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NLP Based Question Answering System 7

NLP Based Question Answering System

引用

2023 7th international conference On Computing, Communication, Control And Automation, ICCUBEA 2023

作者： Patil, Rahul Patil, Promod D. Joshi, Yadneya Khandelwal, Shivam Nalawade, Sarthak Palve, Bhagwat Pimpri Chinchwad College of Engineering Pune India D y Patil Institute of Technology Pune India

ISBN: (纸本)9798350304268

The proliferation of data in various domains has increased the significance of Question Answering systems (QAS), which utilize Natural Language Processing (NLP) techniques to comprehend and respond to natural language queries. This review paper provides a comprehensive overview of recent advancements in QAS that employ NLP techniques. However, this thesis concentrates on specific QA scenarios where the answer is explicitly present in the text source. The objective is to build a QA system that can extract answers from plain text sources quickly, precisely, and accurately, using only a single sentence or a fragment of a sentence. The paper discusses the obstacles involved in creating QAS and how NLP techniques can overcome them. The paper proposes a question answering system that combines extractive and abstractive summarization methods to produce brief and accurate answers to user questions. The system uses keyword extraction and classification to identify pertinent information from a collection of documents and then combines extractive and abstractive summarization approaches to create a comprehensive and concise response. The research findings indicate that the proposed system has significant potential to enhance the effectiveness and efficiency of question answering systems in a range of applications. © 2023 IEEE.

关键词： API knowledge graphs Natural Language Processing Summarization

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An Overview of Making Decisions on Medical Problems Using Fuzzy Cognitive Maps 14

An Overview of Making Decisions on Medical Problems Using Fu...

引用

14th international conference on Information, Intelligence, systems and Applications, IISA 2023

作者： Krimpas, George A. Krimpas, Nikolaos A Groumpos, Peter P. University of Patras Department of Electrical Engineering Patras Greece

ISBN: (纸本)9798350318067

This paper provides an overview of how fuzzy logic can be applied to make decisions on medical problems. Fuzzy logic is a mathematical framework that can handle uncertainty and imprecision, making it a useful tool in the field of medicine. The process of using fuzzy logic to make medical decisions involves defining the problem, identifying relevant variables, assigning membership functions, defining rules, fuzzification, inference, and defuzzification. Fuzzy logic can be used to make decisions related to diagnosis, treatment, risk assessment, and prognosis. While fuzzy logic has several advantages, including the ability to handle uncertainty, it requires a high level of expertise to develop accurate models. Overall, fuzzy logic can provide valuable insights for medical professionals making decisions in situations where there is no clear-cut answer. We also highlight the advantages of FCMs in medicine, including their ability to model complex relationships and their ability to handle uncertainty and imprecision. They also discuss the limitations of FCMs, such as the difficulty in obtaining reliable data and the need for expert knowledge to develop accurate models. The methods presented can be used as a guideline for constructing FCMs in medical applications, while the applications discussed can serve as a source of inspiration for future research. © 2023 IEEE.

关键词： Decision making

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Adversarial learning for De-Identification of Medical-Records

Adversarial learning for De-Identification of Medical-Record...

引用

knowledge engineering and Communication systems (ICKECS), international conference on

作者： H.S Anupama K.R Pradeep M Niranjanamurthy V Kanthraju Cb Darshan Svn Murthy Department of Artificial Intelligence and Machine Learning BMS Institute of Technology and Management Bengaluru Karnataka India Dept. of CSE SJC Institute of Technology Chickballapur Karnataka India

ISBN: (数字)9798350359688

ISBN: (纸本)9798350359695

Medical records may exclusively be disclosed for the purpose of research. Medical researchers can only access the medical records of patient if they are de-identified because of data protection and privacy laws. De-Identified data means the process of removing or masking protected health information (PHI) in order to reduce the risk that subjects identify be connected with data. Automatic de-identification classifiers The goal is to make it affordable to de-identify large amounts of medical records. Current classifiers are trained on costly manually pseudonymized records from a single source, limiting their applicability to new data sources. To improve this, we need larger, more diverse datasets for training more versatile de-identification tools. We propose a method to convert medical text into a secure format without the need for pseudonymization, making it easier to share training data securely.

关键词： Training knowledge engineering Deep learning Privacy Limiting Law Soft sensors

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Artificial Intelligence in Maximizing Product Quality in Automotive Industry: A Case on a South African Tier Two manufacturing Processes

Artificial Intelligence in Maximizing Product Quality in Aut...

引用

international conference on Intelligent System and knowledge engineering, ISKE

作者： Thobile Lungile Mbatha Ndala Yves Mulongo Faculty of Engineering and The Built Enviroment University of Johannesburg South Africa

Over the years, the introduction of Artificial Intelligence has resulted in better process improvements in a variety of industries. Most processes in the automotive industry have adopted Artificial Intelligence as part of their daily operations; however, in tier 2 automotive manufacturers, most of the machines used rely on human interaction for certain things, leaving room for human error and non-conformities. This paper examines tier 2 manufacturers and their use of artificial intelligence machines to ensure better products in parts produced and supplied to tier 1 and some Original Equipment Manufacturers (OEM).

