Abstract: This paper describes the evolution of strategies to
evaluate ePortfolios in an online Master-s of Education (M.Ed.)
degree in Instructional Technology. The ePortfolios are required as a
culminating activity for students in the program. By using Web 2.0
tools to develop the ePortfolios, students are able to showcase their
technical skills, integrate national standards, demonstrate their
professional understandings, and reflect on their individual learning.
Faculty have created assessment strategies to evaluate student
achievement of these skills. To further develop ePortfolios as a tool
promoting authentic learning, faculty are moving toward integrating
transparency as part of the evaluation process.
Abstract: Author presents the results of a study conducted to identify criteria of efficient information system (IS) with serviceoriented architecture (SOA) realization and proposes a ranking method to evaluate SOA information systems using a set of architecture quality criteria before the systems are implemented. The method is used to compare 7 SOA projects and ranking result for SOA efficiency of the projects is provided. The choice of SOA realization project depends on following criteria categories: IS internal work and organization, SOA policies, guidelines and change management, processes and business services readiness, risk management and mitigation. The last criteria category was analyzed on the basis of projects statistics.
Abstract: A new approach is adopted in this paper based
on Turk and Pentland-s eigenface method. It was found that the
probability density function of the distance between the projection
vector of the input face image and the average projection vector of
the subject in the face database, follows Rayleigh distribution. In
order to decrease the false acceptance rate and increase the
recognition rate, the input face image has been recognized using two
thresholds including the acceptance threshold and the rejection
threshold. We also find out that the value of two thresholds will be
close to each other as number of trials increases. During the training,
in order to reduce the number of trials, the projection vectors for each
subject has been averaged. The recognition experiments using the
proposed algorithm show that the recognition rate achieves to
92.875% whilst the average number of judgment is only 2.56 times.
Abstract: Traditional Javanese classic dance is a valuable
inheritance in Java Indonesia. Nowadays, this treasure of culture is
no longer belonging to Javanese people only. Many art departments
from universities around the world already put this as a subject in
their curriculum. Nonetheless, dance is a practical skill. It needs to be
practices so often while accompanied by an instructor to get the right
technique. An interactive Computer Aided Instruction (iCAI) that can
interactively assist the student to practice is developed. By using this
software students can conduct a self practice in studio and get some
feedbacks from the software. This CAI is not intended to replace the
instructor, but to assist them in increasing the student fly-time in
practice.
Abstract: Requirements management is critical to software
delivery success and project lifecycle. Requirements management
and their traceability provide assistance for many software
engineering activities like impact analysis, coverage analysis,
requirements validation and regression testing. In addition
requirements traceability is the recognized component of many
software process improvement initiatives. Requirements traceability
also helps to control and manage evolution of a software system.
This paper aims to provide an evaluation of current requirements
management and traceability tools. Management and test managers
require an appropriate tool for the software under test. We hope,
evaluation identified here will help to select the efficient and
effective tool.
Abstract: Cytogenetic analysis still remains the gold standard method for prenatal diagnosis of trisomy 21 (Down syndrome, DS). Nevertheless, the conventional cytogenetic analysis needs live cultured cells and is too time-consuming for clinical application. In contrast, molecular methods such as FISH, QF-PCR, MLPA and quantitative Real-time PCR are rapid assays with results available in 24h. In the present study, we have successfully used a novel MGB TaqMan probe-based real time PCR assay for rapid diagnosis of trisomy 21 status in Down syndrome samples. We have also compared the results of this molecular method with corresponding results obtained by the cytogenetic analysis. Blood samples obtained from DS patients (n=25) and normal controls (n=20) were tested by quantitative Real-time PCR in parallel to standard G-banding analysis. Genomic DNA was extracted from peripheral blood lymphocytes. A high precision TaqMan probe quantitative Real-time PCR assay was developed to determine the gene dosage of DSCAM (target gene on 21q22.2) relative to PMP22 (reference gene on 17p11.2). The DSCAM/PMP22 ratio was calculated according to the formula; ratio=2 -ΔΔCT. The quantitative Real-time PCR was able to distinguish between trisomy 21 samples and normal controls with the gene ratios of 1.49±0.13 and 1.03±0.04 respectively (p value
Abstract: In this paper, a new learning algorithm based on a
hybrid metaheuristic integrating Differential Evolution (DE) and
Reduced Variable Neighborhood Search (RVNS) is introduced to train
the classification method PROAFTN. To apply PROAFTN, values of
several parameters need to be determined prior to classification. These
parameters include boundaries of intervals and relative weights for
each attribute. Based on these requirements, the hybrid approach,
named DEPRO-RVNS, is presented in this study. In some cases, the
major problem when applying DE to some classification problems
was the premature convergence of some individuals to local optima.
To eliminate this shortcoming and to improve the exploration and
exploitation capabilities of DE, such individuals were set to iteratively
re-explored using RVNS. Based on the generated results on
both training and testing data, it is shown that the performance of
PROAFTN is significantly improved. Furthermore, the experimental
study shows that DEPRO-RVNS outperforms well-known machine
learning classifiers in a variety of problems.
