Reviewerly/exHarmony huggingface dataset:
Computer Aided Malaria Disease Prediction System for Doctor and Patient Interaction

It has been already observed that machine learning has revolutionized the field of computer vision. Hardly a few years ago, It has transformed this field into practically true, in-your-pocket technologies out of those technologies which were usually considered like science fiction. If nearly human-level accuracy can be achieved through modern computer vision system in identifying dog breeds or cars, why not the current disease diagnostic system might not be as much capable of learning to identify the disease (disease pre-screening) using medical data (medical images or biomedical signal)?. This system is useful to help doctors or users to diagnosis the disease of patient in a short time and effectively via the identified symptoms.  Mosquitoes are surviving on earth since millions of years. They have always given tough time to men as important carriers of various diseases. Malaria and dengue remains to be the most vital cause of morbidity and mortality in India and in many other tropical countries with complete 2 to 3 million new cases arising every year. Malaria is a major health problem in the world. Malaria is well-known oldest chronic and most widespread fatal disease that has plagued mankind for centuries, which also causes economical loss.
A Common Framework to Recognize Two-dimensional Languages*

We introduce the two-dimensional rational automata (RA) to recognize languages of pictures, as an extension of the finite automata for strings. A RA processes a picture column by column changing its state. The states are columns of symbols, too. The transition function is realized by a transducer. We prove that RA recognize the family REC of languages recognized by tiling systems. Moreover, RA provide a uniform setting for a lot of important notions, techniques and results presented in the last decades for recognizable two-dimensional languages. The model is also very flexible. In fact, there can be imposed restrictions or added features to easily interesting new classes and examples or to capture known families of languages.
Encoding qubit-qudit states in photon polarization and picosecond time-bins

We introduce a qubit-qutrit information system realized by two degrees of freedom in a single photon: polarization and picosecond time-bin. We demonstrate creation and reconstruction of states in this framework using quantum state tomography [5].
Differentially private convex optimization with piecewise affine objectives: some subgradient approaches

In this paper we propose two new private subgradient methods: the bootstrapped private subgradient method and the private weighted average subgradient method. These are compared via a simulation study with the Laplace mechanism, the exponential mechanism, the private subgradient method and random uniform variables. We find that the exponential mechanism and the private weighted average subgradient method perform best depending on the situation, as instances can be generated for both mechanisms in which one performs better than the other and vice versa. However, the exponential mechanism seems to outperform the private weighted subgradient method in most cases treated in this paper.
The Influence Of Poster On The English Vocabulary Mastery (An Experimental Research At Second Grade Of MTsN 3 Pandeglang)

Enjang Al Ghifari. 142301727. 2018. The Influence Of Poster On The English Vocabulary Mastery (An Experimental Research At Second Grade Of MTsN 3 Pandeglang). Vocabulary is much more important than grammar, because English has the largest vocabulary in the world. The aim of teaching now is to help the student master the vocabulary, so we want to encourage the use of each word for communication and making students feel important to know the English word. This research conducted based on the statement of problems, Does Poster influence on students English vocabulary mastery at MTsN 3 Pandeglang? The aim the research to investigate the influence of poster on students English vocabulary mastery at MTsN 3 Pandeglang. To answer questions above, the writer collected data from 64 students spreading in two classes, each class has 32 students. One class as experimental group, and another one is control group. This research used an experimental research. The writer took sample from 8a class as control group, and 8c class as experimental group. The data was gathered through pretest and posttest. Based on the result, the writer got the score of experimental class, pretest 1880, and post-test score 2400. The pre-test score of control class was 2100, and post-test was 2230The result of analysis of the research show the value of 2.79 it is higher than the value of ttable the level significance 5% and 1% 1.99 and 2.65 .It means Ha (alternative hypothesis) of results is accepted and Ho (null hypothesis) is rejected. It means that significance is the influence of Poster Media toward in Teaching Vocabulary at the Second Grade MTsN 3 Pandeglang. Keywords: poster media, experimental research, vocabulary
ANALISIS PERBANDINGAN KINERJA ALGORITMA FIXED LENGTH BINARY ENCODING DAN ALGORITMA ELIAS GAMMA CODE DALAM KOMPRESI FILE TEKS

