Reviewerly/exHarmony huggingface dataset:
Unsupervised Domain Adaptation in Semantic Segmentation via Orthogonal and Clustered Embeddings.

Deep learning frameworks allowed for a remarkable advancement in semantic segmentation, but the data hungry nature of convolutional networks has rapidly raised the demand for adaptation techniques able to transfer learned knowledge from label-abundant domains to unlabeled ones. In this paper we propose an effective Unsupervised Domain Adaptation (UDA) strategy, based on a feature clustering method that captures the different semantic modes of the feature distribution and groups features of the same class into tight and well-separated clusters. Furthermore, we introduce two novel learning objectives to enhance the discriminative clustering performance: an orthogonality loss forces spaced out individual representations to be orthogonal, while a sparsity loss reduces class-wise the number of active feature channels. The joint effect of these modules is to regularize the structure of the feature space. Extensive evaluations in the synthetic-to-real scenario show that we achieve state-of-the-art performance.
On the Discourse of Online Sports News Headlines

Abstract Sports discourse is one of the most common types of discourses today. It is regarded to be one of the types of media discourses which is supposed to display mainly features of description and commentary, with a unique, specialized vocabulary. This study focuses on sports news headlines published online. One of the objectives of the study is to establish some of the markers with respect to lexical choices, events, and formulation of content. Another objective is to see what ideologies these headlines may reveal.
Kompleks Masjid Dan Asrama Pondok Modern Darussalam Gontor Putri 2 Dengan Pendekatan Arsitektur Perilaku

Islamic boarding schools are one of Indonesia's most distinctive Islamic educational institutions, even the oldest educational institutions in the archipelago. One of them is Pondok Modern Darussalam Gontor or what is often called Pondok Gontor. Parents' awareness of Islamic education for their children causes an increase in the number of students each year. The increase in the number of Gontor Putri 2 students also led to developments in the physical form of the building. New dormitories are added annually. Unfortunately, the construction of this dormitory facility has not been matched with the capacity of the existing mosque. The ideology of an Islamic boarding school makes the mosque a center of activities surrounded by supporting buildings, one of which is the dormitory where students live. Santri have activities that are much different from ordinary students of their age. This activity forms a special pattern of behavior that only the students in it have. The existence of this particular pattern of behavior certainly results in different forms of space. Meanwhile, the existing conditions are not yet fully in accordance with the standard psychological criteria of the santri. Therefore it is necessary to review how the ideal form of the entire mosque and dormitory building should be in accordance with the architectural concept of behavior.Keywords: Islamic Boarding School, Mosque, Dormitory, Behavior Architecture
A method of accelerating CNN computation on DSP

Abstract Because convolution network contains a lot of multiplication and addition operations, there is still room for optimization after it is implemented on the hardware platform. This paper mainly studies the method of accelerating the deep learning algorithm on DSP, proposes to improve the convolution layer calculation by using Winograd algorithm, and implements it on GPDSP. The final results show that it can increase the parallelism of data calculation and significantly reduce the computing time.
Strange spaces of mediated memory

What happens when sites of memory - particularly those commemorating a “dark” past - also function as places of the imagination for media tourists? Such sites may produce a form of heritage dissonance that transforms them into “strange spaces”, where familiar and phantasmagorical elements co-exist in unsettling ways. A fascinating case study can be found in the Gambian village of Juffure, where UNESCO World Heritage Sites commemorating the trans-Atlantic slave trade simultaneously serve as places of the imagination associated with the 1976 novel Roots. In 2015, I visited Juffure with 12 student research participants to assess whether the Roots connection complemented or complicated the historical narratives presented at these sites. Nearly half of my participants read Roots prior to travelling; the rest did not. In subsequent interviews, I assessed whether familiarity with Roots made these sites more comprehensible and resonant for Readers in comparison to Non-Readers. Ultimately, Readers were frequently confused and frustrated that day, as they tried to reconcile the imagined geographies of Roots with the spatial configurations and sense of place they experienced at these heritage sites. This suggests that the Roots connection threatens to complicate the historical narratives at these sites, rendering them as strange spaces of mediated memory.
A decentralized aggregation mechanism for training deep learning models using smart contract system for bank loan prediction.

