Reviewerly/exHarmony huggingface dataset:
The Specifics Of Developing Worldview Competencies In The University Environment

The article reveals the methodical specifics of developing worldview competencies that are intermediate between existential skills – soft skills, and professional skills – hard skills, in the contemporary competency-based model of a specialist. A complex innovative teaching methodology that includes face-to-face lectures, practical sessions, and electronic technologies is considered through the example of the “Politology” discipline. A tool for developing the intellectual and personal resource of students is shown. The purpose of the work is to search an effective pedagogical model of developing worldview competencies in the context of mastering the course of "Politology" in the non-humanitarian university environment. These competencies include political self-identification, activation of civic position, and formation of patriotism. The research objective is to identify the most interesting, meaningful and effective pedagogical methods through testing and interviewing full-time students. Empirical methods of observation, comparison, measurement, theoretical methods of induction and deduction, abstraction, generalization, systematization and interpretation of facts, as well as a mental experiment are used in the article. The study confirmed the hypothesis that the humanities cannot and should not be transferred into electronic distance learning format in the context of digitalization process, since the development of soft skills and associated worldview competencies occurs mostly in interpersonal interaction in face-to-face team work environment.
Empirical Analysis of Context based Content Delivery for M-Learning Scenarios using ANFIS

Today's world is unusually popular with the internet and mobile devices in everyday life.It offers unprecedented possibilities learning with mobility.This kind of learning can be called "M-learning" (Mobile Learning) at any point in the world.Meeting learners ' needs in the current scenario in which collaborative electronic and mobile education systems have become more evolving.Every learners ' needs differ in terms of learning; context, content, learning styles, speed of learning, even including preferences, places.Mobile learning enables the learner to learn while moving, enabling the learner to learn in any time and any place.Learning styles have evolved along with advances in technology; specifically advances in mobile technology and mobile networks.Portable devices such as mobile phones, tabs, iPods, etc. are commonly used today by all.The way we learn has been changed with the use of these devices in education.In M-learning environment the learner has access to the contents everywhere and every time through mobile devices.Customization and learner context awareness are the important factors in providing the learner with relevant content.Appropriate content delivery based on a learner's context is a complex process.So a content delivery system is needed that takes into account learners ' needs such as context, style and devices features.To model such a system neural network with fuzzy reasoning can be used, to accommodate the dynamically changing learning styles, contexts and characteristics of smart device."If-then" conditions can be formed to build the suggestion rules required for such a content delivery system.ANFIS i.e.Artificial Nero Fuzzy Inference System is an integral asset to create fuzzy systems with IF-THEN guidelines.To model and analyze this type of context aware and adaptive content delivery system for an M-learning environment, ANFIS can be used.In this article, use of ANFIS tool is demonstrated for various m-learning scenarios with different contexts.Four different contexts are constructed based on the inputs given by the student learners.Using ANFIS these four scenarios have been analyzed empirically for their performance based on the RMSE of various membership functions.
We can, but should we? The ethics of genetically modified food

This book reflects academically on important and relevant natural scientific disciplines, important technologies and related media to determine and communicate the moral issues and challenges within those specific fields of study, and how to deal with them morally and from a multidimensional South African context. It aims to add scientific, technological and ethical value, locally and globally, by reflecting mainly from the viewpoint of a specific scholars, writing about the most pressing moral issues or challenges raised by problems within their specific field of study. It is written mainly from a qualitative methodological perspective, including autobiographical and participatory views. The co-authors present in respective chapters their research systematically and intersectionally, based on profound theoretical analysis and reasoning. Current research in the basic and implied sciences and technologies requires sound ethical practice based on a defensible moral stance. Moral norms, in our view, are deeply grounded and evolved convictions about justice and injustice, right and wrong, good and bad. It is not about rules. This scholarly book combines the insights and expertise of established South African scholars from different disciplines and backgrounds. The contributors are all deeply committed to the value and validity of science and ethical practice across the moral spectrum. Open and responsible discussions around this topic can lead to the introduction of moral guidelines and regulations to protect the rights of individuals, animals and the environment, while simultaneously facilitating the growth of scientific practice. This collected work, with its very specific and carefully selected grouping of academic fields, aims to innovatively assist in alleviating the shortage of academic publications reflecting on the moral issues in these specific fields.
Research on House Recommendation Model Based on Cosine Similarity in Deep Learning Mode in Grid Environment

