On the Depth of Decision Trees with Hypotheses

In this paper, based on the results of rough set theory, test theory, and exact learning, we investigate decision trees over infinite sets of binary attributes represented as infinite binary information systems. We define the notion of a problem over an information system and study three functions of the Shannon type, which characterize the dependence in the worst case of the minimum depth of a decision tree solving a problem on the number of attributes in the problem description. The considered three functions correspond to (i) decision trees using attributes, (ii) decision trees using hypotheses (an analog of equivalence queries from exact learning), and (iii) decision trees using both attributes and hypotheses. The first function has two possible types of behavior: logarithmic and linear (this result follows from more general results published by the author earlier). The second and the third functions have three possible types of behavior: constant, logarithmic, and linear (these results were published by the author earlier without proofs that are given in the present paper). Based on the obtained results, we divided the set of all infinite binary information systems into four complexity classes. In each class, the type of behavior for each of the considered three functions does not change.

Using Sequence Analysis to Identify Conversational Motifs in Supportive Interactions

This study demonstrates how sequence analysis, which is a method for identifying common patterns in categorical time series data, illuminates the nonlinear dynamics of dyadic conversations by describing chains of behavior that shift categorically, rather than incrementally. When applied to interpersonal interactions, sequence analysis supports the identification of conversational motifs, which can be used to test hypotheses linking patterns of interaction to conversational antecedents or outcomes. As an illustrative example, this study evaluated 285 conversations involving stranger, friend, and dating dyads in which one partner, the discloser, communicated about a source of stress to a partner in the role of listener. Using sequence analysis, we identified three five-turn supportive conversational motifs that had also emerged in a previous study of stranger dyads: discloser problem description, discloser problem processing, and listener-focused dialogue. We also observed a new, fourth motif: listener-focused, discloser questioning. Tests of hypotheses linking the prevalence and timing of particular motifs to the problem discloser’s emotional improvement and perceptions of support quality, as moderated by the discloser’s pre-interaction stress, offered a partial replication of previous findings. The discussion highlights the value of using sequence analysis to illuminate dynamic patterns in dyadic interactions.

Data Science Meets High-Tech Manufacturing – The BTW 2021 Data Science Challenge

For its third installment, the Data Science Challenge of the 19th symposium “Database Systems for Business, Technology and Web” (BTW) of the Gesellschaft für Informatik (GI) tackled the problem of predictive energy management in large production facilities. For the first time, this year’s challenge was organized as a cooperation between Technische Universität Dresden, GlobalFoundries, and ScaDS.AI Dresden/Leipzig. The Challenge’s participants were given real-world production and energy data from the semiconductor manufacturer GlobalFoundries and had to solve the problem of predicting the energy consumption for production equipment. The usage of real-world data gave the participants a hands-on experience of challenges in Big Data integration and analysis. After a leaderboard-based preselection round, the accepted participants presented their approach to an expert jury and audience in a hybrid format. In this article, we give an overview of the main points of the Data Science Challenge, like organization and problem description. Additionally, the winning team presents its solution.

The Influence of Jodipan Color Utilization as a Learning Source of Ability to Solve Problems in The Theme of Enviromental Pollution

The ability to solve problems is a process in which a person identifies a situation, formulates a hypothesis, verifies a hypothesis made by digging up data, and restarts the hypothesis made to become a generalization (Purwanto, 1999). The focus of this research is to analyze the influence of the use of the Kampung Warna Warni Jodipan as a source of learning for students' ability to solve problems in MTs Attaraqqie Malang on the theme of tackling environmental pollution. This study uses an experimental research design in the form of a Quasi-Experimental Design with the type of pretest posttest control group design. The sample in this study were students of class IX A and IX D with purposive sampling technique. Data collection techniques using test questions in the form of problem description. The data analysis technique in this study was to use the independent sample t-test. The results of this study indicate that there is a significant influence on the use of the Kampung Warna Warni Jodipan as a source of learning for students' problem solving abilities, this is evidenced by the results of the independent sample t-test which shows that there is a significant influence on the use of the Kampung Warna Warni Jodipan. , with tcount> ttable which is 5,450> 2,000. This shows that there are significant differences in the ability to solve problems in the experimental and control classes.

Disease Risk and Conservation Implications of Orangutan Translocations

Critically Endangered orangutans are translocated in several situations: reintroduced into historic range where no wild populations exist, released to reinforce existing wild populations, and wild-to-wild translocated to remove individuals from potentially risky situations. Translocated orangutans exposed to human diseases, including Coronavirus Disease 2019 (COVID-19), pose risks to wild and previously released conspecifics. Wildlife disease risk experts recommended halting great ape translocations during the COVID-19 pandemic to minimize risk of disease transmission to wild populations. We collected data on orangutan releases and associated disease risk management in Indonesia during the COVID-19 pandemic, and developed a problem description for orangutan disease and conservation risks. We identified that at least 15 rehabilitated ex-captive and 27 wild captured orangutans were released during the study period. Identified disease risks included several wild-to-wild translocated orangutans in direct contact or proximity to humans without protective equipment, and formerly captive rehabilitated orangutans that have had long periods of contact and potential exposure to human diseases. While translocation practitioners typically employ mitigation measures to decrease disease transmission likelihood, these measures cannot eliminate all risk, and are not consistently applied. COVID-19 and other diseases of human origin can be transmitted to orangutans, which could have catastrophic impacts on wild orangutans, other susceptible fauna, and humans should disease transmission occur. We recommend stakeholders conduct a Disease Risk Analysis for orangutan translocation, and improve pathogen surveillance and mitigation measures to decrease the likelihood of potential outbreaks. We also suggest refocusing conservation efforts on alternatives to wild-to-wild translocation including mitigating human-orangutan interactions, enforcing laws and protecting orangutan habitats to conserve orangutans in situ.

