International Journal of Education and Management Engineering @ijeme
Journal articles - International Journal of Education and Management Engineering
All articles: 694
Scientific article
A way to make job matching work better in Nigeria, where the jobless rate is consistently high. Businesses and users alike might gain from the app's user-friendly layout, which makes it simple to publish jobs. Post jobs and submit resumes. The foundation of the program is the SVM algorithm, which searches job ads and user profiles for appropriate matches depending on parameters like education, experience, and the kind of role. This system learns from user interactions and comments to produce even better matches than job boards, which have significantly lower prediction accuracy. We develop secure and scalable applications using front-end and back-end methodologies with React Native and Node.js. This article outlines the system architecture, algorithmic implementation, and first testing results, illustrating how machine learning might transform the employment sector in poor countries such as Nigeria.
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Scientific article
The accuracy of population forecasts is one of the most important calculations in demography statistics. However, traditional demographic methods used in population projections are tend to produce biased results. The need for accurate prediction of future behavior in a number of areas require the application of reliable and efficient methods. Recently, machine learning (ML) models have emerged as a serious competitor to classical statistical models in the forecasting community. In this study, the performance and capacity of the four different ML models such as Random forest (RF), Decision tree (DT), Linear regression (LR) and K-nearest neighbors (KNN) to the prediction of population has been examined. The aim of the study is to find the best performing regression model among these machine learning algorithms for forecasting of population. The data were collected from the State Statistical Committee of the Republic of Azerbaijan website were used for the analysis. We used five metrics such as mean absolute percentage error (MAPE), mean absolute error (MAE), root mean squared error (RMSE), mean square error (MSE) and R-squared to compare the predictive ability of the models. As the result of the analysis, it has been known that the all ML models showed high results with correlation coefficient of 0.985 - 0.996. Also the KNN and RF prediction models showed the lowest root mean square deviation, means square error and mean absolute error values compared to other models. By effectively using the advantage of the ML algorithms, the forecast of population growth the near future can be observed objectively, and it can provide an objective reference to the strategic planning in the public and private sectors, particularly in education, health and social areas.
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Development of relevance feedback system using regression predictive model and TF-IDF algorithm
Scientific article
Domain-specific retrieval systems developed for a homogenous group of users can potentially optimise the recommendation of relevant web documents in minimal time as compared to generic systems built for a heterogeneous group of users. Domain-specific retrieval systems are normally developed by learning from users’ past interactions, as a group or individual, with an information system. This paper focuses on the recommendation of relevant web documents to a cohort of users based on their search behaviour. Simulated task situations were used to group users of the same domain. The motivation behind this work is to help a cohort of users find relevant documents that will satisfy their information needs effectively. An aggregated implicit predictive model derived from correlating implicit and explicit feedback parameters was integrated with the traditional term frequency/inverse document frequency (tf-idf) algorithm to improve the relevancy of retrieval results. The aggregated model system was evaluated in terms of recall and precision (Mean Average Precision) by comparing it with self-designed retrieval system and a generic system. The performance of the three systems was measured based on the relevant documents returned. The results showed that the aggregated domain-specific system performed better in returning relevant documents as compared to the other two systems.
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Diagnosis of Skin Cancer Using Machine Learning and Image Processing Techniques
Scientific article
Skin Lesion is a part of the skin that can be caused by abnormal growth in the epithelium layer on the skin. There are nine types of skin lesion like Actinic Keratoses (AK), Basal Cell Carcinoma (BCC), Dermatofibroma (DF), Melanoma (MEL), Melanocytic Nevi (MV), Benign Keratosis (BK), Vascular Lesions (VASC), Squamous Cell Carcinoma (SCC), and Pigmented Benign Keratosis (PBK). The aim of this study is to spotlight on the problem of skin lesion classification based on early detection of the disease using deep learning techniques. This approach is used to work out the problem of classifying a dermoscopic image. The dermoscopic is a digital device; in this case Smartphone is attached to a lens and collects the images through the device. The proposed spotlight is built in the region of using Convolutional neural network architecture and ResNet-50 module is used to predict Skin-Lesion classification. The dataset used in this research was taken from kaggle repository. The proposed work uses ResNet-50 CNN model which has yielded 93% of accuracy for detecting Skin Cancer, previous work was carried out using Visual Geometry Group model which yielded 73% accuracy. In the proposed work we have considered 25,000 images of skin lesion. Hence we are able to attain this accuracy with more reliable Machine Learning algorithms compared to the previous work.
