Contextual Parameter Research Articles

Contextual Acceptance of COVID-19 Mitigation Mobile Apps in the United States: Mixed Methods Survey Study on Postpandemic Data Privacy.

The COVID-19 pandemic gave rise to countless user-facing mobile apps to help fight the pandemic ("COVID-19 mitigation apps"). These apps have been at the center of data privacy discussions because they collect, use, and even retain sensitive personal data from their users (eg, medical records and location data). The US government ended its COVID-19 emergency declaration in May 2023, marking a unique time to comprehensively investigate how data privacy impacted people's acceptance of various COVID-19 mitigation apps deployed throughout the pandemic. This research aims to provide insights into health data privacy regarding COVID-19 mitigation apps and policy recommendations for future deployment of public health mobile apps through the lens of data privacy. This research explores people's contextual acceptance of different types of COVID-19 mitigation apps by applying the privacy framework of contextual integrity. Specifically, this research seeks to identify the factors that impact people's acceptance of data sharing and data retention practices in various social contexts. A mixed methods web-based survey study was conducted by recruiting a simple US representative sample (N=674) on Prolific in February 2023. The survey includes a total of 60 vignette scenarios representing realistic social contexts that COVID-19 mitigation apps could be used. Each survey respondent answered questions about their acceptance of 10 randomly selected scenarios. Three contextual integrity parameters (attribute, recipient, and transmission principle) and respondents' basic demographics are controlled as independent variables. Regression analysis was performed to determine the factors impacting people's acceptance of initial data sharing and data retention practices via these apps. Qualitative data from the survey were analyzed to support the statistical results. Many contextual integrity parameter values, pairwise combinations of contextual integrity parameter values, and some demographic features of respondents have a significant impact on their acceptance of using COVID-19 mitigation apps in various social contexts. Respondents' acceptance of data retention practices diverged from their acceptance of initial data sharing practices in some scenarios. This study showed that people's acceptance of using various COVID-19 mitigation apps depends on specific social contexts, including the type of data (attribute), the recipients of the data (recipient), and the purpose of data use (transmission principle). Such acceptance may differ between the initial data sharing and data retention practices, even in the same context. Study findings generated rich implications for future pandemic mitigation apps and the broader public health mobile apps regarding data privacy and deployment considerations.

UDapter: Typology-based Language Adapters for Multilingual Dependency Parsing and Sequence Labeling

Abstract Recent advances in multilingual language modeling have brought the idea of a truly universal parser closer to reality. However, such models are still not immune to the “curse of multilinguality”: Cross-language interference and restrained model capacity remain major obstacles. To address this, we propose a novel language adaptation approach by introducing contextual language adapters to a multilingual parser. Contextual language adapters make it possible to learn adapters via language embeddings while sharing model parameters across languages based on contextual parameter generation. Moreover, our method allows for an easy but effective integration of existing linguistic typology features into the parsing model. Because not all typological features are available for every language, we further combine typological feature prediction with parsing in a multi-task model that achieves very competitive parsing performance without the need for an external prediction system for missing features. The resulting parser, UDapter, can be used for dependency parsing as well as sequence labeling tasks such as POS tagging, morphological tagging, and NER. In dependency parsing, it outperforms strong monolingual and multilingual baselines on the majority of both high-resource and low-resource (zero-shot) languages, showing the success of the proposed adaptation approach. In sequence labeling tasks, our parser surpasses the baseline on high resource languages, and performs very competitively in a zero-shot setting. Our in-depth analyses show that adapter generation via typological features of languages is key to this success.1

Towards a systemic functional approach to context collapse

Abstract This paper presents an initial systemic functional interpretation of the nuclear features of the phenomenon known as “context collapse”, which occurs when multiple online audiences (such as family, friends and coworkers) are “flattened” into a single group of potential recipients. After introducing the fundamental systemic functional dimensions of stratification and instantiation, we briefly present Hasan’s systemic description of the contextual parameter of Tenor, which deals with the potential relations and roles enacted by the participants of an interaction. We propose that such a contextual system enables us to describe with theoretical precision the nuclear features of context collapse: besides one-way digital contact in Mode, the selection of [addressee: absent: category] in the system of TEXTUAL ROLES and a generalized vagueness in the system of SOCIAL ROLES. Finally, we outline two major strategies employed to circumvent it: enactment--based and activation-based.

