Reviewerly/exHarmony huggingface dataset:
My Strategy of Instructional Design for #DigPed

Module One, “Tell Your Truth”-Every participating group and member will  develop a personal website, blog, and shape their identity.Module Two, “Learn Something” Every participating group
A PERFORMANCE ANALYSIS OF STEREO MATCHING ALGORITHMS FOR STEREO VISION APPLICATIONS IN SMART ENVIRONMENTS

Stereo vision is a subfield of computer vision that tends to an essential research issue of reproducing the three-dimensional directions and focuses for depth estimation. This paper gives a relative investigation of stereo vision and matching techniques, utilised to resolve the correspondence problem. The investigation of matching algorithms is done by the use of extensive experiments on the Middlebury benchmark dataset. The tests concentrated on an examination of three stereovision techniques namely mean shift algorithm (MSA), seed growing algorithm (SGA) and multi-curve fitting (MCF) algorithm. With a specific end goal to evaluate the execution, some statistics related insights were computed. The experimental results demonstrated that best outcome is attained by the MCF algorithm in terms of depth estimation, disparity estimation and CT. The presented MCF algorithm attains a minimum computation time (CT) of 2 s whereas the other MSA and SGA require a maximum CT of 8.9 s and 7 s, respectively. The simulation results verified that the MCF algorithm reduces the processing time in a significant way than the compared methods.
Study on Blending Teaching Mode of English Intensive Reading Course Based on Mobile Internet Network

In order to solve the teaching problems which existed in " English Intensive Reading course ", this paper puts forward measure which is the application of blending teaching mode into English Intensive Reading course, i.e. combining the advantages of traditional teaching methods with E-learning. In conclusion, it can not only exhibit the important role of teachers in guiding, inspiring and monitoring the teaching process, but also can cultivate studentsâ€™ creativity and let the students be the main body of learning process.
Python Turtle Graphics

Python is very well supported in terms of graphics libraries. One of the most widely used graphics libraries is the Turtle Graphics library introduced in this chapter. This is partly because it is straight forward to use and partly because it is provided by default with the Python environment (and thus you do not need to install any additional libraries to use it).
Sistem Informasi Kompetisi Film Pendek Di Kota Solo Berbasis Web

Short film competition becomes a place to bring together a film work with its audience and also provide an opportunity for filmmakers to form a wider network. The implementation of short film competitions in Solo City is still limited in managing information that still uses conventional and manual methods so the implementation of short film competitions becomes ineffective and inefficient. Based on these problems, Web-based Short Film Competition Information System in Solo City was developed to provide innovation so the process of organizing short film competitions can run effectively and efficiently. The development of this system uses waterfall method which consist of requirement analysis, system design, system implementation, and testing. The result of testing the Short Film Competition Information System in Solo City showed that 74,6 of respondents agreed that the system could provide convenience the organizers of the competition and expand the distribution process of work for short filmmakers.
Models of guidance in augmented reality

Augmented Reality (AR) is a new and exciting technology withwide potential implementation areas, from medical to industry.One of the fields from which AR is gaining attention is themanned security industry. Unfortunately, this is also one ofthe areas in which formal studies on AR is lacking. Ais studyaims to bridge the gap in knowledge by evaluating an AR-applicationdesigned for the Microsoft HoloLens to supportworking security guards with navigation and a list of currenttasks without negatively affecting their situation awareness.Ae study is based on a pilot project in which the applicationwas designed. Results from the pilot project suggestedthat participants’ situation awareness was enhanced when usinga round model of guidance in AR-navigation compared towhen using an arrow, even though a majority of participantssubjectively preferred the arrows.In the current study, a third model of guidance was added,and potential confounding variables were controlled for. Amajority of participants still preferred the arrows, however,results suggests no significant difference in participants’ situationawareness between the three models of guidance. Aestudy did not replicate results from the pilot project, this mightbe due to limitations pertaining to the AR-technology used inthe study.
Creating Computer Art

Computer Art is defined as any art that uses a computer. However, in the context of this book we mean it to be art that is generated by a computer or more specifically a computer program. The following example, illustrates how in a very few lines of Python code, using the Turtle graphics library, you can create images that might be considered to be computer art.
GOVERNING THE BLOCKCHAIN: WHAT IS THE APPLICABLE LAW?

