• Journal of Animal Environmental Science
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• v.4 no.2
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• pp.97-104
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• 1998

In order to advise how to solve the problems and suggest on the mechanization of beef farm, the facilities and equipment for feeding and supplying water to the animals and transporting manure, and farm machineries of sixty-seven beef cattle farms in western Chungnam Province were surveyed. The results are as follows; 1. The proportions of number of heads per farm for above 70, 50∼70, 30∼50, 10∼30 and below 10 heads were 26, 18, 29, 13 and 13, respectively. The farms with the annual income more than 30 million won are consisted of 67.6% of the farms surveyed which showed to be higher than national average. 2. Only 19% of farms had automatic feeding system. Water was supplied by water cup(45%), opening and shutting water tab(27.6%) and bucket. 3. Cattle manure was transported by manpower (46%) by loader (34%) and by gravitational flow (14%). Most of manure(97%) was composted after treatment of drying or piling up outside. 4. More instruction and education were required because of the insufficient routine checking and fixing for farming machines, and unsystematic education for learning skills. 5. 65% of farms felt unsatisfied about after service(A/S) for their machinery. The main reason why the farmers were not satisfied was that it took too much time to be repaired. 6. When the farms purchased facilities, equipment and machinery, they did not analyze economic value of them and keep a diary. To make effective use of machines, the most available model for purchasing and managing of machines must be developed and applied to various scales of management.

• International journal of advanced smart convergence
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• v.9 no.1
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• pp.63-69
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• 2020

The rapid development in modern industrialization pollutant the water and atmospheric air across the globe that have a major impact on the human and livings health. In worldwide, every country government increasing the importance to improve the outdoor air pollution monitoring and control to provide quality of life and prevent the citizens and livings life from hazard disease. We proposed the environmental dust level detection method for outdoor facilities using sensor fusion technology to measure precise micro-dust level and monitor in realtime. In this proposed approach use the camera sensor and commercial dust level sensor data to predict the micro-dust level with data fusion method. The camera sensor based dust level detection uses the optical flow based machine learning method to detect the dust level and then fused with commercial dust level sensor data to predict the precise micro-dust level of the outdoor facilities and send the dust level informations to the outdoor air pollution monitoring system. The proposed method implemented on raspberry pi based open-source hardware with Internet-of-Things (IoT) framework and evaluated the performance of the system in realtime. The experimental results confirm that the proposed micro-dust level detection is precise and reliable in sensing the air dust and pollution, which helps to indicate the change in the air pollution more precisely than the commercial sensor based method in some extent.

• School Mathematics
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• v.18 no.1
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• pp.159-173
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• 2016

In real educational field, there are cases that concrete problematic situations are introduced after abstract concepts are taught on the contrary to process that abstract from concrete contexts. In other words, there are cases that abstract knowledge has to be concreted. Freudenthal expresses this situation to antidogmatical inversion and indicates negative opinion. However, it is open to doubt that every class situation can proceed to abstract that begins from concrete situations or concrete materials. This study has done a comparative analysis in difference of mathematical thinking between a process that builds abstract context after being abstracted from concrete materials and that concretes abstract concepts to concrete situations and attempts to examine educational implication. For this, this study analyzed the mathematical thinking in the abstract process of concrete materials by manipulating AiC analysis tools. Based on the AiC analysis tools, this study analyzed mathematical thinking in the concrete process of abstract concept by using the way this researcher came up with. This study results that these two processes have opposite learning flow each other and significant mathematical thinking can be induced from concrete process of abstract knowledge as well as abstraction of concrete materials.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.6
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• pp.609-614
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• 2014

Cerebellar ataxia is a steadily progressive neurodegenerative disease associated with loss of motor control, leaving patients unable to walk, talk, or perform activities of daily living. Direct motor instruction in cerebella ataxia patients has limited effectiveness, presumably because an inappropriate closed-loop cerebellar response to the inevitable observed error confounds motor learning mechanisms. Recent studies have validated the age-old technique of employing motor imagery training (mental rehearsal of a movement) to boost motor performance in athletes, much as a champion downhill skier visualizes the course prior to embarking on a run. Could the use of EEG based BCI provide advanced biofeedback to improve motor imagery and provide a "backdoor" to improving motor performance in ataxia patients? In order to determine the feasibility of using EEG-based BCI control in this population, we compare the ability to modulate mu-band power (8-12 Hz) by performing a cued motor imagery task in an ataxia patient and healthy control.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.8B
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• pp.947-953
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• 2011

These days, a consistent and fatal attack attribute toward a database has proportionally evolved in the similar development form to that of security policy. Because of access control-based defensive techniques regarding information created in closed networks and attacks on a limited access pathway, cases of infringement of many systems and databases based on accumulated and learned attack patterns from the past are increasing. Therefore, the paper aims to separate attack information by its types based on a virtual infringement pattern system loaded with dualistic VM in order to ensure stability to limited certification and authority to access, to propose a system that blocks infringement through the intensive management of infringement pattern concerning attack networks, and to improve the mechanism for implementing a test that defends the final database, the optimal defensive techniques, and the security policies, through research.

