Reviewerly/exHarmony huggingface dataset:
Analysis of the Research Trends of Domestic Theses and Dissertations on Piano Pedagogy

본 연구는 국내 피아노교수학 학위과정 석·박사 논문의 연구동향을 파악하고 향후의 과제를 제시하는 데 목적이 있다. 이를 위해 2001년부터 2022년 현재까지 한국교육학술정보원 학술연구정보서비스(RISS)에 등재된 해당 과정의 학위논문 데이터를 확보하고 총 5개의 분석기준 항목을 통해 분석하였다. 분석의 결과는 다음과 같다. 첫째, 피아노교수학 학위논문 발표의 연도별 동향은 RISS 등재가 처음 이루어진 2001년을 시작으로 점진적인 증가율을 보이다가 2018년 이후 감소하고 있는 것으로 나타났다. 둘째, 석·박사 논문 모두 질적 연구 방법(석사 88.49%, 박사 85.29%)을 주로 선택한 것으로 확인되었다. 셋째, 연구대상에 있어서는 고급/전문영역 학습자의 비중이 가장 높았고(석사 37.70%, 박사 50.00%) 박사논문에서는 일부 연구대상에 편중된 현상이 나타났다. 넷째, 학문적 접근 측면으로 볼 때 석사 논문에서는 ‘교육학적인 접근’(45.24%)이, 박사 논문에서는 ‘음악학적 접근’(38.24%)이 주로 이루어지고 있었다. 다섯째, 연구주제/내용에 있어 석사 논문에서는 ‘교수법연구/교수·학습지도방안’(39.29%)을 1순위로 비교적 다양한 유형에 걸쳐 있었고 박사 논문에서는 ‘피아노 음악/레퍼터리 분석’(44.12%)이 주요 유형으로서, 몇몇 유형에 한정된 동향을 보였다. 결론적으로, 현장 중심 양적 연구의 활성화를 바탕으로 피아노교수학이 지닌 고유의 학문적 특성과 현 사회의 교육학적 시류 등을 연구에 반영할 필요가 있으며 특정 주제에 치우치지 않는 다양한 연구주제의 개발이 이루어져야 할 것이다.This study aims to understand the research trends of master’s theses and doctoral dissertations on piano pedagogy and to present future tasks. For this purpose, this study obtained data on theses/dissertations in the relevant courses, listed in the Korea Education & Research Information Service RISS from 2001 using 2022 and analyzed them through a total of five items of analysis criteria. The results of the analysis are as follows. First, the trend of the publication of theses/dissertations on piano pedagogy showed a gradual rate of increase, starting in 2001 when the listing on the RISS began for the first time and has decreased since 2018. Second, both theses and dissertations mainly chose the qualitative research method (Thesis: 88.49%, Dissertation: 85.29%). Third, as for the research subjects, advanced, major/special field learners were given the highest weight (Thesis: 37.70%, Dissertation: 50.00%). The dissertations were concentrated on some research subjects. Fourth, in the aspect of academic approaches, a “pedagogical approach” (45.24%) was mostly made in theses while a “musicological approach” (38.24%) was mostly made in dissertations. Fifth, as for the type of research, theses extended to relatively diverse types with “teaching method research/teaching/learning guidance plan” (39.29%) as the first while “piano music/repertoire analysis” (44.12%) was the main type in dissertations, and they tended to be limited to a few types. It would be necessary to reflect the unique academic characteristics of piano pedagogy and the pedagogical trend in the present society in the research and develop various research topics not weighted on specific topics, based on the revitalization of field-oriented quantitative research in the future.
Design and Implementation of a Target Characteristics Recommender System for Image Interpretation

Aiming at the problem of target characteristics retrieval and image interpretation, a target characteristics recommender system framework based on the target characteristics database and scene template database is designed. The technical methods of target characteristics recommendation are proposed, including target characteristics retrieval using target directory information and word vector, target image recommendation using metric learning and collaborative filtering, and target image interpretation using target category statistics and scene template matching. A target characteristics information recommendation mechanism supporting image interpretation is established, and a target characteristics recommender system for image interpretation is constructed.
Analyzing Memory Leaks

Before we discuss memory leaks, let’s analyze a simple case study. It will help you understand how memory leaks can hamper the smooth execution of an application over the long run. Suppose you have an online application where users need to fill in some data and then click the submit button. We can assume that during this process, you need to use some resources that consume some blocks of computer memory. Obviously, once the process is completed, developers release the allocated blocks of memory. Now assume that unfortunately the developers of the application mistakenly forgot to deallocate some blocks during the process of execution. Because of this misjudgment, let’s say that the application leaks 512 bytes per click. You probably won’t notice any performance degradation from some initial clicks. But what happens if thousands of online users use the application simultaneously? If 1,000,000 users click the submit button, the application will eventually cause 488 MB of memory loss. You cannot allow this for a long time, because if it goes like this, the application becomes slower and slower, and in the worst case, the application can crash. These are common symptoms caused by memory leaks.
Flexible Code Using Polymorphism