Now days, there are many algorithms developed for data compression, but there is no one that is good for compressing various types of files because of different characteristics or file structures. This research explained the result of two compression algorithms in order to know the performance comparison between the Fixed Length Binary Encoding (FLBE) algorithm and the elias gamma code algorithm in compressing text files, especially in format rtf. The parameters being compared are the ratio of compression, compression ratio, redundancy and time. Based on the test results show that the fixed length binary encoding algorithm is better than the elias gamma code algorithm where the average ratio of compression results of fixed length binary encoding algorithm is 1.66 bits while the elias gamma code is 1.62 bits. The average compression ratio of fixed length binary encoding algorithm is 60.9% while Elias Gamma Code is 62.20%. The average value of the redundancy of the fixed length binary encoding algorithm is 39.1% while the gamma code elias is 37.79%. The average time compression value of the fixed length binary encoding algorithm is 16 ms while the elias gamma code is 21 ms.Keywords: comparison, compression, FLBE algorithm, Elias Gamma Code Algorithm, text, rtf
Participar de uma cultura de colaboração com a biblioteca escolar

This article focuses the value of the school library (SL) today, based on international and national reference documents that describe the SL as the “nerve center of the school”. We focus our approach on the collaborative work between teachers (librarian and subject teachers), considering the students as its core, as authors of their learning process. First, we address SL’s design in reference documents. Secondly, we observe the teachers collaborative work and the student profile in that framework. We conclude with a proposal for an information research project and construction of digital products for high school students, adopting the “Big6” model, in close partnership with the school's librarian teacher and collaborative work with two subject teachers.
“Temporal event analysis and visualisation: Optimisation of hospital patient flows”

Event data is present in a variety of domains such as electronic health records, daily living activities and web clickstream records. Current visualization methods to explore event data focus on discovering sequential patterns but present limitations when studying time attributes in event sequences. Time attributes are especially important when studying waiting times or lengths of visit in patient flow analysis. The speaker will present a visual analytics methodology that allows the identification of trends and outliers in respect of duration and time of occurrence in event sequences. The proposed method presents event data using a single Sequential and Time Patterns overview. This visualization allows the derivation of findings  that otherwise could not be obtained using traditional visualizations. The proposed  methodology has been applied to a real-world dataset provided by Sheffield Teaching Hospitals NHS Foundation Trust, for which four classes of conclusions were derived.
Pengaruh Gaya Belajar terhadap Prestasi Belajar Siswa di Kelas IV SD Negeri 03 Karangbangun Matesih Tahun 2018/2019

This study aims to look at significant results of student learning styles on learning The research subjects were all grade IV students of SDN 03 Karangbangun Matesih consisting of 22 students Data collection using questionnaire questionnaire method and documentation Analysis techniques using descriptive statistics, multiple regression analysis, multiple correlation analysis, analysis of simple correlation, degree of destrimination coefficient, effective or relative contribution The results of multiple regression data are Y = 43 486 + 0.371XI, meaning that learning performance is influenced by the learning style and teaching style of the educators. The results of the analysis are (1) The way of student learning has significant impact on Proven learning achievement through the t test obtained thmg> tbel that is 3 with a significant level of 59% From the regression test obtained F 44 859 F 3 467 means that between student learning styles affect student achievement SDN 03 Karangbangun by looking at hypothesis testing about the regression coefficient with e test wait enter student learning style variables of 6,698 2,080, so there is a significant influence between student learning styles on student achievement.
Export of agricultural products and economic growth in Madagascar

This paper examines the impact of agriculture, especially coffee, vanilla, and clove exports on economic growth of Madagascar using time series secondary data covering 1990-2017. The study used Johansen co-integration and vector error correction model approach to estimate the long run and short run impact. The results showed that agricultural exports have short run mixed result on economic growth in Madagascar. Coffee and vanilla export has a positive effect on economic growth in the long run and in the short run. Though, clove export has also a positive long run effect on economic growth, it has a negative impact in the short run. These results will help the policy makers and investors in Madagascar for the decision making since results reveal increase export of agriculture can increase in GDP.
Childhood blindness - Etiological risk factors as evaluated by blind schools survey in Prayagraj and surrounding districts

Childhood blindness - Etiological risk factors as evaluated by blind schools survey in Prayagraj and surrounding districts - IJCEO- Print ISSN No: - 2395-1443 Online ISSN No:- 2395-1451 Article DOI No:- 10.18231/j.ijceo.2019.121, Indian Journal of Clinical and Experimental Ophthalmology-Indian J Clin Exp Ophthalmol
Research Guides: ERH203: Ways of Reading: Find Articles

This course research guide is created for MAJ Hodde's ERH203 class taught in the Fall of 2019.
Non-formal education for life, survival, and living together

