Reviewerly/exHarmony huggingface dataset:
Development of SEL-based STEAM programs using Mechanical Engineering Principle of AUTOMATA

이 연구의 목적은 오토마타의 기계공학적 원리를 활용한 SEL(Social and Emotional Learning, 사회정서학습) 기반 융합인재교육 프로그램을 개발하고 이를 적용하여 현장 적합성을 확인하는데 있다. 이를 위하여 준비, 개발, 개선의 단계에 따라 오토마타의 기계공학적 원리를 활용한 SEL 기반 융합인재교육 프로그램을 개발하고 이를 전문가의 내용 검토와 학생 평가 결과를 바탕으로 수정, 보완하였다. 이 연구를 통해 개발된 융합인재교육 프로그램의 특징은 다음과 같다. 첫째, 개발된 융합인재교육 프로그램은 SEL을 기반으로 한 것으로 2015 개정 교육과정에 기초한 것이다. 둘？？, 개발된 융합인재교육 프로그램은 중, 고등 차시대체형 4종, 중학교 자유학기 2종 총 6개의 프로그램이며 20차시의 프로그램으로 구성되었다. 셋째, 개발된 융합인재교육 프로그램은 오토마타의 기계공학적원리를 기반으로 하여 ‘가족’, ‘과학기술의 영향’, ‘안전’, ‘독서’, ‘생태계’, ‘나’를 주제로 융합되었으며 상황제시, 창의적설계, 감성적체험의 단계에 따라 오토마타의 기계공학적원리를 활용한 교수, 학습 활동이 이루어졌다. 넷째, 개발된 융합인재교육 프로그램은 교사용 교재와 학생용 교재로 구분되었으며 다양한 읽을거리, 활동 예시, QR코드가 포함된 참고자료 등 구체적인 자료로 구성되어 현장 활용도를 높였다. 이 연구를 통하여 개발된 융합인재교육 프로그램은 오토마타의 기계공학적 원리를 이해하는 동시에 사회적으로 충분한 공감능력을 갖출 수 있도록 구성되었으며 이를 통해 인문과 기술이 자연스럽게 융합된 미래 지향적 창의 인재 양성에 기여할 것으로 기대된다.The purpose of this study is to develop a SEL(Social and Emotional Learning)-based STEAM program that utilizes the mechanical engineering principle of automata; it further aims to apply these principles to verify field suitability. For this study, a SEL-based STEAM program was developed using mechanistic principles of automata according to preparation, development, and improvement stages, and revised and supplemented based on the contents of expert review and students’ evaluations. The characteristics of the STEM program developed through this study are as follows. First, the developed STEAM program is based on SEL as well as on the 2015 revised curriculum. Second, the developed STEAM curriculum comprises a total of six programs, and consists of four programs that can be substituted for classes at the middle and high schools and two programs for free semester classes at the middle schools. Third, the developed STEAM program is based on the mechanical engineering principles of “automata,” converging on “family,” “the influence of technology,” “safety,” “reading,” and “ecosystems.” Based on the creative design and the stage of students’ emotional experiences, teaching and learning activities are carried out using the mechanistic principles of automata. Fourth, the developed STEAM program is divided into teachers’ textbooks and students’ textbooks, and it is composed of specific materials such as various readings, activity examples, and reference materials, including QR codes, thus enhancing the utilization of the field. The STEAM program developed through this study was structured to help students to develop adequate social and empathic ability by utilizing the mechanical engineering principles of Automata. Through this program, it is expected to contribute to fostering creative people whose humanities and technology are naturally convergence.
Using Implicit Job Seeker Preferences to Improve Job Recommendation Ranking

