Reviewerly/exHarmony huggingface dataset:
No-Reference Stereo Image Quality Assessment by Learning Dictionaries and Color Visual Characteristics

Since a large proportion of the information that is received daily is in the form of images, a highly effective no-reference stereo image quality assessment (SIQA) method is desired. This paper proposes an improved method that covers wide quality-aware features, including the structure, color, luminance, phase, and human visual system (HVS). To be specific, since human eyes are highly sensitive to the structure of images, the gradient magnitude (GM) and gradient orientation (GO) are extracted from the left and right views of the stereo image. Considering the influence of color distortions, the images are decomposed into the RGB channels to be processed, and the local gradient of the color image is obtained by adding up the RGB gradient vectors. In addition, according to the study of the two main visual channels, especially the cyclopean and disparity maps, the binocular-related images of position and phase congruency are generated. Correspondingly, two special dictionaries for the gradient and phase are trained to parse the high-dimensional sample sets. The experimental results show that the proposed metric always achieves high consistency with human subjective assessments for both symmetric and asymmetric distortions.
Reconstructing Three-Dimensional Human Poses:&#x0D; A Combined Approach of Iterative Calculation on&#x0D; Skeleton Model and Conformal Geometric Algebra

Reconstructing three-dimensional (3D) human poses is an essential step in human bodyanimation. The purpose of this paper is to fill the gap in virtual reality research by reconstructingpostures in a high-precision human model. This paper presents a new approach for 3D human posereconstruction based on the iterative calculation of a skeleton model and conformal geometric algebra,captured by a monocular camera. By introducing the strip information of clothes and prior data ofdifferent human limbs, the location of joint points on the human body will not be affected by theocclusion problem. We then calculate the 3D coordinates of joint points based on the proposed methodof the iterative calculation of the skeleton model, which can solve the high-cost problem caused by theneed for multiple cameras or a depth camera. Subsequently, we utilize high-performance conformalgeometric algebra (CGA) in relation to rotation transformations in order to improve the adjustmentof the postures of the human limbs. Finally, realistic 3D human poses are reconstructed—specifically,the motion of the human limbs—using a rigid transformation of CGA and a smooth connection ofthe limb parts based on a high-precision model. Compared with the existing methods, the proposedapproach can obtain satisfactory and realistic 3D human pose estimation results using grid models.
On Combining Face Local Appearance and Geometrical Features for Race Classification

In the field of demographic attribute classification, race estimation is perhaps the least studied topic in the literature. CNN-based approaches report the best results to the day, but they are computational expensive for practical applications. We propose a simpler approach by combining local appearance and geometrical features to describe face images, and to exploit the race information from different face parts by means of a component-based methodology. Experimental results obtained in the FERET subset from EGA database, with traditional but effective classifiers like Random Forest and Support Vector Machines, are very close to those achieved with a recent deep learning proposal.
The Geo<i>PT</i> Proficiency Testing Programme as a Scheme for the Certification of Geological Reference Materials

ISO Guide 35:2017 provides, for the first time, an alternative way of characterising certified reference materials using proficiency testing. In this paper, the properties of assigned values derived from the well‐established Geo PT proficiency testing scheme are examined. This scheme, designed for laboratories that undertake the routine analysis of silicate rocks and related materials, routinely has over 100 participants contributing results. Following a detailed assessment of the metrological properties of Geo PT assigned values in relation to Guide 35 recommendations, it is demonstrated that these values may be regarded as certified values, provided a number of criteria are met. These criteria include the following: a demonstration of sufficient homogeneity of the candidate CRM; circulation, when judged to be appropriate, of an established matrix‐matched CRM for co‐analysis in that round; the robust statistical analysis of data sets using Geo PT established criteria; a decision whether assigning a value is justified (including a requirement of a minimum of fifteen valid results); and an expert group to manage the certification and the maintenance of appropriate records. In summary, the Geo PT proficiency testing scheme, subject to the arrangements summarised above, is considered to be competent for the certification of geological reference materials.
Getting virtually personal

We build conversational agents to serve as AI interviewers who engage a user in a one-on-one, text-based conversation. Our live demos showcase two special skills of an AI interviewer: (a) ability to actively listen to a user during an interview-responding to complex and diverse user input empathetically; and (b) the ability to automatically infer the user's Big 5 personality traits from the interview. We provide an overview of the technologies that enable these two abilities and real-world applications of such AI interviewers.
An Adaptive Approach to Quantify Plant Features by Using Association Rule-Based Similarity

