• Title/Summary/Keyword: language-specific features

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An Empirical Study on Factors Influencing the Learning Results of Information Technology Using Multimedia (멀티미디어를 이용한 정보기술 교육의 학습 효과에 영향을 미치는 요인에 관한 연구)

  • Kim, Byung-Gon;Kim, Jong-Uk
    • Asia pacific journal of information systems
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    • v.10 no.1
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    • pp.37-59
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    • 2000
  • Recently, the rapid development of information technology has brought enormous changes in education. Consolidation of communications and multimedia technologies are enabling the new educational paradigm such as distance learning and virtual education. Furthermore, many studies in the education engineering field report that teaching using multimedia technologies more enhances students' performance than the traditional instructor-teaching method. However, little research regarding the education using multimedia has been done in the MIS filed. None of multimedia-related studies could be found in the top-ranked MIS journals published in Korea for the last five years, and only a few studies were found even worldwide. In this regard, the purpose of this study is to investigate which features of multimedia software are most important to enhance the teaching results of students, From the previous research, we found out the specific features of the educational multimedia software which are considered to affect the students' performance, and defined the research variables related to those educational software features, And, based on the constructivism and motivation theory of the education engineering field, a theoretical research model and research hypotheses were developed. Perceived usefulness of the class and a student's perceived interests in the class were used as surrogate variables to measure teaching performance. Total 277 students participated separately in one of the two multimedia classes which have continued for three weeks. One was C programming language class and the other was multimedia CD-title development class. Each student listened for the multimedia session of the class using multimedia software and, at the end of the multimedia session, answered the survey questionnaire, The results of the study show that motivation to the class and the contents of education were statistically significant to the students' performance in the class. That implies, not only in the traditional instructor-teaching method but also in the multimedia class, that the contents of education itself and student's motivation to the class are most important to raise instructional results.

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The Bytecode Optimizer (바이트코드 최적화기)

  • 이야리;홍경표;오세만
    • Journal of KIISE:Software and Applications
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    • v.30 no.1_2
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    • pp.73-80
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    • 2003
  • The Java programming language is designed for developing effective applications in a heterogeneous network environment. Major problem in Java is its performance. many attractive features of Java make the development of software easy, but also make it expensive to support ; applications written in Java are often much slower than their counterparts written in C or C++. To use Java`s attractive features without the performance penalty, sophisticated optimizations and runtime systems are required. Optimising Java bytecode has several advantages. First, the bytecode is independent of any compiler that is used to generate it. Second, the bytecode optimization can be performed as a pre=pass to Just-In-Time(JIT) compilation. Many attractive features of Java make the development of software easy, but also make it expensive to support. The goal of this work is to develop automatic construction of code optimizer for Java bytecode. We`ve designed and implemented a Bytecode Optimizer that performs the peephole optimization, bytecode-specific optimization, and method-inlining techniques. Using the Classfile optimizer, we see up to 9% improvement in speed and about 20% size reduction in Java class files, when compared to average code using the interpreter alone.

Automatic Categorization of Islamic Jurisprudential Legal Questions using Hierarchical Deep Learning Text Classifier

  • AlSabban, Wesam H.;Alotaibi, Saud S.;Farag, Abdullah Tarek;Rakha, Omar Essam;Al Sallab, Ahmad A.;Alotaibi, Majid
    • International Journal of Computer Science & Network Security
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    • v.21 no.9
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    • pp.281-291
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    • 2021
  • The Islamic jurisprudential legal system represents an essential component of the Islamic religion, that governs many aspects of Muslims' daily lives. This creates many questions that require interpretations by qualified specialists, or Muftis according to the main sources of legislation in Islam. The Islamic jurisprudence is usually classified into branches, according to which the questions can be categorized and classified. Such categorization has many applications in automated question-answering systems, and in manual systems in routing the questions to a specialized Mufti to answer specific topics. In this work we tackle the problem of automatic categorisation of Islamic jurisprudential legal questions using deep learning techniques. In this paper, we build a hierarchical deep learning model that first extracts the question text features at two levels: word and sentence representation, followed by a text classifier that acts upon the question representation. To evaluate our model, we build and release the largest publicly available dataset of Islamic questions and answers, along with their topics, for 52 topic categories. We evaluate different state-of-the art deep learning models, both for word and sentence embeddings, comparing recurrent and transformer-based techniques, and performing extensive ablation studies to show the effect of each model choice. Our hierarchical model is based on pre-trained models, taking advantage of the recent advancement of transfer learning techniques, focused on Arabic language.

