Recently, machine learning technology has had a significant impact on society, particularly in the medical, manufacturing, marketing, finance, broadcasting, and agricultural aspects of human lives. In this paper, we study how to apply machine learning techniques to foods, which have the greatest influence on the human survival. In the field of Smart Farm, which integrates the Internet of Things (IoT) technology into agriculture, we focus on optimizing the crop growth environment by monitoring the growth environment in real time. KT Smart Farm Solution 2.0 has adopted machine learning to optimize temperature and humidity in the greenhouse. Most existing smart farm businesses mainly focus on controlling the growth environment and improving productivity. On the other hand, in this study, we are studying how to apply machine learning with respect to harvest time so that we will be able to harvest fruits of the highest quality and ship them at an excellent cost. In order to apply machine learning techniques to the field of smart farms, it is important to acquire abundant voluminous data. Therefore, to apply accurate machine learning technology, it is necessary to continuously collect large data. Therefore, the color, value, internal temperature, and moisture of greenhouse-grown fruits are collected and secured in real time using color, weight, and temperature/humidity sensors. The proposed FPSML provides an architecture that can be used repeatedly for a similar fruit crop. It allows for a more accurate harvest time as massive data is accumulated continuously.
The high-tech industry, a leader in the national economy, has a larger investment cost compared to general buildings, a shorter construction period, and requires continuous investment. Therefore, accurate construction cost prediction and quick decision-making are important factors for efficient cost and process management. Overseas, the construction information classification system has been standardized since 1980 and has been continuously developed, improving construction productivity by systematically collecting and utilizing project life cycle information. At domestic construction sites, attempts have been made to standardize the classification system of construction information, but it is difficult to achieve continuous standardization and systematization due to the absence of a standardization body and differences in cost and process management methods for each construction company. Particular, in the case of the high-tech industry, the standardization and systematization level of the construction information classification system for high-tech facility construction is very low due to problems such as large scale, numerous types of work, complex construction and security. Therefore, the purpose of this study is to construct a construction information classification system suitable for high-tech facility construction through collection, classification, and analysis of related project data constructed in Korea. Based on the WBS (Work Breakdown Structure) and CBS (Cost Breakdown Structure) classified and analyzed through this study, a code system through hierarchical classification was proposed, and the cost model of buildings by linking WBS and CBS was three-dimensionalized and the utilized method was presented. Through this, an information classification system based on inter-relationships can be developed beyond the one-way tree structure, which is a general construction information classification system, and effects such as shortening of construction period and cost reduction will be maximized.
Supply electrical conductivity (EC) concentration of the nutrition solution is an important factor in the absorption of nutrients by plants and the management of the root zone, as it can control the vegetative/reproductive growth of a plant. Paprika usually undergoes its reproductive and vegetative growth simultaneously. Therefore, ensuring proper growth of the plant leads to increased yield of paprika. In this study, growth characteristics of paprika were examined according to the EC concentration of a coir and a rockwool substrate. The supply EC was 1.0, 2.0, and 4.0 mS·cm-1 applied at the initial stages of the growth using the rockwool (commonly used by paprika farmers) and the coir substrate with a chip and dust ratio of 50:50 and 70:30. For up to 16 weeks of paprika growth, EC concentrations of 1.0 and 2.0 mS·cm-1 were found to have a greater effect on the growth than EC at 4.0 mS·cm-1. The normality (marketable) rate of fruit, the soluble solid content, and paprika growth showed that the coir was generally better than the rockwool regardless of the supply EC concentration. The values of the yield per plant at an EC concentration of 4.0 mS·cm-1 was mostly similar at 1.6 kg (coir 50:50), 1.5 kg (coir 70:30) and 1.5 kg (rockwool), but the yield of the rockwool was 88%, which was lower than 98% and 94% yield of the coir substrate. Therefore, this concludes that coir substrate is more effective than rockwool at improving paprika productivity. The results also suggest that the use of coir substrate for paprika has many benefits in terms of reducing production costs and preventing environmental destruction during post-processing.
Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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v.40
no.5
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pp.421-428
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2022
The earthwork is a core process of all constructions, and compaction measurement of earthwork play an important role in improving productivity. The analog tests such as Plate Bearing Test and Sand-cone occupy current compaction measurement techniques. Due to advanced 4th Industrial Revolution, research on analog tests combined smart construction technology are actively conducted. DCPT (Dynamic Cone penetration Test), simpler and faster than conventional tests, has recently on rise. However, it is also an analog that measures data manually and has several disadvantages such as history management and data verification. The IoT-based DCPT system developed in this study combines digital wire sensors, mobile phones, and Bluetooth with conventional DCPT. Compare to conventional test methods, IoT-based DCPT has advantages such as performance time, single-person measurement, low cost, mobile-based management, and real-time data verification. In addition, a test bed was built to verify IoT-based DCPT. The test bed was built under similar conditions to the actual earthworks site through roller equipment. DCPT data obtained from 322 stations. As a result, IoT-based DCPT showed good performance, and the test bed was also showed stable results as the compaction was carried out.
International Journal of Computer Science & Network Security
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v.22
no.12
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pp.63-70
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2022
The essence of the definition of "tolerance" is analyzed. Motivational, knowledge and behavioral criteria for tolerance of future teachers are highlighted. Indicators of the motivational criterion are the formation of value orientations, motivational orientation, and the development of empathy. Originality and productivity of thoughts and judgments, tact of dialogue, pedagogical ethics and tact are confirmed as indicators of the knowledge criterion. The behavioral criterion includes social activity as a life position, emotional and volitional endurance, and self-control of one's own position. The formation of tolerance is influenced by a number of factors: the social environment, the information society, existing stereotypes and ideas in society, the system of education and relationships between people, and the system of values. The main factors that contribute to the education of tolerance in future teachers are highlighted. Analyzing the structure of tolerance, it is necessary to distinguish the following functions of tolerance: - motivational (determines the composition and strength of motivation for social activity and behavior, promotes the development of life experience, because it allows the individual to accept other points of view and vision of the solution; - informational (understanding the situation, the personality of another person); - regulatory (tolerance has a close connection with the strong - willed qualities of a person: endurance, selfcontrol, self-regulation, which were formed in the process of Education); - adaptive (allows the individual to develop in the process of joint activity a positive, emotional, stable attitude to the activity itself, which the individual carries out, to the object and subject of joint relations). The implementation of pedagogical functions in the information society: educational, organizational, predictive, informational, communicative, controlling, etc. provides grounds to consider pedagogical tolerance as an integrative personal quality of a representative of any profession in the field of "person-person". The positions that should become conditions for the formation of tolerance of the future teacher in the information society are listed.
This article is aimed for to state the rationality of Mojia and reveal the scientific meaning in the theories related to the motion of objects in Mojing: the basic approach to the principle of gravitation in building castle, and comprehension and application of the principle in the lever devised for improving productivity as well as in an inclined plane. It is denied in this article that the technical advance and the positive influence on the people is achieved by Mojias only because they were occupied in the filed of craft. Mojia was one of the schools of Qin in the early stage who realized how important science wass for the better society focused on humanity. Furthermore, they were the frontiers who pursued the proper society through science. Therefore, the scientific theories claimed by Mojia is not emphasized only on the deducting regularity of nature. Instead, it could be theorized only by guaranteeing the welfare for common people and having close relation to it. The Chinese philosophy in the early Twentieth century had vigorous interest in the Mojia's opinions in science and set about conducting study in this part. Based on the study, it was revealed that the Mojia's opinion toward motion is superior to that of the West. Furthermore, it was proved to reflect the main idea in Mojia: the love for common people. Particularly, the theories from Mojia can be so applicable to today's life that some scholars regret the lack of interest in Mojia for the time and even scold themselves for the retarded progress in science of China.
