International Journal of Education and Management Engineering @ijeme
Статьи журнала - International Journal of Education and Management Engineering
Все статьи: 625
Orphan Adoption Management System using Machine Learning Approach
Статья научная
According to UNICEF, the latest estimate states that there are about 2.7 million children in orphanages. Orphanage is a residence for people who are without parental support or any moral support from anyone. Such orphans require help from people who are in a good financial state to donate them. Generally, in orphanage records are usually maintained for future reference, retrieval, and easy management. The objective of this paper is to help the orphans from different orphanages to get help from the donors who wish to donate them by using our web application. The proposed system helps the staff in reducing manual paper work and enhances tidiness in record keeping since the existing one uses manual keeping, i.e., the use of files and papers. The system allows the orphanage owner to add and modify the orphan records. The system provides suggestions for assignment of these orphans to the caretakers/donors by using SVM (Support Vector Machine) algorithm. Donor can select the orphan and request for adoption from the orphanage owner. The Orphanage owner can accept or reject help from the donor. The proposed system is aimed to facilitate donors with the details of an orphan and providing fund specifically to that orphan.
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Performance Analysis for Heterogeneous & Reconfigurable Computing Based on Scheduling
Статья научная
Right now, heterogeneous & reconfigurable computing is a research hot in the area of high performance computing. Due to the heterogeneity of application tasks and reconfigurability of system architecture, performance analysis for heterogeneous & reconfigurable computing becomes rather difficult. Unfortunately, the existing techniques and methods are no longer suitable for use. This paper presents a performance analysis method based on task scheduling. It builds on system architecture model and task model of heterogeneous & reconfigurable computing. By making use of heterogeneity matching matrix and reconfigurability coupling matrix we achieve optimal selection and matching between computational tasks and processing units. Through task scheduling algorithm, the completion time of application task run on heterogeneous & reconfigurable computing system can be calculated. Finally, we carry out case study.
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Performance with Eloquent and Query Builder in Crowdfunding System with Laravel Framework
Статья научная
Performance is a point of interest that is quite interesting for application owners, how could it not, besides being rich in features and following what they want, there are things that are no less important, namely the issue of the speed of use of an application that must be considered for developers. Because the speed level will affect the user experience in using it. Many factors influence the performance of an application, especially in the website category, one of which is the developer's ability to minimize large amounts of data load. This is the importance of being able to categorize which large data loads need to be considered and which are not. There is a system crowdfunding website that is currently operating using the laravel framework, but there are several obstacles faced where some of the processes in it are rather slow in the process. In this research, how do we choose which process uses process eloquence and which one needs to use the query builder. So that combining eloquent and query builder can be optimal
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Personality Trait Identification Using Unconstrained Cursive and Mood Invariant Handwritten Text
Статья научная
Identification of Personality is a complex process. Personality traits are stable over time .Individual's behavior naturally varies from occasion to occasion. But there is a core consistency which defines the true nature. The paper addresses this issue of behavior. Graphology is normally a technique used to identify the traits. Accuracy of this technique depends on how skilled the analyst is. Although human intervention in handwriting analysis has been effective, but it is costly and prone to fatigue. An automation of handwritten text is proposed. Basically we have considered three important features in the direction of orientation of the lines :(i) up hill (ii) down hill (iii) constant line. Edge histogram and bounding boxes was used for feature extraction .Known classifiers like SVM & ANN are used for training and the results were compared. The results were about 98% for SVM & 70% with ANN. The analysis was done using single line.
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Personalized Search Recommender System: State of Art, Experimental Results and Investigations
Статья научная
Personalized recommender system has attracted wide range of attention among researchers in recent years. These recommender systems suggest products or services depending upon user's personal interest. There has been a huge demand for development of web search apps for gaining knowledge pertaining to user's choice. A strong knowledge base, type of approach for search and several other factors make it accountable for a good personalized web search engine. This paper presents the state of art, challenges and other issues in this context, thereby providing the need for an improved personalized system. The study carried out in this paper reports the overview of existing technologies for building a personalized recommender systems in social networking platforms. Study reported in this article seems to be promising and provides possibilities of research directions, pros & cons and other alternatives.
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Physical and soft sensor technologies for wastewater quality management
Статья научная
Physical sensors are used mostly to detect sludge and odour in wastewater. Black box modelling or data-derived model using the correlation of input-output parameters is the preferred method as we have assessed. This is due to the non-complex approach of such models as opposed to model-driven, mechanistic models. The latter is hard to be adopted for soft-sensor development due to the inherent complexities and uncertainties. The commonest methods for soft sensor model development are ANN and ANFIS. Many other improvements of these methods are achieved by combining with other techniques to enhance the prediction performance of the soft sensors. Accuracy and precision of data collected for soft sensor modelling has become a vital concern at present to ensure the reliability of wastewater quality indices predicted by the soft sensors. Reduction of the level of reliability of the sensor system in monitoring and controlling of WWTPs would lead to serious lapses in the wastewater quality management. In this backdrop we recommend SEVA soft sensor as one of the best potential solutions which could be offered by the existing technologies.
