Performance Index Research Articles

Finite-time decentralized event-triggered state estimation for coupled neural networks under unreliable Markovian network against mixed cyberattacks

Abstract This article investigates the issue of finite-time state estimation in coupled neural networks under random mixed cyberattacks, in which the Markov process is used to model the mixed cyberattacks. To optimize the utilization of channel resources, a decentralized event-triggered mechanism is adopted during the information transmission. By establishing the augmentation system and constructing the Lyapunov function, sufficient conditions are obtained for the system to be finite-time bounded and satisfy the $H_{\infty}$ performance index. Then, under these conditions, a suitable state estimator gain is obtained. Finally, the feasibility of the method is verified by a given illustrative example.

Using a Claim-Support-Question (CSQ) Technique in Teaching and Learning English Reading for the 3rd Year English Education Students at the Department of Foreign Languages, Faculty of Education, National University of Laos

The main purposes of this study were to: 1) examine the efficiency index of reading lesson plans; 2) investigate the effectiveness index of learning reading outcomes; and 3) to study the 3rd year English education students’ satisfaction towards the teaching and learning of reading using a CSQ technique. The research instruments include four lesson plans, a pre-posttest which consists of 21 items, an observation form, and the satisfaction questionnaire, which consists of 22 items. The target group of the study was the 3rd year English education students at the Faculty of Education, National University of Laos, with a total of 28 students (23 female). The data obtained were analysed using a computer program to find the mean ( ), standard deviation (S.D), percentage (%), efficiency index (E1/E2) and effectiveness index (E.I). The findings reveal that: The efficiency index of the reading lesson plans through using a CSQ technique for the 3rd year English education students was 82.05/88.44, which is higher than the criteria of 80/80. The effectiveness index of reading learning performance through using a CSQ technique was 6699, which was equal to 66.99%, which is higher than the criteria .05 (55%). The 3rd year English education students’ satisfaction towards teaching and learning reading through using a critical thinking technique (CSQ) was at a high level ( = 4.29, S.D = 0.77).

Effects of cassava root meal on the growth performance, apparent nutrient digestibility, organ and intestinal indices, and slaughter performance of yellow-feathered broiler chickens.

With the global population growth and shortage of food, the competition between humans and animal for food will become increasingly fierce. Therefore, the development of unconventional energy feed cassava feed is of great significance. The objective of this study was to investigate the effects of cassava root meal (CRM) on the growth performance, apparent digestibility, and organ and intestinal indices of broiler chickens. A total of 140 one-day-old chicks were randomly assigned to four dietary treatment groups [control diet (CT), 15% CRM (CRM15), 30% CRM (CRM30), and 45% CRM (CRM45)] with five replicates of seven birds per replicate. The results showed that the body weight of broiler chickens fed diets containing CRM were significantly lower than that in the CT group at 21 and 42days of age, the average daily gain and average daily feed intake in the CRM group were significantly lower than those in the CT group from 1 to 21days of age. However, from days 22 to 42, there were no significant differences between CRM15 and CT birds regarding average daily gain and average daily feed intake. but there was no difference in feed conversion rate between the CRM15 and CT groups. At 42days of age, there were no significant differences between CRM15 and CT birds in in body measurements, the slaughter performance and the percentage of semi-eviscerated yield. The addition of CRM reduced the proportion of breast and thigh muscles during the feeding period, although we detected no significant difference between CRM15 and CT regarding the apparent digestibility of nutrients. Collectively, our findings indicate that 15% cassava was the optimal proportion for supplementing diets for broiler chicken production.

