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The Impact of Exploration and Exploitation Activities and Market Agility on the Relationship between Big Data Analytics Capability and Firms' Performance (빅 데이터 분석능력과 기업 성과 간의 관계에서 혁신 및 개선 활동과 시장 민첩성의 영향)

  • Jung, He-Kyung;Boo, Jeman
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.45 no.3
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    • pp.150-162
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    • 2022
  • This study investigated the impact of the latest developments in big data analytics capabilities (BDAC) on firm performance. The BDAC have the power to innovate existing management practices. Nevertheless, their impact on firm performance has not been fully is not yet fully elucidated. The BDAC relates to the flexibility of infrastructure as well as the skills of management and firm's personnel. Most studies have explored the phenomena from a theoretical perspective or based on factors such as organizational characteristics. However, this study extends the flow of previous research by proposing and testing a model which examines whether organizational exploration, exploitation and market agility mediate the relationship between the BDAC and firm performance. The proposed model was tested using survey data collected from the long-term employees over 10 years in 250 companies. The results analyzed through structural equation modeling show that a strong BDAC can help improve firm performance. An organization's ability to analyze big data affects its exploration and exploitation thereby affecting market agility, and, consequently, firm performance. These results also confirm the powerful mediating role of exploration, exploitation, and market agility in improving insights into big data utilization and improving firm performance.

Ensuring Information Security in the System of Public Management of Sustainable Development of the Region: EU Experience

  • Zahorskyi, Volodymyr;Bobrovskyi, Oleksii;Bondarenko, Dmytro;Karpa, Marta;Akimov, Oleksandr;Akimova, Liudmyla
    • International Journal of Computer Science & Network Security
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    • v.22 no.8
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    • pp.163-168
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    • 2022
  • The main purpose of the study is to analyze the features of ensuring information security in the system of public administration of the constant development of the region. The actualization of the research topic is because the information has become a powerful means of manipulating the public and individual consciousness, as well as a real weapon used in new types of conflicts, confrontations, and confrontations. Creating opportunities for everyone to access information sources, developing the ability to use it, and at the same time protecting people from dirty information flows create a kind of subject-research field, one of the most relevant aspects of which is the problem of forming and implementing information security policy at the state, public and civil levels. The research methodology involved the use of theoretical and scientific methods. As a result of the study, the key features of ensuring information security in the system of public management of the continuous development of the region of the EU countries were identified.

Development and Validation of a Digital Literacy Scale in the Artificial Intelligence Era for College Students

  • Ha Sung Hwang;Liu Cun Zhu;Qin Cui
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.17 no.8
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    • pp.2241-2258
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    • 2023
  • This study developed digital literacy instruments and tested their effectiveness on college students' perceptions of AI technologies. In creating a new digital literacy test tool, we reviewed the concept and scale of digital literacy based on previous studies that identified the characteristics and measurement of AI literacy. We developed 23 preliminary questions for our research instrument and used a quantitative approach to survey 318 undergraduates. After conducting exploratory and confirmatory factor analysis, we found that digital literacy in the age of AI had four ability sub-factors: critical understanding, artificial intelligence social impact recognition, artificial intelligence technology utilization, and ethical behavior. Then we tested the sub-factors' predictive powers on the perception of AI's usefulness and ease of use. The regression result shows that the most common powerful predictor of the usefulness and ease of use of AI technology was the ability to use AI technology. This finding implies that for college students, the ability to use various tools based on AI technology is an essential competency in the AI era.

