• The KIPS Transactions:PartD
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• v.17D no.1
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• pp.9-16
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• 2010

Web service mashup bacomes one of the important web application development methods. This paper considers a client based mashup, where a page interfaces many service methods asynchronously. Browser systems execute callbacks when the corresponding reply arrives, possibly concurrent to user interface actions. In this case, callbacks and user interface actions share data memory and screen. Moreover, when the user is able to send another request before the previous ones have replied, the shared resource problem becomes more complicated. In order to solve the multiple requests problem, our contributions are as follows. First, we modeled a mashup page with user actions and callbacks, and we presented several types of callbacks. Secondly, concurrency condition is defined between callbacks and user actions in terms of shared resources, and the test method is presented. Also, we proposed the serialization approach to guarantee the safe execution of callbacks. Finally, we applied the proposed concurrency condition on XForms language and extended the XForms browser to implement the proposed approach. The prototype implementation showed that the proposed approach helps enhancing user experience on mashup pages.

• International Journal of Computer Science & Network Security
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• v.23 no.8
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• pp.177-189
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• 2023

Malware detection is an increasingly important operational focus in cyber security, particularly given the fast pace of such threats (e.g., new malware variants introduced every day). There has been great interest in exploring the use of machine learning techniques in automating and enhancing the effectiveness of malware detection and analysis. In this paper, we present a deep recurrent neural network solution as a stacked Long Short-Term Memory (LSTM) with a pre-training as a regularization method to avoid random network initialization. In our proposal, we use global and short dependencies of the inputs. With pre-training, we avoid random initialization and are able to improve the accuracy and robustness of malware threat hunting. The proposed method speeds up the convergence (in comparison to stacked LSTM) by reducing the length of malware OpCode or bytecode sequences. Hence, the complexity of our final method is reduced. This leads to better accuracy, higher Mattews Correlation Coefficients (MCC), and Area Under the Curve (AUC) in comparison to a standard LSTM with similar detection time. Our proposed method can be applied in real-time malware threat hunting, particularly for safety critical systems such as eHealth or Internet of Military of Things where poor convergence of the model could lead to catastrophic consequences. We evaluate the effectiveness of our proposed method on Windows, Ransomware, Internet of Things (IoT), and Android malware datasets using both static and dynamic analysis. For the IoT malware detection, we also present a comparative summary of the performance on an IoT-specific dataset of our proposed method and the standard stacked LSTM method. More specifically, of our proposed method achieves an accuracy of 99.1% in detecting IoT malware samples, with AUC of 0.985, and MCC of 0.95; thus, outperforming standard LSTM based methods in these key metrics.

• Proceedings of the Plant Resources Society of Korea Conference
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• 2023.04a
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• pp.16-16
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• 2023

Metabolomics is the study of global metabolite profiles in a system (cell, tissue, or organism) under a given set of conditions. Metabolomics has its roots in early metabolite profiling studies but is now a rapidly expanding area of scientific research in its own right. In this study, the applications of metabolomics in natural product studies are explored. Ginseng is a well-known herbal medicine and has various pharmacological effects, which include antiaging, anticancer, antifatigue, memory enhancing, immunomodulatory, and stress reducing effects. Metabolomic analysis of organic acids has not been performed for evaluation whether ginseng has been cultivated using conventional or environmental-friendly farming methods. In this study, profiling analysis was conducted for organic acids (OAs) in ginseng roots produced using conventional or environmentfriendly farming methods at five locations in each of five regions. In OA profiles, lactic acid was the most abundant OA in all regions, with the exception for environmentally friendly farmed ginseng in two of the five regions, in which glycolic acid was most abundant OA. OA profiles in all regions showed isocitric acid levels were increased by environment-friendly cultivation, which suggests metabolic differences associated from farming method, and that isocitric acid might be a useful discriminatory biomarker of environmental-friendly and conventional cultivation. The results of the present study suggest metabolomic studies of OAs in ginseng roots might be useful for monitoring whether ginseng has been cultivated using conventional or environmentally friendly farming methods.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.11
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• pp.2924-2944
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• 2023

