International Journal of Modern Education and Computer Science @ijmecs
Статьи журнала - International Journal of Modern Education and Computer Science
Все статьи: 1160
An Investigation into Mobile Application Development Processes: Challenges and Best Practices
Статья научная
The mobile device market has witnessed swift industrial growth over the last decade. The quick expansion of this new computing platform has almost outpaced the software engineering processes customized to mobile application development. However, there is still lack of novel research initiatives around the mobile application development process. There remains a deficiency in development standards and best practices which expose the mobile device to potential attacks. This deficiency needs to be addressed promptly and requires further work. The objective of this research is to better understand the current methodologies adapted and to investigate challenges faced during the mobile application development processes that are different from traditional enterprise application. For this purpose, an online survey was conducted from the mobile research and development community. The survey questions covered the entire mobile application development lifecycle starting with requirements, and ending with bringing to life a complete mobile application. The study contributes towards a greater understanding of mobile application development process, examines real challenges confronted, and investigates the best practices that can be successfully implemented to enhance, evaluate, and improve the performance of the mobile application development process. These findings can also be considered as a possible research topic that indicates the breadth of research requirements and prospects in mobile computing.
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An Investigation of Software Engineering Knowledge of Undergraduate Students
Статья научная
Computer programming (CP) course offered in universities is difficult coupled with insufficient infrastructures and teaching staff. In spite of these, several undergraduate Computer Science (CS) students are increasingly acquiring programming skills and developing commercial applications even without attending formal programming classes. However, software intended for use other than by the developer requires teamwork, the use of software engineering methodologies and quality. What is not known about these undergraduate students is how their programming is learnt or applications developed. This is important in the light of software dependability and cost of failures today. Therefore, this paper investigates how undergraduate CS students learn programming and their software engineering knowledge. The purpose is to gain insights into how knowledge is gained and applied. To accomplish this, the paper conducted a survey utilizing questionnaire and interview on undergraduate students of CS in the University of Venda (UNIVEN). The data collected were analyzed and results quantitatively and qualitatively presented. The results showed that many CS students learned programming via the Internet reusable code, applied development methodology and are aware of software quality during development.
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An Ontology Based Remote Patient Monitoring Framework for Nigerian Healthcare System
Статья научная
There is a rapid increase in the demand of healthcare resources in Nigeria mainly healthcare personnel and healthcare facilities. This is due to the prevalence of chronic diseases such as endemic malaria, arthritis, hypertension, diabetes; an upsurge in the rate of avoidable deaths as well as an exponential increase in the population. However, healthcare resources in Nigeria are insufficient. For instance, in recent times, the ratio of doctors to the inhabitants is 1: 4,857. Moreover, more than 60% of the Nigerian populace resides in rural areas where there are extreme shortages of healthcare practitioners and healthcare facilities due to geographical isolation and lack of opportunities. Hence, the low ratio of healthcare practitioners to patients causes a heavy workload on the healthcare practitioners. This however leads to medical errors as healthcare providers work under intense pressure to attend to the medical needs of their patients. This in turns leads to considerable loss of lives. In order to ameliorate this situation, this paper proposes an ontology based framework that will enable healthcare providers in Nigeria to continuously monitor their patients' health remotely outside the settings of the hospital. This will reduce the workload of the healthcare providers, assist them in decision making process as well as reduce the long waiting hours of the patients within the hospital environment. This framework is also designed to tackle the challenge of semantic interoperability facing healthcare systems around the globe.
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An Ontology-Based Approach for Multi-Agent Systems Engineering
Статья научная
This paper presents OBAMAS (Ontology-Based Approach for Multi-Agent Systems engineering), an ontology-based contribution to Agent Oriented Software Engineering. We propose a formal process for agentification, starting with an analysis phase which consists of the construction of three formal ontologies (a domain ontology, an ontology of functionalities, and an ontology of multi-agents systems) and their alignment to merge in a single one. The second step, which is a design phase, consists of the operationalization of the single ontology in order to infer in a more formal way the agents of the system. A case study is introduced to illustrate OBAMAS and to show its use and effectiveness in a real application, a distance learning system.
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An Optimized Machine Learning Approach for Predicting Parkinson's Disease
Статья научная
Parkinson's disease (PD) is an age-related neurodegenerative disorder affecting millions of elderly people world-wide. The early and accurate diagnosis of PD with available treatment might delay neurodegeneration and prevent disabilities. The existing diagnosis method such as brain scan is an expensive process. The use of speech recognition with machine learning technologies for the diagnosis of PD patients could be less expensive. In this work, we have worked with the voice recorded dataset from UCI machine learning repository. Several studies were performed to identify PD patients from the healthy individuals by using voice recorded data with machine learning algorithms. In this paper, we have proposed an optimized approach of data pre-processing that enhances prediction accuracy for diagnosing PD. We obtain 97.4% prediction accuracy with higher sensitivity, specificity, precision, F1 score and kappa value by using AdaBoost. These improved performance evaluation metrics indicate, the use of voice recording with our optimised machine learning approach is highly reliable in prediction of PD. This approach may have significant implications for early stage diagnosis of PD in a cost-effective manner.
