Reviewerly/exHarmony huggingface dataset:
A Comparative Study of Different Solar Power Tracking Control Techniques

Solar tracking conventionally uses mathematical calculations to know the exact position of the sun. In an attempt to further increase yield efficiency, this paper looks at control techniques to achieve maximum power. Converting irradiation into electricity is the main function of a photovoltaic panel. Then, why not orientate the solar panel in a position where it can yield maximum power? In other words, this research tests the feasibility of building a ‘power tracker’ instead of a solar tracker. The two proposed algorithms are namely, Extremum Seeking Control and Perturb and Observe. Simulations were done on MATLAB/Simulink and a prototype was built for a comparative study of different tracking control techniques.
Towards a Statistical Approach for User Classification in Twitter

In this paper, we propose a novel technique for classifying user accounts on online social networks. The main purpose of our classification is to distinguish the patterns of users from those of organizations and individuals. The ability of distinguishing between the two account types is needed for developing recommendation engines, consumer products opinion mining tools, and information dissemination platforms. However, such a task is non-trivial. Classic and consolidated approaches of text mining use textual features from natural language processing for classification. Nevertheless, such approaches still have some drawbacks like the computational cost and time consumption. In this work, we propose a statistical approach based on post frequency, metadata of user profile, and popularity of posts so as to recognize the type of users without textual content. We performed a set of experiments over a twitter dataset and learn-based algorithms in classification task. Several supervised learning algorithms were tested. We achieved high f-measure results of 96.2% using imbalanced datasets and (GBRT), 1.9% were gains when we used imbalanced datasets with Synthetic Minority Oversampling technique and (RF), this yields 98.1%.
Survey on Classification and Segmentation for HDR Satellite Imagery

Now a day's the most interesting research area in field of Digital Image Processing is Remote sensing. Currently Remote sensing (RS) is being widely used technology which plays most important role in Image analysis. Remote Sensing (RS) generally refers to the use of satellite based sensor technologies respectively. However, the luminance of natural scene present over a large dynamic range. Thus, with a regular camera it becomes complicated to capture the details of an entire scene with good clarity in a single shot. To overcome this problem HDR (High Dynamic Range) imaging has been used. TMO (Tone Mapping Operator) is used to convert HDR image into LDR image which serves good quality of an image, so that we can visualize it over LDR display. Currently in the field of Image processing an image with big data becomes quite difficult to understand. To overcome this analysis problem there is need of image segmentation. Image segmentation is used to compress the data which will helpful to understand. Satellite imagery is one of the wide areas in segmentation and classification. There are various image segmentation techniques are there like edge, threshold, region, clustering and neural network segmentation method. This work focuses image segmentation towards ANN (Artificial Neural Network) because it has some advantages as compare to rest of methods. Image classification techniques like supervised and unsupervised learning discussed in this paper.
Bi-Directional Depth Propagation for 2D-to-3D Conversion with Color/Depth-Based Superpixel Segmentation

In this paper, we propose bi-directional depth propagation for 2D-to-3D conversion with color/depth-based superpixel segmentation. Depth propagation generates the depth image of the query frame based on motion information between two sequential frames. However, color-based superpixel segmentation causes segmentation errors due to weak edge and analogous colors, thus resulting in motion estimation errors. We provide color/depth-based superpixel segmentation for accurate motion estimation instead of the color-based superpixel segmentation. Experimental results show that the proposed method successfully estimates motion vectors for depth propagation and outperforms state-of-the-arts with comparable time cost in terms of PSNR.
9. Usage-based Grammar

This article introduces two major approaches to usage-based study of syntax, Emergent Grammar and Interactional Linguistics. Grammarians studying human languages from these two approaches insist on basing their analyses on data from actual language use, especially everyday conversation in a range of languages. Grammar is viewed as emerging from language use in context, and thus grammatical structure is seen as provisional, negotiable, and ever changing. Linguistic units and categories need to be based on what is found in actual use. Traditional notions are not accepted a priori, unless it is shown that speakers actually orient to them in their everyday use. Findings are stated in terms of both form and function. Since the availability of videotaped data, there has been increasing attention paid to embodied behavior as a component of linguistic communication. Frequently used structures are seen as more basic than rarely used ones, and for this reason, quantitative approaches are common. Building carefully designed, balanced corpora of everyday speech in a range of contexts for multiple languages will be a next major step which would make this usage-based endeavor to human language a viable option.
Repeated Multi-Qubit Readout and Feedback in a Mixed-Species Trapped-Ion Registere

