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Design and Implementation of the Employment Management Decision Support System based on Machine Learning
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作者 Zhigang Ma 《Journal of Electronic Research and Application》 2024年第5期134-140,共7页
To address the challenges of current college student employment management,this study designed and implemented a machine learning-based decision support system for college student employment management.The system coll... To address the challenges of current college student employment management,this study designed and implemented a machine learning-based decision support system for college student employment management.The system collects and analyzes multidimensional data,uses machine learning algorithms for prediction and matching,provides personalized employment guidance for students,and provides decision support for universities and enterprises.The research results indicate that the system can effectively improve the efficiency and accuracy of employment guidance,promote school-enterprise cooperation,and achieve a win-win situation for all parties. 展开更多
关键词 Machine learning Employment of college students decision support system Data analysis
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Applying the Technology Acceptance Model (TAM) in Information Technology System to Evaluate the Adoption of Decision Support System
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作者 Md Azhad Hossain Anamika Tiwari +3 位作者 Sanchita Saha Ashok Ghimire Md Ahsan Ullah Imran Rabeya Khatoon 《Journal of Computer and Communications》 2024年第8期242-256,共15页
With the beginning of the information systems’ spreading, people started thinking about using them for making business decisions. Computer technology solutions, such as the Decision Support System, make the decision-... With the beginning of the information systems’ spreading, people started thinking about using them for making business decisions. Computer technology solutions, such as the Decision Support System, make the decision-making process less complex and simpler for problem-solving. In order to make a high-quality business decision, managers need to have a great deal of appropriate information. Nonetheless, this complicates the process of making appropriate decisions. In a situation like that, the possibility of using DSS is quite logical. The aim of this paper is to find out the intended use of DSS for medium and large business organizations in USA by applying the Technology Acceptance Model (TAM). Different models were developed in order to understand and predict the use of information systems, but the information systems community mostly used TAM to ensure this issue. The purpose of the research model is to determine the elements of analysis that contribute to these results. The sample for the research consisted of the target group that was supposed to have completed an online questionnaire about the manager’s use of DSS in medium and large American companies. The information obtained from the questionnaires was analyzed through the SPSS statistical software. The research has indicated that, this is primarily used due to a significant level of Perceived usefulness and For the Perceived ease of use. 展开更多
关键词 Information Technology decision support System Business Organization in USA Technology Acceptance Model
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Artificial Intelligence Based Meteorological Parameter Forecasting for Optimizing Response of Nuclear Emergency Decision Support System
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作者 BILAL Ahmed Khan HASEEB ur Rehman +5 位作者 QAISAR Nadeem MUHAMMAD Ahmad Naveed Qureshi JAWARIA Ahad MUHAMMAD Naveed Akhtar AMJAD Farooq MASROOR Ahmad 《原子能科学技术》 EI CAS CSCD 北大核心 2024年第10期2068-2076,共9页
This paper presents a novel artificial intelligence (AI) based approach to predict crucial meteorological parameters such as temperature,pressure,and wind speed,typically calculated from computationally intensive weat... This paper presents a novel artificial intelligence (AI) based approach to predict crucial meteorological parameters such as temperature,pressure,and wind speed,typically calculated from computationally intensive weather research and forecasting (WRF) model.Accurate meteorological data is indispensable for simulating the release of radioactive effluents,especially in dispersion modeling for nuclear emergency decision support systems.Simulation of meteorological conditions during nuclear emergencies using the conventional WRF model is very complex and time-consuming.Therefore,a new artificial neural network (ANN) based technique was proposed as a viable alternative for meteorological prediction.A multi-input multi-output neural network was trained using historical site-specific meteorological data to forecast the meteorological parameters.Comprehensive evaluation of this technique was conducted to test its performance in forecasting various parameters including atmospheric pressure,temperature,and wind speed components in both East-West and North-South directions.The performance of developed network was evaluated on an unknown dataset,and acquired results are within the acceptable range for all meteorological parameters.Results show that ANNs possess the capability to forecast meteorological parameters,such as temperature and pressure,at multiple spatial locations within a grid with high accuracy,utilizing input data from a single station.However,accuracy is slightly compromised when predicting wind speed components.Root mean square error (RMSE) was utilized to report the accuracy of predicted results,with values of 1.453℃for temperature,77 Pa for predicted pressure,1.058 m/s for the wind speed of U-component and 0.959 m/s for the wind speed of V-component.In conclusion,this approach offers a precise,efficient,and wellinformed method for administrative decision-making during nuclear emergencies. 展开更多
