• Title/Summary/Keyword: Software Convergence

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A weighted method for evaluating software quality (가중치를 적용한 소프트웨어 품질 평가 방법)

  • Jung, Hye Jung
    • Journal of Digital Convergence
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    • v.19 no.8
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    • pp.249-255
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    • 2021
  • This study proposed a method for determining weights for the eight quality characteristics, such as functionality, reliability, usability, maintainability, portability, efficiency, security, and interoperability, which are suggested by international standards, focusing on software test reports. Currently, the test results for software quality evaluation apply the same weight to 8 quality characteristics to obtain the arithmetic average. Weights for 8 quality characteristics were applied using the results from text analysis, and weights were applied using the results of text analysis of test reports for two products. It was confirmed that the average of test reports according to the weighted quality characteristics was more efficient.

Modified Deep Reinforcement Learning Agent for Dynamic Resource Placement in IoT Network Slicing

  • Ros, Seyha;Tam, Prohim;Kim, Seokhoon
    • Journal of Internet Computing and Services
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    • v.23 no.5
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    • pp.17-23
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    • 2022
  • Network slicing is a promising paradigm and significant evolution for adjusting the heterogeneous services based on different requirements by placing dynamic virtual network functions (VNF) forwarding graph (VNFFG) and orchestrating service function chaining (SFC) based on criticalities of Quality of Service (QoS) classes. In system architecture, software-defined networks (SDN), network functions virtualization (NFV), and edge computing are used to provide resourceful data view, configurable virtual resources, and control interfaces for developing the modified deep reinforcement learning agent (MDRL-A). In this paper, task requests, tolerable delays, and required resources are differentiated for input state observations to identify the non-critical/critical classes, since each user equipment can execute different QoS application services. We design intelligent slicing for handing the cross-domain resource with MDRL-A in solving network problems and eliminating resource usage. The agent interacts with controllers and orchestrators to manage the flow rule installation and physical resource allocation in NFV infrastructure (NFVI) with the proposed formulation of completion time and criticality criteria. Simulation is conducted in SDN/NFV environment and capturing the QoS performances between conventional and MDRL-A approaches.

Intelligent Massive Traffic Handling Scheme in 5G Bottleneck Backhaul Networks

  • Tam, Prohim;Math, Sa;Kim, Seokhoon
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.15 no.3
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    • pp.874-890
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    • 2021
  • With the widespread deployment of the fifth-generation (5G) communication networks, various real-time applications are rapidly increasing and generating massive traffic on backhaul network environments. In this scenario, network congestion will occur when the communication and computation resources exceed the maximum available capacity, which severely degrades the network performance. To alleviate this problem, this paper proposed an intelligent resource allocation (IRA) to integrate with the extant resource adjustment (ERA) approach mainly based on the convergence of support vector machine (SVM) algorithm, software-defined networking (SDN), and mobile edge computing (MEC) paradigms. The proposed scheme acquires predictable schedules to adapt the downlink (DL) transmission towards off-peak hour intervals as a predominant priority. Accordingly, the peak hour bandwidth resources for serving real-time uplink (UL) transmission enlarge its capacity for a variety of mission-critical applications. Furthermore, to advance and boost gateway computation resources, MEC servers are implemented and integrated with the proposed scheme in this study. In the conclusive simulation results, the performance evaluation analyzes and compares the proposed scheme with the conventional approach over a variety of QoS metrics including network delay, jitter, packet drop ratio, packet delivery ratio, and throughput.

Design and Implementation of Disinfection Service Platform based on MVC Pattern Using Web/App

  • Jang, Ye-jin;Jo, Yu-min;Shin, Ji-in;Jang, Yun-jeong;Jeong, Da-woon;Paik, Jong-ho
    • Journal of Internet Computing and Services
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    • v.22 no.6
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    • pp.41-49
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    • 2021
  • Due to the COVID-19 pandemic, issues related to quarantine are emerging. There are various infection prevention methods, but among them, it is certain to frequently disinfect the surface or the entire space of an object that has come into contact with the virus. However, the reality is that the number of times such disinfection is legally designated and the required number of personnel are very different depending on the building and facility. For this reason, there are no companies and systems that can professionally receive orders for disinfection work. In order to solve the aforementioned problems, this paper presents a method to design a disinfection service platform based on the MVC pattern, and implements the required functions based on this. Through this, it is possible to build a more systematic system, and it is hoped that it will be of great help to quarantine with an orderly process for disinfection work.

