• Journal of Radiation Protection and Research
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• v.45 no.3
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• pp.117-129
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• 2020

Background: Radiation portal monitors (RPMs) involving plastic scintillators installed at the border inspection sites can detect illicit trafficking of radioactive sources in cargo containers within seconds. However, RPMs may generate false alarms because of the naturally occurring radioactive materials. To manage these false alarms, we previously suggested an energy-weighted algorithm that emphasizes the Compton-edge area as an outstanding peak. This study intends to evaluate the identification of radioactive sources using an improved energy-weighted algorithm. Materials and Methods: The algorithm was modified by increasing the energy weighting factor, and different peak combinations of the energy-weighted spectra were tested for source identification. A commercialized RPM system was used to measure the energy-weighted spectra. The RPM comprised two large plastic scintillators with dimensions of 174 × 29 × 7 ㎤ facing each other at a distance of 4.6 m. In addition, the in-house-fabricated signal processing boards were connected to collect the signal converted into a spectrum. Further, the spectra from eight radioactive sources, including special nuclear materials (SNMs), which were set in motion using a linear motion system (LMS) and a cargo truck, were estimated to identify the source identification rate. Results and Discussion: Each energy-weighted spectrum exhibited a specific peak location, although high statistical fluctuation errors could be observed in the spectrum with the increasing source speed. In particular, ¹³⁷Cs and ⁶⁰Co in motion were identified completely (100%) at speeds of 5 and 10 km/hr. Further, SNMs, which trigger the RPM alarm, were identified approximately 80% of the time at both the aforementioned speeds. Conclusion: Using the modified energy-weighted algorithm, several characteristics of the energy weighted spectra could be observed when the used sources were in motion and when the geometric efficiency was low. In particular, the discrimination between ⁶⁰Co and ⁴⁰K, which triggers false alarms at the primary inspection sites, can be improved using the proposed algorithm.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.7
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• pp.3-9
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• 2013

This paper proposes a selective-weighted energy detection (S-WED) and a synchronization algorithm appropriate for it in IR-UWB system. Energy detectors that are practical in terms of implementation are employed widely for noncoherent reception in IR-UWB systems. However, they show low performance due to using the energy samples captured at symbol rate. For this reason, weighted energy detectors are developed to improve the performance of EDs. Hence, for WED, not only synchronization but also the weight coefficients are needed to be obtained prior to data detection. Meanwhile, the optimal weighting coefficients of WEDs are known to be energy values. Therefore, synchronization and the weighting coefficients can be obtained simultaneously. This paper proposes an S-WED and a simple synchronization algorithm for it in which sub-intervals having energies under a certain level are excluded in energy accumulation resulting in a simpler WED with a bit performance increase in low SNR region. The proposed algorithm is verified through simulations using the preamble symbol and channel models defined in the IEEE 802.15.4a.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.12 no.6
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• pp.609-615
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• 2000

The energy conservation is one of the most important issues in recent years. Especially, the energy conservation through improved control strategies is one of the most highly possible area to be implemented in the near future. The energy conservation of the ice storage system can be accomplished through the improved control strategies. A real time building load prediction algorithm was developed. The expected highest and the lowest outdoor temperature of the next day were used to estimate the next day outdoor temperature profile. The measured dry bulb temperature and the measured building load were used to estimate system parameters by using the on-line weighted recursive least square method. The estimated hourly outdoor temperatures and the estimated hourly system parameters were used to predict the next day hourly building loads. In order to see the effectiveness of the building load prediction algorithm, two different types of building models were selected and analysed. The simulation results show less than 1% in error for the prediction of the next day building loads. Therefore, this algorithm may successfully be used for the development of improved control algorithms of the ice storage system.

• Journal of international Conference on Electrical Machines and Systems
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• v.3 no.2
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• pp.229-234
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• 2014

In this paper, a design problem of the flywheel energy storage system controller using genetic algorithm (GA) is investigated for a frequency control of the wind diesel hybrid power generation system in an isolated power system. In order to select parameters of the FESS controller, two performance indexes are used. We evaluated a frequency control effect for the wind diesel hybrid power system according to change of the weighted values of a performance index. To verify performance of the FESS controller according to the weighted value of the performance index, the frequency domain analysis using a singular value bode diagram and the dynamic simulations for various weighted values of performance index were performed. To verify control performance of the designed FESS controller, the eigenvalue analysis and the dynamic simulations were performed. The control characteristics with the two designed FESS controller were compared with that of the conventional pitch controller. The simulation results showed that the FESS controller provided better dynamic responses in comparison with the conventional controller.

• Nuclear Engineering and Technology
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• v.55 no.11
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• pp.4282-4286
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• 2023

Nuclear energy is estimated by the machine learning method as the mathematical quantifications where neural networking is the major algorithm of the data propagations from input to output. As the aspect of nuclear energy, the other energy sources of the traditional carbon emission-characterized oil and coal are compared. The artificial intelligence (AI) oriented algorithm like the intelligence of a robot is applied to the modeling in which the mimicking of biological neurons is utilized in the mathematical calculations. There are graphs for nuclear priority weighted by climate factor and for carbon dioxide mitigation weighted by climate factor in which the carbon dioxide quantities are divided by the weighting that produces some results. Nuclear Priority and CO2 Mitigation values give the dimensionless values that are the comparative quantities with the normalization in 2010. The values are 1.0 in 2010 of the graphs which are changed to 24.318 and 0.0657 in 2040, respectively. So, the carbon dioxide emissions could be reduced in this study.

