Reviewerly/exHarmony huggingface dataset:
For Cybersecurity, Computer Science Must Rely on Strong Types

This article shows how fundamental higher-order theories of mathematical structures of computer science (e.g. natural numbers [Dedekind 1888] and Actors [Hewitt et. al. 1973]) are categorical meaning that they can be axiomatized up to a unique isomorphism thereby removing any ambiguity in the mathematical structures being axiomatized. Having these mathematical structures precisely defined can make systems more secure because there are fewer ambiguities and holes for cyberattackers to exploit. For example, there are no infinite elements in models for natural numbers to be exploited. On the other hand, the 1st-order theories of Godel’s results necessarily leave the mathematical structures ill-defined, e.g., there are necessarily models with infinite integers. Cyberattackers have severely damaged national, corporate, and individual security as well causing hundreds of billions of dollars of economic damage. [Sobers 2019] A significant cause of the damage is that current engineering practices are not sufficiently grounded in theoretical principles. In the last two decades, little new theoretical work has been done that practically impacts large engineering projects with the result that computer systems engineering education is insufficient in providing theoretical grounding. If the current cybersecurity situation is not quickly remedied, it will soon become much worse because of the projected development of Scalable Intelligent Systems by 2025 [Hewitt 2019]. Godel strongly advocated that the Turing Machine is the preeminent universal model of computation. A Turing machine formalizes an algorithm in which computation proceeds without external interaction. However, computing is now highly interactive, which this article proves is beyond the capability of a Turing Machine. Instead of the Turing Machine model, this article presents an axiomatization of a universal model of digital computation (including implementation of Scalable Intelligent Systems) up to a unique isomorphism.
Свободни електронни ресурси

The scientific electronic archive of the New Bulgarian University was the first one created in Bulgaria. The first open access document was deposited in it. Its mission is to be a single open electronic space that provides long-term storage and access to the academic achievements of the academic community at the university.
Data parallel implementation of the GRAIL index on many-core architectures

Reachability is among the most common problems to address when working on graphs since it is the base for many other algorithms, and scalable solutions have become of paramount importance with the advent of distributed systems that process large amounts of data. Specifically many applications explore graphs with millions of nodes and vertices, which explains why the development of fast and scalable algorithms entails complex challenges. Modern GPUs are highly parallel systems based on many-core architectures and have gained popularity in parallelizing algorithms that run on large data sets. In this context the NVIDIA CUDA platform has been used to provide a concrete implementation of the developed algorithms. The main focus of this work is to analyze the GRAIL algorithm, which creates a scalable index for answering reachability queries on large graphs, in order to design an implementation that exhibits a greater amount of data parallelism. The GRAIL index relies heavily on depth-first search, which is among the hardest algorithms to develop on parallel systems, so an alternative approach based on breadth-first search will be explored and significant effort will be devoted towards explaining the difficulties encountered and the solutions chosen to overcome them. Finally this work will provide a concrete implementation on CUDA of the proposed algorithms, a comparison between the indexing and search times for the CPU and the GPU based versions and insight on how to conduct further research in future.
Finding Shortest Distance Path and Object Detection and Avoidance Using Image Processing and Artificial Intelligence.

In this work we will be implementing Shortest distance path finding algorithm andobject detection avoidance using Image Processing and artificial intelligence. The workwill be focused on generating shortest path using A star algorithm and object avoidanceusing Image Processing. Work will also represent inserting static map with the help ofimages. Insertion of object will be tested with different shapes and sizes to berepresented on the graph.
교육연극을 활용한 소설교육 방안 연구: 이문구의『우리동네』를 중심으로

