A Novel Fusion System Based on Iris and Ear Biometrics for E-exams

With the rapid spread of the coronavirus epidemic all over the world,educational and other institutions are heading towards digitization.In the era of digitization,identifying educational e-platform users using ear and iris based multi-modal biometric systems constitutes an urgent and interesting research topic to pre-serve enterprise security,particularly with wearing a face mask as a precaution against the new coronavirus epidemic.This study proposes a multimodal system based on ear and iris biometrics at the feature fusion level to identify students in electronic examinations(E-exams)during the COVID-19 pandemic.The proposed system comprises four steps.Thefirst step is image preprocessing,which includes enhancing,segmenting,and extracting the regions of interest.The second step is feature extraction,where the Haralick texture and shape methods are used to extract the features of ear images,whereas Tamura texture and color histogram methods are used to extract the features of iris images.The third step is feature fusion,where the extracted features of the ear and iris images are combined into one sequential fused vector.The fourth step is the matching,which is executed using the City Block Dis-tance(CTB)for student identification.Thefindings of the study indicate that the system’s recognition accuracy is 97%,with a 2%False Acceptance Rate(FAR),a 4%False Rejection Rate(FRR),a 94%Correct Recognition Rate(CRR),and a 96%Genuine Acceptance Rate(GAR).In addition,the proposed recognition sys-tem achieved higher accuracy than other related systems.

THE SIMULTANEOUS AND NON-SIMULTANEOUS BLOW-UP CRITERIA FOR A DIFFUSION SYSTEM

This paper investigates the finite time blow-up of nonnegative solutions for a nonlinear diffusion system with a more complicated source term, which is a product of localized source, local source, and weight function, and complemented by homogeneous Dirichlet boundary conditions. The criteria are proposed to identify simultaneous and nonsimultaneous blow-up solutions. Moreover, the related classification for the four parameters in the model is optimal and complete. The results extend those in Zhang and Yang [12].

Tracking method based on separation and combination of the measurements for radar and IR fusion system

A new distributed fusion method of radar/infrared （IR） tracking system based on separation and combination of the measurements is proposed by analyzing the influence of rate measurement. The rate information separated from the radar measurements together with measurements of IR form a pseudo vector of IR, and the corresponding filter is designed. The results indicate that the method not only makes a great improvement to the local tracker＇s performance, but also improves the global tracking precision efficiently.

A Layered Interactive Neural-fuzzy Fusion System and Its Application in Data Processing

A Layered Interactive Neural-fuzzy Fusion System, which is a general fusion model is presented with its structure and algorithm studied systematically. The system, according to the layering technique, is logically composed of a hierarchical set of subsystems. Subsystems with the same rank make up a specific layer. Corresponding fusion techniques are adopted for each layer. Thus a general scheme from the whole to the detail is obtained for the design of tile fusion system. Furthermore, since the element of the bottom layer can be defined by object-oriented analyzing method, the flexibility of the fusion system is consequently improved. A practical neural-fuzzy fusion system is developed for data processing problem and its performance is proved to be better than the old ones.

A Study of Multi-sensor Data Fusion System Based on MAS for Nutrient Solution Measurement

For complementarity and redundancy of multi-sensor data fusion (MSDF) system,it is an effective approach for multiple components measurement.In order to measure nutrient solution on-line,a dynamic and complex system under greenhouse environment,sensors should have intelligent properties including self-calibration and self-compensation. Meanwhile,it is necessary for multiple sensors to cooperate and interact for enhancing reliability of multi-sensor system. Because of the properties of multi-agent system (MAS),it is an appropriate tool to study MSDF system.This paper proposed an architecture of MSDF system based on MAS for the multiple components measurement of nutrient solution.The sensor agent's structure and function modules are analyzed and described in detail,the formal definitions are given,too.The relations of the sensors are modeled to implement reliability diagnosis of the multi-sensor system,so that the reliability of nutrient control system is enhanced.This study offers an effective approach for the study of MSDF.

