CMMCAN:Lightweight Feature Extraction and Matching Network for Endoscopic Images Based on Adaptive Attention

In minimally invasive surgery,endoscopes or laparoscopes equipped with miniature cameras and tools are used to enter the human body for therapeutic purposes through small incisions or natural cavities.However,in clinical operating environments,endoscopic images often suffer from challenges such as low texture,uneven illumination,and non-rigid structures,which affect feature observation and extraction.This can severely impact surgical navigation or clinical diagnosis due to missing feature points in endoscopic images,leading to treatment and postoperative recovery issues for patients.To address these challenges,this paper introduces,for the first time,a Cross-Channel Multi-Modal Adaptive Spatial Feature Fusion(ASFF)module based on the lightweight architecture of EfficientViT.Additionally,a novel lightweight feature extraction and matching network based on attention mechanism is proposed.This network dynamically adjusts attention weights for cross-modal information from grayscale images and optical flow images through a dual-branch Siamese network.It extracts static and dynamic information features ranging from low-level to high-level,and from local to global,ensuring robust feature extraction across different widths,noise levels,and blur scenarios.Global and local matching are performed through a multi-level cascaded attention mechanism,with cross-channel attention introduced to simultaneously extract low-level and high-level features.Extensive ablation experiments and comparative studies are conducted on the HyperKvasir,EAD,M2caiSeg,CVC-ClinicDB,and UCL synthetic datasets.Experimental results demonstrate that the proposed network improves upon the baseline EfficientViT-B3 model by 75.4%in accuracy(Acc),while also enhancing runtime performance and storage efficiency.When compared with the complex DenseDescriptor feature extraction network,the difference in Acc is less than 7.22%,and IoU calculation results on specific datasets outperform complex dense models.Furthermore,this method increases the F1 score by 33.2%and accelerates runtime by 70.2%.It is noteworthy that the speed of CMMCAN surpasses that of comparative lightweight models,with feature extraction and matching performance comparable to existing complex models but with faster speed and higher cost-effectiveness.

Feature extraction and learning approaches for cancellable biometrics:A survey

Biometric recognition is a widely used technology for user authentication.In the application of this technology,biometric security and recognition accuracy are two important issues that should be considered.In terms of biometric security,cancellable biometrics is an effective technique for protecting biometric data.Regarding recognition accuracy,feature representation plays a significant role in the performance and reliability of cancellable biometric systems.How to design good feature representations for cancellable biometrics is a challenging topic that has attracted a great deal of attention from the computer vision community,especially from researchers of cancellable biometrics.Feature extraction and learning in cancellable biometrics is to find suitable feature representations with a view to achieving satisfactory recognition performance,while the privacy of biometric data is protected.This survey informs the progress,trend and challenges of feature extraction and learning for cancellable biometrics,thus shedding light on the latest developments and future research of this area.

Development of Extraction and Detection Method for a Chemotherapeutic Drug with Phenytoin in Biological Samples

Dexamethasone is classified as a corticosteroid and is commonly used among cancer patients to decrease the amount of swelling around the tumor. Among patients with cancer, in particular brain tumors, seizures can become a daily routine in their everyday lives. To counteract the seizures, an antiepileptic drug such as phenytoin is administered to act as an anticonvulsant. Phenytoin and dexamethasone are frequently administrated concurrently to brain cancer patients. A previous study has shown that phenytoin serum concentration decreases when administrated concurrently with dexamethasone. Thus, it is important to monitor the concentration of these two drugs in biological samples to ensure that the proper dosages are administrated to the patients. This study aims to develop an effective extraction and detection method for dexamethasone and phenytoin. A reverse-phase high-performance liquid chromatography (HPLC) method with UV/Vis detection has been developed to separate phenytoin and dexamethasone at 219 nm and 241 nm respectively from urine samples. The mobile phase consists of a mixture of 0.01 M KH2PO4, acetonitrile, and methanol adjusted to pH 5.6 (48:32:20) and is pumped at a flow rate of 1.0 mL/min. Calibration curves were prepared for phenytoin and dexamethasone (r2 > 0.99). An efficient solid-phase extraction (SPE) method for the extraction of dexamethasone and phenytoin from urine samples was developed with the use of C-18 cartridges. The percent recovery for phenytoin and dexamethasone is 95.4% (RSD = 1.15%) and 81.1% (RSD = 3.56%) respectively.

