Miracle-dz/UniFAR-FTUs huggingface dataset:
A FUZZY LOGIC APPROACH FOR OPTIMAL CONTROL OF CONTINUOUS CASTING PROCESS

Nowadays the continuous casting is used for providing almost one hundred percent of world steel production. A wide range of steel grades is continuously cast with high-quality achievements. The solidifying steel, during its pass through the caster, is subjected to variable thermal conditions and mechanical loading, both of which contribute to the material stresses and strains, the main sources of the defects. Some of these defects might be eliminated by a preceding computer simulation, optimization and subsequent control of the casting process. This paper describes an original algorithm for obtaining such control parameters which ensure the high production rate and the high quality of products as well. This algorithm is based on the keeping surface and core temperatures in the specific ranges corresponding with ductility of steel. The core of the algorithm is our original three-dimensional numerical model of temperature field where heat and mass transfer phenomenon including phase changes is deal with. Geometry and specifications of the caster are taken from the real caster operating in EVRAZ VITKOVICE STEEL, a.s. This model is verified by pyrometers measurements. The optimization part lies above the numerical model and iteratively improves the input parameters (casting speed and cooling rates) in order to reach desired surface and core temperatures. The optimization algorithm is performed by our fuzzy-logic interface and runs in off-line version. Its results can be used as a preparation tool for the real casting process.
Natural Multi-language Interaction between Firefighters and Fire Fighting Robots

Due to rapid development of agent systems and robotics, more and more chances are available for humans to interact with agent-based robotic technology (e.g., Robotic vacuums, robotic surgery, etc.), this trend increases the importance of human-robot interaction including human-robot communication. For the robust human-robot communication, natural language processing (NLP) can be implemented, among various existing natural language processing techniques, Ontological Semantic Technology (OST), which addresses meanings in an easily comprehensible way as a human does, was selected, the OST is a system in an ontology-based structure to deal with multiple natural languages. This research specifically addresses a concept of natural language-based communication with fire fighting robots and humans, and the main domain of this study targets fire fighting situations. In order to implement ontology-based communication with different languages, Korean and English were used for this particular study. This study extends the domain of Ontological Semantic Technology, specifically for communication with robots in a fire fighting domain using Korean and English.
Deferred Annuities and Strategic Asset Allocation

We derive the optimal portfolio choice and consumption pattern over the lifecycle for households facing labor income, capital market, and mortality risk. In addition to stocks and bonds, households also have access to deferred annuities. Deferred annuities offer a hedge against mortality risk and provide similar benefits as Social Security. We show that a considerable fraction of wealth should be annuitized to skim the return enhancing mortality credit. The remaining liquid wealth (stocks and bonds) is used to hedge labor income risk during work life and to earn the equity premium. We find a marginal difference between a strategy involving deferred annuities and one where the investor can purchase immediate life annuities.
A Hybrid Approach for Segmenting and Validating T1-Weighted Normal Brain MR Images by Employing ACM and ANN

This study focuses on segmentation and validation of brain MR images. Artificial Neural Network (ANN) has been applied to obtain the targeted segments from these images. In preprocessing step for avoiding the chances of misclassification during training of ANN, the unwanted skull tissues were removed by employing active contour modeling (ACM). The removal of these tissues leaves an image containing various regions of interest. For training ANN these distinctive regions of interest were clustered into their respective regions by employing KMeans algorithm. Then a neural net work is trained on this classified data which eventually facilitated in obtaining the desired segments. The boundaries of these segments were detected and the pixels constituting these boundaries were counted. For validating the segments produced by ANN, ground truth segments were taken under consideration. The boundaries of these ground truth segments were also detected and pixels forming the edges of these segments were counted. Finally a comparison was drawn between the pixel counts of ANN produced segments and ground truth segments. On the basis of this comparison, accuracy of ANN is calculated.
Semantic subtyping: Dealing set-theoretically with function, union, intersection, and negation types

Subtyping relations are usually defined either syntactically by a formal system or semantically by an interpretation of types into an untyped denotational model. This work shows how to define a subtyping relation semantically in the presence of Boolean connectives, functional types and dynamic dispatch on types, without the complexity of denotational models, and how to derive a complete subtyping algorithm.
Constraint Programming MapReduce'd

