• Journal of the Institute of Electronics Engineers of Korea TE
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• v.39 no.4
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• pp.329-334
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• 2002

For the testability, this paper proposed the algorithm at autonomous synthesis which includes the data path structure as the self testing as possible on high level synthesis method when VHDL, coding is used in the system design area. In the proposed algorithm of this paper, MUXs and registers are assigned to the data path of designed system. And the designed data path could be mapped the H/W specification of described VHDL coding to the testable library. As a results, it was mapped H/W to the assign algorithm that is minimized MUX and the registers in collision graph.

• International Journal of Computer Science & Network Security
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• v.22 no.1
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• pp.139-148
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• 2022

Research into wireless sensor networks (WSNs) is a trendy issue with a wide range of applications. With hundreds to thousands of nodes, most wireless sensor networks interact with each other through radio waves. Limited computational power, storage, battery, and transmission bandwidth are some of the obstacles in designing WSNs. Clustering and routing procedures have been proposed to address these concerns. The wireless sensor network's most complex and vital duty is routing. With the Greedy Perimeter Stateless Routing method (GPSR), an efficient and responsive routing protocol is built. In packet forwarding, the nodes' locations are taken into account while making choices. In order to send a message, the GPSR always takes the shortest route between the source and destination nodes. Weighted directed graphs may be constructed utilising four distinct distance metrics, such as Euclidean, city block, cosine, and correlation distances, in this study. NS-2 has been used for a thorough simulation. Additionally, the GPSR's performance with various distance metrics is evaluated and verified. When compared to alternative distance measures, the proposed GPSR with correlation distance performs better in terms of packet delivery ratio, throughput, routing overhead and average stability time of the cluster head.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.14 no.3
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• pp.201-207
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• 2021

Deep learning, a type of machine learning, performs learning while changing the weights as it progresses through each learning process. Tensor Flow and Keras provide the results of the end of the learning in graph form. Thus, If an error occurs, the result must be discarded. Consequently, existing technologies provide a function to roll back learning results, but the rollback function is limited to results up to five times. Moreover, they applied the concept of MLOps to track the deep learning process, but no rollback capability is provided. In this paper, we construct a system that manages the intermediate value of the learning process by blockchain to record the intermediate learning process and can rollback in the event of an error. To perform the functions of blockchain, the deep learning process and the rollback of learning results are designed to work by writing Smart Contracts. Performance evaluation shows that, when evaluating the rollback function of the existing deep learning method, the proposed method has a 100% recovery rate, compared to the existing technique, which reduces the recovery rate after 6 times, down to 10% when 50 times. In addition, when using Smart Contract in Ethereum blockchain, it is confirmed that 1.57 million won is continuously consumed per block creation.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.48 no.4
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• pp.27-34
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• 2011

In this paper, it was presented a design on the dynamic multimedia fingerprinting code for anti-collusion code(ACC) in the protection of multimedia content. Multimedia fingerprinting code for the conventional ACC, is designed with a mathematical method to increase k to k+1 by transform from BIBD's an incidence matrix to a complement matrix. A codevector of the complement matrix is allowanced fingerprinting code to a user' authority and embedded into a content. In the proposed algorithm, the feature points were drawing from a content which user bought, with based on these to design the dynamical multimedia fingerprinting code. The candidate codes of ACC which satisfied BIBD's v and k+1 condition is registered in the codebook, and then a matrix is generated(Below that it calls "Rhee matrix") with ${\lambda}+1$ condition. In the experimental results, the codevector of Rhee matrix based on a feature point of the content is generated to exist k in the confidence interval at the significance level ($1-{\alpha}$). Euclidean distances between row and row and column and column each other of Rhee matrix is working out same k value as like the compliment matrices based on BIBD and Graph. Moreover, first row and column of Rhee matrix are an initial firing vector and to be a forensic mark of content protection. Because of the connection of the rest codevectors is reported in the codebook, when trace a colluded code, it isn't necessity to solve a correlation coefficient between original fingerprinting code and the colluded code but only search the codebook then a trace of the colluder is easy. Thus, the generated Rhee matrix in this paper has an excellent robustness and fidelity more than the mathematically generated matrix based on BIBD as ACC.

• Therapeutic Science for Rehabilitation
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• v.7 no.1
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• pp.63-77
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• 2018

Objective : The purpose of this study was to investigate the effects of task-oriented training with functional electrical stimulation on hand function in incomplete cervical cord injury. Method : The subjects of the study were 3 adults diagnosed as incomplete cervical cord injury. The design of this study was ABA single-subject research design to compare dominant hand function of before and after intervention and detect individual effects. The experiment consisted of 30sessions, in which baseline process A1 and A2 were implemented 5 sessions each for 10sessions. Intervention B was implemented 20 sessions. The dependent variable was converted to the change of hand function every session, and Canadian Occupational Performance Measure (COPM), Jebsen-Taylor Hand Function Test(JTHFT), Wolf Motor Function Test(WMFT) were selected for outcome measurements. Result analysis was suggested through visual analysis using a graph and comparison of pre, post and follow-up intervention measurements. Results : As a result, the quality and quantity of dominant hand function increased during intervention B compared to the baseline A1 for all subjects. Baseline A2 was also maintained without training. Additionally, JTHFT, WMFT and COPM scores demonstrated improvement and maintain. The follow up JTHFT and WMFT showed increased required time on all subjects and decrease or maintain task performance and satisfaction in COPM. Conclusion : The task-oriented training with function electrical stimulation in this study has been positive effects on hand function and task performance and satisfaction.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.4B
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• pp.708-714
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• 2000

