Hybrid make-to-stock and make-to-order systems: a taxonomic review

Production planning and control (PPC) systems that employ aspects from both make-to-order (MTO) and make-to-stock (MTS) production control are known as hybrid MTS/MTO systems. While both MTO and MTS separately have been studied extensively, their combined use has received less attention. However, the literature on this topic is growing and this paper shows that the review performed in this paper is an important addition to the field. We categorise relevant literature according to a novel taxonomy and show that hybrid MTS/MTO production control can be used in different contexts. In addition, an overview of the modelling techniques and methods used in these papers is provided. Based on the reviewed literature, relevant research questions and directions for future research are identified. Finally, it is shown that hybrid MTS/MTO production control is prevalent in practice by discussing research with industrial applications. The paper contains an overview of research on hybrid MTS/MTO production control to be used as reference for researchers active in the field, and provides managerial insights and directions for future research on this topic.     

Deductive verification of alternating systems

Alternating systems are models of computer programs whose behavior is governed by the actions of multiple agents with, potentially, different goals. Examples include control systems, resource schedulers, security protocols, auctions and election mechanisms. Proving properties about such systems has emerged as an important new area of study in formal verification, with the development of logical frameworks such as the alternating temporal logic ATL*. Techniques for model checking ATL* over finite-state systems have been well studied, but many important systems are infinite-state and thus their verification requires, either explicitly or implicitly, some form of deductive reasoning. This paper presents a theoretical framework for the analysis of alternating infinite-state systems. It describes models of computation, of various degrees of generality, and alternating-time logics such as ATL* and its variations. It then develops a proof system that allows to prove arbitrary ATL* properties over these infinite-state models. The proof system is shown to be complete relative to validities in the weakest possible assertion language. The paper then derives auxiliary proof rules and verification diagrams techniques and applies them to security protocols, deriving a new formal proof of fairness of a multi-party contract signing protocol where the model of the protocol and of the properties contains both game-theoretic and infinite-state (parameterized) aspects.     

Action selection and task sequence learning for hybrid dynamical cognitive agents

As a foundation for action selection and task-sequencing intelligence, the reactive and deliberative subsystems of a hybrid agent can be unified by a single, shared representation of intention. In this paper, we summarize a framework for hybrid dynamical cognitive agents (HDCAs) that incorporates a representation of dynamical intention into both reactive and deliberative structures of a hybrid dynamical system model, and we present methods for learning in these intention-guided agents. The HDCA framework is based on ideas from spreading activation models and belief–desire–intention (BDI) models. Intentions and other cognitive elements are represented as interconnected, continuously varying quantities, employed by both reactive and deliberative processes. HDCA learning methods—such as Hebbian strengthening of links between co-active elements, and belief–intention learning of task-specific relationships—modify interconnections among cognitive elements, extending the benefits of reactive intelligence by enhancing high-level task sequencing without additional reliance on or modification of deliberation. We also present demonstrations of simulated robots that learned geographic and domain-specific task relationships in an office environment.     

Verifying Temporal Properties of Reactive Systems: A STeP Tutorial

We review a number of formal verification techniques supported by STeP, the Stanford Temporal Prover, describing how the tool can be used to verify properties of several versions of the Bakery Mutual exclusion algorithm for mutual exclusion. We verify the classic two-process algorithm and simple variants, as well as an atomic parameterized version. The methods used include deductive verification rules, verification diagrams, automatic invariant generation, and finite-state model checking and abstraction.     

Low-frequency quadrature mode birdcage resonator

The birdcage resonator is frequently used in conventional MRI because of its excellent attributes. Its use in low-field MRI is restricted to field strengths higher than, for example, 0.1 T, dependent on the size of the coil. This is because of the intrinsically low inductance value of the birdcage coils. Furthermore, the sensitivity of the birdcage at low field strengths is significantly lower when compared to, for example, the solenoid. Both problems can be overcome with the multiturn technique and a novel wound birdcage coil. The quadrature mode wound birdcage coil presented in this paper can be used at frequencies as low as 100 kHz. Its sensitivity is also increased when compared to the conventional strip-ring birdcage. Homogeneity effective volume, and methods to increase the resonator bandwidth to match the signal bandwidth are left intact. The latter is a typical low-field problem.     

Collecting Statistics over Runtime Executions

By collecting statistics over runtime executions of a program we can answer complex queries, such as “what is the average number of packet retransmissions” in a communication protocol, or “how often does process P₁ enter the critical section while process P₂ waits” in a mutual exclusion algorithm. We present an extension to linear-time temporal logic that combines the temporal specification with the collection of statistical data. By translating formulas of this language to alternating automata we obtain a simple and efficient query evaluation algorithm. We illustrate our approach with examples and experimental results.     

Expectancy, homework compliance, and initial change in cognitive-behavioral therapy for anxiety.

Belief in one's ability to change is an important cognitive variable related to treatment gains. This study investigated pretreatment expectancy for anxiety change and early homework compliance in relation to initial and total cognitive change in group cognitive-behavioral therapy (CBT) for anxiety. Participants, who met diagnostic criteria for at least 1 anxiety disorder, completed 10 sessions of group CBT. Early homework compliance mediated the relationship between expectancy for anxiety change at baseline and initial change in CBT. In addition, initial cognitive symptom improvement mediated the relationship between homework compliance and posttreatment outcome. These results suggest that expectancy for change is an important cognitive variable that may provide the initial impetus and subsequent momentum for therapeutic involvement and gains. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Effects of constructing versus playing an educational game on student motivation and deep learning strategy use

In this study the effects of two different interactive learning tasks, in which simple games were included were described with respect to student motivation and deep strategy use. The research involved 235 students from four elementary schools in The Netherlands. One group of students (N = 128) constructed their own memory ‘drag and drop’ game, whereas the other group (N = 107) played an existing ‘drag and drop’ memory game. Analyses of covariance demonstrated a significant difference between the two conditions both on intrinsic motivation and deep strategy use. The large effect sizes for both motivation and deep strategy use were in favour of the construction condition. The results suggest that constructing a game might be a better way to enhance student motivation and deep learning than playing an existing game. Despite the promising results, the low level of complexity of the games used is a study limitation.     

Normally Oriented Adhesion versus Friction Forces in Bacterial Adhesion to Polymer‐Brush Functionalized Surfaces Under Fluid Flow

Bacterial adhesion is problematic in many diverse applications. Coatings of hydrophilic polymer chains in a brush configuration reduce bacterial adhesion by orders of magnitude, but not to zero. Here, the mechanism by which polymer‐brush functionalized surfaces reduce bacterial adhesion from a flowing carrier fluid by relating bacterial adhesion with normally oriented adhesion and friction forces on polymer (PEG)‐brush coatings of different softness is studied. Softer brush coatings deform more than rigid ones, which yields extensive bond‐maturation and strong, normally oriented adhesion forces, accompanied by irreversible adhesion of bacteria. On rigid brushes, normally oriented adhesion forces remain small, allowing desorption and accordingly lower numbers of adhering bacteria result. Friction forces, generated by fluid flow and normally oriented adhesion forces, are required to oppose fluid shear forces and cause immobile adhesion. Summarizing, inclusion of friction forces and substratum softness provides a more complete mechanism of bacterial adhesion from flowing carrier fluids than available hitherto.