Abstract: In this study, the Multi-Layer Perceptron (MLP)with Back-Propagation learning algorithm are used to classify to effective diagnosis Parkinsons disease(PD).It-s a challenging problem for medical community.Typically characterized by tremor, PD occurs due to the loss of dopamine in the brains thalamic region that results in involuntary or oscillatory movement in the body. A feature selection algorithm along with biomedical test values to diagnose Parkinson disease.Clinical diagnosis is done mostly by doctor-s expertise and experience.But still cases are reported of wrong diagnosis and treatment. Patients are asked to take number of tests for diagnosis.In many cases,not all the tests contribute towards effective diagnosis of a disease.Our work is to classify the presence of Parkinson disease with reduced number of attributes.Original,22 attributes are involved in classify.We use Information Gain to determine the attributes which reduced the number of attributes which is need to be taken from patients.The Artificial neural networks is used to classify the diagnosis of patients.Twenty-Two attributes are reduced to sixteen attributes.The accuracy is in training data set is 82.051% and in the validation data set is 83.333%.
Abstract: Information and Communication Technologies (ICT) in mathematical education is a very active field of research and innovation, where learning is understood to be meaningful and grasping multiple linked representation rather than rote memorization, a great amount of literature offering a wide range of theories, learning approaches, methodologies and interpretations, are generally stressing the potentialities for teaching and learning using ICT. Despite the utilization of new learning approaches with ICT, students experience difficulties in learning concepts relevant to understanding mathematics, much remains unclear about the relationship between the computer environment, the activities it might support, and the knowledge that might emerge from such activities. Many questions that might arise in this regard: to what extent does the use of ICT help students in the process of understanding and solving tasks or problems? Is it possible to identify what aspects or features of students' mathematical learning can be enhanced by the use of technology? This paper will highlight the interest of the integration of information and communication technologies (ICT) into the teaching and learning of mathematics (quadratic functions), it aims to investigate the effect of four instructional methods on students- mathematical understanding and problem solving. Quantitative and qualitative methods are used to report about 43 students in middle school. Results showed that mathematical thinking and problem solving evolves as students engage with ICT activities and learn cooperatively.
Abstract: Although backpropagation ANNs generally predict
better than decision trees do for pattern classification problems, they
are often regarded as black boxes, i.e., their predictions cannot be
explained as those of decision trees. In many applications, it is
desirable to extract knowledge from trained ANNs for the users to
gain a better understanding of how the networks solve the problems.
A new rule extraction algorithm, called rule extraction from artificial
neural networks (REANN) is proposed and implemented to extract
symbolic rules from ANNs. A standard three-layer feedforward ANN
is the basis of the algorithm. A four-phase training algorithm is
proposed for backpropagation learning. Explicitness of the extracted
rules is supported by comparing them to the symbolic rules generated
by other methods. Extracted rules are comparable with other methods
in terms of number of rules, average number of conditions for a rule,
and predictive accuracy. Extensive experimental studies on several
benchmarks classification problems, such as breast cancer, iris,
diabetes, and season classification problems, demonstrate the
effectiveness of the proposed approach with good generalization
ability.
Abstract: The purpose of the study is to determine the primary mathematics student teachers- views related to use instructional technology tools in course of the learning process and to reveal how the sample presentations towards different mathematical concepts affect their views. This is a qualitative study involving twelve mathematics students from a public university. The data gathered from two semi-structural interviews. The first one was realized in the beginning of the study. After that the representations prepared by the researchers were showed to the participants. These representations contain animations, Geometer-s Sketchpad activities, video-clips, spreadsheets, and power-point presentations. The last interview was realized at the end of these representations. The data from the interviews and content analyses were transcribed and read and reread to explore the major themes. Findings revealed that the views of the students changed in this process and they believed that the instructional technology tools should be used in their classroom.
