Reviewerly/exHarmony huggingface dataset:
Data augmentation on spontaneous Indonesian automatic speech recognition using statistical machine translation

Abstract Language model plays an important role in decoding process of the automatic speech recognition. The accuracy of spontaneous speech recognition is still very low compared to dictated speech of the Indonesian automatic speech recognition. It is due to the lack of the number of spontaneous data. Collecting spontaneous data is also difficult to do, so one of the candidate solutions is to augment data from existing spontaneous data. In this research, experiments are conducted on language models to improve the accuracy of spontaneous Indonesian speech recognition by conducting data augmentation. Data augmentation in this research is done by using statistical machine translation named ‘Moses’. Language modeling technique used here is n-gram. GMM-HMM is used for acoustic modeling. First, spontaneous text corpus is added to the text corpus, then the data augmentation is conducted. When the language model is formed from the addition of a spontaneous text corpus, there is an increase in accuracy of 3.59% relative to the baseline. When data augmentation is done on language model there is an increase in accuracy of 2.74% relative to the baseline. However, this decrease is considered not significant compared to the effort required in collecting spontaneous data manually.
One example of image digital processing of experimental data obtained by the method of photoelasticity

Abstract The article is devoted to the digital processing interferograms (isochromatic fringe patterns) obtained by the photoelasticity method. The application to interpretate the isochromatic fringe patterns allows us to automate image processing, gets to avoid the routine and time-consuming work. The features of the developed software package are described in detail by means the problem of stretching plate with two symmetrical edge notches. The application’s algorithm includes following main steps: image pre-processing, localization interference fringe, fringe tracing. The application creates a text file containing all the necessary data to further determine the stress-strain state (isochromatic fringe’s number and locus of fringes).
TEllipsoid: Ellipsoidal Display for Videoconference System Transmitting Accurate Gaze Direction

We propose “Tellipsoid”, an ellipsoidal display for the video conference system, that can realize not only accurate eye gaze transmission but also practicality in conferences, namely the convenience and the identity of the displayed face. The display consists of an ellipsoidal screen, small projector and convex mirror, where the bottom-installed projector projects the facial image of a remote participant onto the screen via the convex mirror.
Research on Question Answering System Based on Bi-LSTM and Self-attention Mechanism

With the development of artificial intelligence technology, intelligent question answering has become a hot research direction in the field of natural language processing. This paper proposes a question answering method based on Bi-LSTM and self-attention mechanism model. This method uses Bi-LSTM to encode and align the question and answer respectively, then uses self-attention to obtain the relationship between keywords, and finally performs softmax through the fully connected layer to obtain the similarity between the question and answer. Finally, in the experiment, compared with the traditional attention model, the accuracy rate of this model was increased by 1.6%, and the recall rate was increased by 1.5%.
Sketching in HCI: Research Practice &amp; Publication (Advanced)

Sketching in Human Computer Interaction is a valuable tool for subjective practice, but also a tool for engagement with collaborators, stakeholders, and participants. This hands-on practice can be utilised in a variety of contexts. The course enables those already in possession of sketching skills the confidence to take their work to the next level. Drawing from expertise gained by working in both academia and industry, the instructors will lead course attendees on a journey through practical applications of sketching in HCI, from subjective sketching to participant engagement and publishing, using hands on tasks and group activities.
On Monotonic Determinacy and Rewritability for Recursive Queries and Views

A query Q is monotonically determined over a set of views if Q can be expressed as a monotonic function of the view image. In the case of relational algebra views and queries, monotonic determinacy coincides with rewritability as a union of conjunctive queries, and it is decidable in important special cases, such as for CQ views and queries. We investigate the situation for views and queries in the recursive query language Datalog. We give both positive and negative results about the ability to decide monotonic determinacy, and also about the co-incidence of monotonic determinacy with Datalog rewritability.
Print-and-Play: 3D-printed Interactive Objects Without Assembly or Calibration

In recent years, 3D-printing technology has become widely accessible to non-experts and hobbyists, enabling them to fabricate objects of varying geometries. In contrast to this new ease of producing new forms, fabricating objects that can sense user input traditionally requires the assembly of complex circuits and physical parts. With my work, I explore what I call \pap: 3D-printed interactive objects without requiring any post-print activities such as assembly or calibration. I approach this by by externally sensing how the user's actions interact with well-studied physical phenomena (e.g., acoustic resonance and fluid dynamics). I have developed two novel techniques using this principle: , a blow-based interaction technique for fabricated objects using acoustic resonance; and , a technique for fabricating touch-sensitive objects using pneumatic sensing and fluid dynamics principles.
How a Scientific Communicator Transforms into a Producer of Scientific Projects