Ask a developer the following question: “What are the fundamental characteristics of object-oriented programming (OOP)?” You will hear an immediate reply saying that classes (and objects), inheritance, abstraction, encapsulation, and polymorphism are the most important characteristics of OOP. In addition, when you analyze OOP-based enterprise code, you’ll find different forms of polymorphism. But the truth is that a novice programmer rarely uses the power of polymorphism. Why? It is said that object-oriented programmers pass through three important stages. In the first stage, they become familiar with non-object-oriented constructs. In this stage, they use decision statements, looping constructs, etc. In the second stage, they start creating classes and objects and use the inheritance mechanism. Finally, in the third stage, they use polymorphism to achieve late binding and make their programs flexible. But writing the polymorphic is not always easy. Honestly, it is a little bit tough compared to the other features of OOP. Using some simple but powerful code examples, this chapter will make this concept easy for you to understand.
Abstract Class or Interface?

There are many code segments in which you can use an abstract class instead of a C# interface and vice versa. If the code is small and is used to perform a simple task, you may not see the difference between these two techniques. On the contrary, when the code is big and extendable, the choice between them can play a vital role in performance and maintenance.
Organizing Exceptions

Errors in a program can be classified into the following categories: compile-time errors and runtime errors. Compile-time errors are comparatively easy to fix because you know about them much earlier (i.e., at compile time). These may occur mainly due to syntax errors or typing mistakes. The compiler can point to them so that you can take corrective measures immediately. By contrast, runtime errors are dangerous because you encounter them when a program is executing. Programmatically, we call them exceptions. Since the program was compiled earlier, you expected it to run successfully. Why do exceptions occur? These may occur through some careless mistakes; maybe you have implemented the wrong logic, you have ignored some loopholes in the code paths of the program, etc. This type of error is tough to handle and is costly. Even after our best efforts, often these situations are unavoidable. It is also true that many of the failures are beyond the control of a programmer. So, handling these runtime errors is essential when you write an application. C#’s exception handling mechanism is important because it helps you deal with these typical runtime errors in advance.
Make Efficient Templates Using Hooks

This chapter will show you two important techniques. First, you will learn to use a template method. Why is this important? It is important because template methods are one of the fundamental techniques for code reuse. Suppose you follow a multistep algorithm to achieve a task. Using a template method, you can redefine some of these steps (but not all the steps) of the algorithm without altering the calling sequence of these steps.
MSQ: a mobile and social-based Q&amp;A system

Purpose The purpose of this paper is to propose a mobile and social-based question-and-answer (Q&amp;A) system that analyzes users' social relationships and past answering behavior, considers users' interest similarity and answer quality to infer suitable respondents and forwards the questions to users that are willing to give high quality answers. Design/methodology/approach This research applies first-order logic (FOL) inference calculation to generate question/interest ID that combines a users' social information, interests and social network intimacy to choose the nodes that can provide high-quality answers. After receiving a question, a friend can answer it, forward it to their friends according to the number of TTL (Time-to-Live) hops, or send the answer directly to the server. This research collected data from the TripAdvisor.com website and uses it for the experiment. The authors also collected previously answered questions from TripAdvisor.com; thus, subsequent answers could be forwarded to a centralized server to improve the overall performance. Findings The authors have first noticed that even though the proposed system is decentralized, it can still accurately identify the appropriate respondents to provide high-quality answers. In addition, since this system can easily identify the best answerers, there is no need to implement broadcasting, thus reducing the overall execution time and network bandwidth required. Moreover, this system allows users to accurately and quickly obtain high-quality answers after comparing and calculating interest IDs. The system also encourages frequent communication and interaction among users. Lastly, the experiments demonstrate that this system achieves high accuracy, high recall rate, low overhead, low forwarding cost and low response rate in all scenarios. Originality/value This paper proposes a mobile and social-based Q&amp;A system that applies FOL inference calculation to analyze users' social relationships and past answering behavior, considers users' interest similarity and answer quality to infer suitable respondents and forwards the questions to users that are willing to give high quality answers. The experiments demonstrate that this system achieves high accuracy, high recall rate, low overhead, low forwarding cost and low response rate in all scenarios.
Bringing Agility to the Classroom: Integrating Professional Scrum Trainings to an Undergraduate IT Project Management Course

