Truth Values Research Articles

A Multi-truth Discovery Algorithm based on Statement Value Grouping and Data Source Information Richness

As the volume of data continues to grow, it is common for data from the same source to contain multiple domains. Combining domain segmentation can enhance the effectiveness of data fusion. This paper presents a multi-truth discovery algorithm that utilises statement value grouping and domain information richness. The data is first grouped based on their similarity, and the resulting groups replace the original data. Then, the reliability of each data source is calculated by domain. The truth value and reliability of each source are iteratively calculated until the end condition is met. Finally, the appropriate value is selected as the final result from the obtained dataset. Experiments were conducted on real datasets to demonstrate the algorithm's effectiveness.

Informed Ignorance as a Form of Epistemic Injustice

Ignorance, or the lack of knowledge, appears to be steadily spreading, despite the increasing availability of information. The notion of informed ignorance herein proposed to describe the widespread position of being exposed to an abundance of information yet lacking relevant knowledge, which is tied to the exponential growth in misinformation driven by technological developments and social media. Linked to many of societies’ most looming catastrophes, from political polarization to the climate crisis, practices related to knowledge and information are deemed some of the most imminent and daunting modern threats, evidenced by the latest report of the World Economic Forum, which has named misinformation the most severe short-term global risk. This paper’s epistemic perspective links the properties of today’s information culture and the ways in which it interacts with individual capacities and limitations in current technological and socio-political contexts. Such a position is analyzed through the lens of epistemic principles as a contemporary epistemic phenotype that emerges from an environment of ill-adapted and excessive information inputs and leads to a distinctive type of social injustice that is primarily epistemic in nature. While equity and accessibility are widely discussed as important contributing factors to epistemic discrepancies, other overlooked but fundamental issues underlying epistemic injustices are considered, such as information manipulation, cognitive limitations, and epistemic degradation. To effectively face this elusive threat, we propose an inclusive viewpoint that harnesses knowledge from cognitive science, science and technology studies, and social epistemology to inform a unifying theory of its main impacts and driving forces. By adjusting a modern epistemic framework to the described phenomena, we intend to contextually outline its trajectory and possible means of containment based on a shared responsibility to maintain ethical epistemic standards. In a time of international unrest and mounting civil acts of violence, it is pertinent to emphasize the ethical principles of knowledge systems and authorities and suggest policy adaptations to maintain a social contract based on the shared values of truth and freedom.

Variability and bias in microbiome metagenomic sequencing: an interlaboratory study comparing experimental protocols.

Several studies have documented the significant impact of methodological choices in microbiome analyses. The myriad of methodological options available complicate the replication of results and generally limit the comparability of findings between independent studies that use differing techniques and measurement pipelines. Here we describe the Mosaic Standards Challenge (MSC), an international interlaboratory study designed to assess the impact of methodological variables on the results. The MSC did not prescribe methods but rather asked participating labs to analyze 7 shared reference samples (5 × human stool samples and 2 × mock communities) using their standard laboratory methods. To capture the array of methodological variables, each participating lab completed a metadata reporting sheet that included 100 different questions regarding the details of their protocol. The goal of this study was to survey the methodological landscape for microbiome metagenomic sequencing (MGS) analyses and the impact of methodological decisions on metagenomic sequencing results. A total of 44 labs participated in the MSC by submitting results (16S or WGS) along with accompanying metadata; thirty 16S rRNA gene amplicon datasets and 14 WGS datasets were collected. The inclusion of two types of reference materials (human stool and mock communities) enabled analysis of both MGS measurement variability between different protocols using the biologically-relevant stool samples, and MGS bias with respect to ground truth values using the DNA mixtures. Owing to the compositional nature of MGS measurements, analyses were conducted on the ratio of Firmicutes: Bacteroidetes allowing us to directly apply common statistical methods. The resulting analysis demonstrated that protocol choices have significant effects, including both bias of the MGS measurement associated with a particular methodological choices, as well as effects on measurement robustness as observed through the spread of results between labs making similar methodological choices. In the analysis of the DNA mock communities, MGS measurement bias was observed even when there was general consensus among the participating laboratories. This study was the result of a collaborative effort that included academic, commercial, and government labs. In addition to highlighting the impact of different methodological decisions on MGS result comparability, this work also provides insights for consideration in future microbiome measurement study design.

