• Journal of Information Processing Systems
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• 제18권4호
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• pp.562-574
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• 2022

As traditional ways of evaluation prove to be ineffective in evaluating the effect of interactive multimedia physical education (PE) teaching, this study develops a new evaluation model based on the simulated annealing algorithm. After the evaluation subjects and the principle of the evaluation system are determined, different subjects are well chosen to constitute the evaluation system and given the weight. The backpropagation neural network has been improved through the simulated annealing algorithm, whose improvement indicates the completion of the evaluation model. Simulation results show that the evaluation model is highly efficient. Compared with traditional evaluation models, the proposed one enhances students' performance in PE classes by 50%.

• 정보화연구
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• 제11권2호
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• pp.225-233
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• 2014

오디오 산업은 프리미엄 산업으로써 나날이 발전 하고 있다. 입체 음향 시스템에 관한 연구는 많이 진행 되고 있다. 하지만 Audio database, algorithm, evaluation, metadata scheme 이 모두 각각 이루어지고 있다. 하나의 시스템에서 만들어진 audio 알고리즘을 평가 하고, 저장 할 수 있다면 입체 음향 오디오 연구 발전에 도움이 될 것이다. 그래서 이 논문 에서는 실감형 3D 오디오의 알고리즘을 시스템 적으로 평가 할 수 있는 Database Architecture 제안 하고, 이 Database system 구현을 위하여 XML metadata scheme를 정의 하였다. 본 논문에서는 새로운 오디오 평가 DB를 제시하고, 이를 체계적으로 구현하기 위한 설계를 제시하고자 한다.

• 전기학회논문지
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• 제56권10호
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• pp.1770-1774
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• 2007

In this paper we deal with a design of the evaluation system to assess the vehicle operational control algorithm for Personal Rapid Transit(PRT) system. PRT system is different from the conventional rail traffic system in such that the station is off-line so as to guarantee a very short headway. In this study we propose an evaluation system to assess the performance of the proposed vehicle control algorithm. The evaluation system is composed of virtual vehicles, central control system, virtual wayside facilities, monitoring equipments. The virtual vehicles are made up by the laptop computers and the central control system employs Power PC process of Motorola Inc. The wayside facilities are implemented by employing the PXI module of the National Instruments Corporation. In order to test the proposed evaluation system a test algorithm is used, which has been simulated in the combined simulation system between Labview Simulation Interface Toolkit and Matlab/Simulink.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2004년도 하계학술대회 논문집 D
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• pp.2699-2701
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• 2004

This paper describes a new algorithm for human sensibility evaluation using two personality-group templates of electroencephalogram (EEG) signals. EEG signals of two groups arc collected in relaxed state, comfortable state and uncomfortable state. First of all, the characteristics of EEGs in relaxed state for two groups are compared. After verification of the results, an algorithm for sensibility evaluation is developed. In comparison of the characteristics for two personality-group EEG signals. there are distinct difference between the EEG patterns of the extrovert and the introvert. Upon these findings, the algorithm for human sensibility evaluation is designed. The results of the algorithm showed 90.0% of coincidence with given tasks. This seems to be compromising results for subject independent sensibility evaluation using EEG signal.

• 한국항만학회지
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• 제7권1호
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• pp.5-12
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• 1993

In complex decision making such as ill-defined system, one of the main problem is how to treat ambiguous aspect of the decision making. According to the complexity and ambiguity of the objective systems, many types of evaluation attributes are necessary for the rational decision and the relationship among the attributes become complex and fuzzy. Fuzzy integral is very effective to evalute the complex system with interaction between attributes but how to save the evaluation efforts in the decision making process of grading the membership of the objects or alternative is the problem to be tackled. Because the more object there are to evaluate, the number of decisions to made increase exponentially. Therefore, this paper aimes to propose a new evaluation algorithm based on fuzzy integral which can save the evaluator's efforts in decision making process. The proposed algorithm is constructed as follows : First, compose the fuzzy measure by introducing AHP(Analytical Hierachy Process) & mutual interaction coefficient. Second, generate fuzzy measure value of monotone family set for calculating the fuzzy integral. The effectiveness of the proposed algorithm is investigated through the example and sensitivity of interaction coefficient is illustrated.

