• Journal of Oriental Neuropsychiatry
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• v.19 no.1
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• pp.29-42
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• 2008

Objectives : This study was performed to examine the effect of Sinchim on enhancing of memory in rat with water maze. Methods : Experimental animals(white rat) were classfied into normal, control, and aroma sample group. Then, they were injected .{\beta}-amyloid into control and aroma sample group rat's brain about $5{\mu}l$ to injure its brain. After rat smelt Sinchim about 12days, I did water maze test and anatomized its hippocampus. Sections were cut coronally at 30 ${\mu}m$.(XI00) Results: 1. In acquisition test of water maze learning, .{\beta}-amyloid injured group took more time than normal group to reach the escape platform noticeably and through the session of trial, Sinchim aroma sample group shortened time than .l3-amyloid injured group after 6 days. 2. In the acetyltransferase(AchE) immunostained method, it was shown that Sinchim aroma sample recovered tbe syntbesis of ChAT(Choloneacetyltransferase). Conclusion: Smelling Sinchim would be useful for enhancing of memory.

• Neurospine
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• v.15 no.4
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• pp.285-295
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• 2018

As spine surgery flourished in Taiwan and neurosurgeons became more involved in spine surgery towards the end of the 20th century, the Taiwan Neurosurgical Spine Society (TNSS), earlier named the Taiwan Neurospinal Society, was established on March 11, 2001. As its main founder, Dr. Chun-I Huang was elected as the first president of the TNSS. The goals of the TNSS were to promote research, to hold academic seminars, to participate in international conferences, and to exchange clinical experiences. The mission of the TNSS was successful, and the profession of spine surgery in Taiwan advanced during the first decade of the 21st century, culminating in the TNSS joining ASIA SPINE in 2010. Since its establishment, the TNSS has always been supportive of collaboration and communication with the Korean Spinal Neurosurgery Society and the Neurospinal Society of Japan. Through periodical meetings, supported by the TNSS, surgeons worldwide have enjoyed a platform of sharing and mutual learning. To further promote academic research, the TNSS has officially supported the journal Neurospine since 2018. With extensive efforts from local and international surgeons, the TNSS will continue to adhere to its mission and to advance the profession of spine surgery.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.4
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• pp.121-128
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• 2021

In order to design a real time big data collection and analysis system of manufacturing data in a smart factory, it is important to establish an appropriate wired/wireless communication system and protocol. This paper introduces the latest communication protocol, OPC-UA (Open Platform Communication Unified Architecture) based client/server function, applied user interface technology to configure a network for real-time data collection through IoT Integration. Then, Database is designed in MES (Manufacturing Execution System) based on the analysis table that reflects the user's requirements among the data extracted from the new cutting process automation process, bush inner diameter indentation measurement system and tool monitoring/inspection system. In summary, big data analysis system introduced in this paper performs SPC (statistical Process Control) analysis and visualization analysis with interface of OPC-UA-based wired/wireless communication. Through AI learning modeling with XGBoost (eXtream Gradient Boosting) and LR (Linear Regression) algorithm, quality and visualization analysis is carried out the storage and connection to the cloud.

• International Journal of Computer Science & Network Security
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• v.22 no.7
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• pp.171-180
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• 2022

In the knowledge development of online assessment in learning management systems (LMSs), many assessments are evaluated weekly in the summer training course for undergraduate students in the Faculty of Computing and Information Technology at King Abdul-Aziz University in Saudi Arabia. The number of performance assessments in the summer training course reaches 15 weeks. Many of them, however, are sent or done informally or through unreliable ways and cannot be verified by third parties. Therefore, applying the concept of digital transformation is essential. This research study reported herein used the action design research (ADR) method to build a new information technology system that could assist in the digital transformation. An electronic platform was designed, developed, implemented, and evaluated using the ADR method so that the main people involved in the summer training process (i.e., students, academic supervisors, and administrators) would have a high level of satisfaction with it. The study was conducted on 452 students, 105 academic supervisors, and 15 administrative staff and was conducted during the summer semester of 2020. All the training processes were digitally transformed and automated to control and raise the level and reliability of the training. All involved people were satisfied, thus, shifting the process to be in a digital form assist in achieving the high-level goal.

• Journal of Distribution Science
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• v.22 no.5
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• pp.81-91
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• 2024

Purpose: Edutech, which is the application of information and communication technology to education, is being introduced in various ways across all levels, from primary and secondary education to lifelong education. The purpose of this study was to present metadata about Edutech tools to provide the method for providing various Edutech tools. Research design, data, and methodology: To achieve the research purpose, the necessary elements for the metadata of Edutech tools were first derived based on a literature review. A focus group interview (FGI) with experts was conducted to gather opinions on the developed metadata, further validating its appropriateness. Results: The metadata area consisted of "Basic Information", "Product Information", and "Utilization Information". The "Basic Information" section had 9 items, "Product Information" had 8 items, and "Utilization Information" was presented with 4 items. Conclusions: This study proposed metadata for Edutech tools, which can be utilized to develop distribution system to proliferate and harness various Edutech tools in the educational setting. For the future establishment of an Edutech tool distribution system based on this metadata, it's imperative to operate a credible platform to ensure a stable distribution framework.

