Reliability Index Research Articles

Measurement of sustainable attitudes: a scale for business students

Purpose This study aims to present the development and validation of a scale to measure the attitudes of Latin American business students toward sustainable management practices in the economic, social and environmental dimensions. Design/methodology/approach Using a nonprobabilistic sample, the appreciation for sustainable practices in students (ASP-S) scale was administered to a total of 653 undergraduate and graduate business students in Argentina, Colombia, Mexico and Peru. A range of psychometric validity (construct, convergent and discriminant) and reliability criteria were applied. Findings Construct, convergent and discriminant validity was obtained from the ASP-S scale across all samples. During the internal validation process, two factors were found: systemic consciousness (ten items) and sustainable business leadership (nine items), both of which obtained acceptable reliability indices. The resulting structure is equivalent in all four countries. Originality/value The instrument can be applied by educators and learning assurance areas to diagnose and measure the effectiveness of pedagogical strategies used in sustainability courses taught at Latin American business schools. As a result, it has applications for curriculum design. As a valid and reliable instrument set in the context of regional business praxis, it can promote an understanding of sustainable behaviors and practices in future Latin American leaders.

Determining target levels of power distribution system reliability indices using machine learning

Electrical distribution system (EDS) reliability has always been a critical subject due to the considerable share of distribution systems in power interruptions to end-users. Meeting regulatory service quality standards requires distribution companies to achieve defined reliability levels for performance improvement. Conventionally, specialists determine target reliability based on experience, experimental knowledge, and rules of thumb. However, these methods are error-prone and may result in suboptimal investments, economic inefficiency, and inadequate resource allocation in EDS operation and planning. Accordingly, this paper presents a machine learning-based method to determine the target level for EDS's reliability indices based on its historical performance. The approach involves comprehensive analysis of historical EDS reliability data, followed by a data envelopment analysis (DEA) to assess performance across subdivisions like substations or feeders, identifying the most effective units. Subsequently, machine learning models—Random Forest (RF), Support Vector Machine (SVM), and Radial Basis Function (RBF) network—are trained on optimal subdivisions from the DEA stage. These models accurately estimate target reliability for all subdivisions, contributing to the overall determination of the EDS target reliability level. A three-scenario case study validates the proposed method, suggesting its potential applicability as a valuable tool for regulatory agencies in setting EDS reliability targets. While admitting the potential challenges, notably the method's reliance on the quality and completeness of the historical data collected by distribution companies, the paper emphasizes the importance of collaborative efforts to ensure data accuracy and sufficiency. The proposed method leads to a fair mechanism to determine the target level for a real EDS's reliability indices in comparison with a business-as-usual scenario. Moreover, it provides a reliability performance ranking for the EDS's subdivisions.

Fiber Quality of Colored Cotton As a Function of Potassium Fertilization in the Semi-Arid Region

ABSTRACT Naturally colored fiber cotton is an essential alternative green and organic for the textile industry, as it does not require chemical dyeing. However, the low availability of potassium during production can directly affect the quality of the fiber. Based on this, this study aimed to evaluate the fiber quality in naturally colored cotton cultivars submitted to potassium fertilization in a semi-arid region. The experimental design was in randomized blocks, with four replications, and the treatments were arranged in split plots. In the plot, the following were allocated: five K rates (0, 60, 120, 180, and 240 kg ha−1 of K2O); and in the subplots, the four colored cotton cultivars (BRS Rubi, BRS Safira, BRS Topázio, and BRS Verde). The results showed that K is involved in the length, uniformity, short fiber index, micronaire index, and reliability index of naturally colored cotton fibers. A longer fiber length of 30.45 mm was obtained at a dose of 240 kg ha−1 of K2O for the cultivar BRS Topázio. In addition, a higher uniformity (84.95%) was achieved with the dose of 240 kg ha−1 of K2O for BRS Verde. The dose of 240 kg ha−1 of K2O reduced (8.62% and 11.28%) the short fiber index in the cultivars BRS Rubi and BRS Safira, respectively.

