• 제목/요약/키워드: Language Models

검색결과 872건 처리시간 0.025초

IPC에 근거한 래퍼 설계 방법론 (A Wrapper Design Methodology Based On IPCs)

  • 윤창열;장경선
    • 정보처리학회논문지A
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    • 제9A권4호
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    • pp.573-580
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    • 2002
  • IP를 재사용하기 위해서는 테스트 벤치의 작성과 인터페이스 프로토콜 변환 회로 설계 등과 같은 인터페이스 프로토콜에 관련된 작업이 필요하다. 이러한 작업의 결과물은 버스기능모델에서 버스 프로토콜 컴포넌트에 대응하는 인터페이스 프로토콜 컴포넌트를 포함한다. 본 논문에서는 재사용 될 수 있는 인터페이스 프로토콜 컴포넌트를 사용하여 인터페이스 회로를 설계하는 방법론을 제안한다. 인터페이스 프로토콜 컴포넌트는 주어진 인터페이스 포트를 통해서 오는 트랜잭션을 인식하거나 트랜잭션을 사이클 수준으로 실행시켜 준다. 트랜잭션 중심으로 인터페이스 프로토콜을 기술하는 언어를 소개하고, 이 언어로부터 인터레이스 프로토콜 컴포넌트를 합성가능한 VHDL 형태로 생성하는 방법을 설명한다. 실험결과를 통해, 인터페이스 프로토콜 컴포넌트를 이용한 인터페이스 회로 설계 방식이 그렇지 않은 설계 방식에 비하여 많은 추가 면적을 요구하지 않음을 보인다. 제안된 인터페이스 설계 방식에서는 설계자가 IP의 인터페이스 프로토콜을 상세히 이해하지 않아도, 인터페이스 프로토콜 컴포넌트를 재사용할 수 있으므로, 인터페이스 설계 시간을 줄이는데 공헌할 수 있을 것이다.

멀티모달 인터페이스를 위한 음성 및 문자 공용 인식시스템의 구현 (An On-line Speech and Character Combined Recognition System for Multimodal Interfaces)

  • 석수영;김민정;김광수;정호열;정현열
    • 한국멀티미디어학회논문지
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    • 제6권2호
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    • pp.216-223
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    • 2003
  • 본 논문에서는 음성과 온라인 문자를 단일시스템으로 인식할 수 있는 음성 문자 공용인식 시스템을 제안한다. 일반적으로 CHMM(Continuous Hidden Markov Model)은 음성인식과 온라인 문자인식을 위해 매우 유용한 도구로 잘 알려져 있으나, 인식을 위해서는 각각을 독립 시스템으로 구현하고 있어 추가적인 메모리와 계산량을 요구한다. 제안한 공용인식 시스템은 음성인식과 문자인식을 결합하기 위하여 이들을 동일한 CHMM모델로 구성한 후 상태단위로 지속정보를 제어하는 OPDP(One Pass Dynamic Programming) 알고리즘을 통하여 음성과 문자를 인식할 수 있는 확률 통계적 시스템을 구현하였다. 음성은 MFCC(Mel Frequency Cepstrum Coefficient) 파라미터, 문자는 위치 변화량 파라미터와 비트맵 파라미터를 사용하였으며, MLE(Maximum Likelihood Estimation) 추정법을 이용하여 음소와 자소를 결합한 115개의 3상태 9천이 CHMM모델을 구성하였다. 공용인식기의 실험결과 음소 인식률 51.65%, 음성 단어 인식률 88.6%, 자소 인식률 85.3%, 필기체 단어인식률 85.6%를 나타내어 공용인식의 유효함을 확인할 수 있었다.

