期刊文献+
共找到119,003篇文章
< 1 2 250 >
每页显示 20 50 100
Improving the Selection Model of Essential Medicines in China by Evidence-based Thinking
1
作者 Sun Huanzheng Fan Jianing +1 位作者 Dong Li Sun Lihua 《Asian Journal of Social Pharmacy》 2024年第2期99-105,共7页
Objective To sort out the problems in the selection model of essential medicines in China,and to put forward some suggestions to optimize the selection model to ensure the rationality of the medicines in the essential... Objective To sort out the problems in the selection model of essential medicines in China,and to put forward some suggestions to optimize the selection model to ensure the rationality of the medicines in the essential medicines list.Methods The domestic and foreign literature on the selection of essential medicines was reviewed.Then,the opinions on the selection methods and results of essential medicines from foreign literature were investigated to make a comparison with the selection of essential medicines in China.Finally,the general and special laws of the selection process of the essential medicines were explored.Results and Conclusion It is recommended that the selection model of essential medicines in China should be further optimized,and the evidence-based thinking and methods should be utilized to enhance the scientific nature of the selection process. 展开更多
关键词 essential medicine evidence-based thinking comparative study
下载PDF
Factors influencing the continuity of evidence-based practice in perioperative airway management for elderly patients with fractures:A qualitative study
2
作者 Jia Zeng Jia Zhang +5 位作者 Rui Li Zhi-Heng Guo Fang Wu Si-Meng Wang Hai-Yue Zhang Fei-Hu Qian 《World Journal of Clinical Cases》 SCIE 2024年第22期5032-5041,共10页
BACKGROUND More and more evidence-based practices are emerging,but researchers mostly focus on short-term effects,resulting in evidence-based practices not being applied in the clinic in the long term.In this study,we... BACKGROUND More and more evidence-based practices are emerging,but researchers mostly focus on short-term effects,resulting in evidence-based practices not being applied in the clinic in the long term.In this study,we took the evidence-based practice of perioperative airway management in elderly fracture patients as an example and adopted a descriptive phenomenological approach to understand the influencing factors of its sustainability to provide a reference basis for promoting the continuity of evidence-based practice in the clinic.AIM To explore factors influencing the persistence of evidence-based practice in perioperative airway management in elderly patients with fractures.METHODS This study was qualitative research.Nine nurses who implemented evidencebased practice in the orthopedic ward of a tertiary comprehensive hospital in Shanghai from September 2023 to October 2023 were selected using purposive sampling as research subjects.Semi-structured interviews were conducted with them,and the data were analyzed using the Colaizzi phenomenological analysis method based on the three dimensions and ten factors of the NHS sustainability model.RESULTS Three main themes and ten subthemes were identified:Process aspects(benefits to patients,benefits to nurses,lack of follow-up,complex processes);staff aspects(insufficient human resources,inadequate training and education,lack of leadership support);and organizational environment aspects(inadequate infrastructure,poor patient compliance,poor doctor cooperation).CONCLUSION Human resources,training and education,leadership support,infrastructure,and patient-physician collaboration are important factors influencing the sustainability of evidence-based practice for perioperative airway management in older patients with fractures. 展开更多
关键词 ELDERLY FRACTURE Airway management evidence-based practice SUSTAINABILITY Sustainability model
下载PDF
A Portfolio Selection Method Based on Pattern Matching with Dual Information of Direction and Distance
3
作者 Xinyi He 《Applied Mathematics》 2024年第5期313-330,共18页
Pattern matching method is one of the classic classifications of existing online portfolio selection strategies. This article aims to study the key aspects of this method—measurement of similarity and selection of si... Pattern matching method is one of the classic classifications of existing online portfolio selection strategies. This article aims to study the key aspects of this method—measurement of similarity and selection of similarity sets, and proposes a Portfolio Selection Method based on Pattern Matching with Dual Information of Direction and Distance (PMDI). By studying different combination methods of indicators such as Euclidean distance, Chebyshev distance, and correlation coefficient, important information such as direction and distance in stock historical price information is extracted, thereby filtering out the similarity set required for pattern matching based investment portfolio selection algorithms. A large number of experiments conducted on two datasets of real stock markets have shown that PMDI outperforms other algorithms in balancing income and risk. Therefore, it is suitable for the financial environment in the real world. 展开更多
