Reviewerly/exHarmony huggingface dataset:
360-deg shape measurement system based on three-dimensional orientation target

We present a system for 360-deg shape measurement based on three-dimensional (3-D) orientation target. The measurement system mainly includes a CCD camera, digital light projector, 3-D orientation target, and the measured object. The global coordinates for all chessboard corners of the target are calculated based on close-range photogrammetry, for which the relative orientation between camera stations is discussed in detail. According to the homography matrix between the checkerboard and its image plane, the position and orientation of the measuring camera relative to the target are determined. A dot-matrix structured light is designed and projected onto the measured object surface. In each image of the structured light deformed by the object shape, the pixel coordinates of the dot-centers are accurately calculated by the ellipse-fitting algorithm, and then they are all sorted in the same order by the beads-stringing matching method. In the experiment, the designated front, rear, left, and right surfaces of a reference object are measured, and their separate point clouds are automatically stitched together by the 3-D orientation target. Compared with coordinate measurement machine data, the accuracy of the system is demonstrated; the maximum deviations are +1.257 / − 0.977 mm, and the standard deviation is 0.124 mm.
Automation of ILL and EDD services at the Library for Natural Sciences of the Russian Academy of Sciences

The Library for Natural Sciences of the Russian Academy of Sciences possesses unique collections of the national and foreign science literature. It acts as a federal STI authority in the natural and engineering sciences. Therefore, one of the Library’s key functions is delivering materials (originals and fragment copies) from its collection to other libraries within the ILL system. The RAS Library for Natural Sciences heads the country’s largest centralized library system (CLS) embracing 49 affiliates of research organizations in Moscow region. The CLS collections, including those of the Central Library, make the single distributed collection to provide services to ILL subscribers. The peculiar feature of the Library’s ILL services is that it delivers materials to its subscribers (the CLS libraries) not only from the CLS collections alone but also from other Moscow and Russian major library collections. The authors describe the computerized system designed at the Russian Academy of Sciences Library for Natural Sciences and characterize the used ILL technology. The structure of the information base comprises ‘Clients’ and ‘Orders’ units. Order dispatching and cash settlements with subscribers are provided by the system’s management unit; the retrieval and statistical tasks are also accomplished. The user unit supports order generation based on union e-catalogs. Specific features of order generation based on various Internet-catalogs, i. e. journals, books and periodicals, image catalogs of national and foreign books, are examined.
Evaluation of Synthetic Speech by GMM-Based Continuous Detection of Emotional States

The paper describes a system for automatic evaluation of synthetic speech quality based on continuous detection of emotional states throughout the spoken sentence using a Gaussian mixture model (GMM) classification. The final evaluation decision is made by statistical analysis of the results of emotional class differences between the sentences of original male or female voices and the speech synthesized by various methods with different parameters, approaches to prosody manipulation, etc. The basic experiments confirm the functionality of the developed system producing results comparable with those obtained by the standard listening test method. Additional investigations have shown that a number of mixtures, types of speech features, and a speech database used for creation and training of GMMs have a relatively great influence on continuous emotional style detection and the final quality evaluation of the tested synthetic speech.
Distance Learning in the Field of Acmeology of Pedagogical Education

The article is focused on the changes in democratization of pedagogical education contents under free market conditions at the time of increasing information fl ow and on the problems of IT penetration in educational sector. The attention is paid to students’ self-education in terms of acmeology. The practical signifi cance of the results of this study can help in the organization of professional and pedagogical training of students. The prospects for the use of distance learning technologies, new information technologies, including Internet technologies, which allow not only to increase the motivation for learning, but also to prepare students to independently improve their professional level in the fi eld of acmeological support for teacher education, are determined.
Creative Procurement for Your Simulation Program

This chapter is devoted to making it happen and being creative on getting the right “things” at the right time. The focus is on creative ideas for procurement in the realm of simulation. It will begin by reviewing practical ways to know thyself, including ways to determine what your center’s needs are. Next, the chapter will provide ways to identify who the stakeholders are and who the accountable party should be for expenses. This leads to developing a procurement process, which includes selection of purchase strategies, source options, and resources. Reviewing ways to apply this process to a variety of different procurement categories while looking at ways to creatively procure within each of these areas will help situate this process in readers’ minds. The aim is to open the creative juices, boosting procurement successes by giving readers ideas of resources and processes to help during procurement efforts.
Learnable Masks for Pose-Guided View Synthesis

