Reviewerly/exHarmony huggingface dataset:
CapsHash: Deep Supervised Hashing with Capsule Network

To better deal with large-scale image retrieval problem, deep hashing models based on convolutional neural network (CNN) have been widely used as effective methods, which can map similar images to compact binary hash codes with smaller hamming distance. Despite their positive results, CNN-based methods have few limitations, which are unable to understand the spatial relationship between features. To overcome this challenge, in this paper, a novel deep supervised hashing method was proposed based on capsule networks. Our method, referred to as CapsHash, can learn discriminative hash codes and capsule vectors at the same time. Moreover, we introduce a novel compound loss function that has two parts: classification hashing loss and margin loss. This compound loss function can greatly improve the discriminative ability of binary codes and further improve the image retrieval performance. Extensive experiments under different scenarios demonstrate that our CapsHash method can preserve the instance-level similarity and outperform previous state-of-the-art hashing approaches. To the best of our knowledge, CapsHash is the first method about the application of capsule networks in the deep supervised hashing domain.
A Biscriptual Morphological Transducer for Crimean Tatar

This paper describes a weighted finite-state morphological transducer for Crimean Tatar able to analyse and generate in both Latin and Cyrillic orthographies. This transducer was developed by a team including a community member and language expert, a field linguist who works with the community, a Turkologist with computational linguistics expertise, and an experienced computational linguist with Turkic expertise. Dealing with two orthographic systems in the same transducer is challenging as they employ different strategies to deal with the spelling of loan words and encode the full range of the language's phonemes and their interaction. We develop the core transducer using the Latin orthography and then design a separate transliteration transducer to map the surface forms to Cyrillic. To help control the non-determinism in the orthographic mapping, we use weights to prioritise forms seen in the corpus. We perform an evaluation of all components of the system, finding an accuracy above 90% for morphological analysis and near 90% for orthographic conversion. This comprises the state of the art for Crimean Tatar morphological modelling, and, to our knowledge, is the first biscriptual single morphological transducer for any language.
Pengembangan Media Pembelajaran Berbasis Role Playing Game (RPG) Untuk Siswa Kelas X SMK Negeri 3 Yogyakarta

The purpose of this study is to develop a game like learning media program about resistor’s color code reading and simple resistor circuits made in RPG Maker MV game engine for grade X vocational school student. The developed learning media includes: learning media program, student workbook, and a complementary module book. The method of research and development is used in this study. Descriptive analysis was used on the feasibility analysis of learning media. Result of experts and users test validation stated that the developed learning media is in the feasible category based on all validated and tested aspects. First educational expert’s assessment shows feasibility level of 93.04% (Very Feasible). Second educational expert’s assessment shows feasibility level of 72.17% (Feasible). First media expert’s assessment shows feasibility level of 86.65% (Very Feasible). Second media expert’s assessment shows feasibility level of 89.29% (Very Feasible). User trial assessment shows feasibility level of 78.52% (Feasible)
Statistics of Individual Tests for Market Graph Identification in Market Network

The concept of random variables network used to model the complex system of random nature is discussed.The problem of threshold graph identification to network analysis of the complex system is considered as multiple decision statistical procedure.The properties of robustness of different tests for testing individual hypotheses for threshold graph identification are investigated by simulations.Index Terms-random
Generating Quantified Referring Expressions with Perceptual Cost Pruning

We model the production of quantified referring expressions (QREs) that identify collections of visual items.To address this task, we propose a method of perceptual cost pruning, which consists of two steps: (1) determine what subset of quantity information can be perceived given a time limit t, and (2) apply a preference order based REG algorithm, such as the Incremental Algorithm (IA), to this reduced set of information.We demonstrate that this method successfully improves the human-likeness of the IA in the QRE generation task by successfully modeling humangenerated language in most cases.
R-grams: Unsupervised Learning of Semantic Units in Natural Language

This paper investigates data-driven segmentation using Re-Pair or Byte Pair Encoding-techniques. In contrast to previous work which has primarily been focused on subword units for machine translation, we are interested in the general properties of such segments above the word level. We call these segments r-grams, and discuss their properties and the effect they have on the token frequency distribution. The proposed approach is evaluated by demonstrating its viability in embedding techniques, both in monolingual and multilingual test settings. We also provide a number of qualitative examples of the proposed methodology, demonstrating its viability as a language-invariant segmentation procedure.
Analisis Sistem Informasi CRM Untuk Meningkatkan Pelayanan dengan Pendekatan SDLC (Studi Kasus: UMKM “SAKTI”)