关键词 Online Portfolio selection Pattern Matching Similarity Measurement
下载PDF
A Heuristic Radiomics Feature Selection Method Based on Frequency Iteration and Multi-Supervised Training Mode
4
作者 Zhigao Zeng Aoting Tang +2 位作者 Shengqiu Yi Xinpan Yuan Yanhui Zhu 《Computers, Materials & Continua》 SCIE EI 2024年第5期2277-2293,共17页
Radiomics is a non-invasive method for extracting quantitative and higher-dimensional features from medical images for diagnosis.It has received great attention due to its huge application prospects in recent years.We... Radiomics is a non-invasive method for extracting quantitative and higher-dimensional features from medical images for diagnosis.It has received great attention due to its huge application prospects in recent years.We can know that the number of features selected by the existing radiomics feature selectionmethods is basically about ten.In this paper,a heuristic feature selection method based on frequency iteration and multiple supervised training mode is proposed.Based on the combination between features,it decomposes all features layer by layer to select the optimal features for each layer,then fuses the optimal features to form a local optimal group layer by layer and iterates to the global optimal combination finally.Compared with the currentmethod with the best prediction performance in the three data sets,thismethod proposed in this paper can reduce the number of features fromabout ten to about three without losing classification accuracy and even significantly improving classification accuracy.The proposed method has better interpretability and generalization ability,which gives it great potential in the feature selection of radiomics. 展开更多
关键词 Radiomics feature selection machine learning METAHEURISTIC
下载PDF
Evidence-based orthobiologic practice:Current evidence review and future directions
5
作者 Madhan Jeyaraman Naveen Jeyaraman +2 位作者 Swaminathan Ramasubramanian Sangeetha Balaji Sathish Muthu 《World Journal of Orthopedics》 2024年第10期908-917,共10页
The field of orthopedic and regenerative medicine is rapidly evolving with the increasing utilization of orthobiologic.These biologically derived therapies,inc-luding platelet-rich plasma,mesenchymal stem cells,bone m... The field of orthopedic and regenerative medicine is rapidly evolving with the increasing utilization of orthobiologic.These biologically derived therapies,inc-luding platelet-rich plasma,mesenchymal stem cells,bone marrow aspirate con-centrate,stromal vascular fraction(SVF),and autologous chondrocyte implanta-tion,are gaining traction for their potential to enhance the body's natural healing processes.They offer a promising alternative to traditional surgical interventions for musculoskeletal injuries and degenerative conditions.Current evidence su-ggests significant benefits of orthobiologics in treating conditions like osteoarth-ritis,tendon injuries,and spinal disorders,yet inconsistencies in treatment pro-tocols and outcomes persist.The global market for orthobiologics is projected to grow substantially,driven by advancements in biologic therapies such as adipose-derived stem cells and SVF,and the demand for minimally invasive treatments.Despite their promise,regulatory and ethical challenges,as well as the need for high-quality,standardized research,remain significant obstacles.Future dire-ctions in the field include advancements in delivery systems,personalized medi-cine approaches,and the exploration of novel sources like induced pluripotent stem cells,aiming for more targeted and effective treatments.Collaborative efforts are crucial to overcoming these challenges and ensuring the safe and effective application of orthobiologics in clinical practice. 展开更多
关键词 Orthobiologics Platelet-rich plasma Stem cells Musculoskeletal regeneration Regenerative medicine evidence-based medicine
下载PDF
Effect of cetuximab plus FOLFOX4 regimen on clinical outcomes in advanced gastric carcinoma patients receiving evidence-based care
6
作者 Hui Ying Ren-Jun Huang +2 位作者 Xiao-Min Jing Yan Li Qun-Qiu Tong 《World Journal of Clinical Cases》 SCIE 2024年第18期3360-3367,共8页
