Detailed Geometric Information Research Articles

SCViT: A Spatial-Channel Feature Preserving Vision Transformer for Remote Sensing Image Scene Classification

Convolutional neural network (CNN)-based methods are widely used in remote sensing image scene classification and can obtain excellent performances. However, the stacked receptive fields in the CNN-based methods have limitations in modeling the long-range dependencies of local features. The vision transformer (ViT) model provides a good solution as it directly considers the global interactions of local patches by the self-attention mechanism. However, the vanilla ViT model, which simply splits images into fixed-size patches treated as tokens, mainly considers the global information in the spatial domain. In this article, a spatial-channel feature preserving ViT (SCViT) model is proposed, which considers both the detailed geometric information of the high-spatial-resolution (HSR) imagery and the contribution of the different channels contained in the classification token. First, in the proposed method, tokens are generated by progressively aggregating the neighboring overlapping patches to extract the local structural features of the imagery. Second, a multihead self-attention (MSA) mechanism is used to model the global interactions of the tokens in the encoder. A lightweight channel attention (LCA) module is then introduced to consider the importance of the different channels in the classification token. Finally, a multilayer perceptron (MLP) is used to acquire the final results. Compared with the state-of-the-art scene classification methods, the experimental results confirm the potential of using ViT models in remote sensing image scene classification.

DATA INTEROPERABILITY OF BUILDING INFORMATION MODELING AND GEOGRAPHIC INFORMATION SYSTEM IN CONSTRUCTION INDUSTRY

Abstract. Application of Building Information Modeling (BIM) in construction industry has been applied for many years back. This because BIM can provide a better advantage in construction industry in term of controlling and managing construction project during their life cycle. The advantages that can be provide by BIM is focusing on the indoor planning tasks. But, when the construction project involves, besides indoor planning, outdoor planning also is important part that need to be look up. To cover the outdoor planning in construction project, Geographic Information System (GIS) need to be applied. GIS can overcome this problem because GIS mainly for outdoor planning by using their spatial analysis. GIS can offer a high degree of geospatial information and can provide the detailed geometrical and semantic information of building to assisted across improve automation. Towards produce the improved preparation in construction project, BIM and GIS should be integrated. To integrate both domains, the data interoperability between them need to be investigate because they used different data standard. This study focusses on solving the data interoperability through the data integration between BIM and GIS to solve the problem of data mismatch and data missing during data translation process. Industry Foundation Classes (IFC) was used as a data standard to perform the data integration between BIM and GIS. The outcomes from this study show that when the data interoperability applied between BIM and GIS, the problem above can be solved, and the data dimension and their coordinate system also can be control.

Multiple Sensor Synchronization with theRealSense RGB-D Camera

When reconstructing a 3D object, it is difficult to obtain accurate 3D geometric information using a single camera. In order to capture detailed geometric information of a 3D object, it is inevitable to increase the number of cameras to capture the object. However, cameras need to be synchronized in order to simultaneously capture frames. If cameras are incorrectly synchronized, many artifacts are produced in the reconstructed 3D object. The RealSense RGB-D camera, which is commonly used for obtaining geometric information of a 3D object, provides synchronization modes to mitigate synchronization errors. However, the synchronization modes provided by theRealSense cameras can only sync depth cameras and have limitations in the number of cameras that can be synchronized using a single host due to the hardware issue of stable data transmission. Therefore, in this paper, we propose a novel synchronization method that synchronizes an arbitrary number of RealSense cameras by adjusting the number of hosts to support stable data transmission. Our method establishes a master–slave architecture in order to synchronize the system clocks of the hosts. While synchronizing the system clocks, delays that resulted from the process of synchronization were estimated so that the difference between the system clocks could be minimized. Through synchronization of the system clocks, cameras connected to the different hosts can be synchronized based on the timestamp of the data received by the hosts. Thus, our method synchronizes theRealSense cameras to simultaneously capture accurate 3D information of an object at a constant frame rate without dropping it.