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Policy Model in the Desktop Management System
Статья научная
By studying the policy and desktop management systems theories, referencing the Internet Engineering Task Force (IETF) policy model, this paper proposed a policy model that can be applied in specific desktop management system. It mainly explains the whole system framework and its implementation mechanisms, and it discusses the problems and solutions that the policy model uses in the desktop management system.
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Potato Leaf Disease Detection Using Image Processing
Статья научная
The economics of a nation is significantly influenced by agricultural productivity. Finding plant leaf disease is crucial since it significantly reduces agricultural productivity. Traditional detection methods like observing with the naked eye can lead to time-consuming and less accurate results. Farmers can’t always tell the difference between leaf diseases because sometimes they look the same. That’s why researchers have started using automation techniques to accurately detect the main diseases and their symptoms. This research proposed potato leaf disease detection using an image processing technique where the dataset was obtained online. In the proposed method, several image pre-processing techniques are used including data augmentation, gaussian smoothing, image normalization, dimensionality reduction and one hot encoding. CNN, KNN and SVC were used as classifiers. CNN gives the best result with an overall accuracy of 97%. Previous works with different classifiers had several limitations and using CNN the researchers didn’t get satisfying result. For this research a new hybrid model is introduced which can utilize the best of CNN classifier and it will be much more reliable and effective.
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Practical Teaching Staff Construction under New Situation
Статья научная
The practical teaching is a very important component of higher education. It is a special platform which not only integrates abstract and concrete, but also integrates theory and practice. And it is the main channel to cultivate talents with innovative spirit and practical ability. Therefore, the reform of practice education is necessarily the most important work in the present teaching work. In order to achieve the anticipated results, universities should establish diversified mechanism of performance assessment on teacher, establish multi-type mechanism of cultivation on teacher and construct practical teaching teacher staff with reasonable structure.
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Статья научная
The study was aimed to create a predictive model for predicting students’ academic performance based on a neural network algorithm. This is because recently, educational data mining has become very helpful in decision making in an educational context and hence improving students’ academic outcomes. This study implemented a Neural Network algorithm as a data mining technique to extract knowledge patterns from student’s dataset consisting of 480 instances (students) with 16 attributes for each student. The classification metric used is accuracy as the model quality measurement. The accuracy result was below 60% when the Adam model optimizer was used. Although, after applying the Stochastic Gradient Descent optimizer and dropout technique, the accuracy increased to more than 75%. The final stable accuracy obtained was 76.8% which is a satisfactory result. This indicates that the suggested NN model can be reliable for prediction, especially in social science studies.
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Prediction of Mental Health Problems among Higher Education Student Using Machine Learning
Статья научная
Today, mental health problems become serious issues in Malaysia. In generally, mental health problems are health issues that effects on how a person feels, thinks, behaves, and communicate with others. According to National Health and Morbidity Survey (NHMS) 2017, one in five people in Malaysia is depression. Then, two in five people is anxiety and one in ten people is having stress. Higher education student also one of communities that have high risk to face mental health problems. The difficulties in identifying factors of mental health problems become a challenges and obstacle to help the person with mental health problem. Objectives of this paper are (1) review mental health problem among higher education student, (2) the contributing factors and (3) review the existing machine learning to analyse and predict mental health problem among higher education student. Finding of the paper will be used for other study to further discussion on mental health problems for implementation using computational modelling.
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Статья научная
Diabetes has since become global pandemic – which must be diagnosed early enough if the patients are to survive a while longer. Traditional means of detection has its limitations and defects. The adoption of data mining tools and adaptation of machine intelligence is to yield an approach of predictive diagnosis that offers solution to task, which traditional means do not proffer low-cost-effective results. The significance thus, is to investigate data feats rippled with ambiguities and noise as well as simulate model tractability in order to yield a low-cost and robust solution. Thus, we explore a deep learning ensemble for detection of diabetes as a decision support. Model achieved a 95-percent accuracy, with a sensitivity of 0.98. It also agrees with other studies that age, obesity, environ-conditions and family relation to the first/second degrees are critical factors to be watched for type-I and type-II management. While, mothers with/without previous case of gestational diabetes is confirmed if there is: (a) history of babies with weight above 4.5kg at birth, (b) resistant to insulin showing polycystic ovary syndrome, and (c) have abnormal tolerance to insulin.
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Principle of Satellite Navigation Orbit and Positioning
Статья научная
We first have studied the principle of satellite navigation orbit and positioning. Then we have taken GPS and Transit satellite navigation system for example, and have discussed them importantly. We also have introduced GLonass globe satellite navigation system of Russia and Navsat navigation satellite system which studied by ESA.
