Abstract: In this paper, we discuss the paradigm shift in bank
capital from the “gone concern" to the “going concern" mindset. We
then propose a methodology for pricing a product of this shift called
Contingent Capital Notes (“CoCos"). The Merton Model can
determine a price for credit risk by using the firm-s equity value as a
call option on those assets. Our pricing methodology for CoCos also
uses the credit spread implied by the Merton Model in a subsequent
derivative form created by John Hull et al . Here, a market implied
asset volatility is calculated by using observed market CDS spreads.
This implied asset volatility is then used to estimate the probability of
triggering a predetermined “contingency event" given the distanceto-
trigger (DTT). The paper then investigates the effect of varying
DTTs and recovery assumptions on the CoCo yield. We conclude
with an investment rationale.
Abstract: The application of a high frequency signal injection method as speed and position observer in PMSM drives has been a research focus. At present, the precision of this method is nearly good as that of ten-bit encoder. But there are some questions for estimating position polarity. Based on high frequency signal injection, this paper presents a method to compensate position polarity for permanent magnet synchronous motor (PMSM). Experiments were performed to test the effectiveness of the proposed algorithm and results present the good performance.
Abstract: While many studies have conducted the achievement
gap between groups of students in school districts, few studies have
utilized resilience research to investigate achievement gaps within
classrooms. This paper aims to summarize and discuss some recent
studies Waxman, Padr├│n, and their colleagues conducted, in which
they examined learning environment differences between resilient
and nonresilient students in reading and mathematics classrooms.
The classes consist of predominantly Hispanic elementary school
students from low-income families. These studies all incorporated
learning environment questionnaires and systematic observation
methods. Significant differences were found between resilient and
nonresilient students on their classroom learning environments and
classroom behaviors. The observation results indicate that the amount
and quality of teacher and student academic interaction are two of the
most influential variables that promote student outcomes. This paper
concludes by suggesting the following teacher practices to promote
resiliency in schools: (a) using feedback from classroom observation
and learning environment measures, (b) employing explicit teaching
practices; and (c) understanding students on a social and personal
level.
Abstract: In its attempt to offer new ways into autonomy for a
large population of disabled people, assistive technology has largely
been inspired by robotics engineering. Recent human-like robots
carry new hopes that it seems to us necessary to analyze by means of
a specific theory of anthropomorphism. We propose to distinguish a
functional anthropomorphism which is the one of actual wheelchairs
from a structural anthropomorphism based on a mimicking of human
physiological systems. If functional anthropomorphism offers the
main advantage of eliminating the physiological systems
interdependence issue, the highly link between the robot for disabled
people and their human-built environment would lead to privilege in
the future the anthropomorphic structural way. In this future
framework, we highlight a general interdependence principle : any
partial or local structural anthropomorphism generates new
anthropomorphic needs due to the physiological systems
interdependency, whose effects can be evaluated by means of
specific anthropomorphic criterions derived from a set theory-based
approach of physiological systems.
Abstract: The performance of adaptive beamforming degrades
substantially in the presence of steering vector mismatches. This
degradation is especially severe in the near-field, for the
3-dimensional source location is more difficult to estimate than the
2-dimensional direction of arrival in far-field cases. As a solution, a
novel approach of near-field robust adaptive beamforming (RABF) is
proposed in this paper. It is a natural extension of the traditional
far-field RABF and belongs to the class of diagonal loading
approaches, with the loading level determined based on worst-case
performance optimization. However, different from the methods
solving the optimal loading by iteration, it suggests here a simple
closed-form solution after some approximations, and consequently,
the optimal weight vector can be expressed in a closed form. Besides
simplicity and low computational cost, the proposed approach reveals
how different factors affect the optimal loading as well as the weight
vector. Its excellent performance in the near-field is confirmed via a
number of numerical examples.
Abstract: Enzymatic saccharification of biomass for reducing
sugar production is one of the crucial processes in biofuel production
through biochemical conversion. In this study, enzymatic
saccharification of dilute potassium hydroxide (KOH) pre-treated
Tetraselmis suecica biomass was carried out by using cellulase
enzyme obtained from Trichoderma longibrachiatum. Initially, the
pre-treatment conditions were optimised by changing alkali reagent
concentration, retention time for reaction, and temperature. The T.
suecica biomass after pre-treatment was also characterized using
Fourier Transform Infrared Spectra and Scanning Electron
Microscope. These analyses revealed that the functional group such
as acetyl and hydroxyl groups, structure and surface of T. suecica
biomass were changed through pre-treatment, which is favourable for
enzymatic saccharification process. Comparison of enzymatic
saccharification of untreated and pre-treated microalgal biomass
indicated that higher level of reducing sugar can be obtained from
pre-treated T. suecica. Enzymatic saccharification of pre-treated T.
suecica biomass was optimised by changing temperature, pH, and
enzyme concentration to solid ratio ([E]/[S]). Highest conversion of
carbohydrate into reducing sugar of 95% amounted to reducing sugar
yield of 20 (wt%) from pre-treated T. suecica was obtained from
saccharification, at temperature: 40°C, pH: 4.5 and [E]/[S] of 0.1
after 72 h of incubation. Hydrolysate obtained from enzymatic
saccharification of pretreated T. suecica biomass was further
fermented into biobutanol using Clostridium saccharoperbutyliticum
as biocatalyst. The results from this study demonstrate a positive
prospect of application of dilute alkaline pre-treatment to enhance
enzymatic saccharification and biobutanol production from
microalgal biomass.