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심층신경망을 이용한 소스 코드 원작자 식별 (Souce Code Identification Using Deep Neural Network)

  • 임지수
    • 정보처리학회논문지:소프트웨어 및 데이터공학
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    • 제8권9호
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    • pp.373-378
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    • 2019
  • 현재 프로그래밍 소스들이 온라인에서 공개되어 있기 때문에 무분별한 표절이나 저작권에 대한 문제가 일어나고 있다. 그 중 반복된 저자가 작성한 소스코드는 프로그래밍 특성상 고유의 지문이 있을 수 있다. 본 논문은 구글 코드 잼 프로그램 소스를 심층신경망을 이용한 학습을 통해 각각의 저자를 분별하는 것이다. 이 때 원작자의 소스를 예측 기반 벡터나, 주파수 기반 접근법인 TF-IDF등의 전처리기를 사용하여 입력값들을 벡터화해주고, 심층신경망을 이용한 학습을 통해 각 프로그램 소스 원작자를 식별하고자 한다. 전처리기를 이용하여 언어에 독립적인 학습시스템을 구성하고, 기존의 다른 학습 방법들과 비교하였다. 그 중 TF-IDF와 심층신경망을 사용한 모델은 다른 전처리기나 다른 학습방식을 사용한 것보다 좋은 성능을 보임을 확인하였다.

An elasto-plastic damage constitutive model for jointed rock mass with an application

  • Wang, Hanpeng;Li, Yong;Li, Shucai;Zhang, Qingsong;Liu, Jian
    • Geomechanics and Engineering
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    • 제11권1호
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    • pp.77-94
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    • 2016
  • A forked tunnel, as a special complicated underground structure, is composed of big-arch tunnel, multi-arch tunnel, neighborhood tunnels and separate tunnels according to the different distances between two separate tunnels. Due to the complicated process of design and construction, surrounding jointed rock mass stability of the big-arch tunnel which belongs to the forked tunnel during excavation is a hot issue that needs special attentions. In this paper, an elasto-plastic damage constitutive model for jointed rock mass is proposed based on the coupling method considering elasto-plastic and damage theories, and the irreversible thermodynamics theory. Based on this elasto-plastic damage constitutive model, a three dimensional elasto-plastic damage finite element code (D-FEM) is implemented using Visual Fortran language, which can numerically simulate the whole excavation process of underground project and perform the structural stability of the surrounding rock mass. Comparing with a popular commercial computer code, three dimensional fast Lagrangian analysis of continua (FLAC3D), this D-FEM has advantages in terms of rapid computing process, element grouping function and providing more material models. After that, FLAC3D and D-FEM are simultaneously used to perform the structural stability analysis of the surrounding rock mass in the forked tunnel considering three different computing schemes. The final numerical results behave almost consistent using both FLAC3D and D-FEM. But from the point of numerically obtained damage softening areas, the numerical results obtained by D-FEM more closely approach the practical behaviors of in-situ surrounding rock mass.

Development of the Rule-based Smart Tourism Chatbot using Neo4J graph database

  • Kim, Dong-Hyun;Im, Hyeon-Su;Hyeon, Jong-Heon;Jwa, Jeong-Woo
    • International Journal of Internet, Broadcasting and Communication
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    • 제13권2호
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    • pp.179-186
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    • 2021
  • We have been developed the smart tourism app and the Instagram and YouTube contents to provide personalized tourism information and travel product information to individual tourists. In this paper, we develop a rule-based smart tourism chatbot with the khaiii (Kakao Hangul Analyzer III) morphological analyzer and Neo4J graph database. In the proposed chatbot system, we use a morpheme analyzer, a proper noun dictionary including tourist destination names, and a general noun dictionary including containing frequently used words in tourist information search to understand the intention of the user's question. The tourism knowledge base built using the Neo4J graph database provides adequate answers to tourists' questions. In this paper, the nodes of Neo4J are Area based on tourist destination address, Contents with property of tourist information, and Service including service attribute data frequently used for search. A Neo4J query is created based on the result of analyzing the intention of a tourist's question with the property of nodes and relationships in Neo4J database. An answer to the question is made by searching in the tourism knowledge base. In this paper, we create the tourism knowledge base using more than 1300 Jeju tourism information used in the smart tourism app. We plan to develop a multilingual smart tour chatbot using the named entity recognition (NER), intention classification using conditional random field(CRF), and transfer learning using the pretrained language models.