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Problem Solving, Computer Technology, and Students’ Motivation in Learning Mathematics
Статья
In recent years, more and more attentions are given to developing problem solving skills and using computer technology in the teaching and learning of mathematics. Case studies, independent projects, and examples of applications of mathematics are used more and more frequently in mathematics classes in order to enhance students’ development in mathematical thinking and problem solving skills. Two examples of such studies are presented in this paper.
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Programmatically Convert Printable Document to Flash File on Web-based Instruction Platform
Статья научная
Seeing the existing problems of currently known web-based instruction platform and the benefits of flash file, this paper brings up a solution which combines website module with desktop application module based on command-line utility flashprinter.exe and third-party application software, so as to programmatically convert printable documents to flash files, and then detailedly presents the partial main implementation and some run-time interfaces. In the end, the paper draws a conclusion that this solution is applied to web-based instruction platform.
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Programming as an option for females in undergraduate studies
Статья научная
A gender gap exists in undergraduate studies of different careers related to technology. Previous research investigated differences among gender in Science, Technology, Engineering, and Mathematics (STEM) careers and other investigated what influences females to choose a career in computer science. Therefore, an exploratory study was conducted to examine high school student’s perceptions about a technology career in Puerto Rico. The participants on this study were students in different private and public high schools in Puerto Rico, specifically sophomores, juniors and seniors’ females. A sample (n) of 26 female students answered a questionnaire after attending an introductory programming workshop. All of the participants considered the programming workshop as a good experience and they would be interested in attending, and also recommend other girls to attend, future programming events. Results suggest that the highest influence for them to pursue undergraduate studies on a technology program comes from female teachers, mother, and male teachers.
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Promote Research-learning in Teaching of the Basic Theoretical Courses
Статья научная
It is an inevitable choice for college and universities to foster an innovation talent through guiding students to conduct research-learning. In order to foster a “student-oriented” concept and try to bring up the students’ research capabilities in our whole process of teaching, teachers should improve their own teaching abilities and academic levels, carry out research-teaching actively, and make it align with students’ research-learning. It develops research quality and trains students to form an awareness of research so that teachers can promote research-learning in teaching of the basic theoretical courses. This article describes the effectiveness of pilot projects and pilot cases.
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Proposal of Enhanced FDD Process Model
Статья научная
Feature driven development (FDD) is an agile process model that develops software according to the client features. The FDD consists of five processes, several practices and both are providing benefits to improve the software development. Although the FDD provides lots of benefits, but still endures many flaws. In previous research, there have been made numerous modifications in FDD with different aspects. These modifications could not fix all type of flaws and FDD requires improvements in many aspects. These flaws reduce the agility to deliver increments continuously and make an inverse relationship between quality and agility. Due to this relationship, the FDD does not utilize enough time on making extensive documentation, robust design, client or user involvement, and efficient testing. To overcome these issues, an enhanced feature driven development model is proposed. EFDD introduces best practice of agile manifesto named as behavioral driven development used in FDD. In this way, the focus on delivering increments quickly is achieved without affecting the quality of the software. The proposed model provides maximum agility with continuous delivery according to client features and efficient testing strategy which have asses every feature according to client specified functionality.
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Proposal to Improve Mobility in Service Oriented Architecture
Статья научная
Service Oriented Architecture (SOA) is a standard to implement and design applications. It is a channel of communication between service consumer (SC) and service provider (SP). SP offers a service and SC uses a service. Mobile web service verifier component, of SOA architecture, matches best service that is called. Mobile web service verifier component finds a best match of particular service in SP if it is available by the SP. Therefore, there is a pressing need to develop a component that can create a service if it is not found by mobile web service verifier component. This problem is addressed by proposing a new component for SOA architecture called service upgrade (SU) to increase and improve the service creation speed and satisfy SC and SP needs. The questionnaire is used as a research design to evaluate the proposed solution by providing qualitative data. The results show that the majority of respondents are in favor of the proposed solution. It is anticipated that the proposed solution will cater the industrial problem in hand.
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Proposed risk management model to handle changing requirements
Статья научная
The change in requirements while construction of a software may bring into several risks like over budget and extra schedule. The changes in requirements are considered as a high risk to fail the software projects. A good project manager always incorporates risk management paradigm to manage the risks of changing requirements. This research uses available statistical techniques to estimate the cost of risk management with respect to the changing requirement. In addition, a hybrid cost estimation model is proposed using action strategy model to counteract, mitigate and manage the risks of changing requirements. The proposed model is validated using an industrial case study in Saudi Electricity Company (SEC) to conclude the results. The results are found supportive because the proposed model shows significant improvement to estimate the costs of changing requirements as compared to the existing cost estimation models.
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