Reviewerly/exHarmony huggingface dataset:
POIs Category Recommendation for Cultural Country Travel Enterprises Based on Check-In Information

With the ever-increasing popularity of traveling markets, more people are willing to spend their time and enjoy life by visiting some points of interest (POI) especially for the citizens living in cities. Therefore, it is of practical and significant value for travel enterprises to recommend appropriate country POIs to target travelers. However, the massive POIs as well as their diversity place a heavy burden on the POIs recommendation decision making especially when the available historical traveler-POIs check-in data are very sparse. In view of this challenge, the authors put forward a novel cultural country POIs category recommendation method based on historical knowledge and experienced information (e.g., check-in time and POIs category, i.e., CPCR). At last, CPCR method is evaluated via experiments on WS-DREAM dataset.
Immersive Sound Production Using Ambisonics and Advance Audio Practices

It is abundantly clear that across all media platforms 3D immersive sound is critical to the authenticity of high-definition pictures, 360 video, virtual reality and augmented reality. The fact is that multichannel, multi-format audio production is not going away and there should be a commitment by all audio producers and practitioners to advance the quality of audio to the consumer using every tool and practice available.
Few-Shot Content-Level Font Generation

Artistic font design has become an integral part of visual media.However, without prior knowledge of the font domain, it is difficult to create distinct font styles.When the number of characters is limited, this task becomes easier (e.g., only Latin characters).However, designing CJK (Chinese, Japanese, and Korean) characters presents a challenge due to the large number of character sets and complexity of the glyph components in these languages.Numerous studies have been conducted on automating the font design process using generative adversarial networks (GANs).Existing methods rely heavily on reference fonts and perform font style conversions between different fonts.Additionally, rather than capturing style information for a target font via multiple style images, most methods do so via a single font image.In this paper, we propose a network architecture for generating multilingual font sets that makes use of geometric structures as content.Additionally, to acquire sufficient style information, we employ multiple style images belonging to a single font style simultaneously to extract global font style-specific information.By utilizing the geometric structural information of content and a few stylized images, our model can generate an entire font set while maintaining the style.Extensive experiments were conducted to demonstrate the proposed model's superiority over several baseline methods.Additionally, we conducted ablation studies to validate our proposed network architecture.
Cloud Privacy Protection using BlockChain - A Comparative Analysis

This study aims to analyze the determinants of the regional unemployment rates in West Java Province in the period 2010-2019. Due to the diversity of characteristics between regions, this study uses Geographically Weighted Panel Regression (GWPR) analysis. The results showed that all the independent variables used had a significant effect on the regional unemployment rate in West Java. It is recommended that the government encourage efforts to reduce unemployment in their regions by investing more in real sector development, attracting investors in the manufacturing and service sectors, and improving education and skills.
Object recognition based on YOLO v3 network architecture in river patrol scene

With the development of science and technology, the application of artificial neural network and computer vision has become more extensive. Traditional river patrol methods have some inefficiencies and disadvantages in the quality of river patrol. To solve this problem, in this paper, we proposed an approach combined the high-performance YOLO v3 model with the SURF algorithm to detect illegal constructions and behaviors around the river bank. We first take image as the input of YOLO v3 model, then feed the output of YOLO v3 into the SURF algorithm to make a further detection. With this method, we can improve the quality of the river patrol, and enhance the ability to deal with illegal incidents around the river.
Building industrial-education partnerships in acoustics

Strong industry relations can provide many positive impacts for an educational program. The rewards of such an educational-industrial partnership only occur after the hard work of trust-building between the educational provider and the industry partners. A strong partnership requires value generated for both the industrial partner and the educational institution. In this talk, examples will be given of successful and unsuccessful industrial partnerships with academia. The focus will be on educational partnerships, as opposed to industrial research funding. Examples of undergraduate class projects, guest lecturing, professional seminars and webinars, and others will be discussed, in addition to the value streams realized by long time industrial partners.
‘Not-’ Cracker

An item in a verification experiment consists in the presentation of a category name followed by an object. For instance, the name dog could be displayed, followed by the picture of a cat. If the object is not a member of the category-as in the previous example-it is a false item; otherwise, it is a true item. Participants decide, as fast as possible, whether or not the name and the object match; RTs are recorded. To respond to true and false items, one must possess-in one form or another-representations of categories and of their complementary (e.g., not-dog).
Modeling Implicit and Explicit Discovery Learning

This paper describes the theoretical background of an Act-R model of discovery learning in a simulated, conceptual domain: optics. It is assumed that learning in a simulation context consists of both implicit and explicit learning. The Act-R model under development tries to capture both learning types.
Categorization changes object perception

