Intelligent synthetic composite indicators with application

This article is proposing an alternative approach to develop Intelligent Synthetic Composite Indicators (ISCI). The suggested approach utilizes Fuzzy Proximity Knowledge Mining technique to build the qualitative taxonomy initially, and then Fuzzy c-means is employed to form the new composite indicators. A fully worked application is presented. The application uses Information and Communication Technology real variables to form a new unified ICT index, illustrating the method of construction for ISCI. The weighting and aggregation results obtained were compared against Principal Component Analysis, Factor Analysis and the Geometric mean to weight and aggregate synthetic composite indicators. This study also compares and contrasts two special Fuzzy c-means techniques that is, the Optimal Completion Strategy and the Nearest Prototype Strategy to impute missing values. The results are compared against statistical imputation techniques. The validity and robustness of all techniques are evaluated using Monte Carlo simulation. The results obtained suggest a novel, intelligent and non-biased method of building future composite indicators.     

Hereditary Gottron''s acrogeria with recessive transmission: a report of four cases in one family

The tegumental topography of the plerocercoid of Gymnorhynchus gigas is described for the first time. The surface features were examined by scanning electron microscopy. Eight different types of microthrix pattern were found. Differences in the shape and density of microtriches depend on their location. A unique morphological feature is reported herein, namely, filamentous microtriches that were arranged in clusters with a dome-shaped pattern when the bothridial surface was relaxed but sunk into a crater when the bothridial surface was contracted. In contrast to other trypanorhynchan cestodes, palmate microtriches are not found on the tegument of this plerocercoid. The microtriches on the caudal extension gradually increased in length with growing distance from the blastocyst, which showed short knob-like structures. These structures developed into elongated filiform microtriches on the posterior region of the caudal extension.     

Quasi-steady state model of an ice rink refrigeration system

A quasi-steady model for the refrigeration system of an indoor ice rink was developed based on a combination of thermodynamic relations, heat transfer correlations and data available in the manufacturer’s catalogue. The system includes five compressors, rejects heat to the ambient air and uses R-22 to keep a stream of brine at a temperature of approximately −9°C. The model has been validated by comparison with measured values and with data from the manufacturer’s catalogue. It was then used to simulate its performance over a typical meteorological year. Results for a representative day include the number of compressors in operation at any given moment, their power consumption, the coefficient of performance (COP) of the cycle and of the system, as well as the heat rejected by the condensers and the corresponding mass flow rate of the cooling air. They show that the evaporation pressure is essentially constant while the condensation pressure varies from about 1600 to 2000 kPa. The COP of the system varies between 1.9 and 2.5. Results for the entire year show that the heat rejected during phase change is approximately four times that due to desuperheating and demonstrates the interest of recovering heat from both processes. Finally, the model is used to illustrate the advantages of a control strategy which limits the maximum number of simultaneously operating compressors to four. This strategy results in a 10% decrease of the energy used by the compressor motors and a 20% decrease of the peak power demand but increases the temperature of the brine at the exit from the chillers by approximately 0.5°C during short periods following the ice resurfacing operations.     

Maintaining the validity of simulation models using prediction intervals

This paper presents a methodology for maintaining the operational validity of simulation models of observable systems in order to support operational decisions. In this methodology, real-time system data are continuously compared against simultaneous prediction intervals on selected responses constructed using the simulation model. The methodology is illustrated through using a case example of a simulation model of a flexible manufacturing system. Different invalidating discrepancies between the model and the system are investigated. Results indicate that using nontraditional responses may lead to a faster detection of invalidating changes, the speed of detection is a function of the scope of the change, and the model may evolve with the system and continue to be used to guard against random changes.     

Estimating most productive scale size with imprecise-chance constrained input–output orientation model in data envelopment analysis

Varieties of data envelopment analysis (DEA) models have been formulated to assess performance of decision making units (DMUs) in various fields with different data such as: deterministic, interval, fuzzy, etc. Classic DEA requires that values of all inputs and outputs are known exactly. However, this assumption may not be true, since in practice, data can not be precisely measured. Furthermore, a realistic situation is no longer realistic when imprecise and uncertain information are neglected to analyze efficiency of DMUs and measurement errors and data entry errors, etc.     

Design of low-power single-stage operational amplifiers based on an optimized settling model

Settling behavior of operational amplifiers (opamps) is important in many analog signal-processing applications. In this paper, the analysis of single-stage opamps based on settling time has been performed. A simple yet accurate model for the settling response of first-order opamps that modifies conventional models is proposed to revise the equations. The presented approach leads to a new simple settling-based design methodology for single-stage operational amplifiers. Circuit-level simulations demonstrate the effectiveness of the procedure.     

Energetic reasoning revisited: application to parallel machine scheduling

We consider the problem of minimizing makespan on identical parallel machines subject to release dates and delivery times. We present several new feasibility tests and adjustment techniques that consistently improve the classical energetic reasoning approach. Computational results carried out on a set of hard instances provide strong evidence that the performance of a state-of-the-art exact branch-and-bound algorithm is substantially improved through embedding the proposed enhanced energetic reasoning.     

Generalized theory of uncertainty (GTU)—principal concepts and ideas

Uncertainty is an attribute of information. The path-breaking work of Shannon has led to a universal acceptance of the thesis that information is statistical in nature. Concomitantly, existing theories of uncertainty are based on probability theory. The generalized theory of uncertainty (GTU) departs from existing theories in essential ways. First, the thesis that information is statistical in nature is replaced by a much more general thesis that information is a generalized constraint, with statistical uncertainty being a special, albeit important case. Equating information to a generalized constraint is the fundamental thesis of GTU. Second, bivalence is abandoned throughout GTU, and the foundation of GTU is shifted from bivalent logic to fuzzy logic. As a consequence, in GTU everything is or is allowed to be a matter of degree or, equivalently, fuzzy. Concomitantly, all variables are, or are allowed to be granular, with a granule being a clump of values drawn together by a generalized constraint. And third, one of the principal objectives of GTU is achievement of NL-capability, that is, the capability to operate on information described in natural language. NL-capability has high importance because much of human knowledge, including knowledge about probabilities, is described in natural language. NL-capability is the focus of attention in the present paper. The centerpiece of GTU is the concept of a generalized constraint. The concept of a generalized constraint is motivated by the fact that most real-world constraints are elastic rather than rigid, and have a complex structure even when simple in appearance. The paper concludes with examples of computation with uncertain information described in natural language.