Conversational Patterns Research Articles

The mechanism of adolescent environmental passion influencing parent pro-environmental behavior

As environmental education within schools is vigorously pursued, the phenomenon of adolescents influencing their parent pro-environmental behaviors (PEB) is becoming a matter of importance. In order to further understand this phenomenon, utilizing the perspective of reverse socialization, this study constructed a model of the mechanisms underlying adolescent environmental passion (EP) influencing parent PEB. The longitudinal study collected 824 valid paired data points from 154 families, and Multilevel Structural Equation Modeling (MSEM) was employed to verify the model. The results show that adolescent EP positively influences parent PEB, and that adolescent PEB and knowledge transfer play a mediating role. Furthermore, concerning the influence of adolescent EP on adolescent PEB and knowledge transfer, the family conversation pattern plays an amplifying role, while the family conformity pattern has a diminishing effect.

CHATBOT USING LARGE LANGUAGE MODEL

The concept of Natural Language Processing has seen a remarkable advancement in the recent years. This remarkable advancement was particularly with the development of Large Language Models (LLM). Large Language Models are used to develop a human like conversations. This LLM is a part of Natural Language Processing which focuses on enabling computers to understand, interpret, and generate human language. The existing system of chatbots does not generate human like responses. The proposed system of chatbots uses the power of Large Language Models to generate more human like responses, providing the conversation in a natural way. By genereating human like respones, it will be in a natural way for the user. To enhance user experience, the chatbot uses a dynamic learning mechanism, by which it continuously adapt to user preferences and evolving conversational patterns. This system uses feedbacks from the users to refine its responses everytime.Moreover, the chatbot is designed with a multi-turn conversational context awareness, allowing it to maintain coherence and relevance throughout extended dialogues.The effectiveness of the proposed chatbot is evaluated through user testing, comparing its performance against traditional rule-based chatbots and existing conversational agents. This report explains about the usage of Large Language Models in the design and implementation of conversational chatbots. The outcomes of this research contribute to the advancement of intelligent chatbot systems, demonstrating the potential of large language models to significantly enhance conversational AI applications.

The Informativeness Norm of Assertion

AbstractAlthough assertions are often characterised as essentially informative speech acts, there is a widespread disagreement concerning how the informativeness of assertions should be understood. This paper proposes the informativeness norm of assertion, which posits that assertions are speech acts that essentially deliver new information. As a result, if one asserts something that is already commonly known, one’s assertion is improper. The norm is motivated by appealing to unique conversational patterns associated with informative and uninformative uses of assertions, an analogy between assertions and inquiries, and a distinction between assertions and uninformative speech acts. By focusing on the normative approach to speech acts, the paper discusses how particular norms of assertion deal with the data supporting the norm of informativeness. To be informative, the speaker must consider the epistemic position of the audience. Since the majority of norms proposed in the literature are speaker-centred, they fail to explain the submitted data. Looking more broadly, focusing on the informativeness of assertions underscores the crucial role of the audience in construing adequate speech act accounts.

PEMBAGIAN SISA HASIL USAHA DALAM BENTUK BARANG MENURUT AKAD SYIRKAH ‘INÂN: STUDI PADA KOPERASI MANDIRI REUKIH DAYAH INDRAPURI, ACEH