In elementary school, the first step to learning about plants is observing plant features.In this study, we developed a plant search system that allows users to do a search even when they do not know the plant name simply by observing plant characteristics.The system consists of a total of 12 plant features, searches for the features according to the input features, and returns the top 10 plants with the best match.Furthermore, we adopted three different calculation methods for feature calculation, including the fuzzy function, association rule-based similarity (ARBS), and a combination of the two.The calculated results of the three aforementioned approaches are analyzed in case of a single feature input error or n features were input incorrectly; then the Top 1 and Top 3 accuracy are explored.According to the results of this study, the accuracy of ARBS is significantly higher than that of the other two calculation methods, thus proving that calculating the similarity through association rules can greatly increase accuracy.If future researchers were to expand to other features, the various features, even those that are hard to quantify, can also be quantified using the ARBS method easily.
University Teacher Professional Development in the Digital World

These are changing times in education systems around the world. With the start of the new millennium, many societies are engaging in serious educational reforms. One of the key elements in most of these reforms is the professional development of teachers. As universities become more autonomous, with open learning environments, university teachers assume greater responsibility for the content, organisation and monitoring of the learning process, as well as for their own personal career-long professional development. Systems of education and training for teachers need to provide them with the necessary opportunities. All this makes the field of teacher professional development a growing and challenging area, and one that has received major attention during the past few years. This is actual for high educational institutions in Russia as they are both eager and required to become a part of European educational system. This is why we should investigate the issue of professional development: what kind of instruments we can use for increasing the effectiveness of university teacher professional development.
Chapter 7. A cognitive pragmatics of the phatic Internet

Phatic interpretations are typically defined as those arising from an intention to create and maintain ties and social bonds, rather than an intention to transfer substantive information. As such, they are not typical instances of communication in which the eventual relevance centers upon the value of explicitly communicated content. Nowadays we are witnessing the so-called phatic Internet, in which the propositional content transferred to other users is increasingly irrelevant but the effects that this content generates (in terms of emotions and feelings of connection, sociability, group membership, friends’ acknowledgment and mutual awareness, etc.) are utterly relevant. This chapter will argue that it is mainly the feelings and emotions that are generated from phatic interactions (as well as phatic implicatures) that demand an extension of the scope of analysis and new terminology. Specifically, the term phatic effects will be proposed and applied to Internet-mediated communication. These effects are devoid of the qualities of intentionality and propositionality but are nevertheless essential to understanding why many users spend hours exchanging (apparently) irrelevant content with one another through the Net.
OptQuant: Distributed training of neural networks with optimized quantization mechanisms

Nowadays, it has been a common practice to speed up the training of deep neural networks by utilizing multiple computational nodes. It is non-trivial to achieve desirable speed-up due to the potentially large communication overhead in distributed training. To reduce the communication cost, several unbiased random quantization mechanisms were proposed, in which the local workers, i.e., computational nodes, quantize their local gradients before communications with other workers. Most previous quantization mechanisms are static, i.e., the gradients are quantized in the same way during the training process. However, for different neural network models, the distributions of gradients might be very different even after normalization. To minimize the quantization loss better, we design the parameterized unbiased quantization mechanisms and dynamically optimize the quantization mechanism during the training process, using the aggregated information of the gradients. We call the distributed deep learning algorithms with our new quantization method (unbiased) OptQuant algorithms. Theoretically, we show that the unbiased OptQuant algorithms converge faster than the static unbiased quantization. In addition, if we trade-off the bias and the variance in the quantization, the algorithm converges faster. Motivated by this theoretical result, we further design the parameterized biased quantization mechanisms and the biased OptQuant algorithms. We evaluate our algorithms for different deep neural networks with benchmark datasets. Experimental results indicate that the OptQuant algorithms train the neural network models faster than previous quantization algorithms and much faster than the float version.
Developing a Low Cost, Portable Jammer Detection and Localization Device for First Responders

A low cost, portable, robust jammer detection, and localization device is proposed and developed in this work. Intentional or unintentional use of jammers is detrimental to the seamless operation of emergency rescue and public safety missions as it disrupts the critical communication devices. The proposed device employs robust parallel detection algorithms based on Kurtosis and FRactional Fourier Transform (FRFT) to detect the most common types of Radio Frequency Interference (RFI) that affects critical communication signals. As part of preliminary performance analysis, the proposed detection technique is compared to the conventional energy detectors (employed in many commercial interference detectors) and shown to achieve significant improvement (~ 40dB) in probability of detection. The developed device is envisioned to revolutionize the low cost, portable spectrum interference monitoring sector.
Daily Activity Recognition based on Markov Logic Network for Elderly Monitoring

