Reviewerly/exHarmony huggingface dataset:
The CVR narrative as a moebius strip1

Drawing on teaching sessions that I conducted last year, alongside my own practice-based doctoral research in narrative or cinematic VR (CVR) predicated on the Deleuzian notion of immanence, I propose that the CVR screenplay is better understood as a moebius strip than a linear narrative; a tale that turns around on itself. But far from being unorientable like its mathematical paradigm, the moebius narrative can be both oriented and scripted, as I hope to illustrate using student work as well as my own script iterations. Taking it to be both a model and a metaphor, this article explores how a moebius narrative can be designed – and why design thinking is more suitable for this process than traditional screenwriting methods. While still an understanding-in-progress, I find this conceptual framework useful for both practice and pedagogy. This article hopes additionally, therefore, to make a case for pedagogy as a research method in its own right, especially in the context of practice-based research.
Mapping geology and structural features of Kazaure SE, NW Nigeria: Justifying groundwater potential model

This research is focused on the evaluation of lithological units of the Kazaure area, north western Nigeria.The geological mapping was carried out using topographical sheet on a scale of 1:50,000.The methodology adopted for the study involved Field studies and petrographic analysis, which included close observation of outcrops and their exposures, their mineralogy and structures as well as recording of their geographical locations and strike/dips of foliations.The analysis revealed that, the area is underlain by three (3) major rock units: muscovite schist, porphyritic granite and sandstone (Chad Formation) with quartzite occurring as a minor lithology.The trend of lineaments shows a predominating NE-SW direction in the rocks.The cations and anions analyzed revealed that they are within the range of acceptable standard, except the higher concentration ofand which might have formed from acidic water of the area.The dominant water facies in the study area is -.These facies might have taken their sources from rock-water interaction of silicate minerals (Plagioclase feldspar).Wilcox plot of salinity hazard of the water samples indicated that, the water of the area is good for irrigation.It can be classified, the value of electrical conductivity of 0 -250 excellent, 250 -750 good, 750 -2250 doubtful and > 2250 µS/cm unsuitable.It is strongly recommended that the stake holders and governments at all levels enforce further studies of adjacent sheets for sustainable groundwater exploration and exploitation for better human and other domestic use.
Comment on “How to observe and quantify quantum-discord states via correlations”

The protocol proposed in the commented-upon article can certify zero discord; however, it fails to quantify nonzero discord for some states. Further, the protocol is less efficient than calculating discord via performing full quantum state tomography.
Dynamics of Socio-Cultural Processes of Higher Education Institutions: Digital Aspect

A modern University in the XXI century is a center of public communications, which has a certain specificity. At the present stage, the University’s communication space has almost completely switched to a digital format. This is due to several factors. First of all, the digitalization of communication channels and the creation of digital realities is an essential feature of the information society in which society will develop in the foreseeable future. On the other hand, the pandemic that limited traditional forms of communication, including in the University environment, was a factor that accelerated the creation of digital reality at the University. The events of 2020 have become a trigger that intensifies all digital formats of socio-cultural processes. The generality of the changes that have occurred puts forward new requirements for the knowledge, skills and abilities of specialists who determine the country’s economy, science, politics, and socio-cultural sphere today. In these conditions, the digital reality of the University becomes a unique space in which society’s demands for training effective personnel are realized. The digital aspect of the educational process imposes requirements for the possession of digital technologies for teachers and University administration. In the new conditions, the digital space of higher education becomes the basis for creating a digital reality of the entire state, where technologies for the successful development of society are developed and verified.
NSGANetV2: Evolutionary Multi-Objective Surrogate-Assisted Neural Architecture Search

In this paper, we propose an efficient NAS algorithm for generating task-specific models that are competitive under multiple competing objectives. It comprises of two surrogates, one at the architecture level to improve sample efficiency and one at the weights level, through a supernet, to improve gradient descent training efficiency. On standard benchmark datasets (C10, C100, ImageNet), the resulting models, dubbed NSGANetV2, either match or outperform models from existing approaches with the search being orders of magnitude more sample efficient. Furthermore, we demonstrate the effectiveness and versatility of the proposed method on six diverse non-standard datasets, e.g. STL-10, Flowers102, Oxford Pets, FGVC Aircrafts etc. In all cases, NSGANetV2s improve the state-of-the-art (under mobile setting), suggesting that NAS can be a viable alternative to conventional transfer learning approaches in handling diverse scenarios such as small-scale or fine-grained datasets. Code is available at https://github.com/mikelzc1990/nsganetv2
The Keyboard Knows About You

