Titlebook: Innovative Computing and Communications; Proceedings of ICICC Aboul Ella Hassanien,Sameer Anand,Prabhat Kumar Conference proceedings 2024 T

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Kartik Rajput,Manjesh Singh,Arjun Rawat,Raman Tyagi,Jolly Parikh,Rachna Jainion and local explainability, to generate test cases effectively. We further address the problem of localizing individual discrimination failures required for effective model debugging. We introduce a notion called Region of Individual Discrimination or RID, which is an interpretable region in the f

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Ayushman Pranav,Akshat Jain,Ankit Dubey,Mohd Mohsin Ali,Manish Raj,Mohd Abuzar Sayeed). Hence, to further improve interpretability, we propose to quantify the importance of feature interactions in addition to individual features. In this work, we introduce integrated directional gradients (IDG), a game-theory inspired method for assigning importance scores to higher level feature in

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Gastric

Navigating the Threat Landscape of IoT: An Analysis of Attacks,ay in 2022, a 40% increase from the year before. User Datagram Protocol (UDP) spoof flood attacks increased from 16 to 55% in the first half of 2022, according to the same report. By 2025, there will likely be between 17 and 20 billion connected devices worldwide. As more devices are connected to on

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Crop Recommendation System Using Machine Learning and IoT: A Survey,crop recommendations, we can combine the predictive capabilities of ML with the real-time data collection provided by IoT devices to improve and ensure agricultural yields. Together, these allow continuous monitoring of soil water content, nutrient levels, and climate to provide precisely tailored r

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,Lip Movement Detection—A Survey of State-of-the-Art Approaches,will help to suggest the potential future direction in the same. Some of the key features discussed in this paper are different algorithms and methodologies adopted, the dataset used, performance matrices, and their pros and cons in different real-world applications

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Enhancing Road Safety with Smartphone-Based Machine Learning Driver Behavior Classification and Aggwhich is critical for preparing the data for the following stage, and we employed a normalization technique. Then, in the following stage, two approaches will be taken. The first strategy is to directly enter the data into the three classifiers utilized in this work to classify the driving behavior,

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Design and Development of Sporadic Demands in Prediction for Automobile Industry,ievable. The novel technique has demonstrated superior performance in the out-of-sample comparison. Additionally, the findings underscore the reliability of the mean square error as an accurate metric for assessing sporadic demand. .: Croston’s method was applied to predict irregular demands. The Cu

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Blockchain Technology, DApps, and the Dark Web: LEAs Investigation Perspectives,. Further, different DApps involved in dark web platforms are explored along with their features. The paper concludes with the recommendations for LEAs to understand this dark web platform from the perspective of investigator and also to incorporate few changes in the investigation procedures includ