Inconsistent Context Research Articles

Unraveling the inconsistency in captive riders’ behaviors and attitudes within public transportation service usage: An integrated modeling approach

Fostering enduring patronage among passengers for public transportation (PT) services is crucial for sustaining ridership. However, a significant concern arises from the inconsistency between passengers' negative attitudes and their robust patronage behaviors toward PT services, particularly evident among the captive riders. This paradox entails the risk of these passengers potentially shifting to alternative transport modes in the future, thereby diminishing ridership. To unravel the intricate dynamics inherent in the relationship between captive riders' attitudes and behaviors, this study introduces a novel integrated model merging Satisfaction-Loyalty Theory (SLT) with Theory of Planned Behavior (TPB). The integrated model seeks to enhance the comprehension of the mechanisms that drive captive riders' ongoing utilization of PT services, specifically within the context of attitude-behavior inconsistency. Evident in a case study involving 637 samples collected in Dalian, China, the integrated model not only shows excellent goodness-of-fit but also outperforms both the conventional SLT and TPB frameworks. It excels in explaining why captive riders may persist in their behaviors towards the service even in the face of dissatisfaction and highlights how the perceived service quality shapes their attitudes and behaviors. This substantially contributes to the development of targeted service improvement strategies for sustaining captive riders’ continued patronage.

Rethinking Inconsistent Context and Imbalanced Regression in Depression Severity Prediction

Rethinking Inconsistent Context and Imbalanced Regression in Depression Severity Prediction

An extension of the BioAssay Ontology to include pharmacokinetic/pharmacodynamic terminology for the enrichment of scientific workflows

With the capacity to produce and record data electronically, Scientific research and the data associated with it have grown at an unprecedented rate. However, despite a decent amount of data now existing in an electronic form, it is still common for scientific research to be recorded in an unstructured text format with inconsistent context (vocabularies) which vastly reduces the potential for direct intelligent analysis. Research has demonstrated that the use of semantic technologies such as ontologies to structure and enrich scientific data can greatly improve this potential. However, whilst there are many ontologies that can be used for this purpose, there is still a vast quantity of scientific terminology that does not have adequate semantic representation. A key area for expansion identified by the authors was the pharmacokinetic/pharmacodynamic (PK/PD) domain due to its high usage across many areas of Pharma. As such we have produced a set of these terms and other bioassay related terms to be incorporated into the BioAssay Ontology (BAO), which was identified as the most relevant ontology for this work. A number of use cases developed by experts in the field were used to demonstrate how these new ontology terms can be used, and to set the scene for the continuation of this work with a look to expanding this work out into further relevant domains. The work done in this paper was part of Phase 1 of the SEED project (Semantically Enriching electronic laboratory notebook (eLN) Data).

Integration of event experiences to build relational knowledge in the human brain.

We investigated how the human brain integrates experiences of specific events to build general knowledge about typical event structure. We examined an episodic memory area important for temporal relations, anterior-lateral entorhinal cortex, and a semantic memory area important for action concepts, middle temporal gyrus, to understand how and when these areas contribute to these processes. Participants underwent functional magnetic resonance imaging while learning and recalling temporal relations among novel events over two sessions 1 week apart. Across distinct contexts, individual temporal relations among events could either be consistent or inconsistent with each other. Within each context, during the recall phase, we measured associative coding as the difference of multivoxel correlations among related vs unrelated pairs of events. Neural regions that form integrative representations should exhibit stronger associative coding in the consistent than the inconsistent contexts. We found evidence of integrative representations that emerged quickly in anterior-lateral entorhinal cortex (at session 1), and only subsequently in middle temporal gyrus, which showed a significant change across sessions. A complementary pattern of findings was seen with signatures during learning. This suggests that integrative representations are established early in anterior-lateral entorhinal cortex and may be a pathway to the later emergence of semantic knowledge in middle temporal gyrus.

