• Title/Summary/Keyword: Evaluation algorithm

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Effect of Interactive Multimedia PE Teaching Based on the Simulated Annealing Algorithm

  • Zhao, Mingfeng
    • Journal of Information Processing Systems
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    • v.18 no.4
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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%.

An Architecture for 3D Audio Core Algorithm Evaluation DB (3차원 입체 음향 핵심 알고리즘 평가를 위한 DB 설계)

  • Hwang, Jaemin;Kim, Jeonghyuk;Kang, Sanggil
    • Journal of Information Technology and Architecture
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    • v.11 no.2
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    • pp.225-233
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    • 2014
  • In this paper an architecture for 3D audio core algorithm evaluation database system. Due to increase of 3D audio system through multimedia device, an evaluation system is required for evaluating the 3D core algorithms for developing 3D audio system. Conventional evaluation systems have some problems. Researchers have to learn usage of evaluation system, in addition it is inefficient to use and search audio sources because audio sources are not indexed in general. To solve these problems, we design the architecture of 3D audio core algorithm evaluation database system enabling to automatically evaluate core algorithms using database management system. Also we define XML metadata scheme for information of saved audio source in database. This approach allows improving efficiency of search audio source and use of audio database.

An Experimental Evaluation of the Vehicle Control Algorithm in Personal Rapid Transit System (개인고속이동시스템의 차량제어 알고리즘에 대한 실험적 평가)

  • Lee, Jun-Ho
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.56 no.10
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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.

Development of Human Sensibility Evaluation Algorithm through Comparison of Personality-group EEGs (성격 그룹의 뇌파 비교를 통한 감성평가 알고리즘의 개발)

  • Woo, Seung-Jin;Lee, Sang-Han;Kim, Dong-Jun
    • Proceedings of the KIEE Conference
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    • 2004.07d
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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.

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On Evaluation Algorithm for Hierarchical Structure of Attributes with Interaction Relationship (상호연관성을 지닌 계층구조형문제의 평가 알고리즘)

  • Lee C.Y.;Lee S.T.
    • Journal of Korean Port Research
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    • v.7 no.1
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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.

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Evaluation Method of College English Education Effect Based on Improved Decision Tree Algorithm

  • Dou, Fang
    • Journal of Information Processing Systems
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    • v.18 no.4
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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.

Effective incremental attribute evaluation for a hierarchical attribute grammar (계층적 속성문법을 위한 효율적인 점진적 속성평가)

  • 장재춘;김태훈
    • Journal of Internet Computing and Services
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    • v.2 no.3
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    • pp.71-79
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    • 2001
  • In Incremental attribute evaluation algorithm, a new input attribute is exact1y compared with a previous input attribute tree, and then determine which subtrees from the old should be used in constructing the new one. In this paper incremental attribute evaluation algorithm was used to make incremental evlauation of hierarchical attribute grammar more efficient1y, and reconstructing the incremental attribute evaluation algorithm by analyzing that of Carle and Pollock, finally the incremental attribute evaluation algorithm for optimalized attribute tree d' copy was constructed by applying element of attribute !ree dcopy to a new attribute tree d' copy. Also proving that how the reused nod and type of defined parameter in input program carried out the incremental attribute evaluation by using that algorithm.

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Development of Web Accessibility Evaluation Algorithm-Based upon Table Element (웹 접근성 평가 알고리즘 개발-Table 요소 중심으로)

  • Park, Seong-Je;Kim, Jong-Weon
    • Journal of Korea Society of Industrial Information Systems
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    • v.18 no.4
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    • pp.81-87
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    • 2013
  • Due to the development of IT technologies and the Internet penetration, the importance of Web accessibility has greatly increased and accordingly been studied a lot. This study noticed that the current evaluation algorithm for "Table Elements," which are used for data and layout tables, has many problems. Based on the Web Accessibility Guidelines, this study presents an improved evaluation algorithm for "Table Elements" and verifies its validity.

A Design of the Evaluation Devices for the Vehicle Operational Control Algorithm of Personal Rapid Transit System (개인고속이동 시스템의 차량운행제어 알고리즘 검증을 위한 모의 장치 설계에 대한 연구)

  • Lee, Jun-Ho;Shin, Kyung-Ho;Kim, Yong-Kyu
    • Proceedings of the KIEE Conference
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    • 2007.07a
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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.

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An Improved Automated Spectral Clustering Algorithm

  • Xiaodan Lv
    • Journal of Information Processing Systems
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    • v.20 no.2
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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.