Reviewerly/exHarmony huggingface dataset:
Deterministic Hyperparallel Control Gates with Weak Kerr Effects

Abstract By harnessing weak cross‐Kerr nonlinearities, it proposes two deterministic hyperparallel quantum control gates, including the hyperparallel controlled‐NOT (hyper‐CNOT) gate and hyperparallel Fredkin (hyper‐Fredkin) gate for photonic systems in the polarization and spatial degrees of freedom (DoFs), which are composed of two procedures for the implementations of the first polarized control (CNOT and Fredkin) gates and the second spatial control (CNOT and Fredkin) ones in turn. Moreover, compared with the two two‐photon CNOT gates (three‐photon Fredkin gates) in one DoF, the hyper‐CNOT (hyper‐Fredkin) gate is provided with more straightforward quantum circuits, lower computational costs of resource overhead (without the assistance of single photons or entangled states), less cross‐Kerr nonlinear interactions between three photons and the coherent states, and reduces the effect caused by photon‐loss noise. The success probabilities of two quantum control gates are approximated unit by performing the corresponding classical feed‐forward operations based on the different measuring outcomes of the X‐homodyne detectors to be aimed at the coherent states, and they are robust against the photon loss as well, which are feasible with the current technology and convenient in practical applications.
Upcycling Models Under Domain and Category Shift

Deep neural networks (DNNs) often perform poorly in the presence of domain shift and category shift. How to upcycle DNNs and adapt them to the target task remains an important open problem. Unsupervised Domain Adaptation (UDA), especially recently proposed Source-free Domain Adaptation (SFDA), has become a promising technology to address this issue. Nevertheless, existing SFDA methods require that the source domain and target domain share the same label space, consequently being only applicable to the vanilla closed-set setting. In this paper, we take one step further and explore the Source-free Universal Domain Adaptation (SF-UniDA). The goal is to identify “known” data samples under both domain and category shift, and reject those “unknown” data samples (not present in source classes), with only the knowledge from standard pre-trained source model. To this end, we introduce an innovative global and local clustering learning technique (GLC). Specifically, we design a novel, adaptive one-vs-all global clustering algorithm to achieve the distinction across different target classes and introduce a local k-NN clustering strategy to alleviate negative transfer. We examine the superiority of our GLC on multiple benchmarks with different category shift scenarios, including partial-set, open-set, and open-partial-set DA. Remarkably, in the most challenging open-partial-set DA scenario, GLC outperforms UMAD by 14.8% on the VisDA benchmark. The code is available at https://github.com/ispc-lab/GLC.
Metaverse in the urban destinations in China: some insights for the tourism players

Purpose Although the metaverse has gained popularity in recent days, research on metaverse tourism in urban destinations is still lacking. Drawing on existing cases in Chinese urban destinations, this paper aims to provide valuable insights into the development of metaverse tourism in China and provides managerial implications for future urbanmetaverse tourismplayers. Design/methodology/approach Literature from Chinese and international sources was reviewed to highlight the current status of metaverse tourism in the context of Chinese urban tourism. This paper also draws on information provided by online materials, especially the official websites of tour organizers and news media. Findings This paper outlines important aspects of metaverse in Chinese urban tourism. First, cities are the hotbeds of metaverse development, and the metaverse has become a new way to attract urban tourists and a significant element in various exhibitions. Second, the combination of metaverse with China’s extensive and profound traditional culture has made urban tourism full of vitality. Third, China’s game companies are progressively empowering the metaverse tourism industry. Originality/value This paper contributes to the existing knowledge on metaverse tourism based on the Chinese urban tourism context. Furthermore, it highlights the state of the metaverse in Chinese urban tourism during and after the pandemic situation. Lastly, it provides thoughtful implications for tourism players and future tourism development.
Deciding What Not to Say: An Attentional-Probabilistic Approach to Argument Presentation