关键词 prediction of meteorological parameters weather research and forecasting model artificial neural networks nuclear emergency support system
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An Effective Prediction Method for Supporting Decision Making in Real Estate Area Selection
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作者 Haoying Jin Song Yang Mingzhi Zhao 《Journal of Computer and Communications》 2024年第7期105-119,共15页
Real estate has been a dominant industry in many countries. One problem for real estate companies is determining the most valuable area before starting a new project. Previous studies on this issue mainly focused on m... Real estate has been a dominant industry in many countries. One problem for real estate companies is determining the most valuable area before starting a new project. Previous studies on this issue mainly focused on market needs and economic prospects, ignoring the impact of natural disasters. We observe that natural disasters are important for real estate area selection because they will introduce considerable losses to real estate enterprises. Following this observation, we first develop a self-defined new indicator named Average Loss Ratio to predict the losses caused by natural disasters in an area. Then, we adopt the existing ARIMA model to predict the Average Loss Ratio of an area. After that, we propose to integrate the TOPSIS model and the Grey Prediction Model to rank the recommendation levels for candidate areas, thereby assisting real estate companies in their decision-making process. We conduct experiments on real datasets to validate our proposal, and the results suggest the effectiveness of the proposed method. 展开更多
关键词 Real Estate Natural Disaster decision Making Prediction Model
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Automated decision support for Hallux Valgus treatment options using anteroposterior foot radiographs 被引量:2
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作者 Konrad Kwolek Artur Gądek +2 位作者 Kamil Kwolek Radek Kolecki Henryk Liszka 《World Journal of Orthopedics》 2023年第11期800-812,共13页
BACKGROUND Assessment of the potential utility of deep learning with subsequent image analysis to automate the measurement of hallux valgus and intermetatarsal angles from radiographs to serve as a preoperative aid in... BACKGROUND Assessment of the potential utility of deep learning with subsequent image analysis to automate the measurement of hallux valgus and intermetatarsal angles from radiographs to serve as a preoperative aid in establishing hallux valgus severity for clinical decision-making.AIM To investigate the accuracy of automated measurements of angles of hallux valgus from radiographs for further integration with the preoperative planning process.METHODS The data comprises 265 consecutive digital anteroposterior weightbearing foot radiographs.181 radiographs were utilized for training(161)and validating(20)a U-Net neural network to achieve a mean Sørensen–Dice index>97%on bone segmentation.84 test radiographs were used for manual(computer assisted)and automated measurements of hallux valgus severity determined by hallux valgus(HVA)and intermetatarsal angles(IMA).The reliability of manual and computerbased measurements was calculated using the interclass correlation coefficient(ICC)and standard error of measurement(SEM).Inter-and intraobserver reliability coefficients were also compared.An operative treatment recommendation was then applied to compare results between automated and manual angle measurements.RESULTS Very high reliability was achieved for HVA and IMA between the manual measurements of three independent clinicians.For HVA,the ICC between manual measurements was 0.96-0.99.For IMA,ICC was 0.78-0.95.Comparing manual against automated computer measurement,the reliability was high as well.For HVA,absolute agreement ICC and consistency ICC were 0.97,and SEM was 0.32.For IMA,absolute agreement ICC was 0.75,consistency ICC was 0.89,and SEM was 0.21.Additionally,a strong correlation(0.80)was observed between our approach and traditional clinical adjudication for preoperative planning of hallux valgus,according to an operative treatment algorithm proposed by EFORT.CONCLUSION The proposed automated,artificial intelligence assisted determination of hallux valgus angles based on deep learning holds great potential as an accurate and efficient tool,with comparable accuracy to manual measurements by expert clinicians.Our approach can be effectively implemented in clinical practice to determine the angles of hallux valgus from radiographs,classify the deformity severity,streamline preoperative decision-making prior to corrective surgery. 展开更多
关键词 Computer-aided diagnosis Artificial intelligence in orthopedics Automated preoperative decision support Deep learning Medical imaging
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A behavior and physiology-based decision support tool to predict thermal comfort and stress in non-pregnant,mid-gestation,and late-gestation sows
