Reviewerly/exHarmony huggingface dataset:
An Intraoral Camera for Supporting Assistive Devices

Though much research has been conducted into improving the quality of life for individuals with paralysis, there is relatively limited work in this regard on the tongue-computer interface. The tongue is a muscular organ directly connected to the brain through a cranial nerve known as the hypoglossal nerve which is responsible for the motor functions of the tongue. Hence, tongue movements are not affected during spinal cord injuries, which is one of the major causes of paralysis. We propose in this paper a novel method for capturing inputs from the tongue using an intraoral camera. An endoscope camera is attached to a personalized mouthguard to capture images of the tongue. The intraoral environment is lit up with LEDs carefully placed at angles to ensure the images of the tongue are of adequate quality for the processing stage. The features of the captured images of the tongue are then extracted in real-time using image processing techniques which are primarily aimed at efficiently obtaining the contour of the tongue along with the centroid of the detected region. This helps to obtain the orientation and position of the tongue, and the system was successfully able to classify this information into one of 11 possible categories, thus producing 11 distinct outputs for the system which can be used by paralytic patients as inputs to any assistive device. The number of outputs obtained for the developed system are more than most of the other currently available solutions. After testing the system with a data entry application, an average of 19.34 correct selections per minute was obtained from 5 different experiments. In addition, an average error percentage per trial of 3.96% was achieved. The advantages of using the intraoral camera include the non-invasive nature of the system, the number of options available for the user at a given instance, and not requiring the tongue to establish any contact with a sensor or device.
SMALL INFINITARY EPISTEMIC LOGICS

Abstract We develop a series of small infinitary epistemic logics to study deductive inference involving intra-/interpersonal beliefs/knowledge such as common knowledge, common beliefs, and infinite regress of beliefs. Specifically, propositional epistemic logics GL ( L α ) are presented for ordinal α up to a given α o ( α o ≥ ω ) so that GL( L 0 ) is finitary KD n with n agents and GL( L α ) ( α ≥ 1) allows conjunctions of certain countably infinite formulae. GL( L α ) is small in that the language is countable and can be constructive. The set of formulae L α is increasing up to α = ω but stops at ω We present Kripke-completeness for GL( L α ) for each α ≤ ω, which is proved using the Rasiowa–Sikorski lemma and Tanaka–Ono lemma. GL( L α ) has a sufficient expressive power to discuss intra-/interpersonal beliefs with infinite lengths. As applications, we discuss the explicit definability of Axioms T (truthfulness), 4 (positive introspection), 5 (negative introspection), and of common knowledge in GL( L α ) Also, we discuss the rationalizability concept in game theory in our framework. We evaluate where these discussions are done in the series GL( L α ), α ≤ ω .
Combinatorial search in two and more rounds

In a combinatorial search problem we wish to identify an unknown element by binary tests, where the edges of a hypergraph specify the available tests. We show that, for rather general cases of this problem, the worst-case minimum number of tests, even if adaptive testing is permitted, can already be achieved in a small number of rounds of parallel tests. In particular, the maximum number of necessary rounds grows only as the square root of the number of elements, and two rounds are enough if, e.g., the test number is close to the number of elements, or the hypergraph is a graph. We also provide polynomial-time, hardness, and parameterized results on the computational complexity of finding optimal strategies for some cases, including graphs and tree hypergraphs. • We study multi-round combinatorial search on test hypergraphs in full generality. • We show a tight bound on the number of rounds needed for the optimal test number. • In several natural cases, strategies with optimal test number need only two rounds. • Related computational problems are NP-hard but fixed-parameter tractable. • The case of graphs can be completely solved in polynomial time.
Point-Based Policy Synthesis for POMDPs With Boolean and Quantitative Objectives

Effectively planning robust executions under uncertainty is critical for building autonomous robots. Partially observable Markov decision processes (POMDPs) provide a standard framework for modeling many robot applications under uncertainty. We study POMDPs with two kinds of objectives: (1) Boolean objectives for a correctness guarantee of accomplishing tasks and (2) quantitative objectives for optimal behaviors. For robotic domains that require both correctness and optimality, POMDPs with Boolean and quantitative objectives are natural formulations. We present a practical policy synthesis approach for POMDPs with Boolean and quantitative objectives by combining policy iteration and policy synthesis for POMDPs with only Boolean objectives. To improve efficiency, our approach produces approximate policies by performing the point-based backup on a small set of representative beliefs. Despite being approximate, our approach maintains validity (satisfying Boolean objectives) and guarantees improved policies at each iteration before termination. Moreover, the error due to approximation is bounded. We evaluate our approach in several robotic domains. The results show that our approach produces good approximate policies that guarantee task completion.
Personas in Use