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An approach to determination of maximal cliques in undirected graphs
Статья научная
The article proposes the implicit exhaustive search procedure based on the triangle decomposition of graphs for determining the maximal clique in the arbitrary undirected graph G in polynomial time; it has allowed developing an exact algorithm for solving the problem with time complexity not exceeding , where is the number of vertices in the graph G.
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An approach to parallel sorting using ternary search
Статья научная
This paper describe a parallel sorting algorithm which is the combination of counting sort and ternary search. The proposed algorithm is based on split and concurrent selection strategy. First of all the data sequence is distributed among the different processors and are sorted in parallel using counting sort. Then it applies ternary search to find the index position of all elements globally to find the correct position of each elements in data sequence. This paper analyses the computational complexity of proposed parallel sorting algorithm and compares it with some of existing algorithms. The results of proposed algorithms shows that it is better than existing parallel sorting algorithm like parallel merge sort and binary search based sorting algorithm.
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An approximate 4-2 compressor based on spintronic devices
Статья научная
In many classes of applications, mainly in signal and image processing applications, decreasing the static power of computational circuits is a challenge. Multipliers are typically located on the critical path of such systems. A promising approach for energy-efficient design of digital systems is approximate or inexact computing. On the other hand, leakage power and limited scalability become serious obstacles that prevent the continuous miniaturization of the conventional CMOS-based logic circuits. Spin-based devices are considered as promising alternatives for CMOS technology due to their proper characteristics such as near-zero current leakage, sustainability, integrity, low standby power. In this paper a new low power approximate 4-2 compressor is presented which is implemented using spintronic devices. The proposed design is utilized in a multiplier tree for image processing applications. We have simulated and compared the proposed design with state-of-the-art designs in both quantitative and qualitative metrics. The simulation results show that the proposed design has 92% and 188% lower power consumption and PDP, respectively compared to the best state-of-the-art design.
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An effective technique to decline energy expenditure in cloud platforms
Статья научная
The cloud computing is the rapidly growing technology in the IT world. A vital aim of the cloud is to provide the services or resources where they are needed. From the user’s prospective convenient computing resources are limitless thatswhy the client does not worry that how many numbers of servers positioned at one site so it is the liability of the cloud service holder to have large number of resources. In cloud data-centers, huge bulk of power exhausted by different computing devices.Energy conservancy is a major concern in the cloud computing systems. From the last several years, the different number of techniques was implemented to minimize that problem but the expected results are not achieved. Now, in the proposed research work, a technique called Enhanced - ACO that is developed to achieve better offloading decisions among virtual machines when the reliability and proper utilization of resources will also be considered and will use ACO algorithm to balance load and energy consumption in cloud environment. The proposed technique also minimizes energy consumption and cost of computing resources that are used by different processes for execution in cloud. The earliest finish time and fault tolerance is evaluated to achieve the objectives of proposed work. The experimental outcomes show the better achievement of prospective model with comparison of existing one. Meanwhile, energy-awake scheduling approach with Ant colony optimization method is an assuring method to accomplish that objective.
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An efficient adaptive based median technique to de-noise colour and greyscale images
Статья научная
The picture noise is an irregular variation of brightness and color information in pictures. It decreases picture quality and permeability of specific elements inside the picture. The most surely understood noise that corrupts the photo with impulse noise. In this work, an effective algorithm is intended to identify and remove noise from a picture. An improved de-noising calculation in view of the median filter is exhibited for greyscale and colored images. The algorithm incorporates two cases: I) if the chose window contains all pixel values "0" to "255" at that point center preparing pixel supplanted by the mean of qualities. II) If the chosen window does not contain all components "0" and "255" then eliminate "0" and "255" and central preparing pixel is replaced by the median of remaining pixels values. The performance is checked off the purposed algorithm by comparing it with corresponding filters. The experiment checked at various noise proportion 5% to 80% for greyscale and color pictures. Results are checked as far as MSE and PSNR and even at high noise proportion; it gives better outcomes over other existing techniques.
