Review of Traveling Salesman Problem for the genetic algorithms

Genetic Algorithms (GAs) are an evolutionary technique that uses the operators like mutation, crossover and the selection of the most fitted element as solution for problems optimization. The Traveling Salesman Problem (TSP) finds a path with minimal length, closed within a weighted graph in all its nodes and it visits each of them once. This problem is found in many real world applications and where a good solution might help. There are applied many methods for finding a solution for the TSP, but during this study GAs are used as an approximate method of TSP

Bayesiane filter for detecting a spam

The detected of spam messages in terms that better having a spam email in the inbox than a ham message in the junk, has been investigated recently. The main contribution of the paper consists in comparing three antispam filters used more nowadays, and will find that which is filter is of the future. By using filters we will also create some patterns as the result of training with different number of emails. Simulations show that due to the trainging of the filters it will be easier to detect the spams

Implementing 3D Warping Method In Wavelet Domain

A wide class of operations on images can be performed directly in the wavelet domain by operating on coefficients of the wavelet transforms of the images and other matrices defined by these operations. Operating in the wavelet domain enables one to perform these operations progressively in a coarse-to-fine fashion, operate on different resolutions, manipulate features at different scales, and localize the operation in both the spatial and the frequency domains. Performing such operations in the wavelet domain and then reconstructing the result is also often more efficient than performing the same operation in the standard direct fashion. Performing 3D warping in the wavelet domain is in many cases faster than their direct computation. In this paper we demonstrate our approach both on still and sequences of images

A Wearable Fall Detection System based on LoRa LPWAN Technology

Several technological solutions now available in the market offer the possibility of increasing the independent life of people who by age or pathologies otherwise need assistance. In particular, internet-connected wearable solutions are of considerable interest, as they allow continuous monitoring of the user. However, their use poses different challenges, from the real usability of a device that must still be worn to the performance achievable in terms of radio connectivity and battery life. The acceptability of a technology solution, by a user who would still benefit from its use, is in fact often conditioned by practical problems that impact the person’s normal lifestyle. The technological choices adopted in fact strongly determine the success of the proposed solution, as they may imply limitations both to the person who uses it and to the achievable performance. In this document, targeting the case of a fall detection sensor based on a pair of sensorized shoes, the effectiveness of a real implementation of an Internet of Things technology is examined. It is shown how alarming events, generated in a metropolitan context, are effectively sent to a supervision system through Low Power Wide Area Network technology without the need for a portable gateway. The experimental results demonstrate the effectiveness of the chosen technology, which allows the user to take advantage of the support of a wearable sensor without being forced to substantially change his lifestyle

Optimal Share Factors in the Push-Sum Algorithm for Ring and Random Geometric Graph Sensor Networks

The convergence speed of an asynchronous point-to-point version of the push-sum algorithm in sensor networks is investigated both through numerical simulations and theoretical arguments. The main contribution of the paper consists in studying the application of such algorithm in realistic scenarios, represented by non fully-meshed networks. Simulations show that, in this case, convergence may be strongly dependent on the adopted share factor, whose value should be optimized as a function of the connectivity level of the network. Optimum shares are derived for some common topologies, like the ring and the random geometric graph. The effect of possible link failures is also investigated

Efficiency of Unicast and Broadcast Gossip Algorithms for Wireless Sensor Networks

Gossip is a well-known technique for distributed computing in an arbitrarily connected network, that can be adopted effectively in wireless sensor networks. Gossip algorithms have been widely studied in previous literature, but mostly from a theoretical point of view. The aim of this paper isto verify the behavior of the gossip approach in practicalscenarios, through the analysis and interpretation of simulated results. So, we investigate the impact of optimizing the neighbor selection probabilities, the effect of multiple link failures and that of limited transmission radius. The possibility to use broadcast-like algorithms to increase the rate of convergence in averaging problems is also discussed and its advantage estimated