Progress in the extraction and application of collagen peptides

Collagen peptide is the product of complete hydrolysis of collagen,which has a relatively small molecular weight and is more easily absorbed than proteins and amino acids.Collagen peptide not only has unique nutritional value,but also has certain physiological functions,which makes it has great potential value in various fields,so it has set off a wave of research on collagen peptide in the biological world.This paper describes the sources and extraction methods of collagen peptides,and describes the research progress and application of collagen peptides in the medical,food,material and skin care industries according to their physiological functions,which will provide new ideas for the future research of collagen peptides.

Image Feature Extraction and Matching of Augmented Solar Images in Space Weather

Augmented solar images were used to research the adaptability of four representative image extraction and matching algorithms in space weather domain.These include the scale-invariant feature transform algorithm,speeded-up robust features algorithm,binary robust invariant scalable keypoints algorithm,and oriented fast and rotated brief algorithm.The performance of these algorithms was estimated in terms of matching accuracy,feature point richness,and running time.The experiment result showed that no algorithm achieved high accuracy while keeping low running time,and all algorithms are not suitable for image feature extraction and matching of augmented solar images.To solve this problem,an improved method was proposed by using two-frame matching to utilize the accuracy advantage of the scale-invariant feature transform algorithm and the speed advantage of the oriented fast and rotated brief algorithm.Furthermore,our method and the four representative algorithms were applied to augmented solar images.Our application experiments proved that our method achieved a similar high recognition rate to the scale-invariant feature transform algorithm which is significantly higher than other algorithms.Our method also obtained a similar low running time to the oriented fast and rotated brief algorithm,which is significantly lower than other algorithms.

Solvent extraction and separation of cobalt from leachate of spent lithium-ion battery cathodes with N263 in nitrite media

To effectively separate and recover Co(Ⅱ) from the leachate of spent lithium-ion battery cathodes,we investigated solvent extraction with quaternary ammonium salt N263 in the sodium nitrite system.NO_(2)^(-)combines with Co(Ⅱ) to form an anion [Co(NO_(2))_(3)]^(-),and it is then extracted by N263.The extraction of Co(Ⅱ) is related to the concentration of NO_(2)^(-).The extraction efficiency of Co(Ⅱ) reaches the maximum of99.16%,while the extraction efficiencies of Ni(Ⅱ),Mn(Ⅱ),and Li(Ⅰ) are 9.27%-9.80% under the following conditions:30vol% of N263 and15vol% of iso-propyl alcohol in sulfonated kerosene,the volume ratio of the aqueous-to-organic phase is 2:1,the extraction time is 30 min,and1 M sodium nitrite in 0.1 MHNO_(3).The theoretical stages require for the Co(Ⅱ) extraction are performed in the McCabe–Thiele diagram,and the extraction efficiency of Co(Ⅱ) reaches more than 99.00% after three-stage counter-current extraction with Co(Ⅱ) concentration of 2544mg/L.When the HCl concentration is 1.5 M,the volume ratio of the aqueous-to-organic phase is 1:1,the back-extraction efficiency of Co(Ⅱ)achieves 91.41%.After five extraction and back-extraction cycles,the Co(Ⅱ) extraction efficiency can still reach 93.89%.The Co(Ⅱ) extraction efficiency in the actual leaching solution reaches 100%.

Small incision lenticule extraction and femtosecond-assisted laser in situ keratomileusis in patients with deep corneal opacity:case series

