A Novel Machine Learning-Based Hand Gesture Recognition Using HCI on IoT Assisted Cloud Platform

Machine learning is a technique for analyzing data that aids the construction of mathematical models.Because of the growth of the Internet of Things(IoT)and wearable sensor devices,gesture interfaces are becoming a more natural and expedient human-machine interaction method.This type of artificial intelligence that requires minimal or no direct human intervention in decision-making is predicated on the ability of intelligent systems to self-train and detect patterns.The rise of touch-free applications and the number of deaf people have increased the significance of hand gesture recognition.Potential applications of hand gesture recognition research span from online gaming to surgical robotics.The location of the hands,the alignment of the fingers,and the hand-to-body posture are the fundamental components of hierarchical emotions in gestures.Linguistic gestures may be difficult to distinguish from nonsensical motions in the field of gesture recognition.Linguistic gestures may be difficult to distinguish from nonsensical motions in the field of gesture recognition.In this scenario,it may be difficult to overcome segmentation uncertainty caused by accidental hand motions or trembling.When a user performs the same dynamic gesture,the hand shapes and speeds of each user,as well as those often generated by the same user,vary.A machine-learning-based Gesture Recognition Framework(ML-GRF)for recognizing the beginning and end of a gesture sequence in a continuous stream of data is suggested to solve the problem of distinguishing between meaningful dynamic gestures and scattered generation.We have recommended using a similarity matching-based gesture classification approach to reduce the overall computing cost associated with identifying actions,and we have shown how an efficient feature extraction method can be used to reduce the thousands of single gesture information to four binary digit gesture codes.The findings from the simulation support the accuracy,precision,gesture recognition,sensitivity,and efficiency rates.The Machine Learning-based Gesture Recognition Framework(ML-GRF)had an accuracy rate of 98.97%,a precision rate of 97.65%,a gesture recognition rate of 98.04%,a sensitivity rate of 96.99%,and an efficiency rate of 95.12%.

Energy saving effect of building envelope in summer

To explore the energy saving effect of building envelope, the experiments were carried out through a comparison of basic cubicle in summer. Experiments show that if energy efficiency measures are applied only in the external walls and windows, the energy saving cubicles have an average energy efficiency ratio of 27.75% and 27.05% when the air change rates are 1.1 and 1.4 h-1 in summer, with both values being over the standard target value by 25%. And the indoor air temperature of the energy saving cubicle is below that of the basic cubicle. The daily mean temperature difference between the interior surface of insulation wall and no insulation reaches 1.47℃, and the mean temperature difference is up to 8.52℃ between the interior surface and exterior surface of insulating glass and single glass. The two cubicles were simulated for energy consumption using VisualDOE4.0 software under real weather conditions in summer. The results show that the mean deviation is 10.02% between experimental and simulated energy efficiency ratio. The correctness and validity of simulation results of the VisualDOE4.0 software are proved.

The efficiency of long-term straw return to sequester organic carbon in Northeast China＇s cropland

Black soil is one of the most precious soil resources on earth because it has abundant carbon stocks and a relatively high production capacity. However, decreasing organic matter after land reclamation, and the effects of long-term inputs of organic carbon have made it less fertile black soil in Northeast China. Straw return could be an effective method for improving soil organic carbon（SOC） sequestration in black soils. The objective of this study was to evaluate whether straw return effectively increases SOC sequestration. Long-term field experiments were conducted at three sites in Northeast China with varying latitudes and SOC densities. Study plots were subjected to three treatments： no fertilization（CK）; inorganic fertilization（NPK）; and NPK plus straw return（NPKS）. The results showed that the SOC stocks resulting from NPKS treatment were 4.0 and 5.7% higher than those from NPK treatment at two sites, but straw return did not significantly affect the SOC stocks at the third site. Furthermore, at higher SOC densities, the NPKS treatment resulted in significantly higher soil carbon sequestration rates（CSR） than the NPK treatment. The equilibrium value of the CSR for the NPKS treatment equated to cultivation times of 17, 11, and 8 years at the different sites. Straw return did not significantly increase the SOC stocks in regions with low SOC densities, but did enhance the C pool in regions with high SOC densities. These results show that there is strong regional variation in the effects of straw return on the SOC stocks in black soil in Northeast China. Additional cultivations and fertilization practices should be used when straw return is considered as an approach for the long-term improvement of the soil organic carbon pool.

