Abstract: A face recognition system is a computer application for automatically identifying or verifying a person from a digital image or a video frame. A lot of algorithms have been proposed for face recognition. Vector Quantization (VQ) based face recognition is a novel approach for face recognition. Here a new codebook generation for VQ based face recognition using Integrated Adaptive Fuzzy Clustering (IAFC) is proposed. IAFC is a fuzzy neural network which incorporates a fuzzy learning rule into a competitive neural network. The performance of proposed algorithm is demonstrated by using publicly available AT&T database, Yale database, Indian Face database and a small face database, DCSKU database created in our lab. In all the databases the proposed approach got a higher recognition rate than most of the existing methods. In terms of Equal Error Rate (ERR) also the proposed codebook is better than the existing methods.
Abstract: The new, polymer composites consisting of e-glass fiber reinforcement with titanium oxide filler in the double bonded unsaturated polyester resin matrix were made. The glass fiber and titanium oxide reinforcement composites were made in three different fiber lengths (3cm, 5cm, and 7cm), filler content (2 wt%, 4 wt%, and 6 wt%) and fiber content (20 wt%, 40 wt%, and 60 wt%). 27 different compositions were fabricated and a sequence of experiments were carried out to determine tensile strength and impact strength. The vital influencing factors fiber length, fiber content and filler content were chosen as 3 factors in 3 levels of Taguchi’s L9 orthogonal array. The influences of parameters were determined for tensile strength and impact strength by Analysis of variance (ANOVA) and S/N ratio. Using Artificial Neural Network (ANN) an expert system was devised to predict the properties of hybrid reinforcement GFRP composites. The predict models were experimentally proved with the maximum coincidence.
Abstract: Prediction of future research topics by using time series analysis either statistical or machine learning has been conducted previously by several researchers. Several methods have been proposed to combine the forecasting results into single forecast. These methods use fixed combination of individual forecast to get the final forecast result. In this paper, quite different approach is employed to select the forecasting methods, in which every point to forecast is calculated by using the best methods used by similar validation dataset. The dataset used in the experiment is time series derived from research report in Garuda, which is an online sites belongs to the Ministry of Education in Indonesia, over the past 20 years. The experimental result demonstrates that the proposed method may perform better compared to the fix combination of predictors. In addition, based on the prediction result, we can forecast emerging research topics for the next few years.
Abstract: Most of college students in Taiwan do not have sufficient English proficiency to express themselves in written English. Teachers spent a lot of time correcting the errors in students’ English writing, but the results are not satisfactory. This study aims to use blogs as a teaching and learning tool in written English. Before applying peer assessment, students should be trained to be good reviewers. The teacher starts the course by posting the error analysis of students’ first English composition on blogs as the comment models for students. Then the students will go through the process of drafting, composing, peer response and last revision on blogs. Evaluation questionnaires and interviews will be conducted at the end of the course to see the impact and also students’ perception for the course.
Abstract: The main focus of this study is investigating the interference of Arabic in the use of English prepositions by Libyan university students. Prepositions in the tests used in the study were categorized, according to their relation to Arabic, into similar Arabic and English prepositions (SAEP), dissimilar Arabic and English prepositions (DAEP), Arabic prepositions with no English counterparts (APEC), and English prepositions with no Arabic counterparts (EPAC).
The subjects of the study were the first year university students of the English department, Sabrata Faculty of Arts, Azzawia University; both males and females, and they were 100 students. The basic tool for data collection was a test of English prepositions; students are instructed to fill in the blanks with the correct prepositions and to put a zero (0) if no preposition was needed. The test was then handed to the subjects of the study.
The test was then scored and quantitative as well as qualitative results were obtained. Quantitative results indicated the number, percentages and rank order of errors in each of the categories and qualitative results indicated the nature and significance of those errors and their possible sources. Based on the obtained results the researcher could detect that students made more errors in the EPAC category than the other three categories and these errors could be attributed to the lack of knowledge of the different meanings of English prepositions. This lack of knowledge forced the students to adopt what is called the strategy of transfer.
