Situation Model Research Articles

Game-Theoretic Model for the Interaction of the Online Course Design Process Participants within the University

The market of digital educational resources and, in particular, online courses for the higher education system is actively developing. A significant role in creating a high-quality competitive online course is played by the organizational and legal system of interaction between authors and the university. This research article aims at developing a game-theoretical model of interaction between the participants of online course creating process in order to identify optimal (mutually beneficial) options and conditions for partnership interaction between the authors of online courses and the university. To represent the interaction between the authors and the university in terms of game theory, there are analyzed the specific features of creating an online course. The authors are the first to construct a mathematical game model for a typical situation of commercializing an online course within the university-and-author interaction. This situation is interpreted as a dynamic finite paired non-antagonistic non-cooperative game with complete perfect information. The Nash equilibrium, perfect on subgames, is found by the method of backward induction; the profile of optimal strategies is determined. The analysis of the results can help to substantiate, form and improve the strategy of mutually beneficial cooperation between the authors of the online course and the university.

Neural unscrambling of temporal information during a nonlinear narrative.

Although we must experience our lives chronologically, storytellers often manipulate the order in which they relay events. How the brain processes temporal information while encoding a nonlinear narrative remains unclear. Here, we use functional magnetic resonance imaging during movie watching to investigate which brain regions are sensitive to information about time in a narrative and test whether the representation of temporal context across a narrative is more influenced by the order in which events are presented or their underlying chronological sequence. Results indicate that medial parietal regions are sensitive to cued jumps through time over and above other changes in context (i.e., location). Moreover, when processing non-chronological narrative information, the precuneus and posterior cingulate engage in on-the-fly temporal unscrambling to represent information chronologically. Specifically, days that are closer together in chronological time are represented more similarly regardless of when they are presented in the movie, and this representation is consistent across participants. Additional analyses reveal a strong spatial signature associated with higher magnitude jumps through time. These findings are consistent with prior theorizing on medial parietal regions as central to maintaining and updating narrative situation models, and suggest the priority of chronological information when encoding narrative events.

Development of trauma team cognition can be explained by ”split vision”: A grounded theory study

ABSTRACT The aim of this study was to explore interaction of interprofessional hospital trauma teams. A theory about how team cognition is developed through a dynamical process was established using grounded theory methodology. Video recordings of in-real-life resuscitations performed in the emergency ward of a Scandinavian mid-size urban hospital were collected and eligible for inclusion using theoretical sampling. By analyzing interactions during seven trauma resuscitations, the theory that trauma teams perform patient assessment and resuscitation by alternating between two process modes, the two main categories “team positioning” and “sensitivity to the patient,” was generated. The core category “working with split vision” explicates how the teams interplay between the two modes to coordinate team focus with an emergent mental model of the specific situation. Split vision ensures that deeper aspects of the team, such as culture, knowledge, empathy, and patient needs are absorbed to continuously adapt team positioning and create precision in care for the specific patient.

HUB-GA: A heuristic for universal lists broadcasting using genetic algorithm

Broadcasting is a fundamental problem in the information dissemination area. In classical broadcasting, a message must be sent from one network member to all other members as rapidly as feasible. Although this problem is NP-hard for arbitrary graphs, it has several applications in various fields. As a result, the universal lists model, which replicates some real-world restrictions like the memory limits of nodes in large networks, is introduced as a branch of this problem in the literature. In the universal lists model, each node is equipped with a fixed list and has to follow the list regardless of the originator. As opposed to various applications for the problem of broadcasting with universal lists, the literature lacks any heuristic or approximation algorithm. In this regard, we suggest HUB-GA: A heuristic for universal lists broadcasting with genetic algorithm, as the first heuristic for this problem. HUB-GA works toward minimizing the universal lists broadcast time of a given graph with the aid of genetic algorithm. We undertake various numerical experiments on frequently used interconnection networks in the literature, graphs with clique-like structures, and synthetic instances with small-world model in order to cover many possibilities of industrial topologies. We also compare our results with state-of-the-art methods for classical broadcasting, which is proved to be the fastest model among all. Nevertheless of the substantial memory reduction in the universal list model compared to the classical model, our algorithm finds the same broadcast time as the classical model in diverse situations.