Business approaches to promoting projects are integrated into world science, and scientific communicators are transformed into producers of scientific projects, which are included in the project at the start. They assess the potential for for the scientific community (getting into scientific trends, prospects for publishing work in scientific journals), for government agencies or business, (practical application of research results), for the public. Each trigger multiplies the next one, which allows to achieve cyclicality and to multiply the effect of promoting a scientific project, accumulating the scientist's reputation capital, and getting financial support. The article discusses the case of including the producer of a scientific project in a working group, evaluating the effectiveness.
LibGuides: BrowZine Library: Top Journals

Use BrowZine, on your desktop or mobile device, to easily find, read, and monitor thousands of scholarly journals! Selection of BrowZine pages for top journals
Speckled correlation fringes denoising and demodulation using directional total variation and ridgelet transform

One of the challenges in many industrial activities is to analyze the products and investigate their dimensional properties, such as deformations. The digital speckle pattern interferometry technique offers several solutions for the measurement of wide range of parameters (deformations, displacements...) with high accuracy. Generally, there is a correlation between these parameters and the phase of the noisy reflected intensity images (also called correlation fringe patterns or correlograms) of the tested products. Thus, getting access to these parameters requires a good estimation of the phase information. To extract this phase, we propose a ridgelet transform based algorithm for the fringes demodulation, after have been denoised by a new variant of total variation denoising method. These algorithms provide an automatic estimation of the phase feature with high accuracy. Because of such advantages, this method is particularly suitable for real time analyzing of dynamic events even in perturbative environments.
Creating GUIs with Qt Designer

The previous chapters have focused on learning how to manually code GUIs using PyQt. While setting up and arranging GUIs yourself gives you more control over the design process, not everyone will need or want to take the time to do so. Fortunately, Qt provides a great application for setting up the layouts and designing main windows, widgets, or dialogs. Qt Designer is a graphical interface filled with Qt widgets and other tools used for building GUIs. Using the Qt Designer application’s drag and drop interface, you are able to create and customize your own dialogs, windows, and widgets.
The Commemorative Internet Project as an Instrument of Construction and Preservation of Collective Identity (by the Example of “The Memory Book of the Komi Republic”)

The object of study is commemorative internet project “The Memory book of the Komi Republic” as a tool of preservation and translation of living link to the past. It is revealed that similar projects need enlargement of strictly documented forms by families' stories-legends. It allows to illustrate personal attitude of correspondents to the events recording not only rational but emotional participation too.
Notice of Removal: Augmented Reality Based Data Improvement for the Planning of Aircraft Cabin Conversions

Removed.
Distance Education Management System Considering Load Balancing Strategy of Distributed Crawler System

Based on the features of the load balancing strategy of the distributed crawler system, the functional structure of the distance education management system is analyzed. The key technologies and main database structure of the system based on the load balancing strategy of the distributed crawler system are expounded. In the specific implementation process, the design pattern of the business proxy layer based on the load balancing strategy of the distributed crawler system is introduced. The data interaction strategy among the business proxy layer, presentation layer, and business logic middle layer, as well as the effect of the business proxy model, are elaborated. The application of distance education management system in practical implementation is discussed.
VRsneaky: Stepping into an Audible Virtual World with Gait-Aware Auditory Feedback

New VR experiences allow users to walk extensively in the virtual space. Bigger tracking spaces, treadmills and redirected walking solutions are now available. Yet, certain connections to the user's movement are still not made. Here, we specifically see a shortcoming of representations of locomotion feedback in state-of-the-art VR setups. As shown in our paper, providing synchronized step sounds is important for involving the user further into the experience and virtual world, but is often neglected. VRsneaky detects the user's gait and plays synchronized gait-aware step sounds accordingly by attaching force sensing resistors (FSR) and accelerometers to the user's shoe. In an exciting bank robbery the user will try to rob the bank behind a guards back. The tension will increase as the user has to be aware of each step in this atmospheric experience. Each step will remind the user to pay attention to every movement, as each step will be represented using adaptive step sounds resulting in different noise levels.
The Guiding Role of Reward Based on Phased Goal in Reinforcement Learning

