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To identify dense and small-size pedestrians in surveillance systems, high-resolution cameras are widely deployed, where high-resolution images are captured and delivered to off-the-shelf pedestrian detection models. However, given the highly computation-intensive workload brought by the high resolution, the resource-constrained cameras fail to afford accurate inference in real time. To address that, we propose Hode, an offloaded video analytic framework that utilizes multiple edge nodes in proximity to expedite pedestrian detection with high-resolution inputs. Specifically, Hode can intelligently split high-resolution images into respective regions and then offload them to distributed edge nodes to perform pedestrian detection in parallel. A spatio-temporal flow filtering method is designed to enable context-aware region partitioning, as well as a DRL-based scheduling algorithm to allow accuracy-aware load balance among heterogeneous edge nodes. Extensive evaluation results using realistic prototypes show that Hode can achieve up to 2.01% speedup with very mild accuracy loss., Comment: Accepted by IEEE ICC 2023

In this paper, systematic supercritical carbonation tests of steel-polypropylene hybrid fiber reinforced concrete (SPFRC) were carried out to evaluate the performance of SPFRC under supercritical condition. The effects of the length-diameter ratio of steel fiber, volume fraction of steel fiber, and polypropylene fiber on the carbonation depth and compressive strength of concrete under supercritical condition were studied. A one-dimensional mathematical model for the physical-chemical coupling process of supercritical carbonation of cement-based materials was established. The relational model between the equivalent porosity and the compressive strength of fully carbonated SPFRC was also proposed. Results indicate that whether the addition of steel fibers or polypropylene fibers or the inclusion of fibers can accelerate the carbonation process by the increase of porosity. The carbonation depths of SPFRC increase with the increase of the addition of steel fibers and polypropylene fibers. The compressive strength after carbonation is significantly increased. The maximum relative compressive strength was obtained when the volume fraction of steel fibers and polypropylene fibers were 1.5% and 0.0% and the length-diameter ratio of steel fiber was 60, respectively. Furthermore, a mathematical model was proposed to evaluate the equivalent initial porosity of SPFRC.

In this paper, systematic supercritical carbonation tests of steel-polypropylene hybrid fiber reinforced concrete (SPFRC) were carried out to evaluate the performance of SPFRC under supercritical condition. The effects of the length-diameter ratio of steel fiber, volume fraction of steel fiber, and polypropylene fiber on the carbonation depth and compressive strength of concrete under supercritical condition were studied. A one-dimensional mathematical model for the physical-chemical coupling process of supercritical carbonation of cement-based materials was established. The relational model between the equivalent porosity and the compressive strength of fully carbonated SPFRC was also proposed. Results indicate that whether the addition of steel fibers or polypropylene fibers or the inclusion of fibers can accelerate the carbonation process by the increase of porosity. The carbonation depths of SPFRC increase with the increase of the addition of steel fibers and polypropylene fibers. The compressive strength after carbonation is significantly increased. The maximum relative compressive strength was obtained when the volume fraction of steel fibers and polypropylene fibers were 1.5% and 0.0% and the length-diameter ratio of steel fiber was 60, respectively. Furthermore, a mathematical model was proposed to evaluate the equivalent initial porosity of SPFRC.

The heterogeneity of a cement-based material results in a random spatial distribution of carbonation depth, which may significantly affect the mechanical properties and durability of the material. Currently, there is a lack of both experimental and numerical investigations aiming at a statistical understanding of this important phenomenon. This paper presents both experimental and numerical supercritical carbonation test results of concrete blocks. The random fields of porosity and two-dimension random aggregate model of concrete were proposed for the simulation. The carbonation depths are measured and distributed along the carbonation boundary by the proposed rapid image processing technique, which are then statistically studied. The study has shown that considering the random distribution of coarse aggregates and using a random field of porosity with due consideration of spatial correlation and variance, the irregularity of carbonation depth can be realistically captured by the numerical model. Overall the methodology adopted in the paper can provide a foundation for future investigations on probability analysis of carbonation depth and other similar work based on multi-scale and –physics modelling.

The heterogeneity of a cement-based material results in a random spatial distribution of carbonation depth, which may significantly affect the mechanical properties and durability of the material. Currently, there is a lack of both experimental and numerical investigations aiming at a statistical understanding of this important phenomenon. This paper presents both experimental and numerical supercritical carbonation test results of concrete blocks. The random fields of porosity and two-dimension random aggregate model of concrete were proposed for the simulation. The carbonation depths are measured and distributed along the carbonation boundary by the proposed rapid image processing technique, which are then statistically studied. The study has shown that considering the random distribution of coarse aggregates and using a random field of porosity with due consideration of spatial correlation and variance, the irregularity of carbonation depth can be realistically captured by the numerical model. Overall the methodology adopted in the paper can provide a foundation for future investigations on probability analysis of carbonation depth and other similar work based on multi-scale and –physics modelling.

