• International Journal of Computer Science & Network Security
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• 제22권11호
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• pp.373-380
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• 2022

The field of land surveying is changing dramatically due to the way data is processed, analyzed and presented. Also, there is a growing demand for digital spatial information, coming primarily from the GIS (Geographical Information System) user community. Such a demand has created a strong development potential for a new land surveying software. An overview of the development and capabilities of a land surveying software platform based on the Windows system, SurveyingMap, is presented. Among its many features, SurveyingMap provides a lot of adaptability for networks adjustment, geodetic and plane coordinates transformation, contouring, sectioning, DTM (Digital Terrain Model) generation, and large scale mapping applications. The system output is compatible with well known computer aided drafting (CAD) /GIS packages to expand its scope of applications. SurveyingMap is also suitable for non-technical users due to the user-friendly graphic user interface. The system could be used in engineering, architecture, GIS, and academic teaching and research, among other fields. Two applications of SurveyingMap, extension of field control and large scale mapping, for the case study area are established. The results demonstrate that the system is adaptable and reasonably priced for use by college and university students.

• 정보보호학회논문지
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• 제32권5호
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• pp.837-844
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• 2022

정보통신 기술의 비약적인 발전과 비례하여 저작권 침해에 대한 피해도 증가하고 있다. 특히, 최근 몇 년 사이 OTT 플랫폼 시장이 크게 성장하면서 저작권을 침해하는 불법 복제물의 복제 속도와 유통량이 과거와 비교하여 빠르게 증가하고 있다. 그에 따라 국가에서는 불법 스트리밍 사이트를 탐지 및 차단 함으로써 저작권 침해를 방지하기 위해 노력하고 있지만, 불법 스트리밍 사이트의 생산 속도가 빨라 큰 성과를 기대하기 어려운 상황이다. 따라서, 본 논문에서는 차단된 불법 스트리밍 사이트가 빠르게 생산될 수 있는 원인에 대해 분석하였으며, 불법 스트리밍 사이트 58곳을 추적 및 분석하여 분석 결과를 바탕으로 불법 스트리밍 사이트를 효과적으로 차단할 수 있는 방안에 대해 제안한다.

• International Journal of Computer Science & Network Security
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• 제23권8호
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• pp.190-198
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• 2023

To enhance customer satisfaction for higher profits, an e-commerce sector can establish a continuous relationship and acquire new customers. Utilize machine-learning models to analyse their customer's behavioural evidence to produce their competitive advantage to the e-commerce platform by helping to improve overall satisfaction. These models will forecast customers who will churn and churn causes. Forecasts are used to build unique business strategies and services offers. This work is intended to develop a machine-learning model that can accurately forecast retainable customers of the entire e-commerce customer data. Developing predictive models classifying different imbalanced data effectively is a major challenge in collected data and machine learning algorithms. Build a machine learning model for solving class imbalance and forecast customers. The satisfaction accuracy is used for this research as evaluation metrics. This paper aims to enable to evaluate the use of different machine learning models utilized to forecast satisfaction. For this research paper are selected three analytical methods come from various classifications of learning. Classifier Selection, the efficiency of various classifiers like Random Forest, Logistic Regression, SVM, and Gradient Boosting Algorithm. Models have been used for a dataset of 8000 records of e-commerce websites and apps. Results indicate the best accuracy in determining satisfaction class with both gradient-boosting algorithm classifications. The results showed maximum accuracy compared to other algorithms, including Gradient Boosting Algorithm, Support Vector Machine Algorithm, Random Forest Algorithm, and logistic regression Algorithm. The best model developed for this paper to forecast satisfaction customers and accuracy achieve 88 %.

• Nuclear Engineering and Technology
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• 제54권11호
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• pp.3975-3984
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• 2022

Distributed control system architecture is adopted for I&C systems of Prototype Fast Breeder Reactor, where the geographically distributed control systems are connected to centralized servers & display stations via switched Ethernet networks. TCP/IP communication plays a significant role in the successful operations of this architecture. The communication tasks at control nodes are taken care by TCP/IP offload modules; local area switched network is realized using layer-2/3 switches, which are finally connected to network interfaces of centralized servers & display stations. Safety, security, reliability, and fault tolerance of control systems used for safety-related applications of nuclear power plants is ensured by indigenous design and qualification as per guidelines laid down by regulatory authorities. In the case of commercially available components, appropriate suitability analysis is required for getting the operation clearances from regulatory authorities. This paper details the proposed approach for the suitability analysis of TCP/IP communication nodes, including control systems at the field, network switches, and servers/display stations. Development of test platform using commercially available tools and diagnostics software engineered for control nodes/display stations are described. Each TCP link behavior with impaired packets and multiple traffic loads is described, followed by benchmarking of the network switch's routing characteristics and security features.

• International Journal of Computer Science & Network Security
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• 제23권5호
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• pp.1-6
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• 2023

Text mining (TM) is most widely used to process the various unstructured text documents and process the data present in the various domains. The other name for text mining is text classification. This domain is most popular in many domains such as movie reviews, product reviews on various E-commerce websites, sentiment analysis, topic modeling and cyber bullying on social media messages. Cyber-bullying is the type of abusing someone with the insulting language. Personal abusing, sexual harassment, other types of abusing come under cyber-bullying. Several existing systems are developed to detect the bullying words based on their situation in the social networking sites (SNS). SNS becomes platform for bully someone. In this paper, An Enhanced text mining approach is developed by using Ensemble Algorithm (ETMA) to solve several problems in traditional algorithms and improve the accuracy, processing time and quality of the result. ETMA is the algorithm used to analyze the bullying text within the social networking sites (SNS) such as facebook, twitter etc. The ETMA is applied on synthetic dataset collected from various data a source which consists of 5k messages belongs to bullying and non-bullying. The performance is analyzed by showing Precision, Recall, F1-Score and Accuracy.