While Constraint Programming (CP) aims to explore efficiently large search trees, MapReduce (MR) is a framework that focuses on huge databases and text files. In this work, we try to bridge these two cutting-edge paradigms in order to solve Constraint Satisfaction Problems (CSPs) in distributed and/or parallel environments. We implement a CP system that is responsible to distribute the parts of the serial search tree to the workers in order to explore it. MR is responsible to allocate the physical resources of a cluster and assigns them to the workers. The CP and MR phases interchange and this novel coordination results into significant speedups while solving CSPs. Empirically, our approach is applied on common CSPs, such as N Queens and Number Partitioning.
Picture this! Effects of photographs, diagrams, animations, and sketching on learning and beliefs about learning from a geoscience text

Appl Cognit Psychol. 2018;1–11. Summary Many studies have demonstrated that illustrating expository science texts with images that are interesting, but irrelevant for understanding the causal relations underlying scientific phenomena, can cause seduction effects, which can reduce understanding from text. The term “seduction effects” refers to the influence that images are thought to have on readers, seducing them away from deeply processing important information. The present study explores whether images relevant for instructional goals may also show some seduction effects. In this study, the presence of photographic images negatively impacted understanding compared with the presence of relevant animations or instructing students to sketch a drawing during reading. However, the results showed that both photographic images and relevant animations could lead to illusions of understanding, whereas sketching did not. The results suggest that even images that are relevant for instructional goals may sometimes result in seduction effects that deceive readers when judging their own understanding.
Two notions of parsing

The term parsing, derived from Latin pars orationis (parts of speech), was originally used to denote the grammatical explication of se ntences, as practiced in elementary schools. The term was later borrowed into computer science and linguistics, where it has acquired a specialized se nse in connection with the theory of formal languages and grammars. However, in practical applications of natural language processing, the term is al so used to denote the syntactic analysis of sentences in text, without refere nce to any particular formal grammar, a sense which is in many ways quite close to the original grammar school sense. In other words, there are at least two distinct notions of par sing that can be found in the current literature on natural language process ing, notions that are not always clearly distinguished. I will call the two notion s grammar parsing and text parsing, respectively. Although I am certainly not the first to notic e this ambiguity, I feel that it may not have been given the attention that it deserves. While it is true that there are intimate connections between the two notions, they are nevertheless independent notions with quite different properties in some respects. In this paper I will try to pinpoint t hese differences through a comparative discussion of the two notions of parsing. This is motivated primarily by an interest in the problem of text parsi ng and a desire to understand how it is related to the more well-defined probl em of grammar parsing. In a following companion paper I will go on to discuss different strategies for solving the text parsing problem, which may o r may not involve
Automated Evaluation of Short Summaries

Children in elementary school are not only taught to read, but to understand what they are reading. To assess and improve their ability to understand concepts, students are often required to write short summaries of articles. Due to their nature, these documents often include misspelled words, missing punctuation, and erroneous grammatical structure. Evaluating these summaries is a laborious task that not only demands a significant amount of time from professors, but also limits the speed in which students can receive feedback. This paper presents a method for evaluating short summaries written by elementary school students. Our experiments show that incorporating semantic similarity/relatedness measures between words benefits the tasks of attribute selection and attribute weighting. We also show that preprocessing steps, such as the correction of misspelled words, are beneficial for the evaluation of short summaries. Our automatic grader has a mean absolute error of 0.98 when compared to a human grader on a 9-point grading scale. This agreement is comparable to the average agreement between two human graders.
Interacting with a gaze-aware virtual character

In this paper, we present the user's attentive state interpreted through eye gaze while interacting with a virtual character. The underlying narrative in which the approach was tested is based on a classical XIXth century psychological novel: Madame Bovary, by Flaubert. We connected a remote eye tracker with a dynamic 3D world. An empirical study revealed individual user experiences and behavioral patterns. In particular, we identified two different groups of users: one that was showing natural eye gaze behaviors with rhythmic eye gaze shifts between the characters' eyes, face and the scene and another one permanently staring at the character. Interestingly, the group with more natural behaviors towards the character also rated the experience with the system more positively.
The relationship between radio luminosity and black-hole mass in optically selected quasars

