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The feeding unit is an important functional part in the paper industry that requires the development of effective maintenance plan based on its reliability analysis. This study analyzes reliability of the considered unit employing trapezoidal fuzzy numbers in fuzzy λ – τ methodology with Petri net modeling. In this analysis, the collected crisp input data of each subsystem has been fuzzified using trapezoidal fuzzy numbers. Then fuzzy values of several reliability factors of feeding unit, namely, failure rate, repair time, reliability, availability, etc. at ±15%, ±25% and ±40% spread levels have been calculated. Further, the obtained fuzzy values of reliability factors have been defuzzified to analyze system behavior of feeding unit. The analysis is useful for plant maintenance and operation management to understand the behavior of feeding unit in a more realistic manner. [ABSTRACT FROM AUTHOR]

Behaviour analysis has been subject to considerable criticism in recent years. This paper sets out to discuss key values, concepts and perspectives in the field that are essential for current behaviour analytic practice, while highlighting and acknowledging necessary improvements for practice and training. These include the importance of behaviour analysts (BAs) focusing on social validity outcomes; the value of consumer opinions, alongside collaborative and relationship-based practice; the importance of proactive, function-based interventions that take into account learning histories; and the use of system-wide, quality of life interventions, including capable environments. This paper highlights areas where behaviour analysis needs further focus to ensure adherence to the underpinning values of the science and to continue to evolve as a science of behaviour grounded in clear and modern humanist values. This paper additionally reflects on the later development of behaviour analysis in the UK and Ireland and the influence of positive behavioural support (PBS) in graduate teaching and service application to develop values-based practice. [ABSTRACT FROM AUTHOR]

[Display omitted] • The physical and chemical properties of PS and PC were studied systematically. • The reactivity of PC combustion reaction was significantly affected by PS. • PC:PS = 4:1 has the lowest combustion activation energy. • The Kissinger Akahira Sunose model shows a good fitting effect. The co-combustion reactivity and kinetics of petroleum coke (PC) and paper sludge-derived hydrochar (PS) were investigated via thermogravimetric analysis. The physical and chemical structure features were also systematically tested. The results show that the combustion process of PS could be divided into three stages, while for PC only one stage could be clarified. Due to high volatile content, developed pore structure and low carbon-order degree, the combustion reactivity of PS was higher than that of PC. Although the ignition property of the blends could be significantly improved by addition of PS, it changed little for the burnout temperature and as a result the combustion intensity was deteriorated. For the samples with addition of PS from 20 % to 80 %, the comprehensive combustion index decreased from 3.69 × 10-15 to 2.12 × 10-15. The Kissinger AkahiraSunose model-free method was used in the co-combustion reaction of PC and PS, and good fitting results were obtained. For different samples with varying addition of PS, the activation energies were in the range of 107.51–198.44 kJ/mol, with the lowest value obtained at 20 % of PS, which was also the optimum proportion for co-combustion of PC and PS. [ABSTRACT FROM AUTHOR]

The rise of online transactions has led to a corresponding increase in online criminal activities. Account takeover attacks, in particular, are challenging to detect, and novel approaches utilize machine learning to identify compromised accounts. This paper aims to conduct a literature review on account takeover detection and user behavior analysis within the cybersecurity domain. By exploring these areas, the goal is to combat account takeovers and other fraudulent attempts effectively. [ABSTRACT FROM AUTHOR]

The purpose of this study is to present an exhaustive analysis on research paper recommender systems which have become very popular and gained a lot of research attention. Though the major focus is on developing new recommendation algorithms, other research dimensions are left untouched. Renown recommendation classes include content-based approaches, collaborative filtering, link-based algorithms, co-occurrence based approaches, global relevance and hybrid methods. These approaches mainly differ in background knowledge and modes of user behavior analysis. For instance, content-based filtering uses paper descriptions which are mostly word-based features. Collaborative filtering makes predictions based on peers' interests. Link-based algorithms utilize academic associations that exist between different entities in academia. Co-occurrence based techniques incorporate event occurrences to locate related papers. Global relevance adopts a 'one-for-all' policy for recommending popular articles. Hybrid methods combine the above approaches to design efficient algorithms. We have reviewed articles implementing several versions of these classes, however minor customizations make it difficult to categorize the new methods to one of the base classes. We have defined the concept of 'background knowledge and operating principle' for proper classification and to make a clear distinction among the recommendation approaches. We have used a combination of systematic literature review, critical review, and conceptual review to conduct this survey which presents current advancements in the field and discusses popular recommendation approaches. This paper reveals the factors affecting users' behavior and introduces a taxonomy of knowledge acquisition sources. Moreover, various evaluation methods and important performance criteria are explored. Finally, this paper examines the research trends and reports major loopholes in current research to foster the development of efficacious recommender systems. [ABSTRACT FROM AUTHOR]

An introduction is presented in which the editors discuss the contents of the spring 2024 edition of the International Journal of Positive Behavioural Support, featuring research papers, practice papers, a discussion paper critiquing the evolution of values in applied behavior analysis.

