Reviewerly/exHarmony huggingface dataset:
Projected Horizons

Projected Horizons is an installation for the at the California Institute for Telecommunications and Information Technology (Calit2) comprised of visualizations of arctic horizons and an accompanying sound composition. Footage of the jagged horizons of arctic glaciers will slowly pan as an audio composition unfolds, comprised of hydrophone recordings of arctic aquatic life. The rise and fall of the linear line that comprises the horizon will be mirrored in the sonic arc of the accompanying composition.
Research on Teaching Reform of Educational Technology Public course under the background of Educational Information 2.0

The purpose of the public course of educational technology is to train the ability of the students' information technology, which is an important part of the teacher's pre-service education. However, There are many problems in the course, such as the large number of students, the single evaluation method, the limited learning time, which can not be trained according to the characteristics of each subject, and so on. This paper, under the background of education information 2.0, uses the modern information technology means to explore the mixed teaching of the public course of modern education technology based on the network teaching platform. In the form of the combination of the online course and the offline course, the complementary advantages of the classroom teaching and online education are realized, and the idea of reform is made from the aspects of teaching content, teaching means and methods, teaching evaluation and so on, explore a suitable way for the reform of educational technology public course in normal colleges and universities.
Application of the covariance matrix clustering algorithm for partitioning joint sets having various joint pole sizes and densities

An analysis of data collected on rock discontinuities mostly requires the data to be separated into sets. An automatic clustering algorithm that assists in identification of joint sets is always desired. Several algorithms have been proposed, most of which are based on the widely used fuzzy K-means method in which the optimization step involves minimizing the sum of squared distances between objects and the centroids of clusters. Empirical studies have demonstrated that this method tends to generate equally sized clusters, which means clusters of different sizes cannot be adequately distinguished (equal-size problem). This paper introduces the application of a clustering method that applies an optimization criterion based on the estimated covariance matrix to overcome the aforementioned equal-size problem of the K-means clustering scheme. The applicability of the method is demonstrated using both artificial and field data with low dimensionality.
Economic byproducts in copper porphyries: Ag in the Ascutita Cu-porphyry, Romania

"Economic byproducts in copper porphyries: Ag in the Ascutita Cu-porphyry, Romania." Applied Earth Science, 128(2), pp. 46–47
Coupled Semi-supervised Clustering: Exploring Attribute Correlations in Heterogeneous Information Networks

Heterogeneous Information Network (HIN) has been widely adopted in various tasks due to its excellence in modeling complex network data. To handle the additional attributes of nodes in HIN, the Attributed Heterogeneous Information Network (AHIN) was brought forward. Recently, clustering on HIN becomes a hot topic, since it is useful in many applications. Although existing semi-supervised clustering methods in HIN have achieved performance improvements to some extent, these models seldom consider the correlations among attributes which typically exist in real applications. To tackle this issue, we propose a novel model SCAN for semi-supervised clustering in AHIN. Our model captures the coupling relations between mixed types of node attributes and therefore obtains better attribute similarity. Moreover, we propose a flexible constraint method to leverage supervised information and network information for flexible adaption of different datasets and clustering objectives. Extensive experiments have shown that our model outperforms state-of-the-art algorithms.
Bayesian nonparametric analysis of Kingman’s coalescent

Kingman's coalescent is one of the most popular models in population genetics.It describes the genealogy of a population whose genetic composition evolves in time according to the Wright-Fisher model, or suitable approximations of it belonging to the broad class of Fleming-Viot processes.Ancestral inference under Kingman's coalescent has had much attention in the literature, both in practical data analysis, and from a theoretical and methodological point of view.Given a sample of individuals taken from the population at time t > 0, most contributions have aimed at making frequentist or Bayesian parametric inference on quantities related to the genealogy of the sample.In this paper we propose a Bayesian nonparametric predictive approach to ancestral inference.That is, under the prior assumption that the composition of the population evolves in time according to a neutral Fleming-Viot process, and given the information contained in an initial sample of m individuals taken from the population at time t > 0, we estimate quantities related to the genealogy of an additional unobservable sample of size m ≥ 1.As a by-product of our analysis we introduce a class of Bayesian nonparametric estimators (predictors) which can be thought of as Good-Turing type estimators for ancestral inference.The proposed approach is illustrated through an application to genetic data.
Fast Generalized Linear Models by Database Sampling and One-Step Polishing