Robot learning from human demonstrations with inconsistent contexts

Visual imitation learning is a promising approach that promotes robots to learn skills from visual demonstrations. However, current visual imitation learning approaches introduce unreasonable assumptions that the contexts of the visual demonstrations and the robot observations are consistent, which affects the flexibility and scalability of the approaches. It is a key challenge for robots to learn from visual demonstrations with inconsistent contexts. Inconsistent contexts may cause a serious difference in the pixel distribution of the operator and the environment, which makes vision-based control policies hardly effective. In this paper, we propose a novel imitation learning framework to enable robots to reproduce behavior by watching human demonstrations with inconsistent contexts, such as different viewpoints, operators, backgrounds, object appearances and positions. Specifically, our framework consists of three networks: flow-based viewpoint transformation network (FVTrans), robot2human alignment network (RANet) and inverse dynamics network (IDNet). First, FVTrans transforms various third-person demonstrations into the fixed robot execution view. With a meta learning strategy, FVTrans can quickly adapt to novel contexts with few samples. Then, RANet aligns the human and the robot at the feature level. Therefore, the demonstration feature can be used as a subgoal of the current moment. Finally, IDNet predicts the joint angles of the robot. We collect a multi-context dataset on the real robot (UR5) for three tasks, including grasping cups, sweeping garbage and placing objects. We empirically demonstrate that our framework can perform three tasks with a high success rate and be effectively generalized to different contexts.

A Methodological Shift in Favor of (Some) Paraconsistency in the Sciences

Many have contended that non-classical logicians have failed at providing evidence of paraconsistent logics being applicable in cases of inconsistency toleration in the sciences. With this in mind, my main concern here is methodological. I aim at addressing the question of how should we study and explain cases of inconsistent science, using paraconsistent tools, without ruining into the most common methodological mistakes. My response is divided into two main parts: first, I provide some methodological guidance on how to approach cases of inconsistent science; and second, I focus on a peculiar type of formal methodologies for the scrutiny of inconsistent reasoning, the Paraconsistent Alternative Approach (henceforth, PAA) and argue that PAA can enhance a more accurate understanding of sensible reasoning in inconsistent contexts.

Modeling Multiple Views via Implicitly Preserving Global Consistency and Local Complementarity

While self-supervised learning techniques are often used to mining implicit knowledge from unlabeled data via modeling multiple views, it is unclear how to perform effective representation learning in a complex and inconsistent context. To this end, we propose a methodology, specifically consistency and complementarity network (CoCoNet), which avails of strict global inter-view consistency and local cross-view complementarity preserving regularization to comprehensively learn representations from multiple views. On the global stage, we reckon that the crucial knowledge is implicitly shared among views, and enhancing the encoder to capture such knowledge from data can improve the discriminability of the learned representations. Hence, preserving the global consistency of multiple views ensures the acquisition of common knowledge. CoCoNet aligns the probabilistic distribution of views by utilizing an efficient discrepancy metric measurement based on the generalized sliced Wasserstein distance. Lastly on the local stage, we propose a heuristic complementarity-factor, which joints cross-view discriminative knowledge, and it guides the encoders to learn not only view-wise discriminability but also cross-view complementary information. Theoretically, we provide the information-theoretical-based analyses of our proposed CoCoNet. Empirically, to investigate the improvement gains of our approach, we conduct adequate experimental validations, which demonstrate that CoCoNet outperforms the state-of-the-art self-supervised methods by a significant margin proves that such implicit consistency and complementarity preserving regularization can enhance the discriminability of latent representations.

A new inconsistent context fusion algorithm based on BP neural network and modified DST

As the number of various sensors grows fast in real applications such as smart city and intelligent agriculture, context-aware systems would acquire raw context information from dynamic, asynchronous and heterogeneous context providers, but multi-source information usually leads to the situation uncertainty of the system entities involved, which is harmful to appropriate services, and specially the inconsistency is a kind of main uncertainty problems and should be processed properly. A new inconsistent context fusion algorithm based on back propagation (BP) neural network and modified Dempster-Shafer theory (DST) combination rule is proposed in this paper to eliminate the inconsistency to the greatest extent and obtain accurate recognition results. Through the BP neural network, the situations of entities can be recognized effectively, and based on the modified combination rule, the recognition results can be fused legitimately and meaningfully. In order to verify the performance of the proposed algorithm, several experiments under different error rates of context information sources are conducted in the personal identity verification (PIV) application scenario. The experimental results show that the proposed BP neural network and modified DST based inconsistent context fusion algorithm can obtain good performance in most cases.