Using a sample of more than 6000 quasars from the Sloan digital sky survey (SDSS) we compare the black-hole mass distributions of radio-loud and radio-quiet quasars. Based on the virial black-hole mass estimator the radio-loud quasar s (RLQs) are found to harbour systematically more massive black holes than radio-quiet quasars (RQQs) with very high significance ( ≫ 99.99%), with mean black-hole masses of = 8.89 ± 0.02 and = 8.69 ± 0.01 for the RLQs and RQQs respectively. Crucially, the new RLQ and RQQ samples have indistinguishable distributions on the redshift-optical luminosity plane, excluding the possibility that either pa rameter is responsible for the observed black-hole mass difference. Moreover, this black-hole mass difference is shown to be in good agreement with the optical luminosity difference observed between RLQ and RQQ host galaxies at low redshift (i.e. �Mhost = 0.4 − 0.5 magnitudes). Within the SDSS samples, black-hole mass is strongly correlated with both radi o luminosity and the radio-loudness R parameter (> 7σ significance), although the range in radio luminosity at a gi ven blackhole mass is several orders of magnitude. It is therefore cle ar that the influence of additional physical parameters or evolution must also be invoked to explain the quasar radio-loudness dichotomy.
Assessing the Usability of a Prediabetes Self-Care Application: a Multi-Method Approach

Increasing demand for digital technology, worldwide, has unlocked new pathways for diabetes prevention. Health behavioural change theories when integrated in the design of novel health applications can foster effective self-health management and prevention. We developed i-PreventDiabetes, a self-care application for prediabetics, that enables lifestyle monitoring, goal setting and activity planning, which is accessible via both web and mobile. In this study, we evaluated the usability barriers and enablers, and assessed the user experience with the system by using a multi-method approach with 20 participants. This approach includes cognitive walkthrough, think-aloud method, question-asking protocol, System Usability Scale (SUS), User Experience Questionnaire (UEQ), and open-ended questions. The results indicate that the users are satisfied with the concept of preventing diabetes by using a self-care application that includes a variety of functionalities that empowers prediabetics to take charge of their own lifestyle in preventing diabetes.
Optimization of Pulse Duration Parameter for Hela Cells Growth Rate

To introduce a cell or tissue with a gene or DNA, electroporation parameter plays the most important role. Research on electroporation parameters is still in its early stages. Different researches have used different parameters while performing their research. Electroporation is a mechanism of temporarily disrupting the bilayer membrane, in such a way that a hydrophilic pore is established, allowing a pathway into the cell for molecules such as DNA, which then heals up, once again protecting the cell from the outside. There are many theories as to how this can occur, but the simplest view is that a short pulse creates an increase in the trans-membrane potential which if it exceeds a certain threshold (dependent on size and shape of cells) can lead to a thinning of the bilayer, either due to a local dislocation in the membrane. In this study, cervical cancer cells (HeLa cells) was used to expose to single pulse electric field. Thus, for the purpose of this study, the field strength of 1kV/cm was selected and the pulse duration was varied (30µs, 70µs, 100µs, 200µs, 300µs and 600µs) to obtain higher proliferation for a growth rate of HeLa cells. From this study, it is determined that, HeLa cell exposed to 1kV/cm with a pulse duration of 100µs and single pulse revealed the highest and fastest percentage confluence when compared to growth rate of HeLa cell exposed for 30µs, 70µs, 200µs, 300µs and 600µs pulse duration.
Prior versus Contextual Emotion of a Word in a Sentence

A set of words labelled with their prior emotion is an obvious place to start on the automatic discovery of the emotion of a sentence, but it is clear that context must also be considered. No simple function of the labels on the individual words may capture the overall emotion of the sentence; words are interrelated and they mutually influence their affect-related interpretation. We present a method which enables us to take the contextual emotion of a word and the syntactic structure of the sentence into account to classify sentences by emotion classes. We show that this promising method outperforms both a method based on a Bag-of-Words representation and a system based only on the prior emotions of words. The goal of this work is to distinguish automatically between prior and contextual emotion, with a focus on exploring features important for this task.
Evaluation of a hospital pharmacy-based pharmaceutical care services for asthma patients

Objectives To implement and assess hospital-based pharmaceutical care services for patients with asthma. Methods A prospective, randomized, controlled study was conducted in Shaab teaching hospital, Khartoum, Sudan. Patients were allocated randomly either in the intervention group (60) or control group (40) patients. The drug therapy of asthma for the patients in the intervention group was reviewed by a trained pharmacist, and interventions were suggested to the attending physicians for the identified problems. Intervention patients received comprehensive medication counselling and asthma education every 2 weeks, while the control group received the routine medical consultation and dispensing services. The outcome measures were recorded using structured forms at baseline and monitored during a follow-up of every two weeks for 6 months in both groups. Data were analyzed using SPSS version 13, level of significance was p<0.05. Results At the end of the study period the mean reduction in frequency of acute attacks (1.91; SD=0.18 vs. 1.0; SD=0.14; p=0.03), nocturnal asthma symptoms (3.5; SD=0.3 vs. 1.1; SD=0.2; p=0.02) and frequency of using inhaled β2 agonists per week (19.9; SD= 2.1 vs. 3.3; SD=0.3; p=0.01) were significantly greater in the intervention group compared to control. A significant mean reduction (p=0.002) in the days of sickness/week was in the intervention group, while in control group there was an increase in mean days of sickness/week. The intervention group showed a significant greater improvement in the score for assessing the inhalation technique (p<0.001), patient’s knowledge about asthma (p<0.001), and its drug-therapy (p=0.01) compared with control. Conclusion The present findings suggest that pharmacist’s intervention can have positive impact on asthma-related outcomes in patients.
Feeling the forces within materials: bringing inter-molecular bonding to the fore using embodied modelling

