PAREEKSHA: a machine learning approach for intrusion and anomaly detection

A Nagaraja, S Aljawarneh - … of the First International Conference on Data …, 2018 - dl.acm.org
Membership functions help us to identify and know the similarity between two elements such
as vectors or sequences. The objective of this paper is to suggest a membership function …

Enhanced detection of epileptic seizure using EEG signals in combination with machine learning classifiers

W Mardini, MMB Yassein, R Al-Rawashdeh… - IEEE …, 2020 - ieeexplore.ieee.org
Electroencephalogram (EEG) is one of the most powerful tools that offer valuable
information related to different abnormalities in the human brain. One of these abnormalities …

Detection of epileptic seizures from EEG signals by combining dimensionality reduction algorithms with machine learning models

M Zubair, MV Belykh, MUK Naik… - IEEE Sensors …, 2021 - ieeexplore.ieee.org
Epilepsy is a neurological condition that affects the central nervous system. While its effects
are different for each person, they mostly include abnormal behaviour, periods of loss of …

Study of Detection of DDoS attacks in cloud environment Using Regression Analysis

A Nagaraja, U Boregowda, R Vangipuram - International Conference on …, 2021 - dl.acm.org
Distributed Denial of Service (DDoS) attacks in the cloud environment are not as simple as
the same attacks which occur in the traditional physical network environment. Not only one …

VRKSHA: A novel multi-tree based sequential approach for seasonal pattern mining

S Aljawarneh, V Radhakrishna, A Cheruvu - Proceedings of the Fourth …, 2018 - dl.acm.org
Mining association patterns from a time-stamped temporal database is implicitly associated
with task of scanning input database. Finding supports of itemsets requires scanning the …

Mantra: a novel imputation measure for disease classification and prediction

S Aljawarneh, V Radhakrishna, GS Reddy - Proceedings of the first …, 2018 - dl.acm.org
Medical record instances can have missing values which makes them unsuitable for
learning process. Data Imputation is normally done to fill one or more missing data attribute …

Ultimate: unearthing latent time profiled temporal associations

SA Aljawarneh, V Radhakrishna… - Proceedings of the First …, 2018 - dl.acm.org
Discovery of temporal association patterns from temporal databases is extensively studied
by academic research community and applied in various industrial applications. Temporal …

Krishna Sudarsana: A Z-space similarity measure

V Radhakrishna, PV Kumar, V Janaki - Proceedings of the Fourth …, 2018 - dl.acm.org
Similarity profiled association mining from time stamped transaction databases is an
important topic of research relatively less addressed in the field of temporal data mining …

Sequential approach for mining of temporal itemsets

V Radhakrishna, S Aljawarneh, A Cheruvu - Proceedings of the Fourth …, 2018 - dl.acm.org
Sequential approach for mining temporal itemsets initially proposed by Yoo and Sekhar
uses the Euclidean distance measure to discover similarity profiled temporal associations …

Kaala vrksha: extending vrksha for time profiled temporal association mining

V Radhakrishna, S Aljawarneh, PV Kumar… - Proceedings of the first …, 2018 - dl.acm.org
Discovery of frequent itemsets from snapshot databases is most addressed widely in the
literature. The support value of itemsets for frequent itemset mining is a numeric value of one …