Reviewerly/exHarmony huggingface dataset:
Penerapan Model Problem Based Learning dengan Media Rak Telur Rainbow untuk Meningkatkan Hasil Belajar Matematika pada Siswa Kelas II SDN Ajung 02 Jember (Semester II Tahun Pelajaran 2017-2018)

Abstrak: Masalah penelitian ini adalah hasil belajar matematika siswa kelas II SDN Ajung 02 masih rendah, terbukti dari 22 siswa presentasi ketuntasan belajar siswa sebesar 27% dengan rata-rata 59,77 padahal kelas dinyatakan tuntas jika memperoleh 85%. Respon dan aktivitas belajar siswa juga masih rendah terbukti dengan kurang aktifnya siswa saat pembelajaran. Maka peneliti menerapkan model Problem Based Learning (PBL) dengan media rak telur rainbow. Penelitian dilaksanakan di kelas II SDN Ajung 02 Kecamatan Ajung Kabupaten Jember Provinsi Jawa Timur dengan jenis penelitian yang digunakan adalah Penelitian Tindakan Kelas (PTK) dengan 3 siklus yang setiap siklus terdiri dari tahapan perencanaan, pelaksanaan, observasi dan refleksi. Teknik pengumpulan data yang digunakan adalah observasi, tes hasil belajar dan angket pada setiap akhir siklusnya, alat pengumpulan data dilakukan dengan menggunakan lembar panduan observasi, soal-soal tes dan angket. Terbukti pada siklus I persentase hasil belajar siswa 46%, siklus II 68% dan pada siklus III menjadi 86%. Dan persentase hasil aktivitas belajar pada siklus I sebesar 67%, siklus II sebesar 75%, siklus III sebesar 86,5 serta hasil respon siswa pada siklus I sebesar 56,6%, siklus II sebesar 66,67%, dan siklus III sebesar 71,6%.Kata Kunci: Problem Based Learning, Media Rak Telur Rainbow, Hasil BelajarAbstract: The problem of this study is that the mathematics learning outcomes of class II students at SDN Ajung 02 are still low, as evidenced by the 22 students who presented their learning completeness by 27% with an average of 59.77 even though the class was declared complete if it received 85%. The response and learning activities of students are also still low as evidenced by the lack of active students during learning. So the researcher applied the Problem Based Learning (PBL) model with rainbow egg rack media. The research was conducted in class II SDN Ajung 02 Ajung Subdistrict, Jember Regency, East Java Province. The type of research used was Classroom Action Research (CAR) with 3 cycles in which each cycle consisted of stages of planning, implementation, observation and reflection. Data collection techniques used were observation, learning outcomes tests and questionnaires at the end of each cycle, data collection tools were carried out using observation guide sheets, test questions and questionnaires. Evidenced in the first cycle the percentage of student learning outcomes was 46%, cycle II 68% and in cycle III to 86%. And the percentage of learning activities in the first cycle is 67%, cycle II is 75%, cycle III is 86.5 and the results of student responses in the first cycle are 56.6%, cycle II is 66.67%, and cycle III is 71 , 6%.Keywords: Problem Based Learning, Rainbow Egg Rack Media, Learning Outcomes
Continuous integration and delivery applied to large-scale software-intensive embedded systems

Software development has become one of the world’s most important technologies. In parallel with the emergence of software development itself, development methodologies have evolved from the stage-gated waterfall model to more adaptive development frameworks such as XP and Scrum. As a part of XP and other agile methodologies, continuous integration and continuous delivery were introduced to mitigate problems with a long and unpredictable integration process at the final stage of a project. Companies that develop large-scale software-intensive embedded systems develop software systems combined with electronic and mechanical systems. These companies can also utilize the benefits from continuous integration and continuous delivery, but only if continuous integration and continuous delivery could be adapted to challenges and limitations introduced by large-scale and by proximity to hardware. The first part of this thesis identifies the problems that must be taken into account when applying continuous integration to large-scale software-intensive embedded systems. This is followed by definitions and interpretations of continuous integration and continuous delivery applicable to development of large-scale software systems. Finally, the key contributions of the research presented in this thesis are two models and a method, which will help organizations struggling with challenges related to scale and proximity to hardware to better implementations of continuous integration and continuous delivery. These contributions are valuable for both researchers and practitioners, as they provide a systematic approach rather than making changes blindly and hoping for the best.
PROFICIENT AUTOMATED LIBRARY MANAGEMENT SYSTEM(PALMS): A NEW MODEL FOR PUBLIC LIBRARIES OF PAKISTAN.

