Reviewerly/exHarmony huggingface dataset:
Teaching electronic music – journeys through a changing landscape

In this essay, electronic music composer Simon Emmerson examines the development of electronic music in the UK through his own experience as composer and teacher. Based on his lifetime experiences, Emmerson talks about the changing landscape of teaching electronic music composition: "˜learning by doing' as a fundamental approach for a composer to find their own expressive voice; the importance of past technologies, such as analogue equipment and synthesizers; the current tendencies of what he calls the "˜age of the home studio'; the awareness of sonic perception, as opposed to the danger of visual distraction; questions of terminology in electronic music and the shift to the digital domain in studios; among other things. [note by editor].
The 1994 Crime Bill

Research Article| February 01 2020 The 1994 Crime Bill: Legacy and Lessons – Overview and Reflections Richard Rosenfeld Richard Rosenfeld Professor Emeritus, University of Missouri – St. Louis Search for other works by this author on: This Site PubMed Google Scholar Federal Sentencing Reporter (2020) 32 (3): 147–152. https://doi.org/10.1525/fsr.2020.32.3.147 Views Icon Views Article contents Figures & tables Video Audio Supplementary Data Peer Review Share Icon Share Twitter LinkedIn Tools Icon Tools Get Permissions Cite Icon Cite Search Site Citation Richard Rosenfeld; The 1994 Crime Bill: Legacy and Lessons – Overview and Reflections. Federal Sentencing Reporter 1 February 2020; 32 (3): 147–152. doi: https://doi.org/10.1525/fsr.2020.32.3.147 Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentFederal Sentencing Reporter Search This content is only available via PDF. © 2020 Vera Institute of Justice2020 Article PDF first page preview Close Modal You do not currently have access to this content.
Packing Tree Degree Sequences

Abstract A degree sequence is a list of non-negative integers, $${D = d_1, d_2, \ldots , d_n}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:mi>D</mml:mi><mml:mo>=</mml:mo><mml:msub><mml:mi>d</mml:mi><mml:mn>1</mml:mn></mml:msub><mml:mo>,</mml:mo><mml:msub><mml:mi>d</mml:mi><mml:mn>2</mml:mn></mml:msub><mml:mo>,</mml:mo><mml:mo>…</mml:mo><mml:mo>,</mml:mo><mml:msub><mml:mi>d</mml:mi><mml:mi>n</mml:mi></mml:msub></mml:mrow></mml:math> . It is called graphical if there exists a simple graph G such that the degree of the i th vertex is $$d_i$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:msub><mml:mi>d</mml:mi><mml:mi>i</mml:mi></mml:msub></mml:math> ; G is then said to be a realization of D . A tree degree sequence is one that is realized by a tree. In this paper we consider the problem of packing tree degree sequences: given k tree degree sequences, do they have simultaneous (i.e. on the same vertices) edge-disjoint realizations? We conjecture that this is true for any arbitrary number of tree degree sequences whenever they share no common leaves (degree-1 vertices). This conjecture is inspired by work of Kundu (SIAM J Appl Math 28:290–302, 1975) that showed it to be true for 2 and 3 tree degree sequences. In this paper, we give a proof for 4 tree degree sequences and a computer-aided proof for 5 tree degree sequences. We also make progress towards proving our conjecture for arbitrary k . We prove that k tree degree sequences without common leaves and at least $$2k-4$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:mn>2</mml:mn><mml:mi>k</mml:mi><mml:mo>-</mml:mo><mml:mn>4</mml:mn></mml:mrow></mml:math> vertices which are not leaves in any of the trees always have edge-disjoint tree realizations. Additionally, we show that to prove the conjecture, it suffices to prove it for $$n \le 4k - 2$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:mi>n</mml:mi><mml:mo>≤</mml:mo><mml:mn>4</mml:mn><mml:mi>k</mml:mi><mml:mo>-</mml:mo><mml:mn>2</mml:mn></mml:mrow></mml:math> vertices. The main ingredient in all of the presented proofs is to find rainbow matchings in certain configurations.
Evaluation of the estimation of shortwave solar radiation in Japan using the Mountain Microclimate Simulation Model

