Reviewerly/exHarmony huggingface dataset:
Research modelling in civil engineering master'S theses

There are five consecutive stages identified in the Civil Engineering learning process (Vocational school or College programme, Bachelor's or Specialist's programme, programme, Junior Doctorate or Junior Doctorate Military programme, Higher Doctorate programme). Each stage is completed with a qualifying parer that students or degree seekers must defended at public examinations. For the first two stages it is a diploma, and for the rest – a thesis. A transition to a subsequent educational stage envisages a higher level of theoretical development of the problem under study, independence in choosing research topic, justification of means and methods for solving research problems, and personal responsibility for the quality of the research results. Bachelor's programme is understood as an abridged version of traditionally existed Specialist's programme, and programme is completely innovative for Russia. The ways of eliminating the educational lacuna of programme in the Russian Federation have not yet been fully studied, the methodological approaches to the teaching technologies and to the form of completion of programme remain controversial. Directive documents of the Ministry of Education name in parallel the student's final paper both Master's thesis (by analogy with foreign traditions) and Graduation qualification work (by analogy with the traditional practice of the national educational process).
CONTENT AND LANGUAGE INTEGRATED LEARNING IN TASKS OF PROGRAMMING BY CHILDREN

Content-language integrated learning (CLIL) is becoming anincreasingly popular learning format today, this combined approach can greatly savelearning time, while not lowering the quality of learning. At the same time, there areno age restrictions in this approach; it can be applied to both the children's audienceand the young and adult generations. This will be discussed in this work, the authorof the work will propose a combined format for learning a foreign language andprogramming.
Formation of a System of Values as the Basis of Spiritual and Moral Education of Teenagers

The paper analyzes the means of forming intangible values among adolescents at the age of 14 to 18 years. In this regard, special attention is paid to the content of the concept of “value” and the peculiari-ties of its interpretation by scientists in the field of philosophy, psychology and pedagogy. The role of the teacher, the environment, and the family in the formation of axiological priorities in adolescents is established. At the same time, their influence on the spiritual and moral sphere of children is carried out both separately and comprehensively from the per-spective of a single and consistent system of educa-tion. It is noted that fine arts have highly effective means for influencing teenagers’ picture of the world of values. In particular, the author emphasizes the relevance of using modern media tools, the In-ternet and social networks in the system of addi-tional education, which provide teenagers with the opportunity for self-realization and self-improvement. It is argued that the use of technolog-ical progress in the organization of fine arts signifi-cantly increases their effectiveness and contributes to the achievement of creative and educational goals and objectives, including the formation of a system of adolescents’ spiritual and moral values.
A new literature search model for multi data objective programming

Abstract Aiming at the problem that the current literature search algorithms only provide literature clues and original texts, which can not realize the analysis and evaluation, it is the formal comparison and cannot compare the actual contents of new papers and existing literatures; the objective programming target algorithm is introduced to calculate the “copy ratio” of the substantive content by minimizing the deviation between the objective function and the target value; small sample verification is carried out It is feasible and can open up a new idea for the upgrading of literature search tools.
Self-supervised Learning for Pairwise Data Refinement

Pairwise data automatically constructed from weakly supervised signals has been widely used for training deep learning models. Pairwise datasets such as parallel texts can have uneven quality levels overall, but usually contain data subsets that are more useful as learning examples. We present two methods to refine data that are aimed to obtain that kind of subsets in a self-supervised way. Our methods are based on iteratively training dual-encoder models to compute similarity scores. We evaluate our methods on de-noising parallel texts and training neural machine translation models. We find that: (i) The self-supervised refinement achieves most machine translation gains in the first iteration, but following iterations further improve its intrinsic evaluation. (ii) Machine translations can improve the de-noising performance when combined with selection steps. (iii) Our methods are able to reach the performance of a supervised method. Being entirely self-supervised, our methods are well-suited to handle pairwise data without the need of prior knowledge or human annotations.
RP-Rewriter: An Optimized Rewriter for Large Terms in ACL2.

