• Title/Summary/Keyword: model complexity

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Light weight architecture for acoustic scene classification (음향 장면 분류를 위한 경량화 모형 연구)

  • Lim, Soyoung;Kwak, Il-Youp
    • The Korean Journal of Applied Statistics
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    • v.34 no.6
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    • pp.979-993
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    • 2021
  • Acoustic scene classification (ASC) categorizes an audio file based on the environment in which it has been recorded. This has long been studied in the detection and classification of acoustic scenes and events (DCASE). In this study, we considered the problem that ASC faces in real-world applications that the model used should have low-complexity. We compared several models that apply light-weight techniques. First, a base CNN model was proposed using log mel-spectrogram, deltas, and delta-deltas features. Second, depthwise separable convolution, linear bottleneck inverted residual block was applied to the convolutional layer, and Quantization was applied to the models to develop a low-complexity model. The model considering low-complexity was similar or slightly inferior to the performance of the base model, but the model size was significantly reduced from 503 KB to 42.76 KB.

Energy-efficiency Optimization Schemes Based on SWIPT in Distributed Antenna Systems

  • Xu, Weiye;Chu, Junya;Yu, Xiangbin;Zhou, Huiyu
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.15 no.2
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    • pp.673-694
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    • 2021
  • In this paper, we intend to study the energy efficiency (EE) optimization for a simultaneous wireless information and power transfer (SWIPT)-based distributed antenna system (DAS). Firstly, a DAS-SWIPT model is formulated, whose goal is to maximize the EE of the system. Next, we propose an optimal resource allocation method by means of the Karush-Kuhn-Tucker condition as well as an ergodic method. Considering the complexity of the ergodic method, a suboptimal scheme with lower complexity is proposed by using an antenna selection scheme. Numerical results illustrate that our suboptimal method is able to achieve satisfactory performance of EE similar to an optimal one while reducing the calculation complexity.

A novel MobileNet with selective depth multiplier to compromise complexity and accuracy

  • Chan Yung Kim;Kwi Seob Um;Seo Weon Heo
    • ETRI Journal
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    • v.45 no.4
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    • pp.666-677
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    • 2023
  • In the last few years, convolutional neural networks (CNNs) have demonstrated good performance while solving various computer vision problems. However, since CNNs exhibit high computational complexity, signal processing is performed on the server side. To reduce the computational complexity of CNNs for edge computing, a lightweight algorithm, such as a MobileNet, is proposed. Although MobileNet is lighter than other CNN models, it commonly achieves lower classification accuracy. Hence, to find a balance between complexity and accuracy, additional hyperparameters for adjusting the size of the model have recently been proposed. However, significantly increasing the number of parameters makes models dense and unsuitable for devices with limited computational resources. In this study, we propose a novel MobileNet architecture, in which the number of parameters is adaptively increased according to the importance of feature maps. We show that our proposed network achieves better classification accuracy with fewer parameters than the conventional MobileNet.

Effects of the Complexity of 3D Modeling on the Acoustic Simulations and Auralized Sounds (3D 모델의 구체성이 건축음향 시뮬레이션 및 가청화시재에 미치는 영향)

  • Park, Chan-Jae;Haan, Chan-Hoon
    • The Journal of the Acoustical Society of Korea
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    • v.30 no.1
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    • pp.22-32
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    • 2011
  • The present study examined the effects of the complexity of the 3D models on the results of acoustic simulation which is the predominant tool of the acoustical design of buildings. Also, the effects of the 3D model on the auralized sounds were investigated. In order to carry out the study, four 3D models with different levels of complexity were introduced for a real auditorium which have different numbers of surfaces in the persuit of the guidance of odeon room acoustic software. The set-up of models was also based on the level of transition order of the program. And the acoustic experiments were performed measuring room acoustic parameters including SPL, RT, C80, D50. Acoustic computer simulations were performed using four different models. Then, the results of the computer modeling were compared with the measured acoustical parameters. In addition, sound sources were recorded in the field and auralized sounds were made in convolution with the impulse source made from acoustic modeling. Then, subjective tests were undertaken using auralized sounds. As the results, it was found that the result of the acoustic simulation were closer to the real room acoustic properties when 3D model was more particularly made. For the subjective test, the listening materials were acknowledged as similar with the real sound source when more complex 3D model was used. Then, it could be concluded that the complexity of the 3D model affects the results of the acoustic modeling as well as subjective tests.

Increasing Profitability of the Halal Cosmetics Industry using Configuration Modelling based on Indonesian and Malaysian Markets

  • Dalir, Sara;Olya, Hossein GT;Al-Ansi, Amr;Rahim, Alina Abdul;Lee, Hee-Yul
    • Journal of Korea Trade
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    • v.24 no.8
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    • pp.81-100
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    • 2020
  • Purpose - Based on complexity theory, this study develops a configurational model to predict the profitability of Halal cosmetics firms in the Indonesian and Malaysian markets. The proposed research model involves two level configurations-industry context and selling strategies-to predict high and low scores of a firm's profitability. The industry context configuration model comprises industry stability, product homogeneity, price sensitivity, and switching cost. Selling strategies include customer-focused, competitor-focused, and margin-focused approaches. Design/methodology - This is the first empirical study that calculates causal models using a combination of industry context and selling strategy factors to predict profitability. Data obtained from the marketing managers of cosmetics firms are used to test the proposed configurational model using fuzzy-set qualitative comparative analysis (fsQCA). It contributes to the current knowledge of business marketing by identifying the factors necessary to achieve profitability using analysis of condition (ANC). Findings - The results revealed that unique and distinct models explain the conditions for high and low profitability in the Indonesian and Malaysian halal cosmetic markets. While customer-focused selling strategy is necessary to attain a higher profit in both the markets, margin-focused selling strategy appears to be an essential factor only in Malaysia. Complexity of the interactions of selling strategies with industry factors and differences between across two study markets confirmed that complexity theory can support the research configurational model. The theoretical and practical implications are also illustrated. Originality/value - Despite the rapid growth of the global halal industry, there is little knowledge about the halal cosmetic market. This study contributes to the current literature of the halal market by performing a set of asymmetric analytical approaches using a complex theoretical model. It also deepens our understating of how the Korean firms can approach the Muslim consumer's needs to generate more beneficial turnover/revenue.

