Abstract: This qualitative, quantitative mixed-method study explores how students- motivation and interest in creative hands-on activities affected their conceptual understanding of science. The objectives of this research include developing a greater understanding about how creative activities, incorporated into the classroom as instructional strategies, increase student motivation and their learning or mastery of science concepts. The creative activities are viewed as a motivational tool, a specific type of task, which have an impact on student goals. Pre-and-post tests, pre-and-post interviews, and student responses measure motivational-goal theory variables, interest in the activity, and conceptual change. Implications for education and future research will be discussed.
Abstract: HIV-1 genome is highly heterogeneous. Due to this
variation, features of HIV-I genome is in a wide range. For this
reason, the ability to infection of the virus changes depending on
different chemokine receptors. From this point of view, R5 HIV
viruses use CCR5 coreceptor while X4 viruses use CXCR5 and
R5X4 viruses can utilize both coreceptors. Recently, in
Bioinformatics, R5X4 viruses have been studied to classify by using
the experiments on HIV-1 genome.
In this study, R5X4 type of HIV viruses were classified using
Auto Regressive (AR) model through Artificial Neural Networks
(ANNs). The statistical data of R5X4, R5 and X4 viruses was
analyzed by using signal processing methods and ANNs. Accessible
residues of these virus sequences were obtained and modeled by AR
model since the dimension of residues is large and different from
each other. Finally the pre-processed data was used to evolve various
ANN structures for determining R5X4 viruses. Furthermore ROC
analysis was applied to ANNs to show their real performances. The
results indicate that R5X4 viruses successfully classified with high
sensitivity and specificity values training and testing ROC analysis
for RBF, which gives the best performance among ANN structures.
Abstract: Metrics is the process by which numbers or symbols
are assigned to attributes of entities in the real world in such a way as
to describe them according to clearly defined rules. Software metrics
are instruments or ways to measuring all the aspect of software
product. These metrics are used throughout a software project to
assist in estimation, quality control, productivity assessment, and
project control. Object oriented software metrics focus on
measurements that are applied to the class and other characteristics.
These measurements convey the software engineer to the behavior of
the software and how changes can be made that will reduce
complexity and improve the continuing capability of the software.
Object oriented software metric can be classified in two types static
and dynamic. Static metrics are concerned with all the aspects of
measuring by static analysis of software and dynamic metrics are
concerned with all the measuring aspect of the software at run time.
Major work done before, was focusing on static metric. Also some
work has been done in the field of dynamic nature of the software
measurements. But research in this area is demanding for more work.
In this paper we give a set of dynamic metrics specifically for
polymorphism in object oriented system.
Abstract: Language Reforms and potential use of ICTs has been a focal area of Higher Education Commission of Pakistan. Efforts are being accelerated to incorporate fast expanding ICTs to bring qualitative improvement in language instruction in higher education. This paper explores how university teachers are benefitting from ICTs to make their English class effective and what type of problems they face in practicing ICTs during their lectures. An in-depth qualitative study was employed to understand why language teachers tend to use ICTs in their instruction and how they are practicing it. A sample of twenty teachers from five universities located in Islamabad, three from public sector and two from private sector, was selected on non-random (Snowball) sampling basis. An interview with 15 semi-structured items was used as research instruments to collect data. The findings reveal that business English teaching is facilitated and improved through the use of ICTs. The language teachers need special training regarding the practices and implementation of ICTs. It is recommended that initiatives might be taken to equip university language teachers with modern methodology incorporating ICTs as focal area and efforts might be made to remove barriers regarding the training of language teachers and proper usage of ICTs.
Abstract: Chinese Idioms are a type of traditional Chinese idiomatic
expressions with specific meanings and stereotypes structure
which are widely used in classical Chinese and are still common in
vernacular written and spoken Chinese today. Currently, Chinese
Idioms are retrieved in glossary with key character or key word in
morphology or pronunciation index that can not meet the need of
searching semantically. OCIRS is proposed to search the desired
idiom in the case of users only knowing its meaning without any key
character or key word. The user-s request in a sentence or phrase will
be grammatically analyzed in advance by word segmentation, key
word extraction and semantic similarity computation, thus can be
mapped to the idiom domain ontology which is constructed to provide
ample semantic relations and to facilitate description logics-based
reasoning for idiom retrieval. The experimental evaluation shows that
OCIRS realizes the function of searching idioms via semantics, obtaining
preliminary achievement as requested by the users.
