Motion-Encoded Electric Charged Particles Optimization for Moving Target Search Using Unmanned Aerial Vehicles.

In this paper, a new optimization algorithm called motion-encoded electric charged particles optimization (ECPO-ME) is developed to find moving targets using unmanned aerial vehicles (UAV). The algorithm is based on the combination of the ECPO (i.e., the base algorithm) with the ME mechanism. This study is directly applicable to a real-world scenario, for instance the movement of a misplaced animal can be detected and subsequently its location can be transmitted to its caretaker. Using Bayesian theory, finding the location of a moving target is formulated as an optimization problem wherein the objective function is to maximize the probability of detecting the target. In the proposed ECPO-ME algorithm, the search trajectory is encoded as a series of UAV motion paths. These paths evolve in each iteration of the ECPO-ME algorithm. The performance of the algorithm is tested for six different scenarios with different characteristics. A statistical analysis is carried out to compare the results obtained from ECPO-ME with other well-known metaheuristics, widely used for benchmarking studies. The results found show that the ECPO-ME has great potential in finding moving targets, since it outperforms the base algorithm (i.e., ECPO) by as much as 2.16%, 5.26%, 7.17%, 14.72%, 0.79% and 3.38% for the investigated scenarios, respectively.

Optimizing Router Placement of Indoor Wireless Sensor Networks in Smart Buildings for IoT Applications.

Internet of Things (IoT) is characterized by a system of interconnected devices capable of communicating with each other to carry out specific useful tasks. The connection between these devices is ensured by routers distributed in a network. Optimizing the placement of these routers in a distributed wireless sensor network (WSN) in a smart building is a tedious task. Computer-Aided Design (CAD) programs and software can simplify this task since they provide a robust and efficient tool. At the same time, experienced engineers from different backgrounds must play a prominent role in the abovementioned task. Therefore, specialized companies rely on both; a useful CAD tool along with the experience and the flair of a sound expert/engineer to optimally place routers in a WSN. This paper aims to develop a new approach based on the interaction between an efficient CAD tool and an experienced engineer for the optimal placement of routers in smart buildings for IoT applications. The approach follows a step-by-step procedure to weave an optimal network infrastructure, having both automatic and designer-intervention modes. Several case studies have been investigated, and the obtained results show that the developed approach produces a synthesized network with full coverage and a reduced number of routers.

The effects of cell therapy on seizures in animal models of epilepsy: protocol for systematic review and meta-analysis of preclinical studies.

BACKGROUND: Epilepsy is one of the most common and serious brain conditions, characterised by recurrent unprovoked seizures. It affects about 1% of the population worldwide. Despite a range of antiepileptic drugs being available, one third of the patients do not achieve adequate seizure control. Only a minority of these patients may be suitable to undergo surgical resection of the seizure focus, but this is an invasive and not always successful procedure. There is an urgent need to develop more effective treatment options for uncontrolled seizures. With the recent advances in regenerative and translational medicine, cell therapies could prove to be beneficial. Here we describe the protocol for a proposed systematic review and meta-analysis to assess the effects for cell transplantation in animal models of epilepsy. METHODS: We will include all preclinical animal models of epilepsy that evaluate the effects of cell transplantation compared to the untreated control. The primary outcome will be the change in frequency and duration of seizures from baseline measured by video electroencephalography (EEG). The secondary outcomes will include histological and neurobehavioural assessments. We will perform an electronic search of MEDLINE via PubMed, Web of Science, and EMBASE. Search results will be screened independently by two reviewers and confirmed by a third reviewer. Data from eligible studies will be extracted and pooled, and the summary estimate of effect size will be calculated using DerSimonian and Laird random effects meta-analysis. Heterogeneity will be explored using sub-group meta-analysis, and meta-regression risk of bias will be assessed by using the CAMARADES checklist for study quality tool. DISCUSSION: The purpose of this systematic review is to assess and summarise the existing literature in the field of cell transplantation as a treatment for epilepsy in animal models. Efficacy will be measured by evaluating the reduction in seizure intervals, number, and duration, within animal models of epilepsy. Analysis of the existing literature will mark the achievement made in the field and locate the existing gaps, a process that will aid in the search for the next needed step. SYSTEMATIC REVIEW REGISTRATION: CRD42018103628.