Both the functionality and the flexibility of distributed ledger technology (DLT) systems can raise complex questions of applicable law for users. This chapter considers the challenges of establishing what laws or regulations may be relevant to the operation and governance of DLT systems and transactions conducted on them. It highlights the risks of failing to include express contractual clauses to make the parties' choice of law and forum for dispute resolution clear. It also discusses how governing law and jurisdiction will be assessed in the absence of any express contractual clauses, including an explanation of common DLT governance systems.
First Encounter with Bell Nonlocality

This chapter is a self-contained introduction to Bell nonlocality. After a very quick historical motivation, the setting and the definition of nonlocality are given. Five classic examples of Bell tests are then introduced, including the CHSH and the GHZ tests. The remainder of the chapter is a critical reflection that contains two topics: a discussion of possible loopholes that should be avoided, and an elementary presentation of the main interpretations given to the phenomenon of nonlocality.
REASONING OF DECISION MAKING OR SIGN BACKGROUND OF PRACTICAL ARGUMENT

Purpose.The study of the nature of musical being from the standpoint of a fundamentally ontological approach in order to ascertain its possibilities in determining the fundamental ideas of the philosophy of music.Methods.Reduction, phenomenological description, dialectical analysis, hermeneutic interpretation, comparative descriptive method.Results.The subject of dialectical analysis and phenomenological description is pure becoming as the basis of musical existence (A.Losev).From the dialectical point of view, pure becoming is considered as a continuous transition of being into nothing and nothing into being (Hegel).The erroneous points of view on the essence of music, the way a musical work exists, its relation to reality and the specifics of its aesthetic perception are clarified and critically analyzed.Phenomenological description revealed the fundamental principles of the existence of musical formation.Hermeneutic interpretation and comparative descriptive analysis of the results obtained revealed a collision between the rhizomorphic formation (G.Deleuze, F. Guattari) of pure becoming and the musical form.Originality.The fundamental ontological approach to the study of music reveals its essential, universal and constant foundations.As a result, prerequisites are created for the construction and development of a holistic philosophical theory, as well as the formation of strategies for studying concrete historical forms of music in the past, present and future.An important feature of such a theory should be the unity and mutual complementarity of classical and postclassical approaches.Conclusion Among the immediate topics of such research, let us highlight the ontological problems of the form and mode of existence of a musical work, its artistic and aesthetic values, semantic content and ideas.
A Novel Method Based on Support Vector Machines to Classify Bank Transactions

Improvements in information technology have contributed to the development of the e-banking industry. Specifically, despite the reduction of bank charges, e-banking is one of the payment methods that, by employing it based on valid theory, can be successful in satisfying customers due to the easiness of access to financial transactions at any time and place with minimum required tools. A mobile device imposes an increasing amount of time, energy and expense in comparison with face-to-face visits. In spite of many benefits this channel has for customers, there are security concerns for service providers and users in the banking sector. Consequently, in this inquiry, the focus is on the role of the support vector machine neural network in the classification of Mellat mobile transactions.  To implement the intended procedure, after compiling the information in the preprocessing stage and purification and normalization of data, feature selection is done with the main component analysis algorithm. Then, in post-processing stage, the Neural Network supports the Mobile Banking classification as a safe but fake system. In order to compare the suggested method, we use Bayon floors and multilayer perceptron. The outcomes demonstrate that the support vector machine neural network can fulfill the classification of user’s mobile banking transaction with a mean square error of 0.216 and a precision of 94.6% of all data.
Construction and Reform of Undergraduate Teaching System of Engineering Chemistry in Interdisciplinary and Multi-majored Core Foundation Course

The course of Engineering Chemistry curriculum has quite some problems, such as less teaching hours, more contents, less integration with engineering practice, and less information on modern science and technology, and a single teaching method. As students need to learn this course well within a limited number of hours, teachers must clarify the teaching objectives of Engineering Chemistry, optimize the content of reorganized teaching, and break through the traditional teaching model. This work effectively explores the teaching content, curriculum system and teaching methods, and constructs a multi-faceted teaching reform based on teaching materials, multimedia and practices to adapt to the new engineering chemistry teaching system under the new engineering background.
Cognitive Computing based Question-Answering System for Teaching Electrical Motor Concepts

Today is the era of "Big Data", and one has to spend ample amount of time to extract the meaningful information from such a huge store of data.It leads towards such a question answering system which can offer exact and precise answers to user queries.For that there is a requirement of understanding user queries effectively.Thus this paper proposes a cognitive computing powered question answering system in the field of education, which posses the power of Natural Language Processing (NLP).Here, cognitive computing provides the methods for synergism of several powers into a single architecture, NLP provides understanding of the user questions effectively, and Ontology endows with the techniques for the construction of robust knowledge base.So for the realistic implementation of the proposed architecture, the education domain has chosen and will be teaching electrical motor concepts to the edification of the students.
Needs Analysis of ESP Courses for Pre-service Flight Attendants

