• Journal of the Korean Data and Information Science Society
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• v.17 no.3
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• pp.743-752
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• 2006

This paper considers a Bayesian approach to replacement policy model with minimal repair. We use the criterion based on the expected cost and the expected downtime to determine the optimal replacement period. To do so, we obtain the expected cost rate per unit time and the expected downtime per unit time, respectively. When the failure time is Weibull distribution with uncertain parameters, a Bayesian approach is established to formally express and update the uncertain parameters for determining an optimal maintenance policy. Especially, the overall value function suggested by Jiagn and Ji(2002) is applied to obtain the optimal replacement period. The numerical examples are presented for illustrative purpose.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.9
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• pp.3401-3420
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• 2021

We provide a traceable ciphertext-policy attribute based encryption (CP-ABE) construction for monotone access structures (MAS) based on composite order bilinear groups, which is secure adaptively under the standard model. We construct this scheme by making use of an "encoding technique" which represents the MAS by their minimal sets to encrypt the messages. To date, for all traceable CP-ABE schemes, their encryption costs grow linearly with the MAS size, the decryption costs grow linearly with the qualified rows in the span programs. However, in our traceable CP-ABE, the ciphertext is linear with the minimal sets, and decryption needs merely three bilinear pairing computations and two exponent computations, which improves the efficiency extremely and has constant decryption. At last, the detailed security and traceability proof is given.

• Kyungpook Mathematical Journal
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• v.63 no.1
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• pp.131-139
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• 2023

Let V_k,n (ℂ) denote the complex Steifel and Gr_k,n (ℂ) the Grassmann manifolds for 1 ≤ k < n. In this paper, we compute, in terms of the Sullivan minimal models, the evaluation subgroups and, more generally, the relative evaluation subgroups of the fibration p : V_k,k+n (ℂ) → Gr_k,k+n (ℂ). In particular, we prove that G_* (Gr_k,k+n (ℂ), V_k,k+n (ℂ) ; p) is isomorphic to G^rel_* (Gr_k,k+n (ℂ), V_k,k+n (ℂ) ; p) ⊕ G_* (V_k,k+n (ℂ)).

• Journal of Information Technology Applications and Management
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• v.21 no.4_spc
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• pp.485-499
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• 2014

Sharing Economy is the modern main item with ICT Development. Of course sharing economic item is the old and long run mainstream, but by the ICT technological development sharing economy is the fostering and affluent factors in the world economic growth. Though, in Korea, till now sharing economy is minimal, that will growth sharply. We can track various business models of sharing economy. Sharing economy is to buy use right not ownership. With the sharing economic business model wee can make also financial sharing model. In finance model we can divide two kind models. First, we can trace small size lending model with p2p type. And second, we can make financial information transaction model. But till now sharing economic system is not activated, because of many reasons. To activate, first we have to set law and various standards, and also government actively support many sharing economy firms and institutions. To catch up developed countries in the field of sharing economy we have to make aggressive and flexible rules and standards.

• Journal of Applied Reliability
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• v.18 no.2
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• pp.104-113
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• 2018

Purpose: This paper proposes the non-periodic preventive maintenance policy based on the level of cumulative hazard intensity. We aim to construct a cost-effectiveness on the proposed model with relaxing the constraint on reliability. Methods: We use the level of cumulative hazard intensity as a condition variable, instead of reliability. Such a level of cumulative hazard intensity can derive the reliability which decreases as the frequency of preventive maintenance action increases. We also model the imperfect preventive maintenance action using the proportional age setback model. Conclusion: We provide a numerical example to illustrate the proposed model. We also analyze how the parameters of our model affect the optimal preventive maintenance policy. The results show that as long as high reliability is guaranteed, the inefficient preventive maintenance action is performed reducing the system operation time. Moreover, the optimal value of the proposed model is sensitive to changes in preventive maintenance cost and replacement cost.

• Journal of the Korean Data and Information Science Society
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• v.14 no.2
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• pp.393-403
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• 2003

In this paper, various replacement policies for the general failure model are considered. There are two types of failure in the general failure model. One is Type I failure (minor failure) which can be removed by a minimal repair and the other is Type II failure (catastrophic failure) which can be removed only by a complete repair. In this model, when the unit fails at its age t, Type I failure occurs with probability 1-p(t) and Type II failure occurs with probability p(t), $0{\leq}p(t){\leq}1$. Under the model, optimal replacement policies for the long-run average cost rate and the limiting efficiency are considered. Also taking the cost and the efficiency into consideration at the same time, the properties of the optimal policies under the Cost-Priority-Criterion and the Efficiency-Priority-Criterion are obtained.

