syedzayyan/paper_mill_benchmark huggingface dataset:
A Data-Driven Control Strategy for Urban Express Ramp

Expressway, as the main artery of urban traffic, realizes the smooth operation of the whole urban road network through reasonably balancing the traffic flow.However, due to the lack of reasonable and effective traffic control, the safety and congestion of expressways are becoming more and more serious.The development of intelligent network technology provides a new idea to solve the control problem of expressways.In this paper, a data‐driven ramp control model of urban expressway is constructed.The interaction of traffic information is realized through intelligent network connection technology.The cooperative control strategy of vsl and rm is adopted.The mutual feedback of vsl and rm is realized based on the improved metanet model.The simulation experiment based on vissim secondary development shows that the collaborative control strategy under the intelligent network environment could make the vehicle travel time reduced by 20.59% and the speed difference between adjacent sections of the expressway mainline by 34.07%, which realized the coordinated control of the mainline and the on‐ramp under the intelligent network environment, alleviate the expressway traffic congestion, reduce the traffic pressure, and improve the efficiency of the road network.

Journal: Computational Intelligence and Neuroscience (2021)
Publication types: Research Article;
3D Point Cloud Data Registration Algorithm Based on Augmented Reality Technology

Point cloud data registration is one of the key steps in 3d laser scanning data processing.At present, point cloud data registration has the problems of error and is too much time-consuming.In order to solve the above problems, a 3d point cloud data registration algorithm based on augmented reality technology is proposed, and the 3d data registration model is constructed by combining augmented reality technology, build the evaluation index of 3d point cloud data registration, and carry out the initial registration of 3d point cloud based on the evaluation index.The experiment shows that the 3d point cloud data registration algorithm based on augmented reality technology can more effectively improve the accuracy of data registration and avoid the problem of low efficiency of data registration in practice.

Journal: Wireless Communications and Mobile Computing (2023)
Publication types: Research Article;
Wireless Network Sensing of Urban Surface Water Environment Based on Clustering Algorithm

To improve the wireless sensing image extraction technology of urban surface water environment, a regional fcm clustering method combined with water index was proposed in this paper.The normalized water index (ndwi) was obtained by calculating the fusion multispectral wireless sensing image.Through the combination with normalized water index, fuzzy clustering results were obtained by rfcm algorithm proposed in this paper.The optimal threshold was selected to defuzzify the fuzzy clustering results, and finally, the extraction results of urban surface water were obtained.The accuracy of the proposed algorithm was compared with that of the traditional surface water extraction algorithm.The experimental results showed that the size of different neighborhood regions affected the water extraction accuracy.In w city, the kappa coefficient of mfcm16 was 0.41% higher than that of mfcm8, and the overall classification accuracy of mfcm16 was 1.33% higher than that of mfcm.In g city area, the kappa coefficient of mfcm16 was 1.81% higher than that of mfcm8, and the overall classification accuracy of mfcm16 was 1.7% higher than that of mfcm.Comparing the rfcm algorithm with other algorithms, the rfcm algorithm obtained the best experimental results, to reduce the “salt‐and‐pepper phenomenon” effect.

Journal: Wireless Communications and Mobile Computing (2021)
Publication types: Research Article;
Vasoactive Drug Therapy and Clinical Nursing of Patients with Cardiovascular Disease

Cardiovascular disease (cvd) is a common human disease with a large number of patients.Vasoactive drugs have a good effect on the contraction and expansion of blood vessels, which can provide certain help for the management of cardiovascular diseases.However, the clinical care of cardiovascular disease has always been based on the superficial resistance level of body fat, weight, and so on, which is unfavorable for the real recovery of patients with cardiovascular disease.This article aims to quantitatively evaluate the effects of clinical care based on vasoactive drug therapy and intrinsic factors of cardiovascular disease.For the treatment of vasoactive drugs, this paper selects the principle of action of the adrenal hormone to judge and analyze the expansion and contraction of the cardiovascular disease.For the clinical nursing of patients with cardiovascular disease, based on multivariate logistic regression, this paper selects internal factors such as age and blood pressure to model the nursing effect.Experiments have shown that the logistic regression model established in this paper can evaluate well the recovery effect of patients with cardiovascular disease.The auc value of the model reached around 0.9.This showed that the clinical care of patients with cardiovascular disease can not only rationally judge the recovery effect through the model but also adjust the physical and mental conditions of patients with cardiovascular disease according to the coefficients of the model to achieve the best recovery effect.