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An efficient clustering algorithm for spatial datasets with noise
Статья научная
Clustering is the technique of finding useful patterns in a dataset by effectively grouping similar data items. It is an intense research area with many algorithms currently available, but practically most algorithms do not deal very efficiently with noise. Most real-world data are prone to containing noise due to many factors, and most algorithms, even those which claim to deal with noise, are able to detect only large deviations as noise. In this paper, we present a data-clustering method named SIDNAC, which can efficiently detect clusters of arbitrary shapes, and is almost immune to noise – a much desired feature in clustering applications. Another important feature of this algorithm is that it does not require apriori knowledge of the number of clusters – something which is seldom available.
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An environment aware learning-based self-adaptation technique with reusable components
Статья научная
Self-adaptive systems appeared in order to reduce the effort of manual software maintenance. Apart from software attributes, for example, different alternative software modules, self-adaptation decisions depend on environmental attributes, for example, service rate, bandwidth etc. Current well-known self-adaptation approaches can be further improved by incorporating environmental attributes. Moreover, reducing maintenance effort includes minimizing both operational and development effort. To reduce the effort of developing self-adaptive software, the constituent components should be reusable. This paper proposes a technique to incorporate environmental attributes to learning-based self-adaptation and to increase the reuse potential of self-adaptive system components. The environmental attributes are provided as a constraint to an optimization problem which results in an optimal software attribute selection. Design patterns for self-adaptive system components are proposed to improve its reusability. The proposed technique was validated on a news serving website called Znn.com. According to renowned reusability metrics such as Lines of Code (LOC), Message Passing Coupling (MPC) and Lack of Cohesion of Methods 4 (LCOM4), the proposed technique improved reuse potential. The website was further tested for adaptation effectiveness under two scenarios – adaptation and without adaptation. According to our experiments, Adaptation gradually improved the main goal response time of the website where it performed poorly without adaptation.
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An evolutionary model for selecting relevant textual features
Статья научная
From a philosophical point of view, the words of a text or a speech are not held just for informational purposes, but they act and react; they have the power to react on their counterparts. Each word, evokes similar or different senses that can influence and interact with the following words, it has a vibratory property. It's not the words themselves that have the impact, but the semantic reaction behind the words. In this context, we propose a new textual data classification approach while trying to imitate human altruistic behavior in order to show the semantic altruistic stakes of natural language words through statistical, semantic and distributional analysis. We present the results of a word extraction method, which combines a distributional proximity index, a selection coefficient and a co-occurrence index with respect to the neighborhood.
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Статья научная
The intention of this paper is to analyze how a behavior of a student will influence us in gauging their performance level rather than considering their traditional examination scores. This approach is considered to be one of the informal approaches which guide many school managements to identify good, average and poor category of students. The main criteria used here is behavioral science which explores activities and interactions among the student community when they are inside the school campus. School-Wide Positive Behavior Support can assist in addressing the issues related to the prevention, educational identification and effective intervention implementation through its systemic logic, data-based decision making, and capacity building within and across schools. Clustering is the process of grouping a set of data objects into multiple groups or clusters with high similarities and dissimilarities. Dissimilarities and Similarities are assessed on the attribute values describing the objects and often involve distance measures. Clustering acts as a data mining tool by having its roots in many application areas such as biology, security, business intelligence, web search etc. In this survey, we have involved 200 + students who are currently studying engineering streams in various classes that includes first semester to final semester. Their age group was in the range of 18 to 22 years. Their behavioral survey has been conducted over a span of 4 to 6 months by closely observing their activities, mannerisms and then evaluated by entering in to this system by using the evaluation interface. This evaluation interface consists of 15 features with 4 optional choices. Each choice is rated with a specific numeric value. By taking one of the choices among all the 15 features for each of the student, at the end, he/she will get some score which will be stored in a database. With the help of this score, a manual grouping was done. Later, for the same dataset, a soft computing technique has been applied by working with self organizing feature map algorithm for grouping the students.
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Статья научная
Synchronous and asynchronous e-learning are two popular e-learning modes that are commonly used in distant learning education. The study investigates how synchronous and asynchronous e-learning affect the academic performance of students. A questionnaire was used to collect data for this study from some students of the National Open University of Nigeria. The findings showed that students' attitude to synchronous and asynchronous e-learning affect their academic performance. The results demonstrated that only 60% of the respondents understand what asynchronous and synchronous e-learning means. Also, only 55% of the respondents believed that asynchronous and synchronous e-learning mode has a positive impact on their academic performance. Moreover, only 52% of the respondents are of the opinion that the curriculum in use at National Open University needs to be updated to increase the impact of the e-learning mode on the learners.