• The Journal of the Korea institute of electronic communication sciences
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• v.7 no.1
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• pp.45-51
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• 2012

Programming is an area that many students have difficulty on because it requires various skills, such as problem analysis, logical thinking, and procedural problem-solving skills. In this paper, a system visualizing algorithm was used to set up algorithmic concepts easily and effectiveness of the system was analyzed through scholastic achievement test and survey after learning through this process. For evaluation, we divided students who take courses on programming language and algorithm in 3 universities into 2 groups with 6 teams in each group. The group that trained this system visualizing algorithm had scored 17.4 points higher in terms of scholastic achievement than the group that did not train such method. Moreover, according to the survey, the group had higher scores in terms of interest level, concentration level, comprehension, effectiveness, and convenience.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.10a
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• pp.501-503
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• 2017

In the water sector, various data such as flow rate, pressure, water quality and water level are collected during the whole process of water purification plant and piping system. The collected data is stored in each water treatment plant's DB, and the collected data are combined in the regional DB and finally stored in the database server of the head office of the Korea Water Resources Corporation. Various abnormal data can be generated when a measuring instrument measures data or data is communicated over various processes, and it can be classified into missing data and wrong data. The cause of each abnormal data is different. Therefore, there is a difference in the method of detecting the wrong side and the missing side data, but the method of cleansing the data is the same. In this study, a program that can automatically refine missing or wrong data by applying deep learning LSTM (Long Short Term Memory) algorithm will be studied.

• KIEAE Journal
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• v.17 no.5
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• pp.69-76
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• 2017

Purpose: This study aimed at developing an Artificial Neural Network (ANN) model for predicting the amount of cooling energy consumption of the variable refrigerant flow (VRF) cooling system by the different set-points of the control variables, such as supply air temperature of air handling unit (AHU), condenser fluid temperature, condenser fluid pressure, and refrigerant evaporation temperature. Applying the predicted results for the different set-points, the control algorithm, which embedded the ANN model, will determine the most energy efficient control strategy. Method: The ANN model was developed and tested its prediction accuracy by using matrix laboratory (MATLAB) and its neural network toolbox. The field data sets were collected for the model training and performance evaluation. For completing the prediction model, three major steps were conducted - i) initial model development including input variable selection, ii) model optimization, and iii) performance evaluation. Result: Eight meaningful input variables were selected in the initial model development such as outdoor temperature, outdoor humidity, indoor temperature, cooling load of the previous cycle, supply air temperature of AHU, condenser fluid temperature, condenser fluid pressure, and refrigerant evaporation temperature. The initial model was optimized to have 2 hidden layers with 15 hidden neurons each, 0.3 learning rate, and 0.3 momentum. The optimized model proved its prediction accuracy with stable prediction results.

• Journal of Convergence for Information Technology
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• v.11 no.12
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• pp.39-48
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• 2021

The purpose of this study was to identify the degree of grit, resilience, academic self-efficacy, and learning flow of nursing college students in the COVID-19 situation to identify the factors that influence burnout. Data were collected by using questionnaires from 155 students who were in 3rd year of the nursing college in G city, from May 11 to May 25, 2021. Data were analyzed by t-test, ANOVA, Scheffe, Kruskal-Wallis test, Pearson's correlation, and multiple regression. Statistically, burnout showed a significantly negative correlation with grit, resilience and academic self-efficacy. Influencing factors on burnout were resilience, satisfaction of major, academic self-efficacy and satisfaction of clinic practice accounting for 60% of the total change. Based on this study, strategies to enhance resilience, satisfaction of major, academic self-efficacy and satisfaction of clinic practice are required to reduce the burnout of nursing college students in the COVID-19 situation.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.3
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• pp.165-171
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• 2019

The study of the computer architecture has shown that major improvements in price-to-energy performance stems from domain-specific hardware development. This paper analyzes the tensor processing unit (TPU) ASIC which can accelerate the reasoning of the artificial neural network (NN). The core device of the TPU is a MAC matrix multiplier capable of high-speed operation and software-managed on-chip memory. The execution model of the TPU can meet the reaction time requirements of the artificial neural network better than the existing CPU and the GPU execution models, with the small area and the low power consumption even though it has many MAC and large memory. Utilizing the TPU for the tensor flow benchmark framework, it can achieve higher performance and better power efficiency than the CPU or CPU. In this paper, we analyze TPU, simulate the Python modeled OpenTPU, and synthesize the matrix multiplication unit, which is the key hardware.