Welcome to MTI—A New Open Access Journal Dealing with Blue Sky Research and Future Trends in Multimodal Technologies and Interaction

In this era of massive use of computers and other computational devices (e.g., low-cost wearable sensors, smartphones, other smart devices, etc.), the nature of digital data is becoming more complex and heterogeneous

Open-domain neural conversational agents: The step towards artificial general intelligence

Development of conversational agents started half century ago and since then it has transformed into a technology that is accessible in various aspects in everyday life. This paper presents a survey current state-of-the-art in the open domain neural conversational agent research and future research directions towards Artificial General Intelligence (AGI) creation. In order to create a conversational agent which is able to pass the Turing Test, numerous research efforts are focused on open-domain dialogue system. This paper will present latest research in domain of Neural Network reasoning and logical association, sentiment analysis and real-time learning approaches applied to open domain neural conversational agents. As an effort to provide future research directions, current cuttingedge approaches applied to open domain neural conversational agents, current cutting-edge approaches in rationale generation and the state-of-the-art research directions in alternative training methods will be discussed in this paper

Shaping taste

A growing body of empirical research on the crossmodal correspondences, that is, on the associations between abstract features that we share across the senses, demonstrates that people associate (gustatory) tastes and visual shape features in a non-random manner. Such abstract features of shapes (e.g., symmetry or curvature) can, under certain circumstances, guide our taste expectations and even taste experiences. Here, it is argued that the different dimensions of the shapes associated with our food experiences, such as the tableware (what some have called tablescapes), the way in which we plate the food, and the food itself, may all impact the expected and experienced taste of food. Further, we discuss how food experience designers (think chefs, culinary artists, and food companies) may capitalize on these recently-discovered correspondences when designing dining experiences and present directions for future researc

Perceptions and Responsiveness to Intimacy with Robots; A User Evaluation

In human-robot interactions research it is significant to question what measures humans will take to contest the challenges and what will become of them. Levy hypothesizes that robots will stimulate human senses with their many capabilities and humans will accept them as intimate companions because the human perception of intimacy will transform to accommodate various nuances. However, the question remains, how much humans understand and accept intimacies with robots. We argue that perceptions of human-robot interactions (HRI) and intimate interactions with robots have a certain impact on how individuals comprehend intimacies with robots. Long term contact with robots, in terms of robotic technology and conversations, will change our views and practices regarding intimacy with robots. Our study revealed that lack of awareness of the potentials of future AI robots has created a fear; fear of losing both tangible, intangible, and the sense of dominance. Yet, our participants’ intimate interactions with robots produced varying degree of responses that, we believe are revealing another scope of human-robot interactions

Lovotics: Human - Robot Love and Sex Relationships

Intimate relationships, such as love and sex, between human and machines, especially robots, has been one of the topics in science fiction. However, this topic has never been treated in the academic area until recently. The topic was first raised and discussed by David Levy in his book titled “Love and Sex with Robotics” published in 2007. As a result, the subject of human-robot romantic and intimate relationships rapidly developed into an academic research discipline in its own right. Since then, researchers have come up with many implementations of robot companions like sex robots, emotional robots, humanoid robots, and artificial intelligent systems that can simulate human emotions. This book chapter presents a summary of significant activity in this field during the recent years, predicts how the field is likely to develop, and its ethical and legal background. We also discuss our research in physical devices for human-robot love and sex communication

Robots to the Rescue: A Review of Studies on Differential Medical Diagnosis Employing Ontology-Based Chat Bot Technology