RP-Rewriter (Retain-Property) is a verified clause processor that can use some of the existing ACL2 rewrite rules to prove conjectures through term rewriting. Optimized for conjectures that can expand into large terms, the rewriter tries to mimic some of the ACL2 rewriting heuristics but also adds some extra features. It can attach side-conditions to terms that help the rewriter retain properties about them and prevent possibly some very expensive backchaining. The rewriter supports user-defined complex meta rules that can return a special structure to prevent redundant rewriting. Additionally, it can store fast alists even when values are not quoted. RP-Rewriter is utilized for two applications, multiplier design proofs and SVEX simplification, which involve very large terms.
PERAWATAN SISTEM PENDINGIN MESIN DIESEL PADA WHELL LOADER KOMATSU WA120-3CS

The purpose of this study was to determine how to maintain the cooling system of a diesel engine on the Komatsu WA120-3C Whell Loader. This research was conducted in the Implementation of Public Works Agency Yogyakarta. How to collect data using interviews, observation, and documentation. Data analysis uses descriptive qualitative analysis. The results showed that the maintenance of the cooling system on the diesel engine on the Komatsu WA120-3C Whell Loader had run well and had followed the operational standards contained in the manual book. The maintenance performed on the cooling machine includes water pump maintenance, radiator system maintenance, intercooler maintenance, fan maintenance, radiator hose maintenance, radiator pressure cap maintenance.
ПЕДАГОГИЧЕСКОЕ ПРОЕКТИРОВАНИЕ И ЕГО ОСОБЕННОСТИ

The article deals with the concept of «pedagogical design» from different sides. It gives answers to the questions: what is it, and what is its essence and content? The objects of pedagogical design are characterized, its basic principles are given, the most significant conditions of the organization of process of design are highlighted. This article also describes in detail the three stages of the pedagogical process design: modeling, design and construction. The main levels of research work of students in the design of the educational process are stressed. This article shows what can be an object for pedagogical design: pedagogical systems, pedagogical process, pedagogical situations. It gives the definition for forms of pedagogical design, for concept as one of design forms, shows the function of that concept. It describes forms of a lesson design: plan, notes and teacher handbooks.
Research on data access security agent technology in cloud computing security

Abstract Cloud computing is a new application model, with multi-tenant, flexible, fast and easy to scale features, it can significantly reduce operating costs and improve operational efficiency. Cloud computing has received extensive attention from the business community and academia. With the continuous development of cloud computing technology, security and privacy issues have become the biggest obstacles to cloud computing applications. This paper first introduces the main problems faced by access control in the cloud environment, then researches and analyzes the cloud access security agent technology in terms of functional role and key technologies, and predicts the future challenges of the cloud access security agent technology based on the analysis of existing technologies.
Study of Score Coefficient Functions for DBSCAN-based Photometric Invariant Approach in Vision Sensor-Based Shoe Detection for Human Tracking

The problems of accurately tracking people in human-robot co-existing environments are considered as one of the significant problems in present times. A state-of-the-art randomized template matching algorithm, called photometric- invariant CFAsT-Match (PICFAsT-Match), can be implemented in real robot to solve an active problem within this genre, where vision sensing is used for detecting human shoes in challenging real-life environments, during pursuit. The performance of the PICFAsT-match depends on suitable choices of a parameter, named score coefficient. In this chapter, a detailed study on possible choices of the variations of the score-coefficient parameter is performed, and the overall impacts of the chosen variations on the shoe detection outcomes are evaluated.
Context Analysis Using a Bayesian Normal Graph.

Contextual information can be used to help object detection in video and images, or to categorize text. In this work we demonstrate how the Latent Variable Model, expressed as a Factor Graph in Reduced Normal Form, can manage contextual information to support a scene understanding task. In an unsupervised scenario our model learns how various objects can coexist, by associating object variables to a latent Bayesian cluster. The model, that is implemented using probabilistic message propagation, can be used to correct or to assign labels to new images.
A Visual Monitoring Method for Infants in a Room

We propose a method for detecting pre-accident situations of infants (preschool children) in a room. Unforeseen accidents among infants mainly occur in relation to objects in the room, e.g., falls from chairs, burns caused by heaters, accidental ingestion. Accordingly, the proposed method recognizes the states (positions, postures, and movements) of each infant in the room from a video image, determines the relations between the infant and specified objects (places) by referring to a room model, and then detects pre-accident situations of the infant, such as approaching dangerous areas, getting off balance at critical places, and touching unsafe objects.
Parametric Analysis of Autopilot Intelligent Robot (PIR) Using Multiple Surface Gradient Path MSGP