Abstract: Thirty-eight rural school leaders in Solomon Islands responded to a questionnaire aimed at identifying their perceptions of work challenges. The data analysis points to an overwhelming percentage of school leaders feeling they face multifaceted problems in their work settings, including such challenges as untrained teachers, lack of funding, limited learning and teaching resources, and land disputes. The latter in particular is beyond the school leader’s jurisdiction; addressing it needs urgent attention from the principal stakeholder(s). Such challenges, seemingly tangential to the business of schooling, inadvertently affect the provision of good-quality education. The findings demonstrate that contextual challenges raise questions about what powers leadership at school level has to deal with some of them. The suggestion is advanced for the significant place-conscious leadership development to help address some community and cultural challenges. Implications of this paper are likely to be relevant to other similar contexts in the Pacific region and beyond.
Abstract: The aim of this research was to create collaborative learning activities in the course of Principles of Mathematics for graduate level by investigating the students’ ability in proving the mathematics principles as well as their attitudes towards the activities. The samples composed of 2 main group; lecturers and students. The lecturers consisted of 3 teachers who taught the course of Principles of Mathematics at Rajabhat Suan Sunandha Unicersity in the academic year 2012. The students consisted of 32 students joining the cooperative learning activities in the subject of Principles of Mathematics in the academic year 2012. The research tools included activity plan for cooperative learning, testing on mathematics with the reliability of 0.8067 and the attitude questionnaires reported by the students. The results showed that: 1) the efficiency of the developed cooperative learning activities was 69.76/ 68.57 which was lower than the set criteria at 70/70. 2) The students joining the cooperative learning activities were able to prove the principles of mathematics at the average of 70%. 3) The students joining the cooperative learning activities reported moderate attitude towards the activities.
Abstract: Clustering in data mining is an unsupervised learning technique of aggregating the data objects into meaningful groups such that the intra cluster similarity of objects are maximized and inter cluster similarity of objects are minimized. Over the past decades several clustering tools were emerged in which clustering algorithms are inbuilt and are easier to use and extract the expected results. Data mining mainly deals with the huge databases that inflicts on cluster analysis and additional rigorous computational constraints. These challenges pave the way for the emergence of powerful expansive data mining clustering softwares. In this survey, a variety of clustering tools used in data mining are elucidated along with the pros and cons of each software.
Abstract: Over the past epoch a rampant amount of work has been done in the data clustering research under the unsupervised learning technique in Data mining. Furthermore several algorithms and methods have been proposed focusing on clustering different data types, representation of cluster models, and accuracy rates of the clusters. However no single clustering algorithm proves to be the most efficient in providing best results. Accordingly in order to find the solution to this issue a new technique, called Cluster ensemble method was bloomed. This cluster ensemble is a good alternative approach for facing the cluster analysis problem. The main hope of the cluster ensemble is to merge different clustering solutions in such a way to achieve accuracy and to improve the quality of individual data clustering. Due to the substantial and unremitting development of new methods in the sphere of data mining and also the incessant interest in inventing new algorithms, makes obligatory to scrutinize a critical analysis of the existing techniques and the future novelty. This paper exposes the comparative study of different cluster ensemble methods along with their features, systematic working process and the average accuracy and error rates of each ensemble methods. Consequently this speculative and comprehensive analysis will be very useful for the community of clustering practitioners and also helps in deciding the most suitable one to rectify the problem in hand.
Abstract: Associative classification (AC) is a data mining approach that combines association rule and classification to build classification models (classifiers). AC has attracted a significant attention from several researchers mainly because it derives accurate classifiers that contain simple yet effective rules. In the last decade, a number of associative classification algorithms have been proposed such as Classification based Association (CBA), Classification based on Multiple Association Rules (CMAR), Class based Associative Classification (CACA), and Classification based on Predicted Association Rule (CPAR). This paper surveys major AC algorithms and compares the steps and methods performed in each algorithm including: rule learning, rule sorting, rule pruning, classifier building, and class prediction.