Most models of object recognition assume that shape is the primary dimension of recognition and that color and texture play only a secondary role. One reason for this could be that color and texture are generally less diagnostic for recognition and so it would be comparatively more difficult to find evidence of their usage. Another, but as yet unexplored reason for their secondary role, is that color and texture differences are not as well perceived at short exposures of stimuli. We report two experiments that address the perception (as opposed to the usage) of dimensions over the time course of visual processing.
Acquiring Grammars with Complex Heads: A Model Using Have as a Complex Verb

A thorough account of how grammar is acquired must handle the problem of how learners deal with covert grammatical elements. In particular, there is cross-linguistic evidence that languages contain verbs that are formed by incorporating a silent grammatical element (a head, in GB terms). Assuming this to be a possibility in natural grammar, this paper investigates what type of input would enable a learner to identify a verb with covert head incorporation, and thus to identify a grammar that contains such a verb. I show that such a grammar cannot be learned from input that does not give the locations of empty heads in sentential structure.
Two Heads are Better than One: Causality and Similarity in Misconception Discovery

MMD is an algorithm that learns without supervision intensional definitions of classes of knowledge errors using data (similarity) and theory (causality). Causality can be especially useful when similarity fails to discover certain errors due to their entanglement in complex behaviors, while similarity can be especially useful when no causal relationships for robust co-occurring discrepancies are present in the background knowledge. This paper examines the individual and combined effectiveness of MMD’s similarity and causality components in discovering error classes and classifying behaviors in which these errors occur. Experimental results show how similarity and causality can serve to complement each other in the discovery of novice PROLOG programmer errors.
Adaptive federated learning algorithm based on evolution strategies

Federated learning is a deep learning technique that ensures data privacy with multiple device participation by training a globally shared model while storing private data locally. However, in a complex Internet-of-Things (IoT) environment, federated learning faces challenges of statistical heterogeneity and systematic heterogeneity. Because of different local data distributions and high communication costs, over-parameterized models are unsuited for direct deployment in IoT applications. Moreover, nonindependent, identically distributed data make federated learning with parameter-averaging aggregation more difficult to converge. Determining how to build personalized lightweight models for each client based on individual data and then aggregate these models has become a research problem with regard to federated learning. To solve this problem, we propose an adaptive federated learning algorithm based on an evolution strategy. The method regards each participant as an individual by encoding the model architecture through an evolution strategy, and it can adaptively generate a different customized subnet for each client through global optimization. According to the importance of the network unit and genotype, clients extract the corresponding subnets from the server-side supernets and perform local updates, which naturally fits the idea of the dropout. Extensive experiments on real-world datasets demonstrate that the proposed framework considerably improves the model performance compared with conventional federated learning. In particular, when the local data is not independent and uniformly distributed, the framework facilitates clients with limited communication bandwidths and computing power to participate in federated learning; the generalization ability of the global model is improved.
Tests of Remote Association

Do Remote Associates Test (RAT) problems measure the process of remote association? In the present study a new set of RAT problems was generated, and association norms were determined for each test word, providing an index of the remoteness of the association needed to solve each problem. The observed remoteness of each problem correlated with the difficulty of the problems.
Issues in Comparing Symbolic and Connectionist Models

There has been a heated debate between connectionist and symbolic models on the task of learning the past tense of English verbs. Claims are often made, but not often justified, that a new model has a superior generalization ability to the previous ones. In this paper, we first set up a proper criterion for making comparisons between models. We point out a crucial issue in comparison which has been largely ignored in the past. Then we present results on the generalization ability of the symbolic pattern associator, SPA. We challenge connectionist researchers to design connectionist models with similar or better generalization ability.
Force Dynamics in Language and Cognition: An Empirical Evaluation

“Why?” is often the hardest question to answer, but at the same time it is often the most interesting because its answer reveals causes. Talmy (1988) proposes that language has a force dynamic (FD) system for encoding how we think about causes. A strength of Talmy’s framework is that it explains that our understanding of complex situations by way of simpler situations, and it extends the analysis to cover social situations, approach/avoidance situations, etc. For example, according to the framework, our understanding of the Persian gulf conflict (e.g. Hussein finally agreed to permit inspections to avoid the sanctions.) is based on the same processes as our understanding of sentence (a) in Table 1 below. Table 1 https://www.niso.org/standards/z39-96/ns/oasis-exchange/table"> Examples of the 4 Force Dynamic Types (Talmv 1988. p. 55) tendency win/loss resultant: a) The ball kept rolling because of the wind blowing on it. rest fails moves b) The shed kept standing despite the gale wind blowing against it. rest wins static c) The ball kept rolling despite the stiff grass. action wins moves d) The log kept lying on the incline because of the ridge there. action fails static
Learning of First, Second, and Third Person Pronouns