The purpose of this study is to analyze the practical needs of pre-service flight attendant students, identify any problems, and give suggestions on developing English for Specific Purposes (ESP) courses for them. For data collection, the researcher conducted an online survey on the respective needs of 144 university students majoring in airline services and three professors in the department of airline services at G University in Korea and interviewed five students. The questionnaire given to the students was composed of 23 items, and its responses were descriptively analyzed. As for the responses to the interview and open-ended survey questions, the responses were analyzed by coding and were grouped into the guestionnaire categories. Consequently, most students felt that English is an important part of their work. Among the four main English skills, the needs for speaking skills were emphasized. In terms of ESP courses, they wanted a greater variety of English courses and preferred team teaching with an aviation expert and an English education expert. The results of the interview indicated that some of the current English courses were not designed for a specific purpose. Accordingly, this study identified some challenges to designing and implementing an appropriate ESP program matched with future job-related needs.
PENERAPAN LOGIKA FUZZY SUGENO UNTUK PENENTUAN REWARD PADA GAME EDUKASI AKU BISA

This study discusses an application of fuzzy logic in educational game. This game requires a fast player response. We made this game in order to raise children awareness to encounter strangers. In this game, strangers are enemies in the form of hand drawings. The main characters in this game are boy and girl. The player can choose a character as desired. Each selected character has a different level. At each level, there is a level of difficulty based on the ease of passing enemies to reach the goal. The player would win the game once he/she manages to escape from strangers and arrives at home. Each level of the game has an enemy who tries to approach the player. If the enemy caught by the player, it will get consequences according to the fuzzy rules that applied to the game. The application of fuzzy logic in this game is to regulate the form of reward that will receive by the player. The basis for determining reward is the living conditions, time, and scores obtained by the player. In this research, we use fuzzy Sugeno logic for giving rewards. We conclude that fuzzy logic applies to our educational game.
LEGO® Metadata for Reproducibility game pack

This is a set of resources for the LEGO® Metadata for Reproducibility game.The LEGO® Metadata for Reproducibility game is an interactive game for 4-24 players, using LEGO® to help researchers explore the metadata they might need to record to aid reproducibility. The game addresses issues including planning for metadata, formats of metadata recording, standards and automation. The game also draws multiple parallels between recording and communicating the research process and documenting and the creation of a LEGO® model. The process of playing the game draws researchers into discussions on how metadata is captured, recorded and disseminated, which in turn provides an opportunity for signposting to further resources in this area.
The Path of Application-oriented Transformation of Local Undergraduate Colleges and Universities under the Supply-side Reform

With the promotion of supply-side reform in various industries throughout the country, the upgrading and replacement of industrial structure urgently need a large number of high-quality talents. Local undergraduate colleges and universities, as the supply-side of talents, should keep pace with the pace of reform, find their own orientation, clarify the training objectives of application-oriented talents, take the market as the guide, deepen the integration of industry and education, carry out school-enterprise cooperation, strengthen the construction of teaching staff, actively carry out international exchanges and cooperation, and complete the transformation to application-oriented colleges and universities.
Seeing the world from above: Uncovering the neural basis of aerial scene recognition

Recognizing aerial scene imagery is an essential skill in a variety of work domains, yet little is currently known about how this skill forms and develops with experience. The current study aimed to elucidate the neural mechanisms underlying expertise in aerial scene recognition in order to understand the acquisition of experience with aerial imagery. We conducted an intensive six-session behavioral training study combined with multiple fMRI scans using a large set of high-resolution color images of real-world scenes varying in their viewpoint (aerial/terrestrial) and naturalness (manmade/natural). Half of the participants were trained to categorize these visual scenes at a specific-subordinate level (e.g., truss bridge, suspension bridge) and half of the participants passively viewed the same images while performing an orthogonal task. Both groups saw the same scene stimuli for five of the six training sessions; the sixth session consisted of a novel set of scenes to assess learning transfer. We found group-specific improvements in behavioral performance across training sessions and scene dimensions, including learning transfer, with greatest behavioral improvements observed for aerial scenes. In contrast, the passive-viewing group showed no major improvements despite equal exposure to the stimuli. Complementing the behavioral effects, we found experience-related neural changes in the experimental group: response magnitudes in scene-selective cortex (PPA and OPA) were correlated with improvements in behavioral performance for aerial imagery, but not in control regions (e.g., EVC, FFA). Whole-brain analyses revealed that over the course of training with aerial scenes, additional regions were recruited beyond scene-selective cortex, primarily lateral ventral-occipitotemporal cortex and posterior parietal cortex. Together these findings suggest that acquiring experience in categorizing aerial scenes entails the engagement of multiple visual areas involved in object and scene recognition, as well as the potential involvement of top-down attention mechanisms, and visuospatial processing. This research is supported by ONR BAA N00014-16-R-BA01.
Algorithm for Double Encryption and Generating Pseudo Random Sequence for Steganography

