Abstract: The vocational education, enhanced by technology and Recognition of Prior Learning (RPL) is going to be the main ingredient of the future of education. This is coming from the various issues of the current educational system like cost, time, type of course, type of curriculum, unemployment, to name the major reasons. Most millennials like to perform and learn rather than learning how to perform. This is the essence of vocational education be it any field from cooking, painting, plumbing to modern technologies using computers. Even a more theoretical course like entrepreneurship can be taught as to be an entrepreneur and learn about its nuances. The best way to learn accountancy is actually keeping accounts for a small business or grocer and learn the ropes of accountancy and finance. The purpose of this study is to investigate the relationship between vocational skills, RPL and new technologies with future employability. This study implies that individual's knowledge and skills are essential aspects to be emphasized in future education and to give credit for prior experience for future employability. Virtual reality can be used to stimulate workplace situations for vocational learning for fields like hospitality, medical emergencies, healthcare, draughtsman ship, building inspection, quantity surveying, estimation, to name a few. All disruptions in future education, especially vocational education, are going to be technology driven with the advent of AI, ML, IoT, VR, VI etc. Vocational education not only helps institutes cut costs drastically, but allows all students to have hands-on experiences, rather than to be observers. The earlier experiential learning theory and the recent theory of knowledge and skills-based learning modified and applied to the vocational education and development of skills is the proposed contribution of this paper. Apart from secondary research study on major scholarly articles, books, primary research using interviews, questionnaire surveys have been used to validate and test the reliability of the suggested model using Partial Least Square- Structural Equation Method (PLS-SEM), the factors being assimilated using an existing literature review. Major findings have been that there exists high relationship between the vocational skills, RPL, new technology to the future employability through mediation of future employability skills.
Abstract: The psychological present has an actual extension.
When a sequence of instantaneous stimuli falls in this short interval
of time, observers perceive a compresence of events in succession
and the temporal order depends on the qualitative relationships
between the perceptual properties of the events. Two experiments
were carried out to study the influence of perceptual grouping, with
and without temporal displacement, on the duration of auditory
sequences. The psychophysical method of adjustment was adopted.
The first experiment investigated the effect of temporal displacement
of a white noise on sequence duration. The second experiment
investigated the effect of temporal displacement, along the pitch
dimension, on temporal shortening of sequence. The results suggest
that the temporal order of sounds, in the case of temporal
displacement, is organized along the pitch dimension.
Abstract: Digital technologies offer many opportunities in the
design and implementation of brand communication and advertising.
Augmented reality (AR) is an innovative technology in marketing
communication that focuses on the fact that virtual interaction with a
product ad offers additional value to consumers. AR enables
consumers to obtain (almost) real product experiences by the way of
virtual information even before the purchase of a certain product.
Aim of AR applications in relation with advertising is in-depth
examination of product characteristics to enhance product knowledge
as well as brand knowledge. Interactive design of advertising
provides observers with an intense examination of a specific
advertising message and therefore leads to better brand knowledge.
The elaboration likelihood model and the central route to persuasion
strongly support this argumentation. Nevertheless, AR in brand
communication is still in an initial stage and therefore scientific
findings about the impact of AR on information processing and brand
attitude are rare. The aim of this paper is to empirically investigate
the potential of AR applications in combination with traditional print
advertising. To that effect an experimental design with different
levels of interactivity is built to measure the impact of interactivity of
an ad on different variables o advertising effectiveness.
Abstract: The goal of the present paper is to model two classic lines of research in which employees starred, organizational justice and citizenship behavior (OCB), but that have never been studied together when targeting customers. The suggestion is made that a hotel’s fair treatment (in terms of distributive, procedural, and interactional justice) toward customers will be appreciated by the employees, who will reciprocate in kind by favoring the hotel with increased customer-oriented behaviors (COBs). Data were collected from 204 employees at eight upscale hotels in the Canary Islands (Spain). Unlike in the case of perceptions of distributive justice, results of structural equation modeling demonstrate that employees substantively react to interactional and procedural justice toward guests by engaging in customer-oriented behaviors (COBs). The findings offer new reasons why employees decide to engage in COBs, and they highlight potentially beneficial effects of fair treatment toward guests bring to hospitality through promoting COBs.
Abstract: In this paper, we use Generalized Hamiltonian systems approach to synchronize a modified sixth-order Chua's circuit, which generates hyperchaotic dynamics. Synchronization is obtained between the master and slave dynamics with the slave being given by an observer. We apply this approach to transmit private information (analog and binary), while the encoding remains potentially secure.
Abstract: Based on general proportional integral (GPI) observers and sliding mode control technique, a robust control method is proposed for the master-slave synchronization of chaotic systems in the presence of parameter uncertainty and with partially measurable output signal. By using GPI observer, the master dynamics are reconstructed by the observations from a measurable output under the differential algebraic framework. Driven by the signals provided by GPI observer, a sliding mode control technique is used for the tracking control and synchronization of the master-slave dynamics. The convincing numerical results reveal the proposed method is effective, and successfully accommodate the system uncertainties, disturbances, and noisy corruptions.
