Joint inversion of gravity and vertical gradient data based on modified structural similarity index for the structural and petrophysical consistency constraint

Joint inversion is one of the most effective methods for reducing non-uniqueness for geophysical inversion.The current joint inversion methods can be divided into the structural consistency constraint and petrophysical consistency constraint methods,which are mutually independent.Currently,there is a need for joint inversion methods that can comprehensively consider the structural consistency constraints and petrophysical consistency constraints.This paper develops the structural similarity index(SSIM)as a new structural and petrophysical consistency constraint for the joint inversion of gravity and vertical gradient data.The SSIM constraint is in the form of a fraction,which may have analytical singularities.Therefore,converting the fractional form to the subtractive form can solve the problem of analytic singularity and finally form a modified structural consistency index of the joint inversion,which enhances the stability of the SSIM constraint applied to the joint inversion.Compared to the reconstructed results from the cross-gradient inversion,the proposed method presents good performance and stability.The SSIM algorithm is a new joint inversion method for petrophysical and structural constraints.It can promote the consistency of the recovered models from the distribution and the structure of the physical property values.Then,applications to synthetic data illustrate that the algorithm proposed in this paper can well process the synthetic data and acquire good reconstructed results.

Incremental User Identification Across Social Networks Based on User-Guider Similarity Index

Identifying accounts across different online social networks that belong to the same user has attracted extensive attentions.However,existing techniques rely on given user seeds and ignore the dynamic changes of online social networks,which fails to generate high quality identification results.In order to solve this problem,we propose an incremental user identification method based on user-guider similarity index(called CURIOUS),which efficiently identifies users and well captures the changes of user features over time.Specifically,we first construct a novel user-guider similarity index(called USI)to speed up the matching between users.Second we propose a two-phase user identification strategy consisting of USI-based bidirectional user matching and seed-based user matching,which is effective even for incomplete networks.Finally,we propose incremental maintenance for both USI and the identification results,which dynamically captures the instant states of social networks.We conduct experimental studies based on three real-world social networks.The experiments demonstrate the effectiveness and the efficiency of our proposed method in comparison with traditional methods.Compared with the traditional methods,our method improves precision,recall and rank score by an average of 0.19,0.16 and 0.09 respectively,and reduces the time cost by an average of 81%.

Development of endemicity and conservation importance indices for tropical forests and the floral diversity assessment of Mt.Natoo in Benguet,Philippines

The scientific community faces the challenge of measuring progress toward biodiversity targets and indices have been traditionally used.However,recent inventories in secondary tropical mountain forests using traditional biodiversity indices have yielded results that are indistinct with primary ones.This shows the need to develop complementary indices that goes beyond species count but integrates the distribution and conservation status of the species.This study developed endemicity and conservation importance index for tropical forest that incorporated the distribution and conservation status of the species.These indices were applied to Mt.Natoo,a remnant primary mossy forest in Buguias,Benguet,Philippines,that resulted to endemicity index of 81.07 and conservation importance index of 42.90.Comparing these with secondary forest sites with comparable Shannon-Wiener,Simpson,Evenness and Margalef’s indices,our endemicity and conservation indices clearly differentiates primary forest(our study site)with higher values from secondary forests with much lower values.Thus,we are proposing these indices for a direct but scientifically-informed identification of specific sites for conservation and protection in tropical forests.Additionally,our study documented a total of 168 vascular plant species(79 endemic and 12 locally threatened species)in Mt.Nato-o.Majority are of tropical elements for both generic and species levels with some temperate elements that could be attributed to the site's high elevation and semi-temperate climate.These are important baseline information for conservation plans and monitoring of tropical mossy forests.

Employing Diversity and Similarity Indices to Evaluate Geopedological Soil Mapping in Miyaneh, East Azerbaijan Province, Iran

