Reviewerly/exHarmony huggingface dataset:
The Relationship Between Inference Skills and Reading Comprehension

This research aims to reveal the extent to which inference-making ability predicts reading comprehension skill. The research participants consisted of 117 middle-grade students attending 5th and 6th grades. The data was collected by Inference-Making Ability Test and Reading Comprehension Test. The tests were administered to the respondents in a single session and the answers were interpreted by two evaluators. The answers provided by the participants were imported into a statistical software after being coded and were analyzed. The research findings showed that the participants had poor level of inference-making ability. Whereas reading comprehension skills of the participants was at a medium level. While especially lexical inferencing was achieved at a satisfying level, propositional and pragmatic inferencing could not be attained at sufficient levels. The research results assert that inference-making ability predicted reading comprehension skill at a medium level. In light of this finding, it was recommended to introduce and include inference-making strategy in reading and literacy education so that the level of reading comprehension skill would be enhancedges.
Mechanism and Compensation of Measurement Error Induced by Thermal Deformation of Digital Camera in Photo Mechanics

A thermal-induced measurement error induced by thermal deformation of digital camera in photo mechanics methods that has the same magnitude of the error as that in the resistance strain measurement method reduces the accuracy of high-precision measurement substantially and must, therefore, be compensated. Starting from the underlying mechanism of a thermal-induced measurement error, we investigated the image error introduced by thermal behaviours of digital cameras widely used in photo mechanics. We experimentally determined the relationships between the thermal behaviours and temperature, derived the relationship between the image error and measurement error of photo mechanics methods, and eventually established a physical model to explain the underlying relationship between the thermal-induced measurement error and temperature. Furthermore, based on the investigation of the underlying mechanism, we introduced three types of temperature compensation methods for photo mechanics, namely the model compensation method, the preheating method, and the compensation specimen method. We experimentally demonstrated the feasibility of these compensation methods. The model compensation method only needs the data regarding the environmental temperature during operation of the digital camera to implement the correction of the measurement results and enhance the measurement accuracy of photo mechanics methods. The preheating method is suitable for indoor photo mechanics measurements wherein the environmental temperature is almost constant, which ensures that the appearance of thermal balance of the digital camera after a period of self-heating. The compensation specimen method reduces the effective resolution of the images and it also requires that the image error forms in the region of tested specimen are the same as that in the region of the compensation specimen.
Nonlinear system modeling using the takagi-sugeno fuzzy model and long-short term memory cells

The data driven black-box or gray-box models like neural networks and fuzzy systems have some disadvantages, such as the high and uncertain dimensions and complex learning process. In this paper, we combine the Takagi-Sugeno fuzzy model with long-short term memory cells to overcome these disadvantages. This novel model takes the advantages of the interpretability of the fuzzy system and the good approximation ability of the long-short term memory cell. We propose a fast and stable learning algorithm for this model. Comparisons with others similar black-box and grey-box models are made, in order to observe the advantages of the proposal.
Improving Camera Travel for Immersive Colonography

Colonography allows radiologists to navigate intricate subject-specific 3D colon images. Typically, travel is performed via Fly-Through or Fly-Over techniques that enable semi-automatic traveling through a constrained, well-defined path. While these techniques have been studied in non-VR desktop environments, their performance is yet not well understood in VR setups. In this paper, we study the effect of both techniques in immersive colonography and introduce the Elevator technique, which maintains a fixed camera orientation throughout navigation. Results suggest Fly-Over was overall the best for lesion detection at the cost of slower procedures, while Fly-Through may offer a more balanced trade-off between speed and effectiveness.
Digital Competence of a Teacher as a Means of Education Process Managing in a High School

In the era of digitalization, the need to expand management tools is considered to be the main problem of modern education.The implementation of a model for improving the effectiveness of digital competence of a teacher will contribute to the optimal level of Higher education process management.The model is based on two components: knowledge-based and motivation-activity-based. The knowledge component includes selfeducation (advanced training courses, participation in various webinars and forums, etc.).The second component is determined by the desire to improve the quality of the educational process and maintain the image of a modern teacher.The activity component includes the development of electronic courses in readable disciplines, web-quests, knowledge controllingntools and learning results evaluationetc.The article presents the results of the study of the Preschool and Primary Education Faculty teachers' digital competence level(Lobachevsky State University of Nizhny Novgorod, Arzamas branch) which makes it possible to reveal the relationship between the level of digital competence of a teacher and the level a teacher's organizational and controlling functions forming concerning theeducational process management.The results of applying the developed model to improve the effectiveness of teachers' digital competence, as well as experimental research data, indicate its effectiveness.
Speech Act Analysis of English Teacher Talk at SMP Negeri 1 Rangkasbitung

