• Title/Summary/Keyword: hybrid systems

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A Study on Factors Affecting College Dropout Intention: An Hybrid Approach of Topic Modeling and Structural Equation Modeling (대학생의 중도탈락의도에 미치는 요인에 관한 연구: 토픽모델링과 구조방정식모형을 중심으로)

  • Kim, Jae Kyung
    • Journal of Korea Society of Industrial Information Systems
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    • v.27 no.4
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    • pp.81-92
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    • 2022
  • In this study, interview scripts written in the dropout application was analyzed using BERTopic,, and parental influence, academic adaptation, university dissatisfaction was derived as major topics. An empirical study was conducted through a survey of 199 current students with researchmodel composed of those factors affecting dropout intention. The result shows that parental influence had a negative effect on academic adaptation and university satisfaction. Academic adaptation and university satisfaction had a negative effect on the dropout intention. parental influence did not directly affect the dropout intention, but had an indirect positive effect through academic adaptation and university/major satisfaction. The result shows that university satisfaction and academic adaptation is important factor to lower the dropout intention of students who chose current university by parental influence.

Control process design for linking energy storage device to ship power source (선박 전력원에 에너지 저장장치 연계를 위한 제어 프로세스 설계)

  • Oh, Ji-Hyun;Lee, Jong-Hak;Oh, Jin-Seok
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.25 no.11
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    • pp.1603-1611
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    • 2021
  • As IMO environmental regulations are tightened, the need to establish a system that can reduce emissions is increasing, and for this purpose, various power control management systems have been studied and implemented as a new energy management system for ships. In this study, we design a control process through modeling for Bi-Directional Converter (BDC) application with bi-directional power flow to link batteries, which are energy storage devices, to conventional generator power systems, and propose mechanisms for batteries optimized for varying loads. This work models MATLAB/Simulink as a BDC and simulates current control and state of charge (SOC) optimization at the time of charging and discharging batteries according to load scenarios. Through this, the battery, power, and load were interlocked so that the generator operated on board could be operated in the optimal operation range, and power control management was performed to enable the generator to operate in the high fuel efficiency range.

Question Similarity Measurement of Chinese Crop Diseases and Insect Pests Based on Mixed Information Extraction

  • Zhou, Han;Guo, Xuchao;Liu, Chengqi;Tang, Zhan;Lu, Shuhan;Li, Lin
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.15 no.11
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    • pp.3991-4010
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    • 2021
  • The Question Similarity Measurement of Chinese Crop Diseases and Insect Pests (QSM-CCD&IP) aims to judge the user's tendency to ask questions regarding input problems. The measurement is the basis of the Agricultural Knowledge Question and Answering (Q & A) system, information retrieval, and other tasks. However, the corpus and measurement methods available in this field have some deficiencies. In addition, error propagation may occur when the word boundary features and local context information are ignored when the general method embeds sentences. Hence, these factors make the task challenging. To solve the above problems and tackle the Question Similarity Measurement task in this work, a corpus on Chinese crop diseases and insect pests(CCDIP), which contains 13 categories, was established. Then, taking the CCDIP as the research object, this study proposes a Chinese agricultural text similarity matching model, namely, the AgrCQS. This model is based on mixed information extraction. Specifically, the hybrid embedding layer can enrich character information and improve the recognition ability of the model on the word boundary. The multi-scale local information can be extracted by multi-core convolutional neural network based on multi-weight (MM-CNN). The self-attention mechanism can enhance the fusion ability of the model on global information. In this research, the performance of the AgrCQS on the CCDIP is verified, and three benchmark datasets, namely, AFQMC, LCQMC, and BQ, are used. The accuracy rates are 93.92%, 74.42%, 86.35%, and 83.05%, respectively, which are higher than that of baseline systems without using any external knowledge. Additionally, the proposed method module can be extracted separately and applied to other models, thus providing reference for related research.

Stacked Sparse Autoencoder-DeepCNN Model Trained on CICIDS2017 Dataset for Network Intrusion Detection (네트워크 침입 탐지를 위해 CICIDS2017 데이터셋으로 학습한 Stacked Sparse Autoencoder-DeepCNN 모델)

  • Lee, Jong-Hwa;Kim, Jong-Wouk;Choi, Mi-Jung
    • KNOM Review
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    • v.24 no.2
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    • pp.24-34
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    • 2021
  • Service providers using edge computing provide a high level of service. As a result, devices store important information in inner storage and have become a target of the latest cyberattacks, which are more difficult to detect. Although experts use a security system such as intrusion detection systems, the existing intrusion systems have low detection accuracy. Therefore, in this paper, we proposed a machine learning model for more accurate intrusion detections of devices in edge computing. The proposed model is a hybrid model that combines a stacked sparse autoencoder (SSAE) and a convolutional neural network (CNN) to extract important feature vectors from the input data using sparsity constraints. To find the optimal model, we compared and analyzed the performance as adjusting the sparsity coefficient of SSAE. As a result, the model showed the highest accuracy as a 96.9% using the sparsity constraints. Therefore, the model showed the highest performance when model trains only important features.

