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Abstract In practice, fractional factorial split-plot (FFSP) designs are widely used when the levels of some factors are very difficult or expensive to be changed or controlled. The factors of an FFSP design are divided into two groups, the whole plot (WP) and subplot factors. Under the circumstances that the experimenter has some prior information about the significance of the WP factors, the paper gives a new optimal criterion for selecting designs, that is, the minimum aberration of type WP (WP-MA). Construction of optimal fractional factorial split-plot designs with respect to the WP-MA criterion is considered. The WP-MA FFSP designs with 8, 16, and 32 runs are tabulated. Highlights • This paper proposes a new optimal criterion for selecting split-plot designs. • Some theoretical results of design construction for small fractions are provided. • The optimal fractional factorial split-plot designs with 8, 16, and 32 runs are tabulated. [ABSTRACT FROM AUTHOR]

Highlights • We provide a comparative study for dynamic programming multilevel image thresholding using Otsu criterion. • 2.45x is obtained compared with state-of-the-art-algorithm. • Different data sets from different application are used to assess the performance. Abstract Multi-level thresholding of a gray image is one of the basic operations in computer vision, with applications in image enhancement and segmentation. Various criteria for the selection of threshold level values were proposed. One of these criterion is the Otsu criterion that uses maximization of between-class variance approach. Although applying multi-level thresholding to an image is a straightforward operation, computation of the threshold levels with Otsu criterion is a computationally expensive process. In this paper, we revisit a dynamic programming algorithm that provides exact and efficient solution to the problem and compare it with modern meta-heuristic algorithms. We provide a rigorous proof for the correctness of the algorithm. The algorithm computational cost is linear in the number of threshold levels. We compare the algorithm with state of the art algorithms and verify its superior performance. The experiments show that we could gain speedup up to 2.45 ×. [ABSTRACT FROM AUTHOR]

Abstract A perfect combination of fact-based and value-based judgments is what multiple criteria decision-making (MCDM) issues pursue. Tolerability constraints, an important part of value-based judgments, are easily observable and have drawn attention in theory. However, their practical applications in the MCDM process are still in their infancy. This paper aims to fill the gap between theory and application. A framework for tolerability constraints in the context of non-independent criteria is proposed and operated for the first time. In this framework, global tolerability constraints on the overall decision-making process and local constraints on a single criterion are considered at the same time. Furthermore, mandatory/ sufficient requirements are regarded as different aspects of tolerability constraints. Two cases are given to illustrate the application of the proposed framework. In short, the proposed framework deepens the understanding of MCDM issues and extends its application, especially with respect to tolerability requirements. [ABSTRACT FROM AUTHOR]

Abstract The purchasing process consists of multiple, non-isolated phases that describe the interactions between consumers and products. One of these phases is the evaluation of alternatives, in which the consumer compares the benefits that will be obtained from each product or service depending on a set of criteria. Recently, the rise of online ecosystems has fueled the development of new purchasing-decision prediction models (PDPM) based on the shared opinions, concerns, and expectations of customers. Commonly, these PDPMs are constructed as multiple criteria decision analysis (MCDA) methods, where experts ascertain the consumer's purchasing criteria, as well as the importance of them, by means of surveys and their own experience. Although relying on experts may be appropriate for identifying criteria, this approach is not suitable for assessing the importance of said criteria due to the large volume of information available on the Web. Furthermore, the preferences of consumers in online ecosystems evolve constantly. In this regard, we consider that the information about purchase-criteria importance should be derived exclusively from the opinions of consumers. However, the attitude and thought-process leading to purchases contain inherent relationships that consumers are not able to express explicitly; consequently, we explore the possibility to make use of the synergies between criteria along user preferences. This paper proposes a new PDPM that estimates the importance of the criteria and values the alternatives by only considering the opinions expressed by consumers in digital ecosystems, while using an expert-defined set of criteria. The proposed approach extracts the weights of both criteria and alternatives and determines the implicit synergies within them without the need of additional input. Lastly, it uses the Choquet integral for weight and valuation aggregation and determines a purchase ranking. This model has been tested in real examples, obtaining satisfactory results. [ABSTRACT FROM AUTHOR]

