Inferential Reasoning Research Articles

An Analysis of Nyaya Darshana with Special Emphasis on Realism

Nyaya School of Philosophy is distinctly recognized as one of the Six Astika Schools of Hindu Philosophy. Unlike Other Schools, Nyaya is peculiarly known to have proposed five components of Syllogism derived from Inferential Reasoning, both Inductive and Deductive. This treatise aims at clarifying The Nyaya Syllogisms, and successfully arguing for its Logical Realism. Logical Realism, in simple terms, refers to logical facts that are Independent of Mind and Language i.e., they are true synthetic a priori no matter the proposition. This Paper shall advocate the logical structure of Nyaya Syllogism which is independent of both mind and language. Also, the Inferential Reasoning that has been instrumentalized by Gautama to propose such Syllogisms shall be discussed to supplement the paper’s Groundwork. This paper has treated Nyaya in regard to its Epistemology and Logic. The reference to Nyaya, as a metaphysical or Ethical Doctrine, including the ideas of Causation, Fallacies, Truth, and Moksha has, for the most part, been sidelined. The Arguments have been drawn from the Original Works of Gautama called “The Nyaya Sutras” as well as Secondary Works which have further illuminated the works of Gautama. Hence, this Paper shall act as an advancement and supplement to the Nyaya Syllogism. It shall also shed light on the Contributions of Nyaya Syllogism in Syllogistic Logic.

Psilocybin in Palliative Care: An Update.

This review article summarizes clinically and socially relevant developments over the past five years in the therapeutic use of the classical tryptamine psychedelic substance psilocybin, with respect to the common challenges faced by palliative care patients and their care teams. Psilocybin is available in whole fungal and isolated forms but is not yet approved for therapeutic use in the United States. Using targeted database and gray literature searches, and author recall, key sources were identified, reviewed, and synthesized as to the safety and efficacy of psilocybin in palliative care. Life-threatening or life-limiting illnesses and faced by palliative care patients are comorbid with emotional and spiritual distress. Research and field reports reviewed suggest that psilocybin has significant and in some cases, sustained anxiolytic, antidepressant, anti-inflammatory and entheogenic effects with a favorable safety profile. Limitations of the research include the risk for selection bias toward healthy, white, financially privileged individuals, and in general, follow-up timelines too short to appropriately evaluate durability of outcomes in psychospiritual benefits and quality of life. While more research is needed for palliative care populations specifically, reasonable inferences can be made regarding the potential for benefit to palliative care patients from psilocybin's demonstrated anxiolytic, antidepressant, anti-inflammatory and entheogenic effects. However, major legal, ethical and financial barriers to access exist for the general population; obstacles which are likely worsened for geriatric and palliative care patients. Empiric treatment and large-scale controlled trials of psilocybin should be conducted to further investigate the findings of the smaller studies reviewed here across a variety of populations, for a greater understanding of therapeutic benefit and clinically relevant safety criteria, and to support thoughtful legalization and medical access.

Mechanisms in continued influence: The impact of misinformation corrections on source perceptions.

Research on the continued influence effect (CIE) of misinformation has demonstrated that misinformation continues to influence people's beliefs and judgments even after it has been corrected. Although most theorizing about the CIE attempts to explain why corrections do not eliminate belief in and influences of the misinformation, the present research takes a different approach and focuses instead on why corrections do reduce belief in misinformation (even if not entirely). We examined how a correction can change perceptions of the original source of the misinformation and how these changes in perceptions can mediate continued influence effects. We also examined causal evidence linking manipulations of misinformation source perceptions to continued belief and misinformation-relevant inferential reasoning. Study 1 demonstrated that an external correction (i.e., a new source labeling misinformation as false) influences perceptions of the misinformation source, and these perceptions of the misinformation source then correlated with belief in the misinformation. Study 2 replicated the results of Study 1 and used source derogation to manipulate misinformation source perceptions and further lessen continued belief. Study 3 was a preregistered replication of previous results using new methodology. These studies suggest that perceptions of the misinformation source is one mechanism that can cause changes in belief in misinformation, and changes in the perception of a source can be achieved simply by correcting the source or through other means. This approach can be used to find other mechanisms responsible for reducing belief in misinformation.

