INCREMENTAL FAULT DIAGNOSABILITY AND SECURITY/PRIVACY VERIFICATION

Dynamical systems can be classified into two groups. One group is continuoustime systems that describe the physical system behavior, and therefore are typically modeled by differential equations. The other group is discrete event systems (DES)s that represent the sequential and logical behavior of a system. DESs are therefore modeled by discrete state/event models.DESs are widely used for formal verification and enforcement of desired behaviors in embedded systems. Such systems are naturally prone to faults, and the knowledge about each single fault is crucial from safety and economical point of view. Fault diagnosability verification, which is the ability to deduce about the occurrence of all failures, is one of the problems that is investigated in this thesis. Another verification problem that is addressed in this thesis is security/privacy. The two notions currentstate opacity and current-state anonymity that lie within this category, have attracted great attention in recent years, due to the progress of communication networks and mobile devices.Usually, DESs are modular and consist of interacting subsystems. The interaction is achieved by means of synchronous composition of these components. This synchronization results in large monolithic models of the total DES. Also, the complex computations, related to each specific verification problem, add even more computational complexity, resulting in the well-known state-space explosion problem.To circumvent the state-space explosion problem, one efficient approach is to exploit the modular structure of systems and apply incremental abstraction. In this thesis, a unified abstraction method that preserves temporal logic properties and possible silent loops is presented. The abstraction method is incrementally applied on the local subsystems, and it is proved that this abstraction preserves the main characteristics of the system that needs to be verified.The existence of shared unobservable events means that ordinary incremental abstraction does not work for security/privacy verification of modular DESs. To solve this problem, a combined incremental abstraction and observer generation is proposed and analyzed. Evaluations show the great impact of the proposed incremental abstraction on diagnosability and security/privacy verification, as well as verification of generic safety and liveness properties. Thus, this incremental strategy makes formal verification of large complex systems feasible

Diagnosability Verification Using Compositional Branching Bisimulation

This paper presents an efficient diagnosability verification technique, based on a general abstraction approach. More specifically, branching bisimulation including state labels with explicit divergence (BBSD) is defined. This bisimulation preserves the temporal logic property that verifies diagnosability. Based on a proposed BBSD algorithm, compositional abstraction for modular diagnosability verification is shown to offer a significant state space reduction in comparison to state-of-the-art techniques. This is illustrated by verifying non-diagnosability analytically for a set of synchronized components, where the abstracted solution is independent of the number of components and the number of observable events

Verification of diagnosability based on compositional branching bisimulation

This paper presents an efficient diagnosability verification technique, based on a general abstraction approach. We exploit branching bisimulation with explicit divergence (BBED), which preserves the temporal logic property that verifies diagnosability. Furthermore, using compositional abstraction for modular diagnosability verification offers additional state space reduction in comparison to the state-of-the-art techniques

Family language policy in retrospect: Narratives of success and failure in an Indian–Iranian transnational family

In this study, we investigate family language policy in a transnational family through a collaborative autoethnography. Following the theoretical underpinnings of family language policy (Spolsky in J Multiling Multicult Dev 31:3–11, 2012), we present parental language beliefs, management, and practices in retrospect to shine a light on the long-term impact of the family’s language policy on their daughter’s linguistic development in heritage languages (i.e., Persian and Hindi) and English. The components of the family language policy in this cross-cultural transnational family are sketched in the second author’s narratives of her experiences of multilingual childrearing and heritage language maintenance. We engage with, and critique, recent family language scholarship that apply postmodernist lens to examine families’ translingual use of languages at home to get by their daily life, showing how having failed to set boundaries between the home/heritage languages and English over the past nine years has resulted in their child’s predominant proficiency in English. We argue that such failure has its roots in parents’ own past lived, and future imagined, experiences, as well as language ideologies that are polycentric and scaled, the consequences of which concern emotional, linguistic, cultural and social frictions across generations. Drawing on the narratives of success and failure in the family, we call for critical adoption of translingual frameworks in examining family language policy paying careful attention to the long-term impact of such practices at home on children’s linguistic development.publishedVersio