This Innovative Practice Full Paper examines the integration of Professional Scrum Trainings (PST) into an undergraduate class. The PST was integrated into the IT project management course in 2016. The course deals with challenges in IT projects, agile project management, intercultural project teams and IT project controlling. It is held in the Bachelor of Science programs Business Information Systems and Electronic Government, which is provided by the department of business computing at the University of Applied Sciences and Arts -Hochschule Hannover in Germany. We integrate PSTs into the course with the aim to provide the opportunity to our students of a deep dive into the most commonly used agile method Scrum. Also, we collaborated with visiting lecturers from the industry mainly to include practice-relevant problems, challenges, and examples to the students. We prepared, planned, and performed the integration of the PST since 2016 in every term, except the summer term in 2020 due to Covid-19 reasons. This paper presents our approach to integrate PSTs as Scrum seminars into an undergraduate course in higher education. We also analyzed how the students value the integration of PSTs into the IT project management course. Based on our experience and learnings including the quantitative evaluation data, which we conduct regularly, we describe that the students value attending a PST in their studies and benefit from specific experiences related to Scrum in practice. The results include both, classroom and virtual distance teaching during Covid-19. Furthermore, we give three recommendations for other lecturers, which are interested integrating PSTs into their teaching activities. The recommendations refer to the collaboration with professionals from practice, the importance of providing practical relevant knowledge to the students and the possibility of integrating certification providers to the integrated PST. Thus, the paper contributes to an understanding how to integrate agile methods and professional trainings into a higher education context both in the classroom and virtual distance teaching environments.
Text based annotation and integrating visual features for CBIR system in Deep Learning

In content-based image retrieval system, the user’s query results are a set of images sorted according to the feature similarities between the images with respect to the query. In the real world, the images are main information source and represents features of objects like their color, shape and other attributes. From the various domains like fashion, crime prevention and medicine etc, we need some efficient image searching, browsing and retrieval tools. Although lots of work has been done for indexing and retrieval of images, but still there is no universally accepted feature extraction, retrieval and indexing technique available which is both accurate and fast. In this paper we have presented an algorithm which analyzes an image based on objects and RGB components and give similar images as the output. The images will be stored in the database with a certain tag that describes it. These tags can be used for text based image retrieval and helps in visual feature extraction. Most of the current search engines use tag based image retrieval which is time consuming and less accurate in user’s perspective. We have overcome these problems in proposed algorithm. The experimental results, showing the effectiveness of algorithms are presented.
Introduction to the special issue on education in acoustics

A substantial fraction of the membership of the Acoustical Society of America are faculty at various types of educational institutions and are actively engaged in educational activities. However, papers focusing on aspects of teaching, pedagogy, demonstrations, student learning, and other education topics are not often published in JASA, even though the Education in Acoustics Committee regularly offers special sessions on these topics at every ASA meeting. This special issue of JASA dedicated to Education in Acoustics includes 41 papers from authors all over the world. This introduction to the special issue briefly describes each of the papers, which have been organized into several broad categories: teaching methods and exercises; project-based learning; use of experiments, demos, and experiential learning; adapting to teaching during COVID-19; circuit models and impedance concepts; software apps and online resources; teaching musical acoustics; and descriptions of acoustics programs at a variety of institutions.
Getting Authoring Right: How to innovate for meaningful improvement

With so much technology-enabled innovation in assessment, one area has often had too little attention--the exam development phase, often called the "hardest job in publishing." Writing exams is so challenging and so important, not just for the validity of tests but also for the ability of exam providers to innovate their services and operate efficiently. With genuinely enterprise scale solutions finally becoming available in this area, the authors offer a checklist guide for assessment providers to review their authoring processes. They also explain why the combination of modular systems architectures and standards-based approaches to content will liberate assessment owners in tackling this key area in their businesses.
Sistem Penunjang Keputusan Penerimaan Karyawan Baru di PT. Yudita Teratai Cakti Menggunakan Metode Profile Matching

PT. Yudita Teratai Cakti is a company that carries out the hiring process independently or does not use the services of an outsourcing company. In the process of hiring employees, usually PT. Yudita Teratai Cakti uses advertising services in print media such as newspapers and online media such as Facebook and others. In the employee recruitment process at PT. Yudita Teratai Cakti is carried out by the personnel department by selecting and selecting one by one the data of applicants who enter the selection process for prospective employees at the acceptance of new employees at PT. Yudita Teratai Cakti, with the need to apply for a job this system was built, namely carrying out a selection process for prospective employees who applied for work at PT Yudita Teratai Cakti, it is hoped that this system can carry out the selection process using the profile matching calculation method used in this study to be able to provide decision-making information New Employee Recruitment. In order for the implementation of the selection of new employees to meet the demands and expectations of the company, a correlation is needed between the preparation of the test questions and the determined test criteria so that the test results for each new employee show the potential value of each new employee on each of the specified criteria. The decision support system with the profile matching method can assist the role of management or managers in supporting PT. Yudita Teratai Cakti which has objective value with a more effective time.
Optimasi Support Vector Mechine (SVM) Menggunakan K-Means dan K-Medoids untuk Klasterisasi Tema Tugas Akhir