We measure the parity of two 9Be+ion qubits by mapping the relevant operator onto an ancillary 40Ca+qubit, utilizing multi-species entangling gates. Repeated measurement and feedback cycles allow preparation and stabilization of parity subspaces and Bell states. © 2019 The Author(s)
Informação como prova ou monumento: materialidade, institucionalidade e representação

This paper concerns materiality, institutionality and representation modes as aspects comprising information as “proof” or “monument”. It criticizes the power/knowledge relation in practices involving probation contexts in retrieval and storage systems (e.g. the archive), as well as in various knowledge fields. We present the following hypothesis: while the objective or physical dimension of information prioritizes pretensions of representation of reality (emphasis on the probation/authenticity value), the social dimension criticizes pragmatic and symbolic aspects comprised and comprising in discourses about reality (found in the value of monumentality). Our aim is to analyze information as proof or monument from an interdisciplinary perspective, facing various forms of knowledge in Information Science, as well as documental, judiciary, historiographical, archival and diplomatic perspectives, which find in the document their theoretical, methodological, and operational subsidies. We indicate the transformation of materialized “evidence” in an institutionalized “thing” amidst the “proof” assumes: a) subjects with some authority; b) a document bringing together epistemological and political dimensions summarized in their permanent and material (support) condition, and its ephemeral and immaterial (pragmatic and symbolic) condition. As a result, we explore and exemplify epistemological and political implications of representation modes facing the statements: a) “the document, if authentic, leads to the truth”, guiding “information as proof” towards the representation of social reality; and b) “every document is a monument””, guiding the “information as monument” towards legitimizing discourses about reality.
Αυτοκινούμενο όχημα εύρεσης βέλτιστης διαδρομής λαβυρίνθου

The theme of our dissertation is to solve a labyrinth with the optimal (faster) route using a robotic car that is programmed based on the Arduino microcontroller.
Development principles for electronic knowledgebase on ship design

This paper presents development principles and test version of electronic knowledgebase on ship design. The results of this work will enable active use of this knowledgebase, thus contributing to its further improvement.
The Semantic Properties of the Base Verbs in English Deverbal Nominals

The purpose of this study is to explore the semantic properties of the base verbs in English deverbal nominals. The meanings of the deverbal nominals can be classified into an event, a result and both. An event interpretation simply transposes the verbal meaning, and a result interpretation refers to a result or outcome of an event. In this research, it is assumed that a certain class of verbs, which are particularly the base verbs of the deverbal nominals, yields the event and result interpretation in their deverbal nominals, therefore, identifying the semantic similarities of these deverbal nominals. Data sources are extracted from the British National Corpus. Levin’s English Verbs Classes are used for data analysis. The findings showed that the base verbs which hold both an event and a result interpretation, and which hold a result interpretation in their deverbal nominals are related to the change of entity, specifically the change of attribute. Meanwhile, the base verbs which hold an event interpretation are related to the attribute or property of the entity.
Segregation Network for Multi-Class Novelty Detection

Multi-class novelty detection is increasingly becoming an important area of research due to the continuous increase in the number of object categories. It tries to answer the pertinent question: given a test sample, should we even try to classify it? We propose a novel solution using the concept of mixup technique for novelty detection, termed as Segregation Network. During training, a pair of examples are selected from the training data and an interpolated data point using their convex combination is constructed. We develop a suitable loss function to train our model to predict its constituent classes. During testing, each input query is combined with the known class prototypes to generate mixed samples which are then passed through the trained network. Our model which is trained to reveal the constituent classes can then be used to determine whether the sample is novel or not. The intuition is that if a query comes from a known class and is mixed with the set of known class prototypes, then the prediction of the trained model for the correct class should be high. In contrast, for a query from a novel class, the predictions for all the known classes should be low. The proposed model is trained using only the available known class data and does not need access to any auxiliary dataset or attributes. Extensive experiments on two benchmark datasets, namely Caltech 256 and Stanford Dogs and comparisons with the state-of-the-art algorithms justifies the usefulness of our approach.
Non-Gaussian Continuous-Variable Graph States

Mode-tunable photon subtraction is a viable method to introduce non-Gaussian features in continuous-variable graph states. Non-Gaussian properties are shown to spread up to next-to-nearest neighbours of the graphs vertex in which the photon was subtracted. © 2019 The Author(s)
Reinforcement Learning and Blockchain to secure the Internet of Things