Data privacy and sharing has always been a critical issue when trying to build complex deep learning-based systems to model data. Facilitation of a decentralized approach that could take benefit from data across multiple nodes while not needing to merge their data contents physically has been an area of active research. In this paper, we present a solution to benefit from a distributed data setup in the case of training deep learning architectures by making use of a smart contract system. Specifically, we propose a mechanism that aggregates together the intermediate representations obtained from local ANN models over a blockchain. Training of local models takes place on their respective data. The intermediate representations derived from them, when combined and trained together on the host node, helps to get a more accurate system. While federated learning primarily deals with the same features of data where the number of samples being distributed on multiple nodes, here we are dealing with the same number of samples but with their features being distributed on multiple nodes. We consider the task of bank loan prediction wherein the personal details of an individual and their bank-specific details may not be available at the same place. Our aggregation mechanism helps to train a model on such existing distributed data without having to share and concatenate together the actual data values. The obtained performance, which is better than that of individual nodes, and is at par with that of a centralized data setup makes a strong case for extending our technique across other architectures and tasks. The solution finds its application in organizations that want to train deep learning models on vertically partitioned data.
Approximating Ground State Energies and Wave Functions of Physical Systems with Neural Networks

Quantum theory has been remarkably successful in providing an understanding of physical systems at foundational scales. Solving the Schrödinger equation provides full knowledge of all dynamical quantities of the physical system. However closed form solutions to this equation are only available for a few systems and approximation methods are typically used to find solutions. In this paper we address the problem of solving the time independent Schrödinger equation for the ground state solution of physical systems. We propose using end-to-end deep learning approach in a variational optimization scheme for approximating the ground state energies and wave functions of these systems. A neural network realizes a universal trial wave function and is trained in an unsupervised learning framework by optimizing the expectation value of the Hamiltonian of a physical system. The proposed approach is evaluated on physical systems consisting of a particle in a box with and without a perturbation. We demonstrate that our approach obtains approximations of ground state energies and wave functions that are highly accurate, which makes it a potentially plausible candidate for solving more complex physical systems for which analytical solutions are beyond reach.
Image recognition algorithm based on spatial transform convolutional neural network

Abstract Aiming at the problem of classification and recognition of noisy handwritten digits, a connection method is proposed to add a spatial transformation network to a convolutional neural network. The spatial transformation network can not only obtain the output results, but also understand the parts of the input data that have the greatest influence on the results and perform feature extraction, which can improve the performance of the model and enhance the interpretability of the model. The experiment was performed on the Cluttered MNIST dataset, and the effects of the conventional convolutional neural network and the improved neural network with spatial transformation network were compared. The experimental results show that the prediction accuracy of convolutional neural networks based on spatial transformation can reach 97.65%, and the results obtained by this method are better than those of conventional convolutional neural networks.
Formation of Cognitive Flexibility as a Basic Competence of the Future Teachers’ Multicultural Personality

The article presents the results of research work on the formation of cognitive flexibility (CF) as an essential competence of the future teachers’ multicultural personality. It has been shown that various branches of knowledge (psychology, philosophy, clinical medicine, pedagogy, and others) contribute to the scientific and theoretical substantiation of CF, which is included in the TOP-10 most requested competencies in the XXI century. Based on the analysis of the essence and nature of the future teachers’ multicultural personality, the hypothesis that the competence of CF should become a vital component of personal development was put forward. To test this hypothesis, a pedagogical experiment was organised, which covered 33 future teachers studying "Educational, Pedagogical Sciences" at the Precarpathian National University (Ivano-Frankivsk, Ukraine). The experiment was conducted in four stages: on the first preparatory stage, a defined program of experimental activities was made; on the second statement stage, the diagnosis of future teachers’ CF levels was set on the basis of the developed prognostic tools (the Questionnaire Cognitive flexibility was created to define the main features of CF as a component of multicultural competence of the future teacher, tests); on the third formative stage the approbation of our methodology for the formation of CF was carried out, which had no analogues in modern education and pedagogy (this was implemented on the basis of our own special course "Cognitive flexibility and multicultural competence of the future teacher", which was held as a training seminar); on the fourth control stage the results of the experiment were determined. They showed that the indicators of CF formation of future teachers at a high level increased from 9.1% to 41.5% (4.7 times), at the medium level they decreased from 63.6% to 53% (1.2 times). At the low level, they changed from 27% to 5.5% (4.9 times) according to four defined criteria (cognitive abilities, adaptive abilities, flexibility of thinking, and emotional flexibility). This proves the effectiveness of the authors’ methodology for the formation of CF as a basic competence of the multicultural personality of the future teacher. It can be widely used in the training of specialists in various specialities.
Efforts to Improve Alley Reading Skills Using Image Media in Class 1 Students

