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Towards building a semantic grid for E-learning

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2006年 4025卷 128-137页

作者： Tian, Wenya Chen, Huajun Information Technology Department Zhejiang Economic and Trade Polytechnic Hangzhou310018 China Grid Computing Lab College of Computer Science Zhejiang University Hangzhou310027 China

ISBN: (纸本)3540351264

In an E-learning scenario, educational resources, such as course documents, videos, test-bases, courseware, and teacher information etc., are shared across different schools. DartGrid is built upon several techniques from both Semantic web and Grid research areas, and is intended to offer a semantic grid toolkit for data integration. In this paper, a Semantic Grid for E-leaning based on DartGrid is introduced, and it provides a Semantic-based distributed infrastructure for E-learning resource sharing. We explore the essential and fundamental roles played by RDF semantics for e-learning, and implement a set of semantically enabled tools and grid services for E-learning such as semantic browser, ontology service, semantic query service, and semantic registration service. © IFIP international Federation for information processing 2006.

关键词： E-learning

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Enhancing Code Completion with Position Embedding of Abstract Syntax Tree

Enhancing Code Completion with Position Embedding of Abstrac...

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Frontiers technology of information and Computer (ICFTIC), IEEE international conference on

作者： Jiahao Li Junyu Lu Linbo Zhu AHU-IAI AI Joint Laboratory Hefei Comprehensive National Science Center Anhui University Institute of Artificial Intelligence Hefei China School of Data Science University of Science and Technology of China Hefei China Institute of Artificial Intelligence Hefei Comprehensive National Science Center Hefei China

ISBN: (数字)9798331541750

ISBN: (纸本)9798331541767

Code completion is a crucial feature in integrated development environments (IDEs) that enhances both the efficiency and experience of developers. By analyzing the context of preceding code, real-time suggestions can be provided, significantly aiding developers in their work. Recent research has highlighted that the abstract syntax tree (AST) contains rich syntactic and structural information, which can assist deep learning models in better understanding code. As a result, AST-based code completion methods have garnered substantial attention. However, existing approaches often overlook the positional information of nodes within the AST, limiting the model's ability to capture structural relationships in the code. this paper explores the positional relationships between AST nodes and proposes a tree structure position embedding method tailored to the AST. Experimental results validate that this position embedding significantly improves the performance of code completion.

关键词： Deep learning Codes Limiting Computational modeling Syntactics Real-time systems Natural language processing

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A Stylometric Dataset for Bengali Poems 22

A Stylometric Dataset for Bengali Poems

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Proceedings of the 2022 6th international conference on Natural language processing and information Retrieval

作者： Mirza Kamrul Bashar Shuhan Rupasree Dey Sourav Saha Md Shafa Ul Anjum Tarannum Shaila Zaman Software Research and Engineering bKash Limited Bangladesh Computer Science Oregon State University United States of America Business Administration Shahjalal University of Science and Technology Bangladesh Engineering Progoti Systems Limited Bangladesh Computer & Information Science SUNY Polytechnic Institute United States of America

ISBN: (纸本)9781450397629

Poetry is a form of literature that conveys feelings using different styles, aesthetics, and rhythms. the Bengali language has an enriched collection of poems. Every poet has an individual style of expressing their thoughts and emotions. However, stylometric research in this branch of the Bengali language is still in its early stage of development. In this paper, we have presented a stylometric dataset, which has 6,070 poems of 137 poets stored in the textual format. To the best of our knowledge, this is the first stylometric dataset for Bengali poems which will add an extra dimension to the expanding research arena of the Bengali language. To explore the usability of this dataset, we developed poem genre classifiers using deep learning that can classify these poems. Performance analysis of some deep learning classifiers has been presented in addition to classification. the classifiers include GRU and CNN. Among these two, GRU showed better performance by 91.48 in terms of the F1-score. the dataset will be publicly available at https://***/shuhanmirza/Bengali-Poem-Dataset after publishing this article.

关键词： Bengali Poems Corpora Datasets language Resources Natural language processing Stylometric Datasets

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A Secured Communication in Watermarking using Fast Walsh Hadamard Transformation in Image processing

A Secured Communication in Watermarking using Fast Walsh Had...

