• Transactions of Materials Processing
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• v.32 no.2
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• pp.74-80
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• 2023

A deformation behavior of commercially pure titanium (CP-Ti) is highly dependent on material and processing parameters, such as deformation temperature, deformation direction, and strain rate. This study aims to predict the multivariable and nonlinear tensile behavior of CP-Ti using machine learning based on three algorithms: artificial neural network (ANN), light gradient boosting machine (LGBM), and long short-term memory (LSTM). The predictivity for tensile behaviors at the cryogenic temperature was lower than those in the room temperature due to the larger data scattering in the train dataset used in the machine learning. Although LGBM showed the lowest value of root mean squared error, it was not the best strategy owing to the overfitting and step-function morphology different from the actual data. LSTM performed the best as it effectively learned the continuous characteristics of a flow curve as well as it spent the reduced time for machine learning, even without sufficient database and hyperparameter tuning.

• Journal of Korean Society for Quality Management
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• v.49 no.4
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• pp.581-594
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• 2021

Purpose: The purpose of this study is to compare machine learning models for anomaly detection of mechanical facility equipment and suggest an anomaly detection system for mechanical facility equipment in subway stations. It helps to predict failures and plan the maintenance of facility. Ultimately it aims to improve the quality of facility equipment. Methods: The data collected from Daejeon Metropolitan Rapid Transit Corporation was used in this experiment. The experiment was performed using Python, Scikit-learn, tensorflow 2.0 for preprocessing and machine learning. Also it was conducted in two failure states of the equipment. We compared and analyzed five unsupervised machine learning models focused on model Long Short-Term Memory Variational Autoencoder(LSTM-VAE). Results: In both experiments, change in vibration and current data was observed when there is a defect. When the rotating body failure was happened, the magnitude of vibration has increased but current has decreased. In situation of axis alignment failure, both of vibration and current have increased. In addition, model LSTM-VAE showed superior accuracy than the other four base-line models. Conclusion: According to the results, model LSTM-VAE showed outstanding performance with more than 97% of accuracy in the experiments. Thus, the quality of mechanical facility equipment will be improved if the proposed anomaly detection system is established with this model used.

• The Journal of the Korea Contents Association
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• v.9 no.2
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• pp.309-317
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• 2009

This study was to investigate the effects of restoring cognition function and neurotrophic factor in the hippocampus according to memory and learning training in rats affected by brain injury. Brain injury was induced in Sprague-Dawley rats(36 rats) through middle cerebral artery occlusion(MCAo). And then experiment groups were randomly divided into three groups; Group I: Brain injury induction(n=12), Group II: the application for treadmill training after brain injury induction(n=12), Group III: the application for memory and learning training after brain injury induction(n=12). Morris water maze acquisition test and retention test were performed to test cognitive function. And the histological examination was also observed through the immunohistochemistric response of BDNF(brain-derived neurotrophic factor) in the hippocampus. For Morris water maze acquisition test, there were significant interactions among the groups with the time(p<.001). The time to find the circular platform in Group III was more shortened than in Group I, II on the 9th, 10th, 11th and 12th day. For Morris water maze retention test, there were significant differences among the groups(p<.001). The time to dwell on quadrant circular platform in Group III on the 13th day was the longest compared with other groups. And as the result of observing the immunohistochemistric response of BDNF in the hippocampus CA1, the response of immunoreactive positive in Group III on the 7th day increased more than that of Group I, II. These results suggested that the memory and learning training in rats with brain injury has a more significant impact on restoring cognitive function via the changes of neurotropic factor expression and synaptic neuroplasticity.

• The Transactions of the Korean Institute of Power Electronics
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• v.27 no.1
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• pp.48-55
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• 2022

This paper proposes a battery remaining useful life (RUL) prediction method using a deep learning-based EMD-CNN-LSTM hybrid method. The proposed method pre-processes capacity data by applying empirical mode decomposition (EMD) and predicts the remaining useful life using CNN-LSTM. CNN-LSTM is a hybrid method that combines convolution neural network (CNN), which analyzes spatial features, and long short term memory (LSTM), which is a deep learning technique that processes time series data analysis. The performance of the proposed remaining useful life prediction method is verified using the battery aging experiment data provided by the NASA Ames Prognostics Center of Excellence and shows higher accuracy than does the conventional method.

• Journal of the Korea Society of Computer and Information
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• v.25 no.3
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• pp.51-55
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• 2020

In this paper, an improved FAM is proposed by adopting similarity learning in the existing FAM (Fuzzy Associative Memory) used in image restoration. Image restoration refers to the recovery of the latent clean image from its noise-corrupted version. In serious application like face recognition, this process should be noise-tolerant, robust, fast, and scalable. The existing FAM is a simple single layered neural network that can be applied to this domain with its robust fuzzy control but has low capacity problem in real world applications. That similarity measure is implied to the connection strength of the FAM structure to minimize the root mean square error between the recovered and the original image. The efficacy of the proposed algorithm is verified with significant low error magnitude from random noise in our experiment.