Energy saving in rail transport

Aim of this article is to introduce and present advantages and possibilities of using simulation tools to calculate energy flows of tractive vehicle in all phases of its ride. The focus is on the braking phase, especially on the braking energy recuperation that offers the highest energy saving potential.Energetic simulation was carried out as a part of a current railway reconstruction study, which is a good example of possible energetic calculation use. Energetic calculation in the simulation are performed using so called "exact method" developed at the Faculty of Transportation. The advantage of the method is that it provides a high degree of accuracy. Due to the simulation calculation being performed in real-time, the user can enter the calculation even during the simulation. Crucial part ofevery simulation are quality input data, such as vehicle braking characteristic (including all working points below the envelope line together with the efficiency characteristics of the power train parts (engine, transmission, convertor and others)). Also, sufficiently precise (with a precision of 1 meter) railway track details (detailed geometrical and other information on the current and reconstructed railway track or on the railway track proposal.To present savings during the ride, the railway track section on the track Montreál-Sherbrooke was chosen. On this track, (especially electrification and partial reconstruction of the superstructure) is planned. Reconstruction level will be dependant on the local economical and social conditions. However, in the most optimistic case, total electrification of the track will be undertaken, or lower level of the reconstruction when the vehicles that have very similar characteristics. The railway track section is located between the cities of Montreál and Sherbrooke, that are 160 km apart. To compare the current, and possible future, state, comparison of energy consumption of the vehicle was conducted on the same track with the same geometrical characteristics.We can assume that the overall energy intensity of the ride on the newly reconstructed track (eg. with greater radius of the arches) will be lower than the overall energy intensity of the ride on the track before reconstruction. Current data on energetic consumption are not available, therefore they were obtained by simulation and verified by calculations and considered sufficiently accurate.Presumably, the input simulation parameters required for the simulation will not always be delivered in the sufficient quality or will be partly missing completely. In these cases they will be substituted by various algorithms, that can be machine-processed and that are part of the simulation calculations. One of the crucial algorithms is so called "moment efficiency". Its machine processingis not entirely developed and therefore, this simulation will be conducted without its usage. For financial reasons, simulation calculation was verified only by the theoretical physical calculation method. Based on several partial results, emergent computing tool is functional and sufficiently accurate. The simulation program is supposed to be experimentally verified after its finishing.The outcomes presented in this article are calculated by simulated computation and were not confronted with the real situation in any way. However, relevant calculation algorithms, processes and theoretical background of the simulation were already verified on the older software versions. Therefore, the simulated outcomes are supposed to be at least sufficiently accurate to provide preliminary study for the railway reconstruction. Presented calculations were executed by using author’s simulation software.Part of the methodology was taken from the previous, already verified, versions of the software for vehicle ride simulation.

Integrated model of transmission tower surge impedance and multilayer grounding system based on full-wave approach

In this paper, a full-wave approach based on the method of moment (MoM) is proposed to investigate the harmonic impedance of a tower and its connected ground electrode in the frequency domain. The accuracy of the results is validated in comparison with NEC-4. The proposed numerical method is also employed for the evaluation of a full-sized HVDC tower harmonic impedance. The main contribution is the assessment of the harmonic impedance of a real tower with detailed geometrical information connected to the multi-layer grounding system. The validity of the transmission line method is evaluated through comparison with the results computed using the developed full-wave approach at the high frequency. In addition, the simulation results assure that a real tower’s harmonic impedance could be smaller than the value estimated for very simplified models at the high frequencies. When the full-wave method is applied and the precise model of the ground electrode is considered, the harmonic impedance of the tower in the frequency domain and consequently, the transient impedance in the time domain are different, while the grounding system is assumed to be a perfectly conducting plane. These differences can become very significant, especially close to the resonant frequencies. The harmonic impedance of power transmission towers is strongly influenced by the connected grounding system.

Fusion of urban 3D point clouds with thermal attributes using MLS data and TIR image sequences

Buildings take a large proportion of the total energy consumption in the city area in winter, therefore Thermal Infrared (TIR) images are widely used to evaluate the energy consumption and leakage of the building. To overcome the difficulties of image interpretation and occlusion in TIR images, utilizing thermal information in 3D structures that fuse TIR images with usable georeferenced 3D coordinates of buildings, is mandatory. To accomplish this mission, we propose a strategy to generate a thermal point cloud combining Mobile Laser Scanning (MLS) point clouds and TIR images. At first, a key-points extraction method based on line-intersection is presented, which helps to detect key-points from highly distorted TIR images. Then, the semi-automatic and the automatic correspondence determination algorithm based on restricted RANSAC for 6DOF pose estimation is proposed and tested. Finally, a non-local mean strategy for data fusion is applied, which integrates the thermal attributes from image sequences and the geometric property from the point clouds, resulting in a smooth representation of thermal point clouds with comprehensive radiance property for thermal analysis. The fusion result qualitatively presents thermal radiation of elements of buildings with detailed geometric information. The generated thermal point clouds contribute to evaluating the energy efficiency of buildings, or building blocks, analyzing the invisible building structure or pipelines for retrofit, and monitoring the energy usage of buildings for long-term development.

