• Title/Summary/Keyword: Logistic Modeling

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Modeling Growth of Canopy Heights and Stem Diameters in Soybeans at Different Groundwater Level (지하 수위가 다른 조건에서 콩의 초장과 경태 모델링)

  • Choi, Jin-Young;Kim, Dong-Hyun;Kwon, Soon-Hong;Choi, Won-Sik;Kim, Jong-Soon
    • Journal of the Korean Society of Industry Convergence
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    • v.20 no.5
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    • pp.395-404
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    • 2017
  • Cultivating soybeans in rice paddy field reduces labor costs and increases the yield. Soybeans, however, are highly susceptible to excessive soil water in paddy field. Controlled drainage system can adjust groundwater level (GWL) and control soil moisture content, resulting in improvement soil environments for optimum crop growth. The objective of this study was to fit the soybean growth data (canopy height and stem diameter) using Gompertz model and Logistic model at different GWL and validate those models. The soybean, Daewon cultivar, was grown on the lysimeters controlled GWL (20cm and 40cm). The soil textures were silt loam and sandy loam. The canopy height and stem diameter were measured from the 20th days after seeding until harvest. The Gompertz and Logistic models were fitted with the growth data and each growth rate and maximum growth value was estimated. At the canopy height, the $R_2$ and RMSE were 0.99 and 1.58 in Gompertz model and 0.99 and 1.33 in Logistic model, respectively. The large discrepancy was shown in full maturity stage (R8), where plants have shed substantial amount of leaves. Regardless of soil texture, the maximum growth values at 40cm GWL were greater than the value at 20cm GWL. The growth rates were larger at silt loam. At the stem diameter, the $R_2$ and RMSE were 0.96 and 0.27 in Gompertz model and 0.96 and 0.26 in Logistic model, respectively. Unlike the canopy height, the stem diameter in R8 stage didn't decrease significantly. At both GWLs, the maximum growth values and the growth rates at silt loam were all larger than the values at sandy loam. In conclusion, Gompertz model and Logistic model both well fit the canopy heights and stem diameters of soybeans. These growth models can provide invaluable information for the development of precision water management system.

Conceptual Data Modeling of Integrated Information System for Research & Development Configuration Management (연구개발 형상관리 자동화체계에 대한 개념적 데이터모델링)

  • 김인주
    • Journal of the military operations research society of Korea
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    • v.25 no.1
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    • pp.87-106
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    • 1999
  • There are many technical datum in related with design, test & evaluation and logistic support which will be exchanged between geographically isolated units and heterogeneous hardwares & softwares in developing and operating the weapon systems. The paper proposes the conceptual database schema to establish configuration management information systems in which these datum can be automatically interchanged, tracked, audited and status-accounted without errors under the various environments. The paper investigates how to identify and classify the data in accordance with document identification, task analysis, system development, logistic support, system test & evaluation and data management. Furthermore, the investigation includes drawing the subject areas and modeling the conceptual database schema to explain the relationships between these datum. Thus, the paper results in the conceptual framework and data models of configuration management information systems, while additional customization efforts be required in applying the models to a specific weapon systems R&D.

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Modeling Exponential Growth in Population using Logistic, Gompertz and ARIMA Model: An Application on New Cases of COVID-19 in Pakistan

  • Omar, Zara;Tareen, Ahsan
    • International Journal of Computer Science & Network Security
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    • v.21 no.1
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    • pp.192-200
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    • 2021
  • In the mid of the December 2019, the virus has been started to spread from China namely Corona virus. It causes fatalities globally and WHO has been declared as pandemic in the whole world. There are different methods which can fit such types of values which obtain peak and get flattened by the time. The main aim of the paper is to find the best or nearly appropriate modeling of such data. The three different models has been deployed for the fitting of the data of Coronavirus confirmed patients in Pakistan till the date of 20th November 2020. In this paper, we have conducted analysis based on data obtained from National Institute of Health (NIH) Islamabad and produced a forecast of COVID-19 confirmed cases as well as the number of deaths and recoveries in Pakistan using the Logistic model, Gompertz model and Auto-Regressive Integrated Moving Average Model (ARIMA) model. The fitted models revealed high exponential growth in the number of confirmed cases, deaths and recoveries in Pakistan.

Performance and Cost Analysis of Supply Chain Models

  • Bause, F.;Fischer, M.;Kemper, P.;Volker, M.
    • Proceedings of the Korea Society for Simulation Conference
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    • 2001.10a
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    • pp.425-434
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    • 2001
  • In this paper we introduce a general framework for the modeling, analysis and costing of logistic networks including supply chains (SCs). The employed modeling notation, the so-called Process Chain paradigm, is specifically developed for the application field of logistic networks which includes SCs. We view SCs as discrete event dynamic systems (DEDS) and apply corresponding simulative techniques in order to derive performance measures of the Process Chain model under investigation. For this purpose Process Chain models are automatically transformed into the input language of the simulation tool HIT. Subsequently, a cost accounting model using the performance measures is applied to obtain costs which are actually subject of interest. The usefulness and applicability of the approach is illustrated by a typical supply chain example. We investigate the impact of an additional SC channel between a manufacturer and web-consumers on the overall supply chain costs.

