syedzayyan/paper_mill_benchmark huggingface dataset:
Evaluation Model and Decision Analysis of Digital Firms Ranked in Forbes’ Top Companies

This study evaluates the profitability and marketability efficiencies of digital firms ranked in forbes’ list of top companies by using a two‐stage network data envelopment analysis (dea) model with multiplicative efficiency aggregation under the second‐order cone programming (socp) and examines the respective impacts of the 1995–2001 dot‐com bubble and the 2007–2009 global financial crisis on the companies’ efficiencies by applying impulse response function (irf) analysis.The data of our 49 sampled companies are derived from the compustat database.The covered period is 1999–2018.These results present the stable and increasing improvement of profitability and marketability efficiencies; in addition, two crisis events have no significant impact on the performance of digital firms.This research is supposed to offer a reasonable and objective evaluation model to measure the performance of digital firms, providing the managers and investors a reference for making their decision.

Journal: Discrete Dynamics in Nature and Society (2022)
Publication types: Research Article;
Fuzzy Neural Network-Based Evaluation Algorithm for Ice and Snow Tourism Competitiveness

This paper researches and analyzes the evaluation of the competitiveness of ice and snow tourism, uses the improved fuzzy neural network algorithm to process the system flow diagram of ice and snow tourism development through the function and characteristics of the power system of ice and snow tourism, and finally selects more than 40 indicators of the three subsystems of resources, economy, and culture.Based on the construction of cloud fuzzy neural network model, the above method is used for experimental comparison analysis, and experiments are conducted through university of california irvine (uci) dataset and engineering examples to compare with the traditional cloud model, fuzzy neural network, and bp neural network to analyze the operation efficiency, accuracy rate, and several rules of the algorithm.Through the experimental comparative analysis, the cloud fuzzy neural network can fully take into account the randomness and fuzziness of the data, optimize the generation of cloud rules, avoid multidimensional rule disasters, and ensure the operational efficiency of the algorithm; the accuracy rate of the algorithm is improved relative to that of the traditional technology, and it applies to a variety of datasets.And the software is used to test the ice and snow tourism industry system dynamics model to realize the correctness and robustness testing of the model.After the constructed model can reflect the real situation within the error range, the final policy simulation of the model is carried out.

Journal: Complexity (2021)
Publication types: Research Article;
Economic Benefit Evaluation and Analysis Based on Intelligent Agriculture Internet of Things

There has been a consensus on the development of ecological agriculture to promote the leap from traditional agriculture to ecological agriculture, but the unavoidable fact is that the development of ecological agriculture is still relatively slow at the present stage and has not formed a major climate and great influence.The rise of the internet is a technology that has promoted the transformation and upgrading of modern agriculture, changed the traditional agricultural production mode, and accelerated the scientific and technological integration of information.In view of the characteristics and difficulties of agriculture, this paper builds an agricultural internet of things (io t) management system to realize the integrated management of internet equipment and realize the management of environmental data, video data, and agricultural expert knowledge.Then from perception technology, transmission technology, and the perspective of three intelligent information processing technologies, this paper introduces the present state of agricultural io t, analyzes the internet of things to the economic benefits of agricultural production, to research the problems of china’s agricultural development of the internet of things, and puts forward china’s agricultural internet of the future research emphasis and direction of development.

Journal: Journal of Mathematics (2021)
Publication types: Research Article;
Industrial Design Capability Evaluation System under Cloud Service Model

This study focuses on the problem that the multiobjective optimization decision-making process of the design scheme under the cloud service model fails to fully consider the needs of users’ diversity, due to the lack of research on quantitative modeling and evaluation methods of designers’ ability.It affects the reasonable matching between complex design tasks and design ability and hinders the socialized aggregation of design ability.Based on the competency model, facing the industrial designers in the cloud manufacturing model, our paper constructs the design capability evaluation system from the perspectives of yuan shengren capability, industry technology competency, design task competency, and learning capability competency and discusses the design capability evaluation method based on a network analysis method.Through the design capability evaluation of the industrial design cloud service platform, feasibility and scientificity of the method in this paper are verified.This paper proposes a design scheme optimization decision-making method combining quality function configuration and rough set theory.Based on the analysis of the cloud service model, this method introduces the design decision-making process model of user participation and fuzzy evaluation mechanism to carry out cluster analysis and the intelligent transformation of user requirements.A design scheme evaluation index system oriented to user requirements is established, and the importance of design scheme evaluation indexes in the process of networked collaborative design is accurately quantified.Following the principle of combining scientificity and systematicness, a third-order decision-making model for design scheme optimization under the cloud service model is proposed.The model is solved by combining the rough set theory and rough approximation ideal solution.

