Wireless Body Area Sensor Network (WBASN) is gaining significant attention due to its applications in smart health offering cost-effective, efficient, ubiquitous, and unobtrusive telemedicine. WBASNs face challenges including interference, Quality of Service, transmit power, and resource constraints. Recognizing these challenges, this paper presents an energy and Quality of Service-aware routing algorithm. The proposed algorithm is based on each node's Collaboratively Evaluated Value (CEV) to select the most suitable cluster head (CH). The Collaborative Value (CV) is derived from three factors, the node's residual energy, the distance vector between nodes and personal device, and the sensor's density in each CH. The CEV algorithm operates in the following manner: CHs are dynamically selected in each transmission round based on the nodes' CVs. The algorithm considered the patient's condition classification to guarantee safety and attain a response speed appropriate for their current state. So, data is categorized into Very-Critical, Critical, and Normal data classes using the supervised learning vector quantization (LVQ) classifier. Very Critical data is sent to the emergency center to dispatch an ambulance, Critical data is transmitted to a doctor, and Normal data is sent to a data center. This methodology promotes efficient and reliable intra-network communication, ensuring prompt and precise data transmission, and reducing frequent recharging. Comparative analyses reveal that the proposed algorithm outperforms ERRS (Energy-Efficient and Reliable Routing Scheme) and LEACH (low energy adaptive clustering hierarchy) regarding network longevity by 27% and 33%, augmenting network stability by 12% and 45% over the aforementioned protocols, respectively. The performance was conducted in OMNeT++ simulator
Face recognition and identity verification are now critical components of current security and verification technology. The main objective of this review is to identify the most important deep learning techniques that have contributed to the improvement in the accuracy and reliability of facial recognition systems, as well as highlighting existing problems and potential future research areas. An extensive literature review was conducted with the assistance of leading scientific databases such as IEEE Xplore, ScienceDirect, and SpringerLink and covered studies from the period 2015 to 2024. The studies of interest were related to the application of deep neural networks, i.e., CNN, Siamese, and Transformer-based models, in face recogni
... Show MoreThe university course timetable problem (UCTP) is typically a combinatorial optimization problem. Manually achieving a useful timetable requires many days of effort, and the results are still unsatisfactory. unsatisfactory. Various states of art methods (heuristic, meta-heuristic) are used to satisfactorily solve UCTP. However, these approaches typically represent the instance-specific solutions. The hyper-heuristic framework adequately addresses this complex problem. This research proposed Particle Swarm Optimizer-based Hyper Heuristic (HH PSO) to solve UCTP efficiently. PSO is used as a higher-level method that selects low-level heuristics (LLH) sequence which further generates an optimal solution. The proposed a
... Show More<span lang="EN-US">Proper employment of Hybrid Wind/ PV system is often implemented near the load, and it is linked with the grid to study dynamic stability analysis. Generally, instability is because of sudden load demand variant and variant in renewable sources generation. As well as, weather variation creates several factors that affect the operation of the integrated hybrid system. So this paper introduces output result of a PV /wind via power electronic technique; DC chopper; that is linked to Iraqi power system to promote the facilitating achievement of Wind/ PV voltage. Moreover, PSS/E is used to study dynamic power stability for hybrid system which is attached to an effective region of Iraqi Network. The hybrid system
... Show MoreThis research has come out with that, function-based responsibility accounting system has harmful side – effects preventing it of achieving its controlling objective, that is, goal congruence, which are due to its un integrated measures, its focus on measuring measurable behaviors while neglecting behaviors that are hardly measured, and its dependence on standard operating procedures.
In addition, the system hypotheses and measures are designed to fit previous business environment, not the current environment.
The research has also concluded that the suggestive model, that is, activity-based responsibility accounting is designed to get ride of harmful side – effects of functi
... Show MoreTwo- dimensional numerical simulations are carried out to study the elements of observing a Dirac point source and a Dirac binary system. The essential features of this simulation are demonstrated in terms of the point spread function and the modulation transfer function. Two mathematical equations have been extracted to present, firstly the relationship between the radius of optical telescope and the distance between the central frequency and cut-off frequency of the optical telescope, secondly the relationship between the radius of the optical telescope and the average frequency components of the modulation transfer function.