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A Short-term Longitudinal Study on Types and Predictors of Trajectories of Adaptation to Child Care Among Infants and Toddlers: Using Growth Mixture Modeling and Latent Classes Analysis (영아의 어린이집 적응 추이의 유형 및 예측 요인에 대한 단기종단연구: 성장혼합모형과 잠재계층분석을 활용하여)

  • Shin, Nary;Jo, Woori
    • Korean Journal of Childcare and Education
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    • v.16 no.1
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    • pp.115-143
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    • 2020
  • Objective: The purpose of this study was to examine underlying types of developmental trajectories of adaptation to child care among infants and toddlers. This study also aimed to identify latent classes in their child care adaptation types in order to find predictors that account for individual differences. Methods: Participants were 420 mothers of infants and toddlers and 123 teachers. The levels of child care adaptation of participating infants and toddlers were rated monthly from early April to June, 2019. The collected data were analyzed using growth mixture modeling, latent class analysis and multinominal logistic analysis. Results: The results of growth trajectories of child care adaptation showed there were two to four latent groups by dimension of child care adaptation. Also, the groups of individual dimensions of child care adaptation were classified into three latent classes, which were 'complying and positive group', 'negative group', and 'individualized group. Multinominal logistic analysis revealed that children's age, gender, and temperament differentiated the three latent classes of adaptation to child care. Conclusion/Implications: The results show individual characteristics that infants and toddlers possess should be prudently considered in order for successful adaptation to child care.

Risk factors for unexpected readmission and reoperation following open procedures for shoulder instability: a national database study of 1,942 cases

  • John M. Tarazi;Matthew J. Partan;Alton Daley;Brandon Klein;Luke Bartlett;Randy M. Cohn
    • Clinics in Shoulder and Elbow
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    • v.26 no.3
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    • pp.252-259
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    • 2023
  • Background: The purpose of this study was to identify demographics and risk factors associated with unplanned 30-day readmission and reoperation following open procedures for shoulder instability and examine recent trends in open shoulder instability procedures. Methods: The American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) database was queried using current procedural terminology (CPT) codes 23455, 23460, and 23462 to find patients who underwent shoulder instability surgery from 2015 to 2019. Independent sample Student t-tests and chi-square tests were used in univariate analyses to identify demographic, lifestyle, and perioperative variables related to 30-day readmission following repair for shoulder instability. Multivariate logistic regression modeling was subsequently performed. Results: In total, 1,942 cases of open surgical procedures for shoulder instability were identified. Within our study sample, 1.27% of patients were readmitted within 30 days of surgery, and 0.85% required reoperation. Multivariate logistic regression modeling confirmed that the following patient variables were associated with a statistically significant increase in the odds of readmission: open anterior bone block/Latarjet-Bristow procedure, being a current smoker, and a long hospital stay (all P<0.05). Multivariate logistic regression modeling confirmed statistically significant increased odds of reoperation with an open anterior bone block or Latarjet-Bristow procedure (P<0.05). Conclusions: Unplanned 30-day readmission and reoperation after open shoulder instability surgery is infrequent. Patients who are current smokers, have an open anterior bone block or Latarjet-Bristow procedure, or a longer than average hospital stay have higher odds of readmission than others. Patients who undergo an open anterior bone block or Latarjet-Bristow procedure have higher odds of reoperation than those who undergo an open soft-tissue procedure. Level of evidence: III.

Modeling of Breast Cancer Prognostic Factors Using a Parametric Log-Logistic Model in Fars Province, Southern Iran

  • Zare, Najaf;Doostfatemeh, Marzieh;Rezaianzadeh, Abass
    • Asian Pacific Journal of Cancer Prevention
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    • v.13 no.4
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    • pp.1533-1537
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    • 2012
  • In general, breast cancer is the most common malignancy among women in developed as well as some developing countries, often being the second leading cause of cancer mortality after lung cancer. Using a parametric log-logistic model to consider the effects of prognostic factors, the present study focused on the 5-year survival of women with the diagnosis of breast cancer in Southern Iran. A total of 1,148 women who were diagnosed with primary invasive breast cancer from January 2001 to January 2005 were included and divided into three prognosis groups: poor, medium, and good. The survival times as well as the hazard rates of the three different groups were compared. The log-logistic model was employed as the best parametric model which could explain survival times. The hazard rates of the poor and the medium prognosis groups were respectively 13 and 3 times greater than in the good prognosis group. Also, the difference between the overall survival rates of the poor and the medium prognosis groups was highly significant in comparison to the good prognosis group. Use of the parametric log-logistic model - also a proportional odds model - allowed assessment of the natural process of the disease based on hazard and identification of trends.