Konsep Pendidikan Islam Berbasis Tauhid Pada Masa Rasulullah

The aim of this research is to analyze the concept of Islamic education based on monotheism during the time of the Prophet. This type of research is a library study. Data collection with documentation. Data analysis with SLR. The research results obtained are The concept of Islamic education based on monotheism during the time of the Prophet was the main foundation in the formation of Muslim individuals with character. Education at that time was not only focused on academic aspects, but also strengthened faith and awareness of the oneness of Allah. The Prophet as the main role model paid great attention to moral, spiritual and social education, which is based on monotheism. Through these teachings, Muslim society at that time was able to build a strong personality, uphold the values of truth, justice and compassion in all aspects of life, thereby creating a harmonious and dignified society.

The Truth in Social Media

AbstractIn the last chapter of In the beginning was the deed: realism and moralism in political argument, Williams raised the question of truthfulness in politics and warned that the media, particularly, television, and the market of communication in general, work in ways contrary to truthfulness -understood as the combination of the virtues of sincerity and accuracy. In this paper we would like to carry on Williams’ line of thinking in connection with the impact of the new social media platforms on politics. Where Williams focused on television, we will consider the impact of the internet public sphere. After reviewing how the digital social media encourages motivated reasoning in general, we propose to focus on two main phenomena derived from it: the rise of conspiracy theories and the moralization of politics. Conspiracy theories epitomize the risk of self-deception Williams was concerned to signal. On the other hand, the process of moralization of politics triggers sectarianism and hate for the “others”, the outgroup. Both phenomena are not exclusive of the internet sphere, but both are boosted by it, and entail a lack of interest in truth and truthfulness, and in this way they threaten the value of truth for democracy.

Filter-based Stance Network for Rumor Verification

Rumor verification on social media aims to identify the truth value of a rumor, which is important to decrease the detrimental public effects. A rumor might arouse heated discussions and replies, conveying different stances of users that could be helpful in identifying the rumor. Thus, several works have been proposed to verify a rumor by modelling its entire stance sequence in the time domain. However, these works ignore that such a stance sequence could be decomposed into controversies with different intensities, which could be used to cluster the stance sequences with the same consensus. In addition, the existing stance extractors fail to consider both the impact of all previously posted tweets and the reply chain on obtaining the stance of a new reply. To address the above problems, in this article, we propose a novel stance-based network to aggregate the controversies of the stance sequence for rumor verification, termed Filter-based Stance Network (FSNet). As controversies with different intensities are reflected as the different changes of stances, it is convenient to represent different controversies in the frequency domain, but it is hard in the time domain. Our proposed FSNet decomposes the stance sequence into multiple controversies in the frequency domain and obtains the weighted aggregation of them. Specifically, FSNet consists of two modules: the stance extractor and the filter block. To obtain better stance features toward the source, the stance extractor contains two stages. In the first stage, the tweet representation of each reply is obtained by aggregating information from all previously posted tweets in a conversation. Then, the features of stance toward the source, i.e., rumor-aware stance, are extracted with the reply chains in the second stage. In the filter block module, a rumor-aware stance sequence is constructed by sorting all the tweets of a conversation in chronological order. Fourier Transform thereafter is employed to convert the stance sequence into the frequency domain, where different frequency components reflect controversies of different intensities. Finally, a frequency filter is applied to explore the different contributions of controversies. We supervise our FSNet with both stance labels and rumor labels to strengthen the relations between rumor veracity and crowd stances. Extensive experiments on two benchmark datasets demonstrate that our model substantially outperforms all the baselines.

Evaluation of 22 CMIP6 model-derived global soil moisture products of different shared socioeconomic pathways

The Sixth Phase of the Coupled Model Intercomparison Project (CMIP6) provides ample soil moisture (SM) products during 2015–2100, which are widely used in investigating future hydrological pattern. However, there remains limited understanding regarding the accuracy of multi-model CMIP6 SM future simulations following different Shared Socioeconomic Pathways (SSP). This study assesses the spatial–temporal accuracy of 22 CMIP6 model-derived SM products using 670 ground observation stations globally during 2015–2023. Each CMIP6 model encompasses SM estimations from SSP1-2.6 (The sustainable pathway), SSP2-4.5 (The medium pathway), and SSP5-8.5 (Fossil-fueled development). The latest Soil Moisture Active Passive (SMAP) and European Centre for Medium-Range Weather Forecast Reanalysis v5-Land (ERA5-Land) SM products serve as reference benchmarks. The SM among three SSPs within the same model exhibits similar performance in in situ validation, the extended triple collocation assessment, and the classical seasonal decomposition trend analysis. This similarity may suggest a subtle variation in the influence of different SSPs on SM in the early stages of the future scenario. The majority of CMIP6 model-derived SM could reasonably capture the spatial distribution pattern and temporal evolution trend of the truth value. Meanwhile, noticeable discrepancies in accuracy, particularly regarding goodness-of-fit, are evident when compared to SMAP and ERA5-Land SM products. The CMIP6 models could provide better SM estimation in temperate and tropical zones than cold zones. In terms of differences between the land cover types, CMIP6 model-derived SM products perform well over various vegetated regions except for barren, where there are sequential overestimation and relatively low fitting degree. Extensive accuracy discrepancies exist among the 22 CMIP6 model-derived SM products due to variations in model parameterization methods and atmospheric variables.