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作者 Betty R.McConn Allan P.Schinckel +4 位作者 Lindsey Robbins Brianna N.Gaskill Angela R.Green‑Miller Donald C.Lay Jr Jay S.Johnson 《Journal of Animal Science and Biotechnology》 SCIE CAS CSCD 2023年第2期814-826,共13页
Background:Although thermal indices have been proposed for swine,none to our knowledge differentiate by reproductive stage or predict thermal comfort using behavioral and physiological data.The study objective was to ... Background:Although thermal indices have been proposed for swine,none to our knowledge differentiate by reproductive stage or predict thermal comfort using behavioral and physiological data.The study objective was to develop a behavior and physiology-based decision support tool to predict thermal comfort and stress in multiparous(3.28±0.81)non-pregnant(n=11),mid-gestation(n=13),and late-gestation(n=12)sows.Results:Regression analyses were performed using PROC MIXED in SAS 9.4 to determine the optimal environmental indicator[dry bulb temperature(TDB)and dew point]of heat stress(HS)in non-pregnant,mid-gestation,and lategestation sows with respiration rate(RR)and body temperature(TB)successively used as the dependent variable in a cubic function.A linear relationship was observed for skin temperature(T_(S))indicating that TDB rather than the sow HS response impacted T_(S)and so T_(S)was excluded from further analyses.Reproductive stage was significant for all analyses(P<0.05).Heat stress thresholds for each reproductive stage were calculated using the inflections points of RR for mild HS and TB for moderate and severe HS.Mild HS inflection points differed for non-pregnant,mid-gestation,and late gestation sows and occurred at 25.5,25.1,and 24.0℃,respectively.Moderate HS inflection points differed for non-pregnant,mid-gestation,and late gestation sows and occurred at 28.1,27.8,and 25.5℃,respectively.Severe HS inflection points were similar for non-pregnant and mid-gestation sows(32.9℃)but differed for late-gestation sows(30.8℃).These data were integrated with previously collected behavioral thermal preference data to estimate the TDB that non-pregnant,mid-gestation,and late-gestation sows found to be cool(TDB<TDB preference range),comfortable(TDB=TDB preference range),and warm(TDB preference range<TDB<mild HS).Conclusions:The results of this study provide valuable information about thermal comfort and thermal stress thresholds in sows at three reproductive stages.The development of a behavior and physiology-based decision support tool to predict thermal comfort and stress in non-pregnant,mid-gestation,and late-gestation sows is expected to provide swine producers with a more accurate means of managing sow environments. 展开更多
关键词 decision support GESTATION Heat stress Management SOWS Thermal index
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Light-Weighted Decision Support Framework for Selecting Cloud Service Providers
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作者 Abdulmajeed Aljuhani Abdulaziz Alhubaishy +1 位作者 Mohammad Khalid Imam Rahmani Ahmad A.Alzahrani 《Computers, Materials & Continua》 SCIE EI 2023年第2期4293-4317,共25页
Multi-criteria decision making(MCDM)is a technique used to achieve better outcomes for some complex business-related problems,whereby the selection of the best alternative can be made in as many cases as possible.This... Multi-criteria decision making(MCDM)is a technique used to achieve better outcomes for some complex business-related problems,whereby the selection of the best alternative can be made in as many cases as possible.This paper proposes a model,the multi-criteria decision support method,that allows both service providers and consumers to maximize their profits while preserving the best matching process for resource allocation and task scheduling.The increasing number of service providers with different service provision capabilities creates an issue for consumers seeking to select the best service provider.Each consumer seeks a service provider based on various preferences,such as price,service quality,and time to complete the tasks.In the literature,the problem is viewed from different perspectives,such as investigating how to enhance task scheduling and the resource allocation process,improve consumers’trust,and deal with network problems.This paper offers a novel model that considers the preferences of both service providers and consumers to find the best available service provider for each consumer.First,the model adopts the best-worst method(BWM)to gather and prioritize tasks based on consumers’and service providers’preferences.Then,the model calculates and matches similarities between the sets of tasks from the consumer’s side with the sets of tasks from the provider’s side to select the best service provider for each consumer using the two proposed algorithms.The complexity of the two algorithms is found to be O(n3). 展开更多
关键词 Best worst method BWM cloud service provider decision support methods
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An Intelligent Decision Support System for Lung Cancer Diagnosis
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作者 Ahmed A.Alsheikhy Yahia F.Said Tawfeeq Shawly 《Computer Systems Science & Engineering》 SCIE EI 2023年第7期799-817,共19页
