• Title/Summary/Keyword: Integrated Management Systems

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Development Strategies of The Hanwoo [Korean Native Cattle] Industry (한우산업의 발전전략)

  • Kim Jin Suk
    • Proceedings of the Korean Society of Crop Science Conference
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    • 1998.10a
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    • pp.68-111
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    • 1998
  • The structure of the Hanwoo (Korean Native Cattle) Industry remains very weak and vulnerable to the WTO/IMF system. Considering that the majority of cattle farmers are small sized, and that marketing systems are outdated and inefficient, rapid expansion of lower priced beef imports by WTO system and rapid increasing of production costs by IMF system would lead to the deprivation of a regular source of farm income and threaten the stability of rural life. Accordingly, the Hanwoo industry should be expanded in accordance with progress in the implementation of (1) programs for the structural adjustment and (2) measures to compensate for the loss. Efforts for lowering major production factor costs needs to continue, In order to increase the supply of calves at low cost, the programs of collective cow-calf farms should be expanded, thereby reducing the cost of calf purchase, which constitutes the largest share of Hanwoo production cost. Also, feedlot operations should be encouraged for small herd farms in order to achieve a substantial saving in beef production costs by integrated operations from calf production to cattle fattening. A substantial saving would also be made by collective purchase and distribution of various inputs through the cooperatives' channels. Extension services should be strengthened for cattle farm management, cattle care and feeding, prevention of cattle disease, etc. In order to minimize cash outlays for commercial mixed feeds, utilization of far by-products as feeds should be enhanced and production of forage crops productive of resources, such as land and rural labor, during the farm o(f-season, needs to be encouraged. Also, technological development for enhancing the nutritional value of farm by-products should be encouraged. Measures for successful segregation of the Hanwoo beef market should be implemented, thereby enhancing incentive for quality beef producers and protecting consumers willing to pay higher price for quality beef. For development of the Hanwoo industry, a considerable time frame would be required in order for (1) small livestock farmers to make a successful adjustment by staying in the enterprise and achieving increased price efficiency (2) livestock farmers to acquire know-how for producing quality Hanwoo beef, (3) the ongoing Government policy of enhancing price-quality competitiveness, and for improving the quality Hanwoo beef marketing to take root. (4) consumers to increase their ability to distinguish meat quality, and others.

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A study on the Power Characteristics of Hybrid Power System by Active Power Management (능동전력제어에 의한 하이브리드 동력시스템의 출력특성 연구)

  • Lee, Bohwa;Park, Poomin
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.44 no.9
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    • pp.833-841
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    • 2016
  • The 200 W electrically powered unmanned aerial vehicle, which is studied in this research, uses solar cells, a fuel cell and batteries as the main power source simultaneously. The output of each power source performs power control for each power source by the active power control method so that an adequate capacity of the battery could be maintained while limiting the maximum output of the fuel cell. The output variation for each power source under the active power control method was identified through an integrated ground test. In addition, the effect of limiting the maximum output of the fuel cell on the output variation of the entire system was experimentally identified, and it was confirmed that the adequate maximum output value of the fuel cell for preventing the overdischarge of six series-connected, small size batteries for fuel cell systems is 150 W.

Clinical presentation and specific stabilizing exercise management in Lumbar segmental instability (요추분절의 불안정성에 대한 임상적 소개와 안정성 운동관리)

  • Jung Yeon-Woo;Bae Sung-Soo
    • The Journal of Korean Physical Therapy
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    • v.15 no.1
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    • pp.155-170
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    • 2003
  • Lumbar segmental instability is considered to represent a significant sub-group within the chronic low back pain population. This condition has a unique clinical presentation that displays its symptoms and movement dysfunction within the neutral zone of the motion segment. The loosening of the motion segment secondary to injury and associated dysfunction of the local muscle system renders it biomechanically vulnerable in the neutral zone. There in evidence of muscle dysfunction related to the control of the movement system. There is a clear link between reduced proprioceptive input, altered slow motor unit recruitment and the development of chronic pain states. Dysfunction in the global and local muscle systems in presented to support the development of a system of classification of muscle function and development of dysfunction related to musculoskeletal pain. The global muscles control range of movement and alignment, and evidence of dysfunction is presented in terms of imbalance in recruitment and length between the global stability muscles and the global mobility muscles. The local stability muscles demonstrate evidence of failure of aeequate segmental control in terms of allowing excessive uncontrolled translation or specific loss of cross-sectional area at the site of pathology Motor recruitment deficits present as altered timing and patterns of recruitment. The evidence of local and global dysfunction allows the development of an integrated model of movement dysfunction. The clinical diagnosis of this chronic low back pain condition is based on the report of pain and the observation of movement dysfunction within the neutral zone and the associated finding of excessive intervertebral motion at the symptomatic level. Four different clinical patterns are described based on the directional nature of the injury and the manifestation of the patient's symptoms and motor dysfunction. A specific stabilizing exercise intervention based on a motor learning model in proposed and evidence for the efficacy of the approach provided.