Abstract: In this work, position vector of a time-like dual curve
according to standard frame of D31
is investigated. First, it is proven
that position vector of a time-like dual curve satisfies a dual vector
differential equation of fourth order. The general solution of this dual
vector differential equation has not yet been found. Due to this, in
terms of special solutions, position vectors of some special time-like
dual curves with respect to standard frame of D31
are presented.
Abstract: This paper presents a sensor-based motion planning algorithm for 3-DOF car-like robots with a nonholonomic constraint. Similar to the classic Bug family algorithms, the proposed algorithm enables the car-like robot to navigate in a completely unknown environment using only the range sensor information. The car-like robot uses the local range sensor view to determine the local path so that it moves towards the goal. To guarantee that the robot can approach the goal, the two modes of motion are repeated, termed motion-to-goal and wall-following. The motion-to-goal behavior lets the robot directly move toward the goal, and the wall-following behavior makes the robot circumnavigate the obstacle boundary until it meets the leaving condition. For each behavior, the nonholonomic motion for the car-like robot is planned in terms of the instantaneous turning radius. The proposed algorithm is implemented to the real robot and the experimental results show the performance of proposed algorithm.
Abstract: The various types of frequent pattern discovery
problem, namely, the frequent itemset, sequence and graph mining
problems are solved in different ways which are, however, in certain
aspects similar. The main approach of discovering such patterns can
be classified into two main classes, namely, in the class of the levelwise
methods and in that of the database projection-based methods.
The level-wise algorithms use in general clever indexing structures
for discovering the patterns. In this paper a new approach is proposed
for discovering frequent sequences and tree-like patterns efficiently
that is based on the level-wise issue. Because the level-wise
algorithms spend a lot of time for the subpattern testing problem, the
new approach introduces the idea of using automaton theory to solve
this problem.
Abstract: The image segmentation method described in this
paper has been developed as a pre-processing stage to be used in
methodologies and tools for video/image indexing and retrieval by
content. This method solves the problem of whole objects extraction
from background and it produces images of single complete objects
from videos or photos. The extracted images are used for calculating
the object visual features necessary for both indexing and retrieval
processes.
The segmentation algorithm is based on the cooperation among an
optical flow evaluation method, edge detection and region growing
procedures. The optical flow estimator belongs to the class of
differential methods. It permits to detect motions ranging from a
fraction of a pixel to a few pixels per frame, achieving good results in
presence of noise without the need of a filtering pre-processing stage
and includes a specialised model for moving object detection.
The first task of the presented method exploits the cues from
motion analysis for moving areas detection. Objects and background
are then refined using respectively edge detection and seeded region
growing procedures. All the tasks are iteratively performed until
objects and background are completely resolved.
The method has been applied to a variety of indoor and outdoor
scenes where objects of different type and shape are represented on
variously textured background.
Abstract: This paper considers the robust exponential stability issues for a class of uncertain switched neutral system which delays switched according to the switching rule. The system under consideration includes both stable and unstable subsystems. The uncertainties considered in this paper are norm bounded, and possibly time varying. Based on multiple Lyapunov functional approach and dwell-time technique, the time-dependent switching rule is designed depend on the so-called average dwell time of stable subsystems as well as the ratio of the total activation time of stable subsystems and unstable subsystems. It is shown that by suitably controlling the switching between the stable and unstable modes, the robust stabilization of the switched uncertain neutral systems can be achieved. Two simulation examples are given to demonstrate the effectiveness of the proposed method.
