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Job Corps is the United State’s largest and most comprehensive training program for disadvantaged youth aged 16–24 years old. A randomized social experiment concluded that, on average, individuals benefited from the program in the form of higher weekly earnings and employment prospects. At the same time, “young adults” (ages 20–24) realized much higher impacts relative to “adolescents” (ages 16–19). Employing recent nonparametric bounds for causal mediation, we investigate whether these two groups’ disparate effects correspond to them benefiting differentially from distinct aspects of Job Corps, with a particular focus on the attainment of a degree (GED, high school, or vocational). We find that, for young adults, the part of the total effect of Job Corps on earnings (employment) that is due to attaining a degree within the program is at most 41% (32%) of the total effect, whereas for adolescents that part can account for up to 87% (100%) of the total effect. We also find evidence that the magnitude of the part of the effect of Job Corps on the outcomes that works through components of Job Corps other than degree attainment (e.g., social skills, job placement, residential services) is likely higher for young adults than for adolescents. That those other components likely play a more important role for young adults has policy implications for more effectively servicing participants. More generally, our results illustrate how researchers can learn about particular mechanisms of an intervention.

This paper provides a fuller characterization of the analytical upper bounds for American options than has been available to date. We establish properties required of analytical upper bounds without any direct reliance on the exercise boundary. A class of generalized European claims on the same underlying asset is then proposed as upper bounds. This set contains the existing closed form bounds of Margrabe, (1978) and Chen and Yeh (2002) as special cases and allows randomization of the maturity payoff. Owing to the European nature of the bounds, across-strike arbitrage conditions on option prices seem to carry over to the bounds. Among other things, European option spreads may be viewed as ratio positions on the early exercise option. To tighten the upper bound, we propose a quasi-bound that holds as an upper bound for most situations of interest and seems to offer considerable improvement over the currently available closed form bounds. As an approximation, the discounted value of Chen and Yeh's (2002) bound holds some promise. We also discuss implications for parametric and nonparametric empirical option pricing. Sample option quotes for the European (XEO) and the American (OEX) options on the S&P 100 Index appear well behaved with respect to the upper bound properties but the bid–ask spreads are too wide to permit a synthetic short position in the early exercise option.

In this paper, we study partial identification of the distribution of treatment effects of a binary treatment for ideal randomized experiments, ideal randomized experiments with a known value of a dependence measure, and for data satisfying the selection-on-observables assumption, respectively. For ideal randomized experiments, (i) we propose nonparametric estimators of the sharp bounds on the distribution of treatment effects and construct asymptotically valid confidence sets for the distribution of treatment effects; (ii) we propose bias-corrected estimators of the sharp bounds on the distribution of treatment effects; and (iii) we investigate finite sample performances of the proposed confidence sets and the bias-corrected estimators via simulation.

Uncertainty is ubiquitous in practical engineering and scientific research. The uncertainties in parameters can be treated as interval numbers. The prediction of upper and lower bounds of the response of a system including uncertain parameters is of immense significance in uncertainty analysis. This paper aims to evaluate the upper and lower bounds of electric potentials in an electrostatic system efficiently with interval parameters.

The Taylor series expansion is proposed for evaluating the upper and lower bounds of electric potentials in an electrostatic system with interval parameters. The uncertain parameters of the electrostatic system are represented by interval notations. By performing Taylor series expansion on the electric potentials obtained using the equilibrium governing equation and by using the properties of interval mathematics, the upper and lower bounds of the electric potentials of an electrostatic system can be calculated.

To evaluate the accuracy and efficiency of the proposed method, the upper and lower bounds of the electric potentials and the computation time of the proposed method are compared with those obtained using the Monte Carlo simulation, which is referred to as a reference solution. Numerical examples illustrate that the bounds of electric potentials of this method are consistent with those obtained using the Monte Carlo simulation. Moreover, the proposed method is significantly more time-saving.