Attention based multimodal model for Korean speech recognition post-editing (한국어 음성인식 후처리를 위한 주의집중 기반의 멀티모달 모델)

  • Jeong, Yeong-Seok;Oh, Byoung-Doo;Heo, Tak-Sung;Choi, Jeong-Myeong;Kim, Yu-Seop
    • Annual Conference on Human and Language Technology
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    • 2020.10a
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    • pp.145-150
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    • 2020
  • 최근 음성인식 분야에서 신경망 기반의 종단간 모델이 제안되고 있다. 해당 모델들은 음성을 직접 입력받아 전사된 문장을 생성한다. 음성을 직접 입력받는 모델의 특성상 데이터의 품질이 모델의 성능에 많은 영향을 준다. 본 논문에서는 이러한 종단간 모델의 문제점을 해결하고자 음성인식 결과를 후처리하기 위한 멀티모달 기반 모델을 제안한다. 제안 모델은 음성과 전사된 문장을 입력 받는다. 입력된 각각의 데이터는 Encoder를 통해 자질을 추출하고 주의집중 메커니즘을 통해 Decoder로 추출된 정보를 전달한다. Decoder에서는 전달받은 주의집중 메커니즘의 결과를 바탕으로 후처리된 토큰을 생성한다. 본 논문에서는 후처리 모델의 성능을 평가하기 위해 word error rate를 사용했으며, 실험결과 Google cloud speech to text모델에 비해 word error rate가 8% 감소한 것을 확인했다.

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Korean sentence spacing correction model using syllable and morpheme information (음절과 형태소 정보를 이용한 한국어 문장 띄어쓰기 교정 모델)

  • Choi, Jeong-Myeong;Oh, Byoung-Doo;Heo, Tak-Sung;Jeong, Yeong-Seok;Kim, Yu-Seop
    • Annual Conference on Human and Language Technology
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    • 2020.10a
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    • pp.141-144
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    • 2020
  • 한국어에서 문장의 가독성이나 맥락 파악을 위해 띄어쓰기는 매우 중요하다. 또한 자연 언어 처리를 할 때 띄어쓰기 오류가 있는 문장을 사용하면 문장의 구조가 달라지기 때문에 성능에 영향을 미칠 수 있다. 기존 연구에서는 N-gram 기반 통계적인 방법과 형태소 분석기를 이용하여 띄어쓰기 교정을 해왔다. 최근 들어 심층 신경망을 활용하는 많은 띄어쓰기 교정 연구가 진행되고 있다. 기존 심층 신경망을 이용한 연구에서는 문장을 음절 단위 또는 형태소 단위로 처리하여 교정 모델을 만들었다. 본 연구에서는 음절과 형태소 단위 모두 모델의 입력으로 사용하여 두 정보를 결합하여 띄어쓰기 교정 문제를 해결하고자 한다. 모델은 문장의 음절과 형태소 시퀀스에서 지역적 정보를 학습할 수 있는 Convolutional Neural Network와 순서정보를 정방향, 후방향으로 학습할 수 있는 Bidirectional Long Short-Term Memory 구조를 사용한다. 모델의 성능은 음절의 정확도와 어절의 정밀도, 어절의 재현율, 어절의 F1 score를 사용해 평가하였다. 제안한 모델의 성능 평가 결과 어절의 F1 score가 96.06%로 우수한 성능을 냈다.

