Abstract: Individuals are generally associated with different learning styles, which have been explored extensively in recent past. The learning styles refer to the potential of an individual by which s/he can easily comprehend and retain information. Among various learning style models, VARK is the most accepted model which categorizes the learners with respect to their sensory characteristics. Based on the number of preferred learning modes, the learners can be categorized as uni-modal, bi-modal, tri-modal, or quad/multi-modal. Although there is a prevalent belief in the learning styles, however, the model is not being frequently and effectively utilized in the higher education. This research describes the identification model to validate teacher’s didactic practice and student’s performance linkage with the learning styles. The identification model is recommended to check the effective application and evaluation of the various learning styles. The proposed model is a guideline to effectively implement learning styles inventory in order to ensure that it will validate performance linkage with learning styles. If performance is linked with learning styles, this may help eradicate the distrust on learning style theory. For this purpose, a comprehensive study was conducted to compare and understand how VARK inventory model is being used to identify learning preferences and their correlation with learner’s performance. A comparative analysis of the findings of these studies is presented to understand the learning styles of tertiary students in various disciplines. It is concluded with confidence that the learning styles of students cannot be associated with any specific discipline. Furthermore, there is not enough empirical proof to link performance with learning styles.
Abstract: Diabetes is a medical condition that can lead to various diseases such as stroke, heart disease, blindness and obesity. In clinical practice, the concern of the diabetic patients towards the blood glucose examination is rather alarming as some of the individual describing it as something painful with pinprick and pinch. As for some patient with high level of glucose level, pricking the fingers multiple times a day with the conventional glucose meter for close monitoring can be tiresome, time consuming and painful. With these concerns, several non-invasive techniques were used by researchers in measuring the glucose level in blood, including ultrasonic sensor implementation, multisensory systems, absorbance of transmittance, bio-impedance, voltage intensity, and thermography. This paper is discussing the application of the near-infrared (NIR) spectroscopy as a non-invasive method in measuring the glucose level and the implementation of the linear system identification model in predicting the output data for the NIR measurement. In this study, the wavelengths considered are at the 1450 nm and 1950 nm. Both of these wavelengths showed the most reliable information on the glucose presence in blood. Then, the linear Autoregressive Moving Average Exogenous model (ARMAX) model with both un-regularized and regularized methods was implemented in predicting the output result for the NIR measurement in order to investigate the practicality of the linear system in this study. However, the result showed only 50.11% accuracy obtained from the system which is far from the satisfying results that should be obtained.
Abstract: The article demonstrates on a case study how it is
possible to identify MSD risk. It is based on a dissertation Risk
identification model of occupational diseases formation in relation to
the work activity that determines what risk can endanger workers who
are exposed to the specific risk factors. It is evaluated based on
statistical calculations. These risk factors are main cause of upperextremities
musculoskeletal disorders.
Abstract: In this paper the problem of estimating the time delay
between two spatially separated noisy sinusoidal signals by system
identification modeling is addressed. The system is assumed to be
perturbed by both input and output additive white Gaussian noise. The
presence of input noise introduces bias in the time delay estimates.
Normally the solution requires a priori knowledge of the input-output
noise variance ratio. We utilize the cascade of a self-tuned filter with
the time delay estimator, thus making the delay estimates robust to
input noise. Simulation results are presented to confirm the superiority
of the proposed approach at low input signal-to-noise ratios.
Abstract: The nonlinear damping behavior is usually ignored in
the design of a miniature moving-coil loudspeaker. But when the
loudspeaker operated in air, the damping parameter varies with the
voice-coil displacement corresponding due to viscous air flow. The
present paper presents an identification model as inverse problem to
identify the nonlinear damping parameter in the lumped parameter
model for the loudspeaker. Theoretical results for the nonlinear
damping are verified by using laser displacement measurement
scanner. These results indicate that the damping parameter has the
greatly different nonlinearity between in air and vacuum. It is believed
that the results of the present work can be applied in diagnosis and
sound quality improvement of a miniature loudspeaker.
Abstract: Jordan exerts many efforts to nurture their academically gifted students in special schools since 2001. During
the past nine years of launching these schools, their learning and excellence environments were believed to be distinguished compared
to public schools. This study investigated the environments of gifted
students compared with other non-gifted, using a survey instrument
that measures the dimensions of family, peers, teachers, school- support, society, and resources –dimensions rooted deeply in supporting gifted education, learning, and achievement. A total
number of 109 were selected from excellence schools for
academically gifted students, and 119 non-gifted students were selected from public schools. Around 8.3% of the non-gifted students
reported that they “Never" received any support from their surrounding environments, 14.9% reported “Seldom" support, 23.7% reported “ Often" support, 26.0% reported “Frequent" support, and
32.8% reported “Very frequent" support. Where the gifted students reported more “Never" support than the non-gifted did with 11.3%,
“Seldom" support with 15.4%, “Often" support with 26.6%,
“Frequent" support with 29.0%, and reported “Very frequent" support less than the non-gifted students with 23.6%. Unexpectedly,
statistical differences were found between the two groups favoring
non-gifted students in perception of their surrounding environments
in specific dimensions, namely, school- support, teachers, and society. No statistical differences were found in the other dimensions
of the survey, namely, family, peers, and resources. As the
differences were found in teachers, school- support, and society, the
nurturing environments for the excellence schools need to be revised to adopt more creative teaching styles, rich school atmosphere and
infrastructures, interactive guiding for the students and their parents, promoting for the excellence environments, and re-build successful
identification models. Thus, families, schools, and society should
increase their cooperation, communication, and awareness of the
gifted supportive environments. However, more studies to investigate
other aspects of promoting academic giftedness and excellence are recommended.