Reviewerly/exHarmony huggingface dataset:
Genetic Algorithms Applied to the Searching of the Optimal Path in Image-based Robotic Navigation Environments

This paper describes an optimal-path finding strategy based on Genetic Algorithms, applied to mobile robots in static navigation environments.This strategy starts from an image or plan of the environment and is supported by some different image processing algorithms, mainly the image skeletonization.Three different strategies were tested, changing the domain of the optimization target function for the Genetic Algorithm, the first domain was all the points of the environment image less the obstacles or walls, the second domain was similar but using an image with the obstacles dilated, and the final domain was only the points of the skeleton image.The last tested domain is from 99.4% to 99.6% smaller than the others, that implied reductions from 95% to 96% in the overall execution time of the strategy.Likewise, three skeletonization algorithms were tested in order to use the one with less execution time in this proposal.Finally, the proposed path planning strategy was tested on the same environment changing the initial and final points giving as result a valid and optimized path for the mobile robot in all the tested cases, and an overall average optimization time less than 2 minutes.This last, validates this proposal for robotic navigation applications with static obstacles.
Behavior Mode Selection based on Environment Map Understanding by Deep Learning for Planetary Rover

This paper presents a method to select behavior modes autonomously for a planetary rover. In the conventional methods, the behavior modes of a rover are selected by operators. Once the environment changes, however, it takes a long time to drive to the destination, because the intervention by operators is needed. Therefore, autonomous behavior mode selection is required to improve the exploration efficiency. The key idea of the proposed method is to understand the environmental map by deep learning so that a rover can select appropriate behavior mode according to the environment. The simulation study has been conducted to show the validity of the proposed method. The proposed method successfully demonstrates the capability to select behavior modes and to improve the traverse efficiency.
Enhancing Students’ Pronunciation using Android Pronunciation Application

The current study is a classroom action research aimed to investigate the implementation of pronunciation android applications-English Pronunciation, and English Phonetic Pronunciation and English Phonetics-to improve students' pronunciation.The participants in this study were 100 first semester students of English Education Department of Universitas Muhammadiyah Surakarta (UMS) who enrolled in Pronunciation and Phonetics course in academic year 2021/2022.The study consisted of 2 cycles.Each cycle consisted of 4 stages: planning, acting, observing, and reflecting.The techniques for collecting data were pre-test and post-test, obervation, and questionnaire.The quantative data were analysed by comparing the result from pretest and post test whereas the qualitative data were analysed by using constant comparative method.The study found that English Pronunciation, and English Phonetic Pronunciation and English Phonetics can improve the students' pronunciation.
Few-Shot Cross-lingual Transfer for Coarse-grained De-identification of Code-Mixed Clinical Texts

Despite the advances in digital healthcare systems offering curated structured knowledge, much of the critical information still lies in large volumes of unlabeled and unstructured clinical texts.These texts, which often contain protected health information (PHI), are exposed to information extraction tools for downstream applications, risking patient identification.Existing works in de-identification rely on using large-scale annotated corpora in English, which often are not suitable in realworld multilingual settings.Pre-trained language models (LM) have shown great potential for cross-lingual transfer in low-resource settings.In this work, we empirically show the few-shot cross-lingual transfer property of LMs for named entity recognition (NER) and apply it to solve a low-resource and real-world challenge of code-mixed (Spanish-Catalan) clinical notes de-identification in the stroke domain.We annotate a gold evaluation dataset to assess few-shot setting performance where we only use a few hundred labeled examples for training.Our model improves the zero-shot F1-score from 73.7% to 91.2% on the gold evaluation set when adapting Multilingual BERT (mBERT) (Devlin et al., 2019) from the MEDDOCAN (Marimon et al., 2019) corpus with our few-shot cross-lingual target corpus.When generalized to an out-of-sample test set, the best model achieves a humanevaluation F1-score of 97.2%.
METHODOLOGICAL SUPPORT OF THE INFORMATION AND EDUCATIONAL ENVIRONMENT IN THE TRAINING OF A MILITARY SPECIALIST

The article analyzes the distinctive properties of information technologies and the information and educational environment. The question of the expediency of using information technologies in the training of a military specialist is considered, ways of integrating information and pedagogical technologies are proposed. The information and educational environment for the study of general technical disciplines («Applied Geometry and Engineering Graphics», «Mechanics», «Electrical Engineering and Electronics») is presented in a schematic form. Examples of the use of information technologies aimed at improving the efficiency of the educational process are given.
Multi-modal Brain MR Image Registration using A Novel Local Binary Descriptor based on Statistical Approach

