Granularity

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Witold Pedrycz - One of the best experts on this subject based on the ideXlab platform.

  • allocation of information Granularity in optimization and decision making models towards building the foundations of granular computing
    European Journal of Operational Research, 2014
    Co-Authors: Witold Pedrycz
    Abstract:

    Abstract The highly diversified conceptual and algorithmic landscape of Granular Computing calls for the formation of sound fundamentals of the discipline, which cut across the diversity of formal frameworks (fuzzy sets, sets, rough sets) in which information granules are formed and processed. The study addresses this quest by introducing an idea of granular models – generalizations of numeric models that are formed as a result of an optimal allocation (distribution) of information Granularity. Information Granularity is regarded as a crucial design asset, which helps establish a better rapport of the resulting granular model with the system under modeling. A suite of modeling situations is elaborated on; they offer convincing examples behind the emergence of granular models. Pertinent problems showing how information Granularity is distributed throughout the parameters of numeric functions (and resulting in granular mappings) are formulated as optimization tasks. A set of associated information Granularity distribution protocols is discussed. We also provide a number of illustrative examples.

  • analytic hierarchy process ahp in group decision making and its optimization with an allocation of information Granularity
    IEEE Transactions on Fuzzy Systems, 2011
    Co-Authors: Witold Pedrycz, Mingli Song
    Abstract:

    In group decision making, one strives to reconcile differences of opinions (judgments) expressed by individual members of the group. Fuzzy-decision-making mechanisms bring a great deal of flexibility. By admitting membership degrees, we are offered flexibility to exploit different aggregation mechanisms and navigate a process of interaction among decision makers to achieve an increasing level of consistency within the group. While the studies reported so far exploit more or less sophisticated ways of adjusting/transforming initial judgments (preferences) of individuals, in this paper, we bring forward a concept of information Granularity. Here, information Granularity is viewed as an essential asset, which offers a decision maker a tangible level of flexibility using some initial preferences conveyed by each individual that can be adjusted with the intent to reach a higher level of consensus. Our study is concerned with an extension of the well-known analytic hierarchy process to the group decision-making scenario. More specifically, the admitted level of Granularity gives rise to a granular matrix of pairwise comparisons. The granular entries represented, e.g., by intervals or fuzzy sets, supply a required flexibility using the fact that we select the most suitable numeric representative of the reciprocal matrix. The proposed concept of granular reciprocal matrices is used to optimize a performance index, which comes as an additive combination of two components. The first one expresses a level of consistency of the individual pairwise comparison matrices; by exploiting the admitted level of Granularity, we aim at the minimization of the corresponding inconsistency index. The second part of the performance index quantifies a level of disagreement in terms of the individual preferences. The flexibility offered by the level of Granularity is used to increase the level of consensus within the group. Given an implicit nature of relationships between the realizations of the granular pairwise matrices and the values of the performance index, we consider using particle swarm optimization as an optimization vehicle. Two scenarios of allocation of Granularity among decision makers are considered, namely, a uniform allocation of Granularity and nonuniform distribution of Granularity, where the levels of allocated Granularity are also subject to optimization. A number of numeric studies are provided to illustrate an essence of the method.

Luis Martínez - One of the best experts on this subject based on the ideXlab platform.

  • a fusion approach for managing multi Granularity linguistic term sets in decision making
    Fuzzy Sets and Systems, 2000
    Co-Authors: Francisco Herrera, Enrique Herreraviedma, Luis Martínez
    Abstract:

    The aim of this paper is to present a fusion approach of multi-Granularity linguistic information for managing information assessed in different linguistic term sets (multi-Granularity linguistic term sets) together with its application in a decision making problem with multiple information sources, assuming that the linguistic performance values given to the alternatives by the different sources are represented in linguistic term sets with different Granularity and/or semantic. In this context, a decision process based on two steps is proposed with a view to obtaining the solution set of alternatives. First, the fusion of the multi-Granularity linguistic performance values is carried out in order to obtain collective performance evaluations. In this step, on the one hand, the multi-Granularity linguistic information is made uniform using a linguistic term set as the uniform representation base, the basic linguistic term set. On the other hand, the collective performance evaluations of the alternatives are obtained by means of an aggregation operator, being fuzzy sets on the basic linguistic term set. Second, the choice of the best alternative(s) from the collective performance evaluations is performed. To do that, a fuzzy preference relation is computed from the collective performance evaluations using a ranking method of pairs of fuzzy sets in the setting of Possibility Theory, applied to fuzzy sets on the basic linguistic term set. Then, a choice degree may be applied on the preference relation in order to rank the alternatives.

Zhou Xichuan - One of the best experts on this subject based on the ideXlab platform.

