Reviewerly/exHarmony huggingface dataset:
Carrying the organ - the thing on the portative, part 2

The present article is the continuation of the text published in issue 12 of “Notes Muzyczny” from December 2019. This paper is devoted to discussing technical issues connected with designing and constructing Opus 1 Portative built by the author; it also touches on practical performance aspects of portative music. The instrument fully designed and constructed by the author is a one-octave portative with stoppedwoodenpipesanditssoundrangeisc1-c2withanoptiontoretunecs1intobandb 1 into cs2 or d2. The default tuning pitch is a=440Hz but it can be altered within 415-465Hz; the temperament may also be freely changed. One wedge bellow placed at the back of the instrument is used for bellow treading. A leather belt worn over the shoulder and the low weight of the construction allow for playing the instrument not only while sitting but also in a standing position. As compared to similar instruments, this portative has more extended case which fully covers the ends of pipes. Opus 1 Portative was built thanks to a few years of research studies and technical work of the author covering the construction of organ components and independent attempts to miniaturise them for the purpose of construction of this specific instrument. Thanks to that, in order to build Opus 1 the author used a few original solutions – e.g. the way of gluing top corners of the bellow, the way of regulating the airflow through the foot of the pipe or the technique of attaching the handle to the stopper of a stopped pipe, with the limited space above its body. The majority of experimental solutions brought satisfactory results and for the remaining ones Piotr Dziewiecki managed to find ways to overcome the difficulties which arose. The author uses the instrument in his own performance practice both for solo music and for playing in ensembles. The portative is very useful for both fields, ensuring wide dynamics and articulation-related capacities. They are connected with an option to very precisely control the pressure of air powering the pipes and with their way of blowing. Its characteristic sound, warm and full of depth, brings associations with human voice. Thanks to that, vocal-and- instrumental music performed on it, with the portative player rendering the singer’s part, sounds good.
Research on Privacy Protection of Indoor Temperature Acquisition Based on MapReduce Model

The privacy of indoor temperature acquisition system is protected, and the information encryption and secure storage ability of indoor temperature acquisition are improved to prevent data leakage. A privacy protection and anti-attack encryption algorithm of indoor temperature acquisition based on MapReduce model is proposed. The data structure model of privacy protection data in indoor temperature acquisition system is analyzed, the information coding model of indoor temperature data is constructed, and the random sequence analysis of privacy protection data is carried out by combining data vector quantification coding method. MapReduce model and fuzzy block encryption control method are used to improve the anti-attack encryption algorithm of privacy protection data in indoor temperature acquisition system. The simulation results show that the algorithm can resist leakage encryption of privacy protection data in indoor temperature acquisition system, enhance the randomness of key coding distribution of data, reduce the deciphering probability, improve the privacy protection ability of indoor temperature acquisition, reduce the risk of data leakage and attack, improve the privacy protection performance of data encryption, and have good application value in indoor temperature acquisition and information encryption.
Fast hashing with strong concentration bounds

Previous work on tabulation hashing by Pǎtraşcu and Thorup from STOC’11 on simple tabulation and from SODA’13 on twisted tabulation offered Chernoff-style concentration bounds on hash based sums, e.g., the number of balls/keys hashing to a given bin, but under some quite severe restrictions on the expected values of these sums. The basic idea in tabulation hashing is to view a key as consisting of c=O(1) characters, e.g., a 64-bit key as c=8 characters of 8-bits. The character domain Σ should be small enough that character tables of size |Σ| fit in fast cache. The schemes then use O(1) tables of this size, so the space of tabulation hashing is O(|Σ|). However, the concentration bounds by Pǎtraşcu and Thorup only apply if the expected sums are ≪ |Σ|.
Feature Space Oversampling Technique for Imbalanced Classification

The classification problem with imbalanced data is very common in real world. With traditional classification methods, it is generally difficult to obtain satisfactory classification results. Oversampling provides a feasible solution to this kind of classification problems. Existing oversampling methods generally choose borderline minority samples to generate new samples. It would result in too many synthetic minority class samples are in the boundary region such that the original boundary between different classes is changed. To deal with this issue, a feature space oversampling technique (FSOTE) is presented in this study. By the FSOTE algorithm, the minority class clusters are indeed found from the feature space, and the synthetic minority class samples are uniformly filled in the interior of these clusters. Tested on some widely adopted imbalance data sets, it confirms that the classification accuracy is effectively improved by the proposed FSOTE than by some previous methods.
Quantum Electromagnetic Scattering and the Sidelobe Advantage