AIM:To report the safety,efficacy,and accuracy of small-incision lenticule extraction(SMILE)or femtosecondassisted laser in situ keratomileusis(FS-LASIK)for the correction of myopia or myopic astigmatism in patients with deep corneal opacity denoted by anterior segment optical coherence tomography(AS-OCT).METHODS:Four patients with monocular corneal opacity(3 due to mechanical injury,1 due to a firecracker wound)were recruited and treated with refractive surgery(3 for SMILE,1 for FS-LASIK combined with limbal relaxing incision(LRI).Preoperative ocular manifestations,surgical details,postoperative visual outcomes,corneal opacity parameters,and corneal topography were analyzed.RESULTS:Preoperatively,spherical diopter ranged from-3.0 D to-4.75 D with cylinder ranging from-0.75 to-5.0 D,and corrected distance visual acuity(CDVA)ranging from 20/25 to 20/20.One eye’s corneal opacity was located in the central zone and three were in the mid-peripheral optical zone.Three patients underwent uneventful SMILE in both eyes,whilst one patient underwent FS-LASIK for high astigmatism in both eyes and LRI in the right eye.CDVA of the eye with corneal opacity ranged from 20/22to 20/20 one to six weeks postoperatively.Two patients achieved better CDVA and no patients lost Snellen lines.The postoperative diopter was within±0.75 D for all eyes.Significant edema existed above the corneal opacity in one eye and dissipated soon.No eccentric corneal topography or morphological anomaly of the corneal cap or flap was observed.CONCLUSION:The cases demonstrate that SMILE or FS-LASIK is safe and effective to treat myopic astigmatism combined with deep corneal opacity lesions after comprehensive preoperative evaluation and appropriate candidate selection.FS-LASIK combined with LRI is also sufficient for correcting high astigmatism due to corneal scarring.

Melt extraction and mineralization: A case study from the Shuangjianzishan supergiant Ag-Pb-Zn deposit(208 Mt), Inner Mongolia, NE China

The supergiant Shuangjianzishan(SJZ) Ag-Pb-Zn deposit is in the southern segment of the Great Hinggan Range(SGHR), northeast China. Previous studies suggest the ore-forming material and fluid originated from the magmatic system, and the mineralization age was consistent with the diagenetic age. However,the relationship between granitic magmatism and mineralization is still unclear in the SJZ. In this study, CH-O-He-Ar and in-situ S-Pb isotope analyses were conducted to determine the sources of ore-forming fluids and metals, which were combined with geochemistry data of SJZ granitoids from previous studies to constrain the relationship between the magmatism and the mineralization. The C-H-O-He-Ar-S-Pb isotopic compositions suggested the SJZ ore-forming material and fluids were derived from a magmatic source, which has mixed a small amount of mantle-derived materials. In addition, the disseminated sulfide from the syenogranite has comparable S-Pb isotopic composition with the sulfide minerals from ore veins,suggesting that the generation of the SJZ ore-forming fluids has a close relationship with the syenogranite magmatism. Combining with the geochemical characters of the syenogranite, the authors proposed that the mantle-derived fingerprint of the SJZ ore-forming fluid might be caused by the parent magma of the syenogranite, which was derived from partial melting of the juvenile lower crust, and underwent the residual melts segregated from a crystal mush in the shallow magma reservoir. The extraction of the syenogranite parent magma further concentrated the fertilized fluids, which was crucial to mineralization of the SJZ Ag-Pb-Zn deposit.

A 3-month comparison study of subjective and objective visual quality of small incision lenticule extraction and transepithelial photorefractive keratectomy in patients with low and moderate myopia

AIM:To compare the subjective and objective visual quality between small incision lenticule extraction(SMILE)and transepithelial photorefractive keratectomy(t PRK)in patients with low and moderate myopia.METHODS:Patients undertaking SMILE or t PRK for the correction of low and moderate myopia were consecutively recruited in this prospective cohort study with a 3-month follow-up period.Objective evaluation[visual acuity test,manifest refraction,wavefront aberrations,the total cut-off value of the total modulation transfer function(MTFcut-off),and Strehl ratio(SR)]and subjective evaluation of visual quality(quality-of-life questionnaire)were conducted before surgery and at days 1,7,30,and 90 after surgery.RESULTS:A total of 47 patients(94 eyes)with SMILE and 22 patients(22 eyes)with t PRK were enrolled.The uncorrected visual acuity(UCVA)was better in SMILE patients on day 7 after surgery(1.13±0.13 vs 0.99±0.17,t=4.85,P<0.001)but was comparable at days 30 and 90.At day 90,the SMILE group had a lower spherical equivalent(SE)than the t PRK group(0.04±0.31 vs 0.19±0.43,t=2.08,P=0.042).Total higher order aberrations(HOAs)were induced in both surgical types,which were more evident in the t PRK group with 3-mm pupil diameter(0.16±0.07 vs0.11±0.05,t=4.27,P<0.001)and 5-mm pupil diameter(0.39±0.17 vs 0.36±0.11,t=2.33,P=0.022).The MTFcut-offand SR showed a trend of improvement in both SMILE and t PRK patients but were statistically better in the SMILE group with both pupil diameters.There was a significant improvement of contrast sensitivity(CS)over baseline levels at the spatial frequency of 18 cycles/degree(c/d)in the SMILE group(F=2.72,P=0.033)and at 3 c/d(F=3.03,P=0.031),12 c/d(F=3.72,P=0.013),and 18 c/d(F=4.62,P=0.004)in the t PRK group.The subjective quality of life questionnaire showed a steady improvement in the SMILE group(F=8.31,P<0.001)but not the t PRK group.CONCLUSION:SMILE and t PRK are both safe and effective ways to correct low and moderate myopia.A generally better and quicker recovery of visual quality favors the application of SMILE in qualified patients.