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The Software Quality Testing on the basis of the International Standard ISO/IEC 25023 (국제표준 ISO/IEC 25023 을 기반으로 한 소프트웨어 품질평가)

  • Jung, Hye-Jung
    • Journal of the Korea Convergence Society
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    • v.7 no.6
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    • pp.35-41
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    • 2016
  • As software is very important, modern men are interesting software quality testing. In this paper, we analyze the Internation standard and Test data, so, we propose the testing method by analysing testing data. We compare ISO/IEC 9126-2 testing model with ISO/IEC 25023 testing model. On the basis of ISO/IEC 25023, we classify the test data and we analyze the difference of International Standard to functionality, reliability, usability, efficiency, maintainability, portability, compatability, and security. By reality 331 testing data, we classify test data, and analyze difference according to sex. We find regression model by functionality, usability and testing date and we prove difference of testing date and the number of error by tester. Also, we prove difference of the number of error in software type.

Introducing Network Situation Awareness into Software Defined Wireless Networks

  • Zhao, Xing;Lei, Tao;Lu, Zhaoming;Wen, Xiangming;Jiang, Shan
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.12 no.3
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    • pp.1063-1082
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    • 2018
  • The concept of SDN (Software Defined Networking) endows the network with programmability and significantly improves the flexibility and extensibility of networks. Currently a plenty of research works on introducing SDN into wireless networks. Most of them focus on the innovation of the SDN based architectures but few consider how to realize the global perception of the network through the controller. In order to address this problem, a software defined carrier grade Wi-Fi framework called SWAN, is proposed firstly. Then based on the proposed SWAN architecture, a blueprint of introducing the traditional NSA (Network Situation Awareness) into SWAN is proposed and described in detail. Through perceiving various network data by a decentralized architecture and making comprehension and prediction on the perceived data, the proposed blueprint endows the controllers with the capability to aware of the current network situation and predict the near future situation. Meanwhile, the extensibility of the proposed blueprint makes it a universal solution for software defined wireless networks SDWNs rather than just for one case. Then we further research one typical use case of proposed NSA blueprint: network performance awareness (NPA). The subsequent comparison with other methods and result analysis not only well prove the effectiveness of proposed NPA but further provide a strong proof of the feasibility of proposed NSA blueprint.

Research trends on Biometric information change and emotion classification in relation to various external stimulus (다양한 외부 자극에 따른 생체 정보 변화와 감정 분류 연구 동향)

  • Kim, Ki-Hwan;Lee, Hoon-Jae;Lee, Young Sil;Kim, Tae Yong
    • Journal of the Institute of Convergence Signal Processing
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    • v.20 no.1
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    • pp.24-30
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    • 2019
  • Modern people argue that mental health care is necessary because of various factors such as unstable income and conflict with others. Recently, equipments capable of measuring electrocardiogram (ECG) in wearable equipment have been widely used. In the case of overseas, it can be seen as a medical assistant [14]. By using such functions, studies are being conducted to distinguish representative emotions (joy, sadness, anger, etc.) with objective values. However, most studies are increasing accuracy by collecting complex bio-signals in a limited environment. Therefore, we examine the factors that have the greatest influence on the change and discrimination of biometric information on each stimulus.

A study on the success factors of ICT Convergence type-specific start-up enterprise - mainly the case study - (ICT융합 유형별 스타트업 기업의 성공요인에 관한 연구 -사례연구를 중심으로-)

  • Lee, Seo Han;Noh, Seung Hoon
    • Journal of Digital Convergence
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    • v.12 no.12
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    • pp.203-215
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    • 2014
  • Although many studies about start-up existed, It is almost never shown study about ICT convergence start-up enterprise. This study tries to analyze success factor to start-up enterprise in rapidly growing ICT convergence area. Based on 10 entrepreneurial success cases, We figure out the total 29 units success factors utilizing ERIS model. We classify ICT commercialization with 4 types which are software-R&D centric, software marketing centric, software plus hardware R&D centric, software plus hardware marketing centric. Among success factors the most success factor is related entrepreneur;s ability and include major and professional knowledge about ICT's filed, insight through sensitivity about technical paradigm etc. It was derived the success factors indicated in the course of commercialization of ICT Covergence Unlike other forms of the existing start-up entrepreneurs and contributed to typified in four forms startups for ICT Covergence start-up entrepreneurs.