The Experts below are selected from a list of 3810 Experts worldwide ranked by ideXlab platform
Jinwook Burm - One of the best experts on this subject based on the ideXlab platform.
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Area-efficient fast scheduling schemes for MVC Prediction architecture
2011 IEEE International Symposium of Circuits and Systems (ISCAS), 2011Co-Authors: Minsu Choi, Jinwook BurmAbstract:While multi-view video system offers users various three-dimensional scenes, its hardware architecture requires more power consumption, chip size and processing Time. Each view in Group of Group of Pictures (GoGoP) has different frame structure and different number of reference frames. The multi-view video coding (MVC) performance heavily relies on the frame scheduling architecture for motion estimation (ME) and disparity estimation (DE). Therefore, we need to develop efficient frame scheduling schemes for MVC. In this paper, we propose two frame scheduling schemes: hardware resource aware scheduling (HRaS) and buffering Time aware scheduling (BTaS). In the proposed scheduling schemes, the GoGoP is represented by a graph in which edges represent relationship between reference frames and current frames. HRaS relocates frames in GoGoP so that total hardware resources for MVC Prediction are reduced. BTaS relocates the frames based on the number of edges so that Prediction Time and buffering Time of the frames are reduced. Through experimental results, we verified the efficiency of the proposed scheduling architectures in terms of power dissipation, area, MVC Prediction Time, and buffering Time.
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ISCAS - Area-efficient fast scheduling schemes for MVC Prediction architecture
2011 IEEE International Symposium of Circuits and Systems (ISCAS), 2011Co-Authors: Minsu Choi, Jinwook BurmAbstract:While multi-view video system offers users various three-dimensional scenes, its hardware architecture requires more power consumption, chip size and processing Time. Each view in Group of Group of Pictures (GoGoP) has different frame structure and different number of reference frames. The multi-view video coding (MVC) performance heavily relies on the frame scheduling architecture for motion estimation (ME) and disparity estimation (DE). Therefore, we need to develop efficient frame scheduling schemes for MVC. In this paper, we propose two frame scheduling schemes: hardware resource aware scheduling (HRaS) and buffering Time aware scheduling (BTaS). In the proposed scheduling schemes, the GoGoP is represented by a graph in which edges represent relationship between reference frames and current frames. HRaS relocates frames in GoGoP so that total hardware resources for MVC Prediction are reduced. BTaS relocates the frames based on the number of edges so that Prediction Time and buffering Time of the frames are reduced. Through experimental results, we verified the efficiency of the proposed scheduling architectures in terms of power dissipation, area, MVC Prediction Time, and buffering Time.
Josiah Munda - One of the best experts on this subject based on the ideXlab platform.
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Residential solar water heating load profile Prediction (Time-series base)
Proceedings of the Conference on the Industrial and Commercial Use of Energy ICUE, 2016Co-Authors: M. Mlonzi, O. M. Popoola, Josiah MundaAbstract:© 2016 Cape Peninsula University of Technology. Quantification of usage pattern and the effectiveness of solar water heating system as an energy management solution in most previous studies were based on deterministic approach. This approach is error prone. This study presents a computational intelligence modelling - Artificial Neural fuzzy inference systems (ANFIS) based model that has the capability of detecting trends that are complex, non-linear, and ill-defined. Time, ambient temperature, water inlet temperature, water outlet temperature, irradiance level and energy contributed by auxiliary element are the variables considered in the study. Furthermore, the study is Time-series based which often is lacking in most approaches. To ascertain the performance of the methodology, statistical measures / analyses (root mean square error, correlation coefficient, coefficient of determination) were applied and validation process carried out. The applicable methodology in the study presented satisfactory results, with minimal error compared to the actual data. The acquired result showed that the proposed technique can be utilized as an efficient tool for SHW usage pattern development and Prediction.
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Residential solar water heating load profile Prediction (Time-series base)
2016 International Conference on the Industrial and Commercial Use of Energy (ICUE), 2016Co-Authors: M. Mlonzi, O. M. Popoola, Josiah MundaAbstract:Quantification of usage pattern and the effectiveness of solar water heating system as an energy management solution in most previous studies were based on deterministic approach. This approach is error prone. This study presents a computational intelligence modelling - Artificial Neural fuzzy inference systems (ANFIS) based model that has the capability of detecting trends that are complex, non-linear, and ill-defined. Time, ambient temperature, water inlet temperature, water outlet temperature, irradiance level and energy contributed by auxiliary element are the variables considered in the study. Furthermore, the study is Time-series based which often is lacking in most approaches. To ascertain the performance of the methodology, statistical measures / analyses (root mean square error, correlation coefficient, coefficient of determination) were applied and validation process carried out. The applicable methodology in the study presented satisfactory results, with minimal error compared to the actual data. The acquired result showed that the proposed technique can be utilized as an efficient tool for SHW usage pattern development and Prediction.
Shinji Sugawara - One of the best experts on this subject based on the ideXlab platform.
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NetGames - Adaptive delta-causality control scheme with dynamic control of Prediction Time in networked haptic game
2012 11th Annual Workshop on Network and Systems Support for Games (NetGames), 2012Co-Authors: Yusuke Hara, Yutaka Ishibashi, Norishige Fukushima, Shinji SugawaraAbstract:In this paper, we handle an air hockey game which two players play with haptic interface devices as an example of networked real-Time games. To keep the interactivity and media output quality high, we enhance the adaptive Δ (delta)-causality control scheme with Prediction, which the authors previously proposed. In the enhanced scheme, we change the Prediction Time dynamically according to the network delay. Also, we subjectively investigate the effect of the enhanced scheme by QoE (Quality of Experience) assessment.
