Статьи журнала - International Journal of Education and Management Engineering
Все статьи: 613
Efficacy of Assistive Technology for Improved Teaching and Learning in Computer Science
Статья научная
This study examined the efficacy of assistive technology (AT) for improved teaching and learning in computer science (a case study of an inclusive educational system). Two (2) hypotheses were formulated and tested for this study. A descriptive survey method was adopted for this study, the population of this study comprises all Students with special needs and all teachers teaching at Durbar Grammar School, Oyo, Oyo State, Nigeria. A purposive sampling technique was used to select twenty (20) respondents (teachers) and all the Students with special needs were involved (40). A structured questionnaire of two sections (sections A and B to be answered by the Teachers and the Students respectively) which was validated and tested for reliability was used; a reliability coefficient of 0.81 was obtained. Simple percentages and the Chi-square statistical method were used to analyze the collected data which was tested with this study’s hypotheses. The results of this study revealed that AT is capable of improving the teaching and learning of computer science for Students with special needs in an inclusive education if AT is allowed to play its role. It was also discovered that both the teacher and students with special needs were exposed to very little AT and there was no periodical training programme for both the teachers and the students with special needs on the use of AT which has affected their teaching and learning ability. This paper, therefore recommends that a periodical training programme on the use of AT be organized by all the stakeholders in inclusive education for both the students with special needs and all the teachers teaching them.
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Efficient Round Robin Scheduling Algorithm with Dynamic Time Slice
Статья научная
Round Robin (RR) scheduling algorithm is the widely used scheduling algorithm in multitasking. It ensures fairness and starvation free execution of processes. Choosing the time quantum in RR algorithm is very crucial as small time slice results in large number of context switches and large time quantum increases the response time. To overcome these problems of RR scheduling, instead of static time slice dynamic time slice can be used to get optimal performance. The objective of this paper is to modify RR algorithm by adjusting time slices of different rounds depending on the remaining CPU bursts of currently running processes and considering their waiting times until that round in respect of the other processes' waiting times. Experimental analysis reveals that the proposed algorithm produces better average turnaround time, average waiting time and fewer number of context switches than existing algorithms.
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Emerging Trends in Database and its Applications in MNC’s
Статья научная
When information is set for easy retrieval, access, updation, and management, then it is known as Database. Its major purpose is storing aggregations of records and data files that contain information regarding transactions, customer details, product details and financials. The paper deals with a briefing on DBMS which is a collection of inter-related data and set of programs to retrieve and access the data which focuses on :- a) exchange of data, b) retrieve the data, c) storage of data, and d) manipulation on data. The paper also gives a glance on elements of DBMS also describes the architecture which is consist of: a) internal level, b) conceptual level, and c) external level. The paper also mentions some of the uses of databases and will try to give an idea about the applications of Database in different MNC’s and projects in Data ware.
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Emotional Deficiency in Web-based Teaching Environment and Its Solving Strategies
Статья научная
In china, developing rapidly in Internet teaching exits serious lack of affection. This article aims to analyze the features on the lack of affection, reveal the causes of it and try to give corresponding solutions. The results indicate that lack of affection have manifested themselves mainly on lacking affinity for the resources of the network courses, being deficient in emotional information in virtual communication, being careless with emotional communication, the commercialized relations between teachers and students, and the lack of positive emotion. The main reasons that bring about the lack of affection are the impact of traditional education which pays more attention on intellectual education instead of affective education, the difficulties of design of teaching in affective domain, the inadequacy of role transition of teachers, the defects of Internet environment, the inadequacy of interaction in network teaching. At last, based on the perspective of teachers, students, and study resources, corresponding solutions on the lack of affection are given.
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Empirical Study on Forewarning of Urban Sustainable Development
Статья научная
A forewarning model was set up to evaluate the process of urban sustainable development based on fuzzy matter element theory. Taking status of Nan tong city from 2005 to 2008 as an example, we set up an index system of forewarning in the process of urban sustainable development in Nan tong and established the forewarning standards, limits and degrees.
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Empirical analysis of cervical and breast cancer prediction systems using classification
Статья научная
Cancer is a life-threatening disease with high mortality rates. In the Indian subcontinent, women have a higher possibility to be diagnosed with cancer than men. The most common cancers identified in Indian women are Breast Cancer and Cervical Cancer. Both these cancers have high survival rates in case of early prediction. This paper reviews the attributes which are used in the existing datasets for prediction of these two cancers. The paper also proposes new attributes to overcome the limitations of existing ones, which will further increase the effectiveness of cancer prediction systems. The efficiency of existing and proposed attributes is compared by processing datasets through data mining algorithms using WEKA tool. The algorithms used for this study are – J48 (Decision Tree), Na?ve Bayes, Random Forest, Random Tree, KStar and Bagging Algorithm. The empirical analysis done in the paper reported improvement in the efficiency of cancer prediction over existing prediction systems.
