Visualized User Interface for Decision Support System

To work efficiently with DSS, most users need assistance in representation conversion, i. e., translating the specific outcome from the DSS into the universal language of visual. In generally, it is much easier to understand the results from the DSS if they are translated into charts, maps, and other scientific displays, because visualization exploits human natural ability to recognize and understand visual pattern. In this paper we discuss the concept of visualization for DSS. AniGraftool, a software system, is introduced as an example of Visualized User Interface for DSS.

Feed back Mechanism in Decision Support Systems

Feedback mechanism is a specific feature of control systems, however, the similarity has been found in decision support systems. Just because of this, the DSS can provide a flexible learning and thinking environment, and help decision maker to solve semistructured and unstructured problems actively and creatively. In this paper, the role and type of the feedback in decision making are discussed from different point of view. This is also true in DSS because it supports decision making. The feedback design, especially the feedback interface design, is described through a case of practice DSS. Based on these points, the feedback mechanism is an important feature of DSS, and it is one of the differences between DSS and MIS.

Development of multi-functional anchorage support dynamic-static coupling performance test system and its application

In underground engineering with complex conditions,the bolt(cable)anchorage support system is in an environment where static and dynamic stresses coexist,under the action of geological conditions such as high stresses and strong disturbances and construction conditions such as the application of high prestress.It is essential to study the support components performance under dynamic-static coupling conditions.Based on this,a multi-functional anchorage support dynamic-static coupling performance test system(MAC system)is developed,which can achieve 7 types of testing functions,including single component performance,anchored net performance,anchored rock performance and so on.The bolt and cable mechanical tests are conducted by MAC system under different prestress levels.The results showed that compared to the non-prestress condition,the impact resistance performance of prestressed bolts(cables)is significantly reduced.In the prestress range of 50–160 k N,the maximum reduction rate of impact energy resisted by different types of bolts is 53.9%–61.5%compared to non-prestress condition.In the prestress range of 150–300 k N,the impact energy resisted by high-strength cable is reduced by76.8%–84.6%compared to non-prestress condition.The MAC system achieves dynamic-static coupling performance test,which provide an effective means for the design of anchorage support system.

Artificial Intelligence Based Meteorological Parameter Forecasting for Optimizing Response of Nuclear Emergency Decision Support System

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.

Active Fault Tolerant Nonsingular Terminal Sliding Mode Control for Electromechanical System Based on Support Vector Machine

Effective fault diagnosis and fault-tolerant control method for aeronautics electromechanical actuator is concerned in this paper.By borrowing the advantages of model-driven and data-driven methods,a fault tolerant nonsingular terminal sliding mode control method based on support vector machine(SVM)is proposed.A SVM is designed to estimate the fault by off-line learning from small sample data with solving convex quadratic programming method and is introduced into a high-gain observer,so as to improve the state estimation and fault detection accuracy when the fault occurs.The state estimation value of the observer is used for state reconfiguration.A novel nonsingular terminal sliding mode surface is designed,and Lyapunov theorem is used to derive a parameter adaptation law and a control law.It is guaranteed that the proposed controller can achieve asymptotical stability which is superior to many advanced fault-tolerant controllers.In addition,the parameter estimation also can help to diagnose the system faults because the faults can be reflected by the parameters variation.Extensive comparative simulation and experimental results illustrate the effectiveness and advancement of the proposed controller compared with several other main-stream controllers.

Evaluation of G3BP1 in the prognosis of acute and acute-on-chronic liver failure after the treatment of artificial liver support system

BACKGROUND The increased expression of G3BP1 was positively correlated with the prognosis of liver failure.AIM To investigate the effect of G3BP1 on the prognosis of acute liver failure(ALF)and acute-on-chronic liver failure(ACLF)after the treatment of artificial liver support system(ALSS).METHODS A total of 244 patients with ALF and ACLF were enrolled in this study.The levels of G3BP1 on admission and at discharge were detected.The validation set of 514 patients was collected to verify the predicted effect of G3BP1 and the viability of prognosis.RESULTS This study was shown that lactate dehydrogenase(LDH),alpha-fetoprotein(AFP)and prothrombin time were closely related to the prognosis of patients.After the ALSS treatment,the patient’amount of decreased G3BP1 index in difference of G3BP1 between the value of discharge and admission(difG3BP1)<0 group had a nearly 10-fold increased risk of progression compared with the amount of increased G3BP1 index.The subgroup analysis showed that the difG3BP1<0 group had a higher risk of progression,regardless of model for end-stage liver disease high-risk or low-risk group.At the same time,compared with the inflam matory marks[tumor necrosis factor-α,interleukin(IL)-1βand IL-18],G3BP1 had higher discrimination and was more stable in the model analysis and validation set.When combined with AFP and LDH,concordance index was respectively 0.84 and 0.8 in training and validation cohorts.CONCLUSION This study indicated that G3BP1 could predict the prognosis of ALF or ACLF patients treated with ALSS.The combination of G3BP1,AFP and LDH could accurately evaluate the disease condition and predict the clinical endpoint of patients.