&lt;span&gt;Teachers’ talk is a factor that may entail to the smoothness of English teaching and learning experience. Besides, language used by teacher in the classroom is crucial, because it will influence students’ learning process and development. This study investigated the speech acts in the teacher talk at SMP Negeri 1 Rangkasbitung. This study involved the Seventh Grade English teacher of SMP Negeri 1 Rangkasbitung as the data source. Furthermore, this study used Searle’s theory of speech acts classification as the instrument for analyzing the data. Based on the analysis, there were only four types of speech acts found in the teacher talk, 68 % directive speech act, assertive speech acts with 14 %, and the last two of speech act, commissive and expressive speech act, were only 10 % and 8 % in the teacher talk during the teaching-learning process. This study revealed that the majority of teacher talks found in the form of directive speech act, in the other words the classroom interaction went one way which more likely teacher-centeredness. Likewise, the teacher-centeredness make the students talk less and most importantly make the students became dependent and passive learner. In this study, the teacher became the central subject of learning rather than the students, hence it goes against the demands of National Standard and did not follow the principles of current Indonesian curriculum. Therefore, the conclusion which can be drawn from this study is that the teacher should utilize speech acts appropriately because high quality and the appropriateness of the teacher’s speech acts can convey teaching materials effectively, enhance teaching efficiency easily, and provide active learning meaningfully.&lt;/span&gt;
Using Priorities of Hospitalized Patients and Their Caregivers to Develop Personas.

Hospitalized patients and their caregivers often access technologies like patient portals to understand what happens during their hospital stay. Although this access can lead to more patient engagement and positive health outcomes, many find that the technology does not support their needs. As a first step toward improving patient-facing technologies we create personas for hospitalized patients and their caregivers by following the Q Methodology, a technique for quantifying subjective opinion. We clustered 28 hospitalized patients' and 19 caregivers' attitudes towards receiving and managing information and working with their care team. We contribute three patient personas: patients who are (1) accommodating information seekers, (2) involved safety guardians, and (3) self-managing participators. We identify three caregiver personas: (1) cooperative information seekers, (2) vocal participators, and (3) hands-off safety guardians. These personas can inform future tools designed to support communication and information management for hospitalized patients and caregivers.
Writing Strategies Utilized by Successful and Unsuccessful ESL Undergraduate Students in Writing Classroom

&lt;span&gt;The study examined the writing strategies used by undergraduate students in the ESL writing classroom. Three strategies were involved in the writing process which was; pre-writing strategies, while writing strategies and revising strategies. Specifically, the objectives were; (1) &lt;/span&gt;&lt;span&gt;to &lt;/span&gt;&lt;span lang="EN-MY"&gt;examine the &lt;/span&gt;&lt;span lang="IN"&gt;student's preferred strategies of successful and unsuccessful ESL students in the writing process&lt;/span&gt;&lt;span&gt;. In this cross-sectional study, 50 undergraduate ESL students from Universiti Pendidikan Sultan Idris (UPSI) were the targeted sample for this study. Three strategies of the writing process; pre-writing, while writing and revising were measured via a standard questionnaire that adapted from previous studies. The data obtained were analyzed by using the software of Statistical Package for the Social Science (SPSS). The findings of this study indicated ESL students have preferred planning strategies then while writing strategies and revising strategies. Meanwhile, the findings of this study will have significant implications for ESL undergraduate students in their writing. Contributions, limitations, and implications of the study are also discussed.&lt;/span&gt;
Research on Application of Blockchain Technology in Cloud-Network Collaboration

With the deep integration of blockchain, cloud computing and 5G technology, the business model of the Internet is also undergoing subversive changes. Based on the current development trends of the industry, this article illustrates the application prospects of blockchain technology in cloud-network collaboration For users to purchase network services, blockchain technology and consensus accounting are adopted to effectively avoid uploading user data to the Internet company's cloud server, thereby protecting user privacy from threats. This article provides a solution that uses blockchain technology in cloud-network collaboration to ensure transaction security. At the same time, it analyzes the consensus mechanism for the actual application scenario, and selects a consensus mechanism which is suitable for the cloud-network collaborative application scenario.
Progressive System: A Deep-Learning Framework for Real-Time Data in Industrial Production

Deep learning based on a large number of high-quality data plays an important role in many industries. However, deep learning is hard to directly embed in the real-time system, because the data accumulation of the system depends on real-time acquisitions. However, the analysis tasks of such systems need to be carried out in real time, which makes it impossible to complete the analysis tasks by accumulating data for a long time. In order to solve the problems of high-quality data accumulation, high timeliness of the data analysis, and difficulty in embedding deep-learning algorithms directly in real-time systems, this paper proposes a new progressive deep-learning framework and conducts experiments on image recognition. The experimental results show that the proposed framework is effective and performs well and can reach a conclusion similar to the deep-learning framework based on large-scale data.
It Is Time for New Perspectives on How to Fight Bloat in GP

