• The Journal of Traditional Korean Medicine
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• v.15 no.1
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• pp.106-112
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• 2006

The aim of this study was to investigate the cytotoxic effect and its mechanism on Radix Aconiti(RA) extract in lung cancer cell lines. RA extract treatment decreased the cell viability in a dose-dependent fashions in lung cancer cells including A549, H460, H23 and H157 cells. Many investigators reported that A549 and H460 cells expressed wild-type p53, but H23 and H157 cells preserved mutated p53. After treatment with RA extract in A549 and H460 cells, we measured the expression of p53 protein levels using Western blot. analysis. In both cells treated with RA extracts, p53 protein expressions were increased in a dose-dependent manner. In our experiments, RA extracts also have cytotoxic effects in H23 and H157, which have mutated p53. Treatment with RA extract decreased bcl-2 protein expressions in both cells. These results suggest that RA extracts have cytotoxic effects via p53 expression increase and bcl-2 inhibitable pathways in A549, H460 cells and H23, H157 cells, respectively.

• The Journal of Korean Obstetrics and Gynecology
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• v.20 no.3
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• pp.91-110
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• 2007

Purpose : These experiments were undertaken to evaluate the effect of administration of Palmultang on ovarian functions and differential gene expressions related cell viabilities caspase-3, MAPK and MPG in female mice. Materials and Methods : We administered the Palmultang to 6-week-old female ICR mice for 4, 8, or 12 days. The female mice were injected PMSG and hCG for ovarian hyperstimulation. And then recovered ovaries were minced and extracted mRNA and analyzed cell viability related gene expression. We chose the caspase-3 for cell apoptosis, MAPK and MPG genes for cell viability and DNA repair. To compare the differences, we set a control group treated with plain water at the same volume by the same way. Results : In case of administration of Palmultang, the mean number of total ovulated oocytes and the number of morphologically normal oocytes increased significantly compared to a control group. We were also examined the embryonic developmental competence in vitro. The administration of Palmultang in a concentration with 10 and 100 mg/ml were beneficial effect of embryonic development in preimplantation period. The administration of Palmultang play a role of prevention of cell apoptosis and DNA damages and also increased cell proliferation resulted in ovarian functions. Conclusion : From our results suggested that the medication of Palmultang has beneficial effect on reproductive functions of female mice via prevention of cell apoptosis and DNA damaging and promotion of cell proliferation.

• The Journal of the Acoustical Society of Korea
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• v.40 no.5
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• pp.496-502
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• 2021

Recently, deep speaker embedding approach has been widely used in text-independent speaker verification, which shows better performance than the traditional i-vector approach. In this work, to improve the deep speaker embedding approach, we propose a novel method called group-based speaker embedding which incorporates group information. We cluster all speakers of the training data into a predefined number of groups in an unsupervised manner, so that a fixed-length group embedding represents the corresponding group. A Group Decision Network (GDN) produces a group weight, and an aggregated group embedding is generated from the weighted sum of the group embeddings and the group weights. Finally, we generate a group-based embedding by adding the aggregated group embedding to the deep speaker embedding. In this way, a speaker embedding can reduce the search space of the speaker identity by incorporating group information, and thereby can flexibly represent a significant number of speakers. We conducted experiments using the VoxCeleb1 database to show that our proposed approach can improve the previous approaches.

• Journal of Pharmacopuncture
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• v.22 no.1
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• pp.16-27
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• 2019

Generative and vegetative parts of the cactuses have had a long-lasting position in folk medicine and their effects could partly be confirmed in scientific experiments. Nowadays, the cactus, fruits, and cladodes are the focus of many studies because of their desirable properties. Therefore, the summarized reports of valuable properties of medicinal plants may be a good way to familiarize researches with a new source of drugs with lower side effects and higher efficacy. Opuntia dillenii, a well-known member of the Cactaceae family, is used as a medicinal plant in various countries and grows in the desert, semi-desert, tropical and sub-tropical areas. It shows diverse pharmacological activities such as: antioxidant, anti-inflammatory, anti-tumor, neuroprotective, hepatoprotective, hypotensive etc. OD fruit also possesses valuable constitutes for instance: betalains, ascorbic acid, total phenol, protein as well as essential elements which suggest the significant potential of this plant as a complementary therapy against several pathological conditions. This review describes experimental evidence about pharmacological and therapeutic potential of OD in order to give the basis of its application in the prevention and treatment of some chronic diseases. More studies on OD can help better understanding of its pharmacological mechanism of action to explain its traditional uses and to identify its potential new therapeutic applications.

