Imprecise Conditions Research Articles

Failure Mode and Effect Analysis with a Fuzzy Logic Approach

Failure mode and effect analysis (FMEA) is one of the most used techniques in risk management due to its potential to solve multidisciplinary engineering problems. The role of experts is fundamental when developing the FMEA; they identify the failure modes by expressing their opinion based on their experience. A relevant aspect is a way in which the experts evaluate to obtain the indicator of the risk priority number (RPN), which is based on qualitative analysis and a table of criteria where they subjectively and intuitively determine the factor level (severity, occurrence, and detection) for each of the failures. With this, imprecision is present due to the interpretation that each one has regarding the failures. Therefore, this research proposes a fuzzy logic evaluation system with a solid mathematical basis that integrates these conditions of imprecision and uncertainty, thus offering a robust system capable of emulating the evaluation form of experts to support and improve decision making. One of the main contributions of this research is in the defuzzification stage, adjusting the centroid method and treating each set individually. With this, the RPN values approximate to the conventional technique were obtained. Simulations were carried out to test and determine the system’s best structure. The system was validated in a textile company in southern Guanajuato. The results demonstrate that the system reliably represents how experts perform risk assessment.

A Fuzzy Model for Reasoning and Predicting Student’s Academic Performance

Evaluating students’ academic performance is crucial for assessing the quality of education and educational strategies. However, it can be challenging to predict and evaluate academic performance under uncertain and imprecise conditions. To address this issue, many research works have employed fuzzy concepts to analyze, predict, and make decisions about students’ academic performance. This paper investigates the use of fuzzy concepts in research related to evaluating, analyzing, predicting, or making decisions about student academic performance. The paper proposes a fuzzy model, called FPM (Fuzzy Propositional Model), for reasoning and predicting students’ academic performance. FPM aims to address the limitations of previous studies by incorporating propositional logic with fuzzy sets concept, which allows for the representation of uncertainty and imprecision in the data. FPM integrates and transforms if-then rules into weighted fuzzy production rules to predict and evaluate academic performance. This paper tests and evaluates the FPM in two scenarios. In the first scenario, the model predicts and examines the impact of absenteeism on academic performance where there is no clear relation between the two parts of the dataset. In the second scenario, the model predicts the final exam results using the lab exam results, where the data are more related. The FPM provides good results in both scenarios, demonstrating its effectiveness in predicting and evaluating students’ academic performance. A comparison study of the FPM’s results with a linear regression model and previous work showed that the FPM performs better in predicting academic performance and provides more insights into the underlying factors affecting it. Therefore, the FPM could be useful in educational institutions to predict and evaluate students’ academic performance, identify underlying factors affecting it, and improve educational strategies.

An approach to investigate the supplementary inconsistency between time series data for predicting road pavement performance models

ABSTRACT Road agencies commonly face high level complexity of comprehensive pavement maintenance scheduling complications. This could be due to uncertainty of some parameters that substance in the predicting models. Disregarding this uncertainty of such parameters in the road maintenance scheduling problems may lead to imprecise solutions and unreliable road conditions. Frequently time series data that have a hierarchical structure are used for predicting road surface or pavement structure distresses models. However, further realistic and accurate predicted models are those consider supplementary inconsistency between time series data with utilising a predictive approach that imposes knowledge of the input parameters. The purpose of this study is to test this theory by comparing the predictions of models developed using two approaches and their accuracies in utilising the same data. These approaches are the traditional regression model (TRM) with only one level of heterogeneity approach and the hierarchical regression model (HRM) with many levels of heterogeneities approach. A Metro North Western (MNW) urban road network in Victoria (Australia) was considered as the case study for this study investigation where covering the condition of approximately 305 Km of asphalt surfaced pavements. By considering the structure of time series data, the study revealed that more accurate models could predict the pavement behaviour, the deterioration rate, and significantly influenced parameters. In addition, the study highlighted that it is essential to deliberate and process the hierarchical structure of datasets to consider the observed and unobserved heterogeneities in time series data for developing any pavement performance model using either deterministic or probabilistic prediction approaches. Multiple simulation scenarios have been performed for both approaches and the HRM approach shows more reasonable outputs. For predicted deterministic SIR models, road intervention (SIR ≥ 20) are triggered at age 12.5 when using TRM approach and at age 10.5 when using HRM approach. For predicted probabilistic SIR models, the surface condition of a section with SIR weighted average condition values of 2 is triggered at age 17.5 when using TRM approach and at age 10.5 when using HRM approach. This also refers to earlier maintenance scheduling is required when using the later approach because it deals confidentially with each road sections time series data. In that regard, ignoring the uncertainty in time series data of such factors in the road surfacing maintenance scheduling problems may lead to suboptimal solutions and unstable pavement conditions.