The development of information technology is endless. Every day there is something new that we can find outside. Will affect many sectors. One of the fastest growing is UMKM. Screen printing and convection is one of the UMKM that produces and sells plain shirts and screen printing. To improve its services, screen printing and convection information systems need to be developed so that the service is more optimal, effective and efficient. Customer Relationship Management (CRM) is a core business strategy that can support, obtain and retain customers. Based on the results of the needs analysis and system analysis of the company that can be known about the CRM modules needed for the system are Customer Service and Support (CSS) and Entreprise Marketing Automation (EMA).
How to Keep Your Secrets in a Post-Quantum World

Cryptography is the science of keeping secrets.But it is more than that.It is now a flourishing branch of mathematics that, in addition to encryption, also provides other tools to protect security and privacy of individuals, enterprises, data, systems, and transactions.Cryptographic protocols enable us, for example, to create secure communication channels, to guarantee the confidentiality and integrity of messages and data, to authenticate the identity of the sender of a message or the endpoint in a transaction.Cryptography is the foundation of secure e-commerce in the world today, providing the trustworthy systems that allow enterprises and consumers to transact business online.Digital signatures and key exchange are two important building blocks for public-key cryptography, in addition to encryption.Cryptographic systems are often built on the premise that certain math problems are very hard to solve, in the sense that known solutions require enormous computational time and resources.Many of these problems, such as factoring certain types of large numbers, have been studied by mathematicians for many decades.In fact, mathematicians often estimate the projected security of cryptographic systems by plotting the evolution in "running time" and "space requirements" of the best-known attacks.These predictions work well, but only in the absence of major disruptions: new algorithms or technologies that drastically improve the expected running time of attacks.
A fókuszált lézernyaláb keresztmetszeti jellemzőinek szerepe az impulzusos üzemű lézeres vágásnál

In this article investigation of the roles of two important factors of focused laser beam, the focal spot diameter and the Rayleigh length as determining variables of the beam quality were analysed.The equations of these two factors are based on those most commonly used in the literature.The exchange between three different beam quality numbers were shown.It is proven on the basis of the scientific literature, that the beam quality degrades compared to the original data given by the factory of laser.The causes of the beam quality degradation are lens aberrations in the optical path of the given laser, and the shifting of the beam propagation ratio (M 2 ) to higher values.A new equation for estimation of the new, lowest value for M 2 factor is presented, based on the comparison of the laser cut material thickness to the depth of focus, which is two times the Rayleigh length.
An Implementation of Support Vector Machine on the Multi-Label Classification of English-Translated Quranic Verses

One of the attempts to understand the meaning and content of the Quran, the central religious text of Islam, is the topic classification of Quranic verses.Verse topic classification aims to help the reader, so he can easily and quickly find information or knowledge contained in the Quran.In this paper, we build a classification model for the topics of English-translated Quranic verses using Support Vector Machine (SVM).The problem of classification of topics of Quranic verses is categorized as a multi-label classification problem.Hence, we design an SVM-based classifier to solve the multi-label classification of topics of Quranic verses.We also implement several techniques such as preprocessing, feature extraction, and dimensionality reduction to solve this problem.Then, we use Hamming Loss as a performance measure to evaluate our proposed classifier model.We find that our proposed model yields outstanding results.
DETERMINING THE ECONOMIC EFFICIENCY OF INVESTMENTS IN INNOVATIVE PRODUCTS, TAKING INTO ACCOUNT THE CHARACTERISTICS OF INVESTMENT

The process of transition to the digital economy is intensifying the innovative activity of enterprises in all sectors.Creating an innovative product requires significant capital expenditures, and to predict the result is a difficult task.Innovative activities are usually characterized by increased risks that must be considered.These and many other features of innovation require further study, despite the significant scientific groundwork on innovative issues.Determining the economic efficiency of investments in innovative products, taking into account the characteristics of investment, is the goal of this article.
Towards the next phase of the Journal of Numerical Cognition

Towards the Next Phase of the Journal of Numerical Cognition Authors Wim Fias Ghent University, Ghent, Belgium Abstract No abstract available. PDF HTML XML Article info Impact Citations How to Cite License Published at 20. December 2019 https://doi.org/10.5964/jnc.v5i3.272 Issue: Vol. 5 No. 3 (2019) Section: Editorial Share: Z Fias, W. (2019). Towards the Next Phase of the Journal of Numerical Cognition. Journal of Numerical Cognition, 5(3), 260-261. https://doi.org/10.5964/jnc.v5i3.272 More Citation Formats ACM ACS APA ABNT Chicago Harvard IEEE MLA Turabian Vancouver Download Citation Endnote/Zotero/Mendeley (RIS) BibTeX This work is licensed under a Creative Commons Attribution (CC BY) 4.0 International License. PlumX Dimensions Views: Total Abstract PDF HTML XML 353 142 122 59 30
Connecting Users to Articles: An Analysis of the Impact of Article Level Linking on Journal Use Statistics