This paper provides a rapid computational method to estimate the upper and lower bounds of electric potentials in electrostatics analysis with interval parameters. The precision of the proposed method is acceptable for engineering applications, and the computation time of the proposed method is significantly less than that of the Monte Carlo simulation, which is the most widely used method related to uncertainties. The Monte Carlo simulation requires a large number of samplings, and this leads to significant runtime consumption.

Multiple classifier systems have been used widely in computing, communications, and informatics. Combining multiple classifier systems (MCS) has been shown to outperform a single classifier system. It has been demonstrated that improvement in ensemble performance depends on either the diversity among or the performance of individual systems. A variety of diversity measures and ensemble methods have been proposed and studied. However, it remains a challenging problem to estimate the ensemble performance in terms of the performance of and the diversity among individual systems. The purpose of this paper is to study the general problem of estimating ensemble performance for various combination methods using the concept of a performance distribution pattern (PDP).

In particular, the paper establishes upper and lower bounds for majority voting ensemble performance with disagreement diversity measure Dis, weighted majority voting performance in terms of weighted average performance and weighted disagreement diversity, and plurality voting ensemble performance with entropy diversity measure D.

Bounds for these three cases are shown to be tight using the PDP for the input set.

As a consequence of the authors' previous results on diversity equivalence, the results of majority voting ensemble performance can be extended to several other diversity measures. Moreover, the paper showed in the case of majority voting ensemble performance that when the average of individual systems performance P is big enough, the ensemble performance P^m resulting from a maximum (information‐theoretic) entropy PDP is an increasing function with respect to the disagreement diversity Dis. Eight experiments using data sets from various application domains are conducted to demonstrate the complexity, richness, and diverseness of the problem in estimating the ensemble performance.

The solution of dynamic problems of structures using finite element method leads to generalised eigenvalue problem. In general, if the material properties are crisp (exact) then we get crisp eigenvalue problem. But in actual practice, instead of crisp material properties we may have only bounds of values as a result of errors in measurements, observations and calculations or it may be due to maintenance induced error etc. Such bounds of values may be considered in terms of interval or fuzzy numbers. The purpose of this paper is to develop a fuzzy filtering procedure for finding real eigenvalue bounds of different structural problems.

The proposed fuzzy filtering algorithm has been developed in terms of fuzzy number to solve the fuzzy eigenvalue problem. The initial bounds of fuzzy eigenvalues are filtered to obtain precise eigenvalue bounds which are depicted by fuzzy (Triangular Fuzzy Number) plots using α-cut.

Previously, bounds of eigenvalues of interval matrices have been investigated by few authors. But when the structural problem consists of fuzzy material properties, then the interval eigenvalue bounds may be obtained for each interval of the fuzzy number. The proposed algorithm has been applied for standard fuzzy eigenvalue problems which may be extended to generalised fuzzy eigenvalue problems for obtaining filtered fuzzy bounds.

The developed fuzzy filtering method is found to be efficient for different structural dynamics problems with fuzzy material properties.

Embedded technologies are one of the fastest growing sectors in information technology today and they are still open fields with many business opportunities. Hardly any new product reaches the market without embedded systems components any more. However, the main technical challenges include the design and integration, as well as providing the necessary degree of security in an embedded system. This paper aims to focus on a new processor architecture introduced to face security issues.

In the short term, the main idea of this paper focuses on the implementation of a method for the improvement of code security through measurements in hardware that can be transparent to software developers. It was decided to develop a processor core extension that provides an improved capability against software vulnerabilities and improves the security of target systems passively. The architecture directly executes bound checking in hardware without performance loss, whereas checking in software would make any application intolerably slow.

Simulation results demonstrated that the proposed design offers a higher performance and security, when compared with other solutions. For the implementation of the Secure CPU, the SPARC V8‐based LEON 2 processor from Gaisler Research was used. The processor core was adapted and finally synthesised for a GR‐XC3S‐1500 board and extended.

