• Journal of information and communication convergence engineering
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• v.13 no.4
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• pp.221-227
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• 2015

Spectrum sensing plays an essential role in a cognitive radio network, which enables opportunistic access to an underutilized licensed spectrum. In conventional cooperative spectrum sensing (CSS), all cognitive users (CUs) in the network spend the same amount of time on spectrum sensing and waste time in remaining silent when other CUs report their sensing results to the fusion center. This problem is solved by the superposition cooperative spectrum sensing (SPCSS) scheme, where the sensing time of a CU is extended to the reporting time of the other CUs. Subsequently, SPCSS assigns the CUs different sensing times and thus affects both the sensing performance and the throughput of the system. In this paper, we propose an algorithm to determine the optimal sensing time of each CU for SPCSS that maximizes the achieved system throughput. The simulation results prove that the proposed scheme can significantly improve the throughput of the cognitive radio network compared with the conventional CSS.

• Journal of the Ergonomics Society of Korea
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• v.20 no.3
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• pp.1-9
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• 2001

In the present study, the correlation between subjective assessment and EEG for essential odors were investigated quantitatively. EEG signals were measured from 19 electrodes according to the International 10-20 system (Fp1, Fp2, F3/4, F7/8, Fz, C3/4, Cz, P3/4, Pz, T3/4, T5/6, O1/2) from 8 healthy males subjects for four odor(Rose oil bulgarian, Lemon oil misitano, jasmin abs, Laverder oil france (KIMEX co. Ltd) conditions. The result of the subjective assessment shows the most pleasant odor for each subject. and the power spectrum of ${\alpha}/({\alpha}+{\beta})$ of EEG signals from the most pleasant odor was compared with those from the control condition, which has no odor at all. Power spectrum of ${\alpha}/({\alpha}+{\beta})$ of EEG from the most pleasant odor was increased significantly at T4, T6 compared to the control condition. This result implies that the parameter, power spectrum of ${\alpha}/({\alpha}+{\beta})$, could be an important index for signifying the levels of pleasantness for odors.

• Electronics and Telecommunications Trends
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• v.37 no.5
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• pp.70-81
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• 2022

This study derived implications regarding competition policy to establish a reasonable spectrum allocation draft of a 3.7 GHz spectrum band by indepth analysis of 5G spectrum auctions. The following general features were identified by examining auctions of three countries, including the United States, United Kingdom, and Denmark, were completed in 2021. First, securing the minimum bandwidth that is essential for service competition was guaranteed by applying the spectrum cap. Second, a continuous spectrum band was allocated to all mobile network operators. Third, certain requirements were implemented to encourage the expansion of 5G service coverage. The spectrum cap that was implemented in Korea during the most recent spectrum auction was ineffective regarding competition policy. Additionally, it is anticipated that the allocation of 3.7-4.0 GHz spectrum will considerably impact market competition because the continuity of spectrum band is different among mobile service operators. Therefore, it is time to discuss promoting the 5G service competition in Korea by revising related laws.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.48 no.2
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• pp.43-48
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• 2011

Cognitive radio is accepted as an effective and promising approach for resolving the spectrum scarcity problem by allowing secondary users to borrow unused spectrum from primary users. A method of identifying busy and empty spectrum at the given time and space, which is called spectrum sensing, constitutes an essential element of the cognitive radio. In this paper, we propose a receiver-centric spectrum sensing scheme which attempts to detect the primary receiver rather than the primary transmitter. It is shown that the proposed receiver-centric sensing approach results in more efficient spectrum utilization than the conventional transmitter-centric sensing.

• Journal of the Korean Society of Tobacco Science
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• v.4 no.2
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• pp.67-73
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• 1982

Essential oil components from tobacco powder were investigated as flavouring agent. The essential oil was isolated from tobacco powder by a simple distillation /extraction method The extracted essential oil was fractionated into basic, acidic and neutral groups. And the neutral group of essential oil was separated by column chromatography into 10 fractions. Above groups and fractions were tested for tobacco aroma and smoke aroma. The neutral group except most nonpolar fraction displays good flavouring properties which make them highly suitable for improving the flavour and aroma of tobacco and tobacco smoke. The most nonpolar fraction from neutral group was carefully investigated using preparative column, thin layer and gas chromatography ailed by GC/MS coupling. The major subfraction was identified as hydrocarbons on the basis of the IR spectrum. The 58 hydrocarbon components were identified by their mass spectra and was chromatographic retention times.

• Journal of Pharmacopuncture
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• v.11 no.1
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• pp.177-187
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• 2008

