On the Development of SCILAB Compatible Software for the Analysis and Control of Repetitive Processes

In this paper further results on the development of a SCILAB compatible software package for the analysis and control of repetitive processes is described. The core of the package consists of a simulation tool which enables the user to inspect the response of a given example to an input, design a control law for stability and/or performance, and also simulate the response of a controlled process to a specified reference signal

Club COO Leadership: A Comparative Study of Industry

A true leader continues the quest for personal knowledge. The quest is designed to better the leader\u27s life, not necessarily the leader\u27s livelihood. While change is a constant in the lives of club leaders, and some days the leader\u27s vision and purpose change, the underlying ideas and convictions remain constant. Many leadership qualities must be present to be an effective leader. The author\u27s survey club chief operating officers to elicit the characteristics and essential qualities of club leadershi

On the Control of Distributed Parameter Systems using a Multidimensional Systems Setting

The unique characteristic of a repetitive process is a series of sweeps, termed passes, through a set of dynamics defined over a finite duration with resetting before the start of the each new one. On each pass an output, termed the pass profile is produced which acts as a forcing function on, and hence contributes to, the dynamics of the next pass profile. This leads to the possibility that the output, i.e. the sequence of pass profiles, will contain oscillations which increase in amplitude in the pass-to-pass direction. Such behavior cannot be controlled by standard linear systems approach and instead they must be treated as a multidimensional system, i.e. information propagation in more than one independent direction. Physical examples of such processes include long-wall coal cutting and metal rolling. In this paper, stability analysis and control systems design algorithms are developed for a model where a plane, or rectangle, of information is propagated in the passto- pass direction. The possible use of these in the control of distributed parameter systems is then described using a fourthorder wavefront equation

Emotional Intelligence and Organizational Commitment Among Private Club Board and Committee Volunteer Leaders: A Pilot Study

This pilot study explored the relationship between emotional intelligence and organizational commitment among provate club board and committee volunteer members. The top three items, ranked by mean scores, of each of three EI dimensions -- IN, OUT, and RELATIONSHIPS wer discussed. A sample of 57 volunteer leaders furhter was split into high EI and low EI groups based on respndents\u27 overall EO median score. Statistical differences between high and low EI groups in three aspects of organizational commitment - affective, continuance, and normative commitment - wer present. 4 t-test results showed that the difference between high and low EI groups in affective commitment among private club volunteer leaders was statistcally significant at p \u3c.05

Non-perturbative Test of the Witten-Veneziano Formula from Lattice QCD

We compute both sides of the Witten-Veneziano formula using lattice techniques. For the one side we perform dedicated quenched simulations and use the spectral projector method to determine the topological susceptibility in the pure Yang-Mills theory. The other side we determine in lattice QCD with $N_f=2+1+1$ dynamical Wilson twisted mass fermions including for the first time also the flavour singlet decay constant. The Witten-Veneziano formula represents a leading order expression in the framework of chiral perturbation theory and we also employ leading order chiral perturbation theory to relate the flavor singlet decay constant to the relevant decay constant parameters in the quark flavor basis and flavor non-singlet decay constants. After taking the continuum and the SU$(2)$ chiral limits we compare both sides and find good agreement within uncertainties.Comment: 30 pages, 7 figures, version accepted for publicatio

Asteroid Redirect Mission Proximity Operations for Reference Target Asteroid 2008 EV5

NASA's Asteroid Redirect Mission (ARM) is composed of two segments, the Asteroid Redirect Robotic Mission (ARRM), and the Asteroid Redirect Crewed Mission (ARCM). In March of 2015, NASA selected the Robotic Boulder Capture Option1 as the baseline for the ARRM. This option will capture a multi-ton boulder, (typically 2-4 meters in size) from the surface of a large (greater than approx.100 m diameter) Near-Earth Asteroid (NEA) and return it to cis-lunar space for subsequent human exploration during the ARCM. Further human and robotic missions to the asteroidal material would also be facilitated by its return to cis-lunar space. In addition, prior to departing the asteroid, the Asteroid Redirect Vehicle (ARV) will perform a demonstration of the Enhanced Gravity Tractor (EGT) planetary defense technique2. This paper will discuss the proximity operations which have been broken into three phases: Approach and Characterization, Boulder Capture, and Planetary Defense Demonstration. Each of these phases has been analyzed for the ARRM reference target, 2008 EV5, and a detailed baseline operations concept has been developed

