Predictive approaches for the UNIX command line: curating and exploiting domain knowledge in semantics deficit data

Singh, Thoudam Doren; Khilji, Abdullah Faiz Ur Rahman; Divyansha,; Singh, Apoorva; Thokchom, Surmila; Bandyopadhyay, Sivaji

doi:10.1007/s11042-020-10109-y

Cited by 3 publications

(1 citation statement)

References 10 publications

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“…The scarcity of reliable information in local languages prompted the use of pretrained resources specific to the Hindi language in this study. [15] In, "A Comprehensive Study on Data-Driven Fake News Detection Methods'', [16] stacking approach was used consisting of 5 Machine Learning methods and 3 Deep Learning methods. Machine Learning models used: Log-Reg, Decision Tree, K-Nearest Neighbour, RF and Support Vector Machines.…”

Section: Literature Reviewmentioning

confidence: 99%

Interactive Web App for Fake News Detection

2023

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In the contemporary era of technology, individuals who utilize mobile phones and laptops have developed a preference for accessing news through online media. News organizations disseminate news and offer confirmation sources. However, the issue at hand is how to authenticate stories and articles shared on social networks such as WhatsApp groups, Facebook pages, Twitter, and other smaller blogs and social networking sites. It is hazardous for society to accept rumours disguised as news, especially in developing nations like India, where it is crucial to prevent rumours and specialize in honest and verified information. Classifying written articles as misleading or deceptive is not easy to automate, and even experts in a specific field must evaluate several factors before rendering a judgment regarding the validity of a message. This project proposes the use of a machine learning approach to automatically classify news articles. This endeavour explores numerous text characteristics that can be employed to differentiate fabricated news content from actual news.

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Section: Literature Reviewmentioning

confidence: 99%

Interactive Web App for Fake News Detection

2023

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A fitting algorithm based on multi-touch gesture for rapid generation of railway line

Nie

Zhang

et al. 2023

ICA

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Human-computer interaction (HCI) technology plays a critically essential role in the computer-aided design of railway line locations. However, the traditional interactive design with a mouse+keyboard cannot well meet the rapid generation requirements of the railway line during scheme discussion. This research presents a fitting algorithm for the rapid generation of railway lines by using a multi-touch gesture algorithm. The fitting method from free hand-drawing lines to satisfied railway lines is proposed. Then the interactive operation hand gestures are defined and implemented into the railway line location design. The hand-drawing lines generated by defined gestures are automatically fitted with the target horizontal line by using the inflection detection algorithm based on Euclidean Distance (ED). Meanwhile, the vertical line can be fitted by a similar algorithm with an extreme point-to-point (EPP) and chord-to-point distance accumulation (CPDA). Moreover, a real-world example verification is carried out. The multi-touch gesture algorithm is applied for the automatic fitting of the railway line. Compared with the traditional interactive methods, the consumption time of railway line generation by using the multi-touch interactive mode is decreased by about 15%. This research provides fundamental support for rapid scheme discussion of railway line generation based on natural HCI, which is well-matched with modern handheld devices, and the requirements of rapid selection as well as the quick comparison of railway line schemes in the early stage of design.

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A Modern Approach to Securing Critical Infrastructure in Energy Transmission Networks: Integration of Cryptographic Mechanisms and Biometric Data

Manowska,

Boros,

Hassan

et al. 2024

Electronics

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Energy security is a crucial issue for political, environmental, and economic reasons. This article presents a modern approach to securing critical infrastructure in energy transmission networks, which are managed by advanced IT systems. This paper focuses on the integration of cryptographic mechanisms with biometric data, providing an additional layer of protection against cyber threats. The discussed solutions enable the protection of management systems in energy transmission networks, enhancing their resilience to cyberattacks. The use of the command-line interface (CLI) in combination with biometrics allows for precise execution of security tasks such as network monitoring, firewall management, and automation of security tasks. This makes these systems more reliable and secure, which is essential for the stability of energy systems.

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Predictive approaches for the UNIX command line: curating and exploiting domain knowledge in semantics deficit data

Cited by 3 publications

References 10 publications

Interactive Web App for Fake News Detection

Interactive Web App for Fake News Detection

A fitting algorithm based on multi-touch gesture for rapid generation of railway line

A Modern Approach to Securing Critical Infrastructure in Energy Transmission Networks: Integration of Cryptographic Mechanisms and Biometric Data

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