11 research outputs found
Computer Aided Automatic Detection and Classification of EEG Signals for Screening Epilepsy Disorder
No full textInfection in human brain causes brain disorder which is in the form of Epilepsy. The infected area in the brain region generates the irregular pattern signals as focal signals and the other healthy region in the brain generates the regular pattern signals as non-focal signals. Hence, the detection of focal signals from the non-focal signals is important for epileptic surgery in epilepsy patients. This paper proposes a simple and efficient methodology for EEG signals’ classifications using ANFIS classifier. The performance of the proposed EEG signals classification system is evaluated in terms of sensitivity, specificity and accuracy
Hen maternal care inspired optimization framework for attack detection in wireless smart grid network
No full textIn the power grid, communication networks play an important role in exchanging smart grid-based information. In contrast to wired communication, wireless communication offers many benefits in terms of easy setup connections and low-cost high-speed links. Conversely, wireless communications are commonly more vulnerable to security threats than wired ones. All power equipment devices and appliances in the smart distribution grid (SDG) are communicated through wireless networks only. Most security research focuses on keeping the SDG network from different types of attacks. The denial-of-service (DoS) attack is consuming more energy in the network leads to a permanent breakdown of memory. This work proposes a new metaheuristic optimization inspired by maternal care of hen to their children called hen maternal care (HMCO) inspired optimization. The HMCO algorithm mimics the care shown by hen for their children in nature. The mother hen is always watchful and protects its chicks against predators. All chickens utilize different calls to designate flying predators like falcons and owls from ground seekers like foxes and coyotes, showing that they can both survey a danger and advise different chickens how to set themselves up. Our method shows greater performance among other standard algorithms
Retraction Note to: Machine learning method based detection and diagnosis for epilepsy in EEG signal
No full textRetraction note to: Journal of Ambient Intelligence and Humanized Computing (2021) 12:4215–4221 https://doi.org/10.1007/s12652-020-01816-3
The Editor-in-Chief and the publisher have retracted this article. This article was submitted to be part of a guest-edited issue. An investigation concluded that the editorial process of this guest-edited issue was compromised by a third party and that the peer review process has been manipulated. Based on the investigation's findings the Editor-in-Chief therefore no longer has confidence in the results and conclusions of this article.
The authors have not responded to correspondence regarding this retraction
Classification of focal and nonfocal EEG signals using ANFIS classifier for epilepsy detection
No full textImaging systems are rapidly becoming a ubiquitous part of our daily environment. Their success has been made possible by a unique blend of science and technology achieved in the latter part of the 20th century. In addition to performing mundane tasks, imaging systems allow us to study astronomical objects and molecules; they are widely used in quality control and oil exploration. Remarkably, the same principles are used to build non-invasive tools for studying the anatomy and physiology of various human and animal organs, including the most complex one, the brain. The International Journal of Imaging Systems and Technology – Neuroimaging and Brain Mapping is a forum for the exchange of ideas and results relevant to imaging systems and their applications in the field of Neuroscience.
The International Journal of Imaging Systems and Technology - Neuroimaging and Brain Mapping began focusing on the field of Neuroscience in a broad sense in early 2010, including relevant algorithmic research and hardware and software development. The Journal publishes general-interest articles on neuro-imaging. The scope of the Journal includes, but is not limited to, the following
Machine learning method based detection and diagnosis for epilepsy in EEG signal
No full textThe epileptic seizure can be detected using electroencephalogram (EEG) signals. The detection of epileptogenic region in brain is important for the detection of epilepsy disease. The signals from epileptogenic region in brain are focal signal and the signal from normal regions in brain is non-focal signal. Hence, the detection of focal signal is important for epilepsy disease detection. This paper proposes an automatic detection and diagnosis of EEG signals for epilepsy disease using soft computing approaches as adaptive neuro fuzzy inference system (ANFIS) and neural networks (NN). In this paper, the features from decomposed coefficients as bias (B), weight feature (W), entropy(E), activity feature (AF), mobility feature (MF), complexity feature (CF), skewness (S) and kurtosis (K) are extracted for the classification of EEG signals into either focal or non-focal signals for epilepsy disease detection and diagnosis. The detection of focal signal is achieved by ANFIS classifier and the diagnosis of the severity levels in focal signal is achieved by NN classification approach. The proposed method is used in many clinical diagnosis
