Islamic Azad University, Dezful Branch

The article presents a novel audio zero-watermarking technique that is free of creating any watermark data in the original audio. The strategy depends on the robust features of the audio in order to generate an audio fingerprint. Primarily, the audio is divided into non-overlapping frames, and time-based, frequency-based, and structural features are obtained out of each frame. The features are then weighted on the basis of its stability to construct a very robust composite feature representation. The adaptive thresholding scheme is used to apply a binary sequence to the composite representation and the watermark data is then appended to the binary sequence to produce the final audio fingerprint. Lastly, the features extracted along with the corresponding binary sequence that acts as a label of every frame are then fed to a Random Forest (RF) classifier. The feature vectors derived when extracting the attacked audio are fed to the trained Random Forest classifier in order to reconstruct the original binary sequence during extraction. This sequence is subsequently combined with the existing fingerprint and it becomes possible to reconstruct the watermark. The results of simulations indicate that the technique preserves the original quality of the audio, but provides good resistance to numerous types of attacks, such as additive noise, filtering, MP3 compression, re-sampling and re-quantization changes, as well as time and pitch rescaling.

The synthesis of novel nanostructures of a Cu(II) metal-organic coordination complex (MOC), referred to as [Cu2(ox)(phen)2(H2O)2](NO3)2{1}, where $${{{\text{C}}}_{{\text{2}}}}{\text{O}}_{4}^{{2 - }}$$ = ox (oxalate) and phen = C12H8N2 (1,10‑Phenanthroline), was accomplished using two distinct experimental approaches: solvothermal as well as sonochemical techniques. Notably, both methods resulted in the formation of an identical crystalline structure. A range of characterization techniques, including Powder X-ray diffraction, Scanning Electron Microscopy, and Fourier Transform Infrared Spectroscopy, were utilized to analyze the compounds. The complex is characterized by single-crystal X-ray diffraction, which shows Cu atoms (Cu2+) that are 5-coordinated. The effects of various parameters, including sonication time and temperature, were examined for the final morphology of the compounds produced by the sonochemical method. Ultimately, a Hirshfeld Surface Analysis was conducted on the 1. Density functional theory (DFT) calculations at the PBE/6-311++G*/LANL2DZ level (where Perdew–Burke–Ernzerhof (PBE) functional; 6-311++G* = all electron basis set for light atoms; LANL2DZ = effective core potential basis set for Cu) reveal that the Cu(II) complex exhibits high chemical softness (σ = 2.03 eV, inversely related to hardness η), correlating with its strong interaction with prostate cancer protein (Ead = −16.7 kJ mol–1). This thermodynamically favorable binding (negative Ead) involves electrostatic forces, hydrogen bonding, and steric complementarity, suggesting therapeutic potential.

ABSTRACT With recent advances in thermodynamic modeling and optimization, integrating modified Rankine cycles with industrial waste heat sources has become increasingly viable. This study presents a novel small-scale cogeneration system that utilizes waste heat from the clinker cooling section of a cement plant to simultaneously produce electricity and freshwater via reverse osmosis. The system incorporates a modified Rankine cycle enhanced by an ejector for improved energy recovery. A comprehensive 4E analysis – encompassing energy, exergy, economic, and environmental aspects – was carried out. Thermodynamic modeling was based on conservation laws of mass, energy, and momentum, while exergy analysis was conducted using the first and second laws of thermodynamics. Key parameters affecting performance, such as turbine inlet/outlet flow rates and boiler heat input, were optimized using a genetic algorithm developed in Python 3.10. The base case showed energy and exergy efficiencies of 29.13% and 23.08%, respectively. After optimization, these improved to 37.87% (energy) and 31.55% (exergy), alongside an 18.5% cost reduction. The results also showed that the Pressure ratio had the most significant influence on the overall system performance. Sensitivity analysis identified inlet pressure, temperature, and mass flow rate as the most critical variables affecting system performance.

ABSTRACTIn wireless sensor networks (WSNs), nodes typically operate with limited energy supplies, making efficient data gathering essential for prolonging network lifespan. One effective approach to reduce energy consumption is clustering. However, using a fixed sink to collect data can lead to energy depletion in specific nodes, causing bottlenecks. A mobile sink, on the other hand, can address this issue by enhancing network performance and reducing energy load on individual nodes. This paper introduces a hierarchical cluster‐based data aggregation method that employs fuzzy logic alongside a mobile sink to improve energy efficiency. The strategy has two main stages: clustering and data aggregation. In the clustering stage, the process is split into two steps: identifying cluster heads and organizing clusters. A fuzzy inference system assesses each node's potential as a cluster head based on factors such as remaining energy, node connectivity, and centrality. The nodes with the highest scores are selected as primary cluster heads, while those with slightly lower scores serve as backup cluster heads. Clusters are then formed around these chosen heads. In the data aggregation phase, cluster heads gather data from cluster members and forward it either to a mobile sink or directly to the base station (BS). Cluster heads located within a specified range (distance ≤ r) of the BS send data directly, while others route data via the mobile sink. This technique enhances data transmission efficiency and optimizes energy consumption, contributing to overall network improvement. The HDAMM approach demonstrated considerable advancements over earlier methods in terms of energy efficiency, delay reduction, packet delivery rate, and network longevity.

This study presents a proposal for a multi-generation wind power facility designed to fulfill the energy requirements of a five-story residential building in Rome, Italy, comprising ten zero-energy units, each with an area of 120 m2 and two bedrooms. To address the cooling and heating needs of the residential building, an Electrical Compression Chiller was integrated into system. The primary objective of this research is to establish a framework for a zero-energy building by leveraging a wind power installation to provide the energy demands of the residential building. Simulations of residential building were conducted using BEopt software. The proposed wind power facility includes a wind turbine (WT), compressed air energy storage (CAES), gas turbine (GT), and an Electrical compression chiller (ECC), all evaluated within the context of Rome's climate. System modeling utilized EES thermodynamic software, while optimization was performed using the response surface method alongside Minitab software. The optimize the model configuration achieved an exergy efficiency (ERTE) of 30.85 % and a cost rate of 159.90 $/hour, indicating that ten wind turbines represent the ideal number for establishing a wind farm in this context. A case study was carried out to assess the system's performance under Rome's climatic conditions, revealing its capability to generate 25,174,907.69 kWh of electricity, 17,691,708.55 kWh of heating, and 12,656,684.01 kWh of cooling annually. This setup could potentially reduce carbon dioxide emissions by 5135.681 tons and facilitate the expansion of 24 ha of green space in Rome. Additionally, BEopt optimization expressions were employed to simulate residential buildings in two selected cities. The findings indicated that annual energy consumption for electricity, heating, and cooling in the residential building was 1,216,637 kWh, 277,976 kWh, and 932,739.5 kWh respectively. A comparison between the buildings' energy consumption and the system's production confirmed that the proposed wind power facility can adequately meet the energy demands of the five-story residential building throughout the year while allowing for surplus energy storage for alternative uses.