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Статья научная
Currently, the online discussion forums have become the focal point for e-learning in many Higher Learning Institutions (HLIs); this is due to the ubiquitous of Information and Communication Technology (ICT) tools, significant rate and fast growing technology adoption and use in many fields including education. However, developing countries, such as Tanzania, are experiencing technical adoption difficulties, such as limited access to computers, problems with Internet connections as well as the technological reliance gap between tutors and learners; these affect the use of technology in Teaching and Learning (T/L). This study aims to use an Online Discussion Platform (onlineDP) to bridge the technological reliance gap between the tutors and learners in HLIs in Tanzania. In this study, the literature review and qualitative research methods were conducted to develop the prototype of the platform. The UMBC semantic similarity service was used to develop the contents filter used to reduce the number of duplicate discussion questions. The application was mainly developed using Laravel Pre-processor (PHP) framework and My Structured Query Language (MySQL) database. The result is the web-based application prototype that enhances the collaborative learning environment in HLIs in Tanzania. The technologies to be used for T/L, should consider both sides of tutors and learners as well as the theoretical framework for their implementations.
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An optimized approach towards reversible adder/subtractor design on QCA
Статья научная
In the present era of miniaturization, higher power dissipation in form of heat has become a very critical issue for the digital Circuits. This excessive heat may result in the lower chip reliability and even destroy it. Due to this reason a substitute is required for the traditional CMOS technology, Reversible logic is a paradigm in this direction. This paper encompasses of the newly proposed SA reversible logic and basic combinational implementations using a single SA building block only resulting in lower circuit level complexity as well as hardware requirement. The output responses and energy dissipation of proposed SA reversible logic are verified and calculated with the help of QCADesigner and QCADesigner-E simulation tools respectively.
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Analyses of impacting factors of ICT in education management: case study
Статья научная
Research studies and attitudes towards ICT use in education management are shifting, and often significantly. This is likely to have a major impact upon ICT and education management. However, the real significance of the impact for educational management has yet to be seen within this research study. The focus of the research study is to investigate and analyses the ICT usage in Education Management. ICT in teaching has an important role and its impact on the advancement of educational processes related to effective teaching and learning, and modern research in this field is almost irreplaceable. Another important element is the use of different software platforms that facilitate learning visible and make it more concrete, more practical and applicable to everyday life. In order to analyze the data a combination of qualitative and quantitative methodology has been used. In order to analyze this, Case study analysis of high schools in city of Skopje, Macedonia is realized. Insights and recommendations are provided.
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Analysis of Experimental Research Results Focused on Improving Student Psychological Health
Статья научная
The students' psychological health in high education is still being a problematic issue. This article describes the importance of ensuring students' psychological health in higher education today and related empirical research results. The aim of this paper is exploring and analysis research results focused on students' psychological health. To determine the students' psychological health there were used special psychodiagnostic methods. The components of the psychological health were divided as 1) satisfaction level; 2) perceptions of a healthy lifestyle; 3) emotional stability; 4) psychoemotional state; and 5) attitude towards themselves. Obtained results on students' psychological health indicate specific conclusions about various psychological health indicators and the relationship between behaviour and internal health, including in emotional, cognitive and behavioural areas. The results of this research work showed that one of the important indicators of students' psychological health is a decrease in the level of emotional distress and emotional instability (neuroticism, nervousness), a positive change in students' internal state, and an increase in students' satisfaction with their educational environment. The results could be used in the high education system, especially measuring and monitoring students' psychological health.
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Статья научная
The development of the Internet in Indonesia is quite rapid, it is marked by the increasing use of social networks, especially Twitter. Not only to share status or stories, Twitter has become become a means of promotion and campaign for elections. The Twitter data can be used to find out the political polarization in Indonesia that is needed in the 2019 presidential election. The method used in this research is sentiment analysis using naïve bayes classifier and social network analysis using the calculation of network attribute values and centrality values. 8.814 Twitter data was collected using data crawling method. The data are divided into three subsets consisting of jokowi’s sentiments, prabowo’s sentiments, and pilpres’s sentiments. Final result of the sentiment analysis is classified sentiments into positives, negatives, and neutral. The average value of the classification results was 91.27% positive sentiment, 7.56% negatives sentiment, and 1.17% neutral sentiment. This classification yielded the average accuracy of 69.2% for jokowi’s sentiments and 100% for prabowo sentiments. The classification accuracy calculation uses ROCs method. Final results of the social network analysis based on the calculation of network attributes yielded 277 nodes, 7.950 edges, 57,401 average degree, 56.44 average weighted degree, network diameter is 4, 1.853 average path length, 0.201 density, and 5 of number communities. Centrality values generates the 5 most influential actors in social network interactions are jokowi’s of first rank, 2nd SBYudhoyono’s, 3rd detikcom, 4th yjuniardi, 5th mohmahfudmd.
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