About Logically Probable Sentences

The starting point of this paper is the empirically determined ability to reason in natural language by employing probable sentences. A sentence is understood to be logically probable if its schema, expressed as a formula in the language of classical propositional calculus, takes the logical value of truth for the majority of Boolean valuations, i.e., as a logically probable formula. Then, the formal system P is developed to encode the set of these logically probable formulas. Based on natural semantics, a strong completeness theorem for P is proved. Alternative notions of consequence for logically probable sentences are also considered.

The Domains of Monotonicity Processing

Abstract This paper reports an investigation into the nature of Negative Polarity Item (NPI) licensing conditions from a processing perspective. We found that the processing cost of Downward Entailingness (a k a the Monotonicity Effect) is determined by the number of monotonicity reversals of NPI domains, rather than by the number of Downward-Entailing (DE) operators. This conclusion is not based on the standard judgment paradigm, but rather, on the measurement of continuous variables (error rates, Reaction Times (RTs)) in a verification task, in which the truth value of a sentence is determined against a scenario. We conducted two experiments with sentences that contained one or two DE operators, which featured in different syntactic configurations. We explored how RT is affected by the manipulation of both the number of DE operators, and the syntactic environments in which they reside. We ran these experiments in Hebrew and in English, with different participant populations and different testing methods. Despite the linguistic subtlety of the theoretical issues, our results were remarkably sharp, leading to two firm conclusions: (i) that processing time is determined not by the number of DE operators, but rather, by the monotonicity of the minimal constituent in which they reside; (ii) that DE-ness is not a property of operators, but of environments. We show how our results bear directly on the current debate about the nature of monotonicity, which we describe below. Finally, we provide quantitative tests of alternative, non-semantic explanations, and show how our results do not support them.

Psychology of Religion: The Relationship Between Islamic Spirituality and Psychological Well-Being

Psychological well-being is an indicator of individual well-being to meet the criteria for positive psychological functioning. One of the factors that can fulfill a positive psychological function is the presence of a high spirit of spirituality which is assisted by the ability to interpret life which cannot be separated, such as carrying out the values of truth and goodness to achieve prosperity. The aim of this research is to determine the relationship between spirituality and psychological well-being. Respondents in this study totaled 115 people consisting of 32 male and 83 female Muslim respondents with an age range of 18-25 years. In this study, the Ryff scale of psychological well-being and the Swinton scale of spirituality was used. The data collection method uses two scales, namely the spirituality scale and psychological well-being. Data were analyzed using Pearson's Product Moment correlation technique. The results show that the correlation between psychological well-being and Islamic spirituality is 0.528 with a significance value of 0.000. It is known that the correlation is classified as a fairly strong correlation, meaning that there is a fairly strong relationship between psychological well-being and Islamic spirituality. Keywords: relationship, psychological well-being, islamic spirituality

Sane Salvage: Re-reading the Dissemination of Indian Values in Sudha Murty’s The Magic Drum and Other Favourite Stories

Moral values are sets of socio-culturally wrought guidelines for human behaviour that ensure acceptance of individuals as honest and valued members of a given community. Since literature reflects society and defines morality, it often operates as a medium for disseminating moral values specific to an age and a place. Sudha Murty, the chairperson of Infosys, an Indian multinational information technology company, is also a significant Indian writer in English with more than twenty published books to her credit. Though one of life’s achievers, Murty has remained grounded in her roots of Indian tradition and Indian values. In the intended study, I want to analyse selected short stories from Murty's story collection, The MAGIC DRUM and other favourite Stories (2006), to underscore how Murty tries to salvage Indian values for her target readership of children and young adults. As will be shown, her purpose is to regain and retain moral sanity in the face of severe value erosion. I shall briefly discuss stories like The Seed of Truth; A Bottle of Dew and The Lucky Purse on the one hand and The Last Laddoo; The White Crow and Haripant the Wise on the other to foreground her praise of the positive values of truthfulness, diligence, and kindness in the first set of stories and her opposition to the negative traits like niggardliness, exaggeration, and avarice in the second set. I will try to show how Murty highlights values promoted and vices decried. Attempts will also be made to indicate the significance of the author’s invocation of a rural past and invectives against a consumerist culture in the selected short stories.

