Optimizing PID controller parameters for robust automatic voltage regulator system through indirect design approach-2

Automatic voltage regulators(AVR)are designed to manipulate a synchronous generator’s voltage level automatically.Proportional integral derivative(PID)controllers are typically used in AVR systems to regulate voltage.Although advanced PID tuning methods have been proposed,the actual voltage response differs from the theoretical predictions due to modeling errors and system uncertainties.This requires continuous fine tuning of the PID parameters.However,manual adjustment of these parameters can compromise the stability and robustness of the AVR system.This study focuses on the online self-tuning of PID controllers called indirect design approach-2(IDA-2)in AVR systems while preserving robustness.In particular,we indirectly tune the PID controller by shifting the frequency response.The new PID parameters depend on the frequency-shifting constant and the previously optimized PID parameters.Adjusting the frequency-shifting constant modifies all the PID parameters simultaneously,thereby improving the control performance and robustness.We evaluate the robustness of the proposed online PID tuning method by comparing the gain margins(GMs)and phase margins(PMs)with previously optimized PID parameters during parameter uncertainties.The proposed method is further evaluated in terms of disturbance rejection,measurement noise,and frequency response analysis during parameter uncertainty calculations against existing methods.Simulations show that the proposed method significantly improves the robustness of the controller in the AVR system.In summary,online self-tuning enables automated PID parameter adjustment in an AVR system,while maintaining stability and robustness.

Relaxed Stability Criteria for Time-Delay Systems:A Novel Quadratic Function Convex Approximation Approach

This paper develops a quadratic function convex approximation approach to deal with the negative definite problem of the quadratic function induced by stability analysis of linear systems with time-varying delays.By introducing two adjustable parameters and two free variables,a novel convex function greater than or equal to the quadratic function is constructed,regardless of the sign of the coefficient in the quadratic term.The developed lemma can also be degenerated into the existing quadratic function negative-determination(QFND)lemma and relaxed QFND lemma respectively,by setting two adjustable parameters and two free variables as some particular values.Moreover,for a linear system with time-varying delays,a relaxed stability criterion is established via our developed lemma,together with the quivalent reciprocal combination technique and the Bessel-Legendre inequality.As a result,the conservatism can be reduced via the proposed approach in the context of constructing Lyapunov-Krasovskii functionals for the stability analysis of linear time-varying delay systems.Finally,the superiority of our results is illustrated through three numerical examples.

“Instruction-Category” Approach of Test Suite Construction for Oven Embedded System

Being different from testing for popular GUI software, the “instruction-category” approach is proposed for testing embedded system. This approach is constructed by three steps including refining items, drawing instruction-brief and instruction-category, and constructing test suite. Consequently, this approach is adopted to test oven embedded system, and detail process is deeply discussed. As a result, the factual result indicates that the “instruction-category” approach can be effectively applied in embedded system testing as a black-box method for conformity testing.

Impact of improper municipal solid waste management on fostering One Health approach in Ethiopia—challenges and opportunities:a systematic review

Improper disposal of solid waste,predominantly illegal dumping,can lead to severe air and water pollution,land degradation,climate change,and health hazards due to the persistence of hazardous materials.As a result,it is threatening public and animal health,environmental sustainability,and economic development.The One Health approach,which acknowledges the interconnectedness of human,animal,and environmental health,offers a comprehensive solution.This systematic review examines the impact of improper municipal solid waste on fostering One Health approaches at the national level of Ethiopia by identifying key challenges and opportunities.Publications were retrieved from peer-reviewed,indexed journal publications,government documents(policies,proclamations,regulations,and guidelines),and credible non-governmental organization publications from selected electronic databases(Google scholar,PubMed,EMBASE,Global Health,Web of Science,etc.),and governmental offices.Despite efforts to advance the One Health approach in Ethiopia through the formation of the National One Health Steering Committee and technical working groups,implementation is hindered by challenges such as poor sectoral integration,insufficient advocacy,financial constraints,and limited research.These challenges contribute to worsening zoonotic and infectious diseases and environmental issues due to inadequate solid waste management.Nonetheless,opportunities exist through One Health integration via holistic programs,interdisciplinary collaboration,community engagement,policy enhancement,institutional capacity building,and public-private partnerships.Therefore,enhancing sectoral integration and increasing advocacy efforts and securing financial support is necessary to back waste management initiatives and related research.Further research is crucial to understand the impact of solid waste management and the potential benefits of the One Health approach in Ethiopia.

