An Artificial Intelligence Based Virtual Assistant Using Conversational Agents

Conversational agents are natural language interaction interfaces designed to simulate human conversations using Artificial Intelligence (AI). This paper explores current applications of these systems and raises the lack of their availability in education. To address this problem, we provide the design of a conversational agent system, which is efficient and time-saving in assisting student/college seeking information about curriculum, scheduling, teachers, classroom location at any time 24/7/365. To verify and validate the design and implementation of our proposed model, a pilot project has been set up involving three leading academic institutions. This platform is designed and developed to help universities provide continuous and instant assistance to their student, staff, and faculty communities.

Knowledge-Enhanced Conversational Agents

Humanity has fantasized about artificial intelligence tools able to discuss with human beings fluently for decades.Numerous efforts have been proposed ranging from ELIZA to the modern vocal assistants.Despite the large interest in this research and innovation field,there is a lack of common understanding on the concept of conversational agents and general over expectations that hide the current limitations of existing solutions.This work proposes a literature review on the subject with a focus on the most promising type of conversational agents that are powered on top of knowledge bases and that can offer the ground knowledge to hold conversation autonomously on different topics.We describe a conceptual architecture to define the knowledge-enhanced conversational agents and investigate different domains of applications.We conclude this work by listing some promising research pathways for future work.

Argumentative Conversational Agents for Online Discussions

Artificial Intelligence is revolutionising our communication practices and the ways in which we interact with each other. This revolution does not only impact how we communicate, but it affects the nature of the partners with whom we communicate. Online discussion platforms now allow humans to communicate with artificial agents in the form of socialbots. Such agents have the potential to moderate online discussions and even manipulate and alter public opinions. In this paper, we propose to study this phenomenon using a constructed large-scale agent platform. At the heart of the platform lies an artificial agent that can moderate online discussions using argumentative messages. We investigate the influence of the agent on the evolution of an online debate involving human participants. The agent will dynamically react to their messages by moderating, supporting, or attacking their stances. We conducted two experiments to evaluate the platform while looking at the effects of the conversational agent. The first experiment is a large-scale discussion with 1076 citizens from Afghanistan discussing urban policy-making in the city of Kabul. The goal of the experiment was to increase the citizen involvement in implementing Sustainable Development Goals. The second experiment is a small-scale debate between a group of 16 students about globalisation and taxation in Myanmar. In the first experiment, we found that the agent improved the responsiveness of the participants and increased the number of identified ideas and issues. In the second experiment, we found that the agent polarised the debate by reinforcing the initial stances of the participant.

Language Assessment Feedback Towards Pedagogical Conversational Agent

Continuous development of technology provides an opportunity to incorporate feedback in online assessments.The mode of online instruction during the pandemic was the most significant survival change.Technology enabled every teacher and student to enter a virtual classroom to make sense of education.Feedback is part of language instruction and is a powerful key to improving students’learning performance.Feedback plays an influential and crucial role in teaching and learning.Feedback is an invaluable,ultimate learning tool for learners that aids them in not committing the same error again and creates impetus.Thus,knowing about formative exam feedback is students’right because quality feedback allures them.Given students’eagerness,providing feedback is considered a good practice to be followed by all the teaching faculty.Apropos of online feedback,the present study attempts to study how pedagogical agents provide online feedback in language assessments.The study also considers the characteristics of pedagogical conversational agents that are suitable for providing feedback in online language assessment.Simply put,the study encapsulates that screen agents play an essential role in students’motivation and acceptability of learning through feedback.

Artificial Intelligence-Enabled Chatbots in Mental Health:A Systematic Review

Clinical applications of Artificial Intelligence(AI)for mental health care have experienced a meteoric rise in the past few years.AIenabled chatbot software and applications have been administering significant medical treatments that were previously only available from experienced and competent healthcare professionals.Such initiatives,which range from“virtual psychiatrists”to“social robots”in mental health,strive to improve nursing performance and cost management,as well as meeting the mental health needs of vulnerable and underserved populations.Nevertheless,there is still a substantial gap between recent progress in AI mental health and the widespread use of these solutions by healthcare practitioners in clinical settings.Furthermore,treatments are frequently developed without clear ethical concerns.While AI-enabled solutions show promise in the realm of mental health,further research is needed to address the ethical and social aspects of these technologies,as well as to establish efficient research and medical practices in this innovative sector.Moreover,the current relevant literature still lacks a formal and objective review that specifically focuses on research questions from both developers and psychiatrists in AI-enabled chatbotpsychologists development.Taking into account all the problems outlined in this study,we conducted a systematic review of AI-enabled chatbots in mental healthcare that could cover some issues concerning psychotherapy and artificial intelligence.In this systematic review,we put five research questions related to technologies in chatbot development,psychological disorders that can be treated by using chatbots,types of therapies that are enabled in chatbots,machine learning models and techniques in chatbot psychologists,as well as ethical challenges.

