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The positioning problem considered in this paper is an attempt to find system’s of a few points position using accelerations. Today’s industry provides with various types of accelerometers suitable for acceleration measure. That data may be used to trace object movement. Final results showed that such movement trace is possible and may be applicable. The results also showed origins for errors which according to the results, are quite high globally. The final conclusion follows: the model created must be analized further in a deeper level, and error origins must be eliminated or at least minimized by either chosing different solving or modeling methods, either by revising used ones.

The layout optimization-based model is a significant issue for increasing the utilization rate of the wind farm and minimizing its cost per unit of power. For the accurate and reliable wind farm layout optimization design, a novel algorithm based on the hybridization of equilibrium optimizer (EO) and pattern search (PS) technique, named EO-PS, is proposed in this paper. The proposed EO-PS operates in two phases. The first phase implements the EO to explore the search space and reach the promising regions by using an equilibrium pool of elite particles, which contributes to maintaining the diversity of solutions. The second phase integrates the PS to guide the searching towards better vicinities and achieve a high-quality solution by using its detecting and pattern movements to boost the exploitation ability of the proposed method in the last steps. The presented EO-PS algorithm is implemented to deal with single and multi-objective optimization aspects of wind farm layout optimization using different wind speed scenarios. Furthermore, the proposed algorithm is investigated on irregular land space in the Gulf of Suez-Red Sea in Egypt to achieve the optimal layout configuration of the wind farm, which is vital for possible practical planning trends. The comprehensive results and analyses have affirmed that the proposed EO-PS can achieve competitive performance compared to the other state-of-the-state methods, especially in terms of the solution' quality and reliability. • A novel algorithm based on the hybridization optimization approach is proposed. • The proposed approach integrates the merits of two schemes to achieve a high quality of solutions. • The optimization of wind farm layout addresses the optimum sitting among the wind turbines. • The Gulf of Suez-Red Sea in Egypt were used as a realistic case study in this work. [ABSTRACT FROM AUTHOR]

Background and Aims: A present prospective study was conducted to evaluate ocular changes occurring in patients undergoing spine surgery in the prone position. Material and Methods: A total of 44 patients of either sex, belonging to American society of Anaesthesiology I and II (aged 18-60 years) scheduled for elective spine surgery in prone position were enrolled in the study. Baseline IOP and MAP measurement were taken prior to induction. After induction of anaesthesia patients were intubated using flexo-metallic tube of appropriate size. IOP and MAP were recorded after induction of anaesthesia, following completion of surgery and immediately after turning the patient supine and 30 min following extubation. Blood loss and duration of surgery was also noted. The OPP was derived using the formula (OPP = MAP-IOP). Ophthalmic examination was also performed using direct and indirect ophthalmoscopy on the day prior to surgery and on first post-operative day to rule out anterior ischemic optic neuropathy (AION), posterior ischemic optic neuropathy (PION), and retinal ischemia. Results: Mean IOP significantly increased (18.91 ± 3.56 mm Hg) (P < 0.001) at the end of surgery as compared to baseline value 12.85 ± 3.07 mm Hg. As a result mean OPP significantly reduced (75.12 ± 16.45) (P = 0.0018) at the end of the procedure. Conclusion: In patient's undergoing spine surgery in the prone position, careful patient positioning with no extrinsic pressure on the eyes, minimal surgical time and blood loss, and prevention of intraoperative hypotension, should be ensured to prevent the IOP rise and a reduction in OPP which can further prevent post-operative visual disturbance.

Background and Aims: A present prospective study was conducted to evaluate ocular changes occurring in patients undergoing spine surgery in the prone position. Material and Methods: A total of 44 patients of either sex, belonging to American society of Anaesthesiology I and II (aged 18-60 years) scheduled for elective spine surgery in prone position were enrolled in the study. Baseline IOP and MAP measurement were taken prior to induction. After induction of anaesthesia patients were intubated using flexo-metallic tube of appropriate size. IOP and MAP were recorded after induction of anaesthesia, following completion of surgery and immediately after turning the patient supine and 30 min following extubation. Blood loss and duration of surgery was also noted. The OPP was derived using the formula (OPP = MAP-IOP). Ophthalmic examination was also performed using direct and indirect ophthalmoscopy on the day prior to surgery and on first post-operative day to rule out anterior ischemic optic neuropathy (AION), posterior ischemic optic neuropathy (PION), and retinal ischemia. Results: Mean IOP significantly increased (18.91 ± 3.56 mm Hg) (P < 0.001) at the end of surgery as compared to baseline value 12.85 ± 3.07 mm Hg. As a result mean OPP significantly reduced (75.12 ± 16.45) (P = 0.0018) at the end of the procedure. Conclusion: In patient's undergoing spine surgery in the prone position, careful patient positioning with no extrinsic pressure on the eyes, minimal surgical time and blood loss, and prevention of intraoperative hypotension, should be ensured to prevent the IOP rise and a reduction in OPP which can further prevent post-operative visual disturbance. [ABSTRACT FROM AUTHOR]

This paper studies the possibility of upper bounding the position error for range-based positioning algorithms in wireless sensor networks. In this study, we argue that in certain situations when the measured distances between sensor nodes have positive errors, e.g., in non-line-of-sight (NLOS) conditions, the target node is confined to a closed bounded convex set (a feasible set) which can be derived from the measurements. Then, we formulate two classes of geometric upper bounds with respect to the feasible set. If an estimate is available, either feasible or infeasible, the position error can be upper bounded as the maximum distance between the estimate and any point in the feasible set (the first bound). Alternatively, if an estimate given by a positioning algorithm is always feasible, the maximum length of the feasible set is an upper bound on position error (the second bound). These bounds are formulated as nonconvex optimization problems. To progress, we relax the nonconvex problems and obtain convex problems, which can be efficiently solved. Simulation results show that the proposed bounds are reasonably tight in many situations, especially for NLOS conditions. [ABSTRACT FROM AUTHOR]