Image super‐resolution via dynamic network

Convolutional neural networks depend on deep network architectures to extract accurate information for image super‐resolution.However,obtained information of these con-volutional neural networks cannot completely express predicted high‐quality images for complex scenes.A dynamic network for image super‐resolution(DSRNet)is presented,which contains a residual enhancement block,wide enhancement block,feature refine-ment block and construction block.The residual enhancement block is composed of a residual enhanced architecture to facilitate hierarchical features for image super‐resolution.To enhance robustness of obtained super‐resolution model for complex scenes,a wide enhancement block achieves a dynamic architecture to learn more robust information to enhance applicability of an obtained super‐resolution model for varying scenes.To prevent interference of components in a wide enhancement block,a refine-ment block utilises a stacked architecture to accurately learn obtained features.Also,a residual learning operation is embedded in the refinement block to prevent long‐term dependency problem.Finally,a construction block is responsible for reconstructing high‐quality images.Designed heterogeneous architecture can not only facilitate richer structural information,but also be lightweight,which is suitable for mobile digital devices.Experimental results show that our method is more competitive in terms of performance,recovering time of image super‐resolution and complexity.The code of DSRNet can be obtained at https://github.com/hellloxiaotian/DSRNet.

Image Hiding with High Robustness Based on Dynamic Region Attention in the Wavelet Domain

Hidden capacity,concealment,security,and robustness are essential indicators of hiding algorithms.Currently,hiding algorithms tend to focus on algorithmic capacity,concealment,and security but often overlook the robustness of the algorithms.In practical applications,the container can suffer from damage caused by noise,cropping,and other attacks during transmission,resulting in challenging or even impossible complete recovery of the secret image.An image hiding algorithm based on dynamic region attention in the multi-scale wavelet domain is proposed to address this issue and enhance the robustness of hiding algorithms.In this proposed algorithm,a secret image of size 256×256 is first decomposed using an eight-level Haar wavelet transform.The wavelet transform generates one coefficient in the approximation component and twenty-four detail bands,which are then embedded into the carrier image via a hiding network.During the recovery process,the container image is divided into four non-overlapping parts,each employed to reconstruct a low-resolution secret image.These lowresolution secret images are combined using densemodules to obtain a high-quality secret image.The experimental results showed that even under destructive attacks on the container image,the proposed algorithm is successful in recovering a high-quality secret image,indicating that the algorithm exhibits a high degree of robustness against various attacks.The proposed algorithm effectively addresses the robustness issue by incorporating both spatial and channel attention mechanisms in the multi-scale wavelet domain,making it suitable for practical applications.In conclusion,the image hiding algorithm introduced in this study offers significant improvements in robustness compared to existing algorithms.Its ability to recover high-quality secret images even in the presence of destructive attacksmakes it an attractive option for various applications.Further research and experimentation can explore the algorithm’s performance under different scenarios and expand its potential applications.

Stability and accuracy of central difference method for real-time dynamic substructure testing considering mass participation coefficient

For real-time dynamic substructure testing(RTDST),the influence of the inertia force of fluid specimens on the stability and accuracy of the integration algorithms has never been investigated.Therefore,this study proposes to investigate the stability and accuracy of the central difference method(CDM)for RTDST considering the specimen mass participation coefficient.First,the theory of the CDM for RTDST is presented.Next,the stability and accuracy of the CDM for RTDST considering the specimen mass participation coefficient are investigated.Finally,numerical simulations and experimental tests are conducted for verifying the effectiveness of the method.The study indicates that the stability of the algorithm is affected by the mass participation coefficient of the specimen,and the stability limit first increases and then decreases as the mass participation coefficient increases.In most cases,the mass participation coefficient will increase the stability limit of the algorithm,but in specific circumstances,the algorithm may lose its stability.The stability and accuracy of the CDM considering the mass participation coefficient are verified by numerical simulations and experimental tests on a three-story frame structure with a tuned liquid damper.