Competitive strategy selection in retail E-Commerce using IF AHP & TOPSIS methodology

Retail e-commerce has been growing over the years by attracting entrepreneurs’ attention. Increasing interest in retail e-commerce has affected competition and made it necessary to choose the right competition strategy. This study aims at selecting the right competition strategy to be successful in retail e-commerce under vague and imprecise conditions. AHP and TOPSIS methods are used under intuitionistic fuzzy environment, which allows decision-makers to reflect their hesitation in their judgements. After a literature review on retail, e-commerce, and competition strategy, the main criteria and sub-criteria of multicriteria retail e-commerce alternative selection are presented. Cost leadership, differentiation, and focusing strategies are evaluated as competitive strategies, based on the opinions of experts collected through a questionnaire. The results of the study show that the strategies are ranked as differentiation, focus, and cost leadership strategies, respectively.

Healthcare Sustainability Evaluation Using a Hybrid Fuzzy Multi-Criteria Decision-Making Model

Developing a sustainable healthcare system directly depends on the level of maturity in environmental, social, and economic practices. Although there are huge number of researches considering environmental, social, and economic aspects, to the best of our knowledge, no approach was found which unifies these dimensions as an integrated method to assess the current status of sustainable development in healthcare organizations. In order to cope with this gap, this article suggests a method for analyzing the sustainability indicator in healthcare systems by manipulating the sustainability dimensions, criteria, and attributes. The following research has collected 62 attributes and 15 criteria for three sustainability dimensions. A new implementation method is also proposed to make this approach applicable in real-world problems. The contributions of this paper can be distinguished as the healthcare system’s sustainability level in imprecise conditions is obtained, the capability of identifying the weak points in implementing sustainability aspects is presented, and a new methodology for collecting the fundamental data for measuring the sustainability level in healthcare systems is given. The findings of this paper assist the practitioners and experts to successfully evaluate the sustainability level of healthcare systems and significantly improve the performance of them.

Effects of International Customary Law in the Legal Order of the European Union

The customary provisions in EU law formally may take effect and be enforced within the domestic legal orders of the Member States and internal law of the international organizations. However, the substantive question is if and how the customary international law (in force) may be capable of creating individual rights (direct applicability) with a direct effect in national and EU courts. Also an informal relationship may be observed, when the international law and EU law share the same values and may influence each other. In consideration of the foregoing, the objective of this paper is to analyse the status of the rules in question within the legal regime of the EU (formal perspective), and especially their judicial application in the conditions of complexity and imprecision (substantive perspective), but the essential purpose is to analyse the final legal effect given within the EU regime to the international customary law. Keywords: customary law, international law, EU law

Assessing the causal impact of Chinese aid on vegetative land cover in Burundi and Rwanda under conditions of spatial imprecision

There has been considerable debate regarding the efficacy of international aid in meeting the dual goals of human development and environmental sustainability. Many donors have sought to engage with this challenge by introducing environmental safeguard and monitoring initiatives; however, evidence on the success of these interventions is limited. Evaluating aid is a particular challenge in the case of donors that do not disclose information on the nature, geographic location, or extents of their interventions. In such cases, new methods that extract and geoparse data on the activities of opaque donors through the manual interpretation of thousands of news and other articles allow us to investigate the impacts of these activities. However, residual spatial uncertainty in these data remains a potential source of bias. In this article, we apply and discuss a Geographic Simulation and Extrapolation (GeoSIMEX) approach to mitigate the spatial imprecision inherent in geoparsed data. In conjunction with GeoSIMEX, we test and contrast multiple approaches to reducing the imprecision of aid, including high-assumption cases in which other covariates (i.e., nighttime lights) are leveraged to allocate aid. In our application, we find that methods which do not account for spatial imprecision find statistically significant relationships between Chinese aid and vegetation change; after accounting for spatial uncertainty, findings are similar for Rwanda and inconclusive for Burundi.