Highlights • This paper applies a recent concept, namely the concept of stratification. • The dynamicity of the decision environment when a decision is made is considered. • The method mimics the brain's decision making process and has the potential for future applications in artificial intelligence. • The method will be useful to researchers who are applying different MCDM methods. Abstract Multiple Criteria Decision Making (MCDM) methods generally require the decision maker to evaluate alternatives with respect to decision criteria and also to assign importance weightings to the criteria. Then, based on the assigned weightings, the best alternative can be selected. However, after a decision is made it often happens that the decision maker becomes doubtful whether the right weightings have been assigned to the criteria given that a variety of eventualities may occur in the near future. The main aim of this paper is to address this concern and improve the application of MCDM methods by addressing possible fluctuations in the criteria weightings. The recently proposed concept of stratification (CST) is used in conjunction with MCDM methods to stratify the decision environment. The method is then applied to a supplier selection problem. The stratified MCDM (SMCDM) approach is in its early stages only and requires further research to reach its maturity. [ABSTRACT FROM AUTHOR]

Mohr-Coulomb (M-C) criterion is widely used for isotropic brittle materials, although it has some disadvantages which limit its wider application. One important disadvantage of this theory is that it ignores the effect of the intermediate principal stress, although it has an important influence on materials behaviour. Therefore, Mohr-Coulomb theory is actually used only for materials in biaxial state of stress. In this paper, a modified form of Mohr 's criterion has been suggested, in order to overcome this limitation. The modified criterion takes into account the influence of intermediate principal stress in the case of materials under triaxial loading conditions. On the basis of two new hypotheses, a real triaxial state of stress is replaced by a virtual biaxial state of stress. The above mentioned stress states are considered to be equivalent for a material when the failure is imminent in both cases. Both Mohr 's theory and the concept of equivalence of stress states are combined in order to obtain the virtual biaxial state of stress, which is determined using all three principal stresses. The modified Mohr 's theory can be used only for triaxial state of stress. For biaxial and uniaxial state of stress it is reduced to the classical one. The proposed hypotheses have an important advantage because does not require additional material coefficients. The calculated values using the virtual biaxial state of stress and the linear M-C criterion are in good agreement with experimental data for grey cast iron. The article also presents a compact statistical analysis for both stresses and errors, in order to objectively assess the effectiveness of the formulated hypotheses. [ABSTRACT FROM AUTHOR]

In this paper, we consider the two-dimensional dissipative surface quasi-geostrophic equation, and establish a logarithmically improved regularity criterion. Consequently, our result extends the regularity criterion result of Dong and Pavlovié (2009). In addition, a logarithmically improved regularity criterion to the three-dimensional Navier–Stokes equations is also derived by the same arguments. Therefore, this result extends and improves many previous works. [ABSTRACT FROM AUTHOR]

This paper introduces an active learning approach to the fitting of machine learning interatomic potentials. Our approach is based on the D-optimality criterion for selecting atomic configurations on which the potential is fitted. It is shown that the proposed active learning approach is highly efficient in training potentials on the fly, ensuring that no extrapolation is attempted and leading to a completely reliable atomistic simulation without any significant decrease in accuracy. We apply our approach to molecular dynamics and structure relaxation, and we argue that it can be applied, in principle, to any other type of atomistic simulation. The software, test cases, and examples of usage are published at http://gitlab.skoltech.ru/shapeev/mlip/ . [ABSTRACT FROM AUTHOR]

Ground penetrating radar (GPR) is widely used for subsurface detection due to the nondestructive characteristics. GPR signal is non-stationary because of complex medium environment, and time-frequency analysis is the powerful tool for the research of GPR signal. In this paper, a new generalized S transform with parameters optimization is proposed to analyze the GPR signal. In the proposed scheme, first a flexible window function replaces the fixed window function of S transform, then the criterion of time-frequency concentration is used to optimize the parameters of the window function, the aim is to improve the time-frequency resolution and applicability of S transform. The experimental results for synthetic data and practical GPR data show the proposed scheme can enhance the energy concentration in time-frequency domain effectively and provide better layer recognition and target detection performance. [ABSTRACT FROM AUTHOR]

