Education
Jiyang Luo attended Guo Guang Secondary School, one of the most prestigious secondary schools in the People's Republic of China. Because of his exemplary performance, he left school a year early after he was invited to attend Tsinghua University, where he majored in computer science, a major available only to the very top achieving students in China. He became specialized in artificial intelligence, which was still in its infancy in the 1980s.
Early achievements
Jiyang Luo worked with punchcard machines, creating a design aspect that was later patented. Luo's achievments also earned him a national science award. Luo created a start-up in order to market one of his inventions. With the factory site already chosen and investors already committed, Luo suddenly left in order to continue his education in the United States.
Work with neural networks
Continuing to be absorbed in academics, Jiyang became an expert in artificial neural networks during the period he spent researching at Wright State University. He wrote a paper entitled "Instant learning for supervised learning neural networks: arank-expansion algorithm", which would later be published in the journal - Neural Networks, 1994. IEEE World Congress on Computational Intelligence. For his work, he was invited to attend the 1994 World Congress on Neural Networks, hosted by the Institute of Electrical and Electronics Engineers, where he was joined by many fellow scientists and alumni from his home country of China. His research was a breakthrough for the artificial neural network academic community, increasing quality of optimization and decreasing error by proposing new methods of infrastructure and neural network archetecture setup.<ref name="paper1"/>
Neural network archetecture and learning algorithms
Jiyang Luo specified parities in learning error, and presented solutions. He specified in his 1994 paper: "An one-hidden layer neural network architecture is presented. An instant learning algorithm is given to decide the weights of a supervised learning neural network. For an n dimensional, N-pattern training set, a maximum of N-r hidden nodes are required to learn all the patterns within a given precision (where r is the rank, usually the dimension, of the input patterns). Using the inverse of activation function, the algorithms transfer the output to the hidden layer, add bias nodes to the input, expand the rank of input dimension. The proposed architecture and algorithm can obtain either exact solution or minimum least square error of the inverse activation of the output. The learning error only occurs when applying the inverse of activation function. Usually, this can be controlled by the given precision."<ref name="paper2"/>
Indeed, the Oath was first instituted in response to the widespread tendency at that time for physicians to practice according to societal expectations and motives of personal gain, instead of the sole good of patients. The pressing need to codify standards for professional behavior and to unify physicians under that code was met in the Hippocratic Oath. Its core principles served as standard for professional identity and practice for approximately 25 centuries.
These principles include the following:
* The preeminent nature of morality and professional ethics
* Professional dedication to the sanctity of human life under all circumstances
* Refusal to take part in the ending of human life, whether unborn, unwanted, or terminally ill
* Complete patient confidentiality
* Abstinence from all selfish or mischievous activity in caring for patients
* Rejection of any sexual involvement with patients
The Hippocratic Oath is no longer the underpinning of the medical profession that it once was, and its essential meaning has been modified in response to changing socio-political values. Under the postmodern priciples of multiculturalism, relativism, and utilitarianism, such modifications of the Hippocratic Oath either eliminate reference to an Almighty, neutralizing its transcendent nature, or eliminate the prohibitions against taking human life, or both. The American Hippocratic Registry recognizes the potential dangers for the profession of medicine and for the greater society when physicians abrogate their moral and philosophical solidarity and instead practice under the requirements of contravening laws or social norms alone. (See also Nuremberg Code). As such, Hippocratic physicians recognize theirs as a professional duty to patients based on a moral code beyond laws and statutes that may change for no higher reason than majority rule.
Like its counterpart, the Canadian Hippocratic Registry, the American Hippocratic Registry is nonsectarian, and its moral conviction is not based on any particular religious belief. Thus, physicians and other health care providers of any religion or denomination and those of no religious preference may register. Similarly, there is no restriction based on political affiliation or other beliefs. The American Hippocratic Registry is not affiliated with any political group, nor does it have fiduciary ties with any other causes, movements, or organizations.
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