Development of situation models for duration of production cycles of manufacturing finished rolled products. Message 1

The problems of system analysis and development of a complex set of models necessary for constructing an algorithm for situational (multivariant) estimation of the duration of production of different batches of rolled products in the conditions of a modern automated medium-sized shop (object of study), including rigidly connected production sections with continuous and cyclic technological processes (feeding blanks, heating in method furnaces, rolling, cutting the rolled stock into strips, cooling, trimming the ends of the bundles of rolled stock, cutting to cut lengths, forming and tying bundles of finished rolled products, loading bundles into railway cars). The study of the functioning of the rolling shop was carried out in the following order: the study of technological processes; technical characteristics of the main and auxiliary equipment; analysis of technical and economic indicators; performance of chronometric and monitoring observations of the metal flow, the operation of units and equipment; decomposition of the production process into operations, elements and trace elements; analysis of the influence of the human factor in the organization of production and operational management of processes; analysis of expert assessments of real and possible production situations related to the fulfillment of orders for finished products. The duration of production cycles is proposed to be classified as follows: piece (corresponding to a workpiece, a pack of workpieces, a package of finished rolled products); batch (corresponding to the shipment of products); subsystem and system (related to sections, departments, workshop as a whole); technically possible, normative, planned, predictive and actual. Based on the preliminary development of situational batch models of the duration of production cycles of the departments of the shop, a situational system model of the duration of the production cycle for manufacturing a batch of finished rolled products is determined by selecting the models of the unit with the maximum cycle duration. To bring the duration of the production cycles of subsystems and the system as a whole into a comparable form, the quantitative characteristics of rolled products batches are determined. Mathematical models of the duration of the production cycle of the warehouse of blanks are built; technological line. The clock models of work of the warehouse of blanks, the production line, the warehouse of finished products have been formed.

Profile of Mathematics Communication Ability of Seventh-Grade Students in Solving Set Problems Based on Cognitive Style

This study aims to describe the profile of students' mathematical communication ability in solving set problems in terms of field-dependent and field-independent cognitive styles. This research method includes qualitative descriptive research. In this study, the collected data was in the form of words so that it did not emphasize numbers. Participants in this study consisted of three students with a field-dependent cognitive style and three students with a field-independent cognitive style from class VII at one of the junior high schools in North Central Timor Regency. The instruments used are a mathematical communication ability test, Group Embedded Figure Test, and interviews. The results showed that students with a field-independent cognitive style have high mathematical communication abilities. This can be seen from the test results of the three field-independent students who are able to express mathematical ideas through oral, written, demonstration and describe in visual form, are able to analyze, interpret, and evaluate mathematical ideas through oral, written, and other visual forms, and are able to use terms, mathematical notations, and their structures to present ideas, describe relationships, and situation models when solving problems mathematical sets. Meanwhile, students with a field-dependent cognitive style have low mathematical communication abilities. This can be seen from the results of the mathematics communication ability test of the three field-dependent students who have not been able to meet all the indicators of mathematical communication.

ON SOME METHODOLOGICAL ISSUES IN MATHEMATICAL MODELING OF INTERACTING POPULATIONS

In this paper, we focus on some important aspects of model building. The discussion specifically concerns the case of predator–prey interactions. We introduce here two models whose slight difference lies just in the way predators survive. In the former, they are taken to feed only on the modeled prey, i.e., to be specialists; in the second one, they are generalists, i.e., they can survive on other not explicitly modeled food resources. But our main focus is on the prey, that may disappear due to the Allee effect, if reduced to very low numbers. On the other hand, they also exhibit herd behavior. Our main aim is the discussion of the issues of mathematical modeling of such situation. We show on this example that modeling requires much more than equations patching from different systems. The analysis of the models indicates that the ecosystem may collapse in the case of specialist predators. If the predators have other feeding resources, they instead can thrive. Both types of models exhibit bistability between the prey-free state and coexistence.

