Статьи журнала - International Journal of Education and Management Engineering
Все статьи: 590
Numerical Images Acquisition and Transmission Based on Microcontroller and CPLD
Статья научная
This paper presents a digital image acquisition and transmission methods. Using CMOS image sensors, under the control of the CPLD and microcontroller with a USB module, the system realizes the digital image acquisition and transmission. The design principle and system implementation are discussed in this paper. The system has high integration, small size and easy to install and portable .It can be well integrated with pre-processed data and image processing module , this will improve the efficiency of the computers operation. For digital image acquisition applications, size and power consumption are key considerations for hardware and software design problems, the CMOS image sensors used in digital image will have broad prospects.
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Object Motion Direction Detection and Tracking for Automatic Video Surveillance
Статья научная
In today’s world having a smart reliable surveillance system is very much in need. In fact in many public places like banks, jewellery stores, malls, schools and colleges it is basic necessary to have a surveillance system (CCTV). Most of today’s implementations are not smart and they record videos during night even when there is no motion. This will lead to unnecessary storage usage and difficult to get the important part of the footage. And also, most of the today’s implementations are stationary, they can’t track the moving object. This report will outline a naive approach to implement a smart video surveillance system using object motion detection and tracking. Here we are using conventional Background subtraction model to detect motion and we estimate the direction of motion of object by comparing the centroid of the moving object in subsequent frames and track the moving object by rotating the camera using servo. Video recording takes place only when there is movement in the frame which helps in storage efficiency. We are also improving the speed of email alert delivery by using multithreading.
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On Basic Principles in Contrastive Analysis
Статья научная
This paper describes some basic concepts in contrastive linguistics, and discusses its function in language teaching. And it compares the English proverbs containing the animal word horse with the equivalent Chinese proverbs. It aims to find the correspondence of the animal word horse in English and Chinese languages and illustrate the cultural phenomenon behind the translation. This paper finds out that the correspondence is very important and can help to understand the languages and the cultures and contribute to the teaching of language. Relevant study should be based on the cooperation and effort of both linguistics and teachers.
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On RFID Application In the Information System of Rail Logistics Center
Статья научная
Storage and Transportation Base of the railway system has comprehensive advantages in network, specialty and linkage. Thus, the Ministry of Railways plans to rebuild 18 logistic central stations in succession from 2007. They not only perform a core function of regional railway container transport organization, but also connect organically with other means of transportations a regional logistics center. Otherwise, the internet of things in our country is about to enter the application stage of innovation. In order to keep abreast of the times, we should consider the application of RFID in the management system while constructing rail logistics center on the high starting point and high standard. This paper will firstly state the correlative knowledge about rail logistics center and RFID technology, and in detail analyze the design of rail logistics center management information system base on RFID. Its object is to accomplish the information processing automatically and efficiently, and pointed out the construction of management information system on rail logistics center.
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On the Theoretical Framework of Autonomous Learning
Статья научная
The present research presents an overview of the definitions of two basic concepts in autonomous learning: learner autonomy, teacher autonomy. Based on these definitions, taking the Chinese context into consideration, this research attempts to redefine these concepts respectively. The present research is mainly concerned with the relevant theoretical framework of learner autonomy, namely cognitive learning theories, humanistic psychology, and constructivist theories of learning, and holds that developing learners‟ autonomous learning ability is very necessary to foreign language teaching reform in China. Several enlightenments are made in the end.
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Ontology Engineering and Development Aspects: A Survey
Статья научная
Ontology can be defined as hierarchical representation of classes, sub classes, their properties and instances. It has led to understanding the concepts of given domain, deriving relationships and representing them in machine interpretable language. Ontologies are associated with different languages that are used in mapping of multiple ontologies. Several applications of ontologies have led towards realization of semantic web. The current web (2.0) is approaching towards semantic web (3.0) that performs intelligent search and stores results in distributed databases. The paper makes readers aware of various aspects of ontology like types of ontology, ontology development life cycle phases, activities involved in ontology development and ontology engineering tools. Ontology engineering contributes to meaningful search and provides with open source tools for deploying and building ontologies.
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Ontology Mapping of Design Process Knowledge Based on Classification
Статья научная
For the requirements of knowledge reuse in product design process, according to the characteristics of the knowledge representation methods, this paper uses ontology knowledge representation method to construct the product design process knowledge model and gives ontology mapping decision strategy which is based on classification. In the basis of choosing "design department" ontology in human resource management as the heterogeneous ontology of "design organization" ontology in product design process management, lists their concepts set and calculates the similarity of matching concept pairs, finally, outputs the mapping relationship table.
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Статья научная
Online product reviews provide data about the user's perspective on the features that were experienced by them. Product features and corresponding opinions form a major part in analyzing the online product reviews. Extracting features from a huge number of reviews is classified into three major categories such as utilizing language rules, sequence labeling as well as the topic modeling. Latent Dirichlet Allocation (LDA) is one such topic model which clusters the document words into unsupervised learned topics using Dirichlet priors. The words so clustered are the features and opinion words in the product reviews domain. To identify appropriate product features from these clusters a hierarchical, domain independent Feature Ontology Tree (FOT) is applied to LDA clusters. The opinion bearing words of obtained product features are identified by utilizing the document indicators available from topic matrix of LDA. These indicators are useful to backtrack to the corresponding online review in which the product feature is present. The polarity of the opinion bearing word is calculated with the help of SentiWordNet. This improves the accuracy of the features using extracted LDA topic clusters and machine interpretation of polarity of opinion word is satisfactory.
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Optimal and Appropriate Job Allocation Algorithm for Skilled Agents under a Server Constraint
Статья научная
In a combinatorial auction, there has a server, some agents, and some jobs which can be used to reach efficient resource and job allocations among the agents. In our paper, we have shown how any server can achieve maximum throughput as well as maximum profit based on some server constraints where each agent has one or more skills to perform those jobs on a priority basis which can be executed in a whole or partial. This algorithm can effectively distribute the appropriate job allocation among skilled agents with proper acknowledgment to the server after a certain period.
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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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