• International Journal of Computer Science & Network Security
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• v.22 no.11
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• pp.255-259
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• 2022

The new social reality emerging amid the global rise of communication links and integration processes acutely emphasizes the problems of communication in large and small social systems. The method of their communication becomes one of the keys to ensuring global security. It has become the mission of humanitarian education to prepare the younger generations for life in a changing world with no image of the future and increasing uncertainty. In psychological and pedagogical research, there is a growing scientific interest in the problems of interaction of the individual with the social environment. The mental trace of a person's practice in society shapes the experience of social interaction, which constitutes simultaneously the source, tool, and condition for the emergence and development of personality. The study outlines the methodological foundations for the study of individual experiences of social interaction. A hypothesis about the productivity of the functional matrix method is tested. Materials for the training of specialists in the humanities include interdisciplinary approaches to the study and transformation of the experience of social interaction and systematic methodology for the study of complex objects. Fundamental to the study is the systematic-dialectical method, and the matrix method is employed as the instrumental-technological method. The paper presents the results of a multidisciplinary overview of scientific literature concerning the essential characteristics and functions of social interaction and the respective experience. The overview points to the fragmented nature of scientific understanding of the elements of experience outside its integrity and systemic properties. Based on the formula "personality interacts with the social environment", the study presents an algorithm for the application of a systematic methodology for the study of complex objects, which made it possible to identify the system parameters of experience at three levels of cognition and develop the reference structural and functional matrices for the didactic system of its pedagogical enrichment.

• Journal of Ginseng Research
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• v.47 no.1
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• pp.159-165
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• 2023

Background: Red ginseng marc, the residue of red ginseng left after water extraction, is rich in dietary fiber. Dietary fiber derived from fruits or vegetables can promote the proliferation of probiotics, and it is a key technology in the food industry to increase the productivity of probiotics by adding growth-enhancing substances such as dietary fiber. In this study, the effect of red ginseng dietary fiber (RGDF) on the growth of probiotic bacterial strains was investigated at the phenotypic and genetic levels. Methods: We performed transcriptome profiling of Lactiplantibacillus plantarum IDCC3501 in two phases of culture (logarithmic (L)-phase and stationary (S)-phase) in two culture conditions (with or without RGDF) using RNA-seq. Differentially expressed genes (DEGs) were identified and classified according to Gene Ontology terms. Results: The growth of L.plantarum IDCC3501 was enhanced in medium supplemented with RGDF up to 2%. As a result of DEG analysis, 29 genes were upregulated and 30 were downregulated in the RGDF-treated group in the L-phase. In the S-phase, 57 genes were upregulated and 126 were downregulated in the RGDF-treated group. Among the upregulated genes, 5 were upregulated only in the L-phase, 10 were upregulated only in the S-phase, and 3 were upregulated in both the L- and S-phases. Conclusions: Transcriptome analysis could be a valuable tool for elucidating the molecular mechanisms by which RGDF promotes the proliferation of L.plantarum IDCC3501. This growth-promoting effect of RGDF is important, since RGDF could be used as a prebiotic source without additional chemical or enzymatic processing.

• Journal of KIBIM
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• v.13 no.3
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• pp.1-11
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• 2023

In order to use BIM as a tool for improving the productivity and quality of products in the construction industry, a BIM model must be created from the design stage first. Infrastructure structures such as bridges and tunnels are mainly created based on three-dimensional alignment in the generation of BIM models. Especially, generation of BIM models based on three-dimensional linearity has high task difficulty and algorithms for automating BIM modeling for railway infra structures have been suggested in previous studies. This study improved the BIM modeling automation algorithm of railway infrastructures and developed a system based on the algorithm so that it can be easily used by ordinary users. The system was built as an add-in system of Autodesk's Revit. As an improvement first, it is possible to arrange different libraries for each pattern, enabling various uses. In addition, it can be created models of several members with a single process and the system can automatically places structures that are added periodically, such as Rock Bolt and Fore Polling. Finally, 3D length information and volume for each pattern are automatically calculated for more accurate 3D-based volume calculation. This study contributes to increasing user accessibility by building a BIM modeling automation algorithm into a system. The system is expected to improve the efficiency of BIM modeling creation of linear-based infra structures, including railway infrastructure.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.34 no.2
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• pp.301-321
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• 2024

