• International Journal of Computer Science & Network Security
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• v.23 no.7
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• pp.171-185
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• 2023

The cardiovascular syndrome is the dominant reason for death and the number of deaths due to this syndrome has greatly increased recently. Regular cardiac monitoring is crucial in controlling heart parameters, particularly for initial examination and precautions. The quantity of cardiac patients is rising each day and it would increase the load of work for doctors/nurses in handling the patients' situation. Hence, it needed a solution that might benefit doctors/nurses in monitoring the improvement of the health condition of patients in real-time and likewise assure decreasing medical treatment expenses. Regular heart monitoring via wireless body area networks (WBANs) including implantable and wearable medical devices is contemplated as a life-changing technique for medical assistance. This article focuses on the latest development in wearable and implantable devices for cardiovascular monitoring. First, we go through the wearable devices for the electrocardiogram (ECG) monitoring. Then, we reviewed the implantable devices for Blood Pressure (BP) monitoring. Subsequently, the evaluation of leading wearable and implantable sensors for heart monitoring mentioned over the previous six years, the current article provides uncertain direction concerning the description of diagnostic effectiveness, thus intending on making discussion in the technical communal to permit aimed at the formation of well-designed techniques. The article is concluded by debating several technical issues in wearable and implantable technology and their possible potential solutions for conquering these challenges.

• Journal of Internet Computing and Services
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• v.8 no.1
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• pp.1-14
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• 2007

IF handoff events are occurred during the transmission of multimedia traffic, the efficient resource allocation and handoff procedures are necessary to maintain the same QoS of transmitted multimedia traffic because the QoS may be defected by some delay and information loss, This paper proposes a handoff scheme to accommodate multimedia traffic based on the resource reservation procedure using direction estimation, This scheme uses a novel mobile tracking method based on Fuzzy Multi Criteria Decision Making, in which uncertain parameters such as PSS (Pilot Signal Strength), the distance between the mobile and the base station, the moving direction, and the previous location are used in the decision process using the aggregation function in fuzzy set theory, With the position information, the moving direction is determined, The handoff requests for real time sessions are handled based on the direction prediction and the resource reservation scheme, The resources in the estimated adjacent cells should be reserved and allocated to guarantee the continuity of the real time sessions, Through simulation results, we show that our proposed resource reservation method provides a better performance than that of the conventional method.

• The Journal of the Korea Contents Association
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• v.19 no.1
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• pp.132-140
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• 2019

Recently, many cities around the world introduced and operated shared bicycle system to reduce the traffic and air pollution. Seoul also provides shared bicycle service called as "Ddareungi" since 2015. As the use of shared bicycle increases, the demand for bicycle in each station is also increasing. In addition to the restriction on budget, however, there are managerial issues due to the different demands of each station. Currently, while bicycle rebalancing is used to resolve the huge imbalance of demands among many stations, forecasting uncertain demand at the future is more important problem in practice. In this paper, we develop forecasting model for demand for Seoul shared bicycle using statistical time series analysis and apply our model to the real data. In particular, we apply Holt-Winters method which was used to forecast electricity demand, and perform sensitivity analysis on the parameters that affect on real demand forecasting.

• Journal of the Korean Society of Systems Engineering
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• v.18 no.2
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• pp.75-93
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• 2022

Machine learning (ML) data-driven meta-model is proposed as a surrogate model to reduce the excessive computational cost of the physics-based model and facilitate the real-time prediction of a nuclear power plant's transient response. To forecast the transient response three machine learning (ML) meta-models based on recurrent neural networks (RNNs); specifically, Long Short Term Memory (LSTM), Gated Recurrent Unit (GRU), and a sequence combination of Convolutional Neural Network (CNN) and LSTM are developed. The chosen accident scenario is a control element assembly withdrawal at power concurrent with the Loss Of Offsite Power (LOOP). The transient response was obtained using the best estimate thermal hydraulics code, MARS-KS, and cross-validated against the Design and control document (DCD). DAKOTA software is loosely coupled with MARS-KS code via a python interface to perform the Best Estimate Plus Uncertainty Quantification (BEPU) analysis and generate a time series database of the system response to train, test and validate the ML meta-models. Key uncertain parameters identified as required by the CASU methodology were propagated using the non-parametric Monte-Carlo (MC) random propagation and Latin Hypercube Sampling technique until a statistically significant database (181 samples) as required by Wilk's fifth order is achieved with 95% probability and 95% confidence level. The three ML RNN models were built and optimized with the help of the Talos tool and demonstrated excellent performance in forecasting the most probable NPP transient response. This research was guided by the Systems Engineering (SE) approach for the systematic and efficient planning and execution of the research.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.2 no.2
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• pp.81-89
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• 2001