Clinical Evaluation of TruFUSE^(█) Lumbar Facet Fusion System

Introduction: The TruFUSE lumbar facet fusion system is a unique allograft milled bone dowel used to fuse facet joints. We evaluated subjects undergoing TruFUSE fusion for stable grade I spondylolisthesis and stenosis comparing operative time, length of stay, blood loss and outcome to a similar literature-based cohort of patients undergoing pedicle screw fusion (PSF). Methods: From 2009 to 2011, 41 subjects (17 M,24 F, aver. age 69.5 yr) underwent TruFUSE facet fusion along with transverse process bone fusion and laminectomy. Length of stay, operative time, blood loss and outcomes were compared to eight literature-based cohort that analyzed similar parameters following pedicle screw fusion. Results: The 41 subjects’ mean operative time for laminectomy, transverse process fusion and TruFUSE facet fusion was 106 min, with a mean blood loss of145 cm3, and a mean hospital stay of 1.7 days (77% one day). A follow-up at average six months, 33 (80%) subjects reported subjective outcomes of “excellent” or “somewhat improved”, four (10%) “unchanged” and four (10%) “worse”. Flexion and extension radiographs showed 39 of the 41 patients (95%) had spinal stability at an average six months post-op and all (100%) had signs of early fusion. Discussion: TruFUSE subjects had significantly (p - 19 days range). Mean estimated blood loss (EBL) was significantly lower (p 3 compared to321 cm3 and1082 cm3 range for PSF). Subjective outcome and radiographic stability were comparable between groups. Conclusion: This comparison using the TruFUSE lumbar facet fusion system demonstrates improvements in length of stay, surgical blood loss, and operative time in our selected patient population compared to several published lumbar pedicle screw fusion systems outcomes. There may be potential economic benefits as a result of these improvements.

Induction System for a Fusion Reactor: Quantum Mechanics Chained up

In the quest for a sustainable and abundant energy source, nuclear fusion technology stands as a beacon of hope. This study introduces a groundbreaking quantum mechanically effective induction system designed for magnetic plasma confinement within fusion reactors. The pursuit of clean energy, essential to combat climate change, hinges on the ability to harness nuclear fusion efficiently. Traditional approaches have faced challenges in plasma stability and energy efficiency. The novel induction system presented here not only addresses these issues but also transforms fusion reactors into integrated construction systems. This innovation promises compact fusion reactors, marking a significant step toward a clean and limitless energy future, free from the constraints of traditional power sources. This revolutionary quantum induction system redefines plasma confinement in fusion reactors, unlocking clean, compact, and efficient energy production.

Neutronics analysis of a subcritical blanket system driven by a gas dynamic trap-based fusion neutron source for ^(99)Mo production

Gamma-emitting radionuclide ^(99m)Tc is globally used for the diagnosis of various pathological conditions owing to its ideal single-photon emission computed tomography (SPECT) characteristics.However,the short half-life of ^(99m)Tc (T_(1/2)=6 h)makes it difficult to store or transport.Thus,the production of ^(99m)Tc is tied to its parent radionuclide ^(99)Mo (T_(1/2)=66 h).The major production paths are based on accelerators and research reactors.The reactor process presents the potential for nuclear proliferation owing to its use of highly enriched uranium (HEU).Accelerator-based methods tend to use deuterium–tritium(D–T) neutron sources but are hindered by the high cost of tritium and its challenging operation.In this study,a new ^(99)Mo production design was developed based on a deuterium–deuterium (D–D) gas dynamic trap fusion neutron source (GDT-FNS) and a subcritical blanket system (SBS) assembly with a low-enriched uranium (LEU) solution.GDT-FNS can provide a relatively high-neutron intensity,which is one of the advantages of ^(99)Mo production.We provide a Monte Carlo-based neutronics analysis covering the calculation of the subcritical multiplication factor (k_(s)) of the SBS,optimization design for the reflector,shielding layer,and ^(99)Mo production capacity.Other calculations,including the neutron flux and nuclear heating distributions,are also provided for an overall evaluation of the production system.The results demonstrated that the SBS meets the nuclear critical safety design requirement (k_(s)<0.97) and maintained a high ^(99)Mo production capacity.The proposed system can generate approximately 157 Ci ^(99)Mo for a stable 24 h operation with a neutron intensity of 1×10^(14) n/s,which can meet 50%of China’s demand in 2025.

Influence of layer thickness on formation quality,microstructure,mechanical properties,and corrosion resistance of WE43 magnesium alloy fabricated by laser powder bed fusion