Multilingual children’s imaginative worlds and their language use: A chronotopic analysis

Aims and objectives: This study applies the notion of chronotope as an analytical tool to explore the role of globalization, immigration, and transnationalism in shaping multilingual children’s awareness and use of semiotic resources in changing social contexts. Design/methodology/approach: This study is a part of an ongoing collaborative autoethnography (CAE), in which the data come from the second author’s cross-cultural transnational family and are shared with the first author for a collaborative interpretation and analysis. Data and analysis: Data were collected through recording the observations of language practices of a nine-year-old girl in a transnational family, including her plays on her own or with her peers in and outside the home. An ethnographically grounded discourse-analytic approach was employed in analyzing the data. Findings/conclusions: Despite rich linguistic and cultural repertoire, the child situated English on a higher scale level in a hierarchically layered system, and she found imaginative play as a space in which she could explore not only linguistic repertoire but also certain cultural chronotopes. She also demonstrated her awareness of and skills in drawing on variation within the English language to index certain social personae. Originality: The originality of the study lies, first, in the uniqueness of the case being in an Indian-Iranian multilingual transnational family and, second, in the unique methodology—using chronotopes as a theoretical and analytic tool to analyze audio-recorded interactions in a multilingual child’s imaginative plays. Significance/implications: The study has implications for our understanding of how children pick up indexical meanings of linguistic choices and reproduce them in their imaginative worlds. It also sheds light on how language ideologies and practices reproduced by children may result in hierarchization and power difference between linguistic varieties.publishedVersio

Towards Understanding the Benefits and Challenges of Demand Responsive Public Transit- A Case Study in the City of Charlotte, NC

Access to adequate public transportation plays a critical role in inequity and socio-economic mobility, particularly in low-income communities. Low-income workers who rely heavily on public transportation face a spatial disparity between home and work, which leads to higher unemployment, longer job searches, and longer commute times. The overarching goal of this study is to get initial data that would result in creating a connected, coordinated, demand-responsive, and efficient public bus system that minimizes transit gaps for low-income, transit-dependent communities. To create equitable metropolitan public transportation, this paper evaluates existing CATS mobile applications that assist passengers in finding bus routes and arrival times. Our community survey methodology includes filling out questionnaires on Charlotte's current bus system on specific bus lines and determining user acceptance for a future novel smart technology. We have also collected data on the demand and transit gap for a real-world pilot study, Sprinter bus line, Bus line 7, Bus line 9, and Bus lines 97-99. These lines connect all of Charlotte City's main areas and are the most important bus lines in the system. On the studied routes, the primary survey results indicate that the current bus system has many flaws, the major one being the lack of proper timing to meet the needs of passengers. The most common problems are long commutes and long waiting times at stations. Moreover, the existing application provides inaccurate information, and on average, 80 percent of travelers and respondents are inclined to use new technology.Comment: 22 pages, 54 figure

Identifying Nuances in Fake News vs. Satire: Using Semantic and Linguistic Cues

The blurry line between nefarious fake news and protected-speech satire has been a notorious struggle for social media platforms. Further to the efforts of reducing exposure to misinformation on social media, purveyors of fake news have begun to masquerade as satire sites to avoid being demoted. In this work, we address the challenge of automatically classifying fake news versus satire. Previous work have studied whether fake news and satire can be distinguished based on language differences. Contrary to fake news, satire stories are usually humorous and carry some political or social message. We hypothesize that these nuances could be identified using semantic and linguistic cues. Consequently, we train a machine learning method using semantic representation, with a state-of-the-art contextual language model, and with linguistic features based on textual coherence metrics. Empirical evaluation attests to the merits of our approach compared to the language-based baseline and sheds light on the nuances between fake news and satire. As avenues for future work, we consider studying additional linguistic features related to the humor aspect, and enriching the data with current news events, to help identify a political or social message.Comment: Accepted to the 2nd Workshop on NLP for Internet Freedom (NLP4IF): Censorship, Disinformation, and Propaganda. Co-located with EMNLP-IJCNLP 201