Model checking temporal knowledge and commitments in multi-agent systems using reduction

Though modeling and verifying Multi-Agent Systems (MASs) have long been under study, there are still challenges when many different aspects need to be considered simultaneously. In fact, various frameworks have been carried out for modeling and verifying MASs with respect to knowledge and social commitments independently. However, considering them under the same framework still needs further investigation, particularly from the verification perspective. In this article, we present a new technique for model checking the logic of knowledge and commitments (CTLKC⁺). The proposed technique is fully-automatic and reduction-based in which we transform the problem of model checking CTLKC⁺ into the problem of model checking an existing logic of action called ARCTL. Concretely, we construct a set of transformation rules to formally reduce the CTLKC⁺ model into an ARCTL model and CTLKC⁺ formulae into ARCTL formulae to get benefit from the extended version of NuSMV symbolic model checker of ARCTL. Compared to a recent approach that reduces the problem of model checking CTLKC⁺ to another logic of action called GCTL¹, our technique has better scalability and efficiency. We also analyze the complexity of the proposed model checking technique. The results of this analysis reveal that the complexity of our reduction-based procedure is PSPACE-complete for local concurrent programs with respect to the size of these programs and the length of the formula being checked. From the time perspective, we prove that the complexity of the proposed approach is P-complete with regard to the size of the model and length of the formula, which makes it efficient. Finally, we implement our model checking approach on top of extended NuSMV and report verification results for the verification of the NetBill protocol, taken from business domain, against some desirable properties. The obtained results show the effectiveness of our model checking approach when the system scales up.     

Determining patent filing targets based on patent cost retrieval from Patent Examination Data System

I have utilized Patent Examination Data System (PEDS) to propose a patent filing strategy decomposed by sub-divisions within a Research and Development (R&D) department of a large organization. The unique method relies on breaking the patent cost into fixed cost and variable cost. The variable cost is determined by automatically retrieving data from PEDS. The data includes historical average of number of interactions of a patent applicant with the patent office, grouped by technology domains. The variable cost may then be used in a linear programming model to obtain optimal filing targets for each sub-division within the R&D department. The proposed strategy will help an organization to take objective decisions for determining patent filing targets for its sub-divisions, which will eventually help with an efficient patent strategy for the organization.     

FarsBase-KBP: A knowledge base population system for the Persian Knowledge Graph

While most of the knowledge bases already support the English language, there is only one knowledge base for the Persian language, known as FarsBase, which is automatically created via semi-structured web information. Unlike English knowledge bases such as Wikidata, which have tremendous community support, the population of a knowledge base like FarsBase must rely on automatically extracted knowledge. Knowledge base population can let FarsBase keep growing in size, as the system continues working. In this paper, we present a knowledge base population system for the Persian language, which extracts knowledge from unlabelled raw text, crawled from the Web. The proposed system consists of a set of state-of-the-art modules such as an entity linking module as well as information and relation extraction modules designed for FarsBase. Moreover, a canonicalization system is introduced to link extracted relations to FarsBase properties. Then, the system uses knowledge fusion techniques with minimal intervention of human experts to integrate and filter the proper knowledge instances, extracted by each module. To evaluate the performance of the presented knowledge base population system, we present the first gold dataset for benchmarking knowledge base population in the Persian language, which consisting of 22015 FarsBase triples and verified by human experts. The evaluation results demonstrate the efficiency of the proposed system.     

Negative statements considered useful

Knowledge bases (KBs) about notable entities and their properties are an important asset in applications such as search, question answering and dialog. All popular KBs capture virtually only positive statements, and abstain from taking any stance on statements not stored in the KB. This paper makes the case for explicitly stating salient statements that do not hold. Negative statements are useful to overcome limitations of question answering systems that are mainly geared for positive questions; they can also contribute to informative summaries of entities. Due to the abundance of such invalid statements, any effort to compile them needs to address ranking by saliency. We present a statistical inference method for compiling and ranking negative statements, based on expectations from positive statements of related entities in peer groups. Experimental results, with a variety of datasets, show that the method can effectively discover notable negative statements, and extrinsic studies underline their usefulness for entity summarization. Datasets and code are released as resources for further research.     

Bracketing or reinforcing? Socio-economic status,network power,and online deliberation

The extent to which the deliberative scenario brackets socio-economic inequalities (i.e., functioning as an ideal public sphere) has been long-debating. This study empirically addresses this question in the online setting. We test whether offline advantages (i.e., economic and cultural capitals) can be translated into power in online deliberation and how their dynamic relations further influence interlocutors’ deliberation experience (i.e., perceived procedural fairness and validity claim). Power is conceptualized as network power, including prestige (indegree), leadership (outdegree), and brokering power (betweenness). A national sample of Singaporeans participated in a three-week online deliberation, and network power is measured based on the web log. The participants answered a two-wave (i.e., pre- and post-deliberation) survey to indicate individual attributes. Structural equation modeling finds that online deliberation brackets as well as reinforces offline status. Economic capital is suppressed while cultural capital translates into network power, which further influences interlocutors’ evaluation of the deliberation.     

