Refined Sparse Representation Based Similar Category Image Retrieval

Given one specific image,it would be quite significant if humanity could simply retrieve all those pictures that fall into a similar category of images.However,traditional methods are inclined to achieve high-quality retrieval by utilizing adequate learning instances,ignoring the extraction of the image’s essential information which leads to difficulty in the retrieval of similar category images just using one reference image.Aiming to solve this problem above,we proposed in this paper one refined sparse representation based similar category image retrieval model.On the one hand,saliency detection and multi-level decomposition could contribute to taking salient and spatial information into consideration more fully in the future.On the other hand,the cross mutual sparse coding model aims to extract the image’s essential feature to the maximumextent possible.At last,we set up a database concluding a large number of multi-source images.Adequate groups of comparative experiments show that our method could contribute to retrieving similar category images effectively.Moreover,adequate groups of ablation experiments show that nearly all procedures play their roles,respectively.

End-to-end aspect category sentiment analysis based on type graph convolutional networks

For the existing aspect category sentiment analysis research,most of the aspects are given for sentiment extraction,and this pipeline method is prone to error accumulation,and the use of graph convolutional neural network for aspect category sentiment analysis does not fully utilize the dependency type information between words,so it cannot enhance feature extraction.This paper proposes an end-to-end aspect category sentiment analysis(ETESA)model based on type graph convolutional networks.The model uses the bidirectional encoder representation from transformers(BERT)pretraining model to obtain aspect categories and word vectors containing contextual dynamic semantic information,which can solve the problem of polysemy;when using graph convolutional network(GCN)for feature extraction,the fusion operation of word vectors and initialization tensor of dependency types can obtain the importance values of different dependency types and enhance the text feature representation;by transforming aspect category and sentiment pair extraction into multiple single-label classification problems,aspect category and sentiment can be extracted simultaneously in an end-to-end way and solve the problem of error accumulation.Experiments are tested on three public datasets,and the results show that the ETESA model can achieve higher Precision,Recall and F1 value,proving the effectiveness of the model.

A Hybrid Ensemble Learning Approach Utilizing Light Gradient Boosting Machine and Category Boosting Model for Lifestyle-Based Prediction of Type-II Diabetes Mellitus

Addressing classification and prediction challenges, tree ensemble models have gained significant importance. Boosting ensemble techniques are commonly employed for forecasting Type-II diabetes mellitus. Light Gradient Boosting Machine (LightGBM) is a widely used algorithm known for its leaf growth strategy, loss reduction, and enhanced training precision. However, LightGBM is prone to overfitting. In contrast, CatBoost utilizes balanced base predictors known as decision tables, which mitigate overfitting risks and significantly improve testing time efficiency. CatBoost’s algorithm structure counteracts gradient boosting biases and incorporates an overfitting detector to stop training early. This study focuses on developing a hybrid model that combines LightGBM and CatBoost to minimize overfitting and improve accuracy by reducing variance. For the purpose of finding the best hyperparameters to use with the underlying learners, the Bayesian hyperparameter optimization method is used. By fine-tuning the regularization parameter values, the hybrid model effectively reduces variance (overfitting). Comparative evaluation against LightGBM, CatBoost, XGBoost, Decision Tree, Random Forest, AdaBoost, and GBM algorithms demonstrates that the hybrid model has the best F1-score (99.37%), recall (99.25%), and accuracy (99.37%). Consequently, the proposed framework holds promise for early diabetes prediction in the healthcare industry and exhibits potential applicability to other datasets sharing similarities with diabetes.

Asterix Category 033协议的分析与应用

介绍了Asterix Category 033协议的数据项组成、编码的内容以及在监视应用中的关键作用,研究了该协议的CRC编码方式以及报文的组装方式,提出了每个数据项的内容在监视终端和地面接收处理基站中的处理方法。所研究和分析成果为Asterix Category 033协议生成与解析报文提供了依据。

Distribution assessment of soil erosion with revised RUSLE model in Tianshan Mountains

aSoil degradation caused by soil erosion is one of the world's most critical environmental issues.Soil erosion in the Tianshan Mountains has caused various environmental problems in the surrounding areas.This study used remote sensing data to analyze the distribution of the factors influencing soil erosion,and the revised universal soil loss equation(RUSLE)to calculate the total amount and distribution characteristics of soil erosion in the Tianshan Mountains in 2019.Due to the large error of RUSLE in soil erosion estimation in mountainous areas,this study modified RUSLE equation based on the characteristics of snow cover in the Tianshan Mountains.The results show that the average soil erosion was 1690.3 t/(km^(2)·year),of which insignificant erosion,slight erosion and moderate erosion accounted for 42,8%,22.4%and 9.9%,respectively.Severe erosion and above accounted for 13.3%.The accuracy of the soil erosion modulus calculated by the RUSLE was only 61.9%,with an average error of 1631.9 t/(km^(2)·year).The average error of the double-coefficient correction method was 1259.1 t/(km^(2)·year),and the average error of the modified formula method was reduced by 40.3%compared with the RUSLE,reaching 973.7 t/(km^(2)·year),and its accuracy reached 76.2%.Very severe erosion and catastrophic erosion are distributed on mountain ridges with higher elevation and on the northern area with higher precipitation.Snow cover has a certain inhibitory effect on soil erosion,and snow cover in alpine mountains is a factor that cannot be ignored in soil erosion research.