Criminalistic training in modern higher school

The review presents the manuscript of the textbook “Criminalistics”, which is being prepared for publication. In the manuscript, the authors of the textbook, based on the established traditional approaches to criminology textbooks that have developed in Russian science, consistently present the material that is conceptually linked by the table of contents of the publication. It pays special attention not only to the already established and well-established educational knowledge, but also to the knowledge relevant to the current situation in which the law enforcement agencies of Russia function. Consistently in the sections of the criminalistics system in the textbook, the issues of criminalistic identification, forecasting, situational modeling and the basics of information and methodological use of criminalistics data in other types of law enforcement activities are revealed. The textbook reflects almost all the institutes of technical support of the investigation, including the issues of genetic identification of the individual, the study of computer information, the basics of the use of “artificial” intelligence in the investigation of crimes, expert activity in the investigation. Special attention is paid to the tactics of verbal and non-verbal investigative actions. For the first time, the issue of establishing causal relationships in the process of investigating crimes is considered. In the system of private forensic techniques, the authors have included both traditional and current methods of investigating crimes against public security and state power, terrorist and extremist orientation, official and official crimes, as well as crimes committed in the field of computer information.

The Application of Artificial Intelligence in Health Care Resource Allocation Before and During the COVID-19 Pandemic: Scoping Review

Background Imbalanced health care resource distribution has been central to unequal health outcomes and political tension around the world. Artificial intelligence (AI) has emerged as a promising tool for facilitating resource distribution, especially during emergencies. However, no comprehensive review exists on the use and ethics of AI in health care resource distribution. Objective This study aims to conduct a scoping review of the application of AI in health care resource distribution, and explore the ethical and political issues in such situations. Methods A scoping review was conducted following the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews). A comprehensive search of relevant literature was conducted in MEDLINE (Ovid), PubMed, Web of Science, and Embase from inception to February 2022. The review included qualitative and quantitative studies investigating the application of AI in health care resource allocation. Results The review involved 22 articles, including 9 on model development and 13 on theoretical discussions, qualitative studies, or review studies. Of the 9 on model development and validation, 5 were conducted in emerging economies, 3 in developed countries, and 1 in a global context. In terms of content, 4 focused on resource distribution at the health system level and 5 focused on resource allocation at the hospital level. Of the 13 qualitative studies, 8 were discussions on the COVID-19 pandemic and the rest were on hospital resources, outbreaks, screening, human resources, and digitalization. Conclusions This scoping review synthesized evidence on AI in health resource distribution, focusing on the COVID-19 pandemic. The results suggest that the application of AI has the potential to improve efficacy in resource distribution, especially during emergencies. Efficient data sharing and collecting structures are needed to make reliable and evidence-based decisions. Health inequality, distributive justice, and transparency must be considered when deploying AI models in real-world situations.

PENERAPAN GAYA KEPEMIMPINAN SITUASIONAL PERSONALIA PT. ARTO MANUNGGAL

Determining a situational leadership style using an example of a style or model telling, selling, participating and delegating is the aim of this research. The narrative approach uses qualitative methods, namely the approach used in this study. In this study data collection using observation techniques, interviews and documentation. The results based on this research are the personnel of PT. Arto Manunggal explained the situational leadership style or model telling, selling, participating, delegating and the leadership style or model used has a positive effect on achieving the desired goals at PT. Arto Manunggal.

TACTICAL IMPORTANCE OF INVESTIGATIVE CUNNING IN THE INVESTIGATION OF CRIMES

As a type of tactical techniques, investigative cunning is a means of establishing the circumstances of the crime committed. However, this type of tactical techniques is quite ambiguously accepted by both theory and practice of investigation. The purpose of the study, which is the basis of the proposed article, is to justify the tactical importance of investigative cunning, which allows using it to optimize the ongoing investigation. At the same time, a whole arsenal of scientific methods is used: analysis and synthesis, system-activity, situational modeling. They make it possible to study comprehensively the problems that arise in the investigation and can be removed using investigative cunning. The result of the study is the conclusion that investigative cunning is a tool that can increase the effectiveness of the investigation. At the same time, investigative cunning is the key to the investigator’s tactical victory against those who do not want to find out the truth in the case and make a fair procedural decision.