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Employee attendance monitoring system by applying the concept of Enterprise Resource Planning (ERP)
Статья научная
Enterprise Resource Planning (ERP) is a business process management system that integrates and automates the activities of an organisation in terms of its technology, human resources and services. ERP provides an integrated environment that links the business processes of different departments of an organisation into one unit so that departments benefit from each other through their joint transactions. This study applies the ERP concept to create an employee attendance monitoring system (EAMS). Three departments, HR, Finance and the Director of Administration, were linked using the EAMS. The traditional system of attendance monitoring was time consuming and required greater effort. This is because the attendance report needed to be printed from the HR department and then sent to the Finance Department for any necessary actions (i.e. salary deduction). The EAMS will automate the whole process, thus resulting in fair decisions in less time. In the traditional system, the any delay in calculations of attendance can be unwarranted or maintaining an accurate time record can be difficult as it is manually updated. To solve these issues, a computer based monitoring system is required to establish accuracy and fairness. For that purpose, we designed and developed the EAMS. The EAMS automatically calculates any delay in employee attendance using the concept of ERP systems. More precisely, this system will calculate the delay in the attendance within set rules, as defined and applied by the different departments in the organisation. The attendance times will be checked automatically by the system: if there is any delay which violates the set rules of the organisation, necessary action will be taken automatically against the employee in terms of salary deduction or other notifications. To apply the EAMS, we constructed a case study at the “Faculty of Economics and Business Administration at King Abdulaziz University, (Female Section)”. Later, it is hoped, that this system can be used in other organisations based on their needs and enhancement to the existing framework. The expected results of this system are that it will save time and effort for all employees at the Faculty of Economics and Administration. In addition, there will be a reduction of errors in the attendance reports.
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Статья научная
The Indonesian Election is one of the most anticipated political contestations among the Indonesian people. Mainly because the results of the Indonesian Election are leaders in Indonesia ranging from governors and legislative members to the president and vice president of Indonesia, who will lead the next five years, considering the importance of the five-year agenda, the dissemination of good information about work programs, the activities of prospective leaders who will elect in the 2024 election and various news stories are starting to spread on Twitter. Based on this, this research aims to analyze public sentiment on Twitter wa The research method used is SMOTE-Tomek Links to overcome imbalanced data. In contrast, sentiment analysis uses Binary Logistic Regression. Evaluation related to this model measures accuracy and ROC Curves. The evaluation results show that the SMOTE-Tomek Links method is less than optimal for the data used in the research, namely the 2024 election data, with an accuracy value of 0.581 for training data and 0.406 for testing data. Undersampling methods such as Tomek Links and Random (undersampling) show higher values when combined with Binary Logistic Regression in analyzing the sentiment produced in this study, namely 0.983 and 0.938 for the Tomek Links method and 0.964 and 0.902 for the Random (undersampling) method, respectively -each for training and testing data.
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Enlightenment on Chinese Evaluation Standard of Educational Game Software from TEEM's
Статья научная
The author takes the evaluation standard of educational game software（EGS） made by TEEM as an example and analyzes its dimensionality, content and effectiveness. Then the author stresses the enlightenment on the evaluation standard of Chinese EGS about evaluation organization, evaluation scientificity and evaluation efficacy. The aim of this paper is to offer guidance to those enterprises producing EGS, schools and families purchasing EGS, teachers and students using EGS and promote Chinese evaluation standard to match international standard.
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Enterprise Architecture: A Tool for IS Strategy Formulation
Статья научная
Nowadays, many organizations are concerned with how successfully they can formulate an information system (IS) strategy. Have them adopted enterprise architecture, they are concerned of how to activate the business and IS decisions. From a functional perspective, enterprise architecture demonstrates how all information technology elements in an organization, systems, processes and people work together as a whole. Hence, enterprise architecture is an approach of aligning the business area of an organization with the IT area. It has become widely recognized that an enterprise architecture plays a key role in influencing the IS strategy formulation. Strategy formulation in enterprises is a continuous process and it is considered an implicit process that is influenced by a set of factors in which enterprise architecture is a major one. In this paper, we discuss that role that an enterprise architecture plays in influencing the IS strategy formulation.