• The KIPS Transactions:PartB
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• v.11B no.4
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• pp.449-456
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• 2004

This paper proposes a novel recognition model, a recurrent fuzzy associative memory(RFAM), for recognizing time-series patterns contained an ambiguity. RFAM is basically extended from FAM(Fuzzy Associative memory) by adding a recurrent layer which can be used to deal with sequential input patterns and to characterize their temporal relations. RFAM provides a Hebbian-style learning method which establishes the degree of association between input and output. The error back-propagation algorithm is also adopted to train the weights of the recurrent layer of RFAM. To evaluate the performance of the proposed model, we applied it to a word boundary detection problem of speech signal.

• Journal of Ginseng Research
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• v.18 no.1
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• pp.39-43
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• 1994

This study was performed to investigate the effect of ginseng saponin from Korean red ginseng on the learning and memory. Total (50, 100 mg/kg, bw) and panaxadiol saponin (15, 30 mg/kg, bw) treated groups did not show the difference of the time score and the number of error in comparison with control group. Panaxatriol saponin (15, 30 mg/kg, bw) significantly decreased both the time score and the number of error in water maze test. These results indicate that panaxatriol saponin from Korean red ginseng may improve the learning ability of rat in water multiple T-maze.

• Animal cells and systems
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• v.12 no.1
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• pp.11-14
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• 2008

Finding a way to strengthen human cognitive functions, such as learning and memory, has been of great concern since the moment people realized that these functions can be affected and even altered by certain chemicals. Since then, plenty of endeavors have been made to look for safe ways of improving cognitive performances without adverse side-effects. Unfortunately, most of these efforts have turned out to be unsuccessful until now. In this study, we examine the effect of a natural compound, idesolide, on hippocampus-dependent recognition memory. We demonstrate that idesolide is effective in the enhancement of recognition memory, as measured by a novel object recognition task. Thus, idesolide might serve as a novel therapeutic medication for the treatment of memoryrelated brain anomalies such as mild cognitive impairment(MCI) and Alzheimer's disease.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.12
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• pp.983-987
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• 2009

One of the critical themes in the language acquisition is its exposure to linguistic environments. Linguistic environments, which interact with infants, include not only human beings such as its parents but also artificially crafted linguistic media as their functioning elements. An infant learns a language by exploring these extensive language environments around it. Based on such large linguistic data exposure, we propose a machine learning based method on the cognitive mechanism that simulate flexibly and appropriately infant's language learning. The infant's initial stage of language learning comes with sentence learning and creation, which can be simulated by exposing it to a language corpus. The core of the simulation is a memory-based learning model which has language hypernetwork structure. The language hypernetwork simulates developmental and progressive language learning using the structure of new data stream through making it representing of high level connection between language components possible. In this paper, we simulates an infant's gradual and developmental learning progress by training language hypernetwork gradually using 32,744 sentences extracted from video scripts of commercial animation movies for children.

• Journal of Pharmacopuncture
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• v.20 no.1
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• pp.10-17
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• 2017

Objectives: Boswellic acid (BA), a compound isolated from the gum-resin of Boswellia carterii, is a pentacyclic terpenoid that is active against many inflammatory diseases, including cancer, arthritis, chronic colitis, ulcerative colitis, Crohn's disease, and memory impairment, but the mechanism is poorly understood. This study investigated the effects of boswellic acid on spatial learning and memory impairment induced by trimethyltin (TMT) in Wistar rats. Methods: Forty male Wistar rats were randomly divided into 5 groups: Normal group, TMT-administrated rats (8.0 mg/kg, Intraperitoneally, i.p.) and TMT + BA (40, 80 and 160 mg/kg, i.p.)-administrated rats. BA was used daily for 21 days. To evaluate the cognitive improving of BA, we performed the Morris water maze test. Moreover, to investigate the neuroprotective effect of BA, we determined the acetylcholinesterase (AchE) activity, the malondialdehyde (MDA) level as a marker of lipid peroxidation, and the glutathione (GSH) content in the cerebral cortex. Results: Treatment with TMT impaired learning and memory, and treatment with BA at a dose of 160 mg/kg produced a significant improvement in learning and memory abilities in the water maze tasks. Consistent with behavioral data, the activity of AChE was significantly increased in the TMT-injected rats compared to the control group (P < 0.01) whereas all groups treated with BA presented a more significant inhibitory effect against AChE than the TMT-injected animals. In addition, TMT reduced the GSH content and increased the MDA level in the cerebral cortex as compared to the control group) P < 0.01). On the other hand, treatment with BA at 160 mg/kg slightly increased the GSH content and reduced the MDA level in comparison to the TMT-administered group (P < 0.01). Conclusion: The above results suggest that the effect of BA in improving the cognitive function may be mediated through its antioxidant activity.