The present and future of evolutionary algorithms depends on the proper use of modern parallel and distributed computing infrastructures. Although still sequential approaches dominate the landscape, available multi-core, many-core and distributed systems will make users and researchers to more frequently deploy parallel version of the algorithms. In such a scenario, new possibilities arise regarding the time saved when parallel evaluation of individuals are performed. And this time saving is particularly relevant in Genetic Programming. This paper studies how evaluation time influences not only time to solution in parallel/distributed systems, but may also affect size evolution of individuals in the population, and eventually will reduce the bloat phenomenon GP features. This paper considers time and space as two sides of a single coin when devising a more natural method for fighting bloat. This new perspective allows us to understand that new methods for bloat control can be derived, and the first of such a method is described and tested. Experimental data confirms the strength of the approach: using computing time as a measure of individuals’ complexity allows to control the growth in size of genetic programming individuals.
The Effects of Digital Literacy and the Frequency of Contact with Children or Grandchildren via ICT on the Cognitive Function of the Elderly

본 연구는 ‘2017년도 노인 실태조사’에 응답한 65세 이상 노인 8,942명을 대상으로 ICT를 활용한 자녀·손자녀 접촉빈도, 디지털 리터러시 등의 특성이 인지기능에 미치는 영향을 파악하기 위한 이차자료 분석 연구로, 다중 회귀분석을 활용하였다. 연구결과 노인의 인지기능에 가장 큰 영향을 미치는 요인은 디지털 리터러시로 나타났다. 또한 ICT를 활용한 손자녀와의 접촉빈도는 디지털리터러시 및 인지기능과 유의한 상관관계가 있으며 인지기능에 긍정적 영향을 주는 요인임이 새롭게 밝혀졌다. 이를 토대로 노인을대상으로 한 정보화 교육 및 활용의 중요성과 이를 통한 세대 간 의사소통 활성화의 필요성에 대해 논의하였다.The purpose of this study was to analyze the effects of digital literacy and the frequency of contact with children or grandchildren via ICT on cognitive functions of 8,942 adults over age 65 who responded to the 2017 National Survey of Older Koreans, using multiple regression analysis. We found that digital literacy was the most significant factor on cognitive functions of the elderly. Also, the frequency of contact with grandchildren via ICT was a positive factor for cognitive function and had a positive correlation with digital literacy. Based on this results, the importance of digital literacy education and intergenerational communication via ICT were discussed.
Digital Nutrition: Spectral Portraits of Optimal Diet

The algorithm for calculating the values of daily menu portions of dishes in accordance with certain standards is constructed.This is consumption' standards of a given set of controlled essential substances contained in food.Such substances in this work include macronutrients -proteins, fats, carbohydrates, as well as micronutrients-vitamins A, B1, B2, C, PP, carotene and the elements -sodium, potassium, calcium, magnesium, phosphorus, iron.The features of the resulting computational problems associated with the fact that the daily consumption of macronutrients and micronutrients differs in weight by 4-5 orders of magnitude are investigated.To analyze the quality of the computational conditionality for the problem of determining the size of a dish portion, spectral portraits of the dishes nutrient composition matrices are used.The portraits show us the accuracy of calculating the matrix spectrum depending on the accuracy of the matrix elements.Such portraits are built for typical menus without specific exceptions for a conditionally healthy person and for a vegetarian.A comparative analysis of the corresponding nutrient matrices is carried out.An algorithm for selecting dishes and calculating the values of their portions, which is stable for macronutrients, is proposed.It is shown that when the planning horizon increases, the average daily calculated consumption of micronutrients approaches to the recommended standards of the Ministry of health.It is estimated the rate of convergence on micronutrients depending on the menu type.
Improving the Students' Big Data Era Skills through the Online International Project X-culture

Among the most crucial for the specialist of the era of Big Data skills are critical-thinking, problem-solving, collaborative and digital skills. In this paper, we investigate how international online project "X-culture" that was implemented into the course influenced such vital students' skills. To evaluate the impact we used information from the X-culture project database that was collected through various surveys and conducted an interview with students. According to the results received students skills developed significantly after the participation in the project. Also we implemented a correlation analysis to determine weather students' critical-thinking, problem-solving, collaborative and digital skills affected the final reports scores on the international project. In our case collaborative skills played the most substantial role for getting the highest final reports scores while the relationship between digital skills and reports' results was the weakest.
Efficient Implementation of a Self-sufficient Solar-Powered Real-Time Deep Learning-Based System

