Reviewerly/exHarmony huggingface dataset:
SegAttnGAN: Text to Image Generation with Segmentation Attention

In this paper, we propose a novel generative network (SegAttnGAN) that utilizes additional segmentation information for the text-to-image synthesis task. As the segmentation data introduced to the model provides useful guidance on the generator training, the proposed model can generate images with better realism quality and higher quantitative measures compared with the previous state-of-art methods. We achieved Inception Score of 4.84 on the CUB dataset and 3.52 on the Oxford-102 dataset. Besides, we tested the self-attention SegAttnGAN which uses generated segmentation data instead of masks from datasets for attention and achieved similar high-quality results, suggesting that our model can be adapted for the text-to-image synthesis task.
Non-Markovian quantum dynamics: Extended correlated projection superoperators

The correlated projection superoperator techniques provide a better understanding about how correlations lead to strong non-Markovian effects in open quantum systems. Their superoperators are independent of initial state, which may not be suitable for some cases. To improve this, we develop another approach, that is extending the composite system before use the correlated projection superoperator techniques. Such an approach allows the choice of different superoperators for different initial states. We apply these techniques to a simple model to illustrate the general approach. The numerical simulations of the full Schrödinger equation of the model reveal the power and efficiency of the method.
Super-BPD: Super Boundary-to-Pixel Direction for Fast Image Segmentation

Image segmentation is a fundamental vision task and a crucial step for many applications. In this paper, we propose a fast image segmentation method based on a novel super boundary-to-pixel direction (super-BPD) and a customized segmentation algorithm with super-BPD. Precisely, we define BPD on each pixel as a two-dimensional unit vector pointing from its nearest boundary to the pixel. In the BPD, nearby pixels from different regions have opposite directions departing from each other, and adjacent pixels in the same region have directions pointing to the other or each other (i.e., around medial points). We make use of such property to partition an image into super-BPDs, which are novel informative superpixels with robust direction similarity for fast grouping into segmentation regions. Extensive experimental results on BSDS500 and Pascal Context demonstrate the accuracy and efficency of the proposed super-BPD in segmenting images. In practice, the proposed super-BPD achieves comparable or superior performance with MCG while running at ~25fps vs. 0.07fps. Super-BPD also exhibits a noteworthy transferability to unseen scenes. The code is publicly available at https://github.com/JianqiangWan/Super-BPD.
Pendampingan Guru Sains SD Melalui Pelatihan Pembuatan Media Pop-up Book Untuk Meningkatkan Literasi Baca Tulis.

The demands of the development are increasingly advanced with the era of the industrial revolution 4.0, of course, requires teachers to be proficient in mastering teacher competencies, not least in the use of learning media. But in the learning process there is still a lack of learning media. In addition to the implementation of the 2013 curriculum, teachers are still limited in the preparation of administration and learning devices only. In the implementation of the learning process there are still many teachers who use the expository learning model. This is due to the low level of knowledge of SD Negeri Meteseh teachers in making innovations and learning media that implement scientific approaches. The low knowledge of teachers about learning media innovations has the effect of less motivated students in the learning process, especially 3-dimensional learning media. For this reason, the proposing team provided a solution in solving these problems, namely by planning a training program for the teachers of SD Negeri Meteseh in making Learning Media. Learning media in the form of Pop Up Book for elementary school teachers. The result of this activity is that most teachers have never received pop up book learning media training. The teachers gave a positive response to the activities carried out. Teacher creativity in making learning media in the form of pop-up books increases. With the pop-up book the teacher can provide real concepts in the form of 3D images to students at the elementary level. In addition, basic literacy especially in reading skills of elementary students also increases..
From Web Crawl to Clean Register-Annotated Corpora