Space systems are operating in a changing and uncertain space environment and are desired to have autonomous capability for long periods of time without frequent telecommunications from the ground station At the same time. requirements for new set of projects/systems calling for ""autonomous"" operations for long unattended periods of time are emerging. Since, by the nature of space systems, it is desired that they perform their mission flawlessly and also it is of extreme importance to have fault-tolerant sensor/actuator sub-systems for the purpose of validating science measurement data for the mission success. Technology innovations attendant on autonomous data validation and health monitoring are articulated for a growing class of autonomous operations of space systems. The greatest need is on focus research effort to the development of a new class of fault-tolerant space systems such as attitude actuators and sensors as well as validation of measurement data from scientific instruments. The characterization for the next step in evolving the existing control processes to an autonomous posture is to embed intelligence into actively control. modify parameters and select sensor/actuator subsystems based on statistical parameters of the measurement errors in real-time. This research focuses on the identification/demonstration of critical technology innovations that will be applied to Autonomous Spacecraft Health Monitoring/Data Validation Control Systems (ASHMDVCS). Systems (ASHMDVCS).

• Journal of Astronomy and Space Sciences
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• v.28 no.2
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• pp.109-116
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• 2011

The first presented BV light curves of BH UMa confirmed Krajci's (2005) result that BH UMa is an RR Lyr star that belongs to the RRc subgroup. The light curves showed a slight asymmetry of D = 0.453 with an amplitude of about $0.^m58$ in B, $0.^m47$ in V, and $0.^m11$ in B-V and with a small hump between $0.^p82$ and $0.^p86$. We determined nine new times of minimum light and eight times of maximum light. We also analyzed all of the available unanalyzed minimum timings and found for the first time that the period of BH UMa has varied dramatically in at least three independent sinusoidal ways superposed on a secularly downward parabola over 66 years. The secular period decreasing rate was obtained as $6.^d684{\times}10^{-8}y^{-1}$, corresponding to -0.58 s/century. The semi-amplitude and period for each of the three sinusoidal variations were ($0.^d058$, $14.^y44$), ($0.^d044$, $9.^y98$), and ($0.^d005$, $0.^y97$), respectively. It is uncertain whether the periodicity for the shortest period of $0.^y97$ is real or spurious. The secular period decrease, well consistent with those of the other RRc stars, could be considered as a natural result of the evolution of the BH UMa system. The two possible sinusoidal terms were interpreted as both two light-time effects due to two additional bodies orbiting BH UMa and combinations of random fluctuations in the pulsation period of BH UMa. Two interpretations were shortly discussed with related parameters.

• Journal of applied mathematics & informatics
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• v.42 no.4
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• pp.831-854
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• 2024

The transportation problem (TP) is one of the earliest and the most significant implementations of linear programming problem (LPP). It is a specific type of LPP that mostly works with logistics and it is connected to day-to-day activities in our everyday lives. Nowadays decision makers (DM's) aim to reduce the transporting expenses and simultaneously aim to reduce the transporting time of the distribution system so the bi-objective transportation problem (BOTP) is established in the research. In real life, the transportation parameters are naturally uncertain due to insufficient data, poor judgement and circumstances in the environment, etc. In view of this, neutrosophic bi-objective transportation problem (NBOTP) is introduced in this paper. By introducing single-valued trapezoidal neutrosophic numbers (SVTrNNs) to the co-efficient of the objective function, supply and demand constraints, the problem is formulated. The DM's aim is to determine the optimal compromise solution for NBOTP. The extended weighted possibility mean for single-valued trapezoidal neutrosophic numbers based on [40] is proposed to transform the single-valued trapezoidal neutrosophic BOTP (SVTrNBOTP) into its deterministic BOTP. The transformed deterministic BOTP is then solved using the dripping method [10]. Numerical examples are provided to illustrate the applicability, effectiveness and usefulness of the solution approach. A sensitivity analysis (SA) determines the sensitivity ranges for the objective functions of deterministic BOTP. Finally, the obtained optimal compromise solution from the proposed approach provides a better result as compared to the existing approaches and conclusions are discussed for future research.

