Reviewerly/exHarmony huggingface dataset:
A scalable load generation framework for evaluation of video streaming workflows in the cloud

HTTP Adaptive Streaming (HAS) is increasingly deployed at large, gradually replacing traditional broadcast. However, testing large-scale deployments remains challenging, costly and error-prone. Especially, testing with realistic streaming loads from massive numbers of users is challenging and costly. To improve this, we introduce an open-source load testing tool that can be deployed in the cloud or on-premise in a distributed manner, for load generation.
Eye Movement Data Analysis

The aim of the present study is to investigate the separation abilities of three statistical parameters for grouping participants in the visual-motor experiment by their age and gender. These parameters represent different characteristics of the decision-making process and were determined by applying the hierarchical drift diffusion model to the response time and accuracy of the experimental data [1]. The objective function cluster analysis was applied to explore distinct data spaces formed by the parameters’ data. The ability for grouping is assessed and interpreted according to the differences in the subjects’ capabilities to perform the visuo-motor task. The study compares the conclusions based by drift-diffusion model using Bayesian parameter estimation with those based on the cluster analysis in terms of ability to distinguish the performance of different age groups. The investigation of gender effects are uniquely investigated by cluster analysis technique.
Inferring SQL Queries Using Interactivity

Interactivity in language processing plays a pivotal role to allow models to better understand how to build the appropriate output. In the task of Natural Language to SQL, the fact of including the users' interactivity can be one of the practical solutions that haven't been studied deeply in the existing works published in the last decade. Using databases by users with limited familiarity in SQL will create an additional obstacle for these users to better exploit the content stored in the database systems. In this paper we present the already published studies and we discuss the utility of using the interactivity to definitely improve the query generation process in order to construct a model that generalize for unseen and complex sentences and to automatically generate the appropriate outputs.
Modeling the Uncertainty in Pointing of Moving Targets with Arbitrary Shapes

When we try to acquire moving targets such as shooting enemies in computer games, the shapes of these targets are often varied. Considering the effects of target shape in moving target selection is essential for predicting user performances such as error rate in user interfaces involving dynamic content. In this paper, we propose a model to be descriptive of the endpoint uncertainty in pointing of moving targets with arbitrary shapes. The model combines the Gaussian mixture model (GMM) with a Ternary-Gaussian model to describe the impacts of target shape and target motion on selection endpoints of moving targets. Compared to the-state-of-the-art, our model achieved higher performance in the fitting of endpoint distribution and predicting selection error rate.
The Hyper360 Toolset For Enriched 360° Video

360° video is a novel media format, rapidly becoming adopted in media production and consumption as part of today’s ongoing virtual reality revolution. Due to its novelty, there is a lack of tools for producing highly engaging 360° video for consumption on a multitude of platforms. In this work, we describe the work done so far in the Hyper360 project on tools for 360° video. Furthermore, the first pilots which have been produced with the Hyper360 tools are presented.
Exploring Acceptability and Utility of Deformable Interactive Garment Buttons

Wearable devices have received tremendous interest in fitness and personal assistance sectors. Yet most are still worn as auxiliary hardware; falling short in ubiquity and convenience. We examine the potential of a novel deformable wearable device that embeds interactive technologies into garment buttons, and seek to enhance the form factor of buttons to incorporate deformation and motion as inputs. We surveyed garment buttons in everyday clothing to inform an exploratory study, where we investigated social acceptance and elicited interaction gestures using mockups. Our results indicate people mostly prefer smaller sizes, and regard sleeves as the most comfortable area to operate and look at when seen by others. Based on our findings, we discuss potential context of use, possible applications, and future work.
Mobile learning

Challenges faced by the Indonesian tertiary education in implementing mobile learning are mainly related to pedagogical problems rather than technological ones. This preliminary study has identified several problems faced by the tertiary students in their learning. This insight should inform how the design of a sustainable mobile learning ecosystem can be implemented in Indonesia.
Single Image Intrinsic Decomposition Using Transfer Learning

Separating an RGB image into its albedo and shading maps abstracts the idea behind intrinsic image decomposition. It is a prolonged and underdetermined problem in computer vision, and we aim to tackle this problem using an efficient and optimized method. This work is an attempt to decompose the input image into its albedo and shading component using a Deep Convolution Neural Network (DCNN) model considering an encoder-decoder based architecture. Our model uses a pre-trained DenseNet-169 as an encoder for the input image and two decoders for the two output images viz. albedo and shading. The synthetic ground truth images from MPI-Sintel dataset helps in the dense supervision of our model. We show results for both synthetic images and real images from the IIW dataset. Our architecture aims to reduce the number of parameters used while training and has produced better results when compared with previous approaches on the MPI-Sintel dataset.
A Tool to Add a Tutee Agent in a Monologue Lecture Video Improves Students' Watching Experience

