• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.2
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• pp.565-586
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• 2022

Cloud storage's elastic expansibility not only provides flexible services for data owners to store their data remotely, but also reduces storage operation and management costs of their data sharing. The data outsourced remotely in the storage space of cloud service provider also brings data security concerns about data integrity. Data integrity verification has become an important technology for detecting the integrity of remote shared data. However, users without data access rights to verify the data integrity will cause unnecessary overhead to data owner and cloud service provider. Especially malicious users who constantly launch data integrity verification will greatly waste service resources. Since data owner is a consumer purchasing cloud services, he needs to bear both the cost of data storage and that of data verification. This paper proposes a verification control algorithm in data integrity verification for remotely outsourced data. It designs an attribute-based encryption verification control algorithm for multiple verifiers. Moreover, data owner and cloud service provider construct a common access structure together and generate a verification sentinel to verify the authority of verifiers according to the access structure. Finally, since cloud service provider cannot know the access structure and the sentry generation operation, it can only authenticate verifiers with satisfying access policy to verify the data integrity for the corresponding outsourced data. Theoretical analysis and experimental results show that the proposed algorithm achieves fine-grained access control to multiple verifiers for the data integrity verification.

• Journal of Digital Convergence
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• v.19 no.5
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• pp.197-205
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• 2021

Recently, the retail industry has been increasingly demanding information technology convergence and utilization to respond to various external environmental threats such as COVID-19 and to be competitive using AI technologies, but there is a very lack of research and application services. This study is a CCTV video data-driven AI application case study, using CCTV image data collection in retail space, object detection and tracking AI model, time series database to store real-time tracked objects and tracking data, heatmap to analyze congestion and interest in retail space, social access zone.We present the orientation and verify its usability in the direction designed through practical implementation.

• KEPCO Journal on Electric Power and Energy
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• v.8 no.2
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• pp.69-72
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• 2022

This paper actually investigates the load on major large-scale buildings in the downtown area, examines the economic feasibility of installing PV and ESS in a microgrid target building, and evaluates whether an electric vehicle capable of V2G through two buildings is effective as an economical analysis program (HOMER) was analyzed using. It is economical to install a mixture of ESS rather than using the whole PV, and it is shown that if there is an electric vehicle using the V2G function of EV, there is an economic effect to replace the PV. So that Incentives and policies are needed to replace a large area of PV and utilize the existing parking lot to lead EV as a resource of the microgrid. Currently, P2X technology that stores power as ESS or converts it to other energy to control when surplus renewable energy occurs in large-capacity solar power plants and wind farms, etc. This is being applied, and efforts are being made to maintain the stability of the system through the management of surplus power, such as replacing thermal energy through a heat pump. Due to the increase in electric vehicles, which were recognized only as a means of transportation, technologies for using electric vehicles are developing. Accordingly, existing gas stations do not only supply traditional chemical fuels, but electricity, and super stations that also produce electricity have appeared. Super Station is a new concept power plant that can produce and store electricity using solar power, ESS, V2G, and P2G. To take advantage of this, research on an urban microgrid that forms an independent system by tying a large building and several buildings together and supplies power through a super station around the microgrid is in full swing.

• Journal of the Korean Society of Industry Convergence
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• v.25 no.3
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• pp.349-356
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• 2022

Currently, the agricultural population in Korea indicates a decreasing and aging orientation. As the population of farm labor continues to decline, so farmers are feeling the pressure to be stable crop production. To solve the problem caused by the decreasing of farm labor, it is necessary to change over to "Digital agriculture". Digital agriculture is tools that digitally collect, store, analyze, and share electronic data and/or information in agriculture, and aims to integrate the several digital technologies into crop and livestock management and other processes in agriculture fields. In addition, digital agriculture can offer the opportunity to increase crop production, save costs for farmer. Therefore, in this study, for data-based Digital Agriculture, a greenhouse environment monitoring system for crop growth monitoring based on Node-RED, which even beginners can use easily, was developed, and the implemented system was verified in a hydroponic greenhouse. Several sensors, such as temperature, humidity, atmospheric pressure, CO₂, solar radiation, were used to obtain the environmental data of the greenhouse. And the environmental data were processed and visualized using Node-RED and MariaDB installed in rule.box digital. The environment monitoring system proposed in this study was installed in a hydroponic greenhouse and obtained the environmental data for almost two weeks. As a result, it was confirmed that all environmental data were obtained without data loss from sensors. In addition, the dashboard provides the names of installed sensors, real time environmental data, and changes in the last three days for each environmental data. Therefore, it is considered that farmers will be able to easily monitor the greenhouse environment using the developed system in this study.

• Human Ecology Research
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• v.60 no.1
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• pp.131-145
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• 2022

The purpose of this study was to reveal the effects of sales services and organizational member relationships of fashion brand salespersons on job performance and job satisfaction, as well as how job performance, job satisfaction, salesperson services, and organizational member relationships differ according to the sales career and job position. The data were collected by administering a questionnaire to fashion brand salespeople in Gwangju from September to October 2020. Using 235 responses, the data were analyzed with SPSS 27.0 for frequency analysis, reliability analysis, t-test, factor analysis, and regression analysis. The research results were as follows. First, the basic services of the salesperson comprised factors such as 'consideration and convenience', 'appearance and dress', and 'kindness and greeting', which are considered better variables to explain job performance than job satisfaction. Second, the salesperson's professional service consisted of 'fashion product knowledge', 'professional self-management', and 'store display technology' factors, which are good variables to predict job performance. Third, the relationship between the members of a salesperson's organization consists of factors such as 'headquarters relations', 'colleague relations', and 'emotional labor', which was better for explaining job satisfaction than job performance. Fourth, depending on the position, professional salespeople exhibited significantly higher values in job performance, basic and professional services of salespersons, and 'headquarters relations' factors, whereas there were no significant differences in job satisfaction, 'colleague relations' and 'emotional labor'. Lastly, the more sales career, the higher the job performance, and the basic services, professional services, and 'headquarters relations' factors of salespeople were also good.