Medical image registration (MIR) has played an important role in medical image processing during the last decade.Its main objective is to integrate information inherent in two images, from different scanning sources, of the same object for guiding medical treatments such as diagnostic, surgery and therapy.A challenging task of MIR arises from the complex relationships of image intensities between the two images.Its performance is primarily depending on a chosen similarity measure technique.In this work, a statistical local binary descriptor (SLBD) is proposed as novel local descriptor of similarity measure, which is simple for computation and can handle Multi-modal registration more effectively.The proposed SLBD employs two statistical values, i.e., the mean and the standard deviation, of all intensities within the image patch for its computation.Finally, these experimental results have shown that SLBD outperforms other descriptors in terms of registration accuracy.In addition, SLBD has demonstrated that SLBD is robust to different modalities.
An autonomous obstacle avoidance method based on artificial potential field and improved A* algorithm for UAV

The main purpose of autonomous obstacle avoidance path planning of unmanned aerial vehicles (UAVs) is to find a collision-free flight path from the starting point to the target point in the threatened airspace. This paper mainly studies and designs an autonomous obstacle avoidance algorithm for UAVs. Firstly, the research status of obstacle avoidance is reviewed. Secondly, the problem scene is set up, and the basic algorithm used is described. Furthermore, a modified algorithm is designed to solve the problems mentioned above. Finally, the effectiveness of the method is simulated and verified.
ELLIPTICAL SENTENCES AS HEADLINES OF NEWSPAPER ARTICLES

The peculiarities of functioning of elliptical sentences in newspaper headlines, the specific features of their use are revealed.The article is mainly focused on the ellipsis as a syntactic means of compressing bulky sentences in order to achieve dynamic character and brevity of expressions as well as intensity of depicted actions.The functional and stylistic potential of elliptical sentences in English newspaper headlines are determined.The conducted analysis showed that headlines with implicit subjects or predicates are specially created expressive means which make it possible to actualize the important message to the readers.It has been found that a new phenomenon in the modern English newspaper discourse such as the omission of an object, an attribute or adverbial modifier is commonly used.The study has proven that elliptical sentences as headlines of modern newspaper articles serve as a means of compressing the information, focusing readers' attention on certain events that will intrigue and make them want to read.The authors of the articles may resort to the use of colloquial language, elliptical or incomplete sentences and other means in order to arouse the readers' curiosity.The article reveals the tendency to use newspaper headlines to reveal the authors' desire to present information concisely and succinctly and this has become possible due to the language economy and clarity of the message.The study found that elliptical headlines are more commonly used in the newspaper «The Economist» rather than «The Guardian».In addition, newspaper headlines often used play on words, including puns, allusions and metaphors as well as alliterations and assonances, intriguing with their expressiveness, rhythm, subconsciously encouraging readers to read the article, while «The Guardian» offered more analysis and explanation, not just news of different kinds.
Pedagogical system of consolidation of cadet study groups and formation of favourable psychological climate in them

The article is devoted to the issues of consolidation of heterogeneous cadet training groups and the formation of a favorable psychological climate in them. The necessity of developing collectivist relations among cadets in order to increase the effectiveness of their educational activities, foster feelings of mutual assistance and responsibility is considered and justified. The article presents the definition of the cadet training team as a heterogeneous community in terms of characteristics, reveals the psychological structure of the training team, including the components of consolidation, favorable psychological climate, high performance of educational activities and conditions for the development of each cadet. The pedagogical system of consolidation of educational groups of cadets is characterized, considering various contingents of students as subjects, which in this context represent precisely heterogeneous groups, distinguished by one of the characteristics (giftedness, dependent behavior, special educational needs, etc.). The importance of building this system at the initial stage of the formation of the team is emphasized, when with the help of diagnostic tools it is possible to see and understand how the cadet evaluates himself as a person, to build the process of his adaptation and entry into the cadet corps training group.
An ontology for the representation of Earth Observation data: a step towards semantic interoperability