Korean Journal of Construction Engineering and Management
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v.24
no.6
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pp.63-65
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2023
BIM and AR technologies have been assessed as a means of enhancing productivity within the construction industry, through the provision of effortless access to critical data on site, achieved via the projection of 3D models and associated information onto actual structures. However, most of the previous researches for applying AR technology in construction quality management has been performed for construction projects in general, resulting in only overall on-site management solutions. Also, a few previous researches for the application of AR in the quality management of specific elements like reinforcements focused only on simple projection, so conducting specific quality inspection was impossible. Hence, this study aimed to develop a practically applicable BIM-based AR quality management system targeted for reinforcements. For the development of this system, the reinforcement inspection items on the quality checklist used at railway construction sites were analyzed, and four types of AR functions that can effectively address these items were developed and installed. The validation result of the system for the actual railway bridge showed a degradation of projection stability. This problem was solved through model simplification and enhancement of the AR device's hardware performance, and then the normal operation of the system was validated. Subsequently, the final developed reinforcement quality inspection system was evaluated for practical applicability by on-site quality experts, and the efficiency of inspection would significantly increase when using the AR system compared to the current inspection method for reinforcements.
Container volume is a very important factor in accurate evaluation of port performance, and accurate prediction of effective port development and operation strategies is essential. However, it is difficult to improve the accuracy of container volume prediction due to rapid changes in the marine industry. To solve this problem, it is necessary to analyze the impact on port performance using the Internet of Things (IoT) and apply it to improve the competitiveness and efficiency of Busan Port. Therefore, this study aims to develop a prediction model for predicting the future container volume of Busan Port, and through this, focuses on improving port productivity and making improved decision-making by port management agencies. In order to predict port container volume, this study introduced the Extreme Gradient Boosting (XGBoost) technique of a machine learning model. XGBoost stands out of its higher accuracy, faster learning and prediction than other algorithms, preventing overfitting, along with providing Feature Importance. Especially, XGBoost can be used directly for regression predictive modelling, which helps improve the accuracy of the volume prediction model presented in previous studies. Through this, this study can accurately and reliably predict container volume by the proposed method with a 4.3% MAPE (Mean absolute percentage error) value, highlighting its high forecasting accuracy. It is believed that the accuracy of Busan container volume can be increased through the methodology presented in this study.
Due to the recent transition to a non-face-to-face society, many organizations are quickly adapting to foster a smart work environment. The introduction of smart work does not simply end with incorporating ICT systems or solutions into business models since fundamental factors such as forms of employment and work styles need to be in line with the progression of technological advances. However, previous studies regarding smart work focus on improvements in productivity and efficiency from a technology acceptance perspective. Therefore, there is a lack of discussion on innovation resistance from employees and management control when ICT systems are introduced into the workplace. This study empirically analyzes the moderating effects of the organizational control method for employees and innovation resistance within a smart work environment. Additionally, this study aims to identify the structural characteristics that employees resist from an innovation resistance perspective when organizational innovation occurs. The empirical analysis of this study suggests that when smart work such as ICT technology is introduced into the workplace the level of innovation resistance decreases when there is a high level of relative advantage and self-efficacy, whereas the level of innovation resistance increases when there is a high level of use complexity. Moreover, this study revealed that the level of innovation resistance increases when the employees' behaviors were controlled. The results of this study intend to contribute to improving business management by suggesting factors worth considering when incorporating smart work into work places through a thorough case analysis.
With the fierce competition of companies for the attraction of outstanding individuals, job satisfaction of employees has been of importance. In this circumstance, many companies try to invest in job satisfaction improvement by finding employees' everyday experiences and difficulties. However, due to a lack of understanding of the employee experience, their investments are not paying off. This study examined the relationship between employee experience and job satisfaction using employee reviews and company ratings from Glassdoor, one of the largest employee communities worldwide. We use text mining techniques such as K-means clustering and LDA topic-based sentiment analysis to extract key experience factors by job level, and DistilBERT sentiment analysis to measure the sentiment score of each employee experience factor. The drawn employee experience factors and each sentiment score were analyzed quantitatively, and thereby relations between each employee experience factor and job satisfaction were analyzed. As a result, this study found that there is a significant difference between the workplace experiences of managers and general employees. In addition, employee experiences that affect job satisfaction also differed between positions, such as customer relationship and autonomy, which did not affect the satisfaction of managers. This study used text mining and quantitative modeling method based on theory of work adjustment so as to find and verify main factors of employee experience, and thus expanded research literature. In addition, the results of this study are applicable to the personnel management strategy for improving employees' job satisfaction, and are expected to improve corporate productivity ultimately.
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