Reviewerly/exHarmony huggingface dataset:
GLOBALIZATION OF CIVIL ENGINEERING EDUCATION THROUGH THE BOLOGNA PROCESS AND LEARNING OUTCOMES

Actual issues of globalization and internationalization of education in the construction sector are posed in the article. The authors state the fact that the ongoing processes, in particular, the deterioration of the environmental situation on the planet, the negative effects of climate change require unified approaches to the formation of the content of building education and learning outcomes in the form of certain competencies: knowledge, skills. A review of scientific articles in the field of internationalization of building education is given in the article. Among them are articles offering new approaches to integrate building education with environmental and climate education; new teaching methods using digital technologies and 3D virtual learning environments. The authors conducted a sociological survey of employers and revealed a lack of practical knowledge among graduates of construction universities in Russia, meanwhile, construction education in European universities and US universities is becoming more practical, ecological and climate disciplines are including in the curriculum for training civil engineers. Authors' conclusion: special attention in building education should be paid to 1) the development of student mobility, the exchange of curricula and disciplines between universities; 2) strengthening the ecological and climatic component of construction education; 3) the development of joint scientific and educational international projects in the field of construction. The only measure of the quality of construction specialists is the learning outcomes that satisfy the modern requirements.
Removing Labeled Portion from Mammogram Image

Finding of breast tumor which is cancerous at an initial phase is essential and critical for actual treatment and patient recovery. Mammograms are specifically used only in the breast tumor identification. The images taken as mammogram ensure an ability to support physicians in detection of disease affected by cells normal growth. Each mammogram image is having label or number. The paper is based on removing an extra portion like label from mammogram images. To implement this images are used from database which is publicly available mammogram dataset provided by the Mammographic Image Analysis Society. This database contains images those are having three types of fundamental breast tissues. This implementation contains image acquisition, image de-noising, binarization and removing label.
Simultaneous learning algorithm for multiple sets of synonyms with different semantics

Up to now, scholars have proposed some algorithms for learning synonyms of laboratory indicators. However, there is no report on learning multiple synonym sets at same time for outliers of laboratory indicators. Among the outliers of laboratory indicators of diseases, there are multiple synonym sets with various semantics such as {high, higher, increase}, {low, lower, decrease}, {very low, significantly low}. In this paper, a synonym set learning algorithm for different semantics of outliers of laboratory indicators is proposed. Firstly, using the sentence pattern laboratory indicators, outliers, and disease entities from medical texts are extracted; secondly, a set of synonyms for different semantics of laboratory indicators and outliers are learned; thirdly, the correspondences relation of laboratory indicators, outliers, and diseases are established. In the process of the first task, the algorithm is designed like a BERT model, that is, masking any one component and learning it with the other unmasked three parts, then updating the component sets that will include the learned components, and then with the new three unmasked components that includes the updated component sets to learn a new component that is included in the previous unmasked components. These steps run iteratively until every component sets do not varied. The experimental results show that the proposed algorithms is effective.
A Note on Subgroup Security in Discrete Logarithm-Based Cryptography

The membership check of a group is an important operation to implement discrete logarithm-based cryptography in practice securely. Since this check requires costly scalar multiplication or exponentiation operation, several efficient methods have been investigated. In the case of pairing-based cryptography, this is an extended research area of discrete logarithm-based cryptography, Barreto et al. (LATINCRYPT 2015) proposed a parameter choice called subgroup-secure elliptic curves. They also claimed that, in some schemes, if an elliptic curve is subgroup-secure, costly scalar multiplication or exponentiation operation can be omitted from the membership check of bilinear groups, which results in faster schemes than the original ones. They also noticed that some schemes would not maintain security with this omission. However, they did not show the explicit condition of what schemes become insecure with the omission. In this paper, we show a concrete example of insecurity in the sense of subgroup security to help developers understand what subgroup security is and what properties are preserved. In our conclusion, we recommend that the developers use the original membership check because it is a general and straightforward method to implement schemes securely. If the developers want to use the subgroup-secure elliptic curves and to omit the costly operation in a scheme for performance reasons, it is critical to carefully analyze again that correctness and security are preserved with the omission.
Filenail

