• Journal of IKEEE
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• v.7 no.2 s.13
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• pp.281-287
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• 2003

This paper proposed an improvement scheme for effective usage of radio-frequency management system(RFMS), which has been operated to facilitate national spectrum management and monitoring in Korea. Based on the wave propagation models, interference analysis algorithms, and sharing criteria recommended by ITU-R, we derived criteria for the automated selection of the channel interference analysis algorithms and sharing conditions adequate to the environment to be analysed. Then using the obtained criteria, computer and program has been made and shown to select the most appropriate propagation models, interference analysis algorithms, and sharing criteria from the ones provided in RFMS, with the illustrative example.

• Journal of Electrical Engineering and Technology
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• v.13 no.3
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• pp.1173-1184
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• 2018

The lifetime of a lithium-ion battery is one of the most important issues of the energy storage system (ESS) because of its stable and reliable operation. In this paper, the lifetime management method of the lithium-ion battery for energy storage system is proposed. The lifetime of the lithium-ion battery varies, depending on the power usage, operation condition, and, especially the selected depth of discharge (DOD). The proposed method estimates the total lifetime of the lithium-ion battery by calculating the total transferable energy corresponding to the selected DOD and achievable cycle (ACC) data. It is also demonstrated that the battery model can obtain state of charge (SOC) corresponding to the ESS operation simultaneously. The simulation results are presented performing the proposed lifetime management method. Also, the total revenue and entire lifetime prediction of a lithium-ion battery of ESS are presented considering the DOD, operation and various condition for the nations of USA and Korea using the proposed method.

• Proceedings of the Korea Information Processing Society Conference
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• 2018.05a
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• pp.256-259
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• 2018

다수의 사용자가 자원을 공유하는 클라우드 센터에서는 자원 사용량 예측이 힘들기 때문에 지속적으로 가상머신의 자원 부족과 특정 물리 서버에 가상머신들이 집중되는 것을 방지하고자 클라우드 센터를 구성하는 다수의 물리 서버 사이에서 가상머신을 이주시키는 마이그레이션 작업을 수행한다. 가상머신 마이그레이션은 가상머신에게 할당된 자원의 규모에 따라 물리 서버에 가상머신을 균등하게 배치시킬 수 있지만 가상머신의 특정 자원에 따른 자원 집중 현상은 방지할 수 없다. 본 논문에서는 가상머신 마이그레이션 작업 시 자원 집중 현상을 방지하기 위한 기반 정보를 생성하는 가상머신 유형분류 기법을 제안한다. 본 논문에서 제안하는 가상머신 유형분류 기법은 물리 서버에서 실행 중인 가상머신의 자원 사용 정보를 기반으로 CPU, 메모리 유형으로 분류하여 가상머신 마이그레이션을 수행할 때 사용할 수 있는 기반 정보를 제공한다. 또한 본 논문에서 제안한 기법은 실험을 통해 무시할 수 있는 수준의 오버헤드를 발생시키는 것을 확인하였다.

• International Journal of Contents
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• v.14 no.4
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• pp.70-75
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• 2018

The purpose of this corpus-based study was to find 4-word lexical bundles in computer science research articles. As the demand for research articles (RAs) for international publication increases, the need for acquiring field-specific writing conventions for this academic genre has become a burning issue. Particularly, one area of burgeoning interest in the examination of rhetorical structures and linguistic features of RAs is the use of lexical bundles, the indispensable building blocks that make up an academic discourse. To illustrate, different academic discourses rely on distinctive repertoires of lexical bundles. Because lexical bundles are often acquired as a whole, the recurring multi-word sequences can be retrieved automatically to make written discourse more fluent and natural. Therefore, the proper use of rhetorical devices specific to a particular discipline can be a vital indicator of success within the discourse communities. Hence, to identify linguistic features that make up specific registers, this corpus-based study examines the types and usage frequency of lexical bundles in the discipline of CS, one of the most in-demand fields world over. Given that lexical bundles are empirically-derived formulaic multi-word units, identifying core lexical bundles used in RAs, they may provide insights into the specificity of particular CS text types. This will in turn provide empirical evidence of register specificity and technicality within the academic discourse of computer science. As in the results, pedagogical implications and suggestions for future research are discussed.

• Journal of Information Processing Systems
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• v.15 no.4
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• pp.765-784
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• 2019

The smart city is one of the most promising, prominent, and challenging applications of the Internet of Things (IoT). Smart cities rely on everything connected to each other. This in turn depends heavily on technology. Technology literacy is essential to transform a city into a smart, connected, sustainable, and resilient city where information is not only available but can also be found. The smart city vision combines emerging technologies such as edge computing, blockchain, artificial intelligence, etc. to create a sustainable ecosystem by dramatically reducing latency, bandwidth usage, and power consumption of smart devices running various applications. In this research, we present a comprehensive survey of emerging technologies for a sustainable smart city network. We discuss the requirements and challenges for a sustainable network and the role of heterogeneous integrated technologies in providing smart city solutions. We also discuss different network architectures from a security perspective to create an ecosystem. Finally, we discuss the open issues and challenges of the smart city network and provide suitable recommendations to resolve them.

