Reviewerly/exHarmony huggingface dataset:
CycleDRUMS: automatic drum arrangement for bass lines using CycleGAN

Abstract The two main research threads in computer-based music generation are the construction of autonomous music-making systems and the design of computer-based environments to assist musicians . In the symbolic domain, the key problem of automatically arranging a piece of music was extensively studied, while relatively fewer systems tackled this challenge in the audio domain. In this contribution, we propose CycleDRUMS, a novel method for generating drums given a bass line. After converting the waveform of the bass into a mel-spectrogram, we can automatically generate original drums that follow the beat, sound credible, and be directly mixed with the input bass. We formulated this task as an unpaired image-to-image translation problem, and we addressed it with CycleGAN, a well-established unsupervised style transfer framework designed initially for treating images. The choice to deploy raw audio and mel-spectrograms enabled us to represent better how humans perceive music and to draw sounds for new arrangements from the vast collection of music recordings accumulated in the last century. In the absence of an objective way of evaluating the output of both generative adversarial networks and generative music systems, we further defined a possible metric for the proposed task, partially based on human (and expert) judgment. Finally, as a comparison, we replicated our results with Pix2Pix, a paired image-to-image translation network, and we showed that our approach outperforms it.
Extraction Technology of Metal and Solid Fuel from Abandoned Coated Wires and Its Application to Engineer Ethics Education

The importance of education on engineer ethics is increasing in higher education for engineer against the backdrop of human technical incidents that frequently occur in Japan and overseas. We have taken up the recycling problem of abandoned coated wires as a subject of engineering ethics education. Since there is no suitable recycling technology for abandoned coated wires, it is disposed of in landfill and exported overseas. We introduced new recycling technology for abandoned coated wires and verified the effectiveness of applying recycling problem of abandoned coated wires as a subject for engineer ethics education in the institute of technology. It was confirmed from the questionnaire results that this subject was an interesting subject regardless of the specialized field. However it was a subject that was not easy for student to consider from the viewpoints of risk management, compliance, and accountability.
Research on the Application of Block-chain in Internet of Vehicles Insurance

On the basis of the connotation and characteristics of block-chain, combined with the reality and opportunities of Internet of vehicles insurance, this paper explores the application of block-chain technology in the scientific and reasonable pricing, accurate service, prevention of fraud insurance, and provides customers with more reasonable value-added service of Internet of vehicles insurance, so as to accelerate the development of Internet of vehicles insurance.
Assessment of Osteogenic Sarcoma with Histology Images Using Deep Learning

As the life expectancy rate is decreasing globally, it diverts the concern of the human race toward health issues. Cancer is a common disease; the possibility of it being osteogenic sarcoma (osteosarcoma) is rare. Even after advancements in medical science and technology, it is hard to detect it at an early stage. It is the necessity of technology to develop a supportive working system with precise accuracy to identify this type of cancer and serve humanity. The authors thus present the development and execution of a computer-aided diagnosis system based on image processing, machine learning, and deep learning techniques. The dataset used comprises hematoxylin and eosin (H&E) stained histology images obtained through biopsy at different stages of cancer. Features are extracted after performing image segmentation. A convolutional neural network (CNN) is designed/customized for classifying cancer among patients into four categories after successful implementation, viz., viable tumor, non-viable tumor, non-tumor, and viable/non-viable tumor with higher accuracy. Using features proposed by scientists, the accuracy achieved by authors is 91.20%. After further improvements in CNN architecture by authors, the accuracy rate achieved is 93.39%.
플립러닝과 질의응답 기반 중국어문법작문 수업 사례 고찰

This paper first introduces the case of Chinese grammar writing classes from 2014 to 2018. To address the problems raised in the class case, the preceding study is reviewed for Flipped Learning, motivation, and Question-Answer Teaching Method. Finally, classes based on Flipped Learning and Question-Answer Teaching Method are designed and applied to classes. The effects are analyzed through a lecture evaluation and reflection log. Classes for Chinese grammar writing in 2019 can be divided into pre-class, in-class, and after-class. Pre-learning through online lectures and practice questions before class, Q&A during class, and evaluation after class. In particular, it was effective to create motivation for learning and to resolve questions through questions-answer teaching method in class. In particular, it was possible to improve learning efficiency by repeatedly learning the same contents through pre-learning, classe, times evaluations.
Image Registration with a Comparative Feature Matching Approach

