Reviewerly/exHarmony huggingface dataset:
Measurement of quality services in the laboratory

Abstract The problem in this study is complaints about the quality of laboratory services in the Faculty of Engineering which were delivered by students through a pre-research questioner. This problem needs to be corrected by measuring the quality of laboratory services so that it can increase satisfaction from students. The purpose of this research is to find out student satisfaction with the quality of services in the Faculty of Engineering laboratory. The method used in this study is the Service Quality (SERVQUAL). The results of the research obtained using the SERVQUAL model, the lowest values for each dimension were obtained. Tangible; laboratory room are clean, comfortable and spacious in accordance the standard national laboratory. Empathy; Assistants the Laboratory gives attention and prioritizes. Responsiveness; Assistants provide services quickly and precisely. Reliability; The assessment process is an objective and transparant. The Assurance; Assistant has the ability to answer all practical questions. The conclusion of the research that The priority to improve service quality the dimensions of tangible; laboratory room are clean, comfortable and spacious in accordance the standard national laboratory.
Research and Practice of Blending Teaching Model in the “Internet” Era--a Case Study of College English Courses

Nowadays, Internet technology has been widely used in higher education and achieved an excellent teaching effect. In the “Internet” era, the traditional class-based teaching model of college English teaching is unable to effectively meet the learning needs of students. To solve this problem, college leaders and English teachers are required to strengthen their thinking on the Internet, then actively build a blending teaching model.  First, this paper briefly analyzes the current situation of college English teaching, and then expounds the ways to construct the blending teaching model and its key points in the “Internet” era of college English courses, the content is small, but the guidance is strong.
온라인 제품리뷰 데이터를 활용한 제품기회의 동적 모니터링

Improvements of a product can be carried out in accordance with customer requirements for the product, and thus it is necessary for product-based firms to identify product topics customers currently discuss and transform the topics into product opportunities. Despite social media mining studies for product opportunities, they have limitations in monitoring product topics and prioritizing them from dynamic aspects. Therefore, this paper suggests a social media mining-based dynamic product opportunity identification approach, which consists of 1) collecting large-scale online product review data of a product and extracting product-related keywords from them, 2) recognizing common product topics customers interested in through topic modeling, 3) calculating indicators, such as importance, satisfaction and growth, over time for the identified topics, and 4) employing TOPSIS to monitor and prioritize changing product topics. To demonstrate the applicability of the approach, this study carries out a case study with iPad product review data. This study tracks dynamically evolving product opportunities to help set future improvement directions of a product and accordingly enables product-based firms to quickly cope with changing customer needs for their product.
Science activity for gifted young scientist: thermodynamics law experiment media based IoT

TIn this research, thermodynamics law experiments media based IoT was developed and tested. The purpose of this research was to assess the effectiveness of media through a problem-based learning laboratory for gifted young scientists. This research is Research and Development with ADDIE (Analysis, Design, Develompment, Implementation, and Evaluation) models. The research subjects consisted of four expert validators, two teachers and one groups of 108 students in Senior High School 2 in Batang City, Indonesia. Data were gathered by using questionnaires, observation, and written test. The results of the Normalized-gain test were 0.79 for the experiment class and 0.41 and 0.30 for the control class. This media is easily assembled, based on digital, equipped with manuals and student worksheets. The validation results from the media experts 3.81 (Very Good), the results of the validation from the material experts 3.54 (Very Good) and the results of the physics teacher's responses covering all aspects of the material and multimedia 3.68 (Very Good). The results of the validation show that thermodynamic law experiment media based IoT is appropriate to be used as a medium for learning thermodynamics law.
Research on physical education curriculum using “skill theme” proposed by Graham et al.

In this paper, I examine the curriculum theory using “skill theme” and aim to develop strategies regarding “Physical Fitness” course. In this paper, I highlight three design problems from discussion about Physical Fitness: (1) Content organization (knowledge and skills), (2) purpose and application tasks, and (3) annual planning. Graham et al. emphasized that it is important for children to learn motor skills as physical education. Graham et al. further showed how to design a curriculum using “the wheel” consisting of skill themes and movement concepts. A review of “skill theme” approach proposed by Graham et al. provides strategies to address the three design problems: (1) organizing the content of Physical Fitness by combining the skills and concepts of the wheel shown by Graham et al., (2) standing on the view that each child has various skill levels, letting them explore a combination of skills and concepts, and setting challenges to create games and dance activities, or to maneuver the body more effectively in gymnastics, outside existing sports events, (3) treat one skill in a short time, pick up various skills and concepts throughout the year, and deepen in a spiral across school years. These methods of “skill theme” are valuable in considering the curriculum design of Physical Fitness course activities.
HQC-RMRS, an instantiation of the HQC encryption framework with a more efficient auxiliary error-correcting code

