Strategies for Improving Visual Inspection Performance

This paper summarizes recent results obtained in inspection studies including several studies performed by the authors. Both static and dynamic visual inspection tasks are included. Based on these results, a proposed new integrated design procedure for inspection tasks that will approach the optimal design has been formulated. The review of recent research results includes the following primary variables: the speed of the item passing the inspector, the spacing of items, the percentage of defective items, the illumination level, the contrast between the item being inspected and the background, and the effectiveness of individual versus group inspection. The authors have used their research results in combination with the results in the literature to formulate new integrated procedures for designing inspection stations and job procedures. The authors have also analyzed the effects of inspector performance on the overall quality control plans already in use in industry. The economic effects of changes in inspector performance which result from redesign of the inspection task are then demonstrated as a part of the overall design procedure.Yeshttps://us.sagepub.com/en-us/nam/manuscript-submission-guideline

Domain k-Wise Consistency Made as Simple as Generalized Arc Consistency

Abstract. In Constraint Programming (CP), Generalized Arc Consistency (GAC) is the central property used for making inferences when solving Constraint Satisfaction Problems (CSPs). Developing simple and practical filtering algorithms based on consistencies stronger than GAC is a challenge for the CP community. In this paper, we propose to combine k-Wise Consistency (kWC) with GAC, where kWC states that every tuple in a constraint can be extended to every set of k − 1 additional constraints. Our contribution is as follows. First, we derive a domain-filtering consistency, called Domain k-Wise Consistency (DkWC), from the combination of kWC and GAC. Roughly speaking, this property corresponds to the pruning of values of GAC, when enforced on a CSP previously made kWC. Second, we propose a procedure to enforce DkWC, relying on an encoding of kWC to generate a modified CSP called k-interleaved CSP. Formally, we prove that enforcing GAC on the k-interleaved CSP corresponds to enforcing DkWC on the initial CSP. Consequently, we show that the strong DkWC can be enforced very easily in constraint solvers since the k-interleaved CSP is rather immediate to generate and only existing GAC propagators are required: in a nutshell, DkWC is made as simple and practical as GAC. Our experimental results show the benefits of our approach on a variety of benchmarks.

Algebraic Properties of Qualitative Spatio-Temporal Calculi

Qualitative spatial and temporal reasoning is based on so-called qualitative calculi. Algebraic properties of these calculi have several implications on reasoning algorithms. But what exactly is a qualitative calculus? And to which extent do the qualitative calculi proposed meet these demands? The literature provides various answers to the first question but only few facts about the second. In this paper we identify the minimal requirements to binary spatio-temporal calculi and we discuss the relevance of the according axioms for representation and reasoning. We also analyze existing qualitative calculi and provide a classification involving different notions of a relation algebra.Comment: COSIT 2013 paper including supplementary materia

Using Variable-Rate Alerting to Counter Boredom in Human Supervisory Control

A low task load, long duration experiment was conducted to evaluate the impact of cyclical attention switching strategies on operator performance in supervisory domains. The impetus for such a study stems from the lack of prior work to improve human-system performance in low task load supervisory domains through the use of design interventions. In this study, a design intervention in the form of auditory alerts is introduced and the effects of the alerts are examined. The test bed consists of a video game-like simulation environment, which allows a single operator the ability to supervise multiple unmanned vehicles. Each participant in the study completed two different four hour sessions, with and without the alerts. The results suggest that the alerts can be useful for operators who are distracted for a considerable amount of time, but that the alerts may not be appropriate for operators who are able to sustain directed attention for prolonged periods.United States. Office of Naval Researc

On the speed of constraint propagation and the time complexity of arc consistency testing

Establishing arc consistency on two relational structures is one of the most popular heuristics for the constraint satisfaction problem. We aim at determining the time complexity of arc consistency testing. The input structures $G$ and $H$ can be supposed to be connected colored graphs, as the general problem reduces to this particular case. We first observe the upper bound $O(e(G)v(H)+v(G)e(H))$, which implies the bound $O(e(G)e(H))$ in terms of the number of edges and the bound $O((v(G)+v(H))^3)$ in terms of the number of vertices. We then show that both bounds are tight up to a constant factor as long as an arc consistency algorithm is based on constraint propagation (like any algorithm currently known). Our argument for the lower bounds is based on examples of slow constraint propagation. We measure the speed of constraint propagation observed on a pair $G,H$ by the size of a proof, in a natural combinatorial proof system, that Spoiler wins the existential 2-pebble game on $G,H$. The proof size is bounded from below by the game length $D(G,H)$, and a crucial ingredient of our analysis is the existence of $G,H$ with $D(G,H)=\Omega(v(G)v(H))$. We find one such example among old benchmark instances for the arc consistency problem and also suggest a new, different construction.Comment: 19 pages, 5 figure

Remote data collection for public health research in a COVID-19 era: ethical implications, challenges and opportunities.

Physical distancing measures have lead many public health researchers to transition to remote data collection, via mobile phones, online or other virtual platforms. These methods pose a number of challenges related to obtaining informed consent

Constraint Based System-Level Diagnosis of Multiprocessors

Massively parallel multiprocessors induce new requirements for system-level fault diagnosis, like handling a huge number of processing elements in an inhomogeneous system. Traditional diagnostic models (like PMC, BGM, etc.) are insufficient to fulfill all of these requirements. This paper presents a novel modelling technique, based on a special area of artificial intelligence (AI) methods: constraint satisfaction (CS). The constraint based approach is able to handle functional faults in a similar way to the Russel-Kime model. Moreover, it can use multiple-valued logic to deal with system components having multiple fault modes. The resolution of the produced models can be adjusted to fit the actual diagnostic goal. Consequently, constrint based methods are applicable to a much wider range of multiprocessor architectures than earlier models. The basic problem of system-level diagnosis, syndrome decoding, can be easily transformed into a constraint satisfaction problem (CSP). Thus, the diagnosis algorithm can be derived from the related constraint solving algorithm. Different abstraction leveles can be used for the various diagnosis resolutions, employing the same methodology. As examples, two algorithms are described in the paper; both of them is intended for the Parsytec GCel massively parallel system. The centralized method uses a more elaborate system model, and provides detailed diagnostic information, suitable for off-line evaluation. The distributed method makes fast decisions for reconfiguration control, using a simplified model. Keywords system-level self-diagnosis, massively parallel computing systems, constraint satisfaction, diagnostic models, centralized and distributed diagnostic algorithms