Generative artificial intelligence is currently developing rapidly and expanding industrially. The development of generative AI is expected to improve productivity in most industries. However, there is a probability for exploitation of generative AI, and cases that actually lead to crime are emerging. Compared to the fast-growing AI, there is no legislation to regulate the generative AI. In the case of Korea, the crimes and risks related to generative AI has not been clearly classified for legislation. In addition, research on the responsibility for illegal data learned by generative AI or the illegality of the generated data is insufficient in existing research. Therefore, this study attempted to classify crimes related to generative AI for domestic legislation into generative AI for target crimes, generative AI for tool crimes, and other crimes based on ECRM. Furthermore, it suggests technical countermeasures against crime and risk and measures to improve the legal system. This study is significant in that it provides realistic methods by presenting technical countermeasures based on the development stage of AI.

• Informatization Policy
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• v.31 no.3
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• pp.34-47
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• 2024

Artificial intelligence(AI) is regarded as a key tool that can significantly contribute to innovation and improve productivity as digital transformation continues to spread rapidly. Currently, however, there is lack of understanding and empirical research on the factors that influence the adoption of AI by companies. In particular, most studies have been conducted by foreign researchers analyzing data from foreign companies, and domestic studies have limitations in terms of objectivity and timeliness. This study employs econometric methods to identify the determinants of AI adoption at the firm level. To this end, we derive the technological, organizational, and environmental context factors from the perspective of the Technology-Organization-Environment(TOE) framework as a representative theory of technology adoption factors. We then conduct a logistic regression analysis using data from 11,601 Korean firms. This study not only expands the research literature by supplementing the limitations of previous studies in Korea but also provides timely evidence and implications through empirical analysis.

• Archives of design research
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• v.19 no.2 s.64
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• pp.31-42
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• 2006

This study originates from the following critical mind; what will the office of the future be like? and what technology will we rely upon most to communicate with colleagues or to access business information. In the office environment today, new technology has compelled new work paradigm and has greatly affected the capabilities of the individual to work in a more productive and efficient manner. However, even though new computer technology has changed the business world so rapidly, it is very difficult to see the changes that have been taken place. As an aim of the study, creating a mobile tool for office workers that successfully supports their work and communication was explored, and this study explored future work environment with a 5 years technological and social perspective. As a result of this study, the bON brings new visions to the mobile professionals via various interfaces. The bON, a mobile device, is both a system of work and of communication for office workers. The bON, as an integrated tool for working and communicating, forms the basis for a mobile information gateway that is equally capable of functioning as a mobile desk. The basic underlying idea is that all formal meeting places and hallways in the office are equipped with large wall-mounted screens. The bON collaborates with these media in various ways to enhance productivity and efficiency. The main challenge for the bON to enhance both mobility and quality of information is using new technology including bendable and flexible display and soft material display and sensors. To answer for the strong needs for mobility, the whole size of the device is fairly small while the screen is rolled inside the device. For Graphical User Interface, moreover, a new technique called Multi-layering Interface was adopted to stretch user's visual limits and suggests new direction in designing mobile device, equipped with small size display.

• Korean Journal of Environmental Biology
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• v.37 no.3
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• pp.433-445
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• 2019