Research on Lightweight Method of MBD Model for Additive Manufacturing

In order to solve the problems of difficult storage and slow transmission of large data in remote transmission of 3D model for additive manufacturing, a lightweight method on MBD model is proposed. A lossless compression algorithm is applied and improved in this paper to simplified the product data model and minimize data exchange file. At the same time, a detailed geometric information model is retained to realize the rapid transmission of lightweight model, which provides a convenient method for remote transmission and acquisition of 3D model in additive manufacturing process. A case study on the MBD model of a packaging machine has verified is taken as an example to verify the feasibility of the method.

Machine-learning Prediction of Infrared Spectra of Interstellar Polycyclic Aromatic Hydrocarbons

Abstract We design and train a neural network (NN) model to efficiently predict the infrared spectra of interstellar polycyclic aromatic hydrocarbons with a computational cost many orders of magnitude lower than what a first-principles calculation would demand. The input to the NN is based on the Morgan fingerprints extracted from the skeletal formulas of the molecules and does not require precise geometrical information such as interatomic distances. The model shows excellent predictive skill for out-of-sample inputs, making it suitable for improving the mixture models currently used for understanding the chemical composition and evolution of the interstellar medium. We also identify the constraints to its applicability caused by the limited diversity of the training data and estimate the prediction errors using a ensemble of NNs trained on subsets of the data. With help from other machine-learning methods like random forests, we dissect the role of different chemical features in this prediction. The power of these topological descriptors is demonstrated by the limited effect of including detailed geometrical information in the form of Coulomb matrix eigenvalues.

ENHANCEMENT OF DEPTH MAP BY FUSION USING ADAPTIVE AND SEMANTIC-GUIDED SPATIOTEMPORAL FILTERING

Abstract. Extracting detailed geometric information about a scene relies on the quality of the depth maps (e.g. Digital Elevation Surfaces, DSM) to enhance the performance of 3D model reconstruction. Elevation information from LiDAR is often expensive and hard to obtain. The most common approach to generate depth maps is through multi-view stereo (MVS) methods (e.g. dense stereo image matching). The quality of single depth maps, however, is often prone to noise, outliers, and missing data points due to the quality of the acquired image pairs. A reference multi-view image pair must be noise-free and clear to ensure high-quality depth maps. To avoid such a problem, current researches are headed toward fusing multiple depth maps to recover the shortcomings of single-depth maps resulted from a single pair of multi-view images. Several approaches tackled this problem by merging and fusing depth maps, using probabilistic and deterministic methods, but few discussed how these fused depth maps can be refined through adaptive spatiotemporal analysis algorithms (e.g. spatiotemporal filters). The motivation is to push towards preserving the high precision and detail level of depth maps while optimizing the performance, robustness, and efficiency of the algorithm.

Topological features dictate the mechanics of the mammalian brains

Understanding brain mechanics is crucial in the study of pathologies involving brain deformations such as tumor, strokes, or in traumatic brain injury. Apart from the intrinsic mechanical properties of the brain tissue, the topology and geometry of the mammalian brains are particularly important for its mechanical response. We use computational methods in combination with geometric models to understand the role of these features. We find that the geometric quantifiers such as the gyrification index play a fundamental role in the overall mechanical response of the brain. We further demonstrate that topological diversity in brain models is more important than differences in mechanical properties: Topological differences modify not only the stresses and strains in the brain but also its spatial distribution. Therefore, computational brain models should always include detailed geometric information to generate accurate mechanical predictions. These results suggest that mammalian brain gyrification acts as a damping system to reduce mechanical damage in large-mass brain mammals. Our results are relevant in several areas of science and engineering related to brain mechanics, including the study of tumor growth, the understanding of brain folding, and the analysis of traumatic brain injuries.