Deep-learning based 3D reconstruction of lower limb bones from biplanar radiographs for preoperative osteotomy planning

PurposeThree-dimensional (3D) preoperative planning has become the gold standard for orthopedic surgeries, primarily relying on CT-reconstructed 3D models. However, in contrast to standing radiographs, a CT scan is not part of the standard protocol but is usually acquired for preoperative planning purposes only. Additionally, it is costly, exposes the patients to high doses of radiation and is acquired in a non-weight-bearing position.MethodsIn this study, we develop a deep-learning based pipeline to facilitate 3D preoperative planning for high tibial osteotomies, based on 3D models reconstructed from low-dose biplanar standing EOS radiographs. Using digitally reconstructed radiographs, we train networks to localize the clinically required landmarks, separate the two legs in the sagittal radiograph and finally reconstruct the 3D bone model. Finally, we evaluate the accuracy of the reconstructed 3D models for the particular application case of preoperative planning, with the aim of eliminating the need for a CT scan in specific cases, such as high tibial osteotomies.ResultsThe mean Dice coefficients for the tibial reconstructions were 0.92 and 0.89 for the right and left tibia, respectively. The reconstructed models were successfully used for clinical-grade preoperative planning in a real patient series of 52 cases. The mean differences to ground truth values for mechanical axis and tibial slope were 0.52° and 4.33°, respectively.ConclusionsWe contribute a novel framework for the 2D–3D reconstruction of bone models from biplanar standing EOS radiographs and successfully use them in automated clinical-grade preoperative planning of high tibial osteotomies. However, achieving precise reconstruction and automated measurement of tibial slope remains a significant challenge.

Quantitative accuracy of lung function measurement using parametric response mapping: A virtual imaging study.

Parametric response mapping (PRM) is a voxel-based quantitative CT imaging biomarker that measures the severity of chronic obstructive pulmonary disease (COPD) by analyzing both inspiratory and expiratory CT scans. Although PRM-derived measurements have been shown to predict disease severity and phenotyping, their quantitative accuracy is impacted by the variability of scanner settings and patient conditions. The aim of this study was to evaluate the variability of PRM-based measurements due to the changes in the scanner types and configurations. We developed 10 human chest models with emphysema and air-trapping at end-inspiration and end-expiration states. These models were virtually imaged using a scanner-specific CT simulator (DukeSim) to create CT images at different acquisition settings for energy-integrating and photon-counting CT systems. The CT images were used to estimate PRM maps. The quantified measurements were compared with ground truth values to evaluate the deviations in the measurements. Results showed that PRM measurements varied with scanner type and configurations. The emphysema volume was overestimated by 3 ± 9.5 % (mean ± standard deviation) of the lung volume, and the functional small airway disease (fSAD) volume was underestimated by 7.5±19 % of the lung volume. PRM measurements were more accurate and precise when the acquired settings were photon-counting CT, higher dose, smoother kernel, and larger pixel size. This study demonstrates the development and utility of virtual imaging tools for systematic assessment of a quantitative biomarker accuracy.

Calibration of visual measurement system for excavator manipulator pose

The automatic control of excavator operation trajectories is a pivotal technology for autonomous excavators, with the essential prerequisite being the real-time measurement of manipulator poses. Given the complexity of the operating environment, traditional sensor-based measurement methods face limitations, whereas visual measurement emerges as a promising technique. Accurately measuring excavator manipulator poses involves a crucial aspect: mapping the relationship between image information and poses. First, to address the significant errors in pose prediction encountered with machine learning techniques like artificial neural networks, this work introduces a mathematical model for mapping this relationship, referred to as the pose mapping mathematical model, which includes calibrating model parameters. Second, to address the sensitivity of initial values in the calibration process, we propose a residual-guided initialization algorithm. This algorithm aims to ensure that initial values closely approximate the ground truth values, thus preventing matrix singularity at the source and avoiding parameter estimation divergence. Third, to tackle challenges such as unstable lighting conditions and discrepancies between the dataset and the mathematical model, we introduce the random sample consensus-driven Levenberg–Marquardt parameter optimization algorithm to enhance parameter estimation accuracy. Experiments with static and dynamic online measurement demonstrate that our method reduces pose measurement errors compared to existing methods. This research lays a solid foundation for developing visual measurement techniques for excavators and automated manipulator control based on visual measurements, also serving as a valuable reference for research on mechanical arms.