Journal: Contrast Media & Molecular Imaging (2022)
Publication types: Research Article;
Value of Transabdominal Combined Transvaginal Color Doppler Ultrasonography in the Distinguish between Uterine Adenomyoma and Uterine Fibroids

To investigate the value of transabdominal combined transvaginal color doppler ultrasonography in the diagnosis of uterine adenomyoma.Methods .A total of 80 patients with suspected uterine adenomyoma in our hospital from january 2019 to december 2021 were selected as the study subjects.All of them were examined by transabdominal color doppler ultrasound (ta‐cdus) and transvaginal color doppler ultrasound (tv‐cdus), and the postoperative pathological examination results were taken as the gold standard to analyze the diagnostic efficacy of different examination methods for uterine adenomyoma.Results .By postoperative pathological biopsy, 46 cases (57.50%) were diagnosed as positive and 34 cases (42.50%) were diagnosed as negative, including 29 cases of uterine adenomyoma and 5 other cases.The sensitivity, accuracy, and negative predictive value of ta‐cdus combined with tv‐cdus in the diagnosis of adenomyoma were higher than those of ta‐cdus ( p &lt; 0.05), and the kappa value between ta‐cdus and pathological diagnosis was 0.923, which was higher than the 0.615 between tv‐cdus and pathological diagnosis.Ta‐cdus combined with tv‐cdus showed that there were significant differences in the distribution of adier blood flow grades between patients with uterine adenomyoma and uterine fibroids ( p &lt; 0.05), and the adier blood flow grades of patients with uterine adenomyoma were mainly grade 0 and grade i; and the resistance index (ri), peak systolic velocity (vs), and pulsatile index (pi) in patients with uterine adenomyoma were higher than those in patients with uterine fibroids ( p &lt; 0.05).Conclusion .Compared with ta‐cdus, ta‐cdus combined with tv‐cdus is more sensitive and accurate in the diagnosis of uterine adenomyoma and has a good consistency with pathological diagnosis results.Attention should be paid to the blood flow parameter values in the differential diagnosis of uterine fibroids.

Journal: BioMed Research International (2022)
Publication types: Research Article;
Value of Biochemical Indexes of Bone Metabolism in Predicting Osteoporotic Lumbar Fractures

To investigate the value of bone metabolism indexes such as type i procollagen n-terminal propeptide (p1np), 25-hydroxyvitamin d (25(oh)d), osteocalcin (osteoc), and parathyroid hormone (pth) in predicting osteoporotic lumbar fractures.Methods.120 female patients with osteoporosis treated in our hospital were selected as research objects.There were 76 cases in the fracture group and 44 cases in the nonfracture group.The relationship between the levels of p1np, 25(oh)d, osteoc, and pth and the incidence of osteoporotic lumbar fractures were detected and compared between the two groups.The predictive value of biochemical indexes of bone metabolism in patients with osteoporosis was analyzed by roc curve.Results.The levels of p1np and pth in the fracture group were significantly higher than those in the nonfracture group, while 25(oh)d and osteoc levels were lower than those in the nonfracture group.Moreover, the levels of p1np, 25(oh)d, osteoc, and pth are important factors affecting the pathogenesis of osteoporosis.The area under the curve (auc) of fracture in patients with osteoporosis predicted by the combination of p1np, 25(oh)d, osteoc, and pth levels was 0.886, which was greater than the auc predicted by each index (0.796, 0.753, 0.670, and 0.824).The best sensitivity and specificity of comprehensive prediction of each index were 78.95% and 79.10%, respectively.Conclusion.The abnormal changes of p1np, 25(oh)d, osteoc, and pth in female patients with osteoporotic lumbar fracture are closely related to the occurrence of the disease.The combination of these indicators has relatively significant application value in predicting the occurrence of fracture, which is helpful to formulate and guide relevant preventive measures for female patients with osteoporotic lumbar fracture and improve the prognosis.

Journal: Applied Bionics and Biomechanics (2022)
Publication types: Research Article;
Using Artificial Intelligence Technology to Solve the Electronic Health Service by Processing the Online Case Information

With the continuous improvement of economic level and the continuous development of science and technology in china, information technology has begun to integrate into all walks of life.Medical units have begun to change from the traditional medical system to the intelligent system, and the processing of online case information has become an important component of medical informationization.To improve the efficiency of dealing with online case information, this study proposes to establish a fully connected neural network model to deal with online cases.Using jieba word segmentation tool and data preprocessing technology, the data of electronic medical records are sorted out, and the data are quantified using word2vec and other tools, and the data on electronic medical records are converted into one-hot binary variables.The quantified data are trained into a fully connected neural model, and the accuracy rate is about 88%.It is compared with naive bayes and decision tree classification methods, and then a comparative experiment is carried out by solving e-health services in different ways.The results show that the fully connected neural network model has the best classification effect: the highest accuracy rate is about 93.7%, the highest precision rate is about 94.0%, the highest recall rate is about 95.3%, and the highest f1 score is about 94.6%.However, using artificial intelligence technology to solve electronic health services has great advantages, among which efficiency, assistance, and service satisfaction are all higher than 90%, which provides favorable technical support for electronic health services.