Discriminating Possible Causes of Microwave Brightness Temperature Positive Anomalies Related With May 2008 Wenchuan Earthquake Sequence

Based on the spatiotemporally weighted two-step method (STW-TSM), the spatiotemporal characteristics of the residual microwave brightness temperature (MBT) with the Mw7.9 Wenchuan earthquake on May 12, 2008 are revealed by satellite data from the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) sensor. Two significant MBT positive anomalies are found to be exactly in spatial accordance with two geological Quaternary zones, and the detailed geometric information of the MBT positive anomaly is found to be correlated with the microwave frequencies. After eliminating other possible influential factors, including surface temperature, vegetation index, land-surface roughness, and surface soil moisture under the conditions of space, time, and magnitude, and according to the microwave radiative transfer model, the dielectric variation in the ground surface is suggested to be the primary contributor of the MBT positive anomaly. The positive-hole (P-hole) theory is applied to interpret the geological preference of the MBT positive anomalies through a chain process: crustal stress enhancing—P-hole producing and flowing down stress gradients—surface P-hole accumulating—dielectric constant decreasing—and microwave radiation increasing. The stress-resulting effect of the dielectric decrease on MBT the increase provides a novel mechanism for microwave remote-sensing monitoring of crustal stress field alteration, earthquake preparation, and upcoming shocks. This research has a particular significance for searching potential georelations between the tectonic earthquake preparation and the abnormal satellite MBT.

Advanced measurement techniques for braided composite structures: A review of current and upcoming trends

Braiding is an advanced textile manufacturing method that is used to produce two-dimensional and three-dimensional components. Unlike laminated structures, braids have interlaced yarns that form a continuity between layers. This structure allows for improved impact resistance, damage tolerance, and improved through-thickness reinforcement. Despite the numerous advantages of braided composites, braids also have shortcomings. Their highly complex fiber architecture presents challenges in the availability and choice of the strain measuring and characterization techniques. Advanced measurement methods such as optical strain measurement, micro-computed tomography, and in situ strain measurement are required. Optical strain measurement methods such as digital image correlation and high-speed imaging are necessary to accurately measure the complex deformation and failure that braided composites exhibit. X-ray-based micro-computed tomography measurements can provide detailed geometric and morphologic information for braided structures, which is necessary for accurately predicting the mechanical properties of braided structures. Finally, in situ strain measurement methods will provide detailed information on the internal deformation and strain that exists within braided structures. In situ sensors will also allow for in-service health monitoring of braided structures. This paper provides a detailed review of the aforementioned sensing technologies and their relation to the measurement of braided composite structures.

Integrating BIM and IoT for smart bridge management

Considering high risk, long construction period, high construction and maintenance costs, bridge management is asynchronous, unintelligent and inefficient. The purpose of this research is to investigate a new approach with its supporting building information modelling (BIM) and Internet of Things (IoT) tool to enhance the smart management in bridge life cycle. BIM provides detailed geometric and semantic information and IoT contains the management and analysis of the actual condition of the bridge. An example of a super bridge under construction in Xinjiang is used to illustrate the developed system. Results show that the developed system can significantly grasp the quality of the bridge in time, reduce the construction risk and construction period. The developed BIM/IoT-based system is also effective and practical in the quality and risk management among multiple locations, such as smart buildings, smart tunnels, and even smart cities.

Deep Learning-Based Damage Detection from Aerial SfM Point Clouds

Aerial data collection is well known as an efficient method to study the impact following extreme events. While datasets predominately include images for post-disaster remote sensing analyses, images alone cannot provide detailed geometric information due to a lack of depth or the complexity required to extract geometric details. However, geometric and color information can easily be mined from three-dimensional (3D) point clouds. Scene classification is commonly studied within the field of machine learning, where a workflow follows a pipeline operation to compute a series of engineered features for each point and then points are classified based on these features using a learning algorithm. However, these workflows cannot be directly applied to an aerial 3D point cloud due to a large number of points, density variation, and object appearance. In this study, the point cloud datasets are transferred into a volumetric grid model to be used in the training and testing of 3D fully convolutional network models. The goal of these models is to semantically segment two areas that sustained damage after Hurricane Harvey, which occurred in 2017, into six classes, including damaged structures, undamaged structures, debris, roadways, terrain, and vehicles. These classes are selected to understand the distribution and intensity of the damage. The point clouds consist of two distinct areas assembled using aerial Structure-from-Motion from a camera mounted on an unmanned aerial system. The two datasets contain approximately 5000 and 8000 unique instances, and the developed methods are assessed quantitatively using precision, accuracy, recall, and intersection over union metrics.