Earth observation (EO) consists in collecting information related to the Earth's physical, chemical and biological systems.Data are gathered through remote sensing technologies, mainly consisting of satellites, and represent an essential source of information, which can be associated with administrative, social and economic issues in order to support policy analysis and decision-making.In recent years, characterized by an intensification of climate change phenomena and of extreme environmental events, the amount of EO data collected has significantly increased.Nevertheless, their huge volume and heterogeneity do not allow the data to be easily and promptly used by the scientific community.The different methods adopted for collecting, processing, cataloguing and describing data through metadata introduce an additional high level of variability.In this sense, it is important to guarantee technical, syntactic and semantic interoperability among data.This paper focuses on semantic interoperability issues in the EO domain and introduces an ontological representation of knowledge tailored to the concept of Essential Variables (EVs).The ontological model has been defined within a European research program which is also oriented towards the development of a Knowledge Base in the specific domain.Its general intent, however, is to provide a framework concerning a set of EVs, identified and characterized by a community of experts in order to guarantee information and knowledge generation from observable environmental data. 1
Students' self-education in distance education: sociological research perspectives

The article presents theoretical and empirical analysis of the significance of distance learning system in solving the problems of self-education of students' personality, reflecting the sociological aspects of the study. It substantiates the significance of DLS in the long term as a learning platform and as a component of a mixed model, which, in the long term, involves a combination of full-time and distance forms of higher education. The positive and negative aspects affecting the formation of self-developing personal attitudes in the process of using distance learning technology are revealed. The conceptual provisions of formation of methodological basis of sociological research processes of self-education of students are offered. The research problem focused on the use of distance form of higher education as a factor forming skills of self-development, through the implementation of procedures of self-education, which is considered through the totality of its three types: intellectual, spiritual, physical is concretized. The structural model of sociological research indicators developed on the basis of objective-subjective paradigm and structural-functional analysis, where the set of objective indicators is designed to identify external factors and substantiate their impact on the self-development of students' personality, is presented. Subjective indicators, within the framework of the research model, diagnose the existing trends and form promising directions of development of self-education processes and its motivations in the context of distance learning. Recommendations are formulated, which will contribute to the formation of systematized scientific and methodological positions in the development of programs of complex sociological research, collection, processing, analysis and use of the obtained information.
The Importance of Integrating Geological Mapping Information with Validated Assay Data for Generating Accurate Geological Wireframes in Orebody Modelling of Mineral Deposit in Mineral Resource Estimation: A Case Study in AngloGold Ashanti, Obuasi Mine

The basis of accurate mineral resource estimates is to have a geological model which replicates the nature and style of the orebody.Key inputs into the generation of a good geological model are the sample data and mapping information.The Obuasi Mine sample data with a lot of legacy issues were subjected to a robust validation process and integrated with mapping information to generate an accurate geological orebody model for mineral resource estimation in Block 8 Lower.Validation of the sample data focused on replacing missing collar coordinates, missing assays, and correcting magnetic declination that was used to convert the downhole surveys from true to magnetic, fix missing lithology and finally assign confidence numbers to all the sample data.The missing coordinates which were replaced ensured that the sample data plotted at their correct location in space as intended from the planning stage.Magnetic declination data, which was maintained constant throughout all the years even though it changes every year, was also corrected in the validation project.The corrected magnetic declination ensured that the drillholes were plotted on their accurate trajectory as per the planned azimuth and also reflected the true position of the intercepted mineralized fissure(s) which was previously not the case and marked a major blot in the modelling of the Obuasi orebody.The incorporation of mapped data with the validated
Hellenes in the Eccentropolis: Ancient Greek Culture as the basis of Theatrical Theories of the Russian Avant-garde (N. Evreinov, G. Kryzhitsky)

The article analyzes the dynamic aspects of the manifestation of the "mythologeme of antiquity" in the theatrical theory of the outstanding figure of the Russian avant-garde Nikolai Evreinov, reveals the degree of influence of his most important postulate about the Dionysian nature of drama on the philosophical and artistic concept of the "theater of spirit and flesh" Georgy Kryzhitsky as a theorist of the early FEKS (Factory of the eccentric actor), compares their key landmarks in the history of antiquity as avant-gardists. The previously unexplored material of the theoretical works of G. is introduced into scientific circulation. Kryzhitsky of the beginning of 1921-1922, on the basis of which the hypothesis is put forward that the author, almost forgotten today, sought to realize the retrotopia of "theatrical Hellenism" in post-revolutionary Petrograd (Eccentropolis).
Defense Against Adversarial Attacks