Syirkah 'inan is a form of cooperation in capital, management and sharing of business results. Conceptually, this syirkah inan tends to be flexible so that it can be implemented in various partnership businesses including cooperatives, which are flexible in mandatory and voluntary savings as well as in the profit-sharing system, as implemented by the management of the Mandiri Gampong Reukih Dayah Cooperative, Indrapuri District, which is the object of this research. The problem that is the focus of the aim of this research is how to calculate the remaining business results in the form of consumer goods at the Mandiri Cooperative, Indrapuri District, the pattern of conversion of profit sharing value from SHU on consumer goods and a review of the syirkah 'inan contract regarding the distribution of the remaining business results in the form of consumer goods carried out by the management of the Mandiri Cooperative. This research uses a normative sociological approach with descriptive analytical research and data collection techniques through interviews and documentation. The results of the research are that the SHU calculations carried out by the Mandiri Cooperative are calculated every financial year, and the calculations are carried out by the Mandiri Cooperative management in a transparent and accountable manner. The distribution of SHU for members after being allocated the following year's capital and management operational costs is 60% and 40% into SHU which is converted by the Mandiri Cooperative in the form of goods based on the nominal value of the money received by members. Conversion in the form of goods is carried out to make it easier for members to obtain consumer goods more easily and cheaper because the cooperative management buys wholesale so it is cheaper than market prices. Based on a review of the syirkah inan concept, the SHU distribution system in the form of consumer goods is permissible because this pattern is the result of a mutual agreement made by fellow members, while the management only facilitates the members' wishes to make it easier to fulfill family needs in a more practical and cheaper manner. Agreement is the substance of this syirkah inan contract, because in fiqhiyyah the profits are shared based on the agreement.

Characteristics of paralinguistic communication indicating pre-resonance during co-creative design grasped by decision tree analysis

AbstractThe study aims to grasp the dynamic characteristics of paralinguistic communication during co-creation and has developed an analysis methodology by clustering the conversational patterns and determining the criteria more often observed in pre-resonance. The results suggest that pre-resonance is characterized by less silence, a rapid transition in exchanging ideas under one's initiative, and a conversation with equal amounts of utterances between both in a pair. This study reveals implications for better communication that lead to resonance, an essential phenomenon in collaborative design.

Active Chat Monitoring and Suspicious Chat Detection Over Internet

In today's digital landscape, the proliferation of online communication platforms has brought about unprecedented opportunities for interaction and collaboration. However, this vast virtual space also presents challenges in ensuring safety and security, particularly concerning the monitoring of chat activities and the detection of suspicious behaviour. This research paper investigates the methods and technologies employed proactive chat monitoring and random chat across the web. The paper begins by examining the importance of monitoring chat platforms to prevent various forms of malicious activities, including cyberbullying, fraud, terrorism, and other illicit behaviours. It then delves into the techniques utilized for real-time monitoring of chat conversations, such as keyword filtering, sentiment analysis, and natural language processing algorithms. Furthermore, the paper explores the principles behind suspicious chat detection, highlighting the indicators of potentially harmful or illegal activities within chat communications. This includes analysing patterns of conversation, identifying anomalous behaviour, and integrating machine learning models to improve detection accuracy. Moreover, the research discusses the ethical considerations and privacy concerns associated with active chat monitoring, emphasizing the need for transparent policies and safeguards to protect user privacy while ensuring effective security measures. Keywords: Active chat monitoring, Suspicious chat detection, Online communication platforms, Cybersecurity, Malicious activities, Keyword filtering, Sentiment analysis, Natural language processing algorithms.

The Spillover effect of government relocations on economic growth in Chinese cities

This paper investigates the spillover effect of government locations on economic growth by exploring more than 180 relocation events of city governments in China. Empirical results demonstrate that government relocations improve regional economic growth measured by night lights. This positive effect decreases with the distance to city governments’ new locations. Government relocations are also found to accelerate urbanization. Potential mechanisms include the changes in land conversion and firm birth patterns in the move-in areas. These results indicate that the relocation of local governments can be an effective place-based policy to improve economic growth and urbanization.

Semantic SVM: Text and Media Analyzer

Chat analyzers are invaluable tools for understanding communication habits and patterns in digital conversations. This research paper presents a comprehensive overview of a chat analyzer’s capabilities, emphasizing its ability to provide insights into total message count, word usage, emoji frequency, and shared links. Furthermore, it explores the analyzer’s capacity to present data in various formats such as monthly timelines, identifying the most active days and months. Additionally, it examines weekly activity trends, shedding light on users’ engagement levels over time. The paper underscores the significance of such tools in enabling users to track their chat history effectively, offering valuable insights into their communication behaviors.

