• The Korean Journal of Applied Statistics
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• v.32 no.5
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• pp.763-782
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• 2019

This paper proposes a probabilistic document ranking model incorporating term dependencies. Document ranking is a fundamental information retrieval task. The task is to sort documents in a collection according to the relevance to the user query (Qin et al., Information Retrieval Journal, 13, 346-374, 2010). A probabilistic model is a model for computing the conditional probability of the relevance of each document given query. Most of the widely used models assume the term independence because it is challenging to compute the joint probabilities of multiple terms. Words in natural language texts are obviously highly correlated. In this paper, we assume a multinomial distribution model to calculate the relevance probability of a document by considering the dependency structure of words, and propose an information retrieval model to rank a document by estimating the probability with the maximum entropy method. The results of the ranking simulation experiment in various multinomial situations show better retrieval results than a model that assumes the independence of words. The results of document ranking experiments using real-world datasets LETOR OHSUMED also show better retrieval results.

• The Journal of Society for e-Business Studies
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• v.26 no.1
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• pp.29-41
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• 2021

Recently, there are increasing attempts to utilize deep learning methodology in the fashion industry. Accordingly, research dealing with various fashion-related problems have been proposed, and superior performances have been achieved. However, the studies for fashion style classification have not reflected the characteristics of the fashion style that one outfit can include multiple styles simultaneously. Therefore, we aim to solve the multi-label classification problem by utilizing the dependencies between the styles. A multi-label recognition model based on a graph convolution network is applied to detect and explore fashion styles' dependencies. Furthermore, we accelerate model training and improve the model's performance through transfer learning. The proposed model was verified by a dataset collected from social network services and outperformed baselines.

• Journal of Hydrogen and New Energy
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• v.12 no.1
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• pp.51-63
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• 2001

In this paper molecular dynamics simulations were employed to investigate the structural and dynamic properties of hydrogen ions impacted on the Ni (100) surface with the $45^{\circ}$ incident angle. The initial kinetic energies of the hydrogen ion range from 100 to 1,600 eV. Together with the trajectory visualization of hydrogen ions, we computed scattering and penetration yields, mean energies and angles, and probability and energy distributions as a function of longitudinal and azimuthal directions. In the case of lower energy scattering ions, the multiple collision effects were found to be important to the third layers or lower. For higher energy penetrating ions, compared with the normal incident angle, it was significant the effective channeling effects through the Ni layers and the angle dependencies were indicated both in the longitudinal and the azimuthal angle directions.

• Journal of Electrical Engineering and information Science
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• v.2 no.4
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• pp.1-7
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• 1997

A multiprocessor microprocessor named SMPC(scaleable multiprocessor chip) that contains tow IU (integer unit) is presented in this paper. It can execute multiple instructions from several tasks exploiting task-level parallelism that is free from instruction dependencies, and provide high performance and throughput on both single program and multiprogramming environments. the IU is a 32-bit scalar processor expecially designed to boost up the performance of string manipulations which are frequently used in RDBMS(relational data base management system) applications. A memory management unit and a data cache shared by two IUs improve the performance and reduce the chip area required. ETH SMPC is implemented in VLSI circuit by custom design and automated design tools.

• International Journal of CAD/CAM
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• v.2 no.1
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• pp.69-75
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• 2002

This paper presents the development of an Intelligent Cavity Layout Design System (ICLDS) for multiple cavity injection moulds. The system is intended to assist mould designers in cavity layout design at concept design stage. The complexities and principles of cavity layout design as well as various dependencies in injection mould design are introduced. The knowledge in cavity layout design is summarized and classified. The functionality, the overall structure and general process of ICLDS are explained. The paper also discusses such issues as knowledge representation and case-based reasoning used in the development of the system. The functionality of the system is illustrated with an example of cavity layout design problem.

