• Korean Journal of Social Welfare
• /
• v.61 no.4
• /
• pp.137-161
• /
• 2009

In an effort to identify predictors of job performance, research studies in social work administration has been so far on the individual practitioners' levels of knowledge and skills, which could be used in a workplace. As the theoretical concept of organizational environment was fully introduced into social work administration research, however, studies on practitioners' job performance began to have interest in the team or the organizational level variables as well as individual level variables. Along the course of this tendency, this study attempted to test the effect of individual, team, and organizational level variables on the job performance of human service workers. The individual level variables consisted of knowledge, skills, job satisfaction, personality, and counter-productive work behaviors of workers. The team or the organizational level variables included situational constraint, organizational justice, job characteristics, government-dependency, and inter-organizational cooperation. Multi-level complex survey data collected by cluster sampling method from 314 practitioners in 23 organizations were analyzed using Hierarchial Linear Model. Results showed that both task and contextual performance were affected by individual, team, and organizational level variables in various ways.

• The Journal of Information Systems
• /
• v.26 no.4
• /
• pp.163-188
• /
• 2017

Purpose The purpose of this study is to empirically analyze the factors affecting the intention to use the IPA focusing on functional characteristics. Based on the research result, this research has significance in that it not only suggested strategic guidelines for the related business operators, it also helped identify the factors that will influence the intention to use an intelligent personal assistant centering on the functional characteristics of the IPA. Design/methodology/approach Accordingly, in an attempt to identify factors that will influence the intention to use the intelligent personal assistant, we proposed a research model, together with a corresponding hypothesis, which incorporates the functional characteristics (personalization, anthropomorphism, autonomy, communication ability, contextual offer) and perceived enjoyment of the intelligent personal assistant into a technology acceptance model. To verify the research hypothesis of this research, we have conducted a questionnaire survey with individuals who have used an intelligent personal assistant as target. And with the data collected from 215 copies of the questionnaire survey, we have carried out a path analysis using the PLS structural equation. Findings As a result, it turned out that, of the IPA functional characteristics, personalization had a positive effect on perceived usefulness, autonomy had a positive effect on perceived usefulness and perceived ease of use. Also, communication ability had a positive effect on perceived ease of use and perceived enjoyment, and anthropomorphism and contextual offer had a positive effect on perceived ease of use and perceived enjoyment and turned out to be major factors that increased the use intention of intelligent personal assistant.

• The KIPS Transactions:PartD
• /
• v.15D no.5
• /
• pp.599-608
• /
• 2008

Advanced wireless network and sensor technologies are capable of collecting information such as temperature, humidity, weight, and location about objects at real time in logistics area. Besides, users want to be notified of contextual information about interest of objects whenever they want it and wherever they want it. To satisfy these requirements, applications should collect and analyze contextual information at real time, and must support a service that can notify it to wanted users. Event-based service is one of the way to satisfy these requirement of users. In this paper, we design an event notification system focused on location- and RFID-based logistics area. To do this, we present XML-based event expression model, ECA-based profile definition model, and an algorithm that has high scalability by distinguishing event filtering in two steps. Based on these designs, our implemented system can apply to not only logistics area but also intelligent traffic control system based on RFID or GPS devices.

• Journal of Korean Society of Rural Planning
• /
• v.26 no.4
• /
• pp.41-52
• /
• 2020

The purpose of this study is to identify the conflict between residents and governments in partnership arising from the designation of National Important Agricultural Heritage for Damyang Samdari village and to suggest directions for improvement. To this end, residents of Samdari Village in Damyang, designated as an important national agricultural heritage, were interviewed. Interviews were analyzed through grounded theory, categorized into open coding, axial coding, and selective coding, and a paradigm model was constructed. Through this, the central phenomena of resident participation patterns currently appearing in the village were identified, and causal, contextual, and intervening conditions were analyzed. Causal conditions were analyzed as one-sided administrative treatment, assortment matching project, one-time plan, excessive dependence of residents and economic damages of residents at the beginning of the designation of national important agricultural heritage. As a result, conflict between residents and local governments occurred as a central phenomenon, and contextual conditions such as decline in the competitive of bamboo resources and frequent change in managers were also affecting the central phenomenon. As intervening conditions to alleviate the central phenomenon, there are local government's purchase of bamboo fields and fragmentary business effects. The action taken by the residents and officials in response to a fixed conflict is called an action-interaction strategy. Residents refused to change and settled in reality, and local governments avoided conflict. From the beginning of the designation to the present, the villagers gradually lost interest in the National Important Agricultural Heritage due to problems and conflicts that occurred in the process of forming a partnership in the National Important Agricultural Heritage project. Based on the analyzed model, a plan to build the partnership standards on Damyang bamboo field to secure the sustainability of the field and increase the practicality of resident participation, that is partnership, was suggested.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2023.05a
• /
• pp.357-359
• /
• 2023

