A Method for Recognition of Sudden Commencements of Geomagnetic Storms Using Digital Differentiating Filters

This article describes a method for recognizing sudden commencement events using digital differentiating filters. This method is applied to INTERMAGNET observatory data. Maximum amplitude derivatives for the magnetic components (X, Y, Z) and the total intensity (F) of the geomagnetic field are introduced, and the decision-making rule is formulated. The authors developed a procedure for selecting optimal digital differentiating filters. Estimates of probabilities of correct and false recognition of sudden commencements were obtained. The calculations of the probabilistic characteristics have confirmed the effectiveness of the method.

Assessing the effects of the modular approach in math learning on independent creativity of university students

Numerous teachers and researchers are studying the issue of improving the effectiveness of university education and offer innovative technologies to address this challenge. Modular learning is among the most relevant and productive teaching techniques. The paper examines how the modular approach in math learning contributes to the development of independent creativity of university students. The testing was performed at Tyumen Industrial University (Russia) among students of the Applied Geology program numbering 28 individuals in the control group and 27 individuals in the experimental group. The students were given a series of lectures to present new material that was later assimilated and reinforced during practical sessions through blocks and chains of preparatory and auxiliary tasks. To demonstrate their knowledge and grasping of the material, the students passed individual tests and exams. Statistical data were processed using Pearson’s chi-squared test and the Wilcoxon signed-rank test. Based on the decision-making rule, the research confirms the hypothesis that the modular approach is more effective in forming students’ independent creativity in math learning if compared with conventional education. The research results demonstrate that 92% of students in the experimental group set about solving advanced math problems, while in the control group this share was 61%. The share of students in the experimental group who prepared research projects increased from 52% to 89%, while in the control group their number decreased from 56% to 43%. Among the avenues for further research is an attempt to implement applied research projects not only in math learning, but also in applied subjects of study throughout the entire training period. The development of independent creativity of university students is expected to have a positive effect on their ability to absorb the material of other courses.

Artificial Intelligence implemented to recognize patterns of sustainable areas by evaluating the database of socioenvironmental safety restrictions

The several papers recently published, applied to sustainable development, has been considering new methodologies and techniques in identifying the main criteria, in numeric format, that are useful in formulating possible solutions to the solid waste problem. This paper presents the Mathematical and Computational Modeling Process (PM2C), applied in the determination of control variables related to selection of areas destined to the construction of landfills, in order to benefit from new analyzes and values obtained by methods such as AHP (Analytical Hierarchy Process) and GIS (Geographic Information Systems). The main objective of this paper is the use of Artificial Intelligence (AI), through a Decision Tree strategy, as a selective method and optimal solutions in choosing the best area dedicated to the construction of landfills, with the creation and analysis of new values applied to scenarios defined in the paper of Andrade e Barbosa (2015). The results, expressed in analytical and graphical forms, show the individual values for each criterion and new scenarios involved in the phenomena. This paper highlights the importance of incorporating new conditions and criteria to propose a new decision-making rule, simultaneously, associating qualitative and quantitative characteristics, related to social and economic effects, applied to the environment management system. Based on these principles, it was possible to simulate new scenarios that demonstrate, with very high precision, the best values of useful criteria for decision-making in the selection of the optimal area for implementation of a landfill.

As for decision making rules based on research results while forensic science activities

While forensic research, obtained results should be evaluated in order to ensure adoption of correct conclusion regarding the research object. For this purpose forensic experts should use established decision rules to substantiate a statement about conformity of an object or certain requirements, or parameters, or characteristics. Currently, the need to ensure that a decision is made based on results of forensic examination using the concept of decision rules is constantly increasing. Therefore, consideration of the issue of establishing rules for making decisions while forensic science activity at international and national levels is relevant. Relevance of this issue is justified not only by the requirements of ІSO/ IEC 17025:2017 for testing laboratories but by the requirements for the objectivity of expert opinion. ISO/IEC 17025:2017 recognizes that there is no single rule for deciding on conformity. In other words, in a specific situation there will be its own decision making rule. This also applies to forensic science activity. Therefore, this article purpose is necessary for forensic science activity to determine: general guidelines for choosing appropriate decision-making rule; directives for determining the components of decision making rules depending on the object and the task of forensic examination; rules for applying certain requirements to the research results of carried out in accordance with requirements of research methods, research object and the type of quantitative or qualitative research. Thus, this article defines and considers the process of establishing the rules for making decisions, criteria which the rules for m

Punching above Weight: How the African Union Commission Exercises Agency in Politics

Conventional narratives suggest that the African Union Commission (AUC), like most international public administrations and international organisations (IOs) housed in the less materially endowed regions of the world, exercises no meaningful agency on international issues. This article however seeks to show that the AUC is neither a glorified messenger and docile follower of orders of governments nor is it an empty vessel that timidly goes where the wind of governments blows. Rather, the AUC exercises significant agency on issues that affect not just the African continent but also the broader international system. The AUC is often at the heart of international agenda-setting, norm development, decision-making, rule creation, policy development, and it sometimes offer strategic leadership. The article demonstrates six pathways through which the AUC acts like a tail wagging a dog.