Development of a user-friendly training software for pharmacokinetic concepts and models

  • Han, Seunghoon;Lim, Byounghee;Lee, Hyemi;Bae, Soo Hyun
    • Translational and Clinical Pharmacology
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    • 제26권4호
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    • pp.166-171
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    • 2018
  • Although there are many commercially available training software programs for pharmacokinetics, they lack flexibility and convenience. In this study, we develop simulation software to facilitate pharmacokinetics education. General formulas for time courses of drug concentrations after single and multiple dosing were used to build source code that allows users to simulate situations tailored to their learning objectives. A mathematical relationship for a 1-compartment model was implemented in the form of differential equations. The concept of population pharmacokinetics was also taken into consideration for further applications. The source code was written using R. For the convenience of users, two types of software were developed: a web-based simulator and a standalone-type application. The application was built in the JAVA language. We used the JAVA/R Interface library and the 'eval()' method from JAVA for the R/JAVA interface. The final product has an input window that includes fields for parameter values, dosing regimen, and population pharmacokinetics options. When a simulation is performed, the resulting drug concentration time course is shown in the output window. The simulation results are obtained within 1 minute even if the population pharmacokinetics option is selected and many parameters are considered, and the user can therefore quickly learn a variety of situations. Such software is an excellent candidate for development as an open tool intended for wide use in Korea. Pharmacokinetics experts will be able to use this tool to teach various audiences, including undergraduates.

Classes in Object-Oriented Modeling (UML): Further Understanding and Abstraction

  • Al-Fedaghi, Sabah
    • International Journal of Computer Science & Network Security
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    • 제21권5호
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    • pp.139-150
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    • 2021
  • Object orientation has become the predominant paradigm for conceptual modeling (e.g., UML), where the notions of class and object form the primitive building blocks of thought. Classes act as templates for objects that have attributes and methods (actions). The modeled systems are not even necessarily software systems: They can be human and artificial systems of many different kinds (e.g., teaching and learning systems). The UML class diagram is described as a central component of model-driven software development. It is the most common diagram in object-oriented models and used to model the static design view of a system. Objects both carry data and execute actions. According to some authorities in modeling, a certain degree of difficulty exists in understanding the semantics of these notions in UML class diagrams. Some researchers claim class diagrams have limited use for conceptual analysis and that they are best used for logical design. Performing conceptual analysis should not concern the ways facts are grouped into structures. Whether a fact will end up in the design as an attribute is not a conceptual issue. UML leads to drilling down into physical design details (e.g., private/public attributes, encapsulated operations, and navigating direction of an association). This paper is a venture to further the understanding of object-orientated concepts as exemplified in UML with the aim of developing a broad comprehension of conceptual modeling fundamentals. Thinging machine (TM) modeling is a new modeling language employed in such an undertaking. TM modeling interlaces structure (components) and actionality where actions infiltrate the attributes as much as the classes. Although space limitations affect some aspects of the class diagram, the concluding assessment of this study reveals the class description is a kind of shorthand for a richer sematic TM construct.

ELMo 임베딩 기반 문장 중요도를 고려한 중심 문장 추출 방법 (Method of Extracting the Topic Sentence Considering Sentence Importance based on ELMo Embedding)