• Korean System Dynamics Review
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• v.2 no.2
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• pp.25-40
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• 2001

This paper describes the forecast of power plant construction in a competitive korean electricity market. In Korea, KEPCO (Korea Electric Power Corporation, fully controlled by government) was responsible for from the production of the electricity to the sale of electricity to customer. However, the generation part is separated from KEPCO and six generation companies were established for whole sale competition from April 1st, 2001. The generation companies consist of five fossil power companies and one nuclear power company in Korea at present time. Fossil power companies are scheduled to be sold to private companies including foreign investors. Nuclear power company is owned and controlled by government. The competition in generation market will start from 2003. ISO (Independence System Operator will purchase the electricity from the power exchange market. The market price is determined by the SMP(System Marginal Price) which is decided by the balance between demand and supply of electricity in power exchange market. Under this uncertain circumstance, the energy policy planners such as government are interested to the construction of the power plant in the future. These interests are accelerated due to the recent shortage of electricity supply in California. In the competitive market, investors are no longer interested in the investment for the capital intensive, long lead time generating technologies such as nuclear and coal plants. Large unclear and coal plants were no longer the top choices. Instead, investors in the competitive market are interested in smaller, more efficient, cheaper, cleaner technologies such as CCGT(Combined Cycle Gas Turbine). Electricity is treated as commodity in the competitive market. The investors behavior in the commodity market shows that the new investment decision is made when the market price exceeds the sum of capital cost and variable cost of the new facility and the existing facility utilization depends on the marginal cost of the facility. This investors behavior can be applied to the new investments for the power plant. Under these postulations, there is the potential for power plant construction to appear in waves causing alternating periods of over and under supply of electricity like commodity production or real estate production. A computer model was developed to sturdy the possibility that construction will appear in waves of boom and bust in Korean electricity market. This model was constructed using System Dynamics method pioneered by Forrester(MIT, 1961) and explained in recent text by Sternman (Business Dynamics, MIT, 2000) and the recent work by Andrew Ford(Energy Policy, 1999). This model was designed based on the Energy Policy results(Ford, 1999) with parameters for loads and resources in Korea. This Korea Market Model was developed and tested in a small scale project to demonstrate the usefulness of the System Dynamics approach. Korea electricity market is isolated and not allowed to import electricity from outsides. In this model, the base load such as unclear and large coal power plant are assumed to be user specified investment and only CCGT is selected for new investment by investors in the market. This model may be used to learn if government investment in new unclear plants could compensate for the unstable actions of private developers. This model can be used to test the policy focused on the role of unclear investments over time. This model also can be used to test whether the future power plant construction can meet the government targets for the mix of generating resources and to test whether to maintain stable price in the spot market.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.39 no.8
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• pp.751-758
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• 2015

Mathematical models are actively used to reduce the experimental expenses required to understand physical phenomena. However, they are different from real phenomena because of assumptions or uncertain parameters. In this study, we present a calibration and validation method using a paper helicopter and statistical methods to quantify the uncertainty. The data from the experiment using three nominally identical paper helicopters consist of different groups, and are used to calibrate the drag coefficient, which is an unknown input parameter in both analytical models. We predict the predicted fall time data using probability distributions. We validate the analysis models by comparing the predicted distribution and the experimental data distribution. Moreover, we quantify the uncertainty using the Markov Chain Monte Carlo method. In addition, we compare the manufacturing error and experimental error obtained from the fall-time data using Analysis of Variance. As a result, all of the paper helicopters are treated as one identical model.