It Is Clean, But It Still Seems Dirty to Me: Implicit and Explicit Truth of Imagined Contamination as an Explanation of Ego-Dystonic Experience of Obsessions

Individuals suffering from obsessive-compulsive disorder often experience obsessions as ego-dystonic, knowing that a mental event does not reflect reality but acting as if it does. Imagination has been suggested as an important process involved in this mismatch about the actual truth value of obsessions. Imagining false events has been found to impact spontaneous truth evaluations (implicit truth value; ITV), even when people explicitly acknowledged the imagined event as false (explicit truth value; ETV; Shidlovski et al., 2014). The current study examined discrepancies between ITV and ETV along with effects of imagination and their relationship to obsessive-compulsive contamination symptoms. Sixty-two students, recruited across the range of contamination symptoms, participated in this study. First, a table, at which participants were seated, was cleaned in their presence. Next, in a double-categorization autobiographical implicit association test (aIAT), participants classified true or false autobiographical statements together with “clean” or “contaminated” statements regarding the table. Then, they imagined that the table was contaminated prior to the second aIAT administration. ETV was measured by classifying the statements explicitly as true or false. Imagination was associated with reduced ITV, this association did not depend on symptoms, contrary to our predictions. However, symptoms were associated with elevated ETV evaluations of the contaminated statements. Finally, ETV correlated with ITV only for low symptom participants. This correlation was no longer significant following the imagination induction. In conclusion, individuals with contamination symptoms may be more likely to overweigh their explicit evaluations in the presence of contradictory implicit evaluations, creating a discrepancy. This process may account for ego-dystonic experiences reported by OCD patients.

PENGAPLIKASIAN KARAKTER NABI IBRAHIM AS PADA ASPEK PERKEMBANGAN PENDIDIKAN USIA DINI

This research will examine the three characters of Prophet Ibrahim AS in the holy book Al-Qur'an (siddiq, rational, and brave), as the basis for educational values ​​at an early age, with the hope that in the future a generation will be created with honest characters. in all things, think positively and act positively, and are also able to convey truthful values ​​in order to improve the nation's character. This research uses a qualitative approach by conducting an in-depth study of the text of the holy book Al-Qur'an as the main source, which is closely related to the three characters of Prophet Ibrahim AS, shidiq, rational and brave in life. Apart from the holy book Al-Qur'an as the main reference, we also use the literature of tafsir books to make it easier to understand the character of Prophet Ibrahim AS contained in the holy book Al-Qur'an. The main aim of this research is to obtain actual and factual information about the three characters of Prophet Ibrahim AS, Shidiq, rational and brave, then use it as a reference as the main principle in developing educational values ​​at an early age. The temporary conclusion is that by applying the three characters of Prophet Ibrahim AS (Siddiq, Rational and Courageous), to the values ​​of early childhood education, generations will emerge who can understand the direction of life, who are able to take responsibility for every step of their life, by thinking long and being able to uphold truth and justice.

Media baru: tren berita provokatif ditinjau dari etika komunikasi

This study aims to analyse and explain the urgency of communication ethics in the new media era (new media). This study uses a descriptive qualitative method with a post -positivist approach, where researchers observe and identify the phenomenon of communication ethics in new media (new media) Instagram on the @lambe_turah account naturally. This research data was obtained from the Instagram account @lambe_turah as a source of primary data, as well as from a literature review as secondary data. This research data was analysed through data reduction process, data presentation, and drawing conclusions. The results of this study indicate, with technological developments that allow the spread of fast and broad news on social media platforms, the need to maintain integrity, honesty, and peace in communication becomes more urgent. Communication ethics plays a major role in guiding media actors to verify information carefully, avoid sensationalism, and reduce the risk of provocation to individuals or groups. In dealing with the complexity of new media, enforcement of integrity, honesty, and peace becomes a crucial foundation in ensuring public trust, promoting social harmony, and preventing unwanted conflict escalation. Although the dominance of sensational and provocative news in user interest, ethical principles remain relevant in ensuring that the message distributed is true, useful, and not detrimental. With an emphasis on the principles of communication ethics, we can use new media as a means to strengthen the values of truth, justice, and wisdom in society, as well as facilitate a deeper understanding of various groups.

