We present extensive evaluations comparing the performance of taxonomy-based and corpus-based app... more We present extensive evaluations comparing the performance of taxonomy-based and corpus-based approaches on SimLex- 999. The results confirm our hypothesis that taxonomy-based approaches are more suitable to identify similarity. We introduce two new measures of evaluation that show that all measures perform well on a coarse-grained evaluation and that it is not always clear which approach is most suitable when a similarity score is used as a threshold. This leads us to conclude that the inferior performance of corpus-based approaches may not (always) matter.
We performed a comparative study on the Gaussian noise and memristance variation tolerance of thr... more We performed a comparative study on the Gaussian noise and memristance variation tolerance of three crossbar architectures, namely the complementary crossbar architecture, the twin crossbar architecture, and the single crossbar architecture, for neuromorphic image recognition and conducted an experiment to determine the performance of the single crossbar architecture for simple pattern recognition. Ten grayscale images with the size of 32 × 32 pixels were used for testing and comparing the recognition rates of the three architectures. The recognition rates of the three memristor crossbar architectures were compared to each other when the noise level of images was varied from −10 to 4 dB and the percentage of memristance variation was varied from 0% to 40%. The simulation results showed that the single crossbar architecture had the best Gaussian noise input and memristance variation tolerance in terms of recognition rate. At the signal-to-noise ratio of −10 dB, the single crossbar ar...
Abstract An in-depth understanding of fuel additives chemical effects is crucial for optimal use ... more Abstract An in-depth understanding of fuel additives chemical effects is crucial for optimal use or additive design dedicated to more efficient and cleaner combustion. This study aims at investigating the effect of an organometallic octane booster additive named ferrocene on the combustion of a low-octane gasoline at engine-relevant conditions. Rapid compression machine experiments were carried out at 10 bar, from 675 to near 1000 K for stoichiometric (Φ = 1) and lean (Φ = 0.5) mixtures. The neat surrogate fuel was a blend of toluene and n-heptane whose research octane number was 84. The doping level of additive was set at 0.1% molar basis. Ferrocene does not show a remarkable effect on the 1st- stage ignition but presents a strong inhibiting effect on the main ignition of the surrogate fuel at both equivalence ratios. The inhibiting effect increases with temperature within the investigated range. The negative temperature coefficient (NTC) behavior of the surrogate fuel is enhanced by ferrocene. A kinetic model developed by literature data assembly as well as a novel sub-mechanism involving the formation of alcohols from the reactions of iron species is proposed. The kinetic model developed simulates the inhibiting effect of ferrocene reasonably well at both equivalence ratios. Thanks to the validated kinetic model, the chemical effect of ferrocene on the fuel combustion is explored and compared with 2-ethylhexyl nitrate (EHN), which is a conventional reactivity enhancer. Three major differences between the two additives were identified: the high-temperature stability of the fuel additive, the influence of additive on the toluene reactivity and the effect of the additive on the NTC behavior. The results presented in this study contribute to the in-depth comprehension of chemical effect of two fuel additives (ferrocene and EHN) having opposite effects on fuel reactivity.
Wildlife trade is increasingly recognized as an unsustainable threat to primate populations and i... more Wildlife trade is increasingly recognized as an unsustainable threat to primate populations and informing its management is a growing focus and application of primatological research. However, management policies based on ecological research alone cannot address complex socioeconomic or cultural contexts as drivers of wildlife trade. Multidisciplinary research is required to understand trade complexity and identify sustainable management strategies. Here, we define multidisciplinary research as research that combines more than one academic discipline, and highlight how the articles in this issue combine methods and approaches to fill key gaps and offer a more comprehensive understanding of underlying drivers of wildlife trade including consumer demand, enforcement patterns, source population status, and accessibility of targeted species. These articles also focus on how these drivers interact at different scales, how trade patterns relate to ethics, and the potential effectiveness o...
Wildlife trade presents a major threat to primate populations, which are in demand from local to ... more Wildlife trade presents a major threat to primate populations, which are in demand from local to international scales for a variety of uses from food and traditional medicine to the exotic pet trade. We argue that an interdisciplinary framework to facilitate integration of socioeconomic, anthropological, and biological data across multiple spatial and temporal scales is essential to guide the study of wildlife trade dynamics and its impacts on primate populations. Here, we present a new way to design research on wildlife trade in primates using a systems thinking framework. We discuss how we constructed our framework, which follows a social-ecological system framework, to design an ongoing study of local, regional, and international slow loris (Nycticebus spp.) trade in Vietnam. We outline the process of iterative variable exploration and selection via this framework to inform study design. Our framework, guided by systems thinking, enables recognition of complexity in study design,...
