• 제목/요약/키워드: Individual Network

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Recognition of Passports using CDM Masking and ART2-based Hybrid Network

  • Kim, Kwang-Baek;Cho, Jae-Hyun;Woo, Young-Woon
    • Journal of information and communication convergence engineering
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    • 제6권2호
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    • pp.213-217
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    • 2008
  • This paper proposes a novel method for the recognition of passports based on the CDM(Conditional Dilation Morphology) masking and the ART2-based RBF neural networks. For the extraction of individual codes for recognizing, this paper targets code sequence blocks including individual codes by applying Sobel masking, horizontal smearing and a contour tracking algorithm on the passport image. Individual codes are recovered and extracted from the binarized areas by applying CDM masking and vertical smearing. This paper also proposes an ART2-based hybrid network that adapts the ART2 network for the middle layer. This network is applied to the recognition of individual codes. The experiment results showed that the proposed method has superior in performance in the recognition of passport.

Passport Recognition using Fuzzy Binarization and Enhanced Fuzzy RBF Network

  • Kim, Kwang-Baek
    • 한국지능시스템학회논문지
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    • 제14권2호
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    • pp.222-227
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    • 2004
  • Today, an automatic and accurate processing using computer is essential because of the rapid increase of travelers. The determination of forged passports plays an important role in the immigration control system. Hence, as the preprocessing phase for the determination of forged passports, this paper proposes a novel method for the recognition of passports based on the fuzzy binarization and the fuzzy RBF network. First, for the extraction of individual codes for recognizing, this paper targets code sequence blocks including individual codes by applying Sobel masking, horizontal smearing and a contour tracking algorithm on the passport image. Then the proposed method binarizes the extracted blocks using fuzzy binarization based on the trapezoid type membership function. Then, as the last step, individual codes are recovered and extracted from the binarized areas by applying CDM masking and vertical smearing. This paper also proposes an enhanced fuzzy RBF network that adapts the enhanced fuzzy ART network for the middle layer. This network is applied to the recognition of individual codes. The results of the experiments for performance evaluation on the real passport images showed that the proposed method has the better performance compared with other approaches.

INDIVIDUAL AND SOCIAL INCENTIVES VERSUS R&D NETWORK RESTRICTION

  • ALGHAMDI, MOHAMAD
    • Journal of the Korean Society for Industrial and Applied Mathematics
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    • 제23권4호
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    • pp.329-350
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    • 2019
  • This paper examines individual and social strategies to form profitable cooperation networks. These two types of strategies measure network stability and efficiency that may not meet in a single network. We apply restrictions on knowledge flows (R&D spillovers) and links formation to integrate these benefits into structures that ensure high outcomes for both strategies. The results suggest that linking the spillovers to the firms' positions and restricting cooperation contribute to reducing the conflict between the individual and social strategies in the development of cooperative networks.

Recognition of Individual Holstein Cattle by Imaging Body Patterns

  • Kim, Hyeon T.;Choi, Hong L.;Lee, Dae W.;Yoon, Yong C.
    • Asian-Australasian Journal of Animal Sciences
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    • 제18권8호
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    • pp.1194-1198
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    • 2005
  • A computer vision system was designed and validated to recognize an individual Holstein cattle by processing images of their body patterns. This system involves image capture, image pre-processing, algorithm processing, and an artificial neural network recognition algorithm. Optimum management of individuals is one of the most important factors in keeping cattle healthy and productive. In this study, an image-processing system was used to recognize individual Holstein cattle by identifying the body-pattern images captured by a charge-coupled device (CCD). A recognition system was developed and applied to acquire images of 49 cattles. The pixel values of the body images were transformed into input data comprising binary signals for the neural network. Images of the 49 cattle were analyzed to learn input layer elements, and ten cattles were used to verify the output layer elements in the neural network by using an individual recognition program. The system proved to be reliable for the individual recognition of cattles in natural light.

