• International Journal of Computer Science & Network Security
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• v.21 no.12spc
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• pp.463-468
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• 2021

Single image super-resolution (SISR) is an image processing technique, and its main target is to reconstruct the high-quality or high-resolution (HR) image from the low-quality or low-resolution (LR) image. Currently, deep learning-based convolutional neural network (CNN) image super-resolution approaches achieved remarkable improvement over the previous approaches. Furthermore, earlier approaches used hand designed filter to upscale the LR image into HR image. The design architecture of such approaches is easy, but it introduces the extra unwanted pixels in the reconstructed image. To resolve these issues, we propose novel deep learning-based approach known as Lightweight deep CNN-based approach for Single Image Super-Resolution (LDCSIR). In this paper, we propose a new architecture which is inspired by ResNet with Inception blocks, which significantly drop the computational cost of the model and increase the processing time for reconstructing the HR image. Compared with the other state of the art methods, LDCSIR achieves better performance in terms of quantitively (PSNR/SSIM) and qualitatively.

• International Journal of Computer Science & Network Security
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• v.21 no.12spc
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• pp.597-603
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• 2021

The current Sudanese preschool system depends on limited methods of education, children's education needs to be equipped to keep pace with technological development, also, the large gap that exists between the families and the Kindergartens, where many parents have no idea on how their child progresses in the KG context. The aim of this research is to integrate ICT in the preschool education to enhance and improve the preschool education, by building an Integrated Educational Application (Computerized Application for Preschool Education CAPE) which will help to improve the learning outcomes. The researchers used the Experimental Research Methodology, the characteristic of CAPE application is; suitable for children's age, the application style is more attractive to the children and contains a different way to help children get learning. Alawaeel and the Smart Child Kindergartens in Republic of Sudan were selected as a sample of the study, with sample size specifically, 50 children's. Also, the Central Bank of Sudan Kindergarten was selected as one of the institutional Kindergartens for easy communication with parents of children with a sample size 21 children. The study found that; using CAPE application in KG enables children to increase general learning effects and developing child's cognitive skills. Also, the children who were allowed to use CAPE by their parents are performed better in the overall evaluation of KG lessons. Also, using the CAPE in the Pre-School education helps the parents following their children's progress better and more reliable. The researcher recommends that to apply the computerized application and includes the second level. Also, converting the computerized program into an application to be used by children by their self, without the intervention of parents.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.2
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• pp.303-308
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• 2019

Spring framework is widely used as a base technology for e-government frameworks and to the extent it is a standard for web service development tools of Korean public institutions. However, recently, a remote code execution vulnerability(CVE-2018-1270) was found in an application using a spring framework. This paper proposes a method of analyzing the vulnerability experiment using a hacking scenario, Proof Of Concept(POC), in which the spring framework is a hazard to the server. We propose the patch to version 4.3.16 and version 5.0.5 or later as an ultimate response. It is also expected that the proposed experiment analysis on vulnerability of hacking scenario will be used as a data for improving performance of security programs and establishing a new authentication system.

• Journal of Korean Society of Disaster and Security
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• v.13 no.4
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• pp.13-24
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• 2020

Abnormal weather conditions have lately been occurring frequently due to the rapid economic development and global warming. Natural disasters classified as storm and flood damages such as heavy rain, typhoon, strong wind, high seas and heavy snow arouse large-scale human and material damages. To minimize damages, it is important to estimate the scale of damage before disasters occur. This study is intended to develop a strong wind damage estimation function to prepare for strong wind damage among various storm and flood disasters. The developed function reflects weather factors and regional characteristics based on the strong wind damage history found in the Natural Disaster Yearbook. When the function is applied to a system that collects real-time weather information, it can estimate the scale of damage in a short time. In addition, this function can be used as the grounds for disaster control policies of the national and local governments to minimize damages from strong wind.

• International Journal of Computer Science & Network Security
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• v.21 no.6
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• pp.275-285
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• 2021

Ministries of Education are integrating different Learning Management Systems (LMS) to enhance teaching and learning during the lockdown to avoid academic loss. The key factor for delivering a high-quality education through LMS platforms is teachers' acceptance and adoption of the platform. Madrasati platform (which means My school) was introduced by Saudi Arabian Ministry of education as the formal teaching and learning for distance education for public education levels. This study aims to examine the effectiveness, usability and adoption of "Madrasati" platform from teachers' perspectives in Saudi Arabia. "SUS, CSUQ" tests were used to test the usability of the new platform. Using quantitative research design, data were collected using questionnaire. 200 teachers were selected randomly answered the survey. Data was analysed descriptively and inferentially using SPSS (25). The results obtained indicate that the teachers are highly satisfied using Madrasati platform and technically it is well designed. Also, Madrasati has positive effect on teaching quality. Moreover, Madrasati has high usability in teaching. One of the key findings were that the quality of the information content in Madrasati has a strong effect on teachers' perception of the Madrasati usefulness that led to a positive attitude towards Madrasati. These findings would be useful to the ministry of education and institutions trying to integrate technology in their teaching and learning processes. Thus, this paper contributes towards more effective utilisation of the extensive functionalities that Madrasati have to offer, which will contribute toward the development of pedagogy in Saudi Arabia.

