An Agent-Based Model for Refined Cognitive Load and Reading Performance in Reading Companion Robot

This paper presents the importance of modeling dynamical behaviors of human cognitive states that serves as a core foundation in creating intelligent and responsive systems. It discusses in detail the development of a dynamical model of cognitive load and reading performance which acts as the central component of creating a reading companion robot. Simulations results show realistic behaviour patterns that adhere to the literature. Finally, the results produced from an automated verification approach to validate the internal correctness of the proposed model using Temporal Trace Language (TTL) are shown

An Agent-Based Model for Refined Cognitive Load and Reading Performance in Reading Companion Robot

This paper presents the importance of modeling dynamical behaviors of human cognitive states that serves as a core foundation in creating intelligent and responsive systems.It discusses in detail the development of a dynamical model of cognitive load and reading performance which acts as the central component of creating a reading companion robot.Simulations results show realistic behaviour patterns that adhere to the literature. Finally, the results produced from an automated verification approach to validate the internal correctness of the proposed model using Temporal Trace Language (TTL) are shown

Designing an Intelligent System to Support the Elderly

Loneliness among older adults represents a significant societal problem and an important application domain for affective computing. 40% of older adults experience loneliness, which has been linked with various health problems, including an increased risk of cardiovascular disease and death ,by using android studio environment the smart android application built to measure and scale the loneliness level, the Results shows the effects on elderly that uses the application this research built which is InTouch, helps them reduce loneliness and it’s risks upon older people health, direct and indirect strategies directly by sending message with the knowledge of the users and indirectly by sending sms message to their chosen ones (their close friends           list)

Designing an Intelligent System to Support the Elderly

Loneliness among older adults represents a significant societal problem and an important application domain for affective computing. 40% of older adults experience loneliness, which has been linked with various health problems, including an increased risk of cardiovascular disease and death ,by using android studio environment the smart android application built to measure and scale the loneliness level, the Results shows the effects on elderly that uses the application this research built which is InTouch, helps them reduce loneliness and it’s risks upon older people health, direct and indirect strategies directly by sending message with the knowledge of the users and indirectly by sending sms message to their chosen ones (their close friends           list)

An Agent-Based Modeling for a Reader’s Cognitive Load and Performance

Reading performance and cognitive load play an important role to facilitate learners to learn, memorize, and understand a novel piece of information.The cognitive demands of the reading tasks for solving complicated problems, when using poor learning materials, or in a distraction condition such as noise or interruptions, can have a significant impact on reading performance. These conditions can impair the reading performance, and may thus deter effective learning experience. In this paper, an agent computational model is proposed. Different types of relations between extraneous, intrinsic, and germane loads were used to analyze the reader’s performance over time. Simulation experiments under different conditions and parameters setting showed that the model is able to produce realistic behaviour when tested on different types of personalities and conditions. Through mathematical analysis, the equilibria of the model was determined

An agent-based model for refined cognitive load and reading performance in reading companion robot

This paper presents the importance of modeling dynamical behaviors of human cognitive states that serves as a core foundation in creating intelligent and responsive systems. It discusses in detail the development of a dynamical model of cognitive load and reading performance which acts as the central component of creating a reading companion robot. Simulations results show realistic behaviour patterns that adhere to the literature. Finally, the results produced from an automated verification approach to validate the internal correctness of the proposed model using Temporal Trace Language (TTL) are shown

An ambient agent model for a reading companion robot

This paper presents the development of an ambient agent model (software agent) as an initial step to develop a reading companion robot to sup-port reading performance.This ambient agent model provides detailed knowledge (human functioning) about reader’s dynamics states.Based on this human functioning knowledge, a robot will be able to reason about reader’s conditions and provides an appropriate support.Several simulation traces have been generated to illustrate the functioning of the proposed model. Furthermore, the model was verified using an automated trace analysis and the results have shown that the ambient agent model satisfies a number of related properties as presented in related literatures

On modelling cognitive load during reading task

One of the main challenges that hugely effect readers’ performance is cognitive load.It plays a pivotal role to facilitate readers to learn, memorize, and digest a piece of novel information. However, cognitive load can also have insignificant impacts on reading task when the cognitive demands of the reading task when to solve a complex problem. This article proposed a computational model of cognitive load during reading task, based on Cognitive Load theory, to get deep understandings on the dynamics of cognitive load and how the different types of load like intrinsic, extraneous and germane load are affecting the level of cognitive load.A number of simulation experiments were conducted and the results showed that the model is able to produce realistic behaviours under different personalities and conditions. Furthermore, an automated verification was implemented to evaluate the mode

Formal Specifications and Analysis of an Agent-Based Model for Cognitive Aspects of Fear of Crime

This paper presents a cognitive agent model of fear of crime. The proposed model takes personality, environment, and perception of several events as input and calculates internal factors related to cognitive fear of crime, such as the belief about safety, community trust and likelihood of crime activities, and how they affect individual fear of crime. Simulation results suggest that community level of fear of crime and trust may emerge as the outcome of individuals’ reaction towards perception of crime activities related to their exogenous properties. In addition, a formal approach is put forward to evaluate the behaviours of the proposed model by means of formal techniques namely; mathematical analysis, parameter evaluation, and automated logical verification. The first and second approaches analyse the equilibria conditions and follow by automatically checking a number of expected properties as depicted in the literature. One of the major contributions of this model is the possibility that an analytical engine could be further developed to support community wellbeing

Robust Automatic Modulation Classification Using Convolutional Deep Neural Network Based on Scalogram Information

This study proposed a two-stage method, which combines a convolutional neural network (CNN) with the continuous wavelet transform (CWT) for multiclass modulation classification. The modulation signals’ time-frequency information was first extracted using CWT as a data source. The convolutional neural network was fed input from 2D pictures. The second step included feeding the proposed algorithm the 2D time-frequency information it had obtained in order to classify the different kinds of modulations. Six different types of modulations, including amplitude-shift keying (ASK), phase-shift keying (PSK), frequency-shift keying (FSK), quadrature amplitude-shift keying (QASK), quadrature phase-shift keying (QPSK), and quadrature frequency-shift keying (QFSK), are automatically recognized using a new digital modulation classification model between 0 and 25 dB SNRs. Modulation types are used in satellite communication, underwater communication, and military communication. In comparison with earlier research, the recommended convolutional neural network learning model performs better in the presence of varying noise levels