• Journal of KIISE:Software and Applications
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• v.32 no.3
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• pp.227-235
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• 2005

In the embedded system domain, both memory requirement and energy consumption are great concerns. To save memory and energy, the 32 bit ARM processor supports the 16 bit Thumb instruction set. For a given program, the Thumb code is typically smaller than the ARM code. However, the limitations of the Thumb instruction set can often lead to generation of poorer quality code. To generate codes with smaller size but a little slower execution speed, Krishnaswarmy suggests a profiling guided selection algorithm at module level for generating mixed ARM and Thumb codes for application programs. The resulting codes of the algorithm give significant code size reductions with a little loss in performance. When the instruction set is selected at module level, some functions, which should be compiled in Thumb mode to reduce code size, are compiled to ARM code. It means we have additional code size reduction chance. In this paper, we propose a profile guided selection algorithm at function level for generating mixed ARM and Thumb codes for application programs so that the resulting codes give additional code size reductions without loss in performance compared to the module level algorithm. We can reduce 2.7％ code size additionally with no performance penalty

• KOREAN JOURNAL OF CROP SCIENCE
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• v.60 no.1
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• pp.97-106
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• 2015

Platycodon grandiflorum, commonly known as Doraji in Korea, has a wide range of pharmacologic properties, such as reducing adiposity and hyperlipidemia, and antiatherosclerotic effects. However, the mechanisms underlying these effects remain unclear. In order to profile proteins from the nodal segment, callus, root and shoot, high throughput proteome approach was executed in the present study. Two dimensional gels stained with CBB, a total of 84 differential expressed proteins were confirmed out of 839 protein spots using image analysis by Progenesis SameSpot software. Out of total differential expressed spots, 58 differential expressed protein spots (${\geq}$ 2-fold) were analyzed using MASCOT search engine according to the similarity of sequences with previously characterized proteins along with the UniProt database. Out of 58 differential expressed protein, 32 protein spots were up-regulated such as ribulose-1,5-bisphosphate carboxylase, endoplasmic oxidoreductin-1, heat stress transcription factor A3, RNA pseudourine synthase 4, cysteine proteinase, GntR family transcriptional regulator, E3 xyloglucan 6-xylosyltransferase, while 26 differential protein spots were down-regulated such as L-ascorbate oxidase precursor, late embryogenesis abundant protein D-34, putative SCO1 protein, oxygen-evolving enhancer protein 3. However, frequency distribution of identified proteins using iProClass databases, and assignment by function based on gene ontology revealed that the identified proteins from the explants were mainly associated with the nucleic acid binding (17%), transferase activity (14%) and ion binding (12%). In that way, the exclusive protein profile may provide insight clues for better understanding the characteristics of proteins and metabolic activity in various explants of the economically important medicinal plant Platycodon grandiflorum.

• Journal of Animal Science and Technology
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• v.64 no.2
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• pp.247-261
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• 2022

Ketosis is associated with high milk yield during lactating or insufficient feed intake in lactating dairy cows. However, few studies have been conducted on the metabolomics of ketosis in Korean lactating dairy cows. The present study aimed to investigate the serum and urine metabolites profiling of lactating dairy cows through proton nuclear magnetic resonance (¹H-NMR) spectroscopy and comparing those between healthy (CON) and subclinical ketosis (SCK) groups. Six lactating dairy cows were categorized into CON and SCK groups. All experimental Holstein cows were fed total mixed ration. Serum and urine samples were collected from the jugular vein of the neck and by hand sweeping the perineum, respectively. The metabolites in the serum and urine were determined using ¹H-NMR spectroscopy. Identification and quantification of metabolites was performed by Chenomx NMR Suite 8.4 software. Metabolites statistical analysis was performed by Metaboanalyst version 5.0 program. In the serum, the acetoacetate level was significantly (p < 0.05) higher in the SCK group than in the CON group, and whereas acetate, galactose and pyruvate levels tended to be higher. CON group had significantly (p < 0.05) higher levels of 5-aminolevulinate and betaine. Indole-3-acetate, theophylline, p-cresol, 3-hydroxymandelate, gentisate, N-acetylglucosamine, N-nitrosodimethylamine, xanthine and pyridoxine levels were significantly (p < 0.05) higher in the urine of the SCK group than that in the CON group, which had higher levels of homogentisate, ribose, gluconate, ethylene glycol, maltose, 3-methyl-2-oxovalerate and glycocholate. Some significantly (p < 0.05) different metabolites in the serum and urine were associated with ketosis diseases, inflammation, energy balance and body weight. This study will be contributed useful a future ketosis metabolomics studies in Korea.

• Journal of Korea Multimedia Society
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• v.8 no.1
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• pp.79-87
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• 2005

In e-commerce applications, a public key cryptosystem is an important and indispensible element for the basic security operations such as authentication, digital signaturing, and key distribution. In wired network environments, the public key infrastructure certificate, which is based on X.509 specification, has been widely used. On the other hand, it still remains difficult to use the certificate information in wireless network environments due to the inherent limitations of the hand-held devices such as low computational power and short battery life. In this paper, we facilitate a codesign approach by implementing a software public-key cryptosystem and classifying its internal computation overheads quantitatively using a software profiling technique. Moreover, we propose a method to analyze the profiled data and apply it to the problem of software/hardware partitioning in a codesign approach. As an illustrative example, we analyze the computational overheads of an EC-Elfagamal application and examine a critical computational path.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.10a
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• pp.765-768
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• 2012

Recently, the supply ratio of smart devices application has become increasable, utilization of device increases constantly. At the same time, used application is more gentrified. However, using time of devices is decreased. To solve these problems, many research is studying about the hardware/software. One of them is profiling power consumption by process units. The process can be managed, based on measured energy consumption data. These means that it can efficiently use the residual energy. Application at the stage of program design can analyze and used-energy using the trace by considering the low-power can design. In this paper, we studied software-based power-metering framework for android platform. We survey each process-level power consumption measurement techniques, compare advantages and disadvantages of the technique and propose improved measures.

