• JSTS:Journal of Semiconductor Technology and Science
• /
• v.13 no.6
• /
• pp.662-667
• /
• 2013

The effect of fluorine ions, which can be reacted with boron in high-doped BPSG, is investigated on the contact sidewall wiggling profile in semiconductor process. In the semiconductor device, there are many contacts on $p^+/n^+$ source and drain region. However these types of wiggling profile is only observed at the $n^+$ contact region. As a result, we find that the type of plug implantation dopant can affect the sidewall wiggling profile of contact. By optimizing the proper fluorine gas flow rate, both the straight sidewall profile and the desired electrical characteristics can be obtained. In this paper, we propose a fundamental approach to improve the contact sidewall wiggling profile phenomena, which mostly appear in high-doped BPSG on next-generation DRAM products.

• Proceedings of the KSRS Conference
• /
• 2008.10a
• /
• pp.406-409
• /
• 2008

Clustering data streams has an importance over many applications like sensor networks. Existing hierarchical methods follow a semi fuzzy clustering that yields duplicate clusters. In order to solve the problems, we propose an extended online divisive agglomerative clustering on data streams. It builds a tree-like top-down hierarchy of clusters that evolves with data streams using geometric time frame for snapshots. It is an enhancement of the Online Divisive Agglomerative Clustering (ODAC) with a pruning strategy to avoid duplicate clusters. Our main features are providing update time and memory space which is independent of the number of examples on data streams. It can be utilized for clustering sensor data and network monitoring as well as web click streams.

• 한국전산유체공학회:학술대회논문집
• /
• 2005.04a
• /
• pp.123-127
• /
• 2005

The numerical analyses of the complicated flows are widely attempted in these days. Because of the enormous demanding memory and calculation time, parallel processing is used for these problems. In order to obtain calculation efficiency, it is important to choose proper domain decomposition technique and numerical algorithm. In this research we enhanced the efficiency of the CFDS code developed by ADD, using parallel computation and newly developed numerical algorithms. For the huge amount of data transfer between blocks non-blocking method is used, and newly developed data transfer algorithm is used for non-aligned block interface. Recently developed RoeM scheme is adpoted as a spatial difference method, and AF-ADI and LU-SGS methods are used as a time integration method to enhance the convergence of the code. Analyses of the flows around the ONERA M6 wing and the high angle of attack missile configuration are performed to show the efficiency improvement.

• The Journal of the Acoustical Society of Korea
• /
• v.17 no.4E
• /
• pp.3-10
• /
• 1998

This paper concerns the dynamical behavior, in probabilistic sense, of a feedforward neural network performing auto association for novelty. Networks of retinotopic topology having a one-to-one correspondence between and output units can be readily trained using back-propagation algorithm, to perform autoassociative mappings. A novelty filter is obtained by subtracting the network output from the input vector. Then the presentation of a "familiar" pattern tends to evoke a null response ; but any anomalous component is enhanced. Such a behavior exhibits a promising feature for enhancement of weak signals in additive noise. As an analysis of the novelty filtering, this paper shows that the probability density function of the weigh converges to Gaussian when the input time series is statistically characterized by nonsymmetrical probability density functions. After output units are locally linearized, the recursive relation for updating the weight of the neural network is converted into a first-order random differential equation. Based on this equation it is shown that the probability density function of the weight satisfies the Fokker-Planck equation. By solving the Fokker-Planck equation, it is found that the weight is Gaussian distributed with time dependent mean and variance.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2012.10a
• /
• pp.1003-1006
• /
• 2012

The image correction algorithm and system design for CMOS sensor to enhance the image resolution is presented in this paper. The proposed algorithm finds out the image cell from the sensor and process them by the limited memory configuration. The evaluation of the method is done by the designed hardware system. The experimental results are capable of improving contrast per channel and of sensing equalized image quality on an edge of image.

• IMMUNE NETWORK
• /
• v.21 no.1
• /
• pp.4.1-4.18
• /
• 2021

The global outbreak of coronavirus disease 2019 (COVID-19) is still threatening human health, economy, and social life worldwide. As a counteraction for this devastating disease, a number of vaccines are being developed with unprecedented speed combined with new technologies. As COVID-19 vaccines are being developed in the absence of a licensed human coronavirus vaccine, there remain further questions regarding the long-term efficacy and safety of the vaccines, as well as immunological mechanisms in depth. This review article discusses the current status of COVID-19 vaccine development, mainly focusing on antigen design, clinical trials in later stages, and immunological considerations for further study.

• The Journal of the Korean Society for Microbiology
• /
• v.22 no.2
• /
• pp.175-184
• /
• 1987

