Reviewerly/exHarmony huggingface dataset:
The Effectiveness of Smart Learning Based on Expert Systems in Cryptography Courses

The development of science and technology requires universities not only to matter but also to have abilities in their respective fields including Security System. The unavailability of network design laboratory and its minimum, network design, cryptography design and flexibility of face-to-face time in the discussion of material compiled not in accordance with the competencies in this course. To overcome these deficiencies in learning activities, development of a project-based blended learning model is carried out. The development carried out in this study uses the Puslitjaknov development model which reduces the Borg and Gall stages to five stages namely product analysis, initial product design, expert validation and revision, field trials and implementation. Data were collected by interview, observation, questionnaire and test. Data were analyzed using quantitative and qualitative methods to produce research products in the form of books, modules, learning plans and manuals for the use of learning applications. Product validation by experts, practicality tests carried out by users and effectiveness tests with student learning outcomes. Based on the results of data analysis, the results of this study are: 1) Research has successfully developed a project-based blended learning model in Cryptography courses. 2) The developed learning model syntax consists of 9 stages / syntax. 3) In supporting learning activities, modules, RPS and manuals are used for learning applications. All products and models developed have been developed and are categorized as valid, practical and effective.
EHR phenotyping by Natural Language Processing improves detection of patients at risk for preeclampsia

ACOG and USPSTF recommend aspirin (ASA) to reduce the probability of developing preeclampsia. Identification of candidates for ASA prophylaxis is difficult due to the numerous risk factors documented in varying places in the Electronic Health Record (EHR). The aim of this study was to evaluate the performance of 3 detection strategies to identify patients for whom ASA was indicated: (1) clinician detection, (2) EHR phenotyping by discrete field evaluation and (3) EHR phenotyping by Natural Language Processing (NLP). A retrospective cohort study of patients delivering from 10/1/2019 to 2/28/2020 for whom the complete prenatal record was available in the EHR. Patients meeting USPSTF/ACOG criteria for ASA prophylaxis were identified by chart audit. Based on manual chart review, patients recommended or who received ASA were coded as clinical detection. Discrete fields were queried for ICD-10 codes pertinent to the high and moderate risk factors. Finally, NLP using Bidirectional Encoder Representations from Transformers (BERT) in an automated machine learning environment was performed. Model choice was optimized for F1 score (a combination of precision and recall). Among 677 patients, 263 (38.8%) met criteria for ASA prophylaxis and 62 (23.6%) were recommended or received ASA; this served as the clinician detection rate. After application of EHR phenotyping via discrete fields, detection improved to 58.2% (153 received/263 indicated). Last, NLP using BERT yielded the highest detection rate (73.3%) while still maintaining discriminatory capacity (AUC-ROC 0.90) and a low false positive rate (12%). Compared to clinicians, detection of patients who meet criteria for ASA prophylaxis is doubled by implementation of EHR phenotyping based on discrete fields and increased threefold by addition of NLP. Using the criteria, machine learning and NLP can be used to detect patients at increased risk for preeclampsia and can be used to electronically track ASA use for this indication in the EMR, thereby decreasing reliance on labor-intensive, expensive chart audits.View Large Image Figure ViewerDownload Hi-res image Download (PPT)
The Effectiveness of Collaborative Strategic Reading (CSR) and Cooperative-Discussion-Question (Coop-Dis-Q) in Teaching Reading Comprehension

This study aims to measure the effectiveness of collaborative strategic reading (CSR) and cooperative-discussion-question (Coop-Dis-Q) strategies in teaching reading comprehension students with impulsive and reflective cognitive learning styles. To improve students' reading comprehension skills, the researcher wants to study both strategies. This research used 2x2 factorial experimental designs. The subjects were XI MIPA 1 and XI MIPA 4 classes of SMAN 1 Pangkah, Tegal Regency. They were divided into two groups, and categorized impulsive and reflective students. The instruments used were test, pre-test, post-test, and questionnaires. This research indicated that collaborative strategic reading (CSR) was more effective than cooperative-discussion-question (Coop-Dis-Q) to students with impulsive cognitive learning styles. Simultaneously, there was no significant difference between the students who were taught by using collaborative strategic reading (CSR) and those taught by cooperative-discussion-question (Coop-Dis-Q) with reflective cognitive learning style. It meant that CSR was more effective for the students with impulsive cognitive learning styles, while Coop-Dis-Q was effective for the students with reflective cognitive learning styles. Based on the findings, the researchers concludes that CSR and Coop-Dis-Q appeared to improve the students' reading comprehension skills for both impulsive and reflective students.
The Roles of English in the Development of Tourism and Economy in Indonesia