Alzheimer's disease (AD) is a neurological condition that is recognized as one of the primary causes of memory loss. AD currently has no cure. Therefore, the need to develop an efficient model with high precision for timely detection of the disease is very essential. When AD is detected early, treatment would be most likely successful. The most often utilized indicators for AD identification are the Mini-mental state examination (MMSE), and the clinical dementia. However, the use of these indicators as ground truth marking could be imprecise for AD detection. Researchers have proposed several computer-aided frameworks and lately, the supervised model is mostly used. In this study, we propose a novel 3D Convolutional Neural Network Multilayer Perceptron (3D CNN-MLP) based model for AD classification. The model uses Attention Mechanism to automatically extract relevant features from Magnetic Resonance Images (MRI) to generate probability maps which serves as input for the MLP classifier. Three MRI scan categories were considered, thus AD dementia patients, Mild Cognitive Impairment patients (MCI), and Normal Control (NC) or healthy patients. The performance of the model is assessed by comparing basic CNN, VGG16, DenseNet models, and other state of the art works. The models were adjusted to fit the 3D images before the comparison was done. Our model exhibited excellent classification performance, with an accuracy of 91.27% for AD and NC, 80.85% for MCI and NC, and 87.34% for AD and MCI.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.2
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• pp.456-477
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• 2024

With information technology's rapid development, the Internet faces serious security problems. Studies have shown that malware has become a primary means of attacking the Internet. Therefore, adversarial samples have become a vital breakthrough point for studying malware. By studying adversarial samples, we can gain insights into the behavior and characteristics of malware, evaluate the performance of existing detectors in the face of deceptive samples, and help to discover vulnerabilities and improve detection methods for better performance. However, existing adversarial sample generation methods still need help regarding escape effectiveness and mobility. For instance, researchers have attempted to incorporate perturbation methods like Fast Gradient Sign Method (FGSM), Projected Gradient Descent (PGD), and others into adversarial samples to obfuscate detectors. However, these methods are only effective in specific environments and yield limited evasion effectiveness. To solve the above problems, this paper proposes a malware adversarial sample generation method (PixGAN) based on the pixel attention mechanism, which aims to improve adversarial samples' escape effect and mobility. The method transforms malware into grey-scale images and introduces the pixel attention mechanism in the Deep Convolution Generative Adversarial Networks (DCGAN) model to weigh the critical pixels in the grey-scale map, which improves the modeling ability of the generator and discriminator, thus enhancing the escape effect and mobility of the adversarial samples. The escape rate (ASR) is used as an evaluation index of the quality of the adversarial samples. The experimental results show that the adversarial samples generated by PixGAN achieve escape rates of 97%, 94%, 35%, 39%, and 43% on the Random Forest (RF), Support Vector Machine (SVM), Convolutional Neural Network (CNN), Convolutional Neural Network and Recurrent Neural Network (CNN_RNN), and Convolutional Neural Network and Long Short Term Memory (CNN_LSTM) algorithmic detectors, respectively.

• Korean Journal of Food Science and Technology
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• v.52 no.5
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• pp.450-458
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• 2020

The purpose of this study was to conduct a systematic review of the current published research related to improvement in cognitive function. A systematic search was performed in three bibliographic databases (PubMed, Cochrane Library, and EMBASE) using "dementia", "memory", "food", "diet", and "nutrition" as keywords. Meal management intervention, including Dietary Approaches to Stop Hypertension (DASH) diet, Mediterranean (Med) diet, Diet Mediterranean-DASH Intervention for Neurodegenerative Delay (MIND) diet, and other studies, was also included in the analysis. Through extensive screening, 21 articles, out of 2101 papers retrieved, were used for the final systematic review. The methodological quality of the randomized controlled clinical trials (RCTs) was assessed using the Cochrane Risk of Bias tool. These articles recommended vegetables, fruits, whole grains, olive oil, fish, berries, nuts, and beans. In conclusion, this study suggests the potential use of meal management to improve cognitive function.

• The Journal of Internal Korean Medicine
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• v.26 no.1
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• pp.182-198
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• 2005

