Reviewerly/exHarmony huggingface dataset:
Learning large logic programs by going beyond entailment

A major challenge in inductive logic programming (ILP) is learning large programs. We argue that a key limitation of existing systems is that they use entailment to guide the hypothesis search. This approach is limited because entailment is a binary decision: a hypothesis either entails an example or does not, and there is no intermediate position. To address this limitation, we go beyond entailment and use \emph{example-dependent} loss functions to guide the search, where a hypothesis can partially cover an example. We implement our idea in Brute, a new ILP system which uses best-first search, guided by an example-dependent loss function, to incrementally build programs. Our experiments on three diverse program synthesis domains (robot planning, string transformations, and ASCII art), show that Brute can substantially outperform existing ILP systems, both in terms of predictive accuracies and learning times, and can learn programs 20 times larger than state-of-the-art systems.
Research Guides: Knowledge Organization and Metadata Services: Authority Control, USMAI and OCLC

Outlines the mission and responsibilities of the department and provides access to the tools used to accomplish this work. Provides links to cataloging-related organizations, authority control websites, and OCLC resources
Study of photothermal effect in core-shell transport microcontainers

The theoretical study of laser-induced heating of a transport cargo microcontainer constituting a hollow dielectric microcapsule with water filling and a light absorbing polymer shell is presented. By means of FDTD and FEM techniques, the numerical calculations of optical field spatial distribution inside and near the microcapsules are carried out, and the temporal dynamics of temperature profiles of core-shell microparticles of various morphological types (spheres, ellipsoids, boxes, cubes, cylinders) and microcapsule clusters in different configurations is addressed. The spatial configurations of light absorption regions are shown to be substantially dependent on the morphology of the microcapsules. For isolated microcapsules, the most efficient laser heating is realized in capsules of cubic and cylindrical shapes. When the capsules are aggregated into the densely packed cluster, the characteristic heating depth of the whole assembly is higher for cylindrical microcapsules. In sparse microassemblies the square-shaped capsules are preferable for increasing the efficiency of laser heating.
Testing Machine Translation via Referential Transparency

Machine translation software has seen rapid progress in recent years due to the advancement of deep neural networks. People routinely use machine translation software in their daily lives, such as ordering food in a foreign restaurant, receiving medical diagnosis and treatment from foreign doctors, and reading international political news online. However, due to the complexity and intractability of the underlying neural networks, modern machine translation software is still far from robust and can produce poor or incorrect translations; this can lead to misunderstanding, financial loss, threats to personal safety and health, and political conflicts. To address this problem, we introduce referentially transparent inputs (RTIs), a simple, widely applicable methodology for validating machine translation software. A referentially transparent input is a piece of text that should have similar translations when used in different contexts. Our practical implementation, Purity, detects when this property is broken by a translation. To evaluate RTI, we use Purity to test Google Translate and Bing Microsoft Translator with 200 unlabeled sentences, which detected 123 and 142 erroneous translations with high precision (79.3% and 78.3%). The translation errors are diverse, including examples of under-translation, over-translation, word/phrase mistranslation, incorrect modification, and unclear logic.
Speaker Identification of Customer and Agent Using Aws

As everyone knows that Sentimental analysis plays an important role in these days because many start-ups have started with user-driven content [1]. Only finding the voice is not be the real time scenario so finding the Sentiment analysis of agent and customer separately is an important research area in natural language processing. Natural language processing has a wide range of applications like voice recognition, machine translation, product review, aspect-oriented product analysis, sentiment analysis and text classification etc [2]. This process will improve the business by analyze the emotions of the conversation with respect to the customer voice separately and also agent voice separately. In this project author going to perform speaker identification and analyze the sentiment of the customer and agent separately using Amazon Comprehend. Amazon Comprehend is a natural language processing (NLP) service that uses machine learning to extract the content of the voice. By using the speaker identification author can extract the unstructured data like images, voice etc separately so it is easy to analyze the business performance. Thus, will identify the emotions of the conversation and give the output whether the customer conversation is Positive, Negative, Neutral, or Mixed. To perform this author going to use some services from Aws due to some advantages like scaling the resources is easy compare to the normal process like doing physically such as support vector machine (SVM). AWS services like s3 is a object data store, Transcribe which generate the audio to text in raw format, Aws Glue is a ETL Service which will extract transform and load the data from the S3, Aws Comprehend is a NLP service used for finding sentiment of audio, Lambda is a server less where author can write a code, Aws Athena is a analyzing tools which will make complex queries in less time and last there is quick sight is a business intelligent tool where author can visualize the data of customers and also agents.
Real-time Simultaneous 3D Head Modeling and Facial Motion Capture with an RGB-D camera