Optimizing a Transportation System Using Metaheuristics Approaches (EGD/GA/ACO): A Forest Vehicle Routing Case Study

The large-scale optimization problem requires some optimization techniques, and the Metaheuristics approach is highly useful for solving difficult optimization problems in practice. The purpose of the research is to optimize the transportation system with the help of this approach. We selected forest vehicle routing data as the case study to minimize the total cost and the distance of the forest transportation system. Matlab software helps us find the best solution for this case by applying three algorithms of Metaheuristics: Genetic Algorithm (GA), Ant Colony Optimization (ACO), and Extended Great Deluge (EGD). The results show that GA, compared to ACO and EGD, provides the best solution for the cost and the length of our case study. EGD is the second preferred approach, and ACO offers the last solution.

Induced pluripotent stem cell-related approaches to generate dopaminergic neurons for Parkinson's disease

The progressive loss of dopaminergic neurons in affected patient brains is one of the pathological features of Parkinson's disease,the second most common human neurodegenerative disease.Although the detailed pathogenesis accounting for dopaminergic neuron degeneration in Parkinson's disease is still unclear,the advancement of stem cell approaches has shown promise for Parkinson's disease research and therapy.The induced pluripotent stem cells have been commonly used to generate dopaminergic neurons,which has provided valuable insights to improve our understanding of Parkinson's disease pathogenesis and contributed to anti-Parkinson's disease therapies.The current review discusses the practical approaches and potential applications of induced pluripotent stem cell techniques for generating and differentiating dopaminergic neurons from induced pluripotent stem cells.The benefits of induced pluripotent stem cell-based research are highlighted.Various dopaminergic neuron differentiation protocols from induced pluripotent stem cells are compared.The emerging three-dimension-based brain organoid models compared with conventional two-dimensional cell culture are evaluated.Finally,limitations,challenges,and future directions of induced pluripotent stem cell–based approaches are analyzed and proposed,which will be significant to the future application of induced pluripotent stem cell-related techniques for Parkinson's disease.

Enhancing perianal disease management with integrated physical and psychological approaches

This article provides a comprehensive analysis of the study by Hou et al,focusing on the complex interplay between psychological and physical factors in the postoperative recovery(POR)of patients with perianal diseases.The study sheds light on how illness perception,anxiety,and depression significantly influence recovery outcomes.Hou et al developed a predictive model that demonstrated high accuracy in identifying patients at risk of poor recovery.The article explores the critical role of pre-operative psychological assessment,highlighting the need for mental health support and personalized recovery plans in enhancing POR quality.A multidisciplinary approach,integrating mental health professionals with surgeons,anesthesiologists,and other specialists,is emphasized to ensure comprehensive care for patients.The study’s findings serve as a call to integrate psychological care into surgical practice to optimize outcomes for patients with perianal diseases.

Chyle leak following root of mesentery dissection in pancreaticoduodenectomy with inferior infracolic superior mesenteric artery first approach