• Korean Journal of Remote Sensing
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• v.38 no.1
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• pp.73-82
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• 2022

Marine fisheries resources face major anthropogenic threat from unregulated fishing activities; thus require precise detection for protection through marine surveillance. Korea developed an efficient land-based small fishing vessel monitoring system using real-time V-Pass data. However, those data directly do not provide information on fishing activities, thus further efforts are necessary to differentiate their activity status. In Korea, especially in Busan, longlining is practiced by many small fishing vessels to catch several types of fishes that need to be identified for proper monitoring. Therefore, in this study we have improved the existing fishing status classification method by applying Hidden Markov Model (HMM) on V-Pass data in order to further classify their fishing status into three groups, viz. non-fishing, longlining and other types of fishing. Data from 206 fishing vessels at Busan on 05 February, 2021 were used for this purpose. Two tiered HMM was applied that first differentiates non-fishing status from the fishing status, and finally classifies that fishing status into longlining and other types of fishing. Data from 193 and 13 ships were used as training and test datasets, respectively. Using this model 90.45% accuracy in classifying into fishing and non-fishing status and 88.23% overall accuracy in classifying all into three types of fishing statuses were achieved. Thus, this method is recommended for monitoring the activities of small fishing vessels equipped with V-Pass, especially for detecting longlining.

• Journal of the Korea Convergence Society
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• v.13 no.4
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• pp.25-37
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• 2022

The government and private companies are endeavoring to help the digital healthcare industry grow. This includes easing regulations on the big data industry such as the amendment of the Data 3 Act. Despite these efforts, however, there have been constant demands for the amendment of laws related to the medical field and for securing medical data transmissions. In this paper, the Data 3 Act of Korea and the legal system related to healthcare are examined. Then the legal, institutional, and technical aspects of the strategies are compared to understand the issues and implications. Based on this, a legal and institutional strategy suitable for the digital healthcare industry in Korea is suggested. Additionally, a direction to improve social perception along with technical measures such as safe de-identification processing and data transmission are also proposed. This study hopes to contribute to the spread of various convergent industries along with the digital healthcare industry.

• International Journal of Computer Science & Network Security
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• v.21 no.11
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• pp.111-118
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• 2021

The authors of the study highlight the conceptual foundations of the investment mechanism of innovation of enterprises in the context of strategic development. Such indicators of investment attraction for the enterprise as investment attractiveness, investment activity of the enterprise, critical mass of investments, minimum sufficiency of investments and others are singled out. It is proved that the balance of investment resources is facilitated by the action of the investment mechanism of innovation activity at the enterprise in the context of achievements of strategic development tasks. Investment processes and their intensification have an impact on the expansion of production capacity of economic entities in strategic development and on improving the efficiency of existing capacities. The investment mechanism of innovative activity at the enterprise in the context of achievement of tasks of strategic development contains system of complex actions which provides: definition of the clear purpose and tasks for the mechanism and achievement of the purposes of the enterprise; assessment of the investment potential of the enterprise; definition of tasks of innovative development of enterprises and investment resources necessary for this purpose, etc. The tasks of the investment mechanism of innovative activity at the enterprise in the context of achievements of tasks of strategic development and its economic, organizational and information components are singled out, as well as levers of influence and regulators of the investment mechanism of innovation in the enterprise.

• International Journal of Computer Science & Network Security
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• v.22 no.9
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• pp.51-58
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• 2022

The article emphasizes the features of the modern education system in Poland, reveals the peculiarities of improving the professional competence of a specialist in Poland through the implementation of multimedia technologies. Various forms of innovations implemented in improving the professional competence of a specialist are listed: improvement (rationalization), modernization, innovation. The forms of professional improvement through the introduction of computer technologies in general and multimedia technologies, in particular, primarily include various professional courses, qualification, preparatory, methodological conferences, seminars, postgraduate studies, foreign and state internships. At the same time, the main direction is self-education. The subject of professional improvement in the application of computer technologies by specialists is the updating of existing knowledge, exchange of professional experience, planning, as well as discussion of innovative works in which specialists participate. Professional growth of specialists can occur both during work and in higher education institutions during their studies. Modernization of computer technologies, especially multimedia ones, is a necessary condition for the functioning of specialists in modern society, since specialists are at the center of the educational process, during the improvement of professional competence. The main functions of the educational process necessary for improving the professional competence of specialists through the implementation of multimedia technologies are revealed. These functions not only contribute to the professional improvement of specialists, but also affect their solutions and optimize the maintenance of contacts between specialists. The importance of creating conditions that are consistent with the modern needs of innovative education is emphasized.

• International Journal of Computer Science & Network Security
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• v.23 no.8
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• pp.95-100
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• 2023

Due to Traffic accidents people faces health and economical casualties around the world. As the population increases vehicles on road increase which leads to congestion in cities. Congestion can lead to increasing accident risks due to the expansion in transportation systems. Modern cities are adopting various technologies to minimize traffic accidents by predicting mathematically. Traffic accidents cause economical casualties and potential death. Therefore, to ensure people's safety, the concept of the smart city makes sense. In a smart city, traffic accident factors like road condition, light condition, weather condition etcetera are important to consider to predict traffic accident severity. Several machine learning models can significantly be employed to determine and predict traffic accident severity. This research paper illustrated the performance of a hybridized neural network and compared it with other machine learning models in order to measure the accuracy of predicting traffic accident severity. Dataset of city Leeds, UK is being used to train and test the model. Then the results are being compared with each other. Particle Swarm optimization with artificial neural network (PSO-ANN) gave promising results compared to other machine learning models like Random Forest, Naïve Bayes, Nearest Centroid, K Nearest Neighbor Classification. PSO- ANN model can be adopted in the transportation system to counter traffic accident issues. The nearest centroid model gave the lowest accuracy score whereas PSO-ANN gave the highest accuracy score. All the test results and findings obtained in our study can provide valuable information on reducing traffic accidents.