Quantum remote sensing, also known as Quantum Detection and Ranging (QUDAR), is the use of entangled photon states to detect targets at a stand-off distance. It inherently relies on sending many single photons through free space, bouncing off of a target and returning to the sensor. It is therefore necessary to understand how single photons interact and scatter from targets of macroscopic size. This paper relates quantum and classical scattering in the far field regime. Specifically, we show that due to the photon's position uncertainty, the path over which the photon traverses is not well defined, and this causes quantum interference. The result of this interference exactly replicates classical scattering behavior of electromagnetic waves. We will show that one can exactly derive the classical electric field scattering integral using a purely quantum construction. Although this paper focuses on the context of QUDAR, it is very general to any application involving far-field electromagnetic scattering.
THE USER-DRIVEN MINIMUM FEASIBLE PRODUCT – TOWARDS A NOVEL APPROACH ON USER INTEGRATION

Abstract User integration is a key aspect of new product development. When applying corresponding methods, however, there is a communication gap that needs to be overcome by the designer. Prototyping is a means to bridge this disjunction, yet brings its own set of hermeneutic limitations. Taking a closer look at the processual information exchange, we propose the concept of the user-driven minimum feasible product (UD-MFP). It describes the artefact generated by the users themselves in their specific context, which contains the essence of the problem's solution as a possible source of validation.
On Approach to Training in Methods of Software Working Out

The article analyzes the approach to teaching the software design and work-out methods in the framework of "Business-informatics". It proposes developing the teaching process proceeding from the analysis of software reliability criterion. Support of software reliability requirements follows all the steps of software life cycle and implementation of this requirement guarantees the high-quality software development. Special aspects of teaching data engineering within the frame of "Business-Informatics" specialty are described. The thesis considering the used IT relating rather to typical "basic" technologies than to unique IT is analyzed. At the same time the main property of academic activity is its engineering not scientific character. Higher school outputs primarily "the basic" knowledge and qualification in a definite subject domain of modern economic life. Opinion is advanced that in the "Business-Informatics" framework the typical widespread "basic" IT should be taught. The subject steering documents are proposed to be revised toward increase in study hours on IT introduction, backing and practical application and decrease in hours for developing and designing the info systems and IT. Proposal of configuring the software development method study process on the basis of maintenance of reliability criterion instead of now spread in-depth study of all software development is derived from this approach. Such approach is built around basic knowledge of the software life cycle without detailed and in-depth study of the software every life cycle. It is suspected that the business IT specialist mastering such approach will govern successfully the processes of high-quality software designing and developing.Capacity of Specs for software development is analyzed. It is proposed to include a description of quality parameters, clear for the end user, in the Specs to ensure the software reliability. Description of the main reliability provision requirements is given herein.
A formalism to model higher-order function

Recent years have seen a significant renewed interest into functional programming. This approach focuses on a more declarative style of programming, as opposed to the imperative view, which focuses on describing computation steps. Therefore, it sits at a higher abstraction level, particularly useful to describe complex modular applications, such as mobile and web user interfaces. Unfortunately, existing formalisms, tools and techniques to model computer systems are ill-suited to describe highly-functional applications.
Digital Systems for eCTD Creation on the Pharmaceutical Market of the Eurasian Economic Union

Pharmaceutical market integration is highly dependent on digital technologies in general and the Internet in particular. The work aims are to study the available software for creating Electronic common technical documents and the possibility of its application on the Eurasian Economic Union market. To obtain information, the survey was performed based on employees of pharmaceutical companies, which were interviewed to identify the software they are using or plan to use. Based on the obtained results, a list of preferred software was compiled. It contains 9 software products. As part of the second phase of the study, a survey of developers of designated software solutions was conducted. Results showed that for pharmaceutical companies operating in the Eurasian Economic Union region, the issue of software readiness for working with the requirements of domestic regulators is of particular importance. Most foreign software products can be localized only after significant modifications. Domestic software solutions are just beginning to appear and in some cases are highly specialized. For example, programs for planning and meeting regulatory deadlines in the market are represented by single products.
Small Components Parsing VIA Multi-Feature Fusion Network

Part parsing is a fundamental task towards fine image understanding in the multimedia and visual field. At present, the researchers working on part parsing focus on objects with large components, such as human, car. This paper centers on segmenting objects with small components. We call it small components parsing. In this paper, we propose a novel strategy for small components parsing, fusing multi-feature to utilize context information. We introduce Separable Spatial Pyramid module to embed spatial context information by fusing different scale spatial features. In decoding stage, attention-based feature fusion unit is drawn to utilize semantic context information in order to highlight details. Specifically, we design the Residual Upsampling manner to recover more details, considering spatial and channel characteristics. Experiments on RHD-PARSING and CamVid datasets demonstrate our method has achieved decent performance for small components parsing, taking hand parsing as an example, and has reached competitive results in scene parsing.
ELite