Seismic retrofit of steel structures with re-centering friction devices using genetic algorithm and artificial neural network

  • Mohamed Noureldin;Masoum M. Gharagoz;Jinkoo Kim
    • Steel and Composite Structures
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    • v.47 no.2
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    • pp.167-184
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    • 2023
  • In this study, a new recentering friction device (RFD) to retrofit steel moment frame structures is introduced. The device provides both self-centering and energy dissipation capabilities for the retrofitted structure. A hybrid performance-based seismic design procedure considering multiple limit states is proposed for designing the device and the retrofitted structure. The design of the RFD is achieved by modifying the conventional performance-based seismic design (PBSD) procedure using computational intelligence techniques, namely, genetic algorithm (GA) and artificial neural network (ANN). Numerous nonlinear time-history response analyses (NLTHAs) are conducted on multi-degree of freedom (MDOF) and single-degree of freedom (SDOF) systems to train and validate the ANN to achieve high prediction accuracy. The proposed procedure and the new RFD are assessed using 2D and 3D models globally and locally. Globally, the effectiveness of the proposed device is assessed by conducting NLTHAs to check the maximum inter-story drift ratio (MIDR). Seismic fragilities of the retrofitted models are investigated by constructing fragility curves of the models for different limit states. After that, seismic life cycle cost (LCC) is estimated for the models with and without the retrofit. Locally, the stress concentration at the contact point of the RFD and the existing steel frame is checked being within acceptable limits using finite element modeling (FEM). The RFD showed its effectiveness in minimizing MIDR and eliminating residual drift for low to mid-rise steel frames models tested. GA and ANN proved to be crucial integrated parts in the modified PBSD to achieve the required seismic performance at different limit states with reasonable computational cost. ANN showed a very high prediction accuracy for transformation between MDOF and SDOF systems. Also, the proposed retrofit showed its efficiency in enhancing the seismic fragility and reducing the LCC significantly compared to the un-retrofitted models.

ITU-R Study on Frequency Sharing for Mobile Satellite Services (ITU-R의 이동위성업무 주파수 공유 연구 현황)

  • B.J. Ku;D.S. Oh
    • Electronics and Telecommunications Trends
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    • v.38 no.1
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    • pp.55-64
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    • 2023
  • Recently, preparations for 6G have led to the increasing interest in integrated or hybrid communication networks considering low-orbit satellite communication networks with terrestrial mobile communication networks. In addition, the demand for frequency allocation for new mobile services from low-orbit small satellites to provide global internet of things (IoT) services is increasing. The operation of such satellites and terrestrial mobile communication networks may inevitably cause interference in adjacent bands and the same band frequency between satellites and terrestrial systems. Focusing on the results of the recent ITU-R WP4C meeting, this study introduces the current status of frequency sharing and interference issues between satellites and terrestrial systems, and frequency allocation issues for new mobile satellite operations. Coexistence and compatibility studies with terrestrial IMT in L band and 2.6 GHz band, operated by Inmassat and India, respectively, and a new frequency allocation study (WRC-23 AI 1.18) are carried out to reflect satellite IoT demand. For the L band, technical requirements have been developed for emission from IMT devices at 1,492 MHz to 1,518 MHz to bands above 1,518 MHz. Related studies in the 2 GHz and 2.6 GHz bands are not discussed due to lack of contributions at the recent meeting. In particular, concerning the WRC-23 agenda 1.18 study on the new frequency allocation method of narrowband mobile satellite work in the Region 1 candidate band 2,010 MHz to 2,025 MHz, Region 2 candidate bands 1,695 MHz to 1,710 MHz, 3,300 MHz to 3,315 MHz, and 3,385 MHz to 3,400 MHz, ITU-R results show no new frequency allocation to narrow mobile satellite services. Given the expected various collaborations between satellites and the terrestrial component are in the future, interference issues between terrestrial IMT and mobile satellite services are similarly expected to continuously increase. Therefore, participation in related studies at ITU-R WP4C and active response to protect terrestrial IMT are necessary to protect domestic radio resources and secure additional frequencies reflecting satellite service use plans.

Topic Similarity-based Event Routing Algorithm for Wireless Ad-Hoc Publish/Subscribe Systems (Ad-Hoc 무선 환경의 발행/구독 시스템을 위한 구독주제 유사도 기반의 이벤트 라우팅 알고리즘)

  • Nguyen, Hieu Trung;Oh, Sang-Yoon
    • Journal of the Korea Society of Computer and Information
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    • v.14 no.10
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    • pp.11-22
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    • 2009
  • For a wireless ad-hoc network, event routing algorithm of the publish/subscribe system is especially important for the performance of the system because of the dynamic characteristic and constraint network of its own. In this paper, we propose a new hybrid event routing algorithm. TopSim for efficient publish/subscribe system on the wireless ad-hoc network by extending the ShopParent algorithm by considering not only network overheads to choose a Parent of the publish/subscribe tree, but also topic similarity which is closeness of subscriptions. Our evaluation shows our proposed TopSim performs better for the case where a new joining node subscribed to the multiple topics and there is a node among Parent candidate nodes who subscribe to the ones in the list of multiple topics (related topics).