&lt;p&gt;&lt;em&gt;Language is an important component in everyday life. Through language, a person can communicate with other people, so that relationships between people can be well established. In addition, language can also show a person's personality and even a nation. Most members of society assume that people who are polite in language must have a good personality too, and vice versa. This study aims to improve reading aloud skills using image media. This study uses the spiral model PTK method from Kemmis and Taggart. From this research, the results show that students' reading aloud skills can improve with picture media. &lt;/em&gt;&lt;/p&gt;
A COMPARATIVE STUDY OF CLASSIFICATION METHODS ON HUMAN SKIN DETECTION FROM RGB AND YCBCR REPRESENTED COLOR IMAGES

Skin detection has an important place in image processing. Human-computer interaction has made this study area very popular. The most common color space used in skin detection is Red Green and Blue but RGB space can be converted into YCbCr space. Both features give strong information about the properties of the images. In this study, RGB and YCbCr spaces are used to detect human skin. The extracted features are trained by several classification methods. The obtained features are used to segment the human skin by using the chosen classification algorithm and finally, the promising performance results are presented comparatively with the most commonly used classifications methods in the literature.
LibGuides: Academic Librarian - Ania (Professional & Personal): Welcome

This guide explains academic librarians' role within the University and support they offer for students, staff and community.
이중 언어 말뭉치 구축에 대한 제안 ― 한중 말뭉치를 중심으로

Corpus linguistics is a field of applied linguistics devoted to the study of languages using ‘real language’ or actual language samples. The Sejong Project’s Korean-English/Korean-Japanese corpus is an annotated corpus with information on morphological analysis and parsing. The annotated corpus has the advantage of providing users with more accurate information thanks to the linguists’ analysis attached, but there are corresponding disadvantages as well. This paper is aimed at analyzing the advantages and disadvantages of the corpus that have been already built in, and at suggesting a new bilingual corpus model.
5 MEKANISME PIKIR SEBAGAI TEKNIK PENGEMBANGAN KERANGKA KARANGAN

Short stories are a type of prose that does not have a lot of conflict and there are not many characters in it, but has a complex unanimity. However, writing short stories is not easy, because it requires imaginative power and qualified creativity in expressing ideas and processing language. Imaginative processes and creativity do not just exist, but need to be trained intensively and continuously. There are many strategies for writing short stories, especially for beginner writers. The first is compiling the outline of the essay, the second is using the idea development technique. One of the techniques in compiling the outline of the essay is using the cilukba pattern technique. For the technique of developing an essay framework, you can use the 5 thought mechanism technique. Techniques for 5 thought mechanisms, including developing, shrinking, increasing, decreasing, and sideways. This pattern will be used by PGSD students of PGRI Adi Buana University Surabaya class of 2016 to write short stories. The methods used include lecturers making themes, students are tasked with compiling an essay framework based on cilukba patterns, students are tasked with learning the 5 thought mechanism techniques, and students are tasked with developing an essay framework based on the 5 thought mechanism techniques. Based on this, PGSD students of PGRI Adi Buana University Surabaya class of 2016 can write short stories well and can collect these short stories into a collection book ISBN of short stories.
EFEKTIVITAS KEPEMIMPINAN KEPALA SEKOLAH DALAM MENGEMBANGKAN BUDAYA LITERASI DI MADRASAH ALIYAH AZIZIYYAH TANGERANG

This research aimed at finding out the Effectiveness of School Principal’s Leadership in Developing Culture of Literacy at Aziziyyah Islamic High School, Tangerang. The methods used was qualitative approach. The results of this study indicated that the design of literacy culture development in MA Aziziyyah Tangerang has been adapted to the GLS guidelines formulated by the Ministry of Education and Culture. Including the stages: Habituation Stages, Development Stages, and Learning Stages. Indicators of achievement in these stages were met with 30 items out of a total of 37 items. These results indicated that each stage in the design of literacy culture development ran optimally in accordance with the objectives to be achieved. Several factors influenced the development of literacy culture in MA Aziziyyah Tangerang, including: psychosocial factors, leadership factors, environmental factors, organizational factors, ecological factors, and government policies. These factors tended to have a positive impact on the process of developing literacy culture in MA Aziziyyah. The effectiveness of the principal's leadership was the main foundation for optimizing the development of literacy culture. Indicators of achievement related to the effectiveness of MA Aziziyyah school principal leadership in developing a literacy culture fulfilled 6 items out of a total of 7 items. The results showed that the leadership carried out by the principal was quite effective.
Bayesian optimization for selecting training and validation data for supervised machine learning : using Gaussian processes both to learn the relationship between sets of training data and model performance, and to estimate model performance over the entire problem domain

