• The Journal of Information Systems
• /
• v.30 no.4
• /
• pp.277-301
• /
• 2021

Purpose The purpose of this study is to analyze the sentiment responses of the general public to non-face-to-face work using text mining methodology. As the number of non-face-to-face complaints is increasing over time, it is difficult to review and analyze in traditional methods such as surveys, and there is a limit to reflect real-time issues. Approach This study has proposed a method of the research model, first by collecting and cleansing the data related to non-face-to-face work among tweets posted on Twitter. Second, topics and keywords are extracted from tweets using LDA(Latent Dirichlet Allocation), a topic modeling technique, and changes for each section are analyzed through DTM(Dynamic Topic Modeling). Third, the complaints of non-face-to-face work are analyzed through the classification of positive and negative polarity in the COVID-19 section. Findings As a result of analyzing 1.54 million tweets related to non-face-to-face work, the number of IDs using non-face-to-face work-related words increased 7.2 times and the number of tweets increased 4.8 times after COVID-19. The top frequently used words related to non-face-to-face work appeared in the order of remote jobs, cybersecurity, technical jobs, productivity, and software. The words that have increased after the COVID-19 were concerned about lockdown and dismissal, and business transformation and also mentioned as to secure business continuity and virtual workplace. New Normal was newly mentioned as a new standard. Negative opinions found to be increased in the early stages of COVID-19 from 34% to 43%, and then stabilized again to 36% through non-face-to-face work sentiment analysis. The complaints were, policies such as strengthening cybersecurity, activating communication to improve work productivity, and diversifying work spaces.

• International journal of advanced smart convergence
• /
• v.9 no.3
• /
• pp.246-252
• /
• 2020

Facial recognition is a biometric technology that is used in various fields such as user authentication and identification of human characteristics. Face recognition applications are practically used in various fields, but very few applications have been developed to improve the factory work environment. We implemented applications that uses face recognition to identify a specific employee in a factory .work environment and provide customized information for each employee. Factory workers need documents describing the work in order to do their assigned work. Factory managers can use our application to register documents needed for each worker, and workers can view the documents assigned to them. Each worker is identified using face recognition, and by tracking the worker's face during work, it is possible to know that the worker is in the workplace. In addition, as a mobile app for workers is provided, workers can view the contents using a tablet, and we have defined a simple communication protocol to exchange information between our applications. We demonstrated the applications in a factory work environment and found several improvements were required for practical use. We expect these results can be used to improve factory work environments.

• International Journal of Advanced Culture Technology
• /
• v.10 no.2
• /
• pp.307-313
• /
• 2022

Although telecommuting of SMEs has been activated due to the COVID-19 phenomenon, the security model for this is insufficient. Accordingly, the study was divided into threats centered on smartphones and threats centered on smartphone users. As a result of the study, one-third of SMEs are working from home. At this company with 100 employees, more than 50% of them work from home.and In the metal, machinery and chemical industries with factories, 20% of them work from home. As a result of analyzing the correlation between telecommuting according to the presence or absence of a factory, the correlation coefficient (r=-.385) has a clear linear relationship. And, as a result of the regression analysis, the R-squared value was 0.148, so companies with factories are highly related to telecommuting. In other words, we found that SMEs with factories do not want to work from home. In addition, as a result of analyzing the level of security threats, there were great concerns about theft, hacking, and phone taking during remote work. As limitations of the study, there were difficulties in selecting SMEs from the population in a non-face-to-face work environment, and there were limitations in the questionnaire items for deriving a non-face-to-face work environment.

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.16 no.4
• /
• pp.67-74
• /
• 2020

As the information age develops, Online education and Non-face-to-face work are becoming common. Telecommuting such as tele-education and video conferencing through the application of information technology is also becoming common due to the COVID-19. Unexpected information leakage can occur online when the company conducts work remotely or holds meetings. A system to authenticate users is needed to reduce information leakage. In this study, there are various ways to authenticate remote access users. By applying burn authentication using a biometric system, a method to identify users is proposed. The method used in the study was studied the main component analysis method, which recognizes several characteristics in facial recognition and processes interrelationships. It proposed a method that can be easily utilized without additional devices by utilizing a camera connected to a computer by authenticating the user using the shape and characteristics of the face by using the PCA method.

• International Journal of Contents
• /
• v.9 no.3
• /
• pp.9-14
• /
• 2013

In this paper, we will examine single face tracking algorithms with scaling function in a mobile device. Face detection and tracking either in PC or mobile device with scaling function is an unsolved problem. Standard single face tracking method with particle filter has a problem in tracking the objects where the object can move closer or farther from the camera. Therefore, we create an algorithm which can work in a mobile device and perform a scaling function. The key idea of our proposed method is to extract the average of skin color in face detection, then we compare the skin color distribution between the detected face and the tracking face. This method works well if the face position is located in front of the camera. However, this method will not work if the camera moves closer from the initial point of detection. Apart from our weakness of algorithm, we can improve the accuracy of tracking.

