syedzayyan/paper_mill_benchmark huggingface dataset:
Clinical Observation of Low-Temperature Plasma Knife Tonsil Adenoidectomy for Pediatric Snoring and Analysis of Influencing Factors

To investigate the clinical efficacy of low-temperature plasma knife tonsil adenoidectomy for pediatric snoring and to analyze the factors influencing the efficacy.Methods.90 children with snoring who were scheduled for surgical treatment in our hospital from june 2020 to december 2021 were selected as the research objects.According to the random number table method, they were divided into control group (group c) and observation group (group o), with 45 cases in each group.The children in group c were treated with power cutting system to remove adenoids combined with conventional peeling of bilateral tonsils, while the children in group o were treated with low-temperature plasma adenoidectomy combined with bilateral tonsillectomy, and both the groups received psychological care, preoperative preparation, health guidance, postoperative posture care and close monitoring of vital signs during the perioperative period.The clinical efficacy, perioperative related indexes (including operation time, intraoperative bleeding, postoperative pain time, and hospital stay) were compared between the two groups.The apnea-hypopnea index (ahi), oxygen decrement index (odi), longest apnea time (lat), and lowest oxygen saturation (lsa o2) were measured before operation and 1 week after operation to evaluate the ventilatory function of the two groups.According to the curative effect, 90 children with snoring were divided into cure + significant effective group and valid + invalid group.The general data and preoperative biochemical indexes of the two groups were collected, and logistic regression model was used to analyze the related influencing factors of the curative effect.Results.The total effective rate of group o (100.00%, 45 cases) was significantly higher than that of group c (91.11%, 41 cases) (p &lt; 0.05); the operative time, intraoperative bleeding, postoperative pain time, and hospitalization time of group o were shorter/less than those of group c; the ahi, odi, and lat of group o at 1 week after surgery were shorter/less than those of the control group; and lsa o2 was higher than that of group c.The differences were statistically significant (p &lt; 0.05).Univariate analysis showed that there were significant differences in age, bmi, course of disease, preoperative ahi, preoperative lsa o2, and surgical method between cure + significant effective group and valid + invalid group (p &lt; 0.05).Multivariate analysis showed that high bmi, high preoperative ahi, and power cutting system for adenoids combined with routine peeling of the bilateral tonsils were independent risk factors for postoperative outcome in children with obstructive sleep apnea syndrome (osas) (p &lt; 0.05).

Journal: Emergency Medicine International (2022)
Publication types: Clinical Study;
To Explore the Haemostatic Effect of Compression Haemostasis Using an Ultrasonic Probe under the Guidance of Ultrasound after Radial Artery Puncture

To evaluate a new haemostasis method using an ultrasound probe to compress the radial artery and haemostasis under direct vision to replace traditional manual compression of the radial artery.Methods.According to a random number table, 240 patients with gastrointestinal tumours who had undergone arterial puncture were divided into group a (120 cases) and group b (120 cases).In group a, patients were under the guidance of ultrasound to confirm the vascular port, determine the compression position of the ultrasound probe, observe the degree of vascular deformation, and press the radial artery puncture port with pressure to stop bleeding under direct vision.In group b, traditional manual compression was used.All patients received 5 min of compression for haemostasis, and haemostasis conditions were recorded after compression and 24 hours postoperatively.Results.The incidence of bleeding, haematoma, and skin ecchymosis at the puncture site after 5 minutes of compression in group a was lower than that in group b ( p &lt; 0.05 ).No significant difference was found between the two groups at 24 hours after the operation ( p &gt; 0.05 ).Conclusion.The method using an ultrasound probe to guide radial artery compression to haemostasis is better than traditional manual compression when applied for compression haemostasis after removing the radial artery catheter.

Journal: Disease Markers (2021)
Publication types: Clinical Study;
Research on Modern Book Packaging Design under Aesthetic Evaluation Based on Deep Learning Model

The development of information technology has led to the rapid development of modern book packaging design.Book packaging design is different from painting.It is a kind of design process that combines artistry and practicality and has double characteristics.With the continuous progress of society, people’s requirements for book packaging design have become higher and higher, and modern book packaging design has become an important topic in the field of art design.To this end, this paper introduces the machine learning algorithms used in this paper, including the ada boost algorithm and the svr algorithm.Specifically, it includes the principles and specific implementation steps for ada boost classification algorithm and svr regression algorithm, as well as evaluation indexes of ada boost classification and svr regression analysis.Realization of physical books reflects artistry, creativity, professionalism, popularity, and vitality of books in the packaging and design of books in the electronic information era.The stimulation effect of this paper starts from packaging design, inspection mechanism, and brand psychology to get the superior design in modern book packaging design.