03Apr 2019 PROFICIENT AUTOMATED LIBRARY MANAGEMENT SYSTEM(PALMS): A NEW MODEL FOR PUBLIC LIBRARIES OF PAKISTAN. Naveed-e-Sehar , Humera Tariq and S.M.Aqil Burney. Assistant Professor, Department of Library and Information Sciences, University of Karachi, Pakistan. Assistant Professor, Department of Computer Science, University of Karachi, 75270, Pakistan. Meritorious Professor, College of Computer Science, Institute of Business Management, Pakistan.
AR in the Gallery

In recent years, museums have embraced the use of digital technologies to add interactivity to exhibits. New tools such as wireless beacons, QR codes and markerless trackers paired with powerful smartphones are used to implement applications ranging from guides that provide supplementary material as web pages or audio to spatially precise augmented reality (AR). In this work we explore the use of head-mounted (rather than the more common hand-held) AR in a museum space. Our goal is to explore visitor behaviour when using such technology, to inform the design of a future longitudinal study. We found that visitors enjoyed their experience with head-mounted AR and learned fairly quickly how to navigate and interact with virtual content.
A chatbot dialogue model: Understanding human-chatbot collaboration in a complex task environment

The rise of massive open online courses (MOOC) provides means to economize and scale education in response to higher budget restrictions [1] and raises the number of possible enrolled students by an unprecedented amount, compared to traditional higher education courses [2]. However, a disadvantage of MOOCs is the lack of individual support which can’t be addressed economically to a massive audience, often resulting in a less than optimal learning outcome [3]. Chatbots have the potential to alleviate this issue as a supporting tool to help the user learn how to solve a complex set of problems [4]. In 2017, the use of smart assistants in U.S. households like Amazon Echo or Google Home has increased by 128.9 per cent. Future forecasts indicate that their use will likely rise so that by 2022 the majority of the U.S. households will have at least one smart assistant in their home [5]. Chatbots have been around since at least 1966 [6], yet their use in more complex settings currently still involves difficulties, as interactions between users and chatbots remain for the most part simple and usually follow a simple question answer approach [7]. The application of advanced technologies such as deep learning [8] and the recently unveiled Google Duplex, a more technologically advanced smart assistant, already hints in a direction where in the near future smart assistants can act as collaboration partner in solving more complex tasks [9]. However, this remains a research field which is only beginning to unfold, with none or little research taken to how chatbot user interaction can be structurally developed within a problem task scenario. Thus, the aim of this paper is to design a process model on how chatbots and users can collaborate together in order to solve a problem. This model helps chatbot designers to analyze human-chatbot interactions and derive design requirements from it.
Designing the Next Generation of Activity Trackers for Performance Sports

Wearable sport technologies and activity trackers help sportspeople by providing physiological information on their performance. However, professional sportspeople find this information irrelevant due to their high-performance training. They want these devices to provide real-time assistive feedback on their performance, despite the formidable limitations suggested by previous research on giving such feedback. On the other hand, sport coaches already give performance feedback to their sportspeople during their performance.
PENERAPAN ALGORITMA K-MEANS UNTUK PENGELOMPOKAN DAERAH RAWAN BENCANA DI INDONESIA