Objectives : This study was performed to analyze the effective components of essential oil obtained from Yongdamsagantang, which has been efficacious against leukorrhea in gynecologic diseases. Methods : I obtained the essential oils of Yongdamsagan-tang by hydrodistillation extraction method and supercritical fluid extraction(SFE) method, and then I analyzed those by GC/MS(Gas Chromatography/Mass Spectrum). Results : 1. The optimum SFE(Supercritical Fluid Extraction) condition was obtained in the following experiment conditions: pressure 200atm, temperature $45^{\circ}C$, duration of extraction 25minutes. 2. With GC(Gas Chromatography) and GC/MS(Gas Chromato- graphy/Mass Spectrum) analysis, I identified 37 compounds in the Yongdamsagan-tang's essential oil obtained through the SFE method. The main compounds were as follows : 3-Methyl-but-2-enoic acid,2,2-dimethyl-8-oxo-3,4-dihydro-2H,8H -pyrano[3,2-g]chromen-3-yl ester(49.81%), (Z)-6-Pentadecen-1 -ol(3.19%), (-)-Spathulenol(2.40%). 3. I identified 4 compounds in the Yongdamsagan-tang's essential oil obtained through the hydrodistillation method. The main compounds were as follows : 3-Methyl-but-2-enoic acid, 2,2-dimethyl-8-oxo-3,4-dihydro-2H,8H-pyrano [3,2-g]chromen-3-yl ester(2.61%). 4. 3-Methy I-but-2-enoic acid, 2,2-dimethyl-8-oxo-3,4-dihydro-2H,8H-pyrano[3,2-g] chromen-3-yl ester, all were identified in both the SFE method and the hydrodistillation method, but the others were not identified in common. 5. I also conducted an additional test in order to examine the essential oil's antimicrobial action against bacteria. Both MIC(Minimum Inhibitory Concentrations) and MBC(Minimum Bactericidal Concentrations) were $0.125mg/m{\ell}$ against N. meningitidis, however MIC and MBC were $1.0mg/m{\ell}$ in antimicrobial action against 12 different genera of bacteria.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.6
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• pp.2128-2147
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• 2021

Cognitive radio systems are being implemented recently to tackle spectrum underutilization problems and aid efficient data traffic. Spectrum sensing is the crucial step in cognitive applications in which cognitive user detects the presence of primary user (PU) in a particular channel thereby switching to another channel for continuous transmission. In cognitive radio systems, the capacity to precisely identify the primary user's signal is essential to secondary user so as to use idle licensed spectrum. Based on the inherent capability, a new spectrum sensing technique is proposed in this paper to identify all types of primary user signals in a cognitive radio condition. Hence, a spectrum sensing algorithm using improved convolutional neural network and long short-term memory (CNN-LSTM) is presented. The principle used in our approach is simulated annealing that discovers reasonable number of neurons for each layer of a completely associated deep neural network to tackle the streamlining issue. The probability of detection is considered as the determining parameter to find the efficiency of the proposed algorithm. Experiments are carried under different signal to noise ratio to indicate better performance of the proposed algorithm. The PU signal will have an associated modulation format and hence identifying the presence of a modulation format itself establishes the presence of PU signal.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2000.11a
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• pp.38-43
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• 2000

In this present study, the correlation between subjective preference of essential odors and EEG response were investigated quantitatively. EEG signals were measured from 19 electrodes according to the International 10-20 system (Fpl, Fp2, F2/4, F7/8, Fz, C3/4, Cz, P3/4, Pz, T3/4, T5/6, Ol/2) from 8 healthy males subjects in four odor conditions. Four odor conditions (Rose oil bulgarian, Lemon oil misitano, Jasmin abs, Laverder iol france (KIMEX co. Ltd)) were applied for each subject in the experiment. Through the subjective evaluation, the most pleasant odor for each subject was determined. The power spectrum of ${\alpha}$/${\beta}$ of EEG signals from the most pleasant odor was compared with those from the control condition, which has no odor at all. It was observed that the power spectrum of ${\alpha}$/${\beta}$ of EEG from the most pleasant odor was increased significantly on F3, F3, F4,74 comparing to the control condition. This result indicates that the power spectrum of ai${\beta}$ could be a new index for measuring the levels of pleasantness of odors.

• ETRI Journal
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• v.44 no.4
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• pp.613-623
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• 2022

Autism spectrum disorder (ASD) is a developmental disorder associated with cognitive and neurobehavioral disorders. It affects the person's behavior and performance. Autism affects verbal and non-verbal communication in social interactions. Early screening and diagnosis of ASD are essential and helpful for early educational planning and treatment, the provision of family support, and for providing appropriate medical support for the child on time. Thus, developing automated methods for diagnosing ASD is becoming an essential need. Herein, we investigate using various machine learning methods to build predictive models for diagnosing ASD in children using facial images. To achieve this, we used an autistic children dataset containing 2936 facial images of children with autism and typical children. In application, we used classical machine learning methods, such as support vector machine and random forest. In addition to using deep-learning methods, we used a state-of-the-art method, that is, automated machine learning (AutoML). We compared the results obtained from the existing techniques. Consequently, we obtained that AutoML achieved the highest performance of approximately 96% accuracy via the Hyperpot and tree-based pipeline optimization tool optimization. Furthermore, AutoML methods enabled us to easily find the best parameter settings without any human efforts for feature engineering.

• The Pure and Applied Mathematics
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• v.10 no.4
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• pp.217-223
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• 2003

Let $\cal{K}$ be the extension Hilbert space of a Hilbert space $\cal{H}$ and let $\Phi$ be the faithful $\ast$-representation of $\cal{B}(\cal{H})$ on $\cal{k}$. In this paper, we show that if T is an irreducible ${\omega}-hyponormal$ operators such that $ker(T)\;{\subset}\;ker(T^{*})$ and $T^{*}T\;-\;TT^{\ast}$ is compact, then $\sigma_{e}(T)\;=\;\sigma_{e}(\Phi(T))$.