Radiation-induced acoustic computed tomography(RACT)is an evolving biomedical imaging modality that aims to reconstruct the radiation energy deposition in tissues.Traditional backprojection(BP)reconstructions carry no...Radiation-induced acoustic computed tomography(RACT)is an evolving biomedical imaging modality that aims to reconstruct the radiation energy deposition in tissues.Traditional backprojection(BP)reconstructions carry noisy and limited-view artifacts.Model-based algorithms have been demonstrated to overcome the drawbacks of BPs.However,model-based algorithms are relatively more complex to develop and computationally demanding.Furthermore,while a plethora of novel algorithms has been developed over the past decade,most of these algorithms are either not accessible,readily available,or hard to implement for researchers who are not well versed in programming.We developed a user-friendly MATLAB-based graphical user interface(GUI;RACT2D)that facilitates back-projection and model-based image reconstructions for twodimensional RACT problems.We included numerical and experimental X-ray-induced acoustic datasets to demonstrate the capabilities of the GUI.The developed algorithms support parallel computing for evaluating reconstructions using the cores of the computer,thus further accelerating the reconstruction speed.We also share the MATLAB-based codes for evaluating RACT reconstructions,which users with MATLAB programming expertise can further modify to suit their needs.The shared GUI and codes can be of interest to researchers across the globe and assist them in e±cient evaluation of improved RACT reconstructions.展开更多
As computer simulation increasingly supports engine er ing design and manufacture, the requirement for a computer software environment providing an integration platform for computational engineering software increas e...As computer simulation increasingly supports engine er ing design and manufacture, the requirement for a computer software environment providing an integration platform for computational engineering software increas es. A key component of an integrated environment is the use of computational eng ineering to assist and support solutions for complex design. Computer methods fo r structural, flow and thermal analysis are well developed and have been used in design for many years. Many software packages are now available which provi de an advanced capability. However, they are not designed for modelling of powde r forming processes. This paper describes the powder compaction software (PCS_SU T), which is designed for pre- and post-processing for computational simulatio n of the process compaction of powder. In the PCS_SUT software, the adaptive analysis of transient metal powder forming process is simulated by the finite element method based on deformation theories . The error estimates and adaptive remeshing schemes are applied for updated co -ordinate analysis. A generalized Newmark scheme is used for the time domain di scretization and the final nonlinear equations are solved by a Newton-Raphson p rocedure. An incremental elasto-plastic material model is used to simulate the compaction process. To describe the constitutive model of nonlinear behaviour of powder materials, a combination of Mohr-Coulomb and elliptical yield cap model is applied. This model reflects the yielding, frictional and densification char acteristics of powder along with strain and geometrical hardening which occurs d uring the compaction process. A hardening rule is used to define the dependence of the yield surface on the degree of plastic straining. A plasticity theory for friction is employed in the treatment of the powder-tooling interface. The inv olvement of two different materials, which have contact and relative movement in relation to each other, must be considered. A special formulation for friction modelling is coupled with a material formulation. The interface behaviour betwee n the die and the powder is modelled by using an interface element mesh. In the present paper, we have demonstrated pre- and post-processor finite elem ent software, written in Visual Basic, to generate the graphical model and visua lly display the computed results. The software consist of three main part: · Pre-processor: It is used to create the model, generate an app ropriate finite element grid, apply the appropriate boundary conditions, and vie w the total model. The geometric model can be used to associate the mesh with th e physical attributes such as element properties, material properties, or loads and boundary conditions. · Analysis: It can deal with two-dimensional and axi-symmetric applications for linear and non-linear behaviour of material in static and dyna mic analyses. Both triangular and quadrilateral elements are available in the e lement library, including 3-noded, 6-noded and 7-noded (T6B1) triangles and 4 -noded, 8-noded and 9-noded quadrilaterals. The direct implicit algorithm bas ed on the generalized Newmark scheme is used for the time integration and an aut omatic time step control facility is provided. For non-linear iteration, choice s among fully or modified Newton-Raphson method and quasi-Newton method, using the initial stiffness method, Davidon inverse method or BFGS inverse method, ar e possible. · Post-processor: It provides visualization of the computed resu lts, when the finite element model and analysis have been completed. Post-proce ssing is vital to allow the appropriate interpretation of the completed results of the finite element analysis. It provides the visual means to interpret the va st amounts of computed results generated. Finally, the powder behaviour during the compaction of a multi-level component is numerically simulated by the PCS_SUT software, as shown in Fig.1. The predict ive compaction forces at different displacements are computed and compared with the available experimental展开更多
In this paper, the design of a Graphical User Interface for CAN data frame monitoring is presented. The GUI has been developed in the Qt Creator IDE. A touch screen for visualization and control is used, which in turn...In this paper, the design of a Graphical User Interface for CAN data frame monitoring is presented. The GUI has been developed in the Qt Creator IDE. A touch screen for visualization and control is used, which in turn is controlled by a development board with a SoC Cyclone V, through which a Linux operating system is executed.展开更多
