• Journal of Industrial Convergence
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• v.22 no.7
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• pp.15-21
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• 2024

A hiking stick is generally one of the walking aids that allow hikers to walk while relying on their own bodies when walking. A rechargeable battery must be built into the hiking stick, which is an auxiliary device, in order to perform various functions. A separate power supply is required to charge the rechargeable battery. This study is about a self-generated power supply and develops a power generation device using a screw with higher power generation efficiency than the existing method. It is differentiated from the method suggested in this study by comparing and analyzing it with the existing power generation method, and identifying problems therewith. The screw-type power generation device generates power when the climbing stick comes into contact with the ground and when it is separated from the ground. The built-in power generation device does not require a separate power supply, and it can be used by attaching the role of a mobile phone auxiliary battery and a lighting lamp, and it has the effect of being able to find it through location tracking by embedding a GPS sensor, etc., and using lighting to keep the user safe in emergency situations such as distress. The existing generator with built-in mountain climbing stick is difficult to charge due to very weak current and low practicality, but the generator developed in this research could achieve high efficiency to obtain a sufficient current, so it is possible to charge a battery and practicality.

• Journal of the Korea Computer Graphics Society
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• v.30 no.3
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• pp.9-22
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• 2024

Mobility data is important to understand social phenomena and problem. Previous studies have utilized Origin-Destination (OD) visualization methods to represent human's mobility. However, the effectiveness of visualization tools as a method for understanding social phenomena remains unexplored. Therefore, in this study, we developed a visualization tool called SeoulOD-Vis to facilitate understanding social issues. It included three different modules: map visualization, condition selection, and detailed information presentation. We recruited 28 participants to evaluate the SeoulOD-Vis and compared it with a publicly available visualization tool. The results suggested that the SeoulOD-Vis had higher usability and problem-solving performances. Interview results suggested that it attributed to its 'condition selection' and 'detailed information presentation' modules. Our results will contribute to develop visualization tools to solve social problems using mobility data.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.37 no.4
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• pp.259-265
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• 2024

Shape memory alloy (SMA)-textile actuators have attracted significant attention across various fields, including soft robotics and wearable technology. These smooth actuators are developed by combining SMA and simple textile fibers and then knitting them into two loop patterns known as the knit (K-loop) and plain (P-loop) patterns. Both loops are distinguished by opposite bending characteristics owing to loop head geometry. However, the knitting processes for these actuator sheets require expertise and time, resulting in high production costs for knitted loop actuation sheets. This study introduces a novel method by which to assess the strain in SMA textile-based actuators, which experience large deformations when subjected to voltage. Owing to the highly nonlinear constitutive equations of the SMA material, developing an analytical model for numerical analysis is challenging. Therefore, this study employs a novel approach that utilizes a linear constitutive equation to analyze large deformations in SMA material with nonlinear geometry considerations. The user-defined material (UMAT) subroutine integrates the linear constitutive equation into the ABAQUS software suite. This equivalent unit cell (EUC) model is validated by comparing the experimental bending actuation results of K-loops and P-loops.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.131-145
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• 2020