Pose-guided human view synthesis uses a target pose to generate the appearance of a new view of a person. The input view and the target pose can be processed separately with UNet architectures that combine the results in a late fusion stage. UNet architectures link their encoder and decoder with skip connections that preserve the location of spatial features by injecting input information in the decoding process. However, direct skip connections may transfer irrelevant information to the decoder. We overcome this limitation with learnable masks for skip connections that encourage the decoder to use only relevant information from the encoder. We show that adding the proposed mask to UNet architectures improves the performance of view synthesis with only a slight increase in inference time.
TwohandsMusic: Multitask Learning-Based Egocentric Piano-Playing Gesture Recognition System for Two Hands

We present TwohandsMusic, a new real-time system for recognizing egocentric piano-playing gestures on planar objects by using a depth camera. Existing methods have usually recognized single tap gestures of one hand using a sensor installed in front of or under the user's hand. In contrast, we consider recognizing multi-tap gestures of both hands using a depth camera installed near the user's head. Our approach consists of two steps: hand detection and gesture recognition. At the hand detection step, we detect both hands using a 2DCNN (Convolutional Neural Network), called SegNet, and generate cropped hand images, which is to be used in the next step. In the gesture recognition step, we estimate 3D hand poses and classify multi-tap gestures simultaneously using a 3DCNN with multitask learning, called MusicNet. For training and validating of our system, we collect 85K dataset including tapping chords and show improved results over state-of-the-art methods.
Creating a working project of a web-application for training in programming at the initial stage of professional training

The article gives the analysis of the main provisions of the training manual "Software for computer networking and web-servers" of the authors G.A. Lisiev, P.Yu. Romanov, Yu.I. Askerko, which is published in the series "Secondary vocational education". Important aspects of the technology of project training are noted. The article presents the developed by the authors educational and me-thodical material for the consistent implementation of the web-project in teaching programming in high-level languages of students of secondary vocational education.
Virtual Resistance of “Çiftlik (Farm) Bank Scapegoats” and Discursive Atonement of “Being Scammed”

Çiftlik Bank (Farm Bank) is an investment system based on fraud that may be described to be a Ponzi scheme as a commercial term. It reached thousands of investors in Turkey via the service it provided over the internet and attracted attention by leaving a high profit margin for its investors for some time and using some abstract concepts that are held sacred by the majority. Çiftlik Bank created an earning-oriented exclusivity for its investors, but also created suitable scapegoats for the community, along with fraud. This chapter focuses on the rhetorical conflict between the scapegoat virtual group organized with the name “Çiftlik Bank Victims” on Facebook, and the society, as well as the activities of regaining the contingent/select identity.
The Effect of using Wax and Wood as a Watermark Material on the Pottery

Abstract Counterfeiting products in the marketing process often occurs, not only for imported goods, but also for local goods produced by small craftsmen. Watermark will be one way to show the authenticity of a product. Watermark will be one way to show the authenticity of a product. The method used to analyze watermarks is non-destructive testing. This non-destructive test utilizes digital radiography with x-ray exposure. The images obtained from the radiography are then analyzed using ImageJ. The method of analysis carried out is the method of visual analysis and physical analysis methods. The visual method in this study only identified the obtained watermark image. The identification of x-ray distribution in dry and burnt pottery was used as a method of physical analysis. The value of x-ray intensity on exposed pottery is then compared. The watermark material used is wax and wood. The Paraffin content in the candle will turn into gas if it is burned. The carbon content in wood can cause wood to gray to ash if burning is more than ± 6000C. In the process of making wet pottery, wax materials for craftsmen have difficulty printing, this can cause changes in the quality of the earthenware which is not good enough. On earthenware wood materials can be formed properly without changing quality. The watermark produced on wood burning material is not very clear. Material that can be formed in the printing process, does not change during drying, and does not change the quality of wood in the combustion process is wood material material.
Few-Shot Associative Domain Adaptation for Surface Normal Estimation

This paper considers a surface-normal learning algorithm referred to as few-shot kernel associative domain adaptation (FS-KADA) that reduces the domain shift between abundant synthetic source normals and a few real target normals. The FS-KADA takes an unpaired source and target samples as input and captures invariant representations. However, models trained on synthetically rendered normals do not perform well when accurately predicting real environmental normals due to the domain shift. To address this issue, a contextual weighting is considered for learning FS-KADA on the neighborhood of target ground truth, with kernel association in latent spaces and smoothing at predictions. FS-KADA is evaluated on both a real outdoor target dataset (SNOW) and real indoor datasets (NYUv2) using a synthetic indoor dataset (MLT). The state-of-the-art performance was observed on the SNOW dataset. The performance of FS-KADA using a single ground truth of a randomly selected pixel in each image of the NYUv2 is compared with others using the full ground truth.
Chaotic Autonomous Developmental Neural Network