The rapid changes have been occurring in our society: population increase, changed life style and widen gap between rich and poor, and those will pose a fundamental threat to live, livelihoods and public health. Non-formal education (NFE), by nature, has the full potential to provide learning opportunities to socially neglected individuals as well as communities, to secure their basic human needs such as food and water, shelter, health and nutrition, employment, and survive natural or manmade disasters. Japanese experiences of NFE movement in 20th century promotes to reconsider the importance of NFE and its learning for the 21st century.
Data Inventory as the Development and Promotion Basis of Universities Educational Programs

Digitalization affects universities, including management decision-making processes. Different management decisions require different data sets. The paper studies the issues of making managerial decisions at the university on the development and promotion of basic educational programs at the educational services market based on the results of data inventory. Two approaches are proposed: the study of data belonging to the university, and the search for the necessary data in the external environment. The article identifies the areas that need to be studied in order to make managerial decisions on ways to promote the main educational programs at the university, and analyzes the information accumulated both inside the university and in the external environment. The authors of the article proposed an algorithm for database inventory, which involves the identification of data sources, including digital traces, the analysis of the authority to use databases with the necessary registries of information systems and website directories. The result of data inventory should be the design of updating systems for the development and promotion of a university educational program. These actions will lead to the creation of an information system that will collect and process the diverse information needed to adjust the university’s strategy. As a result, the university should expand the functional system that accumulates and systematizes various data required to promote the university educational programs at the market.
LibGuides: Quantum Computing: Home

Taking technology to a new level, quantum computing promises efficient problem solving not feasible on classical computers.
Reevaluation of Active Geologic Structures in the Epicentral Area of the 2018 Northern Osaka Prefecture Earthquake Based on Geomorphological, Geological and Geophysical Exploration Data

The 2018 northern Osaka Prefecture earthquake (Mj 6.1) was caused by ruptures of blind strike-slip and reverse faults. The earthquake was moderate in size but caused severe damages to the northeastern part of the densely populated Osaka metropolitan area. The epicentral area is located at a junction of east-trending strike-slip faults and north-trending reverse faults. In order to better understand the geologic setting of the earthquake, we conducted an integrated analysis of published seismic reflection profiles and gravity basement structure map together with geomorphic and geologic data. We interpreted that the Arima-Takatsuki Tectonic Line fault zone extends about 9 km further to the east of the geomorphologically mapped surface trace. We also found that the Hirakata flexure extends northeast beneath the Yodo River as a southeast-dipping reverse fault. The area bounded by the Arima-Takatsuki Tectonic Line fault zone and northeast extension of the Hirakata flexure is a northeast-trending graben which we call here as the Yodogawa graben. The 2018 earthquake occurred beneath the graben but the ruptured faults do not offset gravity basement. The identification of the previously unknown active faults warrants further geological and geophysical studies of the faults in this highly urbanized area of the Osaka Plain.
RGB-D dynamic facial dataset capture for visual speech recognition

We present a new comprehensive RGB-D dynamic facial dataset capturing system that can be used for facial recognition, emotion recognition, or visual speech processing. Our facial dataset uses an RGB-D (Kinect) camera to record 20 individuals saying 20 common English words or phrases. Using Kinect facial tracking, we not only record the facial features, but also facial outline, RGB data, depth data, mapping between RGB and depth data, facial animation units, facial shape units, and finally 2D and 3D face representations of the face along with the 3D head orientation. The captured RGBD dynamic facial dataset can be employed in several applications. We demonstrate its effectiveness by presenting a new visual speech recognition that employs three-dimensional spatial and temporal data of different facial feature points. The results demonstrate the our RGB-D dynamic facial dataset can be effectively employed in a visual speech recognition system.
OpenAIRE Guidelines for CRIS Managers in DSpace-CRIS

For developers of CRIS platforms, the OpenAIRE Guidelines for CRIS Managers provide guidance to add supportive functionalities for CRIS administrators and users. Exchange of information between individual CRIS systems and the OpenAIRE infrastructure is an example of point-to-point data exchange between CRIS systems, since the OpenAIRE infrastructure itself is a CRIS system. On December 20th, 2018, an updated version was released for the OpenAIRE Guidelines for CRIS Managers. In May 2019, 4Science was awarded the implementation of the Guidelines in the open-source software platform DSpace-CRIS, which extends the DSpace repository platform by research data and information management. Today we can already count more than 100 installations of DSpace-CRIS running in research institutions throughout Europe and other continents, which emphasizes the potential when making their rich research information interlinked and findable in OpenAIRE. The main objectives of this project were to realize the implementation of the latest OpenAIRE Guidelines for CRIS Managers in DSpace-CRIS and to enable DSpace-CRIS platforms to expose research information to OpenAIRE. The implementation targeted DSpace-CRIS releases version 5.10 and version 6.3 and was released as open source in the first phase of the project. The implementation allows every single institution to crosswalk the local DSpace-CRIS configuration, entities and attributes, toward the OpenAIRE CRIS specification in a 1:1, n:1 or 1:n mapping at the instance level. This means that a DSpace item entity, which in DSpace-CRIS is used to represent different sorts of research output, can also be mapped in a different OpenAIRE CRIS Entity (Publication, Patent, Product), depending on a specific metadata of the item or different entities in DSpace-CRIS; for instance the Journal and the Publication can be mapped to the same CERIF Publication Entity. The presentation will deal with the challenges and the results of the project, the lessons learnt by its participants and the expected outcomes and impact on the OpenAIRE and CRIS communities.
Conversations on the nature of reality