In behavior analysis, research on stimulus equivalence has been an area of high activity for more than 45 years. Murray Sidman's contribution was crucial in the development of this field, and, thus, it seems informative to highlight the experiments that were necessary in the development of the descriptive model of equivalence relations and behavior. The purpose of this paper is to provide an overview of the significant work that gave the historical context for Sidman and colleagues' conceptualization of stimulus equivalence as it was presented in 1982. This article emphasizes the 31 papers and chapters written by Sidman and colleagues that focus on research questions within stimulus control. The chapters and papers are organized according to their dimensions in behavior analysis and according to whether they can be categorized as instruction programs or experimental studies. The issues discussed regarding these papers and chapters include types of stimuli, matching, discriminations, and others. Collectively, this early work influenced methods and considerations about stimulus control issues that have been important to the development of stimulus equivalence. [ABSTRACT FROM AUTHOR]

Reproduction in cooperative animal groups is often dominated by one or a few individuals, with the remaining group members relegated to nonreproductive helping roles. This reproductive skew can evolve if helpers receive fitness benefits such as potential future inheritance of the breeding position, but the mechanisms by which inheritance is determined are not well resolved. Polistes paper wasps form highly reproductively skewed groups and inheritance of the breeding position is likely to play a key role in the maintenance of this social structure, making them excellent models for the processes by which simple societies are maintained. Reproductive succession is thought to be determined via an age-based convention in some Polistes species, but there is also evidence for contest-based succession systems in which the replacement queen uses physical aggression to overpower and thereby subordinate her nestmates. Here, we provide evidence that queen succession in colonies of the European paper wasp Polistes dominula is determined via convention rather than contest, with little disruption to the colony's social functioning. We use queen removal experiments and fine-scale behavioral analyses to confirm that age is a strong predictor of succession, and that behavioral responses to queen removal are restricted to the oldest individuals rather than being experienced equally across the group. We provide the most comprehensive and detailed experimental analysis on the dynamics of breeder succession in a cooperatively breeding invertebrate to date, thereby shedding light on the mechanisms by which animal societies are able to maintain cohesion in the face of within-group conflict. [ABSTRACT FROM AUTHOR]

The complexity of school management tasks requires specific training. Studies on leadership agree that such training should be based on reflective practice favored by coaching. This article presents the analysis of the behaviors and intervention strategies of coaches and their relation with reflective learning processes undertaken in discussion groups for the training of principals within the framework of a specific program. The results indicate that coaching requires rigorous training in relation to both leadership and social skills and abilities through which a relationship of trust can be built. Group synergies that encourage reflection on one's own leadership require syntheses and extensions to establish relationships between the facts and avoid valuations and advice, while promoting active listening, the capacity to manage time and formulate questions, and challenge but not disqualify comments that are key to the improvement and quality of the training process. Given the multiple demands for coaches' work to be effective, we observe the need for appropriate and rigorous training in expert knowledge through social skills and abilities that promote a relationship of trust with the participants. [ABSTRACT FROM AUTHOR]

Background: PBS is a proactive, person-centred approach for working with people who have behaviours that are challenging to support. Staff confidence can influence PBS delivery. This paper examined the effects of bespoke PBS training on staff confidence in working with behaviours that are challenging to support in inpatient settings and with individuals across the lifespan. Method and materials: Across 8, 2-day PBS training sessions, 115 staff completed pre and post measures of confidence and provided feedback. Non-parametric tests were used to compare pre and post means and feedback was analysed using descriptive statistics and qualitative content analysis. Results: All measures of confidence improved significantly from pre to post training. PBS training appeared highly acceptable and eight qualitative themes emerged. Conclusions: Bespoke PBS training can significantly improve the confidence of inpatient staff working with people who have behaviours that are challenging to support. Further evaluation is now needed to examine whether these changes translate to practice. [ABSTRACT FROM AUTHOR]

Tail suspension test (TST) and forced swimming test (FST) are widely used in basic research and pharmaceutical screening of potential antidepressant treatments in rodents. In both tests, the measurement of immobility behavior is the main parameter to assess the rats' depressive-like behavior. [Extracted from the article]

The current study explores and dissects the philosophical roots of neo-classical realism. The analysis aims to disclose the theoretical underpinnings of this framework that enable it to describe the state’s behavior. The analysis is based upon a comparative approach that helps to understand the complex synthesis scheme of the neo-classical realist framework. The neo-classical realism is based upon an extensive array of internal and external sets of variables that help to explain foreign policy actions. The bedrock of foreign policy behavior of a state is intricately woven from these interplaying variables. As a matter of fact, the neoclassical realist perspective on security and the distribution of power lays the foundation for the analysis of foreign policy behavior of states. The discussion reveals that the major portions of its attributes are constructed through neo-realist routes synthesizing the domestic intervening variables. Though the framework has the capacity to incorporate complexities of foreign policy and decision-making, however, it cannot be considered an independent theory for foreign policy studies. [ABSTRACT FROM AUTHOR]

The article offers information about the significance of physical aggression in autistic youths and the concerns surrounding their quality of life. It emphasizes the importance of conducting a comprehensive behavioral assessment to understand the individual's life context, health, antecedent conditions, and functions of challenging behavior.