We propose a method to build in real-time animated 3D head models using a consumer-grade RGB-D camera. Our proposed method is the first one to provide simultaneously comprehensive facial motion tracking and a detailed 3D model of the user's head. Anyone's head can be instantly reconstructed and his facial motion captured without requiring any training or pre-scanning. The user starts facing the camera with a neutral expression in the first frame, but is free to move, talk and change his face expression as he wills otherwise. The facial motion is captured using a blendshape animation model while geometric details are captured using a Deviation image mapped over the template mesh. We contribute with an efficient algorithm to grow and refine the deforming 3D model of the head on-the-fly and in real-time. We demonstrate robust and high-fidelity simultaneous facial motion capture and 3D head modeling results on a wide range of subjects with various head poses and facial expressions.
Graphic Technology in Computer Games at Internet Shop Pay for Teenage Impications

This paper discusses about graphic technology in computer games or gaming pc at internet stores with pay implications for adolescents. This paper will examine the existence of a paid internet store that has been offering fast broadband services accessible at the fingertips to surrounding communities. However, there are adolescents who misuse the services provided by accessing computer games with no restrictions, monitoring and escort. This paper will examine whether the adolescent driving factor that is still in school is willing to spend time, energy and invest money solely for enjoying the fun of computer games at a paid internet shop. In addition, paid internet shop dealers who offer dvd and vcd computer games with unlimited payment rates have attracted teenagers. Research on teenager’s attitude towards the influence of computer games. Examine how computer games affect youth health. Besides examining teenage obsessors on computer graphics technology to reality realms and teenage satisfaction exploring computer games at paid internet shops regardless of the surrounding community. Besides examining the negative implications of computer games on the quality of teenage education. Hence the lack of parent’s awareness of child supervision led to the spreading outbreak of school dropouts for being trapped by computer games during school days of fun with computer games at paid internet shops. This paper is obtained through field research such as observation, interviews and questionnaire with one hundred respondents involved in the study area. Through the documentation of the findings of this study can add further references to other researchers in the future.
Exploring Students’ Motivation and Vocabulary Achievement through Labeling Method

Motivation provides energies for students to decide efforts and they pursue it hardly. It is important to build students' motivation in learning English. Researcher's preliminary study toward the fourth grade of MIS Azzikir Kalialia in February 2019 indicated students' motivation was in the low category, while the result of the pre-test showed 35% of students did not achieve success standard in learning vocabulary. The objectives of the study is to explore how students are motivated by using labelling method and to improve students' vocabulary achievement by using labelling method. The number of the subject is 20 students. The instruments are the test, questionnaire, and observation under the Classroom Action Research method. After treatment, the questionnaire indicates students' motivation in high motivation and whole students achieve the standard of vocabulary achievement. Therefore, the labelling method promotes a way of English language teaching to build students' motivation and to improve vocabulary achievement in elementary grade.
Exploring EFL Learners’ Autonomy in Reading Comprehension: Computer-Assisted versus Conventional Contexts

This study explored the autonomy of advanced English as a Foreign Language (EFL) learners in reading comprehension through scaffolding and jigsaw in computer-assisted and conventional contexts. After being homogenized through the reading section of DIALANG proficiency test, a total of 80 female advanced EFL learners with the age range of 21 to 45 were selected as the participants of the study. They were randomly assigned to four groups: experimental group A (scaffolding in a conventional context), experimental group B (scaffolding in a computer-assisted context), experimental group C (jigsaw in a conventional context), and experimental group D (jigsaw in a computer-assisted context). Next, the autonomy in RC questionnaire, which was designed and piloted by Ebadi and Shirzad (in press), was administered as the pretest. Then, the learners in each group took part in three months (16 sessions) autonomy in reading comprehension training courses. After the treatment, the same autonomy in RC questionnaire was administered as the posttest. One-way ANCOVA was used to analyze the quantitative data. The results revealed that although both jigsaw and scaffolding approaches were successful in both conventional and computer assisted contexts from pre-test to post-test, the scaffolding method proved more effective. Moreover, both the scaffolding and jigsaw approaches were more effective in computer-assisted environment compared to conventional contexts, with the scaffolding CA approach outperforming the jigsaw CA technique. The findings’ implications for learners, teachers, and syllabus designers are discussed in both contexts.
LIO*: Low Level Information Flow Control in F*

