The purpose of this study is to provide a rational management strategy to improve the management performance of companies through intellectual property activities. Through this study, we aim to explore countermeasures to strengthen competitiveness in a changing global environment. A survey of 200 companies was conducted from September 1 to October 30, 2023. Statistical analysis was conducted using frequency analysis, exploratory factor analysis, reliability analysis, correlation analysis, multiple regression analysis, and difference analysis. The conclusions are as follows. First, the impact of intellectual property activities on management performance was found to be creation and utilization. Second, the impact of management strategies on management performance was found to be differentiation strategy, cost advantage strategy, and concentration strategy. Third, cost advantage strategy has a partial mediation effect on the relationship between creation activities and managerial performance of intellectual property activities. Fourth, the differentiation strategy has a partial mediating effect on the relationship between the creation of intellectual property activities and managerial performance. In addition, differentiation strategy has a full mediating effect on the relationship between the utilization of intellectual property activities and performance. Fifth, concentration strategy has a partial mediating effect on the relationship between intellectual property activity utilization and management performance. Sixth, there is a difference between creation activities, protection activities, utilization activities, cost advantage strategy, differentiation strategy, financial performance, and non-financial performance based on venture certification status. As the importance of intellectual property is increasing in the era of technological hegemony, IoT companies will need to improve their management performance through venture certification and strategies utilizing intellectual property in order to secure future competitiveness. Based on this study, we hope that IoT companies will maximize their performance by implementing efficient strategies that consider IP activities.
Kim, Seong Kyu;Choi, Woo Bin;Lee, Jong Se;Lee, Won Gok;Choi, Gun Oh;Bae, You Suk
KIPS Transactions on Software and Data Engineering
/
v.11
no.6
/
pp.255-266
/
2022
The quality control of coarse aggregate among aggregates, which are the main ingredients of concrete, is currently carried out by SPC(Statistical Process Control) method through sampling. We construct a smart factory for manufacturing innovation by changing the quality control of coarse aggregates to inspect the coarse aggregates based on this image by acquired images through the camera instead of the current sieve analysis. First, obtained images were preprocessed, and HED(Hollistically-nested Edge Detection) which is the filter learned by deep learning segment each object. After analyzing each aggregate by image processing the segmentation result, fineness modulus and the aggregate shape rate are determined by analyzing result. The quality of aggregate obtained through the video was examined by calculate fineness modulus and aggregate shape rate and the accuracy of the algorithm was more than 90% accurate compared to that of aggregates through the sieve analysis. Furthermore, the aggregate shape rate could not be examined by conventional methods, but the content of this paper also allowed the measurement of the aggregate shape rate. For the aggregate shape rate, it was verified with the length of models, which showed a difference of ±4.5%. In the case of measuring the length of the aggregate, the algorithm result and actual length of the aggregate showed a ±6% difference. Analyzing the actual three-dimensional data in a two-dimensional video made a difference from the actual data, which requires further research.
KIPS Transactions on Computer and Communication Systems
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v.11
no.6
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pp.175-184
/
2022
Blockchain is being studied in various fields such as logistics, fintech, medical care, and the public sector. In the public information software project, some deliverables are omitted because the developed deliverables and the deliverables requested by the project management methodology do not match, and an additional process is required for payment. In this paper, we propose the deliverables management system for public information software project which is configured a distributed environment using the Ethereum blockchain and which has an automatic payment system only when all deliverables are approved. This system can keep the service available in case of system failure, provide transparency and traceability of deliverables management, and can reduce conflicts between the ordering company and the contractor through automatic payment. In this system, the information of deliverables is stored in the blockchain, and the deliverables that their file name is the hash value calculated by using the version information and the hash value of the previous version deliverable, are stored in the SFTP server. Experimental results show that the hash value of the deliverables registered by the contractor is correct, the file name of the deliverables stored in the SFTP server is the same as the hash value registered in the Ethereum blockchain, and the payment is made automatically to the Ethereum address of the contractor when all deliverables are approved.