Lung cancer is the leading cause of cancer-related death around the globe.The treatment and survival rates among lung cancer patients are significantly impacted by early diagnosis.Most diagnostic techniques can identi... Lung cancer is the leading cause of cancer-related death around the globe.The treatment and survival rates among lung cancer patients are significantly impacted by early diagnosis.Most diagnostic techniques can identify and classify only one type of lung cancer.It is crucial to close this gap with a system that detects all lung cancer types.This paper proposes an intelligent decision support system for this purpose.This system aims to support the quick and early detection and classification of all lung cancer types and subtypes to improve treatment and save lives.Its algorithm uses a Convolutional Neural Network(CNN)tool to perform deep learning and a Random Forest Algorithm(RFA)to help classify the type of cancer present using several extracted features,including histograms and energy.Numerous simulation experiments were conducted on MATLAB,evidencing that this system achieves 98.7%accuracy and over 98%precision and recall.A comparative assessment assessing accuracy,recall,precision,specificity,and F-score between the proposed algorithm and works from the literature shows that the proposed system in this study outperforms existing methods in all considered metrics.This study found that using CNNs and RFAs is highly effective in detecting lung cancer,given the high accuracy,precision,and recall results.These results lead us to believe that bringing this kind of technology to doctors diagnosing lung cancer is critical. 展开更多
关键词 Lung cancer artificial intelligence CNN computer-aid diagnosis HISTOGRAM image segmentation decision support systemv
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Artificial Intelligence Enabled Decision Support System on E-Healthcare Environment
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作者 B.Karthikeyan K.Nithya +1 位作者 Ahmed Alkhayyat Yousif Kerrar Yousif 《Intelligent Automation & Soft Computing》 SCIE 2023年第5期2299-2313,共15页
In today’s digital era,e-healthcare systems exploit digital technologies and telecommunication devices such as mobile devices,computers and the inter-net to provide high-quality healthcare services.E-healthcare decis... In today’s digital era,e-healthcare systems exploit digital technologies and telecommunication devices such as mobile devices,computers and the inter-net to provide high-quality healthcare services.E-healthcare decision support sys-tems have been developed to optimize the healthcare services and enhance a patient’s health.These systems enable rapid access to the specialized healthcare services via reliable information,retrieved from the cases or the patient histories.This phenomenon reduces the time taken by the patients to physically visit the healthcare institutions.In the current research work,a new Shuffled Frog Leap Optimizer with Deep Learning-based Decision Support System(SFLODL-DSS)is designed for the diagnosis of the Cardiovascular Diseases(CVD).The aim of the proposed model is to identify and classify the cardiovascular diseases.The proposed SFLODL-DSS technique primarily incorporates the SFLO-based Feature Selection(SFLO-FS)approach for feature subset election.For the pur-pose of classification,the Autoencoder with Gated Recurrent Unit(AEGRU)model is exploited.Finally,the Bacterial Foraging Optimization(BFO)algorithm is employed tofine-tune the hyperparameters involved in the AEGRU method.To demonstrate the enhanced performance of the proposed SFLODL-DSS technique,a series of simulations was conducted.The simulation outcomes established the superiority of the proposed SFLODL-DSS technique as it achieved the highest accuracy of 98.36%.Thus,the proposed SFLODL-DSS technique can be exploited as a proficient tool in the future for the detection and classification of CVD. 展开更多
关键词 E-HEALTHCARE decision support system cardiovascular disease feature selection deep learning
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Assessing Suitability of Irrigation Scheduling Decision Support Systems for Lowland Rice Farmers in Sub-Saharan Africa—A Review
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作者 Aloysius Mubangizi Joshua Wanyama +1 位作者 Nicholas Kiggundu Prossie Nakawuka 《Agricultural Sciences》 CAS 2023年第2期219-239,共21页
Irrigation in lowland rice production systems in Sub-Saharan Africa (SSA) is mainly based on traditional surface irrigation methods with continuous flooding practices. This irrigation method ends up using a lot more w... Irrigation in lowland rice production systems in Sub-Saharan Africa (SSA) is mainly based on traditional surface irrigation methods with continuous flooding practices. This irrigation method ends up using a lot more water that would have otherwise been used to open more land and be used in other water-requiring sectors. Various studies suggest Alternate Wetting and Drying (AWD) as an alternative practice for water management that reduces water use without significantly affecting yield. However, this practice has not been well adopted by the farmers despite its significant benefits of reduced total water use. Improving the adoption of AWD using irrigation Decision Support Systems (DSSs) helps the farmer on two fronts;to know “how much water to apply” and “when to irrigate”, which is very critical in maximizing productivity. This paper reviews the applicability of DSSs using AWD in lowland rice production systems in Sub-Saharan Africa. 展开更多
关键词 Lowland Rice Irrigation Scheduling Forecasting decision support Systems Rice Production Farmer-Led Irrigation AWD
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Optimizing Vaccine Access: A Web-Based Scheduling System with Geo-Tagging Integration and Decision Support for Local Health Centers