Aim Emotion regulation (ER) theories and measurement scales have received considerable attention in clinical and research settings. However, there is a need for independent validation of these scales to ensure rigor within this field. The aim of the current study was to examine the factorial, convergent, and criterion validity of one of the most popular measures of ER, the Cognitive Emotion Regulations Questionnaire (CERQ), both short and long form. Methods The CERQ (and CERQ-short), positive and negative affect schedule, and difficulties in emotion regulation scale were administered to 795 participants (70% female, M age = 36.36). Results Confirmatory factor analysis supported the 9-factor structure of the CERQ-short, but not the full CERQ. Adequate fit for the full CERQ was achieved after the removal of three poorly performing items. Correlations supported the convergent and criterion validity of both scales, although the CERQ-short demonstrated weaker associations than the full scale. Conclusions The factorial, convergent, and criterion validity of the CERQ and CERQ-short were generally supported. However, future research may wish to examine several high inter-factor correlations that were observed among the full CERQ, as well as the weaker validity demonstrated by the CERQ-short. [ABSTRACT FROM AUTHOR]

Several evidences of hydrologic data series being nonstationary in nature have been found to date. This has resulted in the conduct of many studies in the area of nonstationary frequency analysis. Nonstationary probability distribution models involve parameters that vary over time. Therefore, it is not a straightforward process to apply conventional goodness-of-fit tests to the selection of an appropriate nonstationary probability distribution model. Tests that are generally recommended for such a selection include the Akaike’s information criterion (AIC), corrected Akaike’s information criterion (AICc), Bayesian information criterion (BIC), and likelihood ratio test (LRT). In this study, the Monte Carlo simulation was performed to compare the performances of these four tests, with regard to nonstationary as well as stationary generalized extreme value (GEV) distributions. Proper model selection ratios and sample sizes were taken into account to evaluate the performances of all the four tests. The BIC demonstrated the best performance with regard to stationary GEV models. In case of nonstationary GEV models, the AIC proved to be better than the other three methods, when relatively small sample sizes were considered. With larger sample sizes, the AIC, BIC, and LRT presented the best performances for GEV models which have nonstationary location and/or scale parameters, respectively. Simulation results were then evaluated by applying all four tests to annual maximum rainfall data of selected sites, as observed by the Korea Meteorological Administration. [ABSTRACT FROM AUTHOR]

Constrained Clustering allows to make the clustering task more accurate by integrating user constraints, which can be instance-level or cluster-level constraints. Few works consider the integration of different kinds of constraints, they are usually based on declarative frameworks and they are often exact methods, which either enumerate all the solutions satisfying the user constraints, or find a global optimum when an optimization criterion is specified. In a previous work, we have proposed a model for Constrained Clustering based on a Constraint Programming framework. It is declarative, allowing a user to integrate user constraints and to choose an optimization criterion among several ones. In this article we present a new and substantially improved model for Constrained Clustering, still based on a Constraint Programming framework. It differs from our earlier model in the way partitions are represented by means of variables and constraints. It is also more flexible since the number of clusters does not need to be set beforehand; only a lower and an upper bound on the number of clusters have to be provided. In order to make the model-based approach more efficient, we propose new global optimization constraints with dedicated filtering algorithms. We show that such a framework can easily be embedded in a more general process and we illustrate this on the problem of finding the optimal Pareto front of a bi-criterion constrained clustering task. We compare our approach with existing exact approaches, based either on a branch-and-bound approach or on graph coloring on twelve datasets. Experiments show that the model outperforms exact approaches in most cases. [ABSTRACT FROM AUTHOR]

This study investigated factor structure, reliability, and criterion validity of the original 12-item version as well as an abbreviated 10-item version of Mroczek and Kolarz' Negative and Positive Affect Scale (NAPAS). The sample (N = 2718) was drawn from the third wave of the National Study of Midlife in the United States (MIDUS III). Confirmatory Factor Analysis (CFA) and Exploratory Structural Equation Modeling (ESEM) were used to analyze the data. The 12-item version of the scale demonstrated acceptable psychometric properties. Equally good model fit and reliability and identical criterion correlations were also found for the 10-item version of the scale. This suggests that scale shortening did not have any adverse psychometric effects. ESEM produced slightly better fit and considerably lower factor correlations, and thus was considered superior to CFA in the context of this study. Overall, these results indicate that both versions of the NAPAS show evidence of acceptable psychometric quality. Implications of the results and avenues for future research are discussed. [ABSTRACT FROM AUTHOR]