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Comparison Studies of Hybrid and Non-hybrid Forecasting Models for Seasonal and Trend Time Series Data (트렌드와 계절성을 가진 시계열에 대한 순수 모형과 하이브리드 모형의 비교 연구)

  • Jeong, Chulwoo;Kim, Myung Suk
    • Journal of Intelligence and Information Systems
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    • v.19 no.1
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    • pp.1-17
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    • 2013
  • In this article, several types of hybrid forecasting models are suggested. In particular, hybrid models using the generalized additive model (GAM) are newly suggested as an alternative to those using neural networks (NN). The prediction performances of various hybrid and non-hybrid models are evaluated using simulated time series data. Five different types of seasonal time series data related to an additive or multiplicative trend are generated over different levels of noise, and applied to the forecasting evaluation. For the simulated data with only seasonality, the autoregressive (AR) model and the hybrid AR-AR model performed equivalently very well. On the other hand, if the time series data employed a trend, the SARIMA model and some hybrid SARIMA models equivalently outperformed the others. In the comparison of GAMs and NNs, regarding the seasonal additive trend data, the SARIMA-GAM evenly performed well across the full range of noise variation, whereas the SARIMA-NN showed good performance only when the noise level was trivial.

A Study on the Immunization Information Mobile Services using the Smart-Phone (스마트폰을 이용한 예방접종 정보 모바일 서비스에 관한 연구)

  • Kim, Chang-Su;Bae, Geun-Ryang;Lee, Yeon-Kyung;Kim, Myeong-Jin
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2010.10a
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    • pp.681-684
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    • 2010
  • Immunization information recorded on the Immunization rate in the community to identify the effects of immunization can be monitored. Immunization during an accident can be used as a basis for investigating the cause. Thus, immunization records, and more efficient management in the private and public institutions have conducted immunization information systems to manage the development of integrated system has to be. So, the government projects that promote immunization records were computerized registration. And, in 2009 the development of immunization registration system was completed. In this paper, we use the information to a variety of immunization using smart phone design and implement mobile service.

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Improvement of Drought Operation Criteria in Agricultural Reservoirs (농업용 저수지 이수관리를 위한 저수율 가뭄단계기준 개선)

  • Mun, Young-Sik;Nam, Won-Ho;Woo, Seung-Beom;Lee, Hee-Jin;Yang, Mi-Hye;Lee, Jong-Seo;Ha, Tae-Hyun
    • Journal of The Korean Society of Agricultural Engineers
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    • v.64 no.4
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    • pp.11-20
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    • 2022
  • Currently, the operation rule of agricultural reservoirs in case of drought events follows the drought forecast warning standard of agricultural water supply. However, it is difficult to preemptively manage drought in individual reservoirs because drought forecasting standards are set according to average reservoir storage ratio such as 70%, 60%, 50%, and 40%. The equal standards based on average water level across the country could not reflect the actual drought situation in the region. In this study, we proposed the improvement of drought operation rule for agricultural reservoirs based on the percentile approach using past water level of each reservoir. The percentile approach is applied to monitor drought conditions and determine drought criteria in the U.S. Drought Monitoring (USDM). We applied the drought operation rule to reservoir storage rate in extreme 2017 spring drought year, the one of the most climatologically driest spring seasons over the 1961-2021 period of record. We counted frequency of each drought criteria which are existing and developed operation rules to compare drought operation rule determining the actual drought conditions during 2016-2017. As a result of comparing the current standard and the percentile standard with SPI6, the percentile standard showed severe-level when SPI6 showed severe drought condition, but the current standard fell short of the results. Results can be used to improve the drought operation criteria of drought events that better reflects the actual drought conditions in agricultural reservoirs.

A semi-supervised interpretable machine learning framework for sensor fault detection

  • Martakis, Panagiotis;Movsessian, Artur;Reuland, Yves;Pai, Sai G.S.;Quqa, Said;Cava, David Garcia;Tcherniak, Dmitri;Chatzi, Eleni
    • Smart Structures and Systems
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    • v.29 no.1
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    • pp.251-266
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    • 2022
  • Structural Health Monitoring (SHM) of critical infrastructure comprises a major pillar of maintenance management, shielding public safety and economic sustainability. Although SHM is usually associated with data-driven metrics and thresholds, expert judgement is essential, especially in cases where erroneous predictions can bear casualties or substantial economic loss. Considering that visual inspections are time consuming and potentially subjective, artificial-intelligence tools may be leveraged in order to minimize the inspection effort and provide objective outcomes. In this context, timely detection of sensor malfunctioning is crucial in preventing inaccurate assessment and false alarms. The present work introduces a sensor-fault detection and interpretation framework, based on the well-established support-vector machine scheme for anomaly detection, combined with a coalitional game-theory approach. The proposed framework is implemented in two datasets, provided along the 1st International Project Competition for Structural Health Monitoring (IPC-SHM 2020), comprising acceleration and cable-load measurements from two real cable-stayed bridges. The results demonstrate good predictive performance and highlight the potential for seamless adaption of the algorithm to intrinsically different data domains. For the first time, the term "decision trajectories", originating from the field of cognitive sciences, is introduced and applied in the context of SHM. This provides an intuitive and comprehensive illustration of the impact of individual features, along with an elaboration on feature dependencies that drive individual model predictions. Overall, the proposed framework provides an easy-to-train, application-agnostic and interpretable anomaly detector, which can be integrated into the preprocessing part of various SHM and condition-monitoring applications, offering a first screening of the sensor health prior to further analysis.