Dynamic User Activity Prediction using Contextual Service Matching Mechanism

The significance of context-based services is significantly increasing with the advancement of integrated technologies of sensors and ubiquitous technologies. The existing approaches are reviewed to find out that identification of user's activity has more scope of improvement. After reviewing the current literature towards context-based methodologies, it is found that existing methods are devoid of considering dynamic context; while the modelling perspective is mainly towards considering predefined and static contextual information. Further, existing models doesn't have any inclusion of potential belief system nor any incorporation of service matching. Further, practical world case-studies is characterized by complex activity of user while it is quite challenging to extract the accurate contextual information associated with complex user activity. From the practical deployment scenario, the existing system offers less supportability toward collaborative network, which is highly essential to be considered for constraint modelling for user activity detection. Therefore, the proposed manuscript contributes a solution towards existing research problems by introducing a Dynamic User Activity Prediction using Contextual Service Matching Mechanism. A mixed research methodology is used to prove how service matching mechanism is important in contextual service discovery using multimodal activity data. The first contributory solution towards addressing the research problem is by introducing a novel and simplified belief system that considers both static contextual parameters as well as dynamic activity-based contextual parameter. The second contributory solution towards existing problem is to develop a novel service matching module that takes the input from service reposit, user calendar events, and collaborative units for assisting in similarity-based recommendation system. The model considers Hidden Markov Model for activity determination considering states of activity. With a combined usage of user activity context, feature management, and collaborative model, the proposed system offers better granularity in investigating user activity. The experimental and simulation analysis of the proposed outcome shows the enhanced accuracy performance of proposed system under different test environment. The study also investigates the impact of the service matching mechanism as well as relevance feedback on the accuracy to find that the proposed system excels better accuracy.

Научный прогресс и его враги: случай академического словоблудия

The paper discusses the phenomenon of bullshit in the academia as an ob­stacle for progress in natural sciences and the humanities and as a problem of episte­mology and philosophy of science. The authors criticize a popular approach according to which bullshit is defined in terms of the goals or motivations of the bullshitter as a subjectivist and inadequate. Focusing on the phenomenon of bullshit in academic practices, the authors define it in terms of the relevance of the content of a corre­sponding discourse to the topical issues of a given academic discipline and the extent to which the justification proposed in the discourse meets the standard justification criteria in the given discipline. An important component of the proposed definition is the contextual parameter of the judge the perspective of which is represented by a relevant research community. The authors show how the proposed account captures the well-known cases of bullshit as well as solves some of the current problems in social epistemology, such as the nature of group bullshit. The authors argue that the problem of group bullshit arises only when bullshit is understood in terms of indi­vidual intentions or motives. In that case, it is challenging to define group bullshit in a case when no representative of a given group individually supports the bullshit argument put forward by the whole group. For an approach that defines bullshit without appeal to such subjective factors as individual intentions, this problem does not arise because bullshit is independent of the goals of the bullshitter. The authors acknowledge the importance of the motivations of the bullshiter and her strategies. However, they argue that this matter is irrelevant for the definition of bullshit.

Neural Mechanisms of the Contextual Interference Effect and Parameter Similarity on Motor Learning in Older Adults: An EEG Study.