Abstract: This paper studies the mean square exponential synchronization problem of a class of stochastic neutral type chaotic neural networks with mixed delay. On the Basis of Lyapunov stability theory, some sufficient conditions ensuring the mean square exponential synchronization of two identical chaotic neural networks are obtained by using stochastic analysis and inequality technique. These conditions are expressed in the form of linear matrix inequalities (LMIs), whose feasibility can be easily checked by using Matlab LMI Toolbox. The feedback controller used in this paper is more general than those used in previous literatures. One simulation example is presented to demonstrate the effectiveness of the derived results.
Abstract: In the automotive industry test drives are being conducted
during the development of new vehicle models or as a part of
quality assurance of series-production vehicles. The communication
on the in-vehicle network, data from external sensors, or internal
data from the electronic control units is recorded by automotive
data loggers during the test drives. The recordings are used for fault
analysis. Since the resulting data volume is tremendous, manually
analysing each recording in great detail is not feasible.
This paper proposes to use machine learning to support domainexperts
by preventing them from contemplating irrelevant data and
rather pointing them to the relevant parts in the recordings. The
underlying idea is to learn the normal behaviour from available
recordings, i.e. a training set, and then to autonomously detect
unexpected deviations and report them as anomalies.
The one-class support vector machine “support vector data description”
is utilised to calculate distances of feature vectors. SVDDSUBSEQ
is proposed as a novel approach, allowing to classify subsequences
in multivariate time series data. The approach allows to
detect unexpected faults without modelling effort as is shown with
experimental results on recordings from test drives.
Abstract: Every organization is continually subject to new damages and threats which can be resulted from their operations or their goal accomplishment. Methods of providing the security of space and applied tools have been widely changed with increasing application and development of information technology (IT). From this viewpoint, information security management systems were evolved to construct and prevent reiterating the experienced methods. In general, the correct response in information security management systems requires correct decision making, which in turn requires the comprehensive effort of managers and everyone involved in each plan or decision making. Obviously, all aspects of work or decision are not defined in all decision making conditions; therefore, the possible or certain risks should be considered when making decisions. This is the subject of risk management and it can influence the decisions. Investigation of different approaches in the field of risk management demonstrates their progress from quantitative to qualitative methods with a process approach.
Abstract: We present a system that finds road boundaries and
constructs the virtual lane based on fusion data from a laser and a
monocular sensor, and detects forward vehicle position even in no lane
markers or bad environmental conditions. When the road environment
is dark or a lot of vehicles are parked on the both sides of the road, it is
difficult to detect lane and road boundary. For this reason we use
fusion of laser and vision sensor to extract road boundary to acquire
three dimensional data. We use parabolic road model to calculate road
boundaries which is based on vehicle and sensors state parameters and
construct virtual lane. And then we distinguish vehicle position in each
lane.
Abstract: Let k, t, d be arbitrary integers with k ≥ 2, t ≥ 0 and
d = k2 - k. In the first section we give some preliminaries from
Pell equations x2 - dy2 = 1 and x2 - dy2 = N, where N be any
fixed positive integer. In the second section, we consider the integer
solutions of Pell equations x2 - dy2 = 1 and x2 - dy2 = 2t. We
give a method for the solutions of these equations. Further we derive
recurrence relations on the solutions of these equations
Abstract: In this paper zero-dissipative explicit Runge-Kutta
method is derived for solving second-order ordinary differential
equations with periodical solutions. The phase-lag and dissipation
properties for Runge-Kutta (RK) method are also discussed. The new
method has algebraic order three with dissipation of order infinity.
The numerical results for the new method are compared with existing
method when solving the second-order differential equations with
periodic solutions using constant step size.
Abstract: This article provides empirical evidence on the effect
of domestic and international factors on the U.S. current account
deficit. Linear dynamic regression and vector autoregression models
are employed to estimate the relationships during the period from 1986
to 2011. The findings of this study suggest that the current and lagged
private saving rate and foreign current account for East Asian
economies have played a vital role in affecting the U.S. current
account. Additionally, using Granger causality tests and variance
decompositions, the change of the productivity growth and foreign
domestic demand are determined to influence significantly the change
of the U.S. current account. To summarize, the empirical relationship
between the U.S. current account deficit and its determinants is
sensitive to alternative regression models and specifications.
