Reviewerly/exHarmony huggingface dataset:
Principles Governing Indirect Reports

In the literature of indirect reports, some general principles governing the practice of indirect reporting are treated (e.g., Principle of Prudence, Paraphrasis/Form Principle, etc.). However, in this chapter, some new principles are introduced that would make life easier for the participants of indirect reports (the original speaker, the reporter, and the hearer). The chapter is divided into discussions on macro (general rules that govern the whole process of indirect reports, embracing all three participants of indirect reports) and micro (target either one or two of the participants in indirect reports) principles. In this chapter, principles such as Principle of Politeness, Principle of Immunity, Principle of Doubt, and Principle of Commitment are introduced. Moreover, in this chapter, some principles proposed by other researchers are taken into considerations and modified based on new justifications.
Applying design principles to instructional materials

Instructional design is a structured, systematic process of designing and developing an instructional interface. Correct application of instructional design principles influences user behavior and promotes safe and effective use of medical devices and drug delivery products. There are many resources available to the person or team responsible for developing the instructional interface. These resources guide the application of instructional design principles for the best possible design of instructional and training materials. This chapter provides a practical guide to applying design principles during initial development of instructional materials, or when identifying root causes and recommended improvements based on human factors study data.
Head-mounted eye tracker based on android smartphone

This paper presents a wearable eye tracker that tracks points of interests of user at videostream showed at smartphone screen. The system consists head-mounted case for smartphone, point of interest detection algorithm, the software developed for this purposes, and Android smartphone used to show videostream, estimate point of interests at video, and log estimated data into device internal memory.
Maximizing Software Production & Quality with Minimum Staff using Clarity™ - A Real-World Case Study

Software development in today's world has many interesting challenges. Demand for Software Engineers is greater than ever, requiring software engineering staff to be used as efficiently as possible; software development continues to be an activity susceptible to inefficiency, risk and quality issues; and software maintenance challenges are expanding as languages and libraries increase in number and complexity, and software engineers move between companies. The Space Data Systems (SDS) software engineering organization at Southwest Research Institute (SwRI®) produced 33 production software products over a 20-year period with a staff averaging 6 software engineers and testers. During that time, SDS created and refined the Clarity software engineering process in order to produce highly reliable and maintainable software products for the National Aeronautics and Space Administration (NASA), the European Space Agency (ESA) and other customers. With Clarity, SDS raised its average effectiveness for the past six years to 95%, meaning that SDS spent 95% of its time creating new functions or expanding existing functions, as opposed to fixing bugs. Clarity maximizes staff effectiveness by implementing enough process by the right person at the right time to minimize software rework, without slowing core software development and testing activities. Through a system of product-independent checklists and forms, Clarity mitigates error propagation through the software lifecycle process, leveraging the Software Lead as the process executor, and leaving software engineers and software testers to do what they do best - produce quality software products.
Leveraging Large Corpora for Translation Using Sketch Engine

Translation is a demanding, competitive, and labour-intensive activity that requires more than just advanced language skills. If translators are to thrive in such a cutting-edge working environment, they need to possess good computer literacy skills and be well-versed in the art of strategic information mining - in other words, they need to know how to make best use of the plethora of dictionaries, glossaries, books, websites, and other online resources at their disposal in order to find the required information in the shortest amount of time possible. This includes finding translation equivalents and domain-specific terms, checking collocations, idioms, and phrasal verbs, and exploring the way words are used in context by native speakers in order to render the text grammatically, semantically, and stylistically appropriate. Corpora, i.e. large electronic collections of computer-processed, linguistically annotated texts, can serve as an invaluable source of linguistic information, providing the translator with a sample of genuine texts in the target language and, in some cases, translations of similar texts. Over the past two decades, a wide variety of monolingual, comparable, and parallel corpora have been compiled, and these can be searched using either downloadable or online corpus query systems (CQS) such as the Sketch Engine. Whilst computer-assisted translation (CAT) tools such as SDL Trados and MemoQ are a staple of the translation process, translators are still relatively conservative when it comes to using corpora and CQSs to inform their practice. This chapter will introduce the Sketch Engine as a powerful suite of corpus tools for translation and cross-linguistic analysis. Centred around a case study featuring a real-life translation scenario, it will discuss various features of the software which can be used to leverage very large web-based monolingual and parallel corpora for translation, i.e. the concordancer, the word sketches tool, the thesaurus, the term extraction feature, and the corpus building tool.
Algebraic Aspects of Solving Ring-LWE, Including Ring-Based Improvements in the Blum--Kalai--Wasserman Algorithm

