Autonomic computing meets SCADA security

© 2017 IEEE. National assets such as transportation networks, large manufacturing, business and health facilities, power generation, and distribution networks are critical infrastructures. The cyber threats to these infrastructures have increasingly become more sophisticated, extensive and numerous. Cyber security conventional measures have proved useful in the past but increasing sophistication of attacks dictates the need for newer measures. The autonomic computing paradigm mimics the autonomic nervous system and is promising to meet the latest challenges in the cyber threat landscape. This paper provides a brief review of autonomic computing applications for SCADA systems and proposes architecture for cyber security

Quantifying Cognitive Processes in Virtual Learning Simulations

Virtual learning simulations have received increasing attention due various proposed educational, instructional, and institutional advantages; with literature focusing largely on perceptions of this technology and empirical comparisons to other instructional methods. Compared to traditional learning environments, virtual learning environments may present methodological advantages in studying learning processes through applying behavioral tracing techniques. This paper will discuss behavioral indicators of cognitive learning processes used in virtual decision scenarios designed for third year engineering and engineering technology students. Behavioral measures to quantitatively analyze the learning process will be presented. Implications for assessing student learning, instructional strategy selection, and improving higher education quality will be shared from holistic perspective

Autonomic computing architecture for SCADA cyber security

Cognitive computing relates to intelligent computing platforms that are based on the disciplines of artificial intelligence, machine learning, and other innovative technologies. These technologies can be used to design systems that mimic the human brain to learn about their environment and can autonomously predict an impending anomalous situation. IBM first used the term ‘Autonomic Computing’ in 2001 to combat the looming complexity crisis (Ganek and Corbi, 2003). The concept has been inspired by the human biological autonomic system. An autonomic system is self-healing, self-regulating, self-optimising and self-protecting (Ganek and Corbi, 2003). Therefore, the system should be able to protect itself against both malicious attacks and unintended mistakes by the operator

The Decision Making Process of High School Students with High Mathematical Ability in Solving Social Arithmetic Problems

The decision making process is the individual steps in choosing an appropriate alternative choice from the various alternatives available to solve the problem. The purpose of this study is to describe the decision making process of high school students with high mathematical abilities in solving social arithmetic problems. The research approach used in this study is qualitative research. While the type of research is a qualitative descriptive study. The process of collecting data uses several instruments consisting of mathematics ability tests, social arithmetic problem solving tests, and interview guidelines. This research was conducted on 11th grade high school students in one of the state high schools in Sidoarjo. The subjects of this study consisted of one student with high mathematical abilities. The data collection method in this study began with the provision of mathematics ability tests for all students followed by selecting one subject with high mathematical ability through several considerations. The next step, the subject is given a problem solving test and interviewed to get the decision making process carried out by the subject. The results showed that students with high mathematical abilities carried out a series of activities in the stages of the decision making process, namely define the decision, understand the context, identify the options, prioritise the options, evaluate the consequences, review the decisions, and take actions

Usability of Immersive Technology for Education and Training of Firefighters in Brazil

Practice-based training in realistic environments is important in preparing a firefighter. Live infrastructure simulation training with real fire and smoke, using real buildings and equipment, has been the only practice-based training format accepted and available, but sometimes with limitations. The integration of virtual re-ality and artificial intelligence can provide interaction for different fields of application and possibilities for complementary training. However, there is hesitation, often in doubt as to the real, often in fire situations. This article investigates how immersive VR supports cognitive processes and affects fidelity in firefighter training. The data were collected from 91 participating firefighters, including instructor officers and firefight-ers from Paraná and other states, participated in various scenarios, and real and virtual firefighting simula-tions. With tactile feedback, students used PPE for daily use at work and other equipment such as hoses and nozzles. In this bias, the usability of the immersive technology was compared with the real fire simulation performed in training containers. The results showed that tacit and explicit knowledge compared through VR can be shared correctly within the Fire Department facilities

Individual risk profiling for portable devices using a neural network to process the cognitive reactions and the emotional responses to a multivariate situational risk assessment