Journal: Discrete Dynamics in Nature and Society (2021)
Publication types: Research Article;
Activation of TREK1 Channel in the Anterior Cingulate Cortex Improves Neuropathic Pain in a Rat Model

To explore the biological function and mechanism of trek1 in neuropathic pain.Thirty-two healthy rats and rats with sciatic nerve chronic press-fitting model (chronic constriction injury of the sciatic nerve, cci) were selected.Western blot, immunofluorescence staining, and patch clamp technique were performed to explore the biological functions of trek1.The expression of trek1 was decreased in the cci model.The trek1 channel current in the cci model was decreased.After local administration of trek1 channel activator in the anterior cingulate cortex area, the pain behavior of cci rats and the expression of trek1 protein were reversed.The expression of trek1 was downregulated in the acc area of cci rats and the current of trek1 was decreased, which played an important role in the regulation of neuropathic pain.

Journal: Computational Intelligence and Neuroscience (2022)
Publication types: Research Article;
Enterprise Operating State Evaluation Based on Association Rule Algorithm and Data Set

In order to further improve the evaluation quality of enterprise operating efficiency, reduce the error items and invalid items of partition, and improve the objectivity of operating condition evaluation, this study takes listed enterprises as an example and proposes an evaluation method of operating efficiency based on association rule algorithm and data set.In this method, the results of operating efficiency are scientifically analyzed from horizontal and vertical dimensions.The operating cost of total assets of listed companies is taken as indicators, and the correlation test is carried out by kendall’s tau_b.From the longitudinal comparison results, it can be seen that only 12 of the 19 enterprises in the study have small-scale changes and increase year by year, accounting for 63.16%.At the same time, there are also 6 enterprises with an overall trend of decline, which objectively reflects the reasonable operation status and operation scale of enterprises in the study.

Journal: Computational Intelligence and Neuroscience (2022)
Publication types: Research Article;
Performance Evaluation of Knowledge Sharing in an Industry-University-Research Alliance Based on PSO-BPNN

Knowledge sharing performance is very important to evaluate the interests of industry university research alliance.Firstly, this paper puts forward the index system of knowledge sharing performance evaluation of industry university research alliance.A bp neural network (bpnn) and a pso-improved bp neural network (pso-bpnn) are used to establish the evaluation model, and the accuracy of the model is evaluated.The prediction accuracy is evaluated by comparing the predicted value with the target value.Through comparative analysis, it is found that the performance evaluation model based on pso-bp neural network has high accuracy and applicability, and is an effective method of alliance knowledge sharing performance evaluation.

Journal: Computational Intelligence and Neuroscience (2022)
Publication types: Research Article;
Research on the Construction of Crossborder e-Commerce Logistics Service System Based on Machine Learning Algorithms

Based on machine learning algorithms, this paper designs a crossborder e‐commerce logistics service system recommendation algorithm.First, we introduce the meaning of query recommendation, analyze the mechanism of e‐commerce platform shopping search, redesign the query recommendation process on this basis, establish a markov decision process model for the problem, and solve the optimal recommendation strategy through deep machine learning algorithms.Second, we design a simple calculation example, use python programming through a simulated shopping environment, give the solution process of the optimal recommendation strategy in the whole process, and prove the feasibility of the algorithm.The sentiment synthesis word vector is used as the input data structure of the text, the convolutional neural network model and the recurrent neural network model in machine learning are independently designed and constructed, and a shunt is proposed.The rule (shunt) realizes the operation of judging the data and inputting the two machine learning networks.The shunt fully realizes the combination of the advantages of the local feature characterization of the convolutional neural network and the timing characteristics of the recurrent neural network and achieves a more efficient and accurate electrical system.Finally, through simulation experiments, a series of data processing work such as data outlier cleaning, sliding window construction features of data variables, and training set and test set division are designed to convert regression prediction problems into classification problems to predict commodity demand.At the same time, it also compared the effect of the time series model, random forest model, gbdt, single xgboost model, and the model used in this topic and analyzed the reasons for this difference and the application of each model.