The large amount of final project document data from study programs at the Sekolah Tinggi Manajemen Informatika dan Komputer (STMIK) Abulyatama can make a major contribution to the difficulty of the process of grouping a student's final project theme. The clustering process that has been carried out manually so far has been very ineffective and inefficient, so a data mining application is needed to manage the data, especially for clustering the data. The goal to be achieved from writing this thesis is to implement the Support Vector Machine with K-Means and K-Medoids to optimize the final assignment clustering. the results of the Optimization Support Vector Machine (SVM) analysis using K-Means and K-Medoids for Grouping Student Final Project Themes can be concluded in a number of ways, namely; with the K-Means Clustering method it can be seen that there are 23 data mining, 10 networks, 26 artificial intelligence, and 21 websites, and website 11 items.
Sistem Informasi Pelayanan Izin Penelitian pada Badan Kesbangpol Aceh

The purpose of this research is to assist the Aceh Kesbangpol in the research licensing service process to computerize the current system so that it can analyze and assist database processing activities at an even better level of effectiveness and efficiency, so that it is expected to be able to; designing and building a web-based research permit service information system at the Aceh Kesbangpol Agency, implementing a web-based research permit service information system with an integrated SMS Gateway, and producing more effective and efficient research permit service reports. The method used in this design is the waterfall method. Based on the results of research on the research permit service information system at the Aceh Kesbangpol Agency based on the web-based integrated SMS Gateway that has been carried out by the author, several conclusions can be drawn, namely; This research was successful in creating a web-based integrated information system research permission service with SMS Gateway. SMS Gateways.
Sistem Informasi Pemilihan Karyawan Terbaik Menggunakan Metode Simple Additive Weighting (SAW) pada Balai Pendidikan dan Pelatihan Ilmu Pelayaran BP2IP Malahayati

The purpose of this research is to assist the Balai Pendidikan dan Pelatihan Ilmu Pelayaran (BP2IP) Malahayati to process data on the selection of the best employees to computerize the current system so that it can analyze and assist database processing activities at an even better level of effectiveness and efficiency, so that it is expected to be able to ; designing the best web-based Employee Decision Making System (DSS) Application program, the best Employee Decision Making System (DSS) system made in the form of a questionnaire with several alternatives and criteria as basic ingredients in data processing using the Simple Additive Weighting (SAW) Method, and generate reports - more detailed ranking reports, criteria, alternatives, and employees of each required data. Based on the results of the research and decision-making system using the Simple Additive Weighting (SAW) method as the selection of the best employees at the Balai Pendidikan dan Pelatihan Ilmu Pelayaran (BP2IP) Malahayati which has been carried out by the author, several conclusions can be drawn, namely; This research succeeded in creating a decision support system for evaluating the best employee selection at the Balai Pendidikan dan Pelatihan Ilmu Pelayaran (BP2IP) Malahayati, and this research succeeded in conducting alternative rankings from the results of calculating the weight of employee scores using SAW (Simple Additive Weighting).
Research on Energy Consumption Calculation Model of Prefabricated Building Envelope System Based on BIM Technology and 6G Technology

There are foreign software that can directly connect design data to factory equipment for automatic production. However, in China, due to the lack of unified data transmission standards, intelligent production management software and supporting automation Production equipment, resulting in the inability of design data to connect with industrial software-driven components for automated production. Most of the components are still produced manually by workers according to the design drawings. The use of intelligent design software, intelligent manufacturing management system and numerical control equipment can realize design data-driven factory automation production, improve the design and production efficiency of prefabricated buildings, reduce the dependence on labor, and reduce the cost of prefabricated buildings.
Out-of-Distribution Detection Is Not All You Need

The usage of deep neural networks in safety-critical systems is limited by our ability to guarantee their correct behavior. Runtime monitors are components aiming to identify unsafe predictions and discard them before they can lead to catastrophic consequences. Several recent works on runtime monitoring have focused on out-of-distribution (OOD) detection, i.e., identifying inputs that are different from the training data. In this work, we argue that OOD detection is not a well-suited framework to design efficient runtime monitors and that it is more relevant to evaluate monitors based on their ability to discard incorrect predictions. We call this setting out-of-model-scope detection and discuss the conceptual differences with OOD. We also conduct extensive experiments on popular datasets from the literature to show that studying monitors in the OOD setting can be misleading: 1. very good OOD results can give a false impression of safety, 2. comparison under the OOD setting does not allow identifying the best monitor to detect errors. Finally, we also show that removing erroneous training data samples helps to train better monitors.