• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.10
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• pp.3708-3728
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• 2021

Indian herbal plants are used in agriculture and in the food, cosmetics, and pharmaceutical industries. Laboratory-based tests are routinely used to identify and classify similar herb species by analyzing their internal cell structures. In this paper, we have applied computer vision techniques to do the same. The original leaf image was preprocessed using the Chan-Vese active contour segmentation algorithm to efface the background from the image by setting the contraction bias as (v) -1 and smoothing factor (µ) as 0.5, and bringing the initial contour close to the image boundary. Thereafter the segmented grayscale image was fed to a leaky capacitance fired neuron model (LCFN), which differentiates between similar herbs by combining different groups of pixels in the leaf image. The LFCN's decay constant (f), decay constant (g) and threshold (h) parameters were empirically assigned as 0.7, 0.6 and h=18 to generate the 1D feature vector. The LCFN time sequence identified the internal leaf structure at different iterations. Our proposed framework was tested against newly collected herbal species of natural images, geometrically variant images in terms of size, orientation and position. The 1D sequence and shape features of aloe, betel, Indian borage, bittergourd, grape, insulin herb, guava, mango, nilavembu, nithiyakalyani, sweet basil and pomegranate were fed into the 5-fold Bayesian regularization neural network (BRNN), K-nearest neighbors (KNN), support vector machine (SVM), and ensemble classifier to obtain the highest classification accuracy of 91.19%.

• Korean Journal of Pharmacognosy
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• v.52 no.3
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• pp.186-191
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• 2021

We developed a method to identify and quantify 6-hydroxyluteolin 7-O-glucoside in the powder of Salvia plebeia (PS) using high-performance liquid chromatography coupled with diode array detector (HPLC/DAD) and equipped with reverse-phase INNO C18 column. The analytical method was optimized and validated using novel parameters. The obtained values for the limits of detection and quantification were 3.60 and 10.90 ㎍/mL, respectively. Calibration curve showed good linearity in the concentration range tested (0.00625-0.1 mg/mL, r² = 1.0000), high accuracy (96.2-101.4%), and precision values (RSD ≤ 0.27%). Our analysis support the use of our method for accurately identifying and quantifying 6-hydroxyluteolin 7-O-glucoside from PS in routine analyses and large-scale extraction processes for content determination.

• Nuclear Engineering and Technology
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• v.53 no.1
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• pp.216-233
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• 2021

In this work, Rhizophora spp. particleboard phantoms were made using SPI-based adhesives, modified with sodium hydroxide and itaconic acid polyamidoamine-epichlorohydrin (0, 5, 10, and 15 wt%). An X-ray computed tomography (CT) imaging system was used to ascertain the CT numbers and density distribution profiles of the particleboards. The SPI-based/NaOH/IA-PAE/Rhizophora spp. particleboard phantoms with 15 wt% IA-PAE addition level had the highest solid content, flexural strength, flexural modulus, and internal bonding strength of 36.06 ± 1.08%, 18.61 ± 0.38 Nmm^-2, 7605.76 ± 0.89 Nmm^-2, and 0.463 ± 0.053 Nmm^-2, respectively. The moisture content, mass density, water absorption, and dimensional stability were 6.93 ± 0.27%, 0.962 ± 0.037 gcm^-3, 22.36 ± 2.47%, and 10.90 ± 0.86%, respectively. The results revealed that the mass attenuation coefficients and effective atomic number values within the 16.59-25.26 keV photon energy region, were close to the calculated XCOM values in water, with a p-value of 0.077. Moreover, the CT images showed that the dissimilarities in the discrepancy of the profile density decreased as the IA-PAE concentrations increased. Therefore, these results support the appropriateness of the SPI-based/NaOH/IA-PAE/Rhizophora spp. particleboard with 15 wt% IA-PAE adhesive as a suitable tissue-equivalent phantom material for medical health applications.