• International Journal of Computer Science & Network Security
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• 제23권6호
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• pp.35-48
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• 2023

The study aimed to provide a proposed conception of technical solutions to address the educational loss in mathematics in the fifth grade of primary school, and the study adopted the descriptive approach. male and female teachers, and to achieve the study objective, the researcher built a tool for the study, a "questionnaire", in which he used the comprehensive inventory method, and the results of the study showed: identifying the learning outcomes that represent an educational loss, and identifying the learning outcomes that are considered essential in teaching and learning mathematics for the fifth grade of primary school. In the event that it is not achieved by students, it is considered an educational loss that may affect the future of students' education and learning. Because it is a basis for later experiences in mathematics in other classes, and the study also found the effectiveness of the proposed visualization of technical solutions provided to address the educational loss in mathematics for the fifth grade: (short electronic tests, YouTube channel, homework, educational platform, electronic worksheets, and communication channels).

• International Journal of Computer Science & Network Security
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• 제23권11호
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• pp.53-58
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• 2023

The trend of satisfying consumer needs (payment for mobile communication, music services, cab ordering, banking products, and food delivery) on a unified online platform has shaped a digital ecosystem, an instrument creating a unified space of economic interaction. Representatives of e-commerce are major stakeholders in the development of such tools. In particular, subscription services (multiservice subscriptions) allow users to create their own ecosystems based on their personal preferences. The rate of subscription service use is growing around the world, yet understanding of the peculiarities of development of this e-commerce sphere is limited due to insufficient research.The study aims to determine the motives and barriers to the use of subscription services (multiservice subscriptions) by consumers and their relationship with consumer characteristics.Proceeding from an online survey of 200 users, the study determines the relationship between the gender and income of consumers and their use of subscription services, motives and motivators for using subscription services, and barriers to the choice of a particular subscription service. The obtained results may serve as a basis for managerial decisions in e-commerce and for improving the effectiveness of marketing solutions.

• International Journal of Computer Science & Network Security
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• 제23권11호
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• pp.77-82
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• 2023

The article considers online discussion as an interactive learning method in the conditions of distance learning. The essence of discussion and the stages of its organization are described. The main objective of discussion in distance learning is defined as the stimulation of interest in learning and the involvement of various viewpoints in an active discussion of the stated problems. The key role in ensuring the efficiency of a discussion is identified. The article develops a model for organizing asynchronous online discussions on the Moodle platform, highlighting the sequence of stages and their content. An experimental study of the use of the discussion method in the training of students in distance learning conditions is carried out. Based on the results of the methodological experiment, conclusions are drawn about student interest in online discussions. The authors conclude that the interest of students of different specialties in asynchronous online discussions varies, and the greatest interest is demonstrated by linguistics students. Nevertheless, the differences in student interest in online discussions by groups (specialties) are more likely attributable to subjective factors, which do not affect the overall picture in a major way.

• International Journal of Computer Science & Network Security
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• 제23권11호
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• pp.93-98
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• 2023

Instagram is one of the fastest-growing online photo social web services where users share their life images and videos with other users. Image tagging is an essential step for developing Automatic Image Annotation (AIA) methods that are based on the learning by example paradigm. Hashtags can be used on just about any social media platform, but they're most popular on Twitter and Instagram. Using hashtags is essentially a way to group together conversations or content around a certain topic, making it easy for people to find content that interests them. Practically on average, 20% of the Instagram hashtags are related to the actual visual content of the image they accompany, i.e., they are descriptive hashtags, while there are many irrelevant hashtags, i.e., stophashtags, that are used across totally different images just for gathering clicks and for search ability enhancement. Hence in this work, Sorting instagram hashtags all the way through mass tagging using HITS (Hyperlink-Induced Topic Search) algorithm is presented. The hashtags can sorted to several groups according to Jensen-Shannon divergence between any two hashtags. This approach provides an effective and consistent way for finding pairs of Instagram images and hashtags, which lead to representative and noise-free training sets for content-based image retrieval. The HITS algorithm is first used to rank the annotators in terms of their effectiveness in the crowd tagging task and then to identify the right hashtags per image.

• 한국산업융합학회 논문집
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• 제27권2_2호
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• pp.343-356
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• 2024

Super app is an application that provides a variety of services in a unified interface within a single platform. With the acceleration of digital transformation, super apps are becoming more prevalent. This study aims to suggest service enhancement measures by analyzing the user review data before and after the transition to a super app. To this end, user review data from a payment-based super app(Shinhan Play) were collected and studied via topic modeling. Moreover, a matrix for assessing the importance and usefulness of topics is introduced, which relies on the eigenvector centrality of the inter-topic network obtained through topic modeling and the number of review recommendations. This allowed us to identify and categorize topics with high utility and impact. Prior to the transition, the factors contributing to user satisfaction included 'payment service,' 'additional service,' and 'improvement.' Following the transition, user satisfaction was associated with 'payment service' and 'integrated UX.' Conversely, dissatisfaction factors before the transition encompassed issues related to 'signup/installation,' 'payment error/response,' 'security authentication,' and 'security error.' Following the transition, user dissatisfaction arose from concerns regarding 'update/error response' and 'UX/UI.' The research results are expected to be used as a basis for establishing strategies to strengthen service competitiveness by making super app services more user-oriented.