• Nuclear Medicine and Molecular Imaging
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• v.41 no.4
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• pp.299-308
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• 2007

Purpose: The aim of this study was to develop a bioinformatics software and to test it in serum samples of papillary thyroid cancer using mass spectrometry (SELDI-TOF-MS). Materials and Methods: Development of 'Protein analysis' software performing decision tree analysis was done by customizing C4.5. Sixty-one serum samples from 27 papillary thyroid cancer, 17 autoimmune thyroiditis, 17 controls were applied to 2 types of protein chips, CM10 (weak cation exchange) and IMAC3 (metal binding - Cu). Mass spectrometry was performed to reveal the protein expression profiles. Decision trees were generated using 'Protein analysis' software, and automatically detected biomarker candidates. Validation analysis was performed for CM10 chip by random sampling. Results: Decision tree software, which can perform training and validation from profiling data, was developed. For CM10 and IMAC3 chips, 23 of 113 and 8 of 41 protein peaks were significantly different among 3 groups (p<0.05), respectively. Decision tree correctly classified 3 groups with an error rate of 3.3% for CM10 and 2.0% for IMAC3, and 4 and 7 biomarker candidates were detected respectively. In 2 group comparisons, all cancer samples were correctly discriminated from non-cancer samples (error rate = 0%) for CM10 by single node and for IMAC3 by multiple nodes. Validation results from 5 test sets revealed SELDI-TOF-MS and decision tree correctly differentiated cancers from non-cancers (54/55, 98%), while predictability was moderate in 3 group classification (36/55, 65%). Conclusion: Our in-house software was able to successfully build decision trees and detect biomarker candidates, therefore it could be useful for biomarker discovery and clinical follow up of papillary thyroid cancer.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.2A
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• pp.188-194
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• 2007

In order to become ubiquitous world, the compatibility of wireless machines has become the significant characteristic of a communication terminal. Thus, SDR is the most necessary technology and standard. However, among the environment which has different communication protocol, it's difficult to make a terminal with only hardware using ASIC or SoC. This paper suggests the processor that can accelerate several communication protocol. It can be connected with main-processor, and it is specialized PHY layer of network The C-program that is modeled with the wireless protocol IEEE802.11a and IEEE802.11b which are based on widely used modulation way; OFDM and CDM is compiled with ARM cross compiler and done simulation and profiling with Simplescalar-Arm version. The result of profiling, most operations were Viterbi operations and complex floating point operations. According to this result we suggested a co-processor which can accelerate Viterbi operations and complex floating point operations and added instructions. These instructions are simulated with Simplescalar-Arm version. The result of this simulation, comparing with computing only one ARM core, the operations of Viterbi improved as fast as 4.5 times. And the operations of complex floating point improved as fast as twice. The operations of IEEE802.11a are 3 times faster, and the operations of IEEE802.11b are 1.5 times faster.

• Journal of Broadcast Engineering
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• v.16 no.6
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• pp.1018-1025
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• 2011

Scalable Video Coding (SVC) extension of H.264/AVC is a new video coding standard for media convergence by providing diverse videos of different spatial-temporal-quality layers with a single bitstream. Recently, real-time SVC codecs are being developed for the application areas of surveillance video and mobile video, etc. This paper presents the design and implementation of a H.264/SVC decoder based on an embedded DSP using Open SVC Decoder (OSD) which is a real-time software decoder designed for the PC environment. The implementation consists of porting C code of the OSD software from PC to DSP environment, profiling the complexity performance of OSD with further optimization, and integrating the optimized decoder into the TI Davinci EVM (Evaluation Module). 50 QCIF/CIF frames or 15 SD frames per second can be decoded with the implemented DSP-based SVC decoder.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2005.09a
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• pp.134-138
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• 2005

The design of ion channel targeted library is a valuable methodology that can aid in the selection and prioritization of potential ion channel-likeness for ion-channel-targeted bio-screening from large commercial available chemical pool. The differences of property profiling between the 93 ion-channel active compounds from MDDR and CMC database and the ACDSC compounds were classified by suitable descriptors calculated with preADME software. Through the PCA, clustering, and similarity analysis, the compounds capable of ion channel activity were defined in ACDSC compounds pool. The designed library showed a tendency to follow the property profile of ion-channel active compounds and can be implemented with great time and economical efficiencies of ligand-based drug design or virtual high throughput screening from an enormous small molecule space.

• Journal of Microbiology and Biotechnology
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• v.16 no.6
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• pp.832-848
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• 2006

Systems biology has recently become an important research paradigm that is anticipated to decipher the metabolic, regulatory, and signaling networks of complex living organisms on the whole organism level. Thus, various research outputs are being generated, along with the development of many tools and resources for systems biology research. Accordingly, this review provides a comprehensive summary of the current resources and tools for systems biology research that will hopefully be helpful to researchers involved in this field. The resources are categorized into the following five groups: genome information and analysis, transcriptome and proteome databases, metabolic profiling and metabolic control analysis, metabolic and regulatory information, and software for computational systems biology. A summary table and some future perspectives are also provided.