Abstract: Medical image segmentation based on image smoothing followed by edge detection assumes a great degree of importance in the field of Image Processing. In this regard, this paper proposes a novel algorithm for medical image segmentation based on vigorous smoothening by identifying the type of noise and edge diction ideology which seems to be a boom in medical image diagnosis. The main objective of this algorithm is to consider a particular medical image as input and make the preprocessing to remove the noise content by employing suitable filter after identifying the type of noise and finally carrying out edge detection for image segmentation. The algorithm consists of three parts. First, identifying the type of noise present in the medical image as additive, multiplicative or impulsive by analysis of local histograms and denoising it by employing Median, Gaussian or Frost filter. Second, edge detection of the filtered medical image is carried out using Canny edge detection technique. And third part is about the segmentation of edge detected medical image by the method of Normalized Cut Eigen Vectors. The method is validated through experiments on real images. The proposed algorithm has been simulated on MATLAB platform. The results obtained by the simulation shows that the proposed algorithm is very effective which can deal with low quality or marginal vague images which has high spatial redundancy, low contrast and biggish noise, and has a potential of certain practical use of medical image diagnosis.
Abstract: As a method of expanding a higher-order tensor data to tensor products of vectors we have proposed the Third-order Orthogonal Tensor Product Expansion (3OTPE) that did similar expansion as Higher-Order Singular Value Decomposition (HOSVD). In this paper we provide a computation algorithm to improve our previous method, in which SVD is applied to the matrix that constituted by the contraction of original tensor data and one of the expansion vector obtained. The residual of the improved method is smaller than the previous method, truncating the expanding tensor products to the same number of terms. Moreover, the residual is smaller than HOSVD when applying to color image data. It is able to be confirmed that the computing time of improved method is the same as the previous method and considerably better than HOSVD.
Abstract: AAM has been successfully applied to face alignment,
but its performance is very sensitive to initial values. In case the initial
values are a little far distant from the global optimum values, there
exists a pretty good possibility that AAM-based face alignment may
converge to a local minimum. In this paper, we propose a progressive
AAM-based face alignment algorithm which first finds the feature
parameter vector fitting the inner facial feature points of the face and
later localize the feature points of the whole face using the first
information. The proposed progressive AAM-based face alignment
algorithm utilizes the fact that the feature points of the inner part of the
face are less variant and less affected by the background surrounding
the face than those of the outer part (like the chin contour). The
proposed algorithm consists of two stages: modeling and relation
derivation stage and fitting stage. Modeling and relation derivation
stage first needs to construct two AAM models: the inner face AAM
model and the whole face AAM model and then derive relation matrix
between the inner face AAM parameter vector and the whole face
AAM model parameter vector. In the fitting stage, the proposed
algorithm aligns face progressively through two phases. In the first
phase, the proposed algorithm will find the feature parameter vector
fitting the inner facial AAM model into a new input face image, and
then in the second phase it localizes the whole facial feature points of
the new input face image based on the whole face AAM model using
the initial parameter vector estimated from using the inner feature
parameter vector obtained in the first phase and the relation matrix
obtained in the first stage. Through experiments, it is verified that the
proposed progressive AAM-based face alignment algorithm is more
robust with respect to pose, illumination, and face background than the
conventional basic AAM-based face alignment algorithm.
Abstract: This paper investigates the effects of knowledge-based acceleration feedback control integrated with Automatic Generation Control (AGC) to enhance the quality of frequency control of governing system. The Intelligent Acceleration Feedback Controller (IAFC) is proposed to counter the over and under frequency occurrences due to major load change in power system network. Therefore, generator tripping and load shedding operations can be reduced. Meanwhile, the integration of IAFC with AGC, a well known Load-Frequency Control (LFC) is essential to ensure the system frequency is restored to the nominal value. Computer simulations of frequency response of governing system are used to optimize the parameters of IAFC. As a result, there is substantial improvement on the LFC of governing system that employing the proposed control strategy.
Abstract: In this study, the theoretical relationship between pressure and density was investigated on cylindrical hollow fuel briquettes produced of a mixture of fibrous biomass material using a screw press without any chemical binder. The fuel briquettes were made of biomass and other waste material such as spent coffee beans, mielie husks, saw dust and coal fines under pressures of 0.878-2.2 Mega Pascals (MPa). The material was densified into briquettes of outer diameter of 100mm, inner diameter of 35mm and 50mm long. It was observed that manual screw compression action produces briquettes of relatively low density as compared to the ones made using hydraulic compression action. The pressure and density relationship was obtained in the form of power law and compare well with other cylindrical solid briquettes made using hydraulic compression action. The produced briquettes have a dry density of 989 kg/m3 and contain 26.30% fixed carbon, 39.34% volatile matter, 10.9% moisture and 10.46% ash as per dry proximate analysis. The bomb calorimeter tests have shown the briquettes yielding a gross calorific value of 18.9MJ/kg.
