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The use of technology in healthcare became a prevailing necessity during the COVID-19 pandemic. The sanitary services oriented in mental health broadened their way of interaction due to the increase in the need for these services. Healthcare professionals had to develop different learning skills and adapt their abilities to the virtual clinical practice through a digital interface, where communication represented the biggest challenge. The objective of the study was to identify the different adjustments, especially in the communication skills, made by those who provide psychological services by the Virtual Clinic in Psychology and others and clinical psychologists. The authors considered adequate qualitative methodology for the study with an exploratory, descriptive design. The data gathering tool was a semi-structured interview and the word analysis method. The participants are professors that provide psychological care in the Virtual Clinic in Psychology of a nonprofit institution of higher education in Mexico and professionals providing mental health attention.

The missing fundamentals of harmonic theory: Chord roots and their ambiguity in arrangements of jazz standards

Since Lippius and Rameau, chords have roots that are often voiced in the bass, doubled, and used as labels. Psychological experiments and analyses of databases of Western classical music have not produced clear evidence for the psychological reality of chord roots. We analyzed a symbolic database of 100 arrangements of jazz standards (musical instrument digital interface [MIDI] files from midkar.com and thejazzpage.de ). Selection criteria were representativeness and quality.The original songs had been composed in the 1930s and 1950s, and each file had a beat track. Files were converted to chord progressions by identifying tone onsets near beat locations (±10% of beat duration). Chords were classified as triads (major, minor, diminished, suspended) or seventh chords (major–minor, minor, major, half-diminished, diminished, and suspended) plus extra tones. Roots that were theoretically less ambiguous were more often in the bass or (to a lesser extent) doubled. The root of the minor triad was ambiguous, as predicted (conventional root or third). Of the sevenths, the major–minor had the clearest root. The diminished triad was often part of a major–minor seventh chord; the half-diminished seventh, of a dominant ninth. Added notes (“tensions”) tended to minimize dissonance (roughness or inharmonicity). In arrangements of songs from the 1950s, diminished triads and sevenths were less common, and suspended triads more common, relative to the 1930s. Results confirm the psychological reality of chord roots and their specific ambiguities. Results are consistent with Terhardt’s virtual pitch theory and the idea that musical chords emerge gradually from cultural and historic processes. The approach can enrich music theory (including pitch-class set analysis) and jazz pedagogy.

Research on Music Classification Technology Based on Deep Learning

With the advent of the digital music era, digital audio sources have exploded. Music classification (MC) is the basis of managing massive music resources. In this paper, we propose a MC method based on deep learning to improve feature extraction and classifier design based on MIDI (musical instrument digital interface) MC task. Considering that the existing classification technology is limited by the shallow structure, it is difficult for the classifier to learn the time sequence and semantic information of music; this paper proposes a MIDIMC method based on deep learning. In the experiment, we use the MC method proposed in this paper to achieve 90.1% classification accuracy, which is better than the existing classification method based on BP neural network, and verify the music with its classification accuracy. The key point is that the music division method used in this paper has correct MC efficiency. However, due to the limited ability and time involved in the interdisciplinary field, the methodology of this paper has certain limitations, which still needs further research and improvement.

Serangan Empat Hari Di Surakarta Sebagai Sumber Penciptaan Karya Tari Tekad

The research entitled Tekad choreography by Zhola Verucha Taruna aims to find out and explain descriptively about the form of Tekad choreography, which includes the creation process. The theoretical basis used is the theory of structure, according to Suzanne K. Langer. The creation process uses the thoughts of Alma H. Hawkins and uses the approach of Sumandiyo Hadi to explain the choreographic elements. The method used in this research is Practice-Based Research.The results showed that the choreography of Tekad by Zhola Verucha Taruna was non-literal. This dance form consists of four parts. The use of everyday movements is varied with the Aikido movement of the Muso Jihiden Eishin Ryu flow, which has been developed and uses the ideas of the katana as a symbol property of determination. While the music used is music in the form of MIDI (Musical Instrument Digital Interface), and lighting is more about spatial attitudes. The process of creating this dance work uses the principle of re-interpreting the Four-Day General Attack of the City of Surakarta with elements of novelty in the form of works through seeing, feeling, and imagining, and manifesting them into form. Determination is the title of a dance work resulting from exploration, improvisation, and evaluation of ideas into a complete form to accommodate messages or contents about struggle or spirit.

Democratizing finance with Robinhood: Financial infrastructure, interface design and platform capitalism

It is widely claimed that financial technology democratizes financial access and promotes financial inclusion. This paper challenges this dominant narrative of financial technology using the popular US-based mobile investing platform Robinhood as a case study. Analyzing press articles on Robinhood and regulatory filings of online brokerages, the concepts of financial infrastructures and platforms are used to unpack the capitalist logics that drive the platform business model. Specifically, this paper shows how digital interface design plays a central role in Robinhood's articulation of investors into the stock markets, through its simple, minimalist app that keeps users engaged by the productive management of ‘frictions’. The ease of investing via platform-based brokerages has seen investors taking on greater amounts of risk. This paper argues that Robinhood's success is driven by the continued expansion of its user base using various interface design techniques. This allows platform capitalism to be enacted by extracting rent through various revenue streams, where higher rents are derived from more frequent and riskier trading behaviors. The narrative of democratizing finance as employed widely in the financial technology sector thus obscures the capitalist logics and predatory practices that underlie financial technology.

Covid 19 and Challenges in Higher Education: An Empirical Analysis

Over the years the global economy, including India, has undergone a profound change and observed a pioneer role of innovation and technology in every sector. Rapid technological dissemination has seen human or physical touch points being replaced by digital interface. With digitization happening everywhere, it becomes all the more important for the education sector to adapt it in order to keep pace with the challenging world. With the onset of the global pandemic of Covid-19, the only option left with the education sector is to switch to online classes for its smooth and continuous working. This research aims to investigate the challenges that are faced by the students and their level of satisfaction from these classes. The study is based on primary data collected from 700 students of various colleges across Universities in India. The study employs regression models, crosstabs, and various other descriptive statistics for analysis of the data. The findings of the study suggest that the students face a lot of glitches while learning from the online mode of education and would need time to adjust. The research also provides an insight on the scope and the future of online education.

Sequence-Based Explainable Hybrid Song Recommendation

Despite advances in deep learning methods for song recommendation, most existing methods do not take advantage of the sequential nature of song content. In addition, there is a lack of methods that can explain their predictions using the content of recommended songs and only a few approaches can handle the item cold start problem. In this work, we propose a hybrid deep learning model that uses collaborative filtering (CF) and deep learning sequence models on the Musical Instrument Digital Interface (MIDI) content of songs to provide accurate recommendations, while also being able to generate a relevant, personalized explanation for each recommended song. Compared to state-of-the-art methods, our validation experiments showed that in addition to generating explainable recommendations, our model stood out among the top performers in terms of recommendation accuracy and the ability to handle the item cold start problem. Moreover, validation shows that our personalized explanations capture properties that are in accordance with the user’s preferences.