Improvement of the nutritional support management system for patients in intensive care units

BACKGROUND Nutritional support for patients hospitalized in the intensive care unit(ICU)is an important part of clinical treatment and care,but there are significant implementation difficulties.AIM To introduce a modified nutritional support management system for ICU patients based on closed-loop information management and psychological counseling.METHODS The division of functions,personnel training,system construction,development of an intelligent decision-making software system,quality control,and improvement of the whole process were carried out to systematically manage nutritional support for ICU patients.RESULTS Following the implementation of the whole process management system,the scores of ICU medical staff’s knowledge,attitudes/beliefs,and practices regarding nutritional support were comprehensively enhanced.The proportion of hospital bed-days of total enteral nutrition(EN)in ICU patients increased from 5.58%to 11.46%,and the proportion of EN plus parenteral nutrition increased from 42.71%to 47.07%.The rate of EN initiation within 48 h of ICU admission increased from 37.50%to 48.28%,and the EN compliance rate within 72 h elevated from 20.59%to 31.72%.After the implementation of the project,the Self-rating Anxiety Scale score decreased from 61.07±9.91 points to 52.03±9.02 points,the Self-rating Depression Scale score reduced from 62.47±10.50 points to 56.34±9.83 points,and the ICU stay decreased from 5.76±2.77 d to 5.10±2.12 d.CONCLUSION The nutritional support management system based on closed-loop information management and psychological counseling achieved remarkable results in clinical applications in ICU patients.

The Support Systems and Coping Strategies of Infertile Women Attending the Out-Patient Consultation Unit of CHRACERH Yaoundé, Cameroon: A Cross-Sectional Study

Background: Infertility is a complex disorder with significant psycho-social and economic consequences. It globally affects 10% - 15% of couples. In Cameroon, little is known about what women do to overcome the psychosocial aspects of the disease. Objectives: This study aimed to identify the support systems and coping strategies of infertile women attending the outpatient consultation unit of the Gynaecological Endoscopic Surgery and Reproductive Teaching Hospital (CHRACERH), Yaoundé, Cameroon. Methods: A hospital-based cross-sectional study was conducted from the 14th of March to the 6th of April 2023 at CHRACERH Yaoundé. A total of 190 participants were recruited using a convenience sampling method. Data regarding socio-demographic characteristics, support systems and coping strategies were collected using a pretested questionnaire. Descriptive and analytic statistics were conducted using SPSS version 25. Results: The mean age of participants was 39.52 ± 7.64 years. The majority 78.9% of participants were workers (public, private sector, or traders) and were Christians 95.8%. The most common source of psychological support was from family 76.8 and husbands 72.63%. Most of the participants 89.5% resorted to prayer and getting busy 48.4% as a coping strategy. There was no statistically significant relationship between coping strategies and psychological disorders p > 0.05. Conclusion: The main support system of participants was family, husband, and friends. Prayer, getting busy and adoption were the most common coping strategies. There is a need for the Ministry of Public Health and other stakeholders to put in place other support systems and coping strategies (FELICIA) used elsewhere and provide adequate health education and infection control to prevent infertility in Cameroon.

Nursing Care of 10 Patients with Vasovagal Reflex Caused by Artificial Liver Support System Treatment

This study outlines the essential nursing strategies employed in the care of 10 patients experiencing vascular vagal reflex, managed with artificial liver support systems. It highlights a holistic nursing approach tailored to the distinct clinical manifestations of these patients. Key interventions included early detection of psychological issues prior to initiating treatment, the implementation of comprehensive health education, meticulous monitoring of vital signs throughout the therapy, prompt emergency interventions when needed, adherence to prescribed medication protocols, and careful post-treatment observations including venous catheter management. Following rigorous treatment and dedicated nursing care, 7 patients demonstrated significant improvement and were subsequently discharged.

Nutritional Support under the Neuman Systems Model for Stroke Patients

Objective: To explore nutritional support under the Neuman systems model in treating dysphagia in stroke patients. Methods: In this retrospective study, we enrolled 97 patients with dysphagia after stroke admitted to our hospital, and randomly divided them into the Neuman group (n = 51) given nursing intervention based on Neuman systems model and a control group (n = 46) given routine nursing intervention. Both groups received nutritional support for 3 months. Nutritional indexes (serum total protein, plasma albumin, serum albumin, hemoglobin and transferrin levels) and immune indexes (immunoglobulin (Ig) A, IgG, IgM and total lymphocyte count (TLC) in both groups were recorded and compared. Pulmonary function recovery, video fluoroscopic swallowing study score, water swallowing test score, complication rate, and health knowledge mastery level were also compared between the two groups. Results: After the intervention, the Neuman group showed less decrease in the nutritional and immune index scores (serum total protein, plasma albumin, hemoglobin, serum albumin;IgA, IgG, IgM, and TLC;all P Conclusion: For patients with stroke and dysphagia, comprehensive nursing intervention (e.g., nutritional support) under theNeuman systems model can promote the recovery of immune, swallowing, and pulmonary function, reduce complication incidence and facilitate comprehensive rehabilitation, ensuring adequate nutritional intake.