Monologue style lecture video is the majority format delivered on most distance learning platforms such as MOOCs. However, studies found that observing dialogue between a tutor and a tutee could produce better learning than the monologue one, as the observer student learns more from the tutee than the tutor when they are observing the dialogue. In this study, we enhanced the existing monologue video into a dialogue-like video by adding a tutee agent. We propose a system that transforms monologue video into a dialogue-like video. In the initial user study, we found that most of the observer students in our experiment preferred watching dialogue-like lecture videos with tutee agent and had better learning experiences than the monologue one.
The Representation of Food-Related Environments in Virtual Reality

Virtual reality (VR) potentially provides an innovative tool for nutrition education/counselling. The objective of this study was to determine the a) sense of ‘presence’ (the feeling of being in a scene) experienced in two food related VR scenes b) capture information regarding the participants experiences in VR. Two 3D, food-related scenes were created for this study: supermarket or fast food restaurant. The scenes were displayed using a VR head mounted display or on a standard PC monitor. The participants were able to move around each scene and could interact with various elements to obtain nutrition information about a food. Thirty-one adults were recruited for this study and reported to the laboratory on 4 occasions separated by at least 48 hours. Participants were randomized to a treatment order. On reporting to the laboratory, the participants had surface electrodes attached to determine heart rate and electrodermal activity. The participant was then required to sit quietly for 10 minutes for baseline measures to be collected. Then, in the VR treatments, a VR headset was placed on the participants head and the relevant scene displayed. For the PC treatments, the same scenes were displayed on a PC monitor. The participants were required to remain in the different scenes for at least 5 minutes. Then, the headset was removed and the participant completed questionnaires regarding their experiences in the VR and PC scenes. Participants ranged in age from <25 years to over 65 years. All participants used computers in their daily life but generally had no or little experience in VR. Participants reported a higher sense of presence in the VR treatments compared to the PC treatments (P < 0.05). The VR scenes also created a greater sense of the scene being the ‘dominant reality’ and elicited a greater sense that the participant were actually in the scene (P < 0.05). There was no difference in the participant's ability to complete tasks in the VR and PC scenes. Moreover, feelings of nausea were not different between the VR and PC scenes. The participant's heart rate was significantly higher in the VR treatments (P < 0.05). This study provides data that supports the development of VR as a nutrition education/counselling tool. Further research is required to develop VR as an effective education tool. None.
Orthogonal projections on hyperplanes intertwined with unitaries

Fix a point in a finite-dimensional complex vector space and consider the sequence of iterates of this point under the composition of a unitary map with the orthogonal projection on the hyperplane orthogonal to the starting point. We prove that, generically, the series of the squared norms of these iterates sums to the dimension of the underlying space. This leads us to construct a (device-dependent) dimension witness for quantum systems which involves the probabilities of obtaining certain strings of outcomes in a sequential yes-no measurement. The exact formula for this series in non-generic cases is provided as well as its analogue in the real case.
Discovering Specific Sales Patterns Among Different Market Segments

Formulating different marketing strategies to apply to various market segments is a noteworthy undertaking for marketing managers. Accordingly, marketing managers should identify sales patterns among different market segments. The study initially applies the concept of recency–frequency–monetary (RFM) scores to segment transaction datasets into several sub-datasets (market segments) and discovers RFM itemsets from these market segments. In addition, three sales features (unique, common, and particular sales patterns) are defined to identify various sales patterns in this study. In particular, a new criterion (contrast support) is also proposed to discover notable sales patterns among different market segments. This study develops an algorithm, called sales pattern mining (SPMING), for discovering RFM itemsets from several RFM-based market segments and then identifying unique, common, and particular sales patterns. The experimental results from two real datasets show that the SPMING algorithm can discover specific sales patterns in various market segments.
A Distributed Information Retrieval Approach for Copyright Protection

Developments in telecommunications technology has opened up the possibility of circumventing intellectual property in the digital world, outside the legal and technical methods proposed for copyright protection, the information retrieval is considered as a computer field helping to protect these rights by proposing methods of search, analysis and comparison for protected documents.
ScriptFree: Designing Speech Preparation Systems with Adaptive Visual Reliance Control on Script

