Titlebook: Cyber Intelligence and Information Retrieval; Proceedings of CIIR João Manuel R. S. Tavares,Paramartha Dutta,Debabra Conference proceeding

Oafishness

Audio Watermarking in Linear Canonical Transform Domain Using Frequency-Dependent Clusteringintact (Dhar PK, Robust FFT based watermarking scheme for copyright protection of digital audio data, IEEE, China, pp. 181–184, 2011). This paper proposes an effective methodology for watermarking of the audio signal using linear canonical transform (LCT), which has found its use in a multitude of s

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BUMP

DTNMA: Identifying Routing Attacks in Delay-Tolerant Networkck hole attack, etc., affect the network connectivity, thereby increasing the delay in the message delivery rate. Thus, the effective mechanisms need to be identified and implemented to eliminate the different types of vulnerability attacks before implementing anything in DTN. This paper mainly addr

充足

Classification Framework for Fraud Detection Using Hidden Markov Modeling, i.e., classification and regression. In unsupervised learning, we do not supervise model instead we allow machine to work on its own to discover information. Clustering is type of unsupervised learning.

thrombosis

A Review on Security Issues in Healthcare Cyber-Physical Systemsto the security of Healthcare CPS have been discussed in general and included the latest updated papers in the domain, later, has extended the focus to Wireless Sensor Networks and the vulnerabilities faced along with their defense as an overview. The concept of Sensor Only Networks, an advancement

痛苦一生

荒唐

Next Step to the Future of Restaurants Through Artificial Intelligence and Facial Recognitionrving you food. During the period of normalizing going out in the Covid-19 pandemic, there were many issues regarding this? In this paper, the core point is to avoid physical contact and enhance restaurants’ future with AI and its upcoming potential to deliver a new and safer experience to the custo

chuckle

A Comparative Study into Stock Market Prediction Through Various Sentiment Analysis Algorithmss in share markets and can offer more accurate results to analyses data from multiple news sources and historical price movement of individual stocks. By using a two-step process, the model offers a minimum prediction accuracy value of 72%. In the first step, Naïve Bayes algorithm is used to evaluat

BACLE

Bangla Handwritten Digit Recognitionork (CNN) functioning as the classification algorithm. On the NumtaDB image dataset, the performance is systematically evaluated of this process. Finally, 93% accuracy is obtained for NumtaDB dataset, and 92% accuracy rate is obtained for our own dataset using same of the proposed method in experime

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