Whether you work with user journeys, user stories, use cases, scenarios, wire frames, or any other tool that helps you imagine a future system or product, your aim is to understand how different people are going to interact with it.
Providing Professional Self-realization for Technical University Students when Teaching the Humanities

Development of professional competence is impossible without professional self-realization of a student at the University. This article discusses features and conditions of professional self-realization of a Technical University student during their research work (in the humanities) and a model of professional self-realization. The paper is both of theoretical and practical importance. Factors and basic components of student professional self-realization are defined. In the practical part of the study, they are applied to the scientific research training of students. The key concept of study, that is an individual educational path, is projected onto the student scientific activity and is used in its version - individual scientific-educational path. This concept is the basis for a soft model of research and educational process differentiation, as well as for the personality-centered education technologies piloted by the authors in a technical university, based on the example of the humanities. The methods used in the research are empirical (observation), polling methods (surveys), modeling, and the method of competences evaluation.
MMSE detection method in uplink massive MIMO systems based on quantum computing

The minimum mean square error (MMSE) detection method involved matrix inversion operation with excessive computational burden. In this paper, we develop an improved quantum linear system algorithm to solve matrix inversion problem of the MMSE detection method in uplink massive multiple-input and multiple-output (MIMO) systems. In order to apply reasonably the robust computational power of quantum computing, we optimize the preparation of the input state and the extraction of the solution from the final entangled quantum state. We prove that this algorithm can reduce computational complexity to O(Nlog⁡N).
Wearable Device Forensic: Probable Case Studies and Proposed Methodology

Wearable devices have become the face of neoteric technology. What started off as a fashionable trend is gradually becoming an integral part of the user. Devices such as Google Glasses, FitBit, iWatch and other smart watches have been dominating the tech-savvy niche for a while now. The continual real time data collected by wearable devices could be used as forensic evidence to get to an accurate conclusion. Due to the heterogeneous nature of data collected by wearable devices, evidence acquired categorizes into different fields. Data collected by wearable tech of great use in the cracking of cases since it is the closet to the user on a personal level. In certain cases, it has also reduced the time taken to get to the inference. Data collected by these devices that can be utilized for forensics are Geo-location information, Physical and health information of the user, Logs of activities, Account details of Social Media Interaction, Calendar details, Media files, Key Generation Mechanism and Key-Gen logs, etc. This paper details about the practicality of the Digital Forensics of Wearable Devices. A methodology that can be used for the Forensic Analysis has been proposed. The Similarities and the Differences between the Mobile Forensics and Wearable Devices. The Challenges faced during Forensics of Wearable Devices due to ambiguities in present forensic technologies.
Edge Preserved Herringbone Artifact Removal from MRI Using Two-Stage Variational Mode Decomposition

Magnetic Resonance Imaging (MRI) is an efficient and non-invasive method for analyzing the structural features and functional behaviors of internal organs and tissues for medical diagnosis. The artifacts present in MRI mislead the diagnostic procedure. Herringbone artifact is a hardware artifact generated from the outlier in k-space measurement. In realtime MRI, the herringbone artifact has non-stationary noise characteristics. The non-stationary noise characteristics affect the high-frequency characteristics which in turn results in an improper estimation of structural details of the image in the processing stage. The objective of the present work is to exploit the properties of the variational mode decomposition (VMD) in reducing the effective herringbone noise at selected spectral regions (high-frequency regions in particular) of the given MRI data. In the present work, the given herringbone artifact affected image is subjected to VMD in two stages. The reconstructed image by removing the higher frequency VMD modes in two-stages found to enhance the noisy MRI data. In the second stage of processing, the discarded higher frequency VMD mode in the first stage is further decomposed into component modes in order to preserve the high-frequency details. The enhanced image is later reconstructed by adding low-frequency modes obtained in both decomposition stages. The effectiveness of the proposed two-stage VMD based enhancement is confirmed from the improved scores obtained from the non-reference quality measures such as Blind Referenceless Image Spatial Quality Evaluator (BRISQUE) and Naturalness Image Quality Evaluator (NIQE).
Missing sensor network data

We describe details of a missing data method for longitudinal motion sensor data. The method uses Markov Chain Monte Carlo computations on a Bayesian Markovian hierarchical model that is designed for computational efficiency on large data sets. The model can handle special structure of missing sensor observations including intervals of downtime, corrupted neighboring data, and highly correlated observations.
Visualizing Stylistic Differences in Chinese Synonyms

