As countermeasure for preventing dementia of aging population, coimagination method has been developed. The coimagination method helps participants in utilizing brain cognitive functions of maintaining recent episodic memorization, retention and recall by the process of conversations. Hence, the risk of older adults in getting into mild cognitive impairment (MCI), which is a previous stage of dementia caused by disuse of brain cognitive functions, will decline. However, we observed situations of some older adults that recent episodic memory functions were not activated as expected. Such situations are older adults who talk about knowledge rather than episodic memories or older adults who talk about past experiences rather than recent experiences. Therefore, a novel coimagination program named coimagination method with expedition was developed to solve these situations. By adding expedition in a sightseeing area before the coimagination method, older adults have the opportunity to find topic of conversations through expedition. During conversation supported by the coimagination method, older adults are expected to recall their episodic memories in expedition and talk about it. The purpose of this research is to verify the effect of the coimagination method with expedition in older adults, by comparing mental time of older adults in the coimagination methods with and without expedition. Firstly, we estimate the mental time of older adults by analyzing their utterances during conversations supported by both coimagination methods. The past, present and future mental times of participants are enumerated in percentage. Secondly, we study the mental time travelling of participants during conversations. Finally, we study the transition points of mental time to find tendency of participants to talk about recent experiences. In this research, the analytical results validate the effectiveness of helping older adults to talk about recent episodic memories during conversation supported by the coimagination method with expedition compared to the coimagination method.

This paper proposes a novel method to estimate sleep stage in real-time with a non-contact device. The proposed method employs the trigonometric function regression model to estimate prospective heart rate from the partially obtained heart rate and calculates the sleep stage from the estimated heart rate. This paper conducts the subject experiment and it is revealed that the proposed method enables to estimate the sleep stage in real-time, in particular the proposed method has the equivalent estimation accuracy as the previous method that estimates the sleep stage according to the entire heart rate during sleeping.

Due to the advances in medical science, increasing health consciousness, improved quality of food, the average human life span has increased to a great extent. On the other hand, stresses of modern life, overwork and less sleep, increased usage of digital devices and internet, less exercise, are leading us to poor quality of life. Elderly people are more vulnerable to reduced life quality due to deterioration of both physical and mental health. People at any age need to maintain a minimum level of wellbeing to pursue his or her daily activities to lead a fulfilling life. Thus the need of assessing and restoring wellness is very important. Fortunately the progress of information and communication technologies provide use sensor devices and computing platform to feel, monitor and restore the wellness. In this work, a study has been done to define and determine wellness related to daily activities data obtained from various sensors and provide recommendation to the user regarding improvement of life style to achieve wellness. A small-scale experiment has been done using a simple lifelog device. The daily activities data including walking steps, sleep time, inactive period, calories burned are collected from 8 subjects. In addition food intake, eating times, cell phone usage, messaging time, time of interaction with other people and solo time are also manually collected. The correlation of physical activities (walking time, exercise time), mental activities (cell phone usage, study time, interaction with friends) and sleep patterns are studied. A simple parameter Tiredness Factor has been proposed to determine wellness and a recommendation system for improving wellness has been developed. Questionnaire from the subjects about the personal feelings of wellness has been noted and used to evaluate our proposal.

Numerous studies have identified differences between left-handed and right-handed people, especially in the fields of psychology and neuroscience. Using a social media setting, this paper presents a data-driven approach to explore whether a person's handedness can be identified given his or her writing, and shows handedness characteristics that can be inferred from language.

Social media is increasingly populated with bots. To protect the authenticity of the user, experience machine learning algorithms are used to detect these bots. Ethical dimensions of these methods have not been thoroughly considered yet. Taking histogram analysis of Twitter users' profile images as example, the paper demonstrates the trade-offs of accuracy, transparency, and robustness. Because there is no general optimum in ethical considerations, these dimensions form a "devil's triangle".

It is not clear to what the projects of creating an artificial intelligence(AI) that does ethics, is moral, or makes moral judgments amounts. In this paper we discuss some of the extant metaethical theories and debates in moral philosophy by which such projects should be informed, specifically focusing on the project of creating an AI that makes moral judgments. We argue that the scope and aims of that project depend a great deal on antecedent metaethical commitments. Metaethics, therefore, plays the role of an Archimedean fulcrum in this context, very much like the Archimedean role that it is often taken to take in context of normative ethics.

Here ought does require able--computationally and indeed logically intractable systems The question of Robot Ethics is difficult to resolve not because such as Asimov's laws are excluded (Myers, 2010). of the nature of Robots but because of the nature of What makes moral reasoning about intelligent artefacts Ethics. As with all normative considerations, robot ethics requires different from moral reasoning about natural entities is that that we decide what "really" matters--our most fundamental our obligations can be met not only through constructing the priorities. Are we more obliged to our biological socio-ethical system but also through specifications of the kin or to those with whom we share ideas? Do we value the artefacts. This is the definition of an artefact.

We discuss philosophical and ethical issues that arise from a dialogue system intended to portray a real person, using recordings of the person together with a machine agent that selects recordings during a synchronous conversation with a user. System output may count as actions of the speaker if the speaker intends to communicate with users and the outputs represent what the speaker would have chosen to say in context; in such cases the system can justifiably be said to be holding a conversation that is offset in time. The autonomous agent may at times misrepresent the speaker's intentions, and such failures are analogous to good-faith misunderstandings. The user may or may not need to be informed that the speaker is not organically present, depending on the application.

Dialog between drivers and speech-based robot vehicle interfaces can be used as an instrument to find out what drivers might be concerned, confused or curious about in driving simulator studies. Eliciting ongoing conversation with drivers about topics that go beyond navigation, control of entertainment systems, or other traditional driving related tasks is important to getting drivers to engage with the activity in an open-ended fashion. In a structured improvisational Wizard of Oz study that took place in a highly immersive driving simulator, we engaged participant drivers (N=6) in an autonomous driving course where the vehicle spoke to drivers using computer-generated natural language speech. First, using microanalyses of drivers’ responses to the car’s utterances, we identify a set of topics that are expected and treated as appropriate by the participants in our study. Second, we identify a set of topics and conversational strategies that are treated as inappropriate. Third, we show that it is just these unexpected, inappropriate utterances that eventually increase users’ trust into the system, make them more at ease, and raise the system’s acceptability as a communication partner.

Based on the development of several different HRI scenarios using different robots, we have been establishing the SERA ecosystem. SERA is composed of both a model and tools for integrating an AI agent with a robotic embodiment, in humanrobot interaction scenarios. We present the model, and several of the reusable tools that were developed, namely Thalamus, Skene and Nutty Tracks. Finally we exemplify how such tools and model have been used and integrated in five different HRI scenarios using the NAO, Keepon and EMYS robots. Figure 1: Our methodology as an intersection of CGI animation, Human-robot interaction (HRI) systems are spreading as a IVA and robotics techniques.