Empathic Responses of Behavioral-Synchronization in Human-Agent Interaction

Artificial entities,such as virtual agents,have become more pervasive.Their long-term presence among humans requires the virtual agent’s ability to express appropriate emotions to elicit the necessary empathy from the users.Affective empathy involves behavioral mimicry,a synchronized co-movement between dyadic pairs.However,the characteristics of such synchrony between humans and virtual agents remain unclear in empathic interactions.Our study evaluates the participant’s behavioral synchronization when a virtual agent exhibits an emotional expression congruent with the emotional context through facial expressions,behavioral gestures,and voice.Participants viewed an emotion-eliciting video stimulus(negative or positive)with a virtual agent.The participants then conversed with the virtual agent about the video,such as how the participant felt about the content.The virtual agent expressed emotions congruent with the video or neutral emotion during the dialog.The participants’facial expressions,such as the facial expressive intensity and facial muscle movement,were measured during the dialog using a camera.The results showed the participants’significant behavioral synchronization(i.e.,cosine similarity≥.05)in both the negative and positive emotion conditions,evident in the participant’s facial mimicry with the virtual agent.Additionally,the participants’facial expressions,both movement and intensity,were significantly stronger in the emotional virtual agent than in the neutral virtual agent.In particular,we found that the facial muscle intensity of AU45(Blink)is an effective index to assess the participant’s synchronization that differs by the individual’s empathic capability(low,mid,high).Based on the results,we suggest an appraisal criterion to provide empirical conditions to validate empathic interaction based on the facial expression measures.

Luminescence properties of composite material Sr_(2)MgSi_(2)O_(7):Eu^(2+),Dy^(3+)/light conversion agent with multilayer structure

In order to improve the red luminescent properties,Sr_(2)MgSi_(2)O_(7):Eu^(2+),Dy^(3+)was selected as a blue persistent luminescent donor phosphor,while light conversion agent was utilized to tune the persistent luminescent spectra from blue to red.Composite red luminescent material Sr_(2)MgSi_(2)O_(7):Eu^(2+),Dy^(3+)/light conversion agent(SMED/LCA)was fabricated with light conversion agent and Sr_(2)MgSi_(2)O_(7):Eu^(2+),Dy^(3+)at a certain mass ratio.SiO_(2)(Al2 O_(3) or MgF2)were coated on the surface of SMED/LCA through heterogeneous deposition method.The structural and optical characteristics of the resulting samples were launched in terms of X-ray diffraction and emission spectrum as well as afterglow brightness.The results demonstrate that the emission spectrum exhibits two emission bands,and the peaks are located at around 470 and 615 nm.SiO_(2),Al_(2)O_(3) and MgF_(2) are coated on the surface of SMED/LCA like a protective shell to maintain its stability and luminescent properties,the afterglow initial brightness is still up to 0.37 cd/m^(2) and the afterglow color purity calculated from CIE color coordinates is basically unchanged.

Effect of light conversion agent on luminous properties of a new down-converting material SrAl_2O_4:Eu^(2+),Dy^(3+)/light conversion agent

A new luminous material SrAl2O4：Eu^2＋,Dy^3＋/light conversion agent that can emit red light in the darkness after being excited was fabricated by combining light conversion agent on to SrAl2O4：Eu^2＋,Dy^3＋ particles through YsiX3.The morphology of the luminous materials was analyzed by scan electron microscopy（SEM）.The emission behavior was evaluated by fluorescence spectrophotometric analysis and the results demonstrated that the emission spectra of samples had a redshift compared to SrAl2O4：Eu^2＋,Dy^3＋ and the emission intensity rose dramatically at first and then decreased when the ratio of light conversion agent doping was over 1.4 wt.%.And the emission color of SrAl2O4：Eu^2＋,Dy^3＋/light conversion agent was tuned from green（SrAl2O4：Eu^2＋,Dy^3＋）to orange-red.Furthermore,the afterglow property was also investigated,and the results indicated that the afterglow brightness reached 6.5 cd/m^2,and as the light conversion agent concentration increased the brightness intensity decreased.

Luminescence properties of SrB_4_O_7:Sm^(2+) for light conversion agent

A deep red-emitting SrB407：Sm^2＋ phosphor for light conversion agent was synthesized by the conventional solid-state reaction. X-ray powder diffraction （XRD） analysis confirmed the phase formation of SrB4OT：Sm^2＋ materials. Results of luminescence properties showed that the phosphor could be efficiently excited by the UV-vis light region from 250-500 nm, and it exhibited deep red （685 nm） emis- sion corresponding to ^5D0→^7F0 transition of Sm^2＋. The critical quenching concentration of Sm^2＋ in SrB407：Sm^2＋ phosphor was about 0.05, and the corresponding concentration quenching mechanism was verified to be the dipole-dipole interaction according to the Dexter＇s theory. The decay times had few alterations with different concentrations in SrB4OT：xZm^2＋ phosphor.