Effective arguments must be presented in a cohesive manner: simple collections of believed premises and connecting inferences supporting a goal may not persuade the recipient if they are not well ordered. We use semantic activation and Bayesian propagation in a user model to simulate the effect of presenting an argument generated by our system, NAG, to the user. This simulation is used to select a strategy for presenting the argument to the user. The simulation also identifies superfluous lines of reasoning that may be removed, and enables NAG to determine how multiple subarguments for points should be presented, e.g., as multiple individual supports or collectively. A greedy algorithm is then used to apply probabilistic pruning and semantic suppression to further simplify the argument. Probabilistic pruning removes unnecessary premises from the argument. Semantic suppression is used to select portions of the argument which are within the user’s focus of attention, and which are also readily inferred, and hence can be left implicit without damaging the effectiveness of the argument.
Adaptively Secure Constrained Pseudorandom Functions

A constrained pseudo random function (PRF) behaves like a standard PRF, but with the added feature that the (master) secret key holder, having secret key K, can produce a constrained key, $$K_f$$ , that allows for the evaluation of the PRF on a subset of the domain as determined by a predicate function f within some family $$\mathcal {F}$$ . While previous constructions gave constrained PRFs for poly-sized circuits, all reductions for such functionality were based in the selective model of security where an attacker declares which point he is attacking before seeing any constrained keys. In this paper we give new constrained PRF constructions for arbitrary circuits in the random oracle model based on indistinguishability obfuscation. Our solution is constructed from two recently emerged primitives: an adaptively secure Attribute-Based Encryption (ABE) for circuits and a Universal Sampler Scheme as introduced by Hofheinz et al. Both primitives are constructible from indistinguishability obfuscation ( $$i\mathcal {O}$$ ) (and injective pseudorandom generators) with only polynomial loss.
Bayesian Nonparametrics for Sparse Dynamic Networks

In this paper we propose a Bayesian nonparametric approach to modelling sparse time-varying networks. A positive parameter is associated to each node of a network, which models the sociability of that node. Sociabilities are assumed to evolve over time, and are modelled via a dynamic point process model. The model is able to capture long term evolution of the sociabilities. Moreover, it yields sparse graphs, where the number of edges grows subquadratically with the number of nodes. The evolution of the sociabilities is described by a tractable time-varying generalised gamma process. We provide some theoretical insights into the model and apply it to three datasets: a simulated network, a network of hyperlinks between communities on Reddit, and a network of co-occurences of words in Reuters news articles after the September $$11^{th}$$ attacks.
Sensing Atoms and Bits

It was Milgram, Takemura, Utsumi, and Kishino who introduced the Virtuality Continuum in 1995 and highlighted that the distinction between real and virtual was increasingly not a hard boundary but one in which both the real and the virtual coexisted. However, in the intervening years our experience of this continuum has increasingly taken place through flat glass screens that primarily addresses our senses of sight and touch. With the emergence of the so called Internet of Things as a global infrastructure of networked physical objects, or ‘things’, that are readable, recognizable, locatable, addressable, and/or controllable via the Internet, designers will be able to consider interactions that can encompass all of our senses relating to the real and the virtual aspects of these objects as they are constructed from both ‘Atoms and Bits’.
Can Musical Machines Be Expressive? Views from the Enlightenment and Today