Repackaging brings serious threats to Android ecosystem.Software birthmark techniques are typically applied to detect repackaged apps.Birthmarks based on apps'runtime graphical user interfaces(GUI)are effective,es...Repackaging brings serious threats to Android ecosystem.Software birthmark techniques are typically applied to detect repackaged apps.Birthmarks based on apps'runtime graphical user interfaces(GUI)are effective,especially for obfuscated or encrypted apps.However,existing studies are time-consuming and not suitable for handling apps in large scale.In this paper,we propose an effective yet efficient dynamic GUI birthmark for Android apps.Briefly,we run an app with automatically generated GUI events and dump its layout after each event.We divide each dumped layout into a grid,count in each grid cell the vertices of boundary rectangles corresponding to widgets within the layout,and generate a feature vector to encode the layout.Similar layouts are merged at runtime,and finally we obtain a graph as the birthmark of the app.Given a pair of apps to be compared,we build a weighted bipartite graph from their birthmarks and apply a modified version of the maximum-weight-bipartite-matching algorithm to determine whether they form a repackaging pair(RP)or not.We implement the proposed technique in a prototype,GridDroid,and apply it to detect RPs in three datasets involving 527 apks.GridDroid reports only six false negatives and seven false positives,and it takes GridDroid merely 20 microseconds on average to compare a pair of birthmarks.展开更多
This paper deals with a problem of application generation together with their Graphic User Interface （GUI）. Particularly, the source code generator based on dynamic frames was improved for more effective specificati...This paper deals with a problem of application generation together with their Graphic User Interface （GUI）. Particularly, the source code generator based on dynamic frames was improved for more effective specification of GUI. It＇s too demanding for the developers to have specification of the application that contain all physical coordinates and other details of buttons and other GUI elements. The developed solution for this problem is based on post-processing of generated source code using iterators for specifying coordinates and other values of graphic elements. The paper includes two examples of generating web applications and their GUI.展开更多
The rapid and accurate assessment of structural damage following an earthquake is crucial for effective emergency response and post-disaster recovery. Traditional manual inspection methods are often slow, labor-intens...The rapid and accurate assessment of structural damage following an earthquake is crucial for effective emergency response and post-disaster recovery. Traditional manual inspection methods are often slow, labor-intensive, and prone to human error. To address these challenges, this study proposes STPEIC (Swin Transformer-based Framework for Interpretable Post-Earthquake Structural Classification), an automated deep learning framework designed for analyzing post-earthquake images. STPEIC performs two key tasks: structural components classification and damage level classification. By leveraging the hierarchical attention mechanisms of the Swin Transformer (Shifted Window Transformer), the model achieves 85.4% accuracy in structural component classification and 85.1% accuracy in damage level classification. To enhance model interpretability, visual explanation heatmaps are incorporated, highlighting semantically relevant regions that the model uses for decision-making. These heatmaps closely align with real-world structural and damage features, confirming that STPEIC learns meaningful representations rather than relying on spurious correlations. Additionally, a graphical user interface (GUI) has been developed to streamline image input, classification, and interpretability visualization, improving the practical usability of the system. Overall, STPEIC provides a reliable, interpretable, and user-friendly solution for rapid post-earthquake structural evaluation.展开更多
We present CrazyBeachball,a MATLAB-based graphical user interface(GUI)software package designed for focal mechanism inversion using P-wave first-motion polarity and S/P amplitude ratio data.CrazyBeachball integrates s...We present CrazyBeachball,a MATLAB-based graphical user interface(GUI)software package designed for focal mechanism inversion using P-wave first-motion polarity and S/P amplitude ratio data.CrazyBeachball integrates seismic waveform visualization,first-motion polarity picking,and focal mechanism inversion into a single,interactive platform.Unlike conventional methods that involve separate,independent steps,CrazyBeachball streamlines the process and eliminates the need for external data conversion.Its user-friendly interface allows for efficient focal mechanism determination,while its human-machine interaction facilitates enhanced quality control.We demonstrate its effectiveness by determining focal mechanisms for 21 aftershocks from the 2021 M_(S)6.4 Yangbi earthquake sequence,with results aligning with the regional stress field and fault zone geometry.This open-source software package also allows for user customization,enabling adaptation for specific research needs.展开更多
In this investigation,we meticulously annotated a corpus of 21,174 auroral images captured by the THEMIS All-Sky Imager across diverse temporal instances.These images were categorized using an array of descriptors suc...In this investigation,we meticulously annotated a corpus of 21,174 auroral images captured by the THEMIS All-Sky Imager across diverse temporal instances.These images were categorized using an array of descriptors such as'arc','ab'(aurora but bright),'cloudy','diffuse','discrete',and'clear'.Subsequently,we utilized a state-of-the-art convolutional neural network,ConvNeXt(Convolutional Neural Network Next),deploying deep learning techniques to train the model on a dataset classified into six distinct categories.Remarkably,on the test set our methodology attained an accuracy of 99.4%,a performance metric closely mirroring human visual observation,thereby underscoring the classifier’s competence in paralleling human perceptual accuracy.Building upon this foundation,we embarked on the identification of large-scale auroral optical data,meticulously quantifying the monthly occurrence and Magnetic Local Time(MLT)variations of auroras from stations at different latitudes:RANK(high-latitude),FSMI(mid-latitude),and ATHA(low-latitude),under different solar wind conditions.This study paves the way for future explorations into the temporal variations of auroral phenomena in diverse geomagnetic contexts.展开更多