Indonesia is a country located in the equator, which has beautiful natural. It has a mountainous constellation, beaches and wider oceans than land, so that Indonesia has extraordinary natural beauty assets compared to other countries. Behind the beauty of natural it turns out that it has many potential natural disasters in almost all provinces in Indonesia, in the form of landslides, earthquakes, tsunamis, Mount Meletus and others. The problem is that the government must have accurate data to deal with disasters throughout the province, where disaster data can be in categories or groups of regions into very vulnerable, medium, and low disaster areas. It is often found when a disaster occurs, many found that the distribution of long-term assistance because the stock for disaster-prone areas is not well available. In the study, it will be proposed to group disaster-prone areas throughout the province in Indonesia using the k-means algorithm. The expected results can group all regions that are very prone to disasters. Thus, the results can be Province West java, central java very vulnerable categories, provinces Aceh, North Sumatera, West Sumatera, east Java and North Sulawesi in the medium category, provinces Bengkulu, Lampung, Riau Island, Babel, DIY, Bali, West Kalimantan, North Kalimantan, Central Sulawesi, West Sulawesi, Maluku, North Maluku, Papua, west Papua including of rare categories. With the results obtained in this study, the government can map disaster-prone areas as well as prepare emergency response assistance quickly. In order to reduce the death toll and it is important to improve the services of disaster victims. With accurate data can provide prompt and appropriate assistance for victims of natural disasters.
7½ and weekend alarm : designing alarm clocks for the morality of sleep and rest

Although clocks facilitate good time-management, they have been used in ways that are detrimental to wellbeing. For example, alarm clocks are used to force a person to wake before they have had sufficient sleep and the ambient presence of clocks encourages a constant and sometimes unnecessary need for punctuality.In this paper, we discuss two alarm clocks that are designed to respect wellbeing, improving the ethics of user-object and designer-object relationships. ‘7½’ runs for exactly seven-and-a-half hours, regardless of when it was started, allowing a healthy amount of sleep. ‘Weekend Alarm’ hides its clock face over the weekend, when keeping to time may be less important. The clock designs were purposeful but did not always fit with conventional expectations on functionality. We discuss the process of designing these artefacts for the morality of sleep and rest, and how we came to propose the addition of some unconventional functions to their conventional designs. To inform our reflection on our design approach, we evaluated the devices with two types of participants: two temporary owners, who experienced discomfort but were able to cope with 7½ during the three-week trial, and six design experts who provided critical reviews of both designs.
La clase de geografía e historia al revés: mi experiencia con el flipped learning

In the following article we present the results of a teaching experience centered on the flipped classroom approach in Geography and History of ESO, applied with the aim of improving the attitude and academic results of the students. Finally, the results show an improvement in the motivation and learning of the students as a result of applying this approach as a basic teaching practice.
Mathematical Modelling of Atmospheric Pollution in an Industrial Region with a View to Design an Information System Software for Ecological Situation

The paper deals with the issues of information system for monitoring and assessing the ecological situation in an industrial region, based on the mathematical modelling of atmospheric pollution. Our model allows collecting live data and evaluating the possibility of pollution spread. The research object is the air composition changes that occurred under the natural and anthropegenus factors. The purpose of our research is to design an information system software for monitoring and assessing the ecological situation in an industrial region. A mathematical model, based on the hydro-thermodynamics equations, is applied to study the local atmospheric processes that occur in the boundary layer. The following were taken as original equations: equation of motion, continuity equation, heat flow equation and the equation of specific humidity. A modular software system was designed to implement the herein investigated methods and algorithms of solving the problem of the boundary and surface layers and the transfer of impurities.
Software Stack in a Snapshot

The Argonne Leadership Computing Facility is deploying Singularity to allow HPC resources to adopt “containers”—a technology that has benefitted non-HPC resources like cloud computing servers for a few years now. For HPC users, containerization will allow them to easily migrate their software stack between resources with minimal effort. For HPC facilities themselves, containerization gives users more autonomy to deploy the version of the software that best meets their specific needs.
Spark-based real-time proactive image tracking protection model