Journal: Scientific Programming (2022)
Publication types: Research Article;
Digital Image Art Style Transfer Algorithm and Simulation Based on Deep Learning Model

In order to solve the problems of poor region delineation and boundary artifacts in chinese style migration of images, an improved variational autoencoder (vae) method for dress style migration is proposed.Firstly, the yolo v3 model is used to quickly identify the dress localization of the input image, then, the classical semantic segmentation algorithm (fcn) is used to finely delineate the desired dress style migration region twice, and finally, the trained vae model is used to generate the migrated chinese style image.The results show that, compared with the traditional style migration model, the improved vae style migration model can obtain finer synthetic images for dress style migration and can adapt to different chinese traditional styles to meet the application requirements of dress style migration scenarios.We evaluated several deep learning-based models and achieved a bleu value of 0.6 on average.The transformer-based model outperformed the other models, achieving a bleu value of up to 0.72.

Journal: Scientific Programming (2022)
Publication types: Research Article;
DenseNet-Based Classification of MRI Images for Detecting the Difference before and after Treating Liver Cancer

This study aimed to explore the evaluation of adriamycin-loaded microspheres in the treatment of liver cancer under dense net-based magnetic resonance imaging (mri) image classification algorithm.According to different treatment methods, the research objects were classified into a normal saline (saline) group, a doxorubicin raw material (dox) group, and a chitosan cross-linked pectin-doxorubicin conjugate macromolecular (cs-pdc-m) group.Dense net’s migration learning was employed to analyze the dynamic enhanced mri characteristics and classify the mri images.The cs-pdc-m-targeted nanotransfer system was examined with its apparent morphology, drug absorption, and cytotoxicity.Tumor volume was monitored using mri, and alanine aminotransferase (alt) and creatine kinase isoenzyme (ck-mb) values were detected.Results showed that the classification accuracy of liver cancer mri image based on dense net model reached 80% at the arterial hepatobiliary stage.The dox and cs-pdc-m group had obviously smaller tumor volume than that of the saline group p &lt; 0.05 with a statistical meaning.The mortality in the dox group was 30%, while there was no death in the saline and cs-pdc-m groups.Compared with the saline and cs-pdc-m groups, alt and ck-mb from the dox group increased substantially p &lt; 0.05 .Therefore, dox had an inhibitory effect on tumor but damaged the heart and liver.Dox was used to construct cs-pdc-m that could maintain the original treatment effect of dox and inhibit its side effects on the body, so cs-pdc-m had a clinical application value.In conclusion, adriamycin-loaded microspheres could not only maintain the original therapeutic effect of adriamycin but also inhibit its toxic and side effects on the body.The dense net model was applied in the liver cancer mri dynamic image classification algorithm, and the normalization algorithm could improve the accuracy of the liver cancer microvessel classification, thus promoting the diagnostic efficiency of liver cancer diagnosis, which had clinical application value.

Journal: Scientific Programming (2021)
Publication types: Research Article;
Dynamic Logo Design System of Network Media Art Based on Convolutional Neural Network

Nowadays, we are in an era of rapid development of internet technology and unlimited expansion of information dissemination.While the application of new media and digital multimedia has become more popular, it has also brought earth shaking changes to our life.In order to solve the problem that the traditional static visual image has been difficult to meet people’s needs, a network media art dynamic logo design system based on convolutional neural network is proposed.Firstly, the software and hardware platform related to accelerator development is introduced, the advanced integrated design and calculation ip core are determined as the fpga hardware accelerator, and the design objectives and requirements of the accelerator system are analyzed.The overall architecture of the accelerator system is designed.76% of designers believe that the dynamic logo has promoted the corporate image.Then, the function and architecture of ip core are designed based on advanced synthesis, the code structure is standardized, the function is divided, and the operation acceleration is further optimized by using the instruction set of hls.Finally, the design is integrated by vivado hls and vivado ide software.The experiment shows that the accelerator system has low power consumption and high resource utilization.

Journal: Mobile Information Systems (2022)
Publication types: Research Article;
Degree-Based Graph Invariants of some Chemical Structures for the Treatment of Corona Virus

Coronavirus is a family of viruses that cause upper respiratory infections in humans.It has several variants, e.g., sars and mers, and now, a new variant has been identified in 2019 which is the novel coronavirus disease 2019.The novel coronavirus disease 2019 (covid-19) first appeared in wuhan, china, and quickly spread throughout the world.Their incident rate is high in winter or in moderate temperature.Clinically, we identified the virus presence by pcr-based test.Preventive measures and vaccination are the only treatment against coronavirus.Some of them are remdesivir (gs-5734), chloroquine, hydroxychloroquine, theaflavin, ritonavir, and arbidol.A topological index (ti) is a mathematical function that assigns a numerical value to a (molecular) graph and predicts many physical, chemical, biological, thermodynamical, and structural features of that network.In this work, we will calculate a new topological index namely, atom-bond connectivity (abc) index, geometrically arithmetic (ga) index, sombor index, multiplicative sambor index, and its reduced version for the molecular graph of remdesivir (gs-5734), chloroquine, hydroxychloroquine, theaflavin, ritonavir, and arbidol.We also plot our computed results to examine how they were affected by the parameters involved.The results obtained can aid in the design of new medicine for the treatment of covid-19.