This paper deals with the study of a water quality forecast model through application of BP neural network technique and GUI (Graphical User Interfaces) function of MATLAB at Yuqiao reservoir in Tianjin. To overcome t...This paper deals with the study of a water quality forecast model through application of BP neural network technique and GUI (Graphical User Interfaces) function of MATLAB at Yuqiao reservoir in Tianjin. To overcome the shortcomings of traditional BP algorithm as being slow to converge and easy to reach extreme minimum value,the model adopts LM (Leven-berg-Marquardt) algorithm to achieve a higher speed and a lower error rate. When factors affecting the study object are identified,the reservoir's 2005 measured values are used as sample data to test the model. The number of neurons and the type of transfer functions in the hidden layer of the neural network are changed from time to time to achieve the best forecast results. Through simulation testing the model shows high efficiency in forecasting the water quality of the reservoir.展开更多
Indoor environmental quality(IEQ)significantly affects human health and wellbeing.Therefore,continuous IEQ monitoring and feedback is of great concern in both the industrial and academic communities.However,most exist...Indoor environmental quality(IEQ)significantly affects human health and wellbeing.Therefore,continuous IEQ monitoring and feedback is of great concern in both the industrial and academic communities.However,most existing studies only focus on developing sensors that cost-effectively promote IEQ measurement while ignoring interactions between the human side and IEQ monitoring.In this study,an intelligent IEQ monitoring and feedback system-the Intelligent Built Enviroment(IBEM)-is developed.Firstly,the IBEM hardware instrument integrates air temperature,relative humidity,CO_(2),particulate matter with an aerodynamic diameter no greater than _(2.5)μm(PM_(2.5)),and illuminance sensors within a small device.The accuracy of this integrated device was tested through a co-location experiment with reference sensors;the device exhibited a strong correlation with the reference sensors,with a slight deviation(R^(2)>0.97 and slopes between 1.01 and 1.05).Secondly,a wireless data transmission module,a cloud storage module,and graphical user interfaces(i.e.,a web platform and mobile interface)were built to establish a pathway for dataflow and interactive feedback with the occupants of the indoor environments.Thus,the IEQ parameters can be continuously monitored with a high spatiotemporal resolution,interactive feedback can be induced,and synchronous data collection on occupant satisfaction and objective environmental parameters can be realized.IBEM has been widely applied in 131 buildings in 18cities/areas in China,with 1188 sample locations.Among these applications,we report on the targeted IEQ diagnoses of two individual buildings and the exploration of relationships between subjective and objective IEQ data in detail here.This work demonstrates the great value of IBEM in both industrial and academic research.展开更多
Machine Learning has evolved with a variety of algorithms to enable state-of-the-art computer vision applications.In particular the need for automating the process of real-time food item identification,there is a huge...Machine Learning has evolved with a variety of algorithms to enable state-of-the-art computer vision applications.In particular the need for automating the process of real-time food item identification,there is a huge surge of research so as to make smarter refrigerators.According to a survey by the Food and Agriculture Organization of the United Nations(FAO),it has been found that 1.3 billion tons of food is wasted by consumers around the world due to either food spoilage or expiry and a large amount of food is wasted from homes and restaurants itself.Smart refrigerators have been very successful in playing a pivotal role in mitigating this problem of food wastage.But a major issue is the high cost of available smart refrigerators and the lack of accurate design algorithms which can help achieve computer vision in any ordinary refrigerator.To address these issues,this work proposes an automated identification algorithm for computer vision in smart refrigerators using InceptionV3 and MobileNet Convolutional Neural Network(CNN)architectures.The designed module and algorithm have been elaborated in detail and are considerably evaluated for its accuracy using test images on standard fruits and vegetable datasets.A total of eight test cases are considered with accuracy and training time as the performance metric.In the end,real-time testing results are also presented which validates the system’s performance.展开更多
This paper describes the replacement of a controller for a programmable universal machine for assembly (PUMA) 512 robot with a newly designed PC based (open architecture) controller employing a real-time direct contro...This paper describes the replacement of a controller for a programmable universal machine for assembly (PUMA) 512 robot with a newly designed PC based (open architecture) controller employing a real-time direct control of six joints. The original structure of the PUMA robot is retained. The hardware of the new controller includes such in-house designed parts as pulse width modulation (PWM) amplifiers, digital and analog controllers, I/O cards, signal conditioner cards, and 16-bit A/D and D/A boards. An Intel Pentium IV industrial computer is used as the central controller. The control software is implemented using VC++ programming language. The trajectory tracking performance of all six joints is tested at varying velocities. Experimental results show that it is feasible to implement the suggested open architecture platform for PUMA 500 series robots through the software routines running on a PC. By assembling controller from off-the-shell hardware and software components, the benefits of reduced and improved robustness have been realized.展开更多
The corrosion rate is a crucial factor that impacts the longevity of materials in different applications.After undergoing friction stir processing(FSP),the refined grain structure leads to a notable decrease in corros...The corrosion rate is a crucial factor that impacts the longevity of materials in different applications.After undergoing friction stir processing(FSP),the refined grain structure leads to a notable decrease in corrosion rate.However,a better understanding of the correlation between the FSP process parameters and the corrosion rate is still lacking.The current study used machine learning to establish the relationship between the corrosion rate and FSP process parameters(rotational speed,traverse speed,and shoulder diameter)for WE43 alloy.The Taguchi L27 design of experiments was used for the experimental analysis.In addition,synthetic data was generated using particle swarm optimization for virtual sample generation(VSG).The application of VSG has led to an increase in the prediction accuracy of machine learning models.A sensitivity analysis was performed using Shapley Additive Explanations to determine the key factors affecting the corrosion rate.The shoulder diameter had a significant impact in comparison to the traverse speed.A graphical user interface(GUI)has been created to predict the corrosion rate using the identified factors.This study focuses on the WE43 alloy,but its findings can also be used to predict the corrosion rate of other magnesium alloys.展开更多