Abstract: Ensemble learning algorithms such as AdaBoost and
Bagging have been in active research and shown improvements in
classification results for several benchmarking data sets with mainly
decision trees as their base classifiers. In this paper we experiment to
apply these Meta learning techniques with classifiers such as random
forests, neural networks and support vector machines. The data sets
are from MAGIC, a Cherenkov telescope experiment. The task is to
classify gamma signals from overwhelmingly hadron and muon
signals representing a rare class classification problem. We compare
the individual classifiers with their ensemble counterparts and
discuss the results. WEKA a wonderful tool for machine learning has
been used for making the experiments.
Abstract: Inadequate curriculum for software engineering is considered to be one of the most common software risks. A number of solutions, on improving Software Engineering Education (SEE) have been reported in literature but there is a need to collectively present these solutions at one place. We have performed a mapping study to present a broad view of literature; published on improving the current state of SEE. Our aim is to give academicians, practitioners and researchers an international view of the current state of SEE. Our study has identified 70 primary studies that met our selection criteria, which we further classified and categorized in a well-defined Software Engineering educational framework. We found that the most researched category within the SE educational framework is Innovative Teaching Methods whereas the least amount of research was found in Student Learning and Assessment category. Our future work is to conduct a Systematic Literature Review on SEE.
Abstract: The paper discusses European Lifelong Learning policy in the European enlargement to the Balkan. The European Lifelong Learning policy with Human Capital approach is researched in the country case of Macedonia. The paper argues that Human Capital approach focusing on instrumental and economic importance of learning for employability and economic growth needs to be complemented with Capability Approach for intrinsic and noneconomic needs of learning among the ethnic minorities. The paper identifies two dimensions of importance – minority languages and civic education – that the Capability Approach may develop to guarantee equal opportunities to all to benefit from European educational and lifelong learning development and to build an inclusive and socially just democracy in Macedonia.
Abstract: The effect of teaching method on learning
assistance Dunn Review .The study, to compare the effects of
collaboration on teaching mathematics learning courses, including
writing, science, experimental girl students by other methods of
teaching basic first paid and the amount of learning students
methods have been trained to cooperate with other students with
other traditional methods have been trained to compare. The
survey on 100 students in Tehran that using random sampling ¬
cluster of girl students between the first primary selections was
performed. Considering the topic of semi-experimental research
methods used to practice the necessary information by
questionnaire, examination questions by the researcher, in
collaboration with teachers and view authority in this field and
related courses that teach these must have been collected.
Research samples to test and control groups were divided.
Experimental group and control group collaboration using
traditional methods of mathematics courses, including writing and
experimental sciences were trained. Research results using
statistical methods T is obtained in two independent groups show
that, through training assistance will lead to positive results and
student learning in comparison with traditional methods, will
increase also led to collaboration methods increase skills to solve
math lesson practice, better understanding and increased skill
level of students in practical lessons such as science and has been
writing.
Abstract: In the open space of decision support system the
mental impression of a manager-s decision has been the subject of
large importance than the ordinary famous one, when helped by
decision support system. Much of this study is an attempt to realize
the relation of decision support system usage and decision outcomes
that governs the system. For example, several researchers have
proposed so many different models to analyze the linkage between
decision support system processes and results of decision making.
This study draws the important relation of manager-s mental
approach with the use of decision support system. The findings of
this paper are theoretical attempts to provide Decision Support
System (DSS) in a way to exhibit and promote the learning in semi
structured area. The proposed model shows the points of one-s
learning improvements and maintains a theoretical approach in order
to explore the DSS contribution in enhancing the decision forming
and governing the system.
Abstract: This paper explains how mobile learning assures sustainable e-education for multicultural group of students. This paper reports the impact of mobile learning on distance education in multicultural environment. The emergence of learning technologies through CD, internet, and mobile is increasingly adopted by distance institutes for quick delivery and cost-effective purposes. Their sustainability is conditioned by the structure of learners as well as the teaching community. The experimental study was conducted among the distant learners of Vinayaka Missions University located at Salem in India. Students were drawn from multicultural environment based on different languages, religions, class and communities. During the mobile learning sessions, the students, who are divided on language, religion, class and community, were dominated by play impulse rather than study anxiety or cultural inhibitions. This study confirmed that mobile learning improved the performance of the students despite their division based on region, language or culture. In other words, technology was able to transcend the relative deprivation in the multicultural groups. It also confirms sustainable e-education through mobile learning and cost-effective system of instruction. Mobile learning appropriates the self-motivation and play impulse of the young learners in providing sustainable e-education to multicultural social groups of students.