Improving the Functions of Digital Textbooks to Prepare for the post COVID-19 (포스트 코로나를 대비한 디지털교과서의 기능 개선)

  • Kim, Hong-sun;Jeong, Young-sik
    • 한국정보교육학회:학술대회논문집
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    • 2021.08a
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    • pp.283-288
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    • 2021
  • In the COVID-19 situation, digital textbooks have been used in many schools. In order for digital textbooks to become active even in the post COVID-19 era, the functions of digital textbooks must be improved. Digital textbooks are traditional book-type textbooks with glossaries, video materials, and evaluation questions added. Recently, they are being used usefully for practical education by providing realistic contents such as Augmented Reality, Virtual Reality, and 360 images. Therefore, in this study, in order to prepare for the post COVID-19, we found the functional problems of digital textbooks and suggested a way to improve them. First, the layout of digital textbooks should be developed as a responsive layout, deviating from the same form as a book-type textbook. Second, digital textbooks and learning management systems must be integrated. Third, by developing a digital textbook for teachers, teachers should be able to directly reorganize the contents or add external materials. Fourth, learning analysis should be possible using data recorded in digital textbooks. Fifth, in the 2022 revised curriculum, various subjects should be developed as digital textbooks.

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Improving SARIMA model for reliable meteorological drought forecasting

  • Jehanzaib, Muhammad;Shah, Sabab Ali;Son, Ho Jun;Kim, Tae-Woong
    • Proceedings of the Korea Water Resources Association Conference
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    • 2022.05a
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    • pp.141-141
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    • 2022
  • Drought is a global phenomenon that affects almost all landscapes and causes major damages. Due to non-linear nature of contributing factors, drought occurrence and its severity is characterized as stochastic in nature. Early warning of impending drought can aid in the development of drought mitigation strategies and measures. Thus, drought forecasting is crucial in the planning and management of water resource systems. The primary objective of this study is to make improvement is existing drought forecasting techniques. Therefore, we proposed an improved version of Seasonal Autoregressive Integrated Moving Average (SARIMA) model (MD-SARIMA) for reliable drought forecasting with three years lead time. In this study, we selected four watersheds of Han River basin in South Korea to validate the performance of MD-SARIMA model. The meteorological data from 8 rain gauge stations were collected for the period 1973-2016 and converted into watershed scale using Thiessen's polygon method. The Standardized Precipitation Index (SPI) was employed to represent the meteorological drought at seasonal (3-month) time scale. The performance of MD-SARIMA model was compared with existing models such as Seasonal Naive Bayes (SNB) model, Exponential Smoothing (ES) model, Trigonometric seasonality, Box-Cox transformation, ARMA errors, Trend and Seasonal components (TBATS) model, and SARIMA model. The results showed that all the models were able to forecast drought, but the performance of MD-SARIMA was robust then other statistical models with Wilmott Index (WI) = 0.86, Mean Absolute Error (MAE) = 0.66, and Root mean square error (RMSE) = 0.80 for 36 months lead time forecast. The outcomes of this study indicated that the MD-SARIMA model can be utilized for drought forecasting.

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Implementation of Smart Automatic Warehouse to Improve Space Utilization

  • Hwa-La Hur;Yeon-Ho Kuk;Myeong-Chul Park
    • Journal of the Korea Society of Computer and Information
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    • v.28 no.10
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    • pp.171-178
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    • 2023
  • In this paper, we propose a smart automated warehouse to maximize space utilization. Previous elevator-type automatic warehouses were designed with a maximum payload of 100kg on trays, which has the problem of extremely limiting the number of pallets that can be loaded within the space. In this paper, we design a smart warehouse that can maximize space utilization with a maximum vertical stiffness of 300kg. As a result of the performance evaluation of the implemented warehouse, the maximum payload was 500.6kg, which satisfied the original design and requirements, the lifting speed was 0.5m/s, the operating noise of the device was 67.1dB, the receiving and forwarding time of the pallet was 36.92sec, the deflection amount was 4mm, and excellent performance was confirmed in all evaluation items. In addition, the PLC control method, which designs the control UI and control panel separately, was integrated into the PC system to improve interoperability and maintainability with various process management systems. In the future, we plan to develop it into a fully automatic smart warehouse by linking IoT sensor-based logistics robots.