The use of filesystems has become a standard, with a purpose well beyond just storing and accessing application data. For instance, common system security and compliance operations, sush as software or package installation, system and application configurations or process management also leverage a filesystem. Over decades, various system management and security tools have been designed to access system state and to implement their respective functions through a file interface. However, we observe that these tools do not require access to all the files in the filesystem and in some cases they can even work with incomplete file contents. Motivated by these observations, we propose filenail (or Filesystem Thumbnail) a system that exercises an incomplete filesystem state marshalling and un-marshalling protocol. We discuss the use of filenail to implement an effective and optimal disaggregated solution to perform common system security tasks for container clouds. In general, depending on the use-case not all the files in the filesystem are equal and that incomplete filesystem state can be often enough. The results of this paper show filenail is very efficient in capturing and transferring filesystem state of systems and enables implementing disaggregated security solutions in the cloud.
Teaching Directory Services: Topics, Challenges, and Experiences

His current research interests include cyber security and medical informatics.He is particularly interested in applying his research and techniques to real-
RELEVANSI ANTARA MATERI PEMBELAJARAN MENULIS DALAM BUKU PELAJARAN KELAS 5 SEKOLAH DASAR DAN KOMPETENSI DASAR KURIKULUM 2013

The purpose of this study was to describe the relevance of writing learning materials in the grade 5 textbooks of elementary schools and the basic competencies of the 2013 Curriculum. This research is library research (library research), which is research based on searching the literature related to the issues to be discussed. The approach used in this study is a qualitative approach. The results of the data analysis show that between the writing learning material in the 5th grade textbooks of elementary schools and the basic competencies of the 2013 Curriculum, there is a very significant relevance. This conclusion is based on the results of data analysis on two research problems which show the following results: (1) There is a very significant relevance between writing learning materials in grade 5 textbooks of elementary schools and basic competencies of knowledge in the 2013 curriculum; (2) There is a very significant relevance between writing learning materials in grade 5 textbooks of elementary schools and basic competency skills in the 2013 curriculum.
New data-driven methodologies for fault prognostics using evolving fuzzy models

This thesis addresses new data-driven evolving techniques to the problem of fault prognostics. In such problems, accurate predictions of multiple steps ahead are essential for the Remaining Useful Life (RUL) computation of a given asset. The fault prognostics' solutions must be able to model the typically nonlinear behavior of the degradation processes of these assets and be adaptable to each unit's particularities. In this context, the evolving fuzzy systems are models capable of representing such behaviors, in addition to being able to deal with time varying behavior, also present in these problems. In this work, we proposed a new modeling technique for evolving fuzzy systems that use multivariate Gaussian membership functions, making it able to incorporate the complex relationships between the variables of interest, and a recursive learning mechanism built upon a data stream, although historical data can be used as a starting point. In the proposed mechanism, the knowledge is managed through the monitoring of dynamic estimation error thresholds. Moreover, a methodology is proposed to use such techniques in fault prognostics problems, taking into account the model uncertainty propagation in long-term predictions. Three well-established data sets are used to evaluate the proposed model in problems of time-series prediction and fault prognostics. The experiments indicate that the proposed model is competitive in terms of precision and number of free parameters compared to other evolving fuzzy systems and can take advantage of both historical and stream data to estimate the RUL and its uncertainty. Furthermore, in most test scenarios, it may outperform other methods that do not manage new data incorporation or whose knowledge base management is not based on the estimation errors.
LEARNING IN SCHOOL OF LOGIC AND LOGICAL PROGRAMMING FOR PRESENTATION AND PROCESSING OF KNOWLEDGE

New trends in the development of society in the digital age determine the growing role of artificial intelligence (AI). This determines the need for its formal and informal study in different levels and in different volumes in both classroom and extracurricular activities of bulgarian schools. On the basis of a curriculum approved by the Ministry of Education and Science, the development of appropriate teaching resources and aids began. In this report, the authors will present an approach to presenting knowledge with general meaning in artificial intelligence by applying logical inferences, rules and dependencies. The main topics of the curriculum and the way of their structuring will be presented. The main idea is, following the requirements of classical artificial intelligence, to consider different methods and approaches for presenting this theory in the context of high school education.
Assessment of silica content in groundwater of Peninsular Indian region using statistical techniques