Effect of Spraying Parameters on Deposition Efficiency and Wear Behavior of Plasma Sprayed Alumina-Titania Composite Coatings

The effects of parameters, in the process of plasma-sprayed ceramic coating, upon the deposition efficiency of alumina-13 wt.% titania composite coatings are reported. The coatings were prepared by the atmospheric plasma spray process. The plasma torch input power, flow rates of primary, secondary and carrier gas, powder feed rate and spraying distance were considered as variables. The results show that the variations in all the selected spraying parameters strongly affect the deposition efficiency. The micro-hardness, as well as erosive and sliding wear rates of the coating are also affected by these parameters. Especially the input power strongly affects the phase and microstructure of the coatings.

Adsorption Behavior of Reducing End-Modified Cellulose Nanocrystals:A Kinetic Study Using Quartz Crystal Microbalance

In this work,we studied the adsorption of modified cellulose nanocrystals onto solid surfaces by quartz crystal microbalance with dissipation monitoring(QCM-D).Cellulose nanocrystals obtained from tunicate(CNC)were modified at reducing end by amidation reactions.Two different functionalities were investigated:a polyamine dendrimer(CNC-NH_(2)),which interacts with gold surface by the amine groups;and a biotin moiety(CNC-Biot),which has a strong affinity for the protein streptavidin(SAV).QCM-D results revealed different adsorption behaviors between modified and unmodified CNCs.Hence,unmodified CNCs covered almost all the surface forming a rigid and flat layer whereas reducing end modified CNCs remained rather upright forming a hydrated and viscoelastic layer with lower surface coverage.The analysis of adsorption kinetics allowed the calculation of an apparent collision rate factor,which resulted 10-fold higher for unmodified CNCs compared to reducing end modified CNCs,therefore,demonstrating the different adsorption behavior.

Elasticity Ratio of Resource Consumption and the Resource Consumption

Today the resources are becoming scarcer, which should not be regarded as unexhausted any more. Correspondingly, the production would be constrained by the scarcity of resources clearly. Then the economic researchers would pay much more attention to reducing the consumption of natural resources in the future. Therefore this paper brings foreword the conception of elasticity ratio of resource consumption based on the concept of elasticity and analyzes the relationship between the parameters. For the certain relationships between the elasticity ratio of resource consumption and resource consumption, this paper will try to reveal, to keep economy growing while resource consumption reducing, what conditions should be met as to the relationships among resource productivity, its growth rate, energy saving efficiency, economic growth rate and elasticity ratio of resource consumption. This paper proves the relationship between the China＇s energy consumption and economy growth using statistic data from 1978 to 2003.

A new method for evaluating the injection effect of chemical flooding

Hall plot analysis,as a widespread injection evaluation method,however,often fails to achieve the desired result because of the inconspicuous change of the curve shape.Based on the cumulative injection volume,injection rate,and the injection pressure,this paper establishes a new method using the ratio of the pressure to the injection rate（RPI） and the rate of change of the RPI to evaluate the injection efficiency of chemical flooding.The relationship between the RPI and the apparent resistance factor（apparent residual resistance factor） is obtained,similarly to the relationship between the rate of change of the RPI and the resistance factor.In order to estimate a thief zone in a reservoir,the influence of chemical crossflow on the rate of change of the RPI is analyzed.The new method has been applied successfully in the western part of the Gudong 7th reservoir.Compared with the Hall plot analysis,it is more accurate in real-time injection data interpretation and crossflow estimation.Specially,the rate of change of the RPI could be particularly suitably applied for new wells or converted wells lacking early water flooding history.

Evaluation of new large area PMT with high quantum efficiency

The neutrino detector of the Jiangmen Underground Neutrino Observatory（JUNO） is designed to use20 kilotons of liquid scintillator and approximately 16000 20 inch photomultipliers（PMTs）.One of the options is to use the 20 inch R12860 PMT with high quantum efficiency which has recently been developed by Hamamatsu Photonics.The performance of the newly developed PMT preproduction samples is evaluated.The results show that its quantum efficiency is 30%at 400 nm.Its Peak/Valley（P/V） ratio for the single photoelectron is 4.75 and the dark count rate is 27 kHz at the threshold of 3 mV while the gain is at 1 × 10^7.The transit time spread of a single photoelectron is 2.86 ns.Generally the performances of this new 20 inch PMT are improved over the old one of R3600.