Flattening the climate curve

<p>With the arrival of COVID we have learned how to flatten the "pandemic curve" during the past year. Now it is time to finally flatten the global warming, climate change curve.</p><p>The scientific knowledge is clear and unequivocal, but we must now strengthen our scientific communication to the general population, to governments, to industry, and to the private sector, to drive changes to our social behaviour as individuals, workers, communities and general society.</p><p>We talk a lot about private and public partnership; we need also to include also the scientific community in this cooperation. All of society needs to know and understand the challenges, in order to drive changes in social behaviour that reduce greenhouse gases emissions.</p>

Innovative approach for automatic land cover information extraction from LiDAR data

An airborne laser scanning (ALS) system with LiDAR (Light Detection and Ranging) technology is a highly precise and accurate 3D point data acquisition technique. LiDAR technology has been extensively used in digital surface/terrain modelling (DSM/DTM), and related applications such as 3D city modelling and building extraction. The capability of LiDAR systems to record the intensity of the return laser pulse backscattered energy in addition to the range data has motivated researchers to investigate the use of LiDAR intensity data for extracting land cover information. The main goal of this research is to maximize the benefits of the use of LiDAR data independently of any external source of data for automatically extracting accurate land cover information. Several new approaches are introduced in this research: a) classifying and filling the LiDAR intensity point cloud to produce a land cover image, b) combing multiple classified data of multiple LiDAR data-strips, c) statistical analysis segmentation technique that uses the concept of the kurtosis change curve algorithm for automatic classification of LiDAR data, and d) accelerating the classification process of large datasets by partitioning the large datasets into small, manageable datasets. Applying the traditional image classification techniques on LiDAR elevation and intensity data exclusively is included. Pixel-based, object-based, and point-based classification logics are conducted, and their results are compared to reference data. The results indicated that LiDAR data (range and intensity) can independently be used in land cover classification. By applying traditional pixel-based, supervised image classification techniques, the classification results show that auxiliary layers, which are extracted from range and intensity data, can be used for land cover classification. However, applying the supervised classification techniques on the LiDAR point cloud data without converting the data into images (Point-based logic) produced more accurate land cover classification results. The experiments on the proposed classification approach using the statistical analysis segmentation technique (based on the concept of the kurtosis change curve algorithm) show that it can be used to classify LiDAR data for land cover mapping.

Innovative approach for automatic land cover information extraction from LiDAR data

An airborne laser scanning (ALS) system with LiDAR (Light Detection and Ranging) technology is a highly precise and accurate 3D point data acquisition technique. LiDAR technology has been extensively used in digital surface/terrain modelling (DSM/DTM), and related applications such as 3D city modelling and building extraction. The capability of LiDAR systems to record the intensity of the return laser pulse backscattered energy in addition to the range data has motivated researchers to investigate the use of LiDAR intensity data for extracting land cover information. The main goal of this research is to maximize the benefits of the use of LiDAR data independently of any external source of data for automatically extracting accurate land cover information. Several new approaches are introduced in this research: a) classifying and filling the LiDAR intensity point cloud to produce a land cover image, b) combing multiple classified data of multiple LiDAR data-strips, c) statistical analysis segmentation technique that uses the concept of the kurtosis change curve algorithm for automatic classification of LiDAR data, and d) accelerating the classification process of large datasets by partitioning the large datasets into small, manageable datasets. Applying the traditional image classification techniques on LiDAR elevation and intensity data exclusively is included. Pixel-based, object-based, and point-based classification logics are conducted, and their results are compared to reference data. The results indicated that LiDAR data (range and intensity) can independently be used in land cover classification. By applying traditional pixel-based, supervised image classification techniques, the classification results show that auxiliary layers, which are extracted from range and intensity data, can be used for land cover classification. However, applying the supervised classification techniques on the LiDAR point cloud data without converting the data into images (Point-based logic) produced more accurate land cover classification results. The experiments on the proposed classification approach using the statistical analysis segmentation technique (based on the concept of the kurtosis change curve algorithm) show that it can be used to classify LiDAR data for land cover mapping.