Image registration is the technique of aligning multiple images that are captured from diverse sources, dissimilar viewpoints, or different times. In general, the image registration algorithms construct a complete image by mapping the source images on the target image by rotation or translation. This mapping is executed by finding the relative transformation. There are several steps to obtain the desired goal. One of the most important steps is feature matching, as based on the obtained result of matched features, the relative transformation is found. In this paper, a comparison among multiple feature matching algorithms has been presented to provide a better understanding of the image registration technique. Additionally, the outcomes after applying those algorithms onto the images have also been presented to show which of them perform better in given circumstances. This can be useful in various fields of computer vision such as remote sensing, automatic target recognition, and medical imaging.
Multivariate multifractal formalism for simultaneous pointwise (Tuipi)i regularities

Recently, a multivariate multifractal analysis for pointwise regularities based on hierarchical multiresolution quantities was developed. General bounds between the Hausdorff dimension of the intersection of single fractal sets and that of the original sets were derived. Equalities were checked for some synthetic signals that include multiplicative cascades. In this paper, we focus on the setting supplied by simultaneous pointwise (Tuipi)i=1,…,L regularities. The Tup regularity for 1≤p<∞ was first introduced in order to better study elliptic partial differential equations where the natural function space setting is Lp or a Sobolev space which includes unbounded functions. We will prove that both corresponding multivariate multifractal formalism and equalities above hold Baire generically in a given product of Besov spaces ∏i=1,…,LBtisi,ri(Rd), si,ti,ri>0,1≤pi≤∞ such that si−dti>−dpi. We therefore extend previous results where only cases (pi=∞ and si−dti>0 for all i) and (pi=∞, si=dti and ri≤ 1 for all i) for simultaneous pointwise Hölder regularities have been proved.
Combining I-vector and ResNet by Knowledge Distillation for Text-Independent Speaker Verification

For years, i-vector + PLDA model has dominated the text-independent Speaker Verification task. Until recently, Deep Neural Networks and metric-learning method becomes popular. In this paper, we combine these two methods by Knowledge Distillation. First, we propose our residual neural network based on ResNet34 which is trained with AM-Softmax loss. Then MSE loss between ResNet embedding and i-vector is used to do distillation. Experiments on VoxCeleb1 dataset shows that proposed ResNet can outperform widely used i-vector and x-vector method. With only MSE loss, ResNet has better performance than i-vector indicating its good generalization ability. After combining these two losses, the results can be further improved and show that distilling knowledge from i-vector can improve performance of the model with PLDA backend.
Wednesday marked the warmest day of 2021 with temps in the 60s

What fantastic way to celebrate the last day of March!   We high 61 at SeaTac making Wednesday the warmest day of 2021 so far!  Areas farther south saw temperatures in the upper 60s to 70!  Don't get used to it though, our Easter weekend cools off a bit and brings back the chance of some showers too.
Understanding Causes and Remedies of Low Profitability of Cloud Technology Managed Service Delivery Projects in Industry 4.0 Era

To measure is to know. Adequate quantitative measurements are available to know the status of profitability of the projects. Based on these quantitative measurements, in case it is found that a project has recorded less than expected profitability, then it becomes necessary to deep dive and carry out a thorough root cause analysis with the help of in-depth qualitative study. Accordingly the present study is focused on studying and providing understanding of various qualitative aspects associated with profitability of Cloud Technology managed service delivery projects operating in Industry 4.0 scenerio. This study focus at addressing the scope of improvement in an optimum manner and preventing recurrence of the problem with the aim of achieving &amp; maintaining targeted profitability at the project management level. Successful achievement of these objectives depends on the extent of strategic implementation of findings of this study by the concerned project leadership teams.
Positioning sci-tech library in local environment

The author demonstrates the dependence of sci-tech library’s functions and services from its role in the structure of its mother organization. Sci-tech libraries act as independent divisions or a unit within the larger department. In the latter case its activities are less visible therefore it has to demonstrate its efficiency and input to the division or organization. The experience of the Sci-tech Library of Krylov State Research Center (KSRC) is discussed. The library is a structural unit of the Information and Publishing Center. The partnership between the publishing unit and the library determines the efficiency of collaboration within the division which is evidenced by the contribution of the Sci-tech Library to the publishing process; thus, the Library provides bibliographies to the scholarly papers to be published. The author demonstrates that the professional knowledge and expertise of librarians make the library an equal partner, and that the traditional library function is positioned as a unique service. The author also discusses the problems of information culture of professionals, in particular their carelessness toward bibliographic references. The examples are given of frequent problems researcher authors face when providing references. The prospective vectors of the Sci-tech Library’s education activities are analyzed.
Distribution Mapping of Rice, Corn, and Soybean Production Based on Geographic Information Systems in Pandeglang Regency