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作者 Jayson Angelo Batoon Keno Cruz Piad 《Open Journal of Applied Sciences》 CAS 2023年第5期720-730,共11页
The system created aims to produce an online vaccination appointment scheduling system with geo-tagging integration and a decision-support mechanism for neighborhood health clinics. With a decision support mechanism t... The system created aims to produce an online vaccination appointment scheduling system with geo-tagging integration and a decision-support mechanism for neighborhood health clinics. With a decision support mechanism that suggests the essential vaccines based on their account details, it is made to meet the unique vaccination needs of each patient. The system includes immunizations that are accessible locally, and patients and midwives can manage their own corresponding information through personal accounts. Viewers of websites can visualize the distribution of vaccines by purok thanks to geotagging. The Agile Scrum Methodology was modified by the researchers for early delivery, change flexibility, and continual system improvement in order to accomplish the study’s main goal. In order to assess the system’s acceptability in terms of functional adequacy, performance efficiency, compatibility, usability, reliability, security, maintainability, and portability, it was designed in accordance with the ISO 25010 Product Software Quality Standards. Following the assessment, the system was given an average total weighted mean score of 4.62, which represents a verbal interpretation of “strongly agree”. This score demonstrates that the evaluators were in agreement that the system met the requirements of ISO 25010 for Product Software Quality Standards. 展开更多
关键词 Online Appointment Scheduling Geotagging decision support VACCINATION Neighborhood Health Clinics
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Progress of clinical decision support systems in stroke nursing care
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作者 Hainan Liu Lina Qi +2 位作者 Jiaojiao Wang Bo Zhao Jiaxin Mu 《Journal of Translational Neuroscience》 2023年第1期7-11,共5页
Stroke is characterized by high incidence,high recurrence,high disability,and high morbidity and mortality in China,resulting in a heavy social and clinical burden.A clinical decision support system,as an intelli-gent... Stroke is characterized by high incidence,high recurrence,high disability,and high morbidity and mortality in China,resulting in a heavy social and clinical burden.A clinical decision support system,as an intelli-gent computer system,can assist nurses in decision-mak-ing to collect information quickly,make the most suitable personalized decisions for patients,and improve nurses’decision-making judgment and quality of care.Promoting the development and application of decision support sys-tems in stroke nursing significantly enhances the nursing staff’s work quality and patients’prognosis.Therefore,this paper reviews the research progress of domestic and international clinical decision support systems in stroke nursing care to provide other researchers with specific research directions for developing and applying decision support systems in stroke nursing care. 展开更多
关键词 clinical decision support systems STROKE nursing care
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Stress-assisted corrosion mechanism of 3Ni steel by using gradient boosting decision tree machining learning method 被引量:2
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作者 Xiaojia Yang Jinghuan Jia +5 位作者 Qing Li Renzheng Zhu Jike Yang Zhiyong Liu Xuequn Cheng Xiaogang Li 《International Journal of Minerals,Metallurgy and Materials》 SCIE EI CAS CSCD 2024年第6期1311-1321,共11页
Traditional 3Ni weathering steel cannot completely meet the requirements for offshore engineering development,resulting in the design of novel 3Ni steel with the addition of microalloy elements such as Mn or Nb for st... Traditional 3Ni weathering steel cannot completely meet the requirements for offshore engineering development,resulting in the design of novel 3Ni steel with the addition of microalloy elements such as Mn or Nb for strength enhancement becoming a trend.The stress-assisted corrosion behavior of a novel designed high-strength 3Ni steel was investigated in the current study using the corrosion big data method.The information on the corrosion process was recorded using the galvanic corrosion current monitoring method.The gradi-ent boosting decision tree(GBDT)machine learning method was used to mine the corrosion mechanism,and the importance of the struc-ture factor was investigated.Field exposure tests were conducted to verify the calculated results using the GBDT method.Results indic-ated that the GBDT method can be effectively used to study the influence of structural factors on the corrosion process of 3Ni steel.Dif-ferent mechanisms for the addition of Mn and Cu to the stress-assisted corrosion of 3Ni steel suggested that Mn and Cu have no obvious effect on the corrosion rate of non-stressed 3Ni steel during the early stage of corrosion.When the corrosion reached a stable state,the in-crease in Mn element content increased the corrosion rate of 3Ni steel,while Cu reduced this rate.In the presence of stress,the increase in Mn element content and Cu addition can inhibit the corrosion process.The corrosion law of outdoor-exposed 3Ni steel is consistent with the law based on corrosion big data technology,verifying the reliability of the big data evaluation method and data prediction model selection. 展开更多
