• Mass Spectrometry Letters
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• v.1 no.1
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• pp.25-28
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• 2010

The high-throughput identification and accurate quantification of proteins are essential strategies for exploring cellular functions and processes in quantitative proteomics. Stable isotope tagging is a key technique in quantitative proteomic research, accompanied by automated tandem mass spectrometry. For the differential proteome analysis of mouse neuronal cell lines, we used a multiplexed isobaric tagging method, in which a four-plex set of amine-reactive isobaric tags are available for peptide derivatization. Using the four-plex set of isobaric tag for relative and absolute quantitation (iTRAQ) reagents, we analyzed the differential proteome in several stroke time pathways (0, 4, and 8 h) after the mouse neuronal cells have been stressed using a glutamate oxidant. In order to obtain a list of the differentially expressed proteins, we selected those proteins which had apparently changed significantly during the stress test. With 95% of the peptides showing only a small variation in quantity before and after the test, we obtained a list of eight up-regulated and four down-regulated proteins for the stroke time pathways. To validate the iTRAQ approach, we studied the use of oxidant stresses for mouse neuronal cell samples that have shown differential proteome in several stroke time pathways (0, 4, and 8 h). Results suggest that histone H1 might be the key protein in the oxidative injury caused by glutamate-induced cytotoxicity in HT22 cells.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.38 no.3
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• pp.184-195
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• 2005

A preliminary quantitative model of the trophic structure in Gwangyang bay, Korea was obtained using ECOPATH and data from relevant studies to date in the region. The model integrates and analyzes biomass, food spectrum, trophic interactions and the key trophic pathways of the system. The bay model comprises 9 groups of benthic primary producer, phytoplankton, zooplankton, benthos, bivalve, pelagic fish, demersal fish and piscivorous fish. The total system throughput was estimated at $2.4\;kgWW/m^2/yr$, including a consumption of $41\%$, exports of $9\%$, respiratory flows of $24\%$ and flows into detritus of $26\%$. All of which originate from primary producers measured at $52\%$ and detritus of $48\%$. The total biomass was seen to be high compared to the levels of Somme, Delaware, Chesapeake Bays and Seine Estuary. This seems to be possibly due to artificial bivalve aquaculture and overestimation of benthos and benthic primary producer groups. The deviation can be calibrated by neglecting aquaculture and decreasing the habitat area for the groups. The trophic network of the bay shows a low level of recycling and organization as indicated by Finn's cycling index $3.3\%$, Ascendancy $3.1\;kgC/m^2/yr$ bits, Capacity $5.1\;kgC/m^2/yr$ bits and Redundancy $2.2\;kgC/m^2/yr$ bits. A high relative ascendancy of $62\%$ and a low internal relative ascendancy of $18\%$ indicate the system is not fully organized and stable towards disturbances, depending upon external connections. Although the model should be continuously provided with field data and calibrated further in depth, this study is the first trophic model applied to the region. The model can be a useful tool to understand the ecosystem in a quantitative manner.

• Journal of the Korea Society for Simulation
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• v.15 no.4
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• pp.129-136
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• 2006

Grid computing has been appeared for solving large-scaled data which are not solved by a single computer. Grid computing is a new generation platform which connects geographically distributed heterogeneous resources. However, gathering heterogeneous distributed resources produces many difficult problems. Especially. to assure resource reliability is one of the most critical problems. So, we propose a grid resource scheduling model using grid resource reliability measurement. We evaluate resource reliability based on resource status data and apply it to the grid scheduling model in DEVSJAVA modeling and simulation. This paper evaluates parameters such as resource utilization, job loss and average turn-around time and estimates experiment results of our model in comparison with those of existing scheduling models such as a random scheduling model and a round-robin scheduling model. These experiment results showed that the resource reliability measurement scheduling model provides efficient resource allocation and stable Job processing in comparison with a random scheduling model and a round-robin scheduling model.