BACKGROUND The root of mesentery dissection is one of the critical maneuvers,especially in borderline resectable pancreatic head cancer.Intra-abdominal chyle leak(CL)including chylous ascites may ensue in up to 10%of patients after pancreatic resections.Globally recognized superior mesenteric artery(SMA)first approaches are invariably performed.The mesenteric dissection through the inferior infracolic approach has been discussed in this study emphasizing its post-operative impact on CL which is the cornerstone of this study.AIM To assess incidence,risk factors,clinical impact of CL following root of mesentery dissection,and the different treatment modalities.METHODS This is a retrospective study incorporating the patients who underwent dissection of the root of mesentery with inferior infracolic SMA first approach pancreat-oduodenectomy for the ventral body and uncinate mass of pancreas in the Department of Gastrointestinal and General Surgery of Kathmandu Medical College and Teaching Hospital from January 1,2021 to February 28,2024.Intraop-erative findings and postoperative outcomes were analyzed.RESULTS In three years,ten patients underwent root of mesentery dissection with inferior infracolic SMA first approach pancreatoduodenectomy.The mean age was 67.6 years with a male-to-female ratio of 4:5.CL was seen in four patients.With virtue of CL,Clavien-Dindo grade Ⅱ or higher morbidity was observed in four patients.Two patients had a hospital stay of more than 20 days with the former having a delayed gastric emptying and the latter with long-term total parenteral nutrition requirement.The mean operative time was 330 minutes.Curative resection was achieved in 100%of the patients.The mean duration of the intensive care unit and hospital stay were 2.55±1.45 days and 15.7±5.32 days,respectively.CONCLUSION Root of mesentery dissection with lymphadenectomy and vascular resection correlated with occurrence of CL.After complete curative resection,these were managed with total parenteral nutrition without adversely impacting outcome.

Evaluation of soil nutrient status in poplar forest soil by soil nutrient systematic approach

A study was conducted to evaluate the soil nutrient status of poplar plantation by Soil Nutrient Systematic Approach (SNSA) in Jianghan Plain, Hubei Province, China. Soil physiochemical properties were analyzed in laboratory through collection soil samples of study site. Ten treatments of application different fertilizers were designed such as CK, optimum treatment (N, P, K, Zn), N(P, K, Zn), P(N, K, Zn), K(N, P, Zn), +Mg(N, P, K, Zn, Mg), Zn (N,P,K), +2P(N, 2P, K, Zn), +2K(N, P, 2K, Zn), and 2N+2P+2K(2N, 2P, 2K, Zn) for field experiment to test the effect on tree height, diameter (DBH) growth, and dry weight of poplar. The results showed that there was no significant difference in tree heights between treatments with different fertilizers, diameter growth of poplar trees in treatments of lack of N and Zn was significantly slower than that of trees in optimum treatment, and dry weight of poplar dropped significantly for treatment of CK as well as treatments without application N and Zn. It is concluded that N and Zn were main limiting factor for poplar growth. Results from laboratory analysis and field experiment were uniform per-fectly, which proved that SNSA was reliable in evaluating soil nutrient status of poplar plantation.

Application of Maximum Probability Approach to the Fault Diagnosis of a Servo System

In an actual control system, it is often difficult to find out where the faults are if only based on the outside fault phenomena, acquired frequently from a fault system. So the fault diagnosis by outside fault phenomena is considered. Based on the theory of fuzzy recognition and fault diagnosis, this method only depends on experience and statistical data to set up fuzzy query relationship between the outside phenomena (fault characters) and the fault sources (fault patterns). From this relationship the most probable fault sources can be obtained, to attain the goal of quick diagnosis. Based on the above approach, the standard fuzzy relationship matrix is stored in the computer as a system database. And experiment data are given to show the fault diagnosis results. The important parameters can be on line sampled and analyzed, and when faults occur, faults can be found, the alarm is given and the controller output is regulated.

Modeling of Intelligent Integrated Network Management System Using Object Oriented Approach *

The concept of intelligent integrated network management (IINM) is briefly introduced. In order to analyze, design and implement IINM successfully, object oriented approach is testified to be an effective and efficient way. In this paper, object oriented technique is applied to the structural model of IINM system, The Domain object class and the MU object class are used to represent the manager and the managed resources. Especially, NM IA is introduced which is a special object class with intelligent behaviors to manage the resources efficiently.

Anterior vs conventional approach right hepatic resection for large hepatocellular carcinoma:A systematic review and meta-analysis