BACKGROUND Although chemotherapy is effective for treating advanced gastric carcinoma(aGC),it may lead to an adverse prognosis.Establishing a highly effective and low-toxicity chemotherapy regimen is necessary for imp... BACKGROUND Although chemotherapy is effective for treating advanced gastric carcinoma(aGC),it may lead to an adverse prognosis.Establishing a highly effective and low-toxicity chemotherapy regimen is necessary for improving efficacy and outcomes in aGC patients.AIM To determine the efficacy and safety of cetuximab(CET)combined with the FOLFOX4 regimen(infusional fluorouracil,folinic acid,and oxaliplatin)as firstline therapy for patients with aGC,who received evidence-based care(EBC).METHODS A total of 117 aGC patients who received EBC from March 2019 to March 2022 were enrolled.Of these,60 in the research group(RG)received CET+FOLFOX4 as first-line therapy,whereas 57 in the control group(CG)received FOLFOX4.The efficacy[clinical response rate(RR)and disease control rate(DCR)],safety(liver and kidney dysfunction,leukopenia,thrombocytopenia,rash,and diarrhea),serum tumor marker expression[STMs;carbohydrate antigen(CA)19-9,CA72-4,and carcinoembryonic antigen(CEA)],inflammatory indicators[interleukin(IL)-2 and IL-10],and quality of life(QOL)of the two groups were compared.RESULTS A markedly higher RR and DCR were observed in the RG compared with the CG,with an equivalent safety profile between the two groups.RG exhibited notably reduced CA19-9,CA72-4,CEA,and IL-2 levels following treatment,which were lower than the pre-treatment levels and those in the CG.Post-treatment IL-10 was statistically increased in RG,higher than the pre-treatment level and the CG.Moreover,a significantly improved QOL was evident in the RG.CONCLUSION The CET+FOLFOX4 regimen is highly effective as first-line treatment for aGC patients receiving EBC.It facilitates the suppression of STMs,ameliorates the serum inflammatory microenvironment,and enhances QOL,without increased adverse drug effects. 展开更多
关键词 CETUXIMAB FOLFOX4 regimen evidence-based care Advanced gastric carcinoma Efficacy and safety
下载PDF
Analysis of environmental selection pressure of superoxide dismutase in deep-sea sea cucumber
7
作者 Yanan LI Zongfu CHEN +3 位作者 Haibin ZHANG Ruoyu LIU Shuichun CHEN Li LIN 《Journal of Oceanology and Limnology》 SCIE CAS CSCD 2024年第3期893-904,共12页
Manganese superoxide dismutase(MnSOD)is an antioxidant that exists in mitochondria and can effectively remove superoxide anions in mitochondria.In a dark,high-pressure,and low-temperature deep-sea environment,MnSOD is... Manganese superoxide dismutase(MnSOD)is an antioxidant that exists in mitochondria and can effectively remove superoxide anions in mitochondria.In a dark,high-pressure,and low-temperature deep-sea environment,MnSOD is essential for the survival of sea cucumbers.Six MnSODs were identified from the transcriptomes of deep and shallow-sea sea cucumbers.To explore their environmental adaptation mechanism,we conducted environmental selection pressure analysis through the branching site model of PAML software.We obtained night positive selection sites,and two of them were significant(97F→H,134K→V):97F→H located in a highly conservative characteristic sequence,and its polarity c hange might have a great impact on the function of MnSOD;134K→V had a change in piezophilic a bility,which might help MnSOD adapt to the environment of high hydrostatic pressure in the deepsea.To further study the effect of these two positive selection sites on MnSOD,we predicted the point mutations of F97H and K134V on shallow-sea sea cucumber by using MAESTROweb and PyMOL.Results show that 97F→H,134K→V might improve MnSOD’s efficiency of scavenging superoxide a nion and its ability to resist high hydrostatic pressure by moderately reducing its stability.The above results indicated that MnSODs of deep-sea sea cucumber adapted to deep-sea environments through their amino acid changes in polarity,piezophilic behavior,and local stability.This study revealed the correlation between MnSOD and extreme environment,and will help improve our understanding of the organism’s adaptation mechanisms in deep sea. 展开更多
关键词 HOLOTHUROIDEA environmental adaptation positive selection point mutation
下载PDF
A Pricing-Based Cooperative Relay Selection Scheme for Reliable Communications
8
作者 Xiao Yulong Wu Yu +2 位作者 Amr Tolba Chen Ziqiang Li Tengfei 《China Communications》 SCIE CSCD 2024年第8期30-44,共15页
With the rapid development and application of energy harvesting technology,it has become a prominent research area due to its significant benefits in terms of green environmental protection,convenience,and high safety... With the rapid development and application of energy harvesting technology,it has become a prominent research area due to its significant benefits in terms of green environmental protection,convenience,and high safety and efficiency.However,the uneven energy collection and consumption among IoT devices at varying distances may lead to resource imbalance within energy harvesting networks,thereby resulting in low energy transmission efficiency.To enhance the energy transmission efficiency of IoT devices in energy harvesting,this paper focuses on the utilization of collaborative communication,along with pricing-based incentive mechanisms and auction strategies.We propose a dynamic relay selection scheme,including a ladder pricing mechanism based on energy level and a Kuhn-Munkre Algorithm based on an auction theory employing a negotiation mechanism,to encourage more IoT devices to participate in the collaboration process.Simulation results demonstrate that the proposed algorithm outperforms traditional algorithms in terms of improving the energy efficiency of the system. 展开更多