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Essential and New Maintenance KPIs Explained
Статья научная
Maintenance in any manufacturing organization is critical, given its significant role in ensuring business continuity. Maintenance plays a crucial role and has a significant impact on the results of industrial companies. Therefore, it is essential to manage maintenance, observe, understand, and improve actions by adopting well-chosen performance indicators according to the company's needs. These indicators are known as Maintenance KPIs or Key Performance Indicators, which allow for gathering knowledge and exploring the best means to achieve the organization's goals. Maintenance KPIs are critical to keeping track of the function, monitoring performance, and ensuring fulfillment of business expectations. In addition, KPIs drive reliability growth while guiding decisions to improve maintenance efficiency and performance. A helpful maintenance KPIs help to identify the problems causing the maintenance effect and help to select the right strategy to support or correct the actions that produced the results. They also allow to identify the causes of equipment failures (measure the influence of life cycle factors), direct what maintenance does with its time and resources (measure the efficiency and effectiveness of the maintenance group) and identify if maintenance removes failure causes ( measure the improved reliability and operational risk reduction results of maintenance effort) and help drive the business benefits provided by maintenance (measure the contribution to the business value of maintenance). Essential maintenance KPIs are the most commonly used for maintenance management and are adopted by most industries; among these primary KPIs which are essential for maintenance management, we cite Mean Time Between Failure (MTBF), Mean Time To Repair (MTTR), and Overall Equipment (OEE). Nevertheless, it is crucial to continuously redefine and update KPIs to ensure they are appropriate for the organization's current environment, significantly when the constant market or research methodologies change. Hence, researchers and the industry propose several other maintenance KPIs outside the essential ones used in the industry according to the needs and within the performance improvement framework. These proposed KPIs aim to compensate for the lack of maintenance data, the absence of decision support, and the problems related to specific equipment, also in the context of improving the management strategy, the application of predictive maintenance, and the quality control of a maintenance process or the monitoring of systems reviews. Unfortunately, these indicators are not sufficiently known and are, therefore, not used by the industry. However, we believe that some of them should gain maturity and reach the status of widely used traditional indicators, such as the KPI of obsolescence management in maintenance operations and schedule compliance KPIs that aim to link maintenance planning with production. In addition, although not all proposed KPIs in the literature are generalizable, it has been identified that they can sometimes be specific to problematic situations, equipment categories, and even sectors of industry activity. Therefore, this work aims to inventory the most widely used maintenance KPIs and some of the KPIs proposed by researchers and the industry. In addition, we study the trends and challenges of selecting these KPIs and for what purposes they are used to help their understanding and usability. Indeed, Maintenance managers need to select relevant KPIs aligned with the maintenance strategy and the company objectives.
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Evacuation Simulation of Counter-current Behavior Using Agent Model for Pedestrian Dynamics
Статья научная
It is an important issue that all occupants should be able to evacuate to safety from sports stadium under emergency. The behavior of occupants is quite complex, and individual behavior will greatly affect the result of the evacuation. Such as the phenomenon of counter-current behavior, sub-group behavior, following behavior and so on. In this paper, we mainly study the counter-current behavior, and a system simulation model is presented, which based on the agent technology. And in order to study the effect on evacuation, two cases have been studied to analyze the impact of evacuation. Simulation processes and results display that the counter-current behavior will be harmful for the movements of people. Simulation processes and results display that the model is very close to real movements of people.
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Статья научная
This paper is dedicated to a comprehensive analysis of hybrid energy options, with a specific focus on exploring their economic and environmental advantages within the context of an ice cream factory located in Fukuoka, Japan. The study takes a holistic approach, delving into various facets such as power generation, energy expenses, and related factors to uncover the potential benefits associated with specific configurations of hybrid energy solutions. The analysis presented in this study serves as a valuable tool for assessing the impact of different power generation technologies and energy management strategies. It sheds light on how these choices can influence not only the factory's operational costs but also its environmental footprint. By quantifying these effects, the study provides critical insights that can guide decision-makers toward more sustainable and economically sound energy solutions. As a forward-looking application approach, this research envisions the utilization of a PV-wind-diesel-grid-electrolyzer power system. This hybrid configuration serves as a versatile platform for conducting simulation studies, allowing for the exploration of a wide spectrum of potentially viable solutions. The insights derived from these simulations not only facilitate informed decision-making but also pave the way for anticipating and strategically planning future energy implementations. In essence, this study represents a proactive and data-driven approach to energy optimization, offering the ice cream factory in Fukuoka a roadmap to harnessing the benefits of hybrid energy systems, ultimately contributing to both economic efficiency and environmental sustainability. So, at a cost of energy (COE) of 18.313¥ per kWh, this arrangement stands out as an economically advantageous and environmentally friendly solution for the electrification of the ice cream factory.
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Статья научная
Key Process Areas (KPAs) for Software Engineering Institute (SEI) Maturity Level 4 can be described in terms of Quantitative Process Management (QPM) which is the metric to control the quantitative performance of a software project. On the other hand, Software Quality Management (SQM) monitors and controls the quality of the project. The survey conducted in this paper covers around 20 software houses of Pakistan. The study revealed that there is weakness in both KPAs, SQM and QPM. Each KPA defines a set of rules that are necessary to be followed to meet the standard but many organizations fail to follow these rules defined in every KPA. If specified and appropriate measures are taken, the software industry will lift it up to the higher CMMI Level.