One of the causes of several problems on the internet, such as financial fraud, cyber-bullying, and seduction of minors, is the complete anonymity that a malicious user can maintain. Most methods that have been proposed to remove this anonymity are either intrusive, or violate privacy, or expensive. This paper proposes the recognition of certain characteristics of an unknown user through keystroke dynamics, which is the way a person is typing. The evaluation of the method consists of three stages: the acquisition of keystroke dynamics data from 118 volunteers during the daily use of their devices, the extraction and selection of keystroke dynamics features based on their information gain, and the testing of user characteristics recognition by training five well-known machine learning models. Experimental results show that it is possible to identify the gender, the age group, the handedness, and the educational level of an unknown user with high accuracy.
Causal Discovery with Unobserved Confounding and non-Gaussian Data

We consider the problem of recovering causal structure from multivariate observational data. We assume that the data arise from a linear structural equation model (SEM) in which the idiosyncratic errors are allowed to be dependent in order to capture possible latent confounding. Each SEM can be represented by a graph where vertices represent observed variables, directed edges represent direct causal effects, and bidirected edges represent dependence among error terms. Specifically, we assume that the true model corresponds to a bow-free acyclic path diagram, i.e., a graph that has at most one edge between any pair of nodes and is acyclic in the directed part. We show that when the errors are non-Gaussian, the exact causal structure encoded by such a graph, and not merely an equivalence class, can be consistently recovered from observational data. The Bow-free Acylic Non-Gaussian (BANG) method we propose for this purpose uses estimates of suitable moments, but, in contrast to previous results, does not require specifying the number of latent variables a priori. We illustrate the effectiveness of BANG in simulations and an application to an ecology data set.
Immediate Presence of Handwritten Annotation on Moving Picture in Real-Time Collaborative System

Collaborative annotation system allows a remote user to add handwritten annotation directly on local user’s view. However, previous systems cannot present handwritten annotation in real-time until all annotations have been drawn. This paper proposes a technique for collaborative annotation system that enables the immediate presence of handwritten annotation on moving picture during collaboration. This technique extracts coordinates data from handwritten annotation and reorganizes theses data in the order of strokes. Then it transmits these data to local user side in sequence. The local side receives the annotation data and presents the world-stabilized handwritten annotation in the environment. Two major optimizations are carried out in this study. One is the handwritten annotations can accurately and immediately be presented on the local side. The other is the data usage in collaboration is reduced. This research facilitates the communication between geographically dispersed users to achieve efficient collaboration. The proposed system can be applied in various fields.
Regions Based Semi-fragile Watermarking Scheme for Video Authentication

In this paper, we propose a new semi-fragile watermarking scheme in the frequency domain for surveillance videos authentication.Our system starts operating by generating a binary watermark based on a novel watermark construction process.This latter combines Speeded Up Robust Features (SURF) and Maximally Stable Extremal Regions (MSER) detectors to extract frames relevant features that can resist common attacks while being fragile to intentional manipulations.Furthermore, the watermark security is improved using torus automorphism mapping.For the embedding process, Regions of Interest (ROI) are detected and then used as watermark holders.These regions are decomposed into different frequency sub-bands using Singular Value Decomposition (SVD) as well as Discrete Wavelet Transform (DWT).Then, the watermark is embedded in selected bands following an additive method.A blind detection is conducted to extract the hidden signature from the watermarked video.Evaluation results show that the proposed scheme is suitable for authentication purpose since it efficiently discriminates malicious manipulations from non-malicious ones.Besides, it preserves a high level of perceptual quality.
Construction of Big Data Monitoring Platform for Teaching Quality under Intelligent Education

To a great extent, the quality of teaching determines the level of trained talents. Now it has entered the era of intelligent education, coupled with the rapid development of the Internet, has produced a large number of teaching data, which also makes the monitoring and evaluation of teaching quality become particularly difficult. In view of the above problems, this paper proposes the construction of big data monitoring platform for teaching quality under intelligent education. In this paper, the OPC UA unified architecture is used for communication between devices, and the information configuration is based on the spring boot framework to achieve data collection. Then, data processing is based on GRU neural network, and spark distributed computing framework is used to improve the efficiency of data operation. Finally, the monitoring effect is realized by constructing the evaluation system.
Improving Document-Level Neural Machine Translation with Domain Adaptation