Emotionally Resonant Branding: The Role of AI in Synthesising Dynamic Brand Images for Artists in the Music Industry

Artificial Intelligence (AI) expands its recognition rapidly through the past few years in the context of generating content dynamically, remarkably challenging the human creativity. This study aims to evaluate the efficacy of AI in enhancing personal branding for musicians, particularly in crafting brand images based on emotions received from the artist’s music will improve the audience perceptions regarding the artist’s brand. Study used a quantitative approach for the research, gathering primary data from the survey of 191 people—music lovers, musicians and music producers. The survey focuses on preferences, perceptions, and behaviours related to music consumption and artist branding. The study results demonstrate the awareness and understanding of AI’s role in personal branding within the music industry. Also, results indicate that such an adaptive approach enhances audience perceptions of the artist and strengthens emotional connections. Furthermore, over 50% of the participants indicated a desire to attend live events where an artist’s brand image adapts dynamically to their emotions. The study focuses on novel approaches in personal branding based on the interaction of AI-driven emotional data. In contrast to traditional branding concepts, this study indicates that AI can suggest dynamic and emotionally resonant brand identities for artists. The real time audience response gives proper guidance for the decision-making. This study enriches the knowledge of AI’s applicability to branding processes in the context of the music industry and opens the possibilities for additional advancements in building emotionally appealing brand identities.

Analysis of Imaging Characteristics and Dynamic Changes of 3 Cases of Severe Novel Coronavirus Pneumonia in Qinghai Province

Objective:To analyze the characteristics,dynamic changes,and outcomes of the first imaging manifestations of 3 patients with severe COVID-19 in our hospital.Methods:Computed tomography(CT)findings of 3 patients with severe COVID-19 who tested positive by the nucleic acid test in our hospital were selected,mainly focusing on the morphology,distribution characteristics,and dynamic changes of the first CT findings.Results:3 patients with severe pneumonia were older,with one aged 80.The first chest CT examination for all 3 patients differed.Imaging showed a leafy distribution of consolidation,primarily affecting the lower lobes of both lungs and extending subpleurally.A grid-like pattern was observed,along with changes in the consolidation and air bronchogram.These changes had slower absorption,especially in patients with underlying diseases.Conclusion:CT manifestations of severe COVID-19 have specific characteristics and the analysis of their characteristics and dynamic changes provide valuable insights for clinical treatment.

MOVING OBJECT TRACKING IN DYNAMIC IMAGE SEQUENCE BASED ON ESTIMATION OF MOTION VECTORS OF FEATURE POINTS

An improved estimation of motion vectors of feature points is proposed for tracking moving objects of dynamic image sequence. Feature points are firstly extracted by the improved minimum intensity change （MIC） algorithm. The matching points of these feature points are then determined by adaptive rood pattern searching. Based on the random sample consensus （RANSAC） method, the background motion is finally compensated by the parameters of an affine transform of the background motion. With reasonable morphological filtering, the moving objects are completely extracted from the background, and then tracked accurately. Experimental results show that the improved method is successful on the motion background compensation and offers great promise in tracking moving objects of the dynamic image sequence.

A Practical Study of Intelligent Image-Based Mobile Robot for Tracking Colored Objects

Object tracking is one of the major tasks for mobile robots in many real-world applications.Also,artificial intelligence and automatic control techniques play an important role in enhancing the performance of mobile robot navigation.In contrast to previous simulation studies,this paper presents a new intelligent mobile robot for accomplishing multi-tasks by tracking red-green-blue(RGB)colored objects in a real experimental field.Moreover,a practical smart controller is developed based on adaptive fuzzy logic and custom proportional-integral-derivative(PID)schemes to achieve accurate tracking results,considering robot command delay and tolerance errors.The design of developed controllers implies some motion rules to mimic the knowledge of experienced operators.Twelve scenarios of three colored object combinations have been successfully tested and evaluated by using the developed controlled image-based robot tracker.Classical PID control failed to handle some tracking scenarios in this study.The proposed adaptive fuzzy PID control achieved the best accurate results with the minimum average final error of 13.8 cm to reach the colored targets,while our designed custom PID control is efficient in saving both average time and traveling distance of 6.6 s and 14.3 cm,respectively.These promising results demonstrate the feasibility of applying our developed image-based robotic system in a colored object-tracking environment to reduce human workloads.

