New variant of NLMS/F algorithm with low computational cost

Adaptive filters are used in a wide variety of signal processing applications (e.g., acoustic echo cancellation, system identification, channel equalization, etc.). Adaptive algorithms are an essential part of adaptive filters since they update the filter coefficients to model the desired response. Therefore, adaptive algorithms must have low computational cost and high speed of convergence. In this paper, a new variant of the Normalized Least-Mean-Fourth (NLMF) algorithm based on set membership is presented, in addition, a method to automatically adjust the step size is presented. To evaluate its performance, the algorithm was simulated in system identification and acoustic echo cancellation applications. The results demonstrate that the proposed algorithm improves the convergence speed and exhibits low computational cost compared to the conventional NLMS/F algorithm

Detecting Cryptojacking Web Threats: An Approach with Autoencoders and Deep Dense Neural Networks

With the growing popularity of cryptocurrencies, which are an important part of day-to-day transactions over the Internet, the interest in being part of the so-called cryptomining service has attracted the attention of investors who wish to quickly earn profits by computing powerful transactional records towards the blockchain network. Since most users cannot afford the cost of specialized or standardized hardware for mining purposes, new techniques have been developed to make the latter easier, minimizing the computational cost required. Developers of large cryptocurrency houses have made available executable binaries and mainly browser-side scripts in order to authoritatively tap into users’ collective resources and effectively complete the calculation of puzzles to complete a proof of work. However, malicious actors have taken advantage of this capability to insert malicious scripts and illegally mine data without the user’s knowledge. This cyber-attack, also known as cryptojacking, is stealthy and difficult to analyze, whereby, solutions based on anti-malware extensions, blocklists, JavaScript disabling, among others, are not sufficient for accurate detection, creating a gap in multi-layer security mechanisms. Although in the state-of-the-art there are alternative solutions, mainly using machine learning techniques, one of the important issues to be solved is still the correct characterization of network and host samples, in the face of the increasing escalation of new tampering or obfuscation techniques. This paper develops a method that performs a fingerprinting technique to detect possible malicious sites, which are then characterized by an autoencoding algorithm that preserves the best information of the infection traces, thus, maximizing the classification power by means of a deep dense neural network

Physical Variable Measurement Techniques for Fault Detection in Electric Motors

Induction motors are widely used worldwide for domestic and industrial applications. Fault detection and classification techniques based on signal analysis have increased in popularity due to the growing use of induction motors in new technologies such as electric vehicles, automatic control, maintenance systems, and the inclusion of renewable energy sources in electrical systems, among others. Hence, monitoring, fault detection, and classification are topics of interest for researchers, given that the presence of a fault can lead to catastrophic consequences concerning technical and financial aspects. To detect a fault in an induction motor, several techniques based on different physical variables, such as vibrations, current signals, stray flux, and thermographic images, have been studied. This paper reviews recent investigations into physical variables, instruments, and techniques used in the analysis of faults in induction motors, aiming to provide an overview on the pros and cons of using a certain type of physical variable for fault detection. A discussion about the detection accuracy and complexity of the signals analysis is presented, comparing the results reported in recent years. This work finds that current and vibration are the most popular signals employed to detect faults in induction motors. However, stray flux signal analysis is presented as a promising alternative to detect faults under certain operating conditions where other methods, such as current analysis, may fail

Estructura alternante para sistemas de beamforming adaptativo basada en los algoritmos APL/SR-LMS

Beamforming is a wireless communication technique used in telecommunications applications, which is used to separate a desired signal from interfering signals. This technique increases the coverage range and reduces the interference problem, improving the performance of the systems. To achieve this operation, adaptive algorithms are required. In this work, an alternating structure for beamforming systems is presented, which is composed of two algorithms, the Sign Regressor Least Mean Square (SR-LMS) and the Affine Projection Like (APL) algorithm. The results show that the proposed structure has the best characteristics of the combined algorithms, obtaining an algorithm with a high convergence speed and lower computational cost compared to other algorithms based on conventional convex combinations.El Beamforming es una técnica de comunicación inalámbrica utilizada en aplicaciones de telecomunicaciones, la cual se usa para separar una señal deseada de señales interferentes. Esta técnica aumenta el rango de cobertura y reduce el problema de interferencia, mejorando el rendimiento de los sistemas. Para lograr dicho funcionamiento se requiere de algoritmos adaptativos. En este trabajo, se presenta una estructura alternante para sistemas beamforming, la cual está compuesta por dos algoritmos adaptativos, el Sign Regressor Least Mean Square (SR-LMS) y el algoritmo Affine Projection Like (APL). Los resultados demuestran que la estructura propuesta tiene las mejores características de los algoritmos combinados, obteniendo un algoritmo con una alta velocidad de convergencia y menor costo computacional en comparación con otros algoritmos basados en combinaciones convexas convencionales

Modelo de seguridad para la prevención del lavado de dinero.