Abstract: The purposes of the research were to develop online lessons to strengthen the learning process of Master's degree students majoring in Curriculum and Instruction at Suan Sunandha Rajabhat University; to achieve the efficiency criteria of 80/80; and to study the satisfaction of students who use online lessons to strengthen the learning process of Master’s degree students majoring in Curriculum and Instruction at Suan Sunandha Rajabhat University. The sample consisted of 40 university students studying in semester 1, academic year 2012. The sample was determined by Purposive Sampling. Selected students were from the class which the researcher was the homeroom tutor. The tutor was responsible for the teaching of learning process. Tools used in the study were online lessons, 60-point performance test, and evaluation test of satisfaction of students on online lessons. Data analysis yielded the following results; 83.66/88.29 efficiency of online lessons measured against the criteria; the comparison of performance before and after taking online lessons using t-test yielded 29.67. The statistical significance was at 0.05; the average satisfaction level of forty students on online lessons was 4.46 with standard deviation of 0.68.
Abstract: This paper explores the use of project work in a content-based instruction in a Rajabhat University, Thailand. The use of project is to promote kinds of learning expected of student teachers as stated by Thailand Quality Framework: TQF. The kinds of learning are grouped into five domains: Ethical and moral development, knowledge, cognitive skill, interpersonal skills and responsibility, and analytical and communication skills. The content taught in class is used to lead the student teachers to relate their previously-acquired linguistic knowledge to meaningful realizations of the language system in passages of immediate relevance to their professional interests, teaching methods in particular. Two research questions are formulate to guide this study: 1) To what degree are the five domains of learning expected of student teachers after the use of project in a content class?, and 2) What is the academic achievement of the students’ writing skills, as part of the learning domains stated by TQF, against the 70% attainment target after the use of project to enhance the skill? The sample of the study comprised of 38 fourth-year English major students. The data was collected by means of a summative achievement test, student writing works, an observation checklist, and project diary. The scores in the summative achievement test were analyzed by mean score, standard deviation, and t-test. Project diary serves as students’ record of the language acquired during the project. List of structures and vocabulary noted in the diary has shown students’ ability to attend to, recognize, and focus on meaningful patterns of language forms.
Abstract: The generation of an idea that goes through several
phases is affected by individual factors, interests, preferences and
motivation. The purpose of this research was to analyze the
difference in difficulties of generating ideas according to individual
learning styles. A total of 375 technical students from four technical
universities in Malaysia were randomly selected as samples. The
Kolb Learning Styles Inventory and a set of developed questionnaires
were used in this research. The results showed that the most dominant
learning style among technical students is Doer. A total of 319
(85.1%) technical students faced difficulties in solving individual
assignments. Most of the problem faced by technical students is the
difficulty of generating ideas for solving individual assignments.
There was no significant difference in difficulties of generating ideas
according to students’ learning styles. Therefore, students need to
learn higher order thinking skills enabling students to generate ideas
and consequently complete assignments.
Abstract: In this research, the capability of neural networks in
modeling and learning complicated and nonlinear relations has been
used to develop a model for the prediction of changes in the diameter
of bubbles in pool boiling distilled water. The input parameters used
in the development of this network include element temperature, heat
flux, and retention time of bubbles. The test data obtained from the
experiment of the pool boiling of distilled water, and the
measurement of the bubbles form on the cylindrical element. The
model was developed based on training algorithm, which is
typologically of back-propagation type. Considering the correlation
coefficient obtained from this model is 0.9633. This shows that this
model can be trusted for the simulation and modeling of the size of
bubble and thermal transfer of boiling.
Abstract: This study is conducted to investigate the disparity of between learning styles and cognitive abilities specifically in Vocational Education. Felder and Silverman Learning Styles Model (FSLSM) was applied to measure the students’ learning styles while the content in Building Construction Subject consists; knowledge, skills and problem solving were taken into account in constructing the elements of cognitive abilities. Building Construction is one of the vocational courses offered in Vocational Education structure. There are four dimension of learning styles proposed by Felder and Silverman intended to capture student learning preferences with regards to processing either active or reflective, perception based on sensing or intuitive, input of information used visual or verbal and understanding information represent with sequential or global learner. Felder-Solomon Learning Styles Index was developed based on FSLSM and the questions were used to identify what type of student learning preferences. The index consists 44 item-questions characterize for learning styles dimension in FSLSM. The achievement test was developed to determine the students’ cognitive abilities. The quantitative data was analyzed in descriptive and inferential statistic involving Multivariate Analysis of Variance (MANOVA). The study discovered students are tending to be visual learners and each type of learner having significant difference whereas cognitive abilities there are different finding for each type of learners in knowledge, skills and problem solving. This study concludes the gap between type of learner and the cognitive abilities in few illustrations and it explained how the connecting made. The finding may help teachers to facilitate students more effectively and to boost the student’s cognitive abilities.