ABSTRACT We developed a computerised simulation that utilises embodied modelling by letting students play the role of particles in a liquid. We compared the learning of two eight-grade classrooms that used the embodied modelling simulation during a weeklong learning module on phase change, with a comparison group that used an ordinary simulation with no embodied modelling. In the pre-test, neither group mentioned inter-molecular forces in their explanations. In the post-test, significantly more students from the embodied modelling group mentioned inter-molecular bonds in their explanations than their counterparts who used the regular simulation, and realised that inter-molecular forces influence the motion of particles. However, we found little difference between the groups in students’ ability to relate the magnitude of the inter-molecular forces to the magnitude of the boiling point of the material, showing not only the potential but also the limits in developing complex conceptualisations through this approach. Building on these findings, we discuss the affordances of embodied modelling for learning complex models, and suggest future directions for research into embodied modelling.
Causality and the spatial-temporal ordering of events in mobile systems

Several mobile computing applications require that both the order of occurrence of events, and the location of their occurrence, be taken into account during decision making. Thus, processes need to track the location of nodes and synchronize their clocks. In this paper we present a framework, based on the capabilities of Global Positioning System, which provides processes with a global virtual clock and a positioning service. We introduce then the notion of space-time vector used by processes to track the mobility of nodes.
Statistical Tests for Discrete Cross-species Data

Four methods have been proposed that can be used to test for associations between the states of discrete characters in cross-species data and that do not suffer from non-independence due to overcounting of data points. The tests are those of Ridley (1983), Burt (1989), Grafen (1989), and a new test called the ICDE test. The aim of the paper is to measure the Type I error rates for these methods with simulated null distributions of discrete characters. The null data is generated by a model of discrete character evolution, using three shapes of phylogeny: tetratomous, dichotomous, and realistic. Ridley’s and Burt’s tests are both reasonably valid with the realistic phylogeny but biased with the tetratomous and dichotomous phylogenies. Grafen’s phylogenetic regression is reasonably valid with all tree shapes. One version of the ICDE test was valid, the other less so. The invalid results are explained in terms of two kinds of statistical non-independence that arise in discrete data: non-independence due to the reconstruction of character states by parsimony, and the ‘‘family problem’’ in which similar patterns are found in null data in many separate radiations because all the radiations began from the same ancestral state. 7 1996 Academic Press Limited
Towards learning through robotic interaction alone: the joint guided search task

This work proposes a biologically inspired approach that focuses on attention systems that are able to inhibit or constrain what is relevant at any one moment. We propose a radically new approach to making progress in human-robot joint attention called "the joint guided search task". Visual guided search is the activity of the eye as it saccades from position to position recognizing objects in each fixation location until the target object is found. Our research focuses on the exchange of nonverbal behavior toward changing the fixation location while also performing object recognition. Our main goal is a very ambitious goal of sharing attention through probing synthetic foreground maps (i.e. what is being considered by the robotic agent) and the biological attention system of the human.
Machine Translation Model based on Non-parallel Corpus and Semi-supervised Transductive Learning

Although the parallel corpus has an irreplaceable role in machine translation, its scale and coverage is still beyond the actual needs. Non-parallel corpus resources on the web have an inestimable potential value in machine translation and other natural language processing tasks. This article proposes a semi-supervised transductive learning method for expanding the training corpus in statistical machine translation system by extracting parallel sentences from the non-parallel corpus. This method only requires a small amount of labeled corpus and a large unlabeled corpus to build a high-performance classifier, especially for when there is short of labeled corpus. The experimental results show that by combining the non-parallel corpus alignment and the semi-supervised transductive learning method, we can more effectively use their respective strengths to improve the performance of machine translation system.