International Journal of Education and Management Engineering @ijeme
Journal articles - International Journal of Education and Management Engineering
All articles: 694
An Evaluation Model of Tuition Fee in Higher Education
Scientific article
This paper surveys evaluation and pricing of tuition fee from two perspectives: society and school. We use the optimization theory in fuzzy mathematics and operations research to establish the evaluation model based on overall society and school satisfaction degree; Taking maximum overall Satisfaction degree as our goal and all factors of comprehensive tuition fee evaluation as the restriction, we establish the optimization model of tuition fee pricing to get the tuition standard in higher education. Then we classify disciplines according to the specific reality and calculate the grades and reference prices in disciplines of three schools in Guangdong Province, China. We further obtain the reference tuition fee in other provinces using the regional conversion coefficient. At last we give our directions for tuition fee pricing of higher education.
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An Example of Course Project of Real Time Multitask Programming
Scientific article
This paper states a multi-task programming course project experiment item of real time operating system VxWorks. The project is an emulator of railway ticket vending machine. Its research background is Wuhan-Guangzhou high speed railway line ticket vending machine. The contents of the paper includes process flow, function design and analysis, data flow analysis, task division and definition, semaphore control application, test results, etc.
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Scientific article
The main objective of this study was to explore the practice of traditional church education specifically Zema-Bet education in the three selected Ethiopian Orthodox Tewahido churches found in Bahir Dar city. In doing so, a mixed-method research approach with the convergent parallel design was employed. To achieve the purpose of the study, all the three churches of Zema-Bet education teachers, 90 learners, and three leaders were included in the study by using comprehensive, simple random, and purposive sampling techniques, respectively. An open-ended questionnaire, observation, semi-structured interview, and document analysis were employed for data collection. The collected data were analyzed via descriptive analysis technique and data driven word-by-word thematic narrations. The obtained results confirmed that Zema-Bet education learners usually learn by themselves, and sometimes through peer-led groups under the tree shade. The findings further revealed that some of the principles of adult learning (like practical oriented, motivation to learn, self-directed learning, etc.) are applied in Zema-Bet education. Based on the findings, it is recommended that the government should build a teaching-learning center like what has been done in modern education to resolve the absence of well-furnished buildings and teaching-learning places. Moreover, the government, private agencies, and non-government organizations should support Zema-Bet learners by funding and providing learning materials. Attendant offices of the ministry of education should give attention and recognize traditional church education as one basic education modality and center for adult learning.
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Scientific article
Gifted learners require instructional environments that transcend conventional pedagogical boundaries, offering adaptive challenge, metacognitive scaffolding, and high degrees of learner autonomy. This study presents the design, implementation, and empirical evaluation of the AI-Enhanced Self-Directed Learning (AESDL) framework an integrated adaptive system grounded in Treffinger's Independent Learner Model (ILM) and operationalized through an ensemble of five artificial intelligence (AI) technologies: the Google Gemini API (as central orchestration controller), cognitive computing, multi-agent systems (MAS), expert systems, and automatic speech recognition. The model is built upon four core ILM components Guidance, Self-Development, Enrichment, and Seminars/In-Depth Study each computationally instantiated through dedicated AI subsystems. A quasi-experimental pre-test/post-test control group design was employed with 50 gifted secondary school learners (25 experimental, 25 control) drawn from model gifted-education classrooms in Khartoum State, Sudan. The experimental group received eight weeks of instruction via the AESDL system; the control group received equivalent instruction through conventional electronic resources. Outcome measures self-directed learning skills, problem-solving capacity, and academic enrichment achievement (each scored on a 50-point scale) were analyzed using independent-samples t-tests with Cohen's d effect sizes. Results indicated statistically significant and practically large superiority of the AESDL condition: self-directed learning (t(48) = 7.91, p < .001, d = 2.24), problem-solving (t(48) = 5.52, p < .001, d = 1.56), and academic achievement (t(48) = 6.50, p < .001, d = 1.84). These findings advance the empirical evidence base for AI-mediated gifted education and provide actionable design principles for intelligent adaptive learning systems. The control condition comprised conventional electronic learning resources (digital textbooks, instructional videos, and static online exercises). Ninety-five-percent confidence intervals for the between-group mean differences were [9.13, 15.35], [5.62, 12.06], and [7.02, 13.30] for self-directed learning, problem-solving, and academic achievement, respectively. Given the modest sample (n = 50) and the near-ceiling experimental-group scores, these findings should be interpreted with caution regarding potential ceiling effects and limited external validity, and warrant independent replication with larger, more diverse samples.