Information Propagation in Social Networks with Overlapping Community Structure

  • Zhao, Narisa;Liu, Xiaojun
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제11권12호
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    • pp.5927-5942
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    • 2017
  • Many real networks exhibit overlapping community structures. Recent studies have been performed that analyze the impact of overlapping community structure on information propagation, but few of them concerned with individual behaviors. From this point of view, we propose a Markov process model to evaluate the performance of information propagation in social networks with overlapping community structures. In addition, many individual social behaviors are combined in the model. For example, individuals may exhibit selfish behaviors, such as individual and social selfishness, and people may discard the information after they have used it. The accuracy of the model is verified by simulation. Furthermore, the numerical results show that both overlapping community structure of the network and individual behaviors have a significant impact on the outbreak size and propagation speed of the information. Additionally, the overlapping community structure of the social network can reduce the impact of selfishness on information propagation.

「동의보감(東醫寶鑑)」의 안문(眼門) 처방에서 활용된 본초 구성 연구 (A Study of the Herb Composition in the Donguibogam Opthalmic Chapter)

  • 이명선;오용택;김안나;곽화선;정경희;김홍준
    • 대한한의진단학회지
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    • 제23권1호
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    • pp.19-28
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    • 2019
  • Objectives This study has conducted a network analysis of individual prescriptions from the Donguibogam opthalmic Chapter. In addition, medicinal herbs used for internal use were analyzed. By analyzing the correlation of these two this study aims to investigate the significance between individual herbs used in ophthalmic diseases through network analysis. Methods Medicinal herbs from Donguibogam Opthalmic Chapter were analyzed and herbal combinations were extracted from the medicinal herbs by using the network analysis tool NetMiner 4 program. Result Based on network analysis of medicinal herbs from Donguibogam Opthalmic Chapter, frequently used medicinal herbs and herbal combinations were analyzed and were consisted of 4 communities. Conclusion This study shows the most frequent medicinal herbs and herbal combinations from the Donguibogam Opthalmic Chapter. Based on the results significant medicinal herbs and combinations can be considered and moreover can be used to produce a new combination for opthalmic diseases. Further study is required since this study has excluded the component volume of herbs and the individual frequentcy of each combination.

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봉쇄를 갖는 순환 대기네트워크의 수율 분석 (Throughput Analysis for Cyclic Queueing Networks with Production Blocking)

  • 김호균;이창훈
    • 대한산업공학회지
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    • 제22권1호
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    • pp.3-15
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    • 1996
  • An approximation algorithm is presented for cyclic queueing networks with finite buffers. The algorithm decomposes the queueing network into individual queues with revised arrival and service process and revised queue capacity. Then, each queue is analyzed in isolation. The service process reflects the additional delay a unit might undergo due to blocking and the arrival process is described by a 2-phases Coxian ($C_2$) distribution. The individual queues are modelled as $C_2/C_2$/1/B queues. The parameters of the individual queues are computed approximately using an iterative scheme. The population constraint of the closed network is taken into account by ensuring that the sum of the average queue lengths of the individual queues is equal to the number of customers of the network. Extensive numerical experiments show that this method provides a fairly good estimation of the throughput.

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네트워크 구조와 조직학습문화, 지식경영참여가 개인창의성 및 성과에 미치는 영향에 관한 실증분석: SI제안팀과 R&D팀의 비교연구 (Exploring Influence of Network Structure, Organizational Learning Culture, and Knowledge Management Participation on Individual Creativity and Performance: Comparison of SI Proposal Team and R&D Team)

