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3 In addition, user-generated data offers new opportunities to deliver unheard-of voice. However, long-standing challenges for developing regions, such as inadequate technological infrastructure and scarcity of financial and human resources exacerbate existing concerns with big data, such as privacy, imperfect methodology, and interoperability issues.83

Big data provides an infrastructure for transparency in manufacturing, which is the ability to unravel uncertainties such as performance and availability of inconsistent components. Predictive manufacturing as an applicable approach to near-zero downtime and transparency requires a wealth of data and advanced forecasting tools for a systematic process of data into useful information.84 A predictive manufacturing framework begins with the data acquisition where different types of sensory data are available, such as acoustics, vibration, pressure, current, voltage, and controller data. A lot of sensory data, in addition to historical data, builds the big data in manufacturing. The big data generated acts as the input to predictive tools and preventive strategies such as Prognosis and Health Management (PHM) .85

Media and advertising professionals approach big data as many actionable points of information about millions of people. The industry seems to be moving away from the traditional approach of using specific media environments, such as newspapers, magazines or television shows, and instead leverages consumers with technologies that reach target people at optimal times in optimal locations. The ultimate goal is to serve, or transmit, a message or content that (statistically speaking) is in line with the consumer’s mindset. For example, publishing environments increasingly tailor messages (advertisements) and content (articles) to appeal to consumers that have been collected exclusively through various data mining activities.86

The recognition of musical emotions (REM) (Music Emotion Recognition MER) is a recent and evolving field of scientific research. Broadly speaking, it can be said that REM revolves around several ideas regarding the psychological understanding of the relationship between human affection and music. One of the central ideas of REM lies in the ability to determine, through automatic systems, entering various data (musical signals) and variables (computational parameters), which and what type of emotions are perceived from musical compositions, and try to perceive how each one of the forms of its structural features can produce certain types of characteristic reactions in listeners88.

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