Abstract: The aim of this study is to test the “work values"
inventory developed by Tevruz and Turgut and to utilize the concept
in a model, which aims to create a greater understanding of the work
experience. In the study multiple effects of work values, work-value
congruence and work centrality on organizational citizenship
behavior are examined. In this respect, it is hypothesized that work
values and work-value congruence predict organizational citizenship
behavior through work centrality. Work-goal congruence test, Tevruz
and Turgut-s work values inventory are administered along with
Kanungo-s work centrality and Podsakoff et al.-s [47] organizational
citizenship behavior test to employees working in Turkish SME-s.
The study validated that Tevruz and Turgut-s work values inventory
and the work-value congruence test were reliable and could be used
for future research. The study revealed the mediating role of work
centrality only for the relationship of work values and the
responsibility dimension of citizenship behavior. Most important, this
study brought in an important concept, work-value congruence,
which enables a better understanding of work values and their
relation to various attitudinal variables.
Abstract: Persuasive technology has been applied in marketing,
health, environmental conservation, safety and other domains and is
found to be quite effective in changing people-s attitude and
behaviours. This research extends the application domains of
persuasive technology to information security awareness and uses a
theory-driven approach to evaluate the effectiveness of a web-based
program developed based on the principles of persuasive technology
to improve the information security awareness of end users. The
findings confirm the existence of a very strong effect of the webbased
program in raising users- attitude towards information security
aware behavior. This finding is useful to the IT researchers and
practitioners in developing appropriate and effective education
strategies for improving the information security attitudes for endusers.
Abstract: This research explores on the development of the structure of Carbon Credit Registry System those accords to the need of future events in Thailand. This research also explores the big picture of every connected system by referring to the design of each system, the Data Flow Diagram, and the design in term of the system-s data using DES standard. The purpose of this paper is to show how to design the model of each system. Furthermore, this paper can serve as guideline for designing an appropriate Carbon Credit Registry System.
Abstract: Most papers model Joint Replenishment Problem
(JRP) as a (kT,S) where kT is a multiple value for a common review
period T,and S is a predefined order up to level. In general the (T,S)
policy is characterized by a long out of control period which requires
a large amount of safety stock compared to the (R,Q) policy. In this
paper a probabilistic model is built where an item, call it item(i),
with the shortest order time between interval (T)is modeled under
(R,Q) policy and its inventory is continuously reviewed, while the
rest of items (j) are periodically reviewed at a definite time
corresponding to item
Abstract: The method of gait identification based on the nearest neighbor classification technique with motion similarity assessment by the dynamic time warping is proposed. The model based kinematic motion data, represented by the joints rotations coded by Euler angles and unit quaternions is used. The different pose distance functions in Euler angles and quaternion spaces are considered. To evaluate individual features of the subsequent joints movements during gait cycle, joint selection is carried out. To examine proposed approach database containing 353 gaits of 25 humans collected in motion capture laboratory is used. The obtained results are promising. The classifications, which takes into consideration all joints has accuracy over 91%. Only analysis of movements of hip joints allows to correctly identify gaits with almost 80% precision.
Abstract: The performance of high-resolution schemes is investigated for unsteady, inviscid and compressible multiphase flows. An Eulerian diffuse interface approach has been chosen for the simulation of multicomponent flow problems. The reduced fiveequation and seven equation models are used with HLL and HLLC approximation. The authors demonstrated the advantages and disadvantages of both seven equations and five equations models studying their performance with HLL and HLLC algorithms on simple test case. The seven equation model is based on two pressure, two velocity concept of Baer–Nunziato [10], while five equation model is based on the mixture velocity and pressure. The numerical evaluations of two variants of Riemann solvers have been conducted for the classical one-dimensional air-water shock tube and compared with analytical solution for error analysis.
Abstract: Freeze concentration freezes or crystallises the water
molecules out as ice crystals and leaves behind a highly concentrated
solution. In conventional suspension freeze concentration where ice
crystals formed as a suspension in the mother liquor, separation of
ice is difficult. The size of the ice crystals is still very limited which
will require usage of scraped surface heat exchangers, which is very
expensive and accounted for approximately 30% of the capital cost.
This research is conducted using a newer method of freeze
concentration, which is progressive freeze concentration. Ice crystals
were formed as a layer on the designed heat exchanger surface. In
this particular research, a helical structured copper crystallisation
chamber was designed and fabricated. The effect of two operating
conditions on the performance of the newly designed crystallisation
chamber was investigated, which are circulation flowrate and coolant
temperature. The performance of the design was evaluated by the
effective partition constant, K, calculated from the volume and
concentration of the solid and liquid phase. The system was also
monitored by a data acquisition tool in order to see the temperature
profile throughout the process. On completing the experimental
work, it was found that higher flowrate resulted in a lower K, which
translated into high efficiency. The efficiency is the highest at 1000
ml/min. It was also found that the process gives the highest
efficiency at a coolant temperature of -6 °C.
Abstract: This work is a proposed model of CMOS for which
the algorithm has been created and then the performance evaluation
of this proposition has been done. In this context, another commonly
used model called ZSTT (Zero Switching Time Transient) model is
chosen to compare all the vital features and the results for the
Proposed Equivalent CMOS are promising. In the end, the excerpts
of the created algorithm are also included