Verification of stereotactic cranial radiotherapy treatments with MR-based gel dosimeters: practical aspects

Image Guided Radiotherapy (IGRT) systems allow delivering high doses of radiation to a tumour with great precision and accuracy. In this work, we use patient-specific head MR-based gel dosimeters as an end-to-end test to commission IGRT delivery systems, for stereotactic cranial radiotherapy, and investigate possible sources of errors associated with practical aspects of the measurements. A CT scan of a patient is used to 3D print the shape of the cranial bones to create head phantoms with MR-based gel inside. Each phantom was used as a patient, following the radiotherapy workflow which includes: taking a CT scan of the phantom, calculating the dose distribution using a treatment planning system (TPS) and delivering the radiation calculated by the TPS (to target three different lesions: Big, Medium and Small). Each phantom was then scanned on an MR scanner to obtain a T2 map (linear with dose), which was then rigidly registered with the CT scan of the phantom based on the phantom structures. Good agreement was obtained between the normalized R2 (=1/T2) values and TPS simulations. The relationship between R2 values and dose was investigated based on 3D regions including each lesion. Good linearity was found, but different R2-dose values relationship was obtained depending on the selected regions. The impact of applying a registration based on each lesion (and not the phantom structures) was also tested. Results show that the registration has an impact on the relationship between R2 values and dose, and although absolute dose measurements are still not possible with these MR-based gel dosimeters, they provide very detailed geometrical 3D information to validate IGRT radiotherapy treatments with high level of accuracy.

Investigation and modeling of direct toppling using a three-dimensional distinct element approach with incorporation of point cloud geometry

Block toppling instability can be a common problem in natural rock masses, especially in mining environments where excavation activity may trigger discontinuity-controlled instability by modifying the natural slope geometry. Traditional investigations of block toppling failure consider classic kinematic analyses and simplified two-dimensional limit equilibrium methods. This approach is still the most commonly adopted, but the simple two-dimensional conceptual model may often oversimplify the instability mechanisms, ignoring potential critical factors specifically related to the three-dimensional geometry. This paper uses a three-dimensional distinct element method approach applied to an example case study, identifying the critical parameters that influence direct toppling instability in an open pit environment. Terrestrial laser scanning was used to obtain detailed three-dimensional geometrical information of the slope face geometry for subsequent stability analyses. A series of sensitivity analyses on critical parameters such as friction angle, discontinuity shear and normal stiffness, discontinuity spacing, and orientation was performed, using simple conceptual three-dimensional numerical modeling. Results of the analyses revealed the importance of undertaking three-dimensional analyses for direct toppling investigations that allow identification of critical parameters. A three-dimensional distinct element analysis was then performed using a more realistic complex volumetric mesh model of the case study slope which confirmed the previous modeling results but also identified unstable blocks in high slope angle areas, providing useful information for life of mine design. The paper highlights the importance of slope geometry and fracture network orientation on potential slope instability mechanisms.

BIM-based framework to analyze the effect of natural ventilation on thermal comfort and energy performance in buildings

Buildings use significant amount of energy worldwide, with mechanical air-conditioning systems accounting for a large proportion of the total energy consumed. Utilizing natural ventilation can achieve a comfortable indoor thermal environment while reducing the use of air-conditioning and building energy consumption. However, previous studies mainly focused on either thermal comfort or energy conservation by utilizing natural ventilation. The correlation between thermal comfort and energy performance due to the effect of natural ventilation is important, but has not been studied thoroughly in literature. Moreover, natural ventilation in buildings is greatly affected by building geometry, material property, outdoor environmental condition and occupancy, which were not fully incorporated in the previous studies. This paper presents a framework based on building information modeling (BIM) to study the effect of natural ventilation on the correlation between thermal comfort and energy performance. BIM provides 3D building models with detailed geometric and material information as well as the building location and type that help determine the outdoor environmental condition and occupancy, thereby improving the accuracy of natural ventilation simulation. A case study was conducted using the proposed framework, aimed at investigating the natural ventilation in a residential flat in Hong Kong at different seasons. The results show that utilizing natural ventilation cannot always achieve thermal comfort. Natural ventilation brings cool air in late spring (April) during which the indoor temperature can be controlled at a comfortable level and the energy use for mechanical ventilation can be saved. The proposed framework helps evaluate the natural ventilation in buildings for maintaining indoor thermal comfort at minimal energy use, thereby creating a more sustainable built environment.