关键词 weathering steel stress-assisted corrosion gradient boosting decision tree machining learning
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Dysfunctional attitudes,social support,negative life events,and depressive symptoms in Chinese adolescents:A moderated mediation model 被引量:2
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作者 Teng-Fei Yu Li Liu +3 位作者 Lu-Ning Shang Fang-Fang Xu Zhi-Min Chen Li-Ju Qian 《World Journal of Psychiatry》 SCIE 2024年第11期1671-1680,共10页
BACKGROUND Depression is a prevalent psychological issue in adolescents that is significantly related to negative life events(NLEs)and dysfunctional attitudes.High levels of social support can significantly buffer NLE... BACKGROUND Depression is a prevalent psychological issue in adolescents that is significantly related to negative life events(NLEs)and dysfunctional attitudes.High levels of social support can significantly buffer NLEs’effect on depression.Currently,there is limited research on how social support moderates the relationship between NLEs,dysfunctional attitudes,and depression in adolescents in China.It is imperative to investigate this moderating effect to mitigate dysfunctional attitudes in adolescent undergoing depressive mood,ultimately enhancing their overall mental health.AIM To investigate the relationship and underlying mechanisms between specific dysfunctional attitudes,social support,and depression among Chinese adolescents.METHODS This is a cross-sectional study which selected five middle schools in Shandong Province for investigation in March 2022.Participants included 795 adolescents(49.87%male,mage=15.15,SD=1.84,age range=11-18 years old).All participants completed the Dysfunctional Attitude Scale,Adolescent Life Event Scale,Beck Depression Inventory,and Social Support Rating Scale.A moderated mediation model was conducted to examine the relationship between specific dysfunctional attitudes,social support,and depression.RESULTS Results indicated that NLEs affected depression through the mediating role of specific dysfunctional attitudes(autonomy attitudesβ=0.21;perfectionismβ=0.25).Moreover,social support was found to moderate the mediating effect between NLEs,specific dysfunctional attitudes,and depressive symptoms(autonomy attitudes b2=-0.08;perfectionism b2=-0.09).CONCLUSION Dysfunctional attitudes mediated and social support moderated the relationship between NLEs and depression.Social support can buffer depression symptoms among adolescents with autonomy attitudes and perfectionism. 展开更多
关键词 DEPRESSION Dysfunctional attitudes Social support Adolescents Moderated mediation model
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Cognitive interference decision method for air defense missile fuze based on reinforcement learning 被引量:1
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作者 Dingkun Huang Xiaopeng Yan +2 位作者 Jian Dai Xinwei Wang Yangtian Liu 《Defence Technology(防务技术)》 SCIE EI CAS CSCD 2024年第2期393-404,共12页
To solve the problem of the low interference success rate of air defense missile radio fuzes due to the unified interference form of the traditional fuze interference system,an interference decision method based Q-lea... To solve the problem of the low interference success rate of air defense missile radio fuzes due to the unified interference form of the traditional fuze interference system,an interference decision method based Q-learning algorithm is proposed.First,dividing the distance between the missile and the target into multiple states to increase the quantity of state spaces.Second,a multidimensional motion space is utilized,and the search range of which changes with the distance of the projectile,to select parameters and minimize the amount of ineffective interference parameters.The interference effect is determined by detecting whether the fuze signal disappears.Finally,a weighted reward function is used to determine the reward value based on the range state,output power,and parameter quantity information of the interference form.The effectiveness of the proposed method in selecting the range of motion space parameters and designing the discrimination degree of the reward function has been verified through offline experiments involving full-range missile rendezvous.The optimal interference form for each distance state has been obtained.Compared with the single-interference decision method,the proposed decision method can effectively improve the success rate of interference. 展开更多
关键词 Cognitive radio Interference decision Radio fuze Reinforcement learning Interference strategy optimization
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Mechanism of high-preload support based on the NPR anchor cable in layered soft rock tunnels 被引量:1
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作者 SUI Qiru HE Manchao +3 位作者 SHI Mengfan TAO Zhigang ZHAO Feifei ZHANG Xiaoyu 《Journal of Mountain Science》 SCIE CSCD 2024年第4期1403-1418,共16页