Synonyms and near-synonyms are a major source of difficulty in the acquisition of Chinese vocabulary, possibly due to the formal similarities between them. It is also difficult to describe their stylistic differences in a clear and objective manner. The observations found in reference works such as dictionaries can be vague, equivocal, and limited in explanatory power. The present paper demonstrates how the corpus-based, multi-feature, multi-dimensional framework for studying register variation (Biber in Variation across speech and writing. Cambridge University Press, New York, 1988) and Correspondence Analysis, a particular implementation of factor analysis, can be used to show stylistic differences in (near) synonyms by way of two-dimensional bi-plots (“stylistic maps” in a sense). After presenting a two-dimensional analysis for Chinese, five sets of synonyms will be used to demonstrate the approach, together with comparisons with previous observations. Not only can the present approach provide a clearer and more nuanced picture than what introspection allows, it also enables us to go beyond the spoken versus written dichotomy and gain a broader perspective on stylistic variation.
Students’ need on basic English grammar teaching material based on interactive multimedia: an innovative design

This article, a part of dissertation entitled Developing Basic English Grammar Teaching Material based on Interactive Multimedia at University Level, presents the results of a study conducted to find the model of Basic English Grammar teaching material based on interactive multimedia needed by the students. This empirical research employed both quantitative and qualitative analyses. Seventy eight students of English Department of Universitas Negeri Padang were involved. The students were required to articulate their need on a design of Basic English Grammar teaching material based on interactive multimedia. The data were collected through an open questionnaire. The first result is that Basic English Grammar teaching material based on interactive multimedia is very needed (with the score 3.1 out of 4). Second, the result indicates the organization of Basic English Grammar teaching material based on interactive multimedia. The organization consists of six parts. They are Time to watch/sing/read, Time to chat, Time to Focus, Time for fun practice, Time for tube, and Time for action. Third, the students have different learning style. Fourty two students (53.84%) have visual learning style. Twenty two students (28.21%) have audio learning style. The rest, fourteen students (17.95%) have kinestetic learning style. Four, the finding shows the students have their favorite movies, colors, and music. The students like comedy/humor, drama, horror, dokumentary, and action movies; they love pop, jazz, rock, country, and rap music; they adore blue, green, black, pink, and red color. Another important research finding is almost all students (91%) have their own laptop. Those findings will be considerations in designing the Basic English Grammar teaching material based on interactive multimedia. Further research to see the effectiveness of the model of Basic English Grammar teaching material based on interactive multimedia needs to be done.
Experimental realizing image encryption based on optical chaos

Digital image facilitates further cultural exchanges while its potential safety hazards is becoming gradually aus- tere. Therefore assembling the characteristic superiorities of optical chaos and embedded hardware, experimental implementation of image encryption is of great academic value and application prospect. In this paper, we ex- perimental implement a color image encryption system based on optical chaos with ARM-embedded hardware. A vertical-cavity surface emitting laser (VCSEL) subject to positive optoelectronic feedback is utilized in the experiment, and the chaotic signal is gained under suitable parameters. The chaotic optical signal is trans- formed into optical chaotic data through an analog-to-digital converter. In our experiment, optical chaotic data dominates the image encryption process where the improved gravity model and the double sine map are served to encrypt the color image. The encrypted image can be conveyed securely through cloud services, and then our hardware board can inerrably decipher the encrypted image. Experimental results visibly illustrate that we successfully realized the encryption of color images.
Assessing Bioremediation of Soils Polluted with Fuel Oil 6 by Means of Diffuse Reflectance Spectroscopy

This study aimed to assess the bioremediation of soils polluted with fuel oil 6 (FO6) using diffuse reflectance (DR) spectroscopy in the visible and near infrared (Vis-NIR) electromagnetic spectrum. To achieve our goal, we determined the spectral signature of fuel oil 6 (FO6), developed a calibration model to quantify the total petroleum hydrocarbons (TPH), and assessed the bioremediation in soils contaminated with FO6 and inoculated with Pseudomonas aeruginosa. Surface soil samples (SS) (0–30 cm depth) from uncontaminated Entisol soil from Termoesmeraldas Thermal Power Plant, Ecuador and quart sand (QS) samples were spiked with FO6 at a known contamination of 0.5, 1, 3, 6, 9, 12 wt.% on a gravimetric basis. A sample of contaminated Entisol soil was taken to isolate P. aeruginosa from a spill site located in Termoesmeraldas. P. aeruginosa was successfully augmented in a molasses medium. The results suggested that the C–H stretch combination overtone band around 2300 nm is the one that makes the significant contribution to the FO6 spectral signature and for the analysis of FO6 contaminated Entisols soil. The calibration model for QS samples and SS showed an excellent agreement with experimental data R2 = 0.9989 and R2 = 0.9968, respectively. The TPH at 0, 7, 14, 21, and 23 days after inoculation were found using a calibration model developed and the Unach hydrocarbon index (UHI). While the QS samples showed the lower recovery rate (13.6%), the Entisols SS showed the higher recovery rate (45.8%) in 23 days. The use of DR spectroscopy and determination of the FO6 spectral signature allowed the assessment of the bioremediation process of QS and Entisols SS samples. The results showed that DR decreased with increasing the FO6 concentration and soil properties affected the degree of biodegradation.
Usage and impact metrics for Parliamentary libraries