The purpose of this study was to investigate the neural mechanisms of the contextual interference effect (CIE) and parameter similarity on motor learning in older adults. Sixty older adults (mean age, 67.68 ± 3.95 years) were randomly assigned to one of six experimental groups: blocked-similar, algorithm-similar, random-similar, blocked-dissimilar, algorithm-dissimilar, and random-dissimilar. Algorithm practice was a hybrid practice schedule (a combination of blocked, serial, and random practice) that switching between practice schedules were based on error trial number, ≤33%. The sequential motor task was used to record the absolute timing for the absolute timing goals (ATGs). In similar conditions, the participants’ performance was near ATGs (1,350, 1,500, 1,650 ms) and in dissimilar conditions, they performed far ATGs (1,050, 1,500, 1,950 ms) with the same spatial sequence for all groups. EEG signals were continuously collected during the acquisition phase and delayed retention. Data were analyzed in different bands (alpha and beta) and scalp locations (frontal: Fp1, Fp2, F3, F4; central: C3, C4; and parietal: P3, P4) with repeated measures on the last factor. The analyses were included motor preparation and intertrial interval (motor evaluation) periods in the first six blocks and the last six blocks, respectively. The results of behavioral data indicated that algorithm practice resulted in medium error related to classic blocked and random practice during the acquisition, however, algorithm practice outperformed the classic blocked and random practice in the delayed retention test. The results of EEG data demonstrated that algorithm practice, due to optimal activity in the frontal lobe (medium alpha and beta activation at prefrontal), resulted in increased activity of sensorimotor areas (high alpha activation at C3 and P4) in older adults. Also, EEG data showed that similar conditions could affect the intertrial interval period (medium alpha and beta activation in frontal in the last six-block), while the dissimilar conditions could affect the motor preparation period (medium alpha and beta activation in frontal in the first six-block). In conclusion, algorithm practice can enhance motor learning and optimize the efficiency of brain activity, resulting in the achievement of a desirable goal in older adults.

The Cohesion of the Prologue on the Hunger Games Trilogy: A Discourse Analysis

Cohesion is designed to deal with words and phrases that generate a pattern of relations between lexical elements and structures to build an integral and logical text. The analysis of cohesion aims to connect central concepts to the context of writing intended to pursue standards of communication, writing styles, textuality, and a practice of discourse. Accordingly, this study analyzes the cohesion found in the Hunger Games Trilogy by Suzanne Collins. The method of this research is a discourse analysis focusing on Systematic Functional Linguistics (SFL) developed by M.A.K. Halliday. Based on the analysis, the prologue of The Hunger Games and Catching Fire novels can be described in the terms of field, tenor, and mode creating the contextual parameter. The text of the novels is written and is clearly detached, explicit, planned and integrated. While links were observed as characters and places were repeatedly written. The conclusion can be drawn that the two novels aim to tell a story. Furthermore, the texts do not instruct the reader on what to do but rather, it tells what the characters of the story did, are doing, or will do. The novels also implore the reader to read further beyond the prologue and to the main story.

The Cohesion of the Prologue on the Hunger Games Trilogy: A Discourse Analysis

Cohesion is designed to deal with words and phrases that generate a pattern of relations between lexical elements and structures to build an integral and logical text. The analysis of cohesion aims to connect central concepts to the context of writing intended to pursue standards of communication, writing styles, textuality, and a practice of discourse. Accordingly, this study analyzes the cohesion found in the Hunger Games Trilogy by Suzanne Collins. The method of this research is a discourse analysis focusing on Systematic Functional Linguistics (SFL) developed by M.A.K. Halliday. Based on the analysis, the prologue of The Hunger Games and Catching Fire novels can be described in the terms of field, tenor, and mode creating the contextual parameter. The text of the novels is written and is clearly detached, explicit, planned and integrated. While links were observed as characters and places were repeatedly written. The conclusion can be drawn that the two novels aim to tell a story. Furthermore, the texts do not instruct the reader on what to do but rather, it tells what the characters of the story did, are doing, or will do. The novels also implore the reader to read further beyond the prologue and to the main story.