In line with the trend of industrial innovation, IoT technology utilized in a variety of fields is emerging as a key element in creation of new business models and the provision of user-friendly services through the combination of big data. The accumulated data from devices with the Internet-of-Things (IoT) is being used in many ways to build a convenience-based smart system as it can provide customized intelligent systems through user environment and pattern analysis. Recently, it has been applied to innovation in the public domain and has been using it for smart city and smart transportation, such as solving traffic and crime problems using CCTV. In particular, it is necessary to comprehensively consider the easiness of securing real-time service data and the stability of security when planning underground services or establishing movement amount control information system to enhance citizens' or commuters' convenience in circumstances with the congestion of public transportation such as subways, urban railways, etc. However, previous studies that utilize image data have limitations in reducing the performance of object detection under private issue and abnormal conditions. The IoT device-based sensor data used in this study is free from private issue because it does not require identification for individuals, and can be effectively utilized to build intelligent public services for unspecified people. Especially, sensor data stored by the IoT device need not be identified to an individual, and can be effectively utilized for constructing intelligent public services for many and unspecified people as data free form private issue. We utilize the IoT-based infrared sensor devices for an intelligent pedestrian tracking system in metro service which many people use on a daily basis and temperature data measured by sensors are therein transmitted in real time. The experimental environment for collecting data detected in real time from sensors was established for the equally-spaced midpoints of 4×4 upper parts in the ceiling of subway entrances where the actual movement amount of passengers is high, and it measured the temperature change for objects entering and leaving the detection spots. The measured data have gone through a preprocessing in which the reference values for 16 different areas are set and the difference values between the temperatures in 16 distinct areas and their reference values per unit of time are calculated. This corresponds to the methodology that maximizes movement within the detection area. In addition, the size of the data was increased by 10 times in order to more sensitively reflect the difference in temperature by area. For example, if the temperature data collected from the sensor at a given time were 28.5℃, the data analysis was conducted by changing the value to 285. As above, the data collected from sensors have the characteristics of time series data and image data with 4×4 resolution. Reflecting the characteristics of the measured, preprocessed data, we finally propose a hybrid algorithm that combines CNN in superior performance for image classification and LSTM, especially suitable for analyzing time series data, as referred to CNN-LSTM (Convolutional Neural Network-Long Short Term Memory). In the study, the CNN-LSTM algorithm is used to predict the number of passing persons in one of 4×4 detection areas. We verified the validation of the proposed model by taking performance comparison with other artificial intelligence algorithms such as Multi-Layer Perceptron (MLP), Long Short Term Memory (LSTM) and RNN-LSTM (Recurrent Neural Network-Long Short Term Memory). As a result of the experiment, proposed CNN-LSTM hybrid model compared to MLP, LSTM and RNN-LSTM has the best predictive performance. By utilizing the proposed devices and models, it is expected various metro services will be provided with no illegal issue about the personal information such as real-time monitoring of public transport facilities and emergency situation response services on the basis of congestion. However, the data have been collected by selecting one side of the entrances as the subject of analysis, and the data collected for a short period of time have been applied to the prediction. There exists the limitation that the verification of application in other environments needs to be carried out. In the future, it is expected that more reliability will be provided for the proposed model if experimental data is sufficiently collected in various environments or if learning data is further configured by measuring data in other sensors.

• Journal of Intelligence and Information Systems
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• v.24 no.3
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• pp.135-155
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• 2018

The purpose of this study is to analyze the difference of interpretation level and intention to use message framing when autonomous vehicle, which is emerging as the product of 4th industrial revolution, is used as taxi, Interpretation level refers to the interpretation of a product or service, assuming that it will happen in the near future or in the distant future. Message framing refers to the formation of positive or negative expressions or messages at the extremes of benefits and losses. In other words, previous studies interpret the value of a product or service differently according to these two concepts. The purpose of this study is to investigate whether there are differences in intention to use when two concepts are applied when an autonomous vehicle is launched as a taxi. The results are summarized as follows: First, the message format explaining the gain and why should be used when using the autonomous taxi in the message framing configuration, and the loss and how when the autonomous taxi is not used. Messages were constructed and compared. The two message framing differed (t = 3.063), and the message type describing the benefits and reasons showed a higher intention to use. In addition, the results according to interpretation level are summarized as follows. There was a difference in intentions to use when assuming that it would occur in the near future and in the near future with respect to the gain and loss, Respectively. In summary, in order to increase the intention of using autonomous taxis, it is concluded that messages should be given to people assuming positive messages (Gain) and what can happen in the distant future. In addition, this study will be able to utilize the research method in studying intention to use new technology. However, this study has the following limitations. First, it assumes message framing and time without user experience of autonomous taxi. This will be different from the actual experience of using an autonomous taxi in the future. Second, self-driving cars should technical progress is continuing, but laws and institutions must be established in order to commercialize it and build the infrastructure to operate the autonomous car. Considering this fact, the results of this study can not reflect a more realistic aspect. However, there is a practical limit to search for users with sufficient experience in new technologies such as autonomous vehicles. In fact, although the autonomous car to take advantage of the public transportation by taxi is now ready for the road infrastructure, and technical and legal public may not be willing to choose to not have enough knowledge to use the Autonomous cab. Therefore, the main purpose of this study is that by assuming that autonomous cars will be commercialized by taxi you can do to take advantage of the autonomous car, it is necessary to frame the message, why can most effectively be used to find how to deliver. In addition, the research methodology should be improved and future research should be done as follows. First, most students responded in this study. It is also true that it is difficult to generalize the hypotheses to be tested in this study. Therefore, in future studies, it would be reasonable to investigate the population of various distribution considering the age, area, occupation, education level, etc. Where autonomous taxi can be used rather than those who can drive. Second, it is desirable to construct various message framing of the questionnaire, but it is necessary to learn various message framing in advance and to prevent errors in response to the next message framing. Therefore, it is desirable to measure the message framing with a certain amount of time when the questionnaire is designed.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.23-45
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• 2020