International Journal of Pharma and Bio Sciences RESEARCH ARTICLE ARTICALTICLE IMMUNOBIOLOGY ROLE OF THE IMMUNE ORGAN (THYMUS) IN MYSTUS GULIO Corresponding Author
No full textThe present work focused on role of the immune organ in the thymus of Mystus gulio. Haemopoietic tissue was found mainly in the spleen, head kidney, thymus and a small amount occurred in the mesonephros. The clearance of the intraperitoneally injected colloidal carbon was carried out. The phagocyte uptake of carbon, after its intraperitoneal injection. It was first detected in the thymus at 30 min after injection. This article can be downloaded from www.ijpbs.net B- 402KEY WORDS Carbon phagocytosis, Mystus gulio, immune organ and macrophage
Design of storing and restoring array divider circuit using binary decision diagram-based adder/subtractor circuit
No full textThe Binary Decision Diagram (BDD) based circuits are tree-structured, equally
sharing the current/power in the cell, which gives reduced power dissipation and
increasing speed. The proposed BDD based adder/subtractor circuits are designed
and verified in such a way, which trades off the traditional way of full
adder/subtractor design, and achieves the required parameters of high speed, low
latency, lesser occupying area and low power in the design. The schematic
circuits are obtained by using Mentor graphics Silterra 0.13 µm. The proposed
adder/subtractor circuit is implemented into a Restoring Array Divider (RAD)
and Non-restoring Array Divider (NRAD) circuits for 5G base station
application. The proposed full adder gives a power dissipation (32.11 nW), delay
(140 ps) and occupying area (67.5 µm2), which is lower than other reported
circuits. The proposed subtractor circuit is compared with the existing circuits,
which gives more than 95% improvement in Power dissipation and 17.39%
improvement in propagation delay. The layout vs. circuit schematic comparison
has been performed for the proposed adder-based RAD and NRAD and evaluated
for chip area, propagation delay, and power dissipation. The proposed
adder/subtractor-based RAD and NRAD circuits are compared with the results
of existing works. The proposed adder/subtractor circuits give 36.02% power
dissipation than A, Arya et al. DAXD 99.79% and 99.74% than A. Arya et al.
Approximate Divider (ADIV) and Approximate Divider 6 (ADIV6) divider
model circuit. The propagation delay and area are improved by 80% in terms of
delay and more than 14% in terms of area than the recent report designs
Power Efficiency Top-Down ALU for Error Correction and Detection Circuit
No full textAdder circuits and other logic blocks are used in the design of the ALU circuit. The primary goals of this study were to improve the efficiency of a 1-bit ALU and to speed it up without significantly increasing its power consumption. Both the Shannon theorem and mixed Shannon are used in the design of the proposed top-down ALU. Moreover, this article suggested utilising not one but three distinct ALUs: Binvert, Bit Slice, and MIPS. Compared to previously published circuits, the calculated values of power dissipation, propagation latency, and area are all improvements thanks to the simulation results. The proposed circuit is weighed against others that the adder-based ALU model could employ in artificial intelligence (AI)/Expert Systems (ES), Quantum Computing (QC), and Bio-Computing (BC) using parallel processing circuit blocks. When calculating the proposed adder-based ALU circuit's throughput, latency, and EPI, a BSIM4 analyser is used, which provides high throughput and lower latency than reportedfindings due to taking all the care off)
Epileptic EEG signal classifications based on DT-CWT and SVM classifier
No full textContamination in human cerebrum causes the mind issue which is as Epilepsy. The contaminated territory in the cerebrum area creates the unpredictable example signals as focal signs and the other sound locales in the mind produce the standard example signals as non-focal sign. Henceforth, the discovery of focal signs from the non-focal signs is a significant for epileptic medical procedure in epilepsy patients. This paper proposes a straightforward and proficient technique for EEG signals orders utilizing SVM classifier. The exhibition of the proposed EEG signals characterization framework is assessed as far as Sensitivity, Specificity, and Accuracy
Analysis of Kirk effect of an innovated high side Side-Isolated N-LDMOS device
No full textAn ESOA of LDMOS device is very critical for power device performance. Kirk effect is the one of the major problem which leads to poor ESOA performance. The cause of the problem mainly due to the high beta value of parasitic NPN transistor in the p-body. In this study, we proposed a new 3D high side Side-Isolated N-Channel LDMOS which we have obtained not only benchmark Ron and breakdown performance, but also better ESOA without Kirk effect. We have compared the analysis of Kirk effect between the new device and the conventional N-LDMOS structure with LATID technique for the formation of the p-body of both device structures.EICPCI-S(ISTP)[email protected]