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An Image Impulsive Noise Denoising Method Based on Salp Swarm Algorithm
Scientific article
Image noise denoising is a very important task in image processing. Aiming at the shortcomings of traditional median filtering to handle image impulse noise, an approach based on Salp Swarm Algorithm (SSA) to eliminate image impulse noise is presented in the paper. In this method, the improved extremum method is used to detect the position of impulse noise pixels, and then the Salp Swarm algorithm is used to find the optimal pixel value instead of the noise pixel to complete the denoising process of the image. Experimental results testfies that image impulse noise could be effectively filtered out through the proposed method and the manipulated image is clear and more detail could be revealed for human vision.
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An Improved Flower Pollination Algorithm with Chaos
Scientific article
Flower pollination algorithm is a new nature-inspired algorithm, based on the characteristics of flowering plants. In this paper, a new method is developed based on the flower pollination algorithm combined with chaos theory (IFPCH) to solve definite integral. The definite integral has wide ranging applications in operation research, computer science, mathematics, mechanics, physics, and civil and mechanical engineering. Definite integral has always been useful in biostatistics to evaluate distribution functions and other quantities. Numerical simulation results show that the algorithm offers an effective way to calculate numerical value of definite integrals, and it has a high convergence rate, high accuracy and robustness.
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An Improved Multi-objective Evolutionary Algorithm with the Hybrid Strategies
Scientific article
An improved multi-objective evolutionary algorithm with the hybrid strategies is presented in this paper for multi-objective optimization problems. The evolution process is divided into initial exploration stage, the middle feedback stage and the accelerating convergence stage by the amount of non-dominated individuals in the population. The hybrid strategies and adaptive population structure are employed to improve the behavior of the algorithm at the different stages. The proposed algorithm is validated by 3 benchmark test problems. Compared with three other famous multi-objective algorithms by two quality indicators, the proposed algorithm achieves competitive results.
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Scientific article
The mobility of Migrating Instance（MI） brings many risks to the migrating workflow system. Especially, the codes of MI face the risk of being maliciously manipulated by the hostile working places. This paper presents an initiative mechanism of safe-guarding the codes of MI based on danger theory: for MI consists of several modules in order to complete relative tasks, MI will detect whether the block MI determines to run changed before executing. If there are some changes, MI will then perceive whether the changes dangerous; if dangerous, appropriate measures will be taken to amend the damaged codes and then obfuscate them lest this module will be attacked easily again. This mechanism improves the efficiency of MI compared with other mechanism, and makes MI avoid temporary attacks, which are illustrated with the experimental results at the end of this paper.
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An Intelligent Survey of Personalized Information Retrieval using Web Scraper
Scientific article
In this paper we aim to do an intelligent background survey of Personalized Information Retrieval, a specialized and crucial subsection of Information Retrieval or IR. We have chosen the method of IR as Web Scraping, a technique that is extremely popular and is proven to have multi-domain usage.
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An Intelligent, Bilingual Pregnancy Health Monitoring System
Scientific article
This research implements an intelligent, bilingual pregnancy health monitoring system for expectant mothers. A significant problem commonly experienced by expectant mothers in rural areas in Nigeria is the unavailability of a decent antenatal system and a shortage of experienced medical personnel and equipment. The proposed system comprises IoT sensors, including Electrocardiogram (ECG), body temperature, and heart rate sensors, connected to an ESP32 microcontroller for data acquisition and transmission. A predictive system built using Random Forest and Support Vector Machine (SVM) classifiers categorises pregnancy risk into low, medium, and high. A Flask-based web application for real-time data visualization and diagnosis was developed to display the collected data and visually represent the risk level diagnosis. The performances of the predictive models, Random Forest and Support Vector Machine (SVM), were evaluated using accuracy, precision, recall, and F1-score. Random Forest achieved an accuracy surpassing SVMs by a margin of 5.28%. Random Forest and SVM precision were then compared and there was an improvement of 6.49%. In addition, Random Forest had a higher recall than SVM by 6.58%, and also had a performance increase of 6.49% on F1-score as compared to SVM. The comparative analysis shows that the Random Forest model works better than SVM in all the main measures. In this project, the Random Forest model was better than the SVM because it uses ensemble learning to manage the non-linear relationship, imbalance data and noise better to achieve superior accuracy, recall, and the F1 Scores. It was also more reliable in categorizing risks in pregnancy, as it was interpretable, which was also strong and guaranteed the timely and suitable intervention of health care.