Journal: Discrete Dynamics in Nature and Society (2022)
Publication types: Research Article;
Mobile Learning Model of Tour Guide Business in Universities from the Perspective of Distributed Cognition

In order to promote the better development of tour guide business, this article takes the tour guide business teaching in colleges and universities as an example and analyzes the current situation and the effect of students’ learning in the tour guide business course through investigating and researching the current situation of ideological and political teaching of the tour guide business course.It also proposes corresponding improvement measures for the existing problems, so as to improve the ideological and political teaching effect of the tour guide business course.To this end, this study relies on the powerful functions of umu platform and builds a hybrid mobile learning mode based on umu platform by improving the traditional teaching method of “face to face instruction + online lecture.” although the umu-based blended mobile learning model is formally divided into online learning and offline activities, in the actual teaching process, there are both you and me.In the process of online learning, students can realize the convenient learning through mobile app terminal anytime and anywhere, or they can sit comfortably at the study table through the computer; in the offline activity classroom, students can sit in the classroom of umu and communicate with teachers face to face, or they can use their cell phones to project their check-in, opinions, test results, etc.To the big screen.In the whole umu-based hybrid mobile learning model, there is no clear boundary between online learning and offline activities, and online and offline are integrated with each other and crossed according to the actual learning needs to maximize learning efficiency.

Journal: Discrete Dynamics in Nature and Society (2021)
Publication types: Research Article;
Image Segmentation Technology Based on Attention Mechanism and ENet

With the development of today’s society, medical technology is becoming more and more important in people’s daily diagnosis and treatment and the number of computed tomography (ct) images and mri images is also increasing.It is difficult to meet today’s needs for segmentation and recognition of medical images by manpower alone.Therefore, the use of computer technology for automatic segmentation has received extensive attention from researchers.We design a tooth ct image segmentation method combining attention mechanism and enet.First, dilated convolution is used with the spatial information path, with a small downsampling factor to preserve the resolution of the image.Second, an attention mechanism is added to the segmentation network based on ct image features to improve the accuracy of segmentation.Then, the designed feature fusion module obtains the segmentation result of the tooth ct image.It was verified on tooth ct image dataset published by west china hospital, and the average intersection ratio and accuracy were used as the metric.The results show that, on the dataset of west china hospital, mean intersection over union (miou) and accuracy are 83.47% and 95.28%, respectively, which are 3.3% and 8.09% higher than the traditional model.Compared with the multiple watershed algorithm, the chan–vese segmentation algorithm, and the graph cut segmentation algorithm, our algorithm increases the calculation time by 56.52%, 91.52%, and 62.96%, respectively.It can be seen that our algorithm has obvious advantages in miou, accuracy, and calculation time.

Journal: Computational Intelligence and Neuroscience (2022)
Publication types: Research Article;
Artificial Bee Colony Based Gabor Parameters Optimizer (ABC-GPO) for Modulation Classification

Modulation classification is one of the essential requirements in the various cognitive radio applications where prior information about the incoming signal is unknown.The modulation classification using a pattern recognition approach can be achieved in 2 modules: first, parameters are extracted from the noisy signal, and then feature selection is carried out using a gabor filter network (gfn).In the second module, features are exploited for classification purposes.The modulation formats considered for the purpose of classification are bpsk, qpsk, 8psk, 16psk, 64psk, 4fsk, 8fsk, 16fsk, qam, 8qam, 16qam, 32qam, and 64qam.The gabor filter parameters and weights of the adaptive filter are attuned using the delta rule and recursive least square (rls) algorithm until the cost function is minimized.In the end, the artificial bee colony (abc) algorithm is used to optimize the gabor parameters as well as the classifier’s performance.The simulation results show the supremacy of the proposed classifier structure.

Journal: Computational Intelligence and Neuroscience (2022)
Publication types: Research Article;
Optimal Design of International Trade Logistics Based on Internet of Things Technology

With the global industrial integration, trade exchanges between countries are becoming more and more frequent and the competition for related international trade logistics is becoming more and more intense.This paper aims to study the optimization design of international trade logistics based on internet of things technology.For this reason, this paper proposes an rfid method, through which it is possible to master a journey in the actual international trade logistics process.And it optimizes and improves its related paths, shortens the time delayed on the road, and achieves the purpose of mentioning the carrying capacity.And for the actual use effect, the relevant experiments and analysis parts are designed to simulate it.The experimental results of this paper show that the improved and optimized international trade logistics shortens the carrying time by 28.6% and increases the carrying capacity by 34.2%, which greatly promotes the development of the relevant international trade logistics industry.

Journal: Computational Intelligence and Neuroscience (2022)
Publication types: Research Article;
Online Anomaly Detection of Industrial IoT Based on Hybrid Machine Learning Architecture

Industrial io t (iio t) in industry 4.0 integrates everything at the level of information technology with the level of technology of operation and aims to improve business to business (b2b) services (from production to public services).It includes machine to machine (m2m) interaction either for process control (e.g., factory processes, fleet tracking) or as part of self-organizing cyber-physical distributed control systems without human intervention.A critical factor in completing the abovementioned actions is the development of intelligent software systems in the context of automatic control of the business environment, with the ability to analyze in real-time the existing equipment through the available interfaces (hardware-in-the-loop).In this spirit, this paper presents an advanced intelligent approach to real-time monitoring of the operation of industrial equipment.A hybrid novel methodology that combines memory neural networks is used, and bayesian methods that examine a variety of characteristic quantities of vibration signals that are exported in the field of time, with the aim of real-time detection of abnormalities in active iio t equipment are also used.