A Study on the XML/EDI (XML/EDI에 관한 고찰)

  • 전순환
    • The Journal of Information Technology
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    • v.4 no.1
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    • pp.109-124
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    • 2001
  • Electronic Data Interchange (EDI) has been used for business-to-business communication for almost a quarter of a century. Initial efforts Involved inter-company agreements on how to exchange commercial data, initially as information stored on tape and later as messages sent over dedicated data lines. To avoid having to use different protocols to move data between different companies, various Industry groups identified sets of data that could form the basis of individual agreements. The industry groups also sought to agree the format in which fields in such data sets were interchange so that a company only needed to develop one methodology for decoding information received without resource to human intervention. The XML/EDI specific components are built on top of existing standards for transmitting and processing XML-encoded data. These standards define shared features such as: the standard Internet file storage/naming and data transport mechanisms, file and message transfer formats, the syntax of data coded in XML, the way in which XML files can be validated by an XML parser or document object model generator, the way in which XSL presentation and data evaluation scripts can be associated with parsed objects, the use of rules and data management robots to manage application and repository interfaces.

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An Expert System for Foult Diagnosis in a System (전력계통의 고장진단을 위한 전문가 시스템의 연구)

  • Park, Young-Moon;Lee, Heung-Jae
    • Proceedings of the KIEE Conference
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    • 1989.07a
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    • pp.241-245
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    • 1989
  • A knowledge based expert system is a computer program that emulates the reasoning process of a human expert in a specific problem domain. This paper presents an expert system to diagnose the various faults in power system. The developed expert system is represented considering two points; the possibility of solution and the fast processing speed. As uncertainties exist in the facts and rules which comprise the knowledge base of the expert system, Certainty Factor, which is based on the confirmation theory is used for the inexact reasoning. Also, as the diagnosis problem requires the inductive reasoning process in nature, the solution is imperfect and not unique in general. So the expert system is designed to generate all the possible hypothesis in order of the possibility and also it can explain the propagation procedure of the faults for each solution using the built in backtracking mechanism. In realization of the expert system, the processing speed is greatly dependent upon the problem representation, reasoning scheme and search strategy. So, in this paper the fault diagnosis problem itself is analysed from the view point of Artificial Intelligence and as a result, the expert system has the following basic features. 1) The certainty factor is adopted in the inference engine for inexact reasoning. 2) Problem apace is represented using the problem reduction technique. 3) Bidirectional reasoning scheme is used. 4) Best first search strategy is adopted for rapid processing. The expert system was developed us ing PROLOG language.

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Shape Property Study of Hangul Font for Font Classification (글꼴 분류를 위한 한글 글꼴의 모양 특성 연구)

  • Kim, Hyun-Young;Lim, Soon-Bum
    • Journal of Korea Multimedia Society
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    • v.20 no.9
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    • pp.1584-1595
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    • 2017
  • Each cultural community has developed a variety of fonts to express their own language and characters. Hangul has also diversified its font shapes through changing the composition ratio and look of the consonants and vowels. Rather, thanks to the variety of these fonts, a considerable amount of time and effort must be devoted to the selection of a specific font shape. This is related to the fact that the current Hangul service and classification system process the font only with its name or the name of the manufacturer. It means that there is no consensus about the font shape classification system for Hangul. In this study, we propose a shape property set that can be a basis for classifying Hangul fonts. The font shape property set was generated by performing statistical analysis with features which have been studied by the font design experts and was verified through questionnaire using representative fonts based on the classification scheme defined by the Hangul font design classification system standard. This study is meaningful in that it is a study on shape classification properties of K-means and PCA statistical techniques based on font data rather than design field study.

