Reviewerly/exHarmony huggingface dataset:
Compiling Control as Offline Partial Deduction

We present a new approach to a technique known as compiling control, whose aim is to compile away special mechanisms for non-standard atom selection in logic programs. It has previously been conjectured that compiling control could be implemented as an instance of the first Futamura projection, in which an interpreter is specialized for an input program. However, the exact nature of such an interpreter and of the required technique for specialization were never specified. In this work, we propose a Prolog meta-interpreter which applies the desired non-standard selection rule and which is amenable to specialization using offline partial deduction. After the initial analysis phase of compiling control, we collect annotations to specialize the interpreter using the Logen system for offline partial deduction. We also show that the result of the specialization is equivalent to the program obtained using the traditional approach to compiling control. In this way, we simplify the synthesis step.
ENGAGEMENT FOR LEARNERS WITH MULTIPLE INTELLIGENCE USING LOCATION-BASED TECHNOLOGY

Appears in: EDULEARN19 Proceedings Publication year: 2019Pages: 1484-1488ISBN: 978-84-09-12031-4ISSN: 2340-1117doi: 10.21125/edulearn.2019.0447Conference name: 11th International Conference on Education and New Learning TechnologiesDates: 1-3 July, 2019Location: Palma, Spain
Counting points on hyperelliptic curves of type y2 = x2+1 + ax+1 + bx

In this work, we investigate hyperelliptic curves of type C:y2=x2g+1+axg+1+bx over the finite field Fq,q=pn,p>2. For the case of g=3 we propose an algorithm to compute the number of points on the Jacobian of the curve with complexity O˜(log4⁡p) over Fp. In case of g=4 we present a point counting algorithm with complexity O˜(log8⁡q) over Fq. The Jacobian JC splits over an extension of the field Fq on the Jacobians of the curves defined by the Dickson polynomials Dg(x,1) of degree g. For these curves of genus 2,3,5 with equation y2=Dg(x,1)+a and curves of genus 2,4 with equation y2=(x+2)(Dg(x,1)+a), we give the lists of possible characteristic polynomials of the Frobenius endomorphism modulo p.
Preventing Privacy Disclosure from Hostility Attack Base on Associated Attributes

Due to frequent occurrences of user privacy leaking incidents, individuals and businesses are also increasingly concerned about privacy issues. The ε-differential privacy and the refinement of k-anonymity are two popular privacy protection models. However, both of them have their own disadvantages. In order to take advantage of their advantages and avoid their disadvantages, we propose an (l, α)-diversity model to implement privacy protection data publishing. Our method uses sampling to make the data to be published first meet the ε-differential privacy, and then we use mutual information to find the most accurate quasi-identifier attributes associated with sensitive attributes before anonymizing them. After that, we use the generalization method to make the published data set satisfy the (l, α)-diversity model. Experimental results show that our privacy-preserving model is effective, and the algorithm is highly efficient.
Implementation of NN Algorithm Based on the MapReduce Framework

For the nearest neighbor algorithm cannot adapt to the problem of the large case library. How to implement it using MapReduce framework was studied. Map function receive initial data to calculate the similarity value of the case. Reduce function select the largest case of similarity according to the Map function results. The MapReduce framework solves the problem through parallel distributed computing. The typical control system was simulated by the NN algorithm case library. The experiment retrieve the cases on Hadoop based on the traditional method and the MapReduce framework. The searching speed of NN algorithm based on the MapReduce framework is more than 10 times faster than the traditional method. The speedup improve a lot. The accuracy raise 12%–14%.
Introduction to Data Science as a Pathway to Further Study in Computing

Several institutions have recently introduced Introduction to Data Science courses that involve a substantial programming component and do not require CS1 as a prerequisite. Programming and computational thinking are central to the emerging discipline of data science, and so there is overlap between traditional CS1 courses and Introduction to DS.
Video Interactive Captioning with Human Prompts

Video captioning aims at generating a proper sentence to describe the video content. As a video often includes rich visual content and semantic details, different people may be interested in different views. Thus the generated sentence always fails to meet the ad hoc expectations. In this paper, we make a new attempt that, we launch a round of interaction between a human and a captioning agent. After generating an initial caption, the agent asks for a short prompt from the human as a clue of his expectation. Then, based on the prompt, the agent could generate a more accurate caption. We name this process a new task of video interactive captioning (ViCap). Taking a video and an initial caption as input, we devise the ViCap agent which consists of a video encoder, an initial caption encoder, and a refined caption generator. We show that the ViCap can be trained via a full supervision (with ground-truth) way or a weak supervision (with only prompts) way. For the evaluation of ViCap, we first extend the MSRVTT with interaction ground-truth. Experimental results not only show the prompts can help generate more accurate captions, but also demonstrate the good performance of the proposed method.
Practical Teaching System of Electronic Information Engineering Major Based on Cultivation of Innovative and Entrepreneurial Ability