Efficient Route Planning for Real-Time Demand-Responsive Transit

Demand Responsive Transit (DRT) responds to the dynamic users’ requests without any fixed routes and timetablesand determines the stop and the start according to the demands. This study explores the optimization of dynamicvehicle scheduling and real-time route planning in urban public transportation systems, with a focus on busservices. It addresses the limitations of current shared mobility routing algorithms, which are primarily designedfor simpler, single origin/destination scenarios, and do not meet the complex demands of bus transit systems. Theresearch introduces an route planning algorithm designed to dynamically accommodate passenger travel needsand enable real-time route modifications. Unlike traditional methods, this algorithm leverages a queue-based,multi-objective heuristic A∗ approach, offering a solution to the inflexibility and limited coverage of suburbanbus routes. Also, this study conducts a comparative analysis of the proposed algorithm with solutions based onGenetic Algorithm (GA) and Ant Colony Optimization Algorithm (ACO), focusing on calculation time, routelength, passenger waiting time, boarding time, and detour rate. The findings demonstrate that the proposedalgorithmsignificantly enhances route planning speed, achieving an 80–100-fold increase in efficiency over existingmodels, thereby supporting the real-time demands of Demand-Responsive Transportation (DRT) systems. Thestudy concludes that this algorithm not only optimizes route planning in bus transit but also presents a scalablesolution for improving urban mobility.

A New CMOS Image Sensor with a High Fill Factor and the Dynamic Digital Double Sampling Technique

A single CMOS image sensor based on a 0.35μm process along with its design and implementation is introduced. The architecture of an active pixel sensor is used in the chip. The fill factor of a pixel cell can reach 43%,higher than the traditional factor of 30%. Moreover, compared with the conventional method whose fixed pattern noise （FPN） is around 0.5%, a dynamic digital double sampling technique is developed, which possesses simpler circuit architecture and a better FPN suppression outcome. The CMOS image sensor chip is implemented in the 0.35μm mixed signal process of a Chartered by MPW. The experimental results show that the chip operates welt,with an FPN of about 0.17%.

Evaluating pediatric ureteropelvic junction obstruction:Dynamic magnetic resonance urography vs renal scintigraphy 99mtechnetium mercaptoacetyltriglycine

BACKGROUND Ureteropelvic junction obstruction(UPJO)is a common congenital urinary tract disorder in children.It can be diagnosed as early as in utero due to the presence of hydronephrosis or later in life due to symptomatic occurrence.AIM To evaluate the discrepancy between dynamic contrast-enhanced magnetic resonance urography(dMRU)and scintigraphy 99m-technetium mercaptoacetyltriglycine(MAG-3)for the functional evaluation of UPJO.METHODS Between 2016 and 2020,126 patients with UPJO underwent surgery at Robert DebréHospital.Of these,83 received a prenatal diagnosis,and 43 were diagnosed during childhood.Four of the 126 patients underwent surgery based on the clinical situation and postnatal ultrasound findings without undergoing functional imaging evaluation.Split renal function was evaluated preoperatively using scintigraphy MAG-3(n=28),dMRU(n=53),or both(n=40).In this study,we included patients who underwent surgery for UPJO and scintigraphy MAG-3+dMRU but excluded those who underwent only scintigraphy MAG-3 or dMRU.The patients were divided into groups A(<10%discrepancy)and B(>10%discrepancy).We examined the discrepancy in split renal function between the two modalities and investigated the possible risk factors.RESULTS The split renal function between the two kidneys was compared in 40 patients(28 boys and 12 girls)using scintigraphy MAG-3 and dMRU.Differential renal function,as determined using both modalities,showed a difference of<10%in 31 children and>10%in 9 children.Calculation of the relative renal function using dMRU revealed an excellent correlation coefficient with renal scintigraphy MAG-3 for both kidneys.CONCLUSION Our findings demonstrated that dMRU is equivalent to scintigraphy MAG-3 for evaluating split renal function in patients with UPJO.

Machine learning algorithm partially reconfigured on FPGA for an image edge detection system

Unmanned aerial vehicles(UAVs)have been widely used in military,medical,wireless communications,aerial surveillance,etc.One key topic involving UAVs is pose estimation in autonomous navigation.A standard procedure for this process is to combine inertial navigation system sensor information with the global navigation satellite system(GNSS)signal.However,some factors can interfere with the GNSS signal,such as ionospheric scintillation,jamming,or spoofing.One alternative method to avoid using the GNSS signal is to apply an image processing approach by matching UAV images with georeferenced images.But a high effort is required for image edge extraction.Here a support vector regression(SVR)model is proposed to reduce this computational load and processing time.The dynamic partial reconfiguration(DPR)of part of the SVR datapath is implemented to accelerate the process,reduce the area,and analyze its granularity by increasing the grain size of the reconfigurable region.Results show that the implementation in hardware is 68 times faster than that in software.This architecture with DPR also facilitates the low power consumption of 4 mW,leading to a reduction of 57%than that without DPR.This is also the lowest power consumption in current machine learning hardware implementations.Besides,the circuitry area is 41 times smaller.SVR with Gaussian kernel shows a success rate of 99.18%and minimum square error of 0.0146 for testing with the planning trajectory.This system is useful for adaptive applications where the user/designer can modify/reconfigure the hardware layout during its application,thus contributing to lower power consumption,smaller hardware area,and shorter execution time.