关键词 cooperative communication edge net-work energy harvesting relay selection
下载PDF
Evaluating the performance of genomic selection on purebred population by incorporating crossbred data in pigs
9
作者 Jun Zhou Qing Lin +10 位作者 Xueyan Feng Duanyang Ren Jinyan Teng Xibo Wu Dan Wu Xiaoke Zhang Xiaolong Yuan Zanmou Chen Jiaqi Li Zhe Zhang Hao Zhang 《Journal of Integrative Agriculture》 SCIE CAS CSCD 2024年第2期639-648,共10页
Genomic selection(GS)has been widely used in livestock,which greatly accelerated the genetic progress of complex traits.The population size was one of the significant factors affecting the prediction accuracy,while it... Genomic selection(GS)has been widely used in livestock,which greatly accelerated the genetic progress of complex traits.The population size was one of the significant factors affecting the prediction accuracy,while it was limited by the purebred population.Compared to directly combining two uncorrelated purebred populations to extend the reference population size,it might be more meaningful to incorporate the correlated crossbreds into reference population for genomic prediction.In this study,we simulated purebred offspring(PAS and PBS)and crossbred offspring(CAB)base on real genotype data of two base purebred populations(PA and PB),to evaluate the performance of genomic selection on purebred while incorporating crossbred information.The results showed that selecting key crossbred individuals via maximizing the expected genetic relationship(REL)was better than the other methods(individuals closet or farthest to the purebred population,CP/FP)in term of the prediction accuracy.Furthermore,the prediction accuracy of reference populations combining PA and CAB was significantly better only based on PA,which was similar to combine PA and PAS.Moreover,the rank correlation between the multiple of the increased relationship(MIR)and reliability improvement was 0.60-0.70.But for individuals with low correlation(Cor(Pi,PA or B),the reliability improvement was significantly lower than other individuals.Our findings suggested that incorporating crossbred into purebred population could improve the performance of genetic prediction compared with using the purebred population only.The genetic relationship between purebred and crossbred population is a key factor determining the increased reliability while incorporating crossbred population in the genomic prediction on pure bred individuals. 展开更多
关键词 PIGS crossbred population genomic selection reference population construction relationship
下载PDF
Multi-Strategy Assisted Multi-Objective Whale Optimization Algorithm for Feature Selection
10
作者 Deng Yang Chong Zhou +2 位作者 Xuemeng Wei Zhikun Chen Zheng Zhang 《Computer Modeling in Engineering & Sciences》 SCIE EI 2024年第8期1563-1593,共31页
In classification problems,datasets often contain a large amount of features,but not all of them are relevant for accurate classification.In fact,irrelevant features may even hinder classification accuracy.Feature sel... In classification problems,datasets often contain a large amount of features,but not all of them are relevant for accurate classification.In fact,irrelevant features may even hinder classification accuracy.Feature selection aims to alleviate this issue by minimizing the number of features in the subset while simultaneously minimizing the classification error rate.Single-objective optimization approaches employ an evaluation function designed as an aggregate function with a parameter,but the results obtained depend on the value of the parameter.To eliminate this parameter’s influence,the problem can be reformulated as a multi-objective optimization problem.The Whale Optimization Algorithm(WOA)is widely used in optimization problems because of its simplicity and easy implementation.In this paper,we propose a multi-strategy assisted multi-objective WOA(MSMOWOA)to address feature selection.To enhance the algorithm’s search ability,we integrate multiple strategies such as Levy flight,Grey Wolf Optimizer,and adaptive mutation into it.Additionally,we utilize an external repository to store non-dominant solution sets and grid technology is used to maintain diversity.Results on fourteen University of California Irvine(UCI)datasets demonstrate that our proposed method effectively removes redundant features and improves classification performance.The source code can be accessed from the website:https://github.com/zc0315/MSMOWOA. 展开更多