The use of alkylating agent cyclophosphamide(CY), a widely used antitumor drug is well known as a potent immunosuppressant and has been used as a probe for investigating the functional capabilities of lymphocyte subsets of both T and B cells that play an important role in the regulation of the immune response. The present study was undertaken in an effort to assess the effects of CY on immunological memory in murine model. CY, given as a single dose of CY(250mg/kg) before sensitization with sheep red blood cells(SRBC) enhanced the primary response of Arthus and delayed-type hypersensitivity(DTH), as measured by footpad swelling reaction, but suppressed their tertiary DTH response. The similar CY pretreatment enhanced both the primary and tertiary hemagglutinin(HA) responses to SRBC, and the tertiary antibody response against polyvinylpyrroridone(PVP), a thymus-independent antigen but not the primary response against PVP. CY, given as a single dose of 250mg/kg 2 days before the primary immunization and two doses of 100mg/kg 2 days before the secondary and tertiary immunization, markedly suppressed the tertiary DTH and HA responses to SRBC. However, CY, given as small multiple daily doses(10mg/kg) over 4 days before sensitization but not after sensitization, enhanced the secondary HA response to SRBC. Contact sensitivity to dinitrofluorobenzene(DNFB) was suppressed by the drug, given either as a single large dose(300mg/kg) or as multiple dose(10mg/kg) administered 2 days before, together with or after DNFB sensitization. This suppression was more pronounced and more significant when CY was given as multiple dose. However, the enhancement of the secondary contact sensitivity to DNFB by CY was not clear-cut. The splenectomy appears to increase the enhancing effect of CY on contact sensitivity. These results suggest that CY selectively influences the immune response depending on the time of the drug administration relative to immunization and that the secondary or tertiary immune response involve memory cells with different susceptibilities to CY. Moreover, these results suggest that multiple low doses may sesectivley inhibit suppressor T cell proliferation involving DTH, HA or contact sensitivity without effecting helper T cells, but high doses presumably inhibit helper T cells and suppressor T cells with effecting B cells.

• Proceedings of the Ginseng society Conference
• /
• 2002.10a
• /
• pp.55-65
• /
• 2002

Ginseng has been used as a key constituent in traditional medicine prescriptions for centuries. Other than its well-known anti-stress and adaptogenic properties, ginseng has also been shown to be very effective in treating age-related deterioration in metabolic and memory functions. Although it is generally believed that the saponin (GS) fraction of the ginseng root accounts for the bioactivity of ginseng, a direct demonstration on which ginsenoside does what is still generally lacking. In the past decade, our laboratory has endeavored to identify the active GS components involved in energy metabolism, memory, and anti-neurotoxicity. To examine the ergogenic effects of GS in enhancing aerobic capacity, rats were subjected to either severe cold ($40^{\circ}C$ under helium-oxygen, two hours) or exercise workload $(70\%\;VO_{2}max,$ to exhaustion). Acute systemic injection (i.p.) of ginseng GS (5-20 mg/kg) significantly elevated both the total and maximum heat production in rats and improved their cold tolerance. However, pretreating the animal with the optimal dose (10 mg/kg) of GS devoid of $Rg_1\;and\;Rb_1$ failed to elicit any beneficial effects in improving cold tolerance. This indicates that either $Rb_1\;and/or\;Rg_1$ may be essential in exemplifying the thermogenic effect of GS. Further studies showed that only pretreating the animals with $Rb_1(2.5-5\;mg/kg),\;but\;not\;Rg_l,$ resulted in an increase in thermogenesis and cold tolerance. In contrast to the acute effect of GS on cold tolerance, enhancement of exercise performance in rats was only observed after chronic treatment (4 days). Further, we were able to demonstrate that both $Rb_1\;and\;Rg_1$ are effective in enhancing aerobic endurance by exercise. To illustrate the beneficial effects of GS in learning and memory, a passive avoidance paradigm (shock prod) was used. Our results indicated that the scopolamineinduced amnesia can be significantly reversed by chronically treating (4 days) the rats with either $Rb_1\;or\;Rg_1$ (1.25 - 2.5 mg/kg). To further examine its underlying mechanisms, the effects of various GS on ${\beta}-amyloid-modulated$ acetylcholine (ACh) release from the hippocampal slices were examined. It was found that inclusion of $Rb_1$ (0.1 ${\mu}M$), but not $Rg_1$, can attenuate ${\beta}-amyloid-suppressed$ ACh release from the hippocampal slices. Our results demonstrated that $Rb_1\;and\;Rg_1$ are the key components involved in various beneficial effects of GS but they may elicit their effects through different mechanisms.

• Journal of Korea Game Society
• /
• v.15 no.1
• /
• pp.77-88
• /
• 2015

As the smart phone market is drastically expanding, there is a steady growth of recent vicious activities such as data manipulation, billing fraud, identity theft, and leakage of personal information that are security threats to Social Network Games(SNG). Due to the threats, Strong development standard is required for security enhancement of SNG. Nonetheless, short life-spans, additional expenses, and the necessities to provide a sound game service hinders developers from reaching their security goals. Therefore, this research investigates the weak points of SNG through memory manipulation experiments based on the currently provided SNG services. In addition, the research presents counter measures and security enforcements that are light in service load and simplistic which can be applied in the developing process.

• KIISE Transactions on Computing Practices
• /
• v.23 no.7
• /
• pp.417-423
• /
• 2017

Recently, many embedded devices that have the computing capability required for deep learning have become available; hence, many new applications using these devices are emerging. However, these embedded devices have an architecture different from that of PCs and high-performance servers. In this paper, we propose a method that improves the performance of deep-learning framework by considering the architecture of an embedded device that shares memory between the CPU and the GPU. The proposed method is implemented in Caffe, an open-source deep-learning framework, and is evaluated on an NVIDIA Jetson TK1 embedded device. In the experiment, we investigate the image recognition performance of several state-of-the-art deep-learning networks, including AlexNet, VGGNet, and GoogLeNet. Our results show that the proposed method can achieve significant performance gain. For instance, in AlexNet, we could reduce image recognition latency by about 33% and energy consumption by about 50%.