Bawei Biotechnology Listed

On Mar.29th,2024,Bawei Biotechnology was listed at Beijing Stock Exchange.So far,Bawei Biotechnology has smoothly become“the first cosmetics OEM listed at Beijing Stock Exchange”,as well as the first A-share cosmetics enterprise listed in 2024.At the opening quotation,the stock price increase of Bawei Biotechnology exceeded 200%,and the total market value exceeded 1.4 billion yuan.Bawei Biotechnology mainly engages in the R&D,production,sales and detection of cosmetics,with the product category covering skin care product,facial mask,toiletry,and makeup.So far,it has served a total of 1,000 cosmetics brands,including Unilever,Renhe Ingenuity,HBN,SKINTIFIC,Marubi Biotechnology,PROF.

Statistical Analysis of Accident Proneness of Drivers

A mathematical model describing the risks of road accidents has been built on the basis of statistical data of drivers’ accident rate. It has been revealed that drivers can be divided by the degree of their accident proneness into four categories with sharply differing probabilities of road accidents. It has been shown that there is a possibility of classification of drivers in accordance with specified categories.

The Application Value of Ultrasound Imaging in the Differential Diagnosis of Benign and Malignant Breast Nodules of BI-RADS 3 and Above

Objective:To explore the diagnostic value of ultrasound imaging for breast nodules of breast imaging-reporting and data system(BI-RADS)category 3 and above.Methods:From June 2021 to July 2022,163 patients with breast nodules of BI-RADS 3 or above were selected as the research subjects.After pathological diagnosis,24 cases were malignant breast nodules of BI-RADS 3 or above,while 139 cases were benign breast nodules of BI-RADS 3 or above.The diagnosis rate of malignant and benign breast nodules of BI-RADS 3 or above,including 95%CI,was observed and analyzed.Results:The malignant and benign detection rates of conventional ultrasound were 88.63%and 75.00%,respectively,and the malignant and benign detection rates of ultrasound imaging were 93.18%and 87.50%,respectively,with 95%CIs greater than 0.7.Conclusion:Ultrasound imaging can help improve the diagnostic accuracy of benign and malignant breast nodules of BI-RADS 3 and above and reduce the misdiagnosis rate.

A Study on the Correlation Between LIWC Word Categories and Chinese Composition Writing Performance of Fourth,Fifth,and Sixth Grade Students

This study focuses on the analysis of the Chinese composition writing performance of fourth,fifth,and sixth grade students in 16 selected schools in Longhua District,Shenzhen during the spring semester of 2023.Using LIWC(Linguistic Inquiry and Word Count)as a text analysis tool,the study explores the impact of LIWC categories on writing performance which is scaled by score.The results show that the simple LIWC word categories have a significant positive influence on the composition scores of lower-grade students;while complex LIWC word categories have a significant negative influence on the composition scores of lower-grade students but a significant positive influence on the composition scores of higher-grade students.Process word categories have a positive influence on the composition scores of all three grades,but the impact of complex process word categories increases as the grade level rises.

Asterix Category021协议的应用与分析

介绍了Asterix Category 021协议的数据项内容、用户应用程序框架(UAP)的结构、报文数据块的布局,以及ADS-B系统应用该协议的方式,分析了该协议的实例应用和协议报文的解析,提出了处理报文的思路。研究与分析结果可为如何使用Asterix Category 021协议生成与解析报文提供参考。

A Study of English Neologisms in 2015 Based on the Prototype Category Theory

With the development of science and technology, large quantities of neologisms are created. Neologisms are the result of people's conceptualization of new things based on their life experiences. Cognitive linguistics views that categorization of organisms and concrete objects are based on the prototype category. This paper takes 167 English Neologisms from Wordspy in2015 as the data for analysis and finds that these English Neologisms are characterized by family resemblances, degree of membership in category and boundary fuzziness from the view of prototype category theory. This study also has some implications for the research of English language teaching and learning.

Monoidal Category Approach to Dual Hom-quasi-Hopf Algebras

In this paper, we categorify a Hom-associative algebra by imposing the Homassociative law up to some isomorphisms on the multiplication map and requiring that these isomorphisms satisfy the Pentagon axiom, and obtain a 2-Hom-associative algebra. On the other hand, we introduce the dual Hom-quasi-Hopf algebra and show that any dual Homquasi-Hopf algebras can be viewed as a 2-Hom-associative algebra.

Stable t-structures and Homotopy Category of Strongly Copure Projective Modules

In this paper, we study the homotopy category of unbounded complexes of strongly copure projective modules with bounded relative homologies K;（SCP）.We show that the existence of a right recollement of K;（SCP） with respect to K;（SCP）, K;（SCP） and K;（SCP） has the homotopy category of strongly copure projective acyclic complexes as a triangulated subcategory in some case.