This paper presents a self-sufficient solar-powered real-time Deep Learning (DL) based system that runs inference 100% on solar energy and which is composed of an Nvidia Jetson TX2 board and a dual-axis solar tracker based on the cast-shadow principle. In order to have a higher energy being generated by the solar tracker as well as a lower energy consumption by the real-time DL-based system, we have: a) updated our solar tracker's panel with a higher number of polycrystalline photovoltaic (PV) cells and connected it to a chain of two inverters, one accumulator and one solar charge controller; b) implemented a motion detection method that triggers the inference process only when there is substantial movement in webcam frame. Experimental results show that our solar tracker generates sufficient and constant solar energy for all the 4 DL models (VGG-19, InceptionV3, ResNet-50 and MobileNetV2) that are running in real-time on the Nvidia Jetson TX2 platform and which requires more than 5 times less energy when compared to a laptop having a Nvidia GTX 1060 GPU, proving that real-time DL-based systems can be powered by solar trackers without the need of traditional power plugs or need to pay for electricity bills.
Knowledge-Based Semantic Relatedness measure using Semantic features

Measuring semantic relatedness has received much attention for uses in many fields such as information retrieval and natural language processing.For handling synonymous problem in distributional-based measures, many researchers are investigating how to exploit semantic features in lexical sources to form knowledge-based measures.In the knowledge-based measures, a hierarchy model is used to measure the relatedness between words based on only the taxonomical features extracted from a provided lexical source.In this paper, a new knowledge feature-based measure is proposed to build the semantic vector of a word construct on taxonomical and non-taxonomical feature of relation words.The proposed measure utilised the topological parameters that weight the importance of each element in the semantic vector.One of the gold dataset used to assess the proposed model and compare the findings with other related works.The results demonstrated the effectiveness of the proposed model on measuring semantic relatedness between words.In this paper, the research framework is identified based on the observations made on the previous related works that have been conducted for semantic representation and semantic relatedness measures.The required data in this research includes the semantic knowledge-based approach and the evaluation datasets.The semantic knowledge that will be used throughout of this research is extracted from English WordNet 3.1.On the other hand, the evaluation datasets covers the gold standard benchmarks which have been used for evaluating the semantic relatedness measurements and text mining tasks.Finally, the evaluation is preform to evaluate the proposed method (PM) based on approach in this research, in which obtained the result have been analyzed, to discuss and compare based on different performance measure and finding the strength and weakness in this paper, to alternative the semantic representation correlated to this research, to designing and develop the topical-based on the semantic representation method for text mining from Social media.
The use of virtual pathology in teaching medical students: first experience of a medical school in Thailand

<ns4:p>This article was migrated. The article was not marked as recommended. Background and objective:Conventional light microscopy (CLM) has long been used as a teaching modality in pathology courses. Virtual microscopy (VM) has recently challenged traditional practices and revolutionized pathology education. However, most medical schools in Thailand still use CLM to teach pathology to medical students. This study aims to evaluate the effectiveness of VM in terms of undergraduate teaching as the primary experience at Thammasat University.Methods:Participants were 29 second-year medical students who sat in the practical session of the alimentary system pathology using VM as teaching modality. Students took pre- and post-tests with 12 questions covering common alimentary system diseases, followed by 10 survey questions with a five-point Likert-style scale. Test and satisfaction scores were analyzed.Results:There was a significant difference (p&lt;0.01) between student pre-test scores (mean ± SD, 1.7 ± 2.1) and post-test scores (7.1 ± 3.4). VM was viewed as a preferred learning modality, mainly because of its portability (mean: 4.9 on the five-point Likert-scale), satisfactory quality of images (4.4), permitting learning in less time (4.3), and stimulating cooperation between students while improving interaction with teachers (4).Conclusions:Student perceptions of VM as a new teaching-learning tool and their outstanding performance on the knowledge exam suggest that VM has a potential role in undergraduate teaching. The results of this study help to improve pathology teaching strategy in the integrated curriculum.</ns4:p>
Implementation of grey image compression algorithm based on variation partial differential equation

Compression is the key technology for the rapid development of multimedia technology, and images are an important part of multimedia information. For image compression, a grey image compression algorithm based on variation partial differential equations is proposed. On the encoding side, this article first uses a quad tree to segment the image, and then encodes and transmits some pixels. Secondly, an image interpolation algorithm based on variation partial differential equations is used at the decoding end to regenerate the image, effectively eliminating the block effect in the decoded image. Experiments show that this method can obtain higher compression ratio and peak signal-to-noise ratio, especially for images with larger size and less texture detail, and can better maintain large changes in grayscale in the original image. Details, which can easily remove the block effect, have high practical value.