Reviewerly/exHarmony huggingface dataset:
Joint Bilinear End-to-End Dependency Parsing with Prior Knowledge

Dependency parsing aims to identify relationships between words in one sentence. In this paper, we propose a novel graph-based end-to-end dependency parsing model, including POS tagger and Joint Bilinear Model (JBM). Based on prior POS knowledge from dataset, we use POS tagging results to guide the training of JBM. To narrow the gap between edge and label prediction, we pass the knowledge hidden in label prediction procedure in JBM. Motivated by success of deep contextualized word embeddings, this work also finetunes BERT for dependency parsing. Our model achieves 96.85% UAS and 95.01% LAS in English PTB dataset. Moreover, experiments on Universal Dependencies dataset indicates our model also reaches state-of-the-art performance on dependency parsing and POS tagging.
Event Detection with Document Structure and Graph Modelling

Event detection is the basic task of event extraction. Previous studies usually used independent sentences as basic event detection objects. They cannot effectively identify event triggers which depend on document information. Besides, there are correlations between the sentences and words in the document. Therefore, it is necessary to use document information for event detection. In this study, we propose a graph model for event detection based on document structure. It is used to connect sentences and words in a document. Specifically, we finetune BERT model and use Bi-LSTM to learn the sentences and their context features, and then use GCN to model the document relation graph. The document relation graph is based on the parts of speech of all words in different sentences, which contributes to establishing the triggers-triggers relation and triggers-arguments relation. The experimental results on LitBank show that our proposed model outperforms all baselines significantly and verifies the validity of document information.
Recognizing Soft Biometric on Pedestrian Using Convolutional Neural Network

Video surveillance is very important in automatic surveillance. It is usually used to monitor any criminal activity and help to find the perpetrator. In the search for individual among pedestrians when the face image can no longer be recognized, then what can be recognized is the soft-biometric or attribute appears on the pedestrian. The attributes can be in the form of clothes or accessories worn by pedestrians. However, recognizing attributes is a more challenging task as the number of variations of the attribute is increasing. Therefore, there is a need of a system that can effectively recognize the soft-biometric of pedestrians that are expected to help in video surveillance. In this study, we propose a pedestrian soft-biometric recognition system that was built using the Convolutional Neural Network (CNN) method so that it can search for pedestrians wearing various attributes. In recognizing pedestrian soft-biometric, the authors conducted a study using transfer learning from the Resnet50 architecture. As this case belongs to the multi-label classification case, we also observed several scenarios for determining the threshold to better classify the appearance of attributes. Our system able to recognize 35 different attributes with the best results of this research indicate the average accuracy of 90.82% with 80.84% of precision and 81.08% of recall using test data.
A concrete model for a typed linear algebraic lambda calculus

Abstract We give an adequate, concrete, categorical-based model for Lambda- ${\mathcal S}$ , which is a typed version of a linear-algebraic lambda calculus, extended with measurements. Lambda- ${\mathcal S}$ is an extension to first-order lambda calculus unifying two approaches of non-cloning in quantum lambda-calculi: to forbid duplication of variables and to consider all lambda-terms as algebraic linear functions. The type system of Lambda- ${\mathcal S}$ has a superposition constructor S such that a type A is considered as the base of a vector space, while SA is its span. Our model considers S as the composition of two functors in an adjunction relation between the category of sets and the category of vector spaces over $\mathbb C$ . The right adjoint is a forgetful functor U , which is hidden in the language, and plays a central role in the computational reasoning.
Animation Design of the Journey of 40 Years

Animate, formerly Flash professional CC 2015, is a standard for interactive vector graphics and Web animation introduced by macromedia and acquired by Adobe. On December 1, 2015, Adobe upgraded its animation software and renamed it Animate CC 2015.5, thus drawing a line under Flash technology. Designers and developers can use it to create presentations, applications, and other content that allows users to interact. Flash can include simple animations, video content, complex presentations, and applications. But this time we mainly use it to make a two-dimensional animation. [1] This year, 2019, marks the 70th anniversary of the founding of the People's Republic of China. It has been more than 40 years since the launch of reform and opening-up. Over the past 40 years, China has grown from a relatively backward country where food and clothing are a problem to a prosperous modern China. It can be said that in just 40 years, our great country has gone through a variety of milestones, step by step on the road to pursue their dreams. In order to show the great achievements of the motherland and the changes of people's lives in the past 40 years, we created a two-dimensional animation. We mainly develop and produce animation by using animation software, combining tween animation technology and animation's powerful functions, such as frame-by-frame animation rendering, to complete this two-dimensional animation short film. Through the life of a man born in 1978 as an example, through the eyes of the hero of the story, to feel the great decision of reform and opening up, the impact on the life of an ordinary person and the growing prosperity of the motherland.
OPTIMIZING OUR NETWORKED LIVES

