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An established method of modelling a controller using a fuzzy relation is examined in the light of recent criticisms. An alternative formulation of the fuzzy relation is described and use of the fuzzy relation as a synthesis tool is discussed. A new approach to tuning such controllers is proposed.

The law relating to foreign bodies in food and drink continues to grow in volume, if not in clarity. It is generally accepted that their presence may constitute an infringement of Section 2, Food and Drugs Act, 1955; that dust (or cement or paint or any other extraneous matter) adhering to the interior of a bottle means that the bottle is not clean within the meaning of regulation 27 (1), Milk and Dairies Regulations, 1959 or regulation 6 (2), Food Hygiene Regulations, 1960. This has been held to be so even if the dust (or other adherent substance) has been shown to be sterile. In Jones v. Bryn Dairy, Ltd., (1954), Q.B.D., a case under the Milk and Dairies Regulations, 1949 where the offence concerned dust adhering to the interior of a bottle of milk, Lord Goddard made the robust statement of the obvious—“clean means clean”—and rejected the argument that the bottle which contained the very small quantity of dust was clean because the dust itself was sterile. It had yet to be decided that similar considerations applied to a foreign body lying loose in the bottle; that such a bottle of milk was not in a state of thorough cleanliness before use. The decision of the Divisional Court in South Coast Dairies Ltd. v. Halstead (1963), (reported in December, 1963 issue of B.F.J.,) has now done this.

AT the present time leisure is a subject which does not attract much serious attention. Sporadic discussions break out now and again among small groups; or it provides a topic for the popular press during the ‘silly season’. There is, however, a distinct possibility that in the measurable future an Institute of Leisure Study will be needed.

Risk assessment is a very important step toward managing risks in various organizations and industries. One of the most extensively applied risk assessment techniques is failure mode and effects analysis (FMEA). In this paper, a novel fuzzy multiple-criteria decision-making (MCDM)-based FMEA model is proposed for assessing the risks of different failure modes more accurately.

In this model, the weight of each failure mode is considered instead of risk priority number (RPN). Additionally, three criteria of time, cost and profit are added to the three previous risk factors of occurrence (O), severity (S) and detection (D). Furthermore, the weights of the mentioned criteria and the priority weights of the decision-makers calculated by modified fuzzy AHP and fuzzy weighted MULTIMOORA methods, respectively, are considered in the proposed model. A new ranking method of fuzzy numbers is also utilized in both proposed fuzzy MCDM methods.

To show the capability and usefulness of the suggested fuzzy MCDM-based FMEA model, Kerman Steel Industries Factory is considered as a case study. Moreover, a sensitivity analysis is conducted for validating the achieved results. Findings indicate that the proposed model is a beneficial and applicable tool for risk assessment.

To the best of authors’ knowledge, no research has considered the weights of failure modes, the weights of risk factors and the priority weights of decision-makers simultaneously in the FMEA method.

A FIRST attempt to give the dates of the introduction of printing into the various places in a county, generally results in an exhibition of the ignorance of the compiler. Further, when the information has not been systematically collected but simply forms part of a general collection of titles, relating not only to that county but to the country at large, the local specialist will probably quote vaguely of “rushing in where” he “fears to tread.” My only apology, and I consider it a perfectly valid one, for publishing the following notes on Essex printers and booksellers, is that no one else has done it.

Fatigue associated with shift work is a well-established and pervasive problem in policing that affects officer performance, safety, and health. It is critical to understand the extent to which fatigue degrades officer driving performance. Drowsy driving among post-shift workers is a well-established risk factor yet no data are available about officer injuries and deaths due to drowsy driving. The purpose of this paper is to assess the impact of fatigue associated with work shift and prior sleep on officers’ non-operational driving using laboratory experiments to assess post-shift drowsy driving risks and the ability of a well-validated vigilance and reaction-time task to assess these risks.

Experienced police patrol officer volunteers (n=78) from all four shifts of a medium-sized city’s police department were tested using a within- and between-subjects design to assess the impact of fatigue on individual officers, as well as the impact of different work shifts, on post-shift driving performance. Controlled laboratory experiments were conducted during which participants drove high-fidelity driving training simulators on two occasions: immediately following five consecutive 10:40-hour patrol shifts (fatigued condition) and again 72 hours after completing the last shift in a work cycle (rested condition).