This paper discusses the design concept and method about window based and object oriented Graphic User Interface(GUI),and describes the definition of each class in detail. It is developed with Watcom C ++ in...This paper discusses the design concept and method about window based and object oriented Graphic User Interface(GUI),and describes the definition of each class in detail. It is developed with Watcom C ++ in DOS environment.The GUI can be redeveloped conveniently and effectively by users.It consists of window,popup menu,icon,button and other components.展开更多
Determination of an age in a particular tree species can be considered as a vital factor in forest management.In this research we have introduced a novel scheme to determine the accurate age of the tree species in Sri...Determination of an age in a particular tree species can be considered as a vital factor in forest management.In this research we have introduced a novel scheme to determine the accurate age of the tree species in Sri Lanka.This is initially developed for the tree species called‘Hora’(Dipterocarpus zeylanicus)in wet zone of Sri Lanka.Here the core samples are extracted and further analyzed by means of the different image processing techniques such as Gaussian kernel blurring,use of Sobel filters,double threshold analysis,Hough line tran sformation and etc.The operations such as rescaling,slicing and measuring are also used in line with image processing techniques to achieve the desired results.Ultimately a Graphical user interface(GUI)is developed to cater for the user requirements in a user friendly environment.It has been found that the average growth ring identification accuracy of the proposed system is 93%and the overall average accuracy of detecting the age is 81%.Ultimately the proposed system will provide an insight and contributes to the forestry related activities and researches in Sri Lanka.展开更多
Although ant colony algorithm for the heuristic solution of hard combinational optimization problems enjoy a rapidly growing popularity, but little is known about its convergence properties. Based on the introduction ...Although ant colony algorithm for the heuristic solution of hard combinational optimization problems enjoy a rapidly growing popularity, but little is known about its convergence properties. Based on the introduction of the basic principle and mathematical model, a novel approach to the convergence proof that applies directly to the ant colony algorithm is proposed in this paper. Then, a MATLAB GUI- based ant colony algorithm simulation platform is developed, and the interface of this simulation platform is very friendly, easy to use and to modify.展开更多
Robot technology is a very promising technology for agricultural sector, but the existing industrial robot could not deliver the above-mentioned criteria. Industrial robot mainly uses high voltage electrical power, wh...Robot technology is a very promising technology for agricultural sector, but the existing industrial robot could not deliver the above-mentioned criteria. Industrial robot mainly uses high voltage electrical power, which is not available at field and outdoor operation. The only available and reliable power is a hydraulic from the tractor. The harvester robot consumes the hydraulic power from the tractor and at the same time the tractor can be used as a traveling device for the robot. This paper describes the study on the development of autonomous tractor for the oil palm harvester. The development took considerations on the design of the electro-hydraulic system and the control software for the robot structure to be flexible enough to operate in plantation environment.展开更多
The present paper contributes in studying the phase velocities of P- and S-waves in a half space subjected to a compressive initial stress and gravity field. The density and acceleration due to gravity vary quadratica...The present paper contributes in studying the phase velocities of P- and S-waves in a half space subjected to a compressive initial stress and gravity field. The density and acceleration due to gravity vary quadratically along the depth. The dispersion equation is derived in a closed form. It is shown that the phase velocities depend not only on the initial stress, gravity, and direction of propagation but also on the inhomogeneity parameter associated with the density and acceleration due to gravity. Various particular cases are obtained, and the results match with the classical results. Numerical investigations on the phase velocities of P- and S-waves against the wave number are made for various sets of values of the material parameters, and the results are illustrated graphically. The graphical user interface model is developed to generalize the effect.展开更多
One of the most critical steps in medical health is the proper diagnosis of the disease.Dermatology is one of the most volatile and challenging fields in terms of diagnosis.Dermatologists often require further testing...One of the most critical steps in medical health is the proper diagnosis of the disease.Dermatology is one of the most volatile and challenging fields in terms of diagnosis.Dermatologists often require further testing,review of the patient’s history,and other data to ensure a proper diagnosis.Therefore,finding a method that can guarantee a proper trusted diagnosis quickly is essential.Several approaches have been developed over the years to facilitate the diagnosis based on machine learning.However,the developed systems lack certain properties,such as high accuracy.This study proposes a system developed in MATLAB that can identify skin lesions and classify them as normal or benign.The classification process is effectuated by implementing the K-nearest neighbor(KNN)approach to differentiate between normal skin and malignant skin lesions that imply pathology.KNN is used because it is time efficient and promises highly accurate results.The accuracy of the system reached 98%in classifying skin lesions.展开更多
基金supported by the National Institute of Health (R37CA240806)and American Cancer Society (133697-RSG-19-110-01-CCE)support from UCI Chao Family Comprehensive Cancer Center (P30CA062203).