We use the term networked optimization to emphasize a sustained but changing set of techniques, technologies, and calculations to decide the best life -- the optimal -- through infrastructures, design, mathematics and engineering. Optimization is a vital concept at a time of critical interest in infrastructural power. Usually defined as doing actions to make the best or most effective use of something, our panel highlights the different uses of the term across the internet. Used as a selling point by many technology companies, optimization means different things to different actors. Perhaps the most important question on this is optimized for who? From Facebook to 5G, our panelists work across technical and theoretical literatures as well as computer science and humanities to identify the social implications of networked optimization. Author #1 examines how Facebook’s personalization ideology is engineered into its infrastructure to influence people’s behaviors to maximize its advertising value. Author #2 looks to the discourses and infrastructure of Google’s cloud computing that promise a form of global social engineering. Author #3 takes these questions out of the cloud and into the next-generation of the Internet, 5G. The promised new wireless infrastructure makes a major shift in the meta-governance of communications and re-consolidates power in network operators. Finally, Author #4 looks for forms of resistance through the development of Protective Optimization Technologies that help people counter efforts to nudge and shape their behaviours.
Stereo phase unwrapping method based on feedback projection

Eliminating the effective phase ambiguity with as few fringe patterns as possible is a huge challenge for fringe projection profilometry (FPP). The stereo phase unwrapping (SPU) technologies based on geometric constraints can achieve phase unwrapping without projecting any additional patterns, which maximizes the efficiency of the absolute phase retrieval. However, when high-frequency fringes are used, the phase ambiguities will increase which makes SPU unreliable. The adaptive depth constraint (ADC) method can increase the robustness of SPU, but it is difficult to deal with scenarios without the priori depth guidance. In this work, we propose a stereo phase unwrapping method based on feedback projection to robustly unwrap the wrapped phase of dense fringe images. Aiming at the problem that the ADC is too dependent on the last measurement result, a simple and effective deep anomaly detection strategy is proposed. After determining the reconstruction error, through the proposed fully automatic projection feedback mechanism, the absolute depth of the object can be quickly obtained to correct the dynamic depth range of the ADC, thus guiding the acquisition of high-quality 3D information. Experiments prove that this approach can achieve high-speed, real-time, and high-resolution 3D measurement with a measurement speed of 30 Hz under the premise of using two perspectives.
VeZoo – Augmented Reality Experience for the Cali's Zoo

We are implementing a prototype mobile application with augmented reality (AR) that will allow the information of animals to be communicated to the visitors of a zoo, ensuring that more information can be transmitted, updated and delivered in a more didactic and dynamic way through the use of technology.
Automating Stress Detection from Handwritten Documents

Stress is a crucial problem in life, which is growing because of the fast-paced and demanding modern-life. Meanwhile, stress must be detected at early stages to prevent the negative effects on human health. Graphologist who analyze human handwriting have been able to detect stress from human handwriting. This is by extracting some features from the handwriting to detect stress level. The manual stress detection process is expensive, tedious and exhausting. This made the automation of the stress detection system important. Little research has been done on this field. In this research we will focus on automating stress detection from handwritten documents. We are working with graphologist to create a database of handwritten documents for stress detection. Later we will experiment different features to automate stress detection from the person's handwriting.
A Path Planning Method for a Low Observable UAV in Radar Field

In this paper we propose a two-step method for the problem of path planning for a low observable unmanned air vehicle in a radar field. In the first step, we convert the problem into a constrained shortest path problem defined on a directed network graph and then we apply an efficient graph search algorithm for solving it. We implement a probabilistic cost function for the path, assuming an anisotropic vehicle radar cross section. The length of the path is constrained by the maximum range of the vehicle. In the second step, the initial polygonal path is refined using B-Splines. We take the vehicle maneuvering limits into account for the smoothed path.
Perplexing the Liquid University