This study was designed to develop simple tools to easily and efficiently predict the occurrence of algal bloom in agricultural lakes. Physicochemical water quality parameters were examined to reflect the phytoplankton productivity in 182 samples collected from 15 agricultural lakes from April to October 2018. Total phytoplankton abundance was significantly correlated with chlorophyll-a (Chl-a) (r=0.666) and Secchi depth (SD) (r= -0.351). The abundances of cyanobacteria and harmful cyanobacteria were also correlated with Chl-a (r=0.664, r=0.353) and SD (r= -0.340, r= -0.338), respectively, but not with total nitrogen (TN) and total phosphorus (TP). The Chl-a concentration was correlated with SD (r= -0.434), showing a higher similarity than phytoplankton abundance. Therefore, Chl-a and SD were selected as diagnostic factors for algal bloom prediction, instead of analyzing the standing crop of harmful cyanobacteria used in algae alarm systems. Specifically, accurate diagnoses were made using realtime SD measurements. The algal bloom diagnostic tool is an inverse cone-shaped container with an algal bloom diagnosis chart that modified SD and turbidity measurement methods. Lake water was collected to observe the number of rings visible in the container or the number indicated in each ring, depending on the degree of algal bloom,and to determine the final stage of algal blooming by comparison to the colorimetric level on the diagnosis chart. For an accurate diagnosis, we presented 4-step diagnostic criteria based on the concentration of Chl-a and the number of rings and a fan-shaped algal bloom diagnosis chart with Hexa code names. This tool eliminated the variables and errors of previous methods and the results were easily interpreted. This study is expected to facilitate the diagnosis of algal bloom in agricultural lakes and the establishment of an efficient algal bloom management plan.

• Journal of Korean Academy of Nursing Administration
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• v.1 no.1
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• pp.132-146
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• 1995

Even though Korean medical law stipulates that number of patients attended by a nurse is 2.5 for hospitalization and 30 for ambulatory care, the number of patients cared by a nurse per day is much greater than the standard prescribed by the medical law. Current productivity of nurses is not desirable unless the quality of care is considered. And nursing manpower staffing based on neither current nurses' productivity nor standard of medical law cannot respond properly to dynamic situation of the medical services. Under this background, the necessity of more efficient management of nursing manpower occupying 1/3 of total hospital workers has been recognized by many nursing administrators. Many nursing researchers have studied to foretell the nursing manpower objectively on the basis of measured nursing workload according to patient classification as well. Most of These researches, however, have been conducted in the tertiary hospitals, so it is imperative to conduct other researches to predict necessary nursing manpower in the secondary and the primary hospitals. The study was performed to measure nursing workload and predict pertinent nursing manpower to a secondary hospital with 400beds. Nursing workload was surveyed using measuring tool for direct and indirect care hours in a surgical unit and a medical unit. Survey was conducted from Sep.10 to Sep.16 and from Oct.5 to Oct.11, 1994 respectively by two skilled nurses, Subjects were patients, patients' family members and nursing personnels. Results are follows : 1. Patient classification distributed as 22% of class I (mildly ill patient), 57% of class II (moderately ill patient), and 21% of class III (acutely ill patient) in the medical nursing unit, while 23% of class I, 29% of class II, 12% of class III, and 36% of classIV (critically ill patient) in the surgical nursing unit. There was no difference of inpatient number between weekday and weekend. Bed circulation rate was 89% in both units and average patients number per day was 37.4 (total 42beds) in the medical nursing unit, 32.9 (total 37beds) in the medical nursing unit. 2. Direct care hours per day measured as 2.8hrs for class I, 3.3hrs for class II, and 3.5hrs for class III in the medical nursing unit, while 3.1hrs for class I, 3hrs for class II, 2.7hrs for class III, and 2.2hrs for classIV in the surgical nursing unit. Meanwhile, hours for nursing assistant activities per patient by patients' family members were 11mins and 200mins respectively. Direct care hour rate by shift was day 36%, evening 25%, and night 39% in the medical nursing unit, while 40%, 29%, and and 31% respectively in the surgical nursing unit. 3. Measurement and observation activity held 44.2% of direct care activities of nurses and medication 36.7%, communication 11.7%, exercise 1.8%, treatment 1.3%, hygiene 1.3%, elimination and irrigation 1.1%, suction 1%, nutrition 0.5%, thermotherapy 0.3%, oxygen therapy 0.1% in order. 4. Indirect care hours per day were 294.2mins in the medical nursing unit, and 273.9mins in the surgical nursing unit. By shift, evening was the highest in both units. Indirect care hours for each patient were 44.5mins in the medical nursing unit and 46mins in the surgical nursing unit. 5. checking activities including doctor's order, medication, and delivering patients to the next shift occupied 39.7% of indirect care activities, and preparation 26%, recording 23.8%, communication and conference 6.7%, managing equipments 2.1%, messenger activity 1.7% in order. 6. On the ground of these results, nursing manpower needed in a secondary hospital was estimated ; 27 nursing personnels for the medical nursing unit of 37beds, and 20 nursing personnels for the surgical nursing unit of 33beds.