Abstract: In this study, an inland metropolitan area, Gwangju, in Korea was selected to assess the amplification potential of earthquake motion and provide the information for regional seismic countermeasure. A geographic information system-based expert system was implemented for reliably predicting the spatial geotechnical layers in the entire region of interesting by building a geo-knowledge database. Particularly, the database consists of the existing boring data gathered from the prior geotechnical projects and the surface geo-knowledge data acquired from the site visit. For practical application of the geo-knowledge database to estimate the earthquake hazard potential related to site amplification effects at the study area, seismic zoning maps on geotechnical parameters, such as the bedrock depth and the site period, were created within GIS framework. In addition, seismic zonation of site classification was also performed to determine the site amplification coefficients for seismic design at any site in the study area. KeywordsEarthquake hazard, geo-knowledge, geographic information system, seismic zonation, site period.
Abstract: Problem-based learning (PBL) is one of the student
centered approaches and has been considered by a number of higher
educational institutions in many parts of the world as a method of
delivery. This paper presents a creative thinking approach for
implementing Problem-based Learning in Mechanics of Structure
within a Malaysian Polytechnics environment. In the learning
process, students learn how to analyze the problem given among the
students and sharing classroom knowledge into practice. Further,
through this course-s emphasis on problem-based learning, students
acquire creative thinking skills and professional skills as they tackle
complex, interdisciplinary and real-situation problems. Once the
creative ideas are generated, there are useful additional techniques
for tender ideas that will grow into a productive concept or solution.
The combination of creative skills and technical abilities will enable
the students to be ready to “hit-the-ground-running" and produce in
industry when they graduate.
Abstract: A key element of many distribution systems is the
routing and scheduling of vehicles servicing a set of customers. A
wide variety of exact and approximate algorithms have been
proposed for solving the vehicle routing problems (VRP). Exact
algorithms can only solve relatively small problems of VRP, which is
classified as NP-Hard. Several approximate algorithms have proven
successful in finding a feasible solution not necessarily optimum.
Although different parts of the problem are stochastic in nature; yet,
limited work relevant to the application of discrete event system
simulation has addressed the problem. Presented here is optimization
using simulation of VRP; where, a simplified problem has been
developed in the ExtendSimTM simulation environment; where,
ExtendSimTM evolutionary optimizer is used to minimize the total
transportation cost of the problem. Results obtained from the model
are very satisfactory. Further complexities of the problem are
proposed for consideration in the future.
Abstract: Sonogram images of normal and lymphocyte thyroid tissues have considerable overlap which makes it difficult to interpret and distinguish. Classification from sonogram images of thyroid gland is tackled in semiautomatic way. While making manual diagnosis from images, some relevant information need not to be recognized by human visual system. Quantitative image analysis could be helpful to manual diagnostic process so far done by physician. Two classes are considered: normal tissue and chronic lymphocyte thyroid (Hashimoto's Thyroid). Data structure is analyzed using K-nearest-neighbors classification. This paper is mentioned that unlike the wavelet sub bands' energy, histograms and Haralick features are not appropriate to distinguish between normal tissue and Hashimoto's thyroid.
Abstract: This paper presents a new Hybrid Fuzzy (HF) PID type controller based on Genetic Algorithms (GA-s) for solution of the Automatic generation Control (AGC) problem in a deregulated electricity environment. In order for a fuzzy rule based control system to perform well, the fuzzy sets must be carefully designed. A major problem plaguing the effective use of this method is the difficulty of accurately constructing the membership functions, because it is a computationally expensive combinatorial optimization problem. On the other hand, GAs is a technique that emulates biological evolutionary theories to solve complex optimization problems by using directed random searches to derive a set of optimal solutions. For this reason, the membership functions are tuned automatically using a modified GA-s based on the hill climbing method. The motivation for using the modified GA-s is to reduce fuzzy system effort and take large parametric uncertainties into account. The global optimum value is guaranteed using the proposed method and the speed of the algorithm-s convergence is extremely improved, too. This newly developed control strategy combines the advantage of GA-s and fuzzy system control techniques and leads to a flexible controller with simple stricture that is easy to implement. The proposed GA based HF (GAHF) controller is tested on a threearea deregulated power system under different operating conditions and contract variations. The results of the proposed GAHF controller are compared with those of Multi Stage Fuzzy (MSF) controller, robust mixed H2/H∞ and classical PID controllers through some performance indices to illustrate its robust performance for a wide range of system parameters and load changes.