Recent confrontations across institutions of higher learning in South Africa have brought into sharp focus that universities, though they may market themselves as spaces of critical citizenship, are not satisfying the desires of a large section of the students who occupy them. The outbreaks of protests that are untidy and discomfiting – students disrupting classes, occupying the built fabric of the university, or staging spectacular demonstrations – have signaled the possibility that the economy of knowledge-exchange symbolized by universities is exclusionary for these students. The psychic cost of these disruptions has yet to truly be measured. But what has become apparent is that we have entered a transitional after-moment that warrants reading. Indeed, as the surging waters of ‘Fallism’ ebb from the university, it becomes necessary to rethink the ways in which the forms of violence enacted by the universities to defend their solidity demonstrated the limitations of their current form. This article is impelled by the notion that there is no single ‘university’ approached by both students and the network of employees who orchestrate its functions. It asks what other potentials might be realized if we think of the university as a liquid space, rather than a rigidly unyielding one.
Variations of diffusion functions on Perona and Malik model for noise removal

In 1990, Perona and Malik introduced diffusion model which is known as Perona and Malik (P-M) model to preserve the edge or boundaries. The edge indicator used as the variable exponent controls the diffusion mode as edge stopping between P-M diffusion and Gaussian smoothing depending on the image. The application of nonlinear second-order PDE model of P-M model is designed such that smooth areas diffused faster than the other areas and consequently may cause the presence of blocky effect. Hence, numerous modified diffusion functions have been developed to enhance image denoising results in order to overcome the loss of detail and blur in images. The objectives of this paper are to propose modified diffusion functions and compare with existing functions in order to provide alternative diffusion functions with edge and details preservation. Besides that, the modified functions were implemented on an image with different level of noise to made visual comparison with existing functions The proposed functions must be a positive function, monotonically decreasing and also convergent to zero. Results shows that the modified functions were converged rapidly as compared to the existing diffusion functions and able to remove different level of noise. In addition, the quality of image and their details are also preserved after the denoising process.
Research on Evaluation Technology of Pavement Roughness Based on Smartphone

Based on the principle of membership function in fuzzy theory, this research established the prediction model between smartphone acceleration value and pavement roughness level under different detection speeds after processing the sensitive data by detrending term, filtering discrete outliers, and data compensation. Finally, the prediction error of the model was analyzed. The research results show that the membership function can resolve the ambiguity between the pavement roughness level and the acceleration value, with high prediction accuracy, and strong generalization ability, which can accurately reflect the relationship between the acceleration value and the roughness level.
Application of Expert Systems and Simulation Modeling to Calculate Connectivity Between the Nodes of the Graph

The problem of accurately calculating the probability of connectivity of graph nodes is not only very important for practical use, but also belongs to the class of NP-hard problems. The paper gives the place of application of expert systems, simulation modeling and other well-known methods in solving the problem of accurately calculating the probability of connectivity of graph nodes. The rule-based expert system Drools was chosen as the basis of our engine. The Monte Carlo method is used as a basis for simulation modeling. The rules of the Drools expert system and examples of the system operation are given.
Measuring the Semantic Stability of Word Embedding

The techniques of word embedding have a wide range of applications in natural language processing (NLP). However, recent studies have revealed that word embeddings have large amounts of instability, which affects the performance in downstream tasks and the applications in safety-critical fields such as medical diagnosis and financial analysis. Further researches have found that the popular metric of Nearest Neighbors Stability (NNS) is unreliable for qualitative conclusions on diachronic semantic matters, which means NNS cannot fully capture the semantic fluctuations of word vectors. To measure semantic stability more accurately, we propose a novel metric that combines the Nearest Senses Stability (NSS) and the Aligned Sense Stability (ASS). Moreover, previous studies on word embedding stability focus on static embedding models such as Word2vec and ignore the contextual embedding models such as Bert. In this work, we propose the SPIP metric based on Pairwise Inner Product (PIP) loss to extend the stability study to contextual embedding models. Finally, the experimental results demonstrate that CS and SPIP are effective in parameter configuration to minimize embedding instability without training downstream models, outperforming the state-of-the-art metric NNS.
Problems of formation and assessment of competence of library-information industry specialists

