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Intellectual capital - An it-based reporting framework

Intellectual capital - An it-based reporting framework

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4th Conference on Professional knowledge Management Experiences and Visions, WM 2007

作者： Nemetz, Martin Karagiannis, Dimitris University of Vienna Faculty of Computer Science Dept. for Knowledge and Business Engineering Brünner Straße 72 1210 Vienna Austria

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Efficient hybrid web recommendations based on Markov clickstream models and implicit search

Efficient hybrid web recommendations based on Markov clickst...

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IEEE/WIC/ACM International Conference on Web Intelligence, WI 2007

作者： Zhang, Zhiyong Nasraoui, Olfa Knowledge Discovery and Web Mining Lab. Dept. of Computer Science and Engineering University of Louisville Louisville KY 40292 United States

ISBN: (纸本)0769530265

In this paper, we present novel methods that combine (1) Markov Models and (2) web page content search techniques to generate web navigation recommendations. For clickstream modeling, both first-order and second-order Markov Models were studied and a compact storage format for Markov transition matrices was used. For content-based search, a search engine was used to obtain similar-content pages for recommendation to compensate for the sparsity of the Markov model and thus improve coverage. Experiments were conducted on real web clickstream logs, and confirmed the efficiency of the proposed methods. © 2007 IEEE.

关键词： Search engines

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An Enhanced Smart Intelligent Detecting and Alerting System for Industrial Gas Leakage using IoT in Sensor Network 5

An Enhanced Smart Intelligent Detecting and Alerting System ...

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5th International Conference on Smart Systems and Inventive Technology, ICSSIT 2023

作者： Senthil, G.A. Suganthi, P. Prabha, R. Madhumathi, M. Prabhu, S. Sridevi, S. Agni College of Technology Dept. of Information Technology Chennai India Sri Sai Ram Institute of Technology Dept. of Electronics and Communication Engineering Chennai India Karpaga Vinayaga College of Engineering and Technology Dept. of Artificial Intelligence and Data Science Chennai India Sri Ramachandra Engineering and Technology Dept. of Computer Science and Engineering Chennai India

ISBN: (纸本)9781665474672

Leakage of any type of gas has emerged as a hazard in recent years, whether in a typical workplace, boiler, a commercial setting, a café, or a canteen, industries natural gas, coal, refinery products, crude oil, cement, electricity, steel, and fertilizers etc. In this article, I proposed a new invention of an IoT-based gas waste monitoring, leak detection, and alerting system. The research extends on the development of such an intelligent system that can intelligently preserve gas, ensure the safety precaution and pre vent accidents. The technique must be connected to the stove. The design incorporates ultrasonic sensors which identify bio gas leakage in circumstance with in square metre is usage area of industries or cooking place. The Proposed work smart intelligence system is cuts off the gas supply using an automated shutting off device. Whenever a gas leak is detected, consumers will be notified through SMS via GSM, location using GPRS, and will be able to resolve the situation as quickly as feasible. The flame sensor in the technology will supervise flame and fire. The buzzer starts to sound when a fire is detected. Aside from that, the system may save data on the cloud. With the help of this cloud storage solution, every user's daily gas use may be traced. Finally, this approach will aid in recognizing per user natural gas consumption. The system has been examined and is capable of monitoring gas loss, evacuation, and sending an SMS notification and location aid to the user. The precipitate demonstrated its usefulness in conserving a considerable amount of domestically squandered gas. © 2023 IEEE.

关键词： Liquefied petroleum gas

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System and methodology for unknown malware attack

System and methodology for unknown malware attack

引用

International Conference on Sustainable Energy and Intelligent Systems, SEISCON 2011

作者： Murugan, S. Kuppusamy, K. CDAC Knowledge Park No 1 Old Madras Road Bangalore India Dept. Of Computer Science and Engineering Alagappa University Karaikudi India

ISBN: (纸本)9789380430003

Intrusion Detection Prevention Systems are increasingly a key part of systems defense. Various approaches to Intrusion Detection prevention are currently being used, but they are relatively ineffective. Artificial Intelligence plays a driving role in security services. This paper proposes a dynamic model Intelligent Intrusion Detection System, based on specific AI approach for intrusion detection. The techniques that are being investigated includes neural networks and fuzzy logic with network profiling, that uses simple data mining techniques to process the network data. The proposed system is a hybrid system that combines anomaly, misuse and host based detection.

关键词： data mining

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A generic E-Iearning engineering framework embracing the semantic web

A generic E-Iearning engineering framework embracing the sem...