Abstract This study aimed to present the data on the mapping of the distribution of rice, corn and soybean production, based on the geographic information system. The method used in this research was the survey method. The research location was in Pandeglang Regency with the consideration that Pandeglang Regency is one of the areas in Banten Province with variety of potential natural resources, especially the abundant and valuable agricultural crop production.. Data were collected in July 2020-September 2020 and analyzed descriptively. The results showed that the average production was very high for rice (39713.61-62309.88); Corn (240.50-988.47); and soybeans (2524.50-5004.45) while the average production was very low for rice (6967.11-13783.74); Corn (13095.92-32175.48); and Soybean (00.00-166.30) which means that the production yield was very low in several sub-districts in Pandeglang Regency which need attention in this case related to land suitability evaluation.
Copy-Move Image Forgery Detection Using Spatio-Structured SIFT Algorithm

Copy-move image forgery detection (CMIFD) via SIFT algorithm is one of the emerging and effective key-point based strategies. This algorithm is robust against large-scale geometric transformations and various attacks during the forgery process. CMIFD via SIFT algorithm accurately localizes the tampered regions rich in structural content at a cost of key-point matching problem and provides inferior detection accuracy with higher rate of false alarm in localizing relatively smoothed and little structured forgery regions. Natural images are highly structured. Pixels in these images preserve sufficient spatial and structural correlation among each other which should be preserved during the feature matching process. However, SIFT algorithm has no provision to preserve structural correlation among key-points. Consequently, detects insufficient number of key-points for images rich in structural content. To alleviate these bottlenecks, we have proposed an efficient CMIFD scheme by (i) integrating spatial and structural information additionally in the SIFT feature descriptor and (ii) utilized an adaptive strategy in selecting optimal number of matched key-points from a pool of candidate key-points. All these modifications enable to minimize the key-point matching problem and localize both structured and smoothed tampered regions accurately. Outperforming behavior of the proposed method is validated via several experimental result analyses.
Space Planning of Mobile Robot Guided by Path Edge

The visual navigation mobile robot is greatly influenced by environmental parameters, which leads to poor optimization control ability of the robot. In order to improve the stability of the spatial planning of the mobile robot, a guidance algorithm for the spatial planning of the visual navigation mobile robot based on path edge guidance is proposed. The parameter distribution model of spatial distribution of moving path of visual navigation mobile robot is constructed, and the constraint parameters of spatial path planning adjustment of visual navigation mobile robot are analyzed. The steady-state control problem of spatial path planning adjustment of visual navigation mobile robot is transformed into the optimization problem of path edge guidance parameters, which effectively realizes the transformation of moving path characteristics and error compensation correction of path guidance of visual navigation mobile robot. Combined with the motion planning model, the robot spatial behavior path is driven, and the spatial path planning and behavior characteristics steady-state adaptive control of the visual navigation mobile robot are completed. The simulation results show that the path space planning control of visual navigation mobile robot has good stability and superior adaptive control performance, which improves the adaptive control and parameter optimization adjustment ability of visual navigation mobile robot.
Nonlinear Ranking Loss on Riemannian Potato Embedding

We propose a rank-based metric learning method by leveraging a concept of the Riemannian Potato for better separating non-linear data. By exploring the geometric properties of Riemannian manifolds, the proposed loss function optimizes the measure of dispersion using the distribution of Riemannian distances between a reference sample and neighbors and builds a ranked list according to the similarities. We show the proposed function can learn a hypersphere for each class, preserving the similarity structure inside it on Riemannian manifold. As a result, compared with Euclidean distance-based metric, our method can further jointly reduce the intra-class distances and enlarge the inter-class distances for learned features, consistently outperforming state-of-the-art methods on three widely used non- linear datasets.
Implications and Future Directions

Finally, Chapter 7 discusses the implications of our work for the operational task of identity assumption, and for the more theoretical concerns around the linguistic individual and language and identity more generally. We conclude the chapter with our thoughts for the directions similar research might take in the future.
Information support of the system for managing technical assets in railway transportation

