• 제목/요약/키워드: Computer Literature Analysis Techniques

검색결과 34건 처리시간 0.026초

PubMiner: Machine Learning-based Text Mining for Biomedical Information Analysis

  • Eom, Jae-Hong;Zhang, Byoung-Tak
    • Genomics & Informatics
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    • 제2권2호
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    • pp.99-106
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    • 2004
  • In this paper we introduce PubMiner, an intelligent machine learning based text mining system for mining biological information from the literature. PubMiner employs natural language processing techniques and machine learning based data mining techniques for mining useful biological information such as protein­protein interaction from the massive literature. The system recognizes biological terms such as gene, protein, and enzymes and extracts their interactions described in the document through natural language processing. The extracted interactions are further analyzed with a set of features of each entity that were collected from the related public databases to infer more interactions from the original interactions. An inferred interaction from the interaction analysis and native interaction are provided to the user with the link of literature sources. The performance of entity and interaction extraction was tested with selected MEDLINE abstracts. The evaluation of inference proceeded using the protein interaction data of S. cerevisiae (bakers yeast) from MIPS and SGD.

A review of missing video frame estimation techniques for their suitability analysis in NPP

  • Chaubey, Mrityunjay;Singh, Lalit Kumar;Gupta, Manjari
    • Nuclear Engineering and Technology
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    • 제54권4호
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    • pp.1153-1160
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    • 2022
  • The application of video processing techniques are useful for the safety of nuclear power plants by tracking the people online on video to estimate the dose received by staff during work in nuclear plants. Nuclear reactors remotely visually controlled to evaluate the plant's condition using video processing techniques. Internal reactor components should be frequently inspected but in current scenario however involves human technicians, who review inspection videos and identify the costly, time-consuming and subjective cracks on metallic surfaces of underwater components. In case, if any frame of the inspection video degraded/corrupted/missed due to noise or any other factor, then it may cause serious safety issue. The problem of missing/degraded/corrupted video frame estimation is a challenging problem till date. In this paper a systematic literature review on video processing techniques is carried out, to perform their suitability analysis for NPP applications. The limitation of existing approaches are also identified along with a roadmap to overcome these limitations.

Formal Analysis of Distributed Shared Memory Algorithms

  • Muhammad Atif;Muhammad Adnan Hashmi;Mudassar Naseer;Ahmad Salman Khan
    • International Journal of Computer Science & Network Security
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    • 제24권4호
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    • pp.192-196
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    • 2024
  • The memory coherence problem occurs while mapping shared virtual memory in a loosely coupled multiprocessors setup. Memory is considered coherent if a read operation provides same data written in the last write operation. The problem is addressed in the literature using different algorithms. The big question is on the correctness of such a distributed algorithm. Formal verification is the principal term for a group of techniques that routinely use an analysis that is established on mathematical transformations to conclude the rightness of hardware or software behavior in divergence to dynamic verification techniques. This paper uses UPPAAL model checker to model the dynamic distributed algorithm for shared virtual memory given by K.Li and P.Hudak. We analyse the mechanism to keep the coherence of memory in every read and write operation by using a dynamic distributed algorithm. Our results show that the dynamic distributed algorithm for shared virtual memory partially fulfils its functional requirements.

A Survey of Arabic Thematic Sentiment Analysis Based on Topic Modeling

  • Basabain, Seham
    • International Journal of Computer Science & Network Security
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    • 제21권9호
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    • pp.155-162
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    • 2021
  • The expansion of the world wide web has led to a huge amount of user generated content over different forums and social media platforms, these rich data resources offer the opportunity to reflect, and track changing public sentiments and help to develop proactive reactions strategies for decision and policy makers. Analysis of public emotions and opinions towards events and sentimental trends can help to address unforeseen areas of public concerns. The need of developing systems to analyze these sentiments and the topics behind them has emerged tremendously. While most existing works reported in the literature have been carried out in English, this paper, in contrast, aims to review recent research works in Arabic language in the field of thematic sentiment analysis and which techniques they have utilized to accomplish this task. The findings show that the prevailing techniques in Arabic topic-based sentiment analysis are based on traditional approaches and machine learning methods. In addition, it has been found that considerably limited recent studies have utilized deep learning approaches to build high performance models.

