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Performance tests are crucial to measure the quality of software developments, since they allow identifying aspects to be improved in order to achieve customer satisfaction. The objective of this research was to identify the optimal Machine Learning technique to predict whether or not a software development meets the customer's acceptance criteria. A dataset with information obtained from web services performance tests and the F1-score quality metric were used. This paper concludes that, although the Random Forest technique obtained the best score, it is not correct to state that it is the best Machine Learning technique; the quantity and quality of the data used in the training play a very important role, as well as an adequate processing of the information. [ABSTRACT FROM AUTHOR]

Artificial intelligence offers great opportunities for the supply chain, making it a competitive advantage for today's changing market. This paper aims to identify the impacts and opportunities that artificial intelligence software can offer to supply chain in the Colombian banana sector to facilitate the operation and improve the performance. The searching method consists of six steps getting 72 investigations finally. The sources of information were four databases. The main conclusion is the supply chain of the banana sector has everything for implementation of solutions based on intelligent software in order to achieve adaptation, flexibility and context awarenes and execution domain. [ABSTRACT FROM AUTHOR]

In Colombia, social networks have become a powerful tool to disseminate political opinions, especially during the campaign period in the national presidential elections. This paper proposes a hybrid model to predict the outcome of the first round of presidential elections in Colombia in 2018, which aims to minimize absolute error and improve the quality of the final prediction. User activities on Twitter and Facebook were recorded and analyzed with artificial intelligence algorithms, resulting in an accurate prediction consistent with reality. As a core result is highlighted that the RMSE of the hybrid model is around 2.47%, surpassing on average the RMSE of the country's most prominent traditional polling firms. Additionally, the value of electoral abstentionism was also predicted with a differential error of 1.72% in relation to the real value, demonstrating the reliability of the proposed methodology. [ABSTRACT FROM AUTHOR]

This paper describes a process of semi-automatic systematic reviews in scientific research. On the one hand, it is presented a software prototype based on artificial intelligence, semi-automatic systematic reviews tool. On the other hand, a study case of a phd thesis project shows the maps and information with aggregate value. In addition, the software prototype were evaluated by 40 students of master and Ph.D projects, they report the utility of the software tool by a survey. This work presents the modules and functionalities, software architecture and software deployment. Furthermore, a comparative study of a set of similar software tools has been conducted according to the following criteria: input files, analysis and mapping, and software license. Finally, it is discussed the results of the comparative study, the implementation of artificial intelligence techniques, the software scalability and the easiness of include new analysis and maps. [ABSTRACT FROM AUTHOR]

This paper presents a proposal for monitoring temperature in electric power transmission lines by using artificial intelligence. With a temperature monitoring system, the operator can know the current state of the line and carry out control actions to improve reliability, safety and quality of the service. The proposed methodology in the training stage uses optical sensors and devices for recording and storing temperature data. With the historical data, a fuzzy classifier is trained and, the obtained classes are associated with states of normal or failure operation by an expert. In the on line stage, the classifier processes each new sample and assigns an operation state, and then with this information the operator determines the right action on the electric system. The methodology is tested on a section of emulated transmission line in a high voltage laboratory. [ABSTRACT FROM AUTHOR]