关键词 Multi-objective optimization whale optimization algorithm multi-strategy feature selection
下载PDF
A Feature Selection Method Based on Hybrid Dung Beetle Optimization Algorithm and Slap Swarm Algorithm
11
作者 Wei Liu Tengteng Ren 《Computers, Materials & Continua》 SCIE EI 2024年第8期2979-3000,共22页
Feature Selection(FS)is a key pre-processing step in pattern recognition and data mining tasks,which can effectively avoid the impact of irrelevant and redundant features on the performance of classification models.In... Feature Selection(FS)is a key pre-processing step in pattern recognition and data mining tasks,which can effectively avoid the impact of irrelevant and redundant features on the performance of classification models.In recent years,meta-heuristic algorithms have been widely used in FS problems,so a Hybrid Binary Chaotic Salp Swarm Dung Beetle Optimization(HBCSSDBO)algorithm is proposed in this paper to improve the effect of FS.In this hybrid algorithm,the original continuous optimization algorithm is converted into binary form by the S-type transfer function and applied to the FS problem.By combining the K nearest neighbor(KNN)classifier,the comparative experiments for FS are carried out between the proposed method and four advanced meta-heuristic algorithms on 16 UCI(University of California,Irvine)datasets.Seven evaluation metrics such as average adaptation,average prediction accuracy,and average running time are chosen to judge and compare the algorithms.The selected dataset is also discussed by categorizing it into three dimensions:high,medium,and low dimensions.Experimental results show that the HBCSSDBO feature selection method has the ability to obtain a good subset of features while maintaining high classification accuracy,shows better optimization performance.In addition,the results of statistical tests confirm the significant validity of the method. 展开更多
关键词 Feature selection dung beetle optimization KNN transfer function HBCSSDBO
下载PDF
A Federated Learning Framework with Blockchain-Based Auditable Participant Selection
12
作者 Huang Zeng Mingtian Zhang +1 位作者 Tengfei Liu Anjia Yang 《Computers, Materials & Continua》 SCIE EI 2024年第6期5125-5142,共18页
Federated learning is an important distributed model training technique in Internet of Things(IoT),in which participant selection is a key component that plays a role in improving training efficiency and model accurac... Federated learning is an important distributed model training technique in Internet of Things(IoT),in which participant selection is a key component that plays a role in improving training efficiency and model accuracy.This module enables a central server to select a subset of participants to performmodel training based on data and device information.By doing so,selected participants are rewarded and actively perform model training,while participants that are detrimental to training efficiency and model accuracy are excluded.However,in practice,participants may suspect that the central server may have miscalculated and thus not made the selection honestly.This lack of trustworthiness problem,which can demotivate participants,has received little attention.Another problem that has received little attention is the leakage of participants’private information during the selection process.We will therefore propose a federated learning framework with auditable participant selection.It supports smart contracts in selecting a set of suitable participants based on their training loss without compromising the privacy.Considering the possibility of malicious campaigning and impersonation of participants,the framework employs commitment schemes and zero-knowledge proofs to counteract these malicious behaviors.Finally,we analyze the security of the framework and conduct a series of experiments to demonstrate that the framework can effectively improve the efficiency of federated learning. 展开更多
关键词 Federated learning internet of things participant selection blockchain auditability PRIVACY
下载PDF
Selection and application of four QTLs for grain protein content in modern wheat cultivars
13
作者 Zihui Liu Xiangjun Lai +4 位作者 Yijin Chen Peng Zhao Xiaoming Wang Wanquan Ji Shengbao Xu 《Journal of Integrative Agriculture》 SCIE CAS CSCD 2024年第8期2557-2570,共14页