In this article, I show how to fit a generalized linear model to N observations on p variables stored in a relational database, using one sampling query and one aggregation query, as long as N12+δ observations can be stored in memory, for some δ>0. The resulting estimator is fully efficient and asymptotically equivalent to the maximum likelihood estimator, and so its variance can be estimated from the Fisher information in the usual way. A proof-of-concept implementation uses R with MonetDB and with SQLite, and could easily be adapted to other popular databases. I illustrate the approach with examples of taxi-trip data in New York City and factors related to car color in New Zealand. Supplementary materials for this article are available online.
Tracking challenges of QKD over relay satellite

We investigate a quantum key distribution (QKD) system with relay satellite for communication between two distant Earth-based parties, Alice and Bob. The satellite acts as a relay station which simply redirects the QKD signal. It has several advantages that can be decisive. The optical relay provides a high transparency to protocols and wavelengths. The relay node does not have to be trusted. Like entanglement-based or measurement-device-independent satellite QKD, relayassisted QKD suffers from a higher propagation loss than trusted-node scenarios. Challenges are expected when pointing the relay mirror precisely between Alice and Bob and dealing with significant point-ahead angles that result from the satellite velocity. We start our analysis by evaluating the point ahead angles (PAA) of Alice and Bob for scenarios of interest. The difference between the two PAA vectors tells us whether the relay mirror will be able to maintain a bidirectional transmission with beams sent from the ground. Considering a satellite altitude of 500 km and an Alice-Bob separation of 1000 km, observation of large PAA vector difference enjoins us to place additional beacon sources on the satellite. A conceptual design of the relay-tracking system is drafted. Onboard measurements of the beacons from Alice and Bob provide feedback to the relay-mirror positioning control loop. With a typical relay-mirror size of 0.2 m, propagation losses are calculated for different ground antennas. We conclude on the attractiveness and feasibility of satellite relay QKD.
Polylog-LDPC Capacity Achieving Codes for the Noisy Quantum Erasure Channel

We provide polylog sparse quantum codes for correcting the Erasure channel arbitrarily close to the capacity. Specifically, we provide the [[n, k, d]] quantum stabilizer codes that correct for the erasure channel arbitrarily close to the capacity if the erasure probability is at least 0.33 and with a generating set (S <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sub> , S <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> , ... S <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">n-k</sub> ) such that |Si| ≤ log <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2+ζ</sup> (n) for all i and for any ζ > 0 with high probability. In this paper, we show that the result of Delfosse et al. is tight: one can construct capacity approaching codes with weight almost O(1).
Sketching for Latent Dirichlet-Categorical Models

Recent work has explored transforming data sets into smaller, approximate summaries in order to scale Bayesian inference. We examine a related problem in which the parameters of a Bayesian model are very large and expensive to store in memory, and propose more compact representations of parameter values that can be used during inference. We focus on a class of graphical models that we refer to as latent Dirichlet-Categorical models, and show how a combination of two sketching algorithms known as count-min sketch and approximate counters provide an efficient representation for them. We show that this sketch combination -- which, despite having been used before in NLP applications, has not been previously analyzed -- enjoys desirable properties. We prove that for this class of models, when the sketches are used during Markov Chain Monte Carlo inference, the equilibrium of sketched MCMC converges to that of the exact chain as sketch parameters are tuned to reduce the error rate.
The Silent Researcher Critique: A New Method for Obtaining a Critical Response to a Holographic Artwork

The purpose of this article is to provide a plausible answer as to whether the Z-axis of holographic space can be used to depict a chronological narrative with an affective impact. This article describes a practice-based holographic arts study in which the author created interactive artworks with family photographs taken from the late 1800s to the present day, and stacked them in chronological order within the Z-axis of holographic space. The artworks were evaluated by different audiences to determine whether the viewer could perceive the new application of holographic space, and whether the artwork had an affective impact. An art critique method used both in Higher Education settings in the UK and in professional art practice, was adapted as a research tool for use in this study and termed ‘the silent researcher critique’. The findings of the project were that audiences had a new experience when interacting with the works and were impacted emotionally by them, however only a group of experts in art and holography were able to identify and comprehend the new conceptual use of the Z-axis of holographic space. This study’s value can be measured by its offering practice-based arts researchers a novel method of obtaining valuable critical feedback from peers and by its contribution to the aesthetic development of the medium of art holography.
Background Subtraction and Kalman Filter Algorithm for Object Tracking