Recent studies have shown that translation quality of NMT systems can be improved by providing document-level contextual information. In general sentence-based NMT models are extended to capture contextual information from large-scale document-level corpora which are difficult to acquire. Domain adaptation on the other hand promises adapting components of already developed systems by exploiting limited in-domain data. This paper presents FJWU’s system submission at WNGT, we specifically participated in Document level MT task for German-English translation. Our system is based on context-aware Transformer model developed on top of original NMT architecture by integrating contextual information using attention networks. Our experimental results show providing previous sentences as context significantly improves the BLEU score as compared to a strong NMT baseline. We also studied the impact of domain adaptation on document level translationand were able to improve results by adaptingthe systems according to the testing domain.
New AI-IP-EI Trilogy Opens Innovation to New Dimensions; Another Chip in “the Innovation Wall”, What About Emotional Intelligence (EI)?

The red thread of the AI-IP-EI Trilogy fate of this study, may have the appearance of a pot-pourri of intellectual and intelligence natures, as a matter of fact that it emanates from the genesis and practical synergism of the trilogy components.Concretely: The paper goes from: AI (Artificial Intelligence)-to the related IP (Intellectual Property) domain-to the relevance of EI (Emotional Intelligence); thus, forming the new AI-IP-EI Trilogy and its attributes and specific impacts to the new innovation process, and business model dimensions.These impacts are outlined and illustrated in part in essays of specific sections and all along.Several concrete study cases are used in the various dedicated sections; such as cases respective to the inventor status, and the EI factor, to the sport education innovative dimension, as well as to biases as inevitably promoting and revealing, to drastically enlarge open innovation supported by constructivism and creations of musical group as a model of open reflexive education.Overall resulting adapted business models appear to have a massive potential, and a multidimensional reach with a necessary attention to the IP policy on going definition.The durable green dimension is exemplified as well.The Ethics-plus, "@LEAST©", said corpus is proposed.Could a human centric, AI-adapted-IP policy, internationally embraced, take part to some level of arbitrage, normative and enduring reliability in the field of interest?This seems to be "en route".Shall the EI (Emotional Intelligence) factor be supervised?Likely so.Is traditional open innovation renewed to a more comprehensive, more inclusive dimension reminding best business How to cite this paper:
Grama: A Grammar of Model Analysis

Grama is a Python package implementing a functional grammar of model analysis emphasizing the quantification of uncertainties.In Grama a model contains both a function mapping inputs to outputs as well as a distribution characterizing uncertainties on those inputs.This conceptual object unifies the engineer/scientist's definition of a model with that of a statistician.Grama provides an implementation of this model concept, as well as verbs to carry out model-building and model-analysis.
Online Payment Using Blockchain

Increasing list of records is with blockchain where each record is linked with the help of cryptography. Every block in the chain contains timestamp, transaction details and hash of a previous block, hash is cryptographic hash. This is a secured system, which we plan to replace the current online payment system. A current online payment gateway is prone to hackers where the attacker can tamper into the network, thus creating money loss. And not only this but also the transaction has to go through multiple payment systems which consumes time, also creating a risk of transaction getting failed. So, our system would be using blockchain that allows online transactions which would allow online payments to be sent directly from one party to another without going through a financial institution and in a secured way. This system allows online transactions between two parties based on cryptographic proof without relying and trusting for a third party. To record transactions, we use proof of work algorithm which makes computationally impractical for an attacker to change. Digital signatures provide part of the solution for ensuring the security and integrity of the data that is recorded onto a blockchain.
A scene perception system for visually impaired based on object detection and classification using CNN

In this paper we have developed a system for visually impaired people using OCR and machine learning. Optical Character Recognition is an automated data entry tool. To convert handwritten, typed or printed text into data that can be edited on a computer, OCR software is used. The paper documents are scanned on simple systems with an image scanner. Then, the OCR program looks at the image and compares letter shapes to stored letter images. OCR in English has evolved over the course of half a century to a point that we have established application that can seamlessly recognize English text. This may not be the case for Indian languages, as they are much more complex in structure and computation compared to English. Therefore, creating an OCR that can execute Indian languages as suitably as it does for English becomes a must. Devanagari is one of the Indian languages spoken by more than 70% of people in Maharashtra, so some attention should be given to studying ancient scripts and literature. The main goal is to develop a Devanagari character recognition system that can be implemented in the Devanagari script to recognize different characters, as well as some words.
SimsterQ: A Similarity based Clustering Approach to Opinion Question Answering