Aim. JSC RZD is one of the largest and most advanced companies in Russia who actively deploys and uses best practices in asset and risk management. In 2010, the railway industry initiated the project for the management of resources, risks and dependability at lifecycle stages of railway facilities (URRAN) that is currently under way. The aims of this paper are to overview the asset management tasks covered by URRAN; examine the marketed IT tools designed to address such problems; present the progress of the URRAN project in terms of process automation implemented by JSC RZD in light of the international best practice and the specificity of the Company. Methods. The preparation of this paper involved empirical and theoretical research. The authors analysed the URRAN project’s package of guidelines and regulations, public information on the globally available software products enabling asset management, as well as the program documentation of the EKP URRAN automated system. They analysed the functionalities and and engineering solutions used in the development of this automated system. The results of the EKP URRAN deployment and practical application by units and branches of JSC RZD were evaluated. Results. Asset management involves using Enterprise Asset Management Systems (EAMS) specially designed to suit the needs of specific companies or mass-produced “out-of-the-box” systems, e.g. SAP ERP, IBM MAXIMO, ABB AbilityТМ and SimeoTM that are examined in the paper. The EKP URRAN implements a single information space that is a decision support tool for the asset management system as it possesses the required regulatory and procedural resources, hardware and software assets intended for comprehensive management of assets and processes for the purpose of efficient railway service. In the future, the EKP URRAN is to become part of the Digital Platform for Risk and Traffic Safety Management deployed in JSC RZD and will comprise modules that implement dynamic predictive analytics models for the purpose of predicting undesirable events involving infrastructure and rolling stock that may disrupt traffic safety. Conclusions. Further development of the EKP URRAN will soon provide all levels of company management with an efficient tool that allows, in the context of limited resources, making substantiated managerial decisions and rational investment allocation. The EKP URRAN is an asset of JSC RZD designed to be used by the managers and specialists of various JSC RZD units. It can be implemented as a standalone IT product for the purpose of developing and deploying an asset management system in various railway companies.
Comparability of Nizhny Novgorod (Makaryev) Fair Reports of 1813-1917

The article considers comparability of Nizhny Novgorod (Makaryev) Fair reports of 1813-1917. Reports for the mentioned period are not fully available; moreover, formulary of sources changed. Scientific originality of the study lies in the fact that reports of Nizhny Novgorod Fair Administration and Nizhny Novgorod Stock Exchange Committee are for the first time subjected to source study analysis. The research findings are as follows: the author proves that the reports were prepared according to the established procedure, which makes it possible to compare data from different years, in spite of formulary changes and new report forms.
Polymetric analysis and cybernetics

Basic concepts of Polymetric Analysis as universal system of formalization the knowledge are discussed. Correlation between Polymetrric Analysis and cybernetics is researched. It was shown that cybernetics as synthetical science is similar to Polymetric Analysis. But Polymetric Analysis may be represented as functional expansion of computer processor and therefore may be applied for the resolution the problems of artificial intelligence, pattern recognition and other chapters of modern cybernetics. This problem is analyzed with point of S. Beer centurial problem in cybernetics (problem of complexity of information) and has system nature
Recent Trends in Emotion Analysis: A Big Data Analysis Perspective

Human action recognition has recently started to find its way into applications in different applications. Accordingly, human action recognition methods are becoming increasingly important in our daily life. They are used for different purposes such as automation, security, surveillance, health, smart home systems, and customer behaviour prediction, among others. Though have more systems with methods provides a rich pool of choices, it is important to well understand the performance of these systems and their success rates in recognizing the right activities in order to decide on the most appropriate system for the current application domain. This survey tackles this issue by analyzing and commenting on the available human action recognition systems and methods.
NEW TECHNOLOGIES IN HIGHER EDUCATION IN THE AGE OF THE PANDEMIC: A COMPARATIVE STUDY BETWEEN ECUADOR AND SPAIN

J. Navarro Espinosa1, G. Pedrós-Perez2, M.P. Martinez-Jimenez 2, P. Aparicio-Martinez 2 1Universidad Ecotec (ECUADOR) 2Universidad de Córdoba (SPAIN)
Remittances, the Diffusion of Information and Industrialisation in Africa

This study examines the role of information and communication technology (ICT) on remittances for industrialisation in a panel of 49 African countries for the period 1980-2014. The empirical evidence is based on three simultaneity-robust estimation techniques, namely: (i) Instrumental Fixed Effects (FE) in order to control for the unobserved heterogeneity; (ii) Generalised Method of Moments (GMM) to account for persistence in industrialisation; and (iii) Instrumental Quantile Regressions (QR) to control for initial levels of industrialisation. Our best estimators are from FE and QR estimations because the GMM regression outputs largely fail post-estimation diagnostic tests. The following findings are established: (i) There are positive marginal effects from the interaction between remittances and ICT in the FE regressions whereas there are negative marginal impacts from the interaction between remittances and ICT; (ii) Interactions between remittances and mobile phone penetration are positive in the bottom and 90th quantiles whereas the interaction between internet penetration and remittances is positive in the bottom and top quantiles of the industrialisation distribution. Overall, the role of ICT in remittances for industrialisation is much more apparent when existing levels of industrialisation are accounted for. The findings contribute to the debates on the importance of external flows and information infrastructure in economic growth as well as the relevance of remittances in driving economic development in environments where institutions are weak. The value of the study to scholars and policy makers also builds on the fact that the potential for ICT and remittances in Africa can be leveraged to address development challenges on the continent such as the low level of industrialisation.