This study aimed to investigate the effects of an aquaponics system utilizing catfish recirculating water on the growth and water quality in lettuce and chicory cultivation. After 60 d of catfish cultivation in the BFT-AP, the survival rate was 96.0% and average weight gain was 178.5 g. The WGR grew by 241.4% and the SGR was 3.0%. A comparison between lettuce and chicory cultivation using BFT-AP and hydroponics revealed significant increases in shoot height, leaf count per week, and biomass of the cultivated lettuce and chicory. The SPAD values also increased significantly by 15.4-43.3%. Water quality analysis of the BFT-AP systems and crop cultivation beds showed significant differences, except for K and Na. The average NO3- concentration in the sediment pond was significantly higher at 45.3±1.0. Comparison of water temperature, pH, EC, DO, and ORP in the BFT-AP system and crop cultivation beds revealed similar monthly water temperatures from July to September. The pH in the catfish culture pond was 0.3-1.2 lower than that in the crop cultivation beds, and the EC was approximately 0.01- 0.03 dS/m lower in the catfish culture pond than the crop cultivation beds. The monthly average ORP in the catfish culture bed steadily increased to 479.9 mV in October. Bacillus velezensis (AFB2-2) and Chlorella fusca (CF) were applied to the biological activation bed; the population density of CF showed a continuous increase, whereas that of AFB2-2 decreased after 15 d and gradually increased thereafter. Thus, the application of the recirculating aquaponics cultivation technology with catfish (BFT) enhances catfish cultivation and promotes the growth of lettuce and chicory. Therefore, it is considered suitable for the environment-friendly cultivation of lettuce and chicory.
In Bog Lee;Dae Ho Jung;Pyoung Ho Yi;Seung Tak Jeong;Yoon Kyeong Kim
Korean Journal of Environmental Agriculture
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v.42
no.4
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pp.331-337
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2023
Physiological disorders in pear fruit are mainly caused by problems during the growing season, such as lack of calcium in the soil, poor drainage, low porosity, vigorous pruning, and excessive fruiting. In this study, soil physicochemical properties and leaf characteristics were analyzed in pear orchards in four regions of Korea where chlorosis symptoms occurred to determine the causes of chlorosis. The color of chlorotic leaves was diagnosed using the naked eye or SPAD and Hunter values. The soil of the chlorotic orchard had a significantly higher soil pH than that of the regular orchard. Although adequate soil depth was not significantly associated with chlorosis, combined with over-fertilization of the soil with lime, it could potentially impair plant iron uptake. Chlorotic leaves had significantly lower iron and calcium contents and significantly higher magnesium contents than those of regular leaves. Therefore, the intensive occurrence of chlorosis during secondary shoot development around June and July when it is hot and humid may be due to impaired iron and calcium absorption, leading to physiological disorders. To solve this problem, avoiding the over-application of lime and applying foliar fertilizers containing chelated iron is recommended.
KIPS Transactions on Computer and Communication Systems
/
v.12
no.9
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pp.283-290
/
2023
With the recent steady development of IoT technology, it is widely used in medical systems and smart TV watches. 66% of software development is developed through language C, which is vulnerable to memory attacks, and acts as a threat to IoT devices using language C. A stack-smashing overflow attack inserts a value larger than the user-defined buffer size, overwriting the area where the return address is stored, preventing the program from operating normally. IoT devices with low memory capacity are vulnerable to stack smashing overflow attacks. In addition, if the existing vaccine program is applied as it is, the IoT device will not operate normally. In order to defend against stack smashing overflow attacks on IoT devices, we used canaries among several detection methods to set conditions with random values, checksum, and DSLR (random storage locations), respectively. Two canaries were placed within the buffer, one in front of the return address, which is the end of the buffer, and the other was stored in a random location in-buffer. This makes it difficult for an attacker to guess the location of a canary stored in a fixed location by storing the canary in a random location because it is easy for an attacker to predict its location. After executing the detection program, after a stack smashing overflow attack occurs, if each condition is satisfied, the program is terminated. The set conditions were combined to create a number of eight cases and tested. Through this, it was found that it is more efficient to use a detection method using DSLR than a detection method using multiple conditions for IoT devices.