Real-time and high-transmission middle-infrared optical imaging system based on a pixel-wise metasurface micro-polarization array

Real-time polarization medium-wave infrared(MIR)optical imaging systems enable the acquisition of infrared and polarization information for a target.At present,real-time polarization MIR devices face the following problems:poor real-time performance,low transmission and high requirements for fabrication and integration.Herein,we aim to improve the performance of real-time polarization imaging systems in the MIR waveband and solve the above-mentioned defects.Therefore,we propose a MIR polarization imaging system to achieve real-time polarization-modulated imaging with high transmission as well as improved performance based on a pixel-wise metasurface micro-polarization array(PMMPA).The PMMPA element comprises several linear polarization(LP)filters with different polarization angles.The optimization results demonstrate that the transmittance of the center field of view for the LP filters is up to 77%at a wavelength of4.0μm and an extinction ratio of 88 d B.In addition,a near-diffraction-limited real-time MIR imaging optical system is designed with a field of view of 5°and an F-number of 2.The simulation results show that an MIR polarization imaging system with excellent real-time performance and high transmission is achieved by using the optimized PMMPA element.Therefore,the method is compatible with the available optical system design technologies and provides a way to realize real-time polarization imaging in MIR wavebands.

Real-time image processing and display in object size detection based on VC++

Real-time detection for object size has now become a hot topic in the testing field and image processing is the core algorithm. This paper focuses on the processing and display of the collected dynamic images to achieve a real-time image pro- cessing for the moving objects. Firstly, the median filtering, gain calibration, image segmentation, image binarization, cor- ner detection and edge fitting are employed to process the images of the moving objects to make the image close to the real object. Then, the processed images are simultaneously displayed on a real-time basis to make it easier to analyze, understand and identify them, and thus it reduces the computation complexity. Finally, human-computer interaction （HCI）-friendly in- terface based on VC ＋＋ is designed to accomplish the digital logic transform, image processing and real-time display of the objects. The experiment shows that the proposed algorithm and software design have better real-time performance and accu- racy which can meet the industrial needs.

Delay-dependent stability and added damping of SDOF real-time dynamic hybrid testing

It is well-recognized that a transfer system response delay that reduces the test stability inevitably exists in real-time dynamic hybrid testing （RTDHT）. This paper focuses on the delay-dependent stability and added damping of SDOF systems in RTDHT. The exponential delay term is transferred into a rational fraction by the Pad6 approximation, and the delay-dependent stability conditions and instability mechanism of SDOF RTDHT systems are investigated by the root locus technique. First, the stability conditions are discussed separately for the cases of stiffness, mass, and damping experimental substructure. The use of root locus plots shows that the added damping effect and instability mechanism for mass are different from those for stiffness. For the stiffness experimental substructure case, the instability results from the inherent mode because of an obvious negative damping effect of the delay. For the mass case, the delay introduces an equivalent positive damping into the inherent mode, and instability occurs at an added high frequency mode. Then, the compound stability condition is investigated for a general case and the results show that the mass ratio may have both upper and lower limits to remain stable. Finally, a high-emulational virtual shaking table model is built to validate the stability conclusions.

Monitoring Land Use Dynamics in Chanthaburi Province of Thailand Using Digital Remotely Sensed Images

A comprehensive method of image classification was developed for monitoring land use dynamics in Chanthaburi Province of Tailand. RS (Remote Sensing), GIS (Geographical Information System), GPS (Global Positioning System) and ancillary data were combined by the method which adopts the main idea of classifying images by steps from decision tree method and the hybridized supervised and unsupervised classification. An integration of automatic image interpretation, ancillary materials and expert knowledge was realized. Two subscenes of Landsat 5 Thematic Mapper (TM) images of bands 3, 4 and 5 obtained on December 15, 1992, and January 17, 1999, were used for image processing and spatial data analysis in the study. The overall accuracy of the results of classification reached 90%, which was verified by field check.Results showed that shrimp farm land, urban and traffic land, barren land, bush and agricultural developing area increased in area, mangrove, paddy field, swamp and marsh land, orchard and plantation, and tropical grass land decreased, and the forest land kept almost stable. Ecological analysis on the land use changes showed that more attentions should be paid on the effect of land development on ecological environment in the future land planning and management.