Abstract: In this paper, a class of impulsive BAM fuzzy cellular neural networks with time delays in the leakage terms is formulated and investigated. By establishing a delay differential inequality and M-matrix theory, some sufficient conditions ensuring the existence, uniqueness and global exponential stability of equilibrium point for impulsive BAM fuzzy cellular neural networks with time delays in the leakage terms are obtained. In particular, a precise estimate of the exponential convergence rate is also provided, which depends on system parameters and impulsive perturbation intention. It is believed that these results are significant and useful for the design and applications of BAM fuzzy cellular neural networks. An example is given to show the effectiveness of the results obtained here.
Abstract: Bioinformatics methods for predicting the T cell
coreceptor usage from the array of membrane protein of HIV-1 are
investigated. In this study, we aim to propose an effective prediction
method for dealing with the three-class classification problem of
CXCR4 (X4), CCR5 (R5) and CCR5/CXCR4 (R5X4). We made
efforts in investigating the coreceptor prediction problem as follows: 1)
proposing a feature set of informative physicochemical properties
which is cooperated with SVM to achieve high prediction test
accuracy of 81.48%, compared with the existing method with
accuracy of 70.00%; 2) establishing a large up-to-date data set by
increasing the size from 159 to 1225 sequences to verify the proposed
prediction method where the mean test accuracy is 88.59%, and 3)
analyzing the set of 14 informative physicochemical properties to
further understand the characteristics of HIV-1coreceptors.
Abstract: The concepts of knowledge creation and innovation
have a strong relationship but this relationship has not been examined
systematically. This study examines the utilization of knowledge
creation processes of the Theory of Knowledge Creation in Higher
Education Institutions. These processes consist of socialization,
externalization, combination and internalization. This study suggests
that the utilization of these processes will give impacts on innovation
in academic performance. A cross-sectional study was conducted
using survey questionnaires to collect data of the utilization of
knowledge creation processes and classroom-s innovation. The
samples are Business Management students of a Malaysian Higher
Education Institution. The results of this study could help Higher
Education Institutions to enrich the learning process of students
through knowledge creation and innovation.
Abstract: This research was aimed to develop and determine the
quality of online learning activities kit as well as to examine the
learning achievement of students and their satisfaction towards the kit
through authentic assessment. The tools in this research contained
online learning activities kit on plant in Thai literature in compliance
with the School Botanical Garden of Plant Genetic Conservation
Project under the Royal Initiative of Her Royal Highness Princess
Maha Chakri Sirindhorn, the assessment form, the learning
achievement test, the satisfaction form and the authentic assessment
form. The population consisted of 40 students in the second range of
primary years (Prathomsuksa 4 to 6) at Ban Khao Rak School,
Suratthani Province, Thailand. The research results showed that the
content quality of the developed online learning activities kit as
assessed by the experts was 4.70 on average or at very high level.
The pre-test and post-test comparison was made to examine the
learning achievement and it revealed that the post-test score was
higher than the pre-test score with statistical significance at the .01
level. The satisfaction of the sampling group towards the online
learning activities kit was 4.74 or at the highest level. The authentic
assessment showed an average of 1.69 or at good level. Therefore,
the online learning activities kit on plant in Thai literature in
compliance with the School Botanical Garden of Plant Genetic
Conservation Project under the Royal Initiative of Her Royal
Highness Princess Maha Chakri Sirindhorn could be used in real
classroom situations.
Abstract: Steganography is the art of hiding and transmitting data
through apparently innocuous carriers in an effort to conceal the
existence of the data. A lot of steganography algorithms have been
proposed recently. Many of them use the digital image data as a carrier.
In data hiding scheme of halftoning and coordinate projection, still
image data is used as a carrier, and the data of carrier image are
modified for data embedding. In this paper, we present three features
for analysis of data hiding via halftoning and coordinate projection.
Also, we present a classifier using the proposed three features.