Journal: Journal of Healthcare Engineering (2021)
Publication types: Research Article;
Urban Fruit Quality Traceability Model Based on Smart Contract for Internet of Things

In internet of things, compared with the traditional traceability system, the existing system has difficulties in operation, data are easily lost, data are uncoordinated, standards are not unified, and so on.In this paper, based on the characteristics of blockchain, the traceability model of urban fruits is established to reduce the risk of counterfeit and shoddy urban fruits.The collected data is integrated into the chain for diversified display, providing different permissions and platforms for multiple roles.Blockchain and supporting intelligent hardware are used to realize the real record and tracking of the whole process of fruit.Improve the transparency and efficiency of supply chain, and reduce the supply chain cost.The experimental results show that the proposed algorithm model can be applied to the fruit service field and effectively improve the service level of smart city.

Journal: Wireless Communications and Mobile Computing (2021)
Publication types: Research Article;
Ultrasonic Intelligent Diagnosis of Papillary Thyroid Carcinoma Based on Machine Learning

Thyroid diseases are divided into papillary carcinoma and nodular diseases, which are very harmful to the human body.Ultrasound is a common diagnostic method for thyroid diseases.In the process of diagnosis, doctors need to observe the characteristics of ultrasound images, combined with professional knowledge and clinical experience, to give the disease situation of patients.However, different doctors have different clinical experience and professional backgrounds, and the diagnosis results lack objectivity and consistency, so an intelligent diagnosis technology for thyroid diseases based on the ultrasound image is needed in clinic, which can give objective and reliable diagnosis opinions on thyroid diseases by extracting the texture, shape, and other information of the image and assist doctors in clinical diagnosis.This paper mainly studies the intelligent ultrasonic diagnosis of papillary thyroid cancer based on machine learning, compares the ultrasonic characteristics of ptmc diagnosed by using the new ultrasound technology (ceus and ue), and summarizes the differential diagnosis effect and clinical application value of the two technology methods for ptmc.In this paper, machine learning, diffuse thyroid image features, and rbm learning methods are used to study the ultrasonic intelligent diagnosis of papillary thyroid cancer based on machine learning.At the same time, the new contrast-enhanced ultrasound (ceus) technology and ultrasound elastography (ue) technology are used to obtain the experimental phenomena in the experiment of ultrasonic intelligent diagnosis of papillary thyroid cancer.The results showed that 90% of the cases were diagnosed by contrast-enhanced ultrasound and confirmed by postoperative pathology.Ceus and ue have reliable practical value in the diagnosis of ptmc, and the combined application of ceus and ue can improve the sensitivity and accuracy of ptmc diagnosis.

Journal: Journal of Healthcare Engineering (2022)
Publication types: Research Article;
Ultrasonic Imaging of Cardiovascular Disease Based on Image Processor Analysis of Hard Plaque Characteristics

Cardiovascular disease detection and analysis using ultrasonic imaging expels errors in manual clinical trials with precise outcomes.It requires a combination of smart computing systems and intelligent image processors.The disease characteristics are analyzed based on the configuration and precise tuning of the processing device.In this article, a characteristic extraction technique (cet) using knowledge learning (kl) is introduced to improve the analysis precision.The proposed method requires optimal selection of disease features and trained similar datasets for improving the characteristic extraction.The disease attributes and accuracy are identified using the standard knowledge update.The image and data features are segmented using the variable processor configuration to prevent false rates.The false rates due to unidentifiable plaque characteristics result in weak knowledge updates.Therefore, the segmentation and data extraction are unanimously performed to prevent feature misleads.The knowledge base is updated using the extracted and identified plaque characteristics for consecutive image analysis.The processor configurations are manageable using the updated knowledge and characteristics to improve precision.The proposed method is verified using precision, characteristic update, training rate, extraction ratio, and time factor.

Journal: BioMed Research International (2022)
Publication types: Research Article;
UAV Tilt Photography Control for Numerical Simulation of High and Steep Rock Slopes