A Calculation Method for Reliability Index of a Deep–Bedded Karst Tunnel Construction with Cavity Located Ahead of Tunnel Working Face

For the purpose of reliability quantitative assessment of the surrounding rock of the deeply embedded karst tunnel and the geological body around the cavern in the case of the cavern in the forepart of the tunnel face, on the basis of the upper bound limit analysis method, the energy dissipation theory, as well as the reliability theory, the dimensionless performance function of each damage area of the deeply buried karst tunnels could be established in the case of the cavern in the front of the tunnel face. Subsequently, the probability of failure and the reliability index of each damage region of the deep–bedded karst tunnel in the case of the cavern in the front of this tunnel face should be calculated through the Monte Carlo simulation sampling approach. The investigation has demonstrated that the larger the cohesion of the geotechnical body and the larger the internal friction angle within the geotechnical body, the larger the reliability indexes of the geotechnical bodies around the tunnel. The larger the diameter of the cavern and the larger the tunnel burial depth, the greater the probability of failure in the left part of the geotechnical body around this cavern, and the smaller the reliability indexes of these damage areas.

Risk Assessment of Radial Distribution Systems using Modified Jelly Fish Search Algorithm to analyse the Performance Indices

One of the essential techniques for figuring out Power Distribution System performance is reliability evaluation. With time, the range of methods for assessing reliability has grown, and the distribution system's evolution has also become more intricate. The likelihood of a network failing grows with time once it begins to function, especially if it is used for an extended period. Reliability indices have been evaluated using different algorithms such as Particle Swarm Optimization (PSO), Genetic Algorithm (GA) and various modified versions of algorithms. The Jelly Fish Search Algorithm has been used in various power system applications such as to determine the most cost-effective way to dispatch generating units' loads, integrate Distributed Generation (DG) units, track the maximum power of photovoltaic systems, and determine optimal power flow solutions, among other uses. The performance indices for the Radial Distribution System (RDS) have not been evaluated using JFSA.Variation of performance indices with respect to unavailability has not been discussed in the literature. Here an attempt is made to analyse the variation of the indices with the unavailability. The proposed algorithm is evaluated first on 3 load point radial distribution system and the computations are performed on the popular IEEE-RBTS Bus2 test system. Based on the output it is observed that for the both the systems the behaviour of the indices with respect to the unavailability is in similar fashion. The equations are derived for the performance indices using the Minitab. With the equations obtained the Performance indices values can be predicted for the given unavailability value. It is the better appropriate method for the assessing the performance indices of Radia Distribution System.

Monte Carlo simulation study on the reliability of concrete-filled HSS beam-column design provisions

Revisions were recently proposed to the way in which concrete-filled hollow structural section (HSS) members are handled in CSA S16. These revisions were based on previous research, comparisons to experiments, and a first-order reliability method analysis of existing provisions for compression and flexural members. In this paper, this topic is further expanded by using Monte Carlo Simulations (MCS) to determine the inherent reliability of the previous and new design rules for concrete-filled rectangular hollow section (RHS) and circular hollow section (CHS) beam-columns. A representative set of concrete-filled RHS and CHS members with variations in concrete strength, wall slenderness, effective length, and loading eccentricity are analyzed. Using MCS, the reliability index (β+) of each is determined over a range of live-to-dead load (L/D) ratios. Inherent β+ values are compared to the code-specified target (i.e., β+ = 3.0 per Annex B of CSA S16) and the CSA S16:19 and AISC 360-16 provisions.

Reliability Evaluation of Radial Distribution System with different locations and ratings of Photovoltaic

The primary objective of this work is to examine how strategically positioning Photovoltaic (PV) units can have effect on reliability of a distribution system. Feeder-1 of RBTS BUS2 system is used for the reliability evaluation. The study utilizes FMEA technique to evaluate the reliability indices, System Average Interruption Frequency Index (SAIFI), System Average Interruption Duration Index (SAIDI), Energy Not Supplied (ENS) and Average Service Availability (ASAI) linked to electrical interruptions in two different situations such as no PV unit and PV units are placed at different locations with different ratings along the feeder. The outcomes of installing PV units at different points along the distribution feeder are examined and compared. The prime focus lies in identifying the reliability based optimal placement of the PV unit, a determination made based on the reliability indices. By systematically analyzing and comparing the reliability indices under varying conditions, the research aims to provide insights into how the strategic positioning of PV units can lead to a substantial enhancement in the overall reliability of the distribution system. The findings contribute to the broader understanding of integrating renewable energy sources for reliability improvement within distribution systems and offer practical guidance for decision-makers in the field of energy distribution and planning.