Putting visual object recognition in context.

Context plays an important role in visual recognition. Recent studies have shown that visual recognition networks can be fooled by placing objects in inconsistent contexts (e.g. a cow in the ocean). To understand and model the role of contextual information in visual recognition, we systematically and quantitatively investigated ten critical properties of where, when, and how context modulates recognition including amount of context, context and object resolution, geometrical structure of context, context congruence, time required to incorporate contextual information, and temporal dynamics of contextual modulation. The tasks involve recognizing a target object surrounded with context in a natural image. As an essential benchmark, we first describe a series of psychophysics experiments, where we alter one aspect of context at a time, and quantify human recognition accuracy. To computationally assess performance on the same tasks, we propose a biologically inspired context aware object recognition model consisting of a two-stream architecture. The model processes visual information at the fovea and periphery in parallel, dynamically incorporates both object and contextual information, and sequentially reasons about the class label for the target object. Across a wide range of behavioral tasks, the model approximates human level performance without retraining for each task, captures the dependence of context enhancement on image properties, and provides initial steps towards integrating scene and object information for visual recognition.

Impact of Informative Context's Meaning Consistency During Incidental Vocabulary Acquisition.

The authors examined the influence of context meaning consistency on incidental vocabulary acquisition during reading. Context meaning consistency refers to informational context that reflected the same meaning (i.e., consistent) or different meanings (i.e., inconsistent) across two self-paced reading sessions for a given item (both sessions on the same day). The first sentence of each sentence-pair item contained informational context, and the second sentence contained a target word (novel target or known control). Acquisition was assessed via surprise memory tests given right after the reading sessions (immediate) and again approximately a week later (delayed). Inconsistent context was generally associated with inflated reading times and less recall than consistent context, and retention was particularly low when the first encounter with the novel target was during the second reading session. Self-paced reading times were also particularly inflated in the second reading session for items in which readers encountered the novel word version of the target for the first time (i.e., known control encountered during the first reading session instead). Acquisition was facilitated most for novel targets that were presented during both reading sessions in consistent meaning context, but suffered the most in the case of consistent context and the novel target initially encountered in the second session. When presented with different meanings for the same novel target across self-paced reading sessions (inconsistent context condition), the intended meaning for the initial presentation was more likely to remain in memory.

In Capable Hands: An Experimental Study of the Effects of Competence and Consistency on Leadership Approval

Current research demonstrates that instances where leaders’ promises and actions are inconsistent leads to lower public approval and support. While there are exceptions to this trend there is no cohesive framework to address this issue. We introduce a conceptualization where public reactions to a leader’s inconsistency is placed in a broader context of public perception of the leader’s overall competency. We claim the public evaluation of the leader is dependent on her competency. And while inconsistency of a particular act can negatively affect public evaluations of the leader, the extent of that effect is conditioned by leaders’ competency. To test this perspective we experimentally manipulate both the competency of the leader as well as her consistency in following up on her promises. Furthermore, we expand the context of inconsistency to include both international and domestic domains. We find both leaders’ competency and inconsistency matter in public approval. Our findings hold across policy domains and levels of issue salience.

Mood-dependent retrieval in visual long-term memory: dissociable effects on retrieval probability and mnemonic precision

ABSTRACTAlthough memories are more retrievable if observers’ emotional states are consistent between encoding and retrieval, it is unclear whether the consistency of emotional states increases the likelihood of successful memory retrieval, the precision of retrieved memories, or both. The present study tested visual long-term memory for everyday objects while consistent or inconsistent emotional contexts between encoding and retrieval were induced using background grey-scale images from the International Affective Picture System (IAPS). In the study phase, participants remembered colours of sequentially presented objects in a negative (Experiment 1a) or positive (Experiment 2a) context. In the test phase, participants estimated the colours of previously studied objects in either negative versus neutral (Experiment 1a) or positive versus neutral (Experiment 2a) contexts. Note, IAPS images in the test phase were always visually different from those initially paired with the studied objects. We found that reinstating negative context and positive context at retrieval resulted in better mnemonic precision and a higher probability of successful retrieval, respectively. Critically, these effects could not be attributed to a negative or positive context at retrieval alone (Experiments 1b and 2b). Together, these findings demonstrated dissociable effects of emotion on the quantitative and qualitative aspects of visual long-term memory retrieval.