Journal: Journal of Function Spaces (2022)
Publication types: Research Article;
Deep-Learning-Based 3D Reconstruction: A Review and Applications

In recent years, deep learning models have been widely used in 3d reconstruction fields and have made remarkable progress.How to stimulate deep academic interest to effectively manage the explosive augmentation of 3d models has been a research hotspot.This work shows mainstream 3d model retrieval algorithm programs based on deep learning currently developed remotely, and further subdivides their advantages and disadvantages according to the behavior evaluation of the algorithm programs obtained by trial.According to other restoration applications, the main 3d model retrieval algorithms can be divided into two categories: (1) 3d standard restoration methods supported by the model, i.e., both the restored object and the recalled object are 3d models.It can be further divided into voxel-based, point coloring-based, and appearance-based methods, and (2) cross-domain 3d model recovery methods supported by 2d replicas, that is, the retrieval motivation is 2d images, and the recovery appearance is 3d models, including retrieval methods supported by 2d display, 2d depiction-based realistic replication and 3d mold recovery methods.Finally, the work proposed novel 3d fashion retrieval algorithms supported by deep science that are analyzed and ventilated, and the unaccustomed directions of future development are prospected.

Journal: Applied Bionics and Biomechanics (2022)
Publication types: Review Article;
Deep Learning-Based ECG Abnormality Identification Prediction and Analysis

In recent years, china’s economy has been developing rapidly, and people’s life and quality of life have been improving; more importantly, people’s habits and living habits have also developed from the previous “unhygienic” and “not very careful” to the current “healthier, more hygienic, greener and more sophisticated” direction.In the process of this development, due to the rapid development of the economy and the industrialization of cities, the incidence of heart disease is also increasing year by year.According to relevant studies, china’s urbanization process has been unprecedented, the number of urbanized people in china has exploded in recent years, and the ratio of urban to rural population has increased from about 20 percent to about 75 percent today.The effects of the population and the urbanization of urban architecture are affecting people’s physical and mental health, both consciously and unconsciously, causing both positive and negative physical and mental effects on the psychological and physical levels.In this paper, the concept of deep learning is fully utilized to train the cnn neural network model and apply it to the ecg abnormality recognition and prediction examination.In order to fully validate the application and significance of deep learning in ecg abnormality identification and prediction, the whole project was completed through subjective and objective experiments.The experimental results show that, from the subjective aspect, the ecg examination has been accepted by most people for different age groups, and the analysis results of the ecg examination with the deep learning model in this paper are more satisfactory; from the objective aspect, the cnn-ecg abnormality recognition prediction network model trained in this paper has high.The accuracy of the model for ecg abnormality recognition prediction can reach 86% when the learning rate is set to 0.0001 and the batch size is set to 120, and the model can reduce the burden of medical personnel to a certain extent.

Journal: Journal of Sensors (2022)
Publication types: Research Article;
Curative Effect of Prebiotics/Probiotics-Assisted Ketogenic Diet on Children with Refractory Epilepsy

The aim is to study the curative effect of prebiotics/probiotics-assisted ketogenic diet (kd) on children with refractory epilepsy.Methods.A retrospective analysis was performed on the clinical data of 80 children with refractory epilepsy treated in the hospital between december 2018 and december 2020.According to different treatment methods, they were divided into the kd group (36 cases, kd) and combination group (44 cases, prebiotics/probiotics assisted kd).All were followed up for 1 year.The curative effect, electroencephalogram findings, levels of neurotransmitters, quality of life scores, cognitive function (verbal intelligence quotient (viq), performance intelligence quotient (piq)), and incidence of adverse reactions were compared between the two groups.Results.At the last follow-up, the effective rate of the combination group was higher than that of the kd group (95.45% vs 80.56%) ( p &lt; 0.05 ).After 1 year of treatment, video electroencephalogram findings in both groups were improved, and the response rate of the combination group was higher than that of the kd group (97.73% vs 83.33%) ( p &lt; 0.05 ).After 1 year of treatment, levels of viq and piq in both groups were increased, which were higher in the combination group than the kd group ( p &lt; 0.05 ).After 1 year of treatment, the level of 5-hydroxytryptamine (5-ht) in both groups was increased, which was higher in the combination group than the kd group ( p &lt; 0.05 ).After 1 year of treatment, quality of life scores in both groups were increased, which was higher in the combination group than the kd group ( p &lt; 0.05 ).The incidence of adverse reactions in the combination group was lower than that in the kd group (13.64% vs 36.11%) ( p &lt; 0.05 ).Conclusion.The curative effect of prebiotics/probiotics-assisted kd is better on children with refractory epilepsy, which can effectively improve electroencephalogram and quality of life, increase neurotransmitters and cognitive levels, with good safety.

