Search Results (4)

Cetaceans are cast to shore for a large number of reasons, although sometimes it is not clear why. This paper reviews the types and causes of cetacean strandings, focusing on mass strandings that lack a direct scientific explanation. Failure of cetacean orientation due to radiofrequency radiation and alterations in the Earth’s magnetic field produced during solar storms stand out among the proposed causes. This paper proposes the possibility that anthropogenic radiofrequency radiation from military and meteorological radars may also cause these strandings in areas where powerful radars exist. A search of accessible databases of military and meteorological radars in the world was carried out. Research articles on mass live strandings of cetaceans were reviewed to find temporal or spatial patterns in the stranding concentrations along the coast. The data showed certain patterns of spatial and temporal evidence in the stranding concentrations along the coast after radar setup and provided a detailed description of how radars may interfere with cetacean echolocation from a physiological standpoint. Plausible mechanisms, such as interference with echolocation systems or pulse communication systems, are proposed. This work is theoretical, but it leads to a hypothesis that could be empirically tested. Further in-depth studies should be carried out to confirm or reject the proposed hypothesis. Full article

Wildfires kill and injure people, destroy residences, pollute the air, and cause economic loss. In this paper, a low-power Internet of Things (IoT)-based sensor network is developed, which automatically detects fires in forests and sends the location to a central monitoring station with smartphone notifications in a real-time setting. This action helps in the early detection of a fire and firefighters can be notified immediately—thus the spread of the fire and the harm caused by it can be reduced. The proposed system detects fires from the presence of smoke and a sudden increase in temperature. The system also logs the temperature, humidity, carbon dioxide, rain, light, and wind speed in different areas of the forest. The sensor nodes transmit the data to a hub using a long-range wireless transmitter and the hub then sends the data to the central monitoring station using the cellular Internet. The sensor nodes and hub are designed with ultra-low-power hardware and software architecture, consuming current of only 0.37 and 1.4 mA, respectively, so that they can be powered by solar panels throughout the year. The central server and smartphone app contain maps, and the wildfire locations are marked in the case of a fire. In the present study, a prototype of the proposed system is successfully developed and tested. Full article

Building a sophisticated forecasting framework for solar and photovoltaic power production in geographic zones with severe meteorological conditions is very challenging. This difficulty is linked to the high variability of the global solar radiation on which the energy production depends. A suitable forecasting framework might take into account this high variability and could be able to adjust/re-adjust model parameters to reduce sensitivity to estimation errors. The framework should also be able to re-adapt the model parameters whenever the atmospheric conditions change drastically or suddenly—this changes according to microscopic variations. This work presents a new methodology to analyze carefully the meaningful features of global solar radiation variability and extract some relevant information about the probabilistic laws which governs its dynamic evolution. The work establishes a framework able to identify the macroscopic variations from the solar irradiance. The different categories of variability correspond to different levels of meteorological conditions and events and can occur in different time intervals. Thereafter, the tool will be able to extract the abrupt changes, corresponding to microscopic variations, inside each level of variability. The methodology is based on a combination of probability and possibility theory. An unsupervised clustering technique based on a Gaussian mixture model is proposed to identify, first, the categories of variability and, using a hidden Markov model, we study the temporal dependency of the process to identify the dynamic evolution of the solar irradiance as different temporal states. Finally, by means of some transformations of probabilities to possibilities, we identify the abrupt changes in the solar radiation. The study is performed in Guadeloupe, where we have a long record of global solar radiation data recorded at 1 Hertz. Full article

This paper deals with a reduced switch multi-level inverter for the solar photovoltaic system-based 127-level multi-level inverter. The proposed technique uses the minimum number of switches to achieve the maximum steps in staircase AC output voltage when compared to the flying capacitor multi-level inverter, cascaded type multilevel inverter and diode clamped multi-level inverter. The use of a minimum number of switches decreases the cost of the system. To eliminate the switching losses, in this topology a square wave switch is used instead of pulse width modulation. Thereby the total harmonic distortion (THD) and harmonics have been reduced in the pulsating AC output voltage waveform. The performance of 127-level MLI is compared with 15 level, 31-level and 63-level multilevel inverters. The outcomes of the solar photovoltaic system-based 127-level multi-level inverter have been simulated in a MATLAB R2009b environment. Full article