Steganography is the art of hiding the fact that communication is taking place, by hiding information in other information.Many different carrier file formats can be used, but digital images are the most popular because of their frequency on the internet.For hiding secret information in images, there exists a large variety of steganography techniques some are more complex than others and all of them have respective strong and weak points.Different applications may require absolute invisibility of the secret information, while others require a large secret message to be hidden.This project intends to give an overview of image steganography, its uses and techniques.It also attempts to identify the requirements of a good steganography algorithm and briefly reflects on which steganographic techniques are more suitable for which applications.
Path Analysis of Student Management in Higher Education from the Perspective of Positioning Theory

Based on the positioning theory, this paper analyzes the path of talent cultivation in higher education. The paper applies SWOT analysis model to accurately analyze individual students and implement different target management for different groups to build different growth methods. The result will eventually help the students to continue their studies and take the dominant positions in employment and entrepreneurship after the graduation. Specifically this paper emphasizes that the most important point for student management in higher education is to fully explore the endogenous strength of individual students on the basis of finding the correct positioning of individual students, encourage peer-to-peer mutual assistance, and play the role of the word â€˜leaderâ€™ among students, thus effectively improve the management level of higher education.
Logging in Python

Python has included a built-in logging module since Python 2.3. This module, the logging module, defines functions and classes which implement a flexible logging framework that can be used in any Python application/script or in Python libraries/modules.
Mapping information accumulation and integration dynamics across ventral temporal cortex

Studies examining spatial maps of where information is represented in ventral temporal cortex (VTC) have revealed critical organizational principles of the neural underpinnings of visual recognition. However, less is known about the fine spatiotemporal dynamics of information processing across VTC, which can also reveal critical details about the organizational and computational principles underpinning recognition. To fill this gap, we examined data recorded from 383 electrodes (electrocorticography, ECoG) in or on category-sensitive VTC of 38 participants. Temporally specific, multivariate information theoretic measures were used to assess how category-sensitive information evolved over time and space. At the group level and within individual subjects, the onset latency of this information was positively correlated with posterior to anterior VTC coordinate, consistent with fast-feedforward frameworks of the ventral visual stream. However, electrodes also demonstrated a decrease in the rate of information accumulation along the posterior to anterior VTC axis, with information accumulating more slowly and peaking later along a continuous gradient down VTC. We hypothesized that slower rates of information accumulation may be caused by increased diversity of sources that information is being integrated over in more anterior VTC regions. To test this, we examined the functional connectivity between each category-sensitive VTC electrode and all other electrodes implanted in the patients’ brains. The results support our hypothesis, showing that the rate of information accumulation was negatively correlated with functional connectivity to non-visually responsive brain regions, but not connectivity to visually responsive brain regions. This study suggests a novel organizational and computational principle in VTC: the rate of category-sensitive information accumulation is shaped by the diversity of non-visual sources that a region integrates over, which correlates with a posterior-to-anterior gradient of VTC organization.
Phish Webpage Classification Using Hybrid Algorithm of Machine Learning and Statistical Induction Ratios

Although the conventional machine learning-based anti-phishing techniques outperform their competitors in phishing detection, they are still targeted by zero-hour phish webpages due to their constraints of phishing induction. Therefore, phishing induction must be boosted up with the extraction of new features, the selection of robust subsets of decisive features, the active learning of classifiers on a big webpage stream. In this paper, we propose a hybrid feature-based classification algorithm (HFBC) for decisive phish webpage classification. HFBC hybridises two statistical criteria optimised feature occurrence (OFC) and phishing induction ratio (PIR) with the induction settings of the most salient machine learning algorithms, Naïve bays and decision tree. Additionally, we propose two constituent algorithms of features extraction and features selection for holistic phish webpage characterisation. The superiority of our proposed approach is justified and proven throughout chronological, real-time, and comparative analyses against existing machines learning-based anti-phishing techniques.
Correction to: Design for Teaching Surroundings Based on Human-Computer Interaction Techniques

The book was inadvertently published with an incorrect version of an author’s name in Chapter 39 as “Feng Wei” whereas it should have been “Wei Feng”.
Introduction to Testing

This chapter considers the different types of tests that you might want to perform with the systems you develop in Python. It also introduces Test Driven Development