Big data is creating in a wide variety of fields such as medical care, manufacturing, logistics, sales site, SNS, and the dataset characteristics are also diverse. In order to secure the competitiveness of companies, it is necessary to improve decision-making capacity using a classification algorithm. However, most of them do not have sufficient knowledge on what kind of classification algorithm is appropriate for a specific problem area. In other words, determining which classification algorithm is appropriate depending on the characteristics of the dataset was has been a task that required expertise and effort. This is because the relationship between the characteristics of datasets (called meta-features) and the performance of classification algorithms has not been fully understood. Moreover, there has been little research on meta-features reflecting the characteristics of multi-class. Therefore, the purpose of this study is to empirically analyze whether meta-features of multi-class datasets have a significant effect on the performance of classification algorithms. In this study, meta-features of multi-class datasets were identified into two factors, (the data structure and the data complexity,) and seven representative meta-features were selected. Among those, we included the Herfindahl-Hirschman Index (HHI), originally a market concentration measurement index, in the meta-features to replace IR(Imbalanced Ratio). Also, we developed a new index called Reverse ReLU Silhouette Score into the meta-feature set. Among the UCI Machine Learning Repository data, six representative datasets (Balance Scale, PageBlocks, Car Evaluation, User Knowledge-Modeling, Wine Quality(red), Contraceptive Method Choice) were selected. The class of each dataset was classified by using the classification algorithms (KNN, Logistic Regression, Nave Bayes, Random Forest, and SVM) selected in the study. For each dataset, we applied 10-fold cross validation method. 10% to 100% oversampling method is applied for each fold and meta-features of the dataset is measured. The meta-features selected are HHI, Number of Classes, Number of Features, Entropy, Reverse ReLU Silhouette Score, Nonlinearity of Linear Classifier, Hub Score. F1-score was selected as the dependent variable. As a result, the results of this study showed that the six meta-features including Reverse ReLU Silhouette Score and HHI proposed in this study have a significant effect on the classification performance. (1) The meta-features HHI proposed in this study was significant in the classification performance. (2) The number of variables has a significant effect on the classification performance, unlike the number of classes, but it has a positive effect. (3) The number of classes has a negative effect on the performance of classification. (4) Entropy has a significant effect on the performance of classification. (5) The Reverse ReLU Silhouette Score also significantly affects the classification performance at a significant level of 0.01. (6) The nonlinearity of linear classifiers has a significant negative effect on classification performance. In addition, the results of the analysis by the classification algorithms were also consistent. In the regression analysis by classification algorithm, Naïve Bayes algorithm does not have a significant effect on the number of variables unlike other classification algorithms. This study has two theoretical contributions: (1) two new meta-features (HHI, Reverse ReLU Silhouette score) was proved to be significant. (2) The effects of data characteristics on the performance of classification were investigated using meta-features. The practical contribution points (1) can be utilized in the development of classification algorithm recommendation system according to the characteristics of datasets. (2) Many data scientists are often testing by adjusting the parameters of the algorithm to find the optimal algorithm for the situation because the characteristics of the data are different. In this process, excessive waste of resources occurs due to hardware, cost, time, and manpower. This study is expected to be useful for machine learning, data mining researchers, practitioners, and machine learning-based system developers. The composition of this study consists of introduction, related research, research model, experiment, conclusion and discussion.

• Management & Information Systems Review
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• v.35 no.2
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• pp.99-118
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• 2016

With the development of Internet and popularization of smartphones over recent years, social network services are experiencing rapid growth. On top of this, smartphone gaming market is showing a rapid growth and the use of mobile social games is on the significant rise. The occurrence of game data manipulation targeting these services and personal information leakage is highlighting the importance of social gaming security. This study is intended to propose development plans effective and efficient in social game services by figuring out factors putting effects on security dependent behavior of social game users in Korea and carrying out a practical study on the casual relationship between factors influencing security dependent behavior through recognized behavioral control and attitudes for privacy infringement of these factors. To do this, proposed was a study model in which the HBM(Health Belief Model) allowing the social game user to influence security dependent behavior was expanded and applied as a major variable. To verify the study model of this study practically, a survey was conducted among university students in Seoul-based K University and S University who had experienced using social game services. According to the study findings, firstly, the perceived seriousness turned out to provide positive influence to trust. But, the perceived seriousness turned out not to put positive effects on self-efficacy. Secondly, the perceived probability turned out not to put positive effects on self-efficacy and trust. Thirdly, the perceived gain turned out to put positive effects on self-efficacy and trust. Fourthly, the perceived disorder turned out not to put positive effects on self-efficacy and trust. Fifthly, self-efficacy turned out to put positive effects on trust. But, self-efficacy turned out not to put positive effects on security dependent behavior. Sixthly, trust turned out not to put positive effects on security dependent behavior. This study is intended to make a strategic proposal so that social game users can raise awareness of their level of security perception and security willingness through this.