• Journal of Information Processing Systems
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• 제18권4호
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• pp.500-509
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• 2022

With the rapid development of educational informatization, teaching methods become diversified characteristics, but a large number of information data restrict the evaluation on teaching subject and object in terms of the effect of English education. Therefore, this study adopts the concept of incremental learning and eigenvalue interval algorithm to improve the weighted decision tree, and builds an English education effect evaluation model based on association rules. According to the results, the average accuracy of information classification of the improved decision tree algorithm is 96.18%, the classification error rate can be as low as 0.02%, and the anti-fitting performance is good. The classification error rate between the improved decision tree algorithm and the original decision tree does not exceed 1%. The proposed educational evaluation method can effectively provide early warning of academic situation analysis, and improve the teachers' professional skills in an accelerated manner and perfect the education system.

• 인터넷정보학회논문지
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• 제2권3호
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• pp.71-79
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• 2001

점진적 속성 평가 알고리즘에서는 새로운 입력 트리가 기존 입력 트리와 정확히 비교되어서 새로운 트리를 구성할 때 기존 속성 트리의 어떤 서브 트리를 사용해야 하는가를 결정한다. 이 논문에서는 계층적 속성 문법의 점진적 평가를 효율적으로 하기 위해 점진적 속성 평가 알고리즘을 이용하였으며 Carle과 Pollock의 알고리즘을 분석하여 점진적 속성 평가 알고리즘으로 재구성하고, 속성 트리 dcopy의 구성요소를 새로운 속성 트리 d'copy에 적용하여 최적화된 속성 트리 d'copy의 점진적 속성 평가 알고리즘을 구성하였다. 또한 점진적 속성 평가 알고리즘을 이용하여 실제적인 입력 프로그램에서 재사용된 노드의 표현과 정의된 변수 형(type)이 어떻게 점진적인 속성 평가를 수행하는가를 나타내었다.

• 한국산업정보학회논문지
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• 제18권4호
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• pp.81-87
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• 2013

IT 기술의 발달과 인터넷의 확산으로 웹 접근성에 대한 중요성이 극대화 되고 있으며, 그에 따라 다양한 웹 접근성 관련 연구가 진행되고 있다. 특히 데이터 테이블과 레이아웃 테이블 용도로 사용되는 "Table 요소"는 자동화평가도구의 평가에서 많은 문제점을 가지고 있다. 이에 본 연구에서는 웹 접근성 지침을 기반으로 "Table 요소"에 대한 개선된 평가 알고리즘을 제시하고 그 타당성을 검증하였다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2007년도 제38회 하계학술대회
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• pp.1191-1192
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• 2007

In this paper we deal with a design of the evaluation system to assess the vehicle operational control algorithm for Personal Rapid Transit(PRT) system. PRT system is different from the conventional rail traffic system in such point that the station is off-line so as to guarantee a very short headway. In this study we propose a evaluation system to assess the performance of the proposed vehicle control algorithm. The evaluation system is composed of virtual vehicles, central control system, virtual wayside facilities, monitoring equipments. In order to test the proposed evaluation system a test algorithm is used, which has been simulated in the combined simulation system between Labview Simulation Interface Toolkit and Matlab/Simulink.

• Journal of Information Processing Systems
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• 제20권2호
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• pp.185-199
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• 2024

In this paper, an improved automated spectral clustering (IASC) algorithm is proposed to address the limitations of the traditional spectral clustering (TSC) algorithm, particularly its inability to automatically determine the number of clusters. Firstly, a cluster number evaluation factor based on the optimal clustering principle is proposed. By iterating through different k values, the value corresponding to the largest evaluation factor was selected as the first-rank number of clusters. Secondly, the IASC algorithm adopts a density-sensitive distance to measure the similarity between the sample points. This rendered a high similarity to the data distributed in the same high-density area. Thirdly, to improve clustering accuracy, the IASC algorithm uses the cosine angle classification method instead of K-means to classify the eigenvectors. Six algorithms-K-means, fuzzy C-means, TSC, EIGENGAP, DBSCAN, and density peak-were compared with the proposed algorithm on six datasets. The results show that the IASC algorithm not only automatically determines the number of clusters but also obtains better clustering accuracy on both synthetic and UCI datasets.