Reviewerly/exHarmony huggingface dataset:
AESTHETIC ASPECT OF EMOTIVENESS OF POETIC TEXT

The study looks for ways of analyzing the aesthetic aspect of emotiveness in a poem. To accomplish the aim, the author undertakes an attempt to study the essence of the image of aesthetic feeling. Since a poetic text appears to be a complex unity of notional, emotive, and aesthetic codes, the methods of cognitive analysis are employed to formalize deep cognitive and emotive constructs that give rise to aesthetic senses within a poetic text. The study relies on the statement that an image of aesthetic feeling has an emergent nature which means that it appears in the process of poetic text writing as a result of a creative impulse of the author (O. Mandelstam). In the study, the image of aesthetic feeling is regarded as an emotive image of the highest level. On the one hand, it is directed at some well-established aesthetic categories, and on the other, it reveals the author’s attitude to them which is manifested through a sophisticated network of images. A step-by-step analysis of Shel Silverstine’s poem “A Light in the Attic” has been suggested to illustrate a possible way of uncovering image(s) of aesthetic feelings inscribed in the text.
제2차 세계대전 이후 독일 여군의 변천 과정과 그 시사점

This paper examines the history of German Female Soldiers after Second World War and draws implications. German Female Soldiers have worked mostly at Medical Corps during the Cold War and have been active in all areas of the Bundeswehr since 2001. At present, over 20,000 German Female Soldiers work in the Bundeswehr and correspond to 12% of all german troops. There is also a number of women who make military decisions in important positions of the Bundeswehr. In future, they will expand the scope of their activities in response to role changes of the Bundeswehr. Germany Female Soldiers grow as Staatsburger in Uniform because of Innere Fuhrung, laws and regulations that protect the human rights of soldiers. In addition, various systems for Work and Family Balance also contributed to the increase of Germany Female Soldiers. This study can help develop the system for Korean Female Soldiers.
ExplaGraphs: An Explanation Graph Generation Task for Structured Commonsense Reasoning.

Recent commonsense-reasoning tasks are typically discriminative in nature, where a model answers a multiple-choice question for a certain context. Discriminative tasks are limiting because they fail to adequately evaluate the model’s ability to reason and explain predictions with underlying commonsense knowledge. They also allow such models to use reasoning shortcuts and not be “right for the right reasons”. In this work, we present ExplaGraphs, a new generative and structured commonsense-reasoning task (and an associated dataset) of explanation graph generation for stance prediction. Specifically, given a belief and an argument, a model has to predict if the argument supports or counters the belief and also generate a commonsense-augmented graph that serves as non-trivial, complete, and unambiguous explanation for the predicted stance. We collect explanation graphs through a novel Create-Verify-And-Refine graph collection framework that improves the graph quality (up to 90%) via multiple rounds of verification and refinement. A significant 79% of our graphs contain external commonsense nodes with diverse structures and reasoning depths. Next, we propose a multi-level evaluation framework, consisting of automatic metrics and human evaluation, that check for the structural and semantic correctness of the generated graphs and their degree of match with ground-truth graphs. Finally, we present several structured, commonsense-augmented, and text generation models as strong starting points for this explanation graph generation task, and observe that there is a large gap with human performance, thereby encouraging future work for this new challenging task.
The Effects of Users’ Psychological Diversity on Avatars’ Behaviour in the Virtual World

Virtual world has been used in education and psychological studies more and more frequent for its wide applicability to them. The value of user data cannot be overlooked. In view of this, research is conducted on the users’ personality, their preferences for islands’ style, and how active the users are in the virtual world. In this paper, experiment collects 44 participants’ valid user data in virtual world and analyzes their personalities by using Eysenck Personality Questionnaire. It is found that the activity level, and particular preferences for the island’s style are related to users’ personality.
Accelerated Human NMT Evaluation Approaches for NMT Workflow Integration

Attendees to this session will get a clear view into how neural machine translation is leveraged in a large-scale real-life scenario to make substantial cost savings in comparison to conventional approaches without compromising quality. This will include an overview of how quality is measured, when and why quality estimation is applied, what preparations are required to do so, and what attempts are made to minimize the amount of human effort involved. It will also be outlined as to what worked well and what pitfalls are to be avoided to give pointers to others who may be considering similar strategies.
Contrastive Explanations for Model Interpretability