Aiming at the current number of recommended models in the house recommendation system model, the recommendation accuracy and user satisfaction do not meet the needs of users, this paper proposes a house recommendation model based on cosine similarity in the deep learning mode in grid environment. The model first uses the established grid environment, combined with the deep learning mode, through the collection of a large number of housing basic data samples and user feedback information, establishes a mathematical model of housing recommendation, and then integrates the cosine similarity into the recommendation model, through training and parameters. Adjust the model framework gradually. Finally, through the derivation and verification of the simulation experiment, the proposed recommendation model can efficiently recommend the housing information that meets the requirements for the user, and improve the recommendation accuracy and user satisfaction.
Research Guides: Omni Search Tips: Getting Started

Search strategies and new tool features Reasons to sign in and understand what you're searching.
Moving Object Detection for Video Satellite Based on Transfer Learning Deep Convolutional Neural Networks

With the continuous development of the video satellite, its applications in the military and civilian fields are becoming more and more widespread. In recent years, video satellite has become increasingly important to perform real-time detection of moving object, but the influence of various imaging factors usually causes changes in the object features, which greatly increases the difficulty of object detection. Our work aims at the problems of object detection for video satellite, and we apply deep convolutional neural networks (CNNs) to solve these problems for video satellite object detection. In this paper, a deep regression-based CNN object detection method combined with transfer learning is proposed, which can detect the moving object and identify its category in real time. The experiments have shown that the method effectively improves the speed and precision for video satellite object detection under limited samples, which has good generalization on different resolution video images and outperforms other stateof-the-art detection methods. Our method achieves F1-Score of 90.50% in the test set and the average detection time of each image block is about 0.025s, which has lower time overhead and better robustness to rotation and illumination changes of the object.
Research Guides: OAT 151: Finding eBooks

This guide will help students taking OAT 151 complete their first library assignment for the class.
MANtIS: a novel information seeking dialogues dataset

Nowadays, most users access the web through search engine portals. However, information needs can often be ill-defined or too broad to be solvable by a list of results the user has to scroll through, which implies that he is most likely required to refine the need by himself to reach the desired result. In recent years, researchers have attempted to tackle these issues through conversations, more specifically through conversational search. This topic has seen an increase of interest from the research community, proven by the appearance of specialized workshops and seminars. The general public has also started to show interest, proven by the emergence of a wide range of virtual assistants, such as Google Assistant, Microsoft Cortana or Amazon Alexa. As such conversational systems seek to fulfill an information need of a user, they should be able to elicit and fully understand his requirements regardless of the domain, track the conversation as it evolves while attempting to clarify the initial information need and provide suggestions and answers that are based on concrete knowledge sources. Although various developments in domains adjacent to conversational search enabled us to better understand natural language, there is a lack of large-scale datasets that are appropriate for training models to perform conversational search tasks. Through our research, we have built a collection of over 80,000 conversations that fulfill the requirements of a conversational search dataset. We have benchmarked this dataset on three distinct tasks using multiple baselines.
Fixed-term Teachers’Perceptions on the Operation of the Fixed-term Teacher System: An Importance-Satisfaction Analysis

이 연구는 기간제교원제도 운영과 관련하여 제기되는 다양한 쟁점에 대해 기간제교원들이 생각하는 중요도 및 만족도를 분석하여 제도 개선을 위한 시사점을 도출하고자 하였다. 먼저 문헌분석에 기초하여9가지 쟁점(법적 지위, 고용의 안정성, 채용과정의 적절성, 계약조건의 합리성, 처우·복지, 업무분장, 소속감 및 자존감 제고, 전문성 개발 및 연수 기회, 교육활동 성과 관리 및 평가)에 관한 분석 범주를 도출하였고, 전국의 기간제교원을 대상으로 설문조사를 실시하였다. 전체 기간제교원의 1/3에 해당하는 14,592명의 유효한 응답 샘플을 분석한 결과, 기간제교원들은 성공적인 직무수행을 위해 모든 요소에 대 해 중요도를 높게 평가하는 반면에, 만족도 수준은 매우 낮은 것으로 나타났다. 특히 중요도-만족도 간차이가 크게 나타난 항목은 고용안정성이었으며, 이어서 처우·복지, 합리적인 업무분장 순이었다. 이들쟁점사항의 중요도와 만족도에서 개인특성 및 소속학교 유형에 따라 어떻게 다른지 분석한 결과, 성별, 연령, 기간제교원을 선택한 이유, 교직경력에 따라 유의한 차이가 나타났으며, 또한 학교유형과 학교급간에도 유의한 차이가 나타났다. 전반적으로 여성, 40대, 경제적 목적으로 기간제교원을 선택한 집단, 7~10년 경력자, 국공립학교 재직자, 중학교 교사의 중요도 인식이 다른 집단에 비해 높은 반면, 여성, 40대, 경제적 목적 집단, 7~10년 경력자, 사립학교 재직자, 고등학교 교사의 만족도가 가장 낮은 것으로 나타났다. 연구결과를 기초로 하여 제도 개선을 위한 시사점을 논의하였다.This study explores the perception of the fixed-term teachers on the operation of the fixed-term teacher system and investigates if these perceptions change depending on various personal and school characteristics. The study subjects were fixed-term teachers that had been employed in kindergartens, elementary, middle, and high school in July 2018. Data was collected using online surveys, and the amount of legitimate responses gathered comprised about 1/3 of the fixed-term teacher population. To summarize the results, the fixed-term teachers pointed out ‘the lack of employment stability as the most important aspect for their successful job performances. Secondly, when analyzing the differences as to gender, age, work experience, and reasons for choosing career, females, teachers in their 40s, teachers who chose to be a fixed-term teacher for financial reasons, and teachers who had 7-10 years of work experience were more cognizant of the fixed-term teacher policy and were less satisfied with the policy implementation than other corresponding groups. Thirdly, when analyzing the differences as to the type and level of school, on some aspects teachers working in public schools and middle school teachers were more cognizant of the fixed term teacher policy while private school and high school teachers were less satisfied with the policy implementation than other corresponding groups. Based on the results, implications for policy change were discussed.
HMMs and LSTMs for On-line Gesture Recognition on the Stylaero Board : Evaluating and Comparing Two Methods