As numerically, most systems run on dedicated hardware and not on high‐performance general purpose processors. There certainly exists a market even for new hardware to be used in real applications. Thus, the experience from the related project work can lead to valuable and marketable results for businesses and academics.

The purpose of this paper is to acquire strict upper and lower bounds on quantities of slender beams on Winkler foundation in finite element analysis.

It leans on the dual analysis wherein the constitutive relation error (CRE) is used to perform goal-oriented error estimation. Due to the coupling of the displacement field and the stress field in the equilibrium equations of the beam, the prolongation condition for the stress field which is the key ingredient of CRE estimation is not directly applicable. To circumvent this difficulty, an approximate problem and the solution thereof are introduced, enabling the CRE estimation to proceed. It is shown that the strict bounding property for CRE estimation is preserved and strict bounds of quantities of the beam are obtainable thereafter.

Numerical examples are presented to validate the strict upper and lower bounds for quantities of beams on elastic foundation by dual analysis.

This paper deals with one-dimensional (1D) beams on Winkler foundation. Nevertheless, the present work can be naturally extended to analysis of shells and 2D and 3D reaction-diffusion problems for future research.

CRE estimation is extended to analysis of beams on elastic foundation by a decoupling strategy; strict upper bounds of global energy norm error for beams on elastic foundation are obtained; strict bounds of quantities for beams on elastic foundation are also obtained; unified representation and corresponding dual analysis of various quantities of the beam are presented; rigorous derivation of admissible stresses for beams is given.

Supplier selection is a complex multiple criteria decision (MCDM) problem which directly depends on decision makers’ choice. Some decisions are getting involved with linguistic variables and they are not mathematically operable. To solve a typical decision problem through MCDM techniques, a number or a numerical interval should be defined. The purpose of this paper is to focus on that numerical interval and in a case of supplier selection, the aim is to close the decisions to the real number that the decision maker mentions and this number is in a numerical interval.

The proposed method deals with grey relational analysis (GRA) and develops it by applying triangular fuzzy numbers. The grey numbers have two defined bounds; the proposed method defines two fuzzy bounds for each grey attribute. In the proposed method, the fuzzy membership function has been employed for each bounds of grey attribute to make them to fuzzy bounds with two undefined bounds. Also to make comparison, with employing of TOPSIS technique, both of the grey fuzzy combination decision matrix and the original grey decision matrix are obtained.

The results indicate that, except to the ideal solutions, the grey relation coefficient for each alternative is too close to each other. Indeed, they are too close to zero. Applying the proposed method in problem of supplier selection shows the difference between two selected supplier in proposed method and the original grey method.

As mentioned heretofore this paper aims to make decision makers’s decision more accurate and actually there is no other researches which used this combination method.

In structural mechanics, systems with damping factor get converted to nonlinear eigenvalue problems (NEPs), namely, quadratic eigenvalue problems. Generally, the parameters of NEPs are considered as crisp values but because of errors in measurement, observation or maintenance-induced errors, the parameters may have uncertain bounds of values, and such uncertain bounds may be considered in terms of closed intervals. As such, this paper aims to deal with solving nonlinear interval eigenvalue problems (NIEPs) with respect to damped spring-mass systems having interval parameters.

Two methods, namely, linear sufficient regularity perturbation (LSRP) and direct sufficient regularity perturbation (DSRP), have been proposed for solving NIEPs based on sufficient regularity perturbation method for intervals. LSRP may be used for solving NIEPs by linearizing the eigenvalue problems into generalized interval eigenvalue problems, and DSRP may be considered as a direct solution procedure for solving NIEPs.

LSRP and DSRP methods help in computing the lower and upper eigenvalue and eigenvector bounds for NIEPs which contain the crisp eigenvalues. Further, the DSRP method is computationally efficient compared to LSRP.

The efficiency of the proposed methods has been validated by example problems of NIEPs. Moreover, the procedures may be extended for other nonlinear interval eigenvalue application problems.