Contextual Parameter Generation for Knowledge Graph Link Prediction

We consider the task of knowledge graph link prediction. Given a question consisting of a source entity and a relation (e.g., Shakespeare and BornIn), the objective is to predict the most likely answer entity (e.g., England). Recent approaches tackle this problem by learning entity and relation embeddings. However, they often constrain the relationship between these embeddings to be additive (i.e., the embeddings are concatenated and then processed by a sequence of linear functions and element-wise non-linearities). We show that this type of interaction significantly limits representational power. For example, such models cannot handle cases where a different projection of the source entity is used for each relation. We propose to use contextual parameter generation to address this limitation. More specifically, we treat relations as the context in which source entities are processed to produce predictions, by using relation embeddings to generate the parameters of a model operating over source entity embeddings. This allows models to represent more complex interactions between entities and relations. We apply our method on two existing link prediction methods, including the current state-of-the-art, resulting in significant performance gains and establishing a new state-of-the-art for this task. These gains are achieved while also reducing convergence time by up to 28 times.

War, vagueness and hybrid war

ABSTRACTIt has frequently been observed in the literature on hybrid wars that there is a grey zone between peace and war, and that hybrid wars are conflicts which are not clear cases of war. In this paper, I attempt to illuminate this grey zone and the concept and nature of war from the philosophical discussions of vagueness and institutional facts. Vague terms are characterized by the fact that there is no non-arbitrary boundary between entities which lie in their extension, and entities which do not lie in their extension. I apply a theory of vagueness to notions such as “war” and “peace” and go on to suggest that the exact boundary for what counts as a war or not is arbitrary. However, the context in which the conflict occurs determines a range of possible locations for this boundary. The most important contextual parameter is in this respect how the parties to the conflict themselves conceptualize the conflict. I suggest that this can in various ways help us understand grey-zone conflicts.

ДИСКУРСИВНІ РІЗНОВИДИ РИМ

The article raises the problem of the rhyme classification, in particular, in the matter of supplementing it with actual parameters. Interpretation of the rhymed text as a creative process determines its analysis in two diametrically opposite aspects: individualauthorial and general-cultural. In the discourse of author’s creativity, the rhyme is analyzed in terms of the stability of the component composition, the compliance with the completed text, the mandatory employment. In the discourse of national and world culture, rhymes are analyzed on the basis of intertextuality. The rhyme transformation is described in the direction from the original rhyming compound to the result of its development in the new text. Intertextual rhymes are analyzed according to their perceptual potential, the accuracy of the reproduction of the original rhyme, as well as the contextual parameter.

The Prefiltering Techniques in Emotion Based Place Recommendation Derived by User Reviews

Context-aware recommendation systems attempt to address the challenge of identifying products or items that have the greatest chance of meeting user requirements by adapting to current contextual information. Many such systems have been developed in domains such as movies, books, and music, and emotion is a contextual parameter that has already been used in those fields. This paper focuses on the use of emotion as a contextual parameter in a tourist destination recommendation system. We developed a new corpus that incorporates the emotion parameter by employing semantic analysis techniques for destination recommendation. We review the effectiveness of incorporating emotion in a recommendation process using prefiltering techniques and show that the use of emotion as a contextual parameter for location recommendation in conjunction with collaborative filtering increases user satisfaction.

A review of Wendy L. Bowcher and Bradley A. Smith (eds.), Systemic Phonology: Recent Studies in English. Sheffield: Equinox, 2014. vii + 451 pp. £85.00 (hbk), £30.00 (pbk)