Kebebasan Beragama dalam Literatur Tafsir bi Al-Ma'tsur

Beliefs (religion) are closely related to an individual's spiritual experience and cannot be imposed by anyone. The issue becomes different when the position of religion shifts from being private to entering the public sphere, making the choice of religion no longer an absolute fundamental right but subject to control, often leading to "threats" as religious conversion is considered a crime. Ultimately, practicing religion is no longer based on sincerity but rather coercion. In this study, the author limits the examination to the interpretation of bil ma'tsur written by three figures: Ibn Jarir al-Thabari, Abu al-Fida’ Ibn Kathir, and Jalaluddin al-Suyuti. The focus of the study is the tendency of bil ma'tsur interpretation in explaining verses about religious freedom related to theological categories in the religious tradition studied through literature review using content analysis techniques. The approach used is a comparative approach, aiming to portray the interpretations given by Thabari, Ibn Kathir, and al-Suyuti on verses about religious freedom. The research results show that there are four verses that share similarities in affirming the principle of religious freedom, emphasizing that every individual has the freedom to choose and believe in their religion. These four verses are Al-Baqarah verse 256, Yunus verse 99, Al-Kahfi verse 29, and Al-Kafirun verse 6. According to the views of al-Thabari, Ibn Kathir, and al-Suyuti, these verses convey an important message about respecting religious freedom and recognizing the right of every individual to choose their own beliefs, while emphasizing the values of truth and steadfastness in faith

A Real-Time Prediction Approach to Deep Soil Moisture Combining GNSS-R Data and a Water Movement Model in Unsaturated Soil

Deep soil moisture data have wide applications in fields such as engineering construction and agricultural production. Therefore, achieving the real-time monitoring of deep soil moisture is of significant importance. Current soil monitoring methods face challenges in conducting the large-scale, real-time monitoring of deep soil moisture. This paper innovatively proposes a real-time prediction approach to deep soil moisture combining GNSS-R data and a water movement model in unsaturated soil. This approach, built upon surface soil moisture data retrieved from GNSS-R signal inversion, integrates soil–water characteristics and soil moisture values at a depth of 1 m. By employing a deep soil moisture content prediction model, it provides predictions of soil moisture at depths from 0 to 1 m, thus realizing the large-scale, real-time dynamic monitoring of deep soil moisture. The proposed approach was validated in a study area in Goodwell, Texas County, Oklahoma, USA. Predicted values of soil moisture at a randomly selected location in the study area at depths of 0.1 m, 0.2 m, 0.5 m, and 1 m were compared with ground truth values for the period from 25 October to 19 November 2023. The results indicated that the relative error (δ) was controlled within the range of ±14%. The mean square error (MSE) ranged from 2.90 × 10−5 to 1.88 × 10−4, and the coefficient of determination (R2) ranged from 82.45% to 89.88%, indicating an overall high level of fitting between the predicted values and ground truth data. This validates the feasibility of the proposed approach, which has the potential to play a crucial role in agricultural production, geological disaster management, engineering construction, and heritage site preservation.

Count What You Want: Exemplar Identification and Few-Shot Counting of Human Actions in the Wild

This paper addresses the task of counting human actions of interest using sensor data from wearable devices. We propose a novel exemplar-based framework, allowing users to provide exemplars of the actions they want to count by vocalizing predefined sounds ``one'', ``two'', and ``three''. Our method first localizes temporal positions of these utterances from the audio sequence. These positions serve as the basis for identifying exemplars representing the action class of interest. A similarity map is then computed between the exemplars and the entire sensor data sequence, which is further fed into a density estimation module to generate a sequence of estimated density values. Summing these density values provides the final count. To develop and evaluate our approach, we introduce a diverse and realistic dataset consisting of real-world data from 37 subjects and 50 action categories, encompassing both sensor and audio data. The experiments on this dataset demonstrate the viability of the proposed method in counting instances of actions from new classes and subjects that were not part of the training data. On average, the discrepancy between the predicted count and the ground truth value is 7.47, significantly lower than the errors of the frequency-based and transformer-based methods. Our project, code and dataset can be found at https://github.com/cvlab-stonybrook/ExRAC.