Object : This study was designed to research whether the protection and inhibitory effects of cardiovascular diseases in L-NAME induced rat or ECV 304 cell lines through the Cell morphological pattern, Tunel assay, LDH activity, heart rate, blood pressure and immunohistochemistric analysis by Boonsimgieum water extract Methods : Nitric oxide(NO) play an important role in normal and pathophysiological cells including as a messenger molecule, neurotransmitter, microbiocidal agent, or dilator of blood vessels and artheriosclerosis, hypertension, myocardial infarction, respectively. Endothelial cell products can modulate the magnitude of a response to a vasoconstrictor, as evinced by the greater constriction after endothelium removal or NO synthesis blockade. To investigate that Boonsimgieum in the potential contribution of the levels of nitric oxide generated by endothelial nitric oxide synthase (eNOS) and the mechanisms of protection against NG-nitro-L-arginine methyl ester (L-NAME), human ECV 304 cells, which normally do not express eNOS, were expressed by L-NAME. L-NAME stimulated rat or cells were found to be resistant to injury and delayed death following the Boonsimgieum. Inhibition of nitric oxide synthesis abolished the protective effect against L-NAME, thrombin and collagen exposure. Interestingly, such effects have been observed during stimulation with agents such as phenylephrine and KCl on L-NAME mediate rats, were damaged by the NOS inhibitor L-NAME. Result : As the result of this study, In group, the anti-apoptosis and necrosis in the cardiovascular system have a potential capacity for prevented, protected and treating the diseases of cardiovascular system, against the necrosis of rat and ECV 304 cells with Caspase 3 and calpain expression by L-NAME is promoted. Conclusion : these results demonstrate neuroprotective and memory enhancing effects of ZIBU, suggesting its beneficial actions for the treatment of AD.

• Food Science and Industry
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• v.55 no.2
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• pp.154-165
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• 2022

Humans have been breeding the mulberry silkworm for the long period of time to obtain silk fabric and nutrient-rich pupae. Currently, silkworm larvae, pupae, and silk-Fibroin hydrolysates are registered as food raw materials, while silkworm feces and Bombyx batryticatus are registered as Korean traditional medicines. Among sericulture products, individually recognized health functional food ingredients include silk-protein acid-hydrolysates for immunity enhancement, Fibroin-hydrolysates for memory improvement, and freeze-dried 5^th instar and 3^rd-day-silkworm powder for lowering-blood sugar. Recently, HongJam produced by steaming and freeze-drying mature silkworms were reported to have various health-promoting effects such as preventing the onset of Alzheimer's disease and Parkinson's disease, enhancing gastro-intestinal functions, improving skin-whitening and hair growth, and extending healthspan. By consuming silkworm products with various health-promoting effects, it is possible to increase the healthspan of human beings, thereby reducing personal and national medical expenses, resulting in increasing the individual's happiness.

• Korean Journal of Food Science and Technology
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• v.44 no.4
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• pp.428-433
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• 2012

Probiotics and their products, such as yogurt and cheese have been widely consumed in many countries with proven health benefits including anti-microbial activity and anti-diarrheal activity. LHFM (Lactobacillus helveticus - fermented milk) is a processed skim milk powder, fermented by a probiotics, L. helveticus IDCC3801. In the present study, we aimed to investigate the neuroprotective effects and the cognitive improvements of LHFM. LHFM itself did not show any cytotoxicity to the human neuroblastoma cell line, SH-SY5Y; however, it dose-dependently protected against glutamate-induced neuronal cell death. LHFM also attenuated scopolamine-induced memory deficit in Y-maze and Morris-water maze. In the analysis of hippocampus after a behavior test, LHFM significantly increased the acetylcholine level and also inhibited acetylcholine esterase activity. Therefore, the raised acetylcholine release partially contributes to the improvement of learning and memory by a treatment with LHFM. These results suggest that LHFM is an effective material for prevention or improvement of cognitive impairments caused by neuronal cell damage and central cholinergic dysfunction.

• Journal of the Korean Society of Food Science and Nutrition
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• v.38 no.4
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• pp.409-414
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• 2009

The aim of this study was to investigate the ameliorating effects of deer antler extract on the learning and memory impairments induced by the administration of scopolamine (2 mg/kg, i.p.) in rats. Tacrine was used as a positive control agent for evaluating the cognition enhancing activity of deer antler extract in scopolamine-induced amnesia models. The results showed that the deer antler extract-treated group (200 mg/kg, p.o.) and the tacrine-treated group (10 mg/kg, p.o.) significantly ameliorated scopolamine-induced amnesia based on the Morris water maze test. Although there was no statistical significance of brain ACh contents among the experimental groups, the brain ACh contents of the deer antler extract-treated group was slightly higher than that of the scopolamine-treated group. The inhibitory effect of deer antler extract on the acetylcholinesterase activity in the brain was significantly lower than that of scopolamine-treated group. The tacrine- and the deer antler-treated groups reduced the MAO-B activity compared to the scopolamine-treated group, but not significantly. These results suggest that the deer antler extract could be an effective agent for the prevention of the cognitive impairment induced by cholinergic dysfunction.