Due to the Covid-19 pandemic, the home-training app market is growing rapidly and numerous apps are entering the market. It is becoming more difficult for an app to secure the profitability. In this study, by analyzing actual user data of a reward-based home-training app, we propose a model that predicts cash-cow users of the app. Cash-cow users are the users who watch in-stream ads to watch training videos although they cannot earn any rewards by doing so. Thus, these users make profits for the app yet do not incur any costs. The results of this study show that the users who irregularly watch training videos are more likely to be cash-cow users than the users who regularly watch training videos. This result suggests that, paradoxically, for sustainable profitability, home-training apps may need to find a way to retain the users who watch training videos irregularly so that they can be satisfied with the service and continue use the apps.
Yerin Sung;Hyun Seung Choi;Wonseong Song;Vanessa;Yuri Kim;Yeonhae Ryu;Youngjin Kim;Jaemin Im;Dae Seok Kim;Hyun Ho Choi
Journal of Adhesion and Interface
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v.25
no.1
/
pp.169-274
/
2024
Recent attention has been drawn to materials that undergo reversible expansion and contraction in response to external stimuli, leading to morphological changes. These materials hold potential applications in various fields including soft robotics, sensors, and artificial muscles. In this study, a novel material capable of responding to high temperatures for protection or encapsulation is proposed. To achieve this, liquid crystal elastomer (LCE) with nematic-isotropic transition properties and polyimide (PI) with high mechanical strength and thermal stability were utilized. To utilize a solution process, a dope solution was synthesized and introduced into micro-printing techniques to develop a two-dimensional pattern of LCE/PI bilayer structures with sub-millimeter widths. The honeycomb-patterned LCE/PI bilayer mesh combined the mechanical strength of PI with the high-temperature contraction behavior of LCE, and selective printing of LCE facilitated deformation in desired directions at high temperatures. Consequently, the functionality of selectively and reversibly encapsulating specific high-temperature materials was achieved. This study suggests potential applications in various actuator fields where functionalities can be implemented across different temperature ranges without the need for electrical energy input, contingent upon molecular changes in LCE.
The construction of smart communities is a new method and important measure to ensure the security of residential areas. In order to solve the problem of low accuracy in face recognition caused by distorting facial features due to monitoring camera angles and other external factors, this paper proposes the following optimization strategies in designing a face recognition network: firstly, a global graph convolution module is designed to encode facial features as graph nodes, and a multi-scale feature enhancement residual module is designed to extract facial keypoint features in conjunction with the global graph convolution module. Secondly, after obtaining facial keypoints, they are constructed as a directed graph structure, and graph attention mechanisms are used to enhance the representation power of graph features. Finally, tensor computations are performed on the graph features of two faces, and the aggregated features are extracted and discriminated by a fully connected layer to determine whether the individuals' identities are the same. Through various experimental tests, the network designed in this paper achieves an AUC index of 85.65% for facial keypoint localization on the 300W public dataset and 88.92% on a self-built dataset. In terms of face recognition accuracy, the proposed network achieves an accuracy of 83.41% on the IBUG public dataset and 96.74% on a self-built dataset. Experimental results demonstrate that the network designed in this paper exhibits high detection and recognition accuracy for faces in surveillance videos.
The purpose of this study is to determine how the use of retailtech technology affects consumers' purchase intention. Furthermore, this study aims to investigate the mediating effects of technology usefulness and ease of use on this influence relationship and whether experiential marketing moderates consumers' purchase intention. The survey was conducted from August 1, 2023 to September 30, 2023, and a total of 257 people participated in the study. For statistical analysis, hierarchical regression analysis, three-stage mediation regression analysis, and hierarchical three-stage controlled regression analysis were conducted to test the hypothesis. The results of the study are as follows. First, it was confirmed that big data-AI utilization, mobile-SNS utilization, live commerce utilization, and IoT utilization affect purchase intention in retail technology utilization. Second, technology usefulness has a mediating effect on IoT utilization, mobile-SNS utilization, and big data-AI utilization. Third, perceived ease of use of technology mediated the effects of IoT utilization, mobile-SNS utilization, live-commerce utilization, and big data-AI utilization. Fourth, escapist experience has a moderating effect on mobile SNS utilization and live commerce utilization. Fifth, esthetic experience has a moderating effect on mobile-SNS utilization and big data-AI utilization. Through this study, we hope that the domestic distribution industry will contribute to national competitiveness by securing the competitive advantage of companies by utilizing new technologies in entering the global market.
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