• Journal of Positioning, Navigation, and Timing
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• v.11 no.4
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• pp.327-332
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• 2022

The Korea Augmentation Satellite System (KASS) is the Satellite-Based Augmentation System (SBAS) under development in Korea. KASS navigation service support navigation Safety of Life (SoL) service. KASS signal provides corrections to Global Positioning System (GPS) data received from KASS Reference Stations (KRS) and is broadcast form Geostationary Earth Orbiting (GEO) satellites to KASS users and is used by GPS/SBAS user equipment to improve the accuracy, availability, continuity and integrity of the navigation solution. Seven KRS's collect the satellite data and send them to the KASS Processing Stations (KPS) for the generation of the corrections and the monitoring the integrity. For performing its computation the KPS needs to know accurate and reliable KRS antennas coordinates. These coordinates are provided as configuration parameters to the KPS. This means that the reference frame in which the KPS work is the one represented by the set of coordinates provided as input. Therefore, the activity to maintain the accuracy of the KRS antenna coordinates is necessary, knowing that coordinates can evolve due to earth plates movements or earthquakes. In this paper, we analyzed the geodetic survey results for KRS antenna coordinates from Site Acceptance Test (SAT) #1 in December 2020 to August 2022. In the future, it is expected that these activities and planning for KRS coordinates maintenance will be produced and provided to KASS system operators for KPS configuration updates during the KASS lifetime of 15 years. Through these maintenance activities, it is expected that monitoring and analysis of unpredictable events such as earthquakes and seism will be possible in the future.

• Explosives and Blasting
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• v.38 no.4
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• pp.26-36
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• 2020

With the increase of expansion and use of the underground space, the possibility of an underground explosion by terrorists is increasing. In this study, after modeling a circular tunnel excavated at a depth of 50m, an explosion load was applied to the inside of the tunnel. As for the explosion load, the explosion load of the maximum explosive amount for six types of vehicle booms proposed by ATF (Bureau of Alcohol, Tobacco, and Firearms) was calculated. For the rock mass around the circular tunnel, three types of rock grades were selected according to the support pattern suggested in the domestic tunnel design. Nonlinear dynamic analysis was performed to evaluate the influence of the ground structure by examining the surface displacement using the explosion load and rock mass characteristics as parameters. As a result of the analysis, for grade 1 rock, the influence on the uplift of the surface should be considered, and for grade 2 and 3 rocks, the influence on a differential settlement should be considered. In particular, for grade 3 rocks, detailed analysis is required for ground-structure interaction within 40m. Also, it is considered that the influence of Young's modulus is the main factor for the surface displacement.

• Journal of Korean Society on Water Environment
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• v.27 no.5
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• pp.699-709
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• 2011

The uses of multi-dimensional hydrodynamic and water quality models are increasing to support a sustainable management of large dam reservoirs in Korea. Any modeling study requires selection of a proper spatial dimension of the model based on the characteristics of spatial variability of concerned simulation variables. For example, a laterally averaged two-dimensional (2D) model, which has been widely used in many large dam reservoirs in Korea, assumes that the lateral variations of hydrodynamic and water quality variables are negligible. However, there has been limited studies to give a justification of the assumption. The objectives of this study were to present the characteristics of spatial variations of water quality variables through intensive field monitoring in Daechung Reservoir, and provide information on a proper spatial dimension for different water quality parameters. The monitoring results showed that the lateral variations of water temperature are marginal, but those of DO, pH, and conductivity could be significant depending on the hydrological conditions and local algal biomass. In particular, the phytoplankton (Chl-a) and nutrient concentrations showed a significant lateral variation at R2 (Daejeongri) during low flow periods in 2008 possibly because of slow lateral mixing of tributary inflow from So-oak Stream and wind driven patchiness.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.20 no.1
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• pp.41-50
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• 2010

This paper proposes a mutual identification and session key exchange scheme in secure vehicular communication based on the group signature. In VANETs, security requirements such as authentication, conditional privacy, non-repudiation, and confidentiality are required to satisfy various vehicular applications. However, existing VANET security methods based on the group signature do not support a mutual identification and session key exchange for data confidentiality. The proposed scheme allows only one credential to authenticate ephemeral Diffie-Hellman parameters generated every key exchange session. Our scheme provides a robust key exchange and reduces storage and communication overhead. The proposed scheme also satisfies security requirements for various application services in VANETs.