As the basic ability of engineering graduates, the ability of practice and innovation plays an important role in improving the level of scientific and technological innovation in China and enhancing the international competitiveness. On the basis of expounding the current situation of the practical teaching of electronic information major under the guidance of the thought of cultivating innovative and entrepreneurial ability, combining the characteristics of electronic information engineering major, and according to the system frame of “four-dimensional integration”, the paper discussed reform thinking of the practical teaching system in local colleges and universities from four dimensions, including teacher-student, school-enterprise, theory-practice and mechanism-environment, so that to form the practice group of “electronic product design”, “embedded system software development”, “signal processing algorithm and realization”, and to perfect the practice teaching system of innovation and entrepreneurship of electronic information engineering major.
An Improved Artificial Potential Field Method for Path Planning of Mobile Robot with Subgoal Adaptive Selection

As a simple and effective method, artificial potential field method is often used in robot path planning. Based on this, an improved artificial potential field model is proposed to solve the local minimum problem by using a subgoal strategy. In order to show the subgoal adaptive selection feature of the robot, an obstacle potential field function is established and the effectiveness of the adaptive feature is verified by path planning simulation. A double closed-loop control strategy is adopted to track the trajectory planned by the improved artificial potential field method, and simulation results show that the improved artificial potential method is reliable and the robot can well track the trajectory under the action of the controller.
IDEAS HAVE THEIR OWN LIFE

The problem of the psyche and consciousness has been the most mysterious one for a few thousand years and is still unresolved. It has been almost forgotten that Aristotle considered human psyche a structure that is not bound to the body. This idea did not persist, though. It was Hippocrates who ruined it and declared a different concept, which prevailed for many centuries, that the brain is a repository of all mental processes. The author formulates the idea of the brain as the biological interface and proves a non-material theory of the psyche, which is a discovery that requires a change in basic paradigms of human sciences.
Design of Safety Production Supervision and Data Management System Based on Cloud Platform

Safety production refers to the accident prevention and control measures in the production and operation activities, in order to avoid causing personnel injury and property damage accident. This paper firstly analyzes the performance and function of safety production supervision and management system, and points out the problems existing in the existing security supervision and management system. Big data analysis technology is an effective way to solve these problems and can be timely and accurate detection of hidden dangers, improve the ability of the investigation and management. This paper presents design of safety production supervision and data management system based on cloud platform. The system is the unified support system platform based on cloud computing and intelligent terminal technology, and can improve the efficiency of data collection and realize the prediction and early warning of the real by big data technology.
Fuzzy-GRA Trust Model for Cloud Risk Management

Cloud computing is not adequately secure due to the currently used traditional trust methods such as global trust model and local trust model. These are prone to security vulnerabilities. This paper introduces a trust model based on the fuzzy mathematics and gray relational theory. Fuzzy mathematics and gray relational analysis (Fuzzy-GRA) aims to improve the poor dynamic adaptability of cloud computing. Fuzzy-GRA platform is used to test and validate the behavior of the model. Furthermore, our proposed model is compared to other known models. Based on the experimental results, we prove that our model has the edge over other existing models.
Data Quality Problems Identified in the Bioclimatic Data Collection Process - A Survey

Bioclimatic data support several researches that aim to identify the influence of climatic factors on biodiversity on the planet. In order to make these studies possible, the quality of the data that supports the analyzes must be guaranteed from the beginning of the data life cycle so that the results and models generated reflect the real scenario of the investigated phenomena. However, the collection of climate and biodiversity data presents significant challenges. This work performs a survey of the main quality problems identified in the bioclimatic data collection process. The methodological procedure consisted in identifying the problems, assigning the data quality dimension affected, and suggestions for possible solutions to the problems. The results of this survey showed that ambiguous methodological procedures during the data gathering and human interference are important factors for data quality impairment and the information obtained from these data. Thus, the correction of the data should focus on the collection processes and procedures, not the raw data itself.
Design of a Master-Slave Composite Wall Climbing Robot System for Penstock Assembly Welding