We provide a reduction of the Ring-LWE problem to Ring-LWE problems in subrings, in the presence of samples of a restricted form (i.e., $(a,b)$ such that $a$ is restricted to a multiplicative coset of the subring). To create and exploit such restricted samples, we propose Ring-BKW, a version of the Blum--Kalai--Wasserman (BKW) algorithm which respects the ring structure. Off-the-shelf BKW dimension reduction (including coded-BKW and sieving) can be used for the reduction phase. Its primary advantage is that there is no need for back-substitution, and the solving/hypothesis-testing phase can be parallelized. We also present a method to exploit symmetry to reduce table sizes, samples needed, and runtime during the reduction phase. The results apply to 2-power cyclotomic Ring-LWE with parameters proposed for practical use (including all splitting types).
Risk Identification and Assessment Methodology for Restoration Work Utilizing Unmanned Vehicles at Disaster Scenes

Nuclear power plant accidents such as those at Fukushima and Chernobyl release a significant amount of hazardous radiation. It takes a long time to recover from such an accident and the difficulty of the task is very high due to the many risks. Restoration work using unmanned vehicles protects workers from the risk of secondary accidents such as radiation exposure and building collapses. Unmanned tasks in high-risk environments should be performed in accordance with carefully planned and optimized work scenarios that prioritize specific tasks. This study examined the non-radiological and radiological risks, accessibility, task difficulty, and efficiency that determine work priorities in such cases and developed a methodology to assess the risks associated with specific unmanned restoration tasks. The proposed risk assessment methodology is based on a risk matrix that can be used to derive work priorities for each zone at a post-disaster nuclear site.
Quantum State Feedback Control Based on the on-line State Estimation

In this paper the state of Markovian open quantum system is estimated on-line based on the continuous weak measurement and compression sensing theory, and a quantum Lyapunov feedback control law is designed to transfer the state from the initial state to the desired target state based on the state estimated on-line. Numerical simulation experiments are implemented under MATLAB environment. The experimental results show the effectiveness of the on-line estimated state-based feedback control method proposed
Citizen Visual Search Engine: Detection and Curation of Urban Objects

Increasingly, the ubiquity of satellite imagery has made the data analysis and machine learning of large geographical datasets one of the building blocks of visuospatial intelligence. It is the key to discover current (and predict future) cultural, social, financial and political realities. How can we, as designers and researchers, empower citizens to understand and participate in the design of our cities amid this technological shift? As an initial step towards this broader ambition, a series of creative web applications, in the form of visual search engines, has been developed and implemented to data mine large datasets. Using open sourced deep learning and computer vision libraries, these applications facilitate the searching, detecting and curating of urban objects. In turn, the paper proposes and formulates a framework to design truly citizen-centric creative visual search engines – a contribution to citizen science and citizen journalism in spatial terms.
Mobile Application mPodaci (mData)

Mobile application mPodaci (mData) has purpose to get up-to-date data of clients by smartphone. It is written for mobile operating system Android, based on programming language JAVA. It is able to send the data using two ways: email and SMS. It also means that data could be sent using two different kinds of connections: Internet connection, used by email, and phone connection, used for sending SMS messages. The application supports Android from version 15 to the latest.
Academic Mobility of Polytechnic Education in the Aspect of Internationalization and Globalization

Abstract The subject of the research is academic mobility, including mobility of students, teachers, researchers and educational programs. The academic mobility of Polytechnic education is considered in the context of two other objective processes in the world education system – globalization and internationalization. The main purpose of the research is to analyze the meaning of the concept of academic mobility, types of mobility, the importance of mobility for Polytechnic education, the main problems caused by academic mobility and ways to solve them. The development of the education system in the world in recent decades has been revolutionary; the inherent processes that characterize this development are the internationalization and globalization of education. As a result of these processes, there is not only unification, convergence and integration of educational systems, but also the emergence of international standards for the quality of education, increasing interest in foreign students and demand for international educational programs. Academic mobility has become an essential feature of modern education. This term characterizes not only the ability of students to receive education in different parts of the world educational space, but also the personal quality, formed in the learning process, necessary for further personal and professional growth of the future specialist, reflecting its ability to live, adapt and develop in the multicultural world. Prospects for the continuation of this research are in the field of considering the possibilities and expanding cross-border networking and cooperation of world universities.
Interpretation of Implicit Conditions in Database Search Dialogues

