• Journal of Ginseng Research
• /
• v.40 no.1
• /
• pp.9-17
• /
• 2016

Background: Alzheimer's disease (AD) is a progressive brain disease, for which there is no effective drug therapy at present. Ginsenoside Rg1 (G-Rg1) and G-Rg2 have been reported to alleviate memory deterioration. However, the mechanism of their anti-AD effect has not yet been clearly elucidated. Methods: Ultra performance liquid chromatography tandem MS (UPLC/MS)-based metabolomics was used to identify metabolites that are differentially expressed in the brains of AD mice with or without ginsenoside treatment. The cognitive function of mice and pathological changes in the brain were also assessed using the Morris water maze (MWM) and immunohistochemistry, respectively. Results: The impaired cognitive function and increased hippocampal $A{\beta}$ deposition in AD mice were ameliorated by G-Rg1 and G-Rg2. In addition, a total of 11 potential biomarkers that are associated with the metabolism of lysophosphatidylcholines (LPCs), hypoxanthine, and sphingolipids were identified in the brains of AD mice and their levels were partly restored after treatment with G-Rg1 and G-Rg2. G-Rg1 and G-Rg2 treatment influenced the levels of hypoxanthine, dihydrosphingosine, hexadecasphinganine, LPC C 16:0, and LPC C 18:0 in AD mice. Additionally, G-Rg1 treatment also influenced the levels of phytosphingosine, LPC C 13:0, LPC C 15:0, LPC C 18:1, and LPC C 18:3 in AD mice. Conclusion: These results indicate that the improvements in cognitive function and morphological changes produced by G-Rg1 and G-Rg2 treatment are caused by regulation of related brain metabolic pathways. This will extend our understanding of the mechanisms involved in the effects of G-Rg1 and G-Rg2 on AD.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.18 no.12
• /
• pp.2885-2890
• /
• 2014

Localization of a sensor network node using machine learning has been recently studied. It is easy for Support vector machines algorithm to implement in high level language enabling parallelism. Raspberrypi is a linux system which can be used as a sensor node. Pi can be used to construct IP based Hadoop clusters. In this paper, we realized Support vector machine using python language and built a sensor network cluster with 5 Pi's. We also established a Hadoop software framework to employ MapReduce mechanism. In our experiment, we implemented the test sensor network with a variety of parameters and examined based on proficiency, resource evaluation, and processing time. The experimentation showed that with more execution power and memory volume, Pi could be appropriate for a member node of the cluster, accomplishing precise classification for sensor localization using machine learning.

• The Transactions of the Korea Information Processing Society
• /
• v.4 no.3
• /
• pp.639-648
• /
• 1997

As the areas of computer application are expanded, the real-time applicition enviroments that must process as many transactions as possible within their deadlines have been increased recently. Conventional disk based databaes system is not appropriate in real-time transaction processing due to delying time for disk I/O processing. When the system is overloaede, the performance of transaction scheduling technique using earliest deadline first deteriorates rapidly because it can assign the highest priority ot a transaction that has already missed or is about to miss tis deadline. Therfore, the performance of suggested transaction secheduling technique is made to improved by propos-ing the doule locking mechanism based on priority. Finally, in order to evaluate the performance of the proposed priority-based double locking techniques under single proessor and main memory database system environments, the simulation model was developed using the SLAM II language.

• The Transactions of the Korean Institute of Electrical Engineers C
• /
• v.51 no.5
• /
• pp.185-190
• /
• 2002

Capacitor material utilized in the downsizing passive devices and dynamic random access memory(DRAM) requires the physical and electrical properties at given area such as capacitor thickness reduction, relative dielectric constant increase, low leakage current and thermal stability. Common capacitor materials, $SiO_2$, $Si_3N_4$, $SiO_2$/$Si_3N_4$,TaN and et al., used until recently have reached their physical limits in their application to several hundred angstrom scale capacitor. $Ta_2O_{5}$ is known to be a good alternative to the existing materials for the capacitor application because of its high dielectric constant (25 ~35), low leakage current and high breakdown strength. Despite the numerous investigations of $Ta_2O_{5}$ material, there have little been established the clear understanding of the annealing effect on capacitance characteristic and conduction mechanism, design and fabrication for $Ta_2O_{5}$ film capacitor. This study presents the structure-property relationship of reactive-sputtered $Ta_2O_{5}$ MIM capacitor structure processed by annealing in a vacuum. X-ray diffraction patterns skewed the existence of amorphous phase in as-deposited condition and the formation of preferentially oriented-$Ta_2O_{5}$ in 670, $700^{\circ}C$ annealing. On 670, $700^{\circ}C$ annealing under the vacuum, the leakage current decrease and the enhanced temperature-capacitance characteristic stability. and the leakage current behavior is stable irrespective of applied electric field. The results states that keeping $Ta_2O_{5}$ annealed at vacuum gives rise to improvement of electrical characteristics in the capacitor by reducing oxygen-vacancy and the broken bond between Ta and O.