The control of large deformation problems in layered soft rock tunnels needs to solve urgently.The roof problem is particularly severe among the deformation issues in tunnels.This study first analyzes the asymmetric d... The control of large deformation problems in layered soft rock tunnels needs to solve urgently.The roof problem is particularly severe among the deformation issues in tunnels.This study first analyzes the asymmetric deformation modes in layered soft rock tunnels with large deformations.Subsequently,we construct a mechanical model under ideal conditions for controlling the roof of layered soft rock tunnels through high preload with the support of NPR anchor cables.The prominent roles of long and short NPR anchor cables in the support system are also analyzed.The results indicate the significance of high preload in controlling the roof of layered soft rock tunnels.The short NPR anchor cables effectively improve the integrity of the stratified soft rock layers,while the long NPR anchor cables effectively mobilize the self-bearing capacity of deep-stable rock layers.Finally,the high-preload support method with NPR anchor cables is validated to have a good effect on controlling large deformations in layered soft rock tunnels through field monitoring data. 展开更多
关键词 Tunnel engineering Soft rock High-preload support NPR anchor cables
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Analysis of the interaction between bolt-reinforced rock and surface support in tunnels based on convergence-confinement method 被引量:2
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作者 Zhenyu Sun Dingli Zhang +2 位作者 Qian Fang Yanjuan Hou Nanqi Huangfu 《Journal of Rock Mechanics and Geotechnical Engineering》 SCIE CSCD 2024年第6期1936-1951,共16页
To investigate the interaction of the bolt-reinforced rock and the surface support,an analytical model of the convergence-confinement type is proposed,considering the sequential installation of the fully grouted rockb... To investigate the interaction of the bolt-reinforced rock and the surface support,an analytical model of the convergence-confinement type is proposed,considering the sequential installation of the fully grouted rockbolts and the surface support.The rock mass is assumed to be elastic-brittle-plastic material,obeying the linear Mohr-Coulomb criterion or the non-linear Hoek-Brown criterion.According to the strain states of the tunnel wall at bolt and surface support installation and the relative magnitude between the bolt length and the plastic depth during the whole process,six cases are categorized upon solving the problem.Each case is divided into three stages due to the different effects of the active rockbolts and the passive surface support.The fictitious pressure is introduced to quantify the threedimensional(3D)effect of the tunnel face,and thus,the actual physical location along the tunnel axis of the analytical section can be considered.By using the bolt-rock strain compatibility and the rocksurface support displacement compatibility conditions,the solutions of longitudinal tunnel displacement and the reaction pressure of surface support along the tunnel axis are obtained.The proposed analytical solutions are validated by a series of 3D numerical simulations.Extensive parametric studies are conducted to examine the effect of the typical parameters of rockbolts and surface support on the tunnel displacement and the reaction pressure of the surface support under different rock conditions.The results show that the rockbolts are more effective in controlling the tunnel displacement than the surface support,which should be installed as soon as possible with a suitable length.For tunnels excavated in weak rocks or with restricted displacement control requirements,the surface support should also be installed or closed timely with a certain stiffness.The proposed method provides a convenient alternative approach for the optimization of rockbolts and surface support at the preliminary stage of tunnel design. 展开更多
关键词 Analytical model Longitudinal tunnel displacement Fictitious pressure Active rockbolts Surface support reaction pressure Tunnel design
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Stability analysis of longwall top-coal caving face in extra-thick coal seams based on an innovative numerical hydraulic support model 被引量:1
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作者 Jun Guo Wenbo Huang +7 位作者 Guorui Feng Jinwen Bai Lirong Li Zi Wang Luyang Yu Xiaoze Wen Jie Zhang Wenming Feng 《International Journal of Mining Science and Technology》 SCIE EI CAS CSCD 2024年第4期491-505,共15页
The relationship between support and surrounding rock is of great significance to the control of surrounding rock in mining process.In view of the fact that most of the existing numerical simulation methods construct ... The relationship between support and surrounding rock is of great significance to the control of surrounding rock in mining process.In view of the fact that most of the existing numerical simulation methods construct virtual elements and stress servo control to approximately replace the hydraulic support problem,this paper establishes a new numerical model of hydraulic support with the same working characteristics as the actual hydraulic support by integrating numerical simulation software Rhino,Griddle and FLAC3D,which can realize the simulation of different working conditions.Based on this model,the influence mechanism of the supporting strength of hydraulic support on surrounding rock stress regulation and coal stability in front of the top coal caving face in extra thick coal seam were researched.Firstly,under different support intensity,the abutment pressure of the bearing coal and the coal in front of it presents the “three-stage”evolution characteristics.The influence range of support intensity is 15%–30%.Secondly,1.5 MPa is the upper limit of impact that the support strength can have on the front coal failure area.Thirdly,within a displacement range of 2.76 m from the coal wall,a support strength of1.5 MPa provides optimal control of the horizontal displacement of the coal. 展开更多