Applying the Technology Acceptance Model (TAM) in Information Technology System to Evaluate the Adoption of Decision Support System

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.

Design and Implementation of the Employment Management Decision Support System based on Machine Learning

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.

A multi-purpose prototype test system for mechanical behavior of tunnel supporting structure: Development and application

A multi-purpose prototype test system is developed to study the mechanical behavior of tunnel sup-porting structure,including a modular counterforce device,a powerful loading equipment,an advanced intelligent management system and an efficient noncontact deformation measurement system.The functions of the prototype test system are adjustable size and shape of the modular counterforce structure,sufficient load reserve and accurate loading,multi-connection linkage intelligent management,and high-precision and continuously positioned noncontact deformation measurement.The modular counterforce structure is currently the largest in the world,with an outer diameter of 20.5 m,an inner diameter of 16.5 m and a height of 6 m.The case application proves that the prototype test system can reproduce the mechanical behavior of the tunnel lining during load-bearing,deformation and failure processes in detail.

Research on the Voltage Supporting Capability of Multi-VSC-HVDC Subsystems Operation Strategy to Receiving-end LCC-HVDC Network in Weak AC Grid

For the hybrid multi-infeed HVDC system in which the receiving-end grid is a strong AC grid including LCC-HVDC subsystems and multiple VSC-HVDC subsystems,it has higher voltage support capability.However,for weak AC grid,the voltage support capability of the multi-VSC-HVDC subsystems to the LCC-HVDC subsystem(voltage support capability-mVSCs-LCC)can resist the risk of commutation failure.Based on this consideration,this paper proposes an evaluation index called Dynamic Voltage Support Strength Factor(DVSF)for the hybrid multi-infeed system,and uses this index to qualitatively judge the voltage support capability-mVSCs-LCC in weak AC grid.In addition,the proposed evaluation index can also indirectly judge the ability of the LCC-HVDC subsystem to suppress commutation failure.Firstly,the mathematical model of the power flow of the LCC and VSC networks in the steady-state is analyzed,and the concept of DVSF applied to hybrid multi-infeed system is proposed.Furthermore,the DVSF index is also used to qualitatively judge the voltage support capability-mVSCs-LCC.Secondly,the influence of multiple VSC-HVDC subsystems with different operation strategies on the DVSF is analyzed with reference to the concept of DVSF.Finally,the indicators proposed in this paper are compared with other evaluation indicators through MATLAB simulation software to verify its effectiveness.More importantly,the effects of multi-VSC-HVDC subsystems using different coordinated control strategies on the voltage support capability of the receiving-end LCC-HVDC subsystem are also verified.

Support vector regression-based operational effectiveness evaluation approach to reconnaissance satellite system

As one of the most important part of weapon system of systems(WSoS),quantitative evaluation of reconnaissance satellite system(RSS)is indispensable during its construction and application.Aiming at the problem of nonlinear effectiveness evaluation under small sample conditions,we propose an evaluation method based on support vector regression(SVR)to effectively address the defects of traditional methods.Considering the performance of SVR is influenced by the penalty factor,kernel type,and other parameters deeply,the improved grey wolf optimizer(IGWO)is employed for parameter optimization.In the proposed IGWO algorithm,the opposition-based learning strategy is adopted to increase the probability of avoiding the local optima,the mutation operator is used to escape from premature convergence and differential convergence factors are applied to increase the rate of convergence.Numerical experiments of 14 test functions validate the applicability of IGWO algorithm dealing with global optimization.The index system and evaluation method are constructed based on the characteristics of RSS.To validate the proposed IGWO-SVR evaluation method,eight benchmark data sets and combat simulation are employed to estimate the evaluation accuracy,convergence performance and computational complexity.According to the experimental results,the proposed method outperforms several prediction based evaluation methods,verifies the superiority and effectiveness in RSS operational effectiveness evaluation.

Analysis of the interaction between bolt-reinforced rock and surface support in tunnels based on convergence-confinement method

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.

Mechanism of high-preload support based on the NPR anchor cable in layered soft rock tunnels

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.

Translocation of telomerase reverse transcriptase coincided with ATP release in postnatal cochlear supporting cells

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.

Stability analysis of longwall top-coal caving face in extra-thick coal seams based on an innovative numerical hydraulic support model

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.

Artificial Intelligence Enabled Decision Support System on E-Healthcare Environment

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.