Abstract: In this study we present our developed formative
assessment tool for students' assignments. The tool enables lecturers
to define assignments for the course and assign each problem in each
assignment a list of criteria and weights by which the students' work
is evaluated. During assessment, the lecturers feed the scores for each
criterion with justifications. When the scores of the current
assignment are completely fed in, the tool automatically generates
reports for both students and lecturers. The students receive a report
by email including detailed description of their assessed work, their
relative score and their progress across the criteria along the course
timeline. This information is presented via charts generated
automatically by the tool based on the scores fed in. The lecturers
receive a report that includes summative (e.g., averages, standard
deviations) and detailed (e.g., histogram) data of the current
assignment. This information enables the lecturers to follow the class
achievements and adjust the learning process accordingly. The tool
was examined on two pilot groups of college students that study a
course in (1) Object-Oriented Programming (2) Plane Geometry.
Results reveal that most of the students were satisfied with the
assessment process and the reports produced by the tool. The
lecturers who used the tool were also satisfied with the reports and
their contribution to the learning process.
Abstract: Piezoelectric transformers are electronic devices made
from piezoelectric materials. The piezoelectric transformers as the
name implied are used for changing voltage signals from one level to another. Electrical energy carried with signals is transferred by means of mechanical vibration. Characterizing in both electrical and
mechanical properties leads to extensively use and efficiency enhancement of piezoelectric transformers in various applications. In
this paper, study and analysis of electrical and mechanical properties of multi-layer piezoelectric transformers in forms of potential and
displacement distribution throughout the volume, respectively. This
paper proposes a set of quasi-static mathematical model of electromechanical
coupling for piezoelectric transformer by using a set of
partial differential equations. Computer-based simulation utilizing the three-dimensional finite element method (3-D FEM) is exploited
as a tool for visualizing potentials and displacements distribution
within the multi-layer piezoelectric transformer. This simulation was
conducted by varying a number of layers. In this paper 3, 5 and 7 of
the circular ring type were used. The computer simulation based on
the use of the FEM has been developed in MATLAB programming environment.
Abstract: This paper presents a new approach using Combined Artificial Neural Network (CANN) module for daily peak load forecasting. Five different computational techniques –Constrained method, Unconstrained method, Evolutionary Programming (EP), Particle Swarm Optimization (PSO), and Genetic Algorithm (GA) – have been used to identify the CANN module for peak load forecasting. In this paper, a set of neural networks has been trained with different architecture and training parameters. The networks are trained and tested for the actual load data of Chennai city (India). A set of better trained conventional ANNs are selected to develop a CANN module using different algorithms instead of using one best conventional ANN. Obtained results using CANN module confirm its validity.
Abstract: Directional over current relays (DOCR) are commonly used in power system protection as a primary protection in distribution and sub-transmission electrical systems and as a secondary protection in transmission systems. Coordination of protective relays is necessary to obtain selective tripping. In this paper, an approach for efficiency reduction of DOCRs nonlinear optimum coordination (OC) is proposed. This was achieved by modifying the objective function and relaxing several constraints depending on the four constraints classification, non-valid, redundant, pre-obtained and valid constraints. According to this classification, the far end fault effect on the objective function and constraints, and in consequently on relay operating time, was studied. The study was carried out, firstly by taking into account the near-end and far-end faults in DOCRs coordination problem formulation; and then faults very close to the primary relays (nearend faults). The optimal coordination (OC) was achieved by simultaneously optimizing all variables (TDS and Ip) in nonlinear environment by using of Genetic algorithm nonlinear programming techniques. The results application of the above two approaches on 6-bus and 26-bus system verify that the far-end faults consideration on OC problem formulation don-t lose the optimality.
Abstract: A Web-based learning tool, the Learn IN Context
(LINC) system, designed and being used in some institution-s
courses in mixed-mode learning, is presented in this paper. This
mode combines face-to-face and distance approaches to education.
LINC can achieve both collaborative and competitive learning. In
order to provide both learners and tutors with a more natural way to
interact with e-learning applications, a conversational interface has
been included in LINC. Hence, the components and essential features
of LINC+, the voice enhanced version of LINC, are described. We
report evaluation experiments of LINC/LINC+ in a real use context
of a computer programming course taught at the Université de
Moncton (Canada). The findings show that when the learning
material is delivered in the form of a collaborative and voice-enabled
presentation, the majority of learners seem to be satisfied with this
new media, and confirm that it does not negatively affect their
cognitive load.