Simulation of electrothermal characteristics of MEMS energy changer under different current excitation

The simulation model of MEMS energy changer is established by using the finite element analysis software ANSYS. The electrothermal performance of MEMS energy changer under the action of different currents was simulated and analyzed. The bridge area is made of NiCr, and the shape of the bridge area is two different chamfering rectangles. The temperature distribution diagram of MEMS energy changers, the temperature change curve and the phase transition distribution diagram of the bridge region were obtained when the four current values acted on each other. The simulation results are analyzed and discussed.

Study on risk assessment of expressway nighttime maintenance construction: A Dynamic Bayesian Network model

There are many risk factors and large uncertainties in expressway nighttime maintenance construction(ENMC), and the state of risk factors will change dynamically with time. In this study, a Dynamic Bayesian Network (DBN) model was proposed to investigate the dynamic characteristics of the time-varying probability of traffic accidents during expressway maintenance at night. Combined with Leaky Noisy-or gate extended model, the calculation method of conditional probability is determined . By setting evidences for DBN reasoning, the time series change curve of the probability of traffic accidents and other risk factors are obtained. The results show that DBN can be applied to risk assessment of ENMC.

Design and development characteristics research of modular space deployable solar wing

In order to solve the problems of the existing solar wing, such as complex process and obvious structural vibration. a new space deployable solar wing mechanism composed of single DOF modularization was designed. The structure and working principle of the space deployable solar wing are described, and the driving system is briefly introduced. The single module of the solar wing is divided into two parts and the kinematics equations of the kite-shaped mechanism and origami mechanism are established respectively. Secondly, the output motion rule of the bar at the end was solved when the special driving is applied to the kite-shaped mechanism. And based on this output, changed the angle of the origami mechanism’ plates and the change curve of the centre of mass and the angle between the plates is obtained. The study results show that, synthesize considering the shrinkage and the ratio of folding to span, the optimal solution is the angle of plates φ=4°. Through the above research that provide the theoretical basis for the optimization and improvement of the mechanism.

Strategic Adaptation as a Way of Managing Organizational Changes in the Context of Implementing a Safety Oriented Enterprise Management Approach

Strategic adaptation is one of the effective approaches of enterprise management, which is based on implementing safety-oriented management, taking into account current dangers, threats and risks. First, such adaptation is associated with changes in the enterprise management system, aimed at establishing appropriate communications between the structural divisions of the enterprise, the distribution of authorities and responsibility for making decisions, counteracting the opportunistic behavior of employees due to changes in the organizational structure of the enterprise management. In the process of research, the use of L. Greiner's Model of Organizational Change was proposed (for a generalized picture of the sequence of organizational changes), and the Change Curve Model by J. Duck was adapted (when developing a fundamental sequence of measures to identify the main causes of workers' resistance and choose ways to counter it). This allows optimizing the processes of strategic adaptation within the safety oriented approach of enterprise management.

An operational audit for a change model in the hospitality industry

Various models are adopted in the change process for a hotel group: Lewin’s Force Field model, Handy’s Shamrock structure, Hiatt change model, Classic Change Curve, Kotter’s model, Gap Analysis model and McKinsey Seven “S” model. The change model aims to strengthen the hotel's profitability. Traditional orthodoxies are challenged, new paradigms of change and operational audits are implemented.

Simulation of Waste Heat Recovery From Ship Boiler Exhaust Gas

The heat pipe type waste heat recovery system can effectively reduce energy consumption when the ship is sailing in a polar region, so it has great engineering application value. In order to improve the design of the heat pipe waste heat recovery system and ensure that the design parameters meet the design requirements, this project has carried out a three-dimensional simulation analysis of the internal flow field of the heat pipe waste heat recovery system. Through reasonable model processing, application of boundary conditions, and the assignment of physical attributes the flow field characteristics of the key positions of the heat pipe type waste heat recovery system were obtained scientifically and effectively. The model was simulated and calculated, and the flue gas temperature distribution in the evaporator heat exchange tube, the overall temperature distribution of the waste heat recovery system, and the temperature change curve from the cold water entering the condenser to the steady state were obtained. The change curve of the thermal efficiency of the system during the temperature of the flue gas from the evaporator to the steady state.