Given the noticeable and quick progress of digitalization it is well accepted that digital practices are changing business landscapes. However, while this concept is being labelled in the literature it is also often used indistinctively. To avoid misconceptions, we propose to clarify the concept by providing an overview of the existing theory. This research is one of the first attempts to define the "digitalization" term, and to make a distinction between similar ones. The authors have conducted a systematic review of the existing literature, by identifying and synthesizing the existing body of knowledge. While going digital, firms are expecting to enhance their competitive advantage by offering services throughout virtual channels and operationalize its operations management. Furthermore, the literature suggested the development of new digital technologies along with automation and artificial intelligence is enabling a new wave of smart companies, a topic that deserves to be studied in the future.

This study addressed the development of a pilot plant for pyrolysis of scrap tires to obtain carbon black and other byproducts. The work was motivated by the goal of contributing to the development and dissemination of knowledge about existing technologies that allow modern economies to transform waste into valuable products, by documenting and discussing an empirical application in Brazil. Thispaper describes the development of a market for steel scrap, pyrolytic oil and carbon black products obtained from a vacuum pyrolysis process. The research work was conducted in Brazil, and was guided by the twofold purpose of reducing the environmental impacts, while gaining economical sustainability. Modern economies increasingly need to devise strategies to address energy generation while preserving natural ecosystems. These strategies include leveraging the use of renewable energy sources. Acknowledging that scrap tires hold an enormous potential as a sustainable energy option, this study aimed to contribute to the development and maturity of eco-friendly processing approaches to realize its full potential. The work involved a preliminary phase concerned with the operation of vacuum pyrolysis of scrap tires at a laboratorial scale, followed by the design of the pilot plant that operated for 10 years, at the time of the study, with a 100 kg/h batch flow. Results show that the yield of the pyrolysis process was 41% pyrolytic oil, 38% carbon black, 12% gas, and 8.9% steel scrap, with a calorific value of 36 MJ/kg per tire. The carbon black was composed of 90% carbon, and the pyrolytic oil was composed of 66% gasoline and 33% other oils, which have higher quality and can be commercialized with a potential profit over 3 million dollars/year.

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Objectives: The study reported in this article aimed to identify: (i) the most relevant applications supported by smart city infrastructure with an impact on the provision of healthcare; (ii) the types of technologies being used; (iii) the maturity levels of the applications being reported; and (iv) major barriers for their dissemination. Methods: A systematic review was performed based on a literature search. Results: A total of 44 articles were retrieved. These studies reported on smart city applications to support population surveillance, active ageing, healthy lifestyles, disabled people, response to emergencies, care services organization, and socialization. Conclusions: Most of the included articles were either of a descriptive and conceptual nature or in an early stage of development, which means that a major barrier for their dissemination is their lack of concreteness.

Big Data is currently a hot topic of research and development across several business areas mainly due to recent innovations in information and communication technologies. One of the main challenges of Big Data relates to how one should efficiently handle massive volumes of complex data. Due to the notorious complexity of the data that can be collected from multiple sources, usually motivated by increasing data volumes gathered at high velocity, efficient processing mechanisms are needed for data analysis purposes. Motivated by the rapid growth in technology, development of tools, and frameworks for Big Data, there is much discussion about Big Data querying tools and, specifically, those that are more appropriated for specific analytical needs. This paper describes and evaluates the following popular Big Data processing tools: Drill, HAWQ, Hive, Impala, Presto, and Spark. An experimental evaluation using the Transaction Processing Council (TPC‐H) benchmark is presented and discussed, highlighting the performance of each tool, according to different workloads and query types. This article is categorized under: Technologies > Computer Architectures for Data Mining Fundamental Concepts of Data and Knowledge > Big Data Mining Technologies > Data Preprocessing Application Areas > Data Mining Software Tools

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In this paper, we investigate in detail the performance of turbo codes in quasi-static fading channels both with and without antenna diversity. First, we develop a simple and accurate analytic technique to evaluate the performance of turbo codes in quasi-static fading channels. The proposed analytic technique relates the frame error rate of a turbo code to the iterative decoder convergence threshold, rather than to the turbo code distance spectrum. Subsequently, we compare the performance of various turbo codes in quasi-static fading channels. We show that, in contrast to the situation in the AWGN channel, turbo codes with different interleaver sizes or turbo codes based on RSC codes with different constraint lengths and generator polynomials exhibit identical performance. Moreover, we also compare the performance of turbo codes and convolutional codes in quasi-static fading channels under the condition of identical decoding complexity. In particular, we show that turbo codes do not outperform convolutional codes in quasi-static fading channels with no antenna diversity; and that turbo codes only outperform convolutional codes in quasi-static fading channels with antenna diversity.