This paper examines the method of novel education applicated drama in education. It emphasized that novel education based on drama in education reinforces core competencies of convergence and revision curriculum and assists overall growth. Therefore, it was discussed that the drama in education can be used as a useful medium to integrate humanities and arts, cultivate critical and creative thinking power and correct personality through novel texts. Through Lee Moon gu's our neighborhood, this paper searched for the direction of the text for educational plays. First, we explored the possibility of novel education theoretically by examining background and method of educational drama. Next, this paper looked at the teaching and learning principles of novels using educational plays in terms of learning methods. Based on this, this paper proposed a teaching method of novel lesson using educational drama. In the future, I hope that many studies on novel education using educational drama will be done.
IQVIA Institute for Human Data Science Releases 2018 Medicine Use and Spending Results

Top trends included a decline in opioid prescribing and an increase in patient abandonment of scripts throughout 2018.
Hydration of silica and its role in the formation of quartz veins - Part 2

The aqueous chemistry of silica and the formation of abundant polymeric silica species in natural sediment accumulations is set out in Part 1. Part 2 continues to describe the amorphous silica in sediments and presents more evidence for the formation of quartz veins from silica gels. The physical chemistry for the formation of oolites in quartz veins, ptygmatic folding of quartz veins, the enhanced growth of crystals in quartz veins, the precipitation of gold in quartz and the mechanism for replacement or metasomatism by quartz (silicification) are detailed. Current physical chemistry applies not only to precursor silica gel but also to the hydrous precursors of other crystalline rock minerals such as clays, mica, hydrous ferromagnesian minerals and mineral deposits. “The Origin of Rocks and Mineral Deposits - using current physical chemistry of small particle systems” provides a new basis for understanding geological phenomena. This has now been published in Elliston1 2017 (Connor Court, Brisbane, ISBN 978-1-925501-36-0).
Initial Perceived Quality Evaluation for Video Streaming Services

Initial perceived quality (IPQ) reflects users’ perception when waiting for videos to play, which directly determines the user’s willingness to go on watching videos. However, IPQ has never been carefully analyzed and evaluated. In this paper, two types of subjective test methods were elaborately designed, where the IPQ scores were obtained. The accuracy of IPQ scores was checked according to the consistency of the rating results. Then, an objective evaluation model was proposed accordingly to evaluate IPQ. Meanwhile, the relationship between IPQ and users’ unacceptability of initial loading delay was also investigated according to users’ abandonment behavior during the waiting period. A probability model was proposed to evaluate the unacceptability of users using logistic regression analysis. The experimental results show that the proposed models can accurately evaluate IPQ and users’ unacceptability of the initial loading delay. The proposed models can be used as guidelines for service providers to effectively improve the buffering strategy for video streaming services.
APLIKASI PENDAFTARAN PASIEN RAWAT JALAN RUMAH SAKIT MEILIA CIBUBUR BERBASIS WEB

The purpose of this research is to build Application of Outpatient Registration in the hope that patient registration process easier to do, efficient and has been usingthe latest technology by using Web-based application. In the event of a problem can be detected and repaired more easily and quickly. The current system at Meilia CibuburHospital is a hospital-based hospital system, a running system that has been running well and has helped get the required data officer. But on the desktop technology-based application side is limited by the access that must be in one network of Meilia Hospital only. The author studied the existing system and make the application of Outpatient Registration with the aim of renewal of hospital application technology into web-based application of course with no disrupt and almost the same for the workflow officers with existing systems.
The Relationship between Yongmoodo Master`s Emotional Leadership, Trainee`s Trust in Master and Exercise Adherence Intention

This study was designed to find the relationship between Yongmoodo master’s emotional leadership, trainee’s trust in master and exercise adherence intention. To test this, 196 Yongmoodo trainee who are registered in Korea Yongmoodo Association were sampled. The resulting data were processed by means of frequency analysis, exploratory factor analysis, reliability analysis, correlation analysis, and structure modeling using SPSS 21.0 and AMOS 21.0 program. Results derived from the researches based on the aforementioned methods and data analyses are as follows: First, Yongmoodo master’s emotional leadership had significant effect on trust in master. Second, Yongmoodo master’s emotional leadership had significant effect on trainee’s exercise adherence intention. Third, Yongmoodo trainees’ trust in master had significant effect on trainee’s exercise adherence intention.
Artificial intelligent sensors at the core of cyber-physical-systems