Robust Radiometric Normalization of the near Equatorial Satellite Images Using Feature Extraction and Remote Sensing Analysis

Relative radiometric normalization (RRN) minimizes radiometric differences among images caused by inconsistencies of acquisition conditions rather than changes in surface. Scale invariant feature transform (SIFT) has the ability to automatically extract control points (CPs) and is commonly used for remote sensing images. However, its results are mostly inaccurate and sometimes contain incorrect matching caused by generating a small number of false CP pairs. These CP pairs have high false alarm matching. This paper presents a modified method to improve the performance of SIFT CPs matching by applying sum of absolute difference (SAD) in a different manner for the new optical satellite generation called near-equatorial orbit satellite and multi-sensor images. The proposed method, which has a significantly high rate of correct matches, improves CP matching. The data in this study were obtained from the RazakSAT satellite a new near equatorial satellite system. The proposed method involves six steps: 1) data reduction, 2) applying the SIFT to automatically extract CPs, 3) refining CPs matching by using SAD algorithm with empirical threshold, and 4) calculation of true CPs intensity values over all image’ bands, 5) preforming a linear regression model between the intensity values of CPs locate in reverence and sensed image’ bands, 6) Relative radiometric normalization conducting using regression transformation functions. Different thresholds have experimentally tested and used in conducting this study (50 and 70), by followed the proposed method, and it removed the false extracted SIFT CPs to be from 775, 1125, 883, 804, 883 and 681 false pairs to 342, 424, 547, 706, 547, and 469 corrected and matched pairs, respectively.

Fusion of Region Extraction and Cross-Entropy SVM Models for Wheat Rust Diseases Classification

Wheat rust diseases are one of the major types of fungal diseases that cause substantial yield quality losses of 15%–20%every year.The wheat rust diseases are identified either through experienced evaluators or computerassisted techniques.The experienced evaluators take time to identify the disease which is highly laborious and too costly.If wheat rust diseases are predicted at the development stages,then fungicides are sprayed earlier which helps to increase wheat yield quality.To solve the experienced evaluator issues,a combined region extraction and cross-entropy support vector machine(CE-SVM)model is proposed for wheat rust disease identification.In the proposed system,a total of 2300 secondary source images were augmented through flipping,cropping,and rotation techniques.The augmented images are preprocessed by histogram equalization.As a result,preprocessed images have been applied to region extraction convolutional neural networks(RCNN);Fast-RCNN,Faster-RCNN,and Mask-RCNN models for wheat plant patch extraction.Different layers of region extraction models construct a feature vector that is later passed to the CE-SVM model.As a result,the Gaussian kernel function in CE-SVM achieves high F1-score(88.43%)and accuracy(93.60%)for wheat stripe rust disease classification.

Peak extraction and classification from digital elevation models based on the relationship between morphological characteristics and spatial position

A peak is an important topographic feature crucial in quantitative geomorphic feature analysis,digital geomorphological mapping,and other fields.Most peak extraction methods are based on the maximum elevation in a local area but ignore the morphological characteristics of the peak area.This paper proposes three indices based on the morphological characteristics of peaks and their spatial relationship with ridge lines:convexity mean index(CM-index),convexity standard deviation(CSD-index),and convexity imbalance index(CIBindex).We develop computation methods to extract peaks from digital elevation model(DEM).Subsequently,the initial peaks extracted by neighborhood statistics are classified using the proposed indices.The method is evaluated in the Qinghai Tibet Plateau and the Loess Plateau in China.An ASTER Global DEM(ASTGTM2 DEM)with a grid size of 30 m is chosen to assess the suitability of the proposed mountain peak extraction and classification method in different geomorphic regions.DEM data with grid sizes of 30 m and 5 m are used for the Loess Plateau.The mountain peak extraction and classification results obtained from the different resolution DEM are compared.The experimental results show that:(1)The CM-index and the CSDindex accurately reflect the concave or convex morphology of the surface and can be used as supplements to existing surface morphological indices.(2)The three indices can identify pseudo mountain peaks and classify the remaining peaks into single ridge peak(SR-Peak)and multiple ridge intersection peak(MRI-Peak).The visual inspection results show that the classification accuracy in the different study areas exceeds 75%.(3)The number of peaks is significantly higher for the 5 m DEM than for the 30 m DEM because more peaks can be detected at a finer resolution.