ADS-B Category 021报文解析软件的设计与实现

由于ADS-B设备相比雷达和遥测遥控具有低成本、小型化和通用性的优点,且能够对长航时、远距离的飞行目标进行监控,文章规划了Category 021报文的引入方案,对Category 021报文格式进行分析,重点设计开发了Category 021报文解析软件,通过接收并处理ADS-B地面站传送的目标航迹数据,实现了ADS-B信号中合作目标航迹数据的提取与显示,并进行了测试验证。测试结果表明:该方案能有效地实现对飞行目标的快速跟踪监视,增强了对飞行目标的监控手段。

Equivalence of Dynamicity and Balance of Category in “INCEPTION”

"INCEPTION" has become a blockbuster recently and this word reflects the phenomenon:meaning expanding in a specific context,which,as a matter of fact,lives in many fields such as literature,films and speeches.Such words or phrases have both surface and deep meanings whose translation research is mainly placed on literal or literary transfer,leaving out their dynamicity and balance in meaning category.This paper aims to give a brief analysis on such phenomenon and puts forward to a new translation principle:category equivalence in dynamicity and balance.

Research on Category of Maritime English Vocabulary

Through the research on the maritime English vocabulary, the author analyzes the category of Maritime English vocabulary, stresses an important application of Maritime English vocabulary in maritime field.

THE TWO FUNCTORS IN THE FUZZY MODULAR CATEGORY

After defining Hom(chi (A), eta (B)) and chi (A) circle times eta (B) in the fuzzy modular category Fm, the sufficient conditions of the existence for exact Hom functors Hom(delta (M),), and Hom(, delta (M)), as well as exact Tensor functors delta (M)circle times and circle times delta (M) are given in this paper. Finally the weak isomorphisms relations between Horn functors and Tensor functors are displayed.

A Fast Bayesian Evaluation Algorithm Based on the Second Category of Maximum Likelihood

Directing at evaluation for qualifying rate in weaponry test,this article discusses firstly how field test information is flooded with lots of prior information.Then a fast Bayesian evaluation algorithm is presented based on the elaborate analysis of prior information reliability and the second category of maximum likelihood.The example demonstrates that the algorithm presented in this article is better and more robust compared with classical evaluation algorithm for safe-or-failure test and normal Bayesian method,which can make the best of prior information.

Relationship between Category of Weight and Threshold of Maximum Oxidation of Lipids in Congolese Judoists

Background: One of the goals for training in judo is to mimic real situations. In subsaharian countries;there is a lack of knowledge considering relation between category of weight and threshold maximum oxidation of lipids. Objectives: The main objectives of this study were to analyze the effect of category of weight on lipoxmax and to identify the zones of target intensities corresponding to lipoxmax. Materials and Methods:Twenty four male well-training judoists, divided in two groups according to weight, were evaluated during calorimetry effort’ test. For this situation, cardiorespiratory parameters (HR, VO2, VO2max), blood parameter (lactatemia), anthropometric variables and zones of target corresponding to lipox were evaluated. For statistical analysis, Shapiro-Wilks test was used to compare all the data and differences were confirmed by one-way variance. Results: No significant differences were observed among two groups for target intensities to lipox. The judoists of group 1 were aged to 24.1 ± 5.9 years with 1.78 ± 0.07 m versus 20.4 ± 1.6 years with 1.86 ± 0.04 m. Primary results indicated higher intensities for lipoxmax. Also, values of power (% LDC) and VO2 and were significantly higher in the judoists for group 2, with respectively: 45.3 ± 10.2 and 46.4 ± 8.6 ml/min versus 38.2 ± 7.2 and 31.3 ± 7.6 ml/min. Conclusion: High weight in judoists induces high intensities of lipoxmax and change oxidation of lipids markers following training.

Do unemployment and payor category impact length of stay and hospital charges of spine fusion patients?

Introduction: In this paper we investigate the possible connection between socioeconomic status as demarcated by employment and in-surance status and consumption of healthcare resources in spine surgery patients. Methods: The clinical records of 1599 spine surgery pa-tients counted from 2008-2009 were reviewed. The largest groups of patients belonged to MS-DRG 460 (N = 585) and to MS-DRG 473 (N = 700). These two MS-DRG patient groups were used as the study cohort representing patients who, by definition, did not have serious comor-bidities or complications. Results: Unemployed non-cervical patients tended to stay on average 1.8 days longer in hospital and had on average $5800 higher hospital charges. No major differ-ences were noted in length of stay and hospital cost between government and private insurance patients. However, self-pay non-cervical fusion patients had notable increases in length of stay and hospital cost, especially in the >39 and <60 age group with the difference in length of stay amounting to 5 days and in hospital charges to $10,000. Univariate analysis with DRG (460 or 473) as a covariate showed significant impact from employment status on length of stay (F = 4.259, P = 0.014) and less significant impact from payor category on hospital charges (F = 2.229, P = 0.064) in the economically-productive 40 -59 age group. Conclusions: In general, no increase in hospital resource consumption was noted except among self-pay patients, the same group seemingly least able to afford expensive healthcare.