The Evolution of Exchange

Stochastic stability is applied to the problem of exchange. We analyze the stochastic stability of two dynamic trading processes in a simple housing market. In both models traders meet in pairs at random and exchange their houses when trade is mutually beneficial, but occasionally they make mistakes. The models differ in the probability of mistakes. When all mistakes are equally likely, the set of stochastically stable allocations contains the set of efficient allocations. When more serious mistakes are less likely, the stochastically stable states are those allocations, always efficient, with the lowest envy-level.stochastic stability, exchange, housing problem, efficiency, envy.

SINGULAB - A Graphical user Interface for the Singularity Analysis of Parallel Robots based on Grassmann-Cayley Algebra

This paper presents SinguLab, a graphical user interface for the singularity analysis of parallel robots. The algorithm is based on Grassmann-Cayley algebra. The proposed tool is interactive and introduces the designer to the singularity analysis performed by this method, showing all the stages along the procedure and eventually showing the solution algebraically and graphically, allowing as well the singularity verification of different robot poses.Comment: Advances in Robot Kinematics, Batz sur Mer : France (2008

CPLLM: Clinical Prediction with Large Language Models

We present Clinical Prediction with Large Language Models (CPLLM), a method that involves fine-tuning a pre-trained Large Language Model (LLM) for clinical disease prediction. We utilized quantization and fine-tuned the LLM using prompts, with the task of predicting whether patients will be diagnosed with a target disease during their next visit or in the subsequent diagnosis, leveraging their historical diagnosis records. We compared our results versus various baselines, including Logistic Regression, RETAIN, and Med-BERT, which is the current state-of-the-art model for disease prediction using structured EHR data. Our experiments have shown that CPLLM surpasses all the tested models in terms of both PR-AUC and ROC-AUC metrics, displaying noteworthy enhancements compared to the baseline models

Optimizing Computation of Recovery Plans for BPEL Applications

Web service applications are distributed processes that are composed of dynamically bounded services. In our previous work [15], we have described a framework for performing runtime monitoring of web service against behavioural correctness properties (described using property patterns and converted into finite state automata). These specify forbidden behavior (safety properties) and desired behavior (bounded liveness properties). Finite execution traces of web services described in BPEL are checked for conformance at runtime. When violations are discovered, our framework automatically proposes and ranks recovery plans which users can then select for execution. Such plans for safety violations essentially involve "going back" - compensating the executed actions until an alternative behaviour of the application is possible. For bounded liveness violations, recovery plans include both "going back" and "re-planning" - guiding the application towards a desired behaviour. Our experience, reported in [16], identified a drawback in this approach: we compute too many plans due to (a) overapproximating the number of program points where an alternative behaviour is possible and (b) generating recovery plans for bounded liveness properties which can potentially violate safety properties. In this paper, we describe improvements to our framework that remedy these problems and describe their effectiveness on a case study.Comment: In Proceedings TAV-WEB 2010, arXiv:1009.330

Applications of Description Logic and Causality in Model Checking

Model checking is an automated technique for the verification of finite-state systems that is widely used in practice. In model checking, a model M is verified against a specification $\varphi$, exhaustively checking that the tree of all computations of M satisfies $\varphi$. When $\varphi$ fails to hold in M, the negative result is accompanied by a counterexample: a computation in M that demonstrates the failure. State of the art model checkers apply Binary Decision Diagrams(BDDs) as well as satisfiability solvers for this task. However, both methods suffer from the state explosion problem, which restricts the application of model checking to only modestly sized systems. The importance of model checking makes it worthwhile to explore alternative technologies, in the hope of broadening the applicability of the technique to a wider class of systems. Description Logic (DL) is a family of knowledge representation formalisms based on decidable fragments of first order logic. DL is used mainly for designing ontologies in information systems. In recent years several DL reasoners have been developed, demonstrating an impressive capability to cope with very large ontologies. This work consists of two parts. In the first we harness the growing ability of DL reasoners to solve model checking problems. We show how DL can serve as a natural setting for representing and solving a model checking problem, and present a variety of encodings that translate such problems into consistency queries in DL. Experimental results, using the Description Logic reasoner FaCT++, demonstrate that for some systems and properties, our method can outperform existing ones. In the second part we approach a different aspect of model checking. When a specification fails to hold in a model and a counterexample is presented to the user, the counterexample may itself be complex and difficult to understand. We propose an automatic technique to find the computation steps and their associated variable values, that are of particular importance in generating the counterexample. We use the notion of causality to formally define a set of causes for the failure of the specification on the given counterexample. We give a linear-time algorithm to detect the causes, and we demonstrate how these causes can be presented to the user as a visual explanation of the failure