In this paper, we propose a daily activity recognition Method using multiple low-cost infrared portable sensors and power consumption monitors, which are easy to deploy with less risk of privacy violation. It is significant to monitor daily life of elderly living alone to prevent them from having less exercise at home and from being at home with a depression tendency. Taking those sensor values as the input, our method utilizes Markov Logic Network (MLN) to express the association rules of sensors and activities as soft logical expressions. Then using the estimated activities from MLN and user feedbacks, the method trains MLN for better accuracy of recognition. We have implemented our system as a monitoring system that summarizes the activities of daily living as a timetable, which facilitates for remote family to monitor target elderly. We have deployed the system to two real houses of elderly people, and have shown the average accuracy was more than 85%.
Algorithms to compute the Burrows-Wheeler Similarity Distribution

The Burrows-Wheeler transform (BWT) is a well studied text transformation widely used in data compression and text indexing. The BWT of two strings can also provide similarity measures between them, based on the observation that the more their symbols are intermixed in the transformation, the more the strings are similar. In this article we present two new algorithms to compute similarity measures based on the BWT for string collections. In particular, we present practical and theoretical improvements to the computation of the Burrows-Wheeler similarity distribution for all pairs of strings in a collection. Our algorithms take advantage of the BWT computed for the concatenation of all strings, and use compressed data structures that allow reducing the running time with a small memory footprint, as shown by a set of experiments with real and artificial datasets.
A reduction semantics for direct-style asynchronous observables

Asynchronous programming has gained in importance, not only due to hardware developments like multi-core processors, but also due to pervasive asynchronicity in client-side Web programming and large-scale Web applications. However, asynchronous programming is challenging. For example, control-flow management and error handling are much more complex in an asynchronous than a synchronous context. Programming with asynchronous event streams is especially difficult: expressing asynchronous stream producers and consumers requires explicit state machines in continuation-passing style when using widely-used languages like Java. In order to address this challenge, recent language designs like Google's Dart introduce asynchronous generators which allow expressing complex asynchronous programs in a familiar blocking style while using efficient non-blocking concurrency control under the hood. However, several issues remain unresolved, including the integration of analogous constructs into statically-typed languages, and the formalization and proof of important correctness properties. This paper presents a design for asynchronous stream generators for Scala, thereby extending previous facilities for asynchronous programming in Scala from tasks/futures to asynchronous streams. We present a complete formalization of the programming model based on a reduction semantics and a static type system. Building on the formal model, we contribute a complete type soundness proof, as well as the proof of a subject reduction theorem which establishes that the programming model enforces an important state transition protocol for asynchronous streams.
Quantitative detection of internal defects based on morphological opening, filling and binarizing operations on wrapped phase of out-of-plane deformation in digital speckle pattern interferometry

Abstract A novel method used for quantitative detection of internal defects with boundary of arbitrary shape is proposed in this paper for the first time. This method can be used to determine accurately the location and size of internal defects based on sequential morphological opening, filling and binarizing operations on the wrapped phase of out-of-plane deformation in phase-shifting digital speckle pattern interferometry. Because internal defects are detected directly from a wrapped phase rather than an unwrapped phase, the method proposed in this paper requires neither unwrapping of wrapped phase nor denoising of interference fringes when used for quantitative detection of internal defects. Theoretical analysis, numerical simulation, experimental verification and error calculation are presented in this paper.
METHOD OF MODELING IN PEDAGOGICAL RESEARCHES: HISTORY OF DEVELOPMENT AND MODERN CONDITION

Modeling is an attribute of modern pedagogical research. The article presents a retrospective analysis of the use of the modeling method, primarily in pedagogical research. Dependence of modeling on the development of science and other spheres of human activity is discussed. The features of modeling from ancient times to the 15th century, from the 15th century till the end of the 19th century, during the modern period from the beginning of the 20th century until recent times are determined. The author considers only insufficiently developed aspects of modeling in modern pedagogical research. The author's interpretation of modeling as a four-sided relation is given. Various modeling schemes, depending on the objectives of the research and thelinks of modeling with forecasting and design are constructed. The levels of modeling are defined: conceptual, scientific, technological ones. The features of models of each level are described.
A distortion-agnostic video quality metric based on multi-scale spatio-temporal structural information