Tourism is very necessary to continue to be developed to improve the economy in Indonesia and increase the position of the country geographically, which is very strategic for tourism and the world economy. For this reason, the ability to communicate in English is absolutely necessary, in order to compete with workers from other countries, so that they can contribute to the improvement of the national economy. The ability to communicate in English is a strategic sector in the development of highly competitive human resources in the tourism industry sector and in the global economic community. By having good English communication skills, it will be easier to grab market share in the tourism industry sector and the economic sector. The tourism sector as one of the prime industrial development is developed in order to further increase the rate of national development. For this reason, it is necessary that the government continues to increase its resilience, policies, and increase the development of tourism with a view to further developing the community's economy and increasing the ability to speak English so that human resources are able to compete in various tourism industries so that the economy will increase.
Network covert channels capacity limitation by adding random delays before packet sending

Attention to covert channels has largely increased due to the documents published by E. Snowden, which described the software and hardware embedding that implement undeclared features of covert information transfer in the Huawei and Juniper network equipment, Apple mobile phones and computers with the Windows XP operating system. A covert channel can be built using any information technology, but often attackers build covert channels in IP networks, since they are widespread, have a high information transfer rate, and ubiquitous information security measures, such as traffic encryption, do not affect the possibility of covert transmission of information via some types of such channels. The limitation of their bandwidth is a promising direction for countering information leakage via network covert channels. This study considers network timing covert channels, provides a method for assessing their capacity, proposes and investigates a way to counter information leakage via such covert channels by introducing noise having added delays before sending packets. The values of the delays are distributed in two different ways: uniformly and according to distribution with a decreasing probability density function. As an experiment, the temporal characteristics of IP traffic from a host in the internal network to a public service were obtained, which were used to verify the obtained methods for assessing the covert channel capacity. A distinctive feature of the calculations is an illustration of the possibility to minimize the load on the communication channel in the context of introducing a countermeasure method, as well as taking into consideration the fact that the intruder's ability to observe the current conditions in the network allows him to adjust the parameters of information transfer to the load in the communication channel, thereby maintaining the maximum possible covert channel bandwidth.
FORMATION OF STUDENT YOUTH’S SOCIAL ACTIVITY IN THE SPACE OF HIGHER EDUCATION INSTITUTION

the problem of the formation of student youth’s social activity in the space of a higher education institution is considered. Taking into account the modern vectors of development of society due to digitalization, it is necessary to have a positive social development of students as future leaders. The formation of their social activity, as a significant social quality, needs a favorable space and socio-pedagogical direction. Since the leading activity of student youth is educational, it is proposed to consider the space of the institution of higher education for the formation of their social activity.
Human Being in the Dimension of the Psychosociocultural Matrix of Philosophizing

Purpose. The article highlights the demand for critical thinking in everyday life at the present stage of development of globalized culture and emphasizes the role of philosophy as a source of rationality. Philosophizing, which is determined by the psychosociocultural matrix, sets the toposes, vocabulary and rhythms of meaning making, their preservation and transformation. The purpose of the article is to concretize the practices of socio-cultural communication, primarily through the social institute of education, where individuals interact with the psychosociocultural matrix of philosophizing, which mediate the general and individual level in philosophical culture. Theoretical basis of the study are cultural anthropology and phenomenological methods. Originality of the study: based on the philosophy of intersubjectivity, we actualized the rational grounds for formation of adequate judgments in modern culture at the level of everyday life. This justifies the inevitability of the spread of various forms and types of philosophical education, philosophical thinking, ideas and values developed in philosophical communities beyond the narrow circle of professional philosophers. This implies the systemic involvement of philosophers as professionals of meaning-making in solving problems in various non-academic fields – politics, economics, law, etc. The formation of skills of philosophical critical thinking in the process of preparing young people for active civil life is no less important aspect of this. Conclusions lead to an understanding of the existential importance of philosophy and philosophizing and the need for organized forms of knowledge transfer such as the Faculty of Philosophy of the Classical University. There is a mutual interest and interaction of the general culture of society and philosophy as a special kind of culture. Because philosophy actively configures other forms of culture, contributes to the creation of sociocultural identities precisely because of its ability to conceptually reproduce the core of the psychosociocultural matrix that underlies the existence of all these different forms within one society. The sociocultural macro level of philosophical spiritual practices is formed by the psychosociocultural matrix of the philosophical tradition, which retains its longevity from the emergence of philosophy and goes through its history, demonstrating the features of the national reception of philosophy as a national-specific embodiment of sociocultural macro level of the psychosociocultural matrix.
The Searching for Self-Identity in Kazuo Ishiguro’s Never Let Me Go