Vertex-centric block synchronous processing systems, exemplified by Pregel and Giraph, have received extensive attention for graph processing. These systems allow programmers to think only about operations that take place at one vertex and provide the underlying computation framework that involves multiple iterations (supersteps) with communication between neighboring vertices between supersteps. As graphs grow in size to billions of vertices and trillions of edges, processing them in this model face challenges: (1) The poor latency of supersteps dominated by the tasks performed on high degree vertices or densely connected components; and (2) The overwhelming network communication among vertices that can be proved of high redundancy. For many applications, approximate results are acceptable, and if these can be computed rapidly, they may be preferable. Many of the existing approximate solutions suffer from algorithm-specific designs that are not generic or lacking theoretical guarantees on the results' quality. In this paper we tackle this problem using a generic approach that can be incorporated into the graph processing platform. The approach we advocate involves communicating vertex states to a subset of the neighbors at each superstep; this is called selective edge lookup. We show how this approach can be incorporated into two primitive graph operators: BFS and DFS, which can be the basis of many graph analysis workloads. Extensive experiments over real-world and synthetic graphs validate the effectiveness and efficiency of the selective edge lookup approach.
Concepts in Topics. Using Word Embeddings to Leverage the Outcomes of Topic Modeling for the Exploration of Digitized Archival Collections

Within the field of Digital Humanities, unsupervised machine learning techniques such as topic modeling have gained a lot of attention over the last years to explore vast volumes of non-structured textual data. Even if this technique is useful to capture recurring themes across document sets which have no metadata, the interpretation of topics has been consistently highlighted in the literature as problematic. This paper proposes a novel method based on Word Embeddings to facilitate the interpretation of terms which constituted a topic, allowing to discern different concepts automatically within a topic. In order to demonstrate this method, the paper uses the “Cabinet Papers” held and digitised by the The National Archives (TNA) of the United Kingdom (UK). After a discussion of our results, based on coherence measures, we provide details of how we can linguistically interpret these results.
A Case Study on PV System Performance and LCOE of 15.6 kW Hybrid Solar PV System Installed at CST

This paper presents long term performance analysis of 15.6 kW hybrid solar photovoltaic system installed at College of Science and Technology, Rinchending, Bhutan. Data for one year from Photovoltaic hybrid system is collected and analysed. Losses due to shading are also analyzed and found that shading affects only in winter. Energy and economic performances of the system were also calculated using relevant empirical formulae. From the result, the estimated cost of generation is US$ 0.13/kWh or Nu.9/kWh. To install PV system is not financially viable at current electricity tariff in Bhutan, however due to its clean energy and environmental advantage, solar energy harvest is always preferable despite the high cost factor comparing to cheap hydropower in Bhutan.
Development of an Algorithm for Searching the Optimal Trajectory of the Object in the Conditions of Given Restrictions

The article discusses the development of a mathematical model of a mobile robot and a creation of an algorithm for searching the optimal trajectory of a mobile robot in the presence of obstacles in its path. The document describes the kinematic model of the robot and given trajectory on which experiments will be done. The article includes a block diagram of the developed algorithm and experimental results of its modeling.
Anisotropic Median Bilateral Filtering

In this study, a new image filter—Anisotropic Median Bilateral filter (AM-Bilateral) is proposed for image noise reduction. Unlike the Bilateral filter, AM-Bilateral filter is an iterative non-linear filter and decreases image noise continuously in every iteration. Performance evaluation of AM-Bilateral filter is done and compared with Bilateral filter, Median filter and Arithmetic Mean filter using various images with Gaussian noise. The simulation results have shown that AM-Bilateral filter outperforms other filters with higher Peak Signal to Noise Ratio (PSNR) and Structural Similarity (SSIM) on average.
Integrated Path Planning - Collision Avoidance System for UAVs Operating In Obstacle Rich Environment

