Reviewerly/exHarmony huggingface dataset:
Performance of Electromagnetic Oil Circuit Breakers Under Hyperbaric Conditions

Abstract Understanding the influence of ambient hydrostatic pressure in the electric circuit breaking performance of pressure-compensated (PC) electromagnetically actuated oil circuit breakers is essential for the design of reliable deep ocean power systems. Experiments are conducted using an industry-standard 300-V direct current PC power contactor in a hyperbaric chamber. It is identified that at 150-bar pressure, the circuit breaking duration and arc energy reduce fivefold and threefold, respectively, compared to their performance at 1-bar conditions. At pressures greater than 200 bar, the circuit breaker opening duration increases due to the increase in the viscosity of the dielectric PC oil. This leads to increased arc energy and formation of larger carbon conglomerations due to the breakdown of dielectric oil. During the hyperbaric experiments, the pressure-induced viscosity increase was offset by increasing the oil temperature.
RHCS - A Clinical Recommendation System for Geriatric Patients

Medication errors caused by the mistakes of healthcare professionals are still one of the leading causes of death. The problem is even more serious with the elderly people suffering from multiple health problems at the same time. Clinical recommendation systems can be used to prevent such medication errors. In this paper, we present our clinical recommendation system (RHCS) which generates drug recommendations to assist healthcare professionals in making decisions on treatment process of geriatric patients. Geriatric patients refer to elderly patients aged 65 years or over. One of the distinctive points of our study lies in the methodology used, which is empowering collaborative filtering recommendation approach with historical data of geriatric patients. Its ontology-based approach and compatibility with clinical classification systems also make this study prominent. We evaluated RHCS with different types of evaluation metrics, and the results show that it is promising.
Cactus Environment Machine

Existing machines for lazy evaluation use a flat representation of environments, storing the terms associated with free variables in an array. Combined with a heap, this structure supports the shared intermediate results required by lazy evaluation. We propose and describe an alternative approach that uses a shared environment to minimize the overhead of delayed computations. We show how a shared environment can act as both an environment and a mechanism for sharing results. To formalize this approach, we introduce a calculus that makes the shared environment explicit, as well as a machine to implement the calculus, the Cactus Environment Machine. A simple compiler implements the machine and is used to run experiments for assessing performance. The results show reasonable performance and suggest that incorporating this approach into real-world compilers could yield performance benefits in some scenarios.
Efficient indexing and similarity search using the Geometric Near-neighbor Access Tree (GNAT) for Face-Images Data

Efficient access to large multimedia data sets is urgent need for face recognition systems. The feature vectors that characterize face in images data are often high-dimensional. Due to the high dimensions of feature vectors and the large quantity of images in the data set, efficient and effective indexing structures are necessary to speed up searching and querying operation. In this paper we present an efficient face recognition system by combination features indexed into a metric structure GNAT. Its principle, consists to describe each face of database by A threes features Local binary pattern, Fourier descriptor and Histogram of Oriented Gradient, afterward we index a normalized combined features into a GNAT. We use a similarity measure calculated as an affine linear combination of L1 and L2 metrics. Our experimental results show that our technique is both correct and efficient.
How to Derive the Directionality of Verb Ellipsis in Turkish Coordination from General Word Order

This paper addresses some coordinate structure types in Turkish, a head-final language. It proposes a constraint for head-final languages such that, even in word-order free head-final languages, the predicate must be clause-final: clauses must strictly represent the head-final property of the language. This constraint is parametrized, such that it is (near-)absolute for some head-final languages (e.g. Japanese), but limited to embedded clauses in others (e.g. Turkish). The predictions made by this constraint are borne out in Turkish: This constraint is illustrated for scrambling, for Yes/No questions, and for coordinate structures with identical predicates, showing that the ellipsis of that predicate obeys this parametrized constraint. This has immediate consequences for the directionality of such ellipsis: While both forward and backward ellipsis are possible in Turkish root clauses, only backward ellipsis is allowed in embedded clauses. Additional facts in coordinate structure with predicate ellipsis are shown to follow from this constraint, as well.
Real-Time Video Streaming Based on TFRC Using Communication Logging for 5G HetNet