• Bulletin of the Korean Chemical Society
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• v.35 no.1
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• pp.35-38
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• 2014

Herein, we report on the preparation of red fluorescent Si nanoparticles stabilized with styrene. Nano-sized Si particles emit fluorescence under UV excitation, which could be used to open up new applications in the fields of optics and semi-conductor research. Unfortunately, conventional methods for the preparation of red fluorescent Si nanoparticles suffer from the lack of a fully-established standard synthesis protocol. A common initial approach during the preparation of semi-conductors is the etching of crystalline Si wafers in a HF/ethanol/$H_2O$ bath, which provides a uniformly-etched surface of nanopores amenable for further nano-sized modifications via tuning of various parameters. Subsequent sonication of the etched surface crumbles the pores on the wafer, resulting in the dispersion of particles into the solution. In this study, we use styrene to occupy these platforms to stabilize the surface. We determine that the liberated silicon particles in ethanol solution interact with styrene, resulting in the substitution of Si-H bonds with those of Si-C as determined via UV photo-catalysis. The synthesized styrene-coated Si nanoparticles exhibit a stable, bright, red fluorescence under excitation with a 365 nm UV light, and yield approximately 100 mg per wafer with a synthesis time of 2 h. We believe this protocol could be further expanded as a cost-effective and high-throughput standard method in the preparation of red fluorescent Si nanoparticles.

• Journal of Microbiology and Biotechnology
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• v.24 no.11
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• pp.1559-1565
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• 2014

Cellulase and xylanase are main hydrolysis enzymes for the degradation of cellulosic and hemicellulosic biomass, respectively. In this study, our aim was to develop and test the efficacy of a rapid, high-throughput method to screen hydrolytic-enzyme-producing microbes. To accomplish this, we modified the 3,5-dinitrosalicylic acid (DNS) method for microwell plate-based screening. Targeted microbial samples were initially cultured on agar plates with both cellulose and xylan as substrates. Then, isolated colonies were subcultured in broth media containing yeast extract and either cellulose or xylan. The supernatants of the culture broth were tested with our modified DNS screening method in a 96-microwell plate, with a $200{\mu}l$ total reaction volume. In addition, the stability and reliability of glucose and xylose standards, which were used to determine the enzymatic activity, were studied at $100^{\circ}C$ for different time intervals in a dry oven. It was concluded that the minimum incubation time required for stable color development of the standard solution is 20 min. With this technique, we successfully screened 21 and 31 cellulase- and xylanase-producing strains, respectively, in a single experimental trial. Among the identified strains, 19 showed both cellulose and xylan hydrolyzing activities. These microbes can be applied to bioethanol production from cellulosic and hemicellulosic biomass.

• The Journal of the Acoustical Society of Korea
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• v.16 no.2
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• pp.58-65
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• 1997

A new automatic classification method with high and stable accuracy for time-series image data is presented in this paper. This method is based on prior condition that a classified map of the target area already exists, or at least one of the time-series image data had been classified. The classified map is used as a reference map to specify training areas of classification categories. The new automatic classification method consists of five steps, i.e., extraction of training data using reference map, detection of changed pixels based upon the homogeneity of training data, clustering of changed pixels, reconstruction of training data, and classification as like maximum likelihood classifier. In order to evaluate the performance of this method qualitatively, four time-series Landsat TM image data were classified by using this method and a conventional method which needs a skilled operator. As a results, we could get classified maps with high reliability and fast throughput, without a skilled operator.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37A no.12
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• pp.1093-1105
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• 2012

We propose an interference space reuse (ISR) algorithm for the MU-MIMO design in 3-cell downlink interference channels. Also, we provide a strategy for the adoption of the ISR scheme in the cellular network. In the multicell interference channels, the cell edge users may undergo severe interferences and their signals should be protected from the interferers for reliable transmissions. However, the intra cell users do not only experience small interferences but also they require small transmission power for stable communication. We provide a vector design algorithm based on ISR, where intra cell users are served through reusing the cell edge users' interference space. The performance enhancement reaches 20% compared to the fractional frequency reuse (FFR) scheme combined with IA through the scheduling between the cell edge users and the intra cell users. Also, it can be used to enhance the cell edge throughput when the quality of service (QoS) requirements of the intra cell users are fixed.