• International Journal of Computer Science & Network Security
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• v.21 no.1
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• pp.143-151
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• 2021

The enormous prevalence of transferring official confidential digital documents via the Internet shows the urgent need to deliver confidential messages to the recipient without letting any unauthorized person to know contents of the secret messages or detect there existence . Several Steganography techniques such as the least significant Bit (LSB), Secure Cover Selection (SCS), Discrete Cosine Transform (DCT) and Palette Based (PB) were applied to prevent any intruder from analyzing and getting the secret transferred message. The utilized steganography methods should defiance the challenges of Steganalysis techniques in term of analysis and detection. This paper presents a novel and robust framework for color image steganography that combines Linear Congruential Generator (LCG), simulated annealing (SA), Cesar cryptography and LSB substitution method in one system in order to reduce the objection of Steganalysis and deliver data securely to their destination. SA with the support of LCG finds out the optimal minimum sniffing path inside a cover color image (RGB) then the confidential message will be encrypt and embedded within the RGB image path as a host medium by using Cesar and LSB procedures. Embedding and extraction processes of secret message require a common knowledge between sender and receiver; that knowledge are represented by SA initialization parameters, LCG seed, Cesar key agreement and secret message length. Steganalysis intruder will not understand or detect the secret message inside the host image without the correct knowledge about the manipulation process. The constructed system satisfies the main requirements of image steganography in term of robustness against confidential message extraction, high quality visual appearance, little mean square error (MSE) and high peak signal noise ratio (PSNR).

• Journal of The Korean Society of Agricultural Engineers
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• v.63 no.2
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• pp.51-60
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• 2021

Effective nonpoint source (NPS) pollution management requires frequent water quality monitoring, which is, however, often costly to be implemented in practice. Statistical techniques and machine learning methods allow us to identify and focus on fundamental environmental variables that have close relationships with NPS pollutants of interest. This study developed surrogate models to predict the concentrations of suspended sediment (SS) and total phosphorus (T-P) from turbidity and runoff discharge rates using multiple linear regression (MLR) and random forest (RF) methods. The RF models provided acceptable performance in predicting SS and T-P, especially when runoff discharge rates were high. The RF models outperformed the MLR models in all the cases. Such finding highlights the potential of RF techniques and models as a tool to identify fundamental environmental variables that are measured in relatively inexpensive ways or freely available but still able to provide information required to quantify the concentrations of NP S pollutants. The analysis of relative importance rates showed that the temporal variations of SS and T-P concentrations could be more effectively explained by that of turbidity than runoff discharge rate. This study demonstrated that the advanced statistical techniques such as machine learning could help to improve the efficiency of NPS pollutants monitoring.

• The Korean Journal of Pain
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• v.34 no.2
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• pp.156-164
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• 2021

Several types of pain occur following spinal cord injury (SCI); however, neuropathic pain (NP) is one of the most intractable. Invasive and non-invasive brain stimulation techniques have been studied in clinical trials to treat chronic NP following SCI. The evidence for invasive stimulation including motor cortex and deep brain stimulation via the use of implanted electrodes to reduce SCI-related NP remains limited, due to the small scale of existing studies. The lower risk of complications associated with non-invasive stimulation, including transcranial direct current stimulation (tDCS) and repetitive transcranial magnetic stimulation (rTMS), provide potentially attractive alternative central neuromodulation techniques. Compared to rTMS, tDCS is technically easier to apply, more affordable, available, and potentially feasible for home use. Accordingly, several new studies have investigated the efficacy of tDCS to treat NP after SCI. In this review, articles relating to the mechanisms, clinical efficacy and safety of tDCS on SCI-related NP were searched from inception to December 2019. Six clinical trials, including five randomized placebo-controlled trials and one prospective controlled trial, were included for evidence specific to the efficacy of tDCS for treating SCI-related NP. The mechanisms of action of tDCS are complex and not fully understood. Several factors including stimulation parameters and individual patient characteristics may affect the efficacy of tDCS intervention. Current evidence to support the efficacy of utilizing tDCS for relieving chronic NP after SCI remains limited. Further strong evidence is needed to confirm the efficacy of tDCS intervention for treating SCI-related NP.