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Digital Audio Watermarking Based on Artificial Neural Networks
Scientific article
A digital audio watermarking based on artificial neural networks is proposed in this paper. Utilizing the learning and adaptive capabilities of artificial neural networks, the relationship between audio signals and embedded watermark is established by using the important characters of audio signals as the input vector of artificial neural networks, and the watermark were embedded into original audio signals without modifying the audio data. The experimental results show that the embedded watermark is robust to audio signal processing, and the watermarking method does not require the original audio signals for watermarking extraction.
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Discovery and Practice of EDA Experimental Teaching Reform
Scientific article
EDA experiment is one of practical, professional and highly specialized basic application courses in electronic communications professional, how to use EDA laboratory? How to carry out EDA experimental teaching in order to improve teaching effectiveness? These are issues by EDA teaching staff to think and explore. In this paper, with the shortcomings and deficiencies of experimental teaching of traditional EDA, combined the teaching practice of Weifang University, proposed experimental teaching reform thinking of EDA with teaching system systematic, open and teaching methods, teaching evaluation comprehensive, complete security system experiment.
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Discussion Reform of Forestry Panorama Course Teaching
Scientific article
The existing problems such as teaching materials, teaching methods and assessment links of the forestry panorama course teaching are pointed out and some solutions to the problems in thinking are put forward. In addition, the importance and curriculum of the forestry panorama as an entry and enlightenment course is emphasized. The main goal of this paper is to make positive exploration for further deepening reform of course teaching and cultivate high-level forestry talents, and it is hoped to improve course teaching.
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Discussion on Domestic Universities Construction of Digital Teaching Platform
Scientific article
With the rise of Digital Campus 2.0, the construction of digital teaching environment based on multimedia technology, network technology and modern education technology, has gradually become the mainstream of domestic higher education. According to the educational features of colleges and universities, the digital teaching system accessible to spread over should be created in the base of summing up former experiences. This paper points out the existent problems in recent construction process and proposes specific solutions and aims of this construction. Furthermore, it analyzes the main contents of the environment construction, resources construction, team construction and mechanism construction of digital teaching platform.
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Discussion on Teaching Pattern of Cultivating Engineering Application Talent of Automation Specialty
Scientific article
This paper presents some methods to improve teaching pattern of automation specialty to overcome the existing problems in the applications of traditional teaching pattern. These methods include bilingual teaching, class teaching, network teaching and innovation practice teaching. All of these construct a multi-level and stereoscopic teaching pattern, which gives some effective way to cultivate high level creative talented person of automation specialty. The application of the presented teaching pattern in actual teaching practice proves its effectiveness.
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Discussion on Teaching in Computer Course of Information and Computing Science
Scientific article
The information and computing science is the cross-disciplinary of mathematics, information science, planning and control and computing science. The author summarized the experiences through several years teaching practice, analyzed the current situation of the speciality with the actual situation, pointed out some problems in professional curriculum and students’ learning , presented some opinions on o guiding principles in teaching, teaching content and teaching methods . Teachers should play the advantage that the students of this specialty with a solid theoretical foundation in mathematics, content some classic mathematics problems into study of programming languages, combine the computer theory with mathematical theory, optimize the curriculum design subjects , penetrate ideas and methods of software engineering into the teaching experiment. Under the guidance of these opinions, we have gotten some good teaching results.
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Distributed ledger management for an organization using blockchains
Scientific article
In the financial systems of the modern era, trust has always been a missing entity; concentrations of power and trust have given birth to numerous breakdowns. To resolve the problems at this end, the paper attempts for a solution using Blockchains, a data structure that allows for the creation of cryptically secured distributed tamperproof ledgers. The paper discusses the data structure and further disserts on the case study in consideration.
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Dynamic Composition of Web Services by Service Invocation Dynamically
Scientific article
The automatic Web service composition is one of the greatest challenges. The problem of unavailability of public UDDI is motivation to develop an interactive system to search for Web services dynamically using search engines. This paper presents an interactive system for selecting composable Web services automatically and dynamically according to the user requirement through search results of Bingo search engine. The methodology used here is searching for requested functions according to the user requested functional word in the Bingo search engine, finding the search precision by the support of the requested function in the search results, displaying operation elements and allowing the user to select required operation. If the user is unable to enter the input value of the Web services then searching for the Web services that resolves the unknown input. The search process is continued in many levels till the user gets satisfied and the suitable Web services resulted in this process results in the dynamic composition. A composition rule is framed to show the operations of the Web services that are composed according to the user requests during the run time. This is an interactive system, where the user can select required operation from the list of operations. The required parameters to invoke the Web services are filled during runtime automatically resulted into a dynamic invocation of the Web services. Nowadays, QoS information such as availability and response time are not provided by the UDDI due to the absence of UDDI. Therefore, this system tests such information by invoking Web services and qualitative Web services are used to generate composition plan.
