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Geometry of music perception
(2022)
Prevalent neuroscientific theories are combined with acoustic observations from various studies to create a consistent geometric model for music perception in order to rationalize, explain and predict psycho-acoustic phenomena. The space of all chords is shown to be a Whitney stratified space. Each stratum is a Riemannian manifold which naturally yields a geodesic distance across strata. The resulting metric is compatible with voice-leading satisfying the triangle inequality. The geometric model allows for rigorous studies of psychoacoustic quantities such as roughness and harmonicity as height functions. In order to show how to use the geometric framework in psychoacoustic studies, concepts for the perception of chord resolutions are introduced and analyzed.
Generating synthetic data is a relevant point in the machine learning community. As accessible data is limited, the generation of synthetic data is a significant point in protecting patients' privacy and having more possibilities to train a model for classification or other machine learning tasks. In this work, some generative adversarial networks (GAN) variants are discussed, and an overview is given of how generative adversarial networks can be used for data generation in different fields. In addition, some common problems of the GANs and possibilities to avoid them are shown. Different evaluation methods of the generated data are also described.
Die einzelne, allumfassende Managementmethode für ein ganzheitliches Leistungsmanagement gibt es nicht. Vielmehr ist das Zusammenspiel aller erfolgskritischen Managementdisziplinen im Rahmen eines integrativen Managementsystems wichtig, bei dem alle Akteure und Beteiligten auch bei unterschiedlichem Fokus und Sichtweise koordiniert an einem Strang ziehen. Erfolgskritisch ist es jedoch, dass eine unternehmensindividuelle Anpassung mit einem ganzheitlichen Erfahrungshintergrund geplant, komponiert und verzahnt wird. Management Cockpits können als Stufenlösung einen wertvollen Beitrag erbringen, indem sie als Integrationsebene eine Transparenz und Kommunikationsplattform für ein ganzheitliches Leistungsmanagement generieren, selbst wenn die vollständige, fachliche, methodische, prozessuale und technische Integration noch nicht komplett vollzogen bzw. erreicht ist.
Gamification has been increasingly applied to software engineering education in the past. The approaches vary from applying game elements on a conceptual phase in the course to using specific tools to engage the students more and support their learning goals. However, existing tools usually have game elements, such as quizzes or challenges, but do not provide a more computer game-like experience. Therefore, we try to raise the level of gamified learning experience to another level by proposing Gamify-IT. Gamify-IT is a Unity- and web-based game platform intended to help students learn software engineering. It follows an immersive role-play game characteristic where the students explore a world, find and solve minigames and clear dungeons with SE tasks. Lecturers can configure the worlds, e.g., to add content hints. Furthermore, they can add and configure minigames and dungeons to include exercises in a fully gamified way. Thereby, they customize their course in Gamify-IT to adapt the world very precisely to other materials such as lectures or exercises. Results of an evaluation of our initial prototype show that (i) students like to engage with the platform, (ii) students are motivated to learn when using Gamify-IT, and (iii) the minigames support students in understanding the learning objectives.
While the recently emerged microservices architectural style is widely discussed in literature, it is difficult to find clear guidance on the process of refactoring legacy applications. The importance of the topic is underpinned by high costs and effort of a refactoring process which has several other implications, e.g. overall processes (DevOps) and team structure. Software architects facing this challenge are in need of selecting an appropriate strategy and refactoring technique. One of the most discussed aspects in this context is finding the right service granularity to fully leverage the advantages of a microservices architecture. This study first discusses the notion of architectural refactoring and subsequently compares 10 existing refactoring approaches recently proposed in academic literature. The approaches are classified by the underlying decomposition technique and visually presented in the form of a decision guide for quick reference. The review yielded a variety of strategies to break down a monolithic application into independent services. With one exception, most approaches are only applicable under certain conditions. Further concerns are the significant amount of input data some approaches require as well as limited or prototypical tool support.