This paper proposes a hybrid recommendation system (RS) model that overcomes the limitations of traditional approaches such as data sparsity, cold start, and scalability by combining collaborative filtering and context-aware techniques. The objective of this model is to enhance the accuracy of recommendations and provide personalized suggestions by leveraging the strengths of collaborative filtering and incorporating user context features to capture their preferences and behavior more effectively. The approach utilizes a novel method that combines contextual attributes with the original user-item rating matrix of CF-based algorithms. Furthermore, we integrate k-mean++ clustering to group users with similar preferences and finally recommend items that have highly rated by other users in the same cluster. The process of partitioning is the use of the rating matrix into clusters based on contextual information offers several advantages. First, it bypasses of the computations over the entire data, reducing runtime and improving scalability. Second, the partitioned clusters hold similar ratings, which can produce greater impacts on each other, leading to more accurate recommendations and providing flexibility in the clustering process. keywords: Context-aware Recommendation, Collaborative Filtering, Kmean++ Clustering.

• Journal of Korean Academy of Nursing
• /
• v.30 no.5
• /
• pp.1279-1291
• /
• 2000

The main objectives of this study were to analyze the concept of hope, so to provide basic data to develop a valid instrument to measure hope, and to develop hope enhancing nursing intervention a program for cancer patients. The hybrid model approach was applied in three phases, the theoretical phase, the empirical phase, and the analytic phase. The study was developed on universal attributes explaining generalized hope and specific hope, which were revealed in a comprehensive review of the literature. In the empirical phase, eight cancer patients undergoing chemotherapy were interviewed to reveal causes, motivation, and their resource of hope according to The Hope Assessment Guide (Farren, Herth, & Popovich, 1995). In the analytical phase, the results of the two previous stages of the study were compared. The results were as follows : In the theoretical phase, six dimensions of hope emerged; affective, cognitive, behavioral, affiliative, temporal and contextual dimension. The antecedent of hope was loss, crisis, uncertainity, and stress. The consequences were renewal, development of new methods, safety, peace and transcendental competence. In the empirical phase, these six dimensions emerged as theoretical phases were verified and specified as these descriptive terms: feeling, intention, expectation, activity, relation, future- orientation, reality and goal-setting. The antecedent factor of hope was occurrence or recurrence of cancer. The consequence of hope was ability to cope with real condition, feeling of safety and comfort, peace, development of new strategy and recovery of disease. The major content of hope in this phase was related to specific hope, but it was also influenced on by general hope. In the analytic phase, general and specific hope was renamed as trait and state hope. All attributes emerged at the empirical phases, and also emerged at the theoretical phase. However, cognitive and contextual dimensions were revised and specified. In conclusion, the concept of hope is divided into trait hope and state hope, and state hope is an anticipatory expectation that occurs at the time of a stressful stimulus, such as being diagnosed with cancer. Hope is a multidimensional dynamic energized mental state which has the dimensions of affective, cognitive, behavioral, affiliative, temporal and contextual. There should be further studies to develope the state and trait hope scale according to definition and attributes of hope investigated in this study. In addition, considering results of the empirical phase, the family is very a important factor as a resource of hope, so it is necessary to consider family in implementing a nursing intervention program to enhance hope.