• Asia pacific journal of information systems
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• v.18 no.3
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• pp.91-121
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• 2008

Electronic commerce, commonly known as e-commerce or eCommerce, has become a major business trend in these days. The amount of trade conducted electronically has grown extraordinarily by developing the Internet technology. Most electronic commerce has being conducted between businesses to customers; therefore, the researches with respect to e-commerce are to find customer's needs, behaviors through statistical methods. However, the statistical researches, mostly based on a questionnaire, are the static researches, They can tell us the dynamic relationships between initial purchasing and repurchasing. Therefore, this study proposes dynamic research model for analyzing the cause of initial purchasing and repurchasing. This paper is based on the System-Dynamic theory, using the powerful simulation model with some restriction, The restrictions are based on the theory TAM(Technology Acceptance Model), PAM, and TPB(Theory of Planned Behavior). This article investigates not only the customer's purchasing and repurchasing behavior by passing of time but also the interactive effects to one another. This research model has six scenarios and three steps for analyzing customer behaviors. The first step is the research of purchasing situations. The second step is the research of repurchasing situations. Finally, the third step is to study the relationship between initial purchasing and repurchasing. The purpose of six scenarios is to find the customer's purchasing patterns according to the environmental changes. We set six variables in these scenarios by (1) changing the number of products; (2) changing the number of contents in on-line shopping malls; (3) having multimedia files or not in the shopping mall web sites; (4) grading on-line communities; (5) changing the qualities of products; (6) changing the customer's degree of confidence on products. First three variables are applied to study customer's purchasing behavior, and the other variables are applied to repurchasing behavior study. Through the simulation study, this paper presents some inter-relational result about customer purchasing behaviors, For example, Active community actions are not the increasing factor of purchasing but the increasing factor of word of mouth effect, Additionally. The higher products' quality, the more word of mouth effects increase. The number of products and contents on the web sites have same influence on people's buying behaviors. All simulation methods in this paper is not only display the result of each scenario but also find how to affect each other. Hence, electronic commerce firm can make more realistic marketing strategy about consumer behavior through this dynamic simulation research. Moreover, dynamic analysis method can predict the results which help the decision of marketing strategy by using the time-line graph. Consequently, this dynamic simulation analysis could be a useful research model to make firm's competitive advantage. However, this simulation model needs more further study. With respect to reality, this simulation model has some limitations. There are some missing factors which affect customer's buying behaviors in this model. The first missing factor is the customer's degree of recognition of brands. The second factor is the degree of customer satisfaction. The third factor is the power of word of mouth in the specific region. Generally, word of mouth affects significantly on a region's culture, even people's buying behaviors. The last missing factor is the user interface environment in the internet or other on-line shopping tools. In order to get more realistic result, these factors might be essential matters to make better research in the future studies.

• Journal of Global Scholars of Marketing Science
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• v.19 no.1
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• pp.9-21
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• 2009