The autonomous developmental neural network is proposed based on the investigation on the visual pathways. It integrates both object location and object type from images of learned objects in natural complex backgrounds and is used to recognize and identify the scenes. Chaotic motion can distribute homogeneously within a certain range since it has possessed some uncertainty, ergodicity and stochasticity. Hence, the characteristic of chaotic ergodicity is used to solve the global optimal solution of complex nonlinear problems. In this paper, we propose a chaotic autonomous developmental neural network, in which chaotic sequences are utilized to enhance weighs of neural network. Through simulation and analysis, the results show that the chaotic autonomous developmental neural network can enhance the performance of the basic autonomous developmental neural network.
KPTransfer: Improved Performance and Faster Convergence from Keypoint Subset-Wise Domain Transfer in Human Pose Estimation

In this paper, we present a novel approach called KPTransfer for improving modeling performance for keypoint detection deep neural networks via domain transfer between different keypoint subsets. This approach is motivated by the notion that rich contextual knowledge can be transferred between different keypoint subsets representing separate domains. In particular, the proposed method takes into account various keypoint subsets/domains by sequentially adding and removing keypoints. Contextual knowledge is transferred between two separate domains via domain transfer. Experiments to demonstrate the efficacy of the proposed KPTransfer approach were performed for the task of human pose estimation on the MPII dataset, with comparisons against random initialization and frozen weight extraction configurations. Experimental results demonstrate the efficacy of performing domain transfer between two different joint subsets resulting in a PCKh improvement of up to 1.1 over random initialization on joints such as wrists and knee in certain joint splits with an overall PCKh improvement of 0.5. Domain transfer from a different set of joints not only results in improved accuracy but also results in faster convergence because of mutual co-adaptations of weights resulting from the contextual knowledge of the pose from a different set of joints.
Exploring Pain Insensitivity Inducing Gene ZFHX2 by using Deep Convolutional Neural Network

Chronic pain is one of the major health issues which affects wellbeing of casualties ranging from orthopedic damages to unbearable cancer pain. Though analgesics aids in reducing pain sensitization, it has its own defect of causing side effects such as drug resistance and habit formation. Evolutionary research has evidenced that by mutating "ZFHX2" gene, one can achieve pain insensitivity. This work emphases on 1) Designing an early mutation detection tool to identify the presence of pain inducing gene ZFHX2 among various patients from pathological biopsy images using deep convolution neural network. 2) Pharmacogenomic analysis comprising of genomics, epigenomics, metagenomics, environmental genomics has been performed in ZFHX2 gene to identify genetic signature, one of the reasons behind causing chronic pain. 3) Block chain algorithm has been used to secure valuable patient clinical data obtained from pharmacogenomic and other analysis to maintain records in order to avoid clinical theft.
On Simulation of Wave Processes in Electromechanical Systems by a Problem with Two- Point Time Conditions

Wave processes in an infinite membrane under the action of external force at given conditions of the process at two moments of time are modeled by a two-point problem for the D'Alembert equation. A class of quasi-polynomials which is a class of uniqueness solvability of problem is established. Due to the modification of the mathematical model of oscillation, it is possible to propose a differential-symbol method for construction of exact solutions of the problem. The examples of researching the wave processes in a membrane with two fixed given states are proposed. The indicated results can be effectively used in the study of the mathematical models of MEMS oscillations.
Role of elective courses in training of mathematics in profile classes

Article is devoted to the problem of effi ciency of the use of elective courses on mathematics in classes with profi le preparation and their place in training of school students. For this purpose, the tasks and principles of introduction of elective courses to the program of training are considered. For consideration of function of elective courses at separate steps of profi le education are separately submitted. Their teaching is based on independent activity of pupils, and the accent to be put on a form of the organization of elective courses. Therefore, new demands to training of the teacher and the organization of his lessons are made. In the article it is off ered to consider one of new forms of creation of independent activity of pupils as the cure of a problem of profile training, — lessons of the “turned” type. The use of this form will become eff ective for development of the program of elective courses.
Research on Shared Resource Contention of Cloud Data Center

In the process of cloud computing development and popularization, virtualization provides a viable solution to solve the problem of energy consumption and resource utilization. Meanwhile, Virtualization leads to multiple virtual machines competing for shared resources. This paper summarizes the shared resources contention caused by multiple co-tenant virtual machines in cloud data centers. We expound and analyze the main aspects of resource contention, and describe the key technologies to solve this problem. We focus on two main resources: memory and cache. At the end of this paper, the development trend of virtualization is also discussed.
Evaluating PDA using financial analysis for streaming videos: a case study at a US academic library