文摘Radiation-induced acoustic computed tomography(RACT)is an evolving biomedical imaging modality that aims to reconstruct the radiation energy deposition in tissues.Traditional backprojection(BP)reconstructions carry noisy and limited-view artifacts.Model-based algorithms have been demonstrated to overcome the drawbacks of BPs.However,model-based algorithms are relatively more complex to develop and computationally demanding.Furthermore,while a plethora of novel algorithms has been developed over the past decade,most of these algorithms are either not accessible,readily available,or hard to implement for researchers who are not well versed in programming.We developed a user-friendly MATLAB-based graphical user interface(GUI;RACT2D)that facilitates back-projection and model-based image reconstructions for twodimensional RACT problems.We included numerical and experimental X-ray-induced acoustic datasets to demonstrate the capabilities of the GUI.The developed algorithms support parallel computing for evaluating reconstructions using the cores of the computer,thus further accelerating the reconstruction speed.We also share the MATLAB-based codes for evaluating RACT reconstructions,which users with MATLAB programming expertise can further modify to suit their needs.The shared GUI and codes can be of interest to researchers across the globe and assist them in e±cient evaluation of improved RACT reconstructions.
文摘As computer simulation increasingly supports engine er ing design and manufacture, the requirement for a computer software environment providing an integration platform for computational engineering software increas es. A key component of an integrated environment is the use of computational eng ineering to assist and support solutions for complex design. Computer methods fo r structural, flow and thermal analysis are well developed and have been used in design for many years. Many software packages are now available which provi de an advanced capability. However, they are not designed for modelling of powde r forming processes. This paper describes the powder compaction software (PCS_SU T), which is designed for pre- and post-processing for computational simulatio n of the process compaction of powder. In the PCS_SUT software, the adaptive analysis of transient metal powder forming process is simulated by the finite element method based on deformation theories . The error estimates and adaptive remeshing schemes are applied for updated co -ordinate analysis. A generalized Newmark scheme is used for the time domain di scretization and the final nonlinear equations are solved by a Newton-Raphson p rocedure. An incremental elasto-plastic material model is used to simulate the compaction process. To describe the constitutive model of nonlinear behaviour of powder materials, a combination of Mohr-Coulomb and elliptical yield cap model is applied. This model reflects the yielding, frictional and densification char acteristics of powder along with strain and geometrical hardening which occurs d uring the compaction process. A hardening rule is used to define the dependence of the yield surface on the degree of plastic straining. A plasticity theory for friction is employed in the treatment of the powder-tooling interface. The inv olvement of two different materials, which have contact and relative movement in relation to each other, must be considered. A special formulation for friction modelling is coupled with a material formulation. The interface behaviour betwee n the die and the powder is modelled by using an interface element mesh. In the present paper, we have demonstrated pre- and post-processor finite elem ent software, written in Visual Basic, to generate the graphical model and visua lly display the computed results. The software consist of three main part: · Pre-processor: It is used to create the model, generate an app ropriate finite element grid, apply the appropriate boundary conditions, and vie w the total model. The geometric model can be used to associate the mesh with th e physical attributes such as element properties, material properties, or loads and boundary conditions. · Analysis: It can deal with two-dimensional and axi-symmetric applications for linear and non-linear behaviour of material in static and dyna mic analyses. Both triangular and quadrilateral elements are available in the e lement library, including 3-noded, 6-noded and 7-noded (T6B1) triangles and 4 -noded, 8-noded and 9-noded quadrilaterals. The direct implicit algorithm bas ed on the generalized Newmark scheme is used for the time integration and an aut omatic time step control facility is provided. For non-linear iteration, choice s among fully or modified Newton-Raphson method and quasi-Newton method, using the initial stiffness method, Davidon inverse method or BFGS inverse method, ar e possible. · Post-processor: It provides visualization of the computed resu lts, when the finite element model and analysis have been completed. Post-proce ssing is vital to allow the appropriate interpretation of the completed results of the finite element analysis. It provides the visual means to interpret the va st amounts of computed results generated. Finally, the powder behaviour during the compaction of a multi-level component is numerically simulated by the PCS_SUT software, as shown in Fig.1. The predict ive compaction forces at different displacements are computed and compared with the available experimental
文摘In this paper, the design of a Graphical User Interface for CAN data frame monitoring is presented. The GUI has been developed in the Qt Creator IDE. A touch screen for visualization and control is used, which in turn is controlled by a development board with a SoC Cyclone V, through which a Linux operating system is executed.