• Journal of the Korean Operations Research and Management Science Society
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• v.24 no.2
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• pp.1-15
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• 1999

This research involves the development and evaluation of a work flow control model for a type of flexible manufacturing system(FMS) called a flexible flow line(FFL). The control model can be considered as a kind of hybrid intelligent model in that it utilizes both computer simulation and neural network technique. Training data sets were obtained using computer simulation of typical FFL states. And these data sets were used to train the neural network model. The model can easily incorporate particular aspects of a specific FFL such as limited buffer capacity and dispatching rules used. It also dynamically adapts to system uncertainty caused by such factors as machine breakdowns. Performance of the control model is shown to be superior to the random releasing method and the Minimal Part Set(MPS) heuristic in terms of machine utilization and work-in-process inventory level.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.29 no.3
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• pp.135-142
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• 2006

Engineers are always concerned with life cycle costs for making important economic decisions through engineering action like reliability of products. Decisions during the reliability growth development of products involve trade-offs between invested costs and its returns. In order to find minimal LCC containing the reliability improvement cost, production cost, repair and replacement costs, and holding cost of spare parts for failure items we suggest in this paper relationship between development cost and sustaining cost in values of growth parameter $\beta$ of AMSAA model. This model is applied to the reliability growth program based on AMSAA model during R&D phase, the warranty activities of items and the block replacement policy for maintenance of items in avionic equipment.

• IMMUNE NETWORK
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• v.5 no.1
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• pp.36-44
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• 2005

Background: The anti-tumor therapeutic effect of autologous tumor cell lysate pulseddendritic cells (DCs) was studied for non-immunogenic and immune suppressive lung cancer model. To test the possibility as an adjuvant therapy, minimal residual disease model was considered in mouse in vivo experiments. Methods: Syngeneic 3LL lung cancer cells were inoculated intravenously into the C57BL/6 mouse. Autologous tumor cell (3LL) or allogeneic leukemia cell (WEHI-3) lysate pulsed-DCs were injected twice in two weeks. Intraperitoneal DC injection was started one day (MRD model) after tumor cell inoculation. Two weeks after the final DC injection, tumor formation in the lung and the tumor-specific systemic immunity were observed. Tumor-specific lymphocyte proliferation and the IFN-${\gamma}$ secretion were analyzed for the immune monitoring. Therapeutic DCs were cultured from the bone marrow myeloid lineage cells with GM-CSF and IL-4 for 7 days and pulsed with tumor cell lysate for 18 hrs. Results: Compared to the saline treated group, tumor formation was suppressed in 3LL tumor cell lysate pulsed-DC treated group, while 3LL-specific immune stimulation was minimum. WEHI-3-specific immune stimulation occurred in WEHI-3 lysate-pulsed DC treated group, which had no correlation with tumor regression. Conclusion: The data suggest the possible anti-tumor effect of cultured DCs as an adjuvant therapy for minimal residual disease state of lung cancer. The significance of immune modulation in DC therapy including the possible involvement of NK cell as well as antigen-specific cytotoxic T cell activity induction was discussed.

• Korean Journal of Chemical Engineering
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• v.35 no.12
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• pp.2327-2335
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• 2018

Fluid catalytic cracking (FCC) is an important chemical process that is widely used to produce valuable petrochemical products by cracking heavier components. However, many difficulties exist in modeling the FCC process due to its complexity. In this study, a dynamic process model of a FCC process is suggested and its structural observability is analyzed. In the process modeling, yield function for the kinetic model of the riser reactor was applied to explain the product distribution. Hydrodynamics, mass balance and energy balance equations of the riser reactor and the regenerator were used to complete the modeling. The process model was tested in steady-state simulation and dynamic simulation, which gives dynamic responses to the change of process variables. The result was compared with the measured data from operating plaint. In the structural analysis, the system was analyzed using the process model and the process design to identify the structural observability of the system. The reactor and regenerator unit in the system were divided into six nodes based on their functions and modeling relationship equations were built based on nodes and edges of the directed graph of the system. Output-set assignment algorithm was demonstrated on the occurrence matrix to find observable nodes and variables. Optimal locations for minimal addition of measurements could be found by completing the whole output-set assignment algorithm of the system. The result of this study can help predict the state more accurately and improve observability of a complex chemical process with minimal cost.