Sparse and delayed rewards have greatly hindered the deep reinforcement learning, which is supposed to acquire the optimal policy by learning from trajectories. Reward shaping, which has previously been introduced to accelerate learning, is one of the most effective methods to tackle this crucial yet challenging problem. However, how to reasonably implement reward shaping needs to be explored. Currently, the method of reward shaping usually requires a large number of expert demonstrations, and the environment is poorly explored. In this paper, we proposed a method of reward shaping---Reinforcement learning framework based on phased goal, which will accelerate learning convergence speed with less expert examples and explore better especially for tasks where environment rewards are particularly sparse. The framework consists of reward based on phased goal and policy learning using PPO2. The process of acquiring designed reward is divided into stage classification and calculation of goal proximity. Experiments proved that our method can effectively alleviate the problem of sparse reward and obtain higher scores in Atari game than basic algorithm.
Speeded-up Convolution Neural Network for classification tasks using multiscale 2-dimensional decomposition

In this paper, we propose a strategy for network simplification and acceleration. First, we propose to generate a suitable resized image using multiscale patching in the first convolutional layer, which can then be used for the rest of the network. We use p convolutional filters that operate on patches of size m × n, and we first select all the possible non-superposed m × n patches from the available images. If the number of such patches is not sufficient, the remaining ones are collected using scales a × b or c × d such that ab = cd = mn or a = 2 m or b = 2n. Patches generated from the former condition are directly extracted from the images, while the downsampled results are used in the latter case. We also introduce a 2-dimensional decomposition for patch compression, by stacking all the available image patches along the columns and applying a 2D PCA decomposition. Finally, a layer weight decomposition technique followed by module-based finetuning is adopted, for a new fast module-based CNN model. Extensive evaluations using public data sets like MNIST, Pascal VOC, and WebCASIA, and with different state-of-the art CNN architectures like Open-Face, VGG and DarkNet verify that our proposed model is able to accelerate the training process and even to provide higher classification accuracies for small-sized datasets. We obtain 8% increase in Top-1 and Top-5 recognition rates, and 5% increase in F1 score over general interpolation-based resizing.
Thermal bar studies in the Krasnoyarsk Reservoir based on remote sensing datasets

Abstract We study a possibility of using remote sensing datasets to identify a thermal bar in the Krasnoyarsk Reservoir. MODIS thermal band data have been used to produce sets of images showing temporal and spatial temperature distribution across the Krasnoyarsk Reservoir. Thematic maps of temperature distribution across the reservoir have been derived for the spring period of 2016-2019, which show the thermal bar period to commence and end up within about one and the same time interval.
Utilizing Response Time to Find In-between Ratings within Likes and Dislikes

Binary rating methods are known to allow easier and quicker ratings, yet they do not allow users to express how much they like/dislike an item. In this study, we argue that response times in ratings can be used to gauge the degree or strength of user ratings. We asked users to rate a set of movies while collecting individual response times, confidence levels, and reasons for user ratings. We investigate (1) the possibility of utilizing response time as a way to further distinguish likes and dislikes, and (2) the various factors that affect rating time. We find that response time can be used to distinguish between sure and unsure answers, as well as the mental process users take before rating an item. We believe that our study will be informative to better find user preferences and relations between explicit ratings and implicit data.
An Evolutionary Computing Solution to the Jump It Problem

In this paper, we present an evolutionary computing solution to the Jump-It game problem, which is a board playing optimization problem. We compare the evolutionary computing solution with a dynamic programming solution to the problem. We also report on how we used the Jump-It problem to introduce evolutionary computing to undergraduate students in a data mining course.
Ludo Game Implementation to Improve Student’s Motivation and Interest to Learn Mathematics for 3<sup>rd</sup> Grade in SDN 19 Nan Sabaris

Abstract This research is motivated by the low interest and motivation of students to learn mathematics in the third grade of SDN 19 Nan Sabaris. The purpose of this study was to see the effect of Ludo media to increase the interest and motivation of mathematics learning in third grade students of SDN 19 Nan Sabaris. This type of research is quasi-experimental with a sample of all third grade students of SDN 19 Nan Sabaris registered in the 2018/2019 school year. The research instrument used was in the form of a questionnaire to see motivation and student learning interest in mathematics in grade III of SDN 19 Nan Sabaris. The data analysis technique used is paired-sample t-test. The results of data analysis showed that there were significant differences in the results of interest in and motivation to learn mathematics in third grade students at SDN 19 Nan Sabaris. This means that the use of ludo game media can significantly increase students’ interest and motivation in learning about Mathematics.
Multi-Feature Fusion Aerial Image Segmentation in Complex Background