Abstract: A key to success of high quality software development
is to define valid and feasible requirements specification. We have
proposed a method of model-driven requirements analysis using
Unified Modeling Language (UML). The main feature of our method
is to automatically generate a Web user interface mock-up from UML
requirements analysis model so that we can confirm validity of
input/output data for each page and page transition on the system by
directly operating the mock-up. This paper proposes a support method
to check the validity of a data life cycle by using a model checking tool
“UPPAAL" focusing on CRUD (Create, Read, Update and Delete).
Exhaustive checking improves the quality of requirements analysis
model which are validated by the customers through automatically
generated mock-up. The effectiveness of our method is discussed by a
case study of requirements modeling of two small projects which are a
library management system and a supportive sales system for text
books in a university.
Abstract: Nevertheless the widespread application of finite
mixture models in segmentation, finite mixture model selection is
still an important issue. In fact, the selection of an adequate number
of segments is a key issue in deriving latent segments structures and
it is desirable that the selection criteria used for this end are effective.
In order to select among several information criteria, which may
support the selection of the correct number of segments we conduct a
simulation study. In particular, this study is intended to determine
which information criteria are more appropriate for mixture model
selection when considering data sets with only categorical
segmentation base variables. The generation of mixtures of
multinomial data supports the proposed analysis. As a result, we
establish a relationship between the level of measurement of
segmentation variables and some (eleven) information criteria-s
performance. The criterion AIC3 shows better performance (it
indicates the correct number of the simulated segments- structure
more often) when referring to mixtures of multinomial segmentation
base variables.
Abstract: Knowledge development in companies relies on
knowledge-intensive business processes, which are characterized by
a high complexity in their execution, weak structuring,
communication-oriented tasks and high decision autonomy, and often the need for creativity and innovation. A foundation of knowledge development is provided, which is based on a new conception of
knowledge and knowledge dynamics. This conception consists of a three-dimensional model of knowledge with types, kinds and qualities. Built on this knowledge conception, knowledge dynamics is
modeled with the help of general knowledge conversions between
knowledge assets. Here knowledge dynamics is understood to cover
all of acquisition, conversion, transfer, development and usage of
knowledge. Through this conception we gain a sound basis for
knowledge management and development in an enterprise. Especially
the type dimension of knowledge, which categorizes it according to
its internality and externality with respect to the human being, is crucial for enterprise knowledge management and development,
because knowledge should be made available by converting it to
more external types.
Built on this conception, a modeling approach for knowledgeintensive
business processes is introduced, be it human-driven,e-driven or task-driven processes. As an example for this approach, a model of the creative activity for the renewal planning of
a product is given.
Abstract: Let X be a connected space, X be a space, let p : X -→ X be a continuous map and let (X, p) be a covering space of X. In the first section we give some preliminaries from covering spaces and their automorphism groups. In the second section we derive some algebraic properties of both universal and regular covering spaces (X, p) of X and also their automorphism groups A(X, p).
Abstract: “Web of Trust" is one of the recognized goals for
Web 2.0. It aims to make it possible for the people to take
responsibility for what they publish on the web, including
organizations, businesses and individual users. These objectives,
among others, drive most of the technologies and protocols recently
standardized by the governing bodies. One of the great advantages of
Web infrastructure is decentralization of publication. The primary
motivation behind Web 2.0 is to assist the people to add contents for
Collective Intelligence (CI) while providing mechanisms to link
content with people for evaluations and accountability of
information. Such structure of contents will interconnect users and
contents so that users can use contents to find participants and vice
versa. This paper proposes conceptual information storage and
linking model, based on decentralized information structure, that
links contents and people together. The model uses FOAF, Atom,
RDF and RDFS and can be used as a blueprint to develop Web 2.0
applications for any e-domain. However, primary target for this
paper is online trust evaluation domain. The proposed model targets
to assist the individuals to establish “Web of Trust" in online trust
domain.
Abstract: Electrocardiogram (ECG) segmentation is necessary to help reduce the time consuming task of manually annotating ECG's. Several algorithms have been developed to segment the ECG automatically. We first review several of such methods, and then present a new single lead segmentation method based on Adaptive piecewise constant approximation (APCA) and Piecewise derivative dynamic time warping (PDDTW). The results are tested on the QT database. We compared our results to Laguna's two lead method. Our proposed approach has a comparable mean error, but yields a slightly higher standard deviation than Laguna's method.
Abstract: This paper examines the relationships between and
among the various drivers of climate change that have both climatic
and ecological consequences for vegetation and land cover change in
arctic areas, particularly in arctic Alaska. It discusses the various
processes that have created spatial and climatic structures that have
facilitated observable vegetation and land cover changes in the
Arctic. Also, it indicates that the drivers of both climatic and
ecological changes in the Arctic are multi-faceted and operate in a
system with both positive and negative feedbacks that largely results
in further increases or decreases of the initial drivers of climatic and
vegetation change mainly at the local and regional scales. It
demonstrates that the impact of arctic warming on land cover change
and the Arctic ecosystems is not unidirectional and one dimensional
in nature but it represents a multi-directional and multi-dimensional
forces operating in a feedback system.