Semantic SVM: Text and Media Analyzer

Chat analyzers are invaluable tools for understanding communication habits and patterns in digital conversations. This research paper presents a comprehensive overview of a chat analyzer’s capabilities, emphasizing its ability to provide insights into total message count, word usage, emoji frequency, and shared links. Furthermore, it explores the analyzer’s capacity to present data in various formats such as monthly timelines, identifying the most active days and months. Additionally, it examines weekly activity trends, shedding light on users’ engagement levels over time. The paper underscores the significance of such tools in enabling users to track their chat history effectively, offering valuable insights into their communication behaviors.

Analysis of Conversational Implicature Found in the Silence of the Lambs Movie

This research employs a descriptive qualitative approach to examine Conversational Implicatures found in "The Silence of the Lambs" Movie using Grice's Cooperative Principle theory (1975). The objective of the study is to identify the prevalent type of Conversational Implicature and characterize its pattern of usage. The results indicate that Generalized Conversational Implicature (GCI) accounts for 42.2% of the total implicatures, while Particularized Conversational Implicature (PCI) represents 57.8%. Notably, Particularized Conversational Implicature emerges as the dominant type. The patterns identified within Generalized Conversational Implicature (GCI) are (1) conveying additional messages without needing to explain in detail or explicitly,(2) responses that do not require additional explanation, and (3) brief and succinct responses. However, Particularized Conversational Implicature patterns generated are (1) based on the specific context of the situation, (2) based on specific knowledge of the case and the context of the conversation, (3) use of cryptic language and allusions, (4) manipulation of hearing sympathy or understanding by sharing personal desires,(5) the psychological dynamics between the characters,(6) use of indirect questions.

Behind the Scenes: A Qualitative Investigation of Interviewers' Performance in EQ-5D Valuation Studies.

The EuroQol Valuation Technology (EQ-VT) protocol is currently employed by the valuation studies of the EQ family of instruments worldwide. To date, all the evidence in support of the quality control (QC) originates from quantitative indicators. We aimed to explore interviewers' conversational patterns in EQ-VT interviews, beyond quantitative QC indicators, and toprovide a preliminary exploration of how the interaction between interviewer and respondent impacts data quality. Two researchers transcribed and independently coded 24 video-recorded interviews from the Italian EQ-5D-5L valuation study, adopting the conversational analysis framework. The analysis identified positive and negative 'patterns' of conversational practice. These were categorized into themes and sub-themes and were used to score a random sample of 42 video-recorded interviews conducted at different time points by seven interviewers. The conversational analysis identified 20 positive and 14 negative interview patterns, which were grouped into two main themes (i.e., task execution and communication skills). Positive items included appending questions that stimulated respondents' engagement, providing different explanations for an unclear aspect, supporting the participant with useful information for completing the tasks, and increasing the interview's coherence by confirming the respondent answers. Negative patterns included moving forward in the exercise without making sure that the respondent understood, trying to force an answer from the respondent, speaking too fast, and providing incomplete or incorrect explanations of the task. Most interviewers exhibited a moderate increase in positive patterns or a decrease in negative patterns over time. A certain degree of consistency between the quantitative QC results and the qualitative scoring deriving from the interviewer-respondent interaction was observed, with the best and worst performers of the qualitative scoring showing good and bad scores on key QC items, respectively. The identified positive and negative patterns may be useful to inform the training material of EQ-VT studies worldwide and complement the existing QC process.

Landscape of brain myeloid cell transcriptome along the spatiotemporal progression of Alzheimer’s disease reveals distinct sequential responses to Aβ and tau