基金supported by the Leading-Edge Technology Program of Jiangsu Natural Science Foundation of China under Grant No.BK20202001the National Natural Science Foundation of China under Grant No.61932021.
文摘Repackaging brings serious threats to Android ecosystem.Software birthmark techniques are typically applied to detect repackaged apps.Birthmarks based on apps'runtime graphical user interfaces(GUI)are effective,especially for obfuscated or encrypted apps.However,existing studies are time-consuming and not suitable for handling apps in large scale.In this paper,we propose an effective yet efficient dynamic GUI birthmark for Android apps.Briefly,we run an app with automatically generated GUI events and dump its layout after each event.We divide each dumped layout into a grid,count in each grid cell the vertices of boundary rectangles corresponding to widgets within the layout,and generate a feature vector to encode the layout.Similar layouts are merged at runtime,and finally we obtain a graph as the birthmark of the app.Given a pair of apps to be compared,we build a weighted bipartite graph from their birthmarks and apply a modified version of the maximum-weight-bipartite-matching algorithm to determine whether they form a repackaging pair(RP)or not.We implement the proposed technique in a prototype,GridDroid,and apply it to detect RPs in three datasets involving 527 apks.GridDroid reports only six false negatives and seven false positives,and it takes GridDroid merely 20 microseconds on average to compare a pair of birthmarks.
文摘This paper deals with a problem of application generation together with their Graphic User Interface （GUI）. Particularly, the source code generator based on dynamic frames was improved for more effective specification of GUI. It＇s too demanding for the developers to have specification of the application that contain all physical coordinates and other details of buttons and other GUI elements. The developed solution for this problem is based on post-processing of generated source code using iterators for specifying coordinates and other values of graphic elements. The paper includes two examples of generating web applications and their GUI.
基金support from General Project Supported by Natural Science Basic Research Plan in Shaanxi Province of China(2025JC-YBMS-443)Fundamental Research Funds for the Central Universities,CHU(300102213209)+1 种基金Research Funds for the Interdisciplinary Projects,CHU(300104240915)National Natural Science Foundation of China(Grant No.52361135806).
文摘The rapid and accurate assessment of structural damage following an earthquake is crucial for effective emergency response and post-disaster recovery. Traditional manual inspection methods are often slow, labor-intensive, and prone to human error. To address these challenges, this study proposes STPEIC (Swin Transformer-based Framework for Interpretable Post-Earthquake Structural Classification), an automated deep learning framework designed for analyzing post-earthquake images. STPEIC performs two key tasks: structural components classification and damage level classification. By leveraging the hierarchical attention mechanisms of the Swin Transformer (Shifted Window Transformer), the model achieves 85.4% accuracy in structural component classification and 85.1% accuracy in damage level classification. To enhance model interpretability, visual explanation heatmaps are incorporated, highlighting semantically relevant regions that the model uses for decision-making. These heatmaps closely align with real-world structural and damage features, confirming that STPEIC learns meaningful representations rather than relying on spurious correlations. Additionally, a graphical user interface (GUI) has been developed to streamline image input, classification, and interpretability visualization, improving the practical usability of the system. Overall, STPEIC provides a reliable, interpretable, and user-friendly solution for rapid post-earthquake structural evaluation.
基金supported by the National Key Research and Development Program of China(No.2022 YFC3003504)the National Natural Science Foundation of China(No.42174058)the Guangdong Provincial Key Laboratory of Geophysical High-resolution Imaging Technology(No.2022B1212010002).
文摘We present CrazyBeachball,a MATLAB-based graphical user interface(GUI)software package designed for focal mechanism inversion using P-wave first-motion polarity and S/P amplitude ratio data.CrazyBeachball integrates seismic waveform visualization,first-motion polarity picking,and focal mechanism inversion into a single,interactive platform.Unlike conventional methods that involve separate,independent steps,CrazyBeachball streamlines the process and eliminates the need for external data conversion.Its user-friendly interface allows for efficient focal mechanism determination,while its human-machine interaction facilitates enhanced quality control.We demonstrate its effectiveness by determining focal mechanisms for 21 aftershocks from the 2021 M_(S)6.4 Yangbi earthquake sequence,with results aligning with the regional stress field and fault zone geometry.This open-source software package also allows for user customization,enabling adaptation for specific research needs.
基金supported by the General Program of the National Natural Science Foundation of China(Grant No.42374212)the National Magnetic Confinement Fusion Energy Research and Development Program of China(Grant No.2024YFE03020004).