Parliamentary libraries are important in supporting informed decision-making in democracies. Understanding Members’ information needs is important, but the usage and impact of these libraries have been less explored. A particular example of the United Kingdom’s House of Lords Library is studied, collecting and analysing data using techniques from the field of data science. These techniques are useful in extracting information from existing sources that may not have been designed for the purpose of data collection. A number of data sources available at the Lords Library are outlined and an example of how these data can be used to understand Library usage and impact is presented. Results suggest that Member usage varies significantly and that there is a small but significant relationship between usage and making speeches in the chamber. Further work should explore other indicators of impact, but these methods show promise in creating library metrics, particularly in Parliamentary settings.
Cybersecurity: Why Should We be Concerned?

The theme for recent national cybersecurity campaigns emphasized personal accountability and the importance of taking proactive steps to enhance cybersecurity. Personal and professional cyber lines blur as individuals become linked through the integration of the Internet of Things. The responsibility of health care providers to “protect the patient, protect the data” has become a 24/7 obligation. Interprofessional staff add to the challenge. Leadership teams should advance cybersecurity plans to meet the needs of areas such as radiology and support interprofessional education and training for the “connected nurse.”
Instructional Design of CALL Course in Indonesian Higher Education for Future English Teachers: A Case Study

Along with the development of technology, the demand for sufficient preparation program of a future English teacher is increasing. This study aims to explore how the instructional design of Computer Assisted Language Learning (CALL) course in Indonesian higher education for future English Teachers. The focus of this study is on the syllabus implementation of CALL course including the objectives of the CALL course, the CALL materials, and classroom activities in CALL course. The setting of the research was in the English Education Department in one of Islamic University in Indonesia. It is qualitative research with case study design. The data collecting methods are document analysis, observation, and interview. The result revealed that specific syllabus was used in Computer Assisted Language Learning (CALL) preparation program for future English Teachers. It covers of objectives of the CALL course, CALL materials, and CALL activities. The primary objective of the course is those future English teachers are expected to be able to do English teaching and learning using media and technology-based approach. It is reflected on the materials and the activities of CALL course. The materials include theories as well as practices of CALL. Further, the activities encourage future English teachers to review several applications and websites to be used in English teaching and learning, also, practice in designing CALL activities. The implication of this study is for example of designing Computer Assisted Language Learning (CALL) course for future English Teachers
The Groove Pizza

The Groove Pizza is a widely used web application that enables users to program drum patterns on a circular grid. This visualization scheme supports playful rhythm exploration using mathematical concepts like shapes, angles, and patterns. Symmetries and patterns in the visual domain correspond to those in the aural domain and vice versa, giving novice musicians multiple paths into an understanding of rhythm. We discuss the musical and pedagogical design of the Groove Pizza. We then present a variety of real-world drum patterns and discuss how a circular visualization scheme illuminates their structure and functioning.
Effective computer‐assisted pronunciation training based on phone‐sensitive word recommendation

Summary Owing to their autonomous nature, computer‐aided pronunciation training systems are regarded as a useful tool for pronunciation training for beginner‐level students, particularly those who feel uncomfortable having their pronunciation corrected in front of other students or who have difficulty with face‐to‐face training for other reasons. In this study, we propose a computer‐assisted pronunciation training system targeting unacceptable pronunciation due to confusion among contextual allophones, a problem that often emerges from phoneme‐based feedback provided during pronunciation training. To consider the different pronunciation of phonemes according to position, the proposed system is implemented to recommend a set of words focusing on phoneme pairs. Experimental results show that the proposed system results in the improvement of pronunciation skills through training sessions that use recommended words containing phoneme pairs that were initially pronounced incorrectly.
Memetic differential evolution using network centrality measures

The concept of using network centrality measures in the selection process of memetic differential evolution algorithm is proposed. The usual aim for introducing changes in global optimization algorithms is to make it perform better. This short paper does not intend to provide enough experimental details to decide upon the performance of the new method, nevertheless, we definitely obtain interesting insights on how the discovery of local optima were done.