The geopedological viewpoint attempts to distinguish and introduce the smallest map unit that has the highest levels of homogeneity and uniformity with respect to landform, lithology, and soil, especially if the relationship between geomorphology and soils in the region is well defined. This research intended to investigate the degree of validity generalization of results obtained in the geopedology approach for similar landforms in the Miayneh region of East Azerbaijan Province, Iran. For this purpose, soil diversity study was conducted through measuring it in a hierarchical sequence in categories of USDA soil taxonomy and by comparing similar units in the geopedological method through employing pedodiversity and similarity indices. After preparing the initial interpretative map (based on aerial photographs) at a scale of 1:20,000, the HPu211 unit that covered the greatest delineation of study area was selected and 28 soil profiles, about 90 meters apart, were excavated, described, and sampled in this unit. The degree of validity generalization of geopedological results for the mentioned unit was determined by digging 14 other soil profiles in a similar unit, called the validation area, which was located outside of the sample area. Results indicated that the value of Shannon’s diversity index increased from the level of soil order to soil family in both the sample and the generalization areas;however, only at the soil family level were there significant differences between soil diversity in the two areas at the confidence level of 95%. As well as classification of the profiles dug in the generalization area was different from that of the profiles dug in the sample area at the category of soil family. Therefore, it is possible that management generalizability in this method, even at the detailed scale, can satisfy the related needs. Consequently, interpretative or managerial purity of geopedological units must be considered in future research.

Text duplication of papers in four medical related fields

Purpose:To reveal the typical features of text duplication in papers from four medical fields:basic medicine,health management,pharmacology and pharmacy,and public health and preventive medicine.To analyze the reasons for duplication and provide suggestions for the management of medical academic misconduct.Design/methodology/approach:In total,2,469 representative Chinese journal papers were included in our research,which were submitted by researchers in 2020 and 2021.A plagiarism check was carried out using the Academic Misconduct Literature Check System(AMLC).We generated a corrected similarity index based on the AMLC general similarity index for further analysis.We compared the similarity indices of papers in four medical fields and revealed their trends over time;differences in similarity index between review and research articles were also analyzed according to the different fields.Further analysis of 143 papers suspected of plagiarism was also performed from the perspective of sections containing duplication and according to the field of research.Findings:Papers in the field of pharmacology and pharmacy had the highest similarity index(8.67±5.92%),which was significantly higher than that in other fields,except health management.The similarity index of review articles(9.77±10.28%)was significantly higher than that of research articles(7.41±6.26%).In total,143 papers were suspected of plagiarism(5.80%)with similarity indices≥15%;most were papers on health management(78,54.55%),followed by public health and preventive medicine(38,26.58%);90.21%of the 143 papers had duplication in multiple sections,while only 9.79%had duplication in a single section.The distribution of sections with duplication varied among different fields;papers in pharmacology and pharmacy were more likely to have duplication in the data/methods and introduction/background sections,however,papers in health management were more likely to contain duplication in the introduction/background or results/discussion sections.Different structures for papers in different fields may have caused these differences.Research limitations:There were three limitations to our research.Firstly,we observed that a small number of papers have been checked early.It is unknown who conducted the plagiarism check as this can be included in other evaluations,such as applications for Science and technology projects or awards.If the authors carried out the check,text with high similarity indices may have been excluded before submission,meaning the similarity index in our research may have been lower than the original value.Secondly,there were only four medical fields included in our research.Additional analysis on a wider scale is required in the future.Thirdly,only a general similarity index was calculated in our study;other similarity indices were not tested.Practical implications:A comprehensive analysis of similarity indices in four medical fields was performed.We made several recommendations for the supervision of medical academic misconduct and the formation of criteria for defining suspected plagiarism for medical papers,as well as for the improved accuracy of text duplication checks.Originality/value:We quantified the differences between the AMLC general similarity index and the corrected index,described the situation around text duplication and plagiarism in papers from four medical fields,and revealed differences in similarity indices between different article types.We also revealed differences in the sections containing duplication for papers with suspected plagiarism among different fields.

An Algorithm to Reduce Compression Ratio in Multimedia Applications

In recent years,it has been evident that internet is the most effective means of transmitting information in the form of documents,photographs,or videos around the world.The purpose of an image compression method is to encode a picture with fewer bits while retaining the decompressed image’s visual quality.During transmission,this massive data necessitates a lot of channel space.In order to overcome this problem,an effective visual compression approach is required to resize this large amount of data.This work is based on lossy image compression and is offered for static color images.The quantization procedure determines the compressed data quality characteristics.The images are converted from RGB to International Commission on Illumination CIE La^(∗)b^(∗);and YCbCr color spaces before being used.In the transform domain,the color planes are encoded using the proposed quantization matrix.To improve the efficiency and quality of the compressed image,the standard quantization matrix is updated with the respective image block.We used seven discrete orthogonal transforms,including five variations of the Complex Hadamard Transform,Discrete Fourier Transform and Discrete Cosine Transform,as well as thresholding,quantization,de-quantization and inverse discrete orthogonal transforms with CIE La^(∗)b^(∗);and YCbCr to RGB conversion.Peak to signal noise ratio,signal to noise ratio,picture similarity index and compression ratio are all used to assess the quality of compressed images.With the relevant transforms,the image size and bits per pixel are also explored.Using the(n,n)block of transform,adaptive scanning is used to acquire the best feasible compression ratio.Because of these characteristics,multimedia systems and services have a wide range of possible applications.