“Your truth isn’t the Truth”: Data activities and informal inferential reasoning

This paper investigates data activities in an afterschool setting, offering a deeper understanding of the social nature of students’ informal inferences by investigating how informal inferences are negotiated in group interactions, influenced by social norms, and how statistical concepts come into play in learners’ informal inferential reasoning (IIR). Analyses take up a multi-sited orientation to investigate how youth used quantitative and contextual resources during a research activity to make meaning of data and negotiate emergent social tensions. Findings show how data activities that are part of informal inferential reasoning, such as collection, interpretation, generalization, inference, and representation unfolded as social, political, and personal. Implications call for designs for learning that better support working with data and understanding real-world phenomena and sociopolitical issues in ways that leverage youths’ experiences, enabling them to take part in social action as critical community actors.

A Knowledge Inference and Sharing-Based Open-Set Device Recognition Approach for Satellite-Terrestrial-Integrated IoT

Satellite-terrestrial-integrated internet of things (IoT) is an inevitable trend in future development, but open satellite link and massive IoT device access will bring serious security risks. However, most existing recognition models are unable to discover and reject malicious IoT devices since they lack the decision information of these unauthorized devices during training. To address this dilemma, this paper proposes a knowledge inference and sharing-based open-set recognition approach to protect satellite-terrestrial-integrated IoT. It proceeds in two steps. First, knowledge inference, where we construct ideal substitutes for unauthorized devices after reasonable inference on the training set, aims to compensate the model’s missing decision information. Second, knowledge sharing, where we inherit the existing knowledge and modify the model’s decision boundaries through model expansion and knowledge distillation, achieves accurate open-set recognition. Experiments on the ORACLE dataset demonstrated that our approach outperforms other state-of-the-art OSR methods in terms of accuracy and running time. In short, our approach has excellent performance while only slightly increasing computational complexity.

TINDAK PIDANA MENYEBARKAN BERITA BOHONG MERUGIKAN KONSUMEN MELALUI MEDIA SOSIAL INSTAGRAM

Online fraud is when a writer accesses a website using internet services with the intention of fooling one of the people he intends to target. As a result, lawmakers must be more aggressive in punishing those who commit fraud, particularly online fraud, by having a deterrent effect on others who do so. 1) Did the Respondent's activities satisfy the criteria listed in Article 45A Paragraph (1) of the Electronic Transaction Information Law Number 19 of 2016 (Research Decision Number 1085/pid.sus/2020/PN.bdg)? This is the problem formulation for this final work; 2) How do judges penalize those who commit online fraud using the social media platform Instagram (analysis of decision No. 1085/Pid.sus/2020/PN.Bdg). With secondary data and qualitative analysis, this form of study is normative, and inferential reasoning is used to arrive at findings. Conclusion: 1) The respondent's conduct satisfy the conditions outlined in Article 45A (1); 2) based on the judge's sentencing in that case, which was based only on theory, particularly contemporary, which combines all three types of sentencing theories-absolute, relative, and a combination of the two-and must satisfy the following criteria: Deterrence, education, rehabilitation, social control, rehabilitation, restorative justice.

Humour through the Scope of Social Theories and Pragmatic Approaches

Abstract: For many years, humour has been the subject of scientific research and it has been related to movies, television shows, literature, sociology, and others. When analysing how comic effect is achieved, humour can be complicated and multifaceted. For that reason, there is no specific theory that explains humour ideally. However, the various social theories and pragmatic approaches to humour, each of which focuses on the different aspects of humour functioning, complement each other. The article aims to present the propositions on humour and the central claims of different social theories and pragmatic approaches. Attention is focused on the butt of the ridicule, the psychoanalytic aspect of humour, and the surprise element. In addition, human agency, cultural knowledge, linguistic means and cognition, ostensive stimuli, and inferential reasoning are also outlined. Thus, the article contributes to a more profound and adequate understanding of the inventive and resourceful propositions on humour and comic discourse analysis. Keywords: humour, superiority theory, relief theory, incongruity theory, conversational maxims, relevance theory.