NORMALIZED WEIGHTED GEOMETRIC BONFERRONI MEAN OPERATOR OF INTERVAL ROUGH NUMBERS – APPLICATION IN INTERVAL ROUGH DEMATEL-COPRAS

This paper presents a new approach to the treatment of uncertainty and imprecision in multi-criteria decision-making based on interval rough numbers (IRN). The IRN-based approach provides decision-making using only internal knowledge for the data and operational information of a decision-maker. A new normalized weighted geometric Bonferroni mean operator is developed on the basis of the IRN for the aggregation of the IRN (IRNWGBM). Testing of the IRNWGBM operator is performed through the application in a hybrid IR-DEMATEL-COPRAS multi-criteria model which is tested on real case of selection of optimal direction for the creation of a temporary military route. The first part of hybrid model is the IRN DEMATEL model, which provides objective expert evaluation of criteria under the conditions of uncertainty and imprecision. In the second part of the model, the evaluation is carried out using the new interval rough COPRAS technique.

Obowiązek zachowania tajemnicy adwokackiej jako okoliczność uzasadniająca odmowę zeznań w trybie art. 180 § 2 k.p.k.

The paper is devoted to the institution of refusal to testify by a witness in criminal proceedings with indication to the obligation to keep the advocate’s professional secrecy. The refusal itself, though it constitutes an obstacle to the reaching of the material truth, stems from the special character of the profession of an advocate which belongs to the group of the so-called professions of public trust. The paper stresses the ambiguous relationship between corporation regulations and the provisions of the Polish Code of Criminal Proceedings from 1997 and two forms of the secrecy are distinguished, i.e. the strict attorney’s secrecy and the secrecy of the legal defence. The imprecise conditions for releasing a person from the advocate’s secrecy on the basis of Art. 180 § 2 of the Code of Criminal Proceedings have been criticised.

Merlin: Exploratory Analysis with Imprecise Queries

Merlin supports exploratory search in large databases. The user interacts with it by specifying probability distributions over attributes, which express imprecise conditions about the entities of interest. Merlin helps the user home in on the right query conditions by addressing three key challenges: (1) efficiently computing results for an imprecise query, (2) providing feedback about the sensitivity of the result to changes of individual conditions, and (3) suggesting new conditions. We formally introduce the notion of sensitivity and prove structural properties that enable efficient algorithms for quantifying the effect of uncertainty in user-specified conditions. To support interactive responses, we also develop techniques that can deliver probability estimates within a given realtime limit and are able to adapt automatically as interactive query refinement proceeds.

A new fuzzy multi-objective optimisation method with desirability function under uncertainty

Step method (STEM) is one of the most efficient and usable method of multi-objective decision making (MODM), and it is in the interactive category which uses decision makers (DMs) preference information during problem solving. In recent years, step method (STEM) has been developed based on the desirability function, namely D-STEM, in which the shortcoming of the STEM has been removed. To confront the problem in the real-world, paying attention to imprecision and uncertainty in decision making should be considered; however, in such status, D-STEM is unable to solve complex problem under uncertainty. In this paper, a new version of multi-objective optimisation method under a fuzzy environment with desirability function concept, namely FD-STEM, is proposed to deal with uncertain and imprecise conditions. Fuzzy uncertainties and imprecisions are considered in all parameters including objective coefficient, technologic coefficient, resources and decision variables as a fully fuzzy multi-objective optimisation. Finally, in an application example, decision making in manufacturing industry is presented and discussed based on consequents of fuzzy desirability function and with a fuzzy ranking function. Also, by using transformation method, the application example is solved and based on the overall desirability they are compared.

Optimizing the Joint Replenishment and Delivery Scheduling Problem under Fuzzy Environment Using Inverse Weight Fuzzy Nonlinear Programming Method

In reality, decision-makers are always in front of imprecise and vague operational conditions. We propose a practical multiobjective joint replenishment and delivery scheduling (JRD) model with deterministic demand and fuzzy cost. This model minimizes the total cost defuzzified by the signed distance method and maximizes the credibility that the total cost does not exceed the budget level. Then, an inverse weight fuzzy nonlinear programming (IWFNLP) method is adopted to formulate the proposed model. This method embeds the idea of inverse weights into the Max-Min fuzzy model. Thirdly, the fuzzy simulation approach and differential evolution algorithm (DE) are utilized to solve this problem. Results show that solutions derived from the IWFNLP method satisfy the decision-maker’s desirable achievement level of the cost objective and credibility objective. It is an effective decision tool since it can really reflect the relative importance of each fuzzy component. Our study also shows that the improved DE outperforms DE with a faster convergence speed.