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An Internet of Thing based Agribot (IOT- Agribot) for Precision Agriculture and Farm Monitoring
Scientific article
Developing nations like India have a huge potential for agricultural business and better cultivation. Because of the large size of cultivation land, improper water supply systems and lack of technology-based agricultural practices, there is a huge gap among expected and actual quantity and quality of agricultural products. Hence there is a need for significant revival in agribusiness using emerging technologies. The article proposes an intelligent water framework device called Agribot designed for the agricultural industry to minimize the water wastage and a better supply of cultivating materials using the Internet of Things (IoT). Our proposed IOT- Agribot will energize the water framework, improve the cost-effective water usage and reduce the labor force to achieve precision agriculture. The proposed IOT- Agribot has performed well for variable weather conditions, soli type, moisture content and crops.
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An Investigation on the Metric Threshold for Fault- Proneness
Scientific article
The software quality can be enhanced with the awareness and compassionate about the software faults. We acknowledge the impact of threshold of the object-oriented metrics on fault-proneness. The prediction of fault-prone classes in early stage of the life-cycle assures you to allocate the resources effectively. In this paper, we proposed the logistic regression based statistical method and metric threshold to reduce the false alarm for projects that fall outside the risk range. We presented the threshold effects on public datasets collected from the NASA repository and validated the use of threshold on ivy and jedit datasets. The results concluded that proposed methodology achieves the speculative results with projects having similar characteristic.
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Scientific article
Modern technologies like 5G, the Internet of Things (IoT), and Artificial Intelligence (AI) have just come together, creating previously unheard-of chances for creative solutions. As a result, several IoT use cases have come to fruition, particularly in the healthcare industry, enabling the creation of eHealth and mHealth applications for ambient assisted living (AAL). However, there are practical issues with the current healthcare system, such as service delays and exorbitant expenses, which have had serious repercussions, such the untimely passing of famous people from heart attacks. Real-time patient monitoring and therapy with few delays are necessary to solve these pressing challenges. IoT has changed the game in this area by making it easier to establish Remote Patient Monitoring (RPM) systems. Vital indicators can be sent in real time to clinicians using IoT-enabled wearable devices (biosensors), enabling quick intervention and the start of treatment. This article gives an overview of the state-of-the-art in RPM using IoT, highlighting its potential to save time, lower healthcare expenses, and considerably raise patient quality of life and the caliber of healthcare services. It also identifies research holes and ways to use RPM systems, laying the groundwork for further development in this area.
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An approach for software development for the management of an assembly line
Scientific article
The article presents an approach for software development for the management of an assembly line. Basic software tools and hardware solutions that are needed for the development of the software are described. Design of specific software for the management of an assembly line for bottling liquid food products is presented. A specially developed algorithm for the management of the assembly line is described. The realization of the management of the assembly line in the programming environment Simatic Manager Step 7 and the developed user interface in the graphical environment Simatic WinCC Flexible are also presented. The design of software for the management of an assembly line for bottling liquid food products is extremely important for the development of automated manufacturing in Bulgaria. After detailed testing of a trial version of this software, it will be used in Bulgarian company for the management of an assembly line for bottling liquid food products. The developed software is an open system that can be continuously updated and improved. This software is applicable in all manufacturing plants for bottling liquid products from canning, pharmaceutical, cosmetic industries and many others.
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An approach to represent social graph as multi-layer graph using graph mining techniques
Scientific article
In Social Graph, a set of entities or nodes or vertices interact with each other in a complicated manner that can form multiple types of relationships that depend on time and types of complications. Such graphs include multiple subsystems and layers of connectivity. So it is important to take such multi-layer features into account to make easier of understanding of such complex systems. In this paper, the author focuses on a Social Graph to represent in a multi-layer graph based on its characteristics lies in each node or vertex or entity. For this, the author proposes a general model related to Social Graph. For this model, the author proposes an algorithm, SoGraM for representation of Social Graph with multi-layer features using Graph Mining Techniques. Further, the author tries to prove the proposed algorithm with three examples of Social Graph namely Author Graph, Email Graph, and Telephone Graph.