Human microglia are critically involved in Alzheimer’s disease (AD) progression, as shown by genetic and molecular studies. However, their role in tau pathology progression in human brain has not been well described. Here, we characterized 32 human donors along progression of AD pathology, both in time—from early to late pathology—and in space—from entorhinal cortex (EC), inferior temporal gyrus (ITG), prefrontal cortex (PFC) to visual cortex (V2 and V1)—with biochemistry, immunohistochemistry, and single nuclei-RNA-sequencing, profiling a total of 337,512 brain myeloid cells, including microglia. While the majority of microglia are similar across brain regions, we identified a specific subset unique to EC which may contribute to the early tau pathology present in this region. We calculated conversion of microglia subtypes to diseased states and compared conversion patterns to those from AD animal models. Targeting genes implicated in this conversion, or their upstream/downstream pathways, could halt gene programs initiated by early tau progression. We used expression patterns of early tau progression to identify genes whose expression is reversed along spreading of spatial tau pathology (EC > ITG > PFC > V2 > V1) and identified their potential involvement in microglia subtype conversion to a diseased state. This study provides a data resource that builds on our knowledge of myeloid cell contribution to AD by defining the heterogeneity of microglia and brain macrophages during both temporal and regional pathology aspects of AD progression at an unprecedented resolution.

메타분석에 의한 AI 챗봇 기반 영어교육 프로그램의 교육효과 비교

This study endeavors to assess the impact of AI chatbot-based English education programs on the effectiveness of language education for EFL learners. Additionally, it aims to examine moderator variables that influence the efficacy of these programs. A total of seventy-nine dissertations and academic journals, spanning from 2002 to October 2023, were chosen as the subjects for analysis. The effect size was computed utilizing a random effects model. A meta-regression analysis was conducted to validate moderation effects, and Egger's regression test was employed to assess publication bias. The impact of AI education programs was statistically significant, demonstrating a moderate effect size (0.44; 95% Confidence intervals: 0.34-0.54). The results of comparing educational effects in cognitive and non-cognitive domains revealed a higher effect size in the cognitive domain. The effect sizes based on educational outcomes ranked highest to lowest as follows: achievement, motivation, interest, confidence, attitude, and immersion. This study provides valuable insights into areas that need improvement to enhance the educational effects of utilizing AI chatbots. In future designs of English education programs utilizing AI chatbots, enhancing the pronunciation recognition component to ameliorate negative attitudes towards AI and diversifying conversation patterns to elevate learner immersion are anticipated to improve overall educational effectiveness.

Efficacy of initiators on fuel conversion, heat sink, and coke propensity of hydrocarbon fuel under supercritical environment

The investigation includes the cracking characteristics of a multi-component hydrocarbon fuel with a boiling range of 149–224 °C under supercritical environments. The impact of reactor pressure and the influence of initiators on cracking characteristics, such as fuel conversion, coke deposition, gas and liquid product distribution pattern, and heat sink capacities, of the fuel are examined explicitly. The fuel conversion improved by 70.8% as the reactor pressure increased from 2.5 MPa to 5.5 MPa at 650 °C. However, the coke deposition also increased by 55% for the corresponding pressure range. A decrease in the olefin-to-alkane ratio with pressure signifies the possibility of a reduction in unimolecular decomposition reactions and an increase in bimolecular reactions. The efficacy of two initiators, namely triethylamine (TEA) and di-tert-butyl peroxide (DTBP), on heat sinks and coke deposition was also examined. Between the two initiators, the nitrogen-based TEA initiator showed better performance in terms of fuel conversion and coke deposition rate, and the oxygen-based DTBP offered better heat sink capacity. About 22% increment in endothermicity was obtained with 1 wt% DTBP loading at 650 °C under 5.5 MPa pressure.

Dual perspective denoising model for session-based recommendation

Session-based recommendation predicts the next interaction option for an anonymous user based on his/her short-term behavior records. A key challenge faced by session-based recommendation is the processing of noise information. That is, the precise identification of noise items and noise connections. Existing research typically follows two assumptions: (1) the latest interaction item is directly treated as the user’s real-time preference; (2) the temporal order relationship between items is directly treated as the user’s true interaction intention conversion pattern. These strict assumptions ignore two facts: (1) the items that the user accidentally clicked on also exist in the interaction session. (2) the connection edges caused by noise items or user interaction intention drift are also fused into the explicit sequential structure. To address the above two issues, we propose a new Dual Perspective Denoising Model for session-based recommendation called DPDM. Specifically, DPDM mainly consists of two parts: Noise Item Recognition Network and Noise Structure Reconstruction Network. The Noise Item Recognition Network removes noise items from the session through a sparse attention mechanism and virtual target representation. The Noise Structure Reconstruction Network composed of Sequence Module and Co-occurrence Module is used to mine users’ real interaction intention conversion patterns. The Sequence Module captures sequence relationships after removing noise items. The Co-occurrence Module eliminates noise connections by optimizing explicit interaction sequences with L0 activation regularization. Extensive experiments were conducted on three representative real-world datasets, and DPDM achieved positive results, demonstrating the effectiveness of the components in the model.