Renormalization of minimally doubled fermions

We investigate the renormalization properties of minimally doubled fermions, at one loop in perturbation theory. Our study is based on the two particular realizations of Borici-Creutz and Karsten-Wilczek. A common feature of both formulations is the breaking of hyper-cubic symmetry, which requires that the lattice actions are supplemented by suitable counterterms. We show that three counterterms are required in each case and determine their coefficients to one loop in perturbation theory. For both actions we compute the vacuum polarization of the gluon. It is shown that no power divergences appear and that all contributions which arise from the breaking of Lorentz symmetry are cancelled by the counterterms. We also derive the conserved vector and axial-vector currents for Karsten-Wilczek fermions. Like in the case of the previously studied Borici-Creutz action, one obtains simple expressions, involving only nearest-neighbour sites. We suggest methods how to fix the coefficients of the counterterms non-perturbatively and discuss the implications of our findings for practical simulations.Comment: 23 pages, 1 figur

Unusual Thermal Stability of a Site-Ordered MC60 Rocksalt Structure (M=K, Rb, or Cs)

X-ray diffraction and differential scanning calorimetry of MxC60, with x∼1 and M=K, Rb, or Cs, reveal an unusual T-dependent phase sequence. A low-symmetry ground state is found, while the high-T limit is an ordered rocksalt structure in which only the octahedral sites are occupied. The unusual high-T stability of this ordered phase is attributed to the entropy of molecular orientational disorder and/or thermal disorder of the alkali-metal ions within the octahedral sites. Unique to KxC60 with x≥1.4, we find at intermediate temperatures an fcc site-disordered lattice gas phase with random occupancy of tetrahedral and octahedral sites, which is thus isostructural with superconducting K3C60

Improving SNR and reducing training time of classifiers in large datasets via kernel averaging

Kernel methods are of growing importance in neuroscience research. As an elegant extension of linear methods, they are able to model complex non-linear relationships. However, since the kernel matrix grows with data size, the training of classifiers is computationally demanding in large datasets. Here, a technique developed for linear classifiers is extended to kernel methods: In linearly separable data, replacing sets of instances by their averages improves signal-to-noise ratio (SNR) and reduces data size. In kernel methods, data is linearly non-separable in input space, but linearly separable in the high-dimensional feature space that kernel methods implicitly operate in. It is shown that a classifier can be efficiently trained on instances averaged in feature space by averaging entries in the kernel matrix. Using artificial and publicly available data, it is shown that kernel averaging improves classification performance substantially and reduces training time, even in non-linearly separable data

The representational dynamics of task and object processing in humans

Despite the importance of an observer’s goals in determining how a visual object is categorized, surprisingly little is known about how humans process the task context in which objects occur and how it may interact with the processing of objects. Using magnetoencephalography (MEG), functional magnetic resonance imaging (fMRI) and multivariate techniques, we studied the spatial and temporal dynamics of task and object processing. Our results reveal a sequence of separate but overlapping task-related processes spread across frontoparietal and occipitotemporal cortex. Task exhibited late effects on object processing by selectively enhancing task-relevant object features, with limited impact on the overall pattern of object representations. Combining MEG and fMRI data, we reveal a parallel rise in task-related signals throughout the cerebral cortex, with an increasing dominance of task over object representations from early to higher visual areas. Collectively, our results reveal the complex dynamics underlying task and object representations throughout human cortex