Abstract: Polynomial maps offer analytical properties used to obtain better performances in the scope of chaos synchronization under noisy channels. This paper presents a new method to simplify equations of the Exact Polynomial Kalman Filter (ExPKF) given in [1]. This faster algorithm is compared to other estimators showing that performances of all considered observers vanish rapidly with the channel noise making application of chaos synchronization intractable. Simulation of ExPKF shows that saturation drawn on the emitter to keep it stable impacts badly performances for low channel noise. Then we propose a particle filter that outperforms all other Kalman structured observers in the case of noisy channels.
Abstract: The recent trend in field oriented control (FOC) is towards the use of sensorless techniques that avoid the use of speed sensor and flux sensor. Sensors are replaced by estimators or observers to minimise the cost and increase the reliability. In this paper an anlyse of perfomance of a MRAS used in sensorless control of induction motors and sensitvity to machine parameters change are studied.
Abstract: Adaptive observers used in sensorless control of induction motors suffer from instability especally in regenerating mode. In this paper, an optimal feed back gain design is proposed, it can reduce the instability region in the torque speed plane .
Abstract: A model based fault detection and diagnosis
technique for DC motor is proposed in this paper. Fault detection
using Kalman filter and its different variants are compared. Only
incipient faults are considered for the study. The Kalman Filter
iterations and all the related computations required for fault detection
and fault confirmation are presented. A second order linear state
space model of DC motor is used for this work. A comparative
assessment of the estimates computed from four different observers
and their relative performance is evaluated.
Abstract: This paper shows a new method for design of fuzzy observers for Takagi-Sugeno systems. The method is based on Linear matrix inequalities (LMIs) and it allows to insert H constraint into the design procedure. The speed of estimation can tuned be specification of a decay rate of the observer closed loop system. We discuss here also the influence of parametric uncertainties at the output control system stability.
Abstract: In this paper, the performance of two adaptive
observers applied to interconnected systems is studied. The
nonlinearity of systems can be written in a fractional form. The first
adaptive observer is an adaptive sliding mode observer for a Lipchitz
nonlinear system and the second one is an adaptive sliding mode
observer having a filtered error as a sliding surface. After comparing
their performances throughout the inverted pendulum mounted on a
car system, it was shown that the second one is more robust to
estimate the state.
Abstract: A methodology to design a nonlinear observer in a
bond graph approach is proposed. The class of nonlinear observer
with multivariable nonlinearities is considered. A junction structure
of the bond graph observer is proposed. The proposed methodology
to an electrical transformer and a DC motor including the nonlinear
saturation is applied. Nonlinear observers for the transformer and DC
motor based on multivariable circle criterion in the physical domain
are proposed. In order to show the saturation effects on the
transformer and DC motor, simulation results are obtained. Finally,
the paper describes that convergence of the estimates to the true
states is achieved.
Abstract: A new observer based fault detection and diagnosis
scheme for predicting induction motors- faults is proposed in this
paper. Prediction of incipient faults, using different variants of
Kalman filter and their relative performance are evaluated. Only soft
faults are considered for this work. The data generation, filter
convergence issues, hypothesis testing and residue estimates are
addressed. Simulink model is used for data generation and various
types of faults are considered. A comparative assessment of the
estimates of different observers associated with these faults is
included.
Abstract: This paper discusses two observers, which are used
for the estimation of parameters of PMSM. Former one, reduced
order observer, which is used to estimate the inaccessible parameters
of PMSM. Later one, full order observer, which is used to estimate
all the parameters of PMSM even though some of the parameters are
directly available for measurement, so as to meet with the
insensitivity to the parameter variation. However, the state space
model contains some nonlinear terms i.e. the product of different
state variables. The asymptotic state observer, which approximately
reconstructs the state vector for linear systems without uncertainties,
was presented by Luenberger. In this work, a modified form of such
an observer is used by including a non-linear term involving the
speed. So, both the observers are designed in the framework of
nonlinear control; their stability and rate of convergence is discussed.
Abstract: Fisheries management all around the world is
hampered by the lack, or poor quality, of critical data on fish
resources and fishing operations. The main reasons for the chronic
inability to collect good quality data during fishing operations is the
culture of secrecy common among fishers and the lack of modern
data gathering technology onboard most fishing vessels. In response,
OLRAC-SPS, a South African company, developed fisheries datalogging
software (eLog in short) and named it Olrac. The Olrac eLog
solution is capable of collecting, analysing, plotting, mapping,
reporting, tracing and transmitting all data related to fishing
operations. Olrac can be used by skippers, fleet/company managers,
offshore mariculture farmers, scientists, observers, compliance
inspectors and fisheries management authorities. The authors believe
that using eLog onboard fishing vessels has the potential to
revolutionise the entire process of data collection and reporting
during fishing operations and, if properly deployed and utilised,
could transform the entire commercial fleet to a provider of good
quality data and forever change the way fish resources are managed.
In addition it will make it possible to trace catches back to the actual
individual fishing operation, to improve fishing efficiency and to
dramatically improve control of fishing operations and enforcement
of fishing regulations.