Abstract: Construction delay is unavoidable in developing
countries including Malaysia. It is defined as time overrun or
extension of time for completion of a project. The purpose of the
study is to determine the causes of delay in Malaysian construction
industries based on previous worldwide research. The field survey
conducted includes the experienced developers, consultants and
contractors in Malaysia. 34 causes of the construction delay have
been determined and 24 have been selected using the Rasch model
analysis. The analysis result will be used as the baseline for the next
research to find the causes of delay in the Malaysian construction
industry taking place in Malaysian higher learning institutions.
Abstract: E-learning is not restricted to the use of new technologies for the online content, but also induces the adoption of new approaches to improve the quality of education. This quality depends on the ability of these approaches (technical and pedagogical) to provide an adaptive learning environment. Thus, the environment should include features that convey intentions and meeting the educational needs of learners by providing a customized learning path to acquiring a competency concerned In our proposal, we believe that an individualized learning path requires knowledge of the learner. Therefore, it must pass through a personalization of diagnosis to identify precisely the competency gaps to fill, and reduce the cognitive load To personalize the diagnosis and pertinently measure the competency gap, we suggest implementing the formative assessment in the e-learning environment and we propose the introduction of a pre-regulation process in the area of formative assessment, involving its individualization and implementation in e-learning.
Abstract: Modern building automation needs to deal with very
different types of demands, depending on the use of a building and the
persons acting in it. To meet the requirements of situation awareness
in modern building automation, scenario recognition becomes more
and more important in order to detect sequences of events and to react
to them properly. We present two concepts of scenario recognition
and their implementation, one based on predefined templates and the
other applying an unsupervised learning algorithm using statistical
methods. Implemented applications will be described and their advantages
and disadvantages will be outlined.
Abstract: Support Vector Machine (SVM) is a statistical
learning tool that was initially developed by Vapnik in 1979 and later
developed to a more complex concept of structural risk minimization
(SRM). SVM is playing an increasing role in applications to
detection problems in various engineering problems, notably in
statistical signal processing, pattern recognition, image analysis, and
communication systems. In this paper, SVM was applied to the
detection of SAR (synthetic aperture radar) images in the presence of
partially developed speckle noise. The simulation was done for single
look and multi-look speckle models to give a complete overlook and
insight to the new proposed model of the SVM-based detector. The
structure of the SVM was derived and applied to real SAR images
and its performance in terms of the mean square error (MSE) metric
was calculated. We showed that the SVM-detected SAR images have
a very low MSE and are of good quality. The quality of the
processed speckled images improved for the multi-look model.
Furthermore, the contrast of the SVM detected images was higher
than that of the original non-noisy images, indicating that the SVM
approach increased the distance between the pixel reflectivity levels
(the detection hypotheses) in the original images.
Abstract: This research presents a system for post processing of
data that takes mined flat rules as input and discovers crisp as well as
fuzzy hierarchical structures using Learning Classifier System
approach. Learning Classifier System (LCS) is basically a machine
learning technique that combines evolutionary computing,
reinforcement learning, supervised or unsupervised learning and
heuristics to produce adaptive systems. A LCS learns by interacting
with an environment from which it receives feedback in the form of
numerical reward. Learning is achieved by trying to maximize the
amount of reward received. Crisp description for a concept usually
cannot represent human knowledge completely and practically. In the
proposed Learning Classifier System initial population is constructed
as a random collection of HPR–trees (related production rules) and
crisp / fuzzy hierarchies are evolved. A fuzzy subsumption relation is
suggested for the proposed system and based on Subsumption Matrix
(SM), a suitable fitness function is proposed. Suitable genetic
operators are proposed for the chosen chromosome representation
method. For implementing reinforcement a suitable reward and
punishment scheme is also proposed. Experimental results are
presented to demonstrate the performance of the proposed system.