This thesis focuses on the field of Job Recommendation. Particularly, we focus on using implicit preferences exhibited by the job seeker in interactions with a web platform to propose an improved ranking algorithm for a job recommendation platform called Magnet.me. We also study evaluation of relevance, and evaluation of recommendation sorting algorithms to determine the degree of improvement achieved by the proposed algorithm. Using NDCG with different relevance evaluations, we test performance of the proposed algorithm in an online experiment on the job recommendation platform. We find that the evaluation of relevance strongly affects the distinguishability of NDCG. The evaluation shows that our sorting algorthm outperforms the original algorithm when using classical binary relevance, or relevance evaluations that consider items with negative feedback less relevant than items with missing feedback. However, when using relevance evaluations for NDCG that punish missing feedback more than negative feedback, NDCG loses its capability of distinguishing between algorithm performance. Based on baseline sorting algorithm evaluation MRR and the different evaluations using NDCG, we conclude that the proposed recommendation sorting algorithm outperforms the original algorithm.
Media Pembelajaran Computational Thinking Melalui Permainan Digital

Computational Thinking is the ability to solve complex and effective problems containing four main CT material, namely abstraction, decomposition, patterns and algorithms that must be mastered in order to prepare themselves for existing developments, especially in the world of Education, especially the elementary school level. However, based on observations made on the ground, the development of CT has not been well known. This study aims to make CT learning media through digital games, containing explanations of material equipped with digital games that are able to introduce computational thinking in solving problems with the best solutions for students. The research method used is Research and Development with the ADDIE development model (Analysis, Design, Development, Implementation and Evaluation). The subjects of this study were students of grade IV and V of Al-Azhar Elementary School Syifa Budi Solo. Data collection techniques in this study are by observation, questionnaire, Pre test and Post test. The data analysis technique used is calculating the percentage of feasibility from the results of the questionnaire. The result is the use of CT learning media able to improve students' understanding of CT in problem solving.
LibGuides: MATH 6001 Seminal and Current Research in Mathematics Education with Emphasis on Grades 11-14: Course Readings and Suggested Resources

Strategies, tips and links to locate and gather resources for your research projects and course assignments. Links to online resources
Proposal of Replacing Classical Logic with Free Logic for Reasoning with Non-Referring Names in Ordinary Discourse

Reasoning carried out in ordinary language, can not avoid using non-referring names if occasion arises. Semantics of classical logic does not fit well for dealing with sentences with non-referring names of the language. The principle of bivalence does not allow any third truth-value, it does not allow truth-value gap also. The outcome is an ad hoc stipulation that no names should be referentless. The aim of this paper is to evaluate how far free logic with supervaluational semantics is appropriate for dealing with the problems of non-referring names used in sentences of ordinary language, at the cost of validity of some of the classical logical theses/ principles.
Performance assessment of interferometric sensing

We present a review of recent progress in quantitative performance assessment of optical interferometry. Specifically, a three-level framework is introduced for evaluating the sensitivity of optical pathlength measurement. Its application is demonstrated for whitelight interferometry and wavelength shifting interferometry. It shows that there is a performance gap, potentially significant, between currently achieved measurement sensitivity and the sensitivity limit of the system. The framework allows one to accurately assess hardware performance, identify sources of degradation, and devise optimization strategy. It may offer guidance to lower sensor cost and improve commercial competitiveness.
FFT Neural Network to Estimate Some Asymmetric Dynamical Maps

The estimation some asymmetric dynamical maps by selecting an appropriate feed forward artificial neural network, transfer function and node weights, is the aim of our paper. Fast Fourier Transform (FFT) as transfer function is used. By means of the mean square error (MSE), the experimental results of proposed algorithm will compared empirically, with the results of the same network but with traditional transfer functions, Logsig and Tagsig. Different cases of the dynamical systems, Asymmetric Logistic, Asymmetric Logistic -Tent and Asymmetric Tent-Logistic are discussed. The performance of proposed algorithm is best from others in all cases from Both sides, speed and accuracy.
Research Guides: Hawaiian Language: Start Here

This research guide provides links to resources available online and through the UHMC Library. This is a living guide - meaning if you know of other resources that should be added, please do contact us so we can continue to build this research guide.
ACCURACY OF ARTIFICAL INTELLIGENCE BASED DECISION SUPPORT SYSTEM COMBINED WITH BASIC CLASSIFICATION IN COLON POLYP DETERMINATION

All colon polyps have to be removed for histological analysis due to regulatory reasons, causing real health care burden. Virtual-chromoendoscopy only in expert hands may be used for real-time diagnosis of polyp characteristics to support resect and discard strategy. In our present study, we aimed to develop an Artificial Intelligence-based Decision Support System (AI-DSS) that can assist the decision of endoscopist in the real-time determination of sub-centimetric polyp's histology with high accuracy.
Limitations of routing-by-agreement based capsule networks.

