• 말소리와 음성과학
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• 제16권1호
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• pp.57-65
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• 2024

정상압 수두증(normal pressure hydrocephalus, NPH)은 뇌의 뇌척수압은 정상 범위에 있지만 뇌척수액이 정상 수준보다 증가해 뇌실확장증을 유발하는 질환으로, 조음기관의 운동성과 범위가 감소해 조음교대운동(diadochokinesis, DDK)과 말명료도에 영향을 줄 수 있다. 본 연구에서는 NPH 환자 38명과 정상 노인 38명을 대상으로 /파/, /타/, /카/ 및 /파타카/에 대한 DDK 과제를 실시한 후, 정확한 산출만 측정한 DDK(accurate token-DDK)와 부정확한 산출 포함, 모든 산출시도를 측정한 DDK(all token-DDK)의 두 방법을 모두 사용해 그 결과를 비교하였다. 또한 DDK가 NPH와 정상 노인의 두 집단을 얼마나 정확하게 분류 가능한지, 그리고 DDK와 말명료도 간 상관관계는 어떠한지에 대해서도 알아보았다. 연구결과, NPH 집단과 정상 노인 집단 간에는 accurate token-DDK와 all token-DDK 모두에서 유의한 차이가 있었고, 집단 분류정확도는 accurate token-DDK의 경우 75.0%, all token-DDK의 경우 77.6%로 비교적 높았다. 그러나 NPH 집단에서 DDK 속도와 말명료도 측정값 간에는 유의한 상관관계가 없었다. 본 연구는 NPH 환자의 말운동능력을 민감하게 평가하는 데에 DDK가 유용한 방법임을 시사한다.

• International Journal of Advanced Culture Technology
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• 제8권1호
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• pp.157-164
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• 2020

The reinforcement of the token, which is based on the token economy currently applied in blockchain-based cryptography, plays a critical role in forming the cryptographic-related ecosystem. Therefore, in this paper, it was investigated the reinforcement principle of token supporting the Token economy for blockchain model. In order to create a healthy ecosystem based on the reinforcement system principle, it is necessary to find ways to secure scalability by seeking consensus between the participants and the market economy structure so that it can generate an influx of more participants than seeking to maximize profits of certain people. Desirable behavior is defined as an action required by ecosystem participants that have the property of making the token ecosystem sustainable, and to do so, each individual receives appropriate incentives (rewards) when taking this action, ultimately encouraging voluntary participation and action by all participants in the ecosystem to optimize the interests of both individuals and participants. The expected benefit of this study may contribute to the establishment of various business models based on the principle of the reinforcement system.

• International journal of advanced smart convergence
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• 제12권4호
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• pp.171-176
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• 2023

This study is about a speech recognition error correction system designed to detect and correct speech recognition errors before natural language processing to increase the success rate of intent analysis in natural language processing with optimal efficiency in various service domains. An encoder is constructed to embedded the correct speech token and one or more error speech tokens corresponding to the correct speech token so that they are all located in a dense vector space for each correct token with similar vector values. One or more utterance tokens within a preset Manhattan distance based on the correct utterance token in the dense vector space for each embedded correct utterance token are detected through an error detector, and the correct answer closest to the detected error utterance token is based on the Manhattan distance. Errors are corrected by extracting the utterance token as the correct answer.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1992년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 19-21 Oct. 1992
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• pp.37-42
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• 1992

The main purpose of the paper is to derive asymptotic formulae for performance characteristics(throughput, delay) of large-scale token-passing network with buffered stations and to optimize the buffer capacity with respect to the probability of data generation. We consider two versions of token-passing network: uniform and nonuniform token-passing time interval. All results obtained are supported by simulations.

• 한국시뮬레이션학회논문지
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• 제2권1호
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• pp.46-54
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• 1993

Analytic and simulation models for prioritized token ring are presented in this paper. Its protocol is based on prioritized token ring with reservation (R-PTR). Since the protocol of the R-PTR is simple and the performance of the R-PTR is not inferior to that of the IEEE-PTR under almost all traffic load environments, we use the R-PTR as our token ring model. By using the properties of Markovian process, the expressions for average throughput and average packet transmission delay are derived. The results obtained from the analytic model are compared with that of the discrete event simulation model.

