Abstract

Abstract
This manuscript presents a novel framework, the Multidimensional Design Assessment Model, which encompasses a multi-criteria approach to efficiency, eco-efficiency and costs assessment for a given design system in aeronautical industry production. The framework is established by adopting Design-for-X and Multi-Layer Stream Mapping approaches, based on Lean Thinking, for efficiency assessment and adopting modules of ecoPROSYS to eco-efficiency assessment. A real case study from aeronautical sector is given to demonstrate the approach, for the assembly of aircraft structure Horizontal Tale Plane, where different results are presented and discussed for each dimension of analysis and how improvement strategies can be designed.

Abstract
Cardiovascular disease is the leading cause of death in the world, and its early detection is a key to improving long-term health outcomes. The auscultation of the heart is still an important method in the medical process because it is very simple and cheap. To detect possible heart anomalies at an early stage, an automatic method enabling cardiac health low-cost screening for the general population would be highly valuable. By analyzing the phonocardiogram signals, it is possible to perform cardiac diagnosis and find possible anomalies at an early-term. Therefore, the development of intelligent and automated analysis tools of the phonocardiogram is very relevant. In this work, we use simultaneously collected electrocardiograms and phonocardiograms from the Physionet Challenge database with the main objective of determining whether a phonocardiogram corresponds to a normal or abnormal physiological state. Our main contribution is the methodological combination of time domain features and frequency domain features of phonocardiogram signals to improve cardiac disease automatic classification. This novel approach is developed using both features. First, the phonocardiogram signals are segmented with an algorithm based on a logistic regression hidden semi-Markov model, which uses electrocardiogram signals as a reference. Then, two groups of features from the time and frequency domain are extracted from the phonocardiogram segments. One group is based on motifs and the other on Mel-frequency cepstral coefficients. After that, we combine these features into a two-dimensional time-frequency heat map representation. Lastly, a binary classifier is applied to both groups of features to learn a model that discriminates between normal and abnormal phonocardiogram signals. In the experiments, three classification algorithms are used: Support Vector Machines, Convolutional Neural Network, and Random Forest. The best results are achieved when both time and Mel-frequency cepstral coefficients features are considered using a Support Vector Machines with a radial kernel.

Abstract
As video games arc developing fast, many users issue queries related to video games in a daily fashion. While there Were a few attempts to understand their behavior, little is known on how the video game-related searches are done. Digesting and analyzing this search behavior may thus be faced as an important contribution for search engines to provide better results and search services for their users. To overcome this lack of knowledge and to gain more insight into how video game searches are done, we analyze in this paper, a number of game search queries submitted to a general search engine named Parsijoo. The analysis conducted was performed on top of 372,508 game search records extracted from the query logs within 253,516 different search sessions. Different aspects of video game searches are studied, including, their temporal distribution, game version specification. popular game categories, popular game platforms, game search sessions and clicked pages. Overall, the experimental analysis on video game searches shows that the current retrieval methods used by traditional search engines cannot be applied for game searches, thus, different retrieval and search services should be considered for these searches in the future.

Abstract
High concentration of biogenic amines (BA) is an indicator of deterioration of food and the determination of their concentration is an important method of food control. The hydrogen peroxide (H2O2) is a side product of the degradation of BAs by certain enzymes. It is presented an experimental technique grounded on chemiluminescence to measure small quantities of H2O2 with concentrations as low as 0.01%w/w up to 0.08%w/w. Luminol and cobalt hydroxide are added to hydroxyethyl cellulose to obtain an active membrane which will react with the sampling solution and the amount of total light emission is directly related to the H2O2 concentration.

Abstract
This case study was conducted in the scope of the rise of artificial intelligence (AI) in today’s society and provides the answer to the following questions: How are companies following the AI technology revolution?, How are organizational culture and identity changing within companies? and Where are companies investing in order to prepare to the upcoming competitive future? To answer these questions a semi-structured interview was done with Jorge Sousa, the Head of M2M/IoT & API Management & Virtual Assistant - Network and Service Solutions Department in Altice Labs. Altice Labs is owned by the multinational Altice Group and is responsible for the innovation and development of new solutions, technologies and trends in the telecommunications area for all the Altice group. Having already won several awards such as the Dell EMC Award in 2018 and the international Technology Leadership Award in 2017. Altice Labs is in a privileged position that only a few companies are in, performing high tech R&D. From this case study we conclude that organizational Identity and Culture are changing due to the external stimulus that AI is having in the market. These changes are being implemented as a sense-giving function of the organizational leaders and spokesmen that recognize the need of staying competitive in the market. The impact on the labor force status quo, layoffs and company culture are presented, aligning the interviewee’s opinion with the current theories on company culture, offering also an analysis on the tendencies of this revolution and summarizing the interviewee’s perspectives. © Springer Nature Switzerland AG 2019.