and suggest several theoretical and practical implications in the Discussion.

• Bulletin of the Korean Chemical Society
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• v.35 no.4
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• pp.1225-1228
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• 2014

• Journal of Industrial Convergence
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• v.21 no.9
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• pp.23-32
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• 2023

Interest in Serious Games for Healthcare (SGHs) that can improve health through games is increasing. Digital Therapeutics (DTx) is a treatment that must be approved for effectiveness and safety, so it should follow the traditional drug distribution method, but SGHs are wellness products that are more flexible in terms of adoption and diffusion than DTx. SGHs are effective because it can provide customized services through continuous monitoring and feedback. When SGHs are applied to cognitive impairment treatment or behavioral correction, malfunctions and side effects are minor. This study developed research model based on the Valence Framework, gathered data from 142 undergraduates, and demonstrated that only the perceived benefits have a statistically significant positive (+) effect on SGHs acceptance intentions. Based on these results, this study suggests that SGHs companies should promote benefits in accepting SGHs for general users and they need for a distribution and analytics platform strategy based on a data-driven approach.

• Asia pacific journal of information systems
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• v.25 no.4
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• pp.746-762
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• 2015

This study developed a conceptual model that integrated psychological and physical reactions resulting from online tourism reviews through a longitudinal trust-satisfaction model (LSTM) developed based on the extended valence framework and expectation-confirmation theory. Online reviews are essential factor of consumer's purchase decision. This phenomenon is well applied in a tourism context. However, investigations on online reviews in a longitudinal approach in a tourism context are quite limited. Therefore, this study suggests a conceptual model based on LTSM and several propositions about how online tourism reviews, which are divided into factual and experiential reviews, influence the future travelers' perceptions and attitudes, such as expectation, confirmation, and destination loyalty, in a longitudinal format by examining previous related studies. Finally, expected results were discussed and several implications were described theoretically and practically.

• International Journal of Computer Science & Network Security
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• v.23 no.10
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• pp.21-29
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• 2023

Recently there has been an increase in interest and competition in sharing economy platforms. The success stories of many companies have spread in this field, such as Uber, but on the other hand, there are many other companies that have failed. We studied and analyzed the factors that affect the user's participation in the sharing economy platforms as an essential part of this system, and how to maintain the consumer's intention of use without compromising consumer satisfaction, as it has become an issue of great importance on the path to the success of the sharing platforms. Relying on the expanded valence framework and expectation confirmation theory as a basis, we constructed hypotheses that influence intention to participate in participatory platforms. Results show that system quality, trust, perceived benefits, and satisfaction are important factors that positively influence intention to continue to participate. This research is expected to help researchers move forward with research related to the future and help business managers understand user insights and integrate them with their business model to help the success, development and expansion of their business in the Kingdom of Saudi Arabia.

• Bulletin of the Korean Chemical Society
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• v.6 no.5
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• pp.309-311
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• 1985

When a molecule is perturbed by an external field, the perturbed moecue can be described as a doubly perturbed system. Hartree-Fock operator in the absence of the field is the zeroth order Hamiltonian, and a correlation operator and the external field operator are perturbations. The effective Hamiltonian, which is a projection of the total Hamiltonian onto a small finite subspace (usually a valence space), has been formally derived. The influence of the external field to the molecular Hamiltonian itself has been examined within an effective Hamiltonian framework. The first order effective expectation values, for instance electromagnetic transition amplitudes, between valence states are found to be easily calculated - by simply taking matrix elements of the effective external field operator. Implications of the terms in perturbation expansion are discussed.

• Science of Emotion and Sensibility
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• v.17 no.2
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• pp.3-12
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• 2014

A way to increase effectiveness of charitable donation ads is to activate or magnify emotional experiences (e.g., sympathy, empathy, psychological distress) among target audience. Past studies suggest that mental imagery and attention, which activate or magnify emotional experiences, can be influenced by verbal message attributes (i.e., message concreteness and valence) of charitable donation advertisements. Based on the previous research, the study built a conceptual framework for processing of charitable donation advertising: message concreteness and valence ${\rightarrow}$ mental imagery and attention ${\rightarrow}$ emotional experiences ${\rightarrow}$ donation intention. To verify the framework, the study investigated on the influence of message concreteness and valence on mental imagery and attention through assessing ERP responses. It also examined how message concreteness and valence have an effect on the intent to donate through measuring the amount of donation. The study revealed that concrete message activated mental imagery more than abstract message whereas negative message enhanced attentional level more than positive message. Compared to the other conditions, when the message was concrete and negative, the amount of donation was significantly large.

• Bulletin of the Korean Chemical Society
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• v.24 no.6
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• pp.809-811
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• 2003

This brief review contains surveys of both four-component and two-component relativistic molecular theories. First the four-component relativistic approach is reviewed. Emphasis is placed on efficient computational schemes for the four-component Dirac-Hartree-Fock and Dirac-Kohn-Sham methods. Next, in the twocomponent relativistic framework, two relativistic Hamiltonians, RESC and higher-order Douglas-Kroll (DK), are introduced. An illustrative application is shown for the relativistic study on valence photoelectron spectrum of OsO₄. The developing four-component relativistic and approximate quasi-relativistic methods have been packed in a program suite named REL4D.