Abstract: In this paper we objectively measure the performance of an individual offensive lineman in the NFL. The existing literature proposes various measures that rely on subjective assessments of game film, but has yet to develop an objective methodology to evaluate performance. Using a variety of statistics related to an offensive lineman’s performance, we develop a framework to objectively analyze the overall performance of an individual offensive lineman and determine specific linemen who are overvalued or undervalued relative to their salary. We identify eight players across the 2013-2014 and 2014-2015 NFL seasons that are considered to be overvalued or undervalued and corroborate the results with existing metrics that are based on subjective evaluation. To the best of our knowledge, the techniques set forth in this work have not been utilized in previous works to evaluate the performance of NFL players at any position, including offensive linemen.
Abstract: Cellular complexity stems from the interactions
among thousands of different molecular species. Thanks to the
emerging fields of systems and synthetic biology, scientists are
beginning to unravel these regulatory, signaling, and metabolic
interactions and to understand their coordinated action. Reverse
engineering of biological networks has has several benefits but a
poor quality of data combined with the difficulty in reproducing
it limits the applicability of these methods. A few years back,
many of the commonly used predictive algorithms were tested
on a network constructed in the yeast Saccharomyces cerevisiae
(S. cerevisiae) to resolve this issue. The network was a synthetic
network of five genes regulating each other for the so-called in
vivo reverse-engineering and modeling assessment (IRMA). The
network was constructed in S. cereviase since it is a simple and well
characterized organism. The synthetic network included a variety
of regulatory interactions, thus capturing the behaviour of larger
eukaryotic gene networks on a smaller scale. We derive a new set of
algorithms by solving a nonlinear optimization problem and show
how these algorithms outperform other algorithms on these datasets.
Abstract: The material behavior of graphene, a single layer of
carbon lattice, is extremely sensitive to its dielectric environment. We
demonstrate improvement in electronic performance of graphene
nanowire interconnects with full encapsulation by lattice-matching,
chemically inert, 2D layered insulator hexagonal boron nitride (h-
BN). A novel layer-based transfer technique is developed to construct
the h-BN/MLG/h-BN heterostructures. The encapsulated graphene
wires are characterized and compared with that on SiO2 or h-BN
substrate without passivating h-BN layer. Significant improvements
in maximum current-carrying density, breakdown threshold, and
power density in encapsulated graphene wires are observed. These
critical improvements are achieved without compromising the carrier
transport characteristics in graphene. Furthermore, graphene wires
exhibit electrical behavior less insensitive to ambient conditions, as
compared with the non-passivated ones. Overall, h-BN/graphene/h-
BN heterostructure presents a robust material platform towards the
implementation of high-speed carbon-based interconnects.
Abstract: In the past researchers have questioned the
effectiveness of ethics training in higher education. Also, there are
observations that support the view that ethical behaviour (range of
actions)/ethical decision making models used in the past make use of
vignettes to explain ethical behaviour. The understanding remains in
the perspective that these vignettes play a limited role in determining
individual intentions and not actions. Some authors have also agreed
that there are possibilities of differences in one’s intentions and
actions. This paper makes an attempt to fill those gaps by evaluating
real actions rather than intentions. In a way this study suggests the
use of an experiential methodology to explore Berlo’s model of
communication as an action along with orchestration of various
principles. To this endeavor, an attempt was made to use
conversational analysis in the pursuance of evaluating ethical
decision making behaviour among students and middle level
managers. The process was repeated six times with the set of an
average of 15 participants. Similarities have been observed in the
behaviour of students and middle level managers that calls for
understanding that both the groups of individuals have no cognizance
of their actual actions. The deliberations derived out of conversation
were taken a step forward for meta-ethical evaluations to portray a
clear picture of ethical behaviour among participants. This study
provides insights for understanding demonstrated unconscious human
behaviour which may fortuitously be termed both ethical and
unethical.
Abstract: A predictive clustering hybrid regression (pCHR)
approach was developed and evaluated using dataset from H2-
producing sucrose-based bioreactor operated for 15 months. The aim
was to model and predict the H2-production rate using information
available about envirome and metabolome of the bioprocess. Selforganizing
maps (SOM) and Sammon map were used to visualize the
dataset and to identify main metabolic patterns and clusters in
bioprocess data. Three metabolic clusters: acetate coupled with other
metabolites, butyrate only, and transition phases were detected. The
developed pCHR model combines principles of k-means clustering,
kNN classification and regression techniques. The model performed
well in modeling and predicting the H2-production rate with mean
square error values of 0.0014 and 0.0032, respectively.
Abstract: In this present work, the development of an avionics
system for flight data collection of a Raptor 30 V2 is carried out. For the data acquisition both onground and onboard avionics systems are developed for testing of a small-scale Unmanned Aerial Vehicle
(UAV) helicopter. The onboard avionics record the helicopter state
outputs namely accelerations, angular rates and Euler angles, in real time, and the on ground avionics system record the inputs given to
the radio controlled helicopter through a transmitter, in real time. The avionic systems are designed and developed taking into consideration
low weight, small size, anti-vibration, low power consumption, and easy interfacing. To mitigate the medium frequency vibrations
embedded on the UAV helicopter during flight, a damper is designed
and its performance is evaluated. A number of flight tests are carried
out and the data obtained is then analyzed for accuracy and repeatability and conclusions are inferred.
Abstract: In the literature of information theory, there is
necessity for comparing the different measures of fuzzy entropy and
this consequently, gives rise to the need for normalizing measures of
fuzzy entropy. In this paper, we have discussed this need and hence
developed some normalized measures of fuzzy entropy. It is also
desirable to maximize entropy and to minimize directed divergence
or distance. Keeping in mind this idea, we have explained the method
of optimizing different measures of fuzzy entropy.
Abstract: The performance of a sucrose-based H2 production in
a completely stirred tank reactor (CSTR) was modeled by neural
network back-propagation (BP) algorithm. The H2 production was
monitored over a period of 450 days at 35±1 ºC. The proposed model
predicts H2 production rates based on hydraulic retention time
(HRT), recycle ratio, sucrose concentration and degradation, biomass
concentrations, pH, alkalinity, oxidation-reduction potential (ORP),
acids and alcohols concentrations. Artificial neural networks (ANNs)
have an ability to capture non-linear information very efficiently. In
this study, a predictive controller was proposed for management and
operation of large scale H2-fermenting systems. The relevant control
strategies can be activated by this method. BP based ANNs modeling
results was very successful and an excellent match was obtained
between the measured and the predicted rates. The efficient H2
production and system control can be provided by predictive control
method combined with the robust BP based ANN modeling tool.
Abstract: In the present communication, we have proposed
some new generalized measure of fuzzy entropy based upon real
parameters, discussed their and desirable properties, and presented
these measures graphically. An important property, that is,
monotonicity of the proposed measures has also been studied.