We present Labeled Input Output in F* (LIO*), a verified framework that enforces information flow control (IFC) policies developed in F* and automatically extracted to C. Inspired by LIO, we encapsulated IFC policies into effects, but using F* we derived efficient, low level, and provably correct code. Concretely, runtime checks are lifted to static proof obligations, the developed code is automatically extracted to C and proved non-interferent using metaprogramming. We benchmarked our framework on three clients and observed up to 54% speedup when IFC runtime checks are proved statically. Our framework is designed to aid development of embedded devices where both enforcement of security policies and low level efficient code is critical.
THE QUESTION OF ORGANIZATION OF INFORMATION AND TECHNOLOGICAL COMPETENCE IN THE RESEARCH OF PSYCHOLOGISTS AND TEACHERS

The article reveals the features of the formation of information and technological competence in the psychological and pedagogical literature. The influence of information technologies on the formation of information technology competence is reflected
PENGARUH KONSEP DIRI DAN KEMANDIRIAN BELAJAR TERHADAP PRESTASI BELAJAR MATA PELAJARAN OTOMATISASI DAN TATA KELOLA KEUANGAN

ABSTRACT The research was to find out there is or not: 1) the effect of self concept towards learning achievement on automation and finance administration; 2) the effect of self-motivated learning towards learning achievement on automation and finance administration; 3) the effect of self concept and self-motivated learning towards learning achievement on automation and finance administration. This research used quantitative research with a correlational research design. The population in this research were all students of class XI Automation and Office Administration at SMK Negeri 1 Klaten in the academic year 2018/2019 which amounted to 108 students. The sample in this research taken with proportional random sampling technique which amounted to 84 students. Data source from teacher and students. The data collection technique used questionnaire and documentation. The data analysis technique used multiple linear regression analysis with the help of IBM SPSS 23.0 program. The result of research showed that 1) there was a significant positive effect of self concept toward learning achievement on automation and finance administraiton (t count = 4,4801, sign < 0,05); 2) there was a significant positive effect of self-motivated learning toward learning achievement on automation and finance administration (t count = 4,326, sign < 0,05); 3) there was a significant positive effect of self concept and self-motivated learning toward learning achievement on automation and finance administration (F count = 48,654 , sign < 0,05). This result of research showed the amount of effective contribution together equal to 54,6 % and the rest still 45,4% which effected by other variables which not entered in this research. Keywords: Self Concept, Self Motivated Learning and Learning Achievement of Automation and Finance Administration
Intelligent method to cryptocurrency price variation forecasting

Nowadays, accurate prediction of cryptocurrency price variation based on their important role in the world economy is an important and challenging issue. In this study, various parameters that affect the cryptocurrency value have been considered. For the first phase, four major price features of digital currencies have been analysed to determine the effect of each feature on the volatility prediction of future days. This study aims to understand and identify daily trends in the cryptocurrency market while gaining insight into optimal features surrounding their price. For the second phase, the price variation has been predicted with the highest possible accuracy with a new intelligent method. The proposed method consists of a neural network-based prediction algorithm and particle swarm optimisation. The obtained results show the capbility of the proposed method.
Quantum central limit theorem and statistical hypothesis testing in discrete quantum walk

Discrete quantum walk is one of the <i>de facto</i> models of quantum computation and as an efficient tool to develop quantum search algorithms. Although the theoretical model of quantum walks is straightforward, there are many complex scenarios such as coherence decay and/or decoherence in the implementations. It is hard to test experimentally if quantum walk works, or it just decays into a version of classic random walk. We propose a quantum central limit theorem (QCLT) for discrete quantum walks and conduct the statistical hypothesis testing for the standard or decayed walker probability distribution for imperfect quantum walks based on the QCLT. A reliable statistical analysis result is obtained for the imperfect distribution by the experimental quantum walk study.
Cyber Security Behaviour In Organisations

This review explores the academic and policy literature in the context of everyday cyber security in organisations. In so doing, it identifies four behavioural sets that influences how people practice cyber security. These are compliance with security policy, intergroup coordination and communication, phishing/email behaviour, and password behaviour. However, it is important to note that these are not exhaustive and they do not exist in isolation. In addition, the review explores the notion of security culture as an overarching theme that overlaps and frames the four behavioural sets. The aim of this review is therefore to provide a summary of the existing literature in the area of everyday cyber security within the social sciences, with a particular focus on organisational contexts. In doing so, it develops a series of suggestions for future research directions based on existing gaps in the literature. The review also includes a theoretical lens that will aid the understanding of existing studies and wider literatures. Where possible, the review makes recommendations for organisations in relation to everyday cyber security.
Ponarejena zdravila v teoriji in praksi

