Does the Brain Function as a Quantum Phase Computer Using Phase Ternary Computation?

Here we provide evidence that the fundamental basis of nervous communication is derived from a pressure pulse/soliton capable of computation with sufficient temporal precision to overcome any processing errors. Signalling and computing within the nervous system are complex and different phenomena. Action potentials are plastic and this makes the action potential peak an inappropriate fixed point for neural computation, but the action potential threshold is suitable for this purpose. Furthermore, neural models timed by spiking neurons operate below the rate necessary to overcome processing error. Using retinal processing as our example, we demonstrate that the contemporary theory of nerve conduction based on cable theory is inappropriate to account for the short computational time necessary for the full functioning of the retina and by implication the rest of the brain. Moreover, cable theory cannot be instrumental in the propagation of the action potential because at the activation-threshold there is insufficient charge at the activation site for successive ion channels to be electrostatically opened. Deconstruction of the brain neural network suggests that it is a member of a group of Quantum phase computers of which the Turing machine is the simplest: the brain is another based upon phase ternary computation. However, attempts to use Turing based mechanisms cannot resolve the coding of the retina or the computation of intelligence, as the technology of Turing based computers is fundamentally different. We demonstrate that that coding in the brain neural network is quantum based, where the quanta have a temporal variable and a phase-base variable enabling phase ternary computation as previously demonstrated in the retina.

Perspectives of Fuzzy Logic and Their Applications

Fuzzy logic is a highly suitable and applicable basis for developing knowledge-based systems in engineering and applied sciences. The concepts of a fuzzy number plays a fundamental role in formulating quantitative fuzzy variable. These are variable whose states are fuzzy numbers. When in addition, the fuzzy numbers represent linguistic concepts, such as very small, small, medium, and so on, as interpreted in a particular contest, the resulting constructs are usually called linguistic variables. Each linguistic variable the states of which are expressed by linguistic terms interpreted as specific fuzzy numbers is defined in terms of a base variable, the value of which are real numbers within a specific range. A base variable is variable in the classical sense, exemplified by the physical variable (e.g., temperature, pressure, speed, voltage, humidity, etc.) as well as any other numerical variable (e.g., age, interest rate, performance, salary, blood count, probability, reliability, etc.). Logic is the science of reasoning. Symbolic or mathematical logic is a powerful computational paradigm. Just as crisp sets survive on a 2-state membership (0/1) and fuzzy sets on a multistage membership [0 - 1], crisp logic is built on a 2-state truth-value (true or false) and fuzzy logic on a multistage truth-value (true, false, very true, partly false and so on). The author now briefly discusses the crisp logic and fuzzy logic. The aim of this paper is to explain the concept of classical logic, fuzzy logic, fuzzy connectives, fuzzy inference, fuzzy predicate, modifier inference from conditional fuzzy propositions, generalized modus ponens, generalization of hypothetical syllogism, conditional, and qualified propositions. Suitable examples are given to understand the topics in brief.

Estimating pilots’ cognitive load from ocular parameters through simulation and in-flight studies

Eye tracking is the process of measuring either the point of gaze (where one is looking) or the motion of an eye relative to the head. This paper investigated use of eye gaze trackers in military aviation environment to automatically estimate pilot’s cognitive load from ocular parameters. We used a fixed base variable stability flight simulator with longitudinal tracking task and collected data from 14 military pilots. In a second study, we undertook three test flights with a BAES Hawk Trainer aircraft doing air to ground attack training missions and constant G level turn maneuvers up to +5G. Our study found that ocular parameters like rate of fixation is significantly different in different flying conditions and significantly correlate with altitude gradient during air to ground dive training task, normal load factor (G) of the aircraft during constant G level turn maneuvers and pilot’s control inceptor and tracking error in simulation tasks. Results from our studies can be used for real time estimation of pilots’ cognitive load, providing suitable warnings and alerts to the pilot in cockpit and training of military pilots on cognitive load management during operational missions.

Influence of Supervisory Relationship and Satisfaction among Trainee Counselors in Practicum Process

The purpose of this research is to investigate the influence of supervisory relationship on supervision satisfaction among trainee counselors. The Supervisory Relationship Questionnaire (SRQ) is to measure the supervisory relationship and Supervisory Satisfaction Questionnaire (SSQ) is used to measure supervision satisfaction. The finding shows that supervisory relationship and its subscales (Safe Base, Structure, Commitment, Reflective Education, Role Model and Formative Feedback) have a positively significant relationship with supervision satisfaction among trainee counselors (safe base: r = 0.73, p < 0.05, structure: r = 0.65, p < 0.05, commitment: r = 0.69, p < .05, reflective education: r = 0.70, p < 0.05, role model: r = 0.51, p < 0.05, formative feedback: r = 0.71, p < 0.05 and supervisory relationship: r = 0.79, p < 0.05). The findings of this research also found that supervisory relationship, safe base and role model variables have significant influence on supervision satisfaction among trainee counselors with F (1, 98) = 169.59, p < 0.05, Adjusted R2 = 0.63 for supervisory relationship variable, F (3, 96) = 68.68, p < 0.05, Adjusted R2 = 67 for safe base variable and F (2, 97) = 96.47, p < 0.05, Adjusted R2 = 0.65 for role model variable. Supervisory relationship variable has the greatest influence (β = .79) while role model variable has the least influence (β = - 0.28) on supervision satisfaction. As for the theoretical implication, the finding of this research has proven Marina Palomo’s theoretical framework in ‘Bi-directional Model of the Supervisory Relationship’. Meanwhile in practical implication, this research has raised awareness on the importance of supervisory relationship on supervision satisfaction in counseling supervision.

An Appraisal of Stability of a Highway Retaing Wall on a Reservoir Bank

This paper explores the post-Wenzhou earthquake destruction characteristics of the Zipingpu reservoir highway retaining wall and examines influences such as the type of retaining wall, location of retaining wall, and retaining wall design process in the disaster area. The results show that during high intensity earthquakes, the use of flexible reatining methods such as anchor cables and soil nails suitably adds fortification intensity to retaining walls located on buried faults. In addition, in high intensity earthquake areas, the highway section of the curve (especially in the reture curve) must be taken into account earth pressure calculations. Dirt retaining walls are widely used, but in cases in which other designs are used in substitution of the function of dirt retaining walls, determinations must be made regarding the economic efficiency, and technology. Dirt retaining wall loads only calculate for the permanent load and the base variable load, so with respect to earthquake regions where peak value speeds are above 0.2 g, other calculations