Solar radiation is an essential parameter for ecological, agricultural, and other models. However, the availability of large-scale radiation data is usually limited. The Mountain Microclimate Simulation Model (MTCLIM) can resolve such data insufficiency by estimating missing daily shortwave solar radiation data using simple climatological and topographic parameters. Several studies have found the performance of the MTCLIM to be sufficient for the estimation of solar radiation. However, its performance in the East Asian monsoon zone, which is generally characterized by warm wet summers and cold dry winters, has not been thoroughly evaluated. We assessed the performance of the MTCLIM in Japan located at the East Asian monsoon zone. We estimated daily shortwave solar radiation using daily maximum and minimum temperature and precipitation data recorded over 57 years and topographic parameters including slope angle and direction at 41 meteorological stations. Then, we compared the estimated solar radiation with the solar radiation observed at each meteorological station using a simple linear regression equation. The slope of the regression equation without intercept was 0.96 and the coefficient of determination (R2) was 0.61 for all data. The estimation performance was increased for the monthly mean of daily solar radiation (slope=1.03; R2=0.93). The degree of estimation error showed geographical and seasonal trends; stations located at higher latitudes had larger slopes than those at lower latitudes. The bias was largest (positive) in spring and smallest (negative) in summer. This study confirmed that the MTCLIM performed sufficiently well to estimate solar radiation in Japan. In particular, the model’s high performance for the monthly mean of daily solar radiation suggests that it provides estimates of solar radiation that are sufficiently accurate for ecological, agricultural, and other models in which values of average solar radiation for a given period of time are more meaningful than instantaneous daily solar radiation.
Minimal Solvers for Indoor UAV Positioning

In this paper we consider a collection of relative pose problems which arise naturally in applications for visual indoor UAV navigation. We focus on cases where additional information from an onboard IMU is available and thus provides a partial extrinsic calibration through the gravitational vector. The solvers are designed for a partially calibrated camera, for a variety of realistic indoor scenarios, which makes it possible to navigate using images of the ground floor. Current state-of-the-art solvers use more general assumptions, such as using arbitrary planar structures; however, these solvers do not yield adequate reconstructions for real scenes, nor do they perform fast enough to be incorporated in real-time systems. We show that the proposed solvers enjoy better numerical stability, are faster, and require fewer point correspondences, compared to state-of-the-art solvers. These properties are vital components for robust navigation in real-time systems, and we demonstrate on both synthetic and real data that our method outperforms other methods, and yields superior motion estimation.
Case Study on Non-Functional Requirement Change Impact Traceability for Agile Software Development

Currently, it is crucial to develop a complex software on time. Agile software development methodologies provide methods to develop a system in term of time and cost-saving but it has been criticized for software quality management. In this paper, a case study is used to find out the need of NFR change impact traceability approach in most of Agile software methodology. This case study was conducted in an undergraduate course that trained the students on how to develop software using Agile process model.This case study has been conducted for 4 months in an undergraduate-level course, Application Development. The samples of this case study are among Year 3 undergraduate students. The case study shows the lack of traceability techniques in the existing Agile process model (SFDD- Secured Feature Driven Development) that result to non-awareness of NFR change impact during development. Based on the case study mentioned the main objective of the case study conducted in survey is to empirically test the theoretical constructs and the hypothesized relationships of the research issues that concern on the lack of change impact management towards NFR in Agile Software Methodology. TANC (Traceability for Agile Non-Functional Requirement Change Impact) model offered techniques in tracing change impact during the agile development process. Therefore, the result of the case study, a traceability process model needs to design in order to tackle the NFR change impact issues in Agile software development.
Research on Detection Technology of Autonomous Landing Based on Airborne Vision

Abstract In this paper, aiming at the cooperative target detection problem in the process of unmanned helicopter sliding down, a detection method based on complementary filtering is proposed, which fuses improved SSD algorithm and related filtering KCF algorithm. The improved deep learning SSD model redesigns the feature extraction structure to improve the detection effect of small and medium targets for the small target size and large scale change in the landing scene. Then use the detection results of the SSD model to correct the KCF detection, adjust the weight parameters, and output the final fusion detection results. The test results show that the improved model detection accuracy is significantly improved, the detection accuracy in various environments reaches 93.3%, which is higher than 86.1% of the classic SSD model and 87.5% of the Faster-rcnn model. The final proposed fusion detection algorithm has a success rate of 91.1% and a processing speed of 91 hz, which basically satisfies the requirements of the ship.
A Review on Automatic Classification of Breast Cancer Using Supervised Learning Strategies

Breast cancer is the most perilous disease affecting women throughout the world from generations. Modern methodologies and developing approaches are focused on complete and confined rehabilitation of breast malignancy. Complete treatment of breast cancer is possible if it can be identified in the early stages of diagnosis as there is no indication of breast cancer in about 90% of cases. To improve this factor, medical image classification is used in recent years, where tissue images are classified into cancerous and non-cancerous. Many researchers have proposed different approaches to achieve better recognition of breast cancer in initial stages with a very low error rate using medical image classification. These methodologies are studied in this paper to gain state-of-the-art. It is observed that different machine learning and deep learning-based breast cancer classification techniques are widely proposed by researchers. These techniques are effective but still have a scope of improvement.
Technological Imperative: Current Trends in the Foreign Market of Library Technologies