• The Korean Journal of Pain
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• v.32 no.3
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• pp.160-167
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• 2019

Background: Pain is a complex mechanism which involves different systems, including the opioidergic and GABAergic systems. Due to the side effects of chemical analgesic agents, attention toward natural agents have been increased. Artemisinin is an herbal compound with widespread modern and traditional therapeutic indications, which its interaction with the GABAergic system and antinoniceptive effects on neuropathic pain have shown. Therefore, this study was designed to evaluate the antinociceptive effects of artemisinin during inflammatory pain and interaction with the GABAergic and opioidergic systems by using a writhing response test. Methods: On the whole, 198 adult male albino mice were used in 4 experiments, including 9 groups (n = 6) each with three replicates, by intraperitoneal (i.p.) administration of artemisinin (2.5, 5, and 10 mg/kg), naloxone (2 mg/kg), bicuculline (2 mg/kg), saclofen (2 mg/kg), indomethacin (5 mg/kg), and ethanol (10 mL/kg). Writhing test responses were induced by i.p. injection of 10 mL/kg of 0.6% acetic acid, and the percentage of writhing inhibition was recorded. Results: Results showed significant dose dependent anti-nociceptive effects from artemisinin which, at a 10 mg/kg dose, was statistically similar to indomethacin. Neither saclofen nor naloxone had antinociceptive effects and did not antagonize antinociceptive effects of artemisinin, whereas bicuculline significantly inhibited the antinocicptive effect of artemisinin. Conclusions: It seems that antinocicptive effects of artemisinin are mediated by $GABA_A$ receptors.

• Korean Journal of Medicinal Crop Science
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• v.27 no.1
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• pp.38-44
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• 2019

Background: Taraxacum platycarpum has been used in traditional medicine in Korea to treat intoxication and edema and as a diuretic. According to previous reports, it has anti-cancer, anti-gastritis, and anti-inflammation effects. However, the improvement effect of T. platycarpum on rheumatoid arthritis has not been investigated. The anti-oxidative and anti-inflammation effects of the aerial parts of T. platycarpum are different from those of its subterranean parts. Thus, we evaluated the effect of the water extracts of Taraxaci radix (WTR) on type II collagen-induced rheumatoid arthritis (CIA) in animal models. Methods and Results: Rheumatoid arthritis was induced by type II collagen. WTR (100 mg/kg and 500 mg/kg) was administered to the animal models. Methotrexate was used as the positive control. The levels of interleukin-6, TNF-alpha, and type II collagen IgG in the animals were measured by using enzyme-linked immunosorbent assay. Treatment with 500 mg/kg WTR decreased the serum levels of interleukin-6, TNF-alpha, and collagen IgG in the CIA models. Moreover, treatment with WTR diminished the arthritisinduced swelling of the hind legs and monocyte infiltration in the bloodvessels of the animal models. Conclusions: These results indicate that WTR has the potential to improve rheumatoid arthritis by reducing the levels of inflammatory cytokines such as interleukin-6 and TNF-alpha. However, further experiments are required to elucidate the influence of WTR on signal transduction in vitro and in vivo.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.3
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• pp.237-246
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• 2019

In order to improve the accuracy of the rating prediction of the recommendation model, not only user-item rating data are used but also consider auxiliary information of item such as comments, tags, or descriptions. The traditional approaches use a word-level model of the bag-of-words for the auxiliary information. This model, however, cannot utilize the auxiliary information effectively, which leads to shallow understanding of auxiliary information. Convolution neural network (CNN) can capture and extract feature vector from auxiliary information effectively. Thus, this paper proposes character-level deep-Convolution Neural Network based matrix factorization (Char-DCNN-MF) that integrates deep CNN into matrix factorization for a novel recommendation model. Char-DCNN-MF can deeper understand auxiliary information and further enhance recommendation performance. Experiments are performed on three different real data sets, and the results show that Char-DCNN-MF performs significantly better than other comparative models.

