Everyday, people interact with different types of human machine interfaces, and the use of them is increasing, thus, it is necessary to design interfaces which are capable of responding in an intelligent, natural, inexpensive, and accessible way, regardless of social, cultural, economic, or physical features of a user. In this sense, it has been sought out the development of small interfaces to avoid any type of user annoyance. In this paper, bioelectric signals have been analyzed and characterized in order to propose a more natural human-machine interaction system. The proposed scheme is controlled by electromyographic signals that a person can create through arm movements. Such arm signals have been analyzed and characterized by a back-propagation neural network, and by a wavelet analysis, in this way control commands were obtained from such arm electromyographic signals. The developed interface, uses Extensible Messaging and Presence Protocol (XMPP) to send control commands remotely. In the experiment, it manipulated a vehicle that was approximately 52 km away from the user, with which it can be showed that a characterized electromyographic signal can be sufficient for controlling embedded devices such as a Raspberri Pi, and in this way we can use the neural network and the wavelet analysis to generate control words which can be used inside the Internet of Things too. A Tiva-C board has been used to acquire data instead of more popular development boards, with an adequate response. One of the most important aspects related to the proposed interface is that it can be used by almost anyone, including people with different abilities and even illiterate people. Due to the existence of individual efforts to characterize different types of bioelectric signals, we propose the generation of free access Bioelectric Control Dictionary, to define and consult each characterized biosignal.
Cryptographic algorithms (RSA, DSA, and ECC) use modular exponentiation as part of the principal operation. However, Non-profiled Side Channel Attacks such as Simple Power Analysis and Differential Power Analysis compromise cryptographic algorithms that use such operation. In this work, we present a modification of a modular exponentiation algorithm implemented in programmable devices, such as the Field Programmable Gate Array, for which we use Virtex-6 and Artix-7 evaluation boards. It is shown that this proposal is not vulnerable to the attacks mentioned previously. Further, a comparison was made with other related works, which use the same family of FPGAs. These comparisons show that this proposal not only defeats physical attack but also reduces the number of resources. For instance, the present work reduces the Look-Up Tables by 3550 and the number of Flip-Flops was decreased by 62,583 compared with other works. Besides, the number of memory blocks used is zero in the present work, in contrast with others that use a large number of blocks. Finally, the clock cycles (latency) are compared in different programmable devices to perform operations.
El crecimiento acelerado de la tecnología de la información ha extendido el panorama de diferentes aplicaciones que han sido desarrolladas para el Internet de las cosas (IoT), por ejemplo, aplicaciones de monitoreo o manipulación remota de sistemas. Por este motivo, es importante desarrollar sistemas de información enfocadas a aplicaciones remotas donde los usuarios puedan interactuar, controlar dispositivos o replicar diversas tareas. En este trabajo se presenta el desarrollo de una interfaz gráfica de usuario (GUI) en Python, dicha interfaz adopta la filosofía de trabajo de código abierto y utiliza widgets de la librería Tkinter. La interfaz es utilizada en un sistema de control en lazo abierto y monitoreo de señales con un enfoque maestro-esclavo para un sistema electromecánico. Como validación experimental, se detalla el funcionamiento de la GUI en la interacción del entorno virtual con los elementos físicos del sistema.
Resumen. Los altos índices de criminalidad presentes en diversas regiones del Estado de México son un problema social de alto impacto el cual debe ser reducido. Asociado a los grupos criminales se encuentran una serie de marcas que pasando por grafitis se confunden como arte pero que son un indicativo de la zona de influencia de los grupos criminales. La aplicación de las técnicas de inteligencia artificial para resolver problemas de impacto social ha sido uno de los principales objetivos desde su concepción. Los sistemas de procesamiento de imágenes y reconocimiento inteligente de patrones son herramientas útiles para este fin. El presente trabajo presenta un sistema de alertas compuesto por dos etapas: por una parte, se desarrolla un sistema de reconocimiento de imágenes basado en redes neuronales artificiales bajo el enfoque de MultilayerPerceptron y un esquema de entrenamiento de Backpropagation; por otra parte, se desarrolla una aplicación móvil de alertas que identifica la zona por geolocalización e indica las marcas presentes que dan una idea del índice de peligrosidad de la zona, estos índices se obtienen de la correlación entre los grafitis presentes y los reportes de grupos criminales en la zona.Abstract. The high crime rates present in various regions of the State of Mexico are a high impact social problem which must be reduced. Associated with the criminal groups are a series of marks that, passing through graffiti, are confused as art, but they are indicative of the zone of influence of the criminal groups. The application of artificial intelligence techniques to solve problems of social impact has been one of the main objectives since its conception. The systems of image processing and intelligent pattern recognition are useful tools for this purpose. The present work presents an alert system composed of two stages, on the one hand an image recognition system based on artificial neural networks under the Multilayer Perceptron approach and a Backpropagation training scheme. On the other hand, a mobile application of alerts is developed that identifies the zone by
PROLOG is a programming language widely used in the generation of expert and intelligent systems, generally limited to data that is entered directly by a user in the form of software, having little or no interaction with data that is captured directly from a physical environment. This paper presents an implementation of an interface that detects the wavelengths of the visible spectrum, that is, identifies colors, colors that are stored in a knowledge base and then managed by PROLOG. This interface consists of two parts, software and hardware. The hardware is designed by means of the Arduino UNO development board, where a TCS3200 sensor is used. For the development of the software, two tools have been used, on the one hand, the standard programming of the Arduino IDE terminal has been used to manage the inputs and outputs of the Arduino board, and on the other hand, a data management system has been generated, in which PROLOG manages all the data obtained from hardware. This scheme seeks to generate color classifications in a dynamic and intelligent way in the future. The proposed system has the advantage that it is highly economical, easy to perform, uses the logical paradigm of programming, and opens the way to the design of intelligent systems managed by PROLOG from a monitoring of physical variables.
Abstract. The classic human-machine interfaces require mechanical or electronic elements which can be cumbersome or complex in their uses and implementations. As a result, interfaces of such kind can present a rigid communication with devices which we want to control, additionally they may not be a usable tool by people who have lost a body limb and who present different types of corporal disabilities.In this work is showed the development of a human-machine interface which can control a remote device by the characterization of natural human facial movements employing artificial vision and fuzzy logic.Due to the characteristics of the proposed interface, it permits that disabled, untrained, and even illiterate persons can use it easily.This implementation is able to establish a remote communication with any electronic device through the internet by the XMPP protocol, which gives it a dynamism of control over practically any geographical position in the world where internet connection exist, in this way, it is possible to integrate it into the internet of things.
Simple Power Analysis (SPA)
Abstract.Simple power analysis (SPA) attacks are widely used against several cryptosystems, principally against those based on modular exponentiation. Many types of SPA have been reported in the literature in the recent years. There is a real necessity to eliminate the vulnerabilities of cryptosystems, such as CRT-RSA or the Elliptic Curve Cryptosystem, that make them susceptible to these attacks. There are many modular exponentiation algorithms that try to reinforce the security of these systems, of which one was proposed by Da-Zhi et al.Da-zhi's algorithm was presented as a secure and efficient countermeasure against side channel attacks; however, recently it was shown that its security can be defeated. In this paper, a means of protecting the algorithm is presented. The proposed technique can be applied in any algorithm that computes dummy operations through its execution.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.