• Proceedings of the KIPE Conference
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• 2016.07a
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• pp.34-35
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• 2016

This study is to minimize the damage and fire early warning and research on mobile communications network of the emergency fire alarm system based on the IoT to the transmission in real time. The spread of such systems can be expected to businesses expand to technology that can replace or complement existing fire fighting system, it is also expected to a large ripple effect as an important technology that can minimize the damage to real-time detect the ignition point.

• Environmental Analysis Health and Toxicology
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• v.25 no.1
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• pp.1-10
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• 2010

Monitoring toxicity levels in specific biological compartments is necessary to evaluate the ecotoxicological risk associated with soil environmental pollution. Gene expression, as potential biomarker, is increasingly used as rapid early warning systems in environmental monitoring and ecological risk assessment procedures. Various representative species are currently used for the purpose of assessing soil toxicity, however, investigations on toxicological assessments using endpoint based on gene-level have been limited. In this review, we will present the current trends in organisms and endpoints used in soil toxicity study and report gene expression related to toxicity using soil organism, and C. elegans as promising organisms for this approach.

• Journal of Advanced Navigation Technology
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• v.6 no.3
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• pp.211-222
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• 2002

This paper describes the utility of satellite sensors of the missile defense system using the estimation theory. The inherent flight characteristics of the missiles give the limitations in the response time and the countermeasures. In this point, the early warning and surveillance satellites are important. Using the Extended Kalman Filter, it is analysed LPU and MLU in DSP and SBIRS satellites, and presented the quantitative uncertainties of state estimates of non-rotational DSP compare to the rotating one.

• Journal of Intelligence and Information Systems
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• v.9 no.2
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• pp.135-154
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• 2003

Credit scoring system (CSS) starts from an analysis of delinquency trend of each individual or industry. This paper conducts a research on credit card delinquency of bank customers as a preliminary step for building effective credit scoring system to prevent excess loan or bad credit status. To serve this purpose, we use association rules as a rule generating data mining technique. Specifically, we generate sets of rules of customers who are in bad credit status because of delinquency by association rule mining. We expect that the sets of rules generated by association rule mining could act as an estimator of good or bad credit status classifier and basic component of early warning system.

• THE INTERNATIONAL COMMERCE & LAW REVIEW
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• v.27
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• pp.215-232
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• 2005

China had revised Foreign Trade Law in order to fulfill its WTO commitments and duties, and fully exercise its rights and benefits as a WTO member. The main contents of the revised Foreign Trade Law as followed. For the first time, individuals are allowed to conduct foreign trade. Intellectual property is an important component of foreign trade, and protecting intellectual property rights is a key issue. A chapter on Intellectual property protection is one of the major additions to the Foreign Trade Law. New sections have also been added to allow and provide guidance for conducting investigations and seeking relief. Finally, the new law beefs up and clarifies enforcement procedures. It regulates the setting up of early warning and emergency systems and a foreign trade statistics system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.5
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• pp.999-1012
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• 2011

This paper proposes an algorithm that enables mobile nodes to implement self-regulated movements in mobile ad-hoc networks (MANETs). It is important for mobile nodes to maintain a certain level of network-based stability by harmonizing these nodes' movements autonomously due to their limited transmission range and dynamic topology. Entropy methods based on relative position are suggested, as a means for mobile nodes to regulate their local movements. Simulations show that an early warning mechanism is suitable to maintain movement-based stability. Isolation can be reduced by 99%, with an increased network cost of 12% higher power consumption, using the proposed algorithm.

• Journal of Korean Society for Quality Management
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• v.22 no.4
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• pp.40-58
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• 1994

Some systems such as early warning system should be inspected occasionally in order to detect failures. If the system is inspected too frequently, inspection cost increases. On the other hand, if the number of inspections is reduced too much, the undetected system downtime cost increases. Thus, it is of interest to find effective inspection schedule, which minimizes the sum of inspection and downtime costs. When the system has increasing failure rate, inspection intervals get shorter as time goes on. But a common practice is to inspect the system at predetermined periodic intervals. In this paper, periodic inspection policy and a modified periodic inspection policy are considered. The modified policy is easily applicable and cost-effective. Some numerical examples are included in order to explain the modified inspection ploicy and its cost performance.

• Journal of Information Processing Systems
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• v.18 no.4
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• pp.500-509
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• 2022

With the rapid development of educational informatization, teaching methods become diversified characteristics, but a large number of information data restrict the evaluation on teaching subject and object in terms of the effect of English education. Therefore, this study adopts the concept of incremental learning and eigenvalue interval algorithm to improve the weighted decision tree, and builds an English education effect evaluation model based on association rules. According to the results, the average accuracy of information classification of the improved decision tree algorithm is 96.18%, the classification error rate can be as low as 0.02%, and the anti-fitting performance is good. The classification error rate between the improved decision tree algorithm and the original decision tree does not exceed 1%. The proposed educational evaluation method can effectively provide early warning of academic situation analysis, and improve the teachers' professional skills in an accelerated manner and perfect the education system.

• ETRI Journal
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• v.45 no.3
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• pp.379-393
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• 2023

Underwater communication (UWC) is widely used in coastal surveillance and early warning systems. Precise channel estimation is vital for efficient and reliable UWC. The sparse direct-adaptive filtering algorithms have become popular in UWC. Herein, we present an improved adaptive convex-combination method for the identification of sparse structures using a reweighted normalized leastmean-square (RNLMS) algorithm. Moreover, to make RNLMS algorithm independent of the reweighted l₁-norm parameter, a modified sparsity-aware adaptive zero-attracting RNLMS (AZA-RNLMS) algorithm is introduced to ensure accurate modeling. In addition, we present a quantitative analysis of this algorithm to evaluate the convergence speed and accuracy. Furthermore, we derive an excess mean-square-error expression that proves that the AZA-RNLMS algorithm performs better for the harsh underwater channel. The measured data from the experimental channel of SPACE08 is used for simulation, and results are presented to verify the performance of the proposed algorithm. The simulation results confirm that the proposed algorithm for underwater channel estimation performs better than the earlier schemes.

• Journal of the Korean Society of Marine Environment & Safety
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• v.23 no.1
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• pp.91-97
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• 2017

This study contains research on a bio-monitoring system (BMS) capable of detecting abnormal high water temperatures, the shell valve movements (SVMs) of Pacific oysters (Crassostrea gigas), which were measured at four different temperature (5, 10, 20 and $30^{\circ}C$) under laboratory conditions. All the Pacific oysters were kept under fasting conditions for 3 days to prevent the influence of food and excretions before the onset of the experiments. SVMs did not detect at $5^{\circ}C$. However, SVMs increased with an increase in temperature (at $10^{\circ}C$ : $6.31{\pm}2.18times/hr$ and at $20^{\circ}C$: $22.0{\pm}10.0times/hr$). At $30^{\circ}C$, SVMs were divided into two groups: those with no SVMs as at $5^{\circ}C$ and those with SVMs similar to conditions at $20^{\circ}C$($23.9{\pm}9.35times/hr$). This indicates oyster shells maintain a closed condition due to a decrease in metabolism at $30^{\circ}C$, although some Pacific oysters had active SVMs due to an increase in metabolism. If a BMS using the SVM status of Pacific oysters was installed to monitor abnormal high water around oyster farms, early warning levels and serious alerts might be made available more rapidly for SVMs of more than ca. 30 times/hr and closing conditions in a matter of hours, respectively. Therefore, a BMS using the SVMs of Pacific oysters might be an effective early warning system for abnormal high water temperatures.