Expansive soils often pose as a potential geo-hazard for structures built on them due to the volumetric changes associated with moisture variation. Soil water characteristic curve (SWCC) is a direct representation of the pore and grain distribution of clays while the variation of in situ soil matric suction governs the hydration processes. In the present research, five natural expansive clays were studied at their 95% of maximum dry unit weight. Swell behavioral evaluations are conducted using standard test procedures. Both desorption and adsorption SWCC's were determined using pressure cell apparatus and filter paper method. Adsorption paths are utilized for analysis study as swelling behavior is the main scope of the research. A novel path traversed by the soil specimen on the void ratio-moisture content-log (soil suction) plot, and the corresponding slope, namely the modified specific moisture capacity, 'α', is identified as the main influential parameter. This modified specific moisture capacity exhibited direct relationship to swelling strains and swelling pressure of all five natural clays. A simple model for predicting one dimensional swell strain and swell pressure was established based on reliable predictions obtained using the modified specific moisture capacity of clays. [ABSTRACT FROM AUTHOR]

Virtual reality (VR) driving simulators are very promising tools for driver assessment since they provide a controlled and adaptable setting for behavior analysis. At the same time, wearable sensor technology provides a well-suited and valuable approach to evaluating the behavior of drivers and their physiological or psychological state. This review paper investigates the potential of wearable sensors in VR driving simulators. Methods: A literature search was performed on four databases (Scopus, Web of Science, Science Direct, and IEEE Xplore) using appropriate search terms to retrieve scientific articles from a period of eleven years, from 2013 to 2023. Results: After removing duplicates and irrelevant papers, 44 studies were selected for analysis. Some important aspects were extracted and presented: the number of publications per year, countries of publication, the source of publications, study aims, characteristics of the participants, and types of wearable sensors. Moreover, an analysis and discussion of different aspects are provided. To improve car simulators that use virtual reality technologies and boost the effectiveness of particular driver training programs, data from the studies included in this systematic review and those scheduled for the upcoming years may be of interest. [ABSTRACT FROM AUTHOR]

The main topics of the presented papers focus on various aspects of maritime operations and security, including anomaly detection in maritime traffic, collision risk assessment, and the use of Automatic Identification System (AIS) data for enhancing maritime safety and surveillance. These papers cover a wide range of subjects within the maritime domain, such as trajectory clustering, kinematic behaviour analysis, Bayesian networks for risk assessment, resilience analysis of shipping networks, and the development of novel methods for detecting abnormal maritime behaviour. The emphasis is on using data-driven approaches, statistical methodologies, and advanced technologies to improve maritime operations and security. [ABSTRACT FROM AUTHOR]

The importance of simulating patient behavior for medical assessment training has grown in recent decades due to the increasing variety of simulation tools, including standardized/simulated patients, humanoid and android robotpatients. Yet, there is still a need for improvement of current android robotpatients to accurately simulate patient behavior, among which taking into account their hearing loss is of particular importance. This paper is the first to consider hearing loss simulation in an android robot-patient and its results provide valuable insights for future developments. For this purpose, an opensource dataset of audio data and audiograms from human listeners was used to simulate the effect of hearing loss on an automatic speech recognition (ASR) system. The performance of the system was evaluated in terms of both word error rate (WER) and word information preserved (WIP). Comparing different ASR models commonly used in robotics, it appears that the model size alone is insufficient to predict ASR performance in presence of simulated hearing loss. However, though absolute values of WER and WIP do not predict the intelligibility for human listeners, they do highly correlate with it and thus could be used, for example, to compare the performance of hearing aid algorithms. [ABSTRACT FROM AUTHOR]

Purpose: Emotions and emotional contagion are being increasingly recognized as crucial variables influencing individual behavior and organizational functioning. This position paper serves the function as a ready reckoner by reviewing and consolidating existing literature in the field of emotional contagion. The review is categorized into three broad headings: (a) individual, (b) interpersonal, and (c) contextual factors, based on their relationship with emotional contagion. Design/Methodology/Approach: The article focuses on analyzing and critiquing studies of emotional contagion conducted in several streams such as psychological processes, personality, organizational behavior, marketing, and consumer behavior. A conceptual framework of emotional contagion is presented, supplemented with research propositions. Findings: The phenomenon of emotional contagion in workplace and its effects on personal and group outcomes has emerged as a critical area of research. It has been firmly established in literature that spread of emotions, if not properly managed, is bound to influence work effectiveness. Implications: Importance of understanding the effects of transfer of emotions, for both academicians and practicing managers is one of the critical take-aways of this article. Suitable interventions are the need of the hour in order to ensure proper management of emotions. Originality/Value: The contribution of the article is expected to be fourfold, in terms of: (a) presenting a structured and comprehensive review of literature on emotional contagion, (b) identifying gaps in the existing literature, (c) proposing a conceptual framework, and (d) developing propositions for future research. [ABSTRACT FROM AUTHOR]