The HQC encryption framework is a general code-based encryption scheme for which decryption returns a noisy version of the plaintext. Any instantiation of the scheme will therefore use an error-correcting procedure relying on a fixed auxiliary code. Unlike the McEliece encryption framework whose security is directly related to how well one can hide the structure of an error-correcting code, the security reduction of the HQC encryption framework is independent of the nature of the auxiliary decoding procedure which is publicly available. What is expected from it is that the decoding algorithm is both efficient and has a decoding failure rate which can be easily modelized and analyzed. The original error-correction procedure proposed for the HQC framework was to use tensor products of BCH codes and repetition codes. In this paper we consider another code family for removing the error vector deriving from the general framework: the concatenation of Reed-Muller and Reed-Solomon codes. We denote this instantiation of the HQC framework by HQC-RMRS. These codes yield better decoding results than the BCH and repetition codes: overall we gain roughly 17\% in the size of the key and the ciphertext, while keeping a simple modelization of the decoding error rate. The paper also presents a simplified and more precise analysis of the distribution of the error vector output by the HQC protocol.
Video Blogging in the Digital Era for Learning English Speaking

AbstractIn language communication there are various skills that need to be mastered, ranging from reading, writing to speaking. In this study, the author will examine the use of vlogs as a medium of learning to speak in English at IAIN Surakarta more specifically at the sharia faculty and the faculty of usuludin dakwah. The study uses descriptive qualitative methods. The findings were obtained that the vlog media was able to increase student motivation and improve students' abilities or skills, especially in speaking English. Moreover, it can increase self-confidence in students in speaking or daily activitiesKeywords: Vlog, speaking, English
PROBLEMS OF FUNCTIONING OF THE SCIENTIFIC SPHERE OF HIGHER EDUCATION

Conference proceedings are devoted to modern global trends in the development of innovative scientific researches. General issues of the engineering, medical, psychological, philological, economic sciences, history of art, social communications and so on are considered. The publication is designed for scientists, lecturers, postgraduate students, students, as well as for the general readers. International Scientific Conference Modern Global Trends in the Development of Innovative Scientific Researches: Conference Proceedings, March 20th, 2020. Riga, Latvia: Baltija Publishing. 180 pages.
hidden markov random fields and cuckoo search method for medical image segmentation

Segmentation of medical images is an essential part in the process of diagnostics. Physicians require an automatic, robust and valid results. Hidden Markov Random Fields (HMRF) provide powerful model. This latter models the segmentation problem as the minimization of an energy function. Cuckoo search (CS) algorithm is one of the recent nature-inspired meta-heuristic algorithms. It has shown its efficiency in many engineering optimization problems. In this paper, we use three cuckoo search algorithm to achieve medical image segmentation.
Taxonomy and Complete Overview from AI to Deep Convolutional Neural Networks in Computer Vision

Homo sapiens are the only species that top among all the other species on the planet earth and also known for their three important qualities such as learning (patana), thinking (chinthana) and analysis (mamthana). Perhaps this is the only reason, many researchers try to mimic the human intelligence in machine which is still continued till date in the domain known as Artificial Intelligence. The paper focuses on Non-symbolic AI technique which is one of the two main important approaches such as symbolic and non-symbolic AI technique used in solving a problem or finding a solution. The Non-symbolic technique which is either principle-based or similar to that of biologically inspired way of solving problem through distributed and connected Neurons. In this way the paper narrow down from AI to Neural networks to Deep convolutional neural networks and its variations. The major contribution of this paper as it take journey from AI to Deep CNN, the understanding of the concept especially in the application domain such as computer vision is been captured in the form of taxonomy.
Pengaruh Konsep Diri dan Kecerdasan Emosional terhadap Kemampuan Pengambilan Keputusan Siswa

This study aims to investigate the effect of self-concept and emotional intelligence on students' decision making abilities. This research was conducted in eighth grade students of junior high schools in the city of Depok. Determination of the sample is done using cluster random sampling obtained by the sample size of 40 students. The method used to investigate the magnitude of the effect is to use multiple linear regression. Based on the results of research that has been done obtained information that there is a significant influence between self-concept and emotional intelligence on the decision-making abilities of students. The influence of self-concept and emotional intelligence separately on the ability of decision making were 21.72% and 28.09%, respectively. While the influence of the two independent variables together is equal to 81.7%. This illustrates that self-concept and emotional intelligence are important components that must be considered by educators in particular, in developing decision-making abilities.
Guides @ UF: Course Reserves for George A. Smathers Libraries: Basics