In this thesis, methods of implementing an online gesture recognition system for the novel Stylaero Board device are investigated. Two methods are evaluated - one based on LSTMs and one based on HM ...
A Benchmark Dataset for RGB-D Sphere Based Calibration

Accurate calibration of an RGB-D camera couple is an important task in computer vision, especially applications requiring the knowledge of 3D information. Although a variety of algorithms have been proposed, it remains difficult to evaluate existing methods in the literature as different sequences are used. In this paper, we propose a full dataset benchmark, with real and synthetically generated sequences, manually determined ground truth, and evaluation metrics for comparison. Evaluation of three methods using this framework is also provided. The proposed benchmark dataset is available online at http://rfai.lifat.univ-tours.fr/PublicData/ calibrgbd/CalibRGBD.html.
Penerapan Data Mining Menggunakan Algoritma Apriori Pada Website Indie Clothing

Advances in information technology are always accompanied by ever-increasing information needs, and accompanied by a very rapid growth of internet users, this can increase business competitiveness so high that it requires intelligence in business or often called business intelligence to support future needs and predictions for a company. This study examines the application of business intelligence on a clothing website by implementing data mining and using the Apriori algorithm to find the rules or shopping patterns of customers. From the pattern obtained is used to make predictions of interest and product stock, after knowing the customer's interest to shop as well as products and promos, this can increase sales on the Clothing website. The results of this study indicate that the number of itemsset produced is a maximum of 3-itemset, mining results can also be used to estimate stock items and interests as well as promo or discount packages and can be a reference to determine the layout when an offline store will open . Keywords : Data Mining, Apriori Alghoritms, Sales, Business Intelligence
Elektron kitabxanalarda fərdi məlumatların təhlükəsizliyi məsələləri

Today selection of a Library Management System (LMS), that meets the needs of librarians and readers is one of the most important issues in the library and information environment.The article provides information on Alephino LMS applied in the Institute of Information Technology of ANAS.It is also analyzed organization of library work in high level and protection of the confidentiality of personal information in the LMS.
A SURVEY ON PREDICTION OF PRIORITY AND SEVERITY IN THE BUG REPORTS

Software usage has increased by leaps and bounds and it is being used in every sphere of human activity. Bugs in the software would make it ineffective or unstable. As per the statistics 57% of the bugs originate through human made errors. This in turn results in cost overruns, delayed timelines and higher maintenance costs. Detecting the bugs is very crucial at the initial phase as it affects both the quality and accuracy after its deployment. In order to report these kinds of bugs, a system termed “Bug Tracking System” (BTS) exists. While testing any software, BTS receives a huge number of bugs on a daily basis. If the triage (the one who uses his knowledge and experience to analyze and refine the reported bug) starts reading all the bugs then it is possible that many important bugs will remain untreated and it is also difficult for the triage to resolve the bugs within the available time and resources. Hence, Bug priority and severity is an inevitable process in the software maintenance. This paper emphasizes in necessitating a short and fleeting survey on numerous bug priority and severity techniques. We are reviewing and categorizing survey of 30 literature research works in the domain of bug priority severity.
SynSemClass 1.0