Generalized linear mixed-model analyses of driving performance showed that officers working night shifts had significantly greater lane deviation during post-shift, non-operational driving than those working day shifts (F=4.40, df=1, 150, p=0.038). The same method also showed that easy to measure psychomotor vigilance test scores for reaction time predicted both lane deviation (F=31.48, df=1, 151, p < 0.001) and collisions (F=14.10, df=1, 151, p < 0.001) during the simulated drives.

Simulated driving tasks done by participants were generally less challenging than patrol or off-duty driving and likely underestimate the impact of fatigue on police driving post-shift or during extended shifts.

This is the first experimental research to assess the impact of shiftwork, fatigue, and extended shifts on police post-shift drowsy driving, a known risk factor for shift workers in general.

A problem of handling fuzzy quantities in a process of knowledge acquisition and deriving an inference mechanism by means of fuzzy relation equations is studied in extensive way. It is clearly pointed out that both of them are closely related and correspond to various types of fuzzy relation equations that are considered. Their relevance to the form of knowledge collected is also indicated. A problem of dimension reduction of a knowledge base is considered as well. Two modes of the use of the knowledge base (goal‐, and data‐driven) are also studied.

The attributes that influence the selection of applicants and the relevant crediting decisions are naturally distinguished by interactions and interdependencies. A new method of possibilistic discrimination analysis (MPDA) was developed for the second stage to address this phenomenon. The method generates positive and negative discrimination measures for each alternative applicant in relation to a particular attribute. The obtained discrimination pair reflects the interaction of attributes and represents intuitionistic fuzzy numbers (IFNs). For the aggregation of applicant's discrimination intuitionistic fuzzy assessments (with respect to attributes), new intuitionistic aggregation operators, such as AsP-IFOWA and AsP-IFOWG, are defined and studied. The new operators are certain extensions of the well-known Choquet integral and Yager OWA operators. The extensions, in contrast to the Choquet aggregation, take into account all possible interactions of the attributes by introducing associated probabilities of a fuzzy measure.

For optimal planning of investments distribution and decreasing of credit risks, it is crucial to have selected projects ranked within deeply detailed investment model. To achieve this, a new approach developed in this article involves three stages. The first stage is to reduce a possibly large number of applicants for credit, and here, the method of expertons is used. At the second stage, a model of improved decisions is built, which reduces the risks of decision making. In this model, as it is in multi-attribute decision-making (MADM) + multi-objective decision-making (MODM), expert evaluations are presented in terms of utility, gain, and more. At the third stage, the authors construct the bi-criteria discrete intuitionistic fuzzy optimization problem for making the most profitable investment portfolio with new criterion: 1) Maximization of total ranking index of selected applicants' group and classical criterion and 2) Maximization of total profit of selected applicants' group.

The example gives the Pareto fronts obtained by both new operators, the Choquet integral and Yager OWA operators also well-known TOPSIS approach, for selecting applicants and awarding credits. For a fuzzy measure, the possibility measure defined on the expert evaluations of attributes is taken.

The comparative analysis identifies the applicants who will receive the funding sequentially based on crediting resources and their requirements. It has become apparent that the use of the new criterion has given more credibility to applicants in making optimal credit decisions in the environment of extended new operators, where the phenomenon of interaction of all attributes was also taken into account.

The purpose of this paper is to outline a theoretical approach to approximate reasoning. The author shares the view that the emergence of an algebraic approach is vital for the advancement of conceptual understanding as well as technical knowledge of knowledge engineering. The notion of a knowledge diagram is suggested as a unifying framework to explain some significant results in this area. This is a categorial point of view promoting the idea that the concept of transformation be taken as fundamental in place of membership. Entities are characterized by their universal properties which specify their role in relation to other entities. Once the operational description is known, internal structure is of lesser importance.

Examines the ability of an expert computer system to evaluate uncertainty within a valuation context and thus emulate the professional skill of the valuer. Shows that because property valuation programs based on regression analysis require data input for each variable, they are unable to evaluate uncertainty and hence to apply the rational judgement which enables the human valuer to produce a valuation in the light of uncertain or incomplete information.