Manuscript speech is a common type of speech in various official events. However, we often observe that many speakers simply read the script without making eye contact, thereby lowering audience engagement. Practice with proper tools could benefit a speaker considerably. In this work, we iteratively designed ScriptFree, an adaptive speech practice environment where off-the-shelf automatic speech recognition (ASR) is leveraged to measure a speaker's preparation level, and accordingly, the script is adaptively compressed to reduce the speaker's visual reliance toward script mastery. The user study results confirmed that ScriptFree helped the participants to success- fully improve their speech over multiple practice iterations. The results have significant design implications for building adaptive speech practice systems.
Some approaches for determining isomorphism of semigroups of small order

Abstract For a given set of graphs or graph generation algorithm, it is possible to determine a set of invariants whose computational complexity will be low, and this set will work effectively in solving the problem of determining the non-isomorphism of graphs on this set of graphs. We described and investigated in detail two invariants of semigroups, reducing them to invariants of graphs, and then compared the effectiveness of these invariants for algorithmizing the problem of determining the non-isomorphism of semigroups. The comparison results are given in the article.
The Design Of The Semester Exam Scheduling Application At The State Polytechnic Of Sriwijaya

Abstract Scheduling a semester exam at Sriwijaya State Polytechnic is an activity that is always done at the end of each semester. To meet the needs of preparing for the semester exam schedule requires special time and attention so that the exam schedule can be arranged properly. Preparing the semester exam scheduling will be better by using a computer application, so that the leadership and administration can more easily arrange the semester exam scheduling. In addition students and examiners can find out the exam schedule that must be done through the application. But the semester exam scheduling application is not yet available at educational institutions. Before building a good semester exam scheduling application requires a semester exam scheduling application design, so this design can meet all the needs needed when building an application. For this reason, this study aims to build the design of semester exam scheduling applications that can be used by admins, leaders, students and supervisors.
Mixed methods feasibility study of Breathe2Sleep™ a peer modeling approach to PAP self-management.

•PAP adherence interventions require multimodal approaches to address patient needs and preferences. •The first week of PAP use is essential to support self- management and adherence. •Peer modeling self-management program of Breathe2Sleep is based on expert patient experiences underpinning the support through psychoeducational and cognitive behavioral approaches to improve motivation and support for self-management. •This web-based self-tailored self-management program can offer easily accessible support for new PAP users that could be implemented in primary care.
Ten ways of leveraging ontologies for natural language processing and its enterprise applications

In the last years, Artificial Intelligence and Deep Learning have matured from a facinating research area to real-word applications across multiple domains. Enterprises adopt data-driven approaches for various use cases. With the increased adoption, such issues as governance of the models, deployment, scalability, reusablity and maintenance are widely addressed on the engineering side, but not so much on the knowledge side. In this paper, we demonstrate 10 ways of leveraging ontology for Natural Language Processing. Specifically, we explore the usage of ontologies and related standards for labeling schema, configuration, providing lexical data, powering rule engine and automated generation of rules, as well as providing a standard output format. Additionally, we discuss three NLP-based applications: semantic search, question answering and natural language querying and show how they can benefit from ontology usage. The paper summarizes our experience of using ontology in a number of projects for medical, enterprise, financial, legal and security domains.
New role model for teachers in Higher Education?

Abstract The traditional university was for decades not called into question as a place for R---amp---D and higher education. At the one hand this enabled successful independent research, at the other hand there was few need to reflect traditional structures of knowledge transfer. The nowadays omnipresent decrease in financial resources has caused universities to compete for financial support from the business sector; additionally universities have to justify their existence for their duties in education for providing the society with academic skilled working forces. This leads to a competition between the universities and to attract applicants they have to boost the attractivity of the offered study programs. Education became a market. The traditional methods of ex-cathedra teaching have been the standard mean of knowledge transfer for a long time. The pedagogical concepts at the tertiary level were neglected; in many institutions the teaching duties were seen more as a burden than mission. The paper will show that the values of our great philosophers are still valid and how the new teaching approach of Dual Education can fulfill requirements of industry for young academics at the entrance to business life. The development of dual study programs and a new pedagogical approach in teaching methods may be one mean to face the challenges for the successful education especially in the technical sciences.
Modeling a Musician Performing on a Digital Musical Instrument as a Communications Channel