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Anti-Packet-Loss Encrypted Traffic Classification via Masked Autoencoder 18th

Anti-Packet-Loss Encrypted Traffic Classification via Maske...

引用

18th international conference on Wireless Artificial Intelligent Computing systems and Applications, WASA 2024

作者： Yang, Chen Guo, Li Gu, Zheyuan Gou, Gaopeng Lin, Xinjie Xiong, Gang Guan, Yangyang Institute of Information Engineering Chinese Academy of Sciences Beijing China School of Cyber Security University of Chinese Academy of Sciences Beijing China

ISBN: (纸本)9783031714634

Encrypted traffic classification is an important technique for network management and network security assurance. Current mainstream methods utilize machine learning and deep learning techniques for classification, and train models with complete data pre-collected in experimental environments to achieve excellent classification performance. However, real network environments are widely affected by packet loss, which causes traffic data to exhibit a different distribution compared to the training and negatively impacts existing methods. To address this problem, in this paper, we propose APMA, an Anti-Packet-loss encrypted traffic classification method based on Masked Autoencoder, which utilizes two traffic-specific mask pre-training tasks to extract generalized knowledge from large-scale unlabeled traffic, and simulates packet loss to learn robust traffic representations that are applicable to different network environments. Extensive evaluations show that APMA can be applied to a variety of classification scenarios and network environments, achieving over 90% classification accuracy even at 15% packet loss. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Packet loss

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Revolution on Traditional TRIZ Towards DIKWP-TRIZ for Artificial Consciousness Innovation

Revolution on Traditional TRIZ Towards DIKWP-TRIZ for Artifi...

引用

data, Information, knowledge and Wisdom (DIKW), IEEE international conference on

作者： Shiming Gong Yucong Duan Erxiang Dou Zaiwen Feng Hainan University China Peking University China Huazhong Agricultural University China

ISBN: (数字)9798331540548

ISBN: (纸本)9798331540555

Traditional TRIZ (Theory of Inventive Problem Solving) is a systematic method widely used in technical and engineering fields. However, it shows limitations when addressing complex issues such as modern data management, information processing, knowledge integration, and ethical decision-making. This paper proposes the DIKWP-TRIZ model, which combines TRIZ with the DIKWP (data, Information, knowledge, Wisdom, Purpose) framework, introducing new principles and methods to enhance the innovation and problem-solving capabilities of AC systems. Compared to traditional TRIZ, DIKWP-TRIZ demonstrates significant advantages in multidimensional cognitive processing, semantic transformation, and purpose-driven innovation. This paper provides a detailed comparison between DIKWP-TRIZ and traditional TRIZ in terms of coverage completeness and redundancy issues, offering new insights and practical guidance for innovation in complex cognitive systems.

关键词： Technological innovation Ethics Systematics Semantics Redundancy Decision making Information processing data models Problem-solving Cognitive systems

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Optimization of Operating Parameters for Laser Shock Peening Surface Treatment on Components Made from Nickel-Based Super-Alloy INCONEL 718 10th

Optimization of Operating Parameters for Laser Shock Peening...

引用

10th international conference on Design and Modeling of Mechanical systems (CMSM)

作者： Frija, Mounir Dali, Taha Ayeb, Manel Fathallah, Raouf Univ Sousse Inst Appl Sci & Technol Sousse ISSATSo Sousse Tunisia Minist Natl Def Air Force Borj El Amri Aviat Sch Borj El Amri Tunisia Univ Sousse Natl Engn Sch Sousse ENISo Sousse Tunisia Unit Mech Prod Engn & Mat UGPMM UR17ES43 BP 1173 Sfax 3038 Tunisia

ISBN: (纸本)9783031650062;9783031650079

This study is focused on the optimization of laser shock surface treatment for components made from the Nickel-based super alloy INCONEL718. The objective is to enhance the efficiency and effectiveness of this treatment process by leveraging the Design of Experiments (DoE) methodology. In our investigation, we delve into understanding the intricate relationship between the various treatment parameters and the distinct effects they induce during the process. By isolating and examining each parameter's influence on the outcomes, we aim to identify the critical factors that significantly impact the results. This systematic analysis allows us to pinpoint the optimal settings for laser shock treatment, thus minimizing waste and maximizing performance. Furthermore, a key aspect of this study involves the development of empirical mathematical models to approximate the results of numerical simulations. These mathematical formulations serve as valuable tools for aeronautical engineers tasked with modeling laser shock treatment. By translating complex simulation data into practical and actionable mathematical expressions, engineers can more accurately predict the outcomes of laser shock peening surface treatment under varying conditions. The integration of meticulous experimental design, statistical analysis, and empirical modeling offers a holistic approach to optimizing laser shock treatment. The findings from this research hold promise for refining the accuracy and dependability of this vital process in manufacturing components with INCONEL 718, thereby providing valuable advancements for the aerospace industry and its associated domains.

