Search Results - (( developing mobile maximization algorithm ) OR ( java implication based algorithm ))
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Maximizing Lifetime of Homogeneous Wireless Sensor Network through Energy Efficient Clustering Method
Published 2010“…These server nodes are responsible for transmitting the data from cluster head to the base station. Our proposed algorithm for cluster head selection based on residual energy, distance, reliability and degree of mobility. …”
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Citation Index Journal -
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Automated dual-axis solar tracking system based on astronomical equation and global positioning system
Published 2015“…Therefore, this study focuses on designing and developing a portable dual-axis solar tracking system that focuses on portable and mobility purpose. …”
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Thesis -
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Delay and energy-aware routing for efficient data collection in wireless sensor networks / Ihsan Ali
Published 2024“…The presence of several mobile sinks creates a trade-off between maximizing network lifetime and minimizing delay in large-scale, time-sensitive WSNs. …”
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Efficient radio resource management algorithms for downlink long term evolution networks
Published 2018“…Hence, the major problem is developing a scheduling algorithm which creates a trade-off between the system performances. …”
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Quality of service and scheduling performance optimization in LTE networks / Abubakar Auwal Idris
Published 2017“…The developed algorithm is simulated in LTE-Sim simulator released 5 in terms of three QoS metrics (1) Packet Loss Ratio (2) Delay (3) Throughput. …”
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Arduino solar tracker with blynk / Muhammad Azim Hafizi Azlan
Published 2024“…Using IoT connectivity for remote accessibility and Arduino microcontrollers for accuracy and versatility, this modern invention marks a substantial advancement in solar technology. The system maximizes solar energy capture by ensuring correct panel alignment in real-time through the use of servo motors, light sensors, and an intelligent algorithm. …”
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Student Project -
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Advanced solar tracking system with temperature control and real-time monitoring
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Book Section -
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Quality Of Service Aware User Association For Efficient Network Slicing In Multi-Tenant 5g Networks
Published 2022“…Network slicing is one of the key technologies for fifth generation (5G) communications to overcome hurdles such as increased network density and data traffic due to the growing number of mobile devices. Multi-tenant network slicing allows multiple Mobile Virtual Network Operators (MVNOs) to share the physical network infrastructure, each known as a tenant, for service provisioning. …”
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Final Year Project / Dissertation / Thesis -
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Joint optimization of resources allocation for quality of service aware next-generation heterogeneous cellular networks / Hayder Faeq Rasool Alhashimi
Published 2025“…Then, an auction algorithm is proposed to solve the channel assignment optimization problem to maximize the spectrum efficiency (SE). …”
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Thesis -
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Digital Quran With Storage Optimization Through Duplication Handling And Compressed Sparse Matrix Method
Published 2024thesis::doctoral thesis -
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ReSTiNet: An efficient deep learning approach to improve human detection accuracy
Published 2023“…To improve the detection speed and accuracy of ReSTiNet, the residual block within the fire modules is carefully designed to increase the feature propagation and maximize the information flow in the network. The developed approach compresses the well-known Tiny-YOLO architecture while improving the following features: (i) small model size, (ii) faster detection speed, (iii) resolution of overfitting, and (iv) better performance than other compact networks such as SqueezeNet and MobileNet in terms of mAP on the Pascal VOC and MS COCO datasets. …”
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Article -
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ReSTiNet: An Efficient Deep Learning Approach to Improve Human Detection Accuracy
Published 2023“…To improve the detection speed and accuracy of ReSTiNet, the residual block within the fire modules is carefully designed to increase the feature propagation and maximize the information flow in the network. The developed approach compresses the well-known Tiny-YOLO architecture while improving the following features: (i) small model size, (ii) faster detection speed, (iii) resolution of overfitting, and (iv) better performance than other compact networks such as SqueezeNet and MobileNet in terms of mAP on the Pascal VOC and MS COCO datasets. …”
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ReSTiNet : An efficient deep learning approach to improve human detection accuracy
Published 2023“…To improve the detection speed and accuracy of ReSTiNet, the residual block within the fire modules is carefully designed to increase the feature propagation and maximize the information flow in the network. The developed approach compresses the well-known Tiny-YOLO architecture while improving the following features: (i) small model size, (ii) faster detection speed, (iii) resolution of overfitting, and (iv) better performance than other compact networks such as SqueezeNet and MobileNet in terms of mAP on the Pascal VOC and MS COCO datasets. …”
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