Journal: Emergency Medicine International (2022)
Publication types: Research Article;
Curative Effect of Prebiotics/Probiotics Preparations Combined with Zoledronic Acid + Calcitriol Regimen on Patients with Primary Osteoporosis and Their Influences on Bone Metabolism Markers

To explore the curative effect of prebiotics/probiotics preparations combined with zoledronic acid + calcitriol regimen on patients with primary osteoporosis (pop) and the influences of prebiotics/probiotics preparations combined with zoledronic acid + calcitriol regimen on markers of bone metabolism.Methods.126 elderly hospitalized patients with pop in our hospital from january 2020 to december 2021 were divided into the control group (n = 63) and the observation group (n = 63) by the random number table method.The patients in the control group were treated with zoledronic acid and calcitriol, while the patients in the observation group were additionally treated with prebiotics/probiotics preparations.The clinical curative effect, bone metabolism, calcium-phosphorus metabolism indexes, intestinal floras, and cytokines levels before and via treatment between the two groups were compared.Results.The total efficiency of the observation group was higher than that of the control group ( p &lt; 0.05 ).After treatment, the levels of bone gla protein (bgp), total propeptide of type i procollagen (pinp), and β-crosslaps (β-ctx) in both groups were lower than those before treatment, and the levels of bgp, total pinp, and β-ctx in the observation group were lower than those in the control group ( p &lt; 0.05 ).The levels of serum p in the both groups after treatment were lower than those before treatment, and the level of serum p in the observation group was lower than that in the control group ( p &lt; 0.05 ).The number of escherichia coli after treatment in the two groups were less than that before treatment, and the number of escherichia coli in the observation group was less than that in the control group ( p &lt; 0.05 ).The number of bifidobacteria and lactobacilli in the two groups after treatment were more than that before treatment, and the number of bifidobacteria and lactobacilli in the observation group were more than those in the control group ( p &lt; 0.05 ).After treatment, the levels of il-6 and tnf-α in the two groups were lower than those before treatment, and the levels of il-6 and tnf-α in the observation group was lower than those in the control group ( p &lt; 0.05 ).The levels of igf-1 in the two groups after treatment were higher than those before treatment, and the levels of igf-1 in the observation group was higher than that in the control group ( p &lt; 0.05 ).Conclusion.The response rate of prebiotics/probiotics preparations combined with zoledronic acid + calcitriol regimen is high in the treatment of pop patients, which ameliorates bone metabolism and intestinal floras, and suppresses cytokines release in patients with pop.

Journal: Emergency Medicine International (2022)
Publication types: Clinical Study;
Correlation Analysis between Chronic Osteomyelitis and Bacterial Biofilm

To study the role of bacterial biofilm (bbf) in the formation of chronic osteomyelitis and its prevention and treatment.Methods.In this paper, a large amount of relevant literature was searched for analysis and summary, and the key words “chronic osteomyelitis,” “bacterial biofilm,” “infection,” and “debridement” were searched in databases, mainly cnki, wanfang, and wipu.The search was conducted until december 2020.The role of bacterial biofilm formation in chronic osteomyelitis and its prevention were analyzed.Results.Chronic osteomyelitis is formed mainly due to poor blood supply and drug-resistant bacteria, of which cellular biofilm is the most important cause.Bbf forms on the surface of necrotic soft tissue and bone tissue, which has a protective effect on bacteria and greatly enhances their resistance to antibiotics, leading to difficulties in complete bacterial clearance and recurrent infections in osteomyelitis.Conclusion.Through an in-depth study of the molecular biology and signal transduction of osteomyelitis biofilm, antibiotic biofilm treatment strategies and surgical debridement remain the focus of clinical translation of chronic osteomyelitis.

Journal: Stem Cells International (2022)
Publication types: Review Article;
Data Analysis and Processing Application of Deep Learning in Engineering Cost Teaching Evaluation

Based on the poor quality of engineering cost teaching, this paper puts forward the application method of in‐depth learning in engineering cost teaching evaluation.This study aims to construct the engineering cost teaching evaluation system, optimize the engineering cost teaching evaluation algorithm combined with the in‐depth learning method, standardize the evaluation index of the engineering cost teaching system, and realize the research goal of engineering cost teaching evaluation.Finally, the experiment proves that the application effect of in‐depth learning in engineering cost teaching evaluation is obviously better, which can better guide the quality of engineering cost teaching.

Journal: Journal of Mathematics (2022)
Publication types: Research Article;