Underwater Image Enhancement Using MIRNet

In recent years,enhancement of underwater images is a challenging task,which is gaining priority since the human eye cannot perceive images under water.The significant details underwater are not clearly captured using the conventional image acquisition techniques,and also they are expensive.Hence,the quality of the image processing algorithms can be enhanced in the absence of costly and reliable acquisition techniques.Traditional algorithms have certain limitations in the case of these images with varying degrees of fuzziness and color deviation.In the proposed model,the authors used a deep learning model for underwater image enhancement.First,the original image is pre-processed by the white balance algorithm for colour correction and the contrast of the image is improved using the contrast enhancement technique.Next,the pre-processed image is given to the MIRNet for enhancement.MIRNet is a deep learning framework that can be used to enhance the low-light level images.The enhanced image quality is measured using peak signal-to-noise ratio(PSNR),root mean square error(RMSE),and structural similarity index(SSIM)parameters.

Changes of plant species diversity and biomass with reclaimed marshes restoration

Wetland restoration had been implemented for more than two decades in Sanjiang Plain,Northeast China.To assess the restoration effi ciency of wetland vegetation,we investigated plants composition of community,plant species diversity and aboveground biomass of restored sites in a chronosequence of restoration(1,2,3,6,8,11,15 and 25 years)in the Sanjiang Nature Reserve.As comparison,we also investigated the same factors in a cropland and a natural marsh adjacent to the restored sites.The results showed that wetland plant species can invade quickly after croplands were abandoned when there were suitable hydrology conditions.On the early stage of the restoration,weeds were main plant species in the restored sites.Wetland species appeared at the same time but diff ered from the dominant species from the adjacent natural marshes.Common native wetland species could dominance the community after 3-year restoration.Species richness and diversity increased on the early stage,and then decreased to the similar level of the natural marsh with the extension of restoration.Plant biomass could restore easier than the species composition and diversity.Our results indicated that plant species composition and diversity of abandoned reclaimed wetlands can restore gradually by natural succession in Sanjiang Plain.However,25-year restoration site had similarity index of only 56%with the natural marsh,which revealed that two decades are not enough for complete restoration of vegetation.

A floristic survey of the Hyrcanian forests in Northern Iran, using two lowland-mountain transects

We investigated the floristic composition of the Hyrcanian forests and the related forest-steppe ecotone in Northern Iran by using two long ecological transects, from lowland to upper mountain areas. The study was conducted during 2008 and 2009 and yielded the identification of 395 plant taxa belonging to 233 genera and 78 families. Dicots with 300 taxa were the richest groups of the flora, followed by monocots with 75 taxa, pteridophytes with 18 species,and gymnosperms with two species. The largest families were Asteraceae（33 taxa）; Rosaceae（32 taxa）; and Poaceae（30 taxa）, and the most diverse genera included Carex（15 taxa）; Alchemilla（7 taxa）; and Poa, Geranium and Acer（6 taxa each）. Hemicryptophytes were the most dominant life forms in the area（40 %）; followed by geophytes（31.4 %）; phanerophytes（15.4 %）; therophytes（11.4 %）; and chamaephytes（1.8 %）. Phytogeographically,Euro-Siberian/Irano-Turanian elements（86 taxa, 21.8 %）and Euro-Siberian elements（85 taxa, 21.5 %） were the most common chorotypes in the area. Out of 395 taxa, 66taxa（16.7 %） were endemics and subendemics in Iran, of which 26 taxa were exclusively endemics of Iran.According to the IUCN Red List Categories, 48 threatened plant taxa were found in the study area. Plant diversity, life form, and chorotypes in the current study were compared with similar transect studies in other areas of the Hyrcanian forests and in different altitudinal belts, using S？renson similarity indices. Floristic composition of the surveyed transects demonstrated almost 50 % similarity between them.