This paper presents simulation results and network analysis of generative Cascade-Correlation (CC) networks which model the child’s learning of English personal pronouns. The network analysis revealed that overheard speech is crucial in learning the correct semantic rules not only for first and second person pronouns but also for third person pronouns. In addition, in order to induce the fully correct semantic rules without error-correcting feedback, the networks need to learn all three personal pronouns. Network analysis techniques used in the present study proved to be a powerful tool for understanding of what the networks are actually learning.
Contextual Representation of Abstract Nouns: A Neural Network Approach

This paper explores the use of an artificial neural network to investigate the mental representation of abstract noun meanings. Unlike concrete nouns, abstract nouns refer to entities that cannot be pointed to. Cues to their meaning must therefore be in their context of use. It has frequently been shown that the meaning of a word varies with its contexts of use. It is more difficult, however, to identify which elements of context are relevant to a word’s meaning. The present study demonstrates that a connectionist network can be used to examine this problem. A feedforward network learned to distinguish among seven abstract nouns based on characteristics of their verbal contexts in a corpus of randomly selected sentences. The results suggest that, for our sample, the contextual representation of abstract nouns is in principle sufficient to identify and distinguish abstract nouns, and thus meets the functional requirements of concept representation.
Optimization of Robot Path Planning Using Advanced Optimization Techniques

Optimization problems of the robot path panning are very complex. However, due to the complexity of the robot path planning, these problems are difficult to solve with conventional optimization techniques. Therefore, advanced optimization techniques are preferred over conventional optimization techniques for solving the problem of various robot path planning. The purpose of this dissertation is to optimize the path to be traveled by the robot to a specific location (from the origin to the destination) in the constrained area. The path traveled by robot should be collision-free, smooth, and it should not violate any constraint. This dissertation work proposes Jaya, Rao-1, Rao-2, and Rao-3 optimization algorithms for this purpose. The search mechanisms of the Jaya and Rao algorithms are simple and easy to understand. These recently developed optimization algorithms are specific parameter-less. Constrained and unconstrained optimization problems can be solved by these algorithms. Four case studies of robot path planning in a static workspace with static obstacles are presented. The results are compared with those reported by probability and fuzzy logic (PFL), cuckoo search (CS) algorithm, genetic algorithm (GA), firefly algorithm (FA), fuzzy-neural network, algorithm, bacteria foraging optimization (BFO), ant colony optimization (ACO), and particle swarm optimization (PSO). A computer program is developed in MATLAB 2015 environment for robot path planning. Good improvements are observed in the total path length of travel by the robot without collision with the obstacles using Jaya, Rao-1, Rao-2, and Rao-3 algorithms. The total time required for the simulation of experiments is also found comparatively less using these algorithms.
THE ROLE OF ENGLISH EDUCATION TOWARDS STUDENT’S MORALS (At State Vocational High Schools 1 Karawang)

This research is useful for: a. State School 1 Karawang in knowing how much influence English Education in shaping the morals of students in SMK Negeri 1 Karawang. b. The results of this study can be used as information for educators in applying and knowing what factors are the biggest influence on the moral behavior of students in SMK Negeri 1 Karawang. c. As an evaluation material specifically for schools that carry out the learning process by teachers, and schools can monitor the morals of their students so that they are of good character.&#x0D; &#x0D; Keywords: English Education, Roles, Morals
ANALISIS JARINGAN SYARAF TIRUAN METODE BACKPROPOGATION DALAM MEMPREDIKSI KETERSEDIAAN KOMODITAS BERAS BERDASARKAN PROVINSI DI INDONESIA

Food is a major human need that must be completed at any time. This right is one of human rights, stated in article 27 of the 1945 Constitution and in the Rome Declaration (1996). These considerations underlie the issuance of Law No. 7/1996 concerning Food. With these considerations, the Government always considers increasing food security related to increasing domestic production. This research is expected to contribute to the government in order to predict the contribution of rice by province in Indonesia. The data used is data from the National Statistics Agency through the website www.bps.go.id. The data is data on rice / rice production based on provinces in Indonesia in the period of 2010 to 2015. The algorithm used in this study is Artificial Neural Networks with the Backpropagation method. The input (input) variables used are data for 2010 (X1), data for 2011 (X2), data for 2012 (X3), data for 2013 (X4), data for 2014 (X5) and data for 2015 as targets with models training and testing architecture of 4 architectures namely 4-4-1, 4-8-1, 4-16-1, 4-32-1. The resulting output is the best pattern of ANN architecture. The best architectural model is 4-4-1 with 218 days, MSE 0.012728078 and an accuracy rate of 97%. From this model obtained from estimates obtained from provinces in Indonesia.
Faculty Employment Conditions