Classical neural networks add a bias term to the sum of all weighted inputs. For capsule networks, the routing-by-agreement algorithm, which is commonly used to route vectors from lower level capsules to upper level capsules, calculates activations without a bias term. In this paper we show that such a term is also necessary for routing-by-agreement. We will proof that for every input there exists a symmetric input that cannot be distinguished correctly by capsules without a bias term. We show that this limitation impacts the training of deeper capsule networks negatively and that adding a bias term allows for the training of deeper capsule networks. An alternative to a bias is also presented in this paper. This novel method does not introduce additional parameters and is directly encoded in the activation vector of capsules.
Investigating reading culture among students in higher learning institutions in Tanzania

This paper presents findings of a survey conducted in some selected higher education learning institutions in Tanzania to determine the reading patterns of students when they undertake extracurricular activities.. The purpose was to ascertain whether students utilize their time in reading various informational materials for purposes other than academic activities. Electronic questionnaires were conveniently distributed to students at DUCE, IDRP Dodoma, Law School of Tanzania, RUCU Iringa, SLADS Bagamoyo, SUA Morogoro, SUZA, Tumaini University (DSM campus), UDSM and Zanzibar University. The study findings indicate that students spend their spare time reading print and e-newspapers, books and magazines, and access social media that cover aspects such as sports, economic, technological and social issues. They are motivated to read by their desire to learn new aspects of life, expanding their vocabularies, improving reading skills, and acquiring new information. The findings also indicate that students spend their time watching TV, talking to friends, listening to radio, playingand watching games. Furthermore, it was revealed that too much academic work, limited internet connection and family responsibilities are among factors that inhibit their reading habits. The study recommends that academic libraries should work out means to create conducive reading environment for students by stocking more reading resources, conduct more outreachprograms to attract more readers, create reading and writing clubs at schools to empower students in education at large and launch TVprograms which will attract more students to read and learn when undertaking extracurricular activities
Integration of Text-maps in Convolutional Neural Networks for Region Detection among Different Textual Categories.

In this work, we propose a new technique that combines appearance and text in a Convolutional Neural Network (CNN), with the aim of detecting regions of different textual categories. We define a novel visual representation of the semantic meaning of text that allows a seamless integration in a standard CNN architecture. This representation, referred to as text-map, is integrated with the actual image to provide a much richer input to the network. Text-maps are colored with different intensities depending on the relevance of the words recognized over the image. Concretely, these words are previously extracted using Optical Character Recognition (OCR) and they are colored according to the probability of belonging to a textual category of interest. In this sense, this solution is especially relevant in the context of item coding for supermarket products, where different types of textual categories must be identified, such as ingredients or nutritional facts. We evaluated our solution in the proprietary item coding dataset of Nielsen Brandbank, which contains more than 10,000 images for train and 2,000 images for test. The reported results demonstrate that our approach focused on visual and textual data outperforms state-of-the-art algorithms only based on appearance, such as standard Faster R-CNN. These enhancements are reflected in precision and recall, which are improved in 42 and 33 points respectively.
Embeddings and Representation Learning for Structured Data

Performing machine learning on structured data is complicated by the fact that such data does not have vectorial form. Therefore, multiple approaches have emerged to construct vectorial representations of structured data, from kernel and distance approaches to recurrent, recursive, and convolutional neural networks. Recent years have seen heightened attention in this demanding field of research and several new approaches have emerged, such as metric learning on structured data, graph convolutional neural networks, and recurrent decoder networks for structured data. In this contribution, we provide an high-level overview of the state-of-the-art in representation learning and embeddings for structured data across a wide range of machine learning fields.
Analytic versus Synthetic Understanding