Learn about Course Reserves and how they can contribute to your teaching and learning experiences.
The 5 Best Canon AV-1 Camera Lenses

The Canon AV-1 is a great camera. This post will talk about the top 5 lenses to use on the Canon AV-1. More information is below, however, if ...
The Impact of Different Types of Tests in EFL Writing on the Teachers’ Classroom Practices

To promote the quality of national education, a test, especially high-stake test, has received special concern from the government. Such kind of test brings serious consequence (impact) to some related parties like teachers, students, school systems, and society. This article is intended to highlight how different type of testing affects the teachers’ teaching practices in the classrooms. In Indonesian secondary schools, two types of tests, National Examination (NE) and School Examination (SE) are administered to measure students’ achievement in a particular level as well as to decide students’ graduation. The two tests are different at some points. First, the test for NE was developed and administered by the government through the Board of National Education Standard. Meanwhile, the preparation and administration of the test for SE were done by the English teachers at every school. Second, the test of NE was in the form of objective test, whereas, the test of SE is subjective in which the students should create writing products. Using descriptive qualitative research design, the current research investigated how four Indonesian secondary school teachers carried out the teaching of EFL Writing in their classroom as the impact of the two types of test. The findings of this research revealed that the administration of the different types of tests brings different impacts on the preparation and classrooms practices in which the teachers were more enthusiastic and serious to prepare for the SE rather than the NE. It can be concluded that a particular type of test which requires full involvement of the teachers either in the preparation or the administration like SE brings positive impact on their classroom practices.
SINVAD: Search-based Image Space Navigation for DNN Image Classifier Test Input Generation

The testing of Deep Neural Networks (DNNs) has become increasingly important as DNNs are widely adopted by safety critical systems. While many test adequacy criteria have been suggested, automated test input generation for many types of DNNs remains a challenge because the raw input space is too large to randomly sample or to navigate and search for plausible inputs. Consequently, current testing techniques for DNNs depend on small local perturbations to existing inputs, based on the metamorphic testing principle. We propose new ways to search not over the entire image space, but rather over a plausible input space that resembles the true training distribution. This space is constructed using Variational Autoencoders (VAEs), and navigated through their latent vector space. We show that this space helps efficiently produce test inputs that can reveal information about the robustness of DNNs when dealing with realistic tests, opening the field to meaningful exploration through the space of highly structured images.
Combining Experts' Causal Judgments

Consider a policymaker who wants to decide which intervention to perform in order to change a currently undesirable situation. The policymaker has at her disposal a team of experts, each with their own understanding of the causal dependencies between different factors contributing to the outcome. The policymaker has varying degrees of confidence in the experts' opinions. She wants to combine their opinions in order to decide on the most effective intervention. We formally define the notion of an effective intervention, and then consider how experts' causal judgments can be combined in order to determine the most effective intervention. We define a notion of two causal models being \emph{compatible}, and show how compatible causal models can be merged. We then use it as the basis for combining experts' causal judgments. We also provide a definition of decomposition for causal models to cater for cases when models are incompatible. We illustrate our approach on a number of real-life examples.
LibGuides: Art and Design Subject Guide: E-books

This guide will take you through all you need to make the most out of the resources available to you through the library.
Criterion Feedback in College Writing Instruction: Its Effectiveness and Student Perception

The use of computer technologies by writing students has increased, but language teachers and researchers have expressed doubts about their effectiveness and feasibility. In the field of writing assessment, this study examined the effectiveness of Criterion as an automated essay evaluation (AEE) system while addressing two research questions: (a) What types of feedback did Criterion provide to Korean EFL learners? and (b) With respect to their English writing study, how did Korean EFL learners perceive Criterion feedback? Analyses on engineering students'' essays and perception survey data were mainly conducted quantitatively. Results showed that Criterion feedback on the students'' essays was effective for correcting missing articles and number/subject-verb agreement errors and reducing repetitive words. The overall student perception of Criterion feedback was positive. However, vague feedback on organization and development and repeating words; and inaccurate feedback on mechanical errors, mostly spelling errors and articles; and the lack of feedback on errors need to be dealt with as they decrease the reliability of the AEE system as an instructional tool. The results and findings of this study were discussed while offering implications for future avenues of research.
Local semi-supervised approach to brain tissue classification in child brain MRI