Abstract: Background: Longitudinal mood instability is the essential feature of bipolar disorder, however most rating scales are cross sectional in nature, and focus on acute symptoms. By contrast, the NIMH Life Chart Methodology (LCM) characterizes in detail the severity, duration, and frequency of mood episodes. Adherence to daily rating, however, tends to be low. In this study an online version of the LCM, designed to enhance adherence, was compared to the standard paper version. Methods: Patients from a mood disorders specialty clinic were randomized to the standard LCM or an online, open-source adaptation. The online version used hypertext links embedded in a daily email as the primary rating interface. Participants rated for 90days. The total number of days rated and the number of days with complete data were compared for the two groups. Results: Forty-eight patients participated in the study. The online group rated approximately twice as many days compared to the standard group (44.3 versus 20.4, p =.029). The online group also entered complete data for a larger portion of days (55.2% versus 27.7%, p =.039). Limitations: This was a small, short-term study. The implications for longer-term rating are unclear. Conclusions: Despite the advantages of documenting mood fluctuation on a daily basis, the LCM is not commonly used, in part because ensuring adequate adherence can be resource intensive. An easily accessible online adaptation that utilizes email checking behavior can make this tool available to a wider range of patients. [Copyright &y& Elsevier]

This study investigates the auditor characteristics that are related to generation of evidence and documentation review notes by reviewers of audit working papers. To address this question, an analysis was conducted on the contents of review notes prepared in a laboratory experiment. The working papers contained no documentation deficiencies but contained insufficient evidence. As part of an effective review process, the auditor should generate review notes that call for additional evidence gathering. Generating documentation-oriented review notes created inefficiencies for carrying out the review process and corresponding audit task. Stepwise multiple regression analyses identified reviewer characteristics that were significantly associated with each type of review note. These results provide insights into the reviewer characteristics associated with focusing attention on one review-note classification instead of the other. This finding suggests opportunities for future research that more thoroughly explores and controls for the variables identified in this study. [ABSTRACT FROM AUTHOR]

Many theoretical methods have been applied to research user behaviour and requirements. However, the uncertainty associated with customer characteristics often biases the conclusions drawn from customer research and affects the effectiveness of product design. In this paper, Bayesian networks (BN) are introduced into the research on customer behaviour analysis based upon theory of planned behaviour (TPB), and an analysis model driven by customer research data is established from the perspective of user behaviour intention to guide design optimisation. Combining the User background Factor with the TPB Factor, the model analyses the uncertainty of the association between the two, and corrects the errors in the designer's prior knowledge through structural learning. By a case study the paper finds that the evaluations that enhance customers' subjective norms and perceived behavioural control lead to a greater probability of purchase or use. In addition, customers with specific characteristics are more inclined to generate behaviour intention. The paper finally provides a design optimisation plan based upon the result of the research and discusses about the advantages of the research approaches and the directions of future researches. [ABSTRACT FROM AUTHOR]

The article presents a critique of a previously published paper on behavioral and perception geography. The author disagrees with the negative assessment of the power of the image. He claims that the assertions made in the article are too sweeping, the treatment is unbalanced, and errors abound. The assumption that there is a strong relationship between environmental images and actual behavior is widely held. One should not assume that any general environmental image chosen to measure will be directly related to every highly specific environmental action.

Purpose: Proposing an integrated model based on multiple theoretical approaches, such as the theory of planned behavior, the model of goal-directed behavior and self-determination theory, the purpose of this paper is to examine factors influencing college students' campus recycling intention and actual recycling behavior. Design/methodology/approach: An online survey method was used to test the proposed model with college students. A total of 434 students participated in the survey. Findings: This study found that self-determined motivation, attitude toward recycling, perceived behavioral control and negative anticipated emotion had direct effects on campus recycling intention, while recycling intention and self-determined motivation influenced students' actual campus recycling behavior. Research limitations/implications: The findings of the study may not be generalizable to the broader population. Respondents' self-reported assessment of their recycling behaviors may also be a drawback of the study. However, the study provides statistical evidence testing the proposed model of campus recycling. Practical implications: The study's findings provide communication planners for university recycling and sustainability departments with communication and message strategies to enhance college students' recycling behavior. Originality/value: The study proposes a more comprehensive, tailored model that integrates other compelling theoretical models, to address college students' sustainability engagement on campus. [ABSTRACT FROM AUTHOR]

With the development of the Internet and the informatization construction of universities, the massive data accumulated by "campus big data" presents problems such as discreteness and sparseness. Students with abnormal behaviors have become an urgent problem to be solved in student behavior analysis. This paper proposes an early warning method for abnormal behaviour of college students based on multimodal fusion and an improved decision tree (EWMABCS-MFIDT). First, given the insufficient representation of student behavioral portraits and the problems of timeliness and dynamics in behavioral labels, a student behavioral portrait based on the multimodal fusion method is proposed. Second, aiming at the timeliness and backwardness of abnormal behavior prediction, based on student behavior classification prediction, this paper proposes an improved decision tree-based early warning method for abnormal student behavior. Finally, we design a student behavior analysis and early warning framework under the campus big data environment. Taking the abnormal early warning of students' academic performance as an example, compared with other early warning algorithms, the EWMABCS-MFIDT method can improve the accuracy of early warning and make students' educational work more targeted, personalized, and predictive. [ABSTRACT FROM AUTHOR]