Nowadays, the penstock assembly welding of hydroelectric power stations is carried out by manual arc welding. In order to improve the working environment and raise the welding efficiency, this paper proposed a master-slave composite wall-climbing robot system based on gapped permanent magnet adhesion. With the master-slave composite design idea, the payloads of welding robot are shared and the flexibility and stability of the robot are improved. As a key mechanism of wall-climbing robot, the design and layout of the permanent magnetic adhesion module is studied. According to the result of static analysis and dynamic analysis of the welding robot, an optimized layout for adhesion module design is found. A Prototype of the robot system is built and experiments on the adhesion ability and motion ability of the robot system are carried out.
Learning English Motivation By Students of SMK UISU Medan

This research is aimed to determine the type of motivation and factors that influence&#x0D; the motivation of the students of SMK UISU Medan. The sample of this study is all&#x0D; students of SMK UISU Medan. The total respondents in the sample are 52 students&#x0D; from first grade, second grade, and third grade of the school. This researach uses&#x0D; mixed method so that the data will be analyzed quantitatively and qualitatively using&#x0D; Likert scale. The instruments used in this reseaarch are questionnaire and interview.&#x0D; Therefore, the data are collected by sharing questionnaire and conducting. The&#x0D; research finds that the motivation most possessed by the respondents is instrumental&#x0D; motivation, furthermore, teacher’s factor is the main factor that influences student&#x0D; motivation in learning English.
A Feature Point Extraction and Comparison Method Through Representative Frame Extraction and Distortion Correction for 360° Realistic Contents

360° realistic contents are omnidirectional media contents that support front, back, left, right, top and bottom. In addition, they are combined images of images produced using two or more cameras through the stitching process. Therefore 4K UHD is basically supported to represent all directions and distortion occurs in each direction, especially above and below. In this paper, we propose a feature point extraction and similarity comparison method for 360° realistic images by extracting representative frames and correcting distortions. In the proposed method, distortion-less parts for an extracted frame such as the front, back, left, and right directions of the image, except for the largest distortion area such as the up and down directions, are first corrected by a rectangular coordinate system method. Then, the sequence for the similar frames is classified and the representative frame is selected. The feature points are extracted from the selected representative frames by the distortion correction and the similarity can be compared in the subsequent query images. The proposed method is shown, through the experiments, to be superior in speed for the image comparison than other methods, and it is also advantageous when the data to be stored in the server increase in the future.
The fate of the Littlest Higgs with T-parity under 13 TeV LHC data

Little Higgs models - which can most easily be thought of as a variant of composite Higgs models - explain a light Higgs boson at 125 GeV as an pseudo-Nambu-Goldstone boson of a spontaneously broken global symmetry. The mechanism of collective symmetry breaking shifts the UV scale of these models to the 10 TeV scale and higher. T-parity is introduced as a discrete symmetry to remove tree-level constraints on the electroweak precision data. Still after run 1 of LHC, electroweak precision observables gave stronger constraints than Higgs data and direct searches. We present a full recast of all available 13 TeV searches from LHC run 2 to show that now direct searches supersede electroweak precision observables. The latest exclusion limits on the LHT model will be presented, as well as an outlookon the full high-luminosity phase of LHC.
Building Sentimental Word Lexicon for Chinese Movie Comments

Establishing domain-specific sentiment lexicon based on film comments is difficult. To solve this problem, this paper proposes a method based on point mutual information to construct a film sentiment lexicon, and constructs a film evaluation sentiment lexicon to improve the accuracy of the film evaluation sentiment analysis. Firstly, K-means++ clustering is used to select positive and negative seed word sets with obvious sentimental tendency; Then, using the point mutual information (PMI) algorithm to calculate the semantic similarity between the field words and the seed words; Finally get the sentimental vocabulary in the field of film evaluation. The experimental results show that the film evaluation sentiment lexicon constructed in this paper can significantly improve the accuracy of Chinese film evaluation sentiment analysis.
Practical Implementation of a Quantum Algorithm for the Solution of Systems of Linear Systems of Equations