The problem of finding a collision free path for multiple Unmanned Aerial Vehicles, in an obstacle rich environment is addressed in this paper. A two step procedure for generating a collision free path is proposed. Such a path satisfying a certain optimal criteria is found within a small time interval using a modified hybrid Particle Swarm Optimization (PSO) and Artificial Potential Field (APF) methods. Further a worst case scenario is generated in which the number of obstacles in the environment is very high and it is found that as the comparative time required to compute the collision free path is less, the collision becomes unavoidable. Next, an integrated collision avoidance system is included, which then re-defines the colliding way-points in such a manner that we get a collision free path. Simulation results show that the two step procedure proposed in this paper is capable of generating a collision free path in high density obstacle environment.
Rotor Fault Detection under Fast-varying Dynamic Load based on Adaptive Morlet Wavelet Transform

The increasing progress of Electric Vehicles (EVs) is generating considerable interest in terms of Fault Detection and Diagnosis (FDD) methods of electrical machines and drive systems. The FDD techniques are well established for steady state modes, however the continuous intermittent operation of EVs demands the development of new fault recognition approaches which are able to cope with the effects of large transient dynamics. In this paper an adaptive Morlet Wavelet-based method is proposed which is capable of on-line fault detection of induction motors under fast-varying transient regime via Motor Current Signature Analysis. The fundamental frequency of the phase current is removed by using the Hilbert transform. After, the Adaptive Morlet Wavelet Transform is performed in a sliding window. In each window the central frequency of the Morlet Wavelet is adaptively fitted to the estimated error frequency of the phase current determined by using rotor speed measurement data. The State-of-Health of the motor is evaluated by the Wavelet index composed from the adaptively filtered residual current and the original signal's energy. Simulation investigations are performed with the motor operating load conditions prescribed by the New European Driving Cycle (NEDC). The results validate the efficiency and applicability of the proposed method in diagnosis of rotor bar faults.
Decoupling-Gan for Camera Model Identification of JPEG Compressed Images

In recent years, many forensic methods are proposed for camera model identification (CMI). These methods expose the acquisition devices of the images according to the traces left during the imaging process. However, such traces could be easily affected by common image operations, e.g., JPEG compression, which make the camera model identification of post-processed images very difficult. In this paper, we propose a GAN based decoupling network (Decoupling-GAN) to boost the performance of CNN-based model detectors for JPEG compressed images by alleviating the effects of JPEG compression on the camera model identification. Through the adversarial training, we rebuilt the consistency of extracted feature maps between the original images and JPEG compressed ones. Experimental results show that Decoupling-GAN exhibits good robustness performance and outperforms prior arts in terms of detection accuracy under JPEG attacks.
Directed Exploration Via Learnable Probability Distribution For Random Action Selection

We propose a method for optimizing the random action selection of the ε-greedy policy to facilitate more efficient exploration of an environment by a reinforcement learning agent. Our directed ε-greedy policy selects actions with a biased probability where some actions are more likely to be selected than others. The probability distribution used for selecting random actions is the one that tends to lead to actions which increase the agent's uncertainty about its environment. The agent's uncertainty is measured by the error in self-supervised prediction of future environment states at the pixel level, given the previous states and the probabilities of next actions. By propagating the reverse gradient from the future state predictor model to a model generating probability distributions from random noise we create an end-to-end trainable model which learns to generate such action probability distributions for ε-greedy, so as to facilitate directed exploration of the environment. We evaluate our method in two environments: Minecraft and Super Mario Bros. The directed ε-greedy policy achieves an efficient curiosity-driven exploration without the use of any intrinsic reward function, outperforming vanilla ε-greedy exploration, softmax exploration and exploration using intrinsic rewards.
An Industrial Environmental Security Monitoring System in Mobile Device Based on Soft PLC

Industrial environmental security, as one of the most fundamental and challenging problems in Soft PLC control, has received great attention in recent years. Most Soft PLC software has its own operating system, which is not easy to control for managers. This paper proposes a new industrial environmental security monitoring system based on android and discusses the whole architecture and data transition between software and hardware. At the same time, this system adopts the SVM algorithm for warning prediction to get high-accuracy. In android application, users can monitor system status anywhere. In addition, the architecture in this system is transparent for the users and devices, which means the model can be widely used in various industrial control situation.
Opening the algorithm’s black box and understand its ouputs

In this article, we will define the principles of loyalty and watchfulness in algorithm’s usage. We will then explore some of the interpretability techniques, which let us explain the decisions of an algorithm and share them with transparency. We will focus on ways to express indecision in order to increase the trust of the users in those systems. The second part is dedicated to a collection of statistical biases, which can be introduced both in the conception and the usage of those algorithmic processes. We will define a methodology to control the possible outputs (decisions) of an algorithm and keep them from conflicting with the interests of the algorithm designer and users.
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