In order to provide accurate image information for the analysis and treatment of dangerous rocks and rockfalls during the early investigation, a uav tilt photography control method for numerical simulation of high and steep rock slopes is proposed.Based on the uav tilting photography technology, the slope section was obtained through a real 3d modeling and poststage point cloud data processing.Numerical simulation is used to study the motion characteristics of dangerous rock falling in a high and steep slope of a railway station.This essay introduces the application of a uav tilting photography and real 3d modeling technology in the process of rock fall analysis and realizes the real scene restoration of the site.The point cloud data of the site is obtained, and the processing process of the point cloud is introduced in detail.The slope section of the site was obtained based on the point cloud, and roc fall software was used to obtain the motion characteristics of dangerous rock falling (falling trajectory, bouncing height impact energy, and impact velocity).The simulation results show that because of the rugged slope, the falling rocks collide and rebound on the slope for many times.In addition, near the bottom of the slope, there is a steep cliff with a height of 136.21 m, which is approximately 54° from the horizontal line, causing the falling rock to bounce and eventually fall at a higher height.It moves to the bottom of the slope and bounces off the level of the railway line before finally settling on the railway road.The maximum bounce height of falling rock in the process of slope rolling motion reaches 30 m.When falling rock moves near the railway line (coordinate is on the right side of zero), the bounce height is 15∼25 m, which threatens the safety of the railway operation.Conclusion.The uav tilt photography technology can be well applied to the analysis of rockfall motion characteristics of dangerous rocks, and provide an accurate cross-section data information for the study of rockfall motion characteristics of dangerous rocks.

Journal: Journal of Control Science and Engineering (2023)
Publication types: Research Article;
Treatment of Cancer Gene Changes in Chronic Myeloid Leukemia by Big Data Analysis Platform-Based Dasatinib

Based on data mining, an innovative big data analysis platform was utilized to discuss the treatment of cancer in chronic myeloid leukemia (cml) by dasatinib, aiming to offer help to the diagnosis and treatment of cancer.An integrated gene expression analysis system (ieas) was firstly constructed to automatically classify data in the online human mendelian genetic database using clustering algorithms.At the same time, the gene expression profile was analyzed by principal component analysis (pca) in the analysis system.In addition, the efficacy of dasatinib in the treatment of patients with advanced cml was then retrospectively analyzed.The results showed that the ieas system could incorporate the gene expression analysis vectors it contained by java-related technologies, and the generated clustering genes showed similar functions.The clustering algorithm could homogenize data and generate visual clustering heat maps.The analysis results of major elements were diverse under different experimental conditions.The characteristic value of the first major element was the largest.Messenger ribonucleic acid (m rna) datasets of cml patients were selected from cancer genomic map, including 120 samples and 20,614 m rna in total.In micro-rna (mi rna) datasets, there were 202 samples including 1,406 mi rnas.Data were screened by mi rna–m rna regulation template, and 20 differentially expressed m rnas were obtained.In conclusion, the proposed ieas system could mine and analyze the gene expression data.Dasatinib showed good efficacy in the treatment of patients with advanced cml.Besides, it could improve visual queries, and data mining had a broad application prospect in clinical application.Dasatinib was considered to be a good option for patients with advanced cml.

Journal: Applied Bionics and Biomechanics (2022)
Publication types: Research Article;
Traditional Chinese Medicine Treatment and Sports Rehabilitation of Sports Dance Athlete’s Waist Injury

The issue of sports injury and rehabilitation has been a hot topic in competitive sports.With the continuous development of sports dance sports requirements and competition system, the competition is becoming increasingly fierce and the special technical requirements are more stringent; it can easily cause eye damage.Traditional chinese medicine clinics often use chinese medicine internal treatment, external chinese medicine, acupuncture, massage, cupping, scraping, exercise, and other treatment methods to treat waist injuries, which have the characteristics of significant curative effect, small side effects, and being not easy to relapse.It plays an important role in the recovery and treatment of athletes, allowing athletes to better repair, reduce physical discomfort, and achieve better results.The increase in training difficulty and intensity leads to more frequent sports injuries, so the recovery of athletes after injury is particularly important.Based on the above background, the purpose of this article was to study the traditional chinese and western medical treatment and sports rehabilitation for waist injuries of sports dance athletes.This article analyzes the technical problems existing in the training process of sports dance athletes from the perspective of sports training, and analyzes the nature of sports dance athletes’ waist injuries and the causes of injuries.In this article, 45 sports dance athletes were randomly divided into three groups: traditional chinese medicine and western medicine, traditional chinese medicine, and western medicine.Patients treated with the optimized combination of traditional chinese and western medicine were regarded as the traditional chinese and western medicine group.The clinical symptoms, limb circumference, waist function rehabilitation, and overall efficacy of the three groups were observed.At the same time, changes in physical examination indicators before and after treatment were observed to evaluate the safety of the treatment.The experimental results showed that the total effective rate of the chinese and western medicine group was 95%, the total effective rate of the chinese medicine group was 84%, and the total effective rate of the western medicine group was 90%.The symptoms and waist injuries of the three groups were improved to varying degrees.The results of this experiment provide a reference for protecting the physical health and scientific training of athletes, and also provide training ideas and methods for coaches and scientific and medical personnel.

Journal: Contrast Media & Molecular Imaging (2022)
Publication types: Clinical Study;