Cyber-Physical Systems (CPS) are becoming, without pace, more pervasive into embedded systems. Artificial Intelligence, Machine Learning and Deep Learning are mostly confined into the cloud, where unlimited computing resources seems to be available and evolving tirelessly. Unfortunately a layered architecture in which dumb sensors are attached to the cloud would become quickly too centralized, poorly scalable and slowly responsive in the IoT expected scenario that will deploy hundreds of billions of sensors communicating through low data rate networks. In that context, STMicroelectronics is developing solutions to bring Artificial Intelligence closer to the sensors. This talk will review new intelligent technological solutions and mechanisms under development and publicly announced, namely STM32CUBE.AI. The talk will tell how they represent the key ingredients needed to design the current and future generation of artificial intelligent cyber-physical embedded systems and derived applications based on STMicroelectronics heterogeneous sensors, micro controllers and SoCs. In particular, aspects related on how address current interoperability, productivity and constrained embedded resource gaps will be discussed with practical examples based on STM32CUBE.AI. Moreover, the investigation and design of adaptive and cognitive computational-intelligence techniques able to learn, adopting artificial neural networks, and operate in nonstationary environments will be introduced. Finally, the deployment of networked intelligent cyber-physical systems, able to operate in time varying environments, will be also commented.
Motivasi Belajar Manajemen Keuangan Ditinjau Dari Penggunaan Internet Sebagai Media Belajar Dan Lingkungan Kampus Pada Mahasiswa Pendidikan Akuntansi Universitas Muhammadiyah Surakarta Angkatan Tahun 2015

Dwi Ari Prastyoningtyas / A210130135. LEARNING MOTIVATION OF FINANCIAL MANAGEMENT REVIEWED FROM THE USE OF THE INTERNET AS A LEARNING AND CAMPUS ENVIRONMENT MEDIA IN UNIVERSITY ACCOUNTING EDUCATION STUDENTS, MUHAMMADIYAH SURAKARTA FORCE, 2015. Thesis, Teacher Training and Education Faculty, Surakarta Muhammadiyah University. 2019.This study aims to describe: (1) the influence of internet use as a learning medium on financial management learning motivation, (2) the influence of the campus environment on financial management learning motivation, and (3) the influence of internet usage as a learning media and campus environment on financial management learning motivation .The method used in this study is quantitative associative. The population of this study was all 2015 UMS FKIP accounting education students totaling 229 students. The sample of this study was 135 students. Sampling technique uses Probability Sampling. Data collection techniques using questionnaires and documentation. Data analysis techniques used multiple regression analysis, t test, F test, effective contribution, relative contribution.Regression analysis results obtained regression equation: Y = 1.261+ 0.363X1 + 0.653X2, which means that financial management learning motivation in students is influenced by the use of the internet as a learning media and campus environment. Based on the analysis and discussion it can be concluded that: (1) the use of the internet as a learning medium has a significant effect on the motivation to learn financial management. This is evident from the regression analysis which obtained the value of tcount = 5.113> t table = 1.977 and a significant value t table = 1.978 and a significant value Ftable which is 5.276> 1.007 and a significant value <0.05, which is 0.000. (4) the variable use of the internet as a learning media and campus environment gives a big influence together, namely 94.3% while the rest is influenced by other variables not examined in this study.
Analisis Kesalahan Penggunaan Kosakata pada Karangan Deskripsi Siswa yang Berlatarbelakang Bahasa Belitung Kelas X MA Muhammadiyah Gantung Belitung Timur