Negation in context: Evidence from the visual world paradigm.

Literature assumes that negation is more difficult to understand than affirmation, but this might depend on the pragmatic context. The goal of this paper is to show that pragmatic knowledge modulates the unfolding processing of negation due to the previous activation of the negated situation. To test this, we used the visual world paradigm. In this task, we presented affirmative (e.g., her dad was rich) and negative sentences (e.g., her dad was not poor) while viewing two images of the affirmed and denied entities. The critical sentence in each item was preceded by one of three types of contexts: an inconsistent context (e.g., She supposed that her dad had little savings) that activates the negated situation (a poor man), a consistent context (e.g., She supposed that her dad had enough savings) that activates the actual situation (a rich man), or a neutral context (e.g., her dad lived on the other side of town) that activates neither of the two models previously suggested. The results corroborated our hypothesis. Pragmatics is implicated in the unfolding processing of negation. We found an increase in fixations on the target compared to the baseline for negative sentences at 800 ms in the neutral context, 600 ms in the inconsistent context, and 1450 ms in the consistent context. Thus, when the negated situation has been previously introduced via an inconsistent context, negation is facilitated.

Role of the Public Engagement in the Reconstruction and Revival of the Distressed Urban Textures: Case Study of District 4 in Isfahan, Iran

<p class="zhengwen"><span lang="EN-GB">Old textures suffer deficiencies in terms of answering the needs of the today’s life due to old age and the resultant weariness and destruction and even the lack of urban facilities and equipment. When the urban life in part of a city becomes stagnant and no efforts are made to regain its boom. The urban texture in that area will be exposed to wearing out. The goal of this study is to review the existing drawbacks and bottlenecks in the process of the revival of the distressed texture of one of the neighborhoods located in District 4, Isfahan, called Kerdabad. The research method is applied in nature and follows a descriptive analytic approach. The findings of the research covers issues such as incompatible applications, resulting in the fact that 80 percent of respondents attribute their dissatisfaction from the environmental conditions of the neighborhood to workshop areas and agricultural fields in the margin of their neighborhood which in turn has resulted in slum life problems in the neighborhood and formation of an inconsistent social context in which 63 percent of the people are dissatisfied of these conditions. While 70 percent of the respondents express their willingness to refurbish their houses, only 73 percent of the respondents attribute proximity to their workplace as the main reason why they prefer to stay in the neighborhood and 89 inhabitants are not well satisfied with the urban services delivered. </span></p>

Making the incredible credible: Afterimages are modulated by contextual edges more than real stimuli

We explored whether color afterimages and faint physical chromatic stimuli are processed equivalently by the visual system. Afterimage visibility in classic illusions appears to be particularly influenced by consistent contexts, while real stimulus versions of these illusions are absent in the literature. Using both a matching and a nulling paradigm, we present converging evidence that luminance edges enhance the perceived saturation of afterimages more than they do physical stimuli of similar appearance. We suggest that afterimages violate the response norms associated with real stimuli. This leads to the afterimage signal being ambiguous for the visual system, and thus more susceptible to modulation by contexts that increase or decrease the probability of the signal representing a real object. This could explain why afterimages are rarely experienced in everyday life, where they will be overruled by inconsistent context.

Scene context influences without scene gist: Eye movements guided by spatial associations in visual search

Although the use of semantic information about the world seems ubiquitous in every task we perform, it is not clear whether we rely on a scene's semantic information to guide attention when searching for something in a specific scene context (e.g., keys in one's living room). To address this question, we compared contribution of a scene's semantic information (i.e., scene gist) versus learned spatial associations between objects and context. Using the flash-preview-moving-window paradigm Castelhano and Henderson (Journal of Experimental Psychology: Human Perception and Performance 33:753-763, 2007), participants searched for target objects that were placed in either consistent or inconsistent locations and were semantically consistent or inconsistent with the scene gist. The results showed that learned spatial associations were used to guide search even in inconsistent contexts, providing evidence that scene context can affect search performance without consistent scene gist information. We discuss the results in terms of hierarchical organization of top-down influences of scene context.

