Abstract
The current study has as its objective to analyse how the study of languages is affected by new technologies. The way of teaching as well as the learning process are not the same as in older times, so we think that it is important to analyse the phenomenon. There are several advantages to the use of technology, and the future heralds even greater evolution. The effect of technologies on teaching has been very significant and even university professors resort to the usage of websites or other technological tools. The concept of innovation is not only associated to information and communication technologies, but also to the process and innovative supply of methods of access to knowledge. Therefore, associating innovation to the teaching of languages is something completely acceptable, since the usage of technological resources is a form of innovating. Because the final objective is to find a coherent response that indicates what is currently happening in the world of education concerning languages, primary data was obtained via a total of eleven interviews answered by young language students and professors. With this study, we conclude that technologies will continue to have an impact on the future of teaching. There is a general consensus concerning the relevance of obtaining better academic results. Therefore, it is necessary to recognize that learning becomes more facilitated with technology because there is easier access to information.

Abstract
A high-resolution advanced laser induced breakdown spectroscopy prototype was used to quantify lithium (Li) in lithiniferous rocks. Samples were collected from Barroso's mine (Portugal), claimed as Western Europe's largest spodumene Li discovery. 51 samples from a reverse circulation drill were collected, one for each meter interval, dried, milled, pressed into pellets and further analyzed by laser induced breakdown spectroscopy. Quantification was attempted using either linear models based on the intensity of selected Li spectral lines or advanced chemometrics methods. The latter was very successful, with correlation coefficients of 0.97 against certified laboratory results.

Abstract
Due to the rapidly increasing share of electric vehicles (EVs) worldwide, the abundance of EV parking lots (with charging capabilities) is becoming necessary to provide for charging needs in addition to attempting to fully utilize EVs for the benefit of future smart grids. Unmanaged charging of EVs can jeopardize stability and reliability of power systems. Hence, well-operated EV parking lots can be a good solution to enhance system stability. Equipping parking lots with rooftop photovoltaics (PVs) has been gaining interest as a good approach for their design and operation. During the day, when EVs are stationed in the parking lot and particularly in more commercial neighborhoods of cities, the EVs can be charged directly through solar generation, so that minimal stress on the distribution system occurs. This work aims to conduct a comparative study investigating the optimal strategies for the operation of PV-equipped EV parking lots. Multiple parameters are taken into consideration including weather conditions, uncertainty of EV owners' schedules, and EV models. This analysis will result in finding the optimal strategy for the operation of the parking lot from the owner/operator point of view in order to minimize costs and maximize services provided to the grid.

Abstract

Abstract
Demand response (DR) programs offer tremendous opportunities to those who have concerns about the future of energy. Since the DR strategies facilitate new technologies to take part in the power systems, the idea of spreading of electric vehicles (EVs) attracts researchers around the world. In this study, an optimal energy management strategy for EV parking lots considering peak load reduction based DR programs is built in stochastic programming framework, denoted by EV parking lot energy management (EV-PLEM). The proposed EV-PLEM aims to maximize the load factor during the daily operation of an EV parking lot taking into account the uncertain behavior of EVs, such as arrival and departure times together with the stochasticity of the remaining state-of-energy of EVs when they reach the parking lot. A set of case studies is conducted to validate the effectiveness of the suggested EV-PLEM concept, and credible results and useful findings are reported for the cases in which the EV-PLEM is implemented.

Abstract
The analysis of the intern anatomy of wood samples for species identification is a complex task that only experts can perform accurately. Since there are not many experts in the world and their training can last decades, there is great interest in developing automatic processes to extract high-level information from microscopic wood images. The purpose of this work was to develop algorithms that could provide meaningful information for the classification process. The work focuses on hardwoods, which have a very diverse anatomy including many different features. The ray width is one of such features, with high diagnostic value, which is visible on the tangential section. A modified distance function for the DBSCAN algorithm was developed to identify clusters that represent rays, in order to count the number of cells in width. To test both the segmentation and the modified DBSCAN algorithms, 20 images were manually segmented, obtaining an average Jaccard index of 0.66 for the segmentation and an average index M=0.78 for the clustering task. The final ray count had an accuracy of 0.91. © 2019, Springer Nature Switzerland AG.