Scienza, diritto e giustizia internazionale (Science, Law and International Adjudication). By Chiara Ragni

Often, international adjudication needs to confront science. This is particularly so within international legal disputes that concern environmental and/or health matters. Almost a century ago a panel of arbitrators in Trail Smelter was asked to determine the amount of compensation for the reduction in value of land which had been affected by sulphur dioxide gases. The Tribunal, to be able to award damages, had to rely on a ‘just and reasonable inference’, aware that ‘the result [could] be only approximate.’1 In time, these types of assessments have become more frequent, more complex, and more sophisticated. One could refer, for example, to the difficulty in fully understanding the various implications of the presence of certain substances in a river for the health of the organisms present therein. International adjudicators are asked to digest very technical information upon which to base their judicial reasoning or, as it was put by Judges Al-Khasawneh and Simma in their joint dissenting opinion in Pulp Mills, ‘to arrive at a basis for the application of the law to the facts as scientifically certain as is possible in a judicial proceeding.’2 But are adjudicators equipped to do so? How do they conduct such assessments?

The integration of undergraduate students’ informal and formal inferential reasoning

The integration of undergraduate students’ informal and formal inferential reasoning

Exploring the Cognitive-Communication Challenges of Adults With Histories of Traumatic Brain Injury and Criminal Justice System Involvement: A Pilot Study.

The prevalence of traumatic brain injury (TBI) in the criminal justice system (CJS) is well known. Furthermore, the impact of TBI on communication has been well documented; however, no study has explored the communication challenges of those with TBI in the CJS or considered their implications within CJS contexts. Moreover, no study has examined the possible differences in communication between those with TBI and CJS history and those with TBI but no CJS history. This cross-sectional pilot study provides a preliminary exploration of the cognitive-communication challenges in a sample of adults with histories of TBI and CJS involvement compared with a sample of adults with histories of TBI but no CJS involvement. Eight individuals with histories of TBI and CJS involvement were recruited through community agencies. The La Trobe Communication Questionnaire (LCQ) was administered to collect self-reported data on perceived cognitive-communication abilities, including social communication behaviors. Findings were examined and then compared with a previously studied sample of 160 individuals with TBI. Logistic regressions were calculated to determine whether response scores on the LCQ would be predictive of group membership (i.e., TBI + CJS or TBI only). A range of cognitive-communication challenges were reported by both groups. A logistic regression analysis demonstrated a reasonable inference that LCQ responses may predict group membership and support the potential for statistically significant and meaningful results to justify future studies. These challenges have the potential to negatively impact the success of communication interactions within the CJS and illustrate a need for speech-language pathology services for individuals with TBI in the CJS. The nature and magnitude of between-group differences merits further investigation with larger samples to explore whether any specific cognitive-communication challenge is unique to, or predictive of, CJS involvement for purposes of targeted assessment and intervention.

Critical Rationalism and Bayesianism

Most accounts of the scientific method, e.g.s the Deductive-Nomological (D-N), Inductive Statistical (I-S), and so on, attempt to avoid Hume’s problem. Popper’s philosophy of critical rationalism and subjectivist Bayesianism come into conflict here on a number of points. The most noteworthy is on the problem of induction. That is, if science rests on induction (as Sir Francis Bacon would have it), and induction cannot be justified according to the strict demands of classical deductive validity without invoking a circularity, how can we say that science is rational? And how should scientists proceed? Bayesians utilizes a consistent multivalued logic that adheres to the Kolmogorov axioms. And on the other side, Sir Karl Popper maintains that the real logic of science is deductive. It is a myth that induction is even used. I will evaluate both claims through a third-party lens. That is, Micheal Ruse’ s epigenetic account of inferential reasoning. This is a modified version of Hume’s propensity theory. Ultimately, deductivism cannot explain how proto-humans behaved in the wild. How they grew smarter, became tool-using beings, and became the dominant species on the planet.

Clinical Intuition and Working Memory: Implications for Training and Supervision

Competence with emergent intuitive awareness, from fringe-of-consciousness hunches to compelling difference-in-kind realisations, is an imprecise qualitative skill and, on this basis, one generally overlooked in clinical psychology training and supervision. This situation is at marked odds with an expanding literature highlighting that intuitions emerging from unconscious inferential cognition serve as a primary resource in the decision-making of expert practitioners across a dissimilar range of professions. Additionally, (i) over forty years extensive and distinct research into working memory conclusively demonstrates that System 1 autonomous inferential reasoning is the mind’s powerhouse, yet moreover (ii) plays a determining role in attention allocation and thereby meta-level reasoning processes (i.e., System 2; cognitive control/metacognition), the very constituents of reflective practice. In short, the case appears overwhelming for clinical intuition competency training. Additionally, a substantial reflective practice training literature which could readily be modified to include clinical intuition considerations sits immediately at hand. One difficulty, however, is that an accommodating model which will seamlessly link, firstly, difference-in-kind S1 emergent awareness, and, secondly, meta-level reflective practice, is yet to be highlighted. Remarkably, coherence-based reasoning sits in plain sight as a potential bridging position. Finally, expanding upon elementary suggestions in the literature, the toolbox skills ‘slow-onset speech’, ‘affective inquiry’, and ‘therapeutic presence’ are put forward as therapy technique functional for enhancing a clinician’s intuition sensitivity.

