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Gathering the useful information or data from the sensor nodes is the main purpose of WSN. Consumption of energy varies from one node to another node since the data present in the network goes through one or many sensor nodes. As a result of this, the node containing excess load might lose its battery power supply and will cease to function. If the same scenario occurs to a group of neighboring nodes, then all the nodes fall into a stage of premature death which results in the formation of energy-hole within the network. Due to this, the network’s lifetime gets affected and might get over very soon. The above said issue is identified as the key problem in the work. The projected method aims maximization of coverage by enhancing the detection range of remaining nodes to minimize energy holes using the lively bonding and the division of coverage. The projected method increases the lifetime as compared to the existing protocols.

Wireless sensor networks are widely utilized. In the network of wireless sensors, the nodes of sensors normally disseminated arbitrarily are conditional on the method preferred to realize the sensor network. Primarily, the lifespan of a sensor node depends on the active node numbers along with the network connectivity. When a sensor node runs out of power, the sensor node dies too early, affecting network performance. Therefore, an energy hole will be formed with the network. To avoid the problem of energy holes, a number of rules are already proposed. This paper proposed a new method to resolve the problem of energy holes in wireless sensor networks and maximizes the useful life of the network through a different way of cluster head selection using asymmetrical clustering method. This paper proposed PE (probability enhancement) method for choosing the cluster head, which gives improved output compared to LEACH as well as PEGASIS protocol. The result of simulation is performed with MATLAB, and it appears that the projected scheme works better than the previous scheme.

The Martian northern hemisphere (NH) is relatively devoid of ambient magnetic fields compared to the southern hemisphere (SH), which houses the strong crustal field regions. On 2024 May 17, when Mars was hit by a coronal mass ejection (CME), the periapsis of NASA’s Mars Atmosphere and Volatile EvolutioN (MAVEN) spacecraft was entirely in the NH. The dynamic pressure in the ionosphere was enhanced by almost 2 orders of magnitude during the Mars–CME interaction, allowing penetration of solar origin magnetic fields into the Martian ionosphere. Even at altitudes below 500 km, the ratio of magnetic pressure (Pb) to ionospheric thermal pressure (Pth) was amplified more than 100 times, creating an overpressure (OP) regime. This OP condition exposed the topside ionosphere to the CME. The topside ionosphere was severely depleted, with the electron (ne) and O2+ ( nO2+ ) densities being reduced by nearly 50%–100%. The effects were particularly severe at altitudes above 350 km. The dayside ionosphere showed relatively stronger depletion compared to the terminator regions.

Satellite Traces (STs) are the important ionogram signatures for the presence of upwellings in the bottom‐side ionosphere, which provide the necessary seed perturbation for the development of equatorial plasma bubbles (EPBs). In this study, a virtual ionosonde experiment is simulated to investigate the various ST signatures under the presence of shallow, deep, overhead, and off‐centered upwellings in the bottom‐side ionosphere. It is shown that STs occur at higher and lower virtual heights than the main ionogram trace for the off‐centered and overhead upwellings, respectively. The height separation between the main trace and STs increases with the deepening of overhead upwellings. Further, a proof‐of‐concept is demonstrated that multiple STs from ionograms can be used to reconstruct the spatial structure of bottom‐side upwellings, if the precise Angle‐of‐Arrival information can be resolved from the wide beam Ionosonde systems, and can have potential applications in predicting the occurrence of EPBs. Plain Language Summary The ionosphere is the gateway for radio communications between the ground and space. The free electrons and ions in the ionosphere can affect the propagation of radio waves. The structures with turbulent electron density variations in the ionosphere, known as plasma bubbles, can often disrupt radio communication signals beyond the usable levels. Such a situation can lead to severe outages in the satellite‐based (e.g., Global Navigation Satellite System based) positioning, precise navigation, operation of drones, etc. The upwelling structures in the bottom‐side ionosphere are the earliest manifestations of the plasma bubbles, hence, their early detection is vital for forecasting the adverse effects of plasma bubbles. This study illustrates the different characteristic signatures of upwellings on the ionograms and demonstrates a proof‐of‐concept to reconstruct the upwellings from the multiple STs if the precise Angle‐of‐Arrival information is available. Key Points Satellite Traces (STs) occur at lower virtual heights than the main ionogram trace when the upwelling is centered and located overhead of transmitter The precise Angle‐of‐Arrival (AoA) is a crucial parameter to unambiguously interpret ST signatures associated with upwellings of different depths and positions A proof‐of‐concept is demonstrated that multiple STs with AoA values can be used to reconstruct the spatial structure of upwelling

Seismic activity can impact different layers of the Earth’s atmosphere; however, our understanding of lithosphere-atmosphere-ionosphere coupling mechanism still remains limited and is challenging. Previous studies predominantly feature seismo-ionospheric changes associated with large earthquakes/tsunamis. Seismic-induced changes in the Mesosphere-Lower Thermosphere (MLT) region have not been properly addressed and are limited to a few reports. We present, here, rare observations of anomalies in the temperature and airglow of the MLT region using Sounding of the Atmosphere using Broadband Emission Radiometry (SABER) instrument on board Thermosphere Ionosphere Mesosphere Energetics Dynamics (TIMED) spacecraft measurements for 2025 Mw 8.8 Kamchatka Peninsula Earthquake. Beginning with the Mainshock at 23:24:52 UT on 29 July 2025, over a hundred aftershocks (with a majority exceeding intensity-scale of Mw 5.0) occurred near Petropavlovsk-Kamchatsky and Severo-Kuril’sk in Russia and activity continued beyond 31 July. We found an increase in temperature in the 73–83 km range on 30 July. However, the temperature decreased in the ~ 87–97 km range on 30 and 31 July. Further, we noted a minor increase and distinct decrease in the volume emission rate of OH airglow on 30 July over the height range of 76–82 km and 83–90 km, respectively. Comparatively, significant decrease in OH airglow was seen on 31 July in the 81–96 km height range. Unusual gravity wave (GW) activity was, also, noted with predominant presence of waves with vertical wavelength of ~ 18 km. Similar anomalous temperature enhancement and pronounced decrease in OH airglow was seen during the 2011 Mw 9.1 Tohoku-Oki earthquake as well.