Fully automatic identification and discrimination of sperm’s parts in microscopic images of stained human semen smear

In the last years, digital image processing and analysis are used for computer assisted evaluation of semen quality with therapeutic goals or to estimate its fertility by means of spermatozoid motility and morphology. Sperm morphology is assessed routinely as part of standard laboratory analysis in the diagnosis of human male infertility. Nowadays assessments of sperm morphology are mostly done based on subjective criteria. In order to avoid subjectivity, numerous studies that incorporate image analysis techniques in the assessment of sperm morphology have been proposed. The primary step of all these methods is segmentation of sperm’s parts. In this paper, we have proposed a new method for segmentation of sperm’s Acrosome, Nucleus, Mid-piece and identification of sperm’s tail through some points which are placed on the sperm’s tail, accurately. These estimated points could be used to verify the morphological characteristics of sperm’s tail such as length, shape and etc. At first, sperm’s Acrosome, Nucleus and Mid-piece are segmented through a method based on a Bayesian classifier which utilizes the entropy based expectation–maximization (EM) algorithm and Markov random field (MRF) model to obtain and upgrade the class conditional probability density function (CCPDF) and the apriori probability of each class. Then, a pixel at the end of sperm’s Mid-piece, is selected as an initial point. To find other pixels which are placed on the sperm’s tail, structural similarity index (SSIM) is used in an iterative scheme. In order to stop the algorithm automatically at the end of sperm’s tail, local entropy is estimated and used as a feature to determine if a point is located on the sperm’s tail or not. To compare the performance of the proposed approach with those of previous approaches including manual segmentation, the Accuracy, Sensitivity and Specificity were calculated.

A Hybrid Security Framework for Medical Image Communication

Authentication of the digital image has much attention for the digital revolution.Digital image authentication can be verified with image watermarking and image encryption schemes.These schemes are widely used to protect images against forgery attacks,and they are useful for protecting copyright and rightful ownership.Depending on the desirable applications,several image encryption and watermarking schemes have been proposed to moderate this attention.This framework presents a new scheme that combines a Walsh Hadamard Transform(WHT)-based image watermarking scheme with an image encryption scheme based on Double Random Phase Encoding(DRPE).First,on the sender side,the secret medical image is encrypted using DRPE.Then the encrypted image is watermarking based on WHT.The combination between watermarking and encryption increases the security and robustness of transmitting an image.The performance evaluation of the proposed scheme is obtained by testing Structural Similarity Index(SSIM),Peak Signal-to-Noise Ratio(PSNR),Normalized cross-correlation(NC),and Feature Similarity Index(FSIM).

Truncation and Rounding-Based Scalable Approximate Multiplier Design for Computer Imaging Applications

Advanced technology used for arithmetic computing application,comprises greater number of approximatemultipliers and approximate adders.Truncation and Rounding-based Scalable ApproximateMultiplier(TRSAM)distinguish a variety of modes based on height(h)and truncation(t)as TRSAM(h,t)in the architecture.This TRSAM operation produces higher absolute error in Least Significant Bit(LSB)data shift unit.A new scalable approximate multiplier approach that uses truncation and rounding TRSAM(3,7)is proposed to increase themultiplier accuracy.With the help of foremost one bit architecture,the proposed scalable approximate multiplier approach reduces the partial products.The proposed approximate TRSAM multiplier architecture gives better results in terms of area,delay,and power.The accuracy of 95.2%and the energy utilization of 24.6 nJ is observed in the proposed multiplier design.The proposed approach shows 0.11%,0.23%,and 0.24%less Mean Absolute Relative Error(MARE)when compared with the existing approach for the input of 8-bit,16-bit,and 32-bit respectively.It also shows 0.13%,0.19%,and 0.2%less Variance of Absolute Relative Error(VARE)when compared with the existing approach for the input of 8-bit,16-bit,and 32-bit respectively.The proposed approach is implemented with Field-Programmable Gate Array(FPGA)and shows the delay of 3.640,6.481,12.505,22.572,and 36.893 ns for the input of 8-bit,16-bit,32-bit,64-bit,and 128-bit respectively.The proposed approach is applied in digital filters designwhich shows the Peak-Signal-to-NoiseRatio(PSNR)of 25.05 dB and Structural Similarity Index Measure(SSIM)of 0.98 with 393 pJ energy consumptions when used in image application.The proposed approach is simulated with Xilinx and MATLAB and implemented with FPGA.