Space Detumbling Robot Arm Deployment Path Planning Based on Bi-FMT* Algorithm

In order to avoid damage to service satellites and targets during space missions and improve safety and reliability, it is necessary to study how to eliminate or reduce the rotation of targets. This paper focused on a space detumbling robot and studied the space detumbling robot dynamics and robot arm deployment path planning. Firstly, a certain space detumbling robot with a ‘platform + manipulator + end effector’ configuration is proposed. By considering the end effector as a translational joint, the entire space detumbling robot is equivalent to a link system containing six rotating joints and three translational joints, and the detailed derivation process of the kinematic and dynamic model is presented. Then, ADAMS and MATLAB were used to simulate the model, and the MATLAB results were compared with the ADAMS results to verify the correctness of the model. After that, the robot arm deployment problem was analyzed in detail from the aspects of problem description, constraint analysis and algorithm implementation. An algorithm of robot arm deployment path planning based on the Bi-FMT* algorithm is proposed, and the effectiveness of the algorithm is verified by simulation.

The exploration of wave processes in the Arctics geological layers in the presence of the ice field.

The Arctic shelf zone is a very important region in our country due to the huge amounts of hydrocarbons, located there. The exploration of this region is difficult because of the presence of lots of various ice constructions, in particular, ice fields. While carrying out the seismic prospecting works, the reflected waves from the ice field contribute much to the seismograms. It sufficiently complicates the process of further interpretation of the seismograms. Only a few works are devoted to modelling the seismic waves spread through the geological layers of the Arctics in the presence of an ice field as this theme is rather new and needs deeper investigation. In this work we present the results of the investigation of the seismic waves spread in models with an ice field for the 3D case using the grid-characteristic method. The modelling results (wave fields of the velocity distribution and seismograms) allow to identify the reflected waves from the ice field from other waves. In addition, we carried out the comparative analysis of the wave fields and seismograms for the 2D model with an ice field on the surface of the calculated area for the problem description from the work of other authors. The results demonstrate a good qualitative coincidence under different approaches to the solution of the problem.

Security and privacy with K-step opacity for finite automata via a novel algebraic approach

As an important secretive attribute, opacity of cyber-physical systems (CPSs) has attracted considerable attention. Existing works on opacity mainly concentrate on the formal language method by assuming that the intruder tracks partial knowledge of observable transitions. In this paper, under the framework of Boolean semi-tensor product (BSTP) of matrix, we extend the verification of opaque property to algebraic mechanisms that have great advantages in problem description and solution. First, we show that how [Formula: see text]-step opacity problem of nondeterministic finite automata (NFAs) can be transformed to the construction problem of a polynomial matrix that characterizes the state estimation eavesdropped by malicious intruders within the last [Formula: see text] observations. Second, the necessary and sufficient condition of verifying [Formula: see text]-step opacity is obtained, which is equivalent to validate the composition of elements within the polynomial matrix. Finally, the effectiveness of this result is demonstrated by an illustrative example. Taking together, the matrix-based method will be useful to deliver a novel theoretical tool for investigating the privacy-preserving problem in the related area of CPSs.

ONLINE ADVICE: GIVING ADVICE IN AN INTERNET TRAVEL FORUM

This article aims at exploring the discourse moves of giving advice in the online context with an Internet travel forum as an example. The article first reviews relevant literature concerning advice and advice giving. Previous research on online advice giving is also reviewed in the following section. Then, the instrument for data collection of the present study is introduced and online messages, including problem messages and response messages are analyzed from different aspects, e.g. problem description, discursive moves in advice messages and how the initial problem writer responded to the advice-givers. The present study finally reaches to the conclusion that advice and assessment are the two most frequent advice moves in advice messages. <p> </p><p><strong> Article visualizations:</strong></p><p><img src="/-counters-/edu_01/0876/a.php" alt="Hit counter" /></p>

TSN: Performance Creative Choreography Based on Twin Sensor Network

The purpose of this paper is to improve the efficiency of performance creative choreography (PCC). Our research work shows that we can realize the model integration and data optimization for PCC in complex environments based on the combined architecture of sensor network (SN) and machine-learning algorithm (MLA). In order to explain the process and content of this research better, this paper designs a specific problem description framework for PCC, which mainly includes the following content: (1) a twin sensor network (TSN) architecture based on digital twin information interaction is proposed, which defines and describes the acquisition method, classification (creative data, rehearsal data, and live data), and temporal and spatial features of performance data. (2) Proposed a mobile computing method based on director semantic annotation (DSA) as the core computing module of TSN. (3) A spatial dynamic line (SDL) model and a creative activation mechanism (CAM) based on DSA are proposed to realize fast and efficient PCC of dance with the TSN architecture. Experimental results show that the TSN architecture proposed in this article is reasonable and effective. The SDL model achieved significantly better performance with little time increase and improved the computability and aesthetics of PCC. New research ideas are proposed to solve the computational problem of PCC in complex environments.