We present extensive evaluations comparing the performance of taxonomy-based and corpus-based app... more We present extensive evaluations comparing the performance of taxonomy-based and corpus-based approaches on SimLex- 999. The results confirm our hypothesis that taxonomy-based approaches are more suitable to identify similarity. We introduce two new measures of evaluation that show that all measures perform well on a coarse-grained evaluation and that it is not always clear which approach is most suitable when a similarity score is used as a threshold. This leads us to conclude that the inferior performance of corpus-based approaches may not (always) matter.
We performed a comparative study on the Gaussian noise and memristance variation tolerance of thr... more We performed a comparative study on the Gaussian noise and memristance variation tolerance of three crossbar architectures, namely the complementary crossbar architecture, the twin crossbar architecture, and the single crossbar architecture, for neuromorphic image recognition and conducted an experiment to determine the performance of the single crossbar architecture for simple pattern recognition. Ten grayscale images with the size of 32 × 32 pixels were used for testing and comparing the recognition rates of the three architectures. The recognition rates of the three memristor crossbar architectures were compared to each other when the noise level of images was varied from −10 to 4 dB and the percentage of memristance variation was varied from 0% to 40%. The simulation results showed that the single crossbar architecture had the best Gaussian noise input and memristance variation tolerance in terms of recognition rate. At the signal-to-noise ratio of −10 dB, the single crossbar ar...
Abstract An in-depth understanding of fuel additives chemical effects is crucial for optimal use ... more Abstract An in-depth understanding of fuel additives chemical effects is crucial for optimal use or additive design dedicated to more efficient and cleaner combustion. This study aims at investigating the effect of an organometallic octane booster additive named ferrocene on the combustion of a low-octane gasoline at engine-relevant conditions. Rapid compression machine experiments were carried out at 10 bar, from 675 to near 1000 K for stoichiometric (Φ = 1) and lean (Φ = 0.5) mixtures. The neat surrogate fuel was a blend of toluene and n-heptane whose research octane number was 84. The doping level of additive was set at 0.1% molar basis. Ferrocene does not show a remarkable effect on the 1st- stage ignition but presents a strong inhibiting effect on the main ignition of the surrogate fuel at both equivalence ratios. The inhibiting effect increases with temperature within the investigated range. The negative temperature coefficient (NTC) behavior of the surrogate fuel is enhanced by ferrocene. A kinetic model developed by literature data assembly as well as a novel sub-mechanism involving the formation of alcohols from the reactions of iron species is proposed. The kinetic model developed simulates the inhibiting effect of ferrocene reasonably well at both equivalence ratios. Thanks to the validated kinetic model, the chemical effect of ferrocene on the fuel combustion is explored and compared with 2-ethylhexyl nitrate (EHN), which is a conventional reactivity enhancer. Three major differences between the two additives were identified: the high-temperature stability of the fuel additive, the influence of additive on the toluene reactivity and the effect of the additive on the NTC behavior. The results presented in this study contribute to the in-depth comprehension of chemical effect of two fuel additives (ferrocene and EHN) having opposite effects on fuel reactivity.
Wildlife trade is increasingly recognized as an unsustainable threat to primate populations and i... more Wildlife trade is increasingly recognized as an unsustainable threat to primate populations and informing its management is a growing focus and application of primatological research. However, management policies based on ecological research alone cannot address complex socioeconomic or cultural contexts as drivers of wildlife trade. Multidisciplinary research is required to understand trade complexity and identify sustainable management strategies. Here, we define multidisciplinary research as research that combines more than one academic discipline, and highlight how the articles in this issue combine methods and approaches to fill key gaps and offer a more comprehensive understanding of underlying drivers of wildlife trade including consumer demand, enforcement patterns, source population status, and accessibility of targeted species. These articles also focus on how these drivers interact at different scales, how trade patterns relate to ethics, and the potential effectiveness o...
Wildlife trade presents a major threat to primate populations, which are in demand from local to ... more Wildlife trade presents a major threat to primate populations, which are in demand from local to international scales for a variety of uses from food and traditional medicine to the exotic pet trade. We argue that an interdisciplinary framework to facilitate integration of socioeconomic, anthropological, and biological data across multiple spatial and temporal scales is essential to guide the study of wildlife trade dynamics and its impacts on primate populations. Here, we present a new way to design research on wildlife trade in primates using a systems thinking framework. We discuss how we constructed our framework, which follows a social-ecological system framework, to design an ongoing study of local, regional, and international slow loris (Nycticebus spp.) trade in Vietnam. We outline the process of iterative variable exploration and selection via this framework to inform study design. Our framework, guided by systems thinking, enables recognition of complexity in study design,...
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Papers by Minh Duy Le