The web presents unprecedented opportunities for large-scale collection of text in many languages. However, two critical steps in the development of web corpora remain challenging: the identification of clean text from source HTML and the assignment of genre or register information to the documents. In this paper, we evaluate a multilingual approach to this end. Our starting points are the Swedish and French Common Crawl datasets gathered for the 2017 CoNLL shared task, particularly the URLs. We 1) fetch HTML pages based on the URLs and run boilerplate removal, 2) train a classifier to further clean out undesired text fragments, and 3) annotate text registers. We compare boilerplate removal against the CoNLL texts, and find an improvement. For the further cleaning of undesired material, the best results are achieved using Multilingual BERT with monolingual fine-tuning. However, our results are promising also in a cross-lingual setting, without fine-tuning on the target language. Finally, the register annotations show that most of the documents belong to a relatively small set of registers, which are relatively similar in the two languages. A number of additional flags in the annotation are, however, necessary to reflect the wide range of linguistic variation associated with the documents.
Envisioning Jewish HCI

The invisible norms of Christian culture - which includes religious, secular, and atheist Christianity - are hard for those raised within that culture to see. This paper asks what it might look like to design human-computer interactions from outside Christian hegemony. It shares concepts from Jewish thought that can serve as exemplars for innovation in design: elu v'elu, tzedakah, the eishet chayil, and ma'alin bakodesh. This work seeks to inspire others to resist Christian hegemony in their research and system design.
Toward On-Demand Generation of Entangled Photon Pairs with a Quantum Dot

The generation of on-demand, optimally entangled photon pairs remains one of the most formidable challenges in the quantum optics and quantum information community. Despite the fact that recent developments in this area have opened new doors leading toward the realization of sources exhibiting either high brightness or near-unity entanglement fidelity, the challenges to achieve both together persist. Here, we will provide a historical review on the development of quantum dots (QDs) for entangled photon generation, with a focus on nanowire QDs, and address the latest research performed on nanowire QDs, including measuring entanglement fidelity, light-extraction efficiency, dephasing mechanisms, and the detrimental effects of detection systems on the measured values of entanglement fidelity. Additionally, we will discuss results recently observed pertaining to resonant excitation of a nanowire QD, revealing the potential of such sources to outperform spontaneous parametric down-conversion (SPDC) sources, providing a viable solution to the current challenges in quantum optics and quantum information.
Generation and distribution of atomic entanglement in coupled-cavity arrays

We study the dynamics of entanglement in a one-dimensional coupled-cavity array, with each cavity containing a two-level atom, via the Jaynes-Cummings-Hubbard (JCH) Hamiltonian in the single-excitation sector. The model features a rich variety of dynamical regimes that can be harnessed for entanglement control. The protocol is based on setting an excited atom above the ground state and further letting it evolve following the natural dynamics of the Hamiltonian. Here we focus on the concurrence between pairs of atoms and its relation to atom-field correlations and the involved free-field modes. We show that the extension and distribution pattern of pairwise entanglement can be manipulated through a judicious tuning of the atom-cavity coupling strength. By also including static noise in the cavity frequencies, we explore the onset of Anderson localization and its interplay with the atomic trapping known to take place in the strong-hopping regime. Remarkably, we find that the stronger the disorder is, the higher are the atom-field correlations, whereas the atomic concurrence responds nonmonotonically. Overall, our work offers a comprehensive account of the machinery of the single-excitation JCH Hamiltonian and contributes to the design of hybrid light-matter quantum networks.
An Efficient Image Quality Enhancement using Wavelet Transform

Now a days the internet usage is very high. Similarly, the electronic gadgets like mobile, smart phones etc. usage are very high. Images are sent from one device to other device through internet and the receiver gets the image with poor quality due to high compression rates. Large amount of bandwidth is used for transmitting unstructured data such as images and other files. This large bandwidth usage tends to become a burden for the network and slow down the process. So the optimization takes place. In order to enhance the quality of the image and also reduce the transmission of bandwidth size, a novel image compression technique is proposed in this project. Discrete Wavelet transform is used for image processing and it is planned to use MATLAB. This method provides a compression ratio up to 65% and a PSNR value up to 21.73db.
ANÁLISE GEOFÍSICA DA REGIÃO DO RIO CONCEIÇÃO, QUADRILÁTERO FERRÍFERO, ASSOCIADOS A DADOS DE CAMPO, PETROGRÁFICOS E DE IMAGENS AÉREAS

