Feeling Communication : Social and Physical Interactive Communication and Entertainment

この論文は国立情報学研究所の電子図書館事業により電子化されました

SARS-CoV-2 is an Robot Bioweapon

Two possibilities should be considered for the origin of SARS-CoV-2 natural evolution or laboratory creation In our earlier paper titled Unusual Features of the SARS-CoV-2 Genome Suggesting Sophisticated Laboratory Modification as a Biological Robot Rather than Natural Evolution and Delineation of its Probable Synthetic Route we disproved the possibility of SARSCoV- 2 arising naturally through evolution and instead proved that SARS-CoV-2 must have been a product of laboratory modification Despite this and similar efforts the laboratory creation theory continues to be downplayed or even diminished This is fundamentally because the natural origin theory remains supported by several novel coronaviruses published after the start of the outbreak These viruses the RaTG13 bat coronavirus a series of pangolin coronaviruses and the RmYN02 bat coronavirus reportedly share high sequence homology with SARS-CoV-2 and have altogether constructed a seemingly plausible pathway for the natural evolution of SARSCoV- 2 Here however we use in-depth analyses of the available data and literature to prove that these novel animal coronaviruses do not exist in nature and their sequences have been fabricated In addition we also offer our insights on the hypothesis that SARS-CoV-2 may have originated naturally from a coronavirus that infected the Mojiang miner

Turing-Test Evaluation of a Mobile Haptic Virtual Reality Kissing Machine

Various communication systems have been developed to integrate the haptic channel in digital communication. Future directions of such haptic technologies are moving towards realistic virtual reality applications and human-robot social interaction. With the digitisation of touch, robots equipped with touch sensors and actuators can communicate with humans on a more emotional and intimate level, such as sharing a hug or kiss just like humans do. This paper presents the design guideline, implementation and evaluations of a novel haptic kissing machine for smart phones - the Kissenger machine. The key novelties and contributions of the paper are: (i) A novel haptic kissing device for mobile phones, which uses dynamic perpendicular force stimulation to transmit realistic sensations of kissing in order to enhance intimacy and emotional connection of digital communication; (ii) Extensive evaluations of the Kissenger machine, including a lab experiment that compares mediated kissing with Kissenger to real kissing, a unique haptic Turing test that involves the first academic study of humanmachine kiss, and a field study of the effects of Kissenger on long distance relationships

Unusual Features of the SARS-CoV-2 Genome Suggesting Sophisticated Laboratory Modification as a Biological Robot Rather than Natural Evolution and Delineation of its Probable Synthetic Route

The COVID-19 pandemic caused by the novel coronavirus SARS-CoV-2 has led to over 4.24 million deaths worldwide and unprecedented decimation of the global economy. Despite its tremendous impact, the origin of SARS-CoV-2 has remained mysterious and controversial. The natural origin theory, although widely accepted, lacks substantial support. The alternative theory that the virus may have come from a research laboratory is, however, strictly censored on peerreviewed scientific journals. Nonetheless, SARS-CoV-2 shows biological characteristics that are inconsistent with a naturally occurring, zoonotic virus. In this report, we describe the genomic, structural, medical, and literature evidence, which, when considered together, strongly contradicts the natural origin theory. The evidence shows that SARS-CoV2 should be a laboratory product created by using bat coronaviruses ZC45 and/or ZXC21 as a template and/or backbone

Deciphering avian emotions: A novel AI and machine learning approach to understanding chicken vocalizations

In this groundbreaking study, we present a novel approach to interspecies communication, focusing on the understanding of chicken vocalizations. Leveraging advanced mathematical models in artificial intelligence (AI) and machine learning, we have developed a system capable of interpreting various emotional states in chickens, including hunger, fear, anger, contentment, excitement, and distress. Our methodology employs a cutting-edge AI technique we call Deep Emotional Analysis Learning (DEAL), a highly mathematical and innovative approach that allows for the nuanced understanding of emotional states through auditory data. DEAL is rooted in complex mathematical algorithms, enabling the system to learn and adapt to new vocal patterns over time. We conducted our study with a sample of 80 chickens, meticulously recording and analyzing their vocalizations under various conditions. To ensure the accuracy of our system’s interpretations, we collaborated with a team of eight animal psychologists and veterinary surgeons, who provided expert insights into the emotional states of the chickens. Our system demonstrated an impressive accuracy rate of close to 80%, marking a significant advancement in the field of animal communication. This research not only opens up new avenues for understanding and improving animal welfare but also sets a precedent for further studies in AI-driven interspecies communication. The novelty of our approach lies in its application of sophisticated AI techniques to a largely unexplored area of study. By bridging the gap between human and animal communication, we believe our research will pave the way for more empathetic and effective interactions with the animal kingdom