Steel-UHPC composite dowels' pull-out performance studies using machine learning algorithms

  • Zhihua Xiong;Zhuoxi Liang;Xuyao Liu;Markus Feldmann;Jiawen Li
    • Steel and Composite Structures
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    • v.48 no.5
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    • pp.531-545
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    • 2023
  • Composite dowels are implemented as a powerful alternative to headed studs for the efficient combination of Ultra High-Performance Concrete (UHPC) with high-strength steel in novel composite structures. They are required to provide sufficient shear resistance and ensure the transmission of tensile forces in the composite connection in order to prevent lifting of the concrete slab. In this paper, the load bearing capacity of puzzle-shaped and clothoidal-shaped dowels encased in UHPC specimen were investigated based on validated experimental test data. Considering the influence of the embedment depth and the spacing width of shear dowels, the characteristics of UHPC square plate on the load bearing capacity of composite structure, 240 numeric models have been constructed and analyzed. Three artificial intelligence approaches have been implemented to learn the discipline from collected experimental data and then make prediction, which includes Artificial Neural Network-Particle Swarm Optimization (ANN-PSO), Adaptive Neuro-Fuzzy Inference System (ANFIS) and an Extreme Learning Machine (ELM). Among the factors, the embedment depth of composite dowel is proved to be the most influential parameter on the load bearing capacity. Furthermore, the results of the prediction models reveal that ELM is capable to achieve more accurate prediction.

Seismic analysis of a steam generator for Gyeongju and Pohang earthquakes

  • Myung Jo Jhung;Youngin Choi;Changsik Oh;Gangsig Shin;Chan Il Park
    • Nuclear Engineering and Technology
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    • v.55 no.5
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    • pp.1577-1586
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    • 2023
  • Safety qualification of a steam generator is a crucial issue related to faulted condition design loads, including earthquake loads, and it should be ensured that the structural integrity of a steam generator does not exceed its design load. Using data from the Gyeongju and Pohang earthquakes, the two most powerful recorded seismic events in Korea, seismic analyses of a typical steam generator are conducted in this study. The modal characteristics are used to develop an input deck for these analyses. With a time history analysis, the responses of the steam generator in the event of an earthquake are obtained. In particular, the displacement, velocity, and acceleration responses are obtained in the time domain, with these outcomes then used for a detailed structural analysis as part of the ensuing assessment. The response spectra are also generated to determine the response characteristics in the frequency domain, focusing on the response comparisons between the Gyeongju and Pohang earthquakes. Structural integrity can be ensured by performing additional analysis using results obtained from the time history analysis considering the input excitations of various earthquakes considered in the design.

A Study of User Demand on the Web-based Information Services of Government Libraries (중앙 행정기관 자료실의 웹기반 정보서비스에 대한 이용자 요구에 관한 연구)

  • Cho, In-Sook;Jung, Song-Rim
    • Journal of the Korean BIBLIA Society for library and Information Science
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    • v.17 no.2
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    • pp.239-259
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    • 2006
  • The purpose of this study is to propose some strategic directions which can promote the government libraries to provide the most effective and efficient information services. The study analyzes user opinion and demand in terms of the Web-based Information Services. For the analysis, the questionnaires were distributed to the 300 users in 18 government libraries. In the results, the study finds that the government libraries with homepage need to advertise homepage service. to provide the training programs, and to improve the system utility for better valuable homepage services. The government libraries without homepage, first of all, must construct their own homepage reflected in the users demand requiring the powerful retrieval ability, the diversity of contents, the high properness of information services.

Visualization Based Building Anatomy Model for Construction Safety Education

  • Pham, Hai Chien;Le, Quang Tuan;Pedro, Akeem;Park, Chan Sik
    • International conference on construction engineering and project management
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    • 2015.10a
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    • pp.430-434
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    • 2015
  • Safety education at the tertiary level prepares students to enter construction industry with adequate safety knowledge; then accidents can be prevented proactively. However, safety subject has not been paid adequate attention in universities and most institutional safety programs consider safety matters in isolation. Meanwhile, anatomical theory in the medicine field has been successfully adopted and proved potential advantageous in various scientific disciplines. With this regard, this study proposes a visualization based Building Anatomy Model (BAM) for construction safety education, which utilizes the anatomical theory in order to improve student's safety knowledge and practical skill. This BAM consists of two modules: 1) Knowledge Acquisition Module (KAM) aims to deliver safety knowledge to students through building anatomy models; 2) Practical Experience Module (PEM) where students safely perform construction activities by using the system to improve safety skill. The system trial is validated with virtual scenarios derived from real accidents cases. This study emphasizes the visualization based building anatomy model would be a powerful pedagogical method to provide effectively safety knowledge and practical skill for students, as a result, safety competence of students would be enhanced.