Owing to the vulnerabilities of DNN-based systems to adversarial attacks, there has been a recent surge in the design of defense mechanisms against such events. There are three major approaches to defense, i.e., adversarial training, defensive distillation, and the detection of adversarial examples. In this chapter, we review defense techniques against adversarial examples categorizing in terms of the approaches and discuss the capability as well as the difficulty to counter attacks.
Binary Encoded Word Mover’s Distance

Word Mover's Distance is a textual distance metric which calculates the minimum transport cost between two sets of word embeddings.This metric achieves impressive results on semantic similarity tasks, but is slow and difficult to scale due to the large number of floating point calculations.This paper demonstrates that by combining pre-existing lower bounds with binary encoded word vectors, the metric can be rendered highly efficient in terms of computation time and memory while maintaining competitive accuracy on several textual similarity benchmarks.
Using Lognormal_PCA for Orientation Estimation

Local orientation is a feature of multi-dimensional signals.Orientation estimation plays an important role in many image processing and computer vision tasks.This paper presents a method for orientation estimation, which is based on the combination of two already well-known techniques: signal filtering in the Fourier domain with principal component analysis.As experimental results show, this method enjoys excellent precision and robustness.Both simulated and real image examples are presented to demonstrate the proposed method.
A pseudorandom bit generator based on hyperbolic cosine function

In the literature, little attention is paid to devising and analyzing novel one dimensional chaotic mappings. In our previous efforts, we have tried fold, translation &amp; scale on arctangent function &amp; sigmoid function respectively, which brings good results. In this paper, we do the same to obtain a variant of Hyperbolic Cosine Function. Both Bifurcation Diagram &amp; Lyapunov Exponent Spectrum manifest that the new mapping possesses wonderful chaotic properties. Then, a pseudorandom bit generator is designed based on it. Pseudorandom tests demonstrate that the generator is much better than our previous ones. It owns great application prospect.
A Transferable Adversarial Belief Attack With Salient Region Perturbation Restriction

Deep neural networks are vulnerable to adversarial examples which are crafted by adding small perturbations on benign examples. However, most existing attack methods often perform a poor transferability to attack black-box models, especially to attack defense methods. In addition, perturbations added to semantically irrelevant regions of benign examples are usually inefficient for attacks. To address these issues, we propose a transferable adversarial belief attack with salient region perturbation restriction method, which improves transferability of adversarial examples and decreases the amount of perturbations significantly. Specifically, we first design a salient-region-based perturbation restriction strategy to restrict the range of perturbations into a salient region. After that, we present a transferable belief attack method to generate adversarial examples iteratively. Besides, our method can be easily integrated with other gradient-based transfer attack methods to further enhance the transferability of adversarial examples. Extensive experiments on the ImageNet dataset show that our method achieves higher transferability with lower perturbations than the state-of-the-art attack methods.
Personality in Personalisation: A User Study with an Interactive Narrative, a Personality Test and a Personalised Short Story

We present a user study developed to explore the use of psychological frameworks for the personalisation of narratives. Further, we explore using interactive narratives to understand the user’s personality and narrative preferences. The study consists of three sections: an interactive narrative, a personality test, and a personalised short story. Whilst it would appear that at least this interactive narrative could not be used as a personality test per se, it was able to capture some traits. The personalisation appeared to work well, especially regarding relating with the protagonist. It was also found that extraverted people appear to prefer reading narratives with less formal language, and introverts prefer narratives with more formal language .
An Analysis of Elementary School Vulnerability in Flood-prone Areas, Sukoharjo, Indonesia

The impact of the flood not only resulted in paralyzed social, economic, and community activities but also resulted in stopping educational activities.Unfortunately, few studies have examined the vulnerability of the school environment in flood-prone areas.This study aims to analyze the vulnerability of elementary schools in flood-prone areas, Grogol sub-district, Sukoharjo, Indonesia.The sample in this study were all elementary schools located in flood-prone areas, Grogol, Sukoharjo, Indonesia.Vulnerability variables in this study are social and physical variables that are in accordance with the actual conditions of the school.The data analysis technique used in this research is classification and weighting using standard deviation and average deviation.Each variable consists of parameters analyzed, weighted, and classified according to the magnitude of the effect on vulnerability or potential loss if a flood occurs.The results of data analysis show that Kadokan 1, Madegondo 1, Pandeyan 1, Pandeyan 2 State Elementary School belong to the very high vulnerability class, and Madegondo 3 State Elementary School belongs to the high vulnerability class.These results indicate the need for efforts to increase school capacity in dealing with flood disasters.