Correspondence: mjmsxjj@gmail. com School of Foreign Languages, Sun Yat-sen University, Guangzhou 510275, China Systemic Phonology: Recent Studies in English is an extremely timely addition to the literature of systemic functional linguistics (SFL). Despite the importance of phonology to any general description of language, the editors note that this is the first collection focusing on phonology within a SFL framework in the last twenty years. As the title indicates, the collection focuses on the phonological and intonational aspects of the English language within SFL. The introduction by the editors presents a useful orientation to systemic phonology and its place within the general field of phonology, as well as a clear introduction to the purpose and scope of each of the chapters. The volume is divided in five sections and offers an interesting range of studies in systemic phonology. The first section, “Intonation: Construing the Textual Metafunction,” includes four chapters focusing on the role of intonation in the creation of text in context. In Chapter 1, Gerard O’Grady examines the relationship between prosodic prominence and information structure. He illustrates with examples the ambiguity of prosodic prominence in signaling New information, and provides a reconceptualization of what is meant by Given and New. Two different uses of the term New are identified: New1 and New2. New1 is used to mark items which are non-recoverable from the previous context, while New2 is associated with items given prominence for being of particular interest in the discourse. Since the majority of prominences fall on lexical items, O’Grady investigates the relationship between lexical items and tonic and pretonic prominence in three texts: two speeches by the former UK prime minister, Tony Blair, and a monologue from Halliday’s book, A Course in Spoken English: Intonation (1970). The results show that speakers may give prominence to lexical items and project them as New2, regardless of whether the particular items are previously mentioned. By offering a useful categorization of New information to explain prosodic prominence choices, this study greatly enriches our understanding of the semogenic power of intonation in signaling information structure and realizing speakers’ communicative goals. The next chapter, by Annabelle Lukin, explores the relationship between the contextual parameter of mode and the textual metafunction, by analyzing a TV news report concerning the invasion of Iraq. More specifically, it examines how the intonational

Pursuing Meaning

<i>Pursuing Meaning</i>

Intensification without degrees cross-linguistically

In this paper, we examine the semantics of two cross-categorial modifiers that receive an interpretation of intensification: -issimo in Italian, and semu in Washo. Given that both modifiers can combine with a wide range of categories, including those not typically considered grammatically gradable, we argue against an analysis of these modifiers along the lines of e.g., Kennedy and McNally (Language 81(2):345–381, 2005) for very, as uniformly boosting a degree standard. Rather, we argue that the type of modification found with -issimo and semu is one that manipulates a contextual parameter present in the modified expressions, and more specifically universally quantifies over possible contexts of evaluation. Such an analysis allows us to account for the wide distribution of these modifiers, and their co-occurrence with categories that do not encode degree variables. We therefore argue for a typological split in the landscape of intensifiers, both across and within languages, between those that track degree variables, and those that do not.

Improving SAR-Based Urban Change Detection by Combining MAP-MRF Classifier and Nonlocal Means Similarity Weights

In remote sensing change detection, Markov random field (MRF) has been used successfully to model the prior probability using class-labels dependencies. MRF has played an important role in the detection of complex urban changes using optical images. However, the preservation of details in urban change analysis turns out to be a highly complex task if multitemporal SAR images with their speckle are to be used. Here, the ability of MRF to preserve geometric details and to combat speckle effect at the same time becomes questionable. Blob-region phenomenon and fine structures removal are common consequences of the application of traditional MRF-based change detection algorithm. To overcome these limitations, the iterated conditional modes (ICM) framework for the optimization of the maximum a posteriori (MAP-MRF) criterion function is extended to include a nonlocal probability maximization step. This probability model, which characterizes the relationship between pixels' class-labels in a nonlocal scale, has the potential to preserve spatial details and to reduce speckle effects. Two multitemporal SAR datasets were used to assess the proposed algorithm. Experimental results using three density functions [i.e., the log normal (LN), generalized Gaussian (GG), and normal distributions (ND)] have demonstrated the efficiency of the proposed approach in terms of detail preservation and noise suppression. Compared with the traditional MRF algorithm, the proposed approach proved to be less-sensitive to the value of the contextual parameter and the chosen density function. The proposed approach has also shown less sensitivity to the quality of the initial change map when compared with the ICM algorithm.