Feature Extraction and Classification of Photovoltaic Panels Based on Convolutional Neural Network

Photovoltaic(PV)boards are a perfect way to create eco-friendly power from daylight.The defects in the PV panels are caused by various conditions;such defective PV panels need continuous monitoring.The recent development of PV panel monitoring systems provides a modest and viable approach to monitoring and managing the condition of the PV plants.In general,conventional procedures are used to identify the faulty modules earlier and to avoid declines in power generation.The existing deep learning architectures provide the required output to predict the faulty PV panels with less accuracy and a more time-consuming process.To increase the accuracy and to reduce the processing time,a new Convolutional Neural Network(CNN)architecture is required.Hence,in the present work,a new Real-time Multi Variant Deep learning Model(RMVDM)architecture is proposed,and it extracts the image features and classifies the defects in PV panels quickly with high accuracy.The defects that arise in the PV panels are identified by the CNN based RMVDM using RGB images.The biggest difference between CNN and its predecessors is that CNN automatically extracts the image features without any help from a person.The technique is quantitatively assessed and compared with existing faulty PV board identification approaches on the large real-time dataset.The results show that 98%of the accuracy and recall values in the fault detection and classification process.

A review on the extraction and separation of andrographolide from Andrographis paniculata:extraction selectivity,current challenges and strategies

Andrographolide is the main active ingredient of Andrographis paniculata(Burm.f.)Nees,known as“natural antibiotic”.Here,for the purpose of discovering a more efficient,low-cost extraction and separation method,the research status of andrographolide was reviewed.At present,researches only take extraction rate as the only index to optimize extraction parameters,but ignores the importance of extraction selectivity.It is usually meaningless to blindly pursue the extraction rate without considering the difficulty and cost of subsequent separation.So,factors affecting extraction selectivity such as solvent choice,temperature and physicochemical effects caused by extraction technique itself,are first discussed.Different extraction techniques for andrographolide were discussed by comparing the selectivity,efficiency and cost of extraction.The separation procedures of andrographolide such as decolorization,impurity removal,crystallization,membrane separation,solid-phase extraction and partition chromatography and their challenges and possible strategies are also discussed.It is hoped that this review can provide guidance for researchers who are committed to advancing the field of andrographolide extraction and purification.

Extraction and Refining Process of Polysaccharide from Tricholoma matsutake and Verification of Its Whitening Effect

[Objectives]The paper was to determine the extraction and refining process of polysaccharide from Tricholoma matsutake,and to verify its whitening effect.[Methods]With T.matsutake as the research object,the effects of eluent concentration,loading amount and diameter-to-height ratio on the refining process of T.matsutake polysaccharide were explored by orthogonal test,to optimize the dynamic elution conditions of T.matsutake polysaccharide.The survival rate of mouse melanoma cells(B16),inhibition of melanin synthesis and inhibition of tyrosinase activity of crude extract A1 and refined extracts A2-A4 were tested to verify the whitening effect of T.matsutake.[Results]The best extraction and refining process for T.matsutake polysaccharide was:eluent 40%ethanol(volume fraction),loading amount 30 mg/g(polysaccharide-resin),diameter-to-height ratio 1∶8.Under this condition,the extraction rate of T.matsutake can reach up to 33%(A3).The whitening efficacy test showed that crude extract A1 and refined extracts A2-A4 had good whitening effects,and the whitening effects were A3≥A4>A1>A2.[Conclusions]The study provides a reference for the application of T.matsutake polysaccharide in cosmetics.