Laser powder bed fusion(L-PBF)of Mg alloys has provided tremendous opportunities for customized production of aeronautical and medical parts.Layer thickness(LT)is of great significance to the L-PBF process but has not been studied for Mg alloys.In this study,WE43 Mg alloy bulk cubes,porous scaffolds,and thin walls with layer thicknesses of 10,20,30,and 40μm were fabricated.The required laser energy input increased with increasing layer thickness and was different for the bulk cubes and porous scaffolds.Porosity tended to occur at the connection joints in porous scaffolds for LT40 and could be eliminated by reducing the laser energy input.For thin wall parts,a large overhang angle or a small wall thickness resulted in porosity when a large layer thicknesses was used,and the porosity disappeared by reducing the layer thickness or laser energy input.A deeper keyhole penetration was found in all occasions with porosity,explaining the influence of layer thickness,geometrical structure,and laser energy input on the porosity.All the samples achieved a high fusion quality with a relative density of over 99.5%using the optimized laser energy input.The increased layer thickness resulted to more precipitation phases,finer grain sizes and decreased grain texture.With the similar high fusion quality,the tensile strength and elongation of bulk samples were significantly improved from 257 MPa and 1.41%with the 10μm layer to 287 MPa and 15.12%with the 40μm layer,in accordance with the microstructural change.The effect of layer thickness on the compressive properties of porous scaffolds was limited.However,the corrosion rate of bulk samples accelerated with increasing the layer thickness,mainly attributed to the increased number of precipitation phases.

Recent research progress in the mechanism and suppression of fusion welding-induced liquation cracking of nickel based superalloys

Nickel-based superalloys are extensively used in the crucial hot-section components of industrial gas turbines,aeronautics,and astronautics because of their excellent mechanical properties and corrosion resistance at high temperatures.Fusion welding serves as an effective means for joining and repairing these alloys;however,fusion welding-induced liquation cracking has been a challenging issue.This paper comprehensively reviewed recent liquation cracking,discussing the formation mechanisms,cracking criteria,and remedies.In recent investigations,regulating material composition,changing the preweld heat treatment of the base metal,optimizing the welding process parameters,and applying auxiliary control methods are effective strategies for mitigating cracks.To promote the application of nickel-based superalloys,further research on the combination impact of multiple elements on cracking prevention and specific quantitative criteria for liquation cracking is necessary.

Microstructure and thermal properties of dissimilar M300–CuCr1Zr alloys by multi-material laser-based powder bed fusion

Multi-material laser-based powder bed fusion (PBF-LB) allows manufacturing of parts with 3-dimensional gradient and additional functionality in a single step. This research focuses on the combination of thermally-conductive CuCr1Zr with hard M300 tool steel.Two interface configurations of M300 on CuCr1Zr and CuCr1Zr on M300 were investigated. Ultra-fine grains form at the interface due to the low mutual solubility of Cu and steel. The material mixing zone size is dependent on the configurations and tunable in the range of0.1–0.3 mm by introducing a separate set of parameters for the interface layers. Microcracks and pores mainly occur in the transition zone.Regardless of these defects, the thermal diffusivity of bimetallic parts with 50vol% of CuCr1Zr significantly increases by 70%–150%compared to pure M300. The thermal diffusivity of CuCr1Zr and the hardness of M300 steel can be enhanced simultaneously by applying the aging heat treatment.

Data and Ensemble Machine Learning Fusion Based Intelligent Software Defect Prediction System

The software engineering field has long focused on creating high-quality software despite limited resources.Detecting defects before the testing stage of software development can enable quality assurance engineers to con-centrate on problematic modules rather than all the modules.This approach can enhance the quality of the final product while lowering development costs.Identifying defective modules early on can allow for early corrections and ensure the timely delivery of a high-quality product that satisfies customers and instills greater confidence in the development team.This process is known as software defect prediction,and it can improve end-product quality while reducing the cost of testing and maintenance.This study proposes a software defect prediction system that utilizes data fusion,feature selection,and ensemble machine learning fusion techniques.A novel filter-based metric selection technique is proposed in the framework to select the optimum features.A three-step nested approach is presented for predicting defective modules to achieve high accuracy.In the first step,three supervised machine learning techniques,including Decision Tree,Support Vector Machines,and Naïve Bayes,are used to detect faulty modules.The second step involves integrating the predictive accuracy of these classification techniques through three ensemble machine-learning methods:Bagging,Voting,and Stacking.Finally,in the third step,a fuzzy logic technique is employed to integrate the predictive accuracy of the ensemble machine learning techniques.The experiments are performed on a fused software defect dataset to ensure that the developed fused ensemble model can perform effectively on diverse datasets.Five NASA datasets are integrated to create the fused dataset:MW1,PC1,PC3,PC4,and CM1.According to the results,the proposed system exhibited superior performance to other advanced techniques for predicting software defects,achieving a remarkable accuracy rate of 92.08%.