AIM To compare the clinical outcomes of right hepatectomy for large hepatocellular carcinoma via the anterior and conventional approach.METHODS We comprehensively performed an electronic search of Pub Med, EMBASE, and the Cochrane Library for randomized controlled trials(RCTs) or controlled clinical trials(CCTs) published between January 2000 and May 2017 concerning the anterior approach(AA) and the conventional approach(CA) to right hepatectomy. Studies that met the inclusion criteria were included, and their outcome analyses were further assessed using a fixed or random effects model.RESULTS This analysis included 2297 patients enrolled in 16 studies(3 RCTs and 13 CTTs). Intraoperative blood loss [weighted mean difference =-255.21; 95% confidence interval(95%CI):-371.3 to-139.12; P < 0.0001], intraoperative blood transfusion [odds ratio(OR) = 0.42; 95%CI: 0.29-0.61; P < 0.0001], mortality(OR = 0.59; 95%CI: 0.38-0.92; P = 0.02), morbidity(OR = 0.77; 95%CI: 0.62-0.95; P = 0.01), and recurrencerate(OR = 0.62; 95%CI: 0.47-0.83; P = 0.001) were significantly reduced in the AA group. Patients in the AA group had better overall survival(hazard ratio [HR] = 0.71; 95%CI: 0.50-1.00; P = 0.05) and disease-free survival(HR = 0.67; 95%CI: 0.58-0.79; P < 0.0001) than those in the CA group.CONCLUSION The AA is safe and effective for right hepatectomy for large hepatocellular carcinoma and could accelerate postoperative recovery and achieve better survival outcomes than the CA.

New Family of Exact Solutions and Chaotic Soltions of Generalized Breor-Kaup System in （2＋1）-Dimensions via an Extended Mapping Approach

Starting from an extended mapping approach, a new type of variable separation solution with arbitrary functions of generalized (2+1)-dimensional Broer-Kaup system (GBK) system is derived. Then based on the derived solitary wave solution, we obtain some specific chaotic solitons to the (2+1)-dimensional GBK system.

Comparison of the modified Wiltse’s approach with spinal minimally invasive system and traditional approach for the therapy of thoracolumbar fracture

Thoracolumbar fractures are usually treated by open posterior pedicle screw fixation.However,this procedure involves massive paraspinal muscle stripping,inflicting surgical trauma,and prolonged X-ray exposure.In this study,we observed 127 patients with single-segment injury thoracolumbar fractures.Thirty-six patients were treated by the modified Wiltse’s paraspinal approach with minimally invasive channel system,while 91 patients were treated via traditional posterior approach.Operation time,intraoperative blood loss,intraoperative fluoroscopy frequency,screw placement accuracy,visual analogue scale score,and Cobb’s angle of two groups were compared.The X-ray exposure times were notably reduced(4.2±1.6) in the new approach group(P<0.05).The pedicle screw placement accuracy and Cobb’s angle after surgery were similar in the two groups.We conclude that modified Wiltse’s paraspinal approach w ith spinal minimally invasive channel system surgery can significantly reduce the X-ray exposure times and is an alternative therapy for the thoracolumbar fracture.

A Systemic Approach to Integrated E-maintenance of Large Engineering Plants

Large engineering plants （LEPs） have certain unique features that necessitate a maintenance strategy that is a combination of both time and condition based maintenance. Although this requirement is appreciated to varying degrees by asset owners, applied research leading to a systematic development of such a maintenance strategy is the need of the day. Such a strategy should also adopt a wholesome ＂systemic＂ approach so that the realization of the overall objectives of maintenance is maximized. E-maintenance has several potential benefits for large engineering plants. In this paper, a three pronged strategy is suggested for the successful implementation of e-maintenance for LEPs. Firstly, an integrated condition and time based maintenance framework is proposed for LEPs. Secondly, reference is drawn to models for condition and time based maintenance at systemic levels. As a part of the ab initio development of a condition monitoring system for a LEP, one of the characteristics of the condition monitoring system, namely, predictability, is discussed in detail as a sample for a systemic study. Thirdly, emphasis is laid on the information and expertise available in the domain of plant design, operation and maintenance and the same is tapped for incorporation in maintenance decision making.

A New Rational Algebraic Approach to Find Exact Analytical Solutions to a （2＋1）-Dimensional System

In this paper, we present a new rational algebraic approach to uniformly construct a series of exact analytical solutions for nonlinear partial differential equations. Compared with most existing tanh methods and other sophisticated methods, the proposed method not only recovers some known solutions, but also finds some new and general solutions. The solutions obtained in this paper include rational form triangular periodic wave solutions, solitary wave solutions, and elliptic doubly periodic wave solutions. The efficiency of the method can be demonstrated on （2＋1）-dimensional dispersive long-wave equation.