• The KIPS Transactions:PartC
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• v.9C no.5
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• pp.647-654
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• 2002

Ad-hoc networks consist of a set of mobile hosts that communicate using wireless links, without the use of other supporting communication facilities (such as base stations, etc.). Therefore, the topology of an Ad-hoc network frequently changes due to the movement of mobile host, which nay lead to sudden packet loss. Recently, the large amount of research has focused on the routing protocols needed in such an environment. In this paper, TCP Reno, Sack, and Tahoe versions are analysed using DSR protocol which is the representative On-Demand routing protocol in Ad-hoc wireless network. As the result of this simulation, we know that TCP Reno relatively has higher throughput than that of Sack and Tahoe, and TCP Reno has more stable performance than that of TCP Tahoe and Sack, regardless of the speed of mobile node and the size of topology.

• Journal of Information Processing Systems
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• v.16 no.4
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• pp.845-858
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• 2020

This paper proposes a modified end-to-end secure low energy adaptive clustering hierarchy (ME-LEACH) algorithm for enhancing the lifetime of a wireless sensor network (WSN). Energy limitations are a major constraint in WSNs, hence every activity in a WSN must efficiently utilize energy. Several protocols have been introduced to modulate the way a WSN sends and receives information. The end-to-end secure low energy adaptive clustering hierarchy (E-LEACH) protocol is a hierarchical routing protocol algorithm proposed to solve high-energy dissipation problems. Other methods that explore the presence of the most powerful nodes on each cluster as cluster heads (CHs) are the sparsity-aware energy efficient clustering (SEEC) protocol and an energy efficient clustering-based routing protocol that uses an enhanced cluster formation technique accompanied by the fuzzy logic (EERRCUF) method. However, each CH in the E-LEACH method sends data directly to the base station causing high energy consumption. SEEC uses a lot of energy to identify the most powerful sensor nodes, while EERRCUF spends high amounts of energy to determine the super cluster head (SCH). In the proposed method, a CH will search for the nearest CH and use it as the next hop. The formation of CH chains serves as a path to the base station. Experiments were conducted to determine the performance of the ME-LEACH algorithm. The results show that ME-LEACH has a more stable and higher throughput than SEEC and EERRCUF and has a 35.2% better network lifetime than the E-LEACH algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.7
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• pp.2257-2285
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• 2022

Cyber-physical systems (CPS) have been growing exponentially due to improved cloud-datacenter infrastructure-as-a-service (CDIaaS). Incremental expandability (scalability), Quality of Service (QoS) performance, and reliability are currently the automation focus on healthy Tier 4 CDIaaS. However, stable QoS is yet to be fully addressed in Cyber-physical data centers (CP-DCS). Also, balanced agility and flexibility for the application workloads need urgent attention. There is a need for a resilient and fault-tolerance scheme in terms of CPS routing service including Pod cluster reliability analytics that meets QoS requirements. Motivated by these concerns, our contributions are fourfold. First, a Distributed Non-Recursive Cloud Model (DNRCM) is proposed to support cyber-physical workloads for remote lab activities. Second, an efficient QoS stability model with Routh-Hurwitz criteria is established. Third, an evaluation of the CDIaaS DCN topology is validated for handling large-scale, traffic workloads. Network Function Virtualization (NFV) with Floodlight SDN controllers was adopted for the implementation of DNRCM with embedded rule-base in Open vSwitch engines. Fourth, QoS evaluation is carried out experimentally. Considering the non-recursive queuing delays with SDN isolation (logical), a lower queuing delay (19.65%) is observed. Without logical isolation, the average queuing delay is 80.34%. Without logical resource isolation, the fault tolerance yields 33.55%, while with logical isolation, it yields 66.44%. In terms of throughput, DNRCM, recursive BCube, and DCell offered 38.30%, 36.37%, and 25.53% respectively. Similarly, the DNRCM had an improved incremental scalability profile of 40.00%, while BCube and Recursive DCell had 33.33%, and 26.67% respectively. In terms of service availability, the DNRCM offered 52.10% compared with recursive BCube and DCell which yielded 34.72% and 13.18% respectively. The average delays obtained for DNRCM, recursive BCube, and DCell are 32.81%, 33.44%, and 33.75% respectively. Finally, workload utilization for DNRCM, recursive BCube, and DCell yielded 50.28%, 27.93%, and 21.79% respectively.