The grain protein content(GPC)is the key parameter for wheat grain nutritional quality.This study conducted a resampling GWAS analysis using 406 wheat accessions across eight environments,and identified four previousl... The grain protein content(GPC)is the key parameter for wheat grain nutritional quality.This study conducted a resampling GWAS analysis using 406 wheat accessions across eight environments,and identified four previously reported GPC QTLs.An analysis of 87 landraces and 259 modern cultivars revealed the loss of superior GPC haplotypes,especially in Chinese cultivars.These haplotypes were preferentially adopted in different agroecological zones and had broad effects on wheat yield and agronomic traits.Most GPC QTLs did not significantly reduce yield,suggesting that high GPC can be achieved without a yield penalty.The results of this study provide a reference for future GPC breeding in wheat using the four identified QTLs. 展开更多
关键词 BREEDING grain protein content haplotype selection and application WHEAT
下载PDF
Multi-Objective Equilibrium Optimizer for Feature Selection in High-Dimensional English Speech Emotion Recognition
14
作者 Liya Yue Pei Hu +1 位作者 Shu-Chuan Chu Jeng-Shyang Pan 《Computers, Materials & Continua》 SCIE EI 2024年第2期1957-1975,共19页
Speech emotion recognition(SER)uses acoustic analysis to find features for emotion recognition and examines variations in voice that are caused by emotions.The number of features acquired with acoustic analysis is ext... Speech emotion recognition(SER)uses acoustic analysis to find features for emotion recognition and examines variations in voice that are caused by emotions.The number of features acquired with acoustic analysis is extremely high,so we introduce a hybrid filter-wrapper feature selection algorithm based on an improved equilibrium optimizer for constructing an emotion recognition system.The proposed algorithm implements multi-objective emotion recognition with the minimum number of selected features and maximum accuracy.First,we use the information gain and Fisher Score to sort the features extracted from signals.Then,we employ a multi-objective ranking method to evaluate these features and assign different importance to them.Features with high rankings have a large probability of being selected.Finally,we propose a repair strategy to address the problem of duplicate solutions in multi-objective feature selection,which can improve the diversity of solutions and avoid falling into local traps.Using random forest and K-nearest neighbor classifiers,four English speech emotion datasets are employed to test the proposed algorithm(MBEO)as well as other multi-objective emotion identification techniques.The results illustrate that it performs well in inverted generational distance,hypervolume,Pareto solutions,and execution time,and MBEO is appropriate for high-dimensional English SER. 展开更多
关键词 Speech emotion recognition filter-wrapper HIGH-DIMENSIONAL feature selection equilibrium optimizer MULTI-OBJECTIVE
下载PDF
Cloud Datacenter Selection Using Service Broker Policies:A Survey
15
作者 Salam Al-E’mari Yousef Sanjalawe +2 位作者 Ahmad Al-Daraiseh Mohammad Bany Taha Mohammad Aladaileh 《Computer Modeling in Engineering & Sciences》 SCIE EI 2024年第4期1-41,共41页
Amid the landscape of Cloud Computing(CC),the Cloud Datacenter(DC)stands as a conglomerate of physical servers,whose performance can be hindered by bottlenecks within the realm of proliferating CC services.A linchpin ... Amid the landscape of Cloud Computing(CC),the Cloud Datacenter(DC)stands as a conglomerate of physical servers,whose performance can be hindered by bottlenecks within the realm of proliferating CC services.A linchpin in CC’s performance,the Cloud Service Broker(CSB),orchestrates DC selection.Failure to adroitly route user requests with suitable DCs transforms the CSB into a bottleneck,endangering service quality.To tackle this,deploying an efficient CSB policy becomes imperative,optimizing DC selection to meet stringent Qualityof-Service(QoS)demands.Amidst numerous CSB policies,their implementation grapples with challenges like costs and availability.This article undertakes a holistic review of diverse CSB policies,concurrently surveying the predicaments confronted by current policies.The foremost objective is to pinpoint research gaps and remedies to invigorate future policy development.Additionally,it extensively clarifies various DC selection methodologies employed in CC,enriching practitioners and researchers alike.Employing synthetic analysis,the article systematically assesses and compares myriad DC selection techniques.These analytical insights equip decision-makers with a pragmatic framework to discern the apt technique for their needs.In summation,this discourse resoundingly underscores the paramount importance of adept CSB policies in DC selection,highlighting the imperative role of efficient CSB policies in optimizing CC performance.By emphasizing the significance of these policies and their modeling implications,the article contributes to both the general modeling discourse and its practical applications in the CC domain. 展开更多
关键词 Cloud computing cloud service broker datacenter selection QUALITY-OF-SERVICE user request
下载PDF
Optimization-based mode selection scheme for OAM millimeter wave system in the off-axis misalignment case