Robotic application is taking new dimensions around the globe, of which numerous problems are solved with embedded systems, this research introduces gradient vertices method from 3D geometric to perform data capturing using kinematic effect with aid of autopilot Intelligent Robotic (PIR). The research considered Multiple Surface Gradient Path MSGP using Toyota Camry 200x chases model using DC motor Pulse Wide Modulation (PMW). The discretion only Multiple Surface Gradients, distance values and angular pivots with respect to time. The PIR hardware “Raspberry Pi 3B” as the target board is interface with modular peripherals, using python programming language. Auto pilot is archived using different surface gradients and the digital images obtained during experience are stored for further analysis. The use of Tkinter GUI improved user experience in the extermination of the periodic oscillation, gradient values, proximate distance obtained by the PIR Final implementation. The deployment is completed by improvising a prototype model (PIR) suitable for Toyota Camry 200x. It is important to view it in the context of a larger community policing framework. PIR can be classified as intermission robot that can be used for different activities with the available feature kinematic system which make it relevant for multi-purpose activities.
Improved algorithm of decision tree based on neural network

Abstract Decision trees have been applied to solve many data mining problems due to their superior learning and classification capabilities, and have achieved good results. However, for dealing with big data and complex model problems, decision trees show insufficient accuracy and overfitting. In order to solve these problems, neural network is introduced as a decision tree node, and an improved algorithm based on neural network decision tree is proposed. In the neural network decision tree, the classifier learning consists of two stages: the first stage uses a heuristic algorithm with reduced uncertainty to divide the big data, and stops the growth of the decision tree until the node dividing ability is below a certain threshold; in the second stage, the neural network is used to classify the decision-making leaf node with generalization ability. The experimental results show that compared with the traditional classification learning algorithm, the algorithm has a higher accuracy rate and it can determine the size of decision tree through structural adaptation for the classification problem of identifying big data and complex patterns.
Quantum Search Algorithm and Its Applications

Because in IBM’s quantum computers, they only provide quantum gates of single quantum bit and two quantum bits, quantum gates of three quantum bits and many quantum bits must manually be decomposed into quantum gates of single quantum bit and two quantum bits. A good quantum algorithmQuantum algorithm of solving any given problem with the size of the input of n bits must have a constant successful probability of measuring its answer(s) that is close to one as soon as possible. In this chapter, we first illustrate how to decompose quantum gates of three quantum bits and many quantum bits into quantum gates of single quantum bit and two quantum bits. Next, we introduce how to write quantum programs with version 2.0 of Open QASM to implement decomposition among various kinds of quantum gates. A quantum search algorithmQuantum search algorithm that is sometimes known as Grover’s algorithm to find an item in unsorted databasesUnsorted databases with 2n items that satisfies any given condition can give a quadratic speed-up and is the best one known. Hence, we then describe how to write quantum programs with version 2.0 of Open QASM to implement the quantum search algorithm in order to solve various applications.
Quantum Data Processing

This chapter covers the topic of quantum data processing (see Figure 10-1). You will see how quantum data processing algorithms are implemented in day-to-day life. Code examples are presented for algorithms such as k-means, k-medians, and quantum clustering.
Quality Analysis Of Logistics Management Information System Software Using MCALL: Quality Analysis Of Logistics Management Information System Software Using MCALL

The development of information technology is so rapid to make the needs of technology increase. The progress of an organization depends on the information technology used. But in using an information technology must be concerned with the quality of information technology used. Software testing is one of the most important things in determining software quality. This research was conducted to determine the quality of the Logistics Management Information System software that has been used at the Bandung Institute of Technology. This test uses the McCall model framework in which the quality factor variables tested are correctness, reliability, efficiency, integrity, usability, maintainability, flexibility, testability, portability, reusability and interoperability. The data collection method used is the observation method used for information gathering by directly observing the activities of the research object environment and the interview method used to collect data regarding information on Logistics Management Information System software through interviews with several employees who understand the Information System system. Logistics Management. Based on the results of research that has been done there are still some shortcomings including the factors of reliability, efficiency, usability and interopability. While the factors of correctness, maintainability, flexibility, testability, portability and reusability have met the software quality factors and organizational needs.
(Invited) Scanning Microscopic Light Scattering with Machine Learning for Quality Assurance of 3D-Printed Hydrogels

