Rough set and rule-based multicriteria decision aiding

The aim of multicriteria decision aiding is to give the decision maker a recommendation concerning a set of objects evaluated from multiple points of view called criteria. Since a rational decision maker acts with respect to his/her value system, in order to recommend the most-preferred decision, one must identify decision maker's preferences. In this paper, we focus on preference discovery from data concerning some past decisions of the decision maker. We consider the preference model in the form of a set of "if..., then..." decision rules discovered from the data by inductive learning. To structure the data prior to induction of rules, we use the Dominance-based Rough Set Approach (DRSA). DRSA is a methodology for reasoning about data, which handles ordinal evaluations of objects on considered criteria and monotonic relationships between these evaluations and the decision. We review applications of DRSA to a large variety of multicriteria decision problems

Relaxation oscillations and canards in the Jirsa–Kelso excitator model: global flow perspective

This is the author accepted manuscript. The final version is available from Springer via the DOI in this record.Fenichel’s geometric singular perturbation theory and the blowup method have been very successful in describing and explaining global non-linear phenomena in systems with multiple time-scales, such as relaxation oscillations and canards. Recently, the blowup method has been extended to systems with flat, unbounded slow manifolds that lose normal hyperbolicity at infinity. Here, we show that transition between discrete and periodic movement captured by the Jirsa-Kelso excitator is a new example of such phenomena. We, first, derive equations of the Jirsa-Kelso excitator with explicit time scale separation and demonstrate existence of canards in the systems. Then, we combine the slow-fast analysis, blowup method and projection onto the the Poincar´e sphere to understand the return mechanism of the periodic orbits in the singular case, € = 0.KT-A gratefully acknowledges the financial support of the EPSRC via grant EP/N014391/1. This work was supported by The Higher Committee For Education Development in Iraq (HCED) and the University of Mosul

Identification of Biodiversity and Other Forest Attributes for Sustainable Forest Management: Siberian Forest Case Study

This paper attempts to identify characteristics of biodiversity and other (forest) ecosystem conditions that are considered essential for a description of ecosystem functioning and development of sustainable forest management practices in the Siberian forests. This is accomplished through an analysis of net primary production of phytomass (NPP) which acts as a proxy for ecosystem functioning. Rough Sets (RS) analysis is applied to study the Siberian ecoregions classified into compact and cohesive NPP performance classes. Through a heuristic procedure, a reduced set of attributes is generated for a NPP classification problem. In order to interpret relationships between various forest characteristics, so-called "interesting rules" are generated on a basis of reduced problem description. These "interesting rules" provide means to draw conclusions in the form of knowledge statements about functioning of the Siberian forests

An improved direct colorimetric method for the quantitative analysis of urinary hippuric acid as an index of toluene exposure

An improved direct colorimetric method for determining the concentration of urinary hippuric acid as an index of toluene exposure was described. One tenth ml of urine was diluted with 0.4 ml 0.01 M phosphate buffer H 6.9 and mixed with 0.5 ml pyridine. The mixture was layered on 0.2 ml benzenesulfonyl chloride. The reaction was started by mixing for one min with a mechanical shaker. The colored solution was allowed to stand for 30 min, diluted with 5 ml ethanol, and absorbance measured at 410 nm within 30 min after the dilution. The coefficient of variation of this method was 6% and the recovery 103% when urine contains about 0.2-0.5 mg hippuric acid per ml of urine. The concentration was linear up to 2.0 mg per ml hippuric acid in a specimen.</p

Covid-19 and the Role of Intellectual Property - Position Statement of the Max Planck Institute for Innovation and Competition of 7 May 2021

In this Statement, the authors take a position on the waiver of intellectual property (IP) protection currently being considered by the members of the World Trade Organisation. The waiver was initiated by India and South Africa as a measure to enable rapid access to affordable medical products that are necessary to combat Covid-19. The initiative gained momentum after the US decided to support it. The authors do not consider this path to be expedient. The Statement presents factual and legal arguments why a comprehensive waiver of IP protection is unlikely to be a necessary and suitable measure towards the pursued objective. Overall, it argues that IP rights may so far have played an enabling and facilitating rather than hindering role in overcoming Covid-19. The global community might not be better off if IP rights are waived, neither during nor after the pandemic. There are more efficient and direct ways to supply developing countries with vaccines quickly – if the industrialised countries are willing to do their share

Multicriteria decision support using rules that represent rough-graded preference relations

peer reviewedThe approach described in this paper aims to support multicriteria choice and ranking of actions when the input preference information acquired from the decision maker is a graded comprehensive pairwise comparison (or ranking) of reference actions. It is based on decision-rule preference model induced from a rough approximation of the graded comprehensive preference relation among the reference actions. The set of decision rules applied to a new set of actions provides a graded fuzzy preference relation, which can be exploited by weighted-fuzzy net flow score or lexicographic-fuzzy net flow score procedure to obtain a final recommendation in terms of the best choice or of the ranking

Learning the preferences of physicians for the organization of result lists of medical evidence articles

Objectives Despite many clinical decision support systems (CDSSs) being rated as highly usable, CDSSs have not been widely adopted in clinical practice. We posit that there are factors aside from usability that impact adoption of CDSSs; in particular we are interested in the role played by MDs intrinsic motivation to use computer-based support. Our research aim is to investigate the relationship between usability and intrinsic motivation in order to learn about adoption of CDSS in clinical practice. Methods Following the evaluation of a CDSS, 19 MDs completed a 2 part questionnaire about their intrinsic motivation to use computer-based support in general and the usability of the evaluated CDSS. Results The analysis of MDs motivation to use computer-based support demonstrated that MDs are comfortable using computer-based support and in general find using it quite easy (a motivation rating of 0.66 on a (0, 1) scale was computed). However MDs also reported a perceived lack of competence associated with a lack of prior experience using technology in practice, which results in pressure and tension. The considered CDSS scored highly on all usability dimensions and a usability rating of 0.74 was recorded. The examination of the relationship between motivation and usability suggested that users who were motivated to use computer-based support experienced better usability than those who reported low levels of motivation. Conclusions Our small case study suggests that an important factor supplementing the usability of CDSSs is intrinsic motivation to use computer-based support in general. We posit that the lack of such a measure thus far in CDSS evaluation may to some extent explain seeming MD satisfaction with CDSSs on one hand, but their limited adoption on the other. We recommend that clinical managers responsible for deploying CDSS should invest in training MDs to use technology underlying computer-based support applications instead of focusing only on the features of the specific CDSS to be deployed