Denoising Letter Images from Scanned Invoices Using Stacked Autoencoders

Invoice document digitization is crucial for efficient management in industries.The scanned invoice image is often noisy due to various reasons.This affects the OCR(optical character recognition)detection accuracy.In this paper,letter data obtained from images of invoices are denoised using a modified autoencoder based deep learning method.A stacked denoising autoencoder(SDAE)is implemented with two hidden layers each in encoder network and decoder network.In order to capture the most salient features of training samples,a undercomplete autoencoder is designed with non-linear encoder and decoder function.This autoencoder is regularized for denoising application using a combined loss function which considers both mean square error and binary cross entropy.A dataset consisting of 59,119 letter images,which contains both English alphabets(upper and lower case)and numbers(0 to 9)is prepared from many scanned invoices images and windows true type(.ttf)files,are used for training the neural network.Performance is analyzed in terms of Signal to Noise Ratio(SNR),Peak Signal to Noise Ratio(PSNR),Structural Similarity Index(SSIM)and Universal Image Quality Index(UQI)and compared with other filtering techniques like Nonlocal Means filter,Anisotropic diffusion filter,Gaussian filters and Mean filters.Denoising performance of proposed SDAE is compared with existing SDAE with single loss function in terms of SNR and PSNR values.Results show the superior performance of proposed SDAE method.

Species Composition and Stand Structure of Primary and Secondary Moist Evergreen Forests in the Tanintharyi Nature Reserve (TNR) Buffer Zone, Myanmar

The habitat structure and floristic composition examined for this study are of great importance, providing a scientific baseline of information for developing a biodiversity database and in supporting crucial information for the management decision-making process of the buffer zones. The primary objective of this study was to examine the current status of species composition and stand structure of moist evergreen forests distributed in the TNR buffer zone. Forest inventory was conducted in the primary moist evergreen forest (~1 ha) and secondary moist evergreen forest (~1 ha). In the TNR buffer zone, 83 species belonging to 31 families in the primary moist evergreen forest and 86 species belonging to 32 families in the secondary moist evergreen forest were found. The most dominant families in the primary moist evergreen forest were Dipterocarpaceae, Sapindaceae, Meliaceae, Myrtaceae, and Myristicaceae;at species level;this forest was composed of Nephelium lappaceum, Myristica malabarica, Nephelium laurium, Aglaia andamanica, and Diospyros peregrine. The most dominant families in the secondary moist evergreen forest were Myrtaceae, Sapindaceae, Euphorbiaceae, Myristicaceae, and Lauraceae, while Nephelium lappaceum, Syzygium claviflorum, Syzygium sp-1, Eugenia oblate, and Myristica angustifolia were the most dominant at the species level. The results of S?rensen’s similarity index based on common species (Ks) and the similarity index based on species dominance (Kd) were observed at about 55% and 75% between the primary and secondary moist evergreen forests. The basal area (51.39 m2.ha-1) of the primary moist evergreen forest was higher than that (44.50 m2.ha-1) of the secondary moist evergreen forest. Between these two forest types, the Shannon-Wiener, the Simpson and the Evenness indices were not significantly different at (p < 0.05). The total number of trees per hectare (n/ha) of the primary and secondary moist evergreen forests were 910 (±184) and 991 (±183). ?

Performance Analysis of Image Smoothing Techniques on a New Fractional Convolution Mask for Image Edge Detection

We present the analysis of three independent and most widely used image smoothing techniques on a new fractional based convolution edge detector originally constructed by same authors for image edge analysis. The implementation was done using only Gaussian function as its smoothing function based on predefined assumptions and therefore did not scale well for some types of edges and noise. The experiments conducted on this mask using known images with realistic geometry suggested the need for image smoothing adaptation to obtain a more optimal performance. In this paper, we use the structural similarity index measure and show that the adaptation technique for choosing smoothing function has significant advantages over a single function implementation. The new adaptive fractional based convolution mask can smoothly find edges of various types in detail quite significantly. The method can now trap both local discontinuities in intensity and its derivatives as well as locating Dirac edges.

