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227 results for “MR Signals”
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Research ArticleOpen accessIn the abstractNovel Depression Classification Framework Using Optimal Feature Integration with Hybrid Convolution (1D/3D) Based Adaptive Residual DenseNetB. Manjulatha, Suresh PabbojuThis study introduces a novel depression classification method by incorporating multimodal data to reduce this limitation and improve the accuracy of depression diagnosis. In the beginning, the multimodal data such as speech signal, Electroencephalographic (EEG), and text data is obtained from the benchmark datasets. These acquired text data are subjected to the text pre-processing phase, where the stemming, character removal, … …Journal of Computer Science, Vol. 21, Issue 3 · 25 Feb 2025 · 5,860 accessesView PDFCite
Research ArticleOpen accessIn the abstractEnhanced Hybrid Spectrum Sensing Method Using TCDT and IEDT for Cognitive RadioNeha Chaudhary, Rashima Mahajan, Richa Adlakha et al.The development of efficient spectrum sensing techniques has witnessed progressive growth for optimum utilization of spectrum resources in cognitive radio. The primary objective of spectrum sensing is the identification and proper utilization of the spectrum holes. Nowadays, due to the advancement of wireless technologies, the demand for spectrum is also increasing and thus in turn, the requirement for better spectrum … …Journal of Computer Science, Vol. 20, Issue 11 · 20 Nov 2024 · 4,301 accessesView PDFCite
Research ArticleOpen accessIn the abstractEpileptic Seizure Detection Using Integrated Decomposed Features from EEG SignalShupta Das, Suraiya Akter Mumu, M. A. H. Akhand, Md Abdus Samad KamalThe root cause of the seizure is a sudden abnormal excessive electrical discharge in the brain and it is an Epileptic Seizure (ES) when such abnormal electrical activity arises particularly for epilepsy. Recognizing ES is crucial for effective treatment as it often repeats and can lead to serious outcomes. Since epilepsy is a neurological issue, detecting ES by analyzing brain … …Journal of Computer Science, Vol. 20, Issue 10 · 8 Aug 2024 · 4,845 accessesView PDFCite
Research ArticleOpen accessIn the abstractCardiovascular Diseases Identification Using Wavelet Optimization and Modify Cuckoo Search AlgorithmBanit Negi, Abhilekh Bartwal, Agya Ram Verma et al.The problem the author aims to solve is the extraction of discriminatory features in ECG (Electrocardiogram) signals for classification purposes. The scope of the work is to propose a new method for building wavelets that best reflect the discriminatory capacity of ECG signals. The approach involves optimizing the wavelets specifically for the classification function under consideration. To address the problem, … …Journal of Computer Science, Vol. 19, Issue 8 · 3 Aug 2023 · 5,403 accessesView PDFCite
Research ArticleOpen accessIn the abstractDiscrete to Continuous Algorithm for Optimal Channel Selection to Detect Alcoholism through EEG RecordingsHayat Sedrati, Wajih Rhalem et al.Alcoholism is a serious public health issue, and early diagnosis of this brain disease can be performed by analyzing Electroencephalogram (EEG) signals. However, the high dimensionality of EEG datasets requires significant computational time and resources for the automatic processing of EEG signals. This study proposes a novel method to reduce EEG dataset dimensionality using a Discrete to Continuous algorithm (DtC) … …Journal of Computer Science, Vol. 19, Issue 1 · 17 Jan 2023 · 5,904 accessesView PDFCite
Research ArticleOpen accessIn the abstractIntelligent Digital Signal Modulation Recognition using Machine LearningMudhafar Haji Mala Abd, Sadegh AminifarInrecent years, modulation type recognition has received a lot of attentionacross the board. There are several methods to detect modulation types, butthere are only a few effective methods to handle signals with a higher level ofnoise. This study introduces an approach to verify the ability of differentmachine learning algorithms to automatically manage noise in detecting digitalmodulations. This research examines two … …Journal of Computer Science, Vol. 18, Issue 10 · 26 Sep 2022 · 6,095 accessesView PDFCite
Research ArticleOpen accessIn the abstractInvestigations on Orthogonal-Frequency Division Multiplexed-Mode-Division Multiplexed MM Wave-on-Free Space Optics Transmission using Laguerre-Gaussian Modal BeamsAnita Suman, Ajay KumarWe report the simulation-modelling and evaluation of an integrated Orthogonal-Frequency Division Multiplexed (OFDM)-Mode-Division Multiplexed (MDM) Radio-on-Free Space Optics (Ro-FSO) scheme carrying 2-independent 40 GHz millimetre waves (mm Wave) at 20 Gbps per channel for 5th generation wireless applications. The reported Ro-FSO scheme transports 2-independent 20 Gbps 4-Quadrature-Amplitude Modulated (4-QAM) signals, each carrying 40 GHz mm Wave signal over 2-distinct Laguerre-Gaussian … …Journal of Computer Science, Vol. 17, Issue 12 · 15 Dec 2021 · 6,200 accessesView PDFCite
Research ArticleOpen accessIn the abstractPhonocardiogram Classification Based on Machine Learning with Multiple Sound FeaturesKhalid M.O. Nahar, Obaida M. Al-Hazaimeh, Ashraf Abu-Ein, Nasr GharaibehIn this study the heartbeat sound signals were tackled by classifying them into heart disease categories such as normal, artifact, murmur and extrahals in an attempt for early detection of heart defects. Phonocardiogram (i.e., PCG) is used to obtain the digital recording dataset of the heart sounds using an electronic stethoscope or mobile device. Multiple features are extracted from the … …Journal of Computer Science, Vol. 16, Issue 11 · 26 Nov 2020 · 8,259 accessesView PDFCite
Research ArticleOpen accessIn the abstractECG Energy Change Study Based on Variational Mode DecompositionKai Dong, Lin Sun, Hongjun Xiong, Wenbo WangVariational Mode Decomposition (VMD) decomposes the signal into a series of Intrinsic Mode Type Functions (IMTFs) according with variational model and fluctuating characteristics of the signal itself, thus very suitable for the analysis of nonlinear and non-stationary Electrocardiogram (ECG) signal. Energy of ECG signal has certain distribution rules, but which could be affected by diseases; therefore, the study of ECG … …American Journal of Biochemistry and Biotechnology, Vol. 16, Issue 1 · 12 Mar 2020 · 7,397 accessesView PDFCite
Review ArticleOpen accessIn the abstractStrigolactones in Plant Stress Adaptation: Mechanisms and Agricultural PotentialHumayra Ferdus, Mahabuba Mostafa, Md. Motaher HossainAbiotic stresses have significant negative effects on the growth, development, and productivity of crop plants, which are critical to global agricultural production and ecosystem stability. Strigolactones (SLs), a family of carotenoid-derived plant phytohormones, have been identified as playing key roles in plant development and adaptive responses to environmental stimuli. Initially recognized as signaling molecules in host-parasite interactions and as symbiotic … …OnLine Journal of Biological Sciences, Vol. 26, Issue 4 · 3 Oct 2026 · 559 accessesView PDFCite