Recently, the researches to explain Switching Behavior through Theory of Planned Behavior have been discovered. Many researches say that System factors of mobile telecommunication service(MTS) is positively associated with Switching Intention. But There is no difference of system factors between mobile telecommunication services because of IT technique Development. Thus, this study investigated whether switching cost and alternative's attractiveness influence switching intention concerning mobile telecommunication service by adopting Theory of Planned Behavior (TPB) as an underlying theoretical premise. The study also attempted to determine the moderating effects of personal innovativeness on switching intention. For these purposes the author has developed several hypotheses as follows: H-1. The switching cost of different MTS is associated with the attitude of MTS which is using. H-2. The switching cost of different MTS is associated with the subjective norm of MTS which is using. H-3. The switching cost of different MTS is associated with the perceived behavior control of MTS which is using. H-4. The alternative's attractiveness of different MTS is associated with the attitude of MTS which is using. H-5. The alternative's attractiveness of different MTS is associated with the subjective norm of MTS which is using. H-6. The alternative's attractiveness of different MTS is associated with the perceived behavior control of MTS which is using. H-7. The switching cost of different MTS is associated with the switching intention. H-8. The alternative's attractiveness of different MTS is associated with the switching intention. H-9. The attitude of MTS is associated with the switching intention. H-10. The subjective norm of MTS is associated with the switching intention. H-11. The perceived behavior control of MTS is associated with the switching intention. H-12. The personal innovativeness has been a moderating effects to switching intention. Data has been collected from 403 respondents for this study using a questionnaire method. The survey for the actual analysis of the research was done and analyzed with the customers who have an experience of using Mobile telecommunication service and the samples were selected among the middle and high school students who live in Seoul area, the university students who live in Seoul, Gyeonggi and Chungcheng Provinces, and the ordinary workers who are working in Seoul and Gyeonggi Province. The survey was done for 23 days from March 28, 2008 through April 12, 2008. The positive analysis was done with SPSS 12.0K statistics package and visual PLS program using the analysis techniques of frequency analysis, reliability analysis, correlation analysis and factor analysis. In addition, structural equation modeling was conducted using AMOS 5.0. The data was analyzed by frequency analysis using SPSS 12.0 and structural equation modeling using AMOS 5.0. The result of the overall model analysis is as follows: Chi-Square=378.306, d.f.=107, p-value=0.0, GFI=.904, AGFI= 0.863, IFI= 0.939, NFI= 0.917, RMSEA= 0.079, TLI= 0.922. The results of the overall model analysis were coherent. The following study results were revealed: First, switching cost was related positively to attitude, subjective norm and perceived behavior control, three components of TPB. Second, alternative's attractiveness was related negatively to subjective norm but positively to perceived behavior control. Third, switching cost and attitude was related negatively to switching intention, while perceived behavior control was related positively to switching intention. Finally, the study found the moderating effects of personal innovativeness on switching intention. Based on the results, the study offers marketing strategic implications for mobile telecommunication service industry.

• Land and Housing Review
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• v.8 no.1
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• pp.1-11
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• 2017

The government has been constructing and supplying public rental housing to ordinary people in order to stabilize housing since 1989. However, the public rental houses initially supplied to ordinary people are at high risk for safety accidents due to the deterioration of the facilities. Therefore, this study is aimed to propose a solution to solve the life safety hazards of the old rental housing complex as a follow-up study of Analysis of Accident Patterns and Hazard Factor for Life Safety in Rental Housing Complex. Types of life safety accidents that occur in public rental housing complexes are sliding, falling, crash, falling objects, breakage, fire accidents, traffic accidents and criminal accidents. The types of safety accidents that occur in rental housing complexes analyzed in this study are sliding, crashes, falling objects, and fire accidents. Although the incidence of safety accidents such as falling, breakage, traffic accidents and crime accidents in public rental housing complexes is low, these types are likely to cause safety accidents. The method of this study utilized interviews and seminar results, and it suggested ways to solve the life safety hazards in rental housing complexes. Interviews were conducted with residents and managers of rental housing complexes. Seminars were conducted twice with experts in construction, maintenance, asset management, housing welfare and safety. Through interviews and seminars, this study categorizes the life safety hazards that occur in rental housing complexes by types of accidents and suggests ways to resolve them as follows. (1) sliding ; use of flooring materials with high friction coefficient, installation of safety devices such as safety handles, implementation of maintenance, safety inspections and safety education, etc. (2) falling ; supplementation of safety facilities, Improvement of the design method of the falling parts, Safety education, etc. (3) crash ; increase the effective width of the elevator door, increase the effective width of the lamp, improve the lamp type (U type ${\rightarrow}$ I type), etc. (4) falling objects and breakage ; design of furniture considering the usability of residents, replacement of old facilities, enhancement of safety consciousness of residents, safety education, etc. (5) fire accidents ; installation of fire safety equipment, improvement by emergency evacuation, safety inspection and safety education, etc. (6) traffic accidents ; securing parking spaces, installing safety facilities, conducting safety education, etc. (7) criminal accidents; improvement of CCTV pixels, installation of street lights, removal of blind spots in the complex, securing of security, etc. The roles of suppliers, administrators and users of public rental housing proposed in this study are summarized as follows. Suppliers of rental housing should take into consideration the risk factors that may arise not only in the design and construction but also in the maintenance phase and should consider the possibility of easily repairing old facilities considering the life cycle of rental housing. Next, Administrators of rental housing should consider the safety of the users of the rental housing, conduct safety checks from time to time, and immediately remove any hazardous elements within the apartment complex. Finally, the users of the rental housing needs to form a sense of ownership of all the facilities in the rental housing complex, and efforts should be made not to cause safety accidents caused by the user's carelessness. The results of this study can provide the necessary information to enable residents of rental housing complexes to live a safe and comfortable residential life. It is also expected that this information will be used to reduce the incidence of safety accidents in rental housing complexes.