String similarity join with different similarity thresholds based on novel indexing techniques

String similarity join is an essential operation of many applications that need to find all similar string pairs from two given collections. A quantitative way to determine whether two strings are similar is to compute their similarity based on a certain similarity function. The string pairs with similarity above a certain threshold are regarded as results. The current approach to solving the similarity join problem is to use a unique threshold value. There are, however, several scenarios that require the support of multiple thresholds, for instance, when the dataset includes strings of various lengths. In this scenario, longer string pairs typically tolerate much more typos than shorter ones. Therefore, we proposed a so- lution for string similarity joins that supports different simi- larity thresholds in a single operator. In order to support dif- ferent thresholds, we devised two novel indexing techniques： partition based indexing and similarity aware indexing. To utilize the new indices and improve the join performance, we proposed new filtering methods and index probing tech- niques. To the best of our knowledge, this is the first work that addresses this problem. Experimental results on real-world datasets show that our solution performs efficiently while pro- viding a more flexible threshold specification.

The Caucasian corticioid fungi:level of endemism,similarity,and possible contribution to European fungal diversity

We assess the composition of corticioid fungi in the Caucasus region for the first time.The Caucasian corticioids were compared with those of well-documented areas in the Northern Hemisphere using the Tripartite similarity index and cluster analysis.To investigate the significance of the Caucasus region as a possible contributor to the colonization of wood-inhabiting basidiomycetes in Europe,DNA sequences of nuclear ribosomal internal transcribed spacers(ITS1 and ITS2)belonging to the corticioid fungus Peniophorella praetermissa were analysed for comparisons of genetic diversity within and differentiation between geographical regions.Putative species endemism and disjunction of corticioids in the Caucasus region is also discussed.The composition of corticioid fungi in the Caucasus region was found to be distinctly more similar to Europe and North America than to East Asia and India.Similarity tests and molecular Fsts both point to a strong connection between the Caucasus and Europe.The highest molecular diversity in P.praetermissa was in the Caucasus and East Asia as compared with other regions studied.The Caucasus and East Asia were significantly differentiated from each other,and unlike Caucasian samples,East Asian sequences were highly divergent from the European ones.This result suggests that the Caucasus might have been a source of colonization for Europe.Endemism is very low,possibly a common feature for wood-inhabiting saprotrophic fungi.

An Automatic Fuzzy Clustering Algorithm for Discrete Elements

This research proposes a measure called cluster similar index(CSI)to evaluate the similarity of cluster for discrete elements.The CSI is used as a criterion to build the automatic fuzzy clustering algorithm.This algorithm can determine the suitable number of clusters,find the elements in each cluster,give the probability to belong to the clusters of each element,and evaluate the quality of the established clusters at the same time.The proposed algorithm can perform quickly and effectively by the established MATLAB procedure.Several numerical examples illustrate the proposed algorithm and show the advantages in comparing with the existing ones.Finally,applying the proposed algorithm in the image recognition shows potentiality in the reality of this research.

Analyzing the Potential Influence of Shanghai Stock Market Based on Link Prediction Method

In this paper, we analyze the 180 stocks which have the potential influence on the Shanghai Stock Exchange(SSE). First, we use the stock closing prices from January 1, 2005 to June 19, 2015 to calculate logarithmic the correlation coefficient and then build the stock market model by threshold method. Secondly, according to different networks under different thresholds, we find out the potential influence stocks on the basis of local structural centrality. Finally, by comparing the accuracy of similarity index of the local information and path in the link prediction method, we demonstrate that there are best similarity index to predict the probability for nodes connection in the different stock networks.

Isosteric design of friction-reduction and anti-wear lubricant additives with less sulfur content

To reduce harmful sulfur content in lubricant additives, making use of isosterism has been shown to be an effective strategy. When thiobenzothiazole compounds were used as templates, the exchange of sulfur atoms in the thiazole ring with oxygen atoms and NH groups produced twelve isosteres. Similarly, 2-benzothiazole- S-carboxylic acid esters were used as template molecules to produce six isosteres. About 30% of the isosteres exhibited a satisfactory deviation of ±5% relative to the template, ignoring the specific changes in the base oils, the differences in molecular structure, and the friction or wear properties. The template molecules and isosteres in triisodecyl trimellitate exhibited better tribological properties than in trimethylolpropane trioleate or bis(2- ethylhexyl) adipate. Comparative molecular field analysis(CoM FA)- and comparative molecular similarity index analysis(CoMSIA)-quantitative structure tribo-ability relationship(QSTR) models were employed to study the correlation of molecular structures between the base oils and additives. The models indicate that the higher the structural similarities of the base oils and additives are, the more synergetic the molecular force fields of the lubricating system are; the molecular force fields creating synergistic effects will improve tribological performance.