  • Strong but Simple Baseline with Dual-Granularity Triplet Loss for Visible-Thermal Person Re-Identification
    2021
    Co-Authors: Liu Haijun, Chai Yanxia, Tan Xiaoheng, Li Dong, Zhou Xichuan
    Abstract:

    In this letter, we propose a conceptually simple and effective dual-Granularity triplet loss for visible-thermal person re-identification (VT-ReID). In general, ReID models are always trained with the sample-based triplet loss and identification loss from the fine Granularity level. It is possible when a center-based loss is introduced to encourage the intra-class compactness and inter-class discrimination from the coarse Granularity level. Our proposed dual-Granularity triplet loss well organizes the sample-based triplet loss and center-based triplet loss in a hierarchical fine to coarse Granularity manner, just with some simple configurations of typical operations, such as pooling and batch normalization. Experiments on RegDB and SYSU-MM01 datasets show that with only the global features our dual-Granularity triplet loss can improve the VT-ReID performance by a significant margin. It can be a strong VT-ReID baseline to boost future research with high quality.Comment: to be published in IEEE Signal Processing Letter

  • Strong but Simple Baseline with Dual-Granularity Triplet Loss for Visible-Thermal Person Re-Identification
    2020
    Co-Authors: Liu Haijun, Chai Yanxia, Tan Xiaoheng, Li Dong, Zhou Xichuan
    Abstract:

    In this letter, we propose a conceptually simple and effective dual-Granularity triplet loss for visible-thermal person re-identification (VT-ReID). In general, ReID models are always trained with the sample-based triplet loss and identification loss from the fine Granularity level. It is possible when a center-based loss is introduced to encourage the intra-class compactness and inter-class discrimination from the coarse Granularity level. Our proposed dual-Granularity triplet loss well organizes the sample-based triplet loss and center-based triplet loss in a hierarchical fine to coarse Granularity manner, just with some simple configurations of typical operations, such as pooling and batch normalization. Experiments on RegDB and SYSU-MM01 datasets show that with only the global features our dual-Granularity triplet loss can improve the VT-ReID performance by a significant margin. It can be a strong VT-ReID baseline to boost future research with high quality

Mattan Erez - One of the best experts on this subject based on the ideXlab platform.

  • adaptive Granularity memory systems a tradeoff between storage efficiency and throughput
    International Symposium on Computer Architecture, 2011
    Co-Authors: Doe Hyun Yoon, Min Kyu Jeong, Mattan Erez
    Abstract:

    We propose adaptive Granularity to combine the best of fine-grained and coarse-grained memory accesses. We augment virtual memory to allow each page to specify its preferred Granularity of access based on spatial locality and error-tolerance tradeoffs. We use sector caches and sub-ranked memory systems to implement adaptive Granularity. We also show how to incorporate adaptive Granularity into memory access scheduling. We evaluate our architecture with and without ECC using memory intensive benchmarks from the SPEC, Olden, PARSEC, SPLASH2, and HPCS benchmark suites and micro-benchmarks. The evaluation shows that performance is improved by 61% without ECC and 44% with ECC in memory-intensive applications, while the reduction in memory power consumption (29% without ECC and 14% with ECC) and traffic (78% without ECC and 66% with ECC) is significant.

Karen S Quigley - One of the best experts on this subject based on the ideXlab platform.

  • investigating the relationship between emotional Granularity and cardiorespiratory physiological activity in daily life
    Psychophysiology, 2021
    Co-Authors: Katie Hoemann, Zulqarnain Khan, Nada Kamona, Lisa Feldman Barrett, Karen S Quigley
    Abstract:

    Emotional Granularity describes the ability to create emotional experiences that are precise and context-specific. Despite growing evidence of a link between emotional Granularity and mental health, the physiological correlates of Granularity have been under-investigated. This study explored the relationship between Granularity and cardiorespiratory physiological activity in everyday life, with particular reference to the role of respiratory sinus arrhythmia (RSA), an estimate of vagal influence on the heart often associated with positive mental and physical health outcomes. Participants completed a physiologically triggered experience-sampling protocol including ambulatory recording of electrocardiogram, impedance cardiogram, movement, and posture. At each prompt, participants generated emotion labels to describe their current experience. In an end-of-day survey, participants elaborated on each prompt by rating the intensity of their experience on a standard set of emotion adjectives. Consistent with our hypotheses, individuals with higher Granularity exhibited a larger number of distinct patterns of physiological activity during seated rest, and more situationally precise patterns of activity during emotional events: Granularity was positively correlated with the number of clusters of cardiorespiratory physiological activity discovered in seated rest data, as well as with the performance of classifiers trained on event-related changes in physiological activity. Granularity was also positively associated with RSA during seated rest periods, although this relationship did not reach significance in this sample. These findings are consistent with constructionist accounts of emotion that propose concepts as a key mechanism underlying individual differences in emotional experience, physiological regulation, and physical health.