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Scientific article
Field service management (FSM) has been faced with the need to efficiently assign tasks to technicians in field service operations (FSOs). The problem of inefficient task allocation has led to either an over utilization or an under utilization of the organization’s workforce and resources across cities and states. This study focuses on developing a resource-efficient multi-criteria algorithm (Proximity-Skill-Priority, PSP algorithm) for optimized field service task management. A mathematical modelling approach was used to design a unified score that takes into consideration the proximity of the technician to the task location, the skillset of each technician and the priority level of the task at hand while ensuring effective workload balance to ensure unbiased task assignment. The study used adaptive weighting coefficients to ensure that real-time adjustments are made when there are varying time conditions. The model was evaluated through a simulation experiment and benchmarked against three single-rule baselines: Proximity-First, Skill-First, and Priority-First assignment. The performance of the algorithms was measured in a 100-run simulation conducted on a synthetic dataset that is parameterized with the attributes of technicians, task priorities, and geospatial information. The lowest average response time and travel distance were achieved by Proximity-First and Priority-First rules, whereas Skill-First produced the highest first-time-fix-rate surrogate at the cost of substantially higher travel and response values. PSP produced a more balanced trade-off: it improved first-time-fix performance when compared to the proximity-first and priority-first heuristics. At the same time, it balances the severe travel penalty observed under Skill-First assignment. Statistical analysis using Friedman and Wilcoxon signed-rank tests shows that there are significant differences in operation across the different algorithms for the evaluation metrics. These findings show that PSP is best interpreted as a compromise strategy that balances service quality and operational efficiency rather than maximizing any single metric in isolation.
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E-Government in Pakistan – Implementation and Challenges
Scientific article
Today, the explosion of information and ever-improving digital connectivity has revolutionized the way business is performed, how organizations work, how the simplest of everyday chores are supposed to be done. A new world order has emerged; with newer, disruptive innovative ideas being incepted at a pace more than anyone could’ve ever imagined only a few decades ago. Public organizations; just like private ones, had to re-invent themselves in order to sustain and keep up with the increasing expectations of digital and effective public service delivery; From conventional government to E-Government. Implementation of e-Government solutions and strategies has become the topmost prerequisite of good governance in today’s globalized world, yet it remains a challenge in most of the developing countries including Pakistan. Despite countless efforts of the federal and provincial government in trying to go paperless, there remains a gap between the government and citizens, in the context of service delivery and between government employees and administration in the context of effective business process transformations. This paper aims to: •Study different models and indexes devised by scholars and organizations worldwide •Current implementations and the reasons behind their success or failure; based on interviews with people engaged in implementations of different digital solutions. •Study key contrasts in current and proposed business processes and their implications •Study key contrasts between ICT implementation strategies adopted by different counties •Identify recommendations and options for the government including institutional and cultural reforms for effective business transformation and service delivery •Engage with the people directly involved with the current and previous implementations of e-government applications in the country to provide the crux of all the challenges faced in different parts of the country. •Act as a roadmap for future ICT implementations in the country.
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EFL Teachers’ Perceptions of Learner Autonomy and Their Classroom Practices: A Case Study
Scientific article
It is considered that learner autonomy places a great emphasis on learners’ role as independent learners who are able to take control over their learning. That is not to say, teachers become redundant in a classroom. In contrast, the key role of the teacher is to create and maintain learning community. Accordingly, this study attempted to investigate EFL teachers’ perceptions of the promotion of learner autonomy and their teaching practices in a Thai context. It was quantitative-focused research, so data were obtained via a closed-ended questionnaire. The participants consisted of thirty EFL teachers who were teaching English at a Thai university. For data analysis, descriptive statistics and Wilcoxon signed ranks test were employed. The results showed that the participants could perceive the concept of learner autonomy and roles of teachers in autonomous language learning, yet most of them found it difficult to apply their knowledge about learner autonomy in this context. It is hoped that these preliminary findings partly contribute to literature regarding the promotion of learner autonomy in an EFL context.