Contrastive explanations clarify why an event occurred in contrast to another. They are inherently intuitive to humans to both produce and comprehend. We propose a method to produce contrastive explanations in the latent space, via a projection of the input representation, such that only the features that differentiate two potential decisions are captured. Our modification allows model behavior to consider only contrastive reasoning, and uncover which aspects of the input are useful for and against particular decisions. Our contrastive explanations can additionally answer for which label, and against which alternative label, is a given input feature useful. We produce contrastive explanations via both high-level abstract concept attribution and low-level input token/span attribution for two NLP classification benchmarks. Our findings demonstrate the ability of label-contrastive explanations to provide fine-grained interpretability of model decisions.
Uncertainty Quantification of Surrogate Explanations: an Ordinal Consensus Approach

Explainability of black-box machine learning models is crucial, in particular when deployed in critical applications such as medicine or autonomous cars. Existing approaches produce explanations for the predictions of models, however, how to assess the quality and reliability of such explanations remains an open question. In this paper we take a step further in order to provide the practitioner with tools to judge the trustworthiness of an explanation. To this end, we produce estimates of the uncertainty of a given explanation by measuring the ordinal consensus amongst a set of diverse bootstrapped surrogate explainers. While we encourage diversity by using ensemble techniques, we propose and analyse metrics to aggregate the information contained within the set of explainers through a rating scheme. We empirically illustrate the properties of this approach through experiments on state-of-the-art Convolutional Neural Network ensembles. Furthermore, through tailored visualisations, we show specific examples of situations where uncertainty estimates offer concrete actionable insights to the user beyond those arising from standard surrogate explainers.
An Application of Augmented Reality for Introduction Batak Traditional House Architecture

Indonesia has a wealth of the nation in the form of a variety of physical types of architecture, which more often referred to as the Nusantara Architecture. Modern perceptions make people understand that buildings are composed of natural materials, and without planting, foundation means that the structures are primitive. In this research, the media designed to introduce; Batak architecture based on Augmented Reality (AR) Application to enter the physical appearance of Karo Batak, Toba Batak, and Simalungun Batak Architecture. Architectural physical appearance includes the presence of the roof, construction techniques, connection techniques, spatial planning, and compiler materials. The results of this research are the augmented reality application. For further development, it is expected to use a more appropriate introduction method or use another more complete Augmented Reality API.
Learning to Detect Geometric Structures from Images for 3D Parsing

Author(s): Zhou, Yichao | Advisor(s): Ma, Yi | Abstract: Recovering 3D geometries of scenes from 2D images is one of the most fundamental and challenging problems in computer vision. On one hand, traditional geometry-based algorithms such as SfM and SLAM are fragile in certain environments, and the resulting noisy point-clouds are hard to process and interpret. On the other hand, recent learning-based 3D-understanding neural networks parse scenes by extrapolating patterns seen in the training data, which often have limited generalizability and accuracy.In my dissertation, I try to address these shortcomings and combine the advantage of geometric-based and data-driven approaches into an integrated framework. More specifically, I have applied learning-based methods to extract high-level geometric structures from images and use them for 3D parsing. To this end, I have designed specialized neural networks that understand geometric structures such as lines, junctions, planes, vanishing points, and symmetry, and detect them from images accurately; I have created large-scale 3D datasets with structural annotations to support data-driven approaches; and I have demonstrated how to use these high-level abstractions to parse and reconstruct scenes. By combining the power of data-driven approaches and geometric principles, future 3D systems are becoming more accurate, reliable, and easier to implement, resulting in clean, compact, and interpretable scene representations.
A SELF-EDUCATION OF PERSONALITY IS IN PARADIGM OF MODERN EDUCATION

It is investigational as in a oriented of the modern system of education to activity of personality, independence in the choice of subjects and time of mastering of information. It is marked that passing to the new paradigm of education with the dominant of self-education, coincides with the individual necessities of people and takes place at combination of institutional education and self-education. The self-education of personality is considered as the sociocultural phenomenon, that is related not only to education but also with development of society on the whole.
Machine Translation Decoding beyond Beam Search.

Beam search is the go-to method for decoding auto-regressive machine translation models. While it yields consistent improvements in terms of BLEU, it is only concerned with finding outputs with high model likelihood, and is thus agnostic to whatever end metric or score practitioners care about. Our aim is to establish whether beam search can be replaced by a more powerful metric-driven search technique. To this end, we explore numerous decoding algorithms, including some which rely on a value function parameterised by a neural network, and report results on a variety of metrics. Notably, we introduce a Monte-Carlo Tree Search (MCTS) based method and showcase its competitiveness. We provide a blueprint for how to use MCTS fruitfully in language applications, which opens promising future directions. We find that which algorithm is best heavily depends on the characteristics of the goal metric; we believe that our extensive experiments and analysis will inform further research in this area.
Retrieval, Analogy, and Composition: A framework for Compositional Generalization in Image Captioning