The judgment of crimes against humanity in Brazil: Analysis through the critical criminological lens of lola aniyar

In this article we discuss two recent Brazilian Supreme Court judgments about crimes committed during the civil-military dictatorship: Allegation of Disobedience of Fundamental Precept suit n. 153 (constitutionality of the 1979 amnesty law), and Extradition suit n. 1362, that discussed the extradition of an Argentine citizen who was convicted of committing crimes against humanity during the Argentine dictatorship). We analyze the role of the Brazilian Supreme Court in the (re) construction of the “criminal problem” and “criminal control” in relation to crimes against humanity perpetrated during the periods of the Argentine (1978-1983) and Brazilian (1964-1985) dictatorship. We take Lola Aniyar de Castro Thought’s, seeking some inspiration, for whom the criminology of the 21st Century is the “criminology of human rights”, and criminal control would be the thermometer of human rights. In the last part of this article, we discussed what seems to have been “the triumph of Lewis Carroll”, in the metaphor of reversing meanings: when protecting human rights is not to protect human rights, by creating an ad hoc decision-making rule from which “remembering is to forget”, and “forgetting is to remember”, provided that, from the peculiar Rule n. 42, the investigation and accountability for crimes against humanity are not allowed.

Computational medication regimen for Parkinson’s disease using reinforcement learning

Our objective is to derive a sequential decision-making rule on the combination of medications to minimize motor symptoms using reinforcement learning (RL). Using an observational longitudinal cohort of Parkinson’s disease patients, the Parkinson’s Progression Markers Initiative database, we derived clinically relevant disease states and an optimal combination of medications for each of them by using policy iteration of the Markov decision process (MDP). We focused on 8 combinations of medications, i.e., Levodopa, a dopamine agonist, and other PD medications, as possible actions and motor symptom severity, based on the Unified Parkinson Disease Rating Scale (UPDRS) section III, as reward/penalty of decision. We analyzed a total of 5077 visits from 431 PD patients with 55.5 months follow-up. We excluded patients without UPDRS III scores or medication records. We derived a medication regimen that is comparable to a clinician’s decision. The RL model achieved a lower level of motor symptom severity scores than what clinicians did, whereas the clinicians’ medication rules were more consistent than the RL model. The RL model followed the clinician’s medication rules in most cases but also suggested some changes, which leads to the difference in lowering symptoms severity. This is the first study to investigate RL to improve the pharmacological approach of PD patients. Our results contribute to the development of an interactive machine-physician ecosystem that relies on evidence-based medicine and can potentially enhance PD management.

Research on metro passenger flow route selection model based on passengers' familiarity with road network

Road network familiarity is a key attribute that affects passengers’ travel route choice. This paper constructs a differentiated travel generalized cost function based on the passenger’s road network familiarity and the influencing factors of route choice, and uses the Regret Theory to construct a route choice model. By setting passenger decision-making rule weights increase the flexibility of the model. The paper uses the method of combining RP survey and SP survey to conduct route selection behavior survey and calibrate model parameters. Finally, the prediction results before and after the passenger classification are compared with the survey data. The prediction error value is 5.98%, and the prediction accuracy after passenger classification is improved by 6.03%. The effectiveness of the prediction model is verified and the necessity of passenger classification is verified.

A model and the behavioral implications of the calculus of consent: The dilemma of public choice before public choice

The choice of a group decision-making rule is one of the most important political issues. Buchanan and Tullock have provided a framework for analyzing the optimal k-majority rule from the perspective of “methodological individualism.” They proposed the concept of “external costs” and “decision costs” and argued that the optimal k-majority rule takes place where the sum of these two costs–“total costs”–is minimized. Despite the fact that the approach is widely accepted as a tool for dealing with public decision-making rules, the study of formalizing these two costs in a quantitative manner has been relatively rare. We propose a systematic way of modeling these costs considering the assumptions mentioned by Buchanan and Tullock. We find that the resulting shape of the graphs is generally similar to that of the Buchanan-Tullock model, except for some minor details. Then, using this analytical model, we investigate several factors that could affect Buchanan-Tullock’s two costs and the optimal k-majority rule. We show that “clustering of disadvantages” (social factor) and “loss aversion” (personal factor) could increase external costs in Buchanan-Tullock’s model. These factors can result in a separation between the theoretical and actual optimal k-majority rules. Meanwhile, some recent developments in information and communication technologies can not only decrease decision costs, but also increase the same costs simultaneously through amplified “group polarization” (technological factor). If the effect of the former is not the same as that of the latter, this leads to a difference in optimal k-majority rules as well. These discrepancies bring us to the dilemma of “public choice before public choice.”