• Journal of Software Assessment and Valuation
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• v.16 no.2
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• pp.127-133
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• 2020

As the usages of artificial intelligence is increased, the demand to algorithms for small portable devices increases. Also as the embedded system becomes high-performance, it is possible to implement algorithms for high-speed computation and machine learning as well as operating systems. As the machine learning algorithms process repetitive calculations, it depend on the cloud environment by network connection. For an stand alone system, low power consumption and fast execution by optimized algorithm are required. In this study, for the purpose of smart control, an energy measurement sensor is connected to an embedded system, and a real-time monitoring system is implemented to store measurement information as a database. Continuously measured and stored data is applied to a learning algorithm, which can be utilized for optimal power control, and a system interfacing various sensors required for energy measurement was constructed.

• The Journal of the Convergence on Culture Technology
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• v.8 no.6
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• pp.715-725
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• 2022

With the development of digital technology related to mobile, cloud, IoT, even traditional businesses have began to develop strategies for digital transformation. This is regarded as a very important part for business sustainability. However, many of these attempts are being conducted from the management point of view, and there has been little research on user experience design for digital transformation. In this study, Starbucks, which started a offline store business and expanded its experience with online services, was selected as a representative case and user research was conducted on it. Through an usability evaluation and post-task interviews of the Starbucks mobile application users, we discovered important issues of user experience to consider when transforming and expanding services online from offline. Based on the findings, the considersations for designing online user experience were discussed and proposed. These are expected to contribute to the process of researching and implementing digital transformation.

• Journal of Digital Convergence
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• v.20 no.5
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• pp.593-598
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• 2022

Recently, data production has seen explosive growth, and the storage systems to store these big data safely and quickly is evolving in various ways. A typical configuration of storage systems is the use of SSDs with fast data processing speed as a RAID group that can maintain reliable data. However, since NAND flash memory, which composes SSD, has the feature that deterioration if writes more than a certain number of times are repeated, can increase the likelihood of simultaneous failure on multiple SSDs in a RAID group. And this can result in serious reliability problems that data cannot be recovered. Thus, in order to solve this problem, we propose a method of throttling IOs so that each SSD within a RAID group leads to a different life-end. The technique proposed in this paper utilizes SMART to control the state of each SSD and the number of IOs allocated according to the data pattern used step by step. In addition, this method has the advantage of preventing large amounts of concurrency defects in RAID because it induces differential lifetime finishes of SSDs.

• International Journal of Computer Science & Network Security
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• v.23 no.5
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• pp.89-94
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• 2023

Cloud-based technology is used in different organizations around the world for various purposes. Using this technology, the service providers provide the service mainly SaaS, PaaS and while the cloud service consumer consumes the services by paying for the service they used or accessed by the principle of "pay per use". The customer of the services can get any services being at different places or locations using different machines or electronic devices. Under the conditions of being well organized and having all necessary infrastructures, the services can be accessed suitably. The identified problem in this study is that cloud providers control and monitor the system or tools by ignoring the calculation and consideration of various faults made from the cloud provider side during service delivery. There are currently problems with ignoring the consumer or client during the monitoring and mentoring system for cloud services consumed at the customer or client level by SLA provisions. The new framework was developed to address the above-mentioned problems. The framework was developed as a unified modeling language. Eight basic components are used to develop the framework. For this research, the researcher developed a prototype by using a selected cloud tool to simulate and java programming language to write a code as well as MySQL to store data during SLA. The researcher used different criteria to validate the developed framework i.e. to validate SLA that is concerned with a cloud service provider, validate what happened when the request from the client-side is less than what is specified in SLA and above what is specified in SLA as well as implementing the monitoring mechanism using the developed Monitoring component. The researcher observed that with the 1st and 3rd criteria the service level agreement was violated and this indicated that if the Service level agreement is monitored or managed only by cloud service prover, there is a violation of LSA. Therefore, the researcher recommended that the service level agreement be managed by both cloud service providers and service consumers in the cloud computing environment.

• Safety and Health at Work
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• v.13 no.4
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• pp.401-407
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• 2022

Background: The present study aimed to digitally evaluate the risk of overwork-related adverse effects (OrAEs) among employees from various occupational categories in Taiwan. Methods: Anonymous data of employees from seven companies/factories providing occupational health services were analyzed. The studied population comprised 5505 employees, and the data analyzed included employment duration, working hours, shift work schedules, and health checkup results. The risk for OrAEs was assessed by an index, Karo index (0-4, the larger the value, the higher the risk for OrAEs) obtained using a risk matrix made up of cardiocerebral and occupational risk factors. Karo index values of 3 and 4 were categorized as at high risk for OrAEs (h-OrAEs). Results: The 5505 employees had an average employment duration of 8.5 years and a mean age of 39.4 years. The prevalence rates for h-OrAEs of the seven companies/factories ranged from 3.9% to 34.2%. There were significant differences in prevalence rates for h-OrAEs between employees of retail stores and high-tech manufacturing factories. Multivariate analysis results indicated that workers of high-tech manufacturing factories had significantly higher risk for h-OrAEs compared with retail store workers. Conclusion: In terms of satisfying health risk management and legal requirements in Taiwan, the newly issued Karo index, which covers a wide range of occupational risk factors, can serve as an assessment and a warning tool for managing the risk of OrAEs in workplaces. To reduce risks for h-OrAEs, active and prudent control of cerebrocardiovascular risks and working hours is recommended.