Significant research has been carried out in the field of User Behavior Analysis, focused on understanding, modeling and predicting past, present and future behaviors of users. However, the heterogeneity of the approaches makes their comprehension very complicated. Thus, domain and Machine Learning experts have to work together to achieve their objectives. The main motivation for this work is to obtain an understanding of this field by providing a categorization of state-of-the-art works grouping them based on specific features. This paper presents a comprehensive survey of the existing literature in the areas of Cybersecurity, Networks, Safety and Health, and Service Delivery Improvement. The survey is organized based on four different topic-based features which categorize existing works: keywords, application domain, Machine Learning algorithm, and data type. This paper aims to thoroughly analyze the existing references, to promote the dissemination of state-of-the-art approaches discussing their strong and weak points, and to identify open challenges and prospective future research directions. In addition, 127 discussed papers have been scored and ranked according to relevance-based features: paper reputation, maximum author reputation, novelty, innovation and data quality. Both types of features, topic-based and relevance-based have been combined to build a similarity metric enabling a rich visualization of all considered publications. The obtained graphic representation provides a guide of recent advancements in User Behavior Analysis by topic, highlighting the most relevant ones. [ABSTRACT FROM AUTHOR]

The most stringent arable land protection system in China has not effectively prevented construction expansion from excessive occupation of arable land. In this paper, the evolutionary game theory is innovatively used to explore why arable land protection policies did not engender the desired outcomes from the perspective of multi-subject behavior. We first analyze the logic of arable land protection behavior of different participants, including the central government, local administrations and farmers. Then, a tripartite evolutionary game model is established to examine how behavioral interaction among subjects affects policy implementation. And parameter analysis is used to identify the influencing factors of subjects' behavior. Our results show that: First, the ideal strategy combination of (0,1,1) for China's arable land protection cannot be achieved, which indicates that local administrations and farmers will not spontaneously protect arable land in the absence of central government's supervision. Second, the policy effect in Shanghai has undergone a dynamic process from serious failure (2004–2013), mild failure (2013–2018) to effective control (after 2018). Local administrations and farmers are solely responsible for the deviation of policy implementation. Third, local administrations and farmers are more sensitive to the variations of arable land conversion income, political achievements and economic punishment. Thus, political and financial constraints should be imposed on them to promote the strict implementation of arable land protection policy. This paper enriches the existing study regarding arable land protection policy effect. And it is of great practical importance to regulate the subject's behavior and facilitate policy implementation. [ABSTRACT FROM AUTHOR]

With the widespread application of information technology in education, the real-time detection of student behavior in the classroom has become a key issue in improving teaching quality. This paper proposes a Student Behavior Detection (SBD) model that combines YOLOv5, the Contextual Attention (CA) mechanism and OpenPose, aiming to achieve efficient and accurate behavior recognition in complex classroom environments. By integrating YOLOv5 with the CA attention mechanism to enhance feature extraction capabilities, the model's recognition performance in complex backgrounds, such as those with occlusion, is significantly improved. In addition, the feature map generated by the improved YOLOv5 is used to replace VGG-19 in OpenPose, which effectively improves the accuracy of student posture recognition. The experimental results demonstrate that the proposed model achieves a maximum mAP of 82.1% in complex classroom environments, surpassing Faster R-CNN by 5.2 percentage points and YOLOv5 by 4.6 percentage points. Additionally, the F1 score and R value of this model exhibit clear advantages over the other two traditional methods. This model offers an effective solution for intelligent classroom behavior analysis and the optimization of educational management. [ABSTRACT FROM AUTHOR]

The aim of this paper is to provide dental professionals with insight into how the science of behaviour change can be used to support patients to change their oral health behaviours. The paper describes how the fourth version of Delivering Better Oral Health (DBOHv4) published in November 2021, brings together the theory plus key principles and practical tools in Chapter 3 "Behaviour change", to help front-line clinicians achieve the best effect. DBOH is freely available to all online at gov.uk and is a key resource for dental teams for the prevention of oral diseases. [ABSTRACT FROM AUTHOR]

At present, distributed systems have been widely used, and a lot of research has been done on the reliability of distributed systems. However, trusted 3.0 based distributed system node trust behavior recognition research is still relatively rare. This paper focuses on the identification process and evaluation method of distributed node trust behavior. In this paper, call links and resource consumption of software behavior are obtained by burying points during the development phase. Based on the idea of "sense of words and deeds", this paper compares the pre-acquired trust call links with the resource consumption sample data, in order to obtain a credible real-time software behavior model. This paper will focus on the analysis and extend to the distributed environment, and conduct a trusted analysis of software behavior, which provides a new idea for software trusted behavior analysis. [ABSTRACT FROM AUTHOR]

Student behavior research can improve learning efficiency, provide decision evidences for infrastructure management. Existing campus-scale behavioral analysis work have not taken into account the students characteristics and spatiotemporal pattern. Moreover, the visualization methods are weak in wholeness, intuitiveness and interactivity perspectives. In this paper, we design a geospatial dashboard-based student behavior analysis and visualization system considering students characteristics and spatiotemporal pattern. This system includes four components: user monitoring, data mining analysis, behavior prediction and spatiotemporal visualization. Furthermore, a deep learning model based on LSTNet to predict student behaviour. Our work takes WiFi log data of a university in Beijing as dataset. The results show that this system can identify student behavior patterns at a finer granularity by visualization method, which is helpful in improving learning and living efficiency. [ABSTRACT FROM AUTHOR]

The article discusses the 95th Transportation Research Board (TRB) Annual Meeting that was held in Washington D.C. on January 10-14, 2016, focusing on the model travel demand, initially with trip-based and tour-based models in the early 70s and 80s. Topics include the use of social media data to characterize the individual activities, the different individual behavioural attitudes in the formulation of activity-based models, and the dynamic network assignment and equilibrium models.