• ETRI Journal
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• v.43 no.5
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• pp.932-940
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• 2021

Currently, research on network functions virtualization focuses on using microservices in cloud environments. Previous studies primarily focused on communication between nodes in physical infrastructure. Until now, there is no sufficient research on group key management in virtual environments. The service is composed of microservices that change dynamically according to the virtual service. There are dependencies for microservices on changing the group membership of the service. There is also a high possibility that various security threats, such as data leakage, communication surveillance, and privacy exposure, may occur in interactive communication with microservices. In this study, we propose an ID-based group key exchange (idGKE) mechanism between microservices as one group. idGKE defines the microservices' schemes: group key gen, join group, leave group, and multiple group join. We experiment in a real environment to evaluate the performance of the proposed mechanism. The proposed mechanism ensures an essential requirement for group key management such as secrecy, sustainability, and performance, improving virtual environment security.

• Journal of KIISE:Information Networking
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• v.37 no.2
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• pp.85-93
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• 2010

WLAN virtualization can make multiple simultaneous experiments, each of which is conducted by a separate researcher, share scarce wireless resources in an IEEE 802.11 WLAN. The experiment performed in a virtualized WLAN should be consistent with that in a non-virtualized WLAN. The more similar these two experimental results, the better the consistency. To this end, we propose a novel virtualization scheme that has good consistency by preventing multiple simultaneous experiments from interacting with one another, without any modifications to the IEEE 802.11 standard. Through an intensive simulation study, we confirm that the consistency depends not only on the number of simultaneous experiments but also on wireless channel characteristics such as Doppler frequency and Ricean factor. According to such dependencies, the proposed scheme is optimized, so that it supports good consistency.

• Journal of the Korea Society of Computer and Information
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• v.5 no.2
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• pp.37-42
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• 2000

Object technologies like the OMG's CORBA are enabling technologies the aim to facilitate integration implementation of diverse software components in distributed. heterogeneous environment. CORBA and similar object integration technologies define a standard component interconnection and inter-operation model , promote object-oriented principles to encapsulate incompatible component implementations. In this Paper. we present a connector model for software architectural representation of complex component collaborations. Our Connector model is base on research in software achitecture and object-oriented modeling. and part of a design framework for modeling component-based system. We believe the connector concepts to be vary benificial for a clear expression of dependencies between multiple component in Java Bean-based system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.6
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• pp.1833-1848
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• 2022

Named entity recognition (NER) is an important basic task in the field of Natural Language Processing (NLP). Recently deep learning approaches by extracting word segmentation or character features have been proved to be effective for Chinese Named Entity Recognition (CNER). However, since this method of extracting features only focuses on extracting some of the features, it lacks textual information mining from multiple perspectives and dimensions, resulting in the model not being able to fully capture semantic features. To tackle this problem, we propose a novel Multi-view Semantic Feature Fusion Model (MSFM). The proposed model mainly consists of two core components, that is, Multi-view Semantic Feature Fusion Embedding Module (MFEM) and Multi-head Self-Attention Mechanism Module (MSAM). Specifically, the MFEM extracts character features, word boundary features, radical features, and pinyin features of Chinese characters. The acquired font shape, font sound, and font meaning features are fused to enhance the semantic information of Chinese characters with different granularities. Moreover, the MSAM is used to capture the dependencies between characters in a multi-dimensional subspace to better understand the semantic features of the context. Extensive experimental results on four benchmark datasets show that our method improves the overall performance of the CNER model.

• Nuclear Engineering and Technology
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• v.55 no.1
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• pp.119-130
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• 2023

Among the various elements of probabilistic safety assessment (PSA), human failure events (HFEs) and their dependencies are major contributors to the quantification of risk of a nuclear power plant. Currently, the dependency among HFEs is reflected using a post-processing method in PSA, wherein several drawbacks, such as limited propagation of minimal cutsets through the fault tree and improper truncation of minimal cutsets exist. In this paper, we propose a method to model the HFE dependency directly in a fault tree using the if-then-else logic. The proposed method proved to be equivalent to the conventional post-processing method while addressing the drawbacks of the latter. We also developed a software tool to facilitate the implementation of the proposed method considering the need for modeling the dependency between multiple HFEs. We applied the proposed method to a specific case to demonstrate the drawbacks of the conventional post-processing method and the advantages of the proposed method. When applied appropriately under specific conditions, the direct fault-tree modeling of HFE dependency enhances the accuracy of the risk quantification and facilitates the analysis of minimal cutsets.