The groundwater resources from open dug wells are the ultimate and inevitable drinking water source in Chennai municipality. These are of shallow depth of 8 to 10m with a static water depth range of 30 to 75 m. This study's objective was to assess silica (in the form of Silicon Dioxide, SiO2) in groundwater and to establish their baseline concentration. Twelve wells were monitored in the study area, in some parameters, namely: Chloride (Cl-), Total Dissolved Solids (TDS), pH, Electrical Conductivity (EC), and SiO2. We examined the existing relationship between silica and other measured water quality parameters (Cl-, pH, TDS, and EC) using Spearman correlation matrix analysis in SPSS software and Normalized Difference Dispersal Index (NDDI) in Simplex Numerix software that was applied to identify the hotspots of SiO2. The water pH ranges from 8.09 to 8.37 (slightly alkaline) with an appreciable amount of TDS (730.50 to 1294.50 ppm). The groundwater also contains abundant silica (15.50 to 24.0 ppm), Cl- (106 to 438 ppm), and EC (759.50 to 1837.50 µS/cm). Further, a geostatistical tool was used to derive NDDI map of groundwater quality parameters and quantified site-specific variations in parameters, namely SiO2, Cl-, pH, TDS, and EC values. Average NDDI value enrichment was exhibited by SiO2 (0.09, ≈ 0.1) it reﬂects accretion, while average NDDI values of Cl- (–0.09, ≈–0.1), EC (–0.04), TDS (–0.03), and pH (–0.02), it outlined that by dilution in particular groundwater parameter.
Relaxing and Familiar, Guidelines to Develop Interactive Applications for Dementia Patients

Dementia describes a group of symptoms affecting memory, thinking and social abilities. Treatments aim to improve levels of functionality of patients with dementia. Some patients may experience catastrophic episodes during their treatment, these episodes are characterised by excessive emotions or physical response. Psychiatrists have used supportive tools and therapies to improve patients’ levels of functionality, trying to prevent and decrease catastrophic episodes. In this study, we present Memento, an application designed for catastrophic episodes management in patients with dementia through Information Technology. To develop Memento, we identified design aspects that should be considered when developing an application to reduce catastrophic episodes. Our main contribution is the classification of these aspects. To do this, we have analysed our findings in specifications which include the patient needs and characteristics; therapy guidelines; area or environment of interaction; dementia action protocol; and user interface navigation. Our findings may serve as guidelines for the design and development of interactive applications targeted at patients with dementia.
Learning Axioms to Compute Verifiable Symbolic Expression Equivalence Proofs Using Graph-to-Sequence Networks

We target the problem of proving the semantic equivalence between two complex expressions represented as typed trees, and demonstrate our system on expressions from a rich multi-type symbolic language for linear algebra. We propose the first graph-to-sequence deep learning system to generate axiomatic proofs of equivalence between program pairs. We generate expressions which include scalars, vectors and matrices and 16 distinct operators combining them, with 147 distinct axioms of equivalence. We study the robustness of the system to generate proofs of increasing length, demonstrating how incremental graph-to-sequence networks can learn to represent complex and verifiable symbolic reasoning. It achieves 93% average true positive coverage on 10,000 test cases while ensuring zero false positives by design.
Human Body AR: A Mobile Application for Teaching Anatomy for Elementary Students Using Augmented Reality

When the children arrive at the educational institution, they have prior knowledge of the world around them. These previous knowledge’s are the product of their experiences, games, among other activities, and based on this knowledge, they can explain facts and natural phenomena. Traditional teaching methods do not allow adapting to the learning that students need, therefore the use of technological tools in education provides different learning opportunities for both students and teachers. The present research evaluates at the usability level an application that we have developed for the use of augmented reality to improve the anatomy teaching process, the use of this technology allowed us to improve the learning process, the validation of this research was carried out using a methodology to evaluate the didactic value of educational software, and this evaluation was carried out in a group of teachers.
PENGEMBANGAN BAHAN AJAR BAHASA INDONESIA BERBASIS LINGKUNGAN UNTUK SISWA KELAS 1 SD

This research has the background of the problem of lack of innovation in teaching materials used by teachers, thus causing learning goals to be less optimally reached and students less interested in participating in learning. Elementary school. This research is the development of Indonesian teaching materials starting with a simple form developed in a set of interesting environment-based Indonesian teaching materials. The purpose of this study is to optimize the surrounding environment as a basis for making teaching materials, make environmentally based Indonesian teaching materials for grade 1 elementary school students, and describe the results of the effectiveness of environmentally based Indonesian teaching materials for grade 1 elementary school students. This research uses the type of Research and Development. The data in this study are data about the need for environmentally based Indonesian teaching materials, prototypes of environmentally based Indonesian teaching materials come from observations, interviews, questionnaires and documentation. Data sources were obtained from students and grade 1 teachers at SD 2 Besito, SD 3 Karangmalang, and SD 4 Gondosari. The effectiveness test results showed that the Indonesian language teaching materials were environmentally effective, which was shown by the results at SD 2 Besito at 9,430&gt; 2,03, SD 4 Gondosari at 7,570&gt; 2, and SD 3 Karangmalang at 9,277&gt; 2,04, the t test could be it was concluded t arithmetic&gt; t table then Ho was accepted and environmentally based Indonesian teaching materials were effectively applied.
IMPROVING ENGLISH LEARNING CULTURE THROUGH LEARNING MOTIVATION