Application of MSD prevention practices by nursing staff working in healthcare settings

ObjectiveThe objective of this article is to examine the application of MSD prevention practices among nursing staff and to identify organizational factors that may or may not support their application.MethodsWe measured the application of prevention practices and its determinants by means of a questionnaire filled out by 399 nurses and nursing staff in Canada. A qualitative component was conducted with two focus groups in order to validate and enrich the interpretation of the survey results.ResultsResults show that most respondents “often” (4) apply MSD prevention practices in their daily professional tasks. Significant differences were observed based on position, mission of the institution, degree, and training.ConclusionsThe characteristics of the nursing staff (position, training, etc.) and the specificities of the setting must be taken into consideration in MSD prevention interventions for nursing staff.     

What do stakeholders think about knowledge transfer offices? The perspective of firms and research groups in a regional innovation system

Knowledge transfer offices (KTOs) are required to adopt a comprehensive approach to managing a broad set of channels of university–industry collaboration, including collaborative research, business services, exchange of human resources and informal relations within a regional innovation system. The perspectives of firms and academic researchers, the main stakeholders of KTOs, are useful complements to assess KTO activity. The goal of this article is to study the effectiveness that these stakeholders attribute to KTOs. Based on survey data collected in the Spanish region of Andalusia, the article explores stakeholders’ perceptions and determinants. The results show that the level of engagement in a diversified range of activities and the importance attributed to knowledge transfer in the strategy of both research groups and firms are the best predictors of the perceived effectiveness of KTOs. The article also underlines specific differences between the two types of stakeholders.     

Engineering knowledge formalization and proposition for informatics development towards a CAD-integrated DfX system for product design

Target design methodologies (DfX) were developed to cope with specific engineering design issues such as cost-effectiveness, manufacturability, assemblability, maintainability, among others. However, DfX methodologies are undergoing the lack of real integration with 3D CAD systems. Their principles are currently applied downstream of the 3D modelling by following the well-known rules available from the literature and engineers’ know-how (tacit internal knowledge).This paper provides a method to formalize complex DfX engineering knowledge into explicit knowledge that can be reused for Advanced Engineering Informatics to aid designers and engineers in developing mechanical products. This research work wants to define a general method (ontology) able to couple DfX design guidelines (engineering knowledge) with geometrical product features of a product 3D model (engineering parametric data). A common layer for all DfX methods (horizontal) and dedicated layers for each DfX method (vertical) allow creating the suitable ontology for the systematic collection of the DfX rules considering each target. Moreover, the proposed framework is the first step for developing (future work) a software tool to assist engineers and designers during product development (3D CAD modelling).A design for assembly (DfA) case study shows how to collect assembly rules in the given framework. It demonstrates the applicability of the CAD-integrated DfX system in the mechanical design of a jig-crane. Several benefits are recognized: (i) systematic collection of DfA rules for informatics development, (ii) identification of assembly issues in the product development process, and (iii) reduction of effort and time during the design review.     

Decomposition and replacement: Spatial knowledge distillation for monocular depth estimation

Knowledge distillation has become a key technique for making smart and light-weight networks through model compression and transfer learning. Unlike previous methods that applied knowledge distillation to the classification task, we propose to exploit the decomposition-and-replacement based distillation scheme for depth estimation from a single RGB color image. To do this, Laplacian pyramid-based knowledge distillation is firstly presented in this paper. The key idea of the proposed method is to transfer the rich knowledge of the scene depth, which is well encoded through the teacher network, to the student network in a structured way by decomposing it into the global context and local details. This is fairly desirable for the student network to restore the depth layout more accurately with limited resources. Moreover, we also propose a new guidance concept for knowledge distillation, so-called ReplaceBlock, which replaces blocks randomly selected in the decoded feature of the student network with those of the teacher network. Our ReplaceBlock gives a smoothing effect in learning the feature distribution of the teacher network by considering the spatial contiguity in the feature space. This process is also helpful to clearly restore the depth layout without the significant computational cost. Based on various experimental results on benchmark datasets, the effectiveness of our distillation scheme for monocular depth estimation is demonstrated in details. The code and model are publicly available at : https://github.com/tjqansthd/Lap_Rep_KD_Depth.