In this paper, we are presenting a novel method and system for neuropsychological performance testing that can establish a link between cognition and emotion. It comprises a portable device used to interact with a cloud service which stores user information under username and is logged into by the user through the portable device; the user information is directly captured through the device and is processed by artificial neural network; and this tridimensional information comprises user cognitive reactions, user emotional responses and user chronometrics. The multivariate situational risk assessment is used to evaluate the performance of the subject by capturing the 3 dimensions of each reaction to a series of 30 dichotomous questions describing various situations of daily life and challenging the user's knowledge, values, ethics, and principles. In industrial application, the timing of this assessment will depend on the user's need to obtain a service from a provider such as opening a bank account, getting a mortgage or an insurance policy, authenticating clearance at work or securing online payments

Exploring decision-making prospective mathematics teacher in solving geometric proof problems

Facing the current digital era, correct and accurate decisions are needed to deal with the problems. This research aimed to explore the decision-making abilities of prospective mathematics teacher students in solving geometric proof problems. This research was a qualitative descriptive study with research subjects 3 out of 32 students of the 2nd semester Mathematics Education study program. The research instrument is the researcher himself, who is assisted with geometric proof problem tests and interview guidelines. Data analysis was including reduction, presentation, and conclusion. The validity of the research data was tested using methods triangulation. The research results show that subjects with a proof ability of K2 can build and clarify geometric concepts/principles and can assess the reasonableness of ideas even though the subject feels unsure about their choice. Subjects with a proof ability of K3 can build and clarify geometric concept/principle ideas but cannot assess the reasonableness of proof ideas. Subjects with a proof ability of K4 can build ideas of geometric concepts/principles, can clarify even though they are incomplete, and cannot assess the reasonableness of proof ideas. Students need to be equipped with decision-making skills in solving proof problems as preparation to become mathematics teachers in the future

Proxy Tasks and Subjective Measures Can Be Misleading in Evaluating Explainable AI Systems

Explainable artificially intelligent (XAI) systems form part of sociotechnical systems, e.g., human+AI teams tasked with making decisions. Yet, current XAI systems are rarely evaluated by measuring the performance of human+AI teams on actual decision-making tasks. We conducted two online experiments and one in-person think-aloud study to evaluate two currently common techniques for evaluating XAI systems: (1) using proxy, artificial tasks such as how well humans predict the AI's decision from the given explanations, and (2) using subjective measures of trust and preference as predictors of actual performance. The results of our experiments demonstrate that evaluations with proxy tasks did not predict the results of the evaluations with the actual decision-making tasks. Further, the subjective measures on evaluations with actual decision-making tasks did not predict the objective performance on those same tasks. Our results suggest that by employing misleading evaluation methods, our field may be inadvertently slowing its progress toward developing human+AI teams that can reliably perform better than humans or AIs alone

TEACHING HIGHER ORDER THINKING SKILLS IN MATHEMATICS CLASSROOMS: GENDER DIFFERENCES

This case study aims to explore how male and female Indonesian mathematics teachers enact decision-making processes in teaching High-Order Thinking Skills (HOTS). Non-random purposive sampling technique was used to select the participants. The participants involved in this study were two Indonesian mathematics teachers who teach HOTS in their classrooms. The participants were chosen from 87 Indonesian mathematics teachers in 23 secondary schools in East Java, Indonesia, who were invited to our survey and confirmed that they taught HOTS and underwent classroom observation. Data were collected from classroom teaching and interview sessions. The data of classroom teaching consisted of a video-audio recording of two meetings and field notes of observation. In the interview session, we recorded the teachers’ responses during semi-structured interviews. We coded and explained our interpretation for each code. We also conducted investigator triangulation by comparing coding and interpretation made by two researchers and discussing them to find the best representation of the meaning of the data. Our findings indicate that both male and female teachers performed four steps of decision making, consisting of giving problems, asking students to solve, checking, and obtaining new ideas. The difference of male and female teachers’ decision-making process is observed in the process of giving problem (non-contextual vs contextual), how they ask students to solve and check the solution (individual vs group), and the criteria of the new idea of problem-solving (correct vs the best solution). The study findings can be a catalyst for enacting decision-making steps in teaching HOTS. Also, these can be a reflective practice for mathematics teachers to improve their teaching quality