• Journal of Korea Multimedia Society
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• v.10 no.7
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• pp.893-901
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• 2007

Since real-time multimedia applications requiring duality-of-service guarantees are spreading over mobile and wireless networks, energy efficiency in wireless channels is becoming more important. Energy consumption in the channels can be reduced with decreasing the rate of scheduler's outgoing link by means of Dynamic Modulation Scaling (DMS). This paper proposes a fair queuing algorithm, termed Rate Efficient Fair Queuing (REFQ), in order to reduce the outgoing link's rate, which is based on the Latency-Optimized Fair Queuing algorithm developed to enhance Weighted Fair Queuing (WFQ). The performance evaluation result shows that REFQ does decrease the link rate by up to 35% in comparison with that in WFQ, which results in reducing the energy consumption by up to 90% when applied to the DMS based radio modem.

• Nuclear Engineering and Technology
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• v.55 no.10
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• pp.3907-3912
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• 2023

Radiation portal monitors (RPMs) installed at airports and harbors to prevent illicit trafficking of radioactive materials generally use large plastic scintillators. However, their energy resolution is poor and radionuclide identification is nearly unfeasible. In this study, to improve isotope identification, a RPM system based on a multi-array plastic scintillator and convolutional neural network (CNN) was evaluated by measuring the spectra of radioactive sources. A multi-array plastic scintillator comprising an assembly of 14 hexagonal scintillators was fabricated within an area of 50 × 100 cm². The energy spectra of ¹³⁷Cs, ⁶⁰Co, ²²⁶Ra, and ⁴K (KCl) were measured at speeds of 10-30 km/h, respectively, and an energy-weighted algorithm was applied. For the CNN, 700 and 300 spectral images were used as training and testing images, respectively. Compared to the conventional plastic scintillator, the multi-arrayed detector showed a high collection probability of the optical photons generated inside. A Compton maximum peak was observed for four moving radiation sources, and the CNN-based classification results showed that at least 70% was discriminated. Under the speed condition, the spectral fluctuations were higher than those under dwelling condition. However, the machine learning results demonstrated that a considerably high level of nuclide discrimination was possible under source movement conditions.

• Journal of Information Processing Systems
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• v.11 no.2
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• pp.205-228
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• 2015

In this paper, we present a virtual laboratory platform (VLP) baptized Mercury allowing students to make practical work (PW) on different aspects of mobile wireless sensor networks (WSNs). Our choice of WSNs is motivated mainly by the use of real experiments needed in most courses about WSNs. These experiments require an expensive investment and a lot of nodes in the classroom. To illustrate our study, we propose a course related to energy efficient and safe weighted clustering algorithm. This algorithm which is coupled with suitable routing protocols, aims to maintain stable clustering structure, to prevent most routing attacks on sensor networks, to guaranty energy saving in order to extend the lifespan of the network. It also offers a better performance in terms of the number of re-affiliations. The platform presented here aims at showing the feasibility, the flexibility and the reduced cost of such a realization. We demonstrate the performance of the proposed algorithms that contribute to the familiarization of the learners in the field of WSNs.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.41 no.3
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• pp.37-45
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• 2004

In this paper we propose Clustered Group Multicast by Clustering Algorithm in Wireless Mobile Ad-hoc Network. The proposed scheme applies to Weighted Cluster Algorithm Ad-hoc network is a collection of wireless mobile hosts forming a temporary network without the aid of any centralized administration or reliable support services such as wired network and base station. In ad hoc network muting protocol because of limited bandwidth and high mobility robust, simple and energy consume minimal. WCGM method uses a base structure founded on combination weighted value and applies combination weight value to cluster header keeping data transmission by seeped flooding, which is the advantage of the exiting FGMP method. Because this method has safe and reliable data transmission, it shows the effect to decrease both overhead to preserve transmission structure and overhead for data transmission.

• Journal of Communications and Networks
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• v.18 no.4
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• pp.629-638
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• 2016

In this paper, we investigate an energy-efficient resource allocation problem in a two-way relay (TWR) network consisting of multiple user pairs and an amplify-and-forward (AF) relay. As the users and relay have individual energy efficiencies (EE), we formulate a multi-objective optimization problem (MOOP). A single-objective optimization problem (SOOP) of the MOOP is introduced using a weighted-sum method, which achieves a single Pareto optimal point of the MOOP. To derive the algorithm for the SOOP, we propose a more tractable equivalent problem using the Karush-Kuhn-Tucker conditions of the SOOP, which guarantees convergence at the local optimal points. The proposed equivalent problem can be efficiently solved by the proposed iterative algorithm. Numerical results demonstrate the effectiveness of the proposed algorithm in achieving the optimal EE in multi-user AF TWR networks.