Self-identity is an aspect that every human in the world has. Without it, a person is in danger of being negatively affected by those around him/her and by the outside world. Some people are grappling with this identity-forming phase in their search for self-definition. This is reflected in Never Let Me Go by Kazuo Ishiguro. Therefore, this research aims to describe the main characters' search for self-identity as seen in the novel. The type of this research was library research. This research applied a psychological approach, and the data were analyzed using the descriptive qualitative method. The results showed that Kathy and Tommy's quest to find their true selves occurred in childhood, adolescence, and adulthood stages. Narrated by Kathy, she flashed back the memories of how they, Kathy and Tommy, are puzzled because of too many mysteries in Hailsham, the boarding school where they live. They connected each puzzle which could be the answer. But, in the novel, the question they belong to for being different brought them to another question. The process of findings itself flowed as long as they grew. In the end, they found information about their identity as a clone and as an individual.
Teacher Readiness For Digital Transformation Of The Educational Process

The article presents an analysis of the problem of readiness of higher schoolteachers for online education.The modern system of higher education in the context of digital transformation is undergoing a transitional period due to the need to modernize the educational space and the formation of sufficient digital literacy of scientific and pedagogical workers of the university, since at present their successful professional activity is impossible without the productive and innovative use of information and communication technologies that constitute the foundation for professional development of teachers.This process involves not only the constant wide dissemination of knowledge and information, their transformation into digital educational products, but also the presence of the teacher's ability and readiness to effectively organize the educational process in new conditions.According to the authors of the article, the digital readiness of teachers in education should become the subject of systematic scientific analysis.During the study, the authors of the article analyzed Russian and foreign experience on the organization of conditions for the formation of readiness of a modern university teacher for educational activities in a digital environment.The article presents the results of a survey, the purpose of which was to determine the impact of digital educational environment on the professional activities of university teachers and to identify the level of their readiness for digital transformation of educational process.
Evaluation of Synthetic Datasets Generation for Intent Classification Tasks in Portuguese

A chatbot is an artificial intelligence based system aimed at chatting with users, commonly used as a virtual assistant to help people or answer questions. Intent classification is an essential task for chatbots where it aims to identify what the user wants in a certain dialogue. However, for many domains, little data are available to properly train those systems. In this work, we evaluate the performance of two methods to generate synthetic data for chatbots, one based on template questions and another based on neural text generation. We build four datasets that are used training chatbot components in the intent classification task. We intend to simulate the task of migrating a search-based portal to an interactive dialogue-based information service by using artificial datasets for initial model training. Our results show that template-based datasets are slightly superior to those neural-based generated in our application domain, however, neural-generated present good results and they are a viable option when one has limited access to domain experts to hand-code text templates.
Pedagogia Dictionary: Web Application Development

This study aimed to develop a web-based Pedagogia Dictionary application, which is a special dictionary in the field of education and learning.This research was conducted using the D & D (Design and Development) approach or development research that produces a product.This study adopted the stages of the Ellis & Levy (2010) development model consisting of: a) identification of the problem; b) explain the purpose; c) design and develop artifacts; d) testing artifacts; e) evaluating test results, f) communicating test results.The information system modeling used a system through diagrams consisting of flowcharts, data flow diagrams, and entity relationship diagrams.In this study, the questionnaire was used to collect data related to the product that had been designed.The web based Pedagogia Dictionary application is expected to improve the quality of learning at Universitas Pendidikan Indonesia.In further development studies, the Pedagogia Dictionary application can be developed using mobile-based web technology.The findings have implications for the availability of a web-based dictionary as a reference source on the concept content in the fields of education and learning.The development of this application is in accordance with the development of the water fall model system.The usability testing results are a series of product trial results showing that there are several recommendations from respondents.So it can be concluded that the product is good to be an information search system in the form of a pedagogical dictionary dictionary.
Similarity Search and Correlation-Based Exploratory Analysis in EHRs: A Case Study with COVID-19 Databases