Scanning microscopic light scattering (SMILS) is a powerful tool for the characterization of soft and wet matter, including polymer gels, polymer solutions, and the dispersion of nanometer particles. Specially the SMILS has a special advantage to overcome the inhomogenities of the soft and wet matter. For example, the network structure of polymer gels is so stable that the inhomogenities due to the fluctuation under the formation of chemical reaction, i.e. gelation, tends to be fixed in the network structure. This kind of the static inhomogeneites causes the position dependence of the observation of the polymer gels in the experiment of light scattering. The SMILS is able to scan the sample of the soft and wet matter and observes many data in different positions in the same sample to obtain the space-averaged data of the time-averaged correlation functions of scattered photons. Then the SMILS determine the ensemble-averaged correlation function. However, through the actual experiences of the SMILS experiments, we knew that the set of many data in different positions has several bad data due to dust, stray light, and mechanical vibration. By thinning the set of data to remove the bad data, the net result of the ensemble-averaged correlation function tends to improve very well. In the previous studies, we sometimes obtained the 30-100 data in different positions and thinned out the data to remove the 1-70% based on the judgement of the observer. There is a problem that the thinned data may depend on the observer. To overcome this problem, we tried to apply machine learning for the SMILS experiments. In the machine-learning procedure, artificial intelligence was made to learn the thinning operation of the observer as a teacher so that the same thinning operation as the observer could be performed. The below-shown figure shows one of the results of this procedure. It is shown that the raw ensemble-averaged correlation function has the ambiguous four peaks of relaxation modes. However the thinned correlation function by the machine-learning procedure will improve and show only one nice-seeming peak. We will exam the reliability of this novel automation procedure especially for the 3D-printed hydrogel samples and will establish the novel AI-aimed SMILS system to be applied for quality assurance of 3D-printed hydrogels in near future. Figure 1
Botcha: Detecting Malicious Non-Human Traffic in the Wild.

Malicious bots make up about a quarter of all traffic on the web, and degrade the performance of personalization and recommendation algorithms that operate on e-commerce sites. Positive-Unlabeled learning (PU learning) provides the ability to train a binary classifier using only positive (P) and unlabeled (U) instances. The unlabeled data comprises of both positive and negative classes. It is possible to find labels for strict subsets of non-malicious actors, e.g., the assumption that only humans purchase during web sessions, or clear CAPTCHAs. However, finding signals of malicious behavior is almost impossible due to the ever-evolving and adversarial nature of bots. Such a set-up naturally lends itself to PU learning. Unfortunately, standard PU learning approaches assume that the labeled set of positives are a random sample of all positives, this is unlikely to hold in practice. In this work, we propose two modifications to PU learning that make it more robust to violations of the selected-completely-at-random assumption, leading to a system that can filter out malicious bots. In one public and one proprietary dataset, we show that proposed approaches are better at identifying humans in web data than standard PU learning methods.
THE USE OF GUESSING GAME IN TEACHING SPEAKING TO EFL JUNIOR HIGH SCHOOL STUDENTS

The purpose of this study is to investigate the extent to which the use of the guessing game technique developed by Amato (1988) could improve students ’ speaking skill. The population involved in this study was the students from the eighth-grade classes of SMP Negeri 2 Lhokseumawe. To conduct the study, an intact class with 31 students was randomly selected as the research sample. Adopting a pre-experimental research design, this study was conducted in three steps: pre-test, treatment, and post-test. Based on the analysis of the students ’ speaking test results, this study found that the mean score of the pre-test and posttest was 43.06 and 91.45, respectively. The difference of the score was as high as 48.39 which indicated an evident improvement in the students ’ speaking scores. Furthermore, the results of the t-test analysis showed that the t-score was higher than the t-table (5.37 > 1.69) at the level of significance 0.05, and with the degree of freedom (df) 30. It can be concluded that the guessing game technique is an effective strategy in teaching speaking, particularly to students at the level of junior high school.
KAJIAN FAKTOR-FAKTOR PENGHAMBAT KETERAMPILAN BERPIKIR KRITIS SISWA KELAS V SEKOLAH DASAR PADA MATA PELAJARAN BAHASA INDONESIA

The research background of this problem that the critical thinking skills of students of class V SDI Nggari very low marked by the ability of students who are not able to analyze an argument while group discussion, do not dare to ask about material that is not yet understood, as well as the lack of interest of students to write the essay. The of this research is kualitatif thedescritive. The subject of this research is students of class V in SDI Nggari academic year 2017/2018 amounts to those 20. A technique used data in this study is the interview, observations, inquiries, and the test. The data analyzed using the model interactive Mile and Huberman namely the reduction, presenting data, and the withdrawal of the conclusion. The results of research shows several factors barriers skills critical thinking students SDI Nggari class V on the Indonesian language teaching is as follows; 1) students did not dare to convey the argument, 2) teachers less space for students exploration, 3) the use of learning methods moaning, and 4) processing class that are less good.
Quantum Neural Network Algorithms

This chapter covers the topic of quantum neural networks. You will see how quantum neural networks are implemented in real life. Code examples are presented for the quantum neural network topics related to quantum artificial neural networks (ANNs), quantum associative memory, quantum dots, quantum generative adversarial networks (GANs) , and quantum random access memory.