A comparison of vehicle emissions control strategies for smart cities.

Many studies have shown that air quality in cities is affected due to emissions of carbon from vehicles. As a result, policymakers (e.g., municipalities) intensely search for new ways to reduce air pollution due to its relation to health diseases. With this concern, connected vehicle technologies can leverage alternative on-road emissions control policies. The present investigation studies the impact on air pollution by (i) updating vehicles' routes to avoid pollution exposure (route choice policy), (ii) updating vehicles' speed limits (speed control policy), and (iii) considering electric vehicles (EVs). Vehicles are informed in advance about route conditions (i.e., on-road emissions) using the vehicular network. We found that by updating vehicle routes, 7.43% less CO emissions are produced within the evaluated region. Also, we find no evidence of significant emissions reductions in the case of limiting vehicles' speed. Lastly, with 30% of EV penetration, safe CO emissions levels are reached.

Comparative Analysis of Teaching at Public Universities in Sinaloa during Confinement Due to COVID-19.

The COVID-19 pandemic has affected educational institutions around the world. One partial solution for students and teachers to continue the academic process involved the use of software and hardware technologies via the internet. The main objective of this research was to analyze the actions carried out by computer science teachers (and teachers who taught related degrees) in Sinaloa, Mexico, during the COVID-19 confinement period, to determine if the working conditions were different at all educational institutions. Based on quantitative, descriptive-explanatory, correlational, field, and cross-sectional approaches to data collection-a survey was designed and sent to teachers who taught classes in computer science and related careers. The results showed that although teachers felt prepared in designing and implementing virtual courses (90.73%), 68.5% believed that virtual classes were not enough for students (i.e., regarding replacing the training being offered). Likewise, teachers observed that only 27.8% of their students showed real commitment to online classes. In the hypothesis test, a chi-squared value of 3.84 was obtained, with a significance (p-value) of 0.137. There was a probability of error of 13.7%; this is high, considering that the level of significance must be 0.05 (5%) or less. It was concluded that teachers must be permanently trained in the use of new digital technologies; in addition, they must continuously produce academic material and make it available to the educational community. It is necessary for universities to design plans for the regulated use of applications and devices for academic purposes, update study plans and programs, and train teachers and students beyond conventional education.

The external and data loose coupling for the integration of software units: a systematic mapping study.

Integration of legacy and third-party software systems is almost mandatory for enterprises. This fact is based mainly on exchanging information with other entities (banks, suppliers, customers, partners, etc.). That is why it is necessary to guarantee the integrity of the data and keep these integration's up-to-date due to the different global business changes is facing today to reduce the risk in transactions and avoid losing information. This article presents a Systematic Mapping Study (SMS) about integrating software units at the component level. Systematic mapping is a methodology that has been widely used in medical research and has recently begun to be used in Software Engineering to classify and structure the research results that have been published to know the advances in a topic and identify research gaps. This work aims to organize the existing evidence in the current scientific literature on integrating software units for external and data loose coupling. This information can establish lines of research and work that must be addressed to improve the integration of low-level systems.

A multimetric, map-aware routing protocol for VANETs in urban areas.

In recent years, the general interest in routing for vehicular ad hoc networks (VANETs) has increased notably. Many proposals have been presented to improve the behavior of the routing decisions in these very changeable networks. In this paper, we propose a new routing protocol for VANETs that uses four different metrics. which are the distance to destination, the vehicles' density, the vehicles' trajectory and the available bandwidth, making use of the information retrieved by the sensors of the vehicle, in order to make forwarding decisions, minimizing packet losses and packet delay. Through simulation, we compare our proposal to other protocols, such as AODV (Ad hoc On-Demand Distance Vector), GPSR (Greedy Perimeter Stateless Routing), I-GPSR (Improvement GPSR) and to our previous proposal, GBSR-B (Greedy Buffer Stateless Routing Building-aware). Besides, we present a performance evaluation of the individual importance of each metric to make forwarding decisions. Experimental results show that our proposed forwarding decision outperforms existing solutions in terms of packet delivery.