Data storage using peptide sequences

Humankind is generating digital data at an exponential rate. These data are typically stored using electronic, magnetic or optical devices, which require large physical spaces and cannot last for a very long time. Here we report the use of peptide sequences for data storage, which can be durable and of high storage density. With the selection of suitable constitutive amino acids, designs of address codes and error-correction schemes to protect the order and integrity of the stored data, optimization of the analytical protocol and development of a software to effectively recover peptide sequences from the tandem mass spectra, we demonstrated the feasibility of this method by successfully storing and retrieving a text file and the music file Silent Night with 40 and 511 18-mer peptides respectively. This method for the first time links data storage with the peptide synthesis industry and proteomics techniques, and is expected to stimulate the development of relevant fields.

Improving Music Streaming Services Through Metadata: Case Study from JOOX Indonesia

Background of this Study: This article examines how digital music handled on music streaming services, JOOX Indonesia in particular. Purposes: The aims was to bring insight that metadata management skill could help an enhancement over music streaming services through metadata and to improve the user experience when using music streaming services. Method:A single case study is chosen as the research method for this paper. The researcher did three months internship to see how the music file handled on the back end of JOOX. Semi-structured qualitative interviews and documentary analysis were used to collect and triangulate the qualitative data. Findings: The result shows JOOX using its operational self-possession procedures to handle its digital music file and using its own metadata standard with adaptation from music metadata standard. JOOX has a feature that utilizes music lyric. We found that lyric metadata embedded as a distinct entity on their backend system. Since lyric frequently used by the user as an access point when they do the retrieval, we propose to embed lyric as a field on music metadata to improve search result. Conclusion: These research shows are lyric as the essential part when users enjoy the music in music streaming services. By embed lyric on music metadata, lyric could be able as an access point for retrieval. Moreover, lyric as metadata could be part of music digital file handling.

‘Modulation’ by Richard Powers: Digital sound, compression and the short story

This article presents a reading of ‘Modulation’ (2008) by Richard Powers. Firstly, I consider the short story’s representation of the MP3 music file, specifically its effects on how music is circulated and stored, as well as how it sounds. These changes are the result of different processes of compression. The MP3 format makes use of data compression to reduce the file size of a digital recording significantly. Such a loss of information devises new social and material relations between what remains of the original music, the recording industry from which MP3s emerged and the online markets into which they enter. I argue that ‘Modulation’ is a powerful evocation of a watershed moment in how we consume digital sound: what Jonathan Sterne has termed the rise of the MP3 as ‘cultural artifact’. I contend that the short story, like the MP3, is also a compressed manner of representation. I use narrative theory and short story criticism to substantiate this claim, before positioning ‘Modulation’ alongside Powers’s novels of information. I conclude by suggesting that ‘Modulation’ offers an alternative to representing information through an excess of data. This article reads Powers’s compressed prose as a formal iteration of the data compression the story narrates.

Transformation of Nonmultiple Cluster Music Cyclic Shift Topology to Music Performance Style

Music is an abstract art form that uses sound as its means of expression. It has deeply affected our lives. This paper proposes a method for extracting segment features from nonmultiple cluster music files. We divide each piece of music into multiple segments and extract the features of each segment. The specific process includes nonmultiple cluster music file note extraction, main melody extraction, segment division, and segment feature extraction. The segment feature is extracted from a segment of a piece of music, contains the main melody and accompaniment information of the segment, and can reflect the sequence relationship of the notes. This paper proposes a performance style conversion network based on recurrent neural network and convolutional neural network. The bidirectional recurrent neural network based on Gated Recurrent Unit (GRU) is used to extract different styles of note feature vector sequences, and the extracted note feature vector sequence is used to predict the intensity of a specific style, and the intensity changes of different styles of nonmultiple cluster music are better learned. Through the comparison, the multiclassification strategy of “one-to-the-rest” is selected, and the fuzzy recurrent neural network is applied to the shortcomings of the unrecognizable area. Finally, according to the feature extraction method and the principle of the classifier algorithm studied in this paper, a music style classification system is implemented in the MATLAB environment. Experimental simulation shows that this system can effectively classify music performance styles.