In this paper, the collaborative optimization is improved to tackle multidisciplinary problems with coupling design variables within disciplines. The design variables are first distinctly classified into private and public ones according to disciplines. A criterion is then proposed to judge the coupling of private variables with the public variables. For the coupling case, a strategy is suggested to decouple the variables before performing the collaborative optimization. To demonstrate the effectiveness of the improved collaborative optimization, two practical optimization problems are comparatively studied for uncoupled design variables as well as coupled ones. It is shown that the present framework can achieve the better optimal results as compared with other methods. Furthermore, the judge criterion and the decoupling strategy are also validated. [ABSTRACT FROM AUTHOR]

We study a multiperiod portfolio selection problem in which a single period mean-standard-deviation criterion is used to construct a separable multiperiod selection criterion. Using this criterion, we obtain a closed form optimal strategy which depends on selection schemes of investor’s risk preference. As a consequence, we develop a multiperiod portfolio selection scheme. In doing so, we adapt a pseudo dynamic programming principle from other existing results. The analysis is performed in the market of risky assets only, however, we allow both market transitions and intermediate cash injections and offtakes. [ABSTRACT FROM AUTHOR]

College students must regulate much of their learning and hence it is important to discover whether they use effective study techniques, such as testing with feedback. We conducted three experiments to evaluate the degree to which college students use testing with feedback as they are learning key concept definitions. The three main issues of interest concerned (a) whether students tested themselves during practice, (b) whether they followed tests with feedback, and (c) whether they continued to practice until they could correctly recall each definition one or more times. In each experiment, students in the self-regulated group could choose to engage in three activities (test, study, or evaluate test responses) in whatever order or dosage they wanted during practice. For purposes of comparison in each experiment, a Criterion 3 group completed an experimenter-controlled schedule of test-study practice until each definition was correctly recalled three times. All participants completed a final test one week later. Among the key outcomes, students who self-regulated their learning used tests and often sought feedback soon after. When students incorrectly recalled a definition, they typically chose to study the definition, whereas when they recalled some of a definition correctly, they typically chose to evaluate the quality of their response. Although students on average continued to test themselves until they correctly recalled each definition once, they underperformed on the final test as compared to the Criterion 3 group. Thus, in the present context, students do use testing while learning, but results also suggest that they do not take full advantage of this effective study technique. [ABSTRACT FROM AUTHOR]

Background and objectives The Implicit Relational Assessment Procedure (IRAP) is a technique that is attracting a substantial body of research literature, particularly within the clinical domain. Method In response, the present paper outlines a meta-analysis of clinically-focused IRAP effects ( N = 494) to provide the first estimate of how well such effects validate against their respective criterion variables in general. Results The meta-analysis incorporated clinically-focused IRAP effects from 15 studies yielding a large effect size, r ¯ = .45, with a desirably narrow 95% credibility interval (.23, .67). The funnel plot and subsequent sensitivity analyses indicated that this meta-effect was not subject to publication bias. Limitations The present meta-effect is an estimate based upon an IRAP literature that is still evolving rapidly in the clinical domain, and so as per its accompanying credibility interval, all conclusions that follow are necessarily provisional even if bounded. Apart from the fact that the current meta-effect might be subject to inadvertent under- and/or over-estimations of the current literature, the present meta-effect might strengthen with further refinements of the IRAP. Conclusions The current meta-effect provides the means to calculate what sample size would be required to achieve a statistical power of .80 when testing the criterion validity of clinically-focused IRAP effects using a given parametric statistic. For example, first-order Pearson correlations would hypothetically require an N of 29–37 for such purposes depending upon how conservatively over-estimation of the present meta-effect is controlled for. Overall, the IRAP compares favourably with alternative implicit measures in clinical psychology. [ABSTRACT FROM AUTHOR]

Highlights: [•] We develop an assessment procedure of social information processing in adolescents. [•] Construct, content, and criterion validity explorations vary from moderate to high. [•] In secure residential care, adolescents with and without MBID do not differ on SIP. [•] The new SIP test instrument will be adjusted, extended, and improved. [Copyright &y& Elsevier]