Abstract&#x0D; Objective – Electronic resource management challenges and “big deal” cancellations at one Canadian university library contributed to a situation where a number of electronic journal subscriptions at the university’s health sciences library lacked article level linking. The aim of this study was to compare the usage of journals with article level linking enabled to journals where only journal level linking was available or enabled.&#x0D; Methods – A list of electronic journal title subscriptions was generated from vendor and subscription agent invoices. Journal titles were eligible for inclusion if the subscription was available throughout 2018 on the publisher’s platform, if the subscription costs were fully funded by the health sciences library, and if management of the subscription required title-by-title intervention by library staff. Of the 356 journal titles considered, 302 were included in the study. Negative binomial regression was performed to determine the effect of journal vs. article level linking on total COUNTER Journal Report 1 (JR1) successful full-text article requests for 2018, controlling for journal publisher, subject area, journal ranking, and alternate aggregator access.&#x0D; Results – The negative binomial regression model demonstrated that article level linking had a significant, positive effect on total 2018 JR1 (coef: 0.645; p &lt; 0.001). Article level linking increased the expected total JR1 by 90.7% when compared to journals where article level linking was not available or enabled. Differences in predicted usage between journals with article level linking and those without article level linking remained significant at various journal ranking levels. This suggests that usage of both smaller, more specialized journals (e.g., Journal of Vascular Research) and larger, general journals (e.g., New England Journal of Medicine) increases when article level linking is enabled.&#x0D; Conclusions – This study provides statistical evidence that enabling article level linking has a positive impact on journal usage at one academic health sciences library. Although further study is needed, academic libraries should consider enabling article level linking wherever possible in order to facilitate user access, maximize the value of journal subscriptions, and improve convenience for users.
Expectations and Experiences of Technology-Rich Classrooms of Preservice and In-service Teachers in China

Technology-Rich Classrooms (TRCs) have been increasingly constructed in K12 schools. Existing studies revealed that to what extent TRCs play a role in shaping teaching and learning depends on what teachers expect to do and what they do with TRCs. This study aimed at exploring the gap between teachers’ experiences of existing TRCs and their expectations of ideal TRCs. A total of 194 preservice teachers studying at Beijing Normal University (BNU) and 149 in-service teachers who enrolled in a master program at BNU participated in the study. The Smart Classroom Inventory (SCI) a ten-component inventory revised from the previous study, was used to collect the data. Independent-samples t-tests and paired-samples t-tests revealed that: (a) both preservice teachers and in-service teachers reported significantly lower experiences of TRCs than their expectations of ideal ones in terms of most dimensions, with the only exception that preservice teachers’ Technology usage. (b) Whether in existing TRCs, or in ideal ones, both preservice teachers and in-service teachers reported relative lower scores of Flexibility, Learning data, Differentiation, Investigation, and Cooperation than other dimensions. (c) Preservice teachers reported significantly higher scores of Flexibility, Technology usage, Learning data, Differentiation, Investigation, and Cooperation than in-service teachers, while in-service teachers reported significantly higher scores of Physical design, Student Cohesiveness, Equity, and Learning experiences than preservice teachers.4) Preservice teachers reported significantly higher expectation of ideal Physical design, Differentiation than in-service teachers, while they reported significantly lower expectations of ideal Flexibility, Student Cohesiveness, Equity, and Learning experience than in-service teachers. Implications for preservice teachers’ education and in-service teachers’ professional development were discussed.
Query-Sensitive Graph Partitioner for Pattern Matching Applications

Searching and mining in large graphs is critical to a variety of applications, at the core of which is the pattern matching activity. The scalable processing of large graphs requires careful distribution of graphs across clusters. Graph partitioning is the technique that divides a big graph into several non-overlapped subgraphs and assigns each subgraph to a compute node. Traditional workload agnostic partitioners aim to minimize the number of inter-partition edges using only graph topology, which, however, may not obtain the best solution if the workload exhibits skew. Some workload-aware partitioners choose to mine information from a specific workload and use it to minimize the number of inter-partition traversals during execution; however, their methods are not suitable for pattern matching applications. In this work, we propose a query-sensitive graph partitioner that aims to improve existing partitioning for a given pattern matching workload. The partitioner takes any initial partitioning as a starting point and iteratively adjusts it by exchanging chosen clusters across partitions, heuristically reducing the probability of inter-partition traversals. We determine a few implementation-irrelative factors that may increase the traversal probability of an edge and quantify them into a calculable indicator with information from query patterns and graph topology. Then, we propose an efficient algorithm to calculate the indicator and implement a graph repartitioner by combining the indicator with a greedy cluster-exchanging mechanism. Finally, we generate a large heterogeneous labeled graph with real-world data crawled from the Netease Music website and evaluate the partitioning quality of our repartitioner with a few meaningful query patterns of common topologies including line, loop and branching. Compared with a hash-based partitioning, our system can reduce the inter-partition traversals by at least 70%. Compared with the state-of-the-art graph partitioner Metis, our repartitioner can reduce the inter-partition traversals by at least 50%.
Improving Object Detection with Consistent Negative Sample Mining

