The Wireless Sensor Networks (WSNs), which are deployed in harsh environments, are extremely susceptible to localized battery exhaustion as well as intelligent inside routing threats, especially sinkhole and data falsification attacks. In this paper, we present ECHVM (Enhanced Cluster Head selection by Voting and an ECC-based Blockchain Mechanism), a novel, secure, and energy-efficient routing framework to achieve an optimal trade-off between network security and hardware resource efficiency. We present the ECHVM protocol that combines Elliptic Curve Cryptography (ECC) with a lightweight, local distributed ledger to mitigate risks of centralized authority by transferring the verification of crucial network events from a single, highly vulnerable centralized alert sink node to a decentralized, voting-based consensus among neighboring nodes. In this study, a weighted voting algorithm based on node and distance proximity metrics is applied to cluster head selection, where a 51% neighbor consensus rule is leveraged to validate local ledger transactions against malicious acts. Moreover, a local energy density and topological communication geometry-oriented energy-efficient cluster head (CH) selection algorithm is crafted to ensure balanced CH distribution in the high-density areas of the network structure so as to avoid the premature energy hole problem. Using the standard first-order radio energy model, quantitative simulations performed in MATLAB show that ECHVM achieves a malicious node detection rate of 98.2% and extends the network lifetime by 30% compared to state-of-the-art protocols (e.g., ELSO and SEC-HDT) because of proactive topology defense and rapid node sleeping. The results of statistical validation using the Wilcoxon Signed-Rank test confirm that both the reduction in energy consumption and network longevity offered by ECHVM are highly significant (
Various speech enhancement Algorithms (SEA) have been developed in the last few decades. Each algorithm has its advantages and disadvantages because the speech signal is affected by environmental situations. Distortion of speech results in the loss of important features that make this signal challenging to understand. SEA aims to improve the intelligibility and quality of speech that different types of noise have degraded. In most applications, quality improvement is highly desirable as it can reduce listener fatigue, especially when the listener is exposed to high noise levels for extended periods (e.g., manufacturing). SEA reduces or suppresses the background noise to some degree, sometimes called noise suppression alg
... Show MoreFinding the shortest route in wireless mesh networks is an important aspect. Many techniques are used to solve this problem like dynamic programming, evolutionary algorithms, weighted-sum techniques, and others. In this paper, we use dynamic programming techniques to find the shortest path in wireless mesh networks due to their generality, reduction of complexity and facilitation of numerical computation, simplicity in incorporating constraints, and their onformity to the stochastic nature of some problems. The routing problem is a multi-objective optimization problem with some constraints such as path capacity and end-to-end delay. Single-constraint routing problems and solutions using Dijkstra, Bellman-Ford, and Floyd-Warshall algorith
... Show MoreThe gas sensing properties of Co3O4 and Co3O4:Y nano structures were investigated. The films were synthesized using the hydrothermal method on a seeded layer. The XRD, SEM analysis and gas sensing properties were investigated for Co3O4 and Co3O4:Y thin films. XRD analysis shows that all films are polycrystalline in nature, having a cubic structure, and the crystallite size is (11.7)nm for cobalt oxide and (9.3)nm for the Co3O4:10%Y. The SEM analysis of thin films obviously indicates that Co3O4 possesses a nanosphere-like structure and a flower-like structure for Co3O4:Y.
The sen
... Show MoreCriteria to be met in selecting the obtimal areas for generating alternative electric energy from wind
The full energy peak efficiency (ɛ) relation of HpGe detector is determined and compared with the "spectrum shape" relation of natural background (BG) for the (121.8-1408) keV energy range. A one liter Marinelli beaker soil standard containing the Eu-152 material is used in calibration and measurement. A MATLAB fitting program were used obtain the efficiency relation from the experimental values, and to obtain the BG "spectrum shape" relation from the count rates at the corresponding energy values used. The ɛ / BG factor values were 1.154 at the 121.8keV and increase with energy till reaching a maximum value of 4.358 at about 778keV energy and then decrease. These values may be used to extract efficiency from the BG values at the
... Show MoreThe art of theater penetrated various scientific and human fields, as well as touching the facts and events surrounding it, and scientific innovations had a wide field, so it adopted feedback in interactive theater performances, especially the theater of the oppressed. Then came the indicators that resulted from the theoretical framework for the formation of the tool by which the research sample is analyzed, and then the chapter concluded with previous studies. As for the third chapter, it involved the research procedures, and through the research tool and the research method, and by selecting the intentional sample, the sample represented by a play (the story of Shahrour) was analyzed. As for the fourth chapter, it included the results
... Show MoreDisease diagnosis with computer-aided methods has been extensively studied and applied in diagnosing and monitoring of several chronic diseases. Early detection and risk assessment of breast diseases based on clinical data is helpful for doctors to make early diagnosis and monitor the disease progression. The purpose of this study is to exploit the Convolutional Neural Network (CNN) in discriminating breast MRI scans into pathological and healthy. In this study, a fully automated and efficient deep features extraction algorithm that exploits the spatial information obtained from both T2W-TSE and STIR MRI sequences to discriminate between pathological and healthy breast MRI scans. The breast MRI scans are preprocessed prior to the feature
... Show More