Under update intensive workloads (TPC, LinkBench) small updates dominate the write behavior, e.g. 70% of all updates change less than 10 bytes across all TPC OLTP workloads. These are typically performed as in-place updates and result in random writes in page-granularity, causing major write-overhead on Flash storage, a write amplification of several hundred times and lower device longevity.
In this paper we propose an approach that transforms those small in-place updates into small update deltas that are appended to the original page. We utilize the commonly ignored fact that modern Flash memories (SLC, MLC, 3D NAND) can handle appends to already programmed physical pages by using various low-level techniques such as ISPP to avoid expensive erases and page migrations. Furthermore, we extend the traditional NSM page-layout with a delta-record area that can absorb those small updates. We propose a scheme to control the write behavior as well as the space allocation and sizing of database pages.
The proposed approach has been implemented under Shore- MT and evaluated on real Flash hardware (OpenSSD) and a Flash emulator. Compared to In-Page Logging it performs up to 62% less reads and writes and up to 74% less erases on a range of workloads. The experimental evaluation indicates: (i) significant reduction of erase operations resulting in twice the longevity of Flash devices under update-intensive workloads; (ii) 15%-60% lower read/write I/O latencies; (iii) up to 45% higher transactional throughput; (iv) 2x to 3x reduction in overall write
amplification.
Near-Data Processing is a promising approach to overcome the limitations of slow I/O interfaces in the quest to analyze the ever-growing amount of data stored in database systems. Next to CPUs, FPGAs will play an important role for the realization of functional units operating close to data stored in non-volatile memories such as Flash.It is essential that the NDP-device understands formats and layouts of the persistent data, to perform operations in-situ. To this end, carefully optimized format parsers and layout accessors are needed. However, designing such FPGA-based Near-Data Processing accelerators requires significant effort and expertise. To make FPGA-based Near-Data Processing accessible to non-FPGA experts, we will present a framework for the automatic generation of FPGA-based accelerators capable of data filtering and transformation for key-value stores based on simple data-format specifications.The evaluation shows that our framework is able to generate accelerators that are almost identical in performance compared to the manually optimized designs of prior work, while requiring little to no FPGA-specific knowledge and additionally providing improved flexibility and more powerful functionality.
The promise of immutable documents to make it easier and less expensive for consumers and producers to collaborate in a verifiable way would represent an enormous progress, especially as companies strive for establish service contracts which are based on the flow of many small transactions using machine-to-machine communication. The blockchain technology logs these data, verifies the authenticity and make them available for service offers. This work deals with an architecture enabling to setup order processing between consumers and produceers using blockchain. In this way, the technical feasibility is shown and the special characteristics of blockchain production networks will be discussed.
Online credit card fraud presents a significant challenge in the field of eCommerce. In 2012 alone, the total loss due to credit card fraud in the US amounted to $ 54 billion. Especially online games merchants have difficulties applying standard fraud detection algorithms to achieve timely and accurate detection. This paper describes the Special constrains of this domain and highlights the reasons why conventional algorithms are not quite effective to deal with this problem. Our suggested solution for the problem originates from the fields of feature construction joined with the field of temporal sequence data mining. We present Feature construction techniques, which are able to create discriminative features based on a sequence of transaction and are able to incorporate the time into the classification process. In addition to that, a framework is presented that allows for an automated and adaptive change of features in case the underlying pattern is changing.
The relative pros and cons of using students or practitioners in experiments in empirical software engineering have been discussed for a long time and continue to be an important topic. Following the recent publication of “Empirical software engineering experts on the use of students and professionals in experiments” by Falessi, Juristo, Wohlin, Turhan, Münch, Jedlitschka, and Oivo (EMSE, February 2018) we received a commentary by Sjøberg and Bergersen. Given that the topic is of great methodological interest to the community and requires nuanced treatment, we invited two editorial board members, Martin Shepperd and Per Runeson, respectively, to provide additional views.