Currently, innovations in the field of information technology are increasingly becoming the key to the company’s success, its main competitive advantage. The library business is no exception in this regard. The purpose of the study is to study the current trends in the foreign market of library technologies as a factor that directly affects the methods and forms of library work based on information provided on the websites of foreign companies, as well as in summary reports on the development dynamics of the market of library technologies. Specialized companies offer to libraries the new resource management technologies, metadata sets for expanding collection or software tools for optimizing electronic catalogues. They are the providers of innovation for libraries, intermediaries between the end user and the advanced achievements of IT technologies. The author notes that among the priorities of the development of library technology industry the unchallenged leadership belongs to library-information systems of the new generation: first, library service platforms that use cloud technologies and service architecture, and second, advanced integrated library systems with the addition of Web modules, Web applications, etc. The hidden spring of the development of foreign market of library technologies is the fundamental change in the concept of library automation, the transition from unified library systems, managing print and electronic resources and basing on client-server architecture, to universal library service platforms with cloud storage. The author analyses in detail the trends of the library technology market in the United States as the most developed and active market, as well as in Europe and Latin America. The article draws attention to the companies — leaders in the competitive struggle in the market of library technologies. The author concludes that reorientation to network technologies means for libraries, on one hand, increase of efficiency, access to up-to-date online information, closer communication with users, reduction of non-core costs, and on the other hand, constant dependence on network service providers, whose set increases proportionally to the growing differentiation of the market, the maximum openness and partial de-specialisation, compensated by active participation in digital Humanities projects, and ultimately, loss of institutional autonomy.
THE 70-TH ANNIVERSARY OF THE CENTRAL SCIENTIFIC LIBRARY OF THE IRKUTSK SCIENTIFIC CENTER OF THE SB RAS

In 2019, the Central Scientific Library of the Irkutsk Scientific Center of SB RAS (CSL ISC) celebrated its 70th anniversary. The library history began with the creation of the East Siberian Branch of the USSR Academy of Sciences (ESB or Branch) in Irkutsk in February 1949. Immediately the aim of information support for×scientific research arouse. One room was allotted on the second floor of the building on the Red Star street, 18 (now – Sukhe-Bator St.). The first 600 books were purchased at the local library collector. Anna Sergeevna Chumicheva, having at that time rich work experience in various types of libraries: trade-union library, NKVD club, and university library, was appointed director of ESB scientific library. The library acquisition profile was determined in accordance with research directions of institutions that were part of the Branch at the very beginning of its activities: Institute of Geology, Institute of Energy and Chemistry, Biological Sector and Geographic and Economic Sector. Much attention was paid to bibliographic activities: in the 1960-1980s. the staff of ESB scientific library created a series of indexes on hydrogeology, seismicity and engineering geology of Siberia and the Far East, on Lake Baikal. Currently, the Central Library is a methodological center for scientific libraries of academic institutes in Irkutsk and the Irkutsk region. The library has more than 366 thousand documents (books, brochures, journals), including 1000 documents on electronic media, about 4 thousand readers (scientists, graduate students, students), including 1260 online. CSL creates resources of own generation – the electronic database “Lake Baikal”, the database “Abstracts and Dissertations”, etc. In terms of popularizing science, the library has published a series of booklets about scientists and a documentary essay, “Irkutsk Academic-city: milestones in history” (Irkutsk, 2019). Since July 2017, the director of the Central Scientific Library is a young scientist Ivan Leonidovich Trofimov. From 1968 to the present day, the library is located in the building of the Institute of the Earth’s Crust of the Siberian Branch of the USSR Academy of Sciences (since 1992 – SB RAS).
Efficiently Composing Validated Systems Integration Gateways for Dynamic, Diverse Data

Software systems typically evolve independently from one another. Integration opportunities and benefits only become apparent when new users or organizations adopt the system into the composition of a new system of systems solution, typically when new use cases are identified, or tangential needs arise. This leads to systems designed to use different data formats, network protocols, interaction patterns, and other disparities unable to natively communicate with each other. When integration does occur, it is often with custom one-off solutions that bridge the networks and systems in question. While integration may be plausible and even successful, these solutions tend to be costly, slow to produce, and tightly coupled to the specific systems or, even worse, specific versions of systems that they are connecting. In this paper we examine ROGER, a composable and dynamic gateway building framework that helps to address these integration costs and complexities. The ROGER framework abstracts away the common infrastructure needed in any system-bridging middleware, fosters reuse and capability sharing through a composition-driven plug-in framework, and allows for rapid gateway construction through a policy-centric composition structure. ROGER seeks to shorten integration gateway development time, reduce the amount of code creation required to build and deploy new gateways, as well as enable in-mission adaptation and extension of gateway capabilities as mission parameters and system awareness dictates. At the heart of this dynamism and adaptability in ROGER is the Information Flow Policy (IFP), a domain specific language that describes processing pipelines over incoming data streams. This paper presents the design of the compositional model and of the IFP that describes and enables the composition. We use a set of ROGER gateways as a dataset, along with a representative case study, in initial evaluations that show promising results regarding ROGER's ability to reduce development time and cost as well as minimize required skill sets.
The Automated Geoelectrical Data Processing Workflow of the PRIME Infrastructure Monitoring System