Access to medical care is a global issue. Technology-aided approaches have been applied in addressing this. Interventions have however not focused on medical diagnosis as a fully automated procedure and available applications employ mainly text-based inputs rather than conversation in natural language. We explored the utility of ontology-based chatbot technology for the design of intelligent agents for medical diagnosis through a systematic review of the most recent related literature. English articles published in 2011-2016 returned 233 hits which yielded 11 relevant articles after a 3-stage screening. Findings showed that the creation of expert systems had been the focus of many the studies which utilize the physician-system-patient framework with system training based mostly on expert knowledge for designing web- or mobile phone-based applications that serve assistive purposes. Findings further indicated gaps in the design and evaluation of more effective systems deployable as standalone applications, for example, on an embodied robotic system. The need for technology supporting the physical examination part of diagnosis, connection to data sources on patients’ vitals and medical history are also indicated in addition to the need for more qualitative work on natural language-based interaction. The system should be one that is continuously learning. Future works should also be directed towards the building of more robust knowledge base as well as evaluation of theory-based diagnostic methodological option

Thermal Sweet Taste Machine for Multisensory Internet

This paper presents a new taste interface for multisensory communication called "Thermal Sweet Taste Machine". We developed this interface in order to create sweet sensations, by manipulating the temperature on the tongue, without using chemicals. This device device changes the temperature on the surface of the tongue (from 20°C to 40°C) within a short period of time using a computer controlled circuit. Our preliminary user studies suggested that this device would be effective in two ways; producing the sweet sensations without the aid of chemicals, and enhancing the sweetness of the food and drinks. Here we discuss our concept, development of the interface, and some preliminary studies that has been carried out. We believe our technology would enhance the experiences and capabilities in future multisensory communication in different disciplines such as Human-Computer Interaction, human robot interactions, gaming and interacting with artificial agents

Trends in Computer-Aided Diagnosis Using Deep 2 Learning Techniques: A Review of Recent Studies on 3 Algorithm Development 4

With recent focus on deep neural network architectures for development of algorithms for computer-aided diagnosis (CAD), we provide a review of studies within the last 3 years (2015-2017) reported in selected top journals and conferences. 29 studies that met our inclusion criteria were reviewed to identify trends in this field and to inform future development. Studies have focused mostly on cancer-related diseases within internal medicine while diseases within gender-/age-focused fields like gynaecology/pediatrics have not received much focus. All reviewed studies employed image datasets, mostly sourced from publicly available databases (55.2%) and few based on data from human subjects (31%) and non-medical datasets (13.8%), while CNN architecture was employed in most (70%) of the studies. Confirmation of the effect of data manipulation on quality of output and adoption of multi-class rather than binary classification also require more focus. Future studies should leverage collaborations with medical experts to aid future with actual clinical testing with reporting based on some generally applicable index to enable comparison. Our next steps on plans for CAD development for osteoarthritis (OA), with plans to consider multi-class classification and comparison across deep learning approaches and unsupervised architectures were also highlighted

Side channel attacks on smart home systems: A short overview

This paper provides an overview on side-channel attacks with emphasis on vulnerabilities in the smart home. Smart homes are enabled by the latest developments in sensors, communication technologies, internet protocols, and cloud services. The goal of a smart home is to have smart household devices collaborate without involvement of residents to deliver the variety of services needed for a higher quality of life. However, security and privacy challenges of smart homes have to be overcome in order to fully realize the smart home. Side channel attacks assume data is always leaking, and leakage of data from a smart home reveals sensitive information. This paper starts by reviewing side-channel attack categories, then it gives an overview on recent attack studies on different layers of a smart home and their malicious goals

A probability based hybrid energy-efficient privacy preserving scheme to encounter with wireless traffic snooping in smart home

Application of pervasive computing devices in smart homes are rising sharply and due to this matter, demands for efficient privacy protection are increasing urgently. Possibility of interference in wireless networks is proved by previous work. Adversaries can discover contextual information because of traffic monitoring and classifying transmitters based on their radio fingerprints while data packets are encrypted or content is not important for attackers. To conceal communication patterns various approaches have been investigated. They are mainly based on injection of dummy packets into the network traffic and adding delay to transmission time. In this paper, we introduce a hybrid energy-efficient privacy preserving scheme for generating and sending dummy packets through a decision-making algorithm which works based on probability to maximize confusion of attacker in clarifying the real pattern of network traffi