Indexicals in Virtual Environments

In this paper I explored three well-known cases that seem to cast doubt on the notion that a speaker is always at the place of the utterance when the utterance occurs. I gave a few examples produced in Second Life environment, which cannot be handled correctly by evaluating the expression at issue with respect to the traditional view, i.e., the kaplanian framework—where the agent and the utterer will always be identical, and the referent of “I” will always be the utterer. The same happens to “here” and “now”; in each case the character of the indexical is a function from a contextual parameter to the referent of the expression. An example of logical truth peculiar to indexicals is the sentence “I am here now”, since, according to that view, no utterance can take place in a context whose agent is not in its location in its time. Finally I concluded by claiming that particular kinds of utterances produced in virtual environments (VE) break with the logical truth status of “I am here now”.

Normative Reasons Contextualism

This article argues for the view that statements about normative reasons are context‐sensitive. Specifically, they are sensitive to a contextual parameter specifying a relevant person's or group's body of information. The argument for normative reasons contextualism starts from the context‐sensitivity of the normative “ought” and the further premise that reasons must be aligned with oughts. It is incoherent, I maintain, to suppose that someone normatively ought to φ but has most reason not to φ. So given that oughts depend on context, a parallel view about normative reasons is needed. It is shown that the resulting view solves notorious puzzles involving apparently conflicting but equally plausible claims about reasons. These puzzles arise especially in cases where agents have limited information or false beliefs. In these cases, we feel torn between reasons claims that take into account the limitations of the agent's perspective and apparently conflicting claims that are made from a more objective point of view. The contextualist account developed here accommodates both objectivist and subjectivist intuitions. It shows that all of the claims in question can be true, provided that they are relativized to different values of the relevant information parameter. Also, contextualism yields a fruitful approach to the debate about having reasons and the alleged failure of the so‐called “factoring account”.

Automatic Adaptive Parameterization in Local Phase Feature-Based Bone Segmentation in Ultrasound

Intensity-invariant local phase features based on Log-Gabor filters have been recently shown to produce highly accurate localizations of bone surfaces from three-dimensional (3-D) ultrasound. A key challenge, however, remains in the proper selection of filter parameters, whose values have so far been chosen empirically and kept fixed for a given image. Since Log-Gabor filter responses widely change when varying the filter parameters, actual parameter selection can significantly affect the quality of extracted features. This article presents a novel method for contextual parameter selection that autonomously adapts to image content. Our technique automatically selects the scale, bandwidth and orientation parameters of Log-Gabor filters for optimizing local phase symmetry. The proposed approach incorporates principle curvature computed from the Hessian matrix and directional filter banks in a phase scale-space framework. Evaluations performed on carefully designed in vitro experiments demonstrate 35% improvement in accuracy of bone surface localization compared with empirically-set parameterization results. Results from a pilot in vivo study on human subjects, scanned in the operating room, show similar improvements.

Answers without questions: The emergence of fragments in child language

Non-sentential utterances (NSUs), utterances that lack an overt verbal (more generally predicative) constituent, are common in adult speech. This paper presents the results of a corpus study of the emergence of certain classes of NSUs in child language, based primarily on data from the Manchester Corpus from CHILDES. Our principal finding is the late short query effect: the main classes of non-sentential queries (NSQs) are acquired much later than non-sentential answers (NSAs). At a stage when the child has productive use of sentential queries, and has mastered elliptical declaratives and the polar lexemes ‘yes’ and ‘no’, non-sentential questions are virtually absent. This happens despite the fact that such questions are common in the speech of the child's caregivers and that the contexts are ones which should facilitate the production of such NSUs. We argue that these results are intrinsically problematic for analyses of NSUs in terms of a single, generalized mechanism of phonological reduction, as standard in generative grammar. We show how to model this effect within an approach of dialogue-oriented constructionism, wherein NSUs are grammatical words or constructions whose main predicate is a contextual parameter resolved in a manner akin to indexical terms, the relevant aspect of context being the discourse topic. We sketch an explanation for the order of acquisition of NSUs, based on a notion which combines accessibility of contextual parameters and complexity of content construction.