Explore the vast range of titles available.

Temporary disturbances in brain function are caused by epilepsy, a chronic disorder resulting from sudden abnormal firing of brain neurons. This research introduces an innovative real‐time methodology representing detecting epileptic spasms from electroencephalogram (EEG) data. It employs a support vector machine (SVM) alongside embedded zero tree wavelet (EZW) transform. To facilitate precise multiresolution analysis of epileptic convulsions, the EZW method is selected for its capacity to efficiently compress multichannel EEG data while preserving crucial diagnostic features. EZW effectively captures and encodes key patterns in EEG signals, enabling detailed analysis of the subtle variations associated with seizures. This study extracts statistical features such as entropy, kurtosis, skewness, and mean from the compressed EEG segments. These features are then classified using the SVM to distinguish between normal and epileptic states. With a remarkable 99.02% classification accuracy and a false positive rate of only 1.1%, the proposed algorithm demonstrates excellent performance. The novelty lies in integrating SVM with EZW‐based feature extraction and advanced preprocessing, enabling efficient real‐time EEG analysis. Unlike previous works, this approach preserves critical information, enhances classification accuracy, and supports multichannel signals, offering a robust and practical solution for real‐time epilepsy detection. Based on these findings, the method is considered highly suitable for real‐time implementation in clinical environments.

A modified architecture for minimized power dissipation in the maximum a posteriori (MAP) decoder based on clock gating and toggle filtering is proposed in this paper. Log likelihood ratio (LLR) in the trellis structure of the MAP decoder consumes large power. To minimize the power dissipation, toggle-filtering technique is introduced in the LLR unit of MAP decoder and clock-gating approach is introduced in the state metric, branch metric and again in LLR blocks of the MAP decoder. Toggle filter is used to avoid early injection of signals from the state metric and branch metric units. Clock-gating approach is used to keep the idle block in the disabled state. A power dissipation of 53.64 % has been achieved when toggle-filtering technique is applied and 54.4 % when clock-gating technique is applied. Power dissipation of 64.07 % has been achieved for the combined effect of toggle-filtering and clock-gating technique.

A novel approach, Multipeak mean based optimized histogram modification framework (MMOHM) is introduced for the purpose of enhancing the contrast as well as preserving essential details for any given gray scale and colour images. The basic idea of this technique is the calculation of multiple peaks (local maxima) from the original histogram. The mean value of multiple peaks is computed and the input image’s histogram is segmented into two subhistograms based on this multipeak mean (mmean) value. Then, a bicriteria optimization problem is formulated and the subhistograms are modified by selecting optimal contrast enhancement parameters. While formulating the enhancement parameters, particle swarm optimization is employed to find optimal values of them. Finally, the union of the modified subhistograms produces a contrast enhanced and details preserved output image. This mechanism enhances the contrast of the input image better than the existing contemporary HE methods. The performance of the proposed method is well supported by the contrast enhancement quantitative metrics such as discrete entropy, natural image quality evaluator, and absolute mean brightness error.

A body of komatiitic amphibolite, an enclave within the Archean high-grade orthogneisses in southern India, shows mild chemical weathering under semiarid conditions. Along fractures, chemical weathering has advanced (Chemical Index of Alteration [CIA] = 53; CIA of fresh rock ∼26) to the extent that secondary Mg-Fe-Al clay minerals have formed and the rock has turned brownish red, soft, and fine grained. The weathering process has resulted in the mobilization and redistribution of the so-called immobile elements Fe, Al, Ti, and REE effected by the nature of secondary mineral formation (talc vs. aluminous clay minerals) and also possibly by soil microbes. In the initial stages of secondary mineral formation, there is a small loss of Fe, Al, and REE (noticeably Eu). However, in the fracture zone as well as in the incipiently altered zone, there is significant REE enrichment, probably effected by different precipitation mechanisms. Mobilized REE may have come from a minor alteration of clinopyroxene.

The identity of the river along which the famous Harappan Civilization developed and the causes of the demise of this culture are topics of considerable debate. Many of the Harappan sites are located along the ephemeral Ghaggar river within the Thar Desert in the northwestern India and adjacent Pakistan. The Ghaggar was also thought to be the mythical river Saraswati, which was described as glacial-fed river. Sr and Nd isotopic composition of the Ghaggar alluvium as well as Thar Desert sediments suggests a Sub-Himalayan sediment source, with no contribution from the glaciated regions. The development of extensive Harappan Civilization all along the Ghaggar suggests a catchment with high monsoon rainfall. It is likely that with the changes in the monsoon scenario after 3500 BC could have gradually dried up the Ghaggar river and resulted in the migration and/or extinction of the Harappan Civilization on this river.