  • 김은희;임명진;신주현
    • 스마트미디어저널
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    • 제10권1호
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    • pp.39-46
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    • 2021
  • 본 연구는 뉴스 기사에서 기사문을 구성하는 문장별 중요도를 고려하여 요약문을 추출하는 방법에 관한 것으로 문장 중요도에 영향을 주는 특성으로 중심 문장(Topic Sentence)일 확률, 기사 제목 및 다른 문장과의 유사도, 문장 위치에 따른 가중치를 추출하여 문장 중요도를 계산하는 방법을 제안한다. 이때, 중심 문장(Topic Sentence)은 일반 문장과는 구별되는 특징을 가질 것이라는 가설을 세우고, 딥러닝 기반 분류 모델을 학습시켜 입력 문장에 대한 중심 문장 확률값을 구한다. 또한 사전학습된 ELMo 언어 모델을 활용하여 문맥 정보를 반영한 문장 벡터값을 기준으로 문장간 유사도를 계산하여 문장 특성으로 추출한다. LSTM 및 BERT 모델의 중심 문장 분류성능은 정확도 93%, 재현율 96.22%, 정밀도 89.5%로 높은 분석 결과가 나왔으며, 이렇게 추출된 문장 특성을 결합하여 문장별 중요도를 계산한 결과, 기존 TextRank 알고리즘과 비교하여 중심 문장 추출 성능이 10% 정도 개선된 것을 확인할 수 있었다.

System for Supporting the Decision about the Possibility of Concluding the Civil Law Agreements for Medical, Therapeutic and Dental Services

  • Hnatchuk, Yelyzaveta;Hovorushchenko, Tetiana;Shteinbrekher, Daria;Kysil, Tetiana
    • International Journal of Computer Science & Network Security
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    • 제22권10호
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    • pp.155-164
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    • 2022
  • The review of known decisions showed that currently there are no systems and technologies for supporting the decision about the possibility of concluding the civil law agreements for medical, therapeutic and dental services. The paper models the decision-making support process on the possibility of concluding the civil law agreements for medical, therapeutic and dental services, which is the theoretical basis for the development of rules, methods and system for supporting the decision about the possibility of concluding the civil law agreements for medical, therapeutic and dental services. The paper also developed the system for supporting the decision about the possibility of concluding the civil law agreements for medical, therapeutic and dental services, which automatically and free determines the possibility or impossibility of concluding the corresponding civil law agreement for the provision of a corresponding medical service. In the case of formation of a conclusion about the possibility of concluding the agreement, further conclusion and signing of the corresponding agreement takes place. In the case of forming a conclusion about the impossibility of concluding the agreement, a request is made for finalizing the relevant agreement for the provision of the relevant medical service, indicating the reasons for the impossibility of concluding the agreement - missing essential conditions in the agreement. After finalization, the agreement can be analyzed again by the developed system for supporting the decision.

Technology of Decision-Making Support Regarding the Possibility of Donation and Transplantation Considering Civil Law

  • Hnatchuk, Yelyzaveta;Hovorushchenko, Tetiana;Drapak, Georgii;Kysil, Tetiana
    • International Journal of Computer Science & Network Security
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    • 제22권9호
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    • pp.307-315
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    • 2022
  • The review of known decision-making support systems and technologies regarding the possibility of donation and transplantation showed that currently there are no systems and technologies of decision-making support regarding the possibility of donation and transplantation considering civil law. The paper models the decision-making support process regarding the possibility of donation and transplantation, which is a theoretical basis for the development of rules, methods and technology of decision-making support regarding the possibility of donation and transplantation considering civil law. The paper also developed the technology of decision-making support regarding the possibility of donation and transplantation considering civil law as a component of the Unified State Information System for Organ and Tissue Transplantation, which automatically and free of charge determines the possibility/impossibility of donation and transplantation. In the case of the possibility of donation, the admissible type of donation is also determined - over-life or after-life donation - and data about potential donor is entered in the relevant Donor Register. In the case of the possibility of transplantation, if the recipient needs a transplant of one of the paired organs or a part of the organ/tissue, then data about potential recipient are entered in the Transplantation List from both over-life and after-life donor, otherwise, if the recipient needs a transplant of a non-paired organ or both paired organs, then data about potential recipient are entered only in the Transplantation List from after-life donor.