Efficient Support for Video Communications in Wireless Home Networks

This paper investigates the performance of video communications over wireless networks employing the recently proposed Time-Division Unbalanced Carrier Sense Multiple access (TDuCSMA) coordination function. TDuCSMA is fully IEEE 802.11 standard compliant but offers novel bandwidth management capabilities. In this work the peculiar characteristics of TDuCSMA are configured and exploited to maximize the performance of video communications in a realistic home networking scenario. Simulation results show significant performance improvements with respect to legacy IEEE 802.11 network. The video quality gains are up to 13 dB PSNR with 500 ms playout buffer, while the average delay of the video packets is much lower, for the same amount of video traffic offered to the network. These results significantly contribute to enhance the quality of experience of the users of the video communicatio

Low-Complexity Driving Event Detection from Side Information of a 3D Video Encoder

Mobile phones are often found in cars, for instance when they are used as navigation assistants. This work propose to use their camera, which is often already pointed to the road, to perform some low-complexity analysis of the driving context, with the final aim to detect potentially unsafe conditions. Since content understanding algorithms are typically too complex to run in real time on a mobile device, a driving event detection algorithm is presented based on the side information available from video encoders, which are a highly optimized application in mobile phones. A set of interesting and easy-to-extract features has been identified in the side information and then further reduced and adapted to the specific events of interest. A detection algorithm based on support vector machines has been designed and trained on several hours of video annotated by a human operator to extract the events of interest. The detection algorithm is shown to achieve a good identification rate for the considered events and feature sets. Moreover, results also show that the use of a stereoscopic camera significantly improves the performance of the detection algorithm in most case

Technical-economical analysis of cold-ironing. Case study of Venice cruise terminal

Cold-ironing is the practice that enables to power commercial ships by a link to fixed electricity network, in order to reduce pollutant emissions in the port areas caused by marine fuels in auxiliaries engines feeding on board installations during ships stops at quays. The present paper aims to provide an overview of the most important technical and functional features of the concerned ships power systems and to analyze the technical, economic and financial feasibility of this system. In the first part the main technical-constructive elements for the application of Cold-ironing to different types of ship (such as voltage, frequency, power supply and power demand on the quay) are analyzed. The variety of functional situations does not allow to establish general constructive solutions since the cold-ironing system is depending both on the operational mode and the layout of each terminal. In the second part of the paper it has been analyzed the case study of the cruise terminal in Venice (VTP Spa Venice Passenger Terminal) with the aim of verifying the feasibility of a cold-ironing system for power supply of cruise ships on quays. The analysis was based on ships timetable for the year 2012, which includes the arrivals and the departures of 86 different ships with a global volume of 570 movements. Starting from data on dwell times, following the guidelines of the MEET methodology for estimating emission factors [3] it has been estimated pollutant emissions (nitrogen oxide NOx, sulfur oxides SOx, volatile organic compounds VOC, particulates PM, carbon monoxide CO) as a basis to calculate externalities to be considered for the Cost-Benefit Analysis (CBA). Based on a probabilistic analysis of the terminal occupation by ships (disposal of ship stalls on each quays) five operational scenarios were defined. Each scenario has been defined on the basis of an economic evaluation by means of a cost-benefit parametric analysis with the aim of providing the maximum financial results for assigned budgets. From a comparison of the results of the cost-benefit analysis and an estimate of possible investment costs obtained from USA case studies, it is noticed that the scenario providing coverage of both financial and economic investment includes the minimum number of electrified stalls and a ships journeys reorganization. It was also proposed a sensitivity analysis of CBA for the evaluation of indicators variations according to reference conditions variation

A multivariate high-order markov model for the income estimation of a wind farm

The energy produced by a wind farm in a given location and its associated income depends both on the wind characteristics in that location—i.e., speed and direction—and the dynamics of the electricity spot price. Because of the evidence of cross-correlations between wind speed, direction and price series and their lagged series, we aim to assess the income of a hypothetical wind farm located in central Italy when all interactions are considered. To model these cross and auto-correlations efficiently, we apply a high-order multivariate Markov model which includes dependencies from each time series and from a certain level of past values. Besides this, we used the Raftery Mixture Transition Distribution model (MTD) to reduce the number of parameters to get a more parsimonious model. Using data from the MERRA-2 project and from the electricity market in Italy, we estimate the model parameters and validate them through a Monte Carlo simulation. The results show that the simulated income faithfully reproduces the empirical income and that the multivariate model also closely reproduces the cross-correlations between the variables. Therefore, the model can be used to predict the income generated by a wind farm