• Journal of the Korea Computer Graphics Society
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• v.25 no.1
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• pp.23-32
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• 2019

Cybersickness is a symptom of dizziness that occurs while experiencing Virtual Reality (VR) technology and it is presumed to occur mainly by crosstalk between the sensory and cognitive systems. However, since the sensory and cognitive systems cannot be measured objectively, it is difficult to measure cybersickness. Therefore, methodologies for measuring cybersickness have been studied in various ways. Traditional studies have collected answers to questionnaires or analyzed EEG data using machine learning algorithms. However, the system relying on the questionnaires lacks objectivity, and it is difficult to obtain highly accurate measurements with the machine learning algorithms. In this work, we apply Deep Neural Network (DNN) deep learning algorithm for objective cybersickness measurement from EEG data. We also propose a data preprocessing for learning and network structures allowing us to achieve high performance when learning EEG data with the deep learning algorithms. Our approach provides cybersickness measurement with an accuracy up to 98.88%. Besides, we analyze video characteristics where cybersickness occurs by examining the video segments causing cybersickness in the experiments. We discover that cybersickness happens even in unusually persistent changes in the darkness such as the light in a room keeps switching on and off.

• KIPS Transactions on Computer and Communication Systems
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• v.8 no.2
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• pp.35-40
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• 2019

Traditional Malware Detection is susceptible for detecting malware which is modified by polymorphism or obfuscation technology. By learning patterns that are embedded in malware code, machine learning algorithms can detect similar behaviors and replace the current detection methods. Data must collected continuously in order to learn malicious code patterns that change over time. However, the process of storing and processing a large amount of malware files is accompanied by high space and time complexity. In this paper, an HDFS-based distributed processing system is designed to reduce space complexity and accelerate feature extraction time. Using a distributed processing system, we extract two API features based on filtering basis, 2-gram feature and APICFG feature and the generalization performance of ensemble learning models is compared. In experiments, the time complexity of the feature extraction was improved about 3.75 times faster than the processing time of a single computer, and the space complexity was about 5 times more efficient. The 2-gram feature was the best when comparing the classification performance by feature, but the learning time was long due to high dimensionality.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.10
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• pp.3858-3874
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• 2021

As an essential part of the urban transportation system, precise perception of the traffic flow parameters at the traffic signal intersection ensures traffic safety and fully improves the intersection's capacity. Traditional detection methods of road traffic flow parameter can be divided into the micro and the macro. The microscopic detection methods include geomagnetic induction coil technology, aerial detection technology based on the unmanned aerial vehicles (UAV) and camera video detection technology based on the fixed scene. The macroscopic detection methods include floating car data analysis technology. All the above methods have their advantages and disadvantages. Recently, indoor location methods based on wireless signals have attracted wide attention due to their applicability and low cost. This paper extends the wireless signal indoor location method to the outdoor intersection scene for traffic flow parameter estimation. In this paper, the detection scene is constructed at the intersection based on the received signal strength indication (RSSI) ranging technology extracted from the wireless signal. We extracted the RSSI data from the wireless signals sent to the road side unit (RSU) by the vehicle nodes, calibrated the RSSI ranging model, and finally obtained the traffic flow parameters of the intersection entrance road. We measured the average speed of traffic flow through multiple simulation experiments, the trajectory of traffic flow, and the spatiotemporal map at a single intersection inlet. Finally, we obtained the queue length of the inlet lane at the intersection. The simulation results of the experiment show that the RSSI ranging positioning method based on wireless signals can accurately estimate the traffic flow parameters at the intersection, which also provides a foundation for accurately estimating the traffic flow state in the future era of the Internet of Vehicles.