• KSBB Journal
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• v.18 no.6
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• pp.522-528
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• 2003

The purpose of this study is to inquire into molecular epidemiological characteristics of Vibrio parahaemolyticus. For this study, 120 strains(120 strains of Vibrio parahaemolyticus sampled from diarrhea patients) were examined and analyzed for biochemical characteristics, TDH (thermostable direct hemolysin) antibiotics sensitivity and detection of toxR, gyrE, tdh, and tds gents. G-S PCR (Group Specific Polymerase), PFGE (Pulsed-field Gel Electrophoriesis) methods were performed on the materials from patients were results. 1 Vibrio parahaemolyticus didn't grow in 0% density of NaCl, but the fact was found that those grew in 8% density of NaCl. 2. O：K serotypes of Vibrio parahaemolyticus was turned up in domestic patients was 17 types. Among those O3：K6 was the most, it was 68.3%. 3. In 18 kinds of antibiotic tests resistant against Ampicillin, Ticacillin was comparatively high. the case of resistant against Ampicillin, Ticacillin, Vancomycin at the multiple resistant was 52.5%. 4. Toxin gene tdh had only 109 strains among 120 ones isolated from patients held the genes of 199bp size, and 11 strains was negativity 5. In the test of Kanagawa toxic productivity, 107 strains among strains isolated from patients appeared to be positivity reaction 6. The strain that held trh toxin was only 3, and those among test strains had the genes of 250bp size and that had tdh, trh genes at a time were 3 strains, and TDH toxic productivity of those were 16 times, and it was weak. 7. Group Specific-PCR appeared to be useful in the confirmation of O3:K6 serotype interrelations. 8. Three strains which showed difference of 7 DNA sequence even in the same serotype were detected by the result of analyzing the regular gene, toxRS DNA sequence. These strains are differ from general strains which carry infection easily. 9. These mutual dose epidemiological relations were classified into smaller-parts through PFGE method. As a result of such classify, 3 findings were found. V. parahaemolyticus sampled from diarrhea patients were classified into 3 types. And third, the result obtained through PFGE method can be used as a useful tool in a point of molecular-epidemiological view.

• Journal of Bio-Environment Control
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• v.32 no.4
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• pp.434-441
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• 2023

Determining the size or area of a plant's leaves is an important factor in predicting plant growth and improving the productivity of indoor farms. In this study, we developed a convolutional neural network (CNN)-based model to accurately predict the length and width of lettuce leaves using photographs of the leaves. A callback function was applied to overcome data limitations and overfitting problems, and K-fold cross-validation was used to improve the generalization ability of the model. In addition, ImageDataGenerator function was used to increase the diversity of training data through data augmentation. To compare model performance, we evaluated pre-trained models such as VGG16, Resnet152, and NASNetMobile. As a result, NASNetMobile showed the highest performance, especially in width prediction, with an R_squared value of 0.9436, and RMSE of 0.5659. In length prediction, the R_squared value was 0.9537, and RMSE of 0.8713. The optimized model adopted the NASNetMobile architecture, the RMSprop optimization tool, the MSE loss functions, and the ELU activation functions. The training time of the model averaged 73 minutes per Epoch, and it took the model an average of 0.29 seconds to process a single lettuce leaf photo. In this study, we developed a CNN-based model to predict the leaf length and leaf width of plants in indoor farms, which is expected to enable rapid and accurate assessment of plant growth status by simply taking images. It is also expected to contribute to increasing the productivity and resource efficiency of farms by taking appropriate agricultural measures such as adjusting nutrient solution in real time.