With rapid development of the Internet, images are spreading more and more quickly and widely. The phenomenon of image illegal usage emerges frequently, and this has marked impacts on people’s normal life. Therefore, it is of great importance to protect image security and image owner’s rights. At present, most image protection is passive. Most of the time, only when the images had been used illegally and serious adverse consequences had appeared did the image owners discover it. In this paper, a Spark-based real-time proactive image tracking protection model (SRPITP) is proposed to monitor the status of images under protection in real time. Whenever illegal use is found, an alert will be issued to image owners. The model mainly includes image fingerprint extraction module, image crawling module, and image matching module. The experimental results show that in SRPITP, the image matching accuracy rate is above 98.9%, and compared with its stand-alone counterpart, the corresponding time reduction for image extraction and matching are about 58.78% and 61.67%.
“Making Data Matter with Matt Mayernik” [edited interview transcript—blog post]. In Virapongse, A. (ed.), Making Data Matter (blog series)

ESIP is 20 years old! To celebrate, we interviewed ESIP community members on their perspectives on the progress of making Earth science data matter from over the last 20+ years. This is the second in a series of interviews that will be released over the next year. Original blog post: https://www.esipfed.org/esip-interviews/making-data-matter-with-matt-mayernik
Visual Quotes

Visual Quotes, or the communication of motivational text messages in a visual format, are increasingly used across social media and online communities. While physical activity trackers could leverage visual quotes, empirical studies of activity tracking in HCI research have paid little attention to this phenomenon and their potential effects on motivation. In this work, we conducted an online experiment (129 participants) to evaluate the impact of aesthetic appeal in motivational text messages as it relates to extrinsic identified behavior regulation. This is the type of motivation linked to the initial adoption of exercise behavior. The results of our study demonstrate that a perceived motivating text message presented with different levels of aesthetic appeal - ugly, neutral, beautiful - has the same impact on the motivation linked to short-term exercise (extrinsic identified behavior regulation). In other words, the perceived aesthetic appeal did not influence the motivating capability of textual messages for encouraging physical activity.
Generating the Minimal Optimal Language for Cooperative Agents

Inspired by the advantages of languages used in human beings and other creatures, we attempt to create a novel formal language for autonomous agents in a cooperative setting. With a few assumptions, we define a minimal optimal language generation problem which is formulated as a complex optimization problem, where a set of words is automatically generated. These words are derived from symbols extracted from the agents’ perception of the environment. Sentences are formed from word combinations and attached to semantic meanings used to distinguish the situations when communication is required. We then, present an optimal algorithm and an approximate algorithm for generating the smallest word set. Search skills and heuristics are developed to optimize the language generation process. The performance of the proposed approaches is evaluated in several environments in simulation. Finally, we show how the minimal language can be used by agents during planning to coordinate their behaviors and conduct hundreds of task instances to illustrate the benefits of using the language in two domains.
MODERN INFORMATION TECHNOLOGIES AND INNOVATIVE METHODS OF TRAINING IN THE PROCESS OF ARTISTIC SPECIALTIES PROFESSIONALS TRAINING

The article presents the results of the concept analysis, information and communication technology of education as a parallel, interconnected development of computer technology in the framework of educational concept. The potential and prospects for the development of information technologies in the modern educational environment are revealed. Possible methods of information technologies implementation in the sphere of art education are considered. Using traditional didactic approaches, a number of methods have been highlighted that will provide an opportunity to effectively use the latest achievements of information technologies in the educational process of artistic specialties. In order to improve the efficiency of modern computer tools using in the educational process offered variants of classifications, where each of the classifications corresponds to educational tasks of artistic and professional training.Key words: technology, computer technology, design, artistic design, interactive technologies of learning, portfolio, installation, performance.
Quantum tomography of a single-photon state by photon-number parity measurements

