Terrorism Threat in Doctrine Formulating of Military Campaign Scenario to Achieve National Security

Based on the estimation methodology on the potential of the war against terrorism on the transformation of doctrine, the conclusions based on the predictive analysis are: (1) The potential for the war against terrorism has a very strong relevance to the prediction of changes in military campaign doctrine in the long term by producing new war strategies both in terms of ends-means-ways as a result of High Impact Low Probability, (2) Through predictive analysis with extrapolation model, it is found that threats, strategic environment and tradition or history are variables that are expected to remain unchanged, especially in the short term in influencing the preparation of Military Campaign Doctrine, (3) The Projection Model determines if Threat is the variable that changes the most so that it will affect changes in the Military Campaign Doctrine in the short to medium term, (4) Looking for the best solution in realizing the best Military Campaign Doctrine. This can be followed by designing a simulation of the New War Strategy as a result of forecasting the Military Campaign Doctrine.

Using Trend Extrapolation Model to Predict the Needs of Elderly Care Talents in Beijing Institutions

2020-2050 is a period of rapid development of China's population aging, and it is also a critical period for the country to actively respond to population aging. Under the background of the combination of medical care and nursing, institutional elderly care services, as an important branch of the multi-level elderly care service system, have become the main battlefield of the integrated medical and elderly care policy. Therefore, institutional care talents for the aged have also become a key link in improving the quality of life of the elderly population. This paper using trend extrapolation model to predict the needs of elderly care talents in institutions in Beijing, including nursing staff who provide basic living care and professional medical staff who provide services such as rehabilitation, medical treatment, nutrition, and psychological consultation. The results show that, in 2050, the demand for institutional elderly nursing staff in Beijing will exceed 150,000, and the demand for institutional elderly medical staff will reach about 20,000.

Sensorimotor delays in tracking may be compensated by negative feedback control of motion-extrapolated position

Sensorimotor delays dictate that humans act on outdated perceptual information. As a result, continuous manual tracking of an unpredictable target incurs significant response delays. However, no such delays are observed for repeating targets such as the sinusoids. Findings of this kind have led researchers to claim that the nervous system constructs predictive, probabilistic models of the world. However, a more parsimonious explanation is that visual perception of a moving target position is systematically biased by its velocity. The resultant extrapolated position could be compared with the cursor position and the difference canceled by negative feedback control, compensating sensorimotor delays. The current study tested whether a position extrapolation model fit human tracking of sinusoid (predictable) and pseudorandom (less predictable) targets better than the non-biased position control model, Twenty-eight participants tracked these targets and the two computational models were fit to the data at 60 fixed loop delay values (simulating sensorimotor delays). We observed that pseudorandom targets were tracked with a significantly greater phase delay than sinusoid targets. For sinusoid targets, the position extrapolation model simulated tracking results more accurately for loop delays longer than 120 ms, thereby confirming its ability to compensate for sensorimotor delays. However, for pseudorandom targets, this advantage arose only after 300 ms, indicating that velocity information is unlikely to be exploited in this way during the tracking of less predictable targets. We conclude that negative feedback control of position is a parsimonious model for tracking pseudorandom targets and that negative feedback control of extrapolated position is a parsimonious model for tracking sinusoidal targets.