Flexible data queries

The Structured Query Language (SQL) has been established as a standard for querying relational databases. However, users face the problem how to define their requirements for data by the exact query conditions. This work examines advantages of fuzzy queries, which provide a better representation of the user requirements by expressing imprecise conditions through linguistic terms. Further, the paper discusses solving empty and overabundant answer problems, revealing similarities in database entities and applying preferences in query conditions. Finally, paper discusses practical realisations of fuzzy queries.

Extended State Observer for Sensorless Single Phase Stirling Linear Generator Drives

The extended state observer (ESO) was applied in the sensorless single phase Stirling linear generator drives in this paper. The structure of the linear generator was introduced and mathematical model was built. To detect the mover position in the condition of position sensorless, the back-EMF ESO was deduced to calculate the position. This strategy was realized in the simulation and experiment. Compared with the normal state observer, in the conditions of noise and imprecision of generator parameters, ESO would improve the robustness of the system.

Gene network models robust to spatial scaling and noisy input

Many biological systems are inherently noisy, yet demonstrate robustness to perturbations and changes in external influences. Such is the case in the Bicoid–Hunchback (Bcd–Hb) system, which is critical to axis specification in the developing Drosophila embryo. We use this system as motivation to explore the larger problem of how precise patterning can be achieved under imprecise conditions. While evidence suggests Bicoid gradients are uncorrelated with respect to embryo length, downstream genes, such as Hb, are expressed in a precise manner with regard to position along the anterior–posterior (AP)-axis. In addition to precision under variability of embryo length, Hb also exhibits robustness to perturbations to the regulatory network, gene dosage, and temperature. Understanding the reduced variability of patterns in this system is of interest to both experimentalists and theoreticians, lending itself well to the field of mathematical modeling. In this paper, a class of reaction–diffusion models is presented, which produce precise patterns, despite receiving noisy input and other perturbations to the system. An essential property of the network includes the existence of a strong inhibitor for the Hb representative, where the strength of the inhibition is directly related to the amount of variation that can be tolerated. With a higher inhibitory effect, larger perturbations of Bcd can be made with relatively small changes to the location of the Hb boundary. Network topology and interaction strength are the essential properties of the minimal model giving rise to the robust features, and possible interpretations are made with regard to the Bcd–Hb system.

3D Field-Scale Environmental Multimedia System Validation of the Dispersion of Benzene for Trail Road Landfill Site and Its Risk Assessment

In this paper, a new modeling approach incorporating both a new environmental multimedia system (EMS) and the Monte Carlo method (MCM) is developed as a tool for the risk assessment of contaminants. An EMS has been developed and validated by the use of field data and investigation to create a 3D simulation of current conditions of the Trail Road Landfill area. In addition, given the high level of uncertainty associated with EMS practices, the MCM approach is embedded into the developed EMS to deal with vague or imprecise model and site conditions related to uncertainties in the system. In this study, two emission rates were examined for risk assessment of Trail Road Landfill site in the years 2016 and 2026; the data are predicted on the basis of the known production trend from 2001 to 2006. The risk quotient (RQ) factors, combined with present and future rates of chemical pollution, provide spatial and temporal assessment of risk from the leachate in Trail Road Landfill site. Results of the risk assessment approach reveal that as the landfill or oil drilling site becomes depleted, adverse effects on the multimedia environment associated with benzene concentration occur, and the potential risk levels have been quantified for the Trail Road Landfill site. The present study indicates that the dispersion of a large volume of pollutants from the landfill or the oil drilling site poses possible risks to the regional multimedia environment. The new EMS will serve as a risk assessment tool to address the fate and transportation of pollutants in complex multimedia environments. This tool will also be useful in the management of the resulting environmental impacts.

An Evolution of Form and Content: A Practical Guide to Use of the FASB's Conceptual Framework

Equations are only as reliable as we make them. This is true in all disciplines, including accounting. They are forms accommodating content. So, if the balance sheet (A = L OE) and the income statement (R – E = I) equations, for example, structure imprecise business conditions and operations, accountants try to improve their use, not ignore or discard them. The same is true of conceptual frameworks. They are as subject to error or misuse as the balance sheet and income statement equations. Consequently, the accounting profession is not willing to give up on conceptual frameworks, either. Although conceptual frameworks have not been in use as long as, and do not have the same degree of acceptance or understanding as, the income statement and balance sheet, they, too, can be structured to be as useful as the accounting equations. To accomplish this, a conceptual framework’s form is distinguished from its content, similar to distinguishing the form of the balance sheet, A = L OE, from its content. The form and content are then applied to an accounting transaction to demonstrate how to rigorously apply a conceptual framework.