Music Cryptography based on Carnatic Music

Music and cryptography have been linked to one another since ancient times. The idea of replacing plaintext letters with music notes and sending the music file to receiver, is not new. But such replacements sometimes result in music clips which are not pleasant to listeners and thereby leading to the music clip gaining unnecessary extra attention. Most of the works done in this area, fail to ensure the generation of a music clip that invariably conforms to any particular form of music. Melody of the music clip is neglected. In order to address this issue, current paper proposes a novel approach for sharing a secret message based on concepts of Carnatic Classical Music. The method proposed here aims at converting a message in textual format to a music clip before sending it to the receiver. Receiver can then decrypt that message using the knowledge of range of frequency values associated with each musical note also called as 'swara' in Carnatic Classical Music. Each plaintext character from English alphabet is replaced by different combinations of swaras. The set of swaras mapped to each plaintext character is so chosen that the final music file produced as the output of encryption always conforms to a melodic form ('Raga') governed by the framework of Carnatic Classical Music. Ten subject matter experts in the field of Carnatic music have given their opinion about the conformance of these music clips to specified ragas. Also, Mean Opinion Score (MOS) of 25 listeners has been tabulated to test and verify the melodic aspect of these music clips.

Real-Time Optical Music Recognition System for Dulcimer Musical Robot

Traditional optical music recognition (OMR) is an important technology that automatically recognizes scanned paper music sheets. In this study, traditional OMR is combined with robotics, and a real-time OMR system for a dulcimer musical robot is proposed. This system gives the musical robot a stronger ability to perceive and understand music. The proposed OMR system can read music scores, and the recognized information is converted into a standard electronic music file for the dulcimer musical robot, thus achieving real-time performance. During the recognition steps, we treat note groups and isolated notes separately. Specially structured note groups are identified by primitive decomposition and structural analysis. The note groups are decomposed into three fundamental elements: note stem, note head, and note beams. Isolated music symbols are recognized based on shape model descriptors. We conduct tests on real pictures taken live by a camera. The tests show that the proposed method has a higher recognition rate.

Performance analysis of mobile applications developed with different programming tools

This study examines the efficiency of certain software tasks in applications developed using three frameworks for the Android system: Android SDK, Qt and AppInventor. The results obtained using the Android SDK provided the benchmark for comparison with other frameworks. Three test applications were implemented. Each of them had the same functionality. Performance in the following aspects was tested: sorting a list of items using recursion by means of the Quicksort algorithm, access time to a location from a GPS sensor, duration time for reading the entire list of phone contacts, saving large and small files, reading large and small files, image conversion to greyscale, playback time of a music file, including the preparation time. The results of the Android SDK are good. Unexpectedly, it is not the fastest tool, but the time for performing most operations can be considered satisfactory. The Qt framework is overall about 34% faster than the Android SDK. The worst in terms of overall performance is the AppInventor: it is, on average, over 626 times slower than Android SDK.

Music Generation Based on Convolution-LSTM

In this paper, we propose a model that combines Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM) for music generation. We first convert MIDI-format music file into a musical score matrix, and then establish convolution layers to extract feature of the musical score matrix. Finally, the output of the convolution layers is split in the direction of the time axis and input into the LSTM, so as to achieve the purpose of music generation. The result of the model was verified by comparison of accuracy, time-domain analysis, frequency-domain analysis and human-auditory evaluation. The results show that Convolution-LSTM performs better in music genertaion than LSTM, with more pronounced undulations and clearer melody.

STUDENT’S ATTITUDE TOWARDS PEER-TO-PEER MUSIC FILE SHARING AND DOWNLOADING FROM INTERNET-A CROSS SECTIONAL STUDY OF AMERICAN AND MOROCCAN STUDENTS

Purpose: The main aim of this study is to compare two different cultures in terms of ethical and legal use of music sharing technology. Students’ perceptions of downloading from the web and sharing music with each other varies across cultures. Such practices have caused significant losses to the music and film industry. Methodology/Sampling: Primary data was collected from Morocco and US university students on a pretested questionnaire. Besides frequency distributions, chi-square, t-test and confirmatory factor analysis were used as inferential tools. Findings: Results showed a considerable difference in between Moroccan and American students’ attitude in terms of music files sharing and downloading. To Compare to Moroccans, American students were more aware of ethical, and legal aspects of music file sharing and download from the web. Practical Implications: Research findings suggests music industry should focus on making music products more affordable and create awareness towards music piracy through promotional campaigns keeping in mind the cultural differences of end users. The research findings will set a platform for further comparative studies in the same context.