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international conference of Electronics, Communication and Aerospace technology (ICECA)

作者： K. Premkumar H. Twinky S. Naveen M. Kathiresan R. Aravind SRMIST Ramapuram SRMIST

ISBN: (纸本)9781665482721

E-commerce, or electronic commerce, refers to the purchasing and selling of goods and services conducted over electronic systems such as the internet and other computer networks. Consequently, there is a pressing need to bolster the security of data transmission over the internet to accommodate the expansion of e-commerce applications on the World Wide web. Data encryption and information masking techniques were introduced and developed to secure these applications' data. the creation of digital picture watermarking schemes is the subject of this thesis. Our main emphasis in this thesis is on the advancements made possible by the Fast Walsh Hadamard Transformation (FWHT). the primary result of this study is a proposed method for implementing FWHT in digital image watermarking. If a picture is described at multiple resolutions, its decoding can proceed in stages, starting at a lower resolution and working its way up to a higher one. In order to better analyse an image, the FWHT separates it into high- and low-frequency components. the edge components are described in the high frequency portion, while the low frequency portion is further divided into high and low frequency segments. Since the human visual system is more insensitive to abrupt changes in edge contrast, low frequency components are typically employed for watermarking. Several metrics, including Mean Square Error (MSE), Peak Signal-to-Noise Ratio (PSNR), and Structural Similarity Index Metric, were used to compare the efficacy of various watermarking methods (SSIM). the aforesaid analysis forms the basis for applying Level-2 and FWHT to enhance the image quality characteristics. It is determined which of these FWHT produced the best outcomes by comparing the others. the outcome demonstrates that the extracted watermark is just as easy to recognize as the original.

关键词： Measurement Image quality PSNR Image resolution Digital images Image edge detection Watermarking

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A Study to Classify Virus Genome through Analyzing DNA Sequences Using Transformer Model

A Study to Classify Virus Genome Through Analyzing DNA Seque...

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international conference on Electrical Engineering and information & Communication technology (ICEEICT)

作者： Tasnim Binte Shiraj Mohammad Abu Yousuf Department of Information and Communication Technology Bangladesh University of Professionals Dhaka Bangladesh Institute of Information Technology Jahangirnagar University Savar Bangladesh

ISBN: (数字)9798350385779

ISBN: (纸本)9798350385786

In a generic computational environment for biological data processing, classifying DNA sequences is an important task. In recent times, a range of machine learning methods have been successfully applied to implement this task. Still, the hardest part of the process is choosing the features. the most popular representations exacerbate the massive dimensionality issue, because sequences lack unique features. Due to the pathogenic virus's high rate of transmission, early detection and accurate identification are essential for the treatment. It is challenging to predict though, because this virus's polymorphic nature enables it to adapt and survive in a variety of environment. Deep learning (DL) models have recently developed the ability to automatically extract characteristics from the input sequences. Previously, CNN-Bidirectional LSTM and CNN-LSTM structures with Label and K-mer encoding, Random Forests and Gradient Boosting Method, and Linear Discriminant Analysis have been utilized for DNA sequence classification. In this paper, we investigate the impact of a popular and well-established language model, namely Transformer (BERT) which uses self-attention mechanism, to alter the procedure to understand underlying hidden patterns of the virus DNA sequences and correctly classify them.

关键词： Pathogens Computer viruses Biological system modeling DNA Transformers Encoding Convolutional neural networks

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Model-driven development of context-aware services

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Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2006年 4025卷 213-227页

作者： Almeida, João Paulo A. Iacob, Maria-Eugenia Jonkers, Henk Quartel, Dick Telematica Instituut P.O. Box 589 Enschede7500 Netherlands Centre for Telematics and Information Technology University of Twente P.O. Box 217 Enschede7500 Netherlands

ISBN: (纸本)3540351264

In this paper, we define a model-driven design trajectory for context aware services consisting of three levels of models with different degrees of abstraction and platform independence. the models at the highest level of platform independence describe the behaviour of a context-aware service and its environment from an integrated perspective. the models at the intermediate level describe abstract components, which realize the context-aware service in terms of a service-oriented abstract platform. At the lowest level, the realization of a context-aware service is described in terms of specific target technologies, such as web Services, BPEL and Parlay technologies. Our approach allows service designers to concentrate their efforts on the services they intend to create and offer, by facilitating the handling of context information and automating design steps through model transformation. In addition, our approach enables the reuse of platform-independent models for different target platforms. © IFIP international Federation for information processing 2006.

关键词： web services

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Automatic Generation of GIM Data Audit Rules Based on Sentence Embedding Vectors 23

Automatic Generation of GIM Data Audit Rules Based on Senten...

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Proceedings of the 6th international conference on information Technologies and Electrical Engineering

作者： Bing Wu Yuanbin Song Jinhao Cao Institute of Economics and Technology State Grid Zhejiang Electric Power Co. Ltd. China School of Naval Architecture Ocean & Civil Engineering Shanghai Jiao Tong University China

ISBN: (纸本)9798400708299

the digital design results of power substations establish the foundation for their running and maintaining. Currently, the digital design of substations is delivered in the format of Grid information Model (GIM), an alternative Building information Modeling (BIM) format for describing power grid infrastructure in China. Since the correctness, compliance, and consistency of GIM data are necessary conditions for information sharing and business decision support, the GIM data must be audited before sharing among the stakeholders. the traditional manual review of GIM data is too inefficient and costly to execute, and thus the power grid industry seeks automatic review approaches. However, one challenge for automated auditing of GIM data is the lack of auditing rules. In order to establish such a rule base for GIM data auditing, this study first categorizes the audit rules, and proposes an XML encoding method for the audit rules. Meanwhile, the methodology of converting the rules described in natural language into XML is also rules proposed using the SBERT model. the application of the developed tool is demonstrated and verified through case studies.