16
作者 Haie Dou Lei Wang +1 位作者 Bin Kang Baoyu Zheng 《Digital Communications and Networks》 SCIE CSCD 2024年第1期101-108,共8页
Millimeter-wave transmission combined with Orbital Angular Momentum(OAM)has the advantage of reducing the loss of beam power and increasing the system capacity.However,to fulfill this advantage,the antennas at the tra... Millimeter-wave transmission combined with Orbital Angular Momentum(OAM)has the advantage of reducing the loss of beam power and increasing the system capacity.However,to fulfill this advantage,the antennas at the transmitter and receiver must be parallel and coaxial;otherwise,the accuracy of mode detection at the receiver can be seriously influenced.In this paper,we design an OAM millimeter-wave communication system for overcoming the above limitation.Specifically,the first contribution is that the power distribution between different OAM modes and the capacity of the system with different mode sets are analytically derived for performance analysis.The second contribution lies in that a novel mode selection scheme is proposed to reduce the total interference between different modes.Numerical results show that system performance is less affected by the offset when the mode set with smaller modes or larger intervals is selected. 展开更多
关键词 Orbital angular momentum Millimeter wave Off-axis misalignment Mode selection Capacity
下载PDF
A Support Data-Based Core-Set Selection Method for Signal Recognition
17
作者 Yang Ying Zhu Lidong Cao Changjie 《China Communications》 SCIE CSCD 2024年第4期151-162,共12页
In recent years,deep learning-based signal recognition technology has gained attention and emerged as an important approach for safeguarding the electromagnetic environment.However,training deep learning-based classif... In recent years,deep learning-based signal recognition technology has gained attention and emerged as an important approach for safeguarding the electromagnetic environment.However,training deep learning-based classifiers on large signal datasets with redundant samples requires significant memory and high costs.This paper proposes a support databased core-set selection method(SD)for signal recognition,aiming to screen a representative subset that approximates the large signal dataset.Specifically,this subset can be identified by employing the labeled information during the early stages of model training,as some training samples are labeled as supporting data frequently.This support data is crucial for model training and can be found using a border sample selector.Simulation results demonstrate that the SD method minimizes the impact on model recognition performance while reducing the dataset size,and outperforms five other state-of-the-art core-set selection methods when the fraction of training sample kept is less than or equal to 0.3 on the RML2016.04C dataset or 0.5 on the RML22 dataset.The SD method is particularly helpful for signal recognition tasks with limited memory and computing resources. 展开更多
关键词 core-set selection deep learning model training signal recognition support data
下载PDF
On Performance Characteristics of a Nonparametric Subset Selection Procedure with a Small Randomized Block Experimental Design
18
作者 Gary C. McDonald Sajidah Alsaeed 《Applied Mathematics》 2024年第9期630-650,共21页
This article addresses the issue of computing the constant required to implement a specific nonparametric subset selection procedure based on ranks of data arising in a statistical randomized block experimental design... This article addresses the issue of computing the constant required to implement a specific nonparametric subset selection procedure based on ranks of data arising in a statistical randomized block experimental design. A model of three populations and two blocks is used to compute the probability distribution of the relevant statistic, the maximum of the population rank sums minus the rank sum of the “best” population. Calculations are done for populations following a normal distribution, and for populations following a bi-uniform distribution. The least favorable configuration in these cases is shown to arise when all three populations follow identical distributions. The bi-uniform distribution leads to an asymptotic counterexample to the conjecture that the least favorable configuration, i.e., that configuration minimizing the probability of a correct selection, occurs when all populations are identically distributed. These results are consistent with other large-scale simulation studies. All relevant computational R-codes are provided in appendices. 展开更多
关键词 Rank Statistics Least Favorable Configuration Probability of Correct selection Slippage Configuration Equal Spaced Configuration Counterexample Configuration
下载PDF
Multi-Binary Classifiers Using Optimal Feature Selection for Memory-Saving Intrusion Detection Systems