The advancement of automated writing evaluation (AWE) has made it possible to complement instructor input with immediate scoring and qualitative feedback to inform students' writing development. However, little is known about the usefulness of AWE holistic scores for classroom purposes. In our longitudinal mixed-methods study, we utilized Criterion ®, an AWE service developed by Educational Testing Service (ETS), to investigate the use of holistic scores in three university-level English as second language (ESL) writing courses. We investigated the correlation between AWE scores and instructors' numeric grades and analytic ratings on two major course assignments and analyzed AWE score use from the perspectives of three ESL writing instructors and 67 students. Quantitative analyses yielded a series of low to moderate positive correlations between Criterion scores and both the instructors' grades and analytic ratings, which raised issues in integrating the scores for pedagogical purposes; survey and interview data showed that instructors used Criterion scores strategically to gauge students' writing needs. The students also made efforts to revise their papers in order to get a higher score. These findings added to previous work on the usefulness of AWE programs and provided justification for use or non-use of automatically generated scores for classroom-based formative assessment. [Copyright &y& Elsevier]

Abstract: A univariate clustering criterion for stationary processes satisfying a β-mixing condition is proposed extending the work of Bharath et al. (2013) to the dependent setup. The approach is characterized by an alternative sample criterion function based on truncated partial sums which renders the framework amenable to various interesting extensions for which limit results for partial sums are available. Techniques from empirical process theory for mixing sequences play a vital role in the arguments employed in the proofs of the limit theorems. [Copyright &y& Elsevier]

Abstract: We establish a blowup criterion for the two-dimensional (2D) full compressible Navier–Stokes system. The criterion is given in terms of the divergence of the velocity field only, and is independent of the temperature. The criterion tells that once the strong solution blows up, the -norm for the divergence of velocity blows up. [Copyright &y& Elsevier]

Highlights: [•] A modified M–K method for computation of extended stress-based FLC is proposed. [•] The effect of strain path on the predicted extended stress-based FLC is reexamined. [•] This new criterion is much less strain path dependent than the conventional FLC. [•] Through-thickness compressive normal stress is also considered in analysis. [Copyright &y& Elsevier]

Abstract: Criterion for softening of glassy solids, analogous to the Lindemann criterion of melting, is proposed. At glass softening the temperature ratio of root mean square atom displacement to mean interatomic distance is practically of constant value for different glasses. It is assumed that, when the root mean square amplitude of the thermal vibrations of an atom reaches a certain fraction of an interatomic distance, the excited atom loses its stability and the glass–liquid transition begins. The softening process in glasses as in crystals is due to the emergence of vibrational instability of atoms located in the lattice sites. [Copyright &y& Elsevier]

Highlights: [•] A criterion was proposed for predicting size effects in mode II brittle fracture. [•] Experiments were performed on rock samples to evaluate the proposed criterion. [•] Good estimates were provided for size dependent values of mode II fracture resistance. [Copyright &y& Elsevier]

Abstract: In this work an optimization problem on a classical elementary stochastic system, modeled as an Erlang-B (M/M/ ) loss system, is formulated by using a bicriteria approach. The problem is focused on the allocation of a given total of servers to a number of groups of servers capable of carrying certain offered traffic processes assumed as Poissonian in nature. Two main objectives are present in this formulation. First a criterion of equity in the grade of service, measured by the call blocking probabilities, entails that the absolute difference between the blocking probabilities experienced by the calls in the different service groups must be as small as possible. Second a criterion of system economic performance optimization requires the total traffic carried by the system, to be maximized. Relevant mathematical results characterizing the two objective functions and the set of the non-dominated solutions, are presented. An algorithm for traveling on based on the resolution of single criterion convex problems, using a Newton–Raphson method, is also proposed. In each iteration the two first derivatives of the Erlang-B function in the number of circuits (a difficult numerical problem) are calculated using a method proposed earlier. Some computational results are also presented. [Copyright &y& Elsevier]