Summary PRIME (PRoactive Infrastructure Monitoring &amp; Evaluation) is a low-cost geoelectrical ground monitoring system developed by the British Geological Survey. It is designed to integrate with standardised technologies and information delivery platforms to provide remote, near real-time, volumetric monitoring of infrastructure earthworks condition, thereby aiding asset failure prediction and timely intervention. A key recent development has been the implementation of a fully automated data processing workflow to enable regular and timely delivery of information to end-users. It is a customisable procedure, which enables each monitoring objective to have its own combination of processing steps applied to its data. The standard workflow consists of: data filtering and quality assurance; motion sensing (under development); inverse image generation; property translation via petrophysical relationships; and image analysis. The flexible implementation of the workflow will allow for new processing steps to be incorporated as they are developed.
A Multi-document Summarization System for News Articles in Portuguese using Integer Linear Programming

Automatic Text Summarization (ATS) has been demanding intense research in recent years. Its importance is given the fact that ATS systems can aid in the processing of large amounts of textual documents. The ATS task aims to create a summary of one or more documents by extracting their most relevant information. Despite the existence of several works, researches involving the development of ATS systems for documents written in Brazilian Portuguese are still a few. In this paper, we propose a multi-document summarization system following a concept-based approach using Integer Linear Programming for the generation of summaries from news articles written in Portuguese. Experiments using the CSTNews corpus were performed to evaluate different aspects of the proposed system. The experimental results obtained regarding the ROUGE measures demonstrate that the developed system presents encourage results, outperforming other works of the literature.
Neural Pose Transfer by Spatially Adaptive Instance Normalization

Pose transfer has been studied for decades, in which the pose of a source mesh is applied to a target mesh. Particularly in this paper, we are interested in transferring the pose of source human mesh to deform the target human mesh, while the source and target meshes may have different identity information. Traditional studies assume that the paired source and target meshes are existed with the point-wise correspondences of user annotated landmarks/mesh points, which requires heavy labelling efforts. On the other hand, the generalization ability of deep models is limited, when the source and target meshes have different identities. To break this limitation, we proposes the first neural pose transfer model that solves the pose transfer via the latest technique for image style transfer, leveraging the newly proposed component -- spatially adaptive instance normalization. Our model does not require any correspondences between the source and target meshes. Extensive experiments show that the proposed model can effectively transfer deformation from source to target meshes, and has good generalization ability to deal with unseen identities or poses of meshes. Code is available at https://github.com/jiashunwang/Neural-Pose-Transfer .
Bug Report Summarization by Using Swarm Intelligence Approaches

Background: Bug reports are considered as a reference document, during the maintenance phase of the software development process. The developer's counsel them at whatever point they have to know about the reported bug and need to explore past bug solution. This process requires a sustainable amount of time due to a large number of comments. Therefore, the best solution to prevent the developers from reading the whole bug report is to summarize the entire discussion in a couple of sentences. Bug report summarization is the extraction of some important part of bug reports that are useful for investigation, resolving the bug with similar problems, reproducing the bug and checking the status of the bug. If the bug reports have huge volume, variety and velocity information as big data, extractive bug report summarization would be emerging as an issue. However, the examiners, find out the bug report summaries do not meet the expectation of the developer; there is a still need for reading the entire discussion. Objective: (1) To generate generalized unsupervised extractive bug report summarization system, which is easily applicable on any dataset without the need of effort and cost of manually creating summaries for training dataset (2) To handle the extensive number of comments and generate short summaries. (3) To reduce the data sparsity, reduction of information, redundancy and convergence issue for short and lengthy data set. (4) To achieve the semantic summarization solution and explore the large search space. (5) To provide the facility of adjusting the summary percentage. Methods: Particle swarm optimization and Hybridization of Ant Colony Optimization and Particle Swarm Optimization approaches are used with the advantage of feature weighting technique. Conclusion: The efficiency of the proposed approaches are compared with the best existing supervised and unsupervised approaches. The result shows that the Hybrid swarm intelligence approach provided better.