The heterogeneity of a cement-based material results in a random spatial distribution of carbonation depth. Currently, there is a lack of both experimental and numerical investigations aiming at a statistical understanding of this important phenomenon. This paper presents both experimental and numerical supercritical carbonation test results of cement mortar blocks. The carbonation depths are measured along the carbonation boundary by the proposed rapid image processing technique, which are then statistically studied by calculating, e.g., their probability density and power spectral density (PSD). The results indicate that the distribution of the carbonation depth can be approximately represented by a lognormal distribution function and the PSD has quantitative correlation with some of the statistic parameters used in the simulations. In particular, the effects of the autocorrelation lengths and the coefficient of variation of porosity, which are used to define the random porosity field, on the irregularity of carbonation depth are analyzed numerically in details and validated by experimental results. The study has shown that using a random field of porosity with due consideration of spatial correlation and variance, the irregularity of carbonation depth can be realistically captured by the numerical model. The numerical results confirm that lognormal distributions represent the random nature of carbonation depth well and the average and variance of the irregular carbonation depth increase with the increase of carbonation time, autocorrelation length and coefficient of variation of porosity. The study also offers a potential method to numerically calibrate some of the statistic parameters required by a numerical carbonation model through comparing the PSD with that from experimental tests. Overall the methodology adopted in the paper can provide a foundation for future investigations on probability analysis of carbonation depth and other similar work based on multi

The heterogeneity of a cement-based material results in a random spatial distribution of carbonation depth. Currently, there is a lack of both experimental and numerical investigations aiming at a statistical understanding of this important phenomenon. This paper presents both experimental and numerical supercritical carbonation test results of cement mortar blocks. The carbonation depths are measured along the carbonation boundary by the proposed rapid image processing technique, which are then statistically studied by calculating, e.g., their probability density and power spectral density (PSD). The results indicate that the distribution of the carbonation depth can be approximately represented by a lognormal distribution function and the PSD has quantitative correlation with some of the statistic parameters used in the simulations. In particular, the effects of the autocorrelation lengths and the coefficient of variation of porosity, which are used to define the random porosity field, on the irregularity of carbonation depth are analyzed numerically in details and validated by experimental results. The study has shown that using a random field of porosity with due consideration of spatial correlation and variance, the irregularity of carbonation depth can be realistically captured by the numerical model. The numerical results confirm that lognormal distributions represent the random nature of carbonation depth well and the average and variance of the irregular carbonation depth increase with the increase of carbonation time, autocorrelation length and coefficient of variation of porosity. The study also offers a potential method to numerically calibrate some of the statistic parameters required by a numerical carbonation model through comparing the PSD with that from experimental tests. Overall the methodology adopted in the paper can provide a foundation for future investigations on probability analysis of carbonation depth and other similar work based on multi

In order to study the mechanical properties of early-age concrete-filled steel tube (CFST) under continuous construction process, an experimental investigation on six concrete-filled circular steel tubular short columns under multi-level loading was carried out. The influence of multi-level loading with different initial stress degrees, loading time intervals and loading levels on the deformation progression was analyzed. The bearing capacity of the columns was then tested at 28 days after the multi-level loading. The results show that creep deformation of the concrete-filled steel tubes under multi-level loading is significant and cannot be neglected. The deformation of the columns is significantly affected by the applied loading scheme. An increase of the initial stress degrees and increment of loading levels, or a reduction of loading time interval will all result in an increase of the deformation of the columns. However, the multi-level loading process has only small impact on the bearing capacity of the CFST short columns after 28 days.

In this paper, the supercritical carbonation process of cement-based materials is modelled by introducing a random porosity field to simulate the heterogeneous geometry of the carbonation profile. The suitability of two different random fields of porosity, based on the probability density function (PDF) and the ellipsoidal autocorrelation function (EAF) methods, are investigated, respectively, in simulating the distribution of porosity in cement mortar. After incorporating the above random fields into an established supercritical carbonation model, it is found that with some modifications, the EAF method with consideration of spatial correlation produces better simulation of the irregularities of the carbonation zones that have been observed from experimental results. It is also found that for given average porosity and coefficient of variation, the predicted average and maximum carbonation depths have much smaller coefficients of variation. The validated EAF supercritical carbonation model is then used in parametric studies that are conducted to assess the effect of various factors on the carbonation depth of the chemical process.

In this paper, the supercritical carbonation process of cement-based materials is modelled by introducing a random porosity field to simulate the heterogeneous geometry of the carbonation profile. The suitability of two different random fields of porosity, based on the probability density function (PDF) and the ellipsoidal autocorrelation function (EAF) methods, are investigated, respectively, in simulating the distribution of porosity in cement mortar. After incorporating the above random fields into an established supercritical carbonation model, it is found that with some modifications, the EAF method with consideration of spatial correlation produces better simulation of the irregularities of the carbonation zones that have been observed from experimental results. It is also found that for given average porosity and coefficient of variation, the predicted average and maximum carbonation depths have much smaller coefficients of variation. The validated EAF supercritical carbonation model is then used in parametric studies that are conducted to assess the effect of various factors on the carbonation depth of the chemical process.