Improving edit-based unsupervised sentence simplification using fine-tuned BERT

Word suggestion in unsupervised sentence simplification aims to replace complex words of a given sentence with their simpler alternatives. This is mostly done without considering their context within the input sentence. In this paper, we propose a technique that brings context awareness to word suggestion by merging pre-trained BERT models with a successful edit-based unsupervised sentence simplification model. More importantly, we show that only by fine-tuning the BERT model on simple English corpora, simplification results can be improved and even outperform some of the competing supervised methods. Finally, we introduce a framework that involves filtering an arbitrary amount of unlabeled in-domain text for tuning the model in situations where labeled data, as simple and complex, is scarce. This preprocessing step also speeds up the training process by ignoring fine-tuning on unnecessary samples.

Multi-Scale Traffic Aware Cybersecurity Situational Awareness Online Model for Intelligent Power Substation Communication Network

Substation communication network (SCN) provides real-time, high-speed, and reliable data transmissions for the advanced monitoring and control functionalities, which are facing increasing cyberspace threats and attacks. Efficient threat perception and cyber situational awareness are essential to enhance secure and reliable SCN operations. This article explores multiscale SCN traffic pattern characteristics with holistic network traffic, separated network traffic for included devices (especially IoT devices) and separated network traffic of certain types of protocol. The proposed online traffic-oriented SCN traffic anomaly detection and cyber situational awareness models are designed for the network anomalies and cyber-attacks that could cause network traffic pattern variations. We leverage a fractional autoregressive integration moving average (FARIMA)-based dynamic threshold model to detect abnormal traffic patterns without sophisticated computations or deep packet inspection. The SCN real-time operation conditions are timely quantified through the statistical methods with the alliance of SCN topology and protocols. The cyber situational awareness model is further carried out to evaluate the most affected protocol and security risks of various devices in SCN using Grubbs’ test. The experiment results are carried out based on a real 110-kV intelligent power substation. The numerical results confirm the comparative low mean square error (MSE) and low complexity of the online traffic characterization when forecasting holistic network traffic and separated network traffics. Furthermore, the timely and quantified cybersecurity risk analysis is conducted based on the SCN traffic with varying scales to detect cyberspace threats and identify the high-risk SCN devices and the most affected protocol.

Increasing the Payback of Nitrogen Fertilizing of Winter Wheat with the Use of Original Methods for Calculating Their Optimal Doses

In the central zone of the Krasnodar Territory of the Russian Federation, on the pre-Caucasian low-leached heavy-duty chernozem on the basis of the P.P. Lukyanenko National Grain Center, for more than 15 years, new, more effective methods for calculating optimal doses of nitrogen fertilizing of winter wheat, characterized by high payback, have been studied. The methodological basis of the study was the assumption that when calculating optimal doses of nitrogen fertilizers, it is necessary to take into account the initial level of effective soil fertility, the state of agrophytocenosis and the planned yield. The solution of this problem is possible only with the help of a systematic analysis of the relationship of winter wheat yield with the above factors, the construction of a regression multiple nonlinear mathematical model and mathematical modeling of various situations in the search for optimal doses of top dressing. As initial information, the data obtained in long-term multifactorial field experiments were used, which resulted in the development of 2 new methods for determining the optimal doses of nitrogen fertilizing of winter crops (first and second) that meet the above requirements. The results of 3-year field experiments to study the effectiveness and payback of nitrogen fertilizing of winter wheat, depending on the methods of their calculation, are presented. The agro-climatic conditions at the time of the research, although they were different, but in general turned out to be relatively favorable for obtaining a good harvest of winter wheat. In 2015 and 2016, comparative tests of the effectiveness and payback of 2 new methods for calculating the optimal doses of the 1st and 2nd nitrogen fertilizing of winter wheat were carried out. For comparison, 2 well-known, widely used in practice, tabular methods were selected (prototypes 1 and 2). In 2015, the study was carried out with the Grom variety (predecessor - corn for grain), in 2016 - with the Yuca variety (predecessor - winter wheat). It is shown that the use of original methods for calculating optimal doses of 1st and 2nd nitrogen fertilizing of winter wheat significantly increased their efficiency and payback (both 1st and 2nd in total) compared with the prototypes (by 35-200%), at the same time, the payback of nitrogen top dressing, the doses of which were calculated from the prototypes, was ~12- 14 kg/kg (on average for 2 years), and the payback of top dressing calculated according to the original methods was 22-24 kg/kg in 2021 (forerunner - soy, Adel and Bagrat varieties) studied the effectiveness and payback of nitrogen fertilizing when calculating their doses only by original methods. It was shown that even with a high level of yield of winter wheat in the control (~60 c/ha on average for both varieties), the use of 2 nitrogen fertilizing, the doses of which are calculated according to the original methods, allowed to achieve a yield of winter wheat of 80-90 c/ha with a payback of ~22 kg grains/kg of N fertilizers.