Enhancing fatigue reliability prediction of offshore wind turbine jacket joints through individual uncertainties for each degree of freedom of stress concentration factor

This paper presents the fatigue reliability prediction for welded planar tubular joints of offshore fixed jacket support structures. A coupled model is employed to calculate the dynamic response of the jacket support structure under wind and wave loads. Stress concentration factors (SCFs) are evaluated using Efthymiou parametric equations, and the hot-spot stresses at eight locations on the chord and brace of the tubular joints are derived by summing the stress components from axial, in-plane, and out-of-plane actions. The stress distribution is determined using the rainflow counting method, fatigue damage from an S–N curve, and Miner’s rule. Uncertainties associated with the fatigue lifetime evaluation procedure are identified, quantified, and modeled. The focus is specifically given to modeling the uncertainty related to the SCFs, and a framework is proposed to evaluate the fatigue reliability of the joint by incorporating individual uncertainties for each degree of freedom of the SCFs (i.e., axial load crown, axial load saddle, in-plane bending moment, and out-of-plane bending moment). The results reveal that assuming the same uncertainty level (Coefficient of Variation of 0.2) as recommended by DNV-RP-C210 for each degree of freedom of the SCFs and including the uncertainty after obtaining the stress distribution from rainflow counting does not consistently yield conservative reliability index values, as it depends on the critical hot spot. It is essential to note that the simplified assumptions derived from the oil and gas sector may not directly translate to the offshore wind industry due to differences in loading conditions. A reduction of up to approximately 24% in the reliability index is observed for one critical hot spot, while an increase of up to 20% was observed for another. Overall, this paper provides valuable insights into the complex interplay of factors affecting the reliability of joints in offshore fixed jacket support structures, shedding light on the need for tailored approaches to address uncertainties in the specific context of the offshore wind industry.

The Spanish Short Dark Tetrad (SD4): Association With Personality and Psychological Problems.

The Short Dark Tetrad (SD4) is a recently developed instrument for assessing the "dark" personality traits of psychopathy, narcissism, Machiavellianism, and sadism. We aimed to examine the SD4's psychometric properties, adapting it into Spanish and exploring its structure, gender invariance, reliability, concurrent validity, and nomological network. A sample of 668 adults (Mage = 26.36, SD = 10.64, 69.2% females) completed the SD4 and other self-report questionnaires. The results demonstrated sound indices of reliability and concurrent validity, an adequate four-factor structure, and support for gender invariance. Furthermore, most of the findings about the nomological network were in line with prior hypotheses: All four SD4 scales were associated with low levels of agreeableness and antagonism; psychopathy was also related to low conscientiousness, disinhibition and impulse-control problems; narcissism was positively associated with extraversion and negatively associated with internalizing symptoms; Machiavellianism was uncorrelated with impulsivity-related problems, which made it distinct from the psychopathy profile; finally, sadism showed a similar pattern of associations to psychopathy, albeit less strongly linked to impulsivity problems and externalizing behavior. Overall, the SD4 presents sound psychometric properties, although the overlap between psychopathy and sadism warrants some caution.

Capacity optimization of independent hybrid renewable energy system under different operational strategies based on improved gray wolf algorithm

Renewable energy sources such as wind and solar power exhibit strong stochasticity and volatility, resulting in decreased power supply security and sustainability. A strategically optimized hybrid renewable energy system (HRES) is crucial for maintaining stable load operations and achieving sustainable energy development. This paper introduces an energy optimization management model for an independent HRES consisting of wind turbines, photovoltaic systems, diesel generators, and energy storage units. Operational strategies focus on energy storage-led loads following diesel generator-led load prioritizations. The model aims to optimize objectives to include economic, environmental, and power supply reliability indices. A dynamic adaptive parameter approach balances the parameters of the objective function at various instances. The optimal capacity allocation of the model is solved using the improved gray wolf optimization (IGWO) algorithm. This approach incorporates the golden sine strategy, the levy flight strategy, and the dynamic inverse learning strategy into the traditional GWO algorithm. Analyzing different test functions, evaluation metrics, and actual load data indicates that the proposed algorithm excels in global optimization capabilities and search speeds. The model significantly reduces the economic and environmental costs of the HRES microgrids and improves the sustainable development of renewable energy in various scenarios.