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Статья научная
With the development of technology the use of Computer Aided Diagnosis has become a key for breast cancer diagnosis. It is important to increase the accuracy and effective of such systems. The concept of data mining can be applied on the data gathered through such systems for prediction and prevention of breast cancer. In this research, we have conducted the comparison between seven classification algorithms with the help of WEKA (The Waikato Environment for Knowledge Analysis) tool on the 569 instances (10 nucleus attributes) of data with two classes Malignant(M) and Benign (B) of breast cancer aspirate cells. Furthermore the influence of each attribute on prediction was evaluated. The accuracy of these algorithms was above 91% with the highest value of 94.02% for random forest and the predictive power of conclave points was highest whereas lowest was of Fractal Dimension.
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Evaluation of Machine Learning Techniques for Email Spam Classification
Статья научная
Electronic mail (Email) is one of the official and very common way of exchanging data and information over digital and electronic devices. Millions of users worldwide use email to exchange data and information between email servers. On the other hand, unwanted emails or spam became phenomenon challenging major companies and organizations due to the volume of spam which is increasing dramatically every year. Spam is annoying and may contain harmful contents. In addition, spam consume computers, servers, and network resources, causes harmful bottleneck, effect on computing memory and speed of digital devices. Moreover, the time consumed by the users to remove unwanted emails is huge. There are many methods developed to filter spam like keyword matching blacklist/whitelist and header information processing. Though, classical methods like blocking the source to prevent the spam are not effective. This study demonstrates and reviews the performance evaluation of the most popular and effective machine learning techniques and algorithms such as Support Vector Machine, ANN, J48, and Naïve Bayes for email spam classification and filtering. In con conclusion, support vector machine performs better than any individual algorithm in term of accuracy. This research contributes on the for the development of methods and techniques for better detection and prevention of spam.
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Evaluation of Voice & Ear Biometrics Authentication System
Статья научная
The core aim of biometrics authentication methods and technologies is to solve issues and concerns existing in traditional authentication methods like passwords, PIN numbers or identity cards. The Most important concern for business sectors and organizations is to authenticate individuals who interact with them and their services. By considering more than one biometric technology, the authentication process is expected to be more reliable and secure. The Ear and Voice Multimodal Biometrics System is evaluated to compare its performance with ear and voice unimodal systems; the multimodal system takes advantages of the permanence characteristic of ear biometric and voice biometric which is highly acceptable by users. According to the experiment, the ear and voice multimodal system provides better performance than the ear or voice unimodal system. In addition to that, the multimodal system makes a right balance between false rejection and false acceptance rates. This evaluation is intended to contribute to multimodal biometrics research by using behavioral biometric (voice print) and physiological biometric (ear-print) and makes advantage of using both of them in one system.
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Event Stream Processing in BRT Environment
Статья научная
Bus Rapid Transit (BRT) system is a kind of Intelligent Transportation System (ITS), which combines wireless communications, computational technologies, floating car data/floating cellular data technologies, inductive loop detection and so on. The GPS (Global Position System) data and the loop detection data are arriving at the BRT dispatch center massively at the same time so the dispatcher can know the real-time status of buses. The passenger flow data are also captured by devices deployed in the stations and then be passed to center too. How to handle those data at low latency and get some events to be used in bus dispatching is really a problem. In this paper, we propose a framework using ESP (event stream processing) technologies that solves the problem more effectively. At last we demonstrate a prototype system implementation that applies in BRT Line 1 project in Beijing.
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Exact Solutions of Kuramoto-Sivashinsky Equation
Статья научная
Many nonlinear partial differential equations admit traveling wave solutions that move at a constant speed without changing their shapes. It is very important and difficult to search the exact travelling wave solutions.In this work, the auxiliary Riccati equation method and the computer symbolic system Maple are used to study exact solutions for the nonlinear Kuramoto-Sivashinsky equation. Maple can help us solve tedious algebraic calculation. Therefore many exact traveling wave solutions are successfully obtained which include some new kink (or anti-kink) wave solutions and periodic wave solutions.
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Experimental Comparison of Mutation Testing Tools for C Sharp Language
Статья научная
Mutation testing is a popular software testing technique, that inject artificial faults into the program and requires test cases to reveal these faults. In this paper, an experimental comparison is analyzed for different types of mutation testing tools in C Sharp language in .NET framework. Different mutation testing tools are giving different mutation score for a program. The objective of this paper is to investigate why the mutation score is different for different tools, and the scope of generating mutants depending on different types of operators. Four tools, such as, Visual Mutator, Cream, Ninja Turtles, and Nester are selected and applied to a program and analyze the outcome. Among these four mutation testing tools, Visual Mutator is better because of its higher mutation score, and it generates mutants for both common and uncommon standard operators and object level operators.
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