The content of competencies of specialists of library and information industry is revealed, and the value of evaluation in the process of their formation in the article. Used methods for working out the material: analysis, synthesis, comparison, generalization. The results and conclusions of writing the article are as follows. The types of competencies of specialists of library and information industry are summarized, the main of which are: functional (professional), intellectual and social (socio-psychological). Each of the core competencies is complex and is implemented with the help of other competences and skills. Their formation is carried out by means of professional retraining, advanced training, internships and prompt updating of knowledge through non-formal educational channels. Information competence and information literacy is an integral part in developing the professional competence of an employee of the library and information industry, able to meet the needs of the profession and the needs of society. The provision of information literacy, using a curriculum tailored to external variables: education standards, models of education, new technologies and capabilities, and the requirements of society for the information specialist is considered in the American experience. A key criterion for assessing employee performance is the level of professional competence. Assessing the professional competence of library and information professionals can be seen as an integral and important step in the structure of specialist training, as well as a field of applied research aimed at identifying problems in the formation, implementation and development of competencies, finding ways to solve them. Different perceptions of criteria for assessing competence and performance are analyzed and summarized. The results of evaluating the professional competencies of library professionals give an idea of ​​the perceptions and attitudes of users and society to the performance of libraries and their staff.
Cooperation Regulation for HAPF and PV Converter in Microgrid

It is very important to maintain the voltage stability of the microgrid. The hybrid active power filter (HAPF) can achieve not only wide-range reactive power compensation and grid-connected voltage support under the condition of reduced DC voltage demand but also active power injection. Its power control range and characteristics are different from photovoltaic converters. This paper studies the control of parallel HAPF and photovoltaic converter in low voltage microgrid, and to make full use of the power control capabilities of the two devices, the power-sharing algorithms of HAPF and photovoltaic converters were also studied to minimize the total capacity of the microgrid. Therefore, this paper proposes a power reference measurement method, which is embedded in the hierarchical control framework of the microgrid. The results show that the application of the proposed method can achieve the reduction of microgrid capacity when the load requirements are met. Simulation based on droop control further proves the effectiveness of this method.
Dual-level light field reconstruction network based on directional EPI volume

Light field (LF) imaging, which can capture spatial and angular information of light-rays in one shot, has received increasing attention. However, the well-known LF spatio-angular trade-off problem has restricted many applications of LF imaging. In order to alleviate this problem, this paper put forward a dual-level LF reconstruction network to improve LF angular resolution with sparselysampled LF inputs. Instead of using 2D or 3D LF representation in reconstruction process, this paper propose an LF directional EPI volume representation to synthesize the full LF. The proposed LF representation can encourage an interaction of spatial-angular dimensions in convolutional operation, which is benefit for recovering the lost texture details in synthesized sub-aperture images (SAIs). In order to extract the high-dimensional geometric features of the angular mapping from low angular resolution inputs to high angular full LF, a dual-level deep network is introduced. The proposed deep network consists of an SAI synthesis sub-network and a detail refinement sub-network, which allows LF reconstruction in a dual-level constraint (i.e., from coarse to fine). Our network model is evaluated on several real-world LF scenes datasets, and extensive experiments validate that the proposed model outperforms the state-of-the-arts and achieves a better reconstruct SAIs perceptual quality as well.
Forms of Student Work Organization in the Inclusive Education Process

Summary In recent years, increasing attention has been devoted to developing pedagogical approaches that are appropriate in heterogeneous classrooms. Teachers working in inclusive classrooms must develop forms of student work that do not isolate and stigmatize learners with special educational needs. In the first part of the article, the author analyzes the origin and essence of the idea of inclusive education. In the second part of the article, three forms of work organization for students in inclusion classes are characterized: Peer Tutoring, Cooperative Learning and Multi-level Teaching.
Influence of Visual Gap of Avatar Joint Angle on Sense of Embodiment in VR Space Adjusted via C/D Ratio

The movement of an avatar in the VR space is often handled in complete synchronization with the body of the operator, both spatially and temporally. However, if the operator uses an interaction device with a narrow work area, the range of motion of the avatar may be adjusted by tuning the control/display (C/D) ratio. This tuning of the C/D ratio is a technique often used in mouse interaction; however, upon applying the concept of the C/D ratio on an avatar that is connected with the body of an operator, the sense of embodiment felt by the operator of the avatar is affected. In this study, we investigate the subjective effects of the sense of embodiment, presence, and mental workload while performing a point-to-point task between two points, by using the effects of the avatar appearance and the C/D ratio as independent variables.