In recent years, Wireless Sensor Networks (WSNs) are attracting more attention in many fields as they are extensively used in a wide range of applications, such as environment monitoring, the Internet of Things, industrial operation control, electric distribution, and the oil industry. One of the major concerns in these networks is the limited energy sources. Clustering and routing algorithms represent one of the critical issues that directly contribute to power consumption in WSNs. Therefore, optimization techniques and routing protocols for such networks have to be studied and developed. This paper focuses on the most recent studies and algorithms that handle energy-efficiency clustering and routing in WSNs. In addition, the prime issues in these networks are discussed and summarized using comparison tables, including the main features, limitations, and the kind of simulation toolbox. Energy efficiency is compared between some techniques and showed that according to clustering mode “Distributed” and CH distribution “Uniform”, HEED and EECS are best, while in the non-uniform clustering, both DDAR and THC are efficient. According to clustering mode “Centralized” and CH distribution “Uniform”, the LEACH-C protocol is more effective.
This study presents the effect of laser energy on burning loss of magnesium from the holes' drilled in aluminum alloy 5052. High energy free running pulsed Nd:Glass laser of 300 µs pulse duration has been used to perform the experiments. The laser energy was varied from 1.0 to 8.0 Joules, The drilling processes have been carried out under atmospheric pressure and vacuum inside a specially designed chamber. Microhardness of the blind drilled holes has been investigated .The results indicated that the magnesium loss could be manipulated by adjusting the focusing conditions of the laser beam. Almost, the obtained holes were free of cracks with low taper and low sputter deposition. .The holes performed under atmospheric conditions have high
... Show MoreClimate change significantly affects photovoltaic (PV) energy potential in arid regions. This study quantifies climate change impacts on both monofacial and bifacial PV energy potential across Iraq using Community Climate System Model (CCSM4) projections under Representative Concentration Pathway (RCP) 4.5 and RCP8.5 scenarios spanning 2020–2100. Specific mathematical frameworks accounting for thermal and irradiance characteristics were applied across 18 representative regions covering Iraq’s diverse climatic zones, with bifacial systems modeled using dual-surface irradiance capture incorporating ground reflection and thermal dynamics. Results reveal distinct northwest–southe
In this research, the dynamics process of charge transfer from the sensitized D35CPDT dye to tin(iv) oxide( ) or titanium dioxide ( ) semiconductors are carried out by using a quantum model for charge transfer. Different chemical solvents Pyridine, 2-Methoxyethanol. Ethanol, Acetonitrile, and Methanol have been used with both systems as polar media surrounded the systems. The rate for charge transfer from photo-excitation D35CPDTdye and injection into the conduction band of or semiconductors vary from a to for system and from a to for the system, depending on the charge transfer parameters strength coupling, free energy, potential of donor and acceptor in the system. The charge transfer rate in D35CPDT / the syst
... Show MoreThis research proposes the application of the dragonfly and fruit fly algorithms to enhance estimates generated by the Fama-MacBeth model and compares their performance in this context for the first time. To specifically improve the dragonfly algorithm's effectiveness, three parameter tuning approaches are investigated: manual parameter tuning (MPT), adaptive tuning by methodology (ATY), and a novel technique called adaptive tuning by performance (APT). Additionally, the study evaluates the estimation performance using kernel weighted regression (KWR) and explores how the dragonfly and fruit fly algorithms can be employed to enhance KWR. All methods are tested using data from the Iraq Stock Exchange, based on the Fama-French three-f
... Show MoreThis paper introduces a novel nonparametric hybrid cyber-intelligence-based statistical process control and anomaly detection framework in time series data. It is developed to overcome the shortcomings of the classical control schemes in dealing with complex, abnormal, and noisy input data, especially when it is autocorrelated. The proposed methodology combines three technical pillars: First, it utilizes a bidirectional long-short-term memory architecture (Bi-LSTM) to capture long-term time dependency and learn nonlinear patterns, leaving only true deviations as residuals that remove trends and noises from the market. Second, it adopts the Golden Eagle Optimizer (GEO) algorithm for optimal parameter selection. This intelligent algor
... Show MoreThis study presents the multi criteria single-machine model. The machine scheduling problem (MSP) for ntasks on a single machine involves minimizing a function of three criteria: total completion time (C_j),maximum earliest (E_max), and tardiness (〖ΣT〗_j), This is an NP-hard issue. Within this work's theoretical section, we present the mathematical formulation of The presented topic thenhighlights the usefulness of the dominance rule (DR), which may be used to develop effective solutions. Whilein the practical part, one of the important exact methods; The proposed MSP tricriteria are solved by applyingthe Branch and Bound (BAB) method, which finds a set of efficient solutions for 1//F(ΣC_j ,ΣT_j ,E_max) upto n=100 jobs. The BAB appro
... Show MoreEco-friendly concrete is produced using the waste of many industries. It reduces the fears concerning energy utilization, raw materials, and mass-produced cost of common concrete. Several stress-strain models documented in the literature can be utilized to estimate the ultimate strength of concrete components reinforced with fibers. Unfortunately, there is a lack of data on how non-metallic fibers, such as polypropylene (PP), affect the properties of concrete, especially eco-friendly concrete. This study presents a novel approach to modeling the stress-strain behavior of eco-friendly polypropylene fiber-reinforced concrete (PFRC) using meta-heuristic particle swarm optimization (PSO) employing 26 PFRC various mixtures. The cement was partia
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