关键词 Extremely thick coal seam Fully mechanized top coal caving support strength support-surrounding rock interaction
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Attribute Reduction of Hybrid Decision Information Systems Based on Fuzzy Conditional Information Entropy 被引量:1
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作者 Xiaoqin Ma Jun Wang +1 位作者 Wenchang Yu Qinli Zhang 《Computers, Materials & Continua》 SCIE EI 2024年第5期2063-2083,共21页
The presence of numerous uncertainties in hybrid decision information systems(HDISs)renders attribute reduction a formidable task.Currently available attribute reduction algorithms,including those based on Pawlak attr... The presence of numerous uncertainties in hybrid decision information systems(HDISs)renders attribute reduction a formidable task.Currently available attribute reduction algorithms,including those based on Pawlak attribute importance,Skowron discernibility matrix,and information entropy,struggle to effectively manages multiple uncertainties simultaneously in HDISs like the precise measurement of disparities between nominal attribute values,and attributes with fuzzy boundaries and abnormal values.In order to address the aforementioned issues,this paper delves into the study of attribute reduction withinHDISs.First of all,a novel metric based on the decision attribute is introduced to solve the problem of accurately measuring the differences between nominal attribute values.The newly introduced distance metric has been christened the supervised distance that can effectively quantify the differences between the nominal attribute values.Then,based on the newly developed metric,a novel fuzzy relationship is defined from the perspective of“feedback on parity of attribute values to attribute sets”.This new fuzzy relationship serves as a valuable tool in addressing the challenges posed by abnormal attribute values.Furthermore,leveraging the newly introduced fuzzy relationship,the fuzzy conditional information entropy is defined as a solution to the challenges posed by fuzzy attributes.It effectively quantifies the uncertainty associated with fuzzy attribute values,thereby providing a robust framework for handling fuzzy information in hybrid information systems.Finally,an algorithm for attribute reduction utilizing the fuzzy conditional information entropy is presented.The experimental results on 12 datasets show that the average reduction rate of our algorithm reaches 84.04%,and the classification accuracy is improved by 3.91%compared to the original dataset,and by an average of 11.25%compared to the other 9 state-of-the-art reduction algorithms.The comprehensive analysis of these research results clearly indicates that our algorithm is highly effective in managing the intricate uncertainties inherent in hybrid data. 展开更多
关键词 Hybrid decision information systems fuzzy conditional information entropy attribute reduction fuzzy relationship rough set theory(RST)
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Translocation of telomerase reverse transcriptase coincided with ATP release in postnatal cochlear supporting cells 被引量:1
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作者 Yukai Zhang Keyong Tian +9 位作者 Wei Wei Wenjuan Mi Fei Lu Zhenzhen Liu Qingwen Zhu Xinyu Zhang Panling Geng Jianhua Qiu Yongli Song Dingjun Zha 《Neural Regeneration Research》 SCIE CAS CSCD 2024年第5期1119-1125,共7页
The spontaneous bursts of electrical activity in the developing auditory system are derived from the periodic release of adenosine triphosphate(ATP)by supporting cells in the Kölliker’s organ.However,the mechani... The spontaneous bursts of electrical activity in the developing auditory system are derived from the periodic release of adenosine triphosphate(ATP)by supporting cells in the Kölliker’s organ.However,the mechanisms responsible for initiating spontaneous ATP release have not been determined.Our previous study revealed that telomerase reverse transcriptase(TERT)is expressed in the basilar membrane during the first postnatal week.Its role in cochlear development remains unclear.In this study,we investigated the expression and role of TERT in postnatal cochlea supporting cells.Our results revealed that in postnatal cochlear Kölliker’s organ supporting cells,TERT shifts from the nucleus into the cytoplasm over time.We found that the TERT translocation tendency in postnatal cochlear supporting cells in vitro coincided with that observed in vivo.Further analysis showed that TERT in the cytoplasm was mainly located in mitochondria in the absence of oxidative stress or apoptosis,suggesting that TERT in mitochondria plays roles other than antioxidant or anti-apoptotic functions.We observed increased ATP synthesis,release and activation of purine signaling systems in supporting cells during the first 10 postnatal days.The phenomenon that TERT translocation coincided with changes in ATP synthesis,release and activation of the purine signaling system in postnatal cochlear supporting cells suggested that TERT may be involved in regulating ATP release and activation of the purine signaling system.Our study provides a new research direction for exploring the spontaneous electrical activity of the cochlea during the early postnatal period. 展开更多
关键词 apoptosis ATP release Ca2+transients COCHLEA mitochondrial function reactive oxygen species spontaneous electrical activity supporting cells
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