Effects of Ethanol Condensation Reflux Extraction and Ultrasound-assisted Extraction on the Content of Total Flavonoids of Pueraria edulis

With Pueraria edulis from different habitats in Yunnan Province,Guangdong Province and Guangxi Zhuang autonomous region as materials,the medicinal materials of P.edulis were extracted by ethanol condensation reflux extraction and ultrasound-assisted extraction,and the effects of different extraction methods the contents of total flavonoids in P.edulis from different areas were compared.The results showed that the best extraction time for P.edulis in Yunnan Province was 20 min,and that for Guangdong and Guangxi Zhuang Autonomous Region was 30 min.The yield of total flavonoids from P.edulis extracted by the condensation reflux extraction method was relatively better.The content of total flavonoids in P.edulis in Yunnan was the highest with an average content of 0.2557%,while the average content of total flavonoids in P.edulis in Guangdong was the lowest with an average content of 0.2108%.

Studies on Extraction and Activity of Peptides from Haemadipsa hainana

[Objectives]Peptides was extracted from Haemadipsa hainana and its activity was studied.[Methods]Electric stimulation,water extraction and ultrasonic extraction were used to extract the peptides from H.hainana.Then the protein content and molecular weight distribution of H.hainana peptides were detected by the BCA method and SDS-PAGE method,respectively.The antithrombin activity and analgesic activity of the three peptide extracts of H.hainana were detected by Markwardt thrombin titration method and mouse hot plate experiment,respectively.[Results]There extraction methods of electric stimulation,water extraction and ultrasonic extraction were used to extract the peptide extract of H.hainana,and the yields were as follows:water extraction>electrical stimulation>ultrasonic extraction.The three peptide extracts from H.hainana had antithrombin activity,and the antithrombin activity was as follows:water extraction>ultrasonic extraction>electrical stimulation.Through the hot plate experiment in mice,it was verified that the three peptide extracts of H.hainana had analgesic activity,and the analgesic activity was water extraction>electric stimulation>ultrasonic extraction.The analgesic activity of high-dose(100 mg/kg)group of H.hainana obtained by water extraction was slightly weaker than that of tramadol.[Conclusions]This study confirmed that the peptide extract of H.hainana had certain antithrombin and analgesic activity,laying a foundation for the subsequent development and application of H.hainana.

Research Progress in the Extraction and Application of Flavonoids from Ginkgo biloba Leaves

Ginkgo biloba resources in China are enormous. With the demand of the market, the preparation and application of flavonoids have become a current research hotspot. The main active substances in G. biloba leaves, flavonoids, have various functional activities and are widely used in fields such as food, medicine, cosmetics, feed, etc. In this paper, the introduction, functional activity, extraction methods, and application research of flavonoids from G. biloba leaves are reviewed, and the development prospects of flavonoids from G. biloba leaves are expected.

Extraction and Content Determination of Shikimic Acid in Pinus elliottii Engelm

[Objective] The aim was to provide scientific basis for development and utilization of Pinus elliottii Engelm resources.[Method] The extraction process of shikimic acid in Pinus elliottii Engelm was studied,and the content of shikimic acid was determined by HPLC.The HPLC conditions were as follows;Alltima NH2 （5 μm,4.6 mm × 150 mm） column separation;the mobile phase was acetonitrile-2%H3PO4 （90：10）;the flowing velocity was 1 ml/min;test wavelength was 213 nm,the width of belt was 16 nm;reference wavelength was 300 nm,the width of belt was 80 nm.[Result] By the single factor and orthogonal tests,the optimum conditions were found as follows：ethanol concentration 60%,extraction temperature 75 ℃,solid-liquid ratio 1：25,extraction time 2.5 h.The extraction rate of shikimic acid was 1.49%.[Conclusion] Shikimic acid in Pinus elliottii Engelm could be used as a new resource to develop and utilize.

Feature extraction and damage alarming using time series analysis

Aiming at the problem of on-line damage diagnosis in structural health monitoring （SHM）, an algorithm of feature extraction and damage alarming based on auto-regressive moving-average （ARMA） time series analysis is presented. The monitoring data were first modeled as ARMA models, while a principalcomponent matrix derived from the AR coefficients of these models was utilized to establish the Mahalanobisdistance criterion functions. Then, a new damage-sensitive feature index DDSF is proposed. A hypothesis test involving the t-test method is further applied to obtain a decision of damage alarming as the mean value of DDSF had significantly changed after damage. The numerical results of a three-span-girder model shows that the defined index is sensitive to subtle structural damage, and the proposed algorithm can be applied to the on-line damage alarming in SHM.