关键词： Laser Sock Peening INCONEL 718 Optimization Design of Experiments (DoE) Numerical simulations Aeronautical engineering

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Dual-Modeling Decouple Distillation for Unsupervised Anomaly Detection 24

Dual-Modeling Decouple Distillation for Unsupervised Anomaly...

引用

32nd ACM international conference on Multimedia, MM 2024

作者： Liu, Xinyue Wang, Jianyuan Leng, Biao Zhang, Shuo School of Computer Science and Engineering Beihang University Beijing China Key Laboratory of Intelligent Bionic Unmanned Systems Ministry of Education School of Intelligence Science and Technology University of Science and Technology Beijing Beijing China Beijing Key Lab of Traffic Data Analysis and Mining School of Computer & Technology Beijing Jiaotong University Beijing China

ISBN: (纸本)9798400706868

knowledge distillation based on student-teacher network is one of the mainstream solution paradigms for the challenging unsupervised Anomaly Detection task, utilizing the difference in representation capabilities of the teacher and student networks to implement anomaly localization. However, over-generalization of the student network to the teacher network may lead to negligible differences in representation capabilities of anomaly, thus affecting the detection effectiveness. Existing methods address the possible over-generalization by using differentiated students and teachers from the structural perspective or explicitly expanding distilled information from the content perspective, which inevitably results in an increased likelihood of underfitting of the student network and poor anomaly detection capabilities in anomaly center or edge. In this paper, we propose Dual-Modeling Decouple Distillation (DMDD) for the unsupervised Anomaly Detection. In DMDD, a Decouple Student-Teacher Network is proposed to decouple the initial student features into normality and abnormality features. We further introduce Dual-Modeling Distillation based on normal-anomalous image pairs, fitting normality features of anomalous image and the teacher features of the corresponding normal image, widening the distance between abnormality features and the teacher features in anomalous regions. Synthesizing these two distillation ideas, we achieve anomaly detection which focuses on both edge and center of anomaly. Finally, a Multi-perception Segmentation Network is proposed to achieve focused anomaly map fusion based on multiple attention. Experimental results on MVTec AD show that DMDD surpasses SOTA localization performance of previous knowledge distillation-based methods, reaching 98.85% on pixel-level AUC and 96.13% on PRO. © 2024 ACM.

关键词： Students

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Social Media Text to Formal Representation: A knowledge Graph Approach 9

Social Media Text to Formal Representation: A Knowledge Grap...

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9th international conference on Advanced Computing and Communication systems, ICACCS 2023

作者： Kommineni, Yaswanth Phani Somanchi, Srilekha Pavan Kumar, Boina Sai Ladani, Yash Nair, Lekshmi S Amrita Vishwa Vidyapeetham Amrita School of Computing Department of Computer Science and Engineering Amritapuri India

ISBN: (纸本)9798350397376

Social media is an online platform where users freely share their views on various topics. By sharing their views, they come to a mutual agreement or disagreement with other users' views. Users are quite active on social media and the number of users is growing exponentially with time. This leads to an abundance of data available through social media. This data helps us in curating different research problems. One such research problem can be finding similarities between users by analyzing user data. data on social media is available in many forms like textual posts, comments, likes, shares, etc. Users often tend to express their diversity of opinions widely through comments on social media. Many opinionated and active users on social media are found in the comments section under a post. Hence, comments play a major role in determining similarity in user judgment about a topic. Likewise, people liking a post is also an essential feature in finding similarities between users. People with similar opinions tend to like posts of a specific type. This paper talks about how comments, textual posts, and likes for comments can be combined to form something called a keyword or a tag. These tags that are extracted from user data are further used in building a tag network. The tag network is used to make communities of users with similar interests. User grouping can also be done based on these extracted tags and comments under the posts. The proposed methods in this paper to achieve the above-mentioned are TF-IDF (Term frequency-inverse document frequency) followed by the TextRank algorithm. © 2023 IEEE.

关键词： Social networking (online)

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An Analysis of Duckworth-Lewis-Stern Method in the Context of Interrupted Limited over Cricket Matches

An Analysis of Duckworth-Lewis-Stern Method in the Context o...

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international conference on data Analytics and Insights, ICDAI 2023

作者： Hazra, Sudipta Chatterjee, Siddhartha Mandal, Ankita Sarkar, Manali Mandal, Bijoy Kumar NSHM Knowledge Campus West Bengal Durgapur India Institute of Engineering & Management West Bengal Kolkata India

ISBN: (纸本)9789819938773

This study examines the Duckworth-Lewis-Stern method as a way for resetting goals in cricket games that are interrupted and is intended for limited over cricket. An alternative resource table is offered after an examination of the Duckworth-Lewis table. A resource table may be monotonous in the columns and rows that indicates overs and wickets, respectively. The usage of the Duckworth-Lewis-Stern method in international cricket matches is the topic of discussion. This ensures that if a match gets shortened, neither of the teams will be affected, and is thus significant. Even in competitions with a reserve day, it is always favoured if a result can be attained utilizing the "rain-rule". DLS method helps in any rain interrupted match even if multiple interruption in various times in either inning or in both innings, requiring only a particular data table and a handheld calculator. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Rain

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