The problem in this study is how the use of vocabulary in the description essay ofstudents who are from the background of the Belitung language Class X MAMuhammadiyah Gantung East Belitung. This research is a qualitative researchusing descriptive methods. Data collection is done by using documentation andnote-taking techniques. The method used is the Agih method. Agih method is ananalytical method whose determinants are inside and are part of the languagestudied. In this study, researchers used triangulation techniques. Based on theresults of research on the use of vocabulary in the description essays of studentswho are from the background of the Belitung class X MA MuhammadiyahGantung East Belitung, the results show that there is no influence on the use ofBelitung language as a daily language in the student description essay and dataobtained in the form of vocabulary usage which is appropriate and not inaccordance with the requirements for the accuracy of diction, including: 1)synonymous words, 2) use of general words and special words, 3) use ofconnotative and denotative words, 4) continuity of word choices, and 5) use ofsense words.
Simulating CRF with CNN for CNN

Combining CNN with CRF for modeling dependencies between pixel labels is a popular research direction. This task is far from trivial, especially if end-to-end training is desired. In this paper, we propose a novel simple approach to CNN+CRF combination. In particular, we propose to simulate a CRF regularizer with a trainable module that has standard CNN architecture. We call this module a CRF Simulator. We can automatically generate an unlimited amount of ground truth for training such CRF Simulator without any user interaction, provided we have an efficient algorithm for optimization of the actual CRF regularizer. After our CRF Simulator is trained, it can be directly incorporated as part of any larger CNN architecture, enabling a seamless end-to-end training. In particular, the other modules can learn parameters that are more attuned to the performance of the CRF Simulator module. We demonstrate the effectiveness of our approach on the task of salient object segmentation regularized with the standard binary CRF energy. In contrast to previous work we do not need to develop and implement the complex mechanics of optimizing a specific CRF as part of CNN. In fact, our approach can be easily extended to other CRF energies, including multi-label. To the best of our knowledge we are the first to study the question of whether the output of CNNs can have regularization properties of CRFs.
THE ANALYSIS OF CYBER SECURITYTHE EXTENDED CARTESIAN METHOD APPROACHWITH INNOVATIVE STUDY MODELS

Cyber security is the practice of protecting systems, networks, and programs from digital attacks. These cyber attacks are usually aimed at accessing, changing, or destroying sensitive information; extorting money from users; or interrupting normal business processes. Implementing effective cyber security measures is particularly challenging today because there are more devices than people, and attackers are becoming more innovative.This thesis addresses the individuation of the appropriate scientific tools in order to create a methodology and a set of models for establishing the suitable metrics and pertinent analytical capacity in the cyber dimension for social applications. The current state of the art of cyber security is exemplified by some specific characteristics.
PENERAPAN METODE GRAPHIC ORGANIZER PADA PEMBELAJARAN BAHASA INDONESIA UNTUK MENINGKATKAN HASIL BELAJAR PADA SISWA KELAS V DI SD NEGERI 06 BATHIN SOLAPAN

ABSTRACTThe basic problem for students today is the low learning outcomes of students who have not achieved the completeness set by the government in the field of education. As found by researchers at SDN 06 Bathin Solapan, the low yield of class V Indonesian language learning. Class action research aims to improve and improve the learning process in class, classroom action research is an action research carried out with the aim of improving the quality of classroom learning practices. data increases the analysis of observation of teacher activity at the first meeting by 58% with sufficient categories, at the second meeting of 70% in the good category, then at the third meeting amounting to 82% with a very good category, and at the IV meeting 95% with very good category. the increasing data on the observation of student activities at the first meeting was 60% with sufficient categories, at the second meeting 71% in the good category, then at the third meeting 86% with the very good category, and at the IV meeting 94% with the category very good. Data on the improvement of student learning outcomes, namely the daily test I of 83 and the second daily test of 90. By looking at the various data above, we can conclude that the application of the graphic organizer learning method can improve Indonesian language learning outcomes of fifth grade students of SDN 06 Bathin Solapan.
Discovery of inconsistent generalized coherent rules