October 01 2019 Can Musical Machines Be Expressive? Views from the Enlightenment and Today Steven Kemper, Steven Kemper Steven Kemper (educator), Mason Gross School of the Arts, Rutgers University, 81 George Street, New Brunswick, NJ 08901, U.S.A. Email: steven.kemper@rutgers.edu.STEVEN KEMPER is associate professor of music at the Mason Gross School of the Arts at Rutgers University. He is also cofounder of Expressive Machines Musical Instruments. Search for other works by this author on: This Site Google Scholar Rebecca Cypess Rebecca Cypess Rebecca Cypess (educator), Mason Gross School of the Arts, Rutgers University, 81 George Street, New Brunswick, NJ 08901, U.S.A. Email: rebecca.cypess@rutgers.edu.REBECCA CYPESS is associate professor of music at the Mason Gross School of the Arts at Rutgers University. She is the author of Curious and Modern Inventions: Instrumental Music as Discovery in Galileo's Italy (University of Chicago Press, 2016). Search for other works by this author on: This Site Google Scholar Author and Article Information Steven Kemper Steven Kemper (educator), Mason Gross School of the Arts, Rutgers University, 81 George Street, New Brunswick, NJ 08901, U.S.A. Email: steven.kemper@rutgers.edu.STEVEN KEMPER is associate professor of music at the Mason Gross School of the Arts at Rutgers University. He is also cofounder of Expressive Machines Musical Instruments. Rebecca Cypess Rebecca Cypess (educator), Mason Gross School of the Arts, Rutgers University, 81 George Street, New Brunswick, NJ 08901, U.S.A. Email: rebecca.cypess@rutgers.edu.REBECCA CYPESS is associate professor of music at the Mason Gross School of the Arts at Rutgers University. She is the author of Curious and Modern Inventions: Instrumental Music as Discovery in Galileo's Italy (University of Chicago Press, 2016). Received: June 09 2016 Online Issn: 1530-9282 Print Issn: 0024-094X ©2017 ISAST2017ISAST Leonardo (2019) 52 (5): 448–454. https://doi.org/10.1162/leon_a_01477 Article history Received: June 09 2016 Cite Icon Cite Permissions Share Icon Share Twitter LinkedIn Views Icon Views Article contents Figures & tables Video Audio Supplementary Data Search Site Citation Steven Kemper, Rebecca Cypess; Can Musical Machines Be Expressive? Views from the Enlightenment and Today. Leonardo 2019; 52 (5): 448–454. doi: https://doi.org/10.1162/leon_a_01477 Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search nav search search input Search input auto suggest search filter All ContentAll JournalsLeonardo Search Advanced Search This content is only available as a PDF. ©2017 ISAST2017ISAST Article PDF first page preview Close Modal You do not currently have access to this content.
Enhancing metacognitive reinforcement learning using reward structures and feedback

One of the most remarkable aspects of the human mind is its ability to improve itself based on experience. Such learning occurs in a range of domains, from simple stimulus-response mappings, motor skills, and perceptual abilities, to problem-solving, cognitive control, and learning itself. Demonstrations of cognitive and brain plasticity have inspired cognitive training programs. The success of cognitive training has been mixed and the underlying learning mechanisms are not well understood. Feedback is an important component of many effective cognitive training programs, but it remains unclear what makes some feedback structures more effective than others. To address these problems, we model cognitive plasticity as metacognitive reinforcement learning. Here, we develop a metacognitive reinforcement learning model of how people learn how many steps to plan ahead in sequential decision problems, and test its predictions experimentally.The results of our first experiment suggested that our model can discern which reward structures are more conducive to metacognitive learning. This suggests that our model could be used to design feedback structures that make existing environments more conducive to cognitive growth. A follow-up experiment confirmed that feedback structures designed according to our model can indeed accelerate learning to plan. These results suggest that modeling metacognitive learning is a promising step towards building a theoretical foundation for promoting cognitive growth through cognitive training and other interventions.
Algorithm FLARS and recognition of time series anomalies

As a rule, algorithms of recognition of time series anomalies are based on time frequency or statistical analysis . This article is devoted to detailed formal description of new fuzzy set based algorithm FLARS (Fuzzy Logic Algorithm for Recognition of Signals). It recognizes time series anomalies by means «smooth» modelling (in fuzzy mathematics sense) of interpreter’s logic, which searches for anomalies at the record.
An Analysis of Application of Kahoot Games in Teaching English, A Case Study at the Ninth Garde of MTsN Model 1 Pandeglang in Academic Year 2019/2020.