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Adaptive delta-causality control scheme with dynamic control of Prediction Time in networked haptic game
2012 11th Annual Workshop on Network and Systems Support for Games (NetGames), 2012Co-Authors: Yusuke Hara, Yutaka Ishibashi, Norishige Fukushima, Shinji SugawaraAbstract:In this paper, we handle an air hockey game which two players play with haptic interface devices as an example of networked real-Time games. To keep the interactivity and media output quality high, we enhance the adaptive Δ (delta)-causality control scheme with Prediction, which the authors previously proposed. In the enhanced scheme, we change the Prediction Time dynamically according to the network delay. Also, we subjectively investigate the effect of the enhanced scheme by QoE (Quality of Experience) assessment.
Minsu Choi - One of the best experts on this subject based on the ideXlab platform.
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Area-efficient fast scheduling schemes for MVC Prediction architecture
2011 IEEE International Symposium of Circuits and Systems (ISCAS), 2011Co-Authors: Minsu Choi, Jinwook BurmAbstract:While multi-view video system offers users various three-dimensional scenes, its hardware architecture requires more power consumption, chip size and processing Time. Each view in Group of Group of Pictures (GoGoP) has different frame structure and different number of reference frames. The multi-view video coding (MVC) performance heavily relies on the frame scheduling architecture for motion estimation (ME) and disparity estimation (DE). Therefore, we need to develop efficient frame scheduling schemes for MVC. In this paper, we propose two frame scheduling schemes: hardware resource aware scheduling (HRaS) and buffering Time aware scheduling (BTaS). In the proposed scheduling schemes, the GoGoP is represented by a graph in which edges represent relationship between reference frames and current frames. HRaS relocates frames in GoGoP so that total hardware resources for MVC Prediction are reduced. BTaS relocates the frames based on the number of edges so that Prediction Time and buffering Time of the frames are reduced. Through experimental results, we verified the efficiency of the proposed scheduling architectures in terms of power dissipation, area, MVC Prediction Time, and buffering Time.
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ISCAS - Area-efficient fast scheduling schemes for MVC Prediction architecture
2011 IEEE International Symposium of Circuits and Systems (ISCAS), 2011Co-Authors: Minsu Choi, Jinwook BurmAbstract:While multi-view video system offers users various three-dimensional scenes, its hardware architecture requires more power consumption, chip size and processing Time. Each view in Group of Group of Pictures (GoGoP) has different frame structure and different number of reference frames. The multi-view video coding (MVC) performance heavily relies on the frame scheduling architecture for motion estimation (ME) and disparity estimation (DE). Therefore, we need to develop efficient frame scheduling schemes for MVC. In this paper, we propose two frame scheduling schemes: hardware resource aware scheduling (HRaS) and buffering Time aware scheduling (BTaS). In the proposed scheduling schemes, the GoGoP is represented by a graph in which edges represent relationship between reference frames and current frames. HRaS relocates frames in GoGoP so that total hardware resources for MVC Prediction are reduced. BTaS relocates the frames based on the number of edges so that Prediction Time and buffering Time of the frames are reduced. Through experimental results, we verified the efficiency of the proposed scheduling architectures in terms of power dissipation, area, MVC Prediction Time, and buffering Time.
R. Schmidt - One of the best experts on this subject based on the ideXlab platform.
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Reliability Prediction sensitivity analysis — How to perform reliability Prediction Time efficiently
6th IET International Conference on Power Electronics Machines and Drives (PEMD 2012), 2012Co-Authors: G. J. Riedel, T. Huesgen, R. SchmidtAbstract:Reliability Prediction according to reliability standards is often applied to estimate the reliability of electronic systems. Failure rates are typically dependent on their stress conditions (predominantly thermal and electrical stresses). However, getting the exact temperature and stress value for every single component is extremely Time consuming, or someTimes impossible. Here the sensitivity of reliability Prediction on the stresses is investigated in a case study of a voltage-source converter. It is found that for electrical stress designers' rules are sufficient. For thermal stress, measured temperatures where used as input. It was found that reliability Prediction using averaged temperatures can provide very good agreement, compared to reliability Prediction with measured component temperatures. These drastic simplifications allow to perform reliability Prediction in a Time efficient way. The case study was performed using IEC 62380, Telcordia SR 322 (2), and MIL-HDBK 217F(2), including the ANSI/VITA 51.1 (2008) report that updates the 15 year old MIL-HDBK 217F(2).
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Reliability Prediction sensitivity analysis — How to perform reliability Prediction Time efficiently
6th IET International Conference on Power Electronics Machines and Drives (PEMD 2012), 2012Co-Authors: G. J. Riedel, T. Huesgen, R. SchmidtAbstract:Reliability Prediction according to reliability standards is often applied to estimate the reliability of electronic systems. Failure rates are typically dependent on their stress conditions (predominantly thermal and electrical stresses). However, getting the exact temperature and stress value for every single component is extremely Time consuming, or someTimes impossible. Here the sensitivity of reliability Prediction on the stresses is investigated in a case study of a voltage-source converter. It is found that for electrical stress designers' rules are sufficient. For thermal stress, measured temperatures where used as input. It was found that reliability Prediction using averaged temperatures can provide very good agreement, compared to reliability Prediction with measured component temperatures. These drastic simplifications allow to perform reliability Prediction in a Time efficient way. The case study was performed using IEC 62380, Telcordia SR 322 (2), and MIL-HDBK 217F(2), including the ANSI/VITA 51.1 (2008) report that updates the 15 year old MIL-HDBK 217F(2). (6 pages)