Fast Macroblock Mode Selection Algorithm for B Frames in Multiview Video Coding

  • Yu, Mei;He, Ping;Peng, Zongju;Zhang, Yun;Si, Yuehou;Jiang, Gangyi
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.5 no.2
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    • pp.408-427
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    • 2011
  • Intensive computational complexity is an obstacle of enabling multiview video coding for real-time applications. In this paper, we present a fast macroblock (MB) mode selection algorithm for B frames which are based on the computational complexity analyses between the MB mode selection and reference frame selection. Three strategies are proposed to reduce the coding complexity jointly. First, the temporal correlation of MB modes between current MB and its temporal corresponding MBs is utilized to reduce computational complexity in determining the optimal MB mode. Secondly, Lagrangian cost of SKIP mode is compared with that of Inter $16{\times}16$ modes to early terminate the mode selection process. Thirdly, reference frame correlation among different Inter modes is exploited to reduce the number of reference frames. Experimental results show that the proposed algorithm can promote the encoding speed by 3.71~7.22 times with 0.08dB PSNR degradation and 2.03% bitrate increase on average compared with the joint multiview video model.

Efficient power allocation algorithm in downlink cognitive radio networks

  • Abdulghafoor, Omar;Shaat, Musbah;Shayea, Ibraheem;Mahmood, Farhad E.;Nordin, Rosdiadee;Lwas, Ali Khadim
    • ETRI Journal
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    • v.44 no.3
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    • pp.400-412
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    • 2022
  • In cognitive radio networks (CRNs), the computational complexity of resource allocation algorithms is a significant problem that must be addressed. However, the high computational complexity of the optimal solution for tackling resource allocation in CRNs makes it inappropriate for use in practical applications. Therefore, this study proposes a power-based pricing algorithm (PPA) primarily to reduce the computational complexity in downlink CRN scenarios while restricting the interference to primary users to permissible levels. A two-stage approach reduces the computational complexity of the proposed mathematical model. Stage 1 assigns subcarriers to the CRN's users, while the utility function in Stage 2 incorporates a pricing method to provide a power algorithm with enhanced reliability. The PPA's performance is simulated and tested for orthogonal frequency-division multiplexing-based CRNs. The results confirm that the proposed algorithm's performance is close to that of the optimal algorithm, albeit with lower computational complexity of O(M log(M)).

A numerical study of turbulent flows with adverse pressure gradient (역압력 구배가 있는 난류유동에 대한 수치적 연구)

  • 김형수;정태선;최영기
    • Transactions of the Korean Society of Mechanical Engineers
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    • v.15 no.2
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    • pp.668-676
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    • 1991
  • Turbulent flows around tube banks and in the diffuser were studied using a non-orthogonal boundary fitted coordinate system and the modified K-.epsilon. turbulence model. In these cases, many problems emerge which stem from the geometrical complexity of the flow domain and the physical complexity of turbulent flow itself. To treat the complex geometry, governing equations were reformulated in a non-orthogonal coordinate system with Cartesian velocity components and discretised by the finite volume method with a non-staggered variable arrangement. The modified K-.epsilon. model of Hanjalic and Launer was applied to solve above two cases under the condition of strong and mild pressure gradient. The results using the modified K-.epsilon. model results in both test cases.

Biomechanical Analysis of Human Balance Control

  • Shin, Youngkyun;Park, Gu-Bum
    • Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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    • v.28 no.3
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    • pp.63-71
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    • 2014
  • A single-inverted-pendulum model is presented to simulate and predict the passive response of human balance control. This simplified biomechanical model was comprised of a torsional spring and damper, and a lump mass. An estimation of frequency response function was conducted to parameterize the complexity. The frequency domain identification method is used to identify the parameters of the model. The equivalent viscoelastic parameters of standing body were obtained and there was good conformity between the simulation and experimental result.

Modeling the Knowledge Processing System through the Lens of Complexity Theory : Social Energies, Leadership, and the LIFE Model

  • Faucher, Jean-Baptiste P.L.;Everett, Andre M.;Lawson, Rob
    • Journal of Information Technology Applications and Management
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    • v.17 no.3
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    • pp.191-211
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    • 2010
  • Existing models of knowledge processing do not feature a systemic meaning of knowledge management and ignore the role of leadership and social energy in the knowledge processing system (KPS). This conceptual paper introduces the Leadership Invigorating Flows of Energies, (LIFE) Model as an attempt to remedy that situation and provide a more useful description of the KPS. The LIFE Model highlights the role of emergent leadership and flows of social energies as forces encouraging knowledge creation and dynamic diffusion within an organization through the Knowledge Processing Cycle in eight activities interacting with its social knowledge base in a self-organizing system.

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