Recycled needle punched natural jute fiber mats with 32 % by vol. fiber volume content were used as reinforcement for unsaturated polyester matrix composites. This study intended to study the durability of jute mat composites by investigating the flexural properties of jute mat composites including flexural strength and modulus under the effect of hot water absorption at 100oC for 96, 192, 384 h immersion times compared to the virgin specimens. The results showed that as the immersion time of the composites increases, the water absorbed by the composites increases and so the thickness swelling increases. As a result of that, the flexural strength and modulus of jute mats composites decrease compared to the virgin specimens. On the other hand, when the immersed specimens are dried for 6 hours, the flexural strength and modulus of the composites was recovered compared to the immersed specimens due to the decrease in the absorbed water content.

The aims of this research are to investigate the effect of different surface treatmentmethods on the different properties of date palm fiber (DPF) compared to raw DPF fibers such as surface morphology, density, thermal stability, and tensile properties. The first surface treatment is called surface hand cleaning which can be carried out by cleaning the fibers by soft sand cloth; the second one is the same as the first one after DPF heat treatment in the furnace at 100∘C for 1.5 h and the third one is by chemical treatment with 1% NaOH at 100∘C for 1 h.The results showed that the mechanical performance of DPF was enhanced by the different treatments and the chemical treatment has pronounced effect on the behavior of DPF. Raw fibers showed the highest variability and presented the lowest value ofWeibull modulus, whereas the fibers showed less variability by carrying out the different treatments. Moreover, using soda treatment cleans the fiber surface which causes fibrillation and therefore the tensile strength of the fibers increases.

The aims of this research are to investigate the effect of different surface treatmentmethods on the different properties of date palm fiber (DPF) compared to raw DPF fibers such as surface morphology, density, thermal stability, and tensile properties. The first surface treatment is called surface hand cleaning which can be carried out by cleaning the fibers by soft sand cloth; the second one is the same as the first one after DPF heat treatment in the furnace at 100∘C for 1.5 h and the third one is by chemical treatment with 1% NaOH at 100∘C for 1 h.The results showed that the mechanical performance of DPF was enhanced by the different treatments and the chemical treatment has pronounced effect on the behavior of DPF. Raw fibers showed the highest variability and presented the lowest value ofWeibull modulus, whereas the fibers showed less variability by carrying out the different treatments. Moreover, using soda treatment cleans the fiber surface which causes fibrillation and therefore the tensile strength of the fibers increases.

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Coverage is one of the most important performance metrics for wireless sensor network (WSN) since it reflects how well a sensor field is monitored. The coverage issue in WSNs depends on many factors, such as the network topology, sensor sensing model and the most important one is the deployment strategy. Random deployment of the sensor nodes can cause coverage holes formulation. This problem is non-deterministic polynomial-time hard problem. So in this study, a new centralised deployment algorithm based on the immune optimisation algorithm is proposed to relocate the mobile nodes after the initial configuration to maximise the coverage area. Moreover, the proposed algorithm limits the moving distance of the mobile nodes to reduce the dissipation energy in mobility and to ensure the connectivity among the sensor nodes. The performance of the proposed algorithm is compared with the previous algorithms using Matlab simulation. Simulation results clear that the proposed algorithm based on binary and probabilistic sensing models improves the network coverage and the redundant covered area with minimum moving consumption energy. Furthermore, the simulation results show that the proposed algorithm also works when obstacles appear in the sensing field.

Coverage is one of the most important performance metrics for wireless sensor network (WSN) since it reflects how well a sensor field is monitored. The coverage issue in WSNs depends on many factors, such as the network topology, sensor sensing model and the most important one is the deployment strategy. Random deployment of the sensor nodes can cause coverage holes formulation. This problem is non-deterministic polynomial-time hard problem. So in this study, a new centralised deployment algorithm based on the immune optimisation algorithm is proposed to relocate the mobile nodes after the initial configuration to maximise the coverage area. Moreover, the proposed algorithm limits the moving distance of the mobile nodes to reduce the dissipation energy in mobility and to ensure the connectivity among the sensor nodes. The performance of the proposed algorithm is compared with the previous algorithms using Matlab simulation. Simulation results clear that the proposed algorithm based on binary and probabilistic sensing models improves the network coverage and the redundant covered area with minimum moving consumption energy. Furthermore, the simulation results show that the proposed algorithm also works when obstacles appear in the sensing field.

Coverage is one of the most important performance metrics for wireless sensor network (WSN) since it reflects how well a sensor field is monitored. The coverage issue in WSNs depends on many factors, such as the network topology, sensor sensing model and the most important one is the deployment strategy. Random deployment of the sensor nodes can cause coverage holes formulation. This problem is non-deterministic polynomial-time hard problem. So in this study, a new centralised deployment algorithm based on the immune optimisation algorithm is proposed to relocate the mobile nodes after the initial configuration to maximise the coverage area. Moreover, the proposed algorithm limits the moving distance of the mobile nodes to reduce the dissipation energy in mobility and to ensure the connectivity among the sensor nodes. The performance of the proposed algorithm is compared with the previous algorithms using Matlab simulation. Simulation results clear that the proposed algorithm based on binary and probabilistic sensing models improves the network coverage and the redundant covered area with minimum moving consumption energy. Furthermore, the simulation results show that the proposed algorithm also works when obstacles appear in the sensing field.

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