A single-photon state was generated by heralding cavity-enhanced spontaneous parametric downconversion in a PPKTP optical parametric oscillator. The Wigner distribution was reconstructed by quantum state tomography, using photon-number-resolving measurements with a system efficiency of 58±2%. © 2019 The Author(s)
High-performance image retrieval based on bitrate allocation

Image retrieval plays a key role in finding the required online multimedia learning materials quickly. In this paper, we realize a high-performance image retrieval by using bitrate allocation. First, the global descriptor is extracted to represent each image of the database. Second, the intra-group distance and the inter-group distance for each image are computed based on the global descriptor. Then, the retrieval difficulty degree (RDD) is evaluated based on the two types of distances. After that, an accurate bitrate allocation scheme is proposed when building the feature database according to RDD: using a higher bitrate for images that are hard to retrieve and lower bitrate for simpler ones. Finally, the higher retrieval performance is achieved based on the constructed highly efficient database. Experiments demonstrate that our method far outperforms the state-of-the-art on image retrieval benchmarks.
Comparison Study on Convolution Neural Networks (CNNs) vs. Human Visual System (HVS)

Computer vision image recognition has undergone remarkable evolution due to available large-scale datasets (e.g., ImageNet, UECFood) and the evolution of deep Convolutional Neural Networks (CNN). CNN's learning method is data-driven from a sufficiently large training data, containing organized hierarchical image features, such as annotations, labels, and distinct regions of interest (ROI). However, acquiring such dataset with comprehensive annotations, in many domains is still a challenge. Currently, there are three main techniques to employ CNN: train the network from zero; use an off-the-shelf already trained network, and perform unsupervised pre-training with supervised adjustments. Deep learning networks for image classification, regression and feature learning include Inception-v3, ResNet-50, ResNet-101, GoogLeNet, AlexNet, VGG-16, and VGG-19. In this paper we exploit the use of three CNN to solve detection problems. First, the different CNN architectures are evaluated. The studied CNN models contain 5 thousand to 160 million parameters, which can vary depending on the number of layers. Secondly, the different studied CNN's are evaluated, based on dataset sizes, and spatial image context. Results showing performance vs. training time vs. accuracy are analyzed. Thirdly, based on human knowledge and human visual system (HVS) classification, the accuracy of CNN's is studied and compared. Based on obtained results it is possible to conclude that the HVS is more accurate when there is a data set with a wide variety range. However, if the data-set if focused on only niche images, the CNN shows better results than the HVS.
Three-component zoom lens with fixed position of optical center

A method is proposed for calculation of initial parameters of a three-element zoom lens with an identical position of object and image principal planes of the optical system and approximately zero Petzval sum. Such an optical system has a fixed position of its optical center, which does not depend on object distance. The proposed method makes it possible to determine focal length values of individual elements and trajectories of their movements during zooming. The analysis is presented on examples of the calculation of parameters of such optical systems. These systems could be useful in optical measuring methods, photogrammetry, and machine vision techniques.
Introduction to Computer Programming and Python

Computer programming – commonly referred to as “coding” by the cool kids – is the art of creating applications or software. These programs allow us to do everything from solve simple math problems and watch our favorite YouTube videos (I can’t get enough of skydiving bulldogs) to destroying hordes of rampant aliens in our favorite video games and even launching a real-life spaceship into outer space.
Engaging Students in the ETU–TUIL Double Degree Program: Communication Strategy

The paper describes the interaction between Russian-German Engineering Faculty, established on the basis of St. Petersburg Electrotechnical University “LETI” and Technische Universitat Ilmenau, and candidate students interested in undergoing studies and taking internships in Germany pursuing Master’s degrees. The study focuses on the approaches utilized to attract the attention of and inform students to the double degree program. In this research, we analyzed the main communication channels between students and the faculty. The method of participant observation allowed us to discover several weaknesses in media planning. As a result, some recommendations are made to correct the current communication strategy.