Effect of the wind speed on aerodynamic behaviours during the acceleration of a high-speed train under crosswinds

A high-speed train that accelerates under crosswinds can potentially encounter dramatic aerodynamic effects and safety risks. The goal of this study is to reveal the effect of wind speed on the instantaneous vortex structures, pressure distribution, aerodynamic loads and safety indicators of a high-speed train that is accelerating under crosswinds. The three-dimensional and incompressible IDDES method combined with moving overset grid technology is applied to obtain reliable results. The main results are summarized as follows: two typical inclined vortices on the leeward side are observed, and the amplitude and area of the negative pressure in the vortex core region increase with increasing wind speed. The leeward side and the roof exhibit severe pressure fluctuations, and the sensitivity of the pressure from wind speed on the head car is stronger than that on other carriages. For aerodynamic force/moment coefficients, local maximum/minimum values appear during the acceleration process; a reasonable inference for this phenomenon is that a certain range of yaw angles causes the force/moment coefficient to reach the local maximum/minimum values. Wind speed has a significant increasing effect on the maximum values of the lateral force coefficient and rolling moment coefficient, especially for the head car. Although the overturning coefficient and derailment coefficient are less than the prescribed safety thresholds, the overturning risk needs more attention than the derailment risk considering that the maximum value of the overturning coefficient is twice that of the derailment coefficient. The obtained numerical results can provide a preliminary reference for train accelerations under crosswind.

FireNet-v2: Improved Lightweight Fire Detection Model for Real-Time IoT Applications

Fire hazards cause huge ecological, social and economical losses in day to day life. Due to the rapid increase in the prevalence of fire accidents, it has become vital to equip the assets with fire prevention systems. There have been numerous researches to build a fire detection model in order to avert such accidents, with recent approaches leveraging the enormous improvements in computer vision deep learning models. However, most deep learning models have to compromise with their performance and accurate detection to maintain a reasonable inference time and parameter count. In this paper, we present a customized lightweight convolution neural network for early detection of fire. By virtue of low parameter count, the proposed model is amenable to embedded applications in real-time fire monitoring equipment, and even upcoming fire monitoring approaches such as unmanned aerial vehicles (drones). The fire detection results show marked improvement over the predecessor low-parameter-count models, while further reducing the number of trainable parameters. The overall accuracy of FireNet-v2, which has only 318, 460 parameters, was found to be 98.43% when tested over Foggia's dataset.

Development and Application of Convergence Education about a Support Vector Machines for Elementary Learners

This paper proposes an artificial intelligence (AI) convergence education program that teaches the concept and principles of support vector machines (SVM). It was applied to elementary school students to check the effectiveness of education. The developed program describes the decision boundaries and margins of the SVM through the distance between the vertical and parallel lines of the elementary mathematics curriculum. The SVM education program was piloted to 18 3rd graders and 16 5th graders. Students' reactions were observed during classes, and learning output and self-evaluation results were analyzed after the classes. As a result, most students intuitively inferred the location of the trails, which represents the decision boundary. At this time, the overall activity performance accuracy of fifth-grade learners was higher, and the rate of reasonable inference on the principle of setting was also higher. The completion of the fourth-grade math curriculum also affected the students’ understanding. However, in the self-evaluation of the understanding of learning content, contrary to the actual comprehension, the average value was higher in the third grade. This was because middle-grade learners had a greater tendency to feel satisfaction and achievement when they newly learned about the unfamiliar AI principle. However, higher-grade learners presented more meaningful post-class. The novelty of this paper can be found in that it attempted to educate the SVM for elementary learners. In the future, it is necessary to apply the program to a larger number of learners, supplement and develop the program and contribute to the AI principles education for elementary school students. Keywords: support vector machines, artificial intelligence education, convergence education, elementary education, artificial intelligence algorithm. DOI: https://doi.org/10.55463/hkjss.issn.1021-3619.60.75

