The localization of nodes plays a fundamental role in Wireless Sensor and Actors Networks (WSAN) identifying geographically where an event occurred, which facilitates timely response to this action. This article presents a performance evaluation of multi-hop localization range-free algorithms used in WSAN, such as Distance Vector Hop (DV-Hop), Improved DV-Hop (IDV-Hop), and the Weighted DV-Hop (WDV-Hop). In addition, we propose a new localization algorithm, merging WDV-Hop, with the weighted hyperbolic localization algorithm (WH), which includes weights to the correlation matrix of the estimated distances between the node of interest (NOI) and the reference nodes (RN) in order to improve accuracy and precision. As performance metrics, the accuracy, precision, and computational complexity are evaluated. The algorithms are evaluated in three scenarios where all nodes are randomly distributed in a given area, varying the number of RNs, the density of nodes in the network, and radio coverage of the nodes. The results show that in networks with 100 nodes, WDV-Hop outperforms the DV-Hop and IDV-Hop even if the number of RNs is reduced to 10. Moreover, our proposal shows an improvement in terms of accuracy and precision at the cost of increased computational complexity, specifically in the algorithm execution time, but without affecting the hardware cost or power consumption.

The increase of mental illness cases around the world can be described as an urgent and serious global health threat. Around 500 million people suffer from mental disorders, among which depression, schizophrenia, and dementia are the most prevalent. Revolutionary technological paradigms such as the Internet of Things (IoT) provide us with new capabilities to detect, assess, and care for patients early. This paper comprehensively survey works done at the intersection between IoT and mental health disorders. We evaluate multiple computational platforms, methods and devices, as well as study results and potential open issues for the effective use of IoT systems in mental health. We particularly elaborate on relevant open challenges in the use of existing IoT solutions for mental health care, which can be relevant given the potential impairments in some mental health patients such as data acquisition issues, lack of self-organization of devices and service level agreement, and security, privacy and consent issues, among others. We aim at opening the conversation for future research in this rather emerging area by outlining possible new paths based on the results and conclusions of this work.

The unique features of Non-Fungible Tokens (NFT) are becoming increasingly appealing as we spend more of our time online. This increased popularity is nevertheless not free of controversies, and there is a lack of clarity over the final form this digital asset will take. While there are some early adopters, the whole NFT ecosystem will have to be clarified for wider adoption, particularly the purchasing process. This research evaluates a model of the purchasing process of NFTs and the role of trust in this process. The validated model identified that the purchasing process of NFTs has four stages and each stage is affected by trust: (1) Trust in the cryptocurrency wallet, (2) trust in the cryptocurrency purchase, (3) trust in the NFT marketplace, and (4) trust in aftersales services.

Se estudia las características principales del comportamiento del consumidor en plataformas de compra en línea en el estado sur de Sonora. Esto se hace mediante un estudio cualitativo basado en la metodología de la Teoría Fundamentada. La idea principal es identificar y categorizar variables sobre la compra en línea basándose en factores relevantes como la motivación de compra, preferencias, hábitos de consumo y patrones de compra. Para llevar a cabo el estudio, se realizaron entrevistas semi-estructuradas a consumidores del estado sur de Sonora, México, con experiencia en compras en línea. De esta manera, al concluir el análisis, se obtuvieron tres categorías principales: motivación de compra, experiencias del consumidor y comportamiento. También se identificaron una serie de variables que tienen mayor influencia en las preferencias, decisión de compra y el patrón de compra en los consumidores. Los resultados obtenidos proporcionan información de utilidad para la creación de estrategias que permitan tomar decisiones efectivas mediante su aplicación en el diseño de plataformas en línea ofreciendo un servicio personalizado a los consumidores.