Cloud Twin: Native execution of android applications on the Windows Phone

Holder, Ethan; Shah, Eeshan; Davoodi, Mohammed; Tilevich, Eli

doi:10.1109/ase.2013.6693119

Cited by 6 publications

(2 citation statements)

References 7 publications

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“…From a high-level, reading in any form of music and writing out a related, different form is essentially translation, an area which I have previously explored in some depth [47] [45] [48]. There are many research efforts to translate forms of music into other languages or versions.…”

Section: Music Scan and Searchmentioning

confidence: 99%

Musiplectics: computational assessment of the complexity of music scores

Holder

Tilevich

Gillick

2015

2015 ACM International Symposium on New Ideas, New Paradigms, and Reflections on Programming and Software (Onward!)

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In the Western classical tradition, musicians play music from notated sheet music, called a score. When playing music from a score, a musician translates its visual symbols into sequences of instrument-specific physical motions. Hence, a music score's overall complexity represents a sum of the cognitive and mechanical acuity required for its performance. For a given instrument, different notes, intervals, articulations, dynamics, key signatures, and tempo represent dissimilar levels of difficulty, which vary depending on the performer's proficiency. Individual musicians embrace this tenet, but may disagree about the degrees of difficulty. This thesis introduces musiplectics1 , a systematic and objective approach to computational assessment of the complexity of a music score for any instrument. Musiplectics defines computing paradigms for automatically and accurately calculating the complexity of playing a music score on a given instrument. The core concept codifies a two-phase process. First, music experts rank the relative difficulty of individual musical components (e.g., notes, intervals, dynamics, etc.) for different playing proficiencies and instruments. Second, a computing engine automatically applies this ranking to music scores and calculates their respective complexity. As a proof of concept of musiplectics, we present an automated, Web-based application called Musical Complexity Scoring (MCS) for music educators and performers. Musiplectics can engender the creation of practical computing tools for objective and expeditious assessment of a music score's suitability for the abilities of intended performers.This thesis is based on research submitted for publication at ONWARD'15.That this work received support from a Virginia Tech ICAT SEAD grant.1 musiplectics = music + plectics, Greek for the study of complexity DedicationTo the memory of Coppertone Holder, the standard by which all other pets shall be measured.iii Acknowledgments I have not experienced anything in this world quite like the publication of my master's thesis. It has taken only my last two years of graduate school to accomplish, but it has brought me (kicking and screaming at times) further along in those two years than I could have possibly imagined. This process took its toll many times not only on myself, but on all of those close to me. Thus, I'd like to take a moment to graciously acknowledge and thank all of those that had a hand in both shaping my research and keeping my sanity.

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Section: Music Scan and Searchmentioning

confidence: 99%

Musiplectics: computational assessment of the complexity of music scores

Holder

Tilevich

Gillick

2015

2015 ACM International Symposium on New Ideas, New Paradigms, and Reflections on Programming and Software (Onward!)

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“…Now, it supports ARC and we don't have to retain and release the objects. XCode takes care of the job automatically in compile time [21] [22].…”

Section: Memory Management In Iosmentioning

confidence: 99%

Resource management and security issues in mobile phone operating systems: A comparative analysis

Awan

Waqar

Faseeh

et al. 2017

Preprint

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Nowadays Mobile phones are becoming more popular in our daily lives. Mobile technology has a great effect on human life. Our daily tasks are dependent on mobile devices. Memory Management (MM), Security and Performance plays an important role in every handheld device specially in mobile phones, which are very much dependent on their operating system (OS). These embedded operating systems are on the driving seat when we talk about efficient and useful memory management and secure handling. Three popular OS in mobile phones are Android, Windows and iOS (iPhone OS). Each OS has its own way of managing the memory and provide it to certain number of applications. Android is an open software available for the people to modify as per their needs. But Windows and iOS operating systems didn"t allow their software as open source. Researchers have done a large amount of work using different mechanisms and decision makings to develop new ways to manage the memory of these OS"s. This work shows a comparative analysis of different memory management and security related techniques in above three operating systems. In this paper, we present the analysis of memory management and security in mobile phone operating systems with respect to apps, main memory, cache memory and virtual memory. Also, we compare the overall performance of these OS"s in terms of MM, security concerns. This study will help in finding better operating system in terms of efficient memory management and security.

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