Hilbert空间中的fusion-Besselian框架与拟fusion-Riesz基

fusion框架作为Hilbert空间中g-框架的特例,与g-框架有许多类似的性质.该文在已有文献的基础上,借助算子理论知识,举反例说明去掉有限维空间的条件下结论不成立,进一步给出fusion-Besselian框架的算子刻画.结合fusion-Besselian框架的算子刻画和反例1,阐明在探讨该类框架性质时,应关注其适用条件和范围.随后讨论拟fusion-Riesz基与拟Riesz基、fusion-Besselian框架之间的关系.最后讨论fusion-Besselian框架和拟fusion-Riesz基的算子扰动,所得结论补充了算子扰动方面的研究.

Disparity estimation for multi-scale multi-sensor fusion

The perception module of advanced driver assistance systems plays a vital role.Perception schemes often use a single sensor for data processing and environmental perception or adopt the information processing results of various sensors for the fusion of the detection layer.This paper proposes a multi-scale and multi-sensor data fusion strategy in the front end of perception and accomplishes a multi-sensor function disparity map generation scheme.A binocular stereo vision sensor composed of two cameras and a light deterction and ranging(LiDAR)sensor is used to jointly perceive the environment,and a multi-scale fusion scheme is employed to improve the accuracy of the disparity map.This solution not only has the advantages of dense perception of binocular stereo vision sensors but also considers the perception accuracy of LiDAR sensors.Experiments demonstrate that the multi-scale multi-sensor scheme proposed in this paper significantly improves disparity map estimation.

Chinese Clinical Named Entity Recognition Using Multi-Feature Fusion and Multi-Scale Local Context Enhancement

Chinese Clinical Named Entity Recognition(CNER)is a crucial step in extracting medical information and is of great significance in promoting medical informatization.However,CNER poses challenges due to the specificity of clinical terminology,the complexity of Chinese text semantics,and the uncertainty of Chinese entity boundaries.To address these issues,we propose an improved CNER model,which is based on multi-feature fusion and multi-scale local context enhancement.The model simultaneously fuses multi-feature representations of pinyin,radical,Part of Speech(POS),word boundary with BERT deep contextual representations to enhance the semantic representation of text for more effective entity recognition.Furthermore,to address the model’s limitation of focusing just on global features,we incorporate Convolutional Neural Networks(CNNs)with various kernel sizes to capture multi-scale local features of the text and enhance the model’s comprehension of the text.Finally,we integrate the obtained global and local features,and employ multi-head attention mechanism(MHA)extraction to enhance the model’s focus on characters associated with medical entities,hence boosting the model’s performance.We obtained 92.74%,and 87.80%F1 scores on the two CNER benchmark datasets,CCKS2017 and CCKS2019,respectively.The results demonstrate that our model outperforms the latest models in CNER,showcasing its outstanding overall performance.It can be seen that the CNER model proposed in this study has an important application value in constructing clinical medical knowledge graph and intelligent Q&A system.

A Hand Features Based Fusion Recognition Network with Enhancing Multi-Modal Correlation

Fusing hand-based features in multi-modal biometric recognition enhances anti-spoofing capabilities.Additionally,it leverages inter-modal correlation to enhance recognition performance.Concurrently,the robustness and recognition performance of the system can be enhanced through judiciously leveraging the correlation among multimodal features.Nevertheless,two issues persist in multi-modal feature fusion recognition:Firstly,the enhancement of recognition performance in fusion recognition has not comprehensively considered the inter-modality correlations among distinct modalities.Secondly,during modal fusion,improper weight selection diminishes the salience of crucial modal features,thereby diminishing the overall recognition performance.To address these two issues,we introduce an enhanced DenseNet multimodal recognition network founded on feature-level fusion.The information from the three modalities is fused akin to RGB,and the input network augments the correlation between modes through channel correlation.Within the enhanced DenseNet network,the Efficient Channel Attention Network(ECA-Net)dynamically adjusts the weight of each channel to amplify the salience of crucial information in each modal feature.Depthwise separable convolution markedly reduces the training parameters and further enhances the feature correlation.Experimental evaluations were conducted on four multimodal databases,comprising six unimodal databases,including multispectral palmprint and palm vein databases from the Chinese Academy of Sciences.The Equal Error Rates(EER)values were 0.0149%,0.0150%,0.0099%,and 0.0050%,correspondingly.In comparison to other network methods for palmprint,palm vein,and finger vein fusion recognition,this approach substantially enhances recognition performance,rendering it suitable for high-security environments with practical applicability.The experiments in this article utilized amodest sample database comprising 200 individuals.The subsequent phase involves preparing for the extension of the method to larger databases.