The I Journal of the Experimental Analysis of Behavior i announces a special issue on the topic of B Murray Sidman: A Retrospective Appreciation of a Distinguished Scientist b I Issue scheduled for publication i : January, 2021 I Submission deadline i : September 1, 2020 I Editors: Mark Galizio (UNC Wilmington), Iver Iversen (University of North Florida), Andy Lattal (West Virginia University), Karen Lionello-DeNolf (Assumption College), Bill McIlvane (University of Massachusetts Medical School) i Murray Sidman was a leading figure in the field of behavior analysis for almost seventy years, beginning with his creative, pioneering research on free-operant (later known as Sidman) avoidance and continuing with many ground-breaking research topics, such as stimulus equivalence, to his death in May of 2019. It therefore seemed fitting to reflect on and celebrate his professional life with a special issue of I JEAB i dedicated to his influence on all of behavior analysis: basic research, application, translational research, methodology, and conceptual issues. The goal of the issue is to reflect the wide impact of Sidman's work in behavior analysis. [Extracted from the article]

Comments on the adaptability research of A. J. W. Taylor from Antarctica to the South Pacific. Approach to analyzing and ameliorating post-traumatic stress; Usefulness of the behavioral assessments; Focus of the research on stressful environments.

Toppling accidents of heavy machinery such as pile drivers, cranes, high-altitude work vehicles, and jacks have been recurring in the world. In the past, researches focused to find the overturning moment that causes toppling. However, it is believed that the toppling accidents are related to structural stability issues, in which cases the accidents could possibly occur without any overturning moment. Accidents involving the structural instability are difficult to predict as the directions of load and deformation are different. This unpredictability is considered as a fundamental contributing factor to accidents recurring. Theoretical studies by static and dynamic analyses have been performed by the authors. It was found that not only static deformations but also dynamic inertial forces influence the increased risk of toppling. In the cases of structural instability, dynamic inertial force might amplify angular displacement beyond the critical stability angle, leading to rapid toppling and often resulting in significant disasters. Factors leading to toppling as a trigger include unexpected movement onto weak ground, increased magnitude of load and height, and greater ground incline. Taking those factors into consideration, this paper attempts to elucidate the mechanism of pile drivers' toppling by comparing static and dynamic analyses and providing essential information for preventing accidents. From both static and dynamic analyses, toppling behavior will be described in the load--deformation and the support stiffness--deformation relations. Furthermore, a role of temporal element is illustrated as a quick movement of the machines results in increased risk of toppling. [ABSTRACT FROM AUTHOR]

The emerging field of canine science has been slow in adopting automated approaches for data analysis. However, with the dramatic increase in the volume and complexity of the collected behavioral data, this is now beginning to change. This paper aims to systematize the field of automation in canine science. We provide an examination of current automation processes and pipelines by providing a literature review of state-of-the-art studies applying automation in this field. In addition, via an empirical study with researchers in animal behavior, we explore their perceptions and attitudes toward automated approaches for better understanding barriers for a wider adoption of automation. The insights derived from this research could facilitate more effective and widespread utilization of automation within canine science, addressing current challenges and enhancing the analysis of increasingly complex and voluminous behavioral data. This could potentially revolutionize the field, allowing for more objective and quantifiable assessments of dog behavior, which would ultimately contribute to our understanding of dog-human interactions and canine welfare. [ABSTRACT FROM AUTHOR]

One technique, especially in chaos-based cryptographic applications, is to include the message in the evolution of the dynamical system. This paper aims to find out if and to what extent the statistical behavior of the chaotic system is affected by the message inclusion in its dynamic evolution. The study is illustrated by the dynamical system described by the logistic map in cryptographic applications based on images. The evaluation of the statistical behavior was performed on an original scheme proposed. The Monte Carlo analysis of the applied Kolmogorov–Smirnov statistical test revealed that the dynamical system in the processing scheme with message inclusion does not modify its proper statistical behavior (revealed by definition relation). This was possible due to the proposed scheme designed. Namely, this scheme contains a decision switch which, supported by an appropriate choice of the magnitude of the scaling factor, ensures that the values of the dynamical system are maintained in the definition domain. The proposed framework for analyzing the statistical properties and for preserving the dynamical system behavior is one main contribution of this research. The message inclusion scheme also provides an enhancement with cryptographic mixing functions applied internally; the statistical behavior of the dynamical system is also analyzed in this case. Thus, the paper contributes to the theoretical complex characterization of the dynamical system considering also the message inclusion case. [ABSTRACT FROM AUTHOR]