Plant, soil, groundwater and rivers on land are one complexly interconnected system with a strong symbiosis. Managing one such as the lower form of life will simultaneously manage all others. This is the biological management of water on land.

Wireless sensor networks are highly indispensable for securing network protection. Highly critical attacks of various kinds have been documented in wireless sensor network till now by many researchers. The Sybil attack is a massive destructive attack against the sensor network where numerous genuine identities with forged identities are used for getting an illegal entry into a network. Discerning the Sybil attack, sinkhole, and wormhole attack while multicasting is a tremendous job in wireless sensor network. Basically a Sybil attack means a node which pretends its identity to other nodes. Communication to an illegal node results in data loss and becomes dangerous in the network. The existing method Random Password Comparison has only a scheme which just verifies the node identities by analyzing the neighbors. A survey was done on a Sybil attack with the objective of resolving this problem. The survey has proposed a combined CAM-PVM (compare and match-position verification method) with MAP (message authentication and passing) for detecting, eliminating, and eventually preventing the entry of Sybil nodes in the network. We propose a scheme of assuring security for wireless sensor network, to deal with attacks of these kinds in unicasting and multicasting.

Delay is an important parameter in optical packet switching networks and it affects the performance of the network. In this communication, a mathematical analysis is carried out to evaluate the delay. Delay values are analysed for variable length packets for various traffic patterns, viz. non-uniform, Poisson and ON–OFF traffic patterns for various service classes using reservation bit algorithm. The results of the class-based models are compared with the existing port-based first-fit wavelength assignment algorithm. Delay values are reduced by 29% in the class-based model than in the port-based model. Furthermore, packet transmission rate in class-based model is higher by 15.4% than port-based model.

The north-south-trending Ramagiri Schist Belt is trident shaped, with three prongs separating three granitic terranes. Whereas the western and eastern prongs contain metatholeiites and banded ferruginous quartzite, the central prong includes felsic metavolcanics and volcanogenic metasediments. The U-Pb zircon age for the pyroclastics in the central prong of the Ramagiri Schist Belt is 2707±18 Ma, considered as the time of emplacement of the felsic volcanics. To the east of the belt, migmatitic Chenna gneisses yielded a U-Pb zircon age of 2650±7 Ma, inferred as the minimum age of their magmatic precursors. These gneisses had experienced a thermal event at least 100 m.yr. later, as evidenced from the U-Pb titanite age of 2545±1 Ma. From the central Ramagiri Complex, a granodiorite has identical U-Pb zircon and titanite ages of 2613±6 and 2614±4 Ma, respectively, and a quartz diorite has a titanite age of 2595±1 Ma. These intrusives with roof-pendants of pillowed basalts are inferred to have been emplaced as high-level plutons that cooled rapidly. From the western Gangam Complex, U-Pb zircon and titanite ages for a granodiorite were 2528±1 and 2516±3 Ma, respectively, and a monzodiorite has yielded a titanite age of 2510±2 Ma. A postkinematic granitic vein intrusive into the Gangam Complex yielded a titanite age of 2468±4 Ma. The three granitoid terranes separated by a <3-km-wide schist belt do not have common magmatic or metamorphic histories, as evidenced by their distinct titanite and zircon ages. Intrusion of voluminous western Gangam Complex at 2528 Ma did not alter the titanite ages of granitoids in either the central Ramagiri Complex or the eastern Chenna Gneiss just a few kilometers away. Therefore, the Ramagiri Schist Belt, consisting of highly sheared rocks, could represent a terrane boundary between three disparate granitoid terranes juxtaposed after 2516 and before 2468 Ma. Available geological and geochronological information from Kolar, Ramagiri, and adjoining areas suggests that growth of Dharwar continental crust could have been accomplished by both accretion of a series of arcs onto and collision of a large, 2530 Ma continent with an older (<3000 Ma) continent at around 2500 Ma.

The colossal and devastating volumes of the medical records and unremitting flow of big data streams from the Internet of Medical Things (IoMT), mobile applications, and health clouds impose unprecedented challenges in the global healthcare sector. Developing platforms for ingesting, processing, archiving, and investigating such streams of big data in real-time emergency cases is a cumbersome process.