Annals of the New York Academy of SciencesVolume 1458, Issue 1 p. 5-8 COMMENTARY Conversations on the nature of reality Steve Paulson, Steve Paulson annals@nyas.org Wisconsin Public Radio, Madison, WisconsinSearch for more papers by this author Steve Paulson, Steve Paulson annals@nyas.org Wisconsin Public Radio, Madison, WisconsinSearch for more papers by this author First published: 20 November 2019 https://doi.org/10.1111/nyas.14283Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat Volume1458, Issue1Special Issue: Conversations on the Nature of RealityDecember 2019Pages 5-8 RelatedInformation
AI: profili giuridici. Intelligenza Artificiale: criticità emergenti e sfide per il giurista

The research aims at exploring the main legal issues triggered by the implementation of Artificial Intelligence systems, with a view to identifying possible solutions for regulators and lawmakers at national and supranational level. The study moves from a comprehensive overview covering the existing soft law instruments, the core areas captured in academic speculation and the latest developments in case law. It then separately addresses selected sensitive issues that should be on public and private policymakers’ agenda, most notably: the governance of AI; the impact of AI systems on public law; the relationship between AI systems and private and criminal law as well as procedural law. For each of these areas, the research analyzes how the rise of AI systems calls into question well established legal categories and which remedies lawmakers and regulators should take into account to reconcile the need to foster technological developments and that of protecting fundamental rights.
Incremental and Transfer Learning of Contextual Skill Model for Robots

The thesis studies building blocks for robot skill learning. Using these key components, learning frameworks can be constructed which provide robots with the capability to acquire a motion and manipulation skill autonomously. We study skill learning in two contexts: in-contact and free-space motions. In brief, this thesis investigates how to: (1) learn a policy for in-contact tasks; (2) generalize a free-space motion policy to new situations using a contextual skill model (CSM); and (3) transfer the CSM from simulation to real world. Learning an in-contact task such as wood planing from scratch can be time-consuming and dangerous. This problem can be avoided by imitating a policy from a human demonstration. However, a mere imitation may not satisfy the objective of the corresponding in-contact task. The thesis proposes a reinforcement learning (RL) framework for improving the performance of an imitated in-contact policy. The policy search for in-contact tasks has been achieved by making the motion compliant which allows for exploration in the force profile. Generalizing a policy to new situations is fundamental to skill learning as it alleviates the need to learn a new policy in every novel situation. Generalizing a policy refers to synthesizing a function mapping the policy to new situations. The function is referred to as a contextual policy or contextual skill model (CSM). The thesis proposes a parametric CSM. Experiments demonstrated that the parametric CSM can extract a global pattern from a database (DB) of policy parameters leading to significantly better extrapolation capability than with non-parametric CSMs. Furthermore, the underlying model of the CSM is fitted to the DB using a novel model selection approach to better represent the underlying regularities of the task. In order to speed the process of learning, the prediction uncertainty of the CSM is calculated using empirical Bayes (EB) and employed for guiding the exploration process of a model-free policy search. In addition, the most promising task is selected using a novel task manager, allowing for better future generalization performance achieved with minimum effort. In essence, the thesis presents an incremental learning framework,the main components of which are as follows: CSM, policy search, model selection, DB, EB, and a task manager implemented using active learning.Learning a policy in a simulated environment and transferring it to the real world will alleviate the need to learn from scratch or from a demonstration. The thesis proposes to transfer a CSM instead of transferring a single control policy. We developed a simulation-to-real transfer framework which learns a source CSM in simulation incrementally and transfers it to the real world incrementally. Transference of the source CSM has been achieved using sample policies from the target environment. Experiments indicated that one sample policy is sufficient to transfer a CSM to the target environment. The target CSM improved the extrapolation capability significantly better…