Use of black pepper oil in growing-quail diets and its impact on growth, carcass measurements, intestinal microbiota, and blood chemistry

Abstract. Supplements derived from plants are utilized to maintain and promote the growth efficiency of animals. The use of black pepper oil (BPO) has recently generated significant scientific interest, primarily because of its potential beneficial effects on both humans and animals. The goal of the current study was to determine how dietary BPO supplementation affected growth performance, characteristics of growing quails' immunity, antioxidant status, and carcass yield. A total of 240 growing quails (1 week old) were divided into five equal groups, each with 36 birds (four replicates of 12 each). A basal diet containing no BPO (0 g kg−1) was given to the first group, and the second, third, and fourth groups were given a diet that was supplemented with BPO (0.4, 0.8, 1.2, and 1.6 g kg−1, respectively). In comparison to a control group, quails' diets that were supplemented with 0.8 g BPO kg−1 showed improvements in final live body weight, body weight gain, and feed conversion ratio of 10.68 %, 12.6 %, and 18.2 %, respectively. During the whole study period (1 to 5 weeks), quails fed diets with 0.8 g BPO consumed less feed than the other groups and control. Due to BPO treatment, there were no statistically significant changes in any of the carcass parameters. BPO-supplemented groups had significantly elevated plasma levels of albumin and globulin than control groups (P < 0.05), but the albumin/globulin ratio was reported to be significantly decreased (P < 0.05) in birds supplemented with diets containing BPO compared to the control group. When compared to the control, the liver enzyme activity (aspartate transaminase (AST) and alanine transaminase (ALT)) in blood plasma was reported to be significantly increased in the quails given 0.4 and 0.8 g BPO kg−1. Glutathione and catalase activities were significantly higher in the group given diets supplemented with BPO (1.2 g kg−1) than they were in the control group. In comparison to the control, the supplementation of BPO in the diets of quail significantly enhanced (P < 0.05) the lipid profile in the plasma, moreover decreasing the caecal content pH (P < 0.05). In comparison to the control, the populations of lactobacilli, coliform, Salmonella spp., and Escherichia coli in the caecum significantly decreased in the BPO-supplemented groups (P < 0.05). In conclusion, dietary BPO supplementation in Japanese quails' diet can boost growth performance and antioxidant indices, enhance lipid profile and carcass traits, and reduce intestinal infections.

Dynamic implementation and verification of the gauge changing function of high-speed variable gauge bogies

The variable gauge bogie has become an effective method to resolve the different gauge problems existed in cross-country and inter-regional railroad transportation, for which the variable gauge function implementation and dynamic performance is investigated in high-speed variable gauge train. This study provides comprehensive analysis of the stress state of the vehicle’s key components during gauge changing and the motion characteristics of the unlocking-locking device under high-speed operation conditions. The analysis results prove the mechanical properties of key components meet the requirements of national standards, and the gauge changing action can be completed reliably during the gauge changing process. The phenomenon of slippage and resonance will not occur during normal operation, which can ensure the safe operation of the trains. A simulation model for the dynamics of a high-speed variable gauge train with a gauge width of 1435/1520 mm is established based on SIMPACK, which is used to analyse and verify the operational stability, quality and smoothness of the designed variable gauge train. The results indicate that all dynamic performance indices meet the operational requirements.

Enhancing laying performance and immunity via probiotic and vitamin additives during induced molting.

Molting is induced in commercial laying hens to rejuvenate the reproductive system and increase egg production. However, this process causes stress and reduces bird health and performance. The experiment was conducted to study the effect of multi probiotics and vitamin additives on induced molting in 240 ISA Brown hens. Hens were randomly divided into four groups receiving probiotic and vitamin additives (I-IV) during different period of molting. During the whole molting process, the laying performance indexes such as egg laying rate, egg quality, ovary weight and oviduct lengths were measured, and the spleen index, serum immunoglobulin, immune response of NDV and AIV vaccine were monitored. Molted hens resumed 50% egg production in just 37 days, with 1.62% mortality. Egg quality such as egg weight, yolk color, Haugh unit, eggshell strength and protein height were significantly improved. After the second production peak, the reproductive organs and immune organs returned to normal, and the immune antibody titer of NDV vaccine increased significantly. Molting with probiotic and vitamin additives improve the laying performance and egg quality, reduce mortality, significantly improve immune function and vaccine titer, and help to enhance disease resistance and maintain production performance of aged laying hens.

Effect of Different Opening Diet on the Growth, the Structure of the Digestive Tract and Digestive Enzyme Activity of Larval and Juvenile Mystus macropterus.