• Korean Journal of Medicinal Crop Science
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• v.19 no.6
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• pp.456-463
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• 2011

The present study examined the effects of Korean white ginseng (WG, Panax ginseng C. A. Meyer) on the learning and memory function and the neural activity in rats with trimethyltin (TMT)-induced memory deficits. The rats were administered with saline or WG (WG 100 or 300 mg/kg, p.o.) daily for 21 days. The cognitive improving efficacy of WG on the amnesic rats, which was induced by TMT, was investigated by assessing the Morris water maze test and by performing immunohistochemistries on choline acetyltransferase (ChAT), acetylcholinesterase (AchE), cAMP responsive element binding protein (CREB) and brain derived neurotrophic factor (BDNF). The rats treated with TMT injection (control group) showed impaired learning and memory of the tasks, but the rats treated with TMT injection and WG administration produced significant improvement of the escape latency to find the platform in the Morris water maze at the 2nd and 4th days compared to that of the control group. In the retention test, the WG 100 and WG 300 groups showed significantly increased crossing number around the platform compared to that of the control group (p < 0.001). Consistently with the behavioral data, result of immunohistochemistry analysis showed that WG 100 mg/kg significantly alleviated the loss of BDNF-ir neurons in the hippocampus compared to that of the control group (p < 0.01). Also, treatment with WG has a trend to be increased the cholinergic neurons in the hippocampal CA1 and CA3 areas as compared to that of the control group. These results suggest that WG may be useful for improving the cognitive function via regulation of neurotrophic activity.

• The Journal of Korean Institute for Practical Engineering Education
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• v.3 no.2
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• pp.18-26
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• 2011

Computational chemistry is one of the chemistry fields that deals with the theoretical chemistry problem using computer calculations and can be described as the chemistry lab moved on computer space. In line with recent enhancement of processing capability of computers, utilization of high performance computer cannot be overemphasized in the field of computational chemistry in performing complex calculation of huge molecular structure and simulation. While they have to use commands and consoles for high performance computer to execute complex calculation of huge molecular structure and simulation, most of students in natural science and engineering, who are not experts in computer technically, are likely to be unaware of UNIX. Under the circumstances, web-based educational support system for computational chemistry is needed to enable them to practice computational chemistry, even not knowing UNIX command. In this study, e-Chem, one of such educational support systems, is developed by using Liferay portal platform, which is a Java open source more oriented to standard and outstanding in its content management and collaboration function than other web portals. By using this system, even students who are not familiar with computer, are expected to take part in lab classes and save time learning Unix command and also enhance the learning efficiency by using familiar interface.

• Genomics & Informatics
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• v.18 no.2
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• pp.15.1-15.6
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• 2020

Named entity recognition tools are used to identify mentions of biomedical entities in free text and are essential components of high-quality information retrieval and extraction systems. Without good entity recognition, methods will mislabel searched text and will miss important information or identify spurious text that will frustrate users. Most tools do not capture non-contiguous entities which are separate spans of text that together refer to an entity, e.g., the entity "type 1 diabetes" in the phrase "type 1 and type 2 diabetes." This type is commonly found in biomedical texts, especially in lists, where multiple biomedical entities are named in shortened form to avoid repeating words. Most text annotation systems, that enable users to view and edit entity annotations, do not support non-contiguous entities. Therefore, experts cannot even visualize non-contiguous entities, let alone annotate them to build valuable datasets for machine learning methods. To combat this problem and as part of the BLAH6 hackathon, we extended the TextAE platform to allow visualization and annotation of non-contiguous entities. This enables users to add new subspans to existing entities by selecting additional text. We integrate this new functionality with TextAE's existing editing functionality to allow easy changes to entity annotation and editing of relation annotations involving non-contiguous entities, with importing and exporting to the PubAnnotation format. Finally, we roughly quantify the problem across the entire accessible biomedical literature to highlight that there are a substantial number of non-contiguous entities that appear in lists that would be missed by most text mining systems.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.5
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• pp.345-349
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• 2009

Social bookmarking systems are a typical web 2.0 service based on folksonomy, providing the platform for storing and sharing bookmarking information. Spammers in social bookmarking systems denote the users who abuse the system for their own interests in an improper way. They can make the entire resources in social bookmarking systems useless by posting lots of wrong information. Hence, it is important to detect spammers as early as possible and protect social bookmarking systems from their attack. In this paper, we applied a diverse set of machine learning approaches, i.e., decision tables, decision trees (ID3), $na{\ddot{i}}ve$ Bayes classifiers, TAN (tree-augment $na{\ddot{i}}ve$ Bayes) classifiers, and artificial neural networks to this task. In our experiments, $na{\ddot{i}}ve$ Bayes classifiers performed significantly better than other methods with respect to the AUC (area under the ROC curve) score as veil as the model building time. Plausible explanations for this result are as follows. First, $na{\ddot{i}}ve$> Bayes classifiers art known to usually perform better than decision trees in terms of the AUC score. Second, the spammer detection problem in our experiments is likely to be linearly separable.

• Information Systems Review
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• v.23 no.3
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• pp.51-75
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• 2021

Global e-commerce websites offer personalized recommendation services to gain sustainable competitiveness. Existing studies have offered personalized recommendation services using quantitative preferences such as ratings. However, offering personalized recommendation services using only quantitative data has raised the problem of decreasing recommendation performance. For example, a user gave a five-star rating but wrote a review that the user was unsatisfied with hotel service and cleanliness. In such cases, has problems where quantitative and qualitative preferences are inconsistent. Recently, a growing number of studies have considered review data simultaneously to improve the limitations of existing personalized recommendation service studies. Therefore, in this study, we identify review and rating mismatches and build a new user profile to offer personalized recommendation services. To this end, we use deep learning algorithms such as CNN, LSTM, CNN + LSTM, which have been widely used in sentiment analysis studies. And extract sentiment features from reviews and compare with quantitative preferences. To evaluate the performance of the proposed methodology in this study, we collect user preference information using real-world hotel data from the world's largest travel platform TripAdvisor. Experiments show that the proposed methodology in this study outperforms the existing other methodologies, using only existing quantitative preferences.