An Integrated Model of Consumer Involvement Based on Fuzzy Automata

Involvement has become an important variable in consumer behavior and marketing research for a long time. Large amount of literature about involvement has existed now, and different types of involvement have been proposed, and so has the measurement of involvement. In real world, every consumer's decision-making process is not affected by just single involvement, but we are hard to find the research which discusses many antecedents, consequences, and more than one type of involvement at the same time from the existing literature. Because an individual's opinions and attitude have the characteristics of complexity and uncertainty, the data from investigation do not necessarily present a subject's inner minds. This study makes the most of the fuzzy sets, which solve uncertain and imprecise conditions, to transform the opinions belonging to human beings into the more accurate quantity. Consumer involvement is regarded as the object for this empirical study that comprehensively collects plenty of antecedents and consequences for consumer involvement. Especially, consumer involvement is categorized into product involvement, advertising involvement, purchase involvement, situational involvement, and enduring involvement to further discuss their interactions. We take advantage of the fuzzy automata that the inner operation resembles the development of consumer involvement for individuals to develop an integrated model of consumer involvement. The empirical results indicate that in addition to the selection of implications, a fitting model relies on the selection of compositions in the fuzzy automata. The fuzzy automata not only can deal with a great number of variables at the same time, but the interaction between different types of involvement as well.

Using Fuzzy Automata to Develop an Integrated Model for Personal Involvement in Advertising

Because of the reason that the individuals' thoughts have the complicated and uncertain characteristics in the field of social science, this study makes the most of the fuzzy sets, which solve uncertain and imprecise conditions, to transform the opinions belonging to human beings into the quantitative numbers. Advertising involvement is regarded as the object for this empirical study which comprehensively collects plenty of antecedents and consequences for advertising involvement. We take advantage of the fuzzy automata to develop an integrated model of advertising involvement. The results indicate that in addition to the selection of implications, a fitting model relies on the selection of compositions in the fuzzy automata. On the average, the standard composition, which is one of compositions in this study, is the most appropriate method for developing a model of advertising involvement.

The Idea of a Hydraulic Engineering Journal

The beginning of an editorship and the 50th anniversary of the first appearance of the Journal of the Hydraulics Division lend themselves to reflections on the ideals that can animate a hydraulic engineering journal. The contemporary context presents multiple extratechnical challenges. The gap between what is being practiced and what is being published is perceived as widening. Some would prefer a more scientific orientation, arguing that our journal compares unfavorably with other “purer” journals in its rigor and prestige. Recent events involving a prestigious science journal have cast doubt on the efficacy of the conventional peerreview procedure. The interests of our readership seem to be becoming increasingly fragmented and specialized. Developments in electronic publishing promise faster, less expensive publication aimed at more targeted audiences, thereby reinforcing the trend to fragmentation. These general issues are neither new nor peculiar to our journal see Batchelor 1981 for comments on some of these questions . Real-world problems with which hydraulic engineers must grapple are messy. The extremely broad spectrum of length and time scales, the large spatial heterogeneities, compounded by the sparsity of detailed data, the ill-understood or imprecise conditions at highly irregular, possibly deformable boundaries—all contribute to the technical questions that have traditionally fascinated and frustrated the hydraulician. These complexities may, however, pale in comparison with those raised by the more recent interest in the interaction between flow and biota and the larger implications for aqueous ecosystems. A definition of hydraulic engineering will not be attempted here; a personal and bracing view is expressed in Liggett 2002 . Suffice it to say that a response to these challenges requires an equally broad range of methodologies and a similarly heterogeneous journal, where fundamental studies of idealized situations, exploiting sophisticated experimental and theoretical techniques, will jostle with more applied investigations, guided by dimensional analysis and relying heavily on simple lumped models and statistical determination of empirical parameters and coefficients. In the ecology of ideas, a diversity of topics and techniques makes possible cross-fertilization and competition that should lead to a more robust and vibrant hydraulics community. Technical standards must be maintained, although the appropriate level of rigor can become a broad and deformable gray area for some, uncomfortably so with much left to “engineering” judgment. Probably rightly so, rigor has never been a hallmark of engineers;