Semantic Image Search: Case Study for Western Region Tourism in Thailand

  • Chantrapornchai, Chantana;Bunlaw, Netnapa;Choksuchat, Chidchanok
    • Journal of Information Processing Systems
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    • v.14 no.5
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    • pp.1195-1214
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    • 2018
  • Typical search engines may not be the most efficient means of returning images in accordance with user requirements. With the help of semantic web technology, it is possible to search through images more precisely in any required domain, because the images are annotated according to a custom-built ontology. With appropriate annotations, a search can then, return images according to the context. This paper reports on the design of a tourism ontology relevant to touristic images. In particular, the image features and the meaning of the images are described using various properties, along with other types of information relevant to tourist attractions using the OWL language. The methodology used is described, commencing with building an image and tourism corpus, creating the ontology, and developing the search engine. The system was tested through a case study involving the western region of Thailand. The user can search specifying the specific class of image or they can use text-based searches. The results are ranked using weighted scores based on kinds of properties. The precision and recall of the prototype system was measured to show its efficiency. User satisfaction was also evaluated, was also performed and was found to be high.

Intelligent Methods to Extract Knowledge from Process Data in the Industrial Applications

  • Woo, Young-Kwang;Bae, Hyeon;Kim, Sung-Shin;Woo, Kwang-Bang
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.3 no.2
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    • pp.194-199
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    • 2003
  • Data are an expression of the language or numerical values that show some features. And the information is extracted from data for the specific purposes. The knowledge is utilized as information to construct rules that recognize patterns or make a decision. Today, knowledge extraction and application of that are broadly accomplished for the easy comprehension and the performance improvement of systems in the several industrial fields. The knowledge extraction can be achieved by some steps that include the knowledge acquisition, expression, and implementation. Such extracted knowledge is drawn by rules with data mining techniques. Clustering (CL), input space partition (ISP), neuro-fuzzy (NF), neural network (NN), extension matrix (EM), etc. are employed for the knowledge expression based upon rules. In this paper, the various approaches of the knowledge extraction are surveyed and categorized by methodologies and applied industrial fields. Also, the trend and examples of each approaches are shown in the tables and graphes using the categories such as CL, ISP, NF, NN, EM, and so on.

Research on Satisfaction Evaluation Based on Tourist Big Data

  • Guo, Hanwen;Liu, Ziyang;Jiao, Zeyu
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.16 no.1
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    • pp.231-244
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    • 2022
  • With the improvement of people's living standards and the development of tourism, tourists have greater freedom in choosing destinations. Therefore, as an indicator of satisfaction with scenic spots, tourist comments are becoming increasingly prominent. This paper aims to compare and analyze the landscape image of the Five Great Mountains in China and provide specific strategies for its development. The online reviews of tourists on the Online Travel Agency (OTA) website about the Five Great Mountains from 2015 to 2018 are collected as research samples. The text analysis method and R language are used to analyze the content of the tourist reviews, while the high-frequency words in the word cloud are used for visual display. In addition, the entropy weight method is used to determine the index weight and tourist satisfaction is evaluated to understand the weaknesses of those scenic spots. The results of the study show that firstly, the tourist satisfaction with the Five Great Mountains is basically consistent with its popularity. Secondly, through weight analysis, tourists pay special attention to the landscape features and environmental health of the scenic area, so that relevant departments should focus on building the landscape characteristics and improving the environmental health of the scenic area. At the same time, the accommodation and service management of the scenic spot cannot be ignored. Finally, according to the analysis results, suggestions are made on how to improve the tourist satisfaction with the Five Great Mountains.

Retrieval methodology for similar NPP LCO cases based on domain specific NLP

  • No Kyu Seong ;Jae Hee Lee ;Jong Beom Lee;Poong Hyun Seong
    • Nuclear Engineering and Technology
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    • v.55 no.2
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    • pp.421-431
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    • 2023
  • Nuclear power plants (NPPs) have technical specifications (Tech Specs) to ensure that the equipment and key operating parameters necessary for the safe operation of the power plant are maintained within limiting conditions for operation (LCO) determined by a safety analysis. The LCO of Tech Specs that identify the lowest functional capability of equipment required for safe operation for a facility must be complied for the safe operation of NPP. There have been previous studies to aid in compliance with LCO relevant to rule-based expert systems; however, there is an obvious limit to expert systems for implementing the rules for many situations related to LCO. Therefore, in this study, we present a retrieval methodology for similar LCO cases in determining whether LCO is met or not met. To reflect the natural language processing of NPP features, a domain dictionary was built, and the optimal term frequency-inverse document frequency variant was selected. The retrieval performance was improved by adding a Boolean retrieval model based on terms related to the LCO in addition to the vector space model. The developed domain dictionary and retrieval methodology are expected to be exceedingly useful in determining whether LCO is met.