• International Journal of Computer Science & Network Security
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• v.21 no.7
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• pp.359-364
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• 2021

In recent years Hadoop usage has been increasing day by day. The need of development of the technology and its specified outcomes are eagerly waiting across globe to adopt speedy access of data. Need of computers and its dependency is increasing day by day. Big data is exponentially growing as the entire world is working in online mode. Large amount of data has been produced which is very difficult to handle and process within a short time. In present situation industries are widely using the Hadoop framework to store, process and produce at the specified time with huge amount of data that has been put on the server. Processing of this huge amount of data having small files & its storage optimization is a big problem. HDFS, Sequence files, HAR, NHAR various techniques have been already proposed. In this paper we have discussed about various existing techniques which are developed for accessing and storing small files efficiently. Out of the various techniques we have specifically tried to implement the HDFS- HAR, NHAR techniques.

• International Journal of Computer Science & Network Security
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• v.22 no.9
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• pp.316-326
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• 2022

The prompt development in the field of video is the outbreak of online services which replaces the television media within a shorter period in gaining popularity. The online videos are encouraged more in use due to the captions displayed along with the scenes for better understandability. Not only entertainment media but other marketing companies and organizations are utilizing videos along with captions for their product promotions. The need for captions is enabled for its usage in many ways for hearing impaired and non-native people. Research is continued in an automatic display of the appropriate messages for the videos uploaded in shows, movies, educational videos, online classes, websites, etc. This paper focuses on two concerns namely the first part dealing with the machine learning method for preprocessing the videos into frames and resizing, the resized frames are classified into multiple actions after feature extraction. For the feature extraction statistical method, GLCM and Hu moments are used. The second part deals with the deep learning method where the CNN architecture is used to acquire the results. Finally both the results are compared to find the best accuracy where CNN proves to give top accuracy of 96.10% in classification.

• International Journal of Computer Science & Network Security
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• v.23 no.4
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• pp.146-150
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• 2023

In areas where water is scarce, water management is critical. This has an impact on agriculture, as a significant amount of water is used for that purpose. Electronic measurement equipment are essential for regulating and storing soil data. As a result, research has been conducted to manage water usage in the irrigation process. Many equipment for managing soil fertility systems are extremely expensive, making this type of system unaffordable for small farmers. These soil fertility control systems are simple to implement because to recent improvements in IoT technology. The goal of this project is to develop a new methodology for smart irrigation systems. The parameters required to maintain water amount and quality, soil properties, and weather conditions are determined by this IoT-based Smart irrigation System. The system also assists in sending warning signals to the consumer when an error occurs in determining the percentage of moisture in the soil specified for the crop, as well as an alert message when the fertility of the soil changes, since many workers, particularly in big projects, find it extremely difficult to check the soil on a daily basis and operate agricultural devices such as sprinkler and soil fertilizing devices.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.3
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• pp.633-652
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• 2024

Software testing is an important phase as it ensures the software quality. The software testing process comprises of three steps: generation, execution, and evaluation of test cases. Literature claims the usage of single and multiple 'Unified Modeling Language' (UML) diagrams to generate test cases. Using multiple UML diagrams increases test case coverage. However, the existing approaches show limitations in test case generation from UML diagrams. Therefore, in this research study, we propose an approach to generate the test cases using UML State Chart Diagram (SCD), Activity Diagram (AD), and Sequence Diagram (SD). The proposed approach transforms UML diagrams into intermediate forms: SCD Graph, AD Graph, and SD Graph respectively. Furthermore, by integrating these three graphs, a System Testing Graph (STG) is formed. Finally, test cases are identified from STG by using a traversal algorithm such as Depth First Search (DFS) that is an optimization method. The results show that the proposed approach is better compared to existing approaches in terms of coverage and performance. Moreover, the generated test cases have the ability to detect faults at the unit level, integration, and system level testing.

• International Journal of Computer Science & Network Security
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• v.24 no.7
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• pp.59-62
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• 2024

Non-fungible tokens (NFTs) are interchangeable rights to digital assets such as art, in-game items, collectibles or music, etc. NFTs have the potential to be infinitely useful in many industries by increasing security and processing costs for transactions and providing a new platform for the gigeconomy to work through. Its markets have grown fast and significantly since early 2021. We investigate the uses of NFTs and research the facts and figures on the usage of NFTs supporting websites. Using daily data between 2019 to 2021. NFTs took the world by storm in 2021, bringing forth a digital art revolution while becoming one of the fastest-growing asset classes of the year. While the NFTs market has been growing at a rapid pace, many are still wary of entering it because of the theoretical insanity around its worth. NFTs have been out there for quite some time and this trend doesn't plan to go any further. NFTs services have many practical use cases and their potential will only grow over time. While celebrities dive into this marketplace to maintain their onlinepresence andincrease their Net worth.