Securing the IoT world in not a luxury task; it is even a matter of urgency given this exponential growth of IoT market. In fact, one can easily imagine the catastrophic damages of an attack in the field of e-Health or in the smart cities and critical infrastructures management. That being said, serious problems derived from these constrained environments block the proposal of pertinent solutions. This paper is a contribution step in this direction. To address these problems, we expose a global framework inspired from the concept of emergence in order to take advantage of this large number of devices and extract the emergent characteristics that are nonexistent in smaller systems. The framework is built on top of two pillars: Blockchain as architecture and Reinforcement Learning as processing toolkit.
Replying to Tickets

A common requirement of an application is to provide a user with the ability to input longer portions of text. Unfortunately, in many cases, a standard HTML text area will not meet that requirement, as richer functionality is needed. Even a simple line break will mean looking elsewhere for a richer text editor.
Optimizing the Grade Classification Model of Mineralized Zones Using a Learning Method Based on Harmony Search Algorithm

The classification of mineralized areas into different groups based on mineral grade and prospectivity is a practical problem in the area of optimal risk, time, and cost management of exploration projects. The purpose of this paper was to present a new approach for optimizing the grade classification model of an orebody. That is to say, through hybridizing machine learning with a metaheuristic algorithm called Harmony Search (HS), a proper model for the spatial distribution of the grade classes was obtained, while improving the computational cost of the traditional classification methods. The HS is an algorithm inspired by the simulation of the process where a composer tries to harmonize a piece of music. By interpolating the dataset of Cu and Mo concentrations in the surface rock samples taken from Kooh-Panj deposit district, the grid data of the two elements were extracted. To estimate the true number of groups in the dataset, five popular indices were used in this regard, which in turn determined two classes as the optimal number of groups. Harmony Search Learning (HSL) was used to classify the grid dataset of Cu and Mo. The comparison of the results of the proposed approach with the conventional k-means clustering suggested that the use of HSL method significantly reduced the cost function of the problem (up to 13%). The adaptation of the mineralization class derived from HSL and k-means clustering to borehole locations proved that the results of the HSL were more successful in the accurate estimation of the economic mineralization class identified by the exploratory excavations. In this respect, the HSL technique could significantly improve the k-means performance by 25%. Furthermore, the results of the HSL were more consistent with the lithological units and alteration zones involved in the ore-forming processes. The use of the HS-based learning rectified the disadvantages arising from the typical clustering methods regarding the entrapment in local optimums. It also led to the extraction of weak mineralization signals, numerically laid in boundary conditions. This approach can be extended to more than two geochemical variables and can be a valuable tool for the classification of the mineralized areas to design and optimally manage the mineral exploration projects.
Aplikasi Tambal Ban Kota Surakarta Berbasis Mobile Android

The high use of motor vehicle disurakarta not least found leaking tires while driving. The condition is certainly not intended by the riders doing so due to the difficulty in finding a clamp tire where not every place there and provide clamp tires. Hence the need for an application which can make it easier to find help in the community ter clamp close so that helps its users in menghewat time and effort to acquire the services of the nearest tire clamp. Applications that want to be developed by the researchers is the Clamp the tire city of Surakarta the application in design with the use of the tegnologi in LBS degradasikan with google map. Based on the results of tests conducted by researchers in the trial of a black box as young as seuai with the expectation of success running the study. based on the results of a test questionnaire consisting of 30 respondents shows average percentage reaching 86.7%. With the completion of the application Clamp the tire city of Surakarta is expected to help the users of those applications in looking for info or help clamp tires on site around.
Scientists unlock the secrets of a natural petri dish rainbow effect

We’re surrounded by iridescence. It graces butterfly wings, adorns certain minerals, and shines bright from the water droplets on a petri dish lid. When researchers at Pennsylvania State University and the Massachusetts Institute of Technology spotted iridescence in the two-component oil droplets they were studying (shown), though, they weren’t sure where it was coming from. When they investigated, they found that light entering the droplets bounces repeatedly off the curved interface between the two types of oils making up the droplet, a phenomenon called total internal reflection (Nature 2019, DOI: 10.1038/s41586-019-0946-4). The researchers can control how the light bounces by tuning the curvature of that interface with surfactants. They developed a mode l to describe the technique and hope it could one day be used to create vibrant color-shifting inks and displays. Learn more at cenm.ag/iridescence
TEACHER’S SELF-DEVELOPMENT: TEACHER’S SELF-DISCOVERIES REGARDING THE SIGNIFICANCE OF PEDAGOGICAL PERSONALITY DEVELOPMENT DURING PEDAGOGICAL PRACTICE