With the rapid development of Quantum Computers (QC) and QC Simulators, there will be an increased demand for functioning Quantum Algorithms in the near future. Some of the most ubiquitously useful algorithms are solvers for linear systems of equations. Since the conception of the Quantum Linear Solver Algorithm (QLSA) by Harrow, Hassidim and Lloyd (HHL) in 2009, many improvements have been made, although a generic implementation for arbitrary matrices and vectors is still not available. In this thesis a variant of the HHL QLSA is studied, and the open challenges are investigated. Solutions for two of the challenges, namely the Eigenvalue Inversion subroutine and the Higher-Order Ancilla Rotation subroutine, are discussed. As part of the thesis project, these subroutines have been implemented in the QX Quantum Computer Simulator, and the subroutines are combined to form a complete Quantum Linear Solver (QLS), with the restraint that the implementation for the vector and Hamiltonian of the matrix must be provided by the user. A proof-of-concept QLS by Cao et al. is also implemented in the QX simulator, and using the implementation of the vector and Hamiltonian of Cao et al. the complete solver is tested. In the process of this thesis, a framework for basic Quantum Arithmetic is built providing three variants of Integer Adders, two variants of Integer Subtracters, one Integer Multiplier and one Integer Divider. In addition, gates not natively available in the QX simulator are implemented, and a number of improvements and extensions of algorithms presented in the literature are given, making the described algorithms function on the QX simulator and extending features.
Affective Design of a Tailor Made Product Led by Insights from Big Data

How to explore precisely the affective demand of customers is an important area of research for the designers. Here we address this challenge by collecting the online comments of customers as big data, and applying the Software Kismet Affective Engine to perform the semantic cluster analysis of the big data. The design elements of a tailor made product is analyzed and associated with the affective elements of the customers. The key words of design elements and effective elements would be used to build the frame of the affective design data bank. The methods and results of this study could be very important and helpful for the market consultancy and can be extended in many other design areas as well. Especially, the affective elements with high positive valence would be extremely important to enlighten and educate the designers.
Research on Development Status and Trend of Measurement of Highway Engineering Inspection Equipment

Based on the analysis of the current situation of measurement and management of highway engineering testing equipment, the measurement system of highway engineering professional instruments has been initially formed. In order to further guarantee the quality of highway engineering testing, this paper puts forward some suggestions on the traceability and management of measurement instruments throughout their life cycle Introduction.
A Systematic Mapping on Visual Solutions to Support the Comprehension of Software Architecture Evolution

Context: Software visualization has the potential to support specialized stakeholders to understand the software architecture (SA) evolution.To the best of our knowledge, there is no guideline based on which visual solutions should be applied to support the SA evolution comprehension and how to use them.Goal: Analyze the use of visual solutions for the purpose of comprehension with respect to software architecture evolution from the point of view of software architects and developers in the context of both academia and industry.Method: We conducted a Systematic Mapping Study to achieve the stated goal.Results: The study identified 92 papers published from January 2000 to December 2018 as a result of the search strings execution.We selected 12 primary studies and identified a gap in terms of a taxonomy to assist specialists in the development or classification of solutions to support the comprehension of software architecture evolution using visual resources.Conclusion: We observed that despite the relevance of the use of visual solutions to support the comprehension of software architecture evolution, only 12 studies have reported these initiatives, suggesting that there is still room for the use of different visual metaphors to represent its components, relationships and evolution throughout the releases.
Pricing Interval European Option with the Principle of Maximum Entropy

This paper develops the interval maximum entropy model for the interval European option valuation by estimating an underlying asset distribution. The refined solution for the model is obtained by the Lagrange multiplier. The particle swarm optimization algorithm is applied to calculate the density function of the underlying asset, which can be utilized to price the Shanghai Stock Exchange (SSE) 50 Exchange Trades Funds (ETF) option of China and the Boeing stock option of the United States. Results show that maximum entropy distribution provides precise estimations for the underlying asset of interval number situations. In this way, we can get the distribution of the underlying assets and apply it to the interval European option pricing in the financial market.
An Experimental Evaluation of a Teaching Approach for Statistical Process Control for Software Engineers: An Experimental Study

The purpose of this research study is to identify Statistical Process Control methods and their importance for the current software industry. Statistical Process Control is a set of techniques employed for achieving a stable and repeatable process. In organizations that are seeking a high degree of maturity, it is necessary to achieve a statistical control of software processes and to know their behavior and operational performance. However, the use of these techniques by software development organizations has proved to be complex. The approach adopted for the teaching approach involves reading articles and experience performance reports, practical cases, discussion, the use of games and simulators, practical projects and reflection by students on the knowledge learned and activities carried out. In this context, it is expected that the students will feel a greater degree of motivation and reach more advanced levels of learning by being involved in a more playful and practical class atmosphere that simulates the environments encountered in industry. The experiment was conducted with undergraduates enrolled in a Computer Science Bachelor's degree programe, who were divided into a “control group” and an “experimental group”. At the end, the two groups carried out a practical project to evaluate the level of learning reached by the students. The results of the study suggest that there was a difference in the effectiveness of the learning resulting from the teaching approach and traditional instruction. We observed a mean gain of 30.06% in the experimental group, which is evidence of this rise in the learning effectiveness.