A learning culture is needed to facilitate the process of learning English for students and to increase student motivation in learning language (Kim, 2020). This research paper aim to examine and describe Indonesian EFL university students’ motivation whether integrative or instrumental in learning English as foreign language. The method used was quantitative by randomly asking the students  enrolled in undergraduate study program of English Literature in one of the Indonesian universities to fill out a questionnaire adapted from Attitude Motivation Test Battery (AMTB) that was developed by R.C. Gardner (1985). The questionnaire was administered to students who come from 2017 generations to 2020 generations. Moreover, this study also examine whether the differences existed in motivation between old students and new students. The data collected were analyzed by using SPSS program to find out the mean score and standard deviation as to answer the questions of this study. The results indicated that students’ motivation in learning English was more highly instrumental than integrative. This study also revealed that new students had more instrumental motivation and old students had more integrative motivation. Based on the findings, lecturers are expected to improve their way of learning for enhancement the students’ motivation. Learning culture developed should take into account and maintain the motivation of students in language learning.
Exploring diachronic syntactic shifts with dependency length: the case of scientific English

We report on an application of universal dependencies for the study of diachronic shifts in syntactic usage patterns. Our focus is on the evolution of Scientific English in the Late Modern English period (ca. 1700-1900). Our data set is the Royal Society Corpus (RSC), comprising the full set of publications of the Royal Society of London between 1665 and 1996. Our starting assumption is that over time, Scientific English develops specific syntactic choice preferences that increase efficiency in (expert-to-expert) communication. The specific hypothesis we pursue in this paper is that changing syntactic choice preferences lead to greater dependency locality/dependency length minimization, which is associated with positive effects for the efficiency of human as well as computational linguistic processing. As a basis for our measurements, we parsed the RSC using Stanford CoreNLP. Overall, we observe a decrease in dependency length, with long dependency structures becoming less frequent and short dependency structures becoming more frequent over time, notably pertaining to the nominal phrase, thus marking an overall push towards greater communicative efficiency.
Fostering Teacher ICT Competencies in Developing Countries: An ODA Project Case in Peru

Many developing countries consider ICT as a key enabler to improve their educational systems and teachers are viewed as change agents. This paper aims to present how to foster teachers’ ICT competencies in developing countries based on an ODA project case in Peru This study was conducted through three stages: Literature survey, site visit, and policy suggestions. To draw relevant policy suggestions, we employed the framework of the ‘micro-meso-micro’ level of the teacher professional development. The following policy suggestions are discussed: (a) macro level: to develop the national framework of teacher ICT competencies toward knowledge deepening and knowledge creation and the need to develop competency-based ICT training programs, (b) meso-level: to promote teacher communities of practices and school-based research programs, and (c) micro-level: to redesign teacher professional development programs to help teachers better understand the complex relationships between content, pedagogy, and technology, beyond learning about basic ICT literacy skills. This study contributes to the understanding of how ODA projects can approach the issue of teacher ICT capacity building.
Image stacking versus per-frame results combination for video text recognition

In the field of document analysis and recognition using mobile devices for capturing, and the field of object recognition in a video stream, it is important to be able to combine the information received from different frames, since the quality of text recognition depends on the effectiveness of collecting the maximal amount of information about the target object. This paper examines and compares the effectiveness of two different combination approaches, namely pre-combination of images before recognition and the combination of recognition results. The combination methods are briefly described. The quality of the combined results obtained using different methods was measured and compared on the MIDV-500 dataset. The results show that the approach with a combination of text strings recognition results is more effective in comparison with the preliminary combination of images. It can be concluded that simple image stacking with projective alignment does not allow to achieve a comparable recognition results combination quality, and thus in order to include the information about per-frame changes of the text images more sophisticated image combination algorithms need to be employed.