The Repetitive Behaviours Questionnaire for Adults (RBQ-2A) measures two factors of restricted and repetitive behaviours (RRBs) associated with autism. However, the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) provides four criteria for RRBs: repetitive motor behaviours, insistence on sameness, restricted interests, and interest in sensory aspects of the environment (or atypical sensitivity). The current paper aimed to examine whether the RBQ-2A is a psychometrically sound measure of these four factors. Study 1 had university students (N = 368) complete the RBQ-2A and other related measures online and revealed that the RBQ-2A can assess the factors highlighted in the DSM-5 and that these four factors comprise a general RRB construct. Study 2 had individuals disclosing a diagnosis of autism (N = 283) complete the RBQ-2A and other related measures online and supported that this four-factor structure provided good psychometric properties. While the current paper provides findings for an online autistic population, further research is needed to generalize these findings to autistic individuals less likely to partake in online studies (e.g., those with intellectual or language disabilities). Overall, the results suggest that the RBQ-2A reliably and validly assesses RRBs. [ABSTRACT FROM AUTHOR]

In this paper, the compatibility, phase behavior, and crystallization properties of the binary blends of palm kernel stearin (PKS) and anhydrous milk fat (AMF) were investigated by analyzing the solid fat content (SFC), thermal properties, polymorphism, and microstructure, with the aim of providing theoretical guidance for the blending of oils. The results showed that the PKS content primarily determined the SFC trend of the binary blends. However, the binary blends demonstrated poor miscibility and eutectic behavior was predominantly observed in the system, particularly at higher temperatures. Only α and β′ forms appeared in this blended system. Simultaneously, the addition of PKS elevated the liquid phase transition temperature of the binary blends, considerably significantly increased their crystallization rate when the addition of PKS was more than 20% and increased the density and size of the fat crystals. Finally, the mixing design optimization method was used to get the most suitable ratio of the binary blends in the refrigerated cream system with PKS:AMF to be 0.914:0.086. The cream prepared with the above binary blends was indeed superior in overrun and firmness and had high stability. Practical Application: Some fats with special advantages are often limited in their wide application because of their poor crystallization ability. In this paper, the crystallization ability of fats is improved, and their application scenarios are increased through the combination of fats, so as to provide reference for the production of special fats for food. [ABSTRACT FROM AUTHOR]

With the increasing demand for road traffic safety assessment, global concerns about road safety have been rising. This is particularly evident with the widespread adoption of V2X (Vehicle-to-Everything) technology, where people are more intensively focused on how to leverage advanced technological means to effectively address challenges in traffic safety. Through the research of driving style recognition technology, accurate assessment of driving behavior and the provision of personalized safety prompts and warnings have become crucial for preventing traffic accidents. This paper proposes a risk field construction technique based on environmental data collected by in-vehicle sensors. This paper introduces a driving style recognition algorithm utilizing risk field visualization and mask learning technologies. The research results indicate that, compared to traditional classical models, the improved algorithm performs excellently in terms of accuracy, stability, and robustness, enhancing the accuracy of driving style recognition and enabling a more effective evaluation of road safety. [ABSTRACT FROM AUTHOR]

Construction and demolition waste (C&DW) recycling products have drawn worldwide attention over the past few decades. There is a general agreement among researchers that C&DW recycling is an important means for curbing the deterioration of the environment. Previous papers mainly focused on the decision-making behavior of dual stakeholders or tripartite stakeholders, as well as the lack of cooperation among multiple stakeholders. This study explored a dynamic evolutionary game model with three different parameter conditions to research the decision-making behaviors and stable strategies of the multi-stakeholders involved in the C&DW recycling product industry, including government departments and some enterprises. This research also investigated how the government's supervision costs, penalties applied to enterprises, and resource taxes affect the dynamic evolution process of C&DW recycling. This research conducted numerical simulations using Python to analyze stakeholders' behavioral evolutionarily stable strategy (ESS) and the sensitivity to main factors in each stage of the C&DW recycling process to accelerate the development of construction waste resource utilization. Based on the results of the evolutionary game, this paper proposed that the roles of multi-stakeholders are different at different stages of industry development, and that supervision costs, penalties, and resource tax have their own impacts on the C&DW recycling product industry. The paper suggests a range of discussions and simulation studies to highlight the significance of the government's refined and moderate adjustments to the regulatory incentive system and the level of government regulation and involvement at different stages of the process. These adjustments are aimed at promoting the sustainable recycling and utilization of construction and demolition waste (C&DW) products within some countries' construction industry. [ABSTRACT FROM AUTHOR]

Recent advancements in information technology and ship equipment have allowed for the collection of large amounts of data on maritime traffic through automatic identification systems (AIS). This data is crucial for risk assessment and navigation safety, as it provides insights into ship behavior. Researchers have used machine learning and deep learning techniques to analyze AIS data and improve maritime safety. This document summarizes several research papers on topics such as ship classification, anomaly detection, ship grounding frequency estimation, performance-shaping factors in oil tanker operations, resource allocation in search and rescue, container ship stowage planning, and route identification in ice-covered waters. These papers contribute to the understanding of maritime safety and efficiency and provide recommendations for future research. [Extracted from the article]