Mining multiple-level association rules in a predefined taxonomy is an hierarchy that paves the way for generalised rule mining using interestingness measures like support and confidence. Coherent rule mining identifies significant rules in a database without using interestingness measures. In this paper, we propose a new mining algorithm called generalised inconsistent coherent rule mining (GICRM) for mining a new form of generalised coherent rules called inconsistent coherent rules. The discovered rules are called inconsistent because the correlation of the rules changes from one level of taxonomy to another. The rules are mined from a structured dataset of predefined taxonomy. The inconsistent rules mined would be noteworthy at the business point of view for taking strategic decisions in market basket analysis.
PPT-distinguishability for the lattice maximally entangled states

We study the distinguishability of a particular type of maximally entangled -- the states using a new approach of semidefinite program. With this, we successfully construct all sets of four ququad-ququad orthogonal maximally entangled that are locally indistinguishable and find some curious sets of six having interesting property of distinguishability. Also, some of the problems arose from \cite{CosentinoR14} about the PPT-distinguishability of lattice maximally entangled can be answered.
Domestic Widgets: Leveraging Household Creativity in Co-Creating Data Physicalisations

The home environment is a complex design space, especially when it has multiple inhabitants. As such, the home presents challenges for the design of smart products. Householders may be different ages and have differing interests, needs, and attitudes towards technology. We pursued a research-through-design study with family households to envision and ‘co-create’ the future of data-enabled artifacts for their homes. We have iteratively developed domestic research artefacts for these households that are open, data-enabled, physical visualizations. These artefacts - called Domestic Widgets - are customisable in their design and functionality throughout their lifespan. The development process highlights design challenges for sustained co-creation and the leveraging of household creativity in (co-creation) research toolkits. These include the need to allow and inspire iterative customization, the need to accommodate changing roles within the home ecology, and the aim that such design should be inclusive for all family members (irrespective of age and technical proficiency), whilst maintaining a role and purpose in the home. We invite the RTD community to critically discuss our, and other, open and iterative end-user designs for sustained co-creation. By presenting unbuilt and interactive pre-built Domestic Widgets, we interactively foster engagement with practises of sustained co-creation.
Experimental preparation of Gottesman-Kitaev-Preskill states by photon-number-resolving detection

We propose to expand “Fock state filtering” to photon-number-resolving detection and apply it to the generation of displaced single-photon states, cat states, and Gottesman-Kitaev-Preskill ancillas. © 2019 The Author(s)
Take Control of Your Scholarly Identity with Deep Blue

Presentation at Enriching Scholarship 2019 in the University of Michigan Library in Ann Arbor, MI.
Hiding in plain sight: handwriting and applications to steganography

Steganography, the process of hiding secret information within normal-looking data (a cover),lies at the intersection of computer science and security. Recently, these covers have come inthe form of images. The steganographic task must pass two visual inspections: by humansand by machines. If a human examines the image and fails to spot the hidden data, thealgorithm successfully passes the first test. The second task is preventing a machine fromdetecting patterns to reverse engineer the secret information. In 2017, researchers achievedsome success [1], but there were two main issues: the steganography only worked with(a) fully saturated, (b) fixed-size (100 x 100) images. To curb these limitations, a newpipeline is explored to generate non-fixed size cover images with steganographic modificationrather than embedding. This paper explores this new form of steganography with severalkey processes. First, the secret information is encrypted before combining it with the coverusing neural cryptography. Second, the information hides in the stroke data of a person'shandwriting on a white background, increasing task difficulty, forcing the steganographicapproach to be robust to a plethora of data, including sparse images. In this sense, thestrokes are directly modified, rather than inserted or embedded in-between pixels. The resultis a toy problem utilizing realistic, generated, coordinate sequences of human handwritingmodified with slight offsets dependent on the information combined with the coordinates inthe sequence. With these slight offsets, the new generated coordinates are nearly identicalto the original coordinates, preserving the primary structure of the handwriting, but shininglight on a new avenue of steganography based on data modification rather than embedding.