Abstract: This paper is an exploration of the conceptual
confusion between E-learning and M-learning particularly in Africa.
Section I provides a background to the development of E-learning
and M-learning. Section II focuses on the conceptual analysis as it
applies to Africa. It is with an investigative and expansive mind that
this paper is elaborated to respond to a profound question of the
suitability of the concepts in a particular era in Africa. The aim of this
paper is therefore to shed light on which concept best suits the unique
situation of Africa in the era of cloud computing.
Abstract: According to development of communications and
web-based technologies in recent years, e-Learning has became very
important for everyone and is seen as one of most dynamic teaching
methods.
Grid computing is a pattern for increasing of computing power
and storage capacity of a system and is based on hardware and
software resources in a network with common purpose. In this article
we study grid architecture and describe its different layers. In this
way, we will analyze grid layered architecture. Then we will
introduce a new suitable architecture for e-Learning which is based
on grid network, and for this reason we call it Grid Learning
Architecture. Various sections and layers of suggested architecture
will be analyzed; especially grid middleware layer that has key role.
This layer is heart of grid learning architecture and, in fact,
regardless of this layer, e-Learning based on grid architecture will
not be feasible.
Abstract: Collaborative problem solving in e-learning can take
in the form of discussion among learner, creating a highly social
learning environment and characterized by participation and
interactivity. This paper, designed a collaborative learning
environment where agent act as co-learner, can play different roles
during interaction. Since different roles have been assigned to the
agent, learner will assume that multiple co-learner exists to help and
guide him all throughout the collaborative problem solving process,
but in fact, alone during the learning process. Specifically, it answers
the questions what roles of the agent should be incorporated to
contribute better learning outcomes, how agent will facilitate the
communication process to provide social learning and interactivity
and what are the specific instructional strategies that facilitate learner
participation, increased skill acquisition and develop critical thinking.
Abstract: The increasing number of senior population gradually
causes to demand the use of information and communication
technology for their satisfactory lives. This paper presents the
development of an integrated TV based system which offers an
opportunity to provide value added services to a large number of
elderly citizens, and thus helps improve their quality of life. The
design philosophy underlying this paper is to fulfill both technological
and human aspects. The balance between these two dimensions has
been currently stressed as a crucial element for the design of usable
systems in real use, particularly to the elderly who have physical and
mental decline. As the first step to achieve it, we have identified
human and social factors that affect the elder-s quality of life by a
literature review, and based on them, build four fundamental services:
information, healthcare, learning and social network services.
Secondly, the system architecture, employed technologies and the
elderly-friendly system design considerations are presented. This
reflects technological and human perspectives in terms of the system
design. Finally, we describe some scenarios that illustrate the
potentiality of the proposed system to improve elderly people-s quality
of life.
Abstract: In response to address different development challenges, Tanzania is striving to achieve its fourth attribute of the National Development Vision, i.e. to have a well educated and learned society by the year 2025. One of the most cost effective methods that can reach a large part of the society in a short time is to integrate ICT in education through e-learning initiatives. However, elearning initiatives are challenged by limited or lack of connectivity to majority of secondary schools, especially those in rural and remote areas. This paper has explores the possibility for rural secondary school to access online e-Learning resources from a centralized e- Learning Management System (e-LMS). The scope of this paper is limited to schools that have computers irrespective of internet connectivity, resulting in two categories schools; those with internet access and those without. Different connectivity configurations have been proposed according to the ICT infrastructure status of the respective schools. However, majority of rural secondary schools in Tanzania have neither computers nor internet connection. Therefore this is a challenge to be addressed for the disadvantaged schools to benefit from e-Learning initiatives.