Analysis and study of Deep Reinforcement Learning based Resource Allocation for Renewable Powered 5G Ultra-Dense Networks

  • Hamza Ali Alshawabkeh
    • International Journal of Computer Science & Network Security
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    • v.24 no.1
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    • pp.226-234
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    • 2024
  • The frequent handover problem and playing ping-pong effects in 5G (5th Generation) ultra-dense networking cannot be effectively resolved by the conventional handover decision methods, which rely on the handover thresholds and measurement reports. For instance, millimetre-wave LANs, broadband remote association techniques, and 5G/6G organizations are instances of group of people yet to come frameworks that request greater security, lower idleness, and dependable principles and correspondence limit. One of the critical parts of 5G and 6G innovation is believed to be successful blockage the board. With further developed help quality, it empowers administrator to run many systems administration recreations on a solitary association. To guarantee load adjusting, forestall network cut disappointment, and give substitute cuts in case of blockage or cut frustration, a modern pursuing choices framework to deal with showing up network information is require. Our goal is to balance the strain on BSs while optimizing the value of the information that is transferred from satellites to BSs. Nevertheless, due to their irregular flight characteristic, some satellites frequently cannot establish a connection with Base Stations (BSs), which further complicates the joint satellite-BS connection and channel allocation. SF redistribution techniques based on Deep Reinforcement Learning (DRL) have been devised, taking into account the randomness of the data received by the terminal. In order to predict the best capacity improvements in the wireless instruments of 5G and 6G IoT networks, a hybrid algorithm for deep learning is being used in this study. To control the level of congestion within a 5G/6G network, the suggested approach is put into effect to a training set. With 0.933 accuracy and 0.067 miss rate, the suggested method produced encouraging results.

Consumer Acceptance Intention on Block Chain Consensus Mechanismbased Payment System (블록체인 기반 결제시스템에 대한 관광 소비자 수용의도)

  • Jae-Hyun Kwak
    • Information Systems Review
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    • v.21 no.3
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    • pp.27-47
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    • 2019
  • The purpose of this study is to propose a conceptual model for the tourism application of the block chain consensus construct and to test the intention of technology acceptance of potential consumers. First, we have tried to investigate the security, reliability, functionality was derived. Secondary, structural validation of the proposed model confirmed the factors influencing the acceptance of block chain technology in terms of consumers. Based on this, we apply the Unified Theory of Acceptance and Use of Technology to evaluate. Individual innovation and block-chain technology have a strong causal relationship with the proposed block chain acceptance intentions based on the Hybrid Block Chain Consensus system, which shows strong innovation and strong cognitive status. In addition, the factors directly affecting the acceptance of block-chain are the benefits expected from the block chain, the technical infrastructure required to use the service, the perceived benefits available. The influence of the surrounding environment on the adoption of technology and ease of use on new technology did not affect the acceptance intention significantly.

Transcription and Export of RNase MRP RNA in Xenopus Iaevis Oocyetes

  • Jeong, Seon-Ju
    • Animal cells and systems
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    • v.1 no.2
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    • pp.363-370
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    • 1997
  • RNase MRP is a ribonucleoprotein complex with a site-specific endonuclease activity. Its original substrate for cleavage is the small mitochondrial RNA near the mitochondrial DNA replication origin, thus it was proposed to generate the primer for mtDNA replication. Recently, it has been shown to have another substrate in the nucleus, such as pre-S.8S ribosomal RNA in nucleolus. The gene for the RNA component of RNase MRP (MRP RNA) was found to be encoded by the nucleus genome, suggesting an interesting intracellular trafficking of MRP RNA to both mitochondria and nucleolus after transcription in nucleus. In this study, genomic DNA encoding MRP RNA was microinjected into the nucleus of Xenopus oocytes, to analyze promoter regions involved in the transcription. It showed that the proximal sequence element and TATA box are important for basal level transcription; octamer motif and Sp1 binding sites are for elevated level transcription. Most of Xenopus MRP RNA was exported out to the cytoplasm following transcription in the nucleus. Utilizing various hybrid constructs, export of MRP RNA was found to be regulated by the promoter and the 5' half of the coding region of the gene. Interestingly, the transcription in nucleus seems to be coupled to the export of MRP RNA to cytoplasm. Intracellular transport of injected MRP RNA can be easily visualized by whole-mount in situ hybridization following microinjection; it also shows possible intra-nuclear sites for transcription and export of MRP RNA.

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