Dynamically predicting comprehension difficulties through physiological data and intelligent wearables.

Comprehending digital content written in natural language online is vital for many aspects of life, including learning, professional tasks, and decision-making. However, facing comprehension difficulties can have negative consequences for learning outcomes, critical thinking skills, decision-making, error rate, and productivity. This paper introduces an innovative approach to predict comprehension difficulties at the local content level (e.

Challenges and efforts in managing AI trustworthiness risks: a state of knowledge.

This paper addresses the critical gaps in existing AI risk management frameworks, emphasizing the neglect of human factors and the absence of metrics for socially related or human threats. Drawing from insights provided by NIST AI RFM and ENISA, the research underscores the need for understanding the limitations of human-AI interaction and the development of ethical and social measurements. The paper explores various dimensions of trustworthiness, covering legislation, AI cyber threat intelligence, and characteristics of AI adversaries.

Empowering Preventive Care with Chatbot.

Chatbots have become increasingly popular in the healthcare industry. In the area of preventive care, chatbots can provide personalized and timely solutions that aid individuals in maintaining their well-being and forestalling the development of chronic conditions. This paper presents , a chatbot designed specifically for preventive care, that offers information, advice, and monitoring to patients who are undergoing home treatment, providing a cost-effective, personalized, and engaging solution.

KeyRecs: A keystroke dynamics and typing pattern recognition dataset.

Keystroke dynamics can valuably contribute to the development of intelligent authentication systems by enabling a single and continuous authentication process in a passive and non-intrusive manner by continuously verifying a user's identity. This work describes the KeyRecs dataset, which contains fixed-text and free-text samples of user typing behavior and demographic information of the participants age, gender, handedness, and nationality. The keystroke data was obtained from 99 participants of various nationalities who completed password retype and transcription exercises.

Knowledge and Beliefs about Herb/Supplement Consumption and Herb/Supplement-Drug Interactions among the General Population, including Healthcare Professionals and Pharmacists: A Systematic Review and Guidelines for a Smart Decision System.

The increased consumption of a variety of herbs/supplements has been raising serious health concerns. Owing to an inadequate understanding of herb/supplement-drug interactions, the simultaneous consumption of these products may result in deleterious effects and, in extreme cases, even fatal outcomes. This systematic review is aimed at understanding the knowledge and beliefs about the consumption of herbs/supplements and herb/drug-supplement interactions (HDIs).

Holistic Security and Safety for Factories of the Future.

The accelerating transition of traditional industrial processes towards fully automated and intelligent manufacturing is being witnessed in almost all segments. This major adoption of enhanced technology and digitization processes has been originally embraced by the Factories of the Future and Industry 4.0 initiatives.

Influence of Features on Accuracy of Anomaly Detection for an Energy Trading System.

The biggest problem with conventional anomaly signal detection using features was that it was difficult to use it in real time and it requires processing of network signals. Furthermore, analyzing network signals in real-time required vast amounts of processing for each signal, as each protocol contained various pieces of information. This paper suggests anomaly detection by analyzing the relationship among each feature to the anomaly detection model.

Adaptive Portfolio Optimization for Multiple Electricity Markets Participation.

The increase of distributed energy resources, mainly based on renewable sources, requires new solutions that are able to deal with this type of resources' particular characteristics (namely, the renewable energy sources intermittent nature). The smart grid concept is increasing its consensus as the most suitable solution to facilitate the small players' participation in electric power negotiations while improving energy efficiency. The opportunity for players' participation in multiple energy negotiation environments (smart grid negotiation in addition to the already implemented market types, such as day-ahead spot markets, balancing markets, intraday negotiations, bilateral contracts, forward and futures negotiations, and among other) requires players to take suitable decisions on whether to, and how to participate in each market type.