Image captioning systems are expected to have the ability to combine individual concepts when describing scenes with concept combinations that are not observed during training.In spite of significant progress in image captioning with the help of the autoregressive generation framework, current approaches fail to generalize well to novel concept combinations.We propose a new framework that revolves around probing several similar image caption training instances (retrieval), performing analogical reasoning over relevant entities in retrieved prototypes (analogy), and enhancing the generation process with reasoning outcomes (composition).Our method augments the generation model by referring to the neighboring instances in the training set to produce novel concept combinations in generated captions.We perform experiments on the widely used image captioning benchmarks.The proposed models achieve substantial improvement over the compared baselines on both composition related evaluation metrics and conventional image captioning metrics.
Realization of Various Gate level Combinational Circuits using Reversible Fredkin Gate

This paper presents the digital logic gates which are reconstructed using fredkin gate [1]. The advantage of basic fredkin gate is that we could save the thermal waste which comes out due to computation that causes heat as bits just disappear into loss of energy. Such computation won't need any energy input. These assumptions make the gates sound like an energy efficient solution. However the implementation is done at level of logic gates. This can further be used in sequential circuits to increase the life time of transmitter and receiver circuitry of nodes. It will make the transmission and aggregation of information at node very energy efficient. The drawback of this application is it will cost fare amount of time to process data. These technical hurdles will increase latencies at node level. The protocols infused with energy optimization methods and reversible logic gates offered noticeable improvements in achieving performance and ensuring security of data and graphics. Since the 1980s, with work of Fredkin [1], the reversible circuits have been used in building large scale integration of circuits as elementary units of mobile computing, and recently in wireless networks, drug designing and ultra-fast computing technologies [4].
C4I-Cyber Command & Control Supremacy: Why It’s More Critical Than AI & Quantum Supremacy & What You Can Do about It? Security in Post-COVID Virtual Era Beyond Data, Models, Algorithms (Interactive PowerPoint Slides To Accompany Virtual Conference Keynote)

Despite exponential improvements in Data, Models, and, Algorithms and advancements in Artificial Intelligence (AI) and Quantum Computing technologies, the bar on national and organizational Security has been raised by COVID19 global disruptions that include ongoing global cyber-attacks. As world’s first, foremost, and, largest Digital Transformation Network that pioneered Digital and Virtual Organizations practices spanning Silicon Valley, Wall Street, Pentagon, and, worldwide organizations, our latest Air Force Research Lab Ventures are advancing C4I-Cyber Command & Control Practices, Technologies, Ventures, and Networks to meet the post-COVID19 Risk Management realities. In spite of latest AI and Quantum Computing capabilities powering Business-IT Performance, COVID19 has highlighted the critical significance of Resilience and Sustainability of Command and Control (C2) capabilities of Systems powering National Defense & Space, Critical Infrastructures, all Enterprises, and, Intra- and Inter-Enterprise Networks for organizational, national, and, global survival. Given unprecedented global and national cyber-attacks, critical Systems need to advance beyond C2 to include focus on Adversarial C2 and Counter-Adversarial C2 capabilities to survive and thrive. Drawing upon our latest contributions to advancing US Global and National Defense & Space capabilities spanning Air-Space-Cyberspace such as the Advanced Battle Management System (ABMS) Joint All Domain Command & Control (JADC2), our latest State of New York Cybersecurity Conference presentation will help Cyber Security and Risk Management professionals, managers, and, leaders advance Beyond Data, Beyond Models, and, Beyond Algorithms to effectively preempt risks posed by the latest and greatest adversarial threats. We shall build upon our Practices advancing upon the National Institute of Standards and Technology (NIST) Risk Management and Risk Engineering frameworks for AI, Machine Learning, Quantitative, Cyber, Crypto, and, Quantum Risk Computing to counter the C2 risks for enterprises, systems, and, infrastructures – commercial, government, military, and other – connected to the Internet.(Downloadable Interactive PowerPoint Slides To Accompany Virtual Conference Keynote Scheduled for Wednesday, June 9, 2:00 PM - 3:00 PM EDT, New York State Cyber Security Conference, Albany, New York, USA)
До питання формування сучасних педагогічних методик навчання біодизайну при підготовці архітекторів-дизайнерів

International scientific conference «Modern European psychological and pedagogical education. The development of a creative learning environment» : conference proceedings, October 8–9, 2021. Łódź, the Republic of Poland : “Baltija Publishing”, 2021. 162 pages.
The Effect of Self-management and Exercise Immersion on Physical Self-awareness among the Elderly Participating in Sports Activities