Abstract: A new procedure to reduce uncertainties in reservoir simulation models using statistical inference and observed data is presented in this paper. Observed data is used to guide the obtainment of posterior probability density functions (pdf). The process starts by sampling from prior pdf. Through an iterative procedure, posterior pdf is obtained in each iteration, which is used to sample new models for the next iteration, until a stop criterion is reached. A detailed relationship between all uncertain attributes defined in the analysis and well responses (water and oil rate, flow pressure etc.) is performed. Finally, final ensembles are sampled in order to assess the dispersion of the responses before and after the reduction of uncertainty. In order to assess the robustness of the proposed method, three reservoir models were studied. The first case is a simple reservoir with eight uncertain attributes and was used for validation purposes. The second case, is a more complex synthetic model with 16 uncertain attributes. Finally, the application to a real field is shown. The results showed that the proposed method has potential to deal with the problem of reservoir uncertainty management. [Copyright &y& Elsevier]

Abstract: In this paper, the delay-dependent dissipativity of nonlinear delay differential equations is studied. A new dissipativity criterion is derived, which is less conservative than those in the existing literature in some cases, especially for equations with small delays. [Copyright &y& Elsevier]

Abstract: This paper presents a new method for detecting random-valued impulse noise (RVIN) in images. The proposed method is based on similar valued neighbor criterion and the detection of the noisy pixels are realized in maximum four phases. After the corrupted pixels detected in each phase, the median filtering is performed for only these pixels. As such, corrupted pixels are suppressed gradually at the end of the each phase. The performance of the proposed method is evaluated on different test images and compared with ten different comparison filters from the literature. It is shown from simulation results that proposed method provides a significant improvement over comparison filters. [Copyright &y& Elsevier]

Highlights: [•] Space–time constraints are embedded into the multi-state supernetwork approach. [•] Time profiles of activity and parking are coupled with time-dependent travel. [•] The proposed approach reports activity-travel patterns at a high level of detail. [•] A new bi-criterion label correcting “shortest” path algorithm is proposed. [•] Multi-state supernetwork approach is feasible for daily activity-travel scheduling. [ABSTRACT FROM AUTHOR]

Abstract: Autonomous system of stochastic differential equations which has a zero solution is considered. It is assumed that there exists a positive definite with respect to part of the variables function , such that corresponding operator LV is nonpositive. It is proved that if the set does not include entire semitrajectories of the system (2.1) almost surely then the zero solution is asymptotically stable in probability with respect to part of the variables. [Copyright &y& Elsevier]

Highlights: [•] We study a two-agent single-machine multi-objective scheduling problem. [•] We propose a branch-and-bound and seveal simulated annealing algorithms. [•] The branch-and-bound algorithm can solve problems of up to 24 jobs. [•] The mean error percentage of the combined SA algorithm is less than 0.5%. [ABSTRACT FROM AUTHOR]

Abstract: In this work, we study the regularity criterion of the three-dimensional nematic liquid crystal flows. It is proved that if the vorticity satisfies where denotes the critical Besov space, then the solution becomes a regular solution on . This result extends the recent regularity criterion obtained by Fan and Ozawa (2012) [11]. [Copyright &y& Elsevier]

Abstract: This study investigates the important composition of creativity by examining dimensions of restaurant space design from the expert''s perspective. This study presents a novel model of creativity assessment within the context of the Decision Making Trial and Evaluation Laboratory (DEMATEL) method application, and identified 6 main dimensions of creativity (Novelty, Centrality, Importance, Affect, Interactivity and Resolution). Qualitative and quantitative surveys were used in multiple stages of data collection. The results of the DEMATEL analysis show that the “centrality” dimension had significant influence over other dimensions of creativity, while “affect” and “importance” are influences given and received by other dimensions in restaurant space design. Overall, this study identified the relationships and interactions among 6 dimensions and 27 sub-dimensions of creativity and filled a gap created by traditional methods of setting strategies, which only considered the direct effects or single directions of criteria. Theoretical and empirical implications are also discussed. [Copyright &y& Elsevier]