TESINA C7.142

GANADERIA EJIDAL Y EMIGRACION EN EL MUNICIPIO DE SAN LUIS DEL CORDERO, DURANGO, NORTE DE MÉXICO

Extensive ejidal cattle in northern México has developed due adequate water soil and climate conditions; nevertheless, in the past few years a natural resources harm has been observed as well as a trend of emigration of the population. The methodology utilized in this paper was supported in a pool to ejidal cattle producers of the San Luis del Cordero County in the state of Durango, by means of stratified random sampling based on the number of cows. Results have shown that producers owning less than 20 cows depend mostly on remittances from emigrants. This group of producers also are less organized and with less technology for the agricultural and cattle activities. This study presents a characterization of the ejidal cattle production system identifying the main factors that limits this activity. It is concluded that the ejidal cattle located in the middle part of the Occidental Sierra Madre survive due the remittances of emigrants and that the economical growth of this people is more limited by natural causes rather than economical since the people is getting older and the forage availability is diminishing

Determinación de la calidad del semen criopreservado con lecitina de soya o yema de huevo, en machos cabríos

The objective was to compare the quality of cryopreserved goat semen with soy lecithin or egg yolk. The semen was collected from male goats (n=4), two commercial diluents AndroMed® (1% soy lecithin, LS); Optidyl® (20% (v/v) Tris-egg yolk; TY), and a citrate-egg yolk-based diluent (CY) were used in fresh semen (SF) and then cooled from 37 to 4 °C for 2 h (refrigerated semen, SR), afterwards straws were filled with semen and frozen in liquid nitrogen at -196 °C (SC). There were no differences (p>0.05) between diluents in the SF in the mass motility (MM; 4.7±0.26), sperm viability (VE; 74.1±1.66) and individual motility (MI; 62.3±4.0). In the same sense, for the SR there was no difference (p>0.05) between diluents with respect to MM (3.83±0.4) and MI (52.1±6.0), however, the VE varied (p<0.05) according to the diluent, observing the lowest viability in LS vs CY and TY (51.0±13.0 vs 71.3±3.0 and 69.0±3.1). Regarding SC the MM, MI and VE obtained better values (p<0.05) with the diluent TY vs LS and CY (2.4±0.5, 32.5±8.3, 41.3±13.0). The results showed a better cryopreservation of goat semen with the diluent Tris-yolk compared to that of soy lecithinEl objetivo fue comparar la calidad del semen caprino criopreservado con diferentes tratamientos a base de lecitina de soya o yema de huevo. El semen fue colectado de machos cabríos Alpinos (n=4), se utilizaron dos diluyentes comerciales: AndroMed® (1% de lecitina de soya, LS); Optidyl® con 20% (v/v) de Tris-yema de huevo; TY), y un tercer diluyente a base de citrato-yema de huevo (CY), en semen fresco (SF) y después fue enfriado de 37 a 4 °C durante 2 h; semen refrigerado (SR), posteriormente se llenaron pajillas con semen y se congelaron en nitrógeno líquido a -196 °C (SC). No existieron diferencias (p>0.05) entre diluyentes en el SF respecto a motilidad masal (MM; 4.7±0.26), viabilidad espermática (VE; 74.1±1.66) y motilidad individual (MI; 62.3±4.0). En el mismo sentido, para el SR no existió diferencia (p>0.05) entre diluyentes respecto a MM=3.83±0.4, y MI= 52.1±6.0, sin embargo, la VE varió (p<0.05) de acuerdo al diluyente, observando la menor viabilidad en LS vs. CY y TY (51.0±13.0 vs 71.3±3.0 y 69.0±3.1). Respecto al SC, la MM, MI y VE favorecieron (p<0.05) al diluyente TY vs. LS y CY (2.4±0.5, 32.5±8.3, 41.3±13.0). Los resultados mostraron una mejor crio-preservación del semen caprino con el diluente Tris-yema respecto al de lecitina de soy