The fifth-generation (5G) mobile communication system is being researched and developed for launch as a commercial service in 2020. The 5G mobile network will include many radio access technologies, such as LTE, 5G NR, and WLAN. Therefore, a user equipment (UE) will be connected to different types of base stations as it moves within a 5G heterogeneous network. Accordingly, it is assumed that the throughput will change with each change in the serving cell. The 5G mobile network is expected to serve large capacity contents, such as 4K videos. However, a conventional video streaming method cannot effectively use the available bandwidth in a 5G heterogeneous network. In this study, we propose a sending rate adaptation method based on predictions for the available bandwidth. In the proposed method, the available bandwidth is predicted from the communication log data. The communication logging database, including past throughput with its location, is created by a UE. A UE refers to the communication log data for predictions when the serving cell is likely to change. We develop a video streaming device that implements the proposed method and evaluates its performance. The results show that the proposed method can change the sending rate and resolution according to the available bandwidth. The proposed method increases the probability of transmitting high-resolution video, which is not possible with conventional methods. Moreover, we performed subjective evaluation of the transmitted video by the proof-of-concept test. The result of the subjective evaluation shows that the proposed method improves the quality of experience for video streaming.
Digital Curvature Evolution Model for Image Segmentation

Recent works have indicated the potential of using curvature as a regularizer in image segmentation, in particular for the class of thin and elongated objects. These are ubiquitous in biomedical imaging (e.g. vascular networks), in which length regularization can sometime perform badly, as well as in texture identification. However, curvature is a second-order differential measure, and so its estimators are sensitive to noise. The straightforward extensions to Total Variation are not convex, making them a challenge to optimize. State-of-art techniques make use of a coarse approximation of curvature that limits practical applications. We argue that curvature must instead be computed using a multigrid convergent estimator, and we propose in this paper a new digital curvature flow which mimics continuous curvature flow. We illustrate its potential as a post-processing step to a variational segmentation framework.
The School Library Roles in Information Services through Mainstreaming for Enhance 21st Century Learning Skills

Mainstreaming approach are education for all, there are no separation between regular students and special needs students, human rights, respect everyone, and recognition of differences.Encourage appreciation and create a new culture of diversity.Therefore, it is imperative to find a way or innovation to be able to developing skills in the 21st century learning skills and social world of those with special needs equally to others.This article aims to present the concept of mainstreaming in the 21st century.Library 4.0 with role promoting learning for all in the 21st century.Adaptation of librarians to keep pace with digital technology to promote learning and share responsibility for providing digital information services with technology.Participating in joint learning to foster learning in the 21st century, which must find a way and how to design innovation for all learner.And it can be used with everyone in a friendly way, so that students with special needs can be self-reliant and learned together with the normal students side by side.Library service provision is appropriate for mainstreaming and learning in the 21st century.It is important to push for equal education, quality, happiness, skills needed to exist in the 21st century.
Assisting group activity analysis through hand detection and identification in multiple egocentric videos

Research in group activity analysis has put attention to monitor the work and evaluate group and individual performance, which can be reflected towards potential improvements in future group interactions. As a new means to examine individual or joint actions in the group activity, our work investigates the potential of detecting and disambiguating hands of each person in first-person points-of-view videos. Based on the recent developments in automated hand-region extraction from videos, we develop a new multiple-egocentric-video browsing interface that gives easy access to the frames of 1) individual action when only the hands of the viewer are detected, 2) joint action when collective hands are detected, and 3) the viewer checking the others' action as only their hands are detected. We take the evaluation process to explore the effectiveness of our interface with proposed hand-related features which can help perceive actions of interests in the complex analysis of videos involving co-occurred behaviors of multiple people.
A Novel Scheme for Quantum Teleportation of N-Particle Generalized Bell-Type States Using Minimal Entanglement Resources

In this paper, we present an efficient scheme for the teleportation of an arbitrary N-particle generalized Bell-type state using a single Bell pair as entanglement channel. For odd and even N-particle states the scheme slightly differs and it is discussed in detail for the simplest cases, 3 and 4 particle states. Further, we have compared the quantum cost of our scheme with other teleportation schemes which use a single Bell pair as entanglement channel.
Scrambling of quantum information validated by quantum teleportation

The delocalization of information in interacting quantum systems seems to play a key part in their evolution. A method has been developed that could enable the dynamics of this process to be directly probed in experiments. Probing the delocalization of information in interacting quantum systems.
Automatic Altitude Control of Multirotor Aircraft with Consideration of Motion

For the purpose of warehouse stock checking drone development, the automatic altitude control was reconsidered in comparison to human pilot control. The value of gains of PID feedback control were set separately in case that the quadrotor is above or under the command altitude, and is climbing up or descending down. The typical results are shown and discussed in this paper. The proposed technique could control the altitude within ± 0.3 m of error as well as normal human pilot.
On the error-correcting capabilities of iterative error correction codes