The SynSemClass synonym verb lexicon is a result of a project investigating semantic ‘equivalence’ of verb senses and their valency behavior in parallel Czech-English language resources, i.e., relating verb meanings with respect to contextually-based verb synonymy. The lexicon entries are linked to PDT-Vallex (http://hdl.handle.net/11858/00-097C-0000-0023-4338-F), EngVallex (http://hdl.handle.net/11858/00-097C-0000-0023-4337-2), CzEngVallex (http://hdl.handle.net/11234/1-1512), FrameNet (https://framenet.icsi.berkeley.edu/fndrupal/), VerbNet (http://verbs.colorado.edu/verbnet/index.html), PropBank (http://verbs.colorado.edu/%7Empalmer/projects/ace.html), Ontonotes (http://verbs.colorado.edu/html_groupings/), and English Wordnet (https://wordnet.princeton.edu/). Part of the dataset are files reflecting interannotator agreement.
Inventory management Android application

The application has been developed keeping in mind the use of a centralized inventory managing system that could be accessed by all the authorized users, allow them to put forth requests and update the database accordingly. The usability of the application ranges from event managing to basic log keeping in small to medium-sized storages.
The Effect of Applying Internet Browsing in Improving Students’ Reading Comprehension Skill

This research is conducted under the following purpose of study: (1). To find out whether the use of internet browsing can improve the students’ ability in comprehending written text. (2).To find out how effective is the use internet browsing in teaching reading. In doing this research, the writer used pre-experimental descriptive method with one group pre-test and post-test design. It was designed in terms of quantitative research. This method was done to measure students achievement in reading comprehension using internet browsing. The population of this research is the students of SMA Negeri 3 Tondano. The sample is taken from the first year students of SMA Negeri 3 Tondano which consist of eight classes. The sample is one class that consist of 29 students (X IPA 1).The result of the post-test = 2490, the mean score (X) = 85.86 and the standard deviation (s) = 10.44. The total scores of the pre-test = 1810, the mean score (X) = 62.41, and the standard deviation (s) = 14.05. Based on the result above, the increasing of the students’ achievement shows that their abilities in reading comprehension are increasing too. So, it can be concluded that using internet browsing in teaching reading comprehension is effective to increase students’ skill in reading comprehension. In teaching reading, planning is very essential. Since it can lead the teaching and learning activity, the lesson plan plays an important role in the success of teaching students the reading comprehension. English teachers are suggested to applying an appropriate technique in teaching reading comprehension in order to make the teaching and learning process more active and alive. In order to manage the class well, the number of the students have to be limited. Teachers have an important role in choosing the suitable technique to motivate the students in learning reading comprehension. It is hoped that the English teachers use internet browsing in teaching reading comprehension. This strategy is effective in stimulating the students to think critically.
Anchoring biases in estimations of age, weight and height

The main purpose of this thesis was to study the circumstances under which anchoring biases occur for estimation of age, weight and height. Paper I investigated accuracy and biases in age estimates ...
Pengembangan Buku Petunjuk Praktikum IPA Berbasis Learning Cycle Bagi Siswa Kelas IV Sekolah Dasar

The purpose of this study is to produce a science learning manual based on a learning cycle for grade IV students of valid, practical and effective elementary school. The test subjects in this research were grade IV students of SDN 131 / IV Jambi City. This research uses the type of Research and Development (research and development), adopts the ADDIE development model with stages of analysis, design, develop, implementation, and evaluation. The due diligence includes the level of validity and practicality. Data collection instruments in this research development are validity and practicality instruments. The data in this study are quantitative and qualitative data. Quantitative data in the form of the results of the validation of the science practical manual. Qualitative data in the form of teacher and student responses to the developed practical guide. This research resulted in a science learning manual based on a learning cycle with the validity of the material included in the valid category with an average of 3.41, the validity of the display included a very valid category with an average of 3.52. The practicality level of the teacher and student response questionnaire was included in the practical category with an average of 78.75%. Based on the results of the study it can be concluded that the development of science instruction manuals based on leraning cycles for grade IV elementary school students is in the valid and practical categories. From the results of this study it is hoped that the teacher can design a proaticum manual at another grade level.
Multimedia Compression Techniques for Streaming

With the growing popularity of streaming content, streaming platforms have emerged that offer content in resolutions of 4k, 2k, HD etc. Some regions of the world face a terrible network reception. Delivering content and a pleasant viewing experience to the users of such locations becomes a challenge. audio/video streaming at available network speeds is just not feasible for people at those locations. The only way is to reduce the data footprint of the concerned audio/video without compromising the quality. For this purpose, there exists algorithms and techniques that attempt to realize the same. Fortunately, the field of compression is an active one when it comes to content delivering. With a lot of algorithms in the play, which one actually delivers content while putting less strain on the users' network bandwidth? This paper carries out an extensive analysis of present popular algorithms to come to the conclusion of the best algorithm for streaming data. Both audio and video compression are put under scrutiny and are compared on various aspects prime to delivery of data.