Abstract: As the majority of faults are found in a few of its modules so there is a need to investigate the modules that are affected severely as compared to other modules and proper maintenance need to be done on time especially for the critical applications. In this paper, we have explored the different predictor models to NASA-s public domain defect dataset coded in Perl programming language. Different machine learning algorithms belonging to the different learner categories of the WEKA project including Mamdani Based Fuzzy Inference System and Neuro-fuzzy based system have been evaluated for the modeling of maintenance severity or impact of fault severity. The results are recorded in terms of Accuracy, Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE). The results show that Neuro-fuzzy based model provides relatively better prediction accuracy as compared to other models and hence, can be used for the maintenance severity prediction of the software.
Abstract: In this paper a multi-objective nonlinear programming
model of cellular manufacturing system is presented which minimize
the intercell movements and maximize the sum of reliability of cells.
We present a genetic approach for finding efficient solutions to the
problem of cell formation for products having multiple routings.
These methods find the non-dominated solutions and according to
decision makers prefer, the best solution will be chosen.
Abstract: This research is intended to develop a raw material allocation model in timber processing industry in Perum Perhutani Unit I, Central Java, Indonesia. The model can be used to determine the quantity of allocation of timber between chain in the supply chain to select supplier considering factors that are log price and the distance. In determining the quantity of allocation of timber between chains in the supply chain, the model considers the optimal inventory in each chain. Whilst the optimal inventory is determined based on demand forecast, the capacity and safety stock. Problem solving allocation is conducted by developing linear programming model that aims to minimize the total cost of the purchase, transportation cost and storage costs at each chain. The results of numerical examples show that the proposed model can generate savings of the purchase cost of 20.84% and select suppliers with mileage closer.
Abstract: Nowadays Multilevel inverters are widely using in various applications. Modulation strategy at fundamental switching frequency like, SHEPWM is prominent technique to eliminate lower order of harmonics with less switching losses and better harmonic profile. The equations which are formed by SHE are highly nonlinear transcendental in nature, there may exist single, multiple or even no solutions for a particular MI. However, some loads such as electrical drives, it is required to operate in whole range of MI. In order to solve SHE equations for whole range of MI, intelligent techniques are well suited to solve equations so as to produce lest %THDV. Hence, this paper uses Continuous genetic algorithm for minimising harmonics. This paper also presents wavelet based analysis of harmonics. The developed algorithm is simulated and %THD from FFT analysis and Wavelet analysis are compared. MATLAB programming environment and SIMULINK models are used whenever necessary.
Abstract: We describe a work with an evolutionary computing
algorithm for non photo–realistic rendering of a target image. The
renderings are produced by genetic programming. We have used two
different types of strokes: “empty triangle" and “filled triangle" in
color level. We compare both empty and filled triangular strokes to
find which one generates more aesthetic pleasing images. We found
the filled triangular strokes have better fitness and generate more
aesthetic images than empty triangular strokes.
Abstract: Overcurrent (OC) relays are the major protection
devices in a distribution system. The operating time of the OC relays
are to be coordinated properly to avoid the mal-operation of the
backup relays. The OC relay time coordination in ring fed
distribution networks is a highly constrained optimization problem
which can be stated as a linear programming problem (LPP). The
purpose is to find an optimum relay setting to minimize the time of
operation of relays and at the same time, to keep the relays properly
coordinated to avoid the mal-operation of relays.
This paper presents two phase simplex method for optimum time
coordination of OC relays. The method is based on the simplex
algorithm which is used to find optimum solution of LPP. The
method introduces artificial variables to get an initial basic feasible
solution (IBFS). Artificial variables are removed using iterative
process of first phase which minimizes the auxiliary objective
function. The second phase minimizes the original objective function
and gives the optimum time coordination of OC relays.
Abstract: In this paper we introduce an approach via optimization methods to find approximate solutions for nonlinear Fredholm integral equations of the first kind. To
this purpose, we consider two stages of approximation.
First we convert the integral equation to a moment problem and then we modify the new problem to two classes of optimization problems, non-constraint optimization problems
and optimal control problems. Finally numerical examples is
proposed.