• The Journal of the Korea Contents Association
• /
• v.16 no.9
• /
• pp.117-126
• /
• 2016

This study examined the relative effects of different feedback delivery method (face-to-face vs. e-mail) and reinforcement history on work performance. Participants were asked to work on a simulated mobile phone assembly task. They performed for 30 minutes per session and attended 4 sessions. The dependents variable was the percentage of correctly completed work tasks. Of 100 participants recruited, 50 had a reinforcement history and another 50 had no reinforcement history with the feedback provider in this study. The participants in each group were randomly assigned into two experimental conditions: face-to-face feedback and e-mail feedback. The results showed that for the participants who had reinforcement history, the two feedback delivery methods did not produce a significant difference in the percentage of correctly completed work tasks. However, for those who had no reinforcement history, the two feedback methods did produce a significant difference.

• Journal of Korean Society for Quality Management
• /
• v.50 no.3
• /
• pp.545-570
• /
• 2022

Purpose: The purpose of this study was to explore dimensions to improve airline non-face-to-face(untact) service quality and identify shadow work dimensions in the digital environment among them. Methods: This study conducted mixed method. First of all, For finding out the dimensions of airline untact service quality, in-depth interviews were conducted from passengers. The collected data through the survey were analyzed using improved importance-performance analysis(IPA). Second, An online survey was conducted to quantitatively analyze user perception about airline untact service quality, and the importance performance of service quality at each dimension was identified through the revised IPA method. Results: The results of this study are as follows; Through in-depth interviews, 11 dimensions found out and 32 measurement items were developed. and then, through the revised IPA analysis, passengers were highly satisfied with "Cleanliness of in-flight service" and "Reliability of self check-in". Also, We found 3 shadow work dimensions such as "Ease of use of self check-in", "Usefulness of self check-in", and "Responsiveness of self check-in". Conclusion: Airline service providers have to keep high-satisfaction services and urgently improve less satisfied services. In particular, the dimensions related to shadow work have to be improved.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.22 no.2
• /
• pp.476-481
• /
• 1998

It is generally known that in high speed work with more than 1000 m/min cutting speed, according to the work material phenomenon of tool wearing is increased due to the some produced neat and as a result this makes the cutting work impossible. In this study, the high speed cutting is possible because of the different cutting from the presently known fact. That is, most of generated heats influence on the quantity flowing in chip greatly. Therfore, this study aims at the behavior of cutting heat generated at high speed cutting. It makes clearly the euqntity of heat flowing in chip, work materal, tool, and inflowing ratio. The cutting mechanism varies by the changing of cutting depth, slant face and contact area through this study. And it is exammined that the influence of heat of all parts is greatly due to the change the contact length of clearance face. It is confirmed from the exp[eriment that the inflowing heat ratio influences the cutting speed greatly and the heat of clearance face can not be disregarded.

• Journal of Information Technology Services
• /
• v.20 no.4
• /
• pp.95-111
• /
• 2021

Recently, many organizations are actively adopting VDI (Virtual Desktop Infrastructure), an IT-based business system, to build a non-face-to-face business environment for smart-work. However, most of the existing research on VDI has focused on the satisfaction of system service quality or the use of IT resources and investment for VDI introduction. However, research on effective management and utilization of factors according to the characteristics of VDI technology is urgently required. This study is an empirical research study on how VDI technology characteristics affect interactions and work performance by identifying differences in utilization factors between general organization members and IT managers, presenting standards for business utilization and management. This study proposed a model and hypothesis that the system technology characteristics for VDI use are mediated by interactions in which users respond to functions appropriate to their work. In order to verify the hypothesis, a questionnaire survey was conducted on 188 people of companies and institutions that have adopted and used VDI through a questionnaire survey. Data analysis was performed with partial least squares (PLS), a structural equation modeling (SEM) technique that uses a component-based approach to estimation. As a result of the empirical analysis, the same environmental function for performing work, N-th security, and remote access function factors for non-face-to-face work have a significant effect on interactivity, and IT managers have an additional significant effect on the management technology characteristics of resource reallocation. Has been shown to affect. The results of this study aim to minimize trial and error due to new introduction by presenting considerations for future VDI introduction through case analysis.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2021.11a
• /
• pp.647-650
• /
• 2021

The most powerful and modern face recognition techniques are using deep learning methods that have provided impressive performance. The outbreak of COVID-19 pneumonia has spread worldwide, and people have begun to wear a face mask to prevent the spread of the virus, which has led existing face recognition methods to fail to identify people. Mainly, it pushes masked face recognition has become one of the most challenging problems in the face recognition domain. However, deep learning methods require numerous data samples, and it is challenging to find benchmarks of masked face datasets available to the public. In this work, we develop a new simulated masked face dataset that we can use for masked face recognition tasks. To evaluate the usability of the proposed dataset, we also retrained the dataset with ArcFace based system, which is one the most popular state-of-the-art face recognition methods.