Catalytic pyrolysis of FeAlOx and medical plastic waste: Kinetic, slag conversion, and gas emission patterns

The globally substantial increase in medical waste stream and types renders efficient disposal and circularity strategies imperative. Currently, most medical waste disposed of is predominantly plastic materials. A promising approach for its recycling efficiency involves using catalytic pyrolysis to transform plastic waste into reusable pyrolysis oil. This study aimed to characterize gas products and bottom slag of the catalytic pyrolysis of medical waste infusion tubes (PVC) via thermogravimetric (TG) and pyrolysis-gas chromatography-mass spectrometry (Py-GC/MS) analyses. As s bimetallic catalyst known for its exceptional ability as a carbon carrier that can turn carbon into CO at high pyrolysis temperatures, FeAlOx was synthesized and characterized. The addition of 50% (wt) FeAlOx yielded the lowest activation energy (Eα = 108.11 kJ/mol). The catalyst facilitated the breaking of the C-Cl bond in PVC, increasing HCl and light hydrocarbon gases, such as CH4. Prolonged pyrolysis residence times reduced chlorine remnants in the bottom slag, increased its alumina content, and achieved a stable slag composition. The reaction model with varying catalyst additions was dynamically evolved as follows: F1.6→F2→F2.2→F1.5 in the first stage and F2.3→F2.8→F4.8→F2 in the second stage, thus achieving an optimal kinetic and thermodynamic ratio of 5:5. The addition of the catalyst reduced not only the energy consumption and complexity of the two pyrolysis stages of PVC but also the production of pollutants, thus improving the circularity. This study provides actionable insights into the potential of the catalyst-assisted pyrolysis as an effective method for the circular management of medical waste.

Persistent interaction patterns across social media platforms and over time

Growing concern surrounds the impact of social media platforms on public discourse1–4 and their influence on social dynamics5–9, especially in the context of toxicity10–12. Here, to better understand these phenomena, we use a comparative approach to isolate human behavioural patterns across multiple social media platforms. In particular, we analyse conversations in different online communities, focusing on identifying consistent patterns of toxic content. Drawing from an extensive dataset that spans eight platforms over 34 years—from Usenet to contemporary social media—our findings show consistent conversation patterns and user behaviour, irrespective of the platform, topic or time. Notably, although long conversations consistently exhibit higher toxicity, toxic language does not invariably discourage people from participating in a conversation, and toxicity does not necessarily escalate as discussions evolve. Our analysis suggests that debates and contrasting sentiments among users significantly contribute to more intense and hostile discussions. Moreover, the persistence of these patterns across three decades, despite changes in platforms and societal norms, underscores the pivotal role of human behaviour in shaping online discourse.

Harnessing Attention-Based Graph Recurrent Neural Networks for Enhanced Conversational Flow Prediction via Conversational Graph Construction