Efficient and robust lane marking extraction from mobile lidar point clouds

Surveys of roadways with Mobile Laser Scanning (MLS) are now being conducted on a regular basis by many transportation agencies to provide detailed geometric information to support a wide range of applications, including asset management. Most MLS systems provide intensity (return signal strength) data as a point attribute in georeferenced point clouds, which may be used to estimate retro-reflectivity of pavement markings for effective maintenance. Nevertheless, the extraction of pavement markings from mobile lidar data remains an open challenge, due to variable noise, degree of wear on the markings, and road conditions. This paper addresses these challenges, presenting a novel approach for efficient, reliable extraction of lane markings, including those that have been significantly worn. First, using the MLS trajectory information, the lidar data is discretized into smaller sections, and then transformed to the local coordinate system, such that the road surface is near-horizontal for reliable extraction on roads with significant grade. Subsequently, the road surface is extracted using the constrained Random Sampling and Consensus (RANSAC) algorithm and then rasterized into a 2D intensity image to apply image processing techniques, namely: image segmentation to separate the lane markings from the road pavement, and a morphological opening operation to remove small objects. However, the extracted lane markings are prone to over-segmentation, due to occlusions or worn portions caused by moving vehicles. To rectify this, topologically-similar lane markings are associated with each other by computing line parameters (i.e., orientation and distance from the origin), which enables the gaps to be filled among the associated lanes. Finally, the remaining incorrect lane markings are detected and removed through a noise filtering phase using Dip test statistics. Examples of the effectiveness and application of the methodology are shown for a variety of sites with stripes of variable condition to highlight the robustness of the approach. Using optimized parameter values, the algorithm achieved F1 scores of 89–97% when tested on a variety of datasets encompassing a wide range of road scene types.

INTEGRATION OF GIS AND BIM TECHNIQUES IN CONSTRUCTION PROJECT MANAGEMENT – A REVIEW

Abstract. Construction industry has become much more complex due to the large number of people and documentations involved. As a result, the full process of building construction may involve with many different types and format of information that needs to collect, document and share. In order to share this information between architect, contractor, construction manager, etc., there are need to develop a common model that can document and store this information in single platform. BIM represents a series of parametric objects that composed together to form a building model which carries all information includes their physical and functional characteristics and project life cycle information. Since BIM represent the detailed geometrical and semantic information of the building, the application of GIS is needed to manage the construction project's information resources. GIS can use information from many different sources, in many different formats and can link data sets together by common locational data such as coordinate or postal zip code. Besides, GIS can use combinations of data sets to build and analyze integrated information and also can convert the existing digital information into a form that meets the user‟s need. From this point of view, GIS can complement BIM function in order to develop a systematic platform for construction purpose. Finding of this study, there are some drawbacks in this technique especially in the construction application in term of data sharing, data integration and data management. Furthermore, the integration of GIS in BIM is studied and potential techniques are shown to overcome the drawbacks of the construction application.

Asymmetric substitution changes the UV-induced nonradiative decay pathway and the spectra behaviors of β-diketones.

Asymmetric substitution has not been termed as an essential factor in studying photo-induced ultrafast dynamics of molecular system. Asymmetric 4-hydroxybut-3-en-2-one (HEO), together with symmetric malonaldehyde (MA) and acetylacetone (AA), have been provided as target sample to study the nonradiative decay (ND) processes of β-diketones. An effective ND pathway of the three molecules is presented that their excited second (S2) states transfer to first (S1) state by nonadiabatic surface hopping, and then transfer to triplet (T1) state by crossing minimum energy crossing point (MECP), after which decay to ground (S0) state through MECP. More importantly, the asymmetric substitution of HEO induces the proton transfer in the S1 state and generates a proton-transferred conformer with lowest energy, which does not occur for MA and AA. This change exploits a new ND pathway that the S1 state decays to the proton transferred T1 state and then undergoes reverse proton transfer to S0 state through the MECPs between the three states. The two pathways of HEO give detailed energy and geometric information on surface hopping of S2/S1 and MECPs of S1/T1/S0, and interpret the reason of the ND pathway while not spectra emission. This result is significantly different from the previous reported ND pathway of photoisomerization or conical intersection between different states. This work shows that asymmetric substitution changes the molecular structure and then changes their spectra behaviors.