Considering the high sensitivity of human visual perception towards the structural information, a general purpose no-reference video quality assessment (NR-VQA) metric based on local binary patterns (LBP) is proposed. In the proposed metric, 2D LBP method is extended to third dimension using LBP-TOP (LBP from Three Orthogonal Planes) for extracting the spatio-temporal structural information. Further, spatio-temporal structural information is evaluated for multi-resolution local pixel windows to incorporate the human vision system (HVS) characteristic of multi-scale perception. Since LBP only encodes the sign information of local pixel differences, and ignores the degree of variations, a second set of feature based on the magnitude information of local pixel differences is extracted. The magnitude information based LBP-TOP feature set is accumulated on the sign information based LBP-TOP feature set such that the resultant feature set has more spatio-temporal structural information with same feature vector length. To emulate the HVS mechanism of quality feature mapping to a scalar quantity, a simple two-layer feed-forward artificial neural network (ANN) of single hidden layer with four neurons is proposed. The performance of the proposed metric is validated on LIVE, CSIQ, and IVP video quality datasets and consistent performance is observed. Further, the performance of proposed metric is compared with the existing state-of-the-art NR-VQA and other IQA/VQA metrics and have exhibited better performance than the others. The proposed metric is highly consistent in performance with low computational complexity and thus suitable for real-time applications.
The Value of First Impressions

We present the first detailed analysis of ad-blocking's impact on user Web quality of experience (QoE). We use the most popular web-based ad-blocker to capture the impact of ad-blocking on QoE for the top Alexa 5,000 websites. We find that ad-blocking reduces the number of objects loaded by 15% in the median case, and that this reduction translates into a 12.5% improvement on page load time (PLT) and a slight worsening of time to first paint (TTFP) of 6.54%. We show the complex relationship between ad-blocking and quality of experience - despite the clear improvements to PLT in the average case, for the bottom 10 percentile, this improvement comes at the cost of a slowdown on the initial responsiveness of websites, with a 19% increase to TTFP. To understand the relative importance of this trade-off on user experience, we run a large, crowd-sourced experiment with 1,000 users in Amazon Turk. For this experiment, users were presented with websites for which ad-blocking results in both, a reduction of PLT and a significant increase in TTFP. We find, surprisingly, 71.5% of the time users show a clear preference for faster first paint over faster page load times, hinting at the importance of first impressions on web QoE.
Medical Image Encryption

The healthcare industry has been facing a lot of challenges in securing electronic health records (EHR). Medical images have found a noteworthy position for diagnosis leading to therapeutic requirements. Millions of medical images of various modalities are generally safeguarded through software-based encryption. DICOM format is a widely used medical image type. In this chapter, DICOM image encryption implemented on cyclone FPGA and ARM microcontroller platforms is discussed. The methodology includes logistic map, DNA coding, and LFSR towards a balanced confusion – diffusion processes for encrypting 8-bit depth 256 × 256 resolution of DICOM images. For FPGA realization of this algorithm, the concurrency feature has been utilized by simultaneous processing of 128 × 128 pixel blocks which yielded a throughput of 79.4375 Mbps. Noticeably, the ARM controller which replicated this approach through sequential embedded “C” code took 1248 bytes in flash code memory and Cyclone IV FPGA consumed 21,870 logic elements for implementing the proposed encryption scheme with 50 MHz operating clock.
Image Restoration by Second-Order Total Generalized Variation and Wavelet Frame Regularization

It has been proved that total generalized variation (TGV) can better preserve edges while suppressing staircase effect. In this paper, we propose an effective hybrid regularization model based on second-order TGV and wavelet frame. The proposed model inherits the advantages of TGV regularization and wavelet frame regularization, can eliminate staircase effect while protecting the sharp edge, and simultaneously has good capability of sparsely estimating the piecewise smooth functions. The alternative direction method of multiplier (ADMM) is employed to solve the new model. Numerical results show that our proposed model can preserve more details and get higher image visual quality than some current state-of-the-art methods.
Meta-analytic design patterns

Meta-analytics are, in short, patterns for approaching modern data tasks. In this chapter, a broad set of design patterns relevant to data analytics are overviewed. In later chapters, many of these will be described in more rigor and applied to specific problems; however, the intent of this chapter is to provide a sweeping overview of the depth and breadth of meta-analytic design patterns to drive home the cheering message that the large repertoire of patterns to choose from virtually guarantees that a better system can be built than any single existing analytic approach can provide. Armed with the ground truthing and experimental design techniques we have already learned, we end this chapter with a powerful panoply of approaches to extracting an optimal set of information from a given data set.