Conversational flow refers to the progression of a conversation, encompassing the arrangement of topics discussed and how responses are delivered. A smooth flow involves participants taking turns to speak and respond naturally and intuitively. Conversely, a more disjointed flow may entail prolonged pauses or difficulties establishing common ground. Numerous factors influence conversation flow, including the personalities of those involved, their familiarity with each other, and the contextual setting. A conversational graph pattern outlines how a conversation typically unfolds or the underlying structure it adheres to. It involves combining different sentence types, the sequential order of topics discussed, and the roles played by different individuals. Predicting subsequent sentences relies on predefined patterns, the context derived from prior conversation flow in the data, and the trained system. The accuracy of sentence predictions varies based on the probability of identifying sentences that fit the subsequent pattern. We employ the Graph Recurrent Neural Network with Attention (GRNNA) model to generate conversational graphs and perform next-sentence prediction. This model constructs a conversational graph using an adjacency matrix, node features (sentences), and edge features (semantic similarity between the sentences). The proposed approach leverages attention mechanisms, recurrent updates, and information aggregation from neighbouring nodes to predict the next node (sentence). The model achieves enhanced predictive capabilities by updating node representations through multiple iterations of message passing and recurrent updates. Experimental results using the conversation dataset demonstrate that the GRNNA model surpasses the Graph Neural Network (GNN) model in next-sentence prediction, achieving an impressive accuracy of 98.89%.

A Discourse Analysis on Workplace with Hymes 'Speaking Model' Between Owner and Staff In Puri Itoma Corporate kuta Lombok: A study on Ethnography of communication

Ethnography in general is communication in society. Ethnography of communication combines ethnography, description and structural and functional analysis of society and culture, and linguistics of cultural behavior that guides and helps share knowledge, art, morals, beliefs, and everything that people acquire as members of society. Communication Ethnography is an approach to understanding society and culture and reconstructing this ethnic group, especially society in general. Discourse is also very often used in communication in society, at work, offices, schools and public places, both formally and informally. Discourse in English is called discourse and is defined as expression in communicative interaction. Speech events are based on eight speech components. Hymes summarizes these components with the acronym SPEAKING. Ethnography of communication in this discussion refers to the use of language in certain community groups. A smile means, for example, eight components of speech: (1) Setting and scene, (2) Participants, (3) Ending, (4) Sequential action, (5) Key, (6) Instrument, (7) Interaction norms, and (8) Flow. This study shows that the main focus of workplace research is a professional workplace and the ability to express oneself calmly at work. However, as stated in this review article, there are several interesting studies regarding the topic of communication in workplace briefings, for example using relaxed language but still targeting different jobs and power or positions, different nationalities, even different cultures. but still respectful. with each other between the owner and sales marketing staff, as in the discussion above. Another potential growth area is the study of multilingual conversation patterns in the workplace and communication norms at press conferences. Recent research in this area explores the importance of ideology and effectiveness in multilingual communication in the workplace. The research clearly shows the importance of communication ethnography, namely the dense interaction of participants. High network density is essential. This research describes communication competence. each participant is considered to have expressed his opinion. All statements from the meeting created strong communication between the three members. At the same time, it can be assumed that the participants are owners and sellers who have long established close relations, even quite proper, relaxed, clear and concise cooperation. So, their level of cognition deserves thumbs up. Another important thing is to create clear communication in the office space. Another achievement is that Participant 2 is a sales marketer from Germany who is able to adapt to the work environment and belongs to a lower caste. But it shows the same thing as the relevant statement. However, external participants, despite coming from upper caste strata, gave conflicting statements. Even though people from different castes always try to fulfill their demands or desires in conversation.

Cropland Conversion and Its Effect on Rice Production in Lampung Province, Indonesia

Lampung Province is one of the national rice producers in Indonesia. This study aimed to determine the patterns of cropland conversion, specifically rice fields, and available rice fields from 2013-2018 and to analyze the effects of two independent variables (rice field area and rice field conversion rate) on the dependent variable, i.e., total rice production. The conversion rate was calculated from 2013 to 2018, then categorized into three classes, and spatially mapped with rice field area and availability. Multiple regression tests were conducted to determine the relationship between the two independent variables. Results show that while rice fields were concentrated in Lampung Selatan, Lampung Tengah, and Lampung Timur, their conversion to non-agricultural lands was found throughout the province. Rice field areas increased in the north and east but shrunk in the south, west, and center. The statistical analysis revealed that rice field area, conservation rate, and their combination do not affect the amount of rice production in most regencies/cities in the province.