A reconfigurable hybrid intelligent system for robot navigation

Soft computing has come of age to o er us a wide array of powerful and e cient algorithms that independently matured and in uenced our approach to solving problems in robotics, search and optimisation. The steady progress of technology, however, induced a ux of new real-world applications that demand for more robust and adaptive computational paradigms, tailored speci cally for the problem domain. This gave rise to hybrid intelligent systems, and to name a few of the successful ones, we have the integration of fuzzy logic, genetic algorithms and neural networks. As noted in the literature, they are signi cantly more powerful than individual algorithms, and therefore have been the subject of research activities in the past decades. There are problems, however, that have not succumbed to traditional hybridisation approaches, pushing the limits of current intelligent systems design, questioning their solutions of a guarantee of optimality, real-time execution and self-calibration. This work presents an improved hybrid solution to the problem of integrated dynamic target pursuit and obstacle avoidance, comprising of a cascade of fuzzy logic systems, genetic algorithm, the A* search algorithm and the Voronoi diagram generation algorithm

Money and Prices in the Philippines, 1981-1992: A Cointegration Analysis

Based largely on the work of Funke and Hall, estimation results indicate non-causality between money and price level attributed to the interplay of factors such as unstable political and economic environment. P* vector has no significance on potential output since Q instead of Q* has been used.monetary aggregates, causality, price level

Linking the anomaly initialization approach to the mapping paradigm: a proof-of-concept study

Seasonal-to-decadal predictions are initialized using observations of the present climatic state in full field initialization (FFI). Such model integrations undergo a drift toward the model attractor due to model deficiencies that incur a bias in the model. The anomaly initialization (AI) approach reduces the drift by adding an estimate of the bias onto the observations at the expense of a larger initial error. In this study FFI is associated with the fidelity paradigm, and AI is associated with an instance of the mapping paradigm, in which the initial conditions are mapped onto the imperfect model attractor by adding a fixed error term; the mapped state on the model attractor should correspond to the nature state. Two diagnosis tools assess how well AI conforms to its own paradigm under various circumstances of model error: the degree of approximation of the model attractor is measured by calculating the overlap of the AI initial conditions PDF with the model PDF; and the sensitivity to random error in the initial conditions reveals how well the selected initial conditions on the model attractor correspond to the nature states. As a useful reference, the initial conditions of FFI are subjected to the same analysis. Conducting hindcast experiments using a hierarchy of low-order coupled climate models, it is shown that the initial conditions generated using AI approximate the model attractor only under certain conditions: differences in higher-than-first-order moments between the model and nature PDFs must be negligible. Where such conditions fail, FFI is likely to perform better

Expansion coefficient of the pseudo-scalar density using the gradient flow in lattice QCD

We use the Yang-Mills gradient flow to calculate the pseudo-scalar expansion coefficient $c_P^*(t_f)$. This quantity is a key ingredient to obtaining the chiral condensate and strange quark content of the nucleon using the Lattice QCD formulation, which can ultimately determine the spin independent (SI) elastic cross section of dark matter models involving WIMP-nucleon interactions. The goal, using the gradient flow, is to renormalize the chiral condensate and the strange content of the nucleon without a power divergent subtraction. Using Chiral symmetry and the small flow time expansion of the gradient flow, the scalar density at zero flow time can be related to the pseudo-scalar density at non zero flow time. By computing the flow time dependance of the pseudo-scalar density over multiple lattices box sizes, lattice spacings and pion masses, we can obtain the scalar density of the nucleon. Our lattice ensembles are $N_{f}=2+1$, PCAC-CS gauge field configurations, varying over $m_{\pi}\approx \{410,570,700\}$~MeV at $a=0.0907$~fm, with additional ensembles that vary $a\approx \{0.1095,0.0936,0.0684\}$~fm at $m_{\pi} \approx 700$~MeV

Nursing Students\u27 Understanding and Enactment of Resilience: A Grounded Theory Study

The purpose of this study was to explore nursing students’ understanding and enactment of resilience. Stress is considered to be a major factor affecting the health, well-being, and academic performance of nursing students. Resilience has been extensively researched as a process that allows individuals to successfully adapt to adversity and develop positive outcomes as a result. However, relatively little is known about the resilience of nursing students. A constructivist grounded theory study design was used. In-depth individual interviews were conducted with 38 nursing students enrolled in a four-year, integrated baccalaureate nursing degree program at a university in Ontario, Canada. Face-to-face interviews were conducted from January to April 2012. The basic social process of pushing through emerged as nursing students’ understanding and enactment of resilience. Participants employed this process to withstand challenges in their academic lives. This process was comprised of three main phases: stepping into, staying the course, and acknowledging. Pushing through also included a transient disengaging process in which students were temporarily unable to push through their adversities. The process of pushing through was based on a progressive trajectory, which implied that nursing students enacted the process in order to make progress in their academic lives and to attain goals. Study findings provide important evidence for understanding the phenomenon of resilience as a dynamic, contextual process that can be learned and developed, rather than a static trait or personality characteristic