The primary objective of this paper is to investigate the performance of C-D (converging-diverging) nozzles with slanted perforated tabs through numerical simulations. Specifically, the paper focuses on the simulation of supersonic jets controlled by these slanted perforated tabs to evaluate their effectiveness in enhancing mixing efficiency. The simulation methodology involves developing a computational model of the jet and the tabs, utilizing mathematical equations and numerical techniques to solve for fluid flow, pressure, and other relevant variables. This computational approach enables the prediction of jet behaviour and the assessment of how different types of control tabs impact the system. This helps for the design of improved jet engines and other fluid systems that require effective mixing capabilities. The introduction of tabs introduces changes to the potential core and velocity profiles, primarily due to enhanced mixing effects facilitated by the tabs. In a supersonic flow, the potential core is typically shorter than in subsonic flows due to the compressibility effects of the fluid. Even though in literature many studies have been done on sonic jets with perforated tabs and some on supersonic jets with perforated tabs, the uniqueness in this paper is on the blockage area. Blockage area has been kept at a minimum of around one percent for solid tab and for 30° perforated tab it's as low as 0.5%. By incorporating perforated tabs into a supersonic jet, the size of the potential core can be further reduced through enhanced mixing between the jet and the surrounding fluid. Thus, with minimal thrust loss this paper explores maximum benefit of potential core reduction and thereby better mixing efficiency and lesser noise production. Solid tab has better potential core reduction but with lesser blockage area, 30º perforated tab is better in ratio of potential core reduction to blockage area. [ABSTRACT FROM AUTHOR]

More recent research shows the significant impact of accurate demand forecasting on the operation of supply chain system and thus on the performance of the company. Inventories in the production process could represent waste, which results in higher storage costs and consequently a higher product price, which in turn reduces company's competitiveness on the market. Nevertheless, a company must implement a lean production process and consequently carefully control storage and inventory costs. The introduction of a lean production process is closely linked to the risk of stock-outs, and knowledge of this risk in relation to customer habits is therefore a useful piece of information for the line manager's decision-making. This paper will present a mathematical model that relates customer demand for a product to the inventory level in the warehouse or between the work operations of the production process and the risk of potential penalties that arises with the introduction of a lean production process. With this model we can simulate, how to improve the production processes with still acceptable risk, with the goal of achieving a balance between stocks and the leanness of the production process. The paper demonstrates the use of a mathematical model on a concrete example from practice for risk simulation when choosing different production scenarios resulting from changed customer behaviour. [ABSTRACT FROM AUTHOR]

The intensification of municipal-solid-waste (MSW) production, energy usage, and the curb of the landfill have developed the need for our society to use MSW under the vision of a waste-to-energy (WTE) approach to eradicating MSW as well as to address the energy issues across the world. The WTE alteration is an environment-friendly way of disposing of MSW. This study examines the usage of plastic, wood, and paper for refuse-derived fuel (RDF) production. The RDF is solitary of MSW energy yields, whose dependability and superiority are analysed in the current work. Two different RDF have been obtained from diverse waste streams at the plant site to find the finest RDF based on energy efficiency. Plastics, wood, and paper are the principal constituents in the method of occupied RDF. The results exhibited that the RDF-PA holds a high amount of carbon as-well-as hydrogen content and a decent calorific value, which leads to better fuel quality. The retention time under combustion and pyrolysis, the volatile matter portion of RDF, has increased accordingly. As per obtained results, RDF-PA is a good option for energy applications and fuel for combustion and pyrolysis reactions. [ABSTRACT FROM AUTHOR]

This paper aims to identify different connections between organizational behavior and other subjects in order to understand the way this field developed for the past five years. In order to observe these connections a bibliometric analysis was conducted and interpreted. A database of 1188 articles published in English were extracted from the Web of Science and imported in VOSviewer software. The bibliometric analysis conducted showed an increasing number of papers published on organizational behavior in the past two years and the countries with the most published articles on this subject. From the VOSviewer software analysis resulted the 445 keywords co-occurrence map and the map representing the evolution of keywords over the past five years. This research is useful as a starting point for further research involving new connections between organizational behavior and subjects that are discussed. [ABSTRACT FROM AUTHOR]

This paper follows a bibliometric assessment methodology to provide a systematic review of studies devoted to cultural heritage (CH) buildings that simultaneously refer to hygrothermal conditions and/or behavior and climate change (CC) scenarios. Moreover, this paper aims at identifying the main research trend and research gaps in this combined research field, and to provide a critical discussion of previous works relating to CH, hygrothermal behavior, and CC. Scopus database was used for data gathering and export, followed by VOSviewer for network visualization. The advanced search on the database showed that only 36 documents have considered the study of these three subjects together, as of 2022. The majority of research has been carried out in Italy (27% of the relevant documents). This paper further describes some funded research projects on the topic of CH, hygrothermal behavior, and CC. It was concluded that the investigation on this combined research topic is very recent and scarcely unexplored, and further research is required to assess how future CC scenarios will affect the hygrothermal behavior of CH buildings. These new understandings are fundamental for all stakeholders involved in topics related to heritage conservation and assessment of the hygrothermal behavior of buildings. [ABSTRACT FROM AUTHOR]