Design approaches for active,semi-active and passive control systems based on analysis of characteristics of active control force

In this paper, the characteristics of forces in active control systems connected to adjacent levels of a building are analyzed. The following characteristics are observed： （1） active control can provide significantly superior supplemental damping to a building, but causes a small frequency shift; （2） the linear quadratic regulator （LQR）-based control force is composed of an elastic restoring force component and a damping force component, where the damping force is almost identical to the total control force, however, the elastic restoring force is very small; and （3） the active control forces prevent mction most of the time during the entire control process. These three characteristics imply that active control systems connected to adjacent levels of a building behave like passive damping devices with adjustable parameters, namely damping characteristics in an active control, which is the mechanism used by semi-active control devices to reach similar performance as active control systems. Two indices are defined to quantify the damping characteristics of control forces in active control systems. These two indices can also be used to quantify the capacity of semi-active control to achieve the perfonrlance of active control. Based on the above observations, two principles are founded for optimization of parameters of semi-active control devices and passive dampers. The first is that the maximum output force of a semi-active or passive device to be designed is identical to an active device, called ＂design principle＂. The other is the response equivalent principle, which states that the response of a building with semi-active or passive devices is the same as with active devices when the same maximum output force is applied. The design procedure for semi-active control devices and passive dampers is described in detail. Finally, numerical simulations of two benchmark problems is conducted to demonstrate the damping characteristics of active control and investigate the capacity of semi-active control to achieve the same performance as active control.

Multi-model deep learning approach for collaborative filtering recommendation system

As a result of a huge volume of implicit feedback such as browsing and clicks,many researchers are involving in designing recommender systems(RSs)based on implicit feedback.Though implicit feedback is too challenging,it is highly applicable to use in building recommendation systems.Conventional collaborative filtering techniques such as matrix decomposition,which consider user preferences as a linear combination of user and item latent features,have limited learning capacities,hence suffer from a cold start and data sparsity problems.To tackle these problems,the research direction towards considering the integration of conventional collaborative filtering with deep neural networks to maps user and item features.Conversely,the scalability and the sparsity of the data affect the performance of the methods and limit the worthiness of the results of the recommendations.Therefore,the authors proposed a multimodel deep learning(MMDL)approach by integrating user and item functions to construct a hybrid RS and significant improvement.The MMDL approach combines deep autoencoder with a one-dimensional convolution neural network model that learns user and item features to predict user preferences.From detail experimentation on two real-world datasets,the proposed work exhibits substantial performance when compared to the existing methods.

Feedback iterative learning control for time-delay systems based on 2D analysis approach

This paper deals with the iterative learning control （ILC） design for multiple-input multiple-output （MIMO）,time-delay systems （TDS）.Two feedback ILC schemes are considered using the so-called two-dimensional （2D） analysis approach.It shows that continuous-discrete 2D Roesser systems can be developed to describe the entire learning dynamics of both ILC schemes,based on which necessary and sufficient conditions for their stability can be provided.A numerical example is included to validate the theoretical analysis.

A Sensorless State Estimation for A Safety-Oriented Cyber-Physical System in Urban Driving:Deep Learning Approach

In today's modern electric vehicles,enhancing the safety-critical cyber-physical system(CPS)'s performance is necessary for the safe maneuverability of the vehicle.As a typical CPS,the braking system is crucial for the vehicle design and safe control.However,precise state estimation of the brake pressure is desired to perform safe driving with a high degree of autonomy.In this paper,a sensorless state estimation technique of the vehicle's brake pressure is developed using a deep-learning approach.A deep neural network(DNN)is structured and trained using deep-learning training techniques,such as,dropout and rectified units.These techniques are utilized to obtain more accurate model for brake pressure state estimation applications.The proposed model is trained using real experimental training data which were collected via conducting real vehicle testing.The vehicle was attached to a chassis dynamometer while the brake pressure data were collected under random driving cycles.Based on these experimental data,the DNN is trained and the performance of the proposed state estimation approach is validated accordingly.The results demonstrate high-accuracy brake pressure state estimation with RMSE of 0.048 MPa.