In the 21st century, a special place in education is occupied by sustainable development issues, which emphasize the unique role of education in shaping the public opinion. New pedagogical approaches, which show how education could contribute to the evolution of consciousness, are being sought. A shift of paradigms is happening in education: from knowledge memorization to skills, character, meta-learning (Education 2030: Organisation for Economic Cooperation and Development competency framework). The research confirms, to successfully implement the proposed changes in modern pedagogical practice, it is valuable for the teachers to learn the psychology methods and techniques on how to improve and advance personality growth based on the knowledge shared by K.G. Jung, K. Wilber, and A. Maslow. research confirms it is valuable to acquire these methods during theoretical and practical activities for professional development.The study revealed that teacher’s professional competencies, such as communicative, methodological, organizational, creative skills and self-management, improve through familiarization and practical application of this knowledge.The aim of the study is to show the importance of how the psychological insights regarding the development of personality impact the pedagogical practice. Main tasks include literature studies and evaluation, working with a target audience. Research methods: survey.
Understand SQL Performance with Algorithm Analysis

Solving Oracle SQL performance issues is the pinnacle of SQL development. Performance tuning requires a combination of all the skills previously discussed in this book. We need to understand the development process (to know why problems happened and weren’t caught sooner), advanced features (to find alternative ways to implement code), and programming styles (in order to understand the code and rewrite it into something better).
사회통합교육을 위한 이민자 대상 한국어 교재의 개발 방향 연구 - 호주의 AMEP 사례를 중심으로 -

This study explored how the Korea Immigration and Integration Program (KIIP) might better develop its textbooks for immigrants to conform to the paradigm of the immigration policy of encouraging social integration, using the textbooks of the Australian Adult Migrant English Program (AMEP) as examples and a case study of language education programs for immigrants. Our analysis of AMEP textbooks found educational content in four integrated areas: society, culture, economics, and politics. The textbooks’ social education included content such as social activities necessary in private and public areas; food, clothing, and shelter (the necessities of life); public welfare and convenience facilities; leisure and travel; health and medical care; electricity; transportation; communication media; and security. The cultural education included on geography, climate, history, art, religion, marriage, four ceremonial occasions (coming of age, weddings, funerals, and ancestral rites), and national and regional symbols. Education on the economy included content on currency transactions, consumption activities, job searches, jobs, and job performance based on mathematical ability. Finally, education on politics included content on agencies and activities at the legal, national, and community level.
Need to REFUTE and REMOVE Fake Islamic 'Human Embryology' Teachings

Given these deadly and other unknown consequences resulting from and justified by the monumentally fake Islamic human embryology that has been and continues to be published, such fake science teachings should at least be removed from the NIH and other governmental and university educational websites or at least simultaneously refuted (as below).
Development of a Library of Intelligent Agents for VR Applications

Development of a library of intelligent agents for a Virtual Reality application aimed for psychiatric/medical therapists and aid them in studying and eventually treating patients with anxiety disorders. The simulation takes place in a supermarket/grocery store, a typical environment which may cause anxiety and/or fear for patients to be in. The focus of this thesis' work is to create and manage non-human actors: store clients and workers, with special attention on realistic behaviours and animations. Also, because this is part of an ongoing larger project, special attention must be placed on the project's modularity so that it can be easily integrated and/or expanded upon.
Use SQL More Often with Basic Dynamic SQL

Dynamic SQL is a powerful tool that helps us get the most out of Oracle SQL. With dynamic SQL we can build our code at run time. Writing code in code is challenging but offers many opportunities.
Optical Information Processing with Noise-Resistant Entangled Topological States

Linear-optical photonic quantum walks are used to jointly entangle polarization and winding number. This joint entanglement allows polarization entanglement-based quantum information processing tasks to be performed with high degree or error protection. © 2019 The Author(s)
MINAT DAN MOTIVASI PESERTA DIDIK KELAS X ELIND DALAM PEMBELAJARAN BAHASA INDONESIA DI SMK PUSDIKHUBAD CIMAHI

There are many assumptions that the interests and motivations of students can have a big influence on the process of learning Indonesian. Interest is a beginning of the process for students when trying to get knowledge that can be used for their intended interests and goals. While motivation is an insistence on yourself to carry out an activity to reach the goal. The purpose of this study is to see the desires and efforts of students while studying. Researchers use descriptive qualitative research methods and interview techniques. Evidence from this study states that the wishes and efforts of students while carrying out the learning process are still very lacking, because in Indonesian language material, the text is used so much especially with the added lack of students' desire to carry out minimal reading activities. That way, the learning process is not only focused on students but on skills when the teacher conveys learning, so that learning activities are not monotonous and are able to focus students' focus so that they are encouraged when their learning in Indonesian takes place. This can be concluded even though Indonesian is a lesson that must be learned in each school but it is possible that there are still students who are less interested and motivated in the main lesson, namely Indonesian.