The current study explores the relationship between solar variability and tropical cyclone (TC) activity using sunspot number (SSN) and TC best‐track data as respective proxies. We have considered six regions of the globe, for example, EP: Eastern Pacific, NA: North Atlantic, NI: North Indian, SI: South Indian, SP: South Pacific, and WP: Western Pacific. The results show strong anti‐correlation between yearly TC activity and yearly SSN while considering their 11‐year moving averages. This behavior is consistent for TC counts as well as accumulated cyclone energy. However, this is true only for the North Atlantic region. Overall, when we consider all regions together, more TCs (in terms of counts) are observed during lower solar activity periods (SSN < 50) as compared to higher solar activity conditions (SSN > 100). However, the yearly rates remain more or less similar. On the other hand, extreme TC events with a maximum wind speed of 137 knots and higher (category 5) are most likely to occur during the declining phase of a solar cycle and least likely to occur during the ascending phase or the maximum phase. Although solar activity levels are similar during the declining and ascending phases, the yearly occurrence rate is nearly double in the declining phase (1.123) as compared to that in the ascending phase (0.625). Key Points Tropical cyclones (TCs) occurrences and solar activity show strong anti‐correlation in the North Atlantic sector Extreme TCs are most likely to occur during the declining phase of a solar cycle and least likely to occur during the maximum phase The yearly occurrence rate of extreme TCs is nearly double in the declining phase of a solar cycle as compared to that in the ascending phase

High Accessibility and Easy Investment makes Cryptocurrency an important income source for many people. Cryptocurrency is a kind of Digital/Virtual currency which is created using blockchain Technology and is protected by Cryptography. Cryptocurrencies enables users to Accept, Transfer and request the capital between the Users without the requirement of intermediaries such as banks. Now a day many Cryptocurrencies are available across the world such as Bitcoin, Litecoin, Monero, Dogecoin etc. This study is more determined over a very famous and demanding Cryptocurrency known as Bitcoin over the past years. Here, firstly we make an effort to predict the price of bitcoin by examining numerous numbers of parameters that affect the cost of bitcoin. Different kinds of Machine learning models will be used to estimate the price of Bitcoin. This study provides the accuracy and precision of each model that are used in this study and determine the suitable method to estimate the price more accurately.

Development and exploration of several Data analytics techniques in various real-time applications (e.g., Industry, Healthcare Neuroscience) in various domains have led to exploitation of it to extract paramount features from datasets. Following the introduction of new computer technology, the health sector had a significant transformation that compelled it to produce more medical data, which gave rise to a number of new disciplines of study. Quite a few initiatives are made to deal with the medical data and how its usage can be helpful to humans. This inspired academics and other institutions to use techniques like data analytics, its types, machine learning and different algorithms, to extract practical information and aid in decision-making. The healthcare data can be used to develop a health prediction system that can improve a person's health. Based on the dataset provided, making accurate predictions in early disease prediction benefits the human community.

With the development of more compact and powerful methods of designing a digital logic on a silicon chip, most of the signal processing is being implemented in the digital domain. The implementation of an efficient reconfigurable digital decimation filter is presented in the work. In this paper we focuses with the implementation and design of a decimation filter which is used for hearing aid applications. We design decimation filter with the help of the canonic signed digit (CSD) representation. In decimation filter the cascaded integrated comb filter is designed using without multiplier less. The half band and corrector filters are designed using CSD. The decimation filter has been implemented on Xilinx FPGA using Virtex-2 technology and number of slices ,number of LUTs and number of registers are reported and also proposed design is implemented in synopsis design compiler for ASIC implementation and calculated area, power and delay. The resulting architecture is hardware efficient and consumes less power compared to conventional decimation filters. Compared to the normal decimation filter architecture, the proposed decimation filter architecture has less hardware saving of 60% and in addition, it decreases the power consumption of 80%, respectively and the proposed architecture is well suited for decimation filters of the hearing aids.

Hearing aid is an acoustic device which is worn by hearing loss people. To compensate the different types of hearing loss, it is necessary to selectively amplify sounds at required frequencies. The main aim of the hearing aid is to selectively remove the noise signal such that the processed sound matches ones audiogram. To achieve this, the decimation filter in hearing aids can be design using multiplier less architecture which should be able to adjust sound levels at arbitrary frequencies within a given spectrum. In hearing aids, decimation filter plays a key role. This paper presents a low complexity design of a digital finite impulse response (FIR) filter for digital hearing aid application. This paper proposed approximate 4:2 compressor adders in memory less DA based FIR filter architecture. In DA architecture the area of the ROM increases gradually when filter order is increased. Memory less DA is designed using compressor adders is a solution to decrease the power consumption and area of the FIR filters and makes the area and power reduction for hearing aid application. The proposed DA based FIR filter architecture is synthesized on 90 nm technology using Synapsis Application Specific Integrated circuit design compiler. The proposed architecture has 45% reduction in area delay product when distinguish with systolic architecture and 10% less ADP when compare with OBC DA architecture. The proposed design is also implemented Field Programmable Gate Array and the results shows that the proposed architecture has less slices than best existing designs. The proposed architecture is used in decimation filter of hearing aids applications using matlab simulink, which removes the unwanted signal.