Many Faces of Mediation

Many Faces of Mediation

Inferential reasoning ability moderates the influence of mediated exemplars on risk perception

ABSTRACT Research has shown that vivid exemplars bias risk perceptions, raising concerns about the role of media in shaping public opinion. However, receiver characteristics that moderate the influence of vivid exemplars remain understudied. We propose that insofar as exemplars in media portrayals represent (at times biased) samples of the population of events, inferential reasoning ability (IRA) – the knowledge of and skill at applying inferential and statistical principles – may enable people to avoid drawing invalid inferences from exemplars. In two message-exposure experiments employing different designs and stimulus materials, we find that exemplars conditionally influence perceptions of risk, depending on the receiver’s IRA. Specifically, higher IRA was associated with reduced influence of vivid exemplars. This work highlights the importance of accounting for heterogeneous audiences in risk messaging and offers tools for measuring audience IRA.

Assumptions, Hypotheses, and Antecedents

This paper is about the distinction between arguments and conditionals, and the corresponding distinction between premises and antecedents. I will also propose a further distinction between two different kinds of argument, and, correspondingly, two kinds of premise that I will call "assumption" and "hypothesis." The distinction between assumptions, hypotheses, and antecedents is easily made in artificial languages, and we are already familiar with it from our first logic courses (although not necessarily under those names, since there is no standard terminology for the distinction). After explaining their differences in artificial languages, I will argue that there are ordinary-language counterparts of these three notions, meaning that some formal properties of the artificial notions nicely capture some features of the ordinary-language counterparts and their behavior in contexts of reasoning. My next crucial claim is that these three notions often get confused in ordinary language, which leads to problems for translation into symbols. I will suggest a solution to the translation problem by pointing to some distinctive characteristics of the three notions that link them to their artificial-language counterparts. Next, I will argue that this confusion is behind some well-known philosophical problems and puzzles. I will apply the distinctions in order to explain away some famous paradoxes: the direct argument (also known as or-to-if inference), a standard argument for fatalism, and McGee's counterexample to modus ponens. As Stalnaker also solved the first two of these paradoxes by using his theory of reasonable inference, I will elucidate the similarities between our solutions, and also explain why my distinctions apply more broadly, to some cases involving indicative and counterfactuals conditionals, where reasonable inference does not apply.

Neighborhood rough cognitive networks

Rough cognitive network (RCN) is a granularity neural network combining fuzzy cognitive maps with rough set theory, which has the advantages of transparency and interpretability. However, When the existing RCN are applied to the decision-making aspects of practical problems, they exhibit problems such as weak generalization and unstable performance. To solve the above problems, a highly efficient classification decision model neighborhood rough cognitive networks (NRCN) is proposed. It uses a feature selection algorithm based on the neighborhood rough set to minimize the data dimensionality. Moreover, the introductions of sub-neurons and Hellinger distance in proposed model can better discover knowledge and make more reasonable inference decisions. Various open datasets and real financial data are implemented to verify the effectiveness and validity of the proposed method.

Bayesian reasoning with emotional material in patients with schizophrenia.

Delusions are one of the most classical symptoms described in schizophrenia. However, despite delusions are often emotionally charged, they have been investigated using tasks involving non-affective material, such as the Beads task. In this study we compared 30 patients with schizophrenia experiencing delusions with 32 matched controls in their pattern of responses to two versions of the Beads task within a Bayesian framework. The two versions of the Beads task consisted of one emotional and one neutral, both with ratios of beads of 60:40 and 80:20, considered, respectively, as the "difficult" and "easy" variants of the task. Results indicate that patients showed a greater deviation from the normative model, especially in the 60:40 ratio, suggesting that more inaccurate probability estimations are more likely to occur under uncertainty conditions. Additionally, both patients and controls showed a greater deviation in the emotional version of the task, providing evidence of a reasoning bias modulated by the content of the stimuli. Finally, a positive correlation between patients' deviation and delusional symptomatology was found. Impairments in the 60:40 ratio with emotional content was related to the amount of disruption in life caused by delusions. These results contribute to the understanding of how cognitive mechanisms interact with characteristics of the task (i.e., ambiguity and content) in the context of delusional thinking. These findings might be used to inform improved intervention programs in the domain of inferential reasoning.