The red thread of the AI-IP-EI Trilogy fate of this study, may have the appearance of a pot-pourri of intellectual and intelligence natures, as a matter of fact that it emanates from the genesis and practical synergis...The red thread of the AI-IP-EI Trilogy fate of this study, may have the appearance of a pot-pourri of intellectual and intelligence natures, as a matter of fact that it emanates from the genesis and practical synergism of the trilogy components. Concretely: The paper goes from: AI (Artificial Intelligence)—to the related IP (Intellectual Property) domain—to the relevance of EI (Emotional Intelligence);thus, forming the new AI-IP-EI Trilogy and its attributes and specific impacts to the new innovation process, and business model dimensions. These impacts are outlined and illustrated in part in essays of specific sections and all along. Several concrete study cases are used in the various dedicated sections;such as cases respective to the inventor status, and the EI factor, to the sport education innovative dimension, as well as to biases as inevitably promoting and revealing, to drastically enlarge open innovation supported by constructivism and creations of musical group as a model of open reflexive education. Overall resulting adapted business models appear to have a massive potential, and a multidimensional reach with a necessary attention to the IP policy on going definition. The durable green dimension is exemplified as well. The Ethics-plus, “@LEAST<span style="font-family:Verdana, Helvetica, Arial;white-space:normal;background-color:#FFFFFF;">?</span>”, said corpus is proposed. Could a human centric, AI-adapted-IP policy, internationally embraced, take part to some level of arbitrage, normative and enduring reliability in the field of interest? This seems to be “en route”. Shall the EI (Emotional Intelligence) factor be supervised? Likely so. Is traditional open innovation renewed to a more comprehensive, more inclusive dimension reminding best business practice and now “beyond”? Definitely, and will remain an opportunity, all along the 4IR quantum game changer to come. Neither seeking an in-depth expert analysis, nor a grand public over-simplified bavardage, of the trilogy, AI-IP-EI, four a展开更多
The hypothesis of behavioral parameters dependence measured from person’s head movements in quasi-stationary state on COVID-19 disease is discussed. Method for determining the dependence of vestibular-emotional refle...The hypothesis of behavioral parameters dependence measured from person’s head movements in quasi-stationary state on COVID-19 disease is discussed. Method for determining the dependence of vestibular-emotional reflex parameters on COVID-19, various diseases and pathologies are proposed. Micro-movements of a head for representatives of the control group (with a confirmed absence of COVID-19 disease) and a group of patients with a confirmed diagnosis of COVID-19 were studied using vibraimage technology. Parameters and criteria for the diagnosis of COVID-19 for training artificial intelligence (AI) on the control group and the patient group are proposed. 3-layer (one hidden layer) feedforward neural network (40 + 20 + 1 sigmoid neurons) was developed for AI training. AI was firstly trained on the primary sample of patients and a control group. Study of a random sample of people with trained AI was carried out and the possibility of detecting COVID-19 using the proposed method was proved a week before the onset of clinical symptoms of the disease. Number of COVID-19 diagnostic parameters was increased to 26 and AI was trained on a sample of 536 measurements, 268 patient measurement results and 268 measurement results in the control group. The achieved diagnostic accuracy was more than 99%, 4 errors per 536 measurements (2 false positive and 2 false negative), specificity 99.25% and sensitivity 99.25%. The issues of improving the accuracy and reliability of the proposed method for diagnosing COVID-19 are discussed. Further ways to improve the characteristics and applicability of the proposed method of diagnosis and self-diagnosis of COVID-19 are outlined.展开更多
文摘The red thread of the AI-IP-EI Trilogy fate of this study, may have the appearance of a pot-pourri of intellectual and intelligence natures, as a matter of fact that it emanates from the genesis and practical synergism of the trilogy components. Concretely: The paper goes from: AI (Artificial Intelligence)—to the related IP (Intellectual Property) domain—to the relevance of EI (Emotional Intelligence);thus, forming the new AI-IP-EI Trilogy and its attributes and specific impacts to the new innovation process, and business model dimensions. These impacts are outlined and illustrated in part in essays of specific sections and all along. Several concrete study cases are used in the various dedicated sections;such as cases respective to the inventor status, and the EI factor, to the sport education innovative dimension, as well as to biases as inevitably promoting and revealing, to drastically enlarge open innovation supported by constructivism and creations of musical group as a model of open reflexive education. Overall resulting adapted business models appear to have a massive potential, and a multidimensional reach with a necessary attention to the IP policy on going definition. The durable green dimension is exemplified as well. The Ethics-plus, “@LEAST<span style="font-family:Verdana, Helvetica, Arial;white-space:normal;background-color:#FFFFFF;">?</span>”, said corpus is proposed. Could a human centric, AI-adapted-IP policy, internationally embraced, take part to some level of arbitrage, normative and enduring reliability in the field of interest? This seems to be “en route”. Shall the EI (Emotional Intelligence) factor be supervised? Likely so. Is traditional open innovation renewed to a more comprehensive, more inclusive dimension reminding best business practice and now “beyond”? Definitely, and will remain an opportunity, all along the 4IR quantum game changer to come. Neither seeking an in-depth expert analysis, nor a grand public over-simplified bavardage, of the trilogy, AI-IP-EI, four a
文摘The hypothesis of behavioral parameters dependence measured from person’s head movements in quasi-stationary state on COVID-19 disease is discussed. Method for determining the dependence of vestibular-emotional reflex parameters on COVID-19, various diseases and pathologies are proposed. Micro-movements of a head for representatives of the control group (with a confirmed absence of COVID-19 disease) and a group of patients with a confirmed diagnosis of COVID-19 were studied using vibraimage technology. Parameters and criteria for the diagnosis of COVID-19 for training artificial intelligence (AI) on the control group and the patient group are proposed. 3-layer (one hidden layer) feedforward neural network (40 + 20 + 1 sigmoid neurons) was developed for AI training. AI was firstly trained on the primary sample of patients and a control group. Study of a random sample of people with trained AI was carried out and the possibility of detecting COVID-19 using the proposed method was proved a week before the onset of clinical symptoms of the disease. Number of COVID-19 diagnostic parameters was increased to 26 and AI was trained on a sample of 536 measurements, 268 patient measurement results and 268 measurement results in the control group. The achieved diagnostic accuracy was more than 99%, 4 errors per 536 measurements (2 false positive and 2 false negative), specificity 99.25% and sensitivity 99.25%. The issues of improving the accuracy and reliability of the proposed method for diagnosing COVID-19 are discussed. Further ways to improve the characteristics and applicability of the proposed method of diagnosis and self-diagnosis of COVID-19 are outlined.