Model Kepemimpinan Situasional dan Transformasional Kepala Sekolah SMAK Yos Sudarso Batu

The focus of this study is to explain the situational and transformational leadership models that exist in the Principal of SMAK Yos Sudarso Batu. The leadership models that can be observed from this school principal are situational leadership and transformational leadership. These two terms are quite foreign to the ears, because they are rarely mentioned in an organization or institution that are encountered on a daily basis. This leadership model is an expression of how Principal Yos Sudarso is in the organization or foundation he leads. This study aims to describe and analyze the basis, character, and pattern of situational and transformational leadership of school principals. The researcher uses descriptive qualitative method which produces data in the form of words and in writing or verbally from the people and observed behavior. The findings of this study are that a leader who lives a situational and transformational leadership model is a leader who is able to set clear, specific and measurable organizational goals. Cooperative, capable and militant leader. This leader also has a strong determination and commitment, is able to create synergies within the organization and is able to mobilize all member resources.

Effects of two computer-based interventions on reading comprehension: Does strategy instruction matter?

Managing text information to answer questions is one of the most frequent reading activities. These reading situations, called task-oriented reading, are challenging for students since they require specific skills that extend beyond basic reading comprehension skills. This is especiallypronounced when deep comprehension is required. Although many computer-based interventions have focused on teaching strategies to foster text comprehension, the role of strategy instruction in task-oriented reading has not been examined. In this study, we aim to ascertain the efficacy of an intervention based on task-oriented reading strategy instruction (TuinLECweb), in both textbase and situation model levels of comprehension, comparing it with training based on question-answering practice (AutoLEC). Moreover, we analyzed students’ use of the instructional components and resources of the programs and the relationship to their efficacy. One hundred and thirty pupils attending sixth grade participated in this experimental pre-post study. The intervention comprised eight sessions in which students followed the training on their computers in the classroom. Results show that participants in both conditions raised their reading scores; however, while students in AutoLEC training obtained higher textbase scores, students in the TuinLECweb condition improved their situation model performance. Besides, gain in reading comprehension was not related to either instructional components or resources. These findings highlight the key role of strategy instruction in fostering deep comprehension when employing computer-based interventions in task-oriented reading. Moreover, these results point out the needto analyze how students manage the instructional aids offered to them.

Cyber-Physical-Social Awareness Platform for Comprehensive Situation Awareness.