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Scientific article
This project intends to develop an effective educational media that is not only rich in cultural content but also feasible in the museum setting. We want to introduce the Mao-Kung Ting, one of the most valuable collections of the National Palace Museum, to the public in two key aspects—its aesthetic beauty as an antique bronze cauldron, and its historical significance of carrying the longest bronze inscriptions ever discovered among unearthed bronze in China, which has made it plays an important role in the evolution of Chinese characters. Our mission is to develop an interactive installation that could help the audiences to understand this critical cultural heritage with ease. The major techniques that have been employed to facilitate this process include intuitive interactive interface, computer graphics animation, as well as an immersive environment with audio and video.
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Scientific article
There’s a lot of promise around artificial intelligence for education to personalize learning; however, there has been very little research regarding Artificial Intelligence (AI) applications in fields with very few resources for its implementation. This paper describes a proposed AI-based adaptive learning system that aims to personalize STEM education in a low-resource school environment in Kenya. This research addresses the numerous challenges associated with such a system, such as irregular internet access, limited computer hardware in situ and no previous teacher background in both AI and education. To address these issues, an adapted reinforcement learning algorithm will personalize the content shown to students, and a modified liquid neural network is used for the prediction of student success, while not being computationally expensive. As compared to traditional adaptive systems, this adaptive learning platform supports edge computing and offline updates in order to operate in a consistently low connectivity environment. In addition, by continually adjusting the difficulty, format, and rate of delivery of STEM topics to fit the style, prior knowledge, and attention level of the individual student, this platform has been seen to improve the educational experience. An 8-month case study was done with 6 Kenyan low-resource schools and 6 comparison schools located in the city. In this case, we report a 31% increase in the level of understanding of students’ key STEM subjects, 27% reduction in student drop rate from STEM topics, and 43% increase in teacher efficiency over traditional methods. We were also able to predict the level of performance of students to a 89% success while occupying a low 1.9MB memory, making it feasible to be employed on budget Android devices. This study presents evidence that the utilization of AI for personalized adaptive learning technologies in order to minimize the disparities in the provision of STEM education in low-resource settings worldwide is possible.
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Edifice an Educational Framework using Educational Data Mining and Visual Analytics
Scientific article
Educational Data Mining and Visual analytics are two emerging trends in the industry that plays a major role in bringing out changes in the educational institutions. This paper discusses about building an educational framework that suits the higher education in India using the above mentioned technologies. Educational data mining comprises of various technologies and tasks which can applied on educational data to bring out useful information. In this research work, a data ware house is built to store the student data, two data mining tasks classification and association rule mining are applied over the student data set to analyse their performance in the examination. Decision tree algorithm is used to predict the course and program outcome. Association mining is used to analyze the outcome and understand technical capability of the students. The algorithms were found very accurate in predicting and analyzing the performance. Visual analytics is used in the framework to depict the analysis of the student's performance.
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Education Level, Young Migrant Labors and Social Exclusion
Scientific article
With rapid transition in China, young migrant labors begin to replace old ones. However, there are still many obstacles to the citizenization process of young migrant labors, and the main difficulty is social exclusion. From the perspective of social exclusion，this paper uses Logistic Regression, OLS and Ordered Probit to explore the education level‟s impact on young migrant labors‟ social exclusion. Eventually the research discovers that years of education, family burden, psychological gap and friend relationship have a significant effect, and the regression results are steady. Based on it, this paper proposes several ideas of strengthening rural education and reducing exclusion.
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Effective Pedagogical Aspects of the Development of Creative Qualities in Students
Scientific article
The current state of society requires students at educational institutions of any level and direction not only to master knowledge and skills that will be useful in their future professions but also have the ability to conduct an active dialogue with colleagues and management, the ability to clearly and persuasively express their point of view, and the ability to be mobile, active, and creative. This study aims to discuss the effective pedagogical approach on creativity of the students. The taken results of this observation contribute to the manifestation of the future specialist's self-development, self-realization, and the embodiment of his or her own ideas, which are aimed at originality. The student's creative abilities develop in all types of activities that are important for every student. The activation of student creativity is designed not only to awaken and maintain interest in various disciplines and modules, but also, most importantly, to help students realize the need to actualize their own creative abilities in educational and professional activities, ultimately leading to the formation of a graduate specialist competitive on the global education system.
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