The aim of this study is to examine the effect of self-management and exercise immersion on physical self-awareness among the elderly participating in sports activities.This study set those who are 65 years old or over and who regularly participate in sports activities as its population.Sampling was conducted by a random sampling method among non-probability sampling methods.Respondents were asked to respond to the questions on the questionnaire by themselves.After excluding some copies that were not sincerely filled out, 331 copies in total were used for the final analysis.The results obtained through this research process are as follows.First, self-management and exercise immersion have partial positive relationships with physical self-awareness among old people participating in sports activities.Second, self-management has a partial and positive effect on physical self-awareness among old people participating in sports activities.Third, exercise immersion has a partial and positive effect on physical self-awareness among old people participating in sports activities.The above findings prove that selfmanagement and exercise immersion are important elements that affect physical self-awareness among old people participating in sports activities.In particular, given that management of body, a sub-variable of self-management, and cognitive commitment, a sub-variable of exercise immersion, have positive effects on physical self-awareness, voluntary participation in sports activities of old people leads to positive physical self-awareness.
Teachers – The Promoters of Students

A Teacher is a person who inspires and encourages students to strive for greatness. A  great teacher is one, a student remembers and cherishes forever. Teachers are long losting impacts on the lives of their students. But the generation gap is the new age phenomenon. The younger generation is feeling very empty and it has no responsibility, so it is trying to escape from one thing to another thing, trying all sorts of things; drugs yoga, anything that accidently they come by hoping  ‘perhaps this is the thing for me’  But there is no proper guidance and the gap goes on becoming bigger. Parents and teachers are most longer on speaking terms because children think these old people know nothing and old people think that these children are just nuisance. Same fact applies to an experienced teacher and students. Hence a Teacher is a guide and a Teacher is a torch. Teacher at higher level of education should be a different personality in quality then only she /he can handle their group sensitively. Education should not be merely helping the youth to acquire degrees. It should be the head hand and the heart. The last two are neglected in our Schools, Colleges and Universities. Until education begins to take human problems into account, our lives will be very empty. A teacher plays an important role after parents in moulding the students. Students are to be handled with affection and courtesy. In olden teacher was in the center. But today, the teacher has to acknowledge love rather than respect. Class room is a place where young human minds interact with facts, ideas and suppositions – with what is, and what can be. every day is struggle, no doubt in terms of retaining the interest and motivation of students. Higher education in India suffers from lack of direction and purpose. We need better man power planning and reform from higher education through diversification of courses to meet specific needs.
Multiuser immersive virtual reality application for realtime collaboration in design review process

Most project stakeholders have experienced problems understanding each other during a design review process of complex construction projects while staying remotely. In reality, the difficulty of sharing a common understanding during design review among remote project participants is a barrier to a successful project delivery. The recent advancement in visualization technology—Virtual Reality (VR) provides a practical solution to visualize and interact in the virtual environment of design, construction, and maintenance. However, the difficulty of bringing remote participants together in a virtual environment has impeded the implementation of VR technology in Architecture, Engineering and Construction (AEC) industry. The recent development of VR makes possible the solution for interactive visualization for design, construction, and maintenance. To fill the gap, this thesis presents a developed VR application for the realtime collaboration approach for remote users that enables clients and design professionals to clearly explore every aspect of their virtual project and facilitates interpersonal project communication in an interactive VR environment by using VR headsets. The primary aim of this research is to develop and test a VR application that provides not only a shared immersive environment but also realtime interaction between users in the virtual world. To successfully conduct this research study, a comparison was made between the immersive VR and the non-immersive VR experience among 44 students in terms of realtime collaboration in a building inspection task. Results indicated that the users of the developed immersive VR application outperformed those of the non-immersive platform as measured by the percentage of correctly identified design errors during the building inspection experiment. In practice, the developed application is expected to assist the project participants to create a shared immersive environment of their virtual project for an effective design review before construction work begins.
Siamese Networks for Inference in Malayalam Language Texts

Natural language inference is a method of finding inferences in language texts.Understanding the meaning of a sentence and its inference is essential in many language processing applications.In this context, we consider the inference problem for a Dravidian language, Malayalam.Siamese networks train the text hypothesis pairs with word embeddings and language agnostic embeddings, and the results are evaluated against classification metrics for binary classification into entailment and contradiction classes.XLM-R embeddings based Siamese architecture using gated recurrent units and bidirectional long short term memory networks provide promising results for this classification problem.