In this paper, an one-dimensional VLSI array for high speed processing of fractal image compression algorithm based the quad-tree partitioning method is proposed. First of all, the single assignment code algorithm is derived from the sequential Fisher's algorithm, and then the data dependence graph(DG) is obtained. The two-dimension array is designed by projecting this DG along the optimal direction and the one-dimensional VLSI array is designed by transforming the obtained two-dimensional array. The number of Input/Output pins in the designed one-dimensional array can be reduced and the architecture of process elements(PEs) can he simplified by sharing the input pins of range and domain blocks and internal arithmetic units of PEs. Also, the utilization of PEs can be increased by reusing PEs for operations to the each block-size. For fractal image compression of 512X512gray-scale image, the proposed array can be processed fastly about 67 times more than sequential algorithm. The operations of the proposed one-dimensional VLSI array are verified by the computer simulation.

• Journal of Microbiology and Biotechnology
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• v.11 no.3
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• pp.524-528
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• 2001

The measurement of radiation response using simple and informative techniques would be of great value in studying the genetic risk following occupational, therapeutic, or accidental exposure to radiation. When patients receive radiation therapy, many suffer from side effects. Since each patient receives a different dose due to different physical conditions, it is important to measure the exact dose of radiation received by each patient to lessen the side effects. Even though several biological dosimetric systems have already been developed, there is no ideal system that can satisfy all the criteria for an idean dosimetric system, especially for low-dose radiation as used in radiation therapy. In this study, an SOS Chromotest of E. coli PQ37 was evaluated as a novel dosimeter for low-dose gamma-rays. E. coli PQ37 was originally developed to screen chemical mutagens using the SOS Chromotest-a colorimtric assay, based on the induction of ${\beta}$-galactosidase ue to DNA damage. The survival fraction of E. coli PQ37 decreased dose-dependently with an increasing dose of cobalt-60 gamma-rays. Also, a good linear correlation was found between the biological damage revealed by the ${\beta}$-galactosidase expression and the doses of gamma-rays. The expression of ${\beta}$-galactosidase activity that responded to low-dose radiation under 1 Gy was $Y=0.404+(0.089{\pm}0.3)D+(-0.018{\pm}0.16)D^2$ (Y, absorbance at 420 nm; D, Dose of irradiation) as calculated using Graph Pad In Plot and Excel. When a rabbit was fed with capsules containing an agar block embdded with E. coli PQ37 showed a linear response to the radiation doses. Accordingly, the results confirm that E. coli PQ37 can be used as a sensitive biological dosimeter fro cobalt-60 gamma-rays. To the best of our knowledge, this is the first time that a bacterium has been used as a biological dosimeter, especially for low-dose radiation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.1C
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• pp.87-92
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• 2006

An $AB^2$ modular operation is an efficient basic operation for the public key cryptosystems and various systolic architectures for $AB^2$ modular operation have been proposed. However, these architectures have a shortcoming for cryptographic applications due to their high area complexity. Accordingly, this paper presents an partitioned $AB^2$ systolic modular multiplier over GF($2^m$). A dependency graph from the MSB $AB^2$ modular multiplication algorithm is partitioned into 1/3 to get an partitioned $AB^2$ systolic multiplier. The multiplier reduces the area complexity about 2/3 compared with the previous multiplier. The multiplier could be used as a basic building block to implement the modular exponentiation for the public key cryptosystems based on smartcard which has a restricted hardware requirements.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.8
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• pp.81-87
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• 1999

In general, feature detection and tracking algorithms is classified by EBGM using Garbor-jet, NNC-R and STK algorithm using pixel eigenvalue. In those algorithms, EBGM and NCC-R detect features with feature model, but STK algorithm has a characteristics of an automatic feature selection. In this paper, to solve the initial problem of NR tracking in STK algorithm, we detected features using STK algorithm in modelled feature region and tracked features with NR method. In tracking, to improve the tracking accuracy for features by NR method, we proposed BMA-NR method. We evaluated that BMA-NR method was superior to NBMA-NR in that feature tracking accuracy, since BMA-NR method was able to solve the local minimum problem due to search window size of NR.

• Journal of The Korean Association of Information Education
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• v.25 no.5
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• pp.673-681
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• 2021

This study is a case study of artificial intelligence education subjects in the graduate school of education. The main educational contents consisted of understanding and practice of machine learning, data analysis, actual artificial intelligence using Entries, artificial intelligence and physical computing. As a result of the survey on the educational effect after the application of the curriculum, it was found that the students preferred the use of the Entry AI block and the use of the Blacksmith board as a physical computing tool as the priority applied to the elementary education field. In addition, the data analysis area is effective in linking math data and graph education. As a physical computing tool, Husky Lens is useful for scalability by using image processing functions for self-driving car maker education. Suggestions for desirable AI education include training courses by level and reinforcement of data collection and analysis education.