Ika Anggraeni. 152301791. 2019. An Analysis of Application of Kahoot Games in Teaching English, A Case Study at the Ninth Garde of MTsN Model 1 Pandeglang in Academic Year 2019/2020. This research investigated the use kahoot games in teaching English especially vocabulary. This research was to find out whether teaching English by using kahoot games can enhance students’ vocabulary retention. This research used a case study research method. The instrument are used in this research, open-ended questionnaire used to find out the students’ satisfied in learning English espesially vocabulary using kahoot, observation used to find out students’ focus and attention in learning English espesially vocabulary using kahoot, and interview used to find out the effect of using kahoot games application to enhance students’ vocabulary retention. This research involved 25 students at the ninth grade of MTsN Model 1 Pandeglang in academic year 2019/2020. The research finding of the last result showed the students' satisfied in learning English especially vocabulary using kahoot because they feel interesting, fun, and happy. Using kahoot games can enhance their vocabulary retention because learning is easier using it. The class atmosphere is more attractive because the students are completing each other, they enjoy and forget about time. This is also the thing that makes them more focused and gives more attention when learning to use kahoot games. The result of this research shows that learning English using kahoot games can enhance students’ vocabulary retention. Keywords: Kahoot Games, learning English, Students’ Satiesfied, and Vocabulary Retention.
LOCAL CONTENT PROMOTION IN FORMING MALANG CITY PUBLIC LIBRARY LIBARARY'S BRAND EQUITY

Local content is content that is owned by a library with a particular subject, for example the local content of a city or regional public library is a collection of books and non-book libraries that talk about the city or area of the library. But for the Public Library of Malang City, local content is divided into two types, namely collections of authors from Malang and collections that talk about Malang. The local content of Malang City Public Library must be highlighted, one of them is by doing a promotion, to become a differentiator of the public library with other public libraries. This research is a qualitative research with descriptive method. Data retrieval is done by observing and interviewing the librarians of Malang City Public Library and Malang Community.
Emotional Regulation Module Design: The Prevention Againts Child Abuse in Yogyakarta

ABSTRACT This article explains the conceptual framework of an emotional regulation training module designed for parents who commit in act of child abuse in Yogyakarta. In the previous study, 330 parents of early childhood were surveyed in 4 sub-districts in Yogyakarta (Gondomanan, Umbulharjo, Gedongtengen, and Ngampilan) using the closes-ended questionnaire. Data shows 63% of respondents agree that child abuse should not be done and 35% of respondents agree that child abuse can be done only with clear and legal reasons. Surprisingly 98% of respondents reported that they have committed violence to their children physically or non-physically. This phenomena is critical because the parents’ perception about child abuse does not prevent them from committing such behavior. According to the literature review, this condition can be caused by lackness of the emotion regulation of parents. Emotional regulation allows individuals to experience emotional control that initiated from cognitive domain processors that have impact on the affective domain then affects their behavior. A total of 122 parents in the previous study had negative perceptions about their children, namely assuming that they were stubborn children. This condition may negative affections and triggers parents to hurt children. Therefore parents must be able to regulate their emotions to prevent child abuse triggered by anger. Through the results of the research and literature review, we designed an emotional regulation training module for parents who commit in act of child abuse. This emotional regulation training module was developed using Gross (1998) emotional regulation strategies which in five stages that are situation selection, situation modification, attentional deployment, cognitive change, and response modulation. The researcher developed the five stages of the strategy into relevant training activities to increase emotional regulation in parents. The model has been validated by experts and will be trained to parents who commit in child abuse in Yogyakarta. Key Words: emotional regulation, child abuse, parent, early childhood, module
National Investigation Agency Amendment Bill, 2019 - A Critical Analysis

National Investigation Agency is one of the prime and most important investigations of the country. It is a government agency which specializes in the investigating the crimes which fall within the ambit of terrorists activities. In the present scenario the work of this government agency is under question because of various politically motivated decisions that it took. Therefore it becomes very important to analyze the extent of its power.
A facial-expression recognition model using deep learning