Higher Education AbstractsVolume 55, Issue 2 p. 141-142 FACULTY EMPLOYMENT CONDITIONS Faculty Employment Conditions First published: 28 April 2020 https://doi.org/10.1111/hea.16_12146Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat No abstract is available for this article. Volume55, Issue2April 2020Pages 141-142 RelatedInformation
Software Defined Cloud Mini Data Centers – An Effort towards Reduction in Latency of Cloud Traffic Delivery

In demand to growing traffic of cloud and other web services the vendors are offering several alternatives for timely delivering the traffic. The paper is aims to amass reasons and complexity of delays in regard to end to end delivery of cloud traffic. It further focuses on existing solutions its limitations. The findings of the varying latency suggest that most of the delays are cause due to distance covered by the packet throughout its journey. Hence our solution suggests Software Defined Mini cloud data (SDCmDC) centers distributed throughout the world at different geographical areas instead of having a centralized mega data centers. These mini data centers will be interconnected to each other and carrying data local to their geographical location
An Extensive Discussion on Transition of Libraries

The library and information services have witnessed transition due to conceptual, technological and users' needs. The recent developments in the educational organizations and the users' needs have found few technological factors to consider changing trends. The chapter has discussed various aspects such as services, their composition, alterations and role in library's position in the academic community. The library staff and gradual developments have been discussed along with the infrastructural strengths in library. The facets such as educating the users through the information literacy and metaliteracy; Electronic Information Resources Collection, Building and Management and Creation of Web presence among Library Users are highlighted. Digital Information Services and waving the freshness of innovation; Creating Awareness by being among the users and enhancing learning and need of “Innovation and serving the users at individual level” have been discussed in the context of role in research support.
The Impact of Mobile Communication on E-Voting Technology

Various end-customers would agree that, had it not been for scramble/collect I/O, the examination of courseware may never have occurred. In this position paper, we show the frustrating unification of superpages and obstruct control, which epitomizes the sorted out norms of e-casting a ballot development. In this position paper we assemble a permutable contraption for evaluating abundance (Tower), which we use to confirm that IPv7 and different leveled databases can take an interest to achieve this mission.
ATENÇÃO À SAÚDE E QUALIDADE DE VIDA DE PROFESSORES EM ENSINO REMOTO: RELATO DE EXPERIÊNCIA

Teaching is amongst the most health damaging professions. The sudden transition to remote learning during the Covid19 pandemic contributed to an increase in these symptoms, reducing the quality of life and well-being of this population. Taking that into consideration, the aim of this study is to report the experience of the extension project of Health Care for Teachers in Remote Teaching, carried out by QualiMack - Quality of Life and Health at Work Program, of the Center for Biological and Health Sciences of the Mackenzie Presbyterian University. Remote meetings were held based on Health Education, which consisted of 08 meetings for Guidance Groups and 12 for Relaxation Activities. Some material summarizing the main content of the activities proposed was created and disseminated with the purpose of self-instructional reinforcement. A hundred and seventy-six professors from the host institution and 113 from other institutions participated. The strategies increased the participants' health repertoire and contributed to the training and improvement of the team in multidisciplinary work and interaction with the community. &nbsp
Supplemental Material: Dendritic reidite from the Chesapeake Bay impact horizon, Ocean Drilling Program Site 1073 (offshore northeastern USA): A fingerprint of distal ejecta?

Additional information on the sample analyzed, EBSD data (Figures S1 and S2), and methods.&lt;br&gt;
MAKER: Designing and Building the Classical Inverted Pendulum on a Cart

This paper describes the design and build of a pedagogical setup consisting of a two-DOF inverted pendulum, which is mounted on a three-DOF cart.This was a collaborative project between senior students in the departments of mechanical and electrical engineering at the United Arab Emirates University as part of their senior design capstone project.The students with guidance from their faculty mentors followed the various designing and building stages of the design process of the involved mechatronics system.This includes the steps of designing the setup, the building of the prototype, and the testing and verification of the prototype's subsystems.