Landslide susceptibility mapping using Logistic Regression and Fuzzy Set model at the Boeun Area, Korea (로지스틱 회귀분석과 퍼지 기법을 이용한 산사태 취약성 지도작성: 보은군을 대상으로)

  • Al-Mamun, Al-Mamun;JANG, Dong-Ho
    • Journal of The Geomorphological Association of Korea
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    • v.23 no.2
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    • pp.109-125
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    • 2016
  • This study aims to identify the landslide susceptible zones of Boeun area and provide reliable landslide susceptibility maps by applying different modeling methods. Aerial photographs and field survey on the Boeun area identified landslide inventory map that consists of 388 landslide locations. A total ofseven landslide causative factors (elevation, slope angle, slope aspect, geology, soil, forest and land-use) were extracted from the database and then converted into raster. Landslide causative factors were provided to investigate about the spatial relationship between each factor and landslide occurrence by using fuzzy set and logistic regression model. Fuzzy membership value and logistic regression coefficient were employed to determine each factor's rating for landslide susceptibility mapping. Then, the landslide susceptibility maps were compared and validated by cross validation technique. In the cross validation process, 50% of observed landslides were selected randomly by Excel and two success rate curves (SRC) were generated for each landslide susceptibility map. The result demonstrates the 84.34% and 83.29% accuracy ratio for logistic regression model and fuzzy set model respectively. It means that both models were very reliable and reasonable methods for landslide susceptibility analysis.

A Study on RFID System Design and Expanded EPCIS Model for Manufacturing Systems (제조 시스템의 RFID System 설계 및 EPCIS 확장모형 연구)

  • Choi, Weon-Yong;Lee, Jong-Tae
    • Journal of the Korea Safety Management & Science
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    • v.9 no.6
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    • pp.123-135
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    • 2007
  • In the recent years, the companies have manually recorded a production status in a work diary or have mainly used a bar code in order to collect each process's progress status, production performance and quality information in the production and logistics process in real time. But, it requires an additional work because the worker's record must be daily checked or the worker must read it with the bar code scanner. At this time, data's accuracy is decreased owing to the worker's intention or mistake, and it causes the problem of the system's reliability. Accordingly, in order to solve such problem, the companies have introduced RFID which comes into the spotlight in the latest automatic identification field. In order to introduce the RFID technology, the process flow must be analyzed, but the ASME sign used by most manufacturing companies has the difficult problem when the aggregation event occurs. Hence, in this study, the RFID logistic flow analysis Modeling Notation was proposed as the signature which can analyze the manufacturing logistic flow amicably, and the manufacturing logistic flow by industry type was analyzed by using the proposed RFID logistic flow analysis signature. Also, to monitor real-time information through EPCglobal network, EPCISEvent template by industry was proposed, and it was utilized as the benchmarking case of companies for RFID introduction. This study suggested to ensure the decision-making on real-time information through EPCglobal network. This study is intended to suggest the Modeling Notation suitable for RFID characteristics, and the study is intended to establish the business step and to present the vocabulary.

Optimization of Agri-Food Supply Chain in a Sustainable Way Using Simulation Modeling

  • Vostriakova, Viktorija;Kononova, Oleksandra;Kravchenko, Sergey;Ruzhytskyi, Andriy;Sereda, Nataliia
    • International Journal of Computer Science & Network Security
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    • v.21 no.3
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    • pp.245-256
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    • 2021
  • Poor logistical infrastructure and agri-food supply chain management leads to significant food waste in logistic system. The concept of the sustainable value added agri-food chains requires defined approach to the analysis of the existing situation, possible improving strategies and also assessment of these changes impact on further development. The purpose of research is to provide scientific substantiation of theoretical and methodological principles and develop practical recommendations for the improvement of the agri-food logistics distribution system. A case study methodology is used in this article. The research framework is based on 4 steps: Value Stream Mapping (VSM), Gap and Process Analysis, Validation and Improvement Areas Definition and Imitation Modelling. This paper presents the appropriateness of LEAN logistics tools using, in particular, Value Stream Mapping (VSM) for minimizing logistic losses and Simulation Modeling of possible logistics distribution system improvement results. The algorithm of VSM analysis of the agri-food supply chain, which involves its optimization by implementing the principles of sustainable development at each stage, is proposed. The methodical approach to the analysis of possible ways for optimizing the operation of the logistics system of the agri-food distribution is developed. It involves the application of Value Stream Mapping, i.e. designing of stream maps of the creation of the added value in the agri-food supply chain for the current and future state based on the minimization of logistic losses. Simulation modeling of the investment project on time optimization in the agri-food supply chain and economic effect of proposed improvements in logistics product distribution system functioning at the level of the investigated agricultural enterprise has been determined. Improvement of logistics planning and coordination of operations in the supply chain and the innovative pre-cooling system proposed to be introduced have a 3-year payback period and almost 75-80% probability. Based on the conducted VSM analysis of losses in the agri-food supply chain, there have been determined the main points, where it is advisable to conduct optimization changes for the achievement of positive results and the significant economic effect from the proposed measures has been confirmed. In further studies, it is recommended to focus on identifying the synergistic effect of the agri-food supply chain optimization on the basis of sustainable development.