Abstract: This paper was prepared to see the perceptions of online lectures regarding collaborative learning, in terms of how lecturers view online collaborative learning in the higher learning institution. The purpose of this study was conducted to determine the perceptions of online lectures about collaborative learning, especially how lecturers see online collaborative learning in the university. Adult learning education enhance collaborative learning culture with the target of involving learners in the learning process to make teaching and learning more effective and open at the university. This will finally make students learning that will assist each other. It is also to cut down the pressure of loneliness and isolation might felt among adult learners. Their ways in collaborative online was also determined. In this paper, researchers collect data using questionnaires instruments. The collected data were analyzed and interpreted. By analyzing the data, researchers report the results according the proof taken from the respondents. Results from the study, it is not only dependent on the lecturer but also a student to shape a good collaborative learning practice. Rational concepts and pattern to achieve these targets be clear right from the beginning and may be good seen by a number of proposals submitted and include how the higher learning institution has trained with ongoing lectures online. Advantages of online collaborative learning show that lecturers should be trained effectively. Studies have seen that the lecturer aware of online collaborative learning. This positive attitude will encourage the higher learning institution to continue to give the knowledge and skills required.
Abstract: In neural networks, when new patters are learned by a network, they radically interfere with previously stored patterns. This
drawback is called catastrophic forgetting. We have already proposed a biologically inspired dual-network memory model which can much reduce this forgetting for static patterns. In this model, information is first stored in the hippocampal network, and thereafter, it is transferred to the neocortical network using pseudopatterns. Because temporal sequence learning is more important than static pattern learning in the real world, in this study, we improve our conventional dual-network memory model so that it can deal with temporal sequences without catastrophic forgetting. The computer simulation results show the effectiveness of the proposed dual-network memory model.
Abstract: Parallel text alignment is proposed as a way of aligning bahasa Indonesia to words in Javanese. Since the one-to-one word translator does not have the facility to translate pragmatic aspects of Javanese, the parallel text alignment model described uses a phrase pair combination. The algorithm aligns the parallel text automatically from the beginning to the end of each sentence. Even though the results of the phrase pair combination outperform the previous algorithm, it is still inefficient. Recording all possible combinations consume more space in the database and time consuming. The original algorithm is modified by applying the edit distance coefficient to improve the data-storage efficiency. As a result, the data-storage consumption is 90% reduced as well as its learning period (42s).
Abstract: This paper aims to build an Arabic learning language tool using Flash CS4 professional software with action script 3.0 programming language, based on the Computer Aided Language Learning (CALL) material. An extra intention is to provide a primary tool and focus on learning Arabic as a second language to adults. It contains letters, words and sentences at the first stage. This includes interactive practices, which evaluates learners’ comprehension of the Arabic language. The system was examined and it was found that the language structure was correct and learners were satisfied regarding the system tools. The learners found the system tools efficient and simple to use. The paper's main conclusion illustrates that CALL can be applied without any hesitation to second language learners
Abstract: Aim: To investigate students’ perceptions of using e-models in an inquiry-based curriculum. Approach: 52 second-year dental students completed a pre- and post-test questionnaire relating to their perceptions of e-models and their use in inquiry-based learning. The pre-test occurred prior to any learning with e-models. The follow-up survey was conducted after one year's experience of using e-models. Results: There was no significant difference between the two sets of questionnaires regarding students’ perceptions of the usefulness of e-models and their willingness to use e-models in future inquiry-based learning. Most students preferred using both plaster models and e-models in tandem. Conclusion: Students did not change their attitude towards e-models and most of them agreed or were neutral that e-models are useful in inquiry-based learning. Whilst recognizing the utility of 3D models for learning, students' preference for combining these with solid models has implications for the development of haptic sensibility in an operative discipline.