• The Transactions of the Korean Institute of Electrical Engineers
• /
• v.40 no.8
• /
• pp.782-791
• /
• 1991

In the fields of pattern recognition such as speech recognition, several new techniques using Artifical Neural network Models have been proposed and implemented. In particular, the Multilayer Perception Model has been shown to be effective in static speech pattern recognition. But speech has dynamic or temporal characteristics and the most important point in implementing speech recognition systems using Artificial Neural Network Models for continuous speech is the learning of dynamic characteristics and the distributed cues and contextual effects that result from temporal characteristics. But Recurrent Multilayer Perceptron Model is known to be able to learn sequence of pattern. In this paper, the results of applying the Recurrent Model which has possibilities of learning tedmporal characteristics of speech to phoneme recognition is presented. The test data consist of 144 Vowel+ Consonant + Vowel speech chains made up of 4 Korean monothongs and 9 Korean plosive consonants. The input parameters of Artificial Neural Network model used are the FFT coefficients, residual error and zero crossing rates. The Baseline model showed a recognition rate of 91% for volwels and 71% for plosive consonants of one male speaker. We obtained better recognition rates from various other experiments compared to the existing multilayer perceptron model, thus showed the recurrent model to be better suited to speech recognition. And the possibility of using Recurrent Models for speech recognition was experimented by changing the configuration of this baseline model.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.16 no.8
• /
• pp.2787-2800
• /
• 2022

The aging society increases emergency situations of the elderly living alone and a variety of social crimes. In order to prevent them, techniques to detect emergency situations through voice are actively researched. This study proposes CutPaste-based anomaly detection model using multi-scale feature extraction in time series streaming data. In the proposed method, an audio file is converted into a spectrogram. In this way, it is possible to use an algorithm for image data, such as CNN. After that, mutli-scale feature extraction is applied. Three images drawn from Adaptive Pooling layer that has different-sized kernels are merged. In consideration of various types of anomaly, including point anomaly, contextual anomaly, and collective anomaly, the limitations of a conventional anomaly model are improved. Finally, CutPaste-based anomaly detection is conducted. Since the model is trained through self-supervised learning, it is possible to detect a diversity of emergency situations as anomaly without labeling. Therefore, the proposed model overcomes the limitations of a conventional model that classifies only labelled emergency situations. Also, the proposed model is evaluated to have better performance than a conventional anomaly detection model.

• International Journal of Computer Science & Network Security
• /
• v.23 no.9
• /
• pp.47-54
• /
• 2023

For Bengali music emotion classification, deep learning models, particularly CNN and RNN are frequently used. But previous researches had the flaws of low accuracy and overfitting problem. In this research, attention-based Conv1D and BiGRU model is designed for music emotion classification and comparative experimentation shows that the proposed model is classifying emotions more accurate. We have proposed a Conv1D and Bi-GRU with the attention-based model for emotion classification of our Bengali music dataset. The model integrates attention-based. Wav preprocessing makes use of MFCCs. To reduce the dimensionality of the feature space, contextual features were extracted from two Conv1D layers. In order to solve the overfitting problems, dropouts are utilized. Two bidirectional GRUs networks are used to update previous and future emotion representation of the output from the Conv1D layers. Two BiGRU layers are conntected to an attention mechanism to give various MFCC feature vectors more attention. Moreover, the attention mechanism has increased the accuracy of the proposed classification model. The vector is finally classified into four emotion classes: Angry, Happy, Relax, Sad; using a dense, fully connected layer with softmax activation. The proposed Conv1D+BiGRU+Attention model is efficient at classifying emotions in the Bengali music dataset than baseline methods. For our Bengali music dataset, the performance of our proposed model is 95%.

• Journal of Families and Better Life
• /
• v.24 no.1 s.79
• /
• pp.11-30
• /
• 2006

The purpose of this study was to verify a Structural Equation Model that constructed the causations among the leisure constraints, leisure. motivation, and leisure participation. This model posits that constraints determine motivation to participation. Concretely, structural and interpersonal leisure constraints(contextual factors) will affect interpersonal leisure constraints in the light of ecological perspective. Also, leisure constraints will affect leisure motivation based on self-determination theory that may influence leisure participation indirectly. A survey questionnaire was administered to 301 elderly in an institution for the elderly. A measurement model and a structural equation model estimates by Maximum Likelihood method(ML method) utilizing LISREL 8.0 ver. The analysis showed that a goodness of fit is good of structural equation model presented in the study. And, all hypothesis adopted about causations among the leisure constraints, leisure motivation, leisure participation.