Targeting the database search dialogue, we propose to utilise information in the user utterances that do not directly mention the database (DB) field of the backend database system but are useful for constructing database queries. We call this kind of information implicit conditions. Interpreting the implicit conditions enables the dialogue system more natural and efficient in communicating with humans. We formalised the interpretation of the implicit conditions as classifying user utterances into the related DB field while identifying the evidence for that classification at the same time. Introducing this new task is one of the contributions of this paper. We implemented two models for this task: an SVM-based model and an RCNN-based model. Through the evaluation using a corpus of simulated dialogues between a real estate agent and a customer, we found that the SVM-based model showed better performance than the RCNN-based model.
Fitting Analysis of Subjective Evaluation Data Based on Unity Audio-visual Interaction

In this paper, the subjective evaluation data of image localization in Unity audio-visual interaction platform is analyzed. Three classical models are used to fit the experimental data. The regression parameters were compared under three classical models by curve fitting. Regression analysis shows that the linear model has the best fitting effect under the confidence interval of 95%. This paper further analyzes the residual processing, integrates the linear model with the exponential model, and the improved model can better retain effective data, and the regression effect is better than the classical data model.
Recommendation Model Based on Asymmetric Neural Matrix Factorization

In recent years, deep learning has been combined with traditional recommendation system methods to achieve better recommendations. The existing deep matrix factorization recommendation model combines implicit feedback with explicit score to recommend. Although this combination improves the recommendation effect, it fails to make full use of explicit score and implicit feedback. On this basis, this paper proposes an asymmetric neural matrix factorization recommendation model. By constructing a score matrix that can make full use of explicit score and implicit feedback, and using asymmetric neural network to learn the matrix. The new model and the original matrix factorization model were compared on two public datasets, evaluated by HR and NDCG, indicating that the asymmetric neural matrix factorization model has been improved in recommendation.
Error estimation due to approximations in Shack-Hartmann sensor based measurement of high slope freeform wavefront

This paper addresses the challenges and limitations involved in the measurement of steep freeform wavefront by using Shack-Hartmann Sensor (SHS). To estimate the slope errors, Zemax simulation tool is used to design a SHS setup including array of lenslets and detector plane with predefined specifications. In first step, error due to approximation of tilted plane wavefront over curved wavefront is simulated. Plane, tilted, curved and tilted-curved wavefronts are defined using appropriate ray source objects. The centroids of the focal spots of lenslets are calculated based on the detector data obtained by using ray tracing method, which is done by an in-plane scanning aperture for segmented local wavefronts sequentially.The scanning aperture is used to block rays from more than one lenslet array. Centroids from the focus spots are calculated and the slopes are estimated with respect to collimated reference wavefront for each ray trace process. Further, matrix of slope errors is used as an input for MATLAB routines for surface reconstruction and error estimation. Based on the simulation data, it is found that the assumption used in Shack-Hartmann wavefront measurement introduce residual errors. For example a 50 wave peak to valley input and 1.19 mm thick lenslet array can give up to 9 waves of residual form error. However, very thin lenslets can have very less residual error.The effect of shift of focal plane, tilted plane wavefront and curve wavefront during the reconstruction using SHS is reported.
Electronic Public Health and e-Governance