It is argued that understanding is an epistemically more important concept than explanation. Two kinds of understanding are discussed, that based on analysis of the explanandum and a kind that is based on a synthetic method. The distinction between primary and secondary understanding shows that who is asking the why question is of central importance. A problem for causation is introduced that revolves around the degree of isolation that is needed to identify a causal factor and to distinguish causes from their carriers. It is shown that the analytic and synthetic approach can deal with partial understanding, that there can be an increase in understanding without an explanation, and that laws are not necessary for understanding.
SISTEM INFORMASI PENERIMAAN KARYAWAN BERBASIS WEB PADA PT. SINAR SOSROTANGERANG

Human resources is a very important factor in supporting the company's performance. Recruitment system that is conventional, which is part of the admin to manually choose a job application file to be recorded, less efficient and time-consuming and prone to errors. The systems in data processing applicants still used by admin of PT. Sinar Sosro. Information systems are made is a web-based information system that provides ease of data processing applicants by the personnel themselves as applicants to fill the data itself directly online. By using the Information System Web-Based Employee Recruitment is expected to assist the Human Resources Department PT. Sosro Sinar for data processing applicants, and the applicants can access job information and apply online
THE CREATION OF PATTERN OF MAIN CHARACTERS OF WAYANG BEBER FOR DESIGNING OF THE ICONOF PACITAN AS CITY OF TOURISM

Wayang beber is both of a of fine artwork and wayang /puppet show art. In this paper wayang beber is discussed from the point of view of art or craft art in making patterns as designs or references for the realization of works of art with several techniques to adjust the main ingredients. Wayang beber as the original traditional art of Pacitan which contains local wisdom that needs to be conservation efforts, research, creation and innovation.This effort is being done to make  wayang beber is suitable to be used as a source of ideas in the creation of the icon or logo of the Pacitan as a city of tourism. The process of creating this work through stages: problem identification, planning, drawing design, testing and implementation. The results of this drafting were aimed at improving, preserving Pacitan Wayang Beber , which is useful and widely known to the public. This paper is a part of the description of this Art Creation Research with the theme of design or design of tourist icons, through relief designs and sculptures, monument designs / monuments, city garden decoration works, with ideas of form, main characters, ornaments, arrangement patterns, stories and meanings Original Pacitan Wayang Beber. This description describes a part of the creation process in choosing the wayang beber scene, determining the main character, refining the shape and costume of the chosen figure to create a creative, innovative and meaningful Pacitan City Tourism Icon design. The relief works will be made using brass or copper plates. Ikon Pacitan's work can be done for the interior but is more appropriate for the exterior. Based on the identification of the selected wayang beber, the main characters of wayang beber Pacitan namely Dewi Sekartaji, Raden Panji, Naladerma and Tawangalun , were also found ornaments of various motifs of plants typical of Pacitan Wayang Beber . This main character is used as the main subject in the tourist icon design. The Pacitan City Tourism icon / logo is a new creation of wayang Beber combined with the form of gunungan wayang kulit and supplementary decorative motifs. The pattern resulted, is a relief. It was made of brass plate with carving technique and decorated with the technique of sunggingan or coloring by acrylic paint.
Conscious Competence as a New Teacher Educator

The presentation is targeted at new starters in the world of Higher Education, particularly Teacher Education. After being in post for a just over a year, I will provide a personal and reflective account of my journey along the way as a NTE.
Proposed Neural Network with FFT Transfer Function to Estimate Loranz Dynamical Map