A musician performing on a digital musical instrument is modeled as a feed-forward communications channel. A variety of statements are made on the mutual information of the signals flowing through the model. For example, data processing can only reduce or retain mutual information, not increase it.
Adaptive Thouless–Anderson–Palmer Equation for Higher-order Markov Random Fields

The adaptive Thouless–Anderson–Palmer (TAP) mean-field approximation is one of the advanced mean-field approaches, and it is known as a powerful accurate method for Markov random fields (MRFs) with quadratic interactions (pairwise MRFs). In this study, an extension of the adaptive TAP approximation for MRFs with many-body interactions (higher-order MRFs) is developed. We show that the adaptive TAP equation for pairwise MRFs is derived by naive mean-field approximation with diagonal consistency. Based on the equivalence of the approximate equation obtained from the naive mean-field approximation with diagonal consistency and the adaptive TAP equation in pairwise MRFs, we formulate approximate equations for higher-order Boltzmann machines, which is one of simplest higher-order MRFs, via the naive mean-field approximation with diagonal consistency.
An efficient author information retrieval tool for bibliographic record analysis

Digital Bibliography and Library Project dataset is a collection of bibliographic records of computer science publications of various authors and co-authors. It contains approximately 1.5 million bibliographic records. An algorithm for an author’s information retrieval is developed to retrieve deta ils of specific author publications and correlation among authors. Further performance of an author is measured with parameters like consistency, contribution factor, stability, cooperativeness, and solidity. The work presented is tested on the DBLP dataset. Experimental results clearly support the claim that it works efficiently for retrieving specific author-publication records and its analysis with respect to suggested parameters.
Micro pave setting for the triple moon goddess jewelry set designs

Abstract Generally, jewelry is made from gold and silver with the addition of the jewel itself. Frack &amp; Co usually use a diamond with level F color and clarity of DVS (Very Slight Inclusions). Thus jewelry has purposes as beautify of its user, it has another purpose which is as the prestige of the lifestyle of the user. In this research analyzed trends, color, and price. Based on the market-targeted analysis, jewelry design is produced based on two classes of price, the middle-class user (approx. 15-45 million) and the high-class user (45-85 million). The Triple Moon Goddess jewelry set design is using white gold and rose gold 18K and diamond with 0.0010C-0.042C by using the technique of Micro Pave setting and round ash facets, so the diamond looks brighter and bigger. The concept design is based on 3 moon symbols with a crescent shape, full moon, and crescent moon sequence. It is referring to the symbol of life birth, maturity, and wisdom. The jewelry set consists of a woman ring, a bracelet, and a pair of earrings. The production process uses the wax tree and gold casting process.
Performance of super-resolution algorithms under applicative noise

Abstract The paper considers the problem of multi-frame super-resolution under applicative noise which generates distributed regions of outlying observations in low resolution images. The analysis of existing solutions is performed. They include algorithms based on spin-glass models and Markov random fields used to remove applicative noise. The authors suggest their own approach, which involves using a recurrent algorithm of quasi-linear optimal filtering of a sequence of low resolution images together with superpixel segmentation performed in order to determine the regions damaged by applicative noise. The considered algorithms are compared as applied to a set of test images. The results of the experiment demonstrate that the suggested approach allows for more accurate recovery of HR images than the existing analogues.
Blog-based mathematics learning devices

Abstract The development of science and technology today requires learning science and technology-based innovation. Educators must be able to innovate learning by utilizing the internet. Blog-based learning is important as an alternative learning. The purpose of this research is to produce a valid, practical and effective blog-based mathematics learning tools developed consist of RPP, Modules, and the Mathematics Learning Blog. This research is a research developed. The development model used is the ADDIE model (Analyse, Design, Development, Implementation, Evaluation). The subject of the research was grade X students. Based on the results of the development it was obtained that the result of blog-based mathematics learning that were developed met valid, practical, and effective criteria.
Cross-layer approaches for improving the dependability of deep learning systems

Deep Neural Networks (DNNs) - the state-of-the-art computational models for many Artificial Intelligence (AI) applications - are inherently compute and resource-intensive and, hence, cannot exploit traditional redundancy-based fault mitigation techniques for enhancing the dependability of DNN-based systems. Therefore, there is a dire need to search for alternate methods that can improve their reliability without high expenditure of resources by exploiting the intrinsic characteristics of these networks. In this paper, we present cross-layer approaches that, based on the intrinsic characteristics of DNNs, employ software and hardware-level modifications for improving the resilience of DNN-based systems to hardware-level faults, e.g., soft errors and permanent faults.