The Quadrilátero Ferrífero region, located in the southeast portion of the São Francisco Craton, is one of the main metallogenic provinces in Brazil. Fieldwork, petrography, high-resolution airborne geophysics (magnetic and gamma-ray spectrometry data), and aerial images allowed us to produce a new map at the 1:25,000 scale, with important contributions in the lithotypes detailing, understanding of the geological structures and relationship between the different stratigraphic units. Interpretation of airborne geophysical data integrated with field structural and lithological observations were successfully employed in the creation of the litho-structural framework in a poorly exposed Proterozoic and Archean terrain. Airborne gamma-ray spectrometry data aided in the mapping process in areas with regolith cover including erosional ridges. The magnetic total derivative image revealed regional and local structures. In addition, our work details the units of occurrence of Rio das Velhas and Minas Supergroup. The aerial coverage of the Mindá and Santa Quitéria formations strongly increased, as well as the area of the Cauê Formation was better defined. The new geological map provides many improvements over the pre-existing maps. New lithological facies and structures were identified and others become more visible and lithologicalboundaries are refined or confirmed.
Longest Square Subsequence Problem Revisited

The longest square subsequence (LSS) problem consists of computing a longest subsequence of a given string $S$ that is a square, i.e., a longest subsequence of form $XX$ appearing in $S$. It is known that an LSS of a string $S$ of length $n$ can be computed using $O(n^2)$ time [Kosowski 2004], or with (model-dependent) polylogarithmic speed-ups using $O(n^2 (\log \log n)^2 / \log^2 n)$ time [Tiskin 2013]. We present the first algorithm for LSS whose running time depends on other parameters, i.e., we show that an LSS of $S$ can be computed in $O(r \min\{n, M\}\log \frac{n}{r} + n + M \log n)$ time with $O(M)$ space, where $r$ is the length of an LSS of $S$ and $M$ is the number of matching points on $S$.
&lt;strong&gt;Online Sequential Extreme Learning Machine: A New Training Scheme for Restricted Boltzmann Machines&lt;/strong&gt;

Abstract: The main contribution of this paper is to introduce a new iterative training algorithm for restricted Boltzmann machines. The proposed learning path is inspired from online sequential extreme learning machine one of extreme learning machine variants which deals with time accumulated sequences of data with fixed or varied sizes. Recursive least squares rules are integrated for weights adaptation to avoid learning rate tuning and local minimum issues. The proposed approach is compared to one of the well known training algorithms for Boltzmann machines named &amp;ldquo;contrastive divergence&amp;rdquo;, in term of time, accuracy and algorithmic complexity under the same conditions. Results strongly encourage the new given rules during data reconstruction.
UnionPay Payment Scheme Based on Controlled Quantum Teleportation

We propose a UnionPay payment scheme based on controlled quantum teleportation in which the whole process is realized through correlation of the three-particle entangled state, controlled quantum teleportation, and the physical property of quantum mechanics. Combined with some typical quantum key distribution protocols, the proposed UnionPay payment scheme with unconditional security (information theory security)overcomes the limitation of computational security generally existing in traditional UnionPay payment systems.
A network-based approach for discourse analysis from Laclau and Mouffe’s perspectives