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11th International Conference AIMSA 2004 - Artificial Intelligence: Methodology, Systems, and Applications

作者： Lischka, Johannes Karagiannis, Dimitris University of Vienna Inst. for Computer Science and Business Informatics Dept. of Knowledge Engineering Bruenner Strasse 72 A-1210 Vienna Austria

E-Learning has become a serious discipline in IT supported management with the aim of enabling life-long learning. Unfortunately, E-Learning is a bottom-up based technical approach and the vision of life-long learning is not yet reached, because it demands the existence of resource pools as a basis enabling cross referencing of topics, skills and all other resources within an organizational memory. Fortunately, new technologies coming from the Semantic Web and Web-Services communities will be able to overcome some of the hindering technical obstacles providing interoperability between different platforms and programming paradigms so that resources can be personalized and presented on arbitrary clients. This paper embraces these technologies and presents a generic E-Learning engineering approach that fits them into a top-down IT-supported management framework so that business goals may be transformed into a technical environment. Furthermore, this approach also sets grounds for closing the gap to E-Business (e.g. Performance Management like the Balanced Scorecard). © Springer-Verlag Berlin Heidelberg 2004.

关键词： Semantics

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Brain-Powered Vehicles for Individuals with Disabilities Leveraging AI 4

Brain-Powered Vehicles for Individuals with Disabilities Lev...

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4th International Conference on Technological Advancements in Computational sciences, ICTACS 2024

作者： Jaison, T. Jisna Thambi, Priyanka E. Pinheiro, Nikita Scms School of Engineering and Technology Dept. of Artificial Intelligence & Data Science Karukutty India Kalamasery India St. Paul's College Dept. of Computer Science Kalamasery India

ISBN: (纸本)9798350387490

This paper provides a novel method for enhancing mobility and independence for people with disabilities via integrating Brain-pc interface (BCI) generation with artificial intelligence (AI) for vehicle control. The proposed device permits customers to control important vehicle features which includes steerage, braking, and acceleration the usage of their Brain indicators, captured through non-invasive EEG sensors. Preliminary checking out with diverse person agencies established an outstanding accuracy price of over ninety% in deciphering person intentions and efficaciously controlling the automobile. The device adapts to person neural styles, ensuring personalized and dynamic control, and extensively improves person autonomy and self-assurance. However, demanding situations which include sign noise, user variability, and long-time period device stability stay. This studies demonstrates the capacity for BCIs and AI to revolutionize transportation for individuals with disabilities, supplying an exceptional level of independence. Future trends will focus on improving signal clarity, improving machine stability, and addressing regulatory issues to make sure safe, real-world application. © 2024 IEEE.

关键词： Neurons

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Navigation Assistance for the Visually Impaired: An Image Segmentation-based Web Application

Navigation Assistance for the Visually Impaired: An Image Se...

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17th INDIACom;2023 10th International Conference on Computing for Sustainable Global Development, INDIACom 2023

作者： D'Mello, Sejal Prajapati, Vivek Vyas, Hirenkumar Arora, Naveen Mishra, Arpit Vidyavardhini's College of Engineering and Technology Dept. of Artificial Intelligence and Data Science Mumbai India

ISBN: (纸本)9789380544472

The objective of this paper is to create a mobile app that can aid visually impaired people in navigating outdoor surroundings through floor segmentation technique. The app uses phone's camera to capture live video of the user's environment, which will be analyzed to identify and segment the floor area. As a result, the user will be able to obtain audio information regarding their location and distance from nearby objects or obstacles. This proposed system is a practical and low-cost solution that can be effortlessly incorporated into existing smartphone technology, providing an easy-to-use and accessible tool for the visually impaired to navigate through outdoor environments. © 2023 Bharati Vidyapeeth, New Delhi.

关键词： Floors

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Explainable AI for Enhanced Intrusion Detection Systems 3

Explainable AI for Enhanced Intrusion Detection Systems

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3rd International Conference for Advancement in Technology, ICONAT 2024

作者： Ananya, G. Siri, N. Kodipalli, Ashwini Rao, Trupthi Global Academy of Technology Dept. of Computer Science and Engineering Karnataka Bengaluru India Global Academy of Technology Dept. of Electronic and Communication Engineering Karnataka Bengaluru India Global Academy of Technology Dept. of Artificial Intelligence & Data Science Karnataka Bengaluru India