Adaptation analysis and fusion correction method of CMIP6 precipitation simulation data on the Qinghai-Tibetan Plateau

In order to obtain more accurate precipitation data and better simulate the precipitation on the Tibetan Plateau,the simulation capability of 14 Coupled Model Intercomparison Project Phase 6(CMIP6)models of historical precipitation(1982-2014)on the Qinghai-Tibetan Plateau was evaluated in this study.Results indicate that all models exhibit an overestimation of precipitation through the analysis of the Taylor index,temporal and spatial statistical parameters.To correct the overestimation,a fusion correction method combining the Backpropagation Neural Network Correction(BP)and Quantum Mapping(QM)correction,named BQ method,was proposed.With this method,the historical precipitation of each model was corrected in space and time,respectively.The correction results were then analyzed in time,space,and analysis of variance(ANOVA)with those corrected by the BP and QM methods,respectively.Finally,the fusion correction method results for each model were compared with the Climatic Research Unit(CRU)data for significance analysis to obtain the trends of precipitation increase and decrease for each model.The results show that the IPSL-CM6A-LR model is relatively good in simulating historical precipitation on the Qinghai-Tibetan Plateau(R=0.7,RSME=0.15)among the uncorrected data.In terms of time,the total precipitation corrected by the fusion method has the same interannual trend and the closest precipitation values to the CRU data;In terms of space,the annual average precipitation corrected by the fusion method has the smallest difference with the CRU data,and the total historical annual average precipitation is not significantly different from the CRU data,which is better than BP and QM.Therefore,the correction effect of the fusion method on the historical precipitation of each model is better than that of the QM and BP methods.The precipitation in the central and northeastern parts of the plateau shows a significant increasing trend.The correlation coefficients between monthly precipitation and site-detected precipitation for all models after BQ correction exceed 0.8.

High-Efficiency Dynamic Scanning Strategy for Powder Bed Fusion by Controlling Temperature Field of the Heat-Affected Zone

Improvement of fabrication efficiency and part performance was the main challenge for the large-scale powder bed fusion(PBF)process.In this study,a dynamic monitoring and feedback system of powder bed temperature field using an infrared thermal imager has been established and integrated into a four-laser PBF equipment with a working area of 2000 mm×2000 mm.The heat-affected zone(HAZ)temperature field has been controlled by adjusting the scanning speed dynamically.Simultaneously,the relationship among spot size,HAZ temperature,and part performance has been established.The fluctuation of the HAZ temperature in four-laser scanning areas was decreased from 30.85℃to 17.41℃.Thus,the consistency of the sintering performance of the produced large component has been improved.Based on the controllable temperature field,a dynamically adjusting strategy for laser spot size was proposed,by which the fabrication efficiency was improved up to 65.38%.The current research results were of great significance to the further industrial applications of large-scale PBF equipment.

Neutron irradiation influence on high-power thyristor device under fusion environment

Because of their economy and applicability,high-power thyristor devices are widely used in the power supply systems for large fusion devices.When high-dose neutrons produced by deuterium–tritium(D–T)fusion reactions are irradiated on a thyristor device for a long time,the electrical characteristics of the device change,which may eventually cause irreversible damage.In this study,with the thyristor switch of the commutation circuit in the quench protection system(QPS)of a fusion device as the study object,the relationship between the internal physical structure and external electrical parameters of the irradiated thyristor is established.Subsequently,a series of targeted thyristor physical simulations and neutron irradiation experiments are conducted to verify the accuracy of the theoretical analysis.In addition,the effect of irradiated thyristor electrical characteristic changes on the entire QPS is studied by accurate simulation,providing valuable guidelines for the maintenance and renovation of the QPS.

Nondestructive and active interrogation system for special nuclear material:proof of principle and initial results

Herein,we employ the threshold energy neutron analysis(TENA)technique to introduce the world's first active interrogation system to detect special nuclear materials(SNMs),including U-235 and Pu-239.The system utilizes a DD neutron generator based on inertial electrostatic confinement(IEC)to interrogate suspicious objects.To detect secondary neutrons produced during fission reactions induced in SNMs,a tensioned metastable fluid detector(TMFD)is employed.The current status of the system's development is reported in this paper,accompanied by the results from experiments conducted to detect 10 g of highly enriched uranium(HEU).Notably,the experimental findings demonstrate a distinct difference in the count rates of measurements with and without HEU.This difference in count rates surpasses two times the standard deviation,indicating a confidence level of more than 96% for identifying the presence of HEU.The paper presents and extensively discusses the proof-of-principle experimental results,along with the system's planned trajectory.