Precision Agriculture using Internet of Thing with Artificial Intelligence: A Systematic Literature Review

  • Noureen Fatima;Kainat Fareed Memon;Zahid Hussain Khand;Sana Gul;Manisha Kumari;Ghulam Mujtaba Sheikh
    • International Journal of Computer Science & Network Security
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    • 제23권7호
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    • pp.155-164
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    • 2023
  • Machine learning with its high precision algorithms, Precision agriculture (PA) is a new emerging concept nowadays. Many researchers have worked on the quality and quantity of PA by using sensors, networking, machine learning (ML) techniques, and big data. However, there has been no attempt to work on trends of artificial intelligence (AI) techniques, dataset and crop type on precision agriculture using internet of things (IoT). This research aims to systematically analyze the domains of AI techniques and datasets that have been used in IoT based prediction in the area of PA. A systematic literature review is performed on AI based techniques and datasets for crop management, weather, irrigation, plant, soil and pest prediction. We took the papers on precision agriculture published in the last six years (2013-2019). We considered 42 primary studies related to the research objectives. After critical analysis of the studies, we found that crop management; soil and temperature areas of PA have been commonly used with the help of IoT devices and AI techniques. Moreover, different artificial intelligence techniques like ANN, CNN, SVM, Decision Tree, RF, etc. have been utilized in different fields of Precision agriculture. Image processing with supervised and unsupervised learning practice for prediction and monitoring the PA are also used. In addition, most of the studies are forfaiting sensory dataset to measure different properties of soil, weather, irrigation and crop. To this end, at the end, we provide future directions for researchers and guidelines for practitioners based on the findings of this review.

IDEFO 모델링을 이용한 인터넷 전자우편 보안시스템 분석 (Systems Analysis of the Internet E-Mail Security Using IDEFO Modeling)

  • 김중인;김석우
    • 산업공학
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    • 제9권3호
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    • pp.249-256
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    • 1996
  • The Internet e-mail security software and standards, such as PGP (Pretty Good Privacy) and PEM (Privacy Enhanced Mail), have several limitations that should be overcome for their further applications to the Internet and network environments. In order to improve and reengineer those software, details of the As-Is software processing should be analyzed. One of the possible techniques for software analysis is IDEFO function modeling. Although IDEFO has been mainly used for BPR as one of the industrial engineering techniques, it has been rarely applied to the analysis of software processing and reengineering in computer and software engineering fields. Additionally, no sufficient details of PGP and PEM processing are analyzed in the literature. The objective of this paper is to demonstrate the application of the IDEFO to the systems analysis of the Internet e-mail security software as well as to provide software developers with the basis for software improvements.

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Digital Forensic: Challenges and Solution in the Protection of Corporate Crime

  • CHOI, Do-Hee
    • 산경연구논집
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    • 제12권6호
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    • pp.47-55
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    • 2021
  • Purpose: Organizational crime is an offense committed by an individual or an official in a corporate entity for organizational gain. This study aims to explore the literature on challenges facing digital forensics and further discuss possible solutions to such challenges as far as the protection of corporate crime is concerned. Research design, data and methodology: Qualitative textual methodology matches the interpretative approach since it is a quality method meant to consider the inductivity of strategies. Also, a qualitative approach is vital because it is distinct from the techniques used in optimistic paradigms linked to science laws. Results: For achieving justice through the investigation of digital forensic, there is a need to eradicate corporate crimes. This study suggests several solutions to reduce corporate crime such as 'Solving a problem to Anti-forensic Techniques', 'Cloud computing technique', and 'Legal Framework' etc. Conclusion: As corporate crime increases in rate, the data collected by digital forensics increases. The challenge of analyzing chunks of data requires digital forensic experts, who need tools to analyze them. Research findings shows that a change of the operating system and digital evidence interpretation is becoming a challenge as the new computer application software is not compatible with older software's structure.