Managing wind power generation via indexed semi-markov model and copula

Because of the stochastic nature of wind turbines, the output power management of wind power generation (WPG) is a fundamental challenge for the integration of wind energy systems into either power systems or microgrids (i.e., isolated systems consisting of local wind energy systems only) in operation and planning studies. In general, a wind energy system can refer to both one wind farm consisting of a number of wind turbines and a given number of wind farms sited at the area in question. In power systems (microgrid) planning, a WPG should be quantified for the determination of the expected power flows and the analysis of the adequacy of power generation. Concerning this operation, the WPG should be incorporated into an optimal operation decision process, as well as unit commitment and economic dispatch studies. In both cases, the probabilistic investigation of WPG leads to a multivariate uncertainty analysis problem involving correlated random variables (the output power of either wind turbines that constitute wind farm or wind farms sited at the area in question) that follow different distributions. This paper advances a multivariate model of WPG for a wind farm that relies on indexed semi-Markov chains (ISMC) to represent the output power of each wind energy system in question and a copula function to reproduce the spatial dependencies of the energy systems’ output power. The ISMC model can reproduce long-term memory effects in the temporal dependence of turbine power and thus understand, as distinct cases, the plethora of Markovian models. Using copula theory, we incorporate non-linear spatial dependencies into the model that go beyond linear correlations. Some copula functions that are frequently used in applications are taken into consideration in the paper; i.e., Gumbel copula, Gaussian copula, and the t-Student copula with different degrees of freedom. As a case study, we analyze a real dataset of the output powers of six wind turbines that constitute a wind farm situated in Poland. This dataset is compared with the synthetic data generated by the model thorough the calculation of three adequacy indices commonly used at the first hierarchical level of power system reliability studies; i.e., loss of load probability (LOLP), loss of load hours (LOLH) and loss of load expectation (LOLE). The results will be compared with those obtained using other models that are well known in the econometric field; i.e., vector autoregressive models (VAR)

Age-related cognitive decline and the olfactory identification deficit are associated to increased level of depression

Purpose: Previous studies reported a correlation between olfactory function and depression. However, in literature, no data are available for the correlation between depression and all other factors such as age, sex, olfactory, gustatory, and cognitive function in healthy subjects taken together. The aim of this study was to provide a systematic account regarding the association between those variables in a nonclinical population. Methods: Two hundred and seventy-three participants were recruited with an age range of 19–84 years. Olfactory, gustatory, cognitive function, and depression level were evaluated by means of the following tests: the Sniffin’ Sticks test, Taste Strips test, Montreal Cognitive Assessment (MoCA), and Beck Depression Inventory (BDI). Results: In our data, an age-related decrease in olfactory and gustatory function and a decline in cognitive functions such as attention, memory, and language were observed. Instead, no significant differences were observed for the depression level in relation to the different age ranges. However, our results indicated that the depression level could be associated to sex, odor identification impairment, and decreased attention and language. Conclusion: Sex, the odor identification impairment, and an age-related decrease in attention and language are associated with increased level of depression in healthy subjects. Our data can be useful and informative for health care workers, that is, to have adequate preventive strategies to be used whenever these conditions are detected and recognized

The use of distance learning and e-learning in students with learning disabilities: A review on the effects and some hint of analysis on the use during covid-19 outbreak

Even if the use of distance learning and E-learning has a long tradition all over the world and both have been used to keep in contact with students and to provide lessons, support and learning materials, there is an open debate on the balance between advantages and disadvantages in the use of distance learning. This debate is even more central in their use to support students with Learning Disabilities (LDs), an overarching group of neurodevelopmental disorders that affect more than 5% of students. The current COVID-19 outbreak caused school closures and the massive use of E-learning all over the world and it put higher attention on the debate of the effects of E-learning. This paper aims to review papers that investigated the positive and negative effects of the use of Distance Learning and E-learning in students with LDs. We conducted a literature review on the relationship between Distance Learning, E-learning and Learning Disabilities, via Scopus, Eric and Google Scholar electronic database, according to Prisma Guidelines. The findings are summarized using a narrative, but systematic, approach. According to the data resulting from the papers, we also discuss issues to be analyzed in future research and in the use of E-learning during the current pandemic of COVID-19

Gustatory Sensitivity and Food Acceptance in Two Phylogenetically Closely Related Papilionid Species: Papilio hospiton and Papilio machaon.

In herbivorous insects, food selection depends on sensitivity to specific chemical stimuli from host-plants as well as to secondary metabolites (bitter) and to sugars (phagostimulatory). Bitter compounds are noxious, unpalatable or both and evoke an aversive feeding response. Instead, sugars and sugar alcohols play a critical role in determining and enhancing the palatability of foods. We assumed that peripheral taste sensitivity may be related to the width of the host selection. Our model consists of two closely phylogenetically related Papilionid species exhibiting a difference in host plant choice: Papilio hospiton and Papilio machaon. The spike activity of the lateral and medial maxillary styloconic taste sensilla was recorded following stimulation with several carbohydrates, nicotine and NaCl, with the aim of characterizing their gustatory receptor neurons and of comparing their response patterns in the light of their different acceptability in feeding behaviour. The results show that: a) each sensillum houses phagostimulant and phagodeterrent cells; b) the spike activity of the gustatory neurons in response to different taste stimuli is higher in P. hospiton than in P. machaon; c) sugar solutions inhibit the spike activity of the deterrent and salt cells, and the suppression is higher in P. machaon than in P. hospiton. In conclusion, we propose that the different balance between the phagostimulant and phagodeterrent inputs from GRNs of maxillary sensilla may contribute in determining the difference in food choice and host range