关键词： Controlled natural language Grid information model Model audit Natural language processing Rule representation Sentence BERT

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Utilizing Modern Large language Models (LLM) for Financial Trend Analysis and Digest Creation

Utilizing Modern Large Language Models (LLM) for Financial T...

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international conference on Control Systems, Mathematical Modelling, Automation and Energy Efficiency (SUMMA)

作者： Andrei Lazarev Dmitrii Sedov Department of Control and Applied Mathematics Moscow Institute of Physics and Technology Moscow Russia Institute for Statistical Studies and Economics of Knowledge HSE University Moscow Russia

ISBN: (数字)9798331532178

ISBN: (纸本)9798331532185

the exponential growth of information presents a significant challenge for researchers and professionals seeking to remain at the forefront of their fields and this paper introduces an innovative framework for automatically generating insightful financial digests using the power of Large language Models (LLMs), specifically Google's Gemini Pro. By leveraging a combination of data extraction from OpenAlex, strategic prompt engineering, and LLM-driven analysis, we demonstrate the automated example of creating a comprehensive digests that generalize key findings, identify emerging trends. this approach addresses the limitations of traditional analysis methods, enabling the efficient processing of vast amounts of unstructured data and the delivery of actionable insights in an easily digestible format. this paper describes how LLMs work in simple words and how we can use their power to help researchers and scholars save their time and stay informed about current trends. Our study includes step-by-step process, from data acquisition and JSON construction to interaction with Gemini and the automated generation of PDF reports, including a link to the project's Github repository for broader accessibility and further development.

关键词： Navigation Large language models Finance Market research technology forecasting Mathematical models Internet Prompt engineering Data mining Software development management

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A NEW PERCEPTUAL AND ADAPTIVE QUANTIZATION MEthOD FOR LINE SPECTRAL FREQUENCY PARAMETERS BASED ON NOISE-TO-MASK RATIO

A NEW PERCEPTUAL AND ADAPTIVE QUANTIZATION METHOD FOR LINE S...

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6～(th) international conference on Spoken language processing

作者： Woo-Jin Han Yung-Hwan Oh Dept. of Computer Science Korea Advanced Institute of Science and Technology Kusong-dong Yusong-ku Taejon 305-701 Korea Dept. of Computer Science Korea Advanced Institute of Science and Technology Kusong-dong Yusong-ku Taejon 305-701 Korea

In this paper, a new quantization method for line spectral frequency (LSF) parameters based on the perceptually weighted distance measure is presented. We derive the proposed distance measure from the definition of average noise-to-mask ratio (NMR) and show that it can be reduced to the form of weighted LSF distance measure having perceptually meaningful weights. We also propose an adaptive quantization scheme for LSF parameters. In our scheme, the bit rates are minimized by choosing the bit configuration wilh the lowest total bits whose maximum NMR has negative vaiuc. By jointly combining the proposed distance measure and the adaptive bit allocation scheme, the proposed system requires only 862 bps for obtaining 94% perceptually transparent frames, while the conventional systems produce 89% at even 1800 bps.

关键词： LSF A NEW PERCEPTUAL AND ADAPTIVE QUANTIZATION MEthOD FOR LINE SPECTRAL FREQUENCY PARAMETERS BASED ON NOISE-TO-MASK RATIO

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Sanitization of Sepsis News Sentences with the help of Paraphrasing 22

Sanitization of Sepsis News Sentences with the help of Parap...

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Proceedings of the 2022 6th international conference on Natural language processing and information Retrieval

作者： Soma Das Sanjay Chatterji CSE dept Indian Institute of Information Technology Kalyani Research Scholar India and CSE dept Institute of Engineering & Management Assistant Professor India CSE dept Indian Institute of Information Technology Kalyani Assistant Professor India

ISBN: (纸本)9781450397629

the arrival of the internet in the late twentieth century, followed by social media in the twenty-first century, greatly increased the hazards of misinformation, disinformation, propaganda, and hoaxes. New ways of writing news have emerged to insert bias intelligently without making the news a piece of fake news. the correct news is usually manipulated to benefit a person, a group of individuals, a political party, or other factors, or changed to reflect sentiment or prominence. It is a challenging task to Sanitize such news content before presenting it to the reader. In this paper, we deal with the problematic English news sentences defined as Septic sentences. We have identified the Septic sentences and their Septic phrases using Machine Learning algorithms. Sanitization is the process of converting a Septic sentence into a Pure sentence. We illustrate the process of Sanitization in this paper with the help of paraphrasing. the model is able to Sanitize 76% of Septic sentences.

关键词： English News Paraphrasing SEPSIS Sanitization Septic Sentence

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