The aim of this paper is to design a feed forward artificial neural network (Ann) to estimate three dimensional Loranz dynamical map by selecting an appropriate network, transfer function and node weights to get Loranz dynamical map estimation. The proposed network side by side with using Fast Fourier Transform (FFT) as transfer function is used. For different cases of the system, Deterministic, chaotic and noisy, the experimental results of proposed algorithm will compared empirically, by means of the mean square error (MSE) with the results of the same network but with traditional transfer functions, Logsig and Tagsig. The performance of proposed algorithm is best from others in all cases from Both sides, speed and accuracy.
Improving solar data in CIBSE climate files – Survey of measuring networks and test on daylight simulation

This paper investigates the influence of solar radiation models on Climate-BasedDaylight Modelling (CBDM) evaluations. The solar radiation model currentlyimplemented in CIBSE files is compared with high-accuracy reference data, and anew approach based on measured data and separation models is proposed. Anin-depth survey of solar radiation data currently available for British locations is alsopresented. The analysis on solar radiation data and models showed that the currentclimate files under-estimate all irradiance components, whereas a combination of MetOffice data and the Skartveit separation model can drastically improve irradianceestimates. The use of this improved model to derive irradiance values led to asignificant improvement in the reliability of CBDM results as well.
Analisis Nilai Lahan dan Harga Lahan Kecamatan Colomadu Kabupaten Karanganyar Menggunakan Penginderaan Jauh dan Aplikasi SIG

Population density increases every year in Colomadu Sub district, it affect on population need of land it also caused significant increase land value and land price, additional factor such as regional development from economy, facilities, accessibility and other aspects so that the attractiveness of the region becomes higher. Research method using survey method with stratified sampling and purposive sampling, stratified sampling is used for land prices in every class of land values, and purposive sampling is used for image digitizing validation. The method of analysis is using quantitative overlay method by using 4 parameters as well as landuse, positive accessibility, negative accessibility, public utilities. The results of research are land values distribution map divided into 3 classes, land prices distribution and suitability between land values and land prices. High land value is about 6,663 km2 or with percentage 43,03 %; medium land value is about 2,276 km2 or 14,56 %; and low land value is 6,729 km2or 43,03 %. High class land prices is about Rp 5.651.000,00 – Rp 10.000.000,00 ; medium class land prices Rp 2.551.000,00 – Rp 5.650.000,00 and low class land prices is about Rp 500.000,00 – Rp 2.550.000,00. The suitability area between land values and land prices is 10,038 km2 or 64,18 % and the unsuitability area is 5,602 km2 or 35,82 %. The most influential factor in high class land value and medium class land value is land use, while the factor for low class land value is negative accessibility.Keywords : Land Value, Geographic Information System, Remote Sensing, The Most Influential Factors.
Towards a maritime model for cyber-hybrid operations (Conference Presentation)

Presenting, in near real time, a common operating picture (COP) for cyber-hybrid operations (operations that combine cyberspace and real world actors) is a significant problem. Part of this problem is a data association issue that arises from the challenges associated with accurately correlating data related to cyber-physical and purely electronic activities and presenting them in a format that can be easily and quickly understood. While models exist for real world activities, similar models do not exist for correlating them with cyber actors and actions, making this a particularly difficult data organization problem. In particular, there is a notable lack of a unifying cyber-physical conflict model that describes how actors, actions, and artifacts interact to produce cyber-effects. This paper presents a maritime cyber model to address the multi-domain battle (MDB) data organization problem. The model extends Corbitt’s maritime conflict model into the cyberspace and information warfare domains. Cobbitt’s original model considered how commerce and information flowed across the primary media of his day, the sea, and the impact of certain maritime activities on both civilian life and military readiness and activities. The model presented in this paper describes and organizes cyber actors, actions, conflicts, and effects into a simplified framework. Mixed-methods research approaches are used to inductively construct the maritime cyber model using data from recent cyber-physical events. The maritime cyber model also clarifies MDB challenge understanding. We close the paper with examples of how the maritime cyber model can be used to address traditional COP MDB system design challenges.
이층위 신경망 모형을 사용한 포먼트 궤적 기반 모음 유형 분류

The aim of this paper is to classify vowel types attested in the TIMIT corpus of American English using a two-layer neural net with the input feature...