• YAKHAK HOEJI
• /
• v.51 no.6
• /
• pp.463-468
• /
• 2007

Chong Myung Tang is consisted of three medicinal herbs (Acori Graminei Rhizoma, Polygalae Radix and Hoelen cum Radix). It has been used as a medicine for the purpose of learning and memory improvement. In this paper, Chong Myung Tang was screened the biological activities for Alzheimer's disease. The extract (70% ethanol) of Acari Graminei Rhizoma (1 mg/ml) showed that acetylcholinesterase (AChE) and amyloid beta ($A{\beta}$) peptide aggregation inhibitory potency are 43.1% and 76.5%, respectively. The extract of Polygalae Radix showed inhibitory activity against $A{\beta}_{1-42}$ peptide aggregation (51.5%). To predict the drug-likeness, oral absorption ability; blood-brain barrier (BBB) penetraion rate, mutagenecity and carcinogenicity; in silico screening was performed against 16 compounds in the three medicinal herbs. According to the results, all compounds have appropriate chemical structures as medicines. The six compounds in Acori Graminei Rhizoma and the five compounds in Hoelen cum Radix showed excellent oral absorption rate and BBB penetration rate. The four compounds in Polygalae Radix showed excellent oral absorption rate, but their BBB penetration was presented low rate. And, the extract of Hoelen cum Radix didn't show AChE and $A{\beta}_{1-42}$ peptide aggregation inhibitory activities in vitro. Therefore, their activity in brain may be other mechanism. According to all of the results, in silico prediction technology is convenient and effective to determine biological active compounds in medicinal herbs.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.30 no.5
• /
• pp.881-893
• /
• 2020

CFI(Control Flow Integrity) is a mitigation mechanism that protects programs by verifying control flows. IFCC(Indirect Function Call Checks) and SCS(Shadow Call Stack), CFI supported by LLVM Clang compiler, were introduced to protect applications in Android. IFCC protects function calls and SCS protects function returns. In this paper, we propose attacks to bypass CFI on the application environment with IFCC and SCS. Even if IFCC and SCS were applied to user applications, it was confirmed that there were many code segments not protected by IFCC and SCS in the application memory. We execute code in CFI unprotected segments to construct 1) bypassing IFCC to call a protected function, 2) modulating return address via SCS bypass. We identify code segments not protected by IFCC and SCS in Android10 QP1A. 191005.007.A3. We also implement proof-of-concept exploits to demonstrate that modulation of control flow is possible in an environment where IFCC and SCS are applied.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.28 no.4B
• /
• pp.298-305
• /
• 2003

In this paper, we proposed a high performance lookup controller for IP packet forwarding engine of ATM based label edge routers. The lookup controller is designed to provide services such as MPLS, VPN, ELL, and RT services as well as the best effort. For high speed searching for IP addresses, we employed a TCAM based hardware search device not using traditional algorithmic approaches. We also implement lookup control functions into FPGA for fast processing of packet header and lookup control. The proposed lookup controller is designed to support differenciated services for users and to process in pipelined mechanism for performance improvement. A two-step search scheme is also applied to perform lookup for the key combined with multi-field of packet header. We found that the proposed lookup controller provides the performance of about 16M packets per second through simulations.

• Transactions on Electrical and Electronic Materials
• /
• v.1 no.3
• /
• pp.14-17
• /
• 2000

Giga bit dynamic random access memory(DRAM) requires the capacitor of high dielectric films. Some metal oxides films have been proposed as the dielectric material . And Pt is one of the most promising electrode materials. However very little has been done in developing the etching technologoy Pt film. Therefore, it is the first priority to develop the technology for plasma etching of Pt film. In this study, the dry etching of Pt film was investigated in Inductively Coupled Plasma(ICP) etching system with Cl$_2$/Ar and HBr/Cl$_2$/Ar gas mixing. X-ray photoelectron spectroscopy (XPS) was used in analysis of sidewall residues for the understanding of etching mechanism. We found the etch residues on the pattern sidewall is mainly Pt-Pt, Pt-Cl and Pt-Br compounds, Etch profile was observed by Scanning Electron Spectroscopy(SEM) . The etch rate of Pt film at 10%, Cl$_2$/90% Ar gas mixing ration was higher than at 100%. Ar. Addition of HBr to Cl$_2$/Ar as an etching gas led to generally higher selectivity to SiO$_2$. And the etch residues were reduced at 5% HBr/5% Cl$_2$/90% Ar gas mixing ration. These pages provide you with an examples of the layout and style which we wish you to adopt during the preparation of your paper, Make the width of abstract to be 14cm.

• KIISE Transactions on Computing Practices
• /
• v.22 no.5
• /
• pp.201-208
• /
• 2016

Collection and storing of multiple time series data in real time requires large memory space. To solve this problem, the usage of varying sample size is proposed in the compression scheme using discrete cosine transform technique. Time series data set has characteristics such that a higher compression ratio can be achieved with smaller amount of value changes and lower frequency of the value changes. The coefficient of variation and the variability of the differences between adjacent data elements (VDAD) are presumed to be very good measures to represent the characteristics of the time series data and used as key parameters to determine the varying sample size. Test results showed that both VDAD-based and the coefficient of variation-based scheme generate excellent compression ratios. However, the former scheme uses much simpler sample size decision mechanism and results in better compression performance than the latter scheme.

• KIPS Transactions on Software and Data Engineering
• /
• v.5 no.11
• /
• pp.521-526
• /
• 2016

As on-line informal text data have massive in its volume and have unstructured characteristics in nature, there are limitations in applying traditional relational data model technologies for data storage and data analysis jobs. Moreover, using dynamically generating massive social data, social user's real-time reaction analysis tasks is hard to accomplish. In the paper, to capture easily the semantics of massive and informal on-line documents with unsupervised learning mechanism, we design and implement automatic topic extraction systems according to the mass of the words that consists a document. The input data set to the proposed system are generated first, using N-gram algorithm to build multiple words to capture the meaning of the sentences precisely, and Hadoop and Spark (In-memory distributed computing framework) are adopted to run topic model. In the experiment phases, TB level input data are processed for data preprocessing and proposed topic extraction steps are applied. We conclude that the proposed system shows good performance in extracting meaningful topics in time as the intermediate results come from main memories directly instead of an HDD reading.