Symbolic Model Checking of Product-Line Requirements Using SAT-Based Methods

Product line (PL) engineering promotes the de- velopment of families of related products, where individual products are differentiated by which optional features they include. Modelling and analyzing requirements models of PLs allows for early detection and correction of requirements errors – including unintended feature interactions, which are a serious problem in feature-rich systems. A key challenge in analyzing PL requirements is the efficient verification of the product family, given that the number of products is too large to be verified one at a time. Recently, it has been shown how the high-level design of an entire PL, that includes all possible products, can be compactly represented as a single model in the SMV language, and model checked using the NuSMV tool. The implementation in NuSMV uses BDDs, a method that has been outperformed by SAT-based algorithms. In this paper we develop PL model checking using two leading SAT-based symbolic model checking algorithms: IMC and IC3. We describe the algorithms, prove their correctness, and report on our implementation. Evaluating our methods on three PL models from the literature, we demonstrate an improvement of up to 3 orders of magnitude over the existing BDD-based method.NSERC Discovery Grant, 155243-12 || NSERC / Automotive Partnership Canada, APCPJ 386797 - 09 || Ontario Research Fund, RE05-04

Generalized abstraction-refinement for game-based CTL lifted model checking

cation areas ranging from embedded system domains to system-level software and communication protocols. Software Product Line methods and architectures allow effective building many custom variants of a software system in these domains. In many of the applications, their rigorous verification and quality assurance are of paramount importance. Lifted model checking for system families is capable of verifying all their variants simultaneously in a single run by exploiting the similarities between the variants. The computational cost of lifted model checking still greatly depends on the number of variants (the size of configuration space), which is often huge. Variability abstractions have successfully addressed this configuration space explosion problem, giving rise to smaller abstract variability models with fewer abstract configurations. Abstract variability models are given as modal transition systems, which contain may (over-approximating) and must (under-approximating) transitions. Thus, they preserve both universal and existential CTL properties. In this work, we bring two main contributions. First, we define a novel game-based approach for variability-specific abstraction and refinement for lifted model checking of the full CTL, interpreted over 3-valued semantics. We propose a direct algorithm for solving a 3-valued (abstract) lifted model checking game. In case the result of model checking an abstract variability model is indefinite, we suggest a new notion of refinement, which eliminates indefinite results. This provides an iterative incremental variability-specific abstraction and refinement framework, where refinement is applied only where indefinite results exist and definite results from previous iterations are reused. Second, we propose a new generalized definition of abstract variability models, given as so-called generalized modal transition systems, by introducing the notion of (must) hyper-transitions. This results in more precise abstract models in which more CTL formulae can be proved or disproved. We integrate the newly defined generalized abstract variability models in the existing abstraction-refinement framework for game-based lifted model checking of CTL. Finally, we evaluate the practicality of this approach on several system families

Early maladaptive schemas and ICD-11 CPTSD symptoms: Treatment considerations

ObjectivesEarly maladaptive schemas (EMS) can result from adverse interpersonal traumatic experiences. The ICD-11 updated the concept of disorders following traumatic experiences with the new disorder of complex post-traumatic stress disorder (CPTSD). There is now a need to develop and test interventions for CPTSD. An essential step in identifying interventions that are particularly relevant to the treatment of CPTSD is to explore psychological constructs associated more closely with CPTSD compared to PTSD. The current study explored the associations of EMS with PTSD and CPTSD.DesignThe sample consisted of 603 adults (mean age = 41.65, SD = 13.8), recruited through social media and e-mails, and who responded to an online questionnaire.MethodsParticipants completed measures of demographic, traumatic life events, EMS, PTSD and CPTSD symptoms.ResultsOverall, results suggest that participants with CPTSD present with higher schema elevations across all schemas compared to those with PTSD or no diagnosis. Secondly, the schemas of emotional deprivation, abandonment/instability, social isolation/alienation, defectiveness/shame, enmeshment/undeveloped self, subjugation, emotional inhibition and insufficient self-control/self-discipline were significantly associated with the symptom clusters of CPTSD. Finally, results indicate that different schemas form significant associations with the individual symptom clusters of CPTSD.ConclusionsAlthough results require replication in clinical samples, initial findings suggest that specific EMS may be important psychological correlates of CPTSD symptoms. Wider treatment considerations of these findings are discussed