Abstract: In this work we discuss global convergence of a general filter algorithm that depends neither on the definition of the forbidden region, which can be given by the original or slanting filter rule, nor on the way in which the step is computed. This algorithm basically consists of calculating a point not forbidden by the filter from the current point. Assuming that this step must be efficient, in the sense that near a feasible non-stationary point the decrease in the objective function is relatively large, we prove the global convergence of the algorithm. We also discuss that such a condition is satisfied if the step is computed by the SQP or Inexact Restoration methods. For SQP we present a general proof of this result that is valid for both the original and the slanting filter criterion. In order to compare the performance of the general filter algorithm according to the method used to calculate the step and the filter rule regarded, we present numerical experiments performed with problems from CUTEr collection. [Copyright &y& Elsevier]

Abstract: A new scheduling model with two-agent and sum-of-processing-times-based deterioration is proposed in this paper. Two agents compete to perform their respective jobs on a common single machine and each agent has his own criterion to optimize. The sum-of-processing-times-based deterioration of a job is that the actual job processing time is a function of the sum of the normal processing times of the already processed jobs. The objective is to minimize the total completion time of the first agent with the restriction that the makespan of the second agent cannot exceed a given upper bound. The optimal properties of the problems are given and the optimal polynomial time algorithms are proposed to solve the scheduling problems. [Copyright &y& Elsevier]

Abstract: Ensemble methods have been successfully used as a classification scheme. The reduction of the complexity of this popular learning paradigm motivated the appearance of ensemble pruning algorithms. This paper presents a new ensemble pruning method which highly reduces the complexity of ensemble methods and performs better than complete bagging in terms of classification accuracy. More importantly, it is a very fast algorithm. It consists in ordering all base classifiers with respect to a new criterion which exploits an unsupervised ensemble margin. This method highlights the major influence of low margin instances on the performance of the pruning task and, more generally, the potential of low margin instances for the design of better ensembles. Comparison to both the naive approach of randomly pruning base classifiers and another ordering-based pruning algorithm is carried out in an extensive empirical analysis. [Copyright &y& Elsevier]

Objective: To answer 2 research questions: what are the learning curve patterns of novices on the da Vinci skills simulator parameters and what parameters are appropriate for criterion-based robotic training. Materials and Methods: A total of 17 novices completed 2 simulator sessions within 3 days. Each training session consisted of a warming-up exercise, followed by 5 repetitions of the “ring and rail II” task. Expert participants (n = 3) performed a warming-up exercise and 3 repetitions of the “ring and rail II” task on 1 day. We analyzed all 9 parameters of the simulator. Results: Significant learning occurred on 5 parameters: overall score, time to complete, instrument collision, instruments out of view, and critical errors within 1-10 repetitions (P <.05). Economy of motion and excessive instrument force only showed improvement within the first 5 repetitions. No significant learning on the parameter drops and master workspace range was found. Using the expert overall performance score (n = 3) as a criterion (overall score 90%), 9 of 17 novice participants met the criterion within 10 repetitions. Conclusion: Most parameters showed that basic robotic skills are learned relatively quickly using the da Vinci skills simulator, but that 10 repetitions were not sufficient for most novices to reach an expert level. Some parameters seemed inappropriate for expert-based criterion training because either no learning occurred or the novice performance was equal to expert performance. [ABSTRACT FROM AUTHOR]

Abstract: We present a new criterion function for blockmodeling two-way two-mode relation matrices when the number of blocks as well as the equivalence relation are unknown. For this, we specify a measure of fit based on data compression theory, which allows for the comparison of blockmodels of different sizes and block types from different equivalence relations. We arm an alternating optimization algorithm with this criterion and demonstrate that the method reproduces consensual blockings of three datasets without any pre-specification. We perform a simulation study where we compare our compression-based criterion to the commonly used criterion that measures the number of inconsistencies with an ideal blockmodel. [Copyright &y& Elsevier]

Abstract: We consider response-adaptive design of clinical trials under a variance-penalized criterion in the presence of mismeasurement. An explicit expression for the variance-penalized criterion with misclassified dichotomous responses is derived for response-adaptive designs and some properties are discussed. A new target proportion of treatment allocation is proposed under the criterion and related simulation results are presented. [Copyright &y& Elsevier]