Today's world is confronting real issue regarding open security for which visual surveillance framework is required. Object tracking increases loads of enthusiasm for dynamic research in applications, for example, video surveillance, vehicle navigation, video compression and so on. Distinctive strategies are produced for object tracking purpose however that experiences corruption in execution because of occlusion, complex shapes and enlightenments. In this proposed work, discovery of the moving item has been finished utilizing straightforward background subtraction and a Kalman filter algorithm. Following calculation has been completed and attempted on MATLAB 2013a with working system windows. Strategy contrasts and examines different execution measures and different calculations.
City Residents as Videogame Characters in Smart Urban Environments

In this chapter, we argue that residents in future smart cities will have a role that can be compared with that of non-player characters in videogames. They can play, but their play is supervised, there is no free play, there is no spontaneous play, and there will be a McDonaldization and Googlization of play all over the smart world. This view is contrary to the notion that smart technology and citizens’ access to such technology will allow them to reconfigure their urban environments to make them playful. We will illustrate this view with some current examples of control, management, and privatization of urban environments. These examples clearly show that future smart city citizens will not be allowed to use this technology in creative, collaborative, and competitive play; instead, their play will be controlled by smart technology. Will urban operating systems really differ from the engines that control videogame environments? Do we play smart environments, or do these environments play us? Artists and urban activists have commented on these developments with playful yet critical activities and art.
Cross-Lingual Transfer for Distantly Supervised and Low-Resources Indonesian NER

Manually annotated corpora for low-resource languages are usually small in quantity (gold), or large but distantly supervised (silver). Inspired by recent progress of injecting pre-trained language model (LM) on many Natural Language Processing (NLP) task, we proposed to fine-tune pre-trained language model from high-resources languages to low-resources languages to improve the performance of both scenarios. Our empirical experiment demonstrates significant improvement when fine-tuning pre-trained language model in cross-lingual transfer scenarios for small gold corpus and competitive results in large silver compare to supervised cross-lingual transfer, which will be useful when there is no parallel annotation in the same task to begin. We compare our proposed method of cross-lingual transfer using pre-trained LM to different sources of transfer such as mono-lingual LM and Part-of-Speech tagging (POS) in the downstream task of both large silver and small gold NER dataset by exploiting character-level input of bi-directional language model task.
AlgoBOWL

We describe a competition-based group project that has been in use in the Algorithms course at our institution each semester since 2012. The class is given an NP-hard optimization problem; each student group is asked to create a heuristic algorithm for the problem. The heuristic is run on a set of inputs (with each group supplying one input) and groups are ranked based on their aggregate performance within a specified time period. This paper describes our experience with this approach, including challenges, and our recent efforts to address these through a web application used to facilitate the competition.
Chapter 13. Coordination games and disagreement

This essay explores the suitability of coordination games for the study of strategic argumentation in disagreements. An argumentative battle of the sexes (ArgBoS) game is introduced for studying various strategies of rational disagreement resolution. The properties of both normal- and extensive-form ArgBoS are explored. In addition, the strategic effects of burning money will be studied. It will be shown that burning money can have strategic advantages in resolving disagreements.
VC-Dimension Based Generalization Bounds for Relational Learning

In many applications of relational learning, the available data can be seen as a sample from a larger relational structure (e.g. we may be given a small fragment from some social network). In this paper we are particularly concerned with scenarios in which we can assume that (i) the domain elements appearing in the given sample have been uniformly sampled without replacement from the (unknown) full domain and (ii) the sample is complete for these domain elements (i.e. it is the full substructure induced by these elements). Within this setting, we study bounds on the error of sufficient statistics of relational models that are estimated on the available data. As our main result, we prove a bound based on a variant of the Vapnik-Chervonenkis dimension which is suitable for relational data.
Recommendations from a Study of a Multimodal Positive Computing System for Public Speaking

We review some existing multimodal systems for Public Speaking. We then present two versions of a multimodal system for Public Speaking based on Positive Computing. The system uses the Microsoft Kinect to detect voice, body pose, facial expressions and gestures. The system is a real-time system, which gives users feedback on their performance while they are rehearsing a speech. We discuss a study comparing two versions of the system. One version displays a live video-stream of the user. The other displays a computer-generated avatar, which represents the user’s body movements and facial expressions. We discuss user reactions to both versions of the system and make recommendations for future multimodal systems for public speaking.
The Overview of 2D to 3D Automatic Conversion