&lt;p&gt;The current study provides the possibility of merging Laclau and Mouffe’s theory of discourse analysis with network theory to specify an alternative bedstead for studying discourse via a semi-automatic algorithm. To do so, first, considering the text as the discourse of complex system, a semi-automatic algorithm is implemented to transform the interacting linguistic components into a network which is depicted as a graph of vertices connected by edges. Then, some of the graph statistics, e.g. degree, weighted degree, eigenvector centrality, etc., are identified for characterizing the nodes as moments, nodal points, and/or nodal point of identity. Finally, the articulation of the discourse based on the above-mentioned components is studied. The results indicate that the approach is strong enough to pave a way for studying the articulation of the discourse from an alternative view, especially based on Laclau and Mouffe’s theory of discourse analysis.&lt;/p&gt;
The Effects of Person-Centered Expressive Arts Therapy Program on Depression, Anxiety, Emotional awareness, Emotional Expression of Middle-Aged Women

본 연구는 인간중심 표현예술치료의 집단프로그램 활동이 중년기 여성들의 우울, 불안, 정서 인식, 정서표현에 미치는 효과를 알아보기 위한 목적이다. 이를 위해 K시에 소재한 공공기관과 상담소에 홍보하였고 참여를 희망하는 40세에서 60세의 중년여성 36명을 최종 모집하여 처치집단 18명, 통제집단 18명으로 무선 할당하였다. 처치집단에는 주 1회 180분씩 8회기 프로그램을 실시하고 프로그램 전·후, 프로그램 종료 4주 이후에는 추후검사를 하여 공변량(ANCOVA) 분석으로 효과를 검증하였다. 본 연구의 결과를 요약하면 첫째, 사전-사후검사 결과 인간중심 표현예술치료가 중년기 여성의 우울과 불안을 감소시키고 정서인식과 정서표현을 유의하게 향상시키는 것으로 보였다. 둘째, 사전-추후 검사 결과 인간중심 표현예술 치료가 중년기 여성의 우울과 불안의 감소 및 정서표현 향상에는 효과가 지속됨을 알 수 있었지만 정서인식 향상에서는 유의한 차이를 보이지 않았다. 결론적으로 인간중심 표현예술치료 프로그램이 중년기 여성의 정서적 어려움을 개선하는데 효과가 있었음을 확인하였고 이러한 연구결과를 바탕으로 중년기 여성의 다양한 특성을 고려한 후속연구를 제안하였다.The research goal of this paper was to investigate the effect of group-based programs of person-centered expressive arts therapy and whether or not it could affect depression, anxiety, emotional awareness, emotional expression of middle-aged women. 36 women aged 40 to 60 years of age in K City were recruited and 18 experimental groups and 18 control groups were randomly assigned. In the experimental group, the program was, in total, 8 sessions a week for 3 hours once a week, and, four weeks after the program was conducted, the effect was verified by analysis of covariate (ANCOVA). Summarizing the results, first, pre-post examinations showed that person-centered expressive arts therapy reduced depression and anxiety in middle-aged women and significantly improved emotional awareness and emotional expression. Second, as a result of pre-following tests, it was found that person-centered expressive arts therapy was effective in reducing depression and anxiety and improving emotional expression in middle-aged women, but did not show a significant difference in emotional awareness. In conclusion, it was confirmed that the person-centered expressive arts therapy program was effective in improving the emotional difficulties of middle-aged women, and based on the results of these studies, the need for follow-up studies considering various characteristics of middle-aged women shoud be considered.
Hybrid Reasoning Over Large Knowledge Bases Using On-The-Fly Knowledge Extraction

The success of logic-based methods for comparing entities heavily depends on the axioms that have been described for them in the Knowledge Base (KB). Due to the incompleteness of even large and well engineered KBs, such methods suffer from low recall when applied in real-world use cases. To address this, we designed a reasoning framework that combines logic-based subsumption with statistical methods for on-the-fly knowledge extraction. Statistical methods extract additional (missing) axioms for the compared entities with the goal of tackling the incompleteness of KBs and thus improving recall. Although this can be beneficial, it can also introduce noise (false positives or false negatives). Hence, our framework uses heuristics to assess whether knowledge extraction is likely to be advantageous and only activates the statistical components if this is the case. We instantiate our framework by combining lightweight logic-based reasoning implemented on top of existing triple-stores with an axiom extraction method that is based on the labels of concepts. Our work was motivated by industrial use cases over which we evaluate our instantiated framework, showing that it outperforms approaches that are only based on textual information. Besides the best combination of precision and recall, our implementation is also scalable and is currently used in an industrial production environment.
An exploratory PLS study of the academic success/failure