Validation and verification in machine learning is an open problem which becomes increasingly important as its applications becomes more critical. Amongst the applications are autonomous vehicles a ...
Identification of quality problems staff vocational training

Vocational training (VET) is a very complex and understudied system-object, the functioning of which is the subject to a continuous action of a large number of random (uncertain) factors. The coactions of these factors leads to significant inconsistencies in the development of the training program, reducing its effectiveness in relation to the achievement of learning objectives. The lack of commensurability of the real increase in efficiency with the target settings should be considered, first of all, as a problem of software quality. In connection with the insufficiency of the existing theoretical ideas about the internal properties of the educational process (OP), the problem of control synthesis can be solved by observing its inputs and outputs. Observation of the reaction of output quantities to changes in input influences allows us to construct an a posteriori model of the process, i.e. to identify the quality problem in the early stages of its inception.The purpose of this work is to investigate the possibility of ensuring the quality of personnel software by the identification method based on the results of evaluating the input and output signals of the OP as a control object. The methodology of work is based on the concept of integrated quality management (TQM) and the process approach.The main categories of problems of the quality of education are considered and clustered to support the adoption of managerial decisions. The most important features of closed and open problems that need to be considered when making decisions are described. Recommendations were developed on the application of methods of direct and indirect approaches to the identification of quality problems. It has been shown that discussions in cross-functional groups provide, as a rule, the best results in identifying and resolving problems. The value of the study for the theory and practice of software consists in constructing an identification procedure to support the adoption of informed decisions when choosing actions to prevent the development of quality problems.The developed identification procedure can be applied in the software system, providing an acceptable level of satisfaction of the enterprise personnel with the quality of training.
TO THE PROBLEM OF FORMING THE INSTITUTE OF CULTURE IMAGE

Учредитель: ФГБОУ
Предыстория концепции Цифровой Земли

The paper points to the need to study the prehistory of the Digital Earth, provides examples of anticipating geographical products with properties that clearly distinguish them from maps and clearly indicate the properties of the future Digital Earth.
Science and Its Role in Modern Society: Epistemological and Social Aspects

Epistemological and Social AspectsWe live in an age of information and high technology, it seems that a person has already answered all the questions, but the world around us is asking more and more, and we are trying to find answers to them.But nature cannot be forced to say what we would like to hear.Scientific research is not a monologue.Asking a question to nature, a researcher runs the risk of failing, but it is the risk that makes this game so exciting.Science is a risk game, and a game always is exciting, unpredictable and interesting.Science is one of the defining features of modern culture and perhaps its most dynamic component.Today it is impossible to discuss social, cultural, anthropological problems without considering the development of scientific thought.Modern society is entering the informational stage of development, the rationalization of all social life is becoming not only possible, but also vital.On the other hand, the limits of the development of a civilization of a one-sided technological type were revealed: both in connection with the global environmental crisis, and as a result of the impossibility of total control of social processes revealed.Modern science in many respects is essentially, radically different from the science that existed a century or even half a century ago.Its whole appearance and the nature of its relationships with society have changed.It should be noted that there are still three basic concepts of science: science as knowledge, science as activity, science as a social institution.Modern science is an organic unity of these three points.Here, activity is its basis, a kind of "substance", knowledge is a system-forming factor, and a social institution is a way of combining scientists and organizing their joint activities.And these three points make up the full definition of modern science.
Is financial integration driver of income inequality A panel co-integration analysis in Europe

Research on income inequality and finance has become an increasingly popular research area in the post-crisis period. Fully modified (FMOLS) and dynamic OLS (DOLS) co-integrated regression models are employed to empirically explore and estimate the long run co-integration vector for non-stationary panels between 2000 and 2016. The study finds that a NMS-11 with relatively lower integrated international financial flows experience lower levels of income inequality than older EU-15 members that have more integrated international financial flows. These countries experience greater levels of income inequality. Financial development generally leads to decreased income inequality in the whole sample and the NMS-11, whereas the results are mixed for the old EU-15 members. The study recommends government policies, especially in NMS-11 countries and European transition countries, that prioritise further financial market reforms (credit and stock markets) and greater financial freedom and minimise government interference that are vital to development of financial sector and thus economic growth.