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An efficient Group Key Management Scheme for Ad Hoc Networks
Scientific article
Ad Hoc networks are characterized by frequently changing network topology. Due to the lack of central authority, forming security association among a group of members in Ad Hoc networks is more challenging than in traditional networks. With the view in mind, group key management plays an important building block of any secure group communication. In this paper, we proposed a group key management based on Identity-based Cryptosystem and Chinese Remainder Theorem. In the proposed scheme, there are no requirements of member serialization and existence of a central entity. Besides this, the scheme the protocol also many highly desirable properties such as contributory and efficient computation of group key, uniform work load for all sensor nodes and efficient support for high dynamics. Compare to other existing group key agreement protocols, the proposed protocol make no assumption about the structure of the underlying wireless network, making it suitable for Ad Hoc networks.
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An efficient approach for Web mining using semantic Web
Scientific article
The volume of data on the Web is increasing rapidly. The rapidly increased data in Web have brought an urgent need to develop a method to organize that data. At the same time, the level of user expectation of getting précised data is increased highly. Hence, it is tough to satisfy the user satisfaction through the existing system. In this paper, we proposed a model to organize the large volume of data over the Web and retrieve the more relevant data to the user. As an implementation of the proposed model, we built two demo search engine (one for RDF based semantic searching and another for existing searching). We use two different sets of data for testing. For every set of data, the RDF based searching returns more précised data than existing searching. The efficiency of the proposed model is better than the existing searching strategies. In the proposed model, we considered both traditional web and RDF based ontology library to organize the data effectively.
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Scientific article
Grid computing consists of achieving an effectual clustering of the valuable resources having dissimilar locations which will deal with real time scenarios. The grid follows the dispersed procedures having heavy workloads which can be in the form of the traffic files from different locations. Grid computing is related to the extraordinary performance systems like computer clustering or we can say nodes in the grid in such a manner that each set of the node performs different tasks and applications. Grid computers also deals with networks with topology variations and diverse geography which is not essentially to connect substantially to the cluster of computers. As the number of traffic increases day by day, is the challenging task to complete all the allocated processes in the limited time intervals. So this research deals with the efficient scheduling and optimization approach for the resource management using Ant colony optimization and round robin scheduling to obtain low execution intervals with less error rate probabilities. The whole simulation is done in MATLAB environment.
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An efficient software development life cycle model for developing software project
Scientific article
There are different life cycle models available for developing various types of software. Every Software Development Life Cycle (SDLC) model has some advantages and some limitations. In that case software developers decide which SDLC model is suitable for their product. Further, we need development of software in a systematic and disciplined manner. This is advantage of using a life cycle model. A life cycle model forms a common understanding of the activities among the software engineers and helps to develop software in a proper manner, so that time can be reduced. The objective of this paper is to compare all traditional or existing SDLC model with our Proposed SDLC model for development of software in effective and efficient manner.
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An enhanced approach for quantitative prediction of personality in Facebook posts
Scientific article
Social media is a collection of computer-mediated technologies that encourages the creation and sharing of data, thoughts and vocation interests by means of online communities. There are various kinds of web-based social networking i.e. micro-blogs, wikis and social networking sites. Different social media like Facebook, LinkedIn, Google+ and Twitter are the popular sources for connecting people all over the globe. Facebook is one of the commonly used platform where individual’s used to stay in touch, business personnel used for marketing and others used to share expedient information. Due to this lucrative nature, one’s personality can be predicted on the basis of posts created, commented on others post and likes against any posts. We have developed in-house tool using python language that defines personality in terms of psychological model of Big-5 personality traits including extraversion, neuroticism, agreeableness, openness and conscientiousness. The dictionary based approach has been used in this tool in which we have combined three dictionaries (WordNet, SenticNet and Opinion Lexicon). Our proposed technique has shown promising results as we have analyzed 213 unique Facebook profiles and their results outperforms the others. Furthermore a comparative analysis of machine learning classifiers i.e. support vector machine, na?ve bays and decision tree has performed. Our approach succeeds to predict personality traits. We are intended to predict personality from roman English posts in future.
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