In object detection, training samples are divided into negatives and positives simply according to their initial positions on images. Samples which have low overlap with ground-truths are assigned to negatives, and positives otherwise. Once allocated, the negative and positive set are fixed in training. A usually overlooked issue is that certain negatives do not stick to their original states as training proceeds. They gradually regress towards foreground objects rather than away from them, which contradicts the nature of negatives. Training with such inconsistent negatives may confuse detectors in distinguishing between foreground and background, and thus makes training less effective. In this paper, we propose a consistent negative sample mining method to filter out biased negatives in training. Specifically, the neural network takes the regression performance into account, and dynamically activates consistent negatives which have both low input IoUs and low output IoUs for training. In the experiments, we evaluate our method on PASCAL VOC and KITTI datasets, and the improvements on both datasets demonstrate the effectiveness of our method.
Self-Actualization in Main Character’s Life Journey in "The Bell Jar"

Self-actualization is term that is commonly used in psychology theories. The term can be simply translated as the full realization of someone’s potential or true self. This study was conducted to analyze the life journey of the main character of The Bell Jar in achieving herself-actualization. The purposes of this study are to describe the character of the main character in The Bell Jar and to describe the main character in achieving self-actualization and how it is portrayed in the novel. This study was done using a descriptive qualitative method and using Maslow's Hierarchy of Human Needs theory and New Criticism theory to explain the main character and her journey in achieving self-actualization in the form of words. The object of the study was the novel The Bell Jar and this study focused on Esther Greenwood as the main character. List of an observational sheet was used as the research instrument and the data was taken through library research. The analysis was conducted by interpreting Esther’s utterances and actions using New Criticism theory to describe Esther’s characterization and Maslow’s Hierarchy of Human Needs theory to describe Esther’s self-actualization. The study results showed that Esther’s self-actualization is the results of her being able to fulfill her previous stages both directly and indirectly before reaching self-actualization stage along her life journey.&#x0D; Keywords: Characterization, Hierarchy of Human Needs, Life Journey, New Criticism, Self-actualization
Towards Cross-browser Incompatibilities Detection: Asystematic Literature Review

The term Cross Browser Incompatibilities (XBI) stands for compatibility issues which can be observed while rendering a web application in different browsers, such as: Microsoft Edge, Mozilla Firefox, Google Chrome, among others.In order to detect Cross-Browser Incompatibilities -XBIs, Web developers rely on manual inspection of every web page of their applications, rendering them in various configuration environments (considering multiple OS platforms and browser versions).These manual inspections are error-prone and increase the cost of the Web engineering process.This paper has the goal of identify-ing techniques for automatic XBI detection, conducting a Systematic Literature Review (SLR) with focus on studies which report XBI automatic detection strategies.The selected studies were compared accord-ing to the different technological solutions they implemented and were used to elaborate a XBI detection framework which can organize and classify the state-of-the-art techniques and may be used to guide future research activities about this topic.
5G Technology Analysis in Relation to Electromagnetic Waves

Electromagnetic waves are present in most of the main equipment used by humans. The advancement of 5G mobile network technology has been gaining ground in the telecommunications market and with it both positive and potentially negative consequences as it is used. Fundamental research has been conducted to gain knowledge and familiarity with 5G technology, how it works and its millimeter waves, which is a new range of the electromagnetic spectrum, which works with this new very high frequency and the first time used in technology. mobile network, as well as exploratory research through techniques such as bibliographic surveys in search of data such as frequency, related to 5G and the equipment transmitting electromagnetic waves, and conducting a comparative study to determine through the data collected from both , pointing out studies that present the evils that may cause the human being due to the use of high frequency. According to the results obtained on the 5G, the use of mobile network frequency presents no risks compared to other equipment that humans have been using. Therefore, despite the research results, it is still too early to point out possible damage over the years with the use of this technology, not ruling out possible consequences.
The use of innovative technologies to enhance educational and cognitive activities in the process of teaching physics

This article discusses the use of information technology in the training of students of the discipline "Physics".Particular attention is paid to the benefits of using information and communication technologies.