Deep neural networks have been recently putting a breakthrough in pattern recognition, machine learning and artificial intelligence. This paper emphasizes a study based on deep learning framework contributing to the field of expression recognition. The proposed model involves a technique using deep for human facial expression recognition. Images are first preprocessed with normalization manipulation to remove illumination and facilitate enhancement using hat-filtering. At that point, a weighted, focus symmetric nearby paired example (CS-LBP) is connected to each face hinder by piece. The CS-LBP pieces are connected to form an element vector of the face picture. The deep network is trained using the layer-wise strategy. We use the CIFAR-10 dataset is used for training and testing. A database of real images is used for testing the algorithms. GUI has been created which compares trained and tested dataset and specifies the type of expression in the command window.
LANGUAGE POLITENESS IN THE CONVERSATION BETWEEN LECTURERS IN WHATSAPP CHATTING GROUP

This study investigates the occurrences of maxims in the conversation between lecturers in “ WhatsApp”. This study applied qualitative research by collecting the data from WhatsApp and the other source which supports to research. Based on the data, it can be found that the lecturers use six maxim proposed by Leech. They use tact, generosity, approbation, modesty, agreement and sympathy maxim. From the six maxims, the lecturers tend to use agreement maxim in conversation. They use Whatsapp as the media for communication in sharing information, discussing or solving the problem related to increasing of university. Finally, the writer concluded that the conversation between lecturers in WhatsApp group can be said “polite”.
The case against the constitutional validity of mass surveillance programmes

In recent years, we have seen a rise in digital technology. In response to the tempestuous nature of technology and its manifold “threats”, the State has adopted fresh armoury. It has inducted mass surveillance programmes, which collect information on every citizen. In India, these measures were adopted in 2007. India’s bulk phone metadata collection programme, equivalent to the National Security Agency is called the Central Monitoring System. Additionally, India has created the Crime and Criminal Tracking and Network System, a nation-wide reposity of criminal data. This paper delves into a constitutional analysis of the validity of these programmes by identifying the key constitutional concerns and reviewing whether these programmes satisfy the test of proportionality. Finally, this paper critiques the ramifications of these measures on democracy. It argues that these measures stifle the exchange of information in the public sphere and reduce public space for reasoning.
Point of Interest Recommendation Based on User's Interest and Geographic Factors

在基于位置的社交网络中,协同过滤作为目前应用最广泛的推荐技术,存在数据稀疏性和冷启动等问题.针对协同过滤算法的不足,提出了一种结合用户兴趣和地理因素的兴趣点推荐算法.该方法首先通过自适应带宽的核密度分布、朴素贝叶斯算法以及兴趣点的流行度挖掘用户的地理偏好,并根据地理偏好模型筛选出一部分候选推荐兴趣点;然后,为了克服协同过滤算法的数据稀疏性问题和用户冷启动问题,结合用户签到相似性、类别信息和用户信任度构建用户偏好模型进行兴趣点推荐;最后,使用Yelp数据集进行实验分析,结果表明所提出的基于用户兴趣和地理因素的兴趣点推荐模型取得了良好的推荐效果.
Cosmology in a simple 2+1 dimension universe

Particle physics and astrophysics tend to get closer to each other about questions associated to the position of gravitation with respect to the other fundamental interactions. That issue, which is indeed the Gordian node of today's physics, is tightly linked with problems such as the nature of dark energy and dark matter, and the possible existence of hidden additional dimensions. In the present paper, whose goal is firstly pedagogical, we will try to present the stakes and a possible way forward, via a simple model easy to visualize and which does not require long and difficult calculations. We first consider relativistic gravitation in a 2 dimension space-time (one space-like, one time-like), then we derive the cosmological consequences, and finally we outline a field theory in a full 2+1 universe (with one extra dimension). The qualitative results obtained in this simple model of universe can easily be transposed in order to better understand our usual 4-dimension space-time.