Design and evaluation of an ambient assisted living system based on an argumentative multi-agent system

This paper focuses on ambient assisted living systems employed to monitor the ongoing situations of elderly people living independently. Such situations are represented here as contexts inferred by multiple software agents out of the data gathered from sensors within a home. Sensors can give an incomplete, sometimes ambiguous, picture of the world; hence, they often lead to inconsistent contexts and unreliability on the system as a whole. We report on a solution to this problem based on a multi-agent system where each agent is able to support its understanding of the context through arguments. These arguments can then be compared against each other to determine which agent provides the most reliable interpretation of the reality under observation.

Providing internet connectivity and mobility management for MANETs

PurposeThe purpose of this paper is to describe the required functionalities on providing internet connectivity and mobility management for mobile ad hoc networks (MANETs), present discovered problems such as inconsistent contexts, and provide the corresponding solutions. It also provides a hybrid metric for the load‐balance of intra/inter‐MANET traffic over multiple internet gateways (IGWs).Design/methodology/approachThe paper uses both mathematical analyses and simulations to discover the required functionalities and problems on providing internet connectivity and mobility management for MANETs. The proposed hybrid metric for IGW selection is a replacement of the shortest hop‐count (HC) metric, and consider three factors: HC distance, intra‐MANET traffic, and inter‐MANET traffic.FindingsSimulation results show that ad hoc routing protocols, using the proposed metric, get better performance in terms of packet delivery ratio and transmission delay, at the cost of slightly increased signalling overhead.Research limitations/implicationsIn the assessment, simulation results are taken from two mobility scenarios, and the hybrid metric is integrated into only reactive ad hoc routing. Thus, more case studies need to be carried out to demonstrate the outcomes of the proposed metric compared with others.Practical implicationsThis paper provides the needed functionalities for broadening the richness of MANET applications to internet users, and vice verse.Originality/valueThis paper contributes to the research on internetworking and mobility management between MANETs and the internet.

Functional Neuroanatomy of Meaning Acquisition from Context

An important issue in language learning is how new words are integrated in the brain representations that sustain language processing. To identify the brain regions involved in meaning acquisition and word learning, we conducted a functional magnetic resonance imaging study. Young participants were required to deduce the meaning of a novel word presented within increasingly constrained sentence contexts that were read silently during the scanning session. Inconsistent contexts were also presented in which no meaning could be assigned to the novel word. Participants showed meaning acquisition in the consistent but not in the inconsistent condition. A distributed brain network was identified comprising the left anterior inferior frontal gyrus (BA 45), the middle temporal gyrus (BA 21), the parahippocampal gyrus, and several subcortical structures (the thalamus and the striatum). Drawing on previous neuroimaging evidence, we tentatively identify the roles of these brain areas in the retrieval, selection, and encoding of the meaning.

Similar Presentations of Disparate Etiologies: A New Perspective on Oppositional Defiant Disorder

ABSTRACT Oppositional defiant disorder is an individual diagnosis given commonly to children and adolescents who exhibit a pattern of noncompliant and defiant behaviors. Some children's temperament, behaviors, and interpersonal style merit this diagnosis. Other children, however, exhibit behaviors consistent with this diagnosis within the context of their family system. Certainly, the relationship between children's defiant behaviors and problematic circumstances in the family is best evidenced in the most popular treatments for oppositional defiant disorder, which involve working with parents as much as the children. In fact, some treatments of this disorder focus solely on educating the parent about consistency and immediacy in reinforcing positive behavior and ignoring or using time out for negative behavior. The purpose of this paper is to emphasize a different perspective of oppositional defiant disorder, one in which some children experience oppositional behaviors regardless of the parenting they receive and other children exhibit these same behaviors within an inconsistent family context.