In recent years, there has been an increase in online shopping resulting in an increased number of online reviews. Customers cannot delve into the huge amount of data when they are looking for specific aspects of a product. Some of these aspects can be extracted from the product reviews. In this paper we introduced SimsterQ - a clustering based system for answering questions that makes use of word vectors. Clustering was performed using cosine similarity scores between sentence vectors of reviews and questions. Two variants (Sim and Median) with and without stopwords were evaluated against traditional methods that use term frequency. We also used an n-gram approach to study the effect of noise. We used the reviews in the Amazon Reviews dataset to pick the answers. Evaluation was performed both at the individual sentence level using the top sentence from Okapi BM25 as the gold standard and at the whole answer level using review snippets as the gold standard. At the sentence level our system performed slightly better than a more complicated deep learning method. Our system returned answers similar to the review snippets from the Amazon QA Dataset as measured by the cosine similarity. Analysis was also performed on the quality of the clusters generated by our system.
Enabling fast and correct typing in ‘Leichte Sprache’ (Easy Language)

Simplified languages are instruments for inclusion aiming to overcome language barriers. Leichte Sprache (LS), for instance, is a variety of German with reduced complexity (cf. Basic English). So far, LS is mainly provided for, but rarely written by, its target groups, e.g. people with cognitive impairments. One reason may be the lack of technical support during the process from message conceptualization to sentence realization. In the following, we present a system for assisted typing in LS whose accuracy and speed is largely due to the deployment of real time natural-language processing enabling efficient prediction and context-sensitive grammar support.
Quantization for a Mixture of Uniform Distributions Associated with Probability Vectors

Abstract The basic goal of quantization for probability distribution is to reduce the number of values, which is typically uncountable, describing a probability distribution to some finite set and thus approximation of a continuous probability distribution by a discrete distribution. Mixtures of probability distributions, also known as mixed distributions, are an exciting new area for optimal quantization. In this paper, we investigate the optimal quantization for three different mixed distributions generated by uniform distributions associated with probability vectors.
Lower Bounds for XOR of Forrelations

The Forrelation problem, first introduced by Aaronson [Scott Aaronson, 2010] and Aaronson and Ambainis [Scott Aaronson and Andris Ambainis, 2015], is a well studied computational problem in the context of separating quantum and classical computational models. Variants of this problem were used to give tight separations between quantum and classical query complexity [Scott Aaronson and Andris Ambainis, 2015]; the first separation between poly-logarithmic quantum query complexity and bounded-depth circuits of super-polynomial size, a result that also implied an oracle separation of the classes BQP and PH [Ran Raz and Avishay Tal, 2019]; and improved separations between quantum and classical communication complexity [Uma Girish et al., 2021]. In all these separations, the lower bound for the classical model only holds when the advantage of the protocol (over a random guess) is more than ≈ 1/√N, that is, the success probability is larger than ≈ 1/2 + 1/√N. This is unavoidable as ≈ 1/√N is the correlation between two coordinates of an input that is sampled from the Forrelation distribution, and hence there are simple classical protocols that achieve advantage ≈ 1/√N, in all these models.To achieve separations when the classical protocol has smaller advantage, we study in this work the xor of k independent copies of (a variant of) the Forrelation function (where k≪ N). We prove a very general result that shows that any family of Boolean functions that is closed under restrictions, whose Fourier mass at level 2k is bounded by α^k (that is, the sum of the absolute values of all Fourier coefficients at level 2k is bounded by α^k), cannot compute the xor of k independent copies of the Forrelation function with advantage better than O((α^k)/(N^{k/2})). This is a strengthening of a result of [Eshan Chattopadhyay et al., 2019], that gave a similar statement for k = 1, using the technique of [Ran Raz and Avishay Tal, 2019]. We give several applications of our result. In particular, we obtain the following separations:Quantum versus Classical Communication Complexity. We give the first example of a partial Boolean function that can be computed by a simultaneous-message quantum protocol with communication complexity polylog(N) (where Alice and Bob also share polylog(N) EPR pairs), and such that, any classical randomized protocol of communication complexity at most o(N^{1/4}), with any number of rounds, has quasipolynomially small advantage over a random guess. Previously, only separations where the classical protocol has polynomially small advantage were known between these models [Dmitry Gavinsky, 2016; Uma Girish et al., 2021].Quantum Query Complexity versus Bounded Depth Circuits. We give the first example of a partial Boolean function that has a quantum query algorithm with query complexity polylog(N), and such that, any constant-depth circuit of quasipolynomial size has quasipolynomially small advantage over a random guess. Previously, only separations where the constant-depth circuit has polynomially small advantage were known [Ran Raz and Avishay Tal, 2019].