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Purpose: This paper aims to illustrate the potential of high-frequency data for tourism and hospitality analysis, through two research objectives: First, this study describes and test a novel high-frequency forecasting methodology applied on big data characterized by fine-grained time and spatial resolution; Second, this paper elaborates on those estimates' usefulness for visitors and tourism public and private stakeholders, whose decisions are increasingly focusing on short-time horizons. Design/methodology/approach: This study uses the technical communications between mobile devices and WiFi networks to build a high frequency and precise geolocation of big data. The empirical section compares the forecasting accuracy of several artificial intelligence and time series models. Findings: The results robustly indicate the long short-term memory networks model superiority, both for in-sample and out-of-sample forecasting. Hence, the proposed methodology provides estimates which are remarkably better than making short-time decision considering the current number of residents and visitors (Naïve I model). Practical implications: A discussion section exemplifies how high-frequency forecasts can be incorporated into tourism information and management tools to improve visitors' experience and tourism stakeholders' decision-making. Particularly, the paper details its applicability to managing overtourism and Covid-19 mitigating measures. Originality/value: High-frequency forecast is new in tourism studies and the discussion sheds light on the relevance of this time horizon for dealing with some current tourism challenges. For many tourism-related issues, what to do next is not anymore what to do tomorrow or the next week. Plain Language Summary: This research initiates high-frequency forecasting in tourism and hospitality studies. Additionally, we detail several examples of how anticipating urban crowdedness requires high-frequency data and can improve visitors' experience and public and private decision-making. [ABSTRACT FROM AUTHOR]

This paper presents the replacement of a traditional wired communication link of the hyperbaric chambers with a wireless ZigBee-based system. This move allows a reduction in the costs of seals capable of withstanding the internal pressures and gives rise to a more versatile system. The new system is able to capture and process individual vital signs like the electrocardiography signal, and other analog sources, sending the data to an external computer and allowing analysis, representation and sharing with medical staff. This system solves such problems as the attenuation of the signal produced by the metal walls of the hyperbaric chamber and has a coverage area large enough to manage up to six patients with an effective data rate conversion of 2kHz. Furthermore, a battery-based and multiparameter platform is designed for multipatient hyperbaric chambers. [ABSTRACT FROM AUTHOR]

This paper presents a wireless system to send biosignals outside a hyperbaric chamber avoiding wires going through the chamber walls. Hyperbaric chambers are becoming more and more common due to new indications of hyperbaric oxygen treatments. Metallic walls physically isolate patients inside the chamber, where getting a patient’s vital signs turns into a painstaking task. The paper proposes using a ZigBee-based network to wirelessly transmit the patient's biosignals to the outside of the chamber. In particular, a wearable battery supported device has been designed, implemented and tested. Although the implementation has been conducted to transmit the electrocardiography signal, the device can be easily adapted to consider other biosignals. [ABSTRACT FROM AUTHOR]

We report a detailed analysis about the memory soft error rate (SER) dependence with transistor design parameters for six-transistor (6T) SRAM cells fabricated on a 65-nm CMOS commercial technology. SER data are obtained from accelerated test with an Am-241 alpha source. Five 6T cells with different nMOS and pMOS transistors size combinations were fabricated and characterized. After verifying that transistor width increase always provides higher critical charge values, SER data show that this value is improved only when increasing the pMOS transistors width. Memory cells containing non-minimum-width nMOS transistors always exhibit worse SER values than cells with minimum-size ones. In addition, one cell with a higher Qcrit than another can show a worse SER depending on the transistor type whose size is being enlarged. Accordingly to this, we have found that SER may be increased by 76% without modifying cell structure nor impacting cell area. This behavior is qualitatively and quantitatively explained through an analytical model that relates SER to Qcrit and the transistor design parameters. [ABSTRACT FROM PUBLISHER]

This work proposes a methodology to estimate the statistical distribution of the probability that a 6T bit-cell starts up to a given logic value in SRAM memories for PUF applications. First, the distribution is obtained experimentally in a 65-nm CMOS device. As this distribution cannot be reproduced by electrical simulation, we explore the use of an alternative parameter defined as the distance between the origin and the separatrix in the bit-cell state space to quantify the mismatch of the cell. The resulting distribution of this parameter obtained from Monte Carlo simulations is then related to the start-up probability distribution using a two-component logistic function. The reported results show that the proposed imbalance factor is a good predictor for PUF-related reliability estimation with the advantage that can be applied at the early design stages. [ABSTRACT FROM AUTHOR]

Information and communications technologies (ICT)—and more precisely, their use from fulltime connected mobile gadgets—offer valuable opportunities to interact with tourists using their own devices. In order to exploit these benefits, destinations should have appropriate digital infrastructure to allow for bidirectional smart communication with their visitors. However, the spatial distribution of such coverage, and the geographical concurrence of tourism activities and ICT infrastructure, have been poorly examined. This paper contributes to this analysis by quantifying digital accessibility with both a broader regional approach and a narrower local perspective. First, we propose a digital immersion index, and apply it to the Balearic Islands, Spain. Second, alternative Moran's indices are used to study the spatial distribution and correlation of tourism and technological infrastructure for a local destination. The results are presented through easily interpretable maps, which can inform tourism policies, such as identifying and prioritizing ITC investments. [ABSTRACT FROM AUTHOR]

Physically unclonable functions (PUFs) are used as low-cost cryptographic primitives in device authentication and secret key creation. SRAM-PUFs are well-known as entropy sources; nevertheless, due of non-deterministic noise environment during the power-up process, they are subject to low challenge-response repeatability. The dependability of SRAM-PUFs is usually accomplished by combining complex error correcting codes (ECCs) with fuzzy extractor structures resulting in an increase in power consumption, area, cost, and design complexity. In this study, we established effective metrics on the basis of the separatrix concept and cell mismatch to estimate the percentage of cells that, due to the effect of variability, will tend to the same initial state during power-up. The effects of noise and temperature in cell start-up processes were used to validate the proposed metrics. The presented metrics may be applied at the SRAM-PUF design phases to investigate the impact of different design parameters on the percentage of reliable cells for PUF applications. [ABSTRACT FROM AUTHOR]

Modern agriculture requires technology to give precise measures about relevant parameters such as pest control. Here, we developed a decision support system (DSS) based on semi-automatic pest monitoring for managing the olive fruit fly Bactrocera oleae (Rossi), in Mallorca (Balearic Islands, Spain). The DSS was based on an algorithm that took into account spatial and temporal patterns of olive fruit fly population in an orchard where all trees were georeferenced, thus precise treatments against the pest were conducted through a location aware system (LAS). The olive fruit fly adult population was monitored by using ad hoc off-the-grid autonomous electronic traps.The results were compared with those obtained with conventional methods. For a pilot trial, we selected an olive-producing orchard, where from June to October 2015, three plots using LAS management and three plots under conventional control (NO-LAS plots) were compared. Spray threshold considered both adult population and fruit damage. An additional non-sprayed plot was selected for assessing biological control due to the parasitoid, Psyttalia concolor (Szépligeti). Results showed that the use of DSS reduced by 36.84% the volume of insecticide used in LAS compared to NO-LAS plots. Accordingly, time and distance needed for spraying were also reduced. Adult olive fruit fly population was lower in the LAS plots when compared with the NO-LAS plots; conversely, fruit infestation was higher in LAS compared with NO-LAS. The implementation of LAS and DSS at field level allowed real-time monitoring of adult olive flies, thereby increasing the accuracy and precision of sprays in time and space and decreasing impact on natural enemies. [ABSTRACT FROM AUTHOR]