Machine Learning Algorithm Accuracy for Code-Switching Analytics in Detecting Mood

  • Latib, Latifah Abd;Subramaniam, Hema;Ramli, Siti Khadijah;Ali, Affezah;Yulia, Astri;Shahdan, Tengku Shahrom Tengku;Zulkefly, Nor Sheereen
    • International Journal of Computer Science & Network Security
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    • 제22권9호
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    • pp.334-342
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    • 2022
  • Nowadays, as we can notice on social media, most users choose to use more than one language in their online postings. Thus, social media analytics needs reviewing as code-switching analytics instead of traditional analytics. This paper aims to present evidence comparable to the accuracy of code-switching analytics techniques in analysing the mood state of social media users. We conducted a systematic literature review (SLR) to study the social media analytics that examined the effectiveness of code-switching analytics techniques. One primary question and three sub-questions have been raised for this purpose. The study investigates the computational models used to detect and measures emotional well-being. The study primarily focuses on online postings text, including the extended text analysis, analysing and predicting using past experiences, and classifying the mood upon analysis. We used thirty-two (32) papers for our evidence synthesis and identified four main task classifications that can be used potentially in code-switching analytics. The tasks include determining analytics algorithms, classification techniques, mood classes, and analytics flow. Results showed that CNN-BiLSTM was the machine learning algorithm that affected code-switching analytics accuracy the most with 83.21%. In addition, the analytics accuracy when using the code-mixing emotion corpus could enhance by about 20% compared to when performing with one language. Our meta-analyses showed that code-mixing emotion corpus was effective in improving the mood analytics accuracy level. This SLR result has pointed to two apparent gaps in the research field: i) lack of studies that focus on Malay-English code-mixing analytics and ii) lack of studies investigating various mood classes via the code-mixing approach.

컴퓨터 문헌 분석 기반의 토끼전 '어족회의' 대목 내용 유사도에 따른 이본 계통 분류 연구 (A Study of Computational Literature Analysis based Classification for a Pairwise Comparison by Contents Similarity in a section of Tokkijeon, 'Fish Tribe Conference')

  • 김동건;정화영
    • 한국콘텐츠학회논문지
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    • 제22권5호
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    • pp.15-25
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    • 2022
  • 본 연구는 컴퓨터 문헌 분석 기법을 활용하여 <토끼전> '어족회의' 대목의 계열과 계통을 밝히는 데에 목적을 둔다. 우선 각 단락의 이본 유형을 인코딩하여 코퍼스를 구축하고, 이를 바탕으로 해밍 거리를 이용하여 각 이본 간의 거리 행렬을 산출하였다. 그다음 산출된 거리 행렬을 다차원 척도법, 계층적 군집 분석을 적용하여 이본의 군집 양상을 시각화하여, 기존에 토끼전 전체 단락을 대상으로 한 군집 분석 연구와 비교하여 '어족회의' 대목의 계열과 계통 특징을 살펴보았다. 그 결과 토끼전 전체 단락을 대상으로 한 군집 분석이 6개의 계열을 이루고 있는 것과는 달리, '어족회의' 대목은 5개의 계열을 이루고 있다는 점과 몇몇 이본의 계열 출입이 있다는 점을 확인할 수 있었다. 본 연구의 성과는 계산에 의한 객관적이고 실증적인 방법으로 이본 간의 상대적 거리 측정하고 계통 분류를 했다는 점과 토끼전 전체를 내용을 대상으로 한 계열 분석과 대비하여 어족회의 대목 계열의 특징을 밝혔다는 데에 있다.

Hydrodynamic Modeling for Discharge Analysis in a Dielectric Medium with the Finite Element Method under Lightning Impulse

  • Lee, Ho-Young;Lee, Se-Hee
    • Journal of Electrical Engineering and Technology
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    • 제6권3호
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    • pp.397-401
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    • 2011
  • The response of lightning impulse voltage was explored in dielectric liquids employing hydrodynamic modeling with three charge carriers using the finite element method. To understand the physical behavior of discharge phenomena in dielectric liquids, the response of step voltage has been extensively studied recently using numerical techniques. That of lightning impulse voltage, however, has rarely been investigated in technical literature. Therefore, in this paper, we tested impulse response with a tip-sphere electrode which is explained in IEC standard #60897 in detail. Electric field-dependent molecular ionization is a common term for the breakdown process, so two ionization factors were tested and compared for selecting a suitable coefficient with the lightning impulse voltage. To stabilize our numerical setup, the artificial diffusion technique was adopted, and finer mesh segmentation was generated along with the axial axis. We found that the velocity from the numerical result agrees with that from the experimental result on lightning impulse breakdown testing in the literature.