Journal: Computational Intelligence and Neuroscience (2022)
Publication types: Research Article;
Big Data-Driven Vocational Undergraduate Talent Training and Social Needs Adaptability Analysis and Collaborative Path Mining

Ing at the problem of mismatch between talent cultivation and social demand in the process of undergraduate education, this paper proposes a big data-driven method of adaptability analysis and collaborative path mining between vocational undergraduate talent cultivation and social demand.Starting from the big data-driven vocational undergraduate talent training and social needs, this paper points out the problems existing in the current social needs and puts forward the basic framework of vocational undergraduate talent training mode.Secondly, the clustering model of talent training and social demand is analyzed, and the clustering mining method is proposed.Finally, the big data-driven personnel training and social adaptation mining analysis, in their own ability and social needs adaptability analysis, the basic adaptation accounted for a higher proportion.Professional competence has a higher trust value in cluster analysis.Today’s social employment situation is becoming more and more severe, and how to enhance the quality of profession undergraduate students has become one of the theoretical and practical issues worthy of attention in china’s colleges at this stage.The talent training model of colleges and universities is closely in route with the demands of society, and the problem of student hire is prominent.Therefore, this paper proposes a student employability training program that combines the elements of student employability through social needs research.

Journal: Computational Intelligence and Neuroscience (2022)
Publication types: Research Article;
GIS Multimedia Technology in Regional Construction Land Suitability Evaluation in Mountainous Villages and Towns

In order to explore the suitability evaluation of regional construction land in mountainous villages and towns, a method based on gis technology is proposed.Supported by gis and rs technology, the delphi method is used to determine the natural, socioeconomic, and ecological security factors affecting the ecological suitability of regional construction land in mountainous villages and towns, and analytic hierarchy process is used to calculate the weight of relevant influencing factors.Following the principle of giving priority to ecological protection, a set of ecological suitability evaluation model system and method of regional construction land in mountainous villages and towns are established, based on which the basic ecological control areas of mountainous villages and towns in the study area are divided, so as to provide suggestions for rational and effective planning of land resources in mountainous villages and towns.The experimental results show that the k-means clustering method is divided into five categories: the most suitable land, the more suitable land, the basically suitable land, the unsuitable land, and the unavailable land.Finally, according to the suitability grade system of construction land, it is reclassified, the unsuitable land and unavailable land are divided into basic ecological control areas, the most suitable land and more suitable land are divided into construction control areas, and the basically suitable land is listed as ecological buffer areas.It is proved that the basic ecological control area determined by the model method is basically consistent with the current basic ecological control line of a city, which shows that the model is practical and scientific.

Journal: Computational Intelligence and Neuroscience (2022)
Publication types: Research Article;
Construction of Urban Flood Disaster Emergency Management System Using Scenario Construction Technology

Due to the global climate anomaly, ecological environment damage, human activities, and other reasons, flood disaster has become a major threat to mankind.The emergency rescue resources under different subject management and different emergencies have different characteristics, attributes, and management modes, which restrict the unified dispatching, overall management, and efficient utilization of the comprehensive rescue command platform.The frequent occurrence of natural disasters can not only easily affect the public security of society but also pose a great threat to the safety of chinese people’s lives and property.As the first-line person in charge of china’s response to natural disasters, local governments cannot deal with natural disasters well.More than thousands of people die from natural disasters in china every year.The economic losses caused amounted to hundreds of billions.The occurrence of various floods and natural disasters not only affects the local economic and social development but also relates to the production and life of the local people, and the stability of the local society and national unity.How to effectively deal with flood disaster is also an important index system to test the execution and management ability of the party and the government.Therefore, it is necessary to deeply study flood disaster from the theoretical height, hoping to provide reference theoretical support and practical guidance for local county-level government flood disaster emergency management.At the beginning of the urban flood disaster, how to choose an appropriate response plan and implement it in time is an important way to effectively reduce disaster losses.Starting with the basic concept of flood disaster, this study studies and discusses the related theories of flood disaster emergency management, introduces the general situation of flood disaster emergency management, and analyzes the application of scenario construction technology in emergency management.

Journal: Computational Intelligence and Neuroscience (2023)
Publication types: Research Article;