文摘In this investigation,we meticulously annotated a corpus of 21,174 auroral images captured by the THEMIS All-Sky Imager across diverse temporal instances.These images were categorized using an array of descriptors such as'arc','ab'(aurora but bright),'cloudy','diffuse','discrete',and'clear'.Subsequently,we utilized a state-of-the-art convolutional neural network,ConvNeXt(Convolutional Neural Network Next),deploying deep learning techniques to train the model on a dataset classified into six distinct categories.Remarkably,on the test set our methodology attained an accuracy of 99.4%,a performance metric closely mirroring human visual observation,thereby underscoring the classifier’s competence in paralleling human perceptual accuracy.Building upon this foundation,we embarked on the identification of large-scale auroral optical data,meticulously quantifying the monthly occurrence and Magnetic Local Time(MLT)variations of auroras from stations at different latitudes:RANK(high-latitude),FSMI(mid-latitude),and ATHA(low-latitude),under different solar wind conditions.This study paves the way for future explorations into the temporal variations of auroral phenomena in diverse geomagnetic contexts.
基金Project (No.2006AA06Z305) supported by the Hi-Tech Research and Development Program (863) of China
文摘This paper deals with the study of a water quality forecast model through application of BP neural network technique and GUI (Graphical User Interfaces) function of MATLAB at Yuqiao reservoir in Tianjin. To overcome the shortcomings of traditional BP algorithm as being slow to converge and easy to reach extreme minimum value,the model adopts LM (Leven-berg-Marquardt) algorithm to achieve a higher speed and a lower error rate. When factors affecting the study object are identified,the reservoir's 2005 measured values are used as sample data to test the model. The number of neurons and the type of transfer functions in the hidden layer of the neural network are changed from time to time to achieve the best forecast results. Through simulation testing the model shows high efficiency in forecasting the water quality of the reservoir.
基金supported by the China National Key Research and Development(R&D)Program(2018YFE0106100)the National Science Foundation for Distinguished Young Scholars of China(51825802)+3 种基金the Innovative Research Groups of the National Natural Science Foundation of China(51521005)the Strategic Research and Consulting Project of Chinese Academy of Engineering(2021XY-3)the China Postdoctoral Science Foundation(2021M691789)Shuimu Tsinghua Scholar Program(2020SM001)。
文摘Indoor environmental quality(IEQ)significantly affects human health and wellbeing.Therefore,continuous IEQ monitoring and feedback is of great concern in both the industrial and academic communities.However,most existing studies only focus on developing sensors that cost-effectively promote IEQ measurement while ignoring interactions between the human side and IEQ monitoring.In this study,an intelligent IEQ monitoring and feedback system-the Intelligent Built Enviroment(IBEM)-is developed.Firstly,the IBEM hardware instrument integrates air temperature,relative humidity,CO_(2),particulate matter with an aerodynamic diameter no greater than _(2.5)μm(PM_(2.5)),and illuminance sensors within a small device.The accuracy of this integrated device was tested through a co-location experiment with reference sensors;the device exhibited a strong correlation with the reference sensors,with a slight deviation(R^(2)>0.97 and slopes between 1.01 and 1.05).Secondly,a wireless data transmission module,a cloud storage module,and graphical user interfaces(i.e.,a web platform and mobile interface)were built to establish a pathway for dataflow and interactive feedback with the occupants of the indoor environments.Thus,the IEQ parameters can be continuously monitored with a high spatiotemporal resolution,interactive feedback can be induced,and synchronous data collection on occupant satisfaction and objective environmental parameters can be realized.IBEM has been widely applied in 131 buildings in 18cities/areas in China,with 1188 sample locations.Among these applications,we report on the targeted IEQ diagnoses of two individual buildings and the exploration of relationships between subjective and objective IEQ data in detail here.This work demonstrates the great value of IBEM in both industrial and academic research.
基金This work was supported by Taif University Researchers Supporting Project(TURSP)under number(TURSP-2020/10),Taif University,Taif,Saudi Arabia.
文摘Machine Learning has evolved with a variety of algorithms to enable state-of-the-art computer vision applications.In particular the need for automating the process of real-time food item identification,there is a huge surge of research so as to make smarter refrigerators.According to a survey by the Food and Agriculture Organization of the United Nations(FAO),it has been found that 1.3 billion tons of food is wasted by consumers around the world due to either food spoilage or expiry and a large amount of food is wasted from homes and restaurants itself.Smart refrigerators have been very successful in playing a pivotal role in mitigating this problem of food wastage.But a major issue is the high cost of available smart refrigerators and the lack of accurate design algorithms which can help achieve computer vision in any ordinary refrigerator.To address these issues,this work proposes an automated identification algorithm for computer vision in smart refrigerators using InceptionV3 and MobileNet Convolutional Neural Network(CNN)architectures.The designed module and algorithm have been elaborated in detail and are considerably evaluated for its accuracy using test images on standard fruits and vegetable datasets.A total of eight test cases are considered with accuracy and training time as the performance metric.In the end,real-time testing results are also presented which validates the system’s performance.