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A Transformer-Based Emotion Classification Model Using Transfer Learning and SHAP Analysis (전이 학습 및 SHAP 분석을 활용한 트랜스포머 기반 감정 분류 모델)

  • Subeen Leem;Byeongcheon Lee;Insu Jeon;Jihoon Moon
    • Annual Conference of KIPS
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    • 2023.05a
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    • pp.706-708
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    • 2023
  • In this study, we embark on a journey to uncover the essence of emotions by exploring the depths of transfer learning on three pre-trained transformer models. Our quest to classify five emotions culminates in discovering the KLUE (Korean Language Understanding Evaluation)-BERT (Bidirectional Encoder Representations from Transformers) model, which is the most exceptional among its peers. Our analysis of F1 scores attests to its superior learning and generalization abilities on the experimental data. To delve deeper into the mystery behind its success, we employ the powerful SHAP (Shapley Additive Explanations) method to unravel the intricacies of the KLUE-BERT model. The findings of our investigation are presented with a mesmerizing text plot visualization, which serves as a window into the model's soul. This approach enables us to grasp the impact of individual tokens on emotion classification and provides irrefutable, visually appealing evidence to support the predictions of the KLUE-BERT model.

Long range-based low-power wireless sensor node

  • Komal Devi;Rita Mahajan;Deepak Bagai
    • ETRI Journal
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    • v.45 no.4
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    • pp.570-580
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    • 2023
  • Sensor nodes are the most significant part of a wireless sensor network that offers a powerful combination of sensing, processing, and communication. One major challenge while designing a sensor node is power consumption, as sensor nodes are generally battery-operated. In this study, we proposed the design of a low-power, long range-based wireless sensor node with flexibility, a compact size, and energy efficiency. Furthermore, we improved power performance by adopting an efficient hardware design and proper component selection. The Nano Power Timer Integrated Circuit is used for power management, as it consumes nanoamps of current, resulting in improved battery life. The proposed design achieves an off-time current of 38.17309 nA, which is tiny compared with the design discussed in the existing literature. Battery life is estimated for spreading factors (SFs), ranging from SF7 to SF12. The achieved battery life is 2.54 years for SF12 and 3.94 years for SF7. We present the analysis of current consumption and battery life. Sensor data, received signal strength indicator, and signal-to-noise ratio are visualized using the ThingSpeak network.

A Fast IFFT Algorithm for IMDCT of AAC Decoder (AAC 디코더의 IMDCT를 위한 고속 IFFT 알고리즘)

  • Chi, Hua-Jun;Kim, Tae-Hoon;Park, Ju-Sung
    • The Journal of the Acoustical Society of Korea
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    • v.26 no.5
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    • pp.214-219
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    • 2007
  • This paper proposes a new IFFT(Inverse Fast Fourier Transform) algorithm, which is proper for IMDCT(Inverse Modified Discrete Cosine Transform) of MPEG-2 AAC(Advanced Audio Coding) decoder. The $2^n$(N-point) type IMDCT is the most powerful among many IMDCT algorithms, however it includes IFFT that requires many calculation cycles. The IFFT used in $2^n$(N-point) type IMDCT employ the bit-reverse data arrangement of inputs and N/4-point complex IFFT to reduce the calculation cycles. We devised a new data arrangement method of IFFT input and $N/4^{n+1}$-type IFFT and thus we can reduce multiplication cycles, addition cycles, and ROM size.