Optimum Embedment Depths for CFST Column-to-Foundation Connections: Analytical and Reliability-based Approach

In the present study, the pullout capacity models were developed to derive analytical expressions for the minimum required depths of embedment for conventional and two recently published schemes of connection for circular and square concrete-filled steel tubular (CFST) columns. The models were developed by equating the pullout strength of the tube with the pullout capacity of the reinforced concrete (RC) footing. The pullout capacity of the RC footing was a function of the strength of cement grout, footing concrete, and RC footing reinforcement. The analytical expressions derived for the minimum required depths of embedment were utilized to deduce limit state functions. These limit state functions were then employed for the reliability calculations by means of the Monte Carlo Simulation (MCS) technique. The reliability calculations provide optimum embedment depths for CFST columns for the given reliability level. It was shown for the required reliability index of 3.0, the requirements of nominal embedment depth for the second column-to-foundation connecting scheme for circular and square CFST columns are 37.3% and 45.2% less than their corresponding first schemes of connection. This outcome proves the superiority of the second scheme (as a result of mechanical interlocking) over the first scheme. A few parametric studies were also conducted to obtain results of practical value.

A MOGA and extended RPN based approach for heuristic key reliability characteristics analysis in manufacturing

The manufacturing process is the last opportunity to build an ideal design reliability index into a product. With the advancement of intelligent manufacturing technology, the concept of quality evolves from conformance to fitness for use, which emphasizes that reliability should be built into product with quality control. To effectively implement reliability assurance in the manufacturing process, it is necessary to accurately identify the vital few characteristics that are critical to reliability. Thus, a heuristic key reliability characteristic (KRC) analysis in manufacturing model fusing big quality data is proposed. First, on the basis of the fusion big quality data in manufacturing-by-manufacturing system Reliability-operational process Quality- output product Reliability (RQR) chain, a data driven KRC analysis model is proposed, and a reliability proactive control framework in manufacturing driven by KRC is expounded. Second, considering mass quality and reliability data, an effective KRC identification method based on data mining using multi-objectives genetic algorithm (MOGA) is established. Third, considering manufacturing data and product failure risk, an extended risk priority number (RPN) for KRC ranking is proposed. Finally, an example of an insulating base of subway locomotive is provided to verify the proposed approach.

PSYCHOMETRIC EVIDENCE OF A MEASURE OF GENERAL SELF-EFFICACY IN PERUVIAN SCHOOLCHILDREN: INTERNAL STRUCTURE, RELIABILITY AND FACTORIAL INVARIANCE AND PROPOSAL OF A BRIEF VERSION

The present research aims to propose a brief version of a measure of general self-efficacy, based on the Self-Efficacy Scale, and to evaluate its evidence of validity based on internal structure, reliability and factorial invariance according to sex. A total of 806 students (67.5% male and 32.5% female) of secondary level from 13 educational institutions in the city of Arequipa (Peru) participated. The data were processed using Confirmatory Factor Analysis and Item Response Theory. The results indicate that the original 20-item version of the 10-item Brief Alegre Self-Efficacy Scale is unidimensional with adequate goodness-of-fit and reliability indices (ω= .89). In addition, the presence of factorial invariance between males and females was tested. It is concluded that the proposed measure is valid and reliable, with a monotonic level of difficulty. However, more research is needed with representative samples and with respect to other educational variables.