19
作者 Ye-Seul Kil Yu-Ran Jeon +1 位作者 Sun-Jin Lee Il-Gu Lee 《Computer Modeling in Engineering & Sciences》 SCIE EI 2024年第11期1473-1493,共21页
With the rise of remote work and the digital industry,advanced cyberattacks have become more diverse and complex in terms of attack types and characteristics,rendering them difficult to detect with conventional intrus... With the rise of remote work and the digital industry,advanced cyberattacks have become more diverse and complex in terms of attack types and characteristics,rendering them difficult to detect with conventional intrusion detection methods.Signature-based intrusion detection methods can be used to detect attacks;however,they cannot detect new malware.Endpoint detection and response(EDR)tools are attracting attention as a means of detecting attacks on endpoints in real-time to overcome the limitations of signature-based intrusion detection techniques.However,EDR tools are restricted by the continuous generation of unnecessary logs,resulting in poor detection performance and memory efficiency.Machine learning-based intrusion detection techniques for responding to advanced cyberattacks are memory intensive,using numerous features;they lack optimal feature selection for each attack type.To overcome these limitations,this study proposes a memory-efficient intrusion detection approach incorporating multi-binary classifiers using optimal feature selection.The proposed model detects multiple types of malicious attacks using parallel binary classifiers with optimal features for each attack type.The experimental results showed a 2.95%accuracy improvement and an 88.05%memory reduction using only six features compared to a model with 18 features.Furthermore,compared to a conventional multi-classification model with simple feature selection based on permutation importance,the accuracy improved by 11.67%and the memory usage decreased by 44.87%.The proposed scheme demonstrates that effective intrusion detection is achievable with minimal features,making it suitable for memory-limited mobile and Internet of Things devices. 展开更多
关键词 Endpoint detection and response feature selection machine learning malware detection
下载PDF
The suitability assessment on site selection for bottom seeding scallop culture based on analytic hierarchy process
20
作者 Ziniu ZHANG Zhenyan WANG +2 位作者 Guihua LI Meihan ZHAO Wenjian LI 《Journal of Oceanology and Limnology》 SCIE CAS CSCD 2024年第2期647-663,共17页
Scallop culture is an important way of bottom-seeding marine ranching,which is of great significance to improve the current situation of fishery resources.However,there are some problems in site-selection evaluation o... Scallop culture is an important way of bottom-seeding marine ranching,which is of great significance to improve the current situation of fishery resources.However,there are some problems in site-selection evaluation of marine ranching,such as imperfect criteria system,complex structure,untargeted criteria quantification,etc.In addition,no site-selection evaluation method of bottom-seeding culture areas for scallops is available.Therefore,we established a hierarchy structure model according to the analytic hierarchy process(AHP)theory,in which social,physical,chemical,and biological environments are used as main criteria,and marine functional zonation,water depth,current,water temperature,salinity,substrate type,water quality,sediment quality,red tide,phytoplankton,and zooplankton are used as sub-criteria,on which a multi-parameter evaluation system is set up.Meanwhile,the dualism method,assignment method,and membership function method were used to quantify sub-criteria,and a quantitative evaluation for the entire criteria was added,including the evaluation and analysis of two types of unsuitable environmental situations.By overall consideration in scallop yield,quality,and marine ranching construction objectives,the weight of the main criteria could be determined.Five grades in the suitability corresponding to the evaluation result were divided,and the Python language was used to create an evaluation system for efficient calculation and intuitive presentation of the evaluation outcome.Eight marine cases were simulated based on existing survey data,and the results prove that the method is feasible for evaluating and analyzing the site selection of bottom-seeding culture areas for scallops under various environmental situations.The proposed evaluation method can be promoted for the site selection of bottom-seeding marine ranching.This study provided theoretical and methodological references for the site selection evaluation of other types of marine ranching. 展开更多
关键词 marine ranching bottom-seeding scallops site selection evaluation analytic hierarchy process evaluation system
下载PDF
上一页 1 2 250 下一页 到第
使用帮助 返回顶部