Abstract: Focusing on the environmental issues, including the reduction of scrap and consumer residuals, along with the benefiting from the economic value during the life cycle of goods/products leads the companies to have an important competitive approach. The aim of this paper is to present a new mixed nonlinear facility locationallocation model in recycling collection networks by considering multi-echelon, multi-suppliers, multi-collection centers and multifacilities in the recycling network. To make an appropriate decision in reality, demands, returns, capacities, costs and distances, are regarded uncertain in our model. For this purpose, a fuzzy mathematical programming-based possibilistic approach is introduced as a solution methodology from the recent literature to solve the proposed mixed-nonlinear programming model (MNLP). The computational experiments are provided to illustrate the applicability of the designed model in a supply chain environment and to help the decision makers to facilitate their analysis.
Abstract: In a recent major industry-supported research and development study, a novel framework was developed and applied for assessment of reliability and quality performance levels in reallife power systems with practical large-scale sizes. The new assessment methodology is based on three metaphors (dimensions) representing the relationship between available generation capacities and required demand levels. The paper shares the results of the successfully completed stud and describes the implementation of the new methodology on practical zones in the Saudi electricity system.
Abstract: Effectiveness and efficiency of food distribution is necessary to maintain food security in a region. Food supply varies among regions depending on their production capacity; therefore, it is necessary to regulate food distribution. Sea transportation could play a great role in the food distribution system. To play this role and to support transportation needs in the Eastern Indonesia, sea transportation shall be supported by fleet which is adequate and reliable, both in terms of load and worthiness. This research uses Linear Programming (LP) method to analyze food distribution pattern in order to determine the optimal distribution system. In this research, transshipment points have been selected for regions in one province. Comparison between result of modeling and existing shipping route reveals that from 369 existing routes, 54 routes are used for transporting rice, corn, green bean, peanut, soybean, sweet potato, and cassava.
Abstract: Computer programming is considered a very difficult
course by many computer science students. The reasons for the
difficulties include cognitive load involved in programming,
different learning styles of students, instructional methodology and
the choice of the programming languages. To reduce the difficulties
the following have been tried: pair programming, program
visualization, different learning styles etc. However, these efforts
have produced limited success. This paper reviews the problem and
proposes a framework to help students overcome the difficulties
involved.
Abstract: The fuzzy set theory has been applied in many fields,
such as operations research, control theory, and management
sciences, etc. In particular, an application of this theory in decision
making problems is linear programming problems with fuzzy
numbers. In this study, we present a new method for solving fuzzy
number linear programming problems, by use of linear ranking
function. In fact, our method is similar to simplex method that was
used for solving linear programming problems in crisp environment
before.
Abstract: This paper presents a semi-supervised learning algorithm called Iterative-Cross Training (ICT) to solve the Web pages classification problems. We apply Inductive logic programming (ILP) as a strong learner in ICT. The objective of this research is to evaluate the potential of the strong learner in order to boost the performance of the weak learner of ICT. We compare the result with the supervised Naive Bayes, which is the well-known algorithm for the text classification problem. The performance of our learning algorithm is also compare with other semi-supervised learning algorithms which are Co-Training and EM. The experimental results show that ICT algorithm outperforms those algorithms and the performance of the weak learner can be enhanced by ILP system.
Abstract: Standards for learning objects focus primarily on
content presentation. They were already extended to support automatic evaluation but it is limited to exercises with a predefined
set of answers. The existing standards lack the metadata required by specialized evaluators to handle types of exercises with an indefinite
set of solutions. To address this issue existing learning object standards were extended to the particular requirements of a
specialized domain. A definition of programming problems as learning objects, compatible both with Learning Management Systems and with systems performing automatic evaluation of
programs, is presented in this paper. The proposed definition includes
metadata that cannot be conveniently represented using existing standards, such as: the type of automatic evaluation; the requirements
of the evaluation engine; and the roles of different assets - tests cases, program solutions, etc. The EduJudge project and its main services
are also presented as a case study on the use of the proposed definition of programming problems as learning objects.
Abstract: This paper presents the review of past studies
concerning mathematical models for rescheduling passenger railway
services, as part of delay management in the occurrence of railway
disruption. Many past mathematical models highlighted were aimed
at minimizing the service delays experienced by passengers during
service disruptions. Integer programming (IP) and mixed-integer
programming (MIP) models are critically discussed, focusing on the
model approach, decision variables, sets and parameters. Some of
them have been tested on real-life data of railway companies
worldwide, while a few have been validated on fictive data. Based
on selected literatures on train rescheduling, this paper is able to
assist researchers in the model formulation by providing
comprehensive analyses towards the model building. These analyses
would be able to help in the development of new approaches in
rescheduling strategies or perhaps to enhance the existing
rescheduling models and make them more powerful or more
applicable with shorter computing time.