This chapter provides a systemic appreciation of a visionary framework for electronic Public Health (ePH) that I had built in the year 2010 in collaboration Deepankar Medhi, Curators’ Distinguished Professor at the University of Missouri Kansas City (USA) (Chowdhury and Medhi in Systems thinking and E-participation: ICT in the governance of society. Idea Group, Hershey, pp. 69–91, 2010). This framework is in context of enabling e-governance addressing a specific aspect of health and well-being, i.e. Public Health. When complexity is high and the range of interrelationships between various elements is varied and diverse, it is important that any Public Health initiative is able to capture different coexisting factors that influence success, consider the interrelationships between different elements in the environment, and understand how, because of the interrelationships, the system as a whole transforms and evolves. In order to appreciate this, we have resorted to taking a systems perspective in evolving an architectural framework for the ePH. The understanding draws heavily from the Indian context as the country presents an interesting array of the challenges that we have mentioned above. Furthermore, rather than being drawn from existing ICT, our proposed approach is visionary and forward-thinking in terms of what we want to see in future ICT in order to enable the ePH. India is also on the verge of significant change in terms of ICT in public services and related e-governance initiatives. The framework that is proposed will not only be relevant to India, but learning from this can also be inferred for other countries with a similar environment. The conceptual ePH remains visionary and relevant in the current times in the absence of any such solutions that we articulated in 2010. In this chapter, I will delve deeper into the nuances of putting in place such a system both from conceptual and implementation perspectives, and lead a discussion on how the ePH can be positioned in the scheme of e-governance. My discussion here will be contextualised for India and my deliberations will keep in mind the nuances and realities specific to this context.
Research on Tibetan Question Answering Technology Based on Deep Learning

Abstract By applying the theory, technology and system of the Chinese Question Answering system, combining with the background of large data and cloud processing, integrating the theoretical knowledge of Tibetan linguistics, and covering computer high-tech of Tibetan machine translation, neural network learning, problem analysis, classification and answer generation, etc, this paper explores the optimization model of the new Tibetan-Chinese bilingual Question Answering system. Finally, the Tibetan/Chinese bilingual Question Answering system based on deep learning is completed to provide technical support for the economic development of ethnic minority areas.
Modifying Social Dimensions of Human Faces with ModifAE

Author(s): Atalla, Chad E | Advisor(s): Cottrell, Gary | Abstract: At first glance, humans extract social judgments from faces, including how trustworthy, attractive, and aggressive they look. These impressions have profound social, economic, and political consequences, as they subconsciously influence decisions like voting and criminal sentencing. Therefore, understanding human perception of these judgments is important for the social sciences. In this work, we present a modifying autoencoder (ModifAE, pronounced ``modify'') that can model and alter these facial impressions. We assemble a face impression dataset large enough for training a generative model by applying a state-of-the-art (SOTA) impression predictor to faces from CelebA. Then, we apply ModifAE to learn generalizable modifications of these continuous-valued traits in faces (e.g., make a face look slightly more intelligent or much less aggressive). ModifAE can modify face images to create controlled social science experimental datasets, and it can reveal dataset biases by creating direct visualizations of what makes a face salient in social dimensions. The ModifAE architecture is also smaller and faster than SOTA image-to-image translation models, while outperforming SOTA in quantitative evaluations.
How is culture represented in textbooks? – “marriage” in Korean language textbooks used in English-speaking countries

This paper aims to analyse the text and images of marriage culture in Korean textbooks used in English-speaking countries to reveal the underlying social values, beliefs and ideology. I will analyse what Korean textbooks select as a “traditional and formal marriage” culture, how they describe it (who is being highlighted or excluded), and whose viewpoint is represented. According to the analysis, Korean textbooks’ marriage culture involved the “Confucian patriarchal ideology” centred on male adults, which is one of Korea’s major ideologies, and the “romantic love ideology” to conceal the fact that modern materialism has a stronger influence on marriage than love. This tendency is still marked by patriarchal ideology, and often a patriarchal ideology appears with a romantic love ideology. Through these ideologies, textbooks describe the values of happiness and successful marriage; however, this paper discovered the other side of marriage, where women, poorer and less advantaged people are alienated and materialism is valued.
Research on Parallel Computing Method of Hydrological Data Cube

Hydrological data is characterized by large data volume and high dimension. In view of non-hierarchical dimension data in hydrological data, this paper proposed Segmented Parallel Dwarf Cube (SPD-Cube). Firstly, a high-dimensional cube is divided into several low-dimensional segments. Then by calculating the sub-dwarf of each low-dimensional segment, the storage space required for cube materialization is greatly reduced. Finally, combining Map/Reduce technology to construct, store and query several sub-dwarfs in parallel. Experiments show that SPD-Cube not only realizes highly compressed storage of data, but also realizes efficient query by combining Map/Reduce distributed parallel architecture.