The hybrid method of initial partitioning and region merging is widely used in aerial image segmentation. The existing initial partitioning methods are the watershed transform of the Edge Strength Map (ESM) of aerial images. Therefore, if watershed algorithm is used in images with discontinuous edges and lots of noise, it will be easy to produce "improper segmentation". In order to form high-quality initial partitions, we propose a new MRF (YMRF) image segmentation method from the perspective of fully exploiting the image spatial information. The key points of region merging are region similarity measurement, merging process and merging stopping moment, but the problem of region label selection is ignored after the region pair which will be merged is selected. So, we propose a kind of image scene to reflect the necessity of paying attention to this problem and develop a region merging label selection mechanism for the image scene. To solve the problem that merging stopping moment tends to form the result with high homogeneity in the domain, we propose a optimal merging state, which can weaken the homogeneity in the domain. Experimental results show that our algorithm is more effective than the existing methods, when they are used in our unique dataset.
Understanding the Design of Playful Gustosonic Experiences

Sound plays a vital role in our relationship with food, this is highlighted through the term "gustosonic experience". However, when it comes to designing celebratory technology for eating - i.e. technology that celebrates the experiential and in particular often playful aspects of eating , the use of sound has been mostly underexplored. My PhD research explores the opportunity to use interactive technology to enrich playful eating experiences through sounds. Via a research-through-design approach, I designed and evaluated two systems that generate digital sounds as a result of eating ice cream, contributing to our understanding of the design of interactive gustosonic experiences. I hope that this work can guide designers in creating gustosonic experiences supporting a more playful relationship with food.
Determination of catacaustics through cyclographic mapping

Abstract The paper presents a general algorithm of determination of catacaustics given a curvilinear source and a reflector. The algorithm is based on the method of cyclographic mapping as well as the optical property of a cyclographic projection of a spatial curve. The algorithm is consistent and universal; it is suitable for every problem where the light source is given in the form of a central, parallel or diffuse bundle of rays. Through the presented algorithm the analytic solution to the problem of determination of catacaustics is acquired. The results of the study can be utilized in applied geometric optics in design of optical systems consisting of the triad of elements: a light source, a reflector and a receiver.
Mind the gap: Understanding stakeholder reactions to different types of data security

Data security breaches are an increasingly common problem for organizations, yet there are critical gaps in our understanding of how different stakeholders understand and evaluate organizations that have experienced these kinds of security breaches. While organizations have developed relatively standard approaches to responding to security breaches that: (1) acknowledge the situation; (2) highlight how much they value their stakeholders’ privacy and private information; and (3) focus on correcting and preventing the problem in the future, the effectiveness of this response strategy and factors influencing it have not been adequately explored. This experiment focuses on a 2 (type of organization) x 2 (prior knowledge of breach risk) with a control group design. Findings suggest that perceptions of competence is the most important factor influencing outcome variables like behavioral intention and social responsibility evaluations.
A Comparative Study on Bayesian Optimization

Well-known as an effective algorithm for optimizing expensive black-box functions, the popularity of Bayesian Optimization has surged in recent years alongside with the rise of machine learning thanks to its role as the most important algorithm for hyperparameter optimization. Many have used it, few would comprehend, since behind this powerful technique is a plethora of complex mathematical concepts most computer scientists and machine learning practitioners could barely familiarize themselves with. Even its simplest and most traditional building block - Gaussian Process - alone would involve enough advanced multivariate probability that can fill hundreds of pages. This work reviews this powerful algorithm and its traditional components such as Gaussian Process and Upper Confidence Bound in an alternative way by presenting a fresh intuition and filtering the complications of mathematics. Our paper will serve well as a functional reference for applied computer scientists who seek for a quick understanding of the subject to apply the tool more effectively.
The matching of images based on de Rham current formation

Abstract The application of the de Rham current theory for matching forms of images is considered. The determination the measure of differences between simplicial complexes of forms does not imply a point bijective correspondence between the structures of objects. The RKHS method for obtaining object shape metrics is proposed. The study of the forms of objects is proposed to be carried out by forming test vector fields. Simplicial complexes of objects can be supplemented by the functions of the elements representing the signals. To improve the accuracy of matching the forms of the source and terminal images, the original image is subjected to preliminary affine transformation. The minimization of the functional of the squared distance between the image forms is carried out on the basis of the QPSO algorithm.
Online Survey Methodology for User Experience Research

Online surveys are an extremely popular research method in HCI and UX research. Surveys are often perceived to be easy to create [1] and sometimes used even if they are not the most appropriate method [7]. This course will review state-of-the-art methods, drawing from the past 20 years of research on online surveys [3, 4] and present applications for the user experience and HCI context [8]. Upon completion of the class, attendees will have a framework of survey quality, a roadmap to plan & implement, and resources to extend their knowledge of surveys for HCI and UX research. The instructors have conducted hundreds of surveys that tech companies use on a regular basis to inform business and product decisions. They also consult and reviews surveys on a daily basis. Finally, they regularly teach survey research, and have been instrumental in connecting User Experience Research with survey research principles and measurement best practices.