ISBN: (纸本)9798350354171

As everything is turning digital there is a hike in the invasion of digital space, because of which advanced tools are needed. One such tool is the Intrusion Detection System (IDS). In this work, we have tried to detect and classify suspicious connections accurately. This is done by incorporating advanced computing into Intrusion Detection Systems. To achieve this, we have used the Coburg Intrusion Detection dataset. To achieve this, we used the Coburg intrusion detection dataset. We investigate the effectiveness of Single Classifiers and Bagging and Boosting in this context. We proposed a four-stage Ensemble model to classify the connections using its attributes. The proposed model uses four Single Classification models: Logistic Regression, KNN, Decision Tree, and SVM. Before applying the algorithms, the data was Preprocessed. Later, the models were hyper-tuned to increase the accuracy. The results showed that Random Forest outperforms other single classifiers and machine learning algorithms, with a mean accuracy of 99.99%, a precision of 99.99%, and an F1-score of 99.99%. Furthermore, as models are usually hard to understand by using Explainable AI we can increase the transparency of the model. Explainable AI techniques are used to make the advanced computing models reliable and more understandable. This study aims to develop advanced and dependable intrusion detection systems. © 2024 IEEE.

关键词： Network intrusion

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ADN-BERT: Attention-Based Deep Network Model Using BERT for Sarcasm Classification 11th

ADN-BERT: Attention-Based Deep Network Model Using BERT for...

引用

11th International Conference on Frontiers of Intelligent Computing: Theory and Applications, FICTA 2023

作者： Mishra, Pallavi Sharma, Omisha Panda, Sandeep Kumar Dept. of Computer Science and Engineering ICFAI Foundation for Higher Education Telangana Hyderabad India Dept. of Artificial Intelligence and Data Science ICFAI Foundation for Higher Education Telangana Hyderabad India

ISBN: (纸本)9789819967018

Sarcasm classification has gained popularity among researchers due to its complexity and implicit form of context representation. The most challenging aspect of sarcasm identification is to understand the exact context behind the statement. Therefore, a context-based model helps solve this critical task in the research domain. The importance of sarcasm detection and classification is primarily helpful for society to avoid misinterpreting statements or reviews that could affect one’s mental condition and perception. Unfortunately, to increase the retention level of audience toward media news, often the media incorporate sarcasm in their news headlines. However, people find it difficult to detect sarcasm in news headlines, resulting in them having a false impression of the news and spreading it to their surroundings. Therefore, it has become a significant concern among the society to develop a sense of understanding of the hidden context behind the statement before making any type of impression and judgment. In this paper, we have focused on this problem statement and developed a novel technique called an Attention-based deep network model using Bidirectional Encoder Representations from Transformers (BERT) i.e., ADN-BERT to classify news headlines into sarcastic and non-sarcastic categories. The News Headlines dataset is collected from Kaggle, and we have incorporated text augmentation to increase the size of the dataset to yield better results and accuracy. The evaluation metrics used in our study include accuracy, recall, precision, and F1-score. Our proposed model (ADN-BERT) has outperformed the recent state-of-the-art techniques with 94.1% accuracy, 95.2% recall, 94.5% precision, and 94.8% *** check and approve the edits made in the chapter title and running ***. ApprovedPlease check and confirm if the author names and initials are ***, correct. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Sentiment analysis

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Max-Min Fair 3D Trajectory Planning for Solar-Powered UAV-Assisted data Collection

Max-Min Fair 3D Trajectory Planning for Solar-Powered UAV-As...

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2022 IEEE/CIC International Conference on Communications in China, ICCC 2022

作者： Sun, Chao Xiong, Xinxuan Ni, Wei Ohtsuki, Tomoaki Wang, Xin Fudan University Dept. of Communication Science and Engineering Shanghai China Data61 Business Unit Sydney Australia Keio University Dept. of Information and Computer Science Yokohama Japan

ISBN: (数字)9781665484800

ISBN: (纸本)9781665484800

This paper presents a new solar-powered fixed-wing unmanned aerial vehicle (UAV)-assisted data collection technique, where a fixed-wing UAV harvests solar energy to fly and collect data from smart devices (SDs). The minimum of the data upload-ed from any of the SDs is maximized by optimizing the UAV's three-dimensional (3D) trajectory. The key idea is that we develop variable substitution and successive convex approximation (SCA) techniques to convexify the nonconvex data transmission, UAV energy consumption and mobility constraints, as well as the nonconvex energy harvesting constraint. The proposed algorithm guarantees a locally optimal solution satisfying the Karush-Kuhn-Tucker (KKT) conditions. Another important aspect is that an effective set of approximation parameters are identified for accurate approximation of the solar energy harvesting at relatively low altitudes, contributing to the design of efficient 3D trajectories balancing energy harvesting and data collection. Numerical results show that the 3D flight increases uploaded data by 59% as compared to the two-dimensional (2D) flight. © 2022 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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