• Journal of Information Processing Systems
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• 제18권5호
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• pp.628-636
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• 2022

Automatic program repair (APR) techniques focus on automatically repairing bugs in programs and providing correct patches for developers, which have been investigated for decades. However, most studies have limitations in repairing complex bugs. To overcome these limitations, we developed an approach that augments datasets by utilizing token tagging and applying machine learning techniques for APR. First, to alleviate the data insufficiency problem, we augmented datasets by extracting all the methods (buggy and non-buggy methods) in the program source code and conducting token tagging on non-buggy methods. Second, we fed the preprocessed code into the model as an input for training. Finally, we evaluated the performance of the proposed approach by comparing it with the baselines. The results show that the proposed approach is efficient for augmenting datasets using token tagging and is promising for APR.

• International Journal of Advanced Culture Technology
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• 제8권1호
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• pp.128-134
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• 2020

The purpose of this study is to investigate the role and function of tokens to form a healthy blockchain-based ecosystem. Tokens must be constructed in a way that enhances their desired behavior to grow into a healthy token economy. The actions required of ecosystem participants in designing tokens should enable each individual to receive appropriate incentives (rewards) and encourage voluntary participation in taking this action. Also, all ecosystem participants must design to make the token ecosystem self-sustainable by generating profits. For example, in Bitcoin's proof-of-work method, mining is designed as a desirable behavior. Token-based services should be designed to induce multiple engagements, to design penalties for undesirable behavior, and to take into account evolutionary development potentials. Besides, the economic value of the entire token ecosystem will increase if the value that is designed and designed to take into account the revolutionary Innovation Possibility is greater than the reward amount paid to tokens. This study will contribute to presenting relevant service model by presenting how to design tokens and criteria when establishing blockchain-based service model. Future research is needed to discover new facts through a detailed comparative analysis between Tokennomics models.

• 대한전기학회논문지:시스템및제어부문D
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• 제54권10호
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• pp.615-619
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• 2005

Token coherence protocol has many good reasons against snooping/directory-based protocol in terms of latency, bandwidth, and complexity. Token counting easily maintains correctness of the protocol without global ordering of request which is basis of other dominant cache coherence protocols. But this lack of global ordering causes starvation which is not happening in snooping/directory-based protocols. Token coherence protocol solves this problem by providing an emergency mechanism called persistent request. It enforces other processors in the competition (or accessing same shared memory block, to give up their tokens to feed a starving processor. However, as the number of processors grows in a system, the frequency of starvation occurrence increases. In other words, the situation where persistent request occurs becomes too frequent to be emergent. As the frequency of persistent requests increases, not only the cost of each persistent matters since it is based on broadcasting to all processors, but also the increased traffic of persistent requests will saturate the bandwidth of multiprocessor interconnection network. This paper proposes a new request mechanism that defines order of requests to reduce occurrence of persistent requests. This ordering mechanism has been designed to be decentralized since centralized mechanism in both snooping-based protocol and directory-based protocol is one of primary reasons why token coherence protocol has advantage in terms of latency and bandwidth against these two dominant Protocols.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2002년도 춘계학술대회 논문집
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• pp.470-473
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• 2002

Most networks for automation are tuned to an expected traffic at their design stage. During their actual operations, however, the networks experience considerable changes in traffic from time to time. These traffic changes caused by common events like machine failure and production schedule change may adversely affect the network performance and, in turn, the performance of the connected devices. This paper presents communication delay model for Profibus token passing protocol, and introduces TTR selection methods to maintain a uniform level of network performance at all stations under changing network traffic.

• 아동학회지
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• 제8권2호
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• pp.61-71
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• 1987

The effects of token and social reinforcement on inappropriate study behaviors of nursery school children were investigated. The subjects were three nursery school boys, and the target behaviors were : 1) out-of-seat behaviors, 2) bothering other children, and 3) disruptive behaviors. The ABAB(Reversal) design was used in this experiment. It consisted of four periods : baseline, reinforcement I, reversal, and reinforcement II. During the reinforcement period, social reinforcement as well as token reinforcement was applied. In all three subjects, inappropriate study behaviors decreased during the reinforcement periods (I, II), and increased during the reversal period, showing the effects of token and social reinforcement. The subjects showed stability in three post-experimental tests, indicating that modification of inappropriate study behaviors was being maintained.