  • 이건창;서영욱;채성욱;송석우
    • Asia pacific journal of information systems
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    • 제20권4호
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    • pp.101-123
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    • 2010
  • Recently, firms are operating a number of teams to accomplish organizational performance. Especially, ad hoc teams like proposal preparation team are quite different from permanent teams like R&D team in the sense of how the team forms network structure and deals with organizational learning culture and knowledge management participation efforts. Moreover, depending on the team characteristics, individual creativity will differ from each other, which will lead to organizational performance eventually. Previous studies in the field of creativity are lacking in this issue. So main objectives of this study are organized as follows. First, the issue of how to improve individual creativity and organizational performance will be analyzed empirically. This issue will be performed depending on team characteristics such as ad hoc team and permanent team. Antecedents adopted for this research objective are cultural and knowledge factors such as organizational learning culture, and knowledge management participation. Second, the network structure such as degree centrality, and structural hole is used to analyze its influence on individual creativity and organizational performance. SI (System Integration) companies are facing severely tough requirements from clients to submit very creative proposals. Also, R&D teams are widely accepted as relatively creative teams because their responsibilities are focused on suggesting innovative techniques to make their companies remain competitive in the market. SI teams are usually ad hoc, while R&D teams are permanent on an average. By taking advantage of these characteristics of the two kinds of teams, we will prove the validity of the proposed research questions. To obtain the survey data, we accessed 7 SI teams (74 members), and 6 R&D teams (63 members), collecting 137 valid questionnaires. PLS technique was applied to analyze the survey data. Results are as follows. First, in case of SI teams, organizational learning culture affects individual creativity significantly. Meanwhile, knowledge management participation has a significant influence on Individual creativity for the permanent teams. Second, degree centrality Influences individual creativity significantly in case of SI teams. This is comparable with the fact that structural hole has a significant impact on individual creativity for the R&D teams. Practical implications can be summarized as follows: First, network structure of ad hoc team should be designed differently from one of permanent team. Ad hoc team is supposed to show a high creativity in a rather short period, implying that network density among team members should be improved, and those members with high degree centrality should be encouraged to show their Individual creativity and take a leading role by allowing them to get heavily engaged in knowledge sharing and diffusion. In contrast, permanent team should be designed to take advantage of structural hole instead of focusing on network density. Since structural hole can be utilized very effectively in the permanent team, strong arbitrators' merits in the permanent team will increase and therefore helps increase both network efficiency and effectiveness too. In this way, individual creativity in the permanent team is likely to lead to organizational creativity in a seamless way. Second, way of Increasing individual creativity should be sought from the perspective of organizational culture and knowledge management. Organization is supposed to provide a cultural atmosphere in which Innovative idea suggestions and active discussion among team members are encouraged. In this way, trust builds up among team members, facilitating the formation of organizational learning culture. Third, in the ad hoc team, organizational looming culture should be built such a way that individual creativity can grow up fast in a rather short period. Since time is tight, reasonable compensation policy, leader's Initiatives, and learning culture formation should be done In a short period so that mutual trust is built among members quickly, and necessary knowledge and information can be learnt rapidly. Fourth, in the permanent team, it should be kept in mind that the degree of participation in knowledge management determines level of Individual creativity. Therefore, the team ought to facilitate knowledge circulation process such as knowledge creation, storage, sharing, utilization, and learning among team members, which will lead to team performance. In this way, firms must control knowledge networks in permanent team and ad hoc team in a way mentioned above so that individual creativity as well as team performance can be maximized.

궤도회로에서의 공동접지와 단독접지 인터페이스 (Interface between Common earth and Individual earth on the Track circuit)

  • 이길노;김용규;김종기;김학련
    • 한국철도학회:학술대회논문집
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    • 한국철도학회 2005년도 추계학술대회 논문집
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    • pp.269-274
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    • 2005
  • This paper is studied on earth network configuration when common earth is applied to electrified railway system. And the permitted capacity of buried earth cable used for configuring common earth network and application plan of existing individual earth system when common em1:h network is applied to existing electrification line improvement are studied. For this, the configuration of common earth network is examined according to the SNCF regulation, and the interface between common earth and individual earth is analysed on the basis of the existing track circuit used in electrified line.

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Optimization of Cyber-Attack Detection Using the Deep Learning Network

  • Duong, Lai Van
    • International Journal of Computer Science & Network Security
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    • 제21권7호
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    • pp.159-168
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    • 2021
  • Detecting cyber-attacks using machine learning or deep learning is being studied and applied widely in network intrusion detection systems. We noticed that the application of deep learning algorithms yielded many good results. However, because each deep learning model has different architecture and characteristics with certain advantages and disadvantages, so those deep learning models are only suitable for specific datasets or features. In this paper, in order to optimize the process of detecting cyber-attacks, we propose the idea of building a new deep learning network model based on the association and combination of individual deep learning models. In particular, based on the architecture of 2 deep learning models: Convolutional Neural Network (CNN) and Long Short Term Memory (LSTM), we combine them into a combined deep learning network for detecting cyber-attacks based on network traffic. The experimental results in Section IV.D have demonstrated that our proposal using the CNN-LSTM deep learning model for detecting cyber-attacks based on network traffic is completely correct because the results of this model are much better than some individual deep learning models on all measures.