With the rapid development of 3D devices, the depth map extraction method of 2D to 3D conversion has become a research hot spot in the field of computer vision. In this paper, on account of collected literatures and documents, we mainly introduces two methods of automatic depth map extraction based respectively on depth clues and machine learning. The depth map extraction method based on clues of several implementation algorithms is introduced, and its respective advantages and disadvantages are summarized. While for the depth map extraction method based on machine learning, we show the process of depth map extraction as an example. Moreover the parametric method and the non-parametric method are compared, and their respective advantages and disadvantages are pointed out. Finally we summarize the improved depth map extraction algorithm in the recent years, and the technical prospect is also discussed.
The influence of magmatic and volatile evolution upon lanthanoid fractionation within peralkaline magmas (Norra Kärr, Sweden)

"The influence of magmatic and volatile evolution upon lanthanoid fractionation within peralkaline magmas (Norra Kärr, Sweden)." Applied Earth Science, 128(2), p. 45
Beyond Keyword Targeting

As the main revenue source for search engines, sponsored search system retrieves and allocates ads to display on the search result pages. Keyword targeting is widely adopted by most sponsored search systems as the basic model for expressing the advertiser's business and retrieving related ads. In this targeting model, the advertiser should cautiously select lots of keywords relevant to their business to optimize their campaigns, and the sponsored search system retrieves ads based on the relevance between queries and keywords. However, since there is a huge inventory of possible queries and the new queries grow dramatically, it is a great challenge for advertisers to identify and collect lots of relevant bid keywords for their ads, and it also takes great effort to select and maintain high-quality keywords and set corresponding match types for them. In the meantime, the keyword targeting leads to a multi-stage retrieval architecture as it contains the matching between query and keywords and the matching between keywords and ads. The retrieval funnel based on keyword targeting cannot achieve straightforward and optimal matching between search queries and ads. Consequently, traditional keyword targeting method gradually becomes the bottleneck of optimizing advertisers' campaigns and improving the monetization of search ads.
Concentration of measure for radial distributions and consequences for statistical modeling

Motivated by problems in high-dimensional statistics such as mixture modeling for classification and clustering, we consider the behavior of radial densities as the dimension increases. We establish a form of concentration of measure, and even a convergence in distribution, under additional assumptions. This extends the well-known behavior of the normal distribution (its concentration around the sphere of radius square-root of the dimension) to other radial densities. We draw some possible consequences for statistical modeling in high-dimensions, including a possible universality property of Gaussian mixtures.
Merab Mamardashvili and Immanuel Kant: a dialogue on transcendental consciousness and moral responsibility

Mamardashvili always engaged in a dialogue with thinkers of the past, particularly with those philosophers whom he considered to have founded the phenomenological analysis of consciousness. He had a particular fascination for Kant. Not only did Mamardashvili devote to him a series of lectures, but he referenced Kantian themes throughout the entirety of his work. This article focuses on two of those themes. The first is transcendental consciousness, considered as that which makes experience possible without being itself reducible to experience. Consciousness is at the basis of all the different “forms” that make possible our experience of the world. Thinking is possible only in the context of cultural tradition, which is embedded in language. The second is individual moral responsibility. Everyone everywhere takes a stance at all times, here and now, thereby assuming the whole responsibility for their action. Mamardashvili’s dialogue with Kant leads us to consider some of the ethical problems of human civilization.
Implementation of Tibetan-Chinese translation platform based on LSTM algorithm

With the rapid economic development and increasingly frequent language exchanges in Tibet, the traditional statistical machine translation methods are faced with problems such as lack of data and over-fitting of training, resulting in poor translation quality. Combined with the current development of natural language processing (NLP), the LSTM algorithm based on Google's TensorFlow framework is proposed to realize the Tibetan and Chinese neural machine translation method. In the preprocessing stage of corpus, word segmentation module is constructed for tibetan-chinese bilingual parallel corpus by using the combination algorithm of gated circulatory neural network (GRU) and conditional random field (CRF). In the model construction stage, the LSTM method is used to construct the model. The experimental results show that the short and long time memory networks have good translation effects.
Strategies for the Use of Mathematics Textbooks for Primary and Secondary Schools under the Background of “Internet+”

Mathematics textbooks for primary and secondary schools play an important role in elementary education and the realization of their functions and value depends on the scientific and effective use of teachers and students.Therefore, some strategies are put forward: understand the intentions of the mathematics textbook, explore the educational and teaching value of mathematics textbooks, grasp mathematics textbooks as a whole, use mathematics textbooks creatively, attach importance to the comparative study and use of different versions of mathematics textbooks.