With the COVID-19 pandemic, many hospitals have collected Electronic Health Records (EHRs) from patients and shared them publicly. EHRs include heterogeneous attribute types, such as image exams, numerical, textual, and categorical information. Simply posing similarity queries over EHRs can underestimate the semantics and potential information of particular attributes and thus would be best supported by exploratory data analysis methods. Thus, we propose the Sketch method for comparing EHRs by similarity to provide a tool for a correlation-based exploratory analysis over different attributes. Sketch computes the overall data correlation considering the distance space of every attribute. Further, it employs both ANOVA and association rules with lift correlations to study the relationship between variables, allowing a deep data analysis. As a case study, we employed two open databases of COVID-19 cases, showing that specialists can benefit from the inference modules of Sketch to analyze EHRs. Sketch found strong correlations among tuples and attributes, with statistically significant results. The exploratory analysis has shown to complement the similarity search task, identifying and evaluating patterns discovered from heterogeneous attributes.
A Biometric AsymmetricCryptosystem Software Module Based on Convolutional Neural Networks

During the research, the analysis of the existing biometric cryptographic systems was carried out. Some methods that help to generate biometric features were considered and compared with a cryptographic key. For comparing compact vectors of biometric images and cryptographic keys, the following methods are analyzed: designing and training of bidirectional associative memory; designing and training of single-layer and multilayer neural networks. As a result of comparative analysis of algorithms for extracting primary biometric features and comparing the generated image to a private key within the proposed authentication system, it was found that deep convolutional networks and neural network bidirectional associative memory are the most effective approach to process the data. In the research, an approach based on the integration of a biometric system and a cryptographic module was proposed, which allows using of a generated secret cryptographic key based on a biometric sample as the output of a neural network. The RSA algorithm is chosen to generate a private cryptographic key by use of convolutional neural networks and Python libraries. The software authentication module is implemented based on the client-server architecture using various internal Python libraries. Such authentication system should be used in systems where the user data and his valuable information resources are stored or where the user can perform certain valuable operations for which a cryptographic key is required. Proposed software module based on convolutional neural networks will be a perfect tool for ensuring the confidentiality of information and for all information-communication systems, because protecting information system from unauthorized access is one of the most pressing problems. This approach as software module solves the problem of secure generating and storing the secret key and author propose combination of the convolutional neural network with bidirectional associative memory, which is used to recognize the biometric sample, generate the image, and match it with a cryptographic key. The use of this software approach allows today to reduce the probability of errors of the first and second kind in authentication system and absolute number of errors was minimized by an average of 1,5 times. The proportion of correctly recognized images by the comparating together convolutional networks and neural network bidirectional associative memory in the authentication software module increased to 96,97%, which is on average from 1,08 times up to 1,01 times The authors further plan a number of scientific and technical solutions to develop and implement effective methods, tools to meet the requirements, principles and approaches to cybersecurity and cryptosystems for provide integrity and confidentiality of information in experimental computer systems and networks.
Enhanced location tracking in sensor fusion-assisted virtual reality micro-manipulation environments

Virtual reality (VR) technology plays a significant role in many biomedical applications. These VR scenarios increase the valuable experience of tasks requiring great accuracy with human subjects. Unfortunately, commercial VR controllers have large positioning errors in a micro-manipulation task. Here, we propose a VR-based framework along with a sensor fusion algorithm to improve the microposition tracking performance of a microsurgical tool. To the best of our knowledge, this is the first application of Kalman filter in a millimeter scale VR environment, by using the position data between the VR controller and an inertial measuring device. This study builds and tests two cases: (1) without sensor fusion tracking and (2) location tracking with active sensor fusion. The static and dynamic experiments demonstrate that the Kalman filter can provide greater precision during micro-manipulation in small scale VR scenarios.
Making The Casher Application For The Tonguewing Meatball Restaurant Using Mysql And Netbeans

The development of information technology and science in the field of automation has recently had a great influence in almost all fields. An automated system makes all work easier with very accurate results and reduces processing time. In this scientific writing, the author discusses the difficulties in the data collection process, calculating the total price and checking data in a restaurant that still uses the manual method, which is why the author creates this application that aims to simplify and facilitate entrepreneurs help build their business from mistakes or even losses that can be detrimental to both the customer and the restaurant manager. The design of this POS application uses UML, navigation structures and flowcharts. For the software, the author uses NetBeans and MySQL applications to process the database.