文摘This paper describes the replacement of a controller for a programmable universal machine for assembly (PUMA) 512 robot with a newly designed PC based (open architecture) controller employing a real-time direct control of six joints. The original structure of the PUMA robot is retained. The hardware of the new controller includes such in-house designed parts as pulse width modulation (PWM) amplifiers, digital and analog controllers, I/O cards, signal conditioner cards, and 16-bit A/D and D/A boards. An Intel Pentium IV industrial computer is used as the central controller. The control software is implemented using VC++ programming language. The trajectory tracking performance of all six joints is tested at varying velocities. Experimental results show that it is feasible to implement the suggested open architecture platform for PUMA 500 series robots through the software routines running on a PC. By assembling controller from off-the-shell hardware and software components, the benefits of reduced and improved robustness have been realized.
文摘The corrosion rate is a crucial factor that impacts the longevity of materials in different applications.After undergoing friction stir processing(FSP),the refined grain structure leads to a notable decrease in corrosion rate.However,a better understanding of the correlation between the FSP process parameters and the corrosion rate is still lacking.The current study used machine learning to establish the relationship between the corrosion rate and FSP process parameters(rotational speed,traverse speed,and shoulder diameter)for WE43 alloy.The Taguchi L27 design of experiments was used for the experimental analysis.In addition,synthetic data was generated using particle swarm optimization for virtual sample generation(VSG).The application of VSG has led to an increase in the prediction accuracy of machine learning models.A sensitivity analysis was performed using Shapley Additive Explanations to determine the key factors affecting the corrosion rate.The shoulder diameter had a significant impact in comparison to the traverse speed.A graphical user interface(GUI)has been created to predict the corrosion rate using the identified factors.This study focuses on the WE43 alloy,but its findings can also be used to predict the corrosion rate of other magnesium alloys.
文摘This paper discusses the design concept and method about window based and object oriented Graphic User Interface(GUI),and describes the definition of each class in detail. It is developed with Watcom C ++ in DOS environment.The GUI can be redeveloped conveniently and effectively by users.It consists of window,popup menu,icon,button and other components.
文摘Determination of an age in a particular tree species can be considered as a vital factor in forest management.In this research we have introduced a novel scheme to determine the accurate age of the tree species in Sri Lanka.This is initially developed for the tree species called‘Hora’(Dipterocarpus zeylanicus)in wet zone of Sri Lanka.Here the core samples are extracted and further analyzed by means of the different image processing techniques such as Gaussian kernel blurring,use of Sobel filters,double threshold analysis,Hough line tran sformation and etc.The operations such as rescaling,slicing and measuring are also used in line with image processing techniques to achieve the desired results.Ultimately a Graphical user interface(GUI)is developed to cater for the user requirements in a user friendly environment.It has been found that the average growth ring identification accuracy of the proposed system is 93%and the overall average accuracy of detecting the age is 81%.Ultimately the proposed system will provide an insight and contributes to the forestry related activities and researches in Sri Lanka.
文摘Although ant colony algorithm for the heuristic solution of hard combinational optimization problems enjoy a rapidly growing popularity, but little is known about its convergence properties. Based on the introduction of the basic principle and mathematical model, a novel approach to the convergence proof that applies directly to the ant colony algorithm is proposed in this paper. Then, a MATLAB GUI- based ant colony algorithm simulation platform is developed, and the interface of this simulation platform is very friendly, easy to use and to modify.
文摘Robot technology is a very promising technology for agricultural sector, but the existing industrial robot could not deliver the above-mentioned criteria. Industrial robot mainly uses high voltage electrical power, which is not available at field and outdoor operation. The only available and reliable power is a hydraulic from the tractor. The harvester robot consumes the hydraulic power from the tractor and at the same time the tractor can be used as a traveling device for the robot. This paper describes the study on the development of autonomous tractor for the oil palm harvester. The development took considerations on the design of the electro-hydraulic system and the control software for the robot structure to be flexible enough to operate in plantation environment.
基金supported by the Research Fellow of Indian School of Mines in Dhanbad (No. 2010DR0016)
文摘The present paper contributes in studying the phase velocities of P- and S-waves in a half space subjected to a compressive initial stress and gravity field. The density and acceleration due to gravity vary quadratically along the depth. The dispersion equation is derived in a closed form. It is shown that the phase velocities depend not only on the initial stress, gravity, and direction of propagation but also on the inhomogeneity parameter associated with the density and acceleration due to gravity. Various particular cases are obtained, and the results match with the classical results. Numerical investigations on the phase velocities of P- and S-waves against the wave number are made for various sets of values of the material parameters, and the results are illustrated graphically. The graphical user interface model is developed to generalize the effect.
文摘One of the most critical steps in medical health is the proper diagnosis of the disease.Dermatology is one of the most volatile and challenging fields in terms of diagnosis.Dermatologists often require further testing,review of the patient’s history,and other data to ensure a proper diagnosis.Therefore,finding a method that can guarantee a proper trusted diagnosis quickly is essential.Several approaches have been developed over the years to facilitate the diagnosis based on machine learning.However,the developed systems lack certain properties,such as high accuracy.This study proposes a system developed in MATLAB that can identify skin lesions and classify them as normal or benign.The classification process is effectuated by implementing the K-nearest neighbor(KNN)approach to differentiate between normal skin and malignant skin lesions that imply pathology.KNN is used because it is time efficient and promises highly accurate results.The accuracy of the system reached 98%in classifying skin lesions.