One of the crucial factors influencing the growth and viability of larvae and juveniles is their opening diets. The objective of this study was to identify suitable initial feed options for M. macropterus larvae and juveniles. A total of 1200 newly hatched M. macropterus with an average weight of 18.3 mg and an average length of 11.58 mm were selected and randomly divided into four groups. The fish were fed with different opening diets, including rotifer, Artemia nauplii, Tubifex, and micro-diet from six days after hatching (dahs), respectively. Growth indices and activities of digestive enzymes were assessed at 10, 15, 20, 25, 30, 35, and 40 dahs. Histological examination of the structure of the digestive tract was performed at 40 dahs, while survival rates were also documented. The results demonstrated that different diets had no effect on the survival rate of larvae and juveniles of M. macropterus. The growth performance indices were ranked as follows: Tubifex group > Artemia nauplii group > micro-diet group > rotifer group. Remarkably, the Tubifex group exhibited superior growth performance, which was also reflected in the structure of the digestive tract and digestive enzyme activity. Therefore, it is recommended to include Tubifex in the diet of M. macropterus larvae and juvenile during the standardized farming process.

Research on the Energy Management Strategy of a Hybrid Tractor OS-ECVT Based on a Dynamic Programming Algorithm

The multi-degree-of-freedom characteristics of the planetary gear electronic continuously variable transmission (ECVT) configuration in series-parallel hybrid tractors impose more complex requirements for energy management strategies under variable load conditions. For a high-power hybrid tractor, this paper takes the hybrid tractor output-split (OS)-ECVT configuration as the research object and describes the principles of stepless transmission and power-splitting within the configuration. In order to improve the fuel economy of high-power hybrid tractors and the running status of power components, an energy management strategy focused on ploughing conditions based on the Bellman minimum dynamic programming (DP) algorithm is proposed in this paper. Second, equivalent fuel consumption is selected as the performance index for energy-saving control, and the solving principle of the energy management strategy based on the dynamic programming algorithm is established to facilitate the resolution process of the energy management strategy. Finally, the energy-saving control simulation is completed under ploughing conditions. The results show that compared with the energy management strategy based on the optimal operating line (OOL), the energy management strategy based on DP fully utilizes the benefits of low-cost electric energy and enables the hybrid power system to have a wider range of stepless transmission performance. In addition, the hybrid power system has the advantages of enhanced decoupling of speed and torque, higher efficiency, and more economical secondary energy conversion. As a result, the whole machine has enhanced power-split performance, greatly improving the running conditions of the power components. The equivalent fuel consumption values of the energy management strategies based on DP and OOL are about 3.1238 L and 4.2713 L, respectively. The equivalent fuel consumption based on DP is reduced by about 26.87%, which effectively improves the fuel efficiency of hybrid tractors.

A Novel Modeling Optimization Approach for a Seven-Channel Titania Ceramic Membrane in an Oily Wastewater Filtration System Based on Experimentation, Full Factorial Design, and Machine Learning.

This comprehensive study looks at how operational conditions affect the performance of a novel seven-channel titania ceramic ultrafiltration membrane for the treatment of produced water. A full factorial design experiment (23) was conducted to study the effect of the cross-flow operating factors on the membrane permeate flux decline and the overall permeate volume. Eleven experimental runs were performed for three important process operating variables: transmembrane pressure (TMP), crossflow velocity (CFV), and filtration time (FT). Steady final membrane fluxes and permeate volumes were recorded for each experimental run. Under the optimized conditions (1.5 bar, 1 m/s, and 2 h), the membrane performance index demonstrated an oil rejection rate of 99%, a flux of 297 L/m2·h (LMH), a 38% overall initial flux decline, and a total permeate volume of 8.14 L. The regression models used for the steady-state membrane permeate flux decline and overall permeate volume led to the highest goodness of fit to the experimental data with a correlation coefficient of 0.999. A Multiple Linear Regression method and an Artificial Neural Network approach were also employed to model the experimental membrane permeate flux decline and analyze the impact of the operating conditions on membrane performance. The predictions of the Gaussian regression and the Levenberg-Marquardt backpropagation method were validated with a determination coefficient of 99% and a Mean Square Error of 0.07.

Assessment of the Logistics Performance Index of OPEC Countries with ENTROPY,CRITICandLOPCOW-basedEDASMethods

Assessment of the Logistics Performance Index of OPEC Countries with ENTROPY,CRITICandLOPCOW-basedEDASMethods

Performance analysis of IMC-PID controller on PCT-14 air pressure control system

This research presents a comprehensive performance analysis of the IMC-PID controller implemented in the PCT-14 air pressure control system, a platform ideal for experimenting with various control methodologies. The study aims to compare the effectiveness of the IMC-PID controller with IMC-PIDF, Good Gain - PID and Skogestad's - PI controllers, focusing on response time characteristics based on the simulation of the PCT-14′s transfer function. Performance analysis is conducted by comparing system response characteristics to set point changes, including rise time, overshoot, settling time, peak time, and steady-state error. To validate the controller's effectiveness, performance index value such as Integrated Absolute Error (IAE) was calculated. The research findings indicate that the IMC-based PID controller outperforms the Good Gain – PID, Skogestad-PI, and IMC-PIDF controllers in handling set point changes.•Simulating the transfer function of the PCT-14 air pressure control system to examine the response time characteristics of the IMC-PID, IMC-PIDF, Good Gain - PID, and Skogestad's - PI controllers.•Conducting a performance analysis by comparing system response characteristics in response to changes in set point values.•Calculating performance index value, IAE to assess the controllers' effectiveness.

Differential Game-Based Cooperative Interception Guidance Law with Collision Avoidance

To deal with the offense-defense confrontation problem of multi-missile cooperative intercepting a high-speed and large-maneuvering target, a differential game-based cooperative interception guidance law with collision avoidance is proposed, in which the offense-defense parties are the incoming target and the interceptors, respectively. Given that both offense-defense parties have uniformly decreasing speeds and first-order biproper dynamics, the relative motion models among the offense-defense parties are established, and the performance indices of the target and the interceptors are proposed. After that, the cooperative interception guidance law with collision avoidance is derived based on a differential game. The guidance law considers the effects of speed variations and rudder layouts on the motions of both offense-defense parties, ensuring excellent algorithmic real-time property and interception accuracy while introducing inter-missile collision avoidance constraints. In addition, the parameters of the target performance index are set according to the target acceleration information estimated by the interceptors. The simulation results verify the effectiveness of the guidance law designed in this paper, under various three-to-one scenarios, the interceptors could achieve collision-free interceptions with the interception accuracy of less than 5 m and the interception time difference of less than 0.1 s.

A scientometrics review of conventional and soft computing methods in the slope stability analysis

Predicting slope stability is important for preventing and mitigating landslide disasters. This paper examines the existing approaches for analyzing slope stability. There are several established conventional approaches for slope stability analysis that can be applied in this context. However, in recent decades, soft computing methods has been extensively developed and employed in stochastic slope stability analysis, notably as surrogate models to improve computing efficiency in contrast to traditional approaches. Soft computing methods can deal with uncertainty and imprecision, which may be quantified using performance indices like coefficient of determination, in regression and accuracy in classification. This review study focuses on conventional methods such as the Bishop’s method and Janbu’s method, as well as soft computing models such as support vector machine, artificial neural network, Gaussian process regression, decision tree, etc. The advantages and limitations of soft computing techniques in relation to conventional methods have also been thoroughly covered in this paper. The achievements of soft computing methods are summarized from two aspects—predicting factor of safety and classification of slope stability. Key potential research challenges and future prospects are also given.

Comparative analysis of rainfall-runoff simulation using a long short-term memory (LSTM) deep learning model and a conceptual hydrological model, HEC-HMS: a case study of the mountainous river basin of Nepal

Accurate simulation and stream flow prediction are essential for effective water resources planning and management. Hydrological models have long been used for rainfall-runoff modeling; in recent years, with the availability of large datasets, machine learning algorithms, and deep learning techniques have become powerful tools to explore. This study compares rainfall-runoff simulation between the Long and Short-Term Memory (LSTM) (a deep learning model) and the Hydrologic Engineering Centre Hydrologic Modeling System (HEC-HMS) (a conceptual model) for a steep mountainous catchment in Nepal. During calibration (1989–2006) and validation (2007–2016), the HEC-HMS model demonstrated a root mean square error (RMSE) and Nash Sutcliffe Efficiency (NSE) of 18.3 and 0.73 and 22.93 and 0.66, respectively, for the calibration and validation periods. During the same periods, the LSTM model showed values of 7.25 and 0.87 and 19.59 and 0.64, respectively, for the calibration and validation periods. The performance indices show that the LSTM model has performed better than the HEC-HMS model. The outcomes of this study suggest that the LSTM deep learning model can simulate the discharge successfully across steep mountainous catchments characterized by monsoon and snowmelt runoff, even with a wide range of precipitation variation, making it an asset for hydrological modeling and water resources management in the data-scarce region.

Robust [formula omitted] control for LFC of discrete T–S fuzzy MAPS with DFIG and time-varying delays

The H∞ LFC control problem for a class of nonlinear power systems with time-varying delays is under study. Considering uncertainties arising from nonlinear issues such as the generation rate constraint (GRC) and governor dead band (GDB), as well as the high variability of renewable energy sources like wind power, the model is transformed into a discrete-time Takagi–Sugeno (T–S) fuzzy model with parameter uncertainty. By constructing a Lyapunov–Krasovskii functional, and employing difference inequalities and generalized cross-convex matrix inequalities, sufficient conditions for the asymptotic stability of power systems are provided. Based on the obtained conditions, a controller is designed to ensure the asymptotic stability of Multi-Area Power Systems (MAPS), with the performance index being H∞. Finally, simulation results demonstrate the correctness and effectiveness of the theorem.

Basic Mechanical Properties of Self-Compacting Concrete Prepared with Aeolian Sand and Recycled Coarse Aggregate

To protect the environment and reduce the consumption of natural resources, this study investigated the performance of self-compacting concrete (SCC) utilizing aeolian sand (AS) as a replacement for fine aggregate and recycled coarse aggregate (RCA) as a replacement for natural coarse aggregate. Twelve mixing ratios were prepared, with AS replacement ratios at 0, 20%, 40%, and 60% and RCA replacement ratios at 0, 25%, and 50%. The evaluation primarily focused on workability, uniaxial compressive strength, split tensile strength, stress–strain curve, modulus of elasticity, and axial compressive strength. The results indicated that both AS and RCA can enhance the performance of SCC at appropriate replacement ratios, and a 20% AS and 50% RCA replacement ratio significantly improved the performance of SCC. In addition, the effects of AS and RCA replacements on SCC were evaluated by several performance indexes, which provides a basis for subsequent experimental studies and demonstrates the feasibility of incorporating AS and RCA into SCC.

Promoting health information system in guiding decisions for improving performance: an intervention study at the Research Institute of Ophthalmology, Giza, Egypt.

This study aims to design and test a platform of key performance indicators (KPIs) and indices emphasizing achievements and improvement and helping decision-making. An operations research study was designed to analyze data from the Hospital Management Information System (HMIS) from July 2017 to June 2018 at the Research Institute of Ophthalmology (RIO), Giza, Egypt. The HMIS data were submitted to reform covering parameters in service delivery and corresponding indicators and indices. Data were grouped into four themes: human resources and outpatient, inpatient, and surgical operations. A total of 14 performance indicators were deployed to four specific indices and total performance indices and applied to six teams of ophthalmologists at RIO. The decision matrices were deliberated to demonstrate achievements and provide recommendations for subsequent improvements. Throughout 1 year, six teams of ophthalmologists (n = 222) at RIO provided the following services: outpatient (n = 116,043), inpatient (n = 8,081), and surgical operations (n = 9,174). Teams 2, 1, and 6 were the top teams in the total performance index. Team 4 had plunges in the outpatient index, and Team 5 faced limitations in the inpatient index. The study provided a model for upgrading the performance of the management information system (MIS) in health organizations. The KPIs and indices were used not only for documenting successful models of efficient service delivery but also as examples of limitations for further support and interventions.

Optimal robot task scheduling in cluttered environments considering mechanical advantage

Abstract In various industrial robotic applications, the effective traversal of a manipulator amidst obstacles and its ability to reach specific task-points are imperative for the execution of predefined tasks. In certain scenarios, the sequence in which the manipulator reaches these task-points significantly impacts the overall cycle time required for task completion. Moreover, some tasks necessitate significant force exertion at the end-effector. Therefore, establishing an optimal sequence for the task-points reached by the end-effector’s tip is crucial for enhancing robot performance, ensuring collision-free motion and maintaining high-force application at the end-effector’s tip. To maximize the manipulator’s manipulability, which serves as a performance index for assessing its force capability, we aim to establish an optimal collision-free task sequence considering higher mechanical advantage. Three optimization criteria are considered: the cycle time, collision avoidance and the manipulability index. Optimization is accomplished using a genetic algorithm coupled with the Bump-Surface concept for collision avoidance. The effectiveness of this approach is confirmed through simulation experiments conducted in 2D and 3D environments with obstacles employing both redundant and non-redundant robots.

Multidimensional Seismic Fragility Study of Intake Towers Based on Incremental Dynamic Analysis

Assessing the fragility of intake towers using a single damage index does not allow for accurate evaluation of the potential for structural damage under seismic conditions. In this study, based on the probabilistic seismic demand analysis method, the effects of ground motion intensity on maximum displacement, local damage index, and global damage index are considered, and the seismic fragility of an intake tower structure is analyzed. First, 10 natural ground motion records were selected from the ground motion database (PEER) and 2 artificial seismic waves were synthesized. These seismic waves were amplitude-modulated for incremental dynamic analysis (IDA). The trends of the IDA curves were analyzed to divide the performance levels of the intake tower structure. Furthermore, a two-dimensional fragility curve for the intake tower structure was plotted in this study. The maximum displacement in the direction of parallel flow and the damage index were taken into account in the two-dimensional fragility curve. The results show that, under the designed seismic acceleration, the two-dimensional fragility curve for the intake tower structure was lower than the one-dimensional curve. This indicates that the seismic design based on the one-dimensional performance index was unstable. This provides a theoretical reference for seismic optimization design and the strengthening of intake towers. Therefore, it is recommended to use multidimensional fragility analysis to study the seismic performance of intake tower structures in seismic design.

Characterization of Geopolymer Masonry Mortars Incorporating Recycled Fine Aggregates

This study evaluates the characteristics of geopolymer masonry mortars (GMMs) made with slag–fly ash binder and up to 100% recycled fine aggregates (RFAs). For each RFA replacement rate, two types of GMMs, namely N and S types based on ASTM C91, were proportioned and tested for mechanical, physical, and durability properties. Results revealed that using geopolymeric binder enhanced the flow, water retention, compressive strength, sorptivity, and abrasion resistance of GMMs compared to cementitious counterparts but reduced the initial setting time by up to 75%. Subsequent RFA additions negatively affected the flow, setting time, density, water absorption, porosity, and bulk resistivity but enhanced the water retention, sorptivity, and abrasion resistance of GMM. It also reduced the compressive, pull-off, and flexural strengths by 36, 44, and 27%, respectively. Furthermore, S-type mortars exhibited improved bulk resistivity, sorptivity, and abrasion resistance compared to N-type counterparts. A multifunctional performance index deduced that the GMM mixes incorporating 100% RFAs were superior to geopolymeric or cementitious masonry mortars made with natural fine aggregates (NFAs). Such findings emphasize the sustainability of GMMs made with RFAs in masonry construction, eliminating the need for water curing while maintaining comparable or even superior properties compared to cement-based mortars made with NFAs.