Strategies to combat academic failure in higher education rely on the identification and on the knowledge of the causes associated with it. To identify these causes, a questionnaire survey was implemented in a Higher School of Technologies and Engineering. Student-related aspects were those that exhibited the greatest impact on academic success/failure. Teachers and institution/curriculum exhibited an indirect impact through mediation by student-related aspects. Other variables were identified with a negative residual impact on academic success, such as: be displaced from the habitual residence, dislike to study and be a male. With a slightly more relevant impact, emerged the sleep time on the eve of the tests.
An Effective Pipeline for a Real-world Clothes Retrieval System

In this paper, we propose an effective pipeline for clothes retrieval system which has sturdiness on large-scale real-world fashion data. Our proposed method consists of three components: detection, retrieval, and post-processing. We firstly conduct a detection task for precise retrieval on target clothes, then retrieve the corresponding items with the metric learning-based model. To improve the retrieval robustness against noise and misleading bounding boxes, we apply post-processing methods such as weighted boxes fusion and feature concatenation. With the proposed methodology, we achieved 2nd place in the DeepFashion2 Clothes Retrieval 2020 challenge.
A Study on the Development of the Storytelling Contents based on the Exile Life and Literature Works of Man-Jung Kim

This paper proposes how to develop storytelling contents for foster local culture industry based on the lifestyle and literature works of Man-Jung Kim, a great scholar in the late Joseon dynasty.He wrote various literary works such as classic novels, poetries, proses, and criticisms during his exile life.Storytelling content based on his work will play an important role in globalizing Korean contents.The development method of storytelling contents uses the basic elements: 'text + narration + champ' based on the champ theory.We will look at similar storytelling content development cases based on the exile literature in Korea and benchmark them to develop Kim's storytelling content development plans.Twelve experts participate to brainstorm for developing various new ideas of storytelling contents.It is important to approach Kim's work from a comprehensive and integrated perspective in order to develop valuable storytelling contents.Concludingly, to build local cultural assets, it is important to focus not only on the core values of Kim's works, but also in building a collaborative system among local governments, storytellers, cultural artists, tourists, and citizens.
Benchmarking BioRelEx for Entity Tagging and Relation Extraction

Extracting relationships and interactions between different biological entities is still an extremely challenging problem but has not received much attention as much as extraction in other generic domains. In addition to the lack of annotated data, low benchmarking is still a major reason for slow progress. In order to fill this gap, we compare multiple existing entity and relation extraction models over a recently introduced public dataset, BioRelEx of sentences annotated with biological entities and relations. Our straightforward benchmarking shows that span-based multi-task architectures like DYGIE show 4.9% and 6% absolute improvements in entity tagging and relation extraction respectively over the previous state-of-art and that incorporating domain-specific information like embeddings pre-trained over related domains boosts performance.
Building a Universal Dependencies Treebank for Occitan

This paper outlines the ongoing effort of creating the first treebank for Occitan, a low-ressourced regional language spoken mainly in the south of France. We briefly present the global context of the project and report on its current status. We adopt the Universal Dependencies framework for this project. Our methodology is based on two main principles. Firstly, in order to guarantee the annotation quality, we use the agile annotation approach. Secondly, we rely on pre-processing using existing tools (taggers and parsers) to facilitate the work of human annotators, mainly through a delexicalized cross-lingual parsing approach. We present the results available at this point (annotation guidelines and a sub-corpus annotated with PoS tags and lemmas) and give the timeline for the rest of the work.