The influence of the theory of information on development of the error correcting coding theory has been studied. Main differences between the probabilistic approach and the deterministic approach in the analysis of error-correcting capabilities of different classes of linear codes have been demonstrated.The automaton hierarchical models for analysis of permutation decoding of cyclic codes have been developed and a cyclic permutation generator based on two Moore automata has been proposed.A study has been carried out into the regular and irregular states of linear finite-state machines (LFSM) based on the automaton representation of cyclic codes. A possibility of significant simplification of decoding of cyclic codes based on conversion of irregular LFSM syndromes into regular ones using permutations has been shown.The formalized methods for determination of error-correcting capabilities of iteratively decoded cyclic codes (IDCC) have been devised. They imply the replacementof traditional complete checking of all possible options for comparison of code words to directional search for the solution of the assigned problem, which leads to a significant time saving for calculations. The algorithm for determination of error-correcting capabilities of IDCC with respect to double errors is given.It has been shown that all iterative codes increase their error-correcting capabilities with an increase in the number of iterations and one can set it as a percentage for errors of various multiplicities. A distribution of error syndromes to separate iterations has been performed, which makes it possible to reduce the length of a check word in a code. As a result, this leads to an increase in a rate of iterative codes in comparison with the traditional correction codes.A comparative analysis of IDCC and LDPC codes has been carried out to determine a scope of their optimal use
Computational Imaging on the Electric Grid

Night beats with alternating current (AC) illumination. By passively sensing this beat, we reveal new scene information which includes: the type of bulbs in the scene, the phases of the electric grid up to city scale, and the light transport matrix. This information yields unmixing of reflections and semi-reflections, nocturnal high dynamic range, and scene rendering with bulbs not observed during acquisition. The latter is facilitated by a dataset of bulb response functions for a range of sources, which we collected and provide. To do all this, we built a novel coded-exposure high-dynamic-range imaging technique, specifically designed to operate on the grid's AC lighting.
Formation of Hybrid Educational Structures in Russian Engineering Education

In this paper, a substantiation of the hybrid nature of the modernization of the Russian engineering education is given. The influence of integration preferences in the higher education reform on the formation of hybrid educational structures in engineering education of Russia is revealed. The definition of a hybrid system is given and the processes of hybridization of the education sphere are considered. Various aspects of educational hybridization are discussed. The peculiarities of hybrid transformations and their connection with educational reality are considered. The hybrid nature of the competence approach in Russian engineering education is emphasized.
Lessons Learned from an Intelligent Tutoring System for Computer Numerical Control Programming (CNC Tutor)

task analysis, automation, robotics and control, intelligent manufacturing system design, and micro/nano manufacturing
Establishing Trusted and Timely Information Source using Social Media Services

Social media is regarded as one of the most timely sources of information. Nevertheless, malicious users may misuse such media, and it may lead to severe incidents. Countermeasures to remove malicious user accounts and remove untrusted information need to be built. Various studies have been conducted until now. In this paper, we first provide an overview of recent work in this domain and then introduce our approach. Our preliminary experiment shows the feasibility of the research and discusses the future direction of this research.
A Self-driving Car in the Classroom: Design of an Embedded, Behavior-Based Control System for a Car-Like Robot

In this paper we study the design of a small mobile robot that resembles a self-driving car. The robot has been designed on the basis of a cheap, radio controlled toy car, but equipped with an embedded controller, a vision system and range sensors. To keep the robot affordable, low-cost, off-the-shelf components are used in the design. The developed robot is used to demonstrate the behavioral paradigm of the control system design, which is commonly used in mobile robots. The small autonomous car becomes an attractive educational tool, that may give the students an insight in both the hardware and software aspects of mobile robotics.
An Image-Based Multimedia Database and Efficient Detection though Features

Accurate feature detection during Image retrieval is important, data retrieves through image retrieval methods like CBIR and CBIR higher dimension data also need storage and access through different methods, content-based Image retrieval uses query like query by feature and query by example. More focus has made on accurate feature detection because need accurate feature retrieval. In simple words objectives are, to develop methods with sequence to classify features with normalization for efficient image retrieval from bulk dataset and also to improve method for local and global feature retrieval with automatic feature detection along accuracy. After study of different detection-based system, a methodology has been proposed which improves retrieval based on feature detection and feature detection had been improve with combination DWT+PCA+KSVM (polygon kernel +RBF kernel + Linear Kernel).
How is siri different than GUIs?