Most segmentation methods in child brain MRI are supervised and are based on global intensity distributions of major brain structures. The successful implementation of a supervised approach depends on availability of an age-appropriate probabilistic brain atlas. For the study of early normal brain development, the construction of such a brain atlas remains a significant challenge. Moreover, using global intensity statistics leads to inaccurate detection of major brain tissue classes due to substantial intensity variations of MR signal within the constituent parts of early developing brain. In order to overcome these methodological limitations we develop a local, semi-supervised framework. It is based on Kernel Fisher Discriminant Analysis (KFDA) for pattern recognition, combined with an objective structural similarity index (SSIM) for perceptual image quality assessment. The proposed method performs optimal brain partitioning into subdomains having different average intensity values followed by SSIM-guided computation of separating surfaces between the constituent brain parts. The classified image subdomains are then stitched slice by slice via simulated annealing to form a global image of the classified brain. In this paper, we consider classification into major tissue classes (white matter and grey matter) and the cerebrospinal fluid and illustrate the proposed framework on examples of brain templates for ages 8 to 11 months and ages 44 to 60 months. We show that our method improves detection of the tissue classes by its comparison to state-of-the-art classification techniques known as Partial Volume Estimation.
RAPiD: Rotation-Aware People Detection in Overhead Fisheye Images

Recent methods for people detection in overhead, fisheye images either use radially-aligned bounding boxes to represent people, assuming people always appear along image radius or require significant pre-/post-processing which radically increases computational complexity. In this work, we develop an end-to-end rotation-aware people detection method, named RAPiD, that detects people using arbitrarily-oriented bounding boxes. Our fully-convolutional neural network directly regresses the angle of each bounding box using a periodic loss function, which accounts for angle periodicities. We have also created a new dataset with spatio-temporal annotations of rotated bounding boxes, for people detection as well as other vision tasks in overhead fisheye videos. We show that our simple, yet effective method outperforms state-of-the-art results on three fisheye-image datasets. Code and dataset are available at http://vip.bu.edu/rapid .
Conflict Monitoring Optimization Heuristic Inspired by Brain Fear and Conflict Systems

This paper deals with a brain-inspired approach to design evolutionary optimization algorithm. The approach is named as Conflict Monitoring Optimization inspired by two related processes in the Brain, conflict monitoring and fear processing systems. First of all, the current issues of optimization metaheuristic are discussed and challenges are addressed. Afterwards, the paper discusses a brief review of researchers’ works in danger processing (fear) system of the Brain in three different aspects. Then a model based on fear system model is derived and checked out. Next, the role of Anterior Cingulate Cortex in conflict monitoring of information is used as a seal of approval to the proposed algorithm. The finalized algorithm at last, is modified to take mutation parameters to intensify the evolutionary aspects of model. After proposing arbitrary subprograms, the proposed algorithm is checked out with 20 benchmark functions with dimension length of 3, 10 and 50. The evaluation result is compared with well-known metaheuristics for 50 different runs and its effectiveness on different function types is discussed afterwards.
CONTEXTUALISING KNOWLEDGE AS THE BASIS OF NEW MODEL SCHOOL TEACHER PREPARATION

Processes of convergence and integration that characterize contemporary society naturally seep into the education system, first of all at school. Proof of this are the modern State educational standards for general education in Russia, which focuses on the formation, along with subject, metasubject educational results. However, the preparation of teachers is based on subject principle, which hampers the realization of interdisciplinary integration laid down in standards. Increase massif operated knowledge from different disciplinary areas requires new approaches to formation of teachers’ professional skills, primarily, the ability to constantly replenish and build their personal knowledge. Currently, the development of creative abilities of presentation and interpretation training information that is interdisciplinary in nature. An interdisciplinary approach in teaching alters the level and quality of learning. The basis for this approach in the preparation of teachers can become idea of knowledge contextualization. The aim of this paper is theoretical and experimental justification of the need to build a new model of teacher preparation, capable to participate in solving the problems of the integration of school subjects. Methods of theoretical analysis (system, historical and problematic), as well as methods of design and experimental work are used. The article presents the results of experimental work undertaken to search for a new model of teacher preparation, capable to participate in the integration of school subjects (for example mathematics and Russian language), concepts, laid down in model building, revealed the prior directions of its implementation.