Purpose The purpose of this study is to evaluate the pre and post success of patron-driven acquisition (PDA) streaming video projects using financial analysis, thus comparing PDA as a collection building tool against other legacy purchasing practices. Design/methodology/approach This is primarily a quantitative study based on deductive data derived; however, it does include qualitative findings. Hence, it is a mixed study. Findings The study approaches this topic from the viewpoint that ongoing evaluations of PDA projects, based on savings and benefits derived, can be practically conducted and are useful for CD decision-making by purchasing agents in academic libraries. Research limitations/implications Caution should be used when generalizing this study due to its specificity of its library’s collection development (CD) needs and methodology. The study is not intended to be original research, but it builds upon other case studies in this area. Practical implications In addition to improving CD strategies, libraries could use this study to develop a financial valuation methodology, which can help guide purchasing practices. Social implications This study has implications to all library stakeholders. Originality/value Few studies have compared and analyzed streaming video PDA programs using financial analysis in a practical manner to aid library acquisitions.
Validating Measurement Data in Manufacturing Processes

Statistical process control (SPC) is an industry-standard methodology for monitoring and controlling quality during manufacturing processes. In this method, one measures quality data of small samples in preset time intervals or after a specific amount of produced items. Based on this data and some mathematical statistics, one can extrapolate to the entirety and, if necessary, adjust process parameters to ensure perfect quality products. However, this method is conditioned on the fact that the measured data is correct and neither the measuring device nor the inspector manipulated the incoming data. We study the problem of detecting manipulations in measurement data of manufacturing processes, which we refer to as validation of measurement data. To this end, we combine Decision Stump Forests with a novel variation of the Smith-Waterman algorithm to detect characteristics from a predefined list of typical manipulations and test this for feasibility on real data from manufacturers in Germany.
Sufficient Conditions for Composite Frames

In many fields of science and technology, multiscale (or multiresolution) analysis is a useful tool to study data via efficient representation at increasingly precise resolution. In this paper, we present a result on composite wavelet frames (or composite frames), a relatively recent development in a long line of multiscale techniques including the celebrated Fourier and wavelet analyses. Composite frames generalize many traditional wavelet-based constructions and can be used to provide new effective schemes, including such successful examples as shearlets, that capture directionality in data, images in particular. Our construction is motivated by wavelets with composite dilations, which were introduced in Guo et al. (Appl Comput Harmon Anal 20:202–236, 2006). We focus on frames, a robust system that generalizes orthogonal bases and can include redundant elements, and show that we can construct composite frames for $$L^2(\mathbb {R}^n)$$ using two main components: dilation operators from admissible groups and generating functions which are refinable with respect to these groups. We illustrate this theory with the construction of a composite dilation frame based on a Haar wavelet with quincunx dilation and local mollification.
An Automated Driver’s Context Recognition Approach Using Smartphone Embedded Sensors

Context recognition plays an important role in connecting the space between high-level applications and low-level sensors. To recognize human context, various kinds of sensors have been adopted. Among the variety of exploited sensors, smartphone internal sensors such as accelerometer and gyroscope are widely used due to convenience, non-intrusiveness and low deployment cost. Automatic detection of driver's context is a very crucial factor to determine the driver's behaviors. This paper proposes an approach to recognize driver's context which is a very specific research direction in the domain of human context recognition. The objective of this approach is to automatically detect the contexts of drivers using a smartphone's internal sensors. The proposed algorithm explores the power of a smartphone's built-in accelerometer and gyroscope sensors to automatically recognize the driver's context. Supervised machine learning k-nearest neighbor is employed in the proposed algorithm. Empirical results validated the efficiency of the proposed algorithm.
How Popular or Unpopular Have Your Leaders Been - Popularity Tracking and Trend Analysis of Socio-Political Figures

Online news media can serve as a very useful resource in terms of tracking the popularity and trend analyses of socio-political figures. The closest technology developed so far in this regard is Google Trends which is however based on the number of searches conducted by the users on the person or figure. And this is not necessarily a measure of popularity – the searches conducted could well be a random search. In this work, we define popularity (growing and diminishing) in terms of the sentiment scores received by the individual statements or sentences in the online news text with respect to some named-entity or socio-political figure. Based on the sentiment analysis and the named-entity extraction, we plot time-series line graphs that represent the popularity and trend analysis of the respective named-entities. The plots were verified with the help of individual opinion surveys and the conformance was more than 80% which signals that our proof-of-concept is viable and works. In the future, we will be extending the work to Nepali based on whatever has been achieved for English news media texts. We also will be improving the current individual module’s performances for English.