Counterfeit Medicines in Theory and Practice. Counterfeit medicines are a serious global issue triggering a clearly disparate response in different countries. Often, a question arises as to whether the general population is actually aware of the existence of counterfeit medicines, their consequences and the damage they cause. Statistical data and individual cases indicate that crime related to counterfeit medicines is increasing and that the investigation of such crime is complex and often transnational. Furthermore, it is strongly indicated that the profits are extremely high. The present monograph provides both theoretical and practical insights into this complex phenomenon. It offers solutions to certain issues regarding the detection and, investigation of such crimes, as well as the taking of evidence. The prevention of counterfeiting medicines is also presented and discussed in several chapters. The main aim of this monograph is to highlight the importance of raising awareness about the issue of counterfeit medicines.
Audio Covering Signal For Speech Signal Hiding

The demands for exchange secret information among many institutions simulate the rapid development of new strategies. Steganography is a well-known method for hiding data from not permitted access. One of the Steganographic techniques is to hide secret data in one of the file formats such as image, text, audio. In this paper, a steganography technique based on the energy of the audio signal that is used to hide a speech signal is presented. The objective is to examine the effect of the energy parameter in hiding the speech signal within an audio signal without being perceptible by the listener. A technique is to test the different level of energies and durations of both the source and the cover signal. Experimental results show that, in the case of cleaned signals, the technique performing well in the case when the duration of the cover signal is much longer than the duration of the source signal, i.e. the much rooms for the source signal to hide the better performance. Also, the results show that the additive noise can have a tremendous negative impact on system performance.
Robust testing of low-dimensional functions

A natural problem in high-dimensional inference is to decide if a classifier $f:\mathbb{R}^n \rightarrow \{-1,1\}$ depends on a small number of linear directions of its input data. Call a function $g: \mathbb{R}^n \rightarrow \{-1,1\}$, a linear $k$-junta if it is completely determined by some $k$-dimensional subspace of the input space. A recent work of the authors showed that linear $k$-juntas are testable. Thus there exists an algorithm to distinguish between: 1. $f: \mathbb{R}^n \rightarrow \{-1,1\}$ which is a linear $k$-junta with surface area $s$, 2. $f$ is $\epsilon$-far from any linear $k$-junta with surface area $(1+\epsilon)s$, where the query complexity of the algorithm is independent of the ambient dimension $n$. Following the surge of interest in noise-tolerant property testing, in this paper we prove a noise-tolerant (or robust) version of this result. Namely, we give an algorithm which given any $c>0$, $\epsilon>0$, distinguishes between 1. $f: \mathbb{R}^n \rightarrow \{-1,1\}$ has correlation at least $c$ with some linear $k$-junta with surface area $s$. 2. $f$ has correlation at most $c-\epsilon$ with any linear $k$-junta with surface area at most $s$. The query complexity of our tester is $k^{\mathsf{poly}(s/\epsilon)}$. Using our techniques, we also obtain a fully noise tolerant tester with the same query complexity for any class $\mathcal{C}$ of linear $k$-juntas with surface area bounded by $s$. As a consequence, we obtain a fully noise tolerant tester with query complexity $k^{O(\mathsf{poly}(\log k/\epsilon))}$ for the class of intersection of $k$-halfspaces (for constant $k$) over the Gaussian space. Our query complexity is independent of the ambient dimension $n$. Previously, no non-trivial noise tolerant testers were known even for a single halfspace.
Art as an object of expert activity

This article puts to the forefront the problem of unbiased and objective assessment of artworks by the expert community, analysis of the priority criteria of such assessment and chains of perception of professional works of art by the representatives of expert groups. The author leans on the fact that the expert community in the field of art may be defined as a category of professionals possessing extensive knowledge and erudition in the sphere of culture and art, attracted for conducting expertise on the contemporary artworks and cultural heritage of the past centuries. It is underlinesd that the problematic aspect of expert communities in the field of arts is the substantial disaccord of emotional and visual-imager perception different for assessing the works from the perspective of aesthetics, and demand to act by the rules, patterns and methods. The author also points out that the expert community in their practical activity should be guided by realization of the essential rules, laws, formulas, as well as see the zones for their implementation.
Study on Recent Methods of Secure Provable Multi-block Level Data Possession in Distributed Cloud Servers Using Cloud-MapReduce Method

Cloud computing is a developing computing worldview that empowers users to remotely store their data on a cloud in order to appreciate versatile services on-request. It has been discovered that keeping up the security of data from an unapproved user is extremely a noteworthy test. This is a noteworthy worry because data are re-distributed to keep storage at third parties—stated as cloud specialist co-ops. It is especially fundamental to utilize promising strategy that performs encryption on such data before it really get re-appropriate to the third parties. Other than this, other key issues like successful client disavowal and scalability in key administration must need to get addressed while achieving fine grained and flexible access control to cloud storage.