Voice interaction has become an increasingly ubiquitous form of interaction: from in the car, and on your smartphone to dedicated smart devices such as Amazon's Echo. My thesis will compare three popular smartphone voice assistants: Apple's Siri, Google's Assistant and Microsoft's Cortana to native GUI applications on an iPhone to identify the tasks where voice assistants are more effective. In addition, design patterns that voice interfaces employ to increase effectiveness will be identified.
Poster: Improvement of Professional Education Quality by Means of Mathematics Integration with General Education and Vocation-Related Subjects

The paper focuses on the improvement of professional educational quality. From the beginning of training it is necessary to teach students an applied mathematical thinking as a combination of intellectual fundamental structures, oriented on the study and construction of mathematical, ecological and technological objects. The development of a thinking logic, an ability to put into practice axiomatic, multiple-theoretical, inductive and deductive methods, statistics and probability methods of discrete mathematics and methods of optimization permits to resolve any issues of any disciplines and any field successfully. Therefore, we can note an increasing part of the mathematical foundation as a mean of professional tasks resolution through mathematical modeling.
Autoencoder embedding of task-specific information

Task-based measures of image quality (IQ) quantify the ability of an observer to perform a specific task. Such measures are employed for assessing and optimizing medical imaging systems. Although the Bayesian ideal observer is optimal by definition, it is frequently both non-linear and intractable. In such cases, linear observers are commonly employed. However, the optimal linear observer, the Hotelling observer (HO), becomes intractable when considering large images. Channelized methods have become popular for reducing the dimensionality of image data. In this work, we propose a novel method for determining efficient channels by learning them with autoencoders (AEs). Autoencoders are neural networks that can be employed to learn concise representations of data, frequently for the purposes of reducing dimensionality. We trained several AEs to encode task-specific information by modifying the standard loss function and examined the effect of hidden layer size and the use of tied/untied weights on the resulting representation accuracy. Subsequently, HOs were applied to both the original images and the dimensionality-reduced versions of them produced by the AEs. It was demonstrated that, for a suitable specification of the AE, the performance of the HO was relatively unaffected by the encoding of the image. However, the computational cost of inverting the covariance matrix was greatly reduced when the HO was applied with the encoded data due to its reduced dimensionality. Our findings suggest that AEs may represent an attractive alternative to the use of heuristic channels for reducing the dimensionality of image data when seeking to accurately approximate the performance of the HO on signal detection tasks.
Projections for infinitary rewriting (extended version)

Proof terms in term rewriting are a representation means for reduction sequences, and more in general for contraction activity, allowing to distinguish e.g. simultaneous from sequential reduction. Proof terms for finitary, first-order, left-linear term rewriting are described in the literature. In a previous work, we defined an extension of the finitary proof-term formalism, that allows to describe contractions in infinitary first-order term rewriting, and gave a characterisation of permutation equivalence. In this work, we discuss how projections of possibly infinite rewrite sequences can be modelled using proof terms. Again, the foundation is a characterisation of projections for finitary rewriting. We extend this characterisation to infinitary rewriting and also refine it, by describing precisely the role that structural equivalence plays in the development of the notion of projection. The characterisation we propose yields a definite expression, i.e. a proof term, that describes the projection of an infinitary reduction over another. To illustrate the working of projections, we show how a common reduct of a (possibly infinite) reduction and a single step that makes part of it can be obtained via their respective projections. We show, by means of several examples, that the proposed definition yields the expected behaviour also in cases beyond those covered by this result. Finally, we discuss how the notion of limit is used in our definition of projection for infinite reduction.
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A well-known result from the 1960 paper of Erdős and Rényi (1960) [2] tells us that the almost sure theory for first order language on the random graph sequence G(n,cn−1) is not complete. Our paper proposes and proves what the complete set of completions of the almost sure theory for G(n,cn−1) should be. The almost sure theory T consists of two sentence groups: the first states that all the components are trees or unicyclic components, and the second states that, given any k∈N and any finite tree t, there are at least k components isomorphic to t. We define a k-completion of T to be a first order property A, such that if T∪A holds for a graph (which indicates that the property described in sentence A is satisfied by the graph, and for every sentence B in the theory T, the property described by B is also satisfied by the graph), we can fully describe the first order sentences of quantifier depth ≤k that hold for that graph. We show that a k-completion A specifies the numbers, up to “cutoff” k, of the (finitely many) unicyclic component types of given parameters (that only depend on k) that the graph contains. A complete set of k-completions is then the finite collection of all possible k-completions.