A Flexible DSP-Based Network forReal-Time Image-Processing

This paper proposed a general purpose real-time image processing system based on a flexible DSP-based Network, which is implemented by a high bandwidth communication channel, links. The links is realized using FPGA and provides a bandwidth of 12. 8 Gbit/s. Using the links, The topologic of multi-DSP system can be changed online to meet the variabilities of the parallel algorithm of image processing. The system can be assembled with utmost tens of boards and maintain the high communication speed. Analysis of the system adaptivity to image processing is testified followed by actual results. Key words real-time image processing - multi-DSP - flexible - scalable - FPGA - links CLC number TP 303 Foundation item: Supported by the National Natural Science Foundation of China (60135020)Biography: MAO Hai-cen(1973-), male, Ph.D. candidate, research direction: artificial intelligence, expert system, pattern recognition and image processing

A Real-Time System for Monitoring Distant Dynamic Displacement of Structures

Based on digital image processing technique, a real-time system is developed to monitor and detect the dynamic displacement of engineering structures. By processing pictures with a self-programmed software, the real-time coordinate of an object in a certain coordinate system can be obtained, and further dynamic displacement data and curve of the object can also be achieved. That is, automatic gathering and real-time processing of data can be carried out by this system simultaneously. For this system, first, an untouched monitoring technique is adopted, which can monitor or detect objects several to hundreds of meters apart; second, it has flexible installation condition and good monitoring precision of sub-millimeter degree; third, it is fit for dynamic, quasi-dynamic and static monitoring of large engineering structures. Through several tests and applications in large bridges, good reliability and dominance of the system is proved.

THE HIGH RESOLUTION SEISMIC TOMOGRAPHIC IMAGE IN QINGHAI—TIBET PLATEAU AND ITS DYNAMIC IMPLICATIONS

The Qinghai—Tibet plateau and its surrounding areas including Indian subcontinent, Xinjiang, Mongolia, is a largest lithosphere convergence place in the world, which characterized by continent\|continent collision with a thick crust and lithosphere. The high resolution seismic surface wave tomographic inversion has been conducted for studying the 3D velocity structure of crust and upper mantle in those areas. The seismic surface waveform data are from the archives of the CDSN, GSN and GEOSCOPE. About 2400 long period surface waveform recordings are available for both dispersion and waveform tomographic inversion. The block inversion by grid 1°×1°in Qinghai—Tibet plateau and 2°×2°in the surrounding areas were adapted. The resulting maps show the high resolution 3D shear wave velocity variation from earth’s surface to 400km depth.

New multi-DSP parallel computing architecture for real-time image processing

The flexibility of traditional image processing system is limited because those system are designed for specific applications. In this paper, a new TMS320C64x-based multi-DSP parallel computing architecture is presented. It has many promising characteristics such as powerful computing capability, broad I/O bandwidth, topology flexibility, and expansibility. The parallel system performance is evaluated by practical experiment.

Simulation of large-scale numerical substructure in real-time dynamic hybrid testing

A solution scheme is proposed in this paper for an existing RTDHT system to simulate large-scale finite element （FE） numerical substructures. The analysis of the FE numerical substructure is split into response analysis and signal generation tasks, and executed in two different target computers in real-time. One target computer implements the response analysis task, wherein a large time-step is used to solve the FE substructure, and another target computer implements the signal generation task, wherein an interpolation program is used to generate control signals in a small time-step to meet the input demand of the controller. By using this strategy, the scale of the FE numerical substructure simulation may be increased significantly. The proposed scheme is initially verified by two FE numerical substructure models with 98 and 1240 degrees of freedom （DOFs）. Thereafter, RTDHTs of a single frame-foundation structure are implemented where the foundation, considered as the numerical substructure, is simulated by the FE model with 1240 DOFs. Good agreements between the results of the RTDHT and those from the FE analysis in ABAQUS are obtained.