Cyber-physical-social computing system integrates the interactions between cyber, physical, and social spaces by fusing information from these spaces. The result of this fusion can be used to drive many applications in areas such as intelligent transportation, smart cities, and healthcare. Situation Awareness was initially used in military services to provide knowledge of what is happening in a combat zone but has been used in many other areas such as disaster mitigation. Various applications have been developed to provide situation awareness using either IoT sensors or social media information spaces and, more recently, using both IoT sensors and social media information spaces. The information from these spaces is heterogeneous and, at their intersection, is sparse. In this paper, we propose a highly scalable, novel Cyber-physical-social Awareness (CPSA) platform that provides situation awareness by using and intersecting information from both IoT sensors and social media. By combining and fusing information from both social media and IoT sensors, the CPSA platform provides more comprehensive and accurate situation awareness than any other existing solutions that rely only on data from social media and IoT sensors. The CPSA platform achieves that by semantically describing and integrating the information extracted from sensors and social media spaces and intersects this information for enriching situation awareness. The CPSA platform uses user-provided situation models to refine and intersect cyber, physical, and social information. The CPSA platform analyses social media and IoT data using pretrained machine learning models deployed in the cloud, and provides coordination between information sources and fault tolerance. The paper describes the implementation and evaluation of the CPSA platform. The evaluation of the CPSA platform is measured in terms of capabilities such as the ability to semantically describe and integrate heterogenous information, fault tolerance, and time constraints such as processing time and throughput when performing real-world experiments. The evaluation shows that the CPSA platform can reliably process and intersect with large volumes of IoT sensor and social media data to provide enhanced situation awareness.

On the intrinsic curvature of animal whiskers.

Facial vibrissae (whiskers) are thin, tapered, flexible, hair-like structures that are an important source of tactile sensory information for many species of mammals. In contrast to insect antennae, whiskers have no sensors along their lengths. Instead, when a whisker touches an object, the resulting deformation is transmitted to mechanoreceptors in a follicle at the whisker base. Previous work has shown that the mechanical signals transmitted along the whisker will depend strongly on the whisker's geometric parameters, specifically on its taper (how diameter varies with arc length) and on the way in which the whisker curves, often called "intrinsic curvature." Although previous studies have largely agreed on how to define taper, multiple methods have been used to quantify intrinsic curvature. The present work compares and contrasts different mathematical approaches towards quantifying this important parameter. We begin by reviewing and clarifying the definition of "intrinsic curvature," and then show results of fitting whisker shapes with several different functions, including polynomial, fractional exponent, elliptical, and Cesàro. Comparisons are performed across ten species of whiskered animals, ranging from rodents to pinnipeds. We conclude with a discussion of the advantages and disadvantages of using the various models for different modeling situations. The fractional exponent model offers an approach towards developing a species-specific parameter to characterize whisker shapes within a species. Constructing models of how the whisker curves is important for the creation of mechanical models of tactile sensory acquisition behaviors, for studies of comparative evolution, morphology, and anatomy, and for designing artificial systems that can begin to emulate the whisker-based tactile sensing of animals.

Applications of Elzaki decomposition method to fractional relaxation-oscillation and fractional biological population equations

Elzaki decomposition method (EDM) is adopted to deal with the fractional-order relaxation and damped oscillation equation along with time-fractional spatial diffusion biological population model in different suitable habitat situations. In accordance with the graphs for the solutions obtained, the fractional relaxation exhibits super-slow phenomenon due to its extended descent, and fractional damped oscillation is an intermediate process that explains damped oscillation dynamic systems induced by some attenuated oscillations. The biological population model of time-fractional spatial diffusion depicts a rapid rise in population density in an ecosystem in a suitable habitat that is migrating from an unfavourable zone.

Situation updating during discourse comprehension recruits right posterior portion of the multiple-demand network.

Discourse comprehension involves the construction of a mental representation of the situation model as well as a continuous update of this representation. This mental update is cognitively demanding and likely engages the multiple-demand network. However, there is little evidence for the involvement of the multiple-demand network during situation updating. In this study, we used fMRI to test whether situation updating based on the change of spatial location activated the multiple-demand network. In a discourse comprehension task, readers read two-sentence discourses in which the second sentence either continues or introduces a shift of the spatial location information presented in the first sentence. Compared to situation continuation, situation updating reliably activated the right superior parietal lobule. This area is a part of the multiple-demand network as defined by a digit N-back localizer task and locates within the dorsal attention network as defined in the previous study by Yeo et al. in 2011. Our results provide evidence for the reliable involvement of a specific area of the multiple-demand network in situation updating during high-level discourse processing.