Abstract: Dark side traits have been associated as much with success as failure in specific occupations. This study examines the possibility that some “dark side” traits may be advantageous in particular occupations by focusing on the relationship of eleven dark side traits with six, self-report, validated measures of occupation behaviour and potential. Nearly 5000 British adults completed the Hogan Development Survey (HDS), and the Hogan Personality Inventory (HPI) which has six criterion-based measures of occupational scales. Whilst some disorders (i.e. Excitable, Sceptical) seemed consistently associated with low work outcome and potential ratings, others seemed either neutral or positively associated (Bold, Diligent). Some dark side traits were highly variable being positively associated with some occupational scales, but not others (Mischievous, Colourful). The total ‘potential’ index of three potential measures showed most positive correlations with dark-side traits. The present results suggest that the manifestation of specific dark side traits may not always lead to work problems. [Copyright &y& Elsevier]

Abstract: Selection of the appropriate site for solid waste facilities is a complex problem and requires an extensive evaluation process, because it is very difficult to develop a selection criterion that can precisely describe the preference of one location over another. Therefore selection of these sites can be viewed as a multiple criteria decision-making or multiple attributes decision-making problem. For this purpose, we propose a technique that can effectively take managerial preferences and subjective data into consideration, along with quantitative factors. The tool proposed here relies on the use of the analytical network process (ANP) and to help integrate managerial evaluations into a more quantitatively based decision tool, data envelopment analysis (DEA) is applied. In this paper, a location selection procedure is presented to construct an undesirable facility applying ANP and DEA approaches in two stages. In the first stage ANP approach is used, results of this stage are inputs for the second stage. In this stage, DEA is applied to select the best location. Finally, to illustrate the proposed framework, at “Results and discussion” section, a total of four undesirable facility locations are evaluated. [Copyright &y& Elsevier]

Abstract: This paper investigates the problem of global finite-time stabilization of a chain of integrators. Based on finite-time stability theory of homogeneous system, a criterion is proposed for the global finite-time stabilization of the integrators by a single-state feedback control law. The result is then applied to locally finite-time stabilize a multiscroll saturated chaotic system via homogeneous approximation. [Copyright &y& Elsevier]

Abstract: Finding the lowest common ancestor (LCA) of two nodes in a binary tree has been focused both in graph theory and computer science. The paper puts forward and proves an analytic criterion for the LCA of two neighboring nodes in a complete binary tree. The criterion mainly concerns addition, subtraction and bitwise operations, needs no searching procedures and thus is easy to implement in software programming as well as hardware programming. An algorithm that has logarithmic time complexity is also presented with C-language implementation in the paper. [Copyright &y& Elsevier]

Abstract: Index tracking aims to select portfolios that imitate the behavior of a stock index. A tracking strategy is referred to as partial when the tracking portfolio is solely formed by a subset of stocks, so enabling a substantial cost reduction in comparison with full tracking. Three criteria are usually employed in the literature when building the tracking portfolio: tracking error variance, excess return and tracking portfolio variance. This paper considers a new parameter for use with the above: frontier curvature. This criterion is not defined for a particular portfolio, but for all the portfolios that define the tracking frontier. The main implication is that a manager can satisfy different investment profiles with the same subset of stocks. The manager will therefore reduce transaction costs as all the portfolios on the frontier contain the same stocks. [Copyright &y& Elsevier]

Abstract: We consider the framework of stochastic multi-armed bandit problems and study the possibilities and limitations of forecasters that perform an on-line exploration of the arms. These forecasters are assessed in terms of their simple regret, a regret notion that captures the fact that exploration is only constrained by the number of available rounds (not necessarily known in advance), in contrast to the case when the cumulative regret is considered and when exploitation needs to be performed at the same time. We believe that this performance criterion is suited to situations when the cost of pulling an arm is expressed in terms of resources rather than rewards. We discuss the links between the simple and the cumulative regret. One of the main results in the case of a finite number of arms is a general lower bound on the simple regret of a forecaster in terms of its cumulative regret: the smaller the latter, the larger the former. Keeping this result in mind, we then exhibit upper bounds on the simple regret of some forecasters. The paper ends with a study devoted to continuous-armed bandit problems; we show that the simple regret can be minimized with respect to a family of probability distributions if and only if the cumulative regret can be minimized for it. Based on this equivalence, we are able to prove that the separable metric spaces are exactly the metric spaces on which these regrets can be minimized with respect to the family of all probability distributions with continuous mean-payoff functions. [Copyright &y& Elsevier]