Reliability-Based Design Optimization for a Vertical-Type Breakwater with an Emphasis on Sliding, Overturn, and Collapse Failure

To promote the application of reliability-based design within the Korean coastal engineering community, the author conducted reliability analyses and optimized the design of a vertical-type breakwater, considering multiple limit states in the seas off of Pusan and Gunsan – two representative ports in Korea. In this process, rather than relying on design waves of a specific return period, the author intentionally avoided such constraints. Instead, the author characterized the uncertainties associated with wave force, lift force, and overturning moment – key factors significantly influencing the integrity of a vertical-type breakwater. This characterization was achieved by employing a probabilistic model derived from the frequency analysis results of long-term in-situ wave data. The limit state of the vertical-type breakwater encompassed sliding, overturning, and collapse failure, with the close interrelation between wave force, lift force, and moment described using the Nataf joint probability distribution. Simulation results indicate, as expected, that considering only sliding failure underestimates the failure probability. Furthermore, it was shown that the failure probability of vertical-type breakwaters cannot be consistently secured using design waves with a specific return period. In contrast, breakwaters optimally designed to meet the reliability index requirement of <i>β</i>-3.5 to 4 consistently achieve a consistent failure probability across all sea areas.

An Evaluation of the Innovative Funding Models on Effective Administration of Secondary Schools in Imo State, Nigeria

There is room for innovations at every given point in time including in the financial management of educational institutions. Innovative funding models are contemporary funding models explored and used in effective and efficient financial maintenance of an institution. This institution can be educational, financial, religious, business, and so on. This study examined the influence of innovative funding models on administration of secondary schools in Imo State. Two research questions guided the study while two hypotheses were tested at 0.05 level of significance. Descriptive survey research design was adopted for the study. The population for the study was 297 principals which comprised 83 males and 214 females. There was no sampling procedure because the population was manageable. The questionnaire used for data collection was a 15-item structured titled “Innovative Funding Models on Effective Administration of Secondary Schools Questionnaire (IFMEASSQ)”. The questionnaire was validated by three research experts, two experts in Educational Management from the Department of Social Science Education and one expert in Measurement and Evaluation unit of Department of Educational Foundations, all from Faculty of Education, Imo State University (IMSU), Owerri. Cronbach Alpha statistic was used to compute the internal consistency of the instrument which yielded .83 and .81 for clusters 1 and 2 with an overall reliability index of .82 which indicates that the instrument was reliable. The research questions were answered using mean and standard deviation while the hypotheses were tested with t-test statistic. The findings of the study showed that community involvement and corporate sponsorships influence the administration of secondary education in Imo State to a great extent. Based on the findings, the study recommended that Imo State government should create attractive policies that would enhance massive participations of individuals and corporate bodies in the funding administration of secondary schools.

Domestic Violence Experienced by Women: Construction and Validation of a Measurement Method

Domestic violence, also known as intimate partner violence, constitutes a major social scourge recorded in virtually every country in the world. Despite the fact that previous studies investigating this societal phenomenon have evaluated it from various perspectives, little is known about how it is experienced by victims. However, the lack of knowledge of this experience prevents us from understanding that despite the fact that they are involved in relationships marked by violence, many women do not leave them, thus putting their physical and psychological health at risk. To help fill this gap, this research constructs and validates a new scale specific to experienced domestic violence. After formulating and verifying its items, a validation study was conducted with a sample of 406 female participants, aged between 18 and 61 years (M=29.63; SD=8,688). Factor analyses report that this measure has a one-dimensional factor structure with 12 items. The reliability indices are satisfactory (α=.95). The same goes for convergent, discriminant and predictive validity. The scale of experienced domestic violence has a general scope which will allow researchers to carry out an in depth investigation into the psychological, social, economic and political causes and consequences of experienced domestic violence with a view, in particular, to considering interventions for the recovery of the victims.

Managers' Micro-Communities Matter: The Impact of Clinical Supervision Team on Therapist Perception of the Organization.

Positive organizational climate - employee perceptions of their work environment and the impact of this environment on well-being and functioning - is associated with desirable organizational and client-level outcomes in mental health organizations. Clinical supervisors are well-positioned to impact organizational climate, as they serve as intermediaries between higher-level administrators who drive the policies and procedures and the therapists impacted by such decisions. This cross-sectional study examined the role of clinical supervisors as drivers of therapist perceptions of organizational climate within supervisory teams. Specifically, the present study investigated: (1) shared perceptions of organizational climate among therapists on the same supervisory team; (2) predictors of therapist climate perceptions. Eighty-six therapists were supervised by 22 supervisors. Indices of interrater agreement and interrater reliability of therapists on the same supervisory team were examined to determine shared or distinct perceptions of organizational climate. Multi-level models were used to examine whether supervisor attitudes towards evidence-based practices and therapist perceptions of supervisor communication predicted perceived organizational climate. Results showed perceptions of organizational cohesion and autonomy were shared among therapists on the same supervisory team and distinct from therapists on different supervisory teams. Therapist perceptions of their supervisor's communication was positively associated with perceptions of organizational cohesion and autonomy. These findings align with emerging evidence that middle managers shape their employees' experience of their work environment through communication strategies. These findings also point to the potential for intervening at lower organizational levels to improve overall organizational climate.

Interval valued reliability indices assessment of multi-state system using interval $$L_{z}$$-transform

Interval valued reliability indices assessment of multi-state system using interval $$L_{z}$$-transform

Optimizing Learning Environments: Strategic Planning, Organizing, and Storage Techniques Needed for Building Construction Workshops in Technical Colleges

The main purpose of the study was to optimize the learning environments through strategic planning, organizing, and storage techniques needed by teachers for building construction workshops in technical colleges. The study was guided by three specific objectives, three research questions as well as three null hypotheses conducted in Gombe State using descriptive survey research design. The population for the study was 63 individuals, consisting of 21 School Administrators, 28 Building Construction Teachers, and 14 Workshop Staff from all Government Science and Technical Colleges in Gombe State. There was no sampling as the entire population was used because it was manageable. A structured questionnaire tagged titled "Management of Building Construction Workshop for Effective Teaching and Learning Questionnaire (MTBCWETLQ)," divided into four sections (A-D) covering personal data (Section A) and addressing the research questions (Sections B-D). The instrument was validated by three experts from Department of Technology Education, Modibbo Adama University of Technology Yola. A trial test conducted on 10 building construction teachers, 10 workshop staff, and 6 administrators in Adamawa State, outside the study area, yielded a reliability index of 0.90 using the Cronbach alpha method. Data collected for the study was analyzed using Statistical Package for Social Sciences (SPSS) version 26.0. Mean statistics was used to answer the three research questions while ANOVA was used to test the hypotheses at 0.05 level of significance. Findings of the study revealed among others that Planning techniques for managing building construction workshops involve identifying machine locations for safety, arranging facilities based on student enrollment projections, setting up layouts with clear student roles, and establishing appropriate workshop durations. Organizing techniques include arranging tools and materials before and after use, ensuring an efficient flow of materials, selecting equipment based on learning activities, and organizing materials according to their uses for enhanced supervision and safety. It is recommended that Staff involved in managing building construction workshops should undergo training or workshops to improve their planning techniques. Staff should be encouraged to adopt more effective organizing techniques in building construction workshops.

Teachers' Welfare as Determinants of Students Learning Outcomes in Junior Secondary Schools in Delta South Senatorial District

The study examined teachers' welfare as determinants of students’ learning outcomes in Junior Secondary schools in Delta South Senatorial District. The study had a sample size of 364 participants, and the instruments employed were the teachers' welfare questionnaire and the mathematics BECE). An estimate of dependability, using the Cronbach alpha approach, was obtained, and the resulting reliability index was 0.78. The research questions were addressed by calculating the coefficient of determination using Pearson's product moment correlation. Based on this data, it was determined that there is a favorable association between teacher welfare, decent salary payment, teacher advancement, and teacher incentives and student learning outcomes in Junior Secondary Schools in Delta South Senatorial Districts of Delta State. A joyful teacher with first-class welfare package will